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Search Results (255)

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Keywords = cell suppression problem

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22 pages, 9472 KiB  
Article
Cascaded-Filter-Based Reverberation Suppression Method of Short-Pulse Continuous Wave for Active Sonar
by Yonglin Cui, Shuhan Liao, Juncheng Gao, Haidong Zhu, Nengtong Zhao and An Luo
Remote Sens. 2024, 16(16), 2949; https://doi.org/10.3390/rs16162949 - 12 Aug 2024
Viewed by 540
Abstract
Reverberation is the main background interference in active sonar and seriously interferes with the extraction of the target echo. Active sonar systems can use short-pulse continuous wave (CW) signals to reduce the reverberation intensity. However, as the pulse width of the CW signals [...] Read more.
Reverberation is the main background interference in active sonar and seriously interferes with the extraction of the target echo. Active sonar systems can use short-pulse continuous wave (CW) signals to reduce the reverberation intensity. However, as the pulse width of the CW signals decreases, the reverberation envelope exhibits a high-frequency oscillating phenomenon. Active sonar often uses the cell average constant false alarm ratio (CA-CFAR) method to process the reverberation, which steadily decays with transmission distance. However, the high-frequency oscillation of the reverberation envelope deteriorates the performance of CA-CFAR, which causes a higher false alarm rate. To tackle this problem, the formation mechanism of the high-frequency oscillation characteristics of the reverberation envelope of the short-pulse-width CW signals is modeled and analyzed, and on this basis, an α filter is designed to suppress the high-frequency oscillation of the reverberation envelope before applying CA-CFAR. The simulation and lake trial results indicate that this method can effectively suppress high-frequency oscillations of the reverberation envelope, as well as exhibit robustness and resistance to reverberation interference. Full article
Show Figures

Figure 1

Figure 1
<p>Different reverberation backgrounds. (<b>a</b>) Steadily-decay reverberation background. (<b>b</b>) Non-steadily-decay reverberation background.</p>
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<p>The performance comparison of SO-CFAR, GO-CFAR and CA-CFAR.</p>
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<p>Flow diagram of CA-CFAR.</p>
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<p>The oscillations of the reverberation envelope of CW signals with different pulse widths.</p>
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<p>The spectrum of the reverberation envelope of 0.5 s CW.</p>
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<p>The detection performance comparison of CA-CFAR under different reverberation envelope oscillations. (<b>a</b>) Low-frequency oscillation. (<b>b</b>) High-frequency oscillation.</p>
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<p>The cell scattering model.</p>
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<p>The form of backscattered waves and the output of match filter.</p>
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<p>The flowchart of <span class="html-italic">α</span> filter.</p>
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<p>The amplitude frequency characteristic of the <span class="html-italic">α</span> filter.</p>
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<p>The logic of the cascaded reverberation suppression method.</p>
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<p>The simulated reverberation signal and its spectrum. (<b>a</b>) The reverberation signal containing the target echo. (<b>b</b>) The spectrum of the reverberation envelope.</p>
Full article ">Figure 13
<p>Processing results of different methods. (<b>a</b>) CA-CFAR. (<b>b</b>) SO-CFAR. (<b>c</b>) GO-CFAR. (<b>d</b>) <span class="html-italic">α</span>-CA-CFAR.</p>
Full article ">Figure 14
<p>Probability of target detection vs. SRR with CA-CFAR, SO-CFAR, GO-CFAR and <span class="html-italic">α</span>-CA-CFAR.</p>
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<p>False alarm rate vs. RNR with CA-CFAR, SO-CFAR, GO-CFAR and <span class="html-italic">α</span>-CA-CFAR.</p>
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<p>Schematic diagram of the distribution of the lake trial.</p>
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<p>Detection results of different methods for 0.05 s CW. (<b>a</b>) CA-CFAR. (<b>b</b>) SO-CFAR. (<b>c</b>) GO-CFAR. (<b>d</b>) <span class="html-italic">α</span>-CA-CFAR.</p>
Full article ">Figure 18
<p>The spectrum of the reverberation envelope at the bearing of 53°.</p>
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<p>Waveform comparison between target echo and reverberation interference.</p>
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<p>Detection results of different methods for 0.1 s CW. (<b>a</b>) CA-CFAR. (<b>b</b>) SO-CFAR. (<b>c</b>) GO-CFAR. (<b>d</b>) <span class="html-italic">α</span>-CA-CFAR.</p>
Full article ">Figure 21
<p>The spectrum of the reverberation envelope at the bearing of 70° when transmitting a 0.1 s CW signal.</p>
Full article ">Figure 22
<p>Detection results of different methods for 0.2 s CW. (<b>a</b>) CA-CFAR. (<b>b</b>) SO-CFAR. (<b>c</b>) GO-CFAR. (<b>d</b>) <span class="html-italic">α</span>-CA-CFAR.</p>
Full article ">Figure 23
<p>The spectrum of the reverberation envelope at the bearing of 150°.</p>
Full article ">Figure 24
<p>Detection results of different methods for 0.5 s CW. (<b>a</b>) CA-CFAR. (<b>b</b>) SO-CFAR. (<b>c</b>) GO-CFAR. (<b>d</b>) <span class="html-italic">α</span>-CA-CFAR.</p>
Full article ">Figure 25
<p>The spectrum of the reverberation envelope at the bearing of 70° when transmitting a 0.5 s CW signal.</p>
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<p>Simulated target signal and its frequency spectrum emitted by the transponder ship. (<b>a</b>) Simulated target signal. (<b>b</b>) The frequency spectrum of the simulated target signal.</p>
Full article ">Figure 27
<p>The reverberation envelope and its spectrum of the transmission of a 10 s, 495 Hz CW signal. (<b>a</b>) The reverberation envelope of the transmission of a 10 s, 495 Hz CW signal. (<b>b</b>) The frequency spectrum of the reverberation envelope of the transmission of a 10 s, 495 Hz CW signal.</p>
Full article ">
22 pages, 6491 KiB  
Article
Formononetin Defeats Multidrug-Resistant Cancers by Induction of Oxidative Stress and Suppression of P-Glycoprotein
by Ying-Tzu Chang, I-Ting Wu, Ming-Jyh Sheu, Yu-Hsuan Lan and Chin-Chuan Hung
Int. J. Mol. Sci. 2024, 25(15), 8471; https://doi.org/10.3390/ijms25158471 - 2 Aug 2024
Viewed by 632
Abstract
Multidrug resistance (MDR) remains the most difficult problem facing conventional chemotherapy for cancers. Astragalus membranaceus is a historically traditional Chinese medicine. One of its bioactive components, formononetin, exhibits antitumor effects on various cancers. However, the effects of formononetin on MDR cancers have not [...] Read more.
Multidrug resistance (MDR) remains the most difficult problem facing conventional chemotherapy for cancers. Astragalus membranaceus is a historically traditional Chinese medicine. One of its bioactive components, formononetin, exhibits antitumor effects on various cancers. However, the effects of formononetin on MDR cancers have not been evaluated. Therefore, we investigated the defense’s effects of formononetin on MDR. We used rhodamine 123 and doxorubicin efflux assays to analyze the inhibition kinetics of P-glycoprotein (P-gp) mediated-efflux. Cell viability was detected by sulforhodamine B assay, and the synergistic effects of formononetin combined with chemotherapeutic agents were further calculated using CompuSyn software. Molecular docking was performed with iGEMDOCK. We discovered that formononetin considerably induced oxidative stress and the disruption of mitochondrial membrane potential in MDR cancer cells. Furthermore, formononetin inhibits the P-gp efflux function by ATPase stimulation and the uncompetitive inhibition of P-gp-mediated effluxes of rhodamine 123 and doxorubicin. The molecular docking model indicates that formononetin may bind to P-gp by strong hydrogen bonds at Arginine (Arg) 489 and Glutamine (Gln) 912. Formononetin exhibits significant synergistic effects with vincristine and doxorubicin toward MDR cancer cells, and it synergistically suppressed tumor growth in vivo with paclitaxel. These results suggest that formononetin should be seen as a potential candidate for the adjuvant therapy of MDR cancers. Full article
(This article belongs to the Section Molecular Oncology)
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Figure 1

Figure 1
<p>Inhibitory effect of formononetin on P-gp efflux of <span class="html-italic">ABCB1</span>/Flp-In<sup>TM</sup>-293 cells. (<b>A</b>) Chemical structure of formononetin. (<b>B</b>) P-gp overexpressing <span class="html-italic">ABCB1</span>/Flp-In<sup>TM</sup>-293 cells were incubated with serial-dose formononetin or verapamil, a positive control, for 30 min. The intracellular calcein fluorescence was determined to indicate the inhibition of P-gp. Each data are expressed as the mean ± standard error of at least two experiments, each performed in triplicate. Verapamil has used as positive control of P-gp inhibitor. The abbreviations of verapamil and formononetin are VER and FMN, respectively. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to control group.</p>
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<p>(<b>A</b>,<b>B</b>) The effects of FMN on P-gp ATPase activity was detected and data were analyzed as RLUs. After P-gp membranes were incubated with or without FMN, the unmetabolized ATP transformed into a luminescence. FMN could significantly stimulate basal and verapamil-stimulated P-gp ATPase activity. Verapamil (200 µM) was used as positive control. (<b>A</b>,<b>B</b>) Data were presented as the difference between Na3VO<sub>4</sub>-treated samples. Each data are expressed as the mean ± standard error of at least two experiments, each performed in triplicate. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to control group. (<b>C</b>) P-gp substrates were identified by MDR1 shift assay, UIC2 fluorescence was increased during the binding of substrate on P-gp. Vinblastine (22.5 µM), a P-gp standard substrate, was used as positive control. The abbreviations of verapamil and formononetin are VER and FMN, respectively.</p>
Full article ">Figure 3
<p>The kinetic interactions of formononetin on rhodamine 123 or doxorubicin. Michaelis–Menten kinetics of P-gp efflux were determined by the extracellular fluorescence of rhodamine 123 (<b>A</b>) or doxorubicin (<b>C</b>). Lineweaver–Burk plot analysis of formononetin inhibitory mechanism on rhodamine 123 and doxorubicin efflux is shown in (<b>B</b>,<b>D</b>), respectively. Each datum is expressed as the mean ± standard error of at least two experiments, each performed in triplicate. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to nontreatment control.</p>
Full article ">Figure 3 Cont.
<p>The kinetic interactions of formononetin on rhodamine 123 or doxorubicin. Michaelis–Menten kinetics of P-gp efflux were determined by the extracellular fluorescence of rhodamine 123 (<b>A</b>) or doxorubicin (<b>C</b>). Lineweaver–Burk plot analysis of formononetin inhibitory mechanism on rhodamine 123 and doxorubicin efflux is shown in (<b>B</b>,<b>D</b>), respectively. Each datum is expressed as the mean ± standard error of at least two experiments, each performed in triplicate. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to nontreatment control.</p>
Full article ">Figure 4
<p>Effects of formononetin combined with chemotherapeutic agents on cell viabilities of drug-sensitive HeLaS3 cells and MDR KBvin cells. (<b>A</b>,<b>B</b>) The combination effects of formononetin and vincristine or doxorubicin on cell viability by SRB assay in cervical cancer HeLaS3 cells and MDR KBvin cells. Cells were pretreated with drugs alone or compound drug for 72 h. (<b>C</b>) Normalized isobologram for non-constant ratio combination of formononetin and chemotherapeutic drugs. The co-treatment of vincristine or doxorubicin with formononetin for 72 h at different combined concentrations. The actual drug dose was normalized with its corresponding IC<sub>50</sub> and used to determine the synergetic effect of the co-treatments in KBvin cells. The line on the isobologram denotes the half effect from each drug. Antagonism, additive, or synergism effects were indicated above, on, or below the line, respectively. ⊡ formononetin 25 µg/mL + vincristine 1000 nM/doxorubicin 10,000 nM ⊙ formononetin 25 µg/mL + vincristine 100 nM/doxorubicin 1000 nM; ▽ formononetin 20 µg/mL + vincristine 1000 nM; △ formononetin 20 µg/mL + vincristine 100 nM; ⟐ formononetin 20 µg/mL + vincristine 1000 nM; ╳ formononetin 20 µg/mL + vincristine 1000 nM. Data presented as mean ± SE of at least two experiments, each in duplicate. * indicates <span class="html-italic">p</span> value &lt; 0.05 compared with doxorubicin only or vincristine-only group. The abbreviations of vincristine, doxorubicin, and formononetin are VIN, DOX, and FMN, respectively.</p>
Full article ">Figure 4 Cont.
<p>Effects of formononetin combined with chemotherapeutic agents on cell viabilities of drug-sensitive HeLaS3 cells and MDR KBvin cells. (<b>A</b>,<b>B</b>) The combination effects of formononetin and vincristine or doxorubicin on cell viability by SRB assay in cervical cancer HeLaS3 cells and MDR KBvin cells. Cells were pretreated with drugs alone or compound drug for 72 h. (<b>C</b>) Normalized isobologram for non-constant ratio combination of formononetin and chemotherapeutic drugs. The co-treatment of vincristine or doxorubicin with formononetin for 72 h at different combined concentrations. The actual drug dose was normalized with its corresponding IC<sub>50</sub> and used to determine the synergetic effect of the co-treatments in KBvin cells. The line on the isobologram denotes the half effect from each drug. Antagonism, additive, or synergism effects were indicated above, on, or below the line, respectively. ⊡ formononetin 25 µg/mL + vincristine 1000 nM/doxorubicin 10,000 nM ⊙ formononetin 25 µg/mL + vincristine 100 nM/doxorubicin 1000 nM; ▽ formononetin 20 µg/mL + vincristine 1000 nM; △ formononetin 20 µg/mL + vincristine 100 nM; ⟐ formononetin 20 µg/mL + vincristine 1000 nM; ╳ formononetin 20 µg/mL + vincristine 1000 nM. Data presented as mean ± SE of at least two experiments, each in duplicate. * indicates <span class="html-italic">p</span> value &lt; 0.05 compared with doxorubicin only or vincristine-only group. The abbreviations of vincristine, doxorubicin, and formononetin are VIN, DOX, and FMN, respectively.</p>
Full article ">Figure 5
<p>Mechanism of formononetin MDR reversal ability on cancer cells. (<b>A</b>) The effects of formononetin on vincristine-induced cytotoxicity was assessed by apoptosis assay. Apoptotic cells were stained with 5 µL of Annexin V–FITC and propidium iodide (PI) and analyzed by flow cytometry. (<b>B</b>) <span class="html-italic">ABCB1</span> mRNA expression was determined by real-time RT PCR. Cells were pretreated with formononetin 10 µg/mL or 25 µg/mL in HeLaS3 and KBvin for 72 h. Each datum is expressed as the mean ± standard error of at least two experiments, each performed in triplicate. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to control group. The abbreviations of vincristine and formononetin are VIN and FMN, respectively.</p>
Full article ">Figure 5 Cont.
<p>Mechanism of formononetin MDR reversal ability on cancer cells. (<b>A</b>) The effects of formononetin on vincristine-induced cytotoxicity was assessed by apoptosis assay. Apoptotic cells were stained with 5 µL of Annexin V–FITC and propidium iodide (PI) and analyzed by flow cytometry. (<b>B</b>) <span class="html-italic">ABCB1</span> mRNA expression was determined by real-time RT PCR. Cells were pretreated with formononetin 10 µg/mL or 25 µg/mL in HeLaS3 and KBvin for 72 h. Each datum is expressed as the mean ± standard error of at least two experiments, each performed in triplicate. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to control group. The abbreviations of vincristine and formononetin are VIN and FMN, respectively.</p>
Full article ">Figure 6
<p>The docking results showed the superimposition of docked poses of compounds in the P-gp-binding pocket of the 3D structure of formononetin, rhodamine 123, and doxorubicin on P-gp: (<b>A</b>) formononetin, (<b>B</b>) rhodamine 123, (<b>C</b>) doxorubicin.</p>
Full article ">Figure 6 Cont.
<p>The docking results showed the superimposition of docked poses of compounds in the P-gp-binding pocket of the 3D structure of formononetin, rhodamine 123, and doxorubicin on P-gp: (<b>A</b>) formononetin, (<b>B</b>) rhodamine 123, (<b>C</b>) doxorubicin.</p>
Full article ">Figure 7
<p>Intracellular ROS production and mitochondria membrane potential changes in the MDR KBvin cells. The intracellular ROS production was detected in the HeLaS3 (<b>A</b>) and KBvin cells (<b>B</b>). Formononetin with or without chemotherapeutic drugs were treated for 1 h. Menadione was used as a positive control. The mitochondria membrane potential changes were measured in the HeLaS3 (<b>C</b>) and KBvin cells (<b>D</b>). The cells were treated with formononetin or chemotherapeutic drugs only or formononetin combined with chemotherapeutic drug for 6 h. Menadione was used as a positive control. Each datum is expressed as the mean ± standard error of at least two experiments, each per-formed in triplicate. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to control. N-acetylcysteine was applied as the antioxidant, and the cell viabilities were further evaluated by SRB assay in HeLaS3 (<b>E</b>) and KBvin cells (<b>F</b>). * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to with doxorubicin only or vincristine only group. # indicates <span class="html-italic">p</span> &lt; 0.05 compared with formononetin combined doxorubicin or vincristine.</p>
Full article ">Figure 7 Cont.
<p>Intracellular ROS production and mitochondria membrane potential changes in the MDR KBvin cells. The intracellular ROS production was detected in the HeLaS3 (<b>A</b>) and KBvin cells (<b>B</b>). Formononetin with or without chemotherapeutic drugs were treated for 1 h. Menadione was used as a positive control. The mitochondria membrane potential changes were measured in the HeLaS3 (<b>C</b>) and KBvin cells (<b>D</b>). The cells were treated with formononetin or chemotherapeutic drugs only or formononetin combined with chemotherapeutic drug for 6 h. Menadione was used as a positive control. Each datum is expressed as the mean ± standard error of at least two experiments, each per-formed in triplicate. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to control. N-acetylcysteine was applied as the antioxidant, and the cell viabilities were further evaluated by SRB assay in HeLaS3 (<b>E</b>) and KBvin cells (<b>F</b>). * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to with doxorubicin only or vincristine only group. # indicates <span class="html-italic">p</span> &lt; 0.05 compared with formononetin combined doxorubicin or vincristine.</p>
Full article ">Figure 7 Cont.
<p>Intracellular ROS production and mitochondria membrane potential changes in the MDR KBvin cells. The intracellular ROS production was detected in the HeLaS3 (<b>A</b>) and KBvin cells (<b>B</b>). Formononetin with or without chemotherapeutic drugs were treated for 1 h. Menadione was used as a positive control. The mitochondria membrane potential changes were measured in the HeLaS3 (<b>C</b>) and KBvin cells (<b>D</b>). The cells were treated with formononetin or chemotherapeutic drugs only or formononetin combined with chemotherapeutic drug for 6 h. Menadione was used as a positive control. Each datum is expressed as the mean ± standard error of at least two experiments, each per-formed in triplicate. * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to control. N-acetylcysteine was applied as the antioxidant, and the cell viabilities were further evaluated by SRB assay in HeLaS3 (<b>E</b>) and KBvin cells (<b>F</b>). * denotes <span class="html-italic">p</span> &lt; 0.05 as compared to with doxorubicin only or vincristine only group. # indicates <span class="html-italic">p</span> &lt; 0.05 compared with formononetin combined doxorubicin or vincristine.</p>
Full article ">Figure 8
<p>Formononetin combined with paclitaxel suppressed MDR KBvin cell growth in a xenotransplantation model. (<b>A</b>) Formononetin did not express significant toxicity at 48 hpi. (<b>B</b>) In an MDR KBvin xenograft model, we demonstrated that formononetin synergistically suppressed tumor size in combination with paclitaxel. The intensity of red fluorescence is proportional to the tumor size. Scale bar represents 1 mm. * <span class="html-italic">p</span> &lt; 0.05 compared with the control; @ <span class="html-italic">p</span> &lt; 0.05 compared to paclitaxel only group. hpf: hours post-fertilization; hpi: hours post-treatment or post-injection. The abbreviations of paclitaxel and formononetin are PXL and FMN, respectively.</p>
Full article ">Figure 8 Cont.
<p>Formononetin combined with paclitaxel suppressed MDR KBvin cell growth in a xenotransplantation model. (<b>A</b>) Formononetin did not express significant toxicity at 48 hpi. (<b>B</b>) In an MDR KBvin xenograft model, we demonstrated that formononetin synergistically suppressed tumor size in combination with paclitaxel. The intensity of red fluorescence is proportional to the tumor size. Scale bar represents 1 mm. * <span class="html-italic">p</span> &lt; 0.05 compared with the control; @ <span class="html-italic">p</span> &lt; 0.05 compared to paclitaxel only group. hpf: hours post-fertilization; hpi: hours post-treatment or post-injection. The abbreviations of paclitaxel and formononetin are PXL and FMN, respectively.</p>
Full article ">
15 pages, 6600 KiB  
Article
Insight into the Role of Rb Doping for Highly Efficient Kesterite Cu2ZnSn(S,Se)4 Solar Cells
by Chang Miao, Yingrui Sui, Yue Cui, Zhanwu Wang, Lili Yang, Fengyou Wang, Xiaoyan Liu and Bin Yao
Molecules 2024, 29(15), 3670; https://doi.org/10.3390/molecules29153670 - 2 Aug 2024
Viewed by 547
Abstract
Various copper-related defects in the absorption layer have been a key factor impeding the enhancement of the efficiency of Cu2ZnSn(S,Se)4 (CZTSSe) solar cells. Alkali metal doping is considered to be a good strategy to ameliorate this problem. In this article, [...] Read more.
Various copper-related defects in the absorption layer have been a key factor impeding the enhancement of the efficiency of Cu2ZnSn(S,Se)4 (CZTSSe) solar cells. Alkali metal doping is considered to be a good strategy to ameliorate this problem. In this article, Rb-doped CZTSSe (RCZTSSe) thin films were synthesized using the sol–gel technique. The results show that the Rb atom could successfully enter into the CZTSSe lattice and replace the Cu atom. According to SEM results, a moderate amount of Rb doping aided in enhancing the growth of grains in CZTSSe thin films. It was proven that the RCZTSSe thin film had the densest surface morphology and the fewest holes when the doping content of Rb was 2%. In addition, Rb doping successfully inhibited the formation of CuZn defects and correlative defect clusters and promoted the electrical properties of RCZTSSe thin films. Finally, a remarkable power conversion efficiency of 7.32% was attained by the champion RCZTSSe device with a Rb content of 2%. Compared with that of un-doped CZTSSe, the efficiency improved by over 30%. This study offers new insights into the influence of alkali metal doping on suppressing copper-related defects and also presents a viable approach for improving the efficiency of CZTSSe devices. Full article
(This article belongs to the Special Issue Preparation and Application of Key Materials for Solar Cells)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) XRD spectra of RCZTSSe thin films with various Rb contents of 0%, 1%, 2%, 3%, and 5%. (<b>b</b>) Enlarged image of the (112) diffraction peaks.</p>
Full article ">Figure 2
<p>Variation trend in 2θ, FWHM, and intensity of (112) peaks with various Rb-doping contents of RCZTSSe films.</p>
Full article ">Figure 3
<p>(<b>a</b>) Lattice constants a and c of the RCZTSSe thin films with different Rb contents of 0%, 1%, 2%, 3%, and 5%. (<b>b</b>) ƞ and V of the RCZTSSe thin films with various Rb-doping contents.</p>
Full article ">Figure 4
<p>(<b>a</b>) Raman spectra of the RCZTSSe thin films with different Rb-doping contents, and enlarged Raman spectra of the Rb-0% and Rb-2% RCZTSSe thin films in the range of 210–255 cm<sup>−1</sup>. (<b>b</b>) The variation tendency chart of the primary Raman peaks of the A1 mode with different Rb-doping contents.</p>
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<p>XPS spectra of (<b>a</b>) Cu 2<span class="html-italic">p</span>, (<b>b</b>) Zn 2<span class="html-italic">p</span>, (<b>c</b>) Sn 3<span class="html-italic">d</span>, (<b>d</b>) S 2<span class="html-italic">p</span>, (<b>e</b>) Se 3<span class="html-italic">d</span>, and (<b>f</b>) Rb 3<span class="html-italic">d</span> of the RCZTSSe 0thin film.</p>
Full article ">Figure 6
<p>SEM images of RCZTSSe films with various Rb contents: (<b>a</b>) Rb-0%, (<b>b</b>) Rb-1%, (<b>c</b>) Rb-2%, (<b>d</b>) Rb-2%, and (<b>e</b>) Rb-5%. (<b>f</b>) The average grain dimensions in the films. EDS mapping images of Cu, Zn, Sn, S, Se, and Rb elements in the Rb-2% thin film.</p>
Full article ">Figure 7
<p>(<b>a</b>) Atomic percentage of all elements in RCZTSSe films with different Rb contents. (<b>b</b>) Ratio of elemental composition of Rb and Cu in RCZTSSe films with different Rb contents.</p>
Full article ">Figure 8
<p>(<b>a</b>) (αhυ)<sup>2</sup> versus photon energy (hυ) for the RCZTSSe thin films with diverse Rb contents (Rb-0%, Rb-1%, Rb-2%, Rb-3%, and Rb-5%). (<b>b</b>) Variation trend of bandgaps of the RCZTSSe films with Rb content.</p>
Full article ">Figure 9
<p>(<b>a</b>) The diagrammatic configuration of the RCZTSSe solar cell. (<b>b</b>) Optimal J–V curves of RCZTSSe devices with various Rb-doping contents under standard AM 1.5 sunshine. (<b>c</b>) Box diagrams of PCE derived from 15 s olar cells. (<b>d</b>) EQE spectrum of the RCZTSSe solar cells.</p>
Full article ">Figure 10
<p>Statistical box diagrams of performance parameters of Rb-0% and Rb-2% devices: (<b>a</b>) V<sub>oc</sub>, (<b>b</b>) J<sub>sc</sub>, and (<b>c</b>) FF.</p>
Full article ">Figure 11
<p>(<b>a</b>) Temperature profiles of a two-step selenization process. (<b>b</b>) The crystal structure cell of kesterite RCZTSSe.</p>
Full article ">Figure 12
<p>Schematic drawing of the preparation process of an RCZTSSe solar cell. (<b>1</b>) Preparing an RCZTS precursor solution with different Rb-doping content; (<b>2</b>) spin-coating the precursor solution; (<b>3</b>) annealing the RCZTS thin film; (<b>4</b>) selenization in a N<sub>2</sub> atmosphere; (<b>5</b>) preparing a CdS layer by chemical bath deposition; (<b>6</b>) preparing ZnO and ITO layers by magnetron sputtering; (<b>7</b>) preparing a silver electrode.</p>
Full article ">
29 pages, 1618 KiB  
Review
B7H4 Role in Solid Cancers: A Review of the Literature
by Miriam Dawidowicz, Anna Kot, Sylwia Mielcarska, Katarzyna Psykała, Agnieszka Kula, Dariusz Waniczek and Elżbieta Świętochowska
Cancers 2024, 16(14), 2519; https://doi.org/10.3390/cancers16142519 - 11 Jul 2024
Viewed by 988
Abstract
Anti-cancer immunotherapies entirely changed the therapeutic approach to oncological patients. However, despite the undeniable success of anti-PD-1, PD-L1, and CTLA-4 antibody treatments, their effectiveness is limited either by certain types of malignancies or by the arising problem of cancer resistance. B7H4 (aliases B7x, [...] Read more.
Anti-cancer immunotherapies entirely changed the therapeutic approach to oncological patients. However, despite the undeniable success of anti-PD-1, PD-L1, and CTLA-4 antibody treatments, their effectiveness is limited either by certain types of malignancies or by the arising problem of cancer resistance. B7H4 (aliases B7x, B7H4, B7S1, VTCN1) is a member of a B7 immune checkpoint family with a distinct expression pattern from classical immune checkpoint pathways. The growing amount of research results seem to support the thesis that B7H4 might be a very potent therapeutic target. B7H4 was demonstrated to promote tumour progression in immune “cold” tumours by promoting migration, proliferation of tumour cells, and cancer stem cell persistence. B7H4 suppresses T cell effector functions, including inflammatory cytokine production, cytolytic activity, proliferation of T cells, and promoting the polarisation of naïve CD4 T cells into induced Tregs. This review aimed to summarise the available information about B7H4, focusing in particular on clinical implications, immunological mechanisms, potential strategies for malignancy treatment, and ongoing clinical trials. Full article
(This article belongs to the Special Issue Clinical and Immunological Therapy for Solid Tumors)
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<p>B7H4 structure and function. Figure upper part, the effect of B7H4 interaction with its receptor (unknown). Figure lower part, the effect of B7H4 knockdown on tumour cells. APC-antigen presenting cells; Treg, regulator T cells; TAMs, tumour associated macrophages; EMT, epithelial-to-mesenchymal transition.</p>
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<p>Cold and hot immune tumour microenvironment. The leading cellular players shaping iTME composition in the hot tumour phenotype (<b>A</b>) and the cold tumour phenotype (<b>B</b>). NK, natural killer cells; M1, macrophages of type 1; M2, macrophages of type 2; MDSC, myeloid-derived suppressor cells; Tc CD8, T cells CD8 lymphocytes; Tc CD4, T cells CD4 lymphocytes; T reg, regulator T cells; PD-L1, programmed cell death-ligand 1; B7H4, B7 homolog 4.</p>
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<p>Basic overview of immunotherapeutic approaches targeting B7H4. Monoclonal antibodies; Adoptive cell therapy, CAR T cells; Antibody–drug conjugates; Bispecific antibodies.</p>
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11 pages, 2276 KiB  
Article
An Antibody of the Secreted Isoform of Disintegrin and Metalloprotease 9 (sADAM9) Inhibits Epithelial–Mesenchymal Transition and Migration of Prostate Cancer Cell Lines
by Yura Jotatsu, Shain-Ying Sung, Ming-Heng Wu, Shunya Takeda, Yuto Hirata, Koki Maeda, Shiuh-Bin Fang, Kuan-Chou Chen and Katsumi Shigemura
Int. J. Mol. Sci. 2024, 25(12), 6646; https://doi.org/10.3390/ijms25126646 - 17 Jun 2024
Viewed by 808
Abstract
Prostate cancer (PC) is the most common cancer diagnosed in men worldwide. Currently, castration-resistant prostate cancer (CRPC), which is resistant to androgen deprivation therapy, has a poor prognosis and is a therapeutic problem. We investigated the antitumor effects on PC of an antibody [...] Read more.
Prostate cancer (PC) is the most common cancer diagnosed in men worldwide. Currently, castration-resistant prostate cancer (CRPC), which is resistant to androgen deprivation therapy, has a poor prognosis and is a therapeutic problem. We investigated the antitumor effects on PC of an antibody neutralizing secreted disintegrin and metalloproteinase domain-containing protein 9 (sADAM9), which is a blood-soluble form. We performed proliferation assays, wound healing assays, invasion assays, Western blot (WB), and an in vivo study in which a sADAM9 neutralizing antibody was administered intratumorally to PC-bearing mice. In invasion assays, the sADAM9 neutralizing antibody significantly inhibited invasion in all cell lines (TRAMP-C2: p = 0.00776, LNCaP: p = 0.000914, PC-3: p = 0.0327, and DU145: p = 0.0254). We examined epithelial–mesenchymal transition (EMT) markers, one of the metastatic mechanisms, in WB and showed downregulation of Slug in TRAMP-C2, LNCaP, and DU145 and upregulation of E-cadherin in TRAMP-C2 and PC-3 by sADAM9 neutralization. In mouse experiments, the sADAM9 neutralizing antibody significantly suppressed tumor growth compared to controls (1.68-fold in TRAMP-C2, 1.89-fold in LNCaP, and 2.67-fold in PC-3). These results suggested that the sADAM9 neutralizing antibody inhibits invasion, migration, and tumor growth in PC. Previous studies examined the anti-tumor effect of knockdown of total ADAM9 or sADAM9, but this study used the new technology of neutralizing antibodies for sADAM9. This may be novel because there was no animal study using a neutralizing antibody for sADAM9 to see the relationship between ADAM9 expression and prostate cancer. Full article
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<p>Comparison of cell proliferation change between control groups and sADAM9 neutralizing antibody groups. The absorbance when antibodies were administered in each group was set at 1, and we evaluated the cell proliferation ability by comparing the relative absorbance. (<b>A</b>) 0.05 µg/mL sADAM9 neutralizing antibody (sADAM9 antibody) suppressed cell proliferation in LNCaP at 72 h (<span class="html-italic">p</span> = 0.0161). (<b>B</b>) The PC-3 sADAM9 antibody was suppressed at 48 h (<span class="html-italic">p</span> = 0.0131). (<b>C</b>) In DU145, the sADAM9 neutralizing antibody did not inhibit cell proliferation significantly. (<b>D</b>) In TRAMP-C2, 0.05 µg/mL sADAM9 neutralizing antibody significantly inhibited cell proliferation (24 h: <span class="html-italic">p</span> = 0.00343, 48 h: <span class="html-italic">p</span> = 0.00411, and 72 h: <span class="html-italic">p</span> = 0.000410), and 0.1 µg/mL sADAM9 neutralizing antibody inhibited cell proliferation (24 h: <span class="html-italic">p</span> = 0.0473, 48 h: <span class="html-italic">p</span> = 0.000681, and 72 h: <span class="html-italic">p</span> = 0.00142). *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Comparison of the inhibitory effect on wound healing in the sADAM9 neutralizing antibody treatment and control groups. Microscopic images of the changes in the wound and graphs showing the covered area rates calculated from the images are shown. (<b>A</b>) The sADAM9 neutralizing antibody (sADAM9 antibody) significantly inhibited wound healing in LNCaP at 72 h (<span class="html-italic">p</span> =0.00281). (<b>B</b>) The PC-3 antibody was inhibited at 24 h (<span class="html-italic">p</span> = 0.00691), 48 h (<span class="html-italic">p</span> = 0.0295), and 72 h (<span class="html-italic">p</span> = 0.00179). (<b>C</b>) In DU145, the sADAM9 neutralizing antibody significantly inhibited wound healing at 6 h (<span class="html-italic">p</span> = 0.0410) and 24 h (<span class="html-italic">p</span> = 0.00543). (<b>D</b>) In TRAMP-C2, the sADAM9 neutralizing antibody significantly inhibited wound healing at 12 h (<span class="html-italic">p</span> = 0.0211) and 24 h (<span class="html-italic">p</span> = 0.00655) compared to the control. *: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.01. “Migration rate” means ”rate of covered area” in graphs. These graphs show the rate of wounds that have been closed by cell migration (100× magnification).</p>
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<p>Comparison of the inhibitory effect of the sADAM9 neutralizing antibody on invasive ability in treated and control groups. sADAM9 neutralizing antibody (sADAM9 antibody) decreased invasive cells in LNCaP (<b>A</b>), PC-3 (<b>B</b>), DU145 (<b>C</b>), and TRAMP-C2 (<b>D</b>) (LNCaP: <span class="html-italic">p</span> = 0.000914, PC-3: <span class="html-italic">p</span> = 0.0327, DU145: <span class="html-italic">p</span> = 0.0254, and TRAMP-C2: <span class="html-italic">p</span> = 0.00776). *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Protein expression levels of E-cadherin, N-cadherin, Vimentin, and Slug. (<b>A</b>) The sADAM9 neutralizing antibody decreased the expression of Slug, an EMT induction marker, in LNCaP, DU145, and TRAMP-C2. (<b>B</b>) The sADAM9 neutralizing antibody (sADAM9 antibody) increased the protein expression levels of the epithelial marker E-cadherin compared to the control (Ctrl) group in TRAMP-C2 and PC-3 (<b>B</b>). The expression of N-cadherin, a mesenchymal marker, decreased in LNCaP, and Vimentin decreased in DU145 after sADAM9 neutralization. The molecular weights of E-cadherin, N-cadherin, Vimentin, Slug, and beta-actin were 120 kDa, 99.7 kDa, 54 kDa, 30 kDa, and 42 kDa, respectively.</p>
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<p>Relative tumor volume changes in sADAM9 neutralizing antibody and control groups in mice prostate cancer models. We set the tumor volume before each antibody administration as 1 and compared the relative tumor volumes of the control and treated groups. (<b>A</b>) The sADAM9 neutralizing antibody significantly inhibited tumor growth in LNCaP (Day 1: <span class="html-italic">p</span> = 0.00274, Day 2: <span class="html-italic">p</span> = 0.00276, Day 3: <span class="html-italic">p</span> = 0.00711, Day 4: <span class="html-italic">p</span> = 0.0140, and Day 7: <span class="html-italic">p</span> = 0.0382). (<b>B</b>) In PC-3, antibodies inhibited tumor growth (Day 4: <span class="html-italic">p</span> = 0.0500, Day 5: <span class="html-italic">p</span> = 0.0460, Day 8: <span class="html-italic">p</span> = 0.0417, Day 9: <span class="html-italic">p</span> = 0.0356, and Day 10: <span class="html-italic">p</span> = 0.0450). (<b>C</b>) In TRAMP-C2, the sADAM9 neutralizing antibody also significantly inhibited tumor growth (Day 1: <span class="html-italic">p</span> = 0.0394, Day 2: <span class="html-italic">p</span> = 0.00619, Day 3: <span class="html-italic">p</span> = 0.0343, Day 8: <span class="html-italic">p</span> = 0.0280, Day 9: <span class="html-italic">p</span> = 0.0136, and Day 10: <span class="html-italic">p</span> = 0.0165). *: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.01.</p>
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19 pages, 3945 KiB  
Article
A Novel Finite Element-Based Method for Predicting the Permeability of Heterogeneous and Anisotropic Porous Microstructures
by Paris Mulye, Elena Syerko, Christophe Binetruy and Adrien Leygue
Materials 2024, 17(12), 2873; https://doi.org/10.3390/ma17122873 - 12 Jun 2024
Viewed by 609
Abstract
Permeability is a fundamental property of porous media. It quantifies the ease with which a fluid can flow under the effect of a pressure gradient in a network of connected pores. Porous materials can be natural, such as soil and rocks, or synthetic, [...] Read more.
Permeability is a fundamental property of porous media. It quantifies the ease with which a fluid can flow under the effect of a pressure gradient in a network of connected pores. Porous materials can be natural, such as soil and rocks, or synthetic, such as a densified network of fibres or open-cell foams. The measurement of permeability is difficult and time-consuming in heterogeneous and anisotropic porous media; thus, a numerical approach based on the calculation of the tensor components on a 3D image of the material can be very advantageous. For this type of microstructure, it is important to perform calculations on large samples using boundary conditions that do not suppress the transverse flows that occur when flow is forced out of the principal directions. Since these are not necessarily known in complex media, the permeability determination method must not introduce bias by generating non-physical flows. A new finite element-based method proposed in this study allows us to solve very high-dimensional flow problems while limiting the biases associated with boundary conditions and the small size of the numerical samples addressed. This method includes a new boundary condition, full permeability tensor identification based on the multiscale homogenization approach, and an optimized solver to handle flow problems with a large number of degrees of freedom. The method is first validated against academic test cases and against the results of a recent permeability benchmark exercise. The results underline the suitability of the proposed approach for heterogeneous and anisotropic microstructures. Full article
(This article belongs to the Special Issue Finite Element Modeling of Microstructures in Composite Materials)
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<p>Overview and scope of PoroS: The input can be either a segmented 3D scan of the material or a digital twin of the material generated using TexGen<sup>®</sup>. The scope of PoroS consists of the Stokes flow problem solver and a full-field homogenization subroutine. Thus, the output of the solver consists of flow fields of the flow problems and a full 3D permeability tensor.</p>
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<p>(<b>a</b>) Poiseuille flow in a 3D pipe with a circular cross section. (<b>b</b>) Cross sectional view of the pipe. (<b>c</b>) Comparison of the <math display="inline"><semantics> <msub> <mi>V</mi> <mi>x</mi> </msub> </semantics></math> profile in the middle of the domain obtained using PoroS with the known analytical solution.</p>
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<p>(<b>a</b>) Magnitude of velocity field in [<math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m/s] in case of a body force-driven flow (<math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi>f</mi> </msub> <mo>=</mo> <mn>0.493</mn> </mrow> </semantics></math>). (<b>b</b>) Comparison of the normalized transverse permeability (<math display="inline"><semantics> <mrow> <msub> <mi>K</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> <mo>/</mo> <msup> <mi>R</mi> <mn>2</mn> </msup> </mrow> </semantics></math>) obtained using an analytical expression from [<a href="#B30-materials-17-02873" class="html-bibr">30</a>], numerical simulations performed using a body force-driven flow, and numerical simulations performed using a Dirichlet condition-driven flow.</p>
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<p>Geometry of the models for the calculation of the longitudinal permeability: a square channel of cross section: (<b>a</b>) <math display="inline"><semantics> <mrow> <mn>20</mn> <mo>×</mo> <mn>20</mn> </mrow> </semantics></math> [<math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m]; (<b>b</b>) <math display="inline"><semantics> <mrow> <mn>40</mn> <mo>×</mo> <mn>40</mn> </mrow> </semantics></math> [<math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m]; (<b>c</b>) <math display="inline"><semantics> <mrow> <mn>60</mn> <mo>×</mo> <mn>60</mn> </mrow> </semantics></math> [<math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m]; (<b>d</b>) <math display="inline"><semantics> <mrow> <mn>80</mn> <mo>×</mo> <mn>80</mn> </mrow> </semantics></math> [<math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m].</p>
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<p>(<b>a</b>) The 3D segmented image used as an input for the international virtual permeability benchmark. (<b>b</b>) Comparison of results obtained with PoroS solver with body forcing with respect to all the results of the benchmark participants.</p>
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<p>Comparison with the benchmark results: transverse sections (<b>a</b>); <math display="inline"><semantics> <msub> <mi>K</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> </semantics></math> (<b>b</b>); <math display="inline"><semantics> <msub> <mi>K</mi> <mrow> <mi>y</mi> <mi>y</mi> </mrow> </msub> </semantics></math> (<b>c</b>); <math display="inline"><semantics> <msub> <mi>K</mi> <mrow> <mi>z</mi> <mi>z</mi> </mrow> </msub> </semantics></math> (<b>d</b>).</p>
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<p>Comparison with the benchmark results: (<b>a</b>) longitudinal sections; (<b>b</b>) <math display="inline"><semantics> <msub> <mi>K</mi> <mrow> <mi>y</mi> <mi>y</mi> </mrow> </msub> </semantics></math>.</p>
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<p>(<b>a</b>) Geometry of a 2D channel network inclined at <math display="inline"><semantics> <msup> <mn>60</mn> <mo>∘</mo> </msup> </semantics></math>. (<b>b</b>) Voxelized zoomed view of geometry.</p>
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<p>Field of <math display="inline"><semantics> <mrow> <mo>|</mo> <mi mathvariant="bold-italic">V</mi> <mo>|</mo> </mrow> </semantics></math> in [<math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m/s] for (<b>a</b>) flow problem in X and (<b>b</b>) flow problem in Y.</p>
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<p>Local fibres’ misalignment changing the flow principal directions in the case of the longitudinally cut sub-volume 10 (refer to <a href="#materials-17-02873-f007" class="html-fig">Figure 7</a>a) from the international virtual permeability benchmark case.</p>
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23 pages, 1553 KiB  
Review
Cell-Based Therapy for Fibrosing Interstitial Lung Diseases, Current Status, and Potential Applications of iPSC-Derived Cells
by Yusuke Nakamura, Seiji Niho and Yasuo Shimizu
Cells 2024, 13(11), 893; https://doi.org/10.3390/cells13110893 - 22 May 2024
Viewed by 1293
Abstract
Fibrosing interstitial lung diseases (FILDs), e.g., due to idiopathic pulmonary fibrosis (IPF), are chronic progressive diseases with a poor prognosis. The management of these diseases is challenging and focuses mainly on the suppression of progression with anti-fibrotic drugs. Therefore, novel FILD treatments are [...] Read more.
Fibrosing interstitial lung diseases (FILDs), e.g., due to idiopathic pulmonary fibrosis (IPF), are chronic progressive diseases with a poor prognosis. The management of these diseases is challenging and focuses mainly on the suppression of progression with anti-fibrotic drugs. Therefore, novel FILD treatments are needed. In recent years, cell-based therapy with various stem cells has been investigated for FILD, and the use of mesenchymal stem cells (MSCs) has been widely reported and clinical studies are also ongoing. Induced pluripotent stem cells (iPSCs) have also been reported to have an anti-fibrotic effect in FILD; however, these have not been as well studied as MSCs in terms of the mechanisms and side effects. While MSCs show a potent anti-fibrotic effect, the possibility of quality differences between donors and a stable supply in the case of donor shortage or reduced proliferative capacity after cell passaging needs to be considered. The application of iPSC-derived cells has the potential to overcome these problems and may lead to consistent quality of the cell product and stable product supply. This review provides an overview of iPSCs and FILD, followed by the current status of cell-based therapy for FILD, and then discusses the possibilities and perspectives of FILD therapy with iPSC-derived cells. Full article
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<p>Schematic of cell-based therapy for FILD. (<b>a</b>) Examples of the cells used in cell-based therapy in pulmonary fibrosis; (<b>b</b>,<b>c</b>) the mechanism of the action of the anti-fibrotic effect of stem cells for pulmonary fibrosis. It has been reported that MSCs, iPSCs, and AT2 have anti-fibrotic effects through several mechanisms described in (<b>b</b>,<b>c</b>). <b>Abbreviations</b>: AT2, alveolar epithelial type II; Coll, collagen; CTGF, connective tissue growth factor; IL, interleukin; FGF, fibroblast growth factor; INF-γ, interferon gamma; MMP, matrix metalloproteinase; MSCs, mesenchymal stem cells; PDGF, platelet-derived growth factor; TGF-β, transforming growth factor-beta 1; Th2-type, T helper 2 type; TNF-α, tumor necrosis factor-α. (↑; indicates upregulation or increase. ↓; indicates downregulation or decrease.)</p>
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<p>Treatment strategies for fibrosing interstitial lung diseases with induced pluripotent stem cells. Cell-based therapy with induced pluripotent stem cells (iPSCs) per se is likely to be difficult for several reasons. There is a possibility that effective cell-based therapy can be achieved by inducing iPSCs from cells with efficient anti-fibrotic activity and differentiating them into cells with high anti-fibrotic activity because iPSCs may retain the characteristics of the parent cells from which they were generated. <b>Abbreviations</b>: AT2, alveolar epithelial type II; HGF, hepatocyte growth factor; iPSCs, induced pluripotent stem cells; MSCs, mesenchymal stem cells. ↑: indicates enhanced.</p>
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27 pages, 5136 KiB  
Article
maGENEgerZ: An Efficient Artificial Intelligence-Based Framework Can Extract More Expressed Genes and Biological Insights Underlying Breast Cancer Drug Response Mechanism
by Turki Turki and Y-h. Taguchi
Mathematics 2024, 12(10), 1536; https://doi.org/10.3390/math12101536 - 15 May 2024
Viewed by 904
Abstract
Understanding breast cancer drug response mechanisms can play a crucial role in improving treatment outcomes and survival rates. Existing bioinformatics-based approaches are far from perfect and do not adopt computational methods based on advanced artificial intelligence concepts. Therefore, we introduce a novel computational [...] Read more.
Understanding breast cancer drug response mechanisms can play a crucial role in improving treatment outcomes and survival rates. Existing bioinformatics-based approaches are far from perfect and do not adopt computational methods based on advanced artificial intelligence concepts. Therefore, we introduce a novel computational framework based on an efficient support vector machine (esvm) working as follows: First, we downloaded and processed three gene expression datasets related to breast cancer responding and non-responding to treatments from the gene expression omnibus (GEO) according to the following GEO accession numbers: GSE130787, GSE140494, and GSE196093. Our method esvm is formulated as a constrained optimization problem in its dual form as a function of λ. We recover the importance of each gene as a function of λ, y, and x. Then, we select p genes out of n, which are provided as input to enrichment analysis tools, Enrichr and Metascape. Compared to existing baseline methods, including deep learning, results demonstrate the superiority and efficiency of esvm, achieving high-performance results and having more expressed genes in well-established breast cancer cell lines, including MD-MB231, MCF7, and HS578T. Moreover, esvm is able to identify (1) various drugs, including clinically approved ones (e.g., tamoxifen and erlotinib); (2) seventy-four unique genes (including tumor suppression genes such as TP53 and BRCA1); and (3) thirty-six unique TFs (including SP1 and RELA). These results have been reported to be linked to breast cancer drug response mechanisms, progression, and metastasizing. Our method is available publicly on the maGENEgerZ web server. Full article
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<p>Flowchart of the introduced AI-based framework identifying drugs, drug targets, critical genes, and transcription factors in breast cancer. Figure created with BioRender.com.</p>
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<p>(<b>a</b>) UpSet plot of gene lists provided by the computational methods when using Dataset1. (<b>b</b>) Nine clusters in a protein–protein interaction based on genes of esvm coupled with Metascape. (<b>c</b>) Twelve transcription factors, according to Metascape, when coupled with genes from esvm. (<b>d</b>) Process and pathway enrichment analysis provided by Metascape according to the 100 genes of esvm.</p>
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<p>(<b>a</b>) UpSet plot of gene lists provided by the computational methods when using Dataset1. (<b>b</b>) Nine clusters in a protein–protein interaction based on genes of esvm coupled with Metascape. (<b>c</b>) Twelve transcription factors, according to Metascape, when coupled with genes from esvm. (<b>d</b>) Process and pathway enrichment analysis provided by Metascape according to the 100 genes of esvm.</p>
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<p>Tamoxifen and fulvestrant anticancer drugs inhibit estrogen, causing DNA damage and cell death. SERM is a selective estrogen receptor modulator. SERD is a selective estrogen degrader.</p>
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<p>(<b>a</b>) UpSet plot of gene lists provided by the computational methods when using Dataset2. (<b>b</b>) Three clusters in a protein–protein interaction based on genes of esvm coupled with Metascape. (<b>c</b>) Eighteen transcription factors, according to Metascape, when coupled with genes from esvm. (<b>d</b>) Process and pathway enrichment analysis provided by Metascape according to the 100 genes of esvm.</p>
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<p>Hydroxycarbamide and gemcitabine inhibit the ribonucleotide reductase (RNR) enzyme, which inhibits DNA replication during the cell cycle and induces apoptosis.</p>
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<p>(<b>a</b>) UpSet plot of gene lists provided by the computational methods when using Dataset3. (<b>b</b>) Three clusters in a protein–protein interaction based on genes of esvm coupled with Metascape. (<b>c</b>) Twenty transcription factors, according to Metascape, when coupled with genes from esvm. (<b>d</b>) Process and pathway enrichment analysis provided by Metascape according to the genes of esvm.</p>
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<p>Ceritinib and erlotinib are anaplastic lymphoma kinase (ALK) and epidermal growth factor receptor (EGFR) inhibitors, respectively.</p>
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<p>Classification models are compared for predicting the drug responses of TCH, TCHTy, and TCTy in breast cancer (BC) patients when Dataset1 is used. Gene importance when esvm (<b>a</b>) and lasso (<b>b</b>) are applied. Computational running time (<b>c</b>) for esvm and lasso. Boxplot and strip chart of drug sensitivity prediction for BC patients using esvm (<b>d</b>) and lasso (<b>e</b>). ROC curve (<b>f</b>) demonstrates the prediction performance. TCH is docetaxel, carboplatin, and trastuzumab. TCHTy is docetaxel, carboplatin, trastuzumab, and lapatinib. TCTy is docetaxel, carboplatin, and lapatinib. PCR is a pathological complete response. RD is a residual disease.</p>
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<p>Classification models are compared for predicting TFEC drug responses in breast cancer (BC) patients when Dataset2 is used. Gene importance when esvm (<b>a</b>) and lasso (<b>b</b>) are applied. Computational running time (<b>c</b>). Boxplot and strip chart of drug sensitivity prediction for BC patients sensitive against those resistant to the drug treatment for esvm (<b>d</b>) and lasso (<b>e</b>). ROC curve (<b>f</b>) demonstrates the prediction performance. TFEC is docetaxel, 5-fluorouracil, epirubicin, and cyclophosphamide.</p>
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<p>Classification models are compared for predicting multiple drug combination responses in breast cancer (BC) patients when Dataset3 is used. Gene importance when esvm (<b>a</b>) and lasso (<b>b</b>) are applied. Computational running time (<b>c</b>). Boxplot and strip chart of drug sensitivity prediction for BC patients sensitive against those resistant to the drug treatment for esvm (<b>d</b>) and lasso (<b>e</b>). ROC curve (<b>f</b>) demonstrates the prediction performance.</p>
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<p>Computational running time for our model esvm against baseline methods (SVM and lasso) using simulated data of increased dimensionality.</p>
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14 pages, 3420 KiB  
Article
Carnosic Acid Inhibits Herpes Simplex Virus Replication by Suppressing Cellular ATP Synthesis
by Georgina Horváth, Edit Molnár, Zoltán Szabó, Gábor Kecskeméti, László Juhász, Szabolcs Péter Tallósy, József Nyári, Anita Bogdanov, Ferenc Somogyvári, Valéria Endrész, Katalin Burián and Dezső P. Virok
Int. J. Mol. Sci. 2024, 25(9), 4983; https://doi.org/10.3390/ijms25094983 - 3 May 2024
Viewed by 970
Abstract
Acquiring resistance against antiviral drugs is a significant problem in antimicrobial therapy. In order to identify novel antiviral compounds, the antiviral activity of eight plants indigenous to the southern region of Hungary against herpes simplex virus-2 (HSV-2) was investigated. The plant extracts and [...] Read more.
Acquiring resistance against antiviral drugs is a significant problem in antimicrobial therapy. In order to identify novel antiviral compounds, the antiviral activity of eight plants indigenous to the southern region of Hungary against herpes simplex virus-2 (HSV-2) was investigated. The plant extracts and the plant compound carnosic acid were tested for their effectiveness on both the extracellular and intracellular forms of HSV-2 on Vero and HeLa cells. HSV-2 replication was measured by a direct quantitative PCR (qPCR). Among the tested plant extracts, Salvia rosmarinus (S. rosmarinus) exhibited a 90.46% reduction in HSV-2 replication at the 0.47 μg/mL concentration. Carnosic acid, a major antimicrobial compound found in rosemary, also demonstrated a significant dose-dependent inhibition of both extracellular and intracellular forms of HSV-2. The 90% inhibitory concentration (IC90) of carnosic acid was between 25 and 6.25 μg/mL. Proteomics and high-resolution respirometry showed that carnosic acid suppressed key ATP synthesis pathways such as glycolysis, citrate cycle, and oxidative phosphorylation. Inhibition of oxidative phosphorylation also suppressed HSV-2 replication up to 39.94-fold. These results indicate that the antiviral action of carnosic acid includes the inhibition of ATP generation by suppressing key energy production pathways. Carnosic acid holds promise as a potential novel antiviral agent against HSV-2. Full article
(This article belongs to the Special Issue Recent Advances in Herpesviruses)
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<p>MTT cell viability assay of Vero cells incubated with the plant extracts. Cell culture media of HSV-2 infected Vero cells were replaced with plant extracts resulting in the concentration range of 60–0.47 mg/mL. Vero cells were incubated for 24 h, 37 °C, 5%CO<sub>2</sub>. Viability of the treated cells was compared to the untreated controls. Data are mean ± SD (<span class="html-italic">n</span> = 3). Statistical comparisons of cell viabilities (treated vs. untreated control) were performed by one-way ANOVA analysis corrected by Dunnett’s multiple comparison test. *: <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Impact of plant extracts on HSV-2 replication. Cell culture media of HSV-2 infected Vero cells were replaced with medium containing 7.5–0.47 mg/mL of plant extracts. Vero cells were incubated for 24 h, 37 °C, 5%CO<sub>2</sub>. At 24 h post-infection, Vero cells were lysed and a direct qPCR was applied to measure the HSV-2 genome concentrations. Data are mean ± SD (<span class="html-italic">n</span> = 3). Statistical comparisons of qPCR Ct values (treated vs. untreated control) were performed by one-way ANOVA analysis corrected by Dunnett’s multiple comparison test. *: <span class="html-italic">p</span> &lt; 0.05. N.D: not done.</p>
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<p>Impact of carnosic acid on host cell viability and HSV-2 replication. (<b>A</b>), Impact of 24 h carnosic acid treatment on Vero cell viability measured by MTT assay. (<b>B</b>), Impact of 24 h carnosic acid treatment on HSV-2 replication in Vero cells measured by direct qPCR. (<b>C</b>), Impact of 30 min carnosic acid treatment on Vero cell viability measured by MTT assay. (<b>D</b>), Impact of 30 min carnosic acid treatment of HSV-2 virions on HSV-2 replication measured by direct qPCR 24 h post-infection. (<b>E</b>), Impact of 24 h carnosic acid treatment on HeLa cell viability measured by MTT assay. (<b>F</b>), Impact of 24 h carnosic acid treatment on HSV-2 replication in HeLa cells measured by direct qPCR. (<b>G</b>), Impact of 30 min carnosic acid treatment on HeLa cell viability measured by MTT assay. (<b>H</b>), Impact of 30 min carnosic acid treatment of HSV-2 virions on HSV-2 replication measured by direct qPCR 24 h post-infection. MTT data are mean ± SD (<span class="html-italic">n</span> = 4), and qPCR data are mean ± SD (<span class="html-italic">n</span> = 3). Statistical comparisons of treated vs. untreated samples were performed by one-way ANOVA analysis corrected by Dunnett’s multiple comparison test. *: <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Proteomics analysis of carnosic acid treated HeLa cells. HeLa cells were treated with 25 μg/mL carnosic acid for 24 h. Five replicates were made and were compared to the untreated control cells. (<b>A</b>), Volcano plot of the upregulated and downregulated proteins in the carnosic acid-treated HeLa cells. (Carnosic acid/control fold change ≥1.18 with q-value &lt; 0.05 (red color); carnosic acid/control fold change ≤1/1.18 with q-value &lt; 0.05 (grey color)). (<b>B</b>), Functional analysis of the upregulated proteins. Graph shows the most significantly altered functional groups/pathways. (<b>C</b>), Functional analysis of the downregulated proteins. Graph shows the most significantly altered functional groups/pathways. Plot sizes for both the up- and downregulated proteins indicate the number of proteins related to a category, and plot color indicates the significance (−log<sub>10</sub> FDR) of protein enrichment in a category.</p>
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<p>KEGG pathway analysis of carnosic acid downregulated proteins associated with glycolysis/gluconeogenesis. (<b>A</b>,<b>B</b>), Glycolysis/gluconeogenesis pathway and its downregulated proteins. The mapping of significantly downregulated proteins onto KEGG pathways was performed by ShinyGO software. Downregulated proteins of the pathway were labeled blue.</p>
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<p>KEGG pathway analysis of carnosic acid downregulated proteins associated with citrate cycle and oxidative phosphorylation. (<b>A</b>,<b>B</b>), Citrate cycle (TCA cycle) pathway and its down-regulated proteins. (<b>C</b>,<b>D</b>), Oxidative phosphorylation pathway and its downregulated proteins. The mapping of significantly downregulated proteins onto KEGG pathways was performed by ShinyGO software. Downregulated proteins of the pathways were labeled blue.</p>
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<p>Mitochondrial effects of carnosic acid. (<b>A</b>), High-resolution respirometry of carnosic acid-treated HeLa cells. ROUTINE-, ATP-linked respiration, LEAK, and maximal capacity of the electron transport system (ETS) were significantly attenuated in carnosic acid-treated HeLa cells in comparison with control. The comparison of oxygen consumption values was performed by the Mann–Whitney U test ** <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>), Impact of inhibition of oxidative phosphorylation on HSV-2 replication. After HSV-2 infection, culture media were replaced with a media containing oligomycin at a 16–0 μg/mL concentration. HeLa cells were incubated for 24 h, 37 °C, 5%CO<sub>2</sub>. HSV-2 replication was measured by direct qPCR. Statistical analysis of qPCR data was performed by one-way ANOVA analysis corrected by Dunnett’s multiple comparison test. **: <span class="html-italic">p</span> &lt; 0.001.</p>
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14 pages, 3301 KiB  
Technical Note
Algorithm for the Weak Target Joint Detection and Ambiguity Resolution Based on Ambiguity Matrix
by Yitong Mao, Chong Song and Bingnan Wang
Remote Sens. 2024, 16(9), 1597; https://doi.org/10.3390/rs16091597 - 30 Apr 2024
Cited by 1 | Viewed by 691
Abstract
The looking-down mode of space airship bistatic radars faces complex sea–land clutter, and the mode of wide-range surveillance and the over-sight detection of the satellite platform generates a low SNR and range–Doppler ambiguity. The method traditionally used involves the transmission of multiple Pulse [...] Read more.
The looking-down mode of space airship bistatic radars faces complex sea–land clutter, and the mode of wide-range surveillance and the over-sight detection of the satellite platform generates a low SNR and range–Doppler ambiguity. The method traditionally used involves the transmission of multiple Pulse Repetition Frequencies (PRFs) and correlating them to solve the ambiguity. However, with a low SNR, the traditional disambiguation fails due to the large number of false alarms and target omissions. In order to solve this problem, a new algorithm for multi-target joint detection and range–Doppler disambiguation based on an ambiguity matrix is presented. Firstly, all possible state values corresponding to the ambiguous sequence are filled into the ambiguity matrix one by one. Secondly, the state values in the matrix cell are divided into several groups of subsequences according to the PRF. By disambiguating multiple sets of subsequences, performing subsequence fusion, and then undertaking point aggregation, the targets can be effectively detected in scenarios with a strong clutter rate, the false alarms can be suppressed, and the disambiguation of the range and Doppler is completed. The simulation shows that the proposed algorithm has the strong ability to detect targets and perform ambiguity resolution in the scenario of a multi-target and multi-false alarm. Full article
(This article belongs to the Special Issue Target Detection, Tracking and Imaging Based on Radar)
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<p>The motion relationship of the target relative to the airship and satellite.</p>
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<p>The workflow of the joint detection and disambiguation algorithm.</p>
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<p>The boundary effect diagram of the matrix.</p>
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<p>Schematic diagram of the method proposed to distinguish targets and false alarms.</p>
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<p>The point at the edge of the matrix region may produce four predictions.</p>
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<p>The ambiguous measurements under PRF = 2100 Hz, <span class="html-italic">λ</span> = 20: (<b>a</b>) range measurements in 100 s; (<b>b</b>) velocity measurements in 100 s.</p>
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<p>The estimation results for the target range dimension and Doppler dimension were obtained using different methods: (<b>a</b>) the range results of the proposed method in 100 s; (<b>b</b>) the velocity results of the proposed method in 100 s; (<b>c</b>) the range results of the traditional method in 100 s; (<b>d</b>) the velocity results of the traditional method in 100 s.</p>
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<p>The average OSPA distance of the traditional method and the method based on the ambiguity matrix.</p>
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<p>The target number estimation of the method based on the ambiguity matrix.</p>
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<p>The average OSPA range of the proposed algorithm and the method based on the ambiguity matrix.</p>
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<p>The probability that the proposed algorithm and the method based on the ambiguity matrix achieve detection.</p>
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21 pages, 7268 KiB  
Article
Joint Implementation Method for Clutter Suppression and Coherent Maneuvering Target Detection Based on Sub-Aperture Processing with Airborne Bistatic Radar
by Zhi Sun, Xingtao Jiang, Haonan Zhang, Jiangyun Deng, Zihao Xiao, Chen Cheng, Xiaolong Li and Guolong Cui
Remote Sens. 2024, 16(8), 1379; https://doi.org/10.3390/rs16081379 - 13 Apr 2024
Viewed by 827
Abstract
An airborne bistatic radar working in downward-looking mode confronts two major challenges for low-altitude target detection. One is range cell migration (RCM) and Doppler migration (DM) resulting from the relative motion of the radar and target. The other is the non-stationarity characteristic of [...] Read more.
An airborne bistatic radar working in downward-looking mode confronts two major challenges for low-altitude target detection. One is range cell migration (RCM) and Doppler migration (DM) resulting from the relative motion of the radar and target. The other is the non-stationarity characteristic of clutter due to the radar configuration. To solve these problems, this paper proposes a joint implementation method based on sub-aperture processing to achieve clutter suppression and coherent maneuvering target detection. Specifically, clutter Doppler compensation and sliding window processing are carried out to realize sub-aperture space–time processing, removing the clutter non-stationarity resulting from the bistatic geometric configuration. Thus, the output matrix of clutter suppression in the sub-aperture could be obtained. Then, the elements with the same phase of this matrix are superimposed and rearranged to achieve the reconstructed 2-D range-pluse echo matrix. Next, the aperture division with respect to slow time is conducted and the RCM correction based on modified location rotation transform (MLRT) and coherent integration (CI) are realized within each sub-aperture. Finally, the matched filtering process (MFP) is applied to compensate for the RCM/DM among different sub-apertures to coherently integrate the maneuvering target energy of all sub-apertures. The simulation and measured data processing results prove the validity of the proposed method. Full article
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<p>Three-dimensional geometric configuration of airborne bistatic radar and maneuvering target.</p>
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<p>Flow chart of signal processing.</p>
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<p>The <span class="html-italic">i</span>-th primary sub-aperture echo data within the correlation time interval.</p>
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<p>Single target simulation results for the proposed method at the −7 dB SCNR. (<b>a</b>) PC result. (<b>b</b>) Sub-aperture space–time filtering. (<b>c</b>) Target echo signal recovery. (<b>d</b>) CI result of the 25-th tertiary sub-aperture. (<b>e</b>) CI result of all sub-apertures.</p>
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<p>Single target simulation results for the proposed method at the −19 dB SCNR. (<b>a</b>) PC result. (<b>b</b>) Target echo signal recovery. (<b>c</b>) CI result of the 25-th tertiary sub-aperture. (<b>d</b>) CI result of all sub-apertures.</p>
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<p>Single target simulation results for several existing methods at the −19 dB SCNR. (<b>a</b>) KT-MFP. (<b>b</b>) GRFT. (<b>c</b>) ARFT. (<b>d</b>) Sub-CPI STAP based on GRFT.</p>
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<p>Multi-target simulation results for the proposed method. (<b>a</b>) PC result. (<b>b</b>) Echo signal recovery of target 1. (<b>c</b>) Echo signal recovery of target 2. (<b>d</b>) CI result of the 25-th sub-aperture for target 1. (<b>e</b>) CI result of the 25-th tertiary sub-aperture for target 2. (<b>f</b>) CI result of all sub-apertures for target 1. (<b>g</b>) CI result of all sub-apertures for target 2.</p>
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<p>Real data processing results. (<b>a</b>) PC result. (<b>b</b>) KT-MFP. (<b>c</b>) GRFT. (<b>d</b>) ARFT. (<b>e</b>) Sub-CPI STAP based on GRFT. (<b>f</b>) Proposed method.</p>
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<p>Detection performance.</p>
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9 pages, 557 KiB  
Review
The Marine Alga Sargassum horneri Is a Functional Food with High Bioactivity
by Masayoshi Yamaguchi
Nutraceuticals 2024, 4(2), 181-189; https://doi.org/10.3390/nutraceuticals4020012 - 8 Apr 2024
Viewed by 1169
Abstract
Functional food factors can play a preventive and therapeutic role in several human diseases. The marine alga Sargassum horneri (S. horneri) has restorative effects in several types of metabolic disorders, including osteoporosis, diabetes, inflammatory conditions, and cancer cell growth. Osteoporosis is [...] Read more.
Functional food factors can play a preventive and therapeutic role in several human diseases. The marine alga Sargassum horneri (S. horneri) has restorative effects in several types of metabolic disorders, including osteoporosis, diabetes, inflammatory conditions, and cancer cell growth. Osteoporosis is widely recognized as a major public health problem. Bone loss associated with ageing and diabetic states was prevented through the intake of bioactive compounds from S. horneri water extract in vivo by stimulating osteoblastic bone formation and inhibiting osteoclastic bone resorption in vitro. The intake of S. horneri water extract was found to have preventive effects on diabetic findings with an increase in serum glucose and lipid components. Furthermore, the S. horneri component has been shown to suppress adipogenesis from rat bone marrow cells and inflammatory conditions in vitro. Notably, the growth of bone metastatic human breast cancer MDA-MB-231 cells, which induce bone loss with osteolytic effects, was suppressed through culturing with the S. horneri water extract component in vitro. The S. horneri component, which has a molecular weight of less than 1000, was found to suppress the activation of NF-κB signaling by tumor necrosis factor-α, a cytokine associated with inflammation, in osteoblastic cells and macrophage RAW264.7 cells in vitro, suggesting a molecular mechanism. The bioactive component of S. horneri may play a multifunctional role in the prevention and treatment of metabolic disorders. This review outlines the advanced knowledge of the biological activity of the aqueous extract components of S. horneri and discusses the development of health supplements using this material. Full article
(This article belongs to the Special Issue Functional Foods as a New Therapeutic Strategy 2.0)
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<p>The cellular mechanism by which the <span class="html-italic">S. horneri</span> component exerts its osteogenic effects. Osteoclasts are differentiated from stem cells. RANKL stimulates osteoclastogenesis. Osteoblastic cells are differentiated from bone marrow mesenchymal stem cells and are stimulated by bone growth factors (TGF-β1 and BMP-2). The <span class="html-italic">S. horneri</span> component stimulates osteoblastic bone formation and suppresses osteoclastic bone resorption, thereby increasing bone mass. The <span class="html-italic">S. horneri</span> component suppresses TNF-α- and RANKL-enhanced NF-κB activation in osteoblasts and osteoclasts, suggesting a possible molecular mechanism for the osteogenic effects of the <span class="html-italic">S. horneri</span> component. In addition, bone marrow mesenchymal stem cells are differentiated into adipocytes. The <span class="html-italic">S. horneri</span> component suppresses adipogenesis from bone marrow mesenchymal stem cells. This may lead to the prevention of obesity and associated bone loss.</p>
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14 pages, 1811 KiB  
Article
Sulforaphane Ameliorates High-Fat-Diet-Induced Metabolic Abnormalities in Young and Middle-Aged Obese Male Mice
by Jing Luo, Hana Alkhalidy, Zhenquan Jia and Dongmin Liu
Foods 2024, 13(7), 1055; https://doi.org/10.3390/foods13071055 - 29 Mar 2024
Viewed by 1256
Abstract
Type 2 diabetes (T2D) is still a fast-growing health problem globally. It is evident that chronic insulin resistance (IR) and progressive loss of β-cell mass and function are key features of T2D etiology. Obesity is a leading pathogenic factor for developing IR. The [...] Read more.
Type 2 diabetes (T2D) is still a fast-growing health problem globally. It is evident that chronic insulin resistance (IR) and progressive loss of β-cell mass and function are key features of T2D etiology. Obesity is a leading pathogenic factor for developing IR. The aim of the present study was to determine whether sulforaphane (SFN), a natural compound derived from cruciferous vegetables, can prevent (prevention approach) or treat (treatment approach) obesity and IR in mouse models. We show that dietary intake of SFN (0.5 g/kg of HFD) for 20 weeks suppressed high-fat diet (HFD)-induced fat accumulation by 6.04% and improved insulin sensitivity by 23.66% in young male mice. Similarly, dietary provision of SFN (0.25 g/kg) significantly improved blood lipid profile, glucose tolerance, and insulin sensitivity of the middle-aged male mice while it had little effects on body composition as compared with the HFD group. In the treatment study, oral administration of SFN (40 mg/kg) induced weight loss and improved insulin sensitivity and plasma lipid profile in the diet-induced-obesity (DIO) male mice. In all three studies, the metabolic effects of SFN administration were not associated with changes in food intake. In vitro, SFN increased glucose uptake in C2C12 myotubes and increased fatty acid and pyruvate oxidation in primary human skeletal muscle cells. Our results suggest that SFN may be a naturally occurring insulin-sensitizing agent that is capable of improving the metabolic processes in HFD-induced obesity and IR and thereby may be a promising compound for T2D prevention. Full article
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<p>The chemical structures of glucoraphanin and sulforaphane.</p>
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<p>Long-term dietary supplementation with SFN suppressed HFD-induced adiposity and improved insulin sensitivity and hypertension status in young mice: (<b>A</b>) While HFD feeding results in the development of obesity showed that dietary SFN supplementation had little effect on body weight in young mice, (<b>B</b>) SFN supplement significantly lowered FBG at weeks 2, 6, and 8. (<b>C</b>) HFD feeding increased body fat and decreased lean mass in week 9, while SFN supplement significantly lowered body fat accumulation and increased lean mass as compared to the HFD group. (<b>D</b>) SFN supplement ameliorated hypertension as compared to HFD at week 9. (<b>E</b>) SFN supplement significantly improved insulin sensitivity as compared to HFD group at week 18. (<b>F</b>) AUC of ITT results. Data are shown as Mean ± SEM (<span class="html-italic">n</span> = 16) (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001). STD: standard chow diet; HFD: high-fat diet; HFD+SFN: HFD supplemented with sulforaphane (0.5 g/kg diet).</p>
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<p>Short-term dietary intake of SFN enhanced glucose homeostasis and lipid profile in HFD-fed obese mice. Short-term HFD supplemented with 0.25 g/kg SFN had little effect on body weight in middle-aged male mice (<b>A</b>). Body composition was measured following 7 weeks of HFD and fat mass was significantly higher in both HFD feeding groups (<b>B</b>). SFN supplement increased lean mass as compared to HFD group after 7 weeks of HFD feeding (<b>C</b>) (* <span class="html-italic">p</span> &lt; 0.05 vs. STD, # <span class="html-italic">p</span> &lt; 0.05 vs. HFD). Fasting blood glucose was higher in HFD group and SFN slightly lowered blood glucose but not statistically significantly (<b>D</b>). SFN intervention significantly decreased fasting insulin concentration after 7 weeks (<b>E</b>). Dietary supplementation with SFN significantly decreased serum cholesterol (<b>F</b>) and HDL (<b>G</b>), and slightly decreased triglycerides (<b>H</b>) after 7 weeks of treatment. Data are displayed as Mean ± SEM (<span class="html-italic">n</span> = 8) (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001). STD: standard chow diet; HFD: high-fat diet; HFD+SFN: HFD supplemented with SFN (0.25 g/kg diet).</p>
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<p>Short-term dietary supplementation of SFN promoted insulin sensitivity and ameliorated hyperglycemia induced by HFD. Blood glucose levels were measured after a glucose challenge (<b>A</b>) and AUC was calculated (<b>B</b>). SFN supplement significantly improved glucose tolerance as compared to HFD group after 7 weeks of feeding. Blood glucose levels were measured after an insulin challenge (<b>C</b>) and AUC was calculated (<b>D</b>). SFN supplement significantly improved insulin sensitivity as compared to HFD group after 7 weeks of feeding. Data are displayed as Mean ± SEM (<span class="html-italic">n</span> = 8) (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01). STD: standard chow diet; HFD: high-fat diet; HFD+SFN: HFD supplemented with SFN (0.25 g/kg diet).</p>
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<p>Treatment with SFN promotes weight loss and insulin sensitivity in diet-induced obese mice. SFN enhanced body weight loss (<b>A</b>). There was no effect on body composition (<b>B</b>), cage activity (<b>C</b>), or the average energy expenditure (<b>D</b>). SFN treatment improved insulin sensitivity after 30 days (<b>E</b>,<b>F</b>). Data are displayed as Mean ± SEM (<span class="html-italic">n</span> = 9–15) (* <span class="html-italic">p</span> &lt; 0.05). Con: control group (oral gavage with vehicle); SFN: SFN treatment group (oral gavage with 40 mg/kg SFN).</p>
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<p>Treatment with SFN promoted lipid profile in DIO mice and enhanced energy oxidation in vitro. Circulating triglycerides and total cholesterol were lower in SFN treatment group (<b>A</b>). Fecal lipid profile was slightly higher in SFN treatment group (<b>B</b>). Data are displayed as Mean ± SEM (<span class="html-italic">n</span> = 7–9). HF: high-fat diet + vehicle; HF+SFN: HF diet + 40 mg/kg sulforaphane in vehicle. (<b>C</b>) SFN treatment at 10 nM and 100 nM significantly increased glucose uptake in C2C12 differentiated myotubes. SFN treatment at 1 μM significantly increased fatty acid oxidation (<b>D</b>) and pyruvate oxidation (<b>E</b>) in primary human skeletal muscle cells. Data are displayed as Mean ± SEM (<span class="html-italic">n</span> = 3) (* <span class="html-italic">p</span> &lt; 0.05 vs. control).</p>
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15 pages, 4598 KiB  
Article
N-Acetylcysteine Alleviates D-Galactose-Induced Injury of Ovarian Granulosa Cells in Female Rabbits by Regulating the PI3K/Akt/mTOR Signaling Pathway
by Jiawei Cai, Yunpeng Li, Bohao Zhao, Zhiyuan Bao, Jiali Li, Shaoning Sun, Yang Chen and Xinsheng Wu
Antioxidants 2024, 13(4), 384; https://doi.org/10.3390/antiox13040384 - 22 Mar 2024
Cited by 1 | Viewed by 1510
Abstract
The ovary plays a crucial role in the reproductive system of female animals. Ovarian problems such as ovarian insufficiency, premature aging, polycystic ovary syndrome, and ovarian cysts may lead to ovulation disorders, abnormal hormone secretion, or luteal dysfunction, thereby increasing the risk of [...] Read more.
The ovary plays a crucial role in the reproductive system of female animals. Ovarian problems such as ovarian insufficiency, premature aging, polycystic ovary syndrome, and ovarian cysts may lead to ovulation disorders, abnormal hormone secretion, or luteal dysfunction, thereby increasing the risk of infertility and abortion. Only when the ovarian function and other organs in the reproductive system remain healthy and work normally can female animals be ensured to carry out reproductive activities regularly, improve the pregnancy rate and litter size, promote the healthy development of the fetus, and then improve their economic value. The follicle, as the functional unit of the ovary, is composed of theca cells, granulosa cells (GCs), and oocytes. GCs are the largest cell population and main functional unit in follicles and provide the necessary nutrients for the growth and development of follicles. N-acetylcysteine (NAC) is a prevalent and cell-permeable antioxidant molecule that effectively prevents apoptosis and promotes cellular survival. Over the past few years, its function in boosting reproductive performance in animals at the cellular level has been widely acknowledged. However, its specific role and mechanism in influencing GCs is yet to be fully understood. The objective of this study was to examine the effects of NAC on ovarian damage in female rabbits. For this purpose, D-galactose (D-gal) was first used to establish a model of damaged GCs, with exposure to 1.5 mg/mL of D-gal leading to substantial damage. Subsequently, varying concentrations of NAC were introduced to determine the precise mechanism through which it influences cell damage. Based on the results of the Cell Counting Kit-8 assay, flow cytometry, and Western blotting, it was found that 0.5 mg/mL of NAC could significantly suppress cell apoptosis and promote proliferation. In particular, it decreased the expression levels of Bax, p53, and Caspase-9 genes, while concurrently upregulating the expression of the BCL-2 gene. Moreover, NAC was found to alleviate intracellular oxidative stress, suppress the discharge of mitochondrial Cytochrome c, and boost the enzymatic activities of CAT (Catalase), GSH (Glutathione), and SOD (Superoxide dismutase). RNA sequencing analysis subsequently underscored the critical role of the PI3K/Akt/mTOR pathway in governing proliferation and apoptosis within GCs. These findings demonstrated that NAC could significantly influence gene expression within this pathway, thereby clarifying the exact relationship between the PI3K/Akt/mTOR signaling cascade and the underlying cellular processes controlling proliferation and apoptosis. In conclusion, NAC can reduce the expression of Bax, p53, and Caspase-9 genes, inhibit the apoptosis of GCs, improve cell viability, and resist D-gal-induced oxidative stress by increasing the activity of CAT, GSH, and SOD. The molecular mechanism of NAC in alleviating D-gal-induced ovarian GC injury in female rabbits by regulating the PI3K/Akt/mTOR signaling pathway provides experimental evidence for the effect of NAC on animal reproductive function at the cellular level. Full article
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<p>Construction of a D-gal-induced ovarian GC injury model. (<b>A</b>) The experimental process to study the model of ovarian GCs in vitro. (<b>B</b>) Morphological changes in GCs following a 12 h culture with varying doses of D-gal in vitro. (<b>C</b>) The CCK-8 assay was used to assess the effects of varying D-gal concentrations on the proliferation of GCs. (<b>D</b>) Calculation of IC50 values representing the drug concentration which causes a 50% reduction in cell proliferation. (<b>E</b>) WB analysis was performed to evaluate the expression levels of the PCNA protein in GCs following a 12 h exposure to varying concentrations of D-gal. (<b>F</b>) The rate of apoptosis in GCs was quantified by flow cytometry following a 12 h exposure to different concentrations of D-gal. (<b>G</b>) qRT-PCR was used to assess the expression levels of apoptosis-related genes in GCs after treatment with 0.5, 1, and 1.5 mg/mL of D-gal. (<b>H</b>) WB analysis was performed to examine the expression levels of apoptosis-related proteins in GCs after treatment with 0.5, 1, and 1.5 mg/mL of D-gal. All data are presented as mean ± SEM and were statistically analyzed with paired two-tailed <span class="html-italic">t</span>-tests at * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Construction of a D-gal-induced ovarian GC injury model. (<b>A</b>) The experimental process to study the model of ovarian GCs in vitro. (<b>B</b>) Morphological changes in GCs following a 12 h culture with varying doses of D-gal in vitro. (<b>C</b>) The CCK-8 assay was used to assess the effects of varying D-gal concentrations on the proliferation of GCs. (<b>D</b>) Calculation of IC50 values representing the drug concentration which causes a 50% reduction in cell proliferation. (<b>E</b>) WB analysis was performed to evaluate the expression levels of the PCNA protein in GCs following a 12 h exposure to varying concentrations of D-gal. (<b>F</b>) The rate of apoptosis in GCs was quantified by flow cytometry following a 12 h exposure to different concentrations of D-gal. (<b>G</b>) qRT-PCR was used to assess the expression levels of apoptosis-related genes in GCs after treatment with 0.5, 1, and 1.5 mg/mL of D-gal. (<b>H</b>) WB analysis was performed to examine the expression levels of apoptosis-related proteins in GCs after treatment with 0.5, 1, and 1.5 mg/mL of D-gal. All data are presented as mean ± SEM and were statistically analyzed with paired two-tailed <span class="html-italic">t</span>-tests at * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>NAC decreased D-gal-induced apoptosis and increased cell viability in ovarian GCs. (<b>A</b>) Morphological changes in GCs after exposure to different concentrations of NAC for 12 h in vitro. (<b>B</b>) The CCK-8 assay was used to assess the proliferation rate of GCs when exposed to different doses of the NAC treatment. (<b>C</b>) The expression levels of the PCNA protein in GCs, treated with different concentrations of NAC for 12 h, as determined by WB. (<b>D</b>) The apoptosis rate of GCs was measured after a 12 h incubation with different levels of NAC using Annexin V-FITC/PI staining and subsequent flow cytometry analysis. (<b>E</b>) The expression levels of apoptosis-related genes in GCs treated with 0.5, 1, and 1.5 mg/mL of NAC were assessed through qRT-PCR. (<b>F</b>) The expression of apoptosis-related genes in GCs treated with 0.5, 1, and 1.5 mg/mL NAC was then analyzed by WB. All data are presented as mean ± SEM and the results were statistically analyzed with paired two-tailed <span class="html-italic">t</span>-tests at * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>NAC can alleviate D-gal-induced oxidative stress in GCs. (<b>A</b>) Enzymatic assays revealed the activities of CAT, GSH, and SOD within GCs. (<b>B</b>) The protein expression level of Cyt c in mitochondria was assessed, with Cytochrome c oxidase IV (COX IV) serving as an internal control for the mitochondrial content. (<b>C</b>,<b>D</b>) Flow cytometry was then applied to detect changes in intracellular levels of ROS after treatment with 1.5 mg/mL of D-gal and 0.5 mg/mL of NAC. Data are presented as mean ± SEM; distinct lowercase letters (a, b, c) denote significant differences among groups, while identical letters imply the absence of a statistically significant difference. Statistical analysis was conducted using a paired two-tailed <span class="html-italic">t</span>-test.</p>
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<p>RNA-Seq analysis of NAC’s effect on rabbit ovarian GCs. (<b>A</b>) Volcano plot of DEGs. (<b>B</b>) Venn diagram illustrating DEG overlap between the control, 1.5 mg/mL D-gal-treated, and 0.5 mg/mL NAC-treated groups. (<b>C</b>) GO enrichment statistics were visualized as histogram plots where the horizontal axis represented GO classifications, the vertical axis showed gene counts, and the various colors represented different primary categories. (<b>D</b>) Dot plot presenting the top 20 enriched KEGG pathways; each dot symbolized a pathway with its name on the <span class="html-italic">y</span>-axis and enrichment factor on the <span class="html-italic">x</span>-axis. (<b>E</b>) The expression levels of <span class="html-italic">CDCA7</span>, <span class="html-italic">MSRB1</span>, <span class="html-italic">PAICS</span>, <span class="html-italic">THRB</span>, <span class="html-italic">ATF3,</span> and <span class="html-italic">KLF12</span> genes at the time of sequencing. (<b>F</b>) The expression levels of <span class="html-italic">CDCA7</span>, <span class="html-italic">MSRB1</span>, <span class="html-italic">PAICS</span>, <span class="html-italic">THRB</span>, <span class="html-italic">ATF3,</span> and <span class="html-italic">KLF12</span> genes were detected by qPCR. Data are presented as mean ± SEM; distinct lowercase letters (a, b, c) denote significant differences between groups, while identical letters imply the absence of a statistically significant difference. Statistical analysis was conducted using a paired two-tailed <span class="html-italic">t</span>-test.</p>
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<p>RNA-Seq analysis of NAC’s effect on rabbit ovarian GCs. (<b>A</b>) Volcano plot of DEGs. (<b>B</b>) Venn diagram illustrating DEG overlap between the control, 1.5 mg/mL D-gal-treated, and 0.5 mg/mL NAC-treated groups. (<b>C</b>) GO enrichment statistics were visualized as histogram plots where the horizontal axis represented GO classifications, the vertical axis showed gene counts, and the various colors represented different primary categories. (<b>D</b>) Dot plot presenting the top 20 enriched KEGG pathways; each dot symbolized a pathway with its name on the <span class="html-italic">y</span>-axis and enrichment factor on the <span class="html-italic">x</span>-axis. (<b>E</b>) The expression levels of <span class="html-italic">CDCA7</span>, <span class="html-italic">MSRB1</span>, <span class="html-italic">PAICS</span>, <span class="html-italic">THRB</span>, <span class="html-italic">ATF3,</span> and <span class="html-italic">KLF12</span> genes at the time of sequencing. (<b>F</b>) The expression levels of <span class="html-italic">CDCA7</span>, <span class="html-italic">MSRB1</span>, <span class="html-italic">PAICS</span>, <span class="html-italic">THRB</span>, <span class="html-italic">ATF3,</span> and <span class="html-italic">KLF12</span> genes were detected by qPCR. Data are presented as mean ± SEM; distinct lowercase letters (a, b, c) denote significant differences between groups, while identical letters imply the absence of a statistically significant difference. Statistical analysis was conducted using a paired two-tailed <span class="html-italic">t</span>-test.</p>
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<p>RNA-Seq analysis of NAC’s effect on rabbit ovarian GCs. (<b>A</b>) Volcano plot of DEGs. (<b>B</b>) Venn diagram illustrating DEG overlap between the control, 1.5 mg/mL D-gal-treated, and 0.5 mg/mL NAC-treated groups. (<b>C</b>) GO enrichment statistics were visualized as histogram plots where the horizontal axis represented GO classifications, the vertical axis showed gene counts, and the various colors represented different primary categories. (<b>D</b>) Dot plot presenting the top 20 enriched KEGG pathways; each dot symbolized a pathway with its name on the <span class="html-italic">y</span>-axis and enrichment factor on the <span class="html-italic">x</span>-axis. (<b>E</b>) The expression levels of <span class="html-italic">CDCA7</span>, <span class="html-italic">MSRB1</span>, <span class="html-italic">PAICS</span>, <span class="html-italic">THRB</span>, <span class="html-italic">ATF3,</span> and <span class="html-italic">KLF12</span> genes at the time of sequencing. (<b>F</b>) The expression levels of <span class="html-italic">CDCA7</span>, <span class="html-italic">MSRB1</span>, <span class="html-italic">PAICS</span>, <span class="html-italic">THRB</span>, <span class="html-italic">ATF3,</span> and <span class="html-italic">KLF12</span> genes were detected by qPCR. Data are presented as mean ± SEM; distinct lowercase letters (a, b, c) denote significant differences between groups, while identical letters imply the absence of a statistically significant difference. Statistical analysis was conducted using a paired two-tailed <span class="html-italic">t</span>-test.</p>
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<p>NAC inhibited D-gal-induced GC apoptosis through the PI3K/Akt/mTOR pathway. (<b>A</b>) WB determined the expression levels of p-PI3K, PI3K, p-AKT, AKT, p-mTOR, and mTOR. (<b>B</b>) IF was used to detect the expression of <span class="html-italic">Bax</span> and <span class="html-italic">BCL-2</span> genes in the control, 1.5 mg/mL D-gal-treated, and 0.5 mg/mL NAC-treated groups. Scale bar: 20 μm. Data are presented as mean ± SEM; distinct lowercase letters (a, b, c) denote significant differences between groups, while identical letters imply the absence of statistically significant differences. Statistical analysis was performed using paired two-tailed <span class="html-italic">t</span>-tests.</p>
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20 pages, 3888 KiB  
Review
Scarring and Skin Fibrosis Reversal with Regenerative Surgery and Stem Cell Therapy
by Aurora Almadori and Peter EM Butler
Cells 2024, 13(5), 443; https://doi.org/10.3390/cells13050443 - 3 Mar 2024
Viewed by 4597
Abstract
Skin scarring and fibrosis affect millions of people worldwide, representing a serious clinical problem causing physical and psychological challenges for patients. Stem cell therapy and regenerative surgery represent a new area of treatment focused on promoting the body’s natural ability to repair damaged [...] Read more.
Skin scarring and fibrosis affect millions of people worldwide, representing a serious clinical problem causing physical and psychological challenges for patients. Stem cell therapy and regenerative surgery represent a new area of treatment focused on promoting the body’s natural ability to repair damaged tissue. Adipose-derived stem cells (ASCs) represent an optimal choice for practical regenerative medicine due to their abundance, autologous tissue origin, non-immunogenicity, and ease of access with minimal morbidity for patients. This review of the literature explores the current body of evidence around the use of ASCs-based regenerative strategies for the treatment of scarring and skin fibrosis, exploring the different surgical approaches and their application in multiple fibrotic skin conditions. Human, animal, and in vitro studies demonstrate that ASCs present potentialities in modifying scar tissue and fibrosis by suppressing extracellular matrix (ECM) synthesis and promoting the degradation of their constituents. Through softening skin fibrosis, function and overall quality of life may be considerably enhanced in different patient cohorts presenting with scar-related symptoms. The use of stem cell therapies for skin scar repair and regeneration represents a paradigm shift, offering potential alternative therapeutic avenues for fibrosis, a condition that currently lacks a cure. Full article
(This article belongs to the Section Tissues and Organs)
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Figure 1

Figure 1
<p>The wound healing response. The stages of wound healing following injury involve hemostasis, inflammation, proliferation, and remodeling. Fibroblasts play a crucial role in the formation of cutaneous scars post-injury. Inhibition of these cells leads to a more regenerative phenotype, resulting in reduced scarring. Reproduced with permission from Jones et al., Transfusions, published by Wiley, 2019 [<a href="#B7-cells-13-00443" class="html-bibr">7</a>].</p>
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<p>Cellular mechanism of skin fibrosis. Fibroblast activation plays a critical role in the development of fibrosis. A blood vessel (Bv), neutrophils (Ne), macrophages (Mc), and mast cells (Ma) are indicated. ECM: extracellular matrix. Reproduced from Fertala et al., Biomolecules; published by MDPI, 2023 [<a href="#B11-cells-13-00443" class="html-bibr">11</a>].</p>
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<p>Fat grafting technique. The adipose tissue is harvested from the abdomen, inner thighs, knees, or hips (<b>A</b>); it is processed via centrifugation at 3000 rpm per 3 minutes to concentrate the fraction rich in ASCs (<b>B</b>); after discarding the upper and lower parts, the purified adipose tissue rich with ASCs is then available to be grafted in the recipient site (<b>C</b>).</p>
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<p>SVF and ASCs. The diagram illustrates different options for processing the adipose tissue to obtain progenitors cells (SVF, stromal vascular fraction, or ASCs, adipose-derived stem cells). Option (<b>A</b>) (in green) shows the passages that start with collagenase digestion (1) leading to enzymatically obtained SVF (e-SVF), which is a heterogeneous cell population mainly composed of ASCs, perivascular cells, endothelial cells, inflammatory cells, cell debris, and erythrocytes obtained from the lipoaspirate after collagenase digestion. After culture expansion (3), e-SVF yields a homogeneous population of plastic-adherent cells, the ASCs, that are described as CD31−, CD34+, CD45−, CD90+, CD105−, and CD146−. Option (<b>B</b>) (in blue) shows an alternative method to select mechanically obtained SVF (m-SVF) suspended in a solution mainly composed of broken adipocytes and cell debris.</p>
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<p>PRP consists of peripheral blood collection (<b>A</b>); centrifugation to separate the blood into different components (<b>B</b>); and selection of the fraction of plasma rich with platelets for injection at the recipient site (<b>C</b>).</p>
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<p>Commonalities among different fibrotic skin conditions successfully treated with ASCs-based therapies.</p>
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<p>Fat grafting for reversing scars. The image represents an example of a facial scar treated with fat grafting by our team.</p>
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<p>Mechanism of action. The diagram illustrates how fat grafting and ASCs-based therapies reduce scarring and skin fibrosis with a combination of mechanical (1) and paracrine (2) effects. The latter is mediated mainly by the ASCs, which can release cytokines and growth factors with pro-angiogenetic, immunomodulatory, and trophic effects.</p>
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