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14 pages, 9837 KiB  
Article
Cenozoic Reactivation of the Penacova-Régua-Verin and Manteigas-Vilariça-Bragança Fault Systems (Iberian Peninsula): Implication in Their Seismogenic Potential
by Sandra González-Muñoz and Fidel Martín-González
Geosciences 2024, 14(9), 243; https://doi.org/10.3390/geosciences14090243 (registering DOI) - 10 Sep 2024
Viewed by 219
Abstract
The Penacova-Régua-Verin (PRV) and the Manteigas-Vilariça-Bragança (MVB) are two of the longest faults of the Iberian Peninsula. These faults striking NNE–SSW, over lengths of >200 km, were developed during late-Variscan Orogeny and reactivated in response to the Alpine Cycle tectonics. Their tectonic evolution [...] Read more.
The Penacova-Régua-Verin (PRV) and the Manteigas-Vilariça-Bragança (MVB) are two of the longest faults of the Iberian Peninsula. These faults striking NNE–SSW, over lengths of >200 km, were developed during late-Variscan Orogeny and reactivated in response to the Alpine Cycle tectonics. Their tectonic evolution during Alpine compression (Cenozoic) and their implication in the active tectonic activity of Iberia are under discussion. Their recent tectonic activity is recorded in the vertical offset of geomorphological surfaces, in the associated pull-apart basins, and in M > 7 paleoseismic events. Based on the vertical surface offset of Pliocene surfaces (140–300 m for the MVB fault and 150–200 m for the PRV), together with the horizontal offset (1300–1600 m for MVBF fault and 600–1400 m for PRVF), we can conclude that they were reactivated as left-lateral strike-slip faults with a reverse component during the Pliocene (3.6 Ma)–present. These results indicate that these faults are not related to the strain transmission during the collision with Eurasia (Eocene–Oligocene). However, they are related to the intraplate strain of the southern collision with the African plate during the Upper Neogene. The estimated slip-rate is 0.2–0.5 mm/a for both faults. These slip-rates evidence important implications for the seismic hazard of this intraplate region. Full article
(This article belongs to the Section Structural Geology and Tectonics)
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Figure 1

Figure 1
<p>Schematic geological map of the Iberian Massif and the location of the study area. Modified from [<a href="#B12-geosciences-14-00243" class="html-bibr">12</a>,<a href="#B29-geosciences-14-00243" class="html-bibr">29</a>].</p>
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<p>Tectonic models proposed for the PRV and MVB faults during the Cenozoic: (<b>a</b>) Model proposed by (e.g., [<a href="#B5-geosciences-14-00243" class="html-bibr">5</a>,<a href="#B9-geosciences-14-00243" class="html-bibr">9</a>]). (<b>b</b>) The model proposed by (e.g., [<a href="#B13-geosciences-14-00243" class="html-bibr">13</a>,<a href="#B14-geosciences-14-00243" class="html-bibr">14</a>]).</p>
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<p>(<b>a</b>) Panoramic view toward the south of the Vilariça pull-apart basin, showing the uplift of the western block across the fundamental surface. The number corresponds to the topographic profile in <a href="#geosciences-14-00243-f005" class="html-fig">Figure 5</a>. (<b>b</b>) Field picture of the pre-tectonic sediments (arkoses of Fm. Vilariça). (<b>c</b>) Field picture of the syn-tectonic sediments (conglomerates with blocks of quartzite and angular granites immersed in a sandy matrix, Fm. Bragança). (<b>d</b>) Field aspect of the fault breccia of the PRVF northern part. (<b>e</b>) Field picture of the Viana del Bollo basin and its syn-tectonic sediments, consisting mainly of sandy matrix conglomerates and quartzite cobbles. Note the 30° tilting, indicating the fault activity after its deposits. (<b>f</b>) Field picture of the syn-tectonic sediments in Viana do Bolo basin. Locations shown in <a href="#geosciences-14-00243-f004" class="html-fig">Figure 4</a>.</p>
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<p>(<b>a</b>) Geological map of the traces and associated basins of the PRV and MVB faults. (<b>b</b>) Detailed map of the Chaves, Vila Real, and Telões basins. (<b>c</b>) Detailed map of the Mórtagua basin. (<b>d</b>) Detailed map of the Vilariça basin. (<b>e</b>) Detailed map of the Longroiva basin. (GLM) Galaico-Leoneses Mountains; (PCS) Portugal Central System.</p>
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<p>Main surfaces in the study area, with the vertical offset value measured and the localization of the profiles in <a href="#geosciences-14-00243-f006" class="html-fig">Figure 6</a>. Modified and improved from [<a href="#B21-geosciences-14-00243" class="html-bibr">21</a>,<a href="#B33-geosciences-14-00243" class="html-bibr">33</a>,<a href="#B34-geosciences-14-00243" class="html-bibr">34</a>].</p>
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<p>Profiles of surfaces through the PRV and MVB fault systems. The location of the profiles is shown in <a href="#geosciences-14-00243-f005" class="html-fig">Figure 5</a>.</p>
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<p>(<b>a</b>) Schema of the excess area technique. Modified from [<a href="#B45-geosciences-14-00243" class="html-bibr">45</a>]. (<b>b</b>) Digital elevation model map with the localization of the profiles (yellow lines) used for the area restoration technique. (<b>c</b>) Profiles and total uplift area for the Cantabrian Mountain (A-A′) and Galaico-Leoneses Mountains (B-B′).</p>
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11 pages, 2190 KiB  
Article
Does Applying Morpholine to Saliva-Contaminated Acrylic Resin Improve the Repair Bond Strength?
by Awiruth Klaisiri, Nantawan Krajangta, Kasidit Assawarattanaphan, Jaratchom Sriperm, Wisarut Prawatvatchara, Niyom Thamrongananskul and Tool Sriamporn
J. Compos. Sci. 2024, 8(9), 349; https://doi.org/10.3390/jcs8090349 - 6 Sep 2024
Viewed by 282
Abstract
The current study evaluates the effect of morpholine on saliva-contaminated acrylic resin repaired with light-cured resin composites. Sixty rods of self-curing acrylic resin were fabricated and assigned into four groups of fifteen specimens and surface-treated with saliva, phosphoric acid (PH), morpholine (MR), liquid [...] Read more.
The current study evaluates the effect of morpholine on saliva-contaminated acrylic resin repaired with light-cured resin composites. Sixty rods of self-curing acrylic resin were fabricated and assigned into four groups of fifteen specimens and surface-treated with saliva, phosphoric acid (PH), morpholine (MR), liquid MMA monomer, and a universal adhesive agent (UA, Singlebond Universal) based on the following techniques: group 1, saliva; group 2, saliva + PH + MMA + UA; group 3, saliva + MMA + UA; and group 4, saliva + MR + MMA + UA. An Ultradent model was placed at the center of the specimen, and then the resin composite was pressed and light-cured for 20 s. A mechanical testing device was used to evaluate the samples’ shear bond strength (SBS) scores. The debonded specimen areas were inspected under a stereomicroscope to identify their failure mechanisms. The data were assessed by employing the one-way ANOVA approach, and the significance level (p < 0.05) was established with Tukey’s test. The greatest SBS scores for group 2 (30.46 ± 2.26 MPa) and group 4 (32.10 ± 2.72 MPa) did not differ statistically significantly from one another. The lowest SBS recorded for group 1 was 1.38 ± 0.87 MPa. All of the fractured samples in group 1 had an adhesive failure profile. Groups 2 and 4 had the greatest percentages of cohesive failures. This study concluded that applying phosphoric acid and morpholine to sandblasted self-curing acrylic resin contaminated with saliva before MMA and universal adhesive agents are applied is the most efficient protocol for stimulating SBS when it is repaired with light-cured resin composites. Full article
(This article belongs to the Section Biocomposites)
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Figure 1
<p>Schematic of the methodology. Abbreviations: PH, phosphoric acid; MMA, methyl methacrylate; UA, universal adhesive; MR, morpholine; SBS, shear bond strength.</p>
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<p>The SBS test configuration.</p>
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<p>The stereomicroscope picture for group 1; all adhesive failures.</p>
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<p>The stereomicroscope pictures for group 2: (<b>A</b>), mixed failure; (<b>B</b>), cohesive failure.</p>
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<p>The stereomicroscope pictures for group 3: (<b>A</b>), mixed failure; (<b>B</b>), cohesive failure.</p>
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<p>The stereomicroscope pictures for group 4; (<b>A</b>), mixed failure; (<b>B</b>), cohesive failure.</p>
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15 pages, 4386 KiB  
Article
POSS and PAG Dual-Containing Chemically Amplified Photoresists by RAFT Polymerization for Enhanced Thermal Performance and Acid Diffusion Inhibition
by Haimeng Yu, Shaoshuai Liu, Haiyan Fu, Zepeng Cui, Liangshun Zhang and Jia Tian
Appl. Sci. 2024, 14(17), 7722; https://doi.org/10.3390/app14177722 - 2 Sep 2024
Viewed by 468
Abstract
A random copolymer (PTBM), utilized as deep ultra-violet (DUV) photoresist, was prepared by reversible addition-fragmentation chain transfer (RAFT) polymerization with tert-butyl methacrylate (tBMA), methyl methacrylate (MMA), triphenylsulfonium p-styrenesulfonate (TPS-SS), and functional poly (sesquicarbonylsiloxanes) (POSS-MA) as the monomer components, and 4-cyano-4-[(dodecylsulfanylthiocarbonyl) sulfanyl]pentanoic acid [...] Read more.
A random copolymer (PTBM), utilized as deep ultra-violet (DUV) photoresist, was prepared by reversible addition-fragmentation chain transfer (RAFT) polymerization with tert-butyl methacrylate (tBMA), methyl methacrylate (MMA), triphenylsulfonium p-styrenesulfonate (TPS-SS), and functional poly (sesquicarbonylsiloxanes) (POSS-MA) as the monomer components, and 4-cyano-4-[(dodecylsulfanylthiocarbonyl) sulfanyl]pentanoic acid (CDSPA) as the RAFT reagent. Fourier transform infrared spectroscopy (FT-IR) and proton nuclear magnetic resonance (1H NMR) proved successful synthesis. Ultraviolet absorption spectroscopy (UV) analysis verified the transparency of the polymer in the DUV band. RAFT polymerization kinetics showed that the polymerization rate conformed to the first-order kinetic relationship, and the polymerization process exhibited a typical controlled free radical polymerization behavior. Thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and static thermo-mechanical analysis (TMA) showed that the incorporation of POSS groups improved the thermal properties of the copolymer. According to scanning electron microscopy (SEM) images, the copolymerization of photoacid monomers (TPS-SS) resulted in photoresist copolymers exhibiting good resistance to acid diffusion and low roughness. Full article
(This article belongs to the Section Applied Thermal Engineering)
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<p>(<b>A</b>) Polymerization kinetic curves of PTBM-0, PTBM-4 and PBM. Dependence of the molecular weight and polydispersity (<span class="html-italic">M</span><sub>w</sub>/<span class="html-italic">M</span><sub>n</sub>) on the conversion for (<b>B</b>) PTBM-0, (<b>C</b>) PTBM-4, and (<b>D</b>) PBM.</p>
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<p>GPC traces of (<b>A</b>) PTBM-0, (<b>B</b>) PTBM-4, and (<b>C</b>) PBM corresponding to different polymerization time points.</p>
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<p>(<b>A</b>) GPC curves of PTBM-4 and after removal of RAFT terminal group of PTBM-4. (<b>B</b>) Photographs of copolymers with RAFT terminal group, and (<b>C</b>) after removal of RAFT terminal group.</p>
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<p><sup>1</sup>H NMR spectra of (<b>A</b>) PTBM-0, (<b>B</b>) PTBM-4, and (<b>C</b>) PBM.</p>
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<p>FT-IR curves of PTBM-0, PTBM-4, and PBM.</p>
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<p>UV–vis absorption curves of PTBM-0, PTBM-4, PBM, and TPS-ST (dissolved in ethyl lactate, 0.1 mg/mL).</p>
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<p>(<b>A</b>) TGA curve of PTBM-4, (<b>B</b>) DSC curves of PTBM-0, PTBM-1, PTBM-2, PTBM-3, and PTBM-4.</p>
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<p>TMA curves of PTBM-0, PTBM-1, PTBM-2, PTBM-3, and PTBM-4.</p>
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<p>FT-IR of PTBM-4 before and after exposure.</p>
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<p>SEM images of photolithographic patterns of (<b>A</b>) PTBM-0, (<b>B</b>) PTBM-1, (<b>C</b>) PTBM-2, (<b>D</b>) PTBM-3, (<b>E</b>) PTBM-4, and (<b>F</b>) PBM.</p>
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<p>Synthetic route of the copolymer PTBM.</p>
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16 pages, 12121 KiB  
Article
Study on the Response Mechanism of Climate and Land Use Change to Evapotranspiration in Aksu River Basin
by Gang Zheng, Guanghui Wei, Fanghong Han, Yan Cao and Fan Gao
Atmosphere 2024, 15(9), 1055; https://doi.org/10.3390/atmos15091055 - 1 Sep 2024
Viewed by 331
Abstract
Research on evapotranspiration and its drivers in the Aksu River Basin from the perspectives of climate change and land use is of great significance for promoting the efficient use and precise allocation of its water resources. Theil-Sen median trend analysis (T-S) and the [...] Read more.
Research on evapotranspiration and its drivers in the Aksu River Basin from the perspectives of climate change and land use is of great significance for promoting the efficient use and precise allocation of its water resources. Theil-Sen median trend analysis (T-S) and the Mann–Kendall nonparametric test (M-K), in addition to correlation analysis, partial correlation analysis, complex correlation analysis, and driving-factor zoning principles, were used to examine the characteristics of the spatiotemporal changes in evapotranspiration and to explore the driving mechanism of the changes in evapotranspiration. The results indicated that the range of fluctuations in the multiyear average evapotranspiration in the Aksu River Basin from 2001 to 2020 was between 481.58 and 772.37 mm/a, which showed the spatial distribution characteristics of being high in the west and central part of the basin, and low in the north and south of the basin. The positive correlation between evapotranspiration and precipitation was stronger, and the negative correlations with temperature and relative humidity were stronger. The change in evapotranspiration in cultivated land is mainly driven by precipitation and relative humidity × precipitation; for grassland, the main drivers were relative humidity and precipitation × relative humidity; for woodland, the main drivers were relative humidity and other climatic factors; and for other land types, the main drivers were other climatic factors. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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<p>Map of the Aksu River Basin, China.</p>
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<p>Interannual variability in evapotranspiration and climatic factors from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Changes in the monthly mean evapotranspiration and in the precipitation, temperature, and relative humidity from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Spatial analysis of the mean evapotranspiration and the trends in the changes in evapotranspiration from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Correlation analysis of seasonal evapotranspiration with precipitation, temperature, and relative humidity from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Correlation analysis of seasonal evapotranspiration with precipitation, temperature, and relative humidity from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Spatial distributions of the correlation coefficients between evapotranspiration and climatic factors from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Spatial distributions of the partial correlation coefficients between evapotranspiration and (<b>a</b>) precipitation and (<b>b</b>) relative humidity from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Distribution of the compound correlation coefficients between evapotranspiration and climatic factors from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Spatial distribution of the drivers of evapotranspiration and climatic factors from 2001 to 2020 in the Aksu River Basin.</p>
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<p>Changes in the areas and evapotranspiration according to different types of land use in the Aksu River Basin from 2001 to 2020.</p>
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<p>The proportions of the types of land use for the drivers of evapotranspiration in 2001, 2010, and 2020 in the Aksu River Basin.</p>
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19 pages, 84736 KiB  
Article
Newly Discovered NE-Striking Dextral Strike-Slip Holocene Active Caimashui Fault in the Central Part of the Sichuan-Yunnan Block and Its Tectonic Significance
by Xin Tan, Kuan Liang, Baoqi Ma and Zhongtai He
Remote Sens. 2024, 16(17), 3203; https://doi.org/10.3390/rs16173203 - 29 Aug 2024
Viewed by 318
Abstract
The Sichuan-Yunnan block is a tectonically active region in China, with frequent large earthquakes occurring in and around it. Despite most earthquakes being concentrated along boundary faults, intraplate faults also have the potential to generate damaging earthquakes. Remote sensing makes it possible to [...] Read more.
The Sichuan-Yunnan block is a tectonically active region in China, with frequent large earthquakes occurring in and around it. Despite most earthquakes being concentrated along boundary faults, intraplate faults also have the potential to generate damaging earthquakes. Remote sensing makes it possible to identify these potential earthquake source faults. During an active fault investigation in the Liangshan area, a distinct lithological boundary named Caimashui fault was found. The geometric distribution and kinematic parameter of the fault is crucial for assessing seismic hazards and understanding the deformation pattern within the Sichuan-Yunnan block. The Caimashui fault is mapped with remote sensing interpretation, a field survey, and UAV measurement. Through trenching and Quaternary dating, the Late Quaternary active characteristics of the fault are studied. The fault is a Holocene active dextral strike-slip fault with a reverse component, exhibiting a dextral strike-slip rate of ~0.70 ± 0.11 mm/a. Paleoseismic investigation shows that the last surface rupture event of the Caimashui fault occurred later than 4150 ± 30a BP, with a magnitude of M ≥ 7.0. The fault may act as a secondary splitting fault, absorbing the deformation caused by various sinistral strike-slip rates of the boundary faults and the potential energy from the counterclockwise rotation of the Central Yunnan micro-block. Full article
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<p>Tectonic setting and distribution map of the southeast margin of the Tibetan Plateau. (<b>a</b>) Tectonic location of the study area. Black rectangle shows the study area. ATF: Altyn Tagh fault, QHF: Qilian-Haiyuan fault, KF: Kunlunshan fault, XF: Xianshuihe fault, XJF: Xiaojiang fault, RRF: Red River fault, JLF: Jiali fault, CF: Karakorum fault, HFT: Himalayan Frontal Thrust. (<b>b</b>) Main active tectonics in the study area. The fault locations are modified from [<a href="#B41-remotesensing-16-03203" class="html-bibr">41</a>]. Colored circles represent historically and instrumentally documented earthquakes, which are modified from [<a href="#B34-remotesensing-16-03203" class="html-bibr">34</a>,<a href="#B36-remotesensing-16-03203" class="html-bibr">36</a>,<a href="#B42-remotesensing-16-03203" class="html-bibr">42</a>]. XF: Xianshuihe fault, ANHF: Aninghe fault, ZMHF: Zemuhe fault, DLSF: Daliangshan fault, LMSFZ: Longmenshan fault zone, LJ-XJHF: Lijiang-Xiaojinhe fault, XGDF: Xigeda fault, YMF: Yuanmou fault, CMSF: Caimashui fault, QJF: Qujiang fault, SJF: Shiping-Jianshui fault.</p>
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<p>Geological features and fault distributions near the Caimashui fault. Lithological data are obtained from 1:200,000 geologic maps (<a href="https://www.ngac.org.cn" target="_blank">https://www.ngac.org.cn</a>).</p>
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<p>Tectonic landforms caused by the Caimashui fault near Huoshi Town (see location in <a href="#remotesensing-16-03203-f002" class="html-fig">Figure 2</a>). (<b>a</b>) Satellite image (from Google Earth) of the fault trace. (<b>b</b>) Tectonic landforms around the Sanjiaozhuang site. (<b>c</b>) Tectonic landforms around the Xiaochacun site. (<b>d</b>) Tectonic landforms around the Tangjiawan site. (<b>e</b>) Tectonic landforms around the Huoshi Town site. For locations, see <a href="#remotesensing-16-03203-f003" class="html-fig">Figure 3</a>a. Red arrows and red lines indicate the location of the fault.</p>
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<p>Tectonic landforms around the Xiaochacun trench; see location in <a href="#remotesensing-16-03203-f003" class="html-fig">Figure 3</a>c. (<b>a</b>) Shaded relief map (from UAV-derived DEM) and interpreted map, showing the fault scarp, fault trough, and offset terrace. (<b>b</b>) Aerial image showing the tectonic landforms along the fault. (<b>c</b>) Field photo of the offset terrace. (<b>d</b>) Field photo of the ground fissures. (<b>e</b>) Aerial photo of the Xiaochacun trench, with broken white lines indicating fault scarps. (<b>f</b>) Field photo of the fault scarp.</p>
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<p>(<b>a</b>) Photo mosaic and (<b>b</b>) interpreted map of the west wall of the Xiaochacun trench. (<b>c</b>) Photo mosaic and (<b>d</b>) interpreted map of the east wall of the Xiaochacun trench. Black lines indicate the stratigraphic contacts between units. Red lines indicate the fault planes. Black dots show the locations of the radiocarbon samples, labeled with their corresponding calibrated ages.</p>
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<p>Sketch maps showing the formation and evolution of sag ponds in Xiaochacun. (<b>a</b>,<b>b</b>) Ridges and gullies before the formation of the sag ponds; (<b>c</b>,<b>d</b>) show the fault displacing the ridges, leading to the formation of sag ponds 1 and 2; (<b>e</b>,<b>f</b>) show the gullies cutting through the sag ponds, resulting in the abandonment of the sag ponds and their subsequent displacement by ongoing fault activity.</p>
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<p>Geometrical and tectonic model of the Sichuan-Yunnan tectonic zone. (<b>a</b>) Fault slip rates and the distribution of strong earthquakes on the Sichuan-Yunnan block. (<b>b</b>) A cartoon model showing that the slip rate difference between the left-slip faults and right-slip faults inside the block leads to counterclockwise rotation (modified from [<a href="#B8-remotesensing-16-03203" class="html-bibr">8</a>]). WYMB: West Yunnan microblock; CYMB: Central Yunnan microblock; NCF: Nanhua-Chuxiong fault; JSJF: Jinshajiang fault; SJF: Shiping-Jianshui fault; QJF: Qujiang fault.</p>
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7 pages, 1215 KiB  
Case Report
From Pancytopenia to Hyperleukocytosis, an Unexpected Presentation of Immune Reconstitution Inflammatory Syndrome in an Infant with Methylmalonic Acidemia
by Samuel Sassine, Amandine Remy, Tanguy Demaret, François Proulx, Julie Autmizguine, Fatima Kakkar, Thai Hoa Tran, Caroline Laverdière, Ellery T. Cunan, Catalina Maftei, Grant Mitchell, Hélène Decaluwe and Jade Hindié
Children 2024, 11(8), 990; https://doi.org/10.3390/children11080990 - 14 Aug 2024
Viewed by 961
Abstract
A 2.5-month-old girl admitted for failure to thrive and severe pancytopenia was diagnosed with methylmalonic acidemia (MMA) secondary to transcobalamin II deficiency, an inborn error of vitamin B12 metabolism. Opportunistic Cytomegalovirus and Pneumocystis jirovecii pneumonia led to severe acute respiratory distress syndrome (ARDS) [...] Read more.
A 2.5-month-old girl admitted for failure to thrive and severe pancytopenia was diagnosed with methylmalonic acidemia (MMA) secondary to transcobalamin II deficiency, an inborn error of vitamin B12 metabolism. Opportunistic Cytomegalovirus and Pneumocystis jirovecii pneumonia led to severe acute respiratory distress syndrome (ARDS) and immune reconstitution inflammatory syndrome (IRIS) after treatment initiation with vitamin B12 supplementation. In children with interstitial pneumonia-related ARDS, normal lymphocyte count should not delay invasive procedures required to document opportunistic infections. MMA can be associated with underlying lymphocyte dysfunction and vitamin B12 supplementation can fully reverse the associated immunodeficiency. IRIS may appear in highly treatment-responsive forms of pancytopenia in children and prompt treatment of dysregulated inflammation with high-dose corticosteroids should be initiated. Full article
(This article belongs to the Section Pediatric Allergy and Immunology)
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<p>After hydroxocobalamin treatment, the white blood cell (WBC) count dramatically increased and the respiratory status of the patient deteriorated, both compatible with immune reconstitution inflammatory syndrome (IRIS). One month after hydroxocobalamin treatment, coupled with a 2 week corticosteroid course, complete blood count normalized. White blood cells (<b>A</b>) and neutrophils (<b>B</b>) responded dramatically to hydroxocobalamin treatment. Platelets (<b>C</b>) normalized after a delayed overshoot. Hemoglobin (<b>D</b>) slowly normalized after a rapid increase in reticulocytes (<b>D</b>) (Rtc, gray curve) soon after hydroxocobalamin injection.</p>
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<p>Patients X-ray, CT-scan and growth charts. Chest CT-scan confirming severe interstitial lung disease (<b>A</b>), chest X-ray showing interstitial lung disease (<b>B</b>), patient weight (<b>C</b>) and height (<b>D</b>) growth chart. The red lines represent the patient’s curve.</p>
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9 pages, 429 KiB  
Article
Adherence to Cysteamine Therapy Among Patients Diagnosed with Cystinosis in Saudi Arabia: A Prospective Cohort Study
by Reem Algasem, Nedaa Zainy, Essam Alsabban, Hamad Almojalli, Khalid Alhasan, Tariq Ali, Deiter Broering and Hassan Aleid
Pharmacy 2024, 12(4), 123; https://doi.org/10.3390/pharmacy12040123 - 8 Aug 2024
Viewed by 672
Abstract
Cystinosis is a rare autosomal recessive disorder in which cystine crystals accumulate within the cellular lysosomes, causing damage to multiple organs. Due to challenges with the stringent cysteamine treatment regimen and side effects, adherence is often sub-optimal. This study aimed to assess the [...] Read more.
Cystinosis is a rare autosomal recessive disorder in which cystine crystals accumulate within the cellular lysosomes, causing damage to multiple organs. Due to challenges with the stringent cysteamine treatment regimen and side effects, adherence is often sub-optimal. This study aimed to assess the level of adherence to cysteamine therapy among cystinosis patients in Saudi Arabia and its impact on their quality of life. Electronic medical record data of 39 cystinosis patients from the Department of Nephrology at King Faisal Specialist Hospital and Research Center in Saudi Arabia were reviewed, and 25 patients were included in this study. Out of the 25 patients included in the final analysis, 64% (n = 16) were female. The mean age was 19.04 years. Almost all patients (23/25, 92%) were on oral IR cysteamine therapy, and 52% (13/25) were on topical cysteamine eye drop treatment. Of the 15 patients who responded to the Morisky Medication Adherence Scale-8 (MMAS-8) questionnaire, only 4 (26.7%) were highly adherent to cysteamine therapy. Most of the respondents (7/15, 46.7%) showed a medium level of treatment adherence. Based on the medication possession ratio for oral cysteamine, only 6 out of 23 patients (26.1%) were found to be 96–100% adherent. For the cysteamine eye drops, only 5/13 patients (38.4%) were 76–95% adherent. The 36-Item Short Form Health Survey (SF-36) used to assess patients’ health-related outcomes showed that their quality of life was affected in the domains of ‘social functioning’ and ‘energy/fatigue.’ Despite a small sample size, this study shows sub-optimal adherence to cysteamine treatment in patients from Saudi Arabia. The possible reasons for low treatment adherence could be a high frequency of administration and treatment-related side effects. Full article
(This article belongs to the Section Pharmacy Practice and Practice-Based Research)
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<p>Patient recruitment scheme.</p>
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25 pages, 7059 KiB  
Article
Propionic Acidemia, Methylmalonic Acidemia, and Cobalamin C Deficiency: Comparison of Untargeted Metabolomic Profiles
by Anna Sidorina, Giulio Catesini, Elisa Sacchetti, Cristiano Rizzo and Carlo Dionisi-Vici
Metabolites 2024, 14(8), 428; https://doi.org/10.3390/metabo14080428 - 2 Aug 2024
Viewed by 606
Abstract
Methylmalonic acidemia (MMA), propionic acidemia (PA), and cobalamin C deficiency (cblC) share a defect in propionic acid metabolism. In addition, cblC is also involved in the process of homocysteine remethylation. These three diseases produce various phenotypes and complex downstream metabolic effects. In this [...] Read more.
Methylmalonic acidemia (MMA), propionic acidemia (PA), and cobalamin C deficiency (cblC) share a defect in propionic acid metabolism. In addition, cblC is also involved in the process of homocysteine remethylation. These three diseases produce various phenotypes and complex downstream metabolic effects. In this study, we used an untargeted metabolomics approach to investigate the biochemical differences and the possible connections among the pathophysiology of each disease. The significantly changed metabolites in the untargeted urine metabolomic profiles of 21 patients (seven MMA, seven PA, seven cblC) were identified through statistical analysis (p < 0.05; log2FC > |1|) and then used for annotation. Annotated features were associated with different metabolic pathways potentially involved in the disease’s development. Comparative statistics showed markedly different metabolomic profiles between MMA, PA, and cblC, highlighting the characteristic species for each disease. The most affected pathways were related to the metabolism of organic acids (all diseases), amino acids (all diseases), and glycine and its conjugates (in PA); the transsulfuration pathway; oxidative processes; and neurosteroid hormones (in cblC). The untargeted metabolomics study highlighted the presence of significant differences between the three diseases, pointing to the most relevant contrast in the cblC profile compared to MMA and PA. Some new biomarkers were proposed for PA, while novel data regarding the alterations of steroid hormone profiles and biomarkers of oxidative stress were obtained for cblC disease. The elevation of neurosteroids in cblC may indicate a potential connection with the development of ocular and neuronal deterioration. Full article
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<p>PCA obtained from untargeted metabolomics data acquired by C18 and HILIC columns in negative ionization mode. Both experimental conditions demonstrate the major separation of the cblC group and the closer similarity between the MMA and PA groups.</p>
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<p>Pathway enrichment analysis. Node size (pathway impact) corresponds to the relative number and position of matched metabolites in the selected pathway; colors, varying from yellow to red, indicate the different levels of significance. The named pathways include only those with <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Conventional organic acid biomarkers of MMA, PA, and cblC: (<b>a</b>) methylmalonic acid, (<b>b</b>) 2-methylcitric acid, (<b>f</b>) 2-methyl-3-hydroxy-valeric acid, (<b>g</b>) 2-methyl-oxo-valeric acid, (<b>h</b>) 3-oxo-valeric acid; Krebs cycle organic acids (<b>c</b>) citric acid, (<b>d</b>) malic acid, (<b>e</b>) fumaric acid; and ketones (<b>i</b>) 2-butanone, (<b>j</b>) 3-pentanone significantly changed between three acidemias. *—<span class="html-italic">p</span>-value &lt; 0.05; **—<span class="html-italic">p</span>-value &lt; 0.01; ***—<span class="html-italic">p</span>-value &lt; 0.001; N.S.—non-significant.</p>
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<p>Significantly changed amino acids: (<b>a</b>) valine, (<b>b</b>) isoleucine, (<b>c</b>) threonine, (<b>m</b>) lysine; and small peptides (<b>d</b>) valylvaline, (<b>e</b>) isoleucylvaline, (<b>f</b>) isoleucylalanine, (<b>g</b>) glutamylisoleucine, (<b>h</b>) butyl-alpha-aspartyl-allothreoninate, (<b>j</b>) aspartyl-phenylalanine, (<b>k</b>) prolylproline, (<b>l</b>) glycylglycyl-alanyl-2-methylalanine increased in cblC may be a result of dietary differences between groups. Significantly changed levels of (<b>i</b>) dimethylglycine, (<b>n</b>) citrulline, (<b>o</b>) methionine, and (<b>p</b>) glycine reflect the involvement of different metabolic pathways in the diseases. *—<span class="html-italic">p</span>-value &lt; 0.05; **—<span class="html-italic">p</span>-value &lt; 0.01; ***—<span class="html-italic">p</span>-value &lt; 0.001; N.S.—non-significant.</p>
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<p>Glycine and carnitine conjugates. Glycine conjugates increased only in PA group: (<b>a</b>) propionylglycine, (<b>b</b>) butyrylglycine, (<b>c</b>) tiglylglycine, (<b>g</b>) glycine conjugate of propionylcarnitine; carnitine conjugates increased in MMA and PA: (<b>e</b>) propionylcarnitine; and in MMA and cblC: (<b>f</b>) c4DC-carnitine; (<b>d</b>) free carnitine had no differences between groups. *—<span class="html-italic">p</span>-value &lt; 0.05; **—<span class="html-italic">p</span>-value &lt; 0.01; ***—<span class="html-italic">p</span>-value &lt; 0.001; N.S.—non-significant.</p>
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<p>Increased (<b>a</b>) homocysteine and transsulfuration pathway metabolites in cblC: (<b>b</b>) cystathionine, (<b>c</b>) cysteine, (<b>d</b>) 2-hydroxybyryric acid; and oxidized sulfur-containing anions: (<b>e</b>) sulfuric and (<b>f</b>) thiosulfuric acid. *—<span class="html-italic">p</span>-value &lt; 0.05; **—<span class="html-italic">p</span>-value &lt; 0.01; ***—<span class="html-italic">p</span>-value &lt; 0.001; N.S.—non-significant.</p>
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<p>New characteristic compounds of cblC disease. (<b>a</b>) Oxidative stress biomarkers. (<b>b</b>) Steroid hormones with putative annotations belonging to androstane core class, namely 3β,8xi,9xi,14xi,17β-androst-5-ene-3,17-diyl bis hydrogen sulfate, androsterone sulfate, 16α-hydroxydehydroepiandrosterone-3-sulfate, 4-androstene-3β,17β-diol disulfate, dehydroepiandrosterone sulfate, 16,17-dihydroxyandrost-5-en-3-yl hydrogen sulfate, 9-hydroxyandrosta-1,4-diene-3,17-dione, and pregnane core class, namely 3β-(phenylacetoxy)pregna-5-ene-20-one; 3,20-dioxopregn-4-en-17-yl 4-methylbenzoate; 3α,5α-20-oxopregnan-3-yl beta-D-glucopyranosiduronic acid. *—<span class="html-italic">p</span>-value &lt; 0.05; **—<span class="html-italic">p</span>-value &lt; 0.01; ***—<span class="html-italic">p</span>-value &lt; 0.001; N.S.—non-significant.</p>
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<p>The CxHyNO features significantly increased in PA. ***—<span class="html-italic">p</span>-value &lt; 0.001; N.S.—non-significant.</p>
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<p>(<b>a</b>) The heatmap based on the 25 most up-/down-regulated features in PA (<span class="html-italic">p</span> &lt; 0.001); (<b>b</b>) the heatmap based on the 25 most up-/down-regulated features in MMA (<span class="html-italic">p</span> &lt; 0.001); (<b>c</b>) the heatmap based on the 25 most up-/down-regulated features in cblC (<span class="html-italic">p</span> &lt; 0.001).</p>
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<p>The most relevant findings from the relative comparison of the metabolomic profiles in PA, MMA, and cblC. ↑ (↓)—metabolites significantly increased (decreased) with respect to other two acidemias. Dashed boxes—physiological processes involving significantly changed metabolites.</p>
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24 pages, 26872 KiB  
Article
Opening and Post-Rift Evolution of Alpine Tethys Passive Margins: Insights from 1D Numerical Modeling of the Jurassic Mikulov Formation in the Vienna Basin Region, Austria
by Darko Spahić, Eun Young Lee, Aleksandra Šajnović and Rastimir Stepić
Geosciences 2024, 14(8), 202; https://doi.org/10.3390/geosciences14080202 - 30 Jul 2024
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Abstract
This study employed 1D numerical pseudo models to examine the Upper Jurassic carbonate succession, focusing on the Mikulov Formation in the Vienna Basin region. It addresses the protracted and complex history of the Jurassic source rock play, revealing a transition from rapid syn-rift [...] Read more.
This study employed 1D numerical pseudo models to examine the Upper Jurassic carbonate succession, focusing on the Mikulov Formation in the Vienna Basin region. It addresses the protracted and complex history of the Jurassic source rock play, revealing a transition from rapid syn-rift (>200 m/Ma) to slower post-rift sedimentation/subsidence of the overlying layers during extensional deformation (up to 120 m/Ma with a thickness of 1300 m). This provides valuable insights into the rift-to-drift stage of the central Alpine Tethys margin. The Mikulov marls exhibit characteristics of a post-rift passive margin with slow sedimentation rates. However, a crustal stretching analysis using syn-rift heat flow sensitivity suggested that thermal extension of the basement alone cannot fully explain the mid-Jurassic syn-rift stage in this segment of the Alpine Tethys. The sensitivity analysis showed that the mid-late Jurassic differential syn-rift sequences were exposed to slightly cooler temperatures than the crustal stretching model predicted. Heat flow values below 120 mW/m2 aligned with measurements from deeply settled Mesozoic successions, suggesting cold but short gravity-driven subsidence. This may account for the relatively low thermal maturation of the primary source rock interval identified by the time-chart analysis, despite the complex tectonic history and considerable sedimentary burial. The post-Mesozoic changes in the compaction trend are possibly linked to the compressional thrusting of the Alpine foreland and postdating listric faulting across the Vienna Basin. Full article
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<p>(<b>a</b>) Tectonic outline of the Alpine–Carpathian system in central, eastern, and southern Europe, encompassing the Vienna Basin (VB) and surrounding regions (Molasse Zone, Waschberg Unit (WU), Flysch Zone, Northern Calcareous Alps (NCA), and Central Alps). In the Vienna Basin, major fault lines on the pre-Neogene surface, including the Steinberg fault (SF) and the Vienna Basin Transfer Fault (VBTF), are shown (based on [<a href="#B9-geosciences-14-00202" class="html-bibr">9</a>,<a href="#B10-geosciences-14-00202" class="html-bibr">10</a>,<a href="#B11-geosciences-14-00202" class="html-bibr">11</a>]). (<b>b</b>) Geological profile (Section A) across the central Vienna Basin, Molasse Basin, and underlying tectonic units (revised from [<a href="#B12-geosciences-14-00202" class="html-bibr">12</a>]).</p>
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<p>(<b>a</b>) Paleogeography map of the Late Jurassic (~150 Ma), showing the Alpine Tethys, passive margin, and surroundings (red square). The area where the Late Jurassic carbonates were deposited and subsequently became part of the Vienna Basin’s basement is approximately indicated with a yellow square. The paleogeographical reconstruction is from [<a href="#B21-geosciences-14-00202" class="html-bibr">21</a>]. (<b>b</b>) Jurassic to Neogene development model of the Vienna Basin region (based on [<a href="#B22-geosciences-14-00202" class="html-bibr">22</a>,<a href="#B23-geosciences-14-00202" class="html-bibr">23</a>]).</p>
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<p>Stratigraphic framework, depositional environment, and tectonic phases of the Vienna Basin region, encompassing the autochthonous and allochthonous units and the Neogene sedimentary succession. Major petroleum system elements (PSEs) are indicated (based on [<a href="#B19-geosciences-14-00202" class="html-bibr">19</a>,<a href="#B22-geosciences-14-00202" class="html-bibr">22</a>,<a href="#B25-geosciences-14-00202" class="html-bibr">25</a>,<a href="#B26-geosciences-14-00202" class="html-bibr">26</a>,<a href="#B41-geosciences-14-00202" class="html-bibr">41</a>,<a href="#B42-geosciences-14-00202" class="html-bibr">42</a>,<a href="#B43-geosciences-14-00202" class="html-bibr">43</a>,<a href="#B44-geosciences-14-00202" class="html-bibr">44</a>,<a href="#B45-geosciences-14-00202" class="html-bibr">45</a>,<a href="#B46-geosciences-14-00202" class="html-bibr">46</a>]).</p>
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<p>(<b>a</b>) The structure map of the Vienna Basin, showing the faulted pre-Neogene basement surface with major oil and gas fields (modified from [<a href="#B11-geosciences-14-00202" class="html-bibr">11</a>,<a href="#B25-geosciences-14-00202" class="html-bibr">25</a>]). Locations of Zistersdorf Depression (ZD) and wells Maustrenk ÜT1 (M) and Zistersdorf ÜT (Z) are indicated. AT—Austria; SK—Slovakia; CZ—Czech Rep. (<b>b</b>) Geological cross-section across the Steinberg fault and Zistersdorf depression in the Vienna Basin, illustrating the autochthonous and allochthonous units and the assumed deeper basement structure. Major stratigraphic and structural units with well positions are marked (revised from [<a href="#B23-geosciences-14-00202" class="html-bibr">23</a>]).</p>
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<p>Geological cross-section providing a comprehensive view of the Alpine thrust sheets in the Vienna Basin region, derived from 2D seismic data (see <a href="#geosciences-14-00202-f001" class="html-fig">Figure 1</a>a for Section B location; based on [<a href="#B13-geosciences-14-00202" class="html-bibr">13</a>] and references therein). This section depicts the thrust units and zones characterized by active extensional detachment and Miocene sedimentation as well as out-of-sequence thrusting. In the context of our study, the detachment layers, predominantly comprised of Jurassic Mikulov Fm., are of particular importance.</p>
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<p>(<b>a</b>) Mikulov isopach map, depicting thickness beneath the central Vienna and its surrounding areas (revised from [<a href="#B14-geosciences-14-00202" class="html-bibr">14</a>]). (<b>b</b>) Vitrinite reflectance trend with increasing depth (data from [<a href="#B14-geosciences-14-00202" class="html-bibr">14</a>] and references therein).</p>
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<p>Boundary conditions for our models in PetroMod. (<b>a</b>) Standard heat flow values following the syn-rift stage based on the McKenzie model [<a href="#B39-geosciences-14-00202" class="html-bibr">39</a>], with an approximate value of 120 mW/m<sup>2</sup> from 190 Ma to 170 Ma. (<b>b</b>) Mean surface temperature, providing constraints on the temperatures at the bottom of the basin in southern Europe, based on data from [<a href="#B75-geosciences-14-00202" class="html-bibr">75</a>]. (<b>c</b>) Sediment–Water-Interface Temperature (SWIT) setting for southern Europe. (<b>d</b>) Paleowater depth (PWD) trends.</p>
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<p>Computed sedimentation rates by 1D pseudo modeling; different 1D input data of (<b>a</b>) 400 m, (<b>b</b>) 1300 m, and (<b>c</b>) 700 m in thickness.</p>
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<p>Time plots for computed parameters of the Mikulov Fm. from the Late Jurassic to the present day using different 1D input data; (<b>a</b>) 400 m, (<b>b</b>) 1300 m, and (<b>c</b>) 700 m thicknesses. The parameters shown include the maximum effective stress, layer thickness over time, sedimentation rate, and EASY%Ro. At the end of the Jurassic and the beginning of the Cretaceous, the sedimentation rates (blue line) showed an abrupt decrease; the computed layer thickness (pale red line) decreased due to compaction and tectonic exhumation; the thermal maturity (green line) remained low throughout the rifting, post-rift, and tectonic exhumation periods.</p>
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<p>Tests of crustal models relative to varying syn-rift heat flow values. Colors indicate present-day thermal maturation levels; yellow denotes overmature stages, red denotes the gas generation stage, green represents different stages of the oil window, and blue denotes the not matured sections. (<b>a</b>,<b>b</b>) show differences in the computed depth-related temperature for different Mesozoic formations.</p>
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<p>Time-depth diagrams based on the model’s analysis of Jurassic–Paleogene events, applying a thickness of 1300 m for the Mikulov Fm. (<b>a</b>) A 2D section model showing the change in computed subsurface heat flow according to paleowater depth input data (maximum water depth during the syn-rift). (<b>b</b>) Computed heat flow according to sedimentation rates. (<b>c</b>) Computed thermal maturity. Please note that the values were changed after the Paleocene events.</p>
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<p>(<b>a</b>) Approximation of Mikulov detachment during the onset of extension (Oligocene). PA1–3 indicate the differential pressures on the margin. (<b>b</b>) Extensional displacement following the remobilization of detachment. The remobilization is followed by the expulsion onset of fluids and gases (see green and red in (<b>a</b>)). The curve shows how the workaround considers the footwall downwelling of subthrust layers (at the expense of hanging wall upthrusting during the Alpine orogeny). (<b>c</b>) Parameters used for interpretation and calibration were temperature, burial history, effective porosity, bulk density, hydrocarbon generation pressure, overpressure, and lithostatic pressure.</p>
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22 pages, 8679 KiB  
Article
An Analysis of the Mechanisms Involved in Glacial Lake Outburst Flooding in Nyalam, Southern Tibet, in 2018 Based on Multi-Source Data
by Yixing Zhao, Wenliang Jiang, Qiang Li, Qisong Jiao, Yunfeng Tian, Yongsheng Li, Tongliang Gong, Yanhong Gao and Weishou Zhang
Remote Sens. 2024, 16(15), 2719; https://doi.org/10.3390/rs16152719 - 24 Jul 2024
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Abstract
Glacial Lake Outburst Flood (GLOF) events, particularly prevalent in Asia’s High Mountain regions, pose a significant threat to downstream regions. However, limited understanding of triggering mechanisms and inadequate observations pose significant barriers for early warnings of impending GLOFs. The 2018 Nyalam GLOF event [...] Read more.
Glacial Lake Outburst Flood (GLOF) events, particularly prevalent in Asia’s High Mountain regions, pose a significant threat to downstream regions. However, limited understanding of triggering mechanisms and inadequate observations pose significant barriers for early warnings of impending GLOFs. The 2018 Nyalam GLOF event in southern Tibet offers a valuable opportunity for retrospective analysis. By combining optical and radar remote sensing images, meteorological data, and seismicity catalogs, we examined the spatiotemporal evolution, triggering factors, and the outburst mechanism of this event. Our analysis reveals a progressive retreat of 400–800 m for the parent glaciers between 1991 and 2018, increasing the runoff areas at glacier termini by 167% from 2015 to 2018 and contributing abundant meltwater to the glacial lake. In contrast, the lake size shrunk, potentially due to a weakening moraine dam confirmed by SAR interferometry, which detected continuous subsidence with a maximum line-of-sight (LOS) rate of ~120 mm/a over the preceding ~2.5 years. Additionally, temperature and precipitation in 2018 exceeded the prior decade’s average. Notably, no major earthquakes preceded the event. Based on these observations, we propose a likely joint mechanism involving high temperatures, heavy precipitation, and dam instability. An elevated temperature and precipitation accelerated glacial melt, increasing lake water volume and seepage through the moraine dam. This ultimately compromised dam stability and led to its failure between 3 August 2018 and 6 August 2018. Our findings demonstrate the existence of precursory signs for impending GLOFs. By monitoring the spatiotemporal evolution of environmental factors and deformation, it is possible to evaluate glacial lake risk levels. This work contributes to a more comprehensive understanding of GLOF mechanisms and is of significant importance for future glacial lake risk assessments. Full article
(This article belongs to the Section Earth Observation for Emergency Management)
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<p>Location plots of the study area. (<b>a</b>) Map around the Tibetan Plateau. (<b>b</b>) Topography of the study area. The red rectangle denotes the Sentienl-1 data coverage. The red pentagram represents the location of the 2018 Nyalam GLOF. The red circles denote historical earthquakes (1930–2018, M &gt; 5.0) around the study area. F1–F3 represent three active faults near the glacial lake. F1: Nam Co–Xuru Couture fault; F2: the South Tibetan Detachment System (STDS); F3: the Main Central Thrust (MCT). (<b>c</b>) Three-dimensional topographic map of the study area. The overlaid imagery is from Google Earth. GL-A and GL-B represent glacial lakes A and B, respectively. G-a, G-b, and G-c represent parent glaciers a, b, and c, respectively.</p>
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<p>The workflow of this study.</p>
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<p>Schematic diagram of the indicator analysis.</p>
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<p>Sentinel-1 T121 interferograms for the SBAS-InSAR analysis.</p>
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<p>G-b terminus change in the period 1991–2019. The yellow line is the extent of the glacier in 1991; the pink line is the extent of the glacier in each year. Images (<b>1</b>–<b>20</b>) are Landsat 30 m TM/ETM+ images; images (<b>21</b>,<b>22</b>,<b>24</b>,<b>25</b>) are 16 m Gaofen-1 WFV images; and images (<b>23</b>,<b>26</b>,<b>27</b>) are 2 m Gaofen-1 PMS, Gaofen-2 PMS, and Gaofen-6 PMS images, respectively.</p>
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<p>G-c terminus change in the period 1991–2019. The yellow line is the extent of the glacier in 1991; the pink line is the extent of the glacier in each year. Images (<b>1</b>–<b>20</b>) are Landsat 30 m TM/ETM+ images; images (<b>21</b>,<b>22</b>,<b>24</b>,<b>25</b>) are 16 m Gaofen-1 WFV images; and images (<b>23</b>,<b>26</b>,<b>27</b>) are 2 m Gaofen-1 PMS, Gaofen-2 PMS, and Gaofen-6 PMS images, respectively.</p>
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<p>The glacial lake extent change in the period 1991–2019. Images (<b>1</b>–<b>20</b>) use Landsat TM/ETM data with a spatial resolution of 30 m; images (<b>21</b>,<b>22</b>,<b>24</b>,<b>25</b>) use Gaofen-1 WFV data with a spatial resolution of 16 m; images (<b>23</b>,<b>26</b>,<b>27</b>) use Gaofen-1 PMS, Gaofen-2 PMS, and Gaofen-6 PMS data, respectively, with a spatial resolution of 2 m; and image (<b>27</b>) is the aftermath of the GLOF.</p>
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<p>Area changes for lakes and glaciers. (<b>a</b>) Extents of GL-A and GL-B lakes; (<b>b</b>,<b>c</b>) extents of glacier G-b and G-c, respectively; (<b>d</b>–<b>g</b>) plots of the GL-A area, GL-B area, the distance between GL-A and G-b, and the distance between GL-A and G-c, respectively. The dotted lines represent the trend line.</p>
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<p>Optical remote sensing image recognition of glacier terminus flow channel. The black rectangles represent the range of the glacier terminus flow channel. (<b>a</b>,<b>b</b>) The optical remote sensing images from different periods before the GLOF event.</p>
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<p>Surface deformation monitoring results of the mountains around the glacial lake. (<b>a</b>) The surface deformation monitored as a whole; (<b>b</b>) an enlarged version of (<b>a</b>). P1–P6 are the selected typical deformation areas.</p>
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<p>The time-series deformation results of <a href="#remotesensing-16-02719-f010" class="html-fig">Figure 10</a>.</p>
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<p>The faults and seismic data for the year prior to the GLOF. The red circles are earthquakes that occurred around the glacier up to one year before the GLOF. The brown and yellow lines are the 2015 Nepal Earthquake Intensity Map from the USGS. The glacial lake is located in the intensity area of the Nepal M8.1 earthquake in 2015.</p>
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<p>Meteorological conditions from January to August 2018, measured at the Tingri weather station, compared to the long-term climatology data (1976–2015). The pink columns represent the time points of GLOF occurrences.</p>
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<p>Meteorological conditions from January to August 2018, measured at the Tingri weather station, compared to the long-term climatology data (1976–2015). The pink columns represent the time points of GLOF occurrences.</p>
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10 pages, 772 KiB  
Case Report
Renal Replacement Therapy in Methylmalonic Aciduria-Related Metabolic Failure: Case Report and Literature Review
by Giovanni Pintus, Nicola Vitturi, Gianni Carraro, Livia Lenzini, Giorgia Gugelmo, Ilaria Fasan, Alberto Madinelli, Alberto Burlina, Angelo Avogaro and Lorenzo Arcangelo Calò
J. Clin. Med. 2024, 13(15), 4304; https://doi.org/10.3390/jcm13154304 - 23 Jul 2024
Viewed by 727
Abstract
Background: Methylmalonic Aciduria (MA) without homocystinuria (or isolated MA) is a group of rare inherited metabolic disorders which leads to the accumulation of methylmalonic acid (MMA), a toxic molecule that accumulates in blood, urine, and cerebrospinal fluid, causing acute and chronic complications including [...] Read more.
Background: Methylmalonic Aciduria (MA) without homocystinuria (or isolated MA) is a group of rare inherited metabolic disorders which leads to the accumulation of methylmalonic acid (MMA), a toxic molecule that accumulates in blood, urine, and cerebrospinal fluid, causing acute and chronic complications including metabolic crises, acute kidney injury (AKI), and chronic kidney disease (CKD). Detailed Case Description: Herein, we report a case of a 39-year-old male with MA and stage IV CKD who experienced acute metabolic decompensation secondary to gastrointestinal infection. The patient underwent a single hemodialysis (HD) session to correct severe metabolic acidosis unresponsive to medical therapy and to rapidly remove MMA. The HD session resulted in prompt clinical improvement and shortening of hospitalization. Discussion: MMA accumulation in MA patients causes acute and life-threatening complications, such as metabolic decompensations, and long-term complications such as CKD, eventually leading to renal replacement therapy (RRT). Data reported in the literature show that, overall, all dialytic treatments (intermittent HD, continuous HD, peritoneal dialysis) are effective in MMA removal. HD, in particular, can be useful in the emergency setting to control metabolic crises, even with GFR > 15 mL/min. Kidney and/or liver transplantations are often needed in MA patients. While a solitary transplanted kidney can be rapidly affected by MMA exposure, with a decline in renal function even in the first year of follow-up, the combined liver–kidney transplantation showed better long-term results due to a combination of reduced MMA production along with increased urinary excretion. Conclusions: Early diagnosis, multidisciplinary management and preventive measures are pivotal in MA patients to avoid recurrent AKI episodes and, consequently, to slow down CKD progression. Full article
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<p>Trends over the last 6 years in renal function and methylmalonic acid levels. The raw data and trend for eGFR (mL/min, CKD-EPI formula) are reported in red; those for plasma and urinary methylmalonic acid (p-MMA, μmol/L; u-MMA, mmol/mol) are reported in blue and brown, respectively. Hospitalizations during the follow-up period are marked in purple for acute kidney injury on chronic kidney disease, green for worsening of peripheral edema, red for the hospitalization referred to in this case report. Data included from the referral of the patient to our Center for Metabolic Disorders (Azienda Ospedaliera di Padova, Padova, Italy) in 2018.</p>
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7 pages, 398 KiB  
Case Report
Biochemical Pattern of Methylmalonyl-CoA Epimerase Deficiency Identified in Newborn Screening: A Case Report
by Evelina Maines, Roberto Franceschi, Francesca Rivieri, Giovanni Piccoli, Björn Schulte, Jessica Hoffmann, Andrea Bordugo, Giulia Rodella, Francesca Teofoli, Monica Vincenzi, Massimo Soffiati and Marta Camilot
Int. J. Neonatal Screen. 2024, 10(3), 53; https://doi.org/10.3390/ijns10030053 - 18 Jul 2024
Viewed by 666
Abstract
Methylmalonyl-CoA epimerase enzyme (MCEE) is responsible for catalyzing the isomeric conversion between D- and L-methylmalonyl-CoA, an intermediate along the conversion of propionyl-CoA to succinyl-CoA. A dedicated test for MCEE deficiency is not included in the newborn screening (NBS) panels but it can be [...] Read more.
Methylmalonyl-CoA epimerase enzyme (MCEE) is responsible for catalyzing the isomeric conversion between D- and L-methylmalonyl-CoA, an intermediate along the conversion of propionyl-CoA to succinyl-CoA. A dedicated test for MCEE deficiency is not included in the newborn screening (NBS) panels but it can be incidentally identified when investigating methylmalonic acidemia and propionic acidemia. Here, we report for the first time the biochemical description of a case detected by NBS. The NBS results showed increased levels of propionylcarnitine (C3) and 2-methylcitric acid (MCA), while methylmalonic acid (MMA) and homocysteine (Hcy) were within the reference limits. Confirmatory analyses revealed altered levels of metabolites, including MCA and MMA, suggesting a block in the propionate degradation pathway. The analysis of methylmalonic pathway genes by next-generation sequencing (NGS) allowed the identification of the known homozygous nonsense variation c.139C>T (p.R47X) in exon 2 of the MCE gene. Conclusions: Elevated concentrations of C3 with a slight increase in MCA and normal MMA and Hcy during NBS should prompt the consideration of MCEE deficiency in differential diagnosis. Increased MMA levels may be negligible at NBS as they may reach relevant values beyond the first days of life and thus could be identified only in confirmatory analyses. Full article
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<p>The pathway of propionyl-CoA to succinyl-CoA metabolism. See <a href="#sec3dot2-IJNS-10-00053" class="html-sec">Section 3.2</a>.</p>
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27 pages, 29974 KiB  
Article
Evidence of Dextral Strike-Slip Movement of the Alakol Lake Fault in the Western Junggar Based on Remote Sensing
by Wenxing Yi, An Li, Liangxin Xu, Zongkai Hu and Xiaolong Li
Remote Sens. 2024, 16(14), 2615; https://doi.org/10.3390/rs16142615 - 17 Jul 2024
Viewed by 535
Abstract
The NW-SE-trending dextral strike-slip faults on the north side of the Tian Shan, e.g., the Karatau fault, Talas–Fergana fault, Dzhalair–Naiman fault, Aktas fault, Dzhungarian fault, and Chingiz fault, play an important role in accommodating crustal shortening. The classic viewpoint is that these strike-slip [...] Read more.
The NW-SE-trending dextral strike-slip faults on the north side of the Tian Shan, e.g., the Karatau fault, Talas–Fergana fault, Dzhalair–Naiman fault, Aktas fault, Dzhungarian fault, and Chingiz fault, play an important role in accommodating crustal shortening. The classic viewpoint is that these strike-slip faults are an adjustment product caused by the difference in the crustal shortening from west to east. Another viewpoint attributes the dextral strike-slip fault to large-scale sinistral shearing. The Alakol Lake fault is a typical dextral strike-slip fault in the north Tian Shan that has not been reported. It is situated along the northern margin of the Dzhungarian gate, stretching for roughly 150 km from Lake Ebinur to Lake Alakol. Our team utilized aerial photographs, satellite stereoimagery, and field observations to map the spatial distribution of the Alakol Lake fault. Our findings provided evidence supporting the assertion that the fault is a dextral strike-slip fault. In reference to its spatial distribution, the Lake Alakol is situated in a pull-apart basin that lies between two major dextral strike-slip fault faults: the Chingiz and Dzhungarian faults. The Alakol Lake fault serves as a connecting structure for these two faults, resulting in the formation of a mega NW-SE dextral strike-slip fault zone. According to our analysis of the dating samples taken from the alluvial fan, as well as our measurement of the displacement of the riser and gully, it appears that the Alakol Lake fault has a dextral strike-slip rate of 0.8–1.2 mm/a (closer to 1.2 mm/a). The strike-slip rate of the Alakol Lake fault is comparatively higher than that of the Chingiz fault in the northern region (~0.7 mm/a) but slower than that of the Dzhungarian fault in the southern region (3.2–5 mm/a). The Chingiz–Alakol–Dzhungarian fault zone shows a gradual decrease in deformation towards the interior of the Kazakhstan platform. Full article
(This article belongs to the Special Issue Remote Sensing for Geology and Mapping)
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<p>(<b>a</b>) The digital elevation model shows the distribution of the main Quaternary faults in the northern Tian Shan region (modified after Xu et al., 2016) [<a href="#B34-remotesensing-16-02615" class="html-bibr">34</a>]. Blue arrows show the GPS measurements from Wang and Shen (2020) [<a href="#B23-remotesensing-16-02615" class="html-bibr">23</a>]. The blue dashed lines (A–A’) show the locations of the GPS profiles. The white circles show the major cities. The black dashed boxes show the locations of <a href="#remotesensing-16-02615-f002" class="html-fig">Figure 2</a>. DZF—Dzhungarian fault; ALF—Alakol Lake fault; CF—Chingiz fault; KSHF—Kashihe fault; ETF—East Tacheng fault; TLF—TuoLi fault; and DF—Daerbute fault. (<b>b</b>) The global digital elevation model shows the tectonic location of the research area (<b>a</b>). (<b>c</b>) Swath GPS profile A–A’ shows the velocity components parallel to (blue dots) the profile striking N320°W [<a href="#B20-remotesensing-16-02615" class="html-bibr">20</a>]. The brown line and gray shadow show the mean value and range of elevation with 50 km width along the profile A–A’. The blue-shaded rectangles are the visually fitted range of the GPS velocities. The blue letters and numbers represent the GPS observation stations’ abbreviations.</p>
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<p>The extension of the Alakol Lake fault is shown on Google Earth. The red lines show the location of the fault trace. The red triangular arrows indicate dextral strike-slip movement. The black boxes are the study sites. The white circles show the major cities.</p>
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<p>Field collection locations of the OSL samples: (<b>a</b>) sample AL-01; (<b>b</b>) sample AL-02; (<b>c</b>) sample AL-03; and (<b>d</b>) sample AL-04. (<b>e</b>) The field site shows a dextral alluvial fan and the fault scarp, which is also where the sample AL-04 was collected. (<b>f</b>) Sample AL-05. (<b>g</b>) The field site indicates the fault trace and fault scarp, which is also where the sample AL-05 was collected. The red triangular arrows indicate the fault trace.</p>
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<p>Site 1: (<b>a</b>) The hillshade map, which was built from a high-resolution UAV DEM using ArcGIS 10.8, shows structural and geomorphological characters of the Alakol Lake fault. The red lines are the fault trace. The red dotted lines show that the fault traces are either unclear or covered. The red triangular arrows indicate dextral strike-slip movement. The black solid line (A–A’) marks the location of the profile in (<b>c</b>). Four stages of alluvial fans (T1–T4) are developed along the stream channel, and the shadows with different colors depict the corresponding alluvial fans. The white dashed lines and the pink dashed lines represent the fit lines of the T4 riser. The white dotted box represents the range of (<b>b</b>). (<b>b</b>) The image of the hillshade map displays a detailed view of the geomorphic surface in (<b>a</b>). The white and pink dashed lines in the image represent the fit lines. The white and pink arrows indicate the preferred offset. (<b>c</b>) Topographic profile across the fault extracted from the UAV DEM was used to measure the vertical offset. The blue dashed lines are fit lines. (<b>d</b>) The field photo shows the fault trace and alluvial fans. The white oval highlights the house for scale. (<b>e</b>) The field photo was shot in the northwest. The red dashed line represents the fault. Q represents the alluvial fan deposits (probably middle–upper Pleistocene), N represents the Neogene sandstone, and C represents the Carboniferous granite.</p>
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<p>Site 2: (<b>a</b>) The hillshade map image, which was made using the high-resolution UAV DEM, shows the geomorphological expression of the Alakol Lake fault. The red lines are the fault trace. The red triangular arrows indicate dextral strike-slip movement. The two blue curves represent the horizontal offset of the gullies. The orange curve represents the dextrally displaced ridge. The black solid lines (A–A’ and B–B’) indicate the location of the extracted fault scarp. All of the white dashed lines represent the fit lines. The white arrows indicate the preferred offset. (<b>b</b>) Two topographic profiles across the fault extracted from the UAV DEM were used to measure the vertical offset. The blue dashed lines are fit lines. (<b>c</b>) The field photo shows the dextrally displaced ridge. The dotted orange lines show the location of the ridge. The red triangles indicate the fault trace. The blue dashed line indicates the dextral channel. The white ovals highlight the people for scale.</p>
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<p>Site 3: (<b>a</b>) The hillshade map image, which was made using the high-resolution UAV DEM, shows the geomorphological expression of the Alakol Lake fault. The red lines are the fault trace, and the scales indicate the slope direction of the fault scarp. The red triangular arrows indicate dextral strike-slip movement. The black dotted box represents the range of Figure c. The orange shadows represent T1, and purple shadows represent T2. The blue curves represent the dextrally displaced edge of the alluvial fans, and the white dashed lines represent the fit lines. The white arrows indicate the preferred offset. The black solid lines (A–A’ and B–B’) indicate the location of the extracted fault scarps. (<b>b</b>) Topographic profiles across the fault extracted from the UAV DEM were used to measure the vertical offset. The blue dashed lines are fit lines. (<b>c</b>) A photo taken by the drone shows the fault traces and a pull-apart basin.</p>
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<p>Site 4: (<b>a</b>) The hillshade map image, which was made using the high-resolution UAV DEM, shows the geomorphological expression of the Alakol Lake fault. The red line is the fault trace, and the scales indicate the slope direction of the fault scarp. Two red triangular arrows indicate dextral strike-slip movement. The orange shadow represents T1, and the purple shadows represent T2. The blue curves with arrows represent the dextrally displaced gullies, and the white dashed lines represent the fit lines. The white arrows indicate the preferred offset. The spring symbol composed of the blue circle and blue curve indicates the location of the fault spring. The black solid lines (A–A’, B–B’) indicate the location of the extracted fault scarps. The black dotted box represents the range of (<b>b</b>,<b>c</b>). (<b>b</b>) The enlarged hillshade map image shows the more detailed geomorphic surface in (<b>a</b>). Four identical red triangles indicate the fault trace. (<b>c</b>) A field photo of the range corresponding to (<b>b</b>). (<b>d</b>) Topographic profiles across the fault extracted from the UAV DEM were used to measure the vertical offset. The blue dashed lines are fit lines. (<b>e</b>) The field photo shows the dextrally displaced gully and fault scarp. (<b>f</b>) The field photo shows the fault scarp. The dotted white line indicates the geomorphic surface. Two red arrows show the fault scarp. (<b>g</b>) The picture shows the fault spring in the field.</p>
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<p>Site 5: (<b>a</b>) The hillshade map image, which was made using the high-resolution UAV DEM, shows the geomorphological expression of the Alakol Lake fault. Different colored shadows represent different alluvial fans. The red lines indicate clear fault traces, while the red dotted lines show fault traces that are either not visible or are covered. The white arrows indicate the preferred offset. The red triangular arrows indicate dextral strike-slip movement. The scales indicate the slope direction of the fault scarp. The white dashed lines represent the dextrally displaced T2 alluvial fan. The black solid lines (A–A’, B–B’) indicate the location of the extracted fault scarps. (<b>b</b>) Topographic profiles across the fault extracted from the UAV DEM were used to measure the vertical offset. The blue dashed lines are fit lines. (<b>c</b>) The field photo shows the fault trace and the different alluvial fans. The red arrows indicate the fault scarp and fault trace, and the white circle represents the iron tower as a reference.</p>
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<p>Site 6: (<b>a</b>) View of the Pleiades DEM shows the geomorphological expression of the Alakol Lake fault. (<b>b</b>) Hillshade map image, which was made using the high-resolution UAV DEM, shows the enlarged geomorphic surface. The red lines are the fault traces, and the red dotted lines show that the fault traces are not clear or are covered. The red triangular arrows indicate dextral strike-slip movement. The scales indicate the slope direction of the fault scarp. Different colored shadows represent different alluvial fans. The green curve represents the dextrally displaced alluvial fan. The blue curve represents the dextrally displaced gullies. All of the white dashed lines represent the fit lines. The white arrows indicate the preferred offset. (<b>c</b>,<b>d</b>) The fault breccia indicated by the white arrow revealed in the field.</p>
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<p>Site 7: (<b>a</b>) View of the Pleiades DEM shows some displaced alluvial fans. The translucent green shades are the alluvial fans. The red lines are the fault traces, and the red triangular arrows indicate dextral strike-slip movement. The blue curves represent the stream channels. (<b>b</b>) Hillshade map image, which was made by the high-resolution UAV DEM, shows the geomorphic surface of enlarged alluvial fan 2. (<b>c</b>) The outline of alluvial fans identified based on the texture and color characteristics in the Pleiades satellite image.</p>
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<p>Site 8: (<b>a</b>) View of the Pleiades DEM shows the fault trace and the displaced geomorphic surface. The red triangles indicate the fault trace. The blue dashed lines indicate the displaced gullies, while the yellow dashed lines indicate the displaced T3 riser. (<b>b</b>) View of the enlarged geomorphic surface shows the displaced gullies. The red triangular arrows indicate dextral strike-slip movement. (<b>c</b>) The back-slipped view of the gullies.</p>
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<p>Site 9: (<b>a</b>) The location of site 9 is shown on Google Earth. (<b>b</b>) The fault trace and geomorphic surface are shown on Google Earth. Six identical red triangles indicate the fault trace. Two red triangular arrows indicate dextral strike-slip movement. The black solid lines (A–A’ and B–B’) show where the topographic profiles were extracted. The white boxes represent the viewing areas of (<b>d</b>,<b>e</b>). (<b>c</b>) Topographic profiles (A–A’ and B–B’) across the fault extracted from the DEM were used to measure the vertical offset. The blue dashed lines are fit lines. (<b>d</b>,<b>e</b>) Some images of the displaced gullies taken on Google Earth. The blue dashed lines indicate the displaced gullies. The white dashed lines represent the fit lines. The white arrows indicate the preferred offset.</p>
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<p>(<b>a</b>) Simplified geological model map of the new fault in the western Junggar. The white arrows indicate the relative movement directions of the Tacheng Basin, Junggar Alatau, and Junggar Basin. DZF—Dzhungarian fault; ALF—Alakol Lake fault; CF—Chingiz fault; LF—Lepsy fault; KSHF—Kashihe fault; DF—Daerbute fault; TLF—TuoLi fault; ETF—East Tacheng fault; and NTF—North Tacheng fault. (<b>b</b>) Evolutionary model map of Lake Alakol and the Alakol Lake fault.</p>
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15 pages, 6639 KiB  
Article
Shear Bond Strength of Clear Aligner Attachment Using 4-META/MMA-TBB Resin Cement on Glazed Monolithic Zirconia
by Kasidit Nitasnoraset, Apiwat Riddhabhaya, Chidchanok Sessirisombat, Hitoshi Hotokezaka, Noriaki Yoshida and Irin Sirisoontorn
Polymers 2024, 16(14), 1988; https://doi.org/10.3390/polym16141988 - 11 Jul 2024
Viewed by 578
Abstract
Increasing demand for adult orthodontic treatment using clear aligners has highlighted challenges in bonding clear aligner attachments to various restorations. Specifically, the bond strength of clear aligner attachments to glazed monolithic zirconia has not been extensively studied. This study aims to compare the [...] Read more.
Increasing demand for adult orthodontic treatment using clear aligners has highlighted challenges in bonding clear aligner attachments to various restorations. Specifically, the bond strength of clear aligner attachments to glazed monolithic zirconia has not been extensively studied. This study aims to compare the shear bond strength (SBS) and mode of failure (MOF) of conventional bonding methods versus Superbond C&B (4-META/MMA-TBB resin cement) for clear aligner attachments on glazed monolithic zirconia. Fifty sintered and glazed zirconia samples were divided into five groups and attached with clear aligner attachments: Si (silane), B (bonding agent), SiB (bonding agent and silane), SU (Superbond C&B), and SiSU (silane and Superbond C&B). SBS and MOF of these samples were analyzed. Results indicated a significant difference in bond strength among the groups. SiSU exhibited the highest bond strength, followed by SU, while B had the lowest bond strength. SEM analysis revealed that SiSU and SU predominantly exhibited mixed failure, indicating high bond strength without affecting the glazed layers of the zirconia. In contrast, B exhibited only adhesive failure at the interface, resulting in insufficient bond strength for effective orthodontic treatment. In conclusion, using 4-META/MMA-TBB resin cement provides high bond strength for clear aligner attachments on glazed zirconia with minimal material damage during debonding. Full article
(This article belongs to the Special Issue Polymers Strategies in Dental Therapy)
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<p>The chemical structure of 4META/MMA molecule with TBB initiator, which undergoes polymerization and forms 4META/MMA-TBB resin cement [<a href="#B23-polymers-16-01988" class="html-bibr">23</a>].</p>
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<p>SEM micrograph with 1000× magnification of the zirconia surface after being treated with HF and superbond C&amp;B; (<b>a</b>) zirconia surface; (<b>b</b>) resin-impregnated layer; (<b>c</b>) Superbond C&amp;B.</p>
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<p>Zirconia blocks were sintered, glazed, and embedded in a polyvinylchloride tube fixed with pouring resin.</p>
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<p>A representative specimen of the glazed monolithic zirconia attached with clear aligner attachment with cross-sectional SEM image (original magnification 30×); A, zirconia layer; B, adhesive layer; C, clear aligner attachment layer; black line, zirconia-adhesive interface; white line, adhesive-base of attachment interface.</p>
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<p>The SEM-EDS (Energy Dispersive X-ray Spectroscopy) analysis image confirms the interface between the zirconia surface and composite resin attachment. In the SEM image, area A is identified as the zirconia layer, area B as the adhesive layer, and area C as the clear aligner attachment layer. (<b>a</b>) SEM image; (<b>b</b>) EDX analysis; (<b>c</b>) Elemental mapping analysis. Elemental mapping shows a thin, red-colored layer near the top with a high presence of carbon, indicating resin cement and resin composite. This area also shows a prominent presence of oxygen, suggesting an oxide layer. An orange-colored layer signifies a significant silicon presence in the composite resin, with scattered regions indicating minor aluminum content. The yellow-colored map shows potassium distributed along a specific horizontal layer, indicating its presence in the 4-META/MMA-TBB resin cement included as part of the catalyst system. Potassium is typically used to enhance adhesive properties and promote polymerization. The green-colored area reveals a substantial zirconium presence, confirming the zirconia layer predominantly in the lower part of the interface.</p>
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<p>The areas of the attachment bases were calculated using image analysis software (ImageJ software version 0.5.7, NIH, Bethesda, MD, USA) as 7.0253 mm<sup>2</sup>.</p>
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<p>The adhesive remnant index (ARI) encompasses the following values: (<b>0</b>) indicates the absence of adhesive on the zirconia surface; (<b>1</b>) indicates less than 50% adhesive remnants on the zirconia surface; (<b>2</b>) indicates more than 50% adhesive remnants on the zirconia surface; and (<b>3</b>) indicates the total amount of adhesive remnants on the zirconia surface.</p>
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<p>Box plots represent the shear bond strength values of clear aligner attachments bonded to glazed monolithic zirconia surfaces; X indicates the mean SBS value of each group.</p>
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<p>SEM examination at 100× and 500× magnification showed that both the zirconia sites in the SU and SiSU groups had a combination of adhesive and cohesive failure on the debonded surfaces. There were no instances of adhesive failure reported at the interfaces between the ceramic–cement or resin composite–cement.</p>
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<p>SEM micrograph 10× magnification of surface characteristics on the zirconia surface after shear bond strength test. The dotted loops represent 7 mm<sup>2</sup> of composite attachment base, Zr: Zirconia, SP: Superbond C&amp;B, Sc: Silane coupling agent. (<b>A</b>) Adhesive failure occurred at the interface between the zirconia surface and composite attachment base. (<b>B</b>) Mixed failure includes a small part of silane on the zirconia surface. (<b>C</b>) Mixed failure includes the part of silane–zirconia interface failure as well as a part of cohesive failure in composite attachment. (<b>D</b>) Mixed failure includes the part of zirconia–adhesive interface failure with a little adhesive area between adhesive and attachment. (<b>E</b>) Mixed failure includes zirconia–adhesive interface failure and cohesive failure in resin.</p>
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16 pages, 4896 KiB  
Article
Chemical and Physical Denudation Rates in the Poços de Caldas Alkaline Massif, Minas Gerais State, Brazil
by Fabiano Tomazini da Conceição, Rafael Carvalho Alves de Mello, Alexandre Martins Fernandes and Diego de Souza Sardinha
Minerals 2024, 14(7), 700; https://doi.org/10.3390/min14070700 - 9 Jul 2024
Viewed by 506
Abstract
Chemical and physical denudation rates have been assessed in areas with different lithologies. Surprisingly, there are no studies that attempt to document these rates in the Poços de Caldas Alkaline Massif (PC), the largest alkaline magmatism in South America and an important Al [...] Read more.
Chemical and physical denudation rates have been assessed in areas with different lithologies. Surprisingly, there are no studies that attempt to document these rates in the Poços de Caldas Alkaline Massif (PC), the largest alkaline magmatism in South America and an important Al supergene deposit in Brazil. Therefore, the chemical and physical denudation rates were assessed and explained in the PC. Surface water and rainwater samples were collected at the Amoras Stream basin, covering one complete hydrological cycle (2016). All samples were analyzed for dissolved cations, silica, anions, total dissolved solids (TDS), and total suspended solids (TSS). The results reflected the seasonal variation on discharge, water temperature, and electrical conductivity in the Amoras Stream, with most of the cations, anions, silica TDS, and TSS being carried in the wet season. Partial hydrolysis and silicate incongruent dissolution are the main water/rock interactions in the PC, with an atmospheric/soil CO2 consumption rate of 1.6 × 105 mol/km2/a. The annual fluxes of Cl, PO43−, NO3, and Al3+ were significantly influenced from rainwater. Chemical and physical weathering rates were 4 ± 0.8 and 3.0 ± 0.6 m/Ma in the PC, respectively, indicating that under the current climatic condition, the weathering profile is in dynamic equilibrium. Full article
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<p>A map of Southeast Brazil, showing the main geological units relative to the Cratons, Orogenic Belts, and Paraná Sedimentary basin, modified from Fernandes [<a href="#B37-minerals-14-00700" class="html-bibr">37</a>], and the geological map of Poços de Caldas Alkaline Massif [<a href="#B41-minerals-14-00700" class="html-bibr">41</a>].</p>
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<p>An image from Google Earth Pro (May 2024), with the location of the Amoras Stream basin inserted entirely in the Poços de Caldas Alkaline Massif. A ~60 km long topographic transverse, showing the geomorphological features of the Poços de Caldas Alkaline Massif.</p>
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<p>The Amoras Stream basin, with the location of the study area, as well as the surface water and rainwater sampling points.</p>
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<p>The relationship between discharge (Q) and total dissolved solids (TDS) and total suspended solids (TSS) in the Amoras Stream (<b>a</b>). Instantaneous daily flux (Idf) in the Amoras Stream basin, which was calculated using the values of TDS, TSS, and Q (<b>b</b>).</p>
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<p>The contribution of different sources (%) to dissolved cations, anions, SiO<sub>2</sub>, TDS, and TSS in the Poços de Caldas Alkaline Massif.</p>
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<p>The Na-normalized molar ratio diagrams, with the end-members representing the small carbonates, silicates, and evaporites’ watersheds [<a href="#B2-minerals-14-00700" class="html-bibr">2</a>].</p>
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<p>The Gibbs diagram [<a href="#B65-minerals-14-00700" class="html-bibr">65</a>] illustrates the control of the water/rock interactions in the characteristics of the surface waters in the Poços de Caldas Alkaline Massif. Data from southeastern Brazil coastal areas were obtained by Danelon and Moreira-Nordemann [<a href="#B62-minerals-14-00700" class="html-bibr">62</a>].</p>
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