Search Results (496)

Crop nitrogen (N) and phosphorus (P) use efficiencies (NUE/PUE) are important to minimize wastage and nutrient pollution, but no improved crop for both is currently available. We addressed them together in rice, in the view of its high consumption of NPK fertilizers. We analyzed 46 morphophysiological parameters for the N/P response in three popular indica genotypes, namely, BPT 5204, Panvel 1, and CR Dhan 301 at low, medium, and normal N/P doses. They include 18 vegetative, 15 physiological, and 13 reproductive parameters. The segregation of significantly N/P-responsive parameters correlating with NUE/PUE revealed 21 NUE, 22 PUE, and 12 common parameters. Feature selection analyses revealed the common high-ranking parameters including the photosynthetic rate at the reproductive stage, tiller number, root–shoot ratio, culm thickness, and flag leaf width. The venn selection using the reported NUE/PUE-related candidate genes in rice revealed five genes in common for both, namely OsIAA3, OsEXPA10, OsCYP75B4, OsSultr3;4, and OsFER2, which were associated with three of the common traits for NUE/PUE. Their expression studies using qRT-PCR revealed the opposite regulation in contrasting genotypes for OsSultr3;4 and OsEXPA10 in N-response and for OsFER2 in P-response, indicating their role in contrasting N/P use efficiencies. Overall, CR Dhan 301 has the highest NUE and PUE followed by Panvel 1 and BPT5204 among the studied genotypes. Full article

Parasitoid wasps play a crucial role in the efficient control of pests, a substantial menace to human health and well-being. Tetrastichus hagenowii (Ratzeburg) stands out as the most effective egg parasitoid wasp for controlling American cockroaches, but accurate and stable reference genes for quantitative real-time polymerase chain reaction of T. hagenowii genes are still lacking. In this study, we assessed seven candidate nuclear genes, including α-tubulin (α-TUB), elongation factor-1-alpha (EF-1α), β-actin (Actin), ribosomal protein 49 (RP49), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), nicotinamide adenine dinucleotide (NADH), and elongation factor 2 (EF2) of T. hagenowii. By analyzing expression stability with four algorithms (Delta Ct, geNorm, NormFinder, and BestKeeper), as well as comprehensive ranking with RefFinder, we identified α-TUB as the most stable reference gene for the larval, pupal, female adult, and male adult stages. Subsequently, we estimated the transcript levels of vitellogenin (Vg) and cuticle protein (CP) after normalization with α-TUB across various developmental stages. Significantly higher expression levels of CP and Vg were observed in pupae and female adults, respectively, consistent with previous findings in other insects. This study offers a reliable reference gene for normalizing transcription levels of T. hagenowii genes. Full article

The enzyme ROCK1 plays a pivotal role in the disruption of the tight junction protein CLDN1, a downstream effector influencing various cellular functions such as cell migration, adhesion, and polarity. Elevated levels of ROCK1 pose challenges in HCV, where CLDN1 serves as a crucial entry factor for viral infections. This study integrates a drug screening protocol, employing a combination of quantitative structure–activity relationship machine learning (QSAR-ML) techniques; absorption, distribution, metabolism, and excretion (ADME) predictions; and molecular docking. This integrated approach allows for the effective screening of specific compounds, using their calculated features and properties as guidelines for selecting drug-like candidates targeting ROCK1 inhibition in HCV treatment. The QSAR-ML model, validated with scores of 0.54 (R²), 0.15 (RMSE), and 0.71 (CCC), demonstrates its predictive capabilities. The ADME-Docking study’s final results highlight notable compounds from ZINC15, specifically ZINC000071318464, ZINC000073170040, ZINC000058568630, ZINC000058591055, and ZINC000058574949. These compounds exhibit the best ranking Vina scores for protein–ligand binding with the crystal structure of ROCK1 at the C2 pocket site. The generated features and calculated pIC₅₀ bioactivity of these compounds provide valuable insights, facilitating the identification of structurally similar candidates in the ongoing exploration of drugs for ROCK1 inhibition. Full article

The identification of new compounds with potential activity against CXC chemokine receptor type 4 (CXCR4) has been broadly studied, implying several chemical families, particularly AMD3100 derivatives. Molecular modeling has played a pivotal role in the identification of new active compounds. But, has its golden age ended? A virtual library of 450,000 tetraamines of general structure 8 was constructed by using five spacers and 300 diamines, which were obtained from the corresponding commercially available cyclic amines. Diversity selection was performed to guide the virtual screening of the former database and to select the most representative set of compounds. Molecular docking on the CXCR4 crystal structure allowed us to rank the selection and identify those candidate molecules with potential antitumor activity against diffuse large B-cell lymphoma (DLBCL). Among them, compound A{17,18} stood out for being a non-symmetrical structure, synthetically feasible, and with promising activity against DLBCL in in vitro experiments. The focused study of symmetrical-related compounds allowed us to identify potential pre-hits (IC50~20 µM), evidencing that molecular design is still relevant in the development of new CXCR4 inhibitor candidates. Full article

The goal of our study was to identify and assess the functionally significant SNPs with potentially important roles in the development of type 2 diabetes mellitus (T2DM) and/or their effect on individual response to antihyperglycemic medication with metformin. We applied a bioinformatics approach to identify the regulatory SNPs (rSNPs) associated with allele-asymmetric binding and expression events in our paired ChIP-seq and RNA-seq data for peripheral blood mononuclear cells (PBMCs) of nine healthy individuals. The rSNP outcomes were analyzed using public data from the GWAS (Genome-Wide Association Studies) and Genotype-Tissue Expression (GTEx). The differentially expressed genes (DEGs) between healthy and T2DM individuals (GSE221521), including metformin responders and non-responders (GSE153315), were searched for in GEO RNA-seq data. The DEGs harboring rSNPs were analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We identified 14,796 rSNPs in the promoters of 5132 genes of human PBMCs. We found 4280 rSNPs to associate with both phenotypic traits (GWAS) and expression quantitative trait loci (eQTLs) from GTEx. Between T2DM patients and controls, 3810 rSNPs were detected in the promoters of 1284 DEGs. Based on the protein-protein interaction (PPI) network, we identified 31 upregulated hub genes, including the genes involved in inflammation, obesity, and insulin resistance. The top-ranked 10 enriched KEGG pathways for these hubs included insulin, AMPK, and FoxO signaling pathways. Between metformin responders and non-responders, 367 rSNPs were found in the promoters of 131 DEGs. Genes encoding transcription factors and transcription regulators were the most widely represented group and many were shown to be involved in the T2DM pathogenesis. We have formed a list of human rSNPs that add functional interpretation to the T2DM-association signals identified in GWAS. The results suggest candidate causal regulatory variants for T2DM, with strong enrichment in the pathways related to glucose metabolism, inflammation, and the effects of metformin. Full article

Drought stress, which significantly affects growth and reduces grain yield, is one of the main problems for wheat crops. Producing promising drought-tolerant wheat cultivars with high yields is one of the main targets for wheat breeders. In this study, a total of seven drought-tolerant wheat genotypes were screened for the presence of 19 specific drought tolerance genes. The genotypes were tested under normal and drought conditions for two growing seasons. Four spike traits, namely, spike length (SPL), grain number per spike (GNPS), number of spikelets per spike (NSPS), and grain yield per spike (GYPS), were scored. The results revealed that drought stress decreased the SPL, GNPS, NSPS, and GYPS, with ranges ranging from 2.14 (NSPS) to 13.92% (GNPS) and from 2.40 (NSPS) to 11.09% (GYPS) in the first and second seasons, respectively. ANOVA revealed high genetic variation among the genotypes for each trait under each treatment. According to the drought tolerance indices, Omara 007 presented the highest level of drought tolerance (average of sum ranks = 3), whereas both Giza-36 genotypes presented the lowest level of drought tolerance (average of sum ranks = 4.8) among the genotypes tested. Among the 19 genes tested, 11 were polymorphic among the selected genotypes. Omara 007 and Omara 002 presented the greatest number of specific drought tolerance genes (nine) tested in this study, whereas Sohag-5, Giza-36, and PI469072 presented the lowest number of drought tolerance genes (four). The number of different genes between each pair of genotypes was calculated. Seven different genes were found between Omara 007 and Giza-36, Omara 007 and Sohag-5, and Omara 002 and PI469072. The results of this study may help to identify the best genotypes for crossing candidate genotypes, and not merely to genetically improve drought tolerance in wheat. Full article

Mechanized harvesting is a crucial step in the agricultural production of foxtail millet (Setaria italica), as its peduncles are susceptible to bending and breaking during the harvesting process, leading to yield losses and deterioration in grain quality. To evaluate the suitability of foxtail millet for mechanical harvesting, this study comprehensively analyzed the biomechanical properties of the peduncles and related biological morphological characteristics of 116 foxtail millet accessions, establishing a system for indicator screening and comprehensive evaluation. Using partial correlation analysis and R-type cluster analysis, four biomechanical and seven related morphological indices of the peduncle were screened from 22 candidate indicators, with their coefficient of variation ranging from 6% to 80%. The entropy method was used to assign weights to the selected indices, with biomechanical factors contributing 47.4%, peduncle morphology 20.2%, spike morphology 27.6%, and plant height 4.8%. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Rank-Sum Ratio (RSR) methods were applied to rank and grade the classification of the 116 foxtail millet varieties into four performance groups: Excellent (8 varieties), Good (50 varieties), Moderate (51 varieties), and Poor (7 varieties). This study provides a scientific basis for the selection and evaluation of foxtail millet varieties. Full article

Sound source identification technology based on a microphone array has many application scenarios. The compressive beamforming method has attracted much attention due to its high accuracy and high-resolution performance. However, for the far-field measurement problem of large microphone arrays, existing methods based on fixed grids have the defect of basis mismatch. Due to the large number of grid points representing potential sound source locations, the identification accuracy of traditional grid adjustment methods also needs to be improved. To solve this problem, this paper proposes a sound source identification method based on adaptive grid splitting and refinement. First, the initial source locations are obtained through a sparse Bayesian learning framework. Then, higher-weight candidate grids are retained, and local regions near them are split and updated. During the iteration process, Green’s function and the source strength obtained in the previous iteration are multiplied to get the sound pressure matrix. The robust principal component analysis model of the Gaussian mixture separates and replaces the sound pressure matrix with a low-rank matrix. The actual sound source locations are gradually approximated through the dynamically adjusted sound pressure low-rank matrix and optimized grid transfer matrix. The performance of the method is verified through numerical simulations. In addition, experiments on a standard aircraft model are conducted in a wind tunnel and speakers are installed on the model, proving that the proposed method can achieve fast, high-precision imaging of low-frequency sound sources in an extensive dynamic range at long distances. Full article

The increase in installed PV capacity worldwide and the intermittent nature of solar resources highlight the importance of power prediction for grid integration of this technology. Therefore, there is an urgent need for an effective prediction model, but the choice of model hyperparameters greatly affects the prediction performance. In this paper, a multi-strategy improved snowmelt algorithm (MISAO) is proposed for optimizing intrinsic computing-expressive empirical mode decomposition with adaptive noise (ICEEMDAN) and weighted least squares support vector machine for PV power forecasting. Firstly, a cyclic chaotic mapping initialization strategy is used to generate a uniformly distributed high-quality population, which facilitates the algorithm to enter the appropriate search domain quickly. Secondly, the Gaussian diffusion strategy enhances the local exploration ability of the intelligences and extends their search in the solution space, effectively preventing them from falling into local optima. Finally, a stochastic follower search strategy is employed to reserve better candidate solutions for the next iteration, thus achieving a robust exploration–exploitation balance. With these strategies, the optimization performance of MISAO is comprehensively improved. In order to comprehensively evaluate the optimization performance of MISAO, a series of numerical optimization experiments were conducted using IEEE CEC2017 and test sets, and the effectiveness of each improvement strategy was verified. In terms of solution accuracy, convergence speed, robustness, and scalability, MISAO was compared with the basic SAO, various state-of-the-art optimizers, and some recently developed improved algorithms. The results showed that the overall optimization performance of MISAO is excellent, with Friedman average rankings of 1.80 and 1.82 in the two comparison experiments. In most of the test cases, MISAO delivered more accurate and reliable solutions than its competitors. In addition, the altered algorithm was applied to the selection of hyperparameters for the ICEEMDAN-WLSSVM PV prediction model, and seven neural network models, including WLSSVM, ICEEMDAN-WLSSVM, and MISAO-ICEEMDAN-WLSSVM, were used to predict the PV power under three different weather types. The results showed that the models have high prediction accuracy and stability. The MAPE, MAE and RMSE of the proposed model were reduced by at least 25.3%, 17.8% and 13.3%, respectively. This method is useful for predicting the output power, which is conducive to the economic dispatch of the grid and the stable operation of the power system. Full article

The passion fruit, Passiflora edulis, recognized for its rich nutritional properties, has long been used for its varied ethnobotanical applications. This study investigates the therapeutic potential of P. edulis var. Tainung No. 1 rind extracts by examining their polyphenolic content (TPC), total flavonoid content (TFC), anti-skin aging activities against key enzymes such as elastase, tyrosinase, and hyaluronidase, and their ability to inhibit bacterial growth, single-stranded DNA-binding protein (SSB), and their cytotoxic effects on oral carcinoma cells. The acetone extract from the rind exhibited the highest levels of TPC, TFC, anti-SSB, and antibacterial activities. The antibacterial effectiveness of the acetone-extracted rind was ranked as follows: Escherichia coli > Pseudomonas aeruginosa > Staphylococcus aureus. A titration curve for SSB inhibition showed an IC₅₀ value of 313.2 μg/mL, indicating the potency of the acetone extract in inhibiting SSB. It also significantly reduced the activity of enzymes associated with skin aging, particularly tyrosinase, with a 54.5% inhibition at a concentration of 100 μg/mL. Gas chromatography–mass spectrometry (GC–MS) analysis tentatively identified several major bioactive compounds in the acetone extract, including stigmast-5-en-3-ol, vitamin E, palmitic acid, stigmasterol, linoleic acid, campesterol, and octadecanoic acid. Molecular docking studies suggested some of these compounds as potential inhibitors of tyrosinase and SSB. Furthermore, the extract demonstrated anticancer potential against Ca9-22 oral carcinoma cells by inhibiting cell survival, migration, and proliferation and inducing apoptosis. These results underscore the potential of P. edulis (Tainung No. 1) rind as a promising candidate for anti-skin aging, antibacterial, and anticancer applications, meriting further therapeutic investigation. Full article

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 13 major effect QTLs that contributed more than 10% toward phenotypic variation (PV) and 9 stable QTLs that could be repeatedly mapped in different generations. Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosomes D1 and D11. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18–21.45% of PV and qFS-A11-1 in F2:3, F2:4, and F2:5 with 6.05–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, while Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality. Full article

Lexical substitution aims to generate a list of equivalent substitutions (i.e., synonyms) to a sentence’s target word or phrase while preserving the sentence’s meaning to improve writing, enhance language understanding, improve natural language processing models, and handle ambiguity. This task has recently attracted much attention in many languages. Despite the richness of Arabic vocabulary, limited research has been performed on the lexical substitution task due to the lack of annotated data. To bridge this gap, we present the first Arabic lexical substitution benchmark dataset AraLexSubD for benchmarking lexical substitution pipelines. AraLexSubD is manually built by eight native Arabic speakers and linguists (six linguist annotators, a doctor, and an economist) who annotate the 630 sentences. AraLexSubD covers three domains: general, finance, and medical. It encompasses 2476 substitution candidates ranked according to their semantic relatedness. We also present the first Arabic lexical substitution pipeline, AraLexSub, which uses the AraBERT pre-trained language model. The pipeline consists of several modules: substitute generation, substitute filtering, and candidate ranking. The filtering step shows its effectiveness by achieving an increase of 1.6 in the F1 score on the entire AraLexSubD dataset. Additionally, an error analysis of the experiment is reported. To our knowledge, this is the first study on Arabic lexical substitution. Full article

Dendrobium fimbriatum is a perennial herb, and its stems are high-grade tea and nourishing medicinal materials. Various solvent extracts of D. fimbriatum were evaluated for their anti-inflammatory, anti-acetylcholinesterase (AChE), antioxidant, and anti-α-glucosidase properties. Acetone and EtOAc extracts showed significant antioxidant effects. Acetone, n-hexane, and EtOAc extracts revealed potent inhibition against α-glucosidase. EtOAc, n-hexane, and dichloromethane extracts displayed significant anti-AChE activity. Among the isolated constituents, gigantol, moscatin, and dendrophenol showed potent antioxidant activities in FRAP, DPPH, and ABTS radical scavenging tests. Moscatin (IC₅₀ = 161.86 ± 16.45 μM) and dendrophenol (IC₅₀ = 165.19 ± 13.25 μM) displayed more potent anti-AChE activity than chlorogenic acid (IC₅₀ = 236.24 ± 15.85 μM, positive control). Dendrophenol (IC₅₀ = 14.31 ± 3.17 μM) revealed more efficient anti-NO activity than quercetin (positive control, IC₅₀ = 23.09 ± 1.43 μM). Analysis of AChE and iNOS inhibitory components was performed using molecular docking and/or the bioaffinity ultrafiltration method. In bioaffinity ultrafiltration, the binding affinity of compounds to the enzyme (acetylcholinesterase and inducible nitric oxide synthase) was determined using the enrichment factor (EF). Among the main components of the EtOAc extract from D. fimbriatum stem, moscatin, dendrophenol, gigantol, and batatasin III with acetylcholinesterase exhibited the highest binding affinities, with affinity values of 66.31%, 59.48%, 54.60%, and 31.87%, respectively. Moreover, the affinity capacity of the identified compounds with inducible nitric oxide synthase can be ranked as moscatin (88.99%) > dendrophenol (65.11%) > gigantol (44.84%) > batatasin III (27.18%). This research suggests that the bioactive extracts and components of D. fimbriatum stem could be studied further as hopeful candidates for the prevention or treatment of hyperglycemia, oxidative stress-related diseases, and nervous disorders. Full article

As precision medicine such as targeted therapy and immunotherapy often have limited accessibility, low response rate, and evolved resistance, it is urgent to develop simple, low-cost, and quick-turnaround personalized diagnostic technologies for drug response prediction with high sensitivity, speed, and accuracy. The major challenges of drug response prediction strategies employing digital database modeling are the scarcity of labeled clinical data, applicability only to a few classes of drugs, and losing the resolution at the individual patient level. Although these challenges have been partially addressed by large-scale cancer cell line datasets and more patient-relevant cell-based systems, the integration of different data types and data translation from pre-clinical to clinical utilities are still far-fetched. To overcome the current limitations of precision medicine with a clinically proven drug response prediction assay, we have developed an innovative and proprietary technology based on in vitro patient testing and in silico data analytics. First, a patient-derived gene expression signature was established via the transcriptomic profiling of cell-free mRNA (cfmRNA) from the patient’s blood. Second, a gene-to-drug data fusion and overlaying mechanism to transfer data were performed. Finally, a semi-supervised method was used for the database searching, matching, annotation, and ranking of drug efficacies from a pool of ~700 approved, investigational, or clinical trial drug candidates. A personalized drug response report can be delivered to inform clinical decisions within a week. The PGA (patient-derived gene expression-informed anticancer drug efficacy) test has significantly improved patient outcomes when compared to the treatment plans without PGA support. The implementation of PGA, which combines patient-unique cfmRNA fingerprints with drug mapping power, has the potential to identify treatment options when patients are no longer responding to therapy and when standard-of-care is exhausted. Full article

All novel materials should be analyzed for their potential environmental hazard. In this study, the toxicity of different silver–chitosan nanocomposites—potential candidates for wound dressings or antimicrobial surface coatings—was evaluated using environmentally relevant aquatic microcrustaceans Daphnia magna and Thamnocephalus platyurus and naturally luminescent bacteria Vibrio fischeri. Three silver-chitosan nanocomposites (nAgCSs) with different weight ratios of Ag to CS were studied. Citrate-coated silver nanoparticles (nAg-Cit), AgNO₃ (ionic control) and low molecular weight chitosan (LMW CS) were evaluated in parallel. The primary size of nAgCSs was ~50 nm. The average hydrodynamic sizes in deionized water were ≤100 nm, and the zeta potential values were positive (16–26 mV). The nAgCSs proved very toxic to aquatic crustaceans: the 48-h EC₅₀ value for D. magna was 0.065–0.232 mg/L, and the 24-h LC₅₀ value for T. platyurus was 0.25–1.04 mg/L. The toxic effect correlated with the shedding of Ag ions (about 1%) from nAgCSs. Upon exposure of V. fischeri to nAgCSs for 30 min, bacterial luminescence was inhibited by 50% at 13–33 mg/L. However, the inhibitory effect (minimum bactericidal concentration, MBC) on bacterial growth upon 1 h exposure was observed at higher concentrations of nAgCSs, 40–65 mg/L. LMW CS inhibited bacterial luminescence upon 30-min exposure at 5.6 mg/L, but bacterial growth was inhibited at a much higher concentration (1 h MBC > 100 mg/L). The multi-trophic test battery, where D. magna was the most sensitive test organism, ranked the silver-chitosan nanocomposites from ‘extremely toxic’ [L(E)C₅₀ ≤ 0.1 mg/L] to ‘very toxic’ [L(E)C₅₀ > 0.1–1 mg/L]. Chitosan was toxic (EC(L)₅₀) to crustaceans at ~12 mg/L, and ranked accordingly as ‘harmful’ [L(E)C₅₀ > 10–100 mg/L]. Thus, silver-chitosan nanocomposites may pose a hazard to aquatic organisms and must be handled accordingly. Full article