Search Results (367)

Tramadol acts via μ-opioid receptor agonism and monoamine reuptake inhibition but is clinically limited by metabolic dependence, interindividual variability, and addiction risks. Structural modification aims to resolve these limitations. This review systematically summarizes tramadol’s structure–activity relationships and mechanisms, focusing on key strategies for structural optimization. Major advances include: (i) synergistic strategies, such as tramadol–celecoxib cocrystals (tramadol and celecoxib coexist in the supramolecular crystal network at a 1:1 molar ratio), achieving multimodal analgesia at lower doses; (ii) mechanism-balancing strategies such as tapentadol (derivatives of tramadol with a dual mechanism of action), which enhance μ-opioid agonism and norepinephrine reuptake inhibition while attenuating serotonergic effects to improve efficacy; (iii) metabolic optimization utilizing M1 analogues to circumvent CYP2D6 polymorphisms (tramadol is metabolized by this enzyme into the active metabolite M1 to exert analgesic effects); and (iv) pharmacophore optimization leveraging tramadol–morphine homology and “message–address” concepts to design selective ligands. Novel derivatives demonstrate improved potency and metabolic stability but continue to face challenges regarding opioid risks and clinical translation. Future research should integrate rational drug design, delivery systems, and personalized medicine to facilitate the development of safer next-generation analgesics. Full article

In disease control and precision management in aquaculture, rapid and accurate identification of common fish diseases is pivotal to mitigating economic losses and ensuring aquaculture profitability. However, fish diseases are characterized by subtle symptoms, polymorphic lesions, and high susceptibility to environmental perturbations such as water turbidity and illumination fluctuations. Existing detection models generally suffer from inadequate lightweight design, poor fine-grained lesion feature extraction, and deficient adaptability to class imbalance, failing to meet the stringent requirements of precise diagnosis in real-world aquaculture scenarios. To address these challenges, this study proposes FDR-Net: a fine-grained lesion detection model for tilapia via multi-scale feature enhancement and spatial attention fusion. Using image data of Nile tilapia (Oreochromis niloticus) covering 6 common diseases and healthy individuals (from the NTD-1 dataset), the model incorporates symmetry-aware design logic, leveraging the morphological and textural symmetry of healthy tilapia tissues to capture lesion-induced symmetry-breaking features, thereby improving fine-grained lesion detection accuracy. Through depth-width scaling coefficients, FDR-Net achieves lightweight optimization while integrating three core modules and a task-specific loss function for full-chain optimization: specifically, a Micro-lesion Feature Enhancement Module (MLFEM) is embedded in key feature layers of the backbone network to accurately extract edge and texture features of incipient fine-grained lesions via multi-scale frequency decomposition and residual fusion; subsequently, a Lightweight Multi-scale Position Attention Module (MS_PSA) and a Single-modal Intra-feature Contrastive Fusion Module (SMICFM) are collaboratively deployed—the former focusing on spatial localization of lesion features, and the latter enhancing lesion-background discriminability through channel-spatial feature recalibration and contrastive fusion; finally, a Class-Aware Weighted Hybrid Loss (CAWHL) function is combined with customized small-target anchor boxes to alleviate class imbalance and further improve localization and classification accuracy of fine-grained lesions. Empirical evaluations on the NTD-1 dataset demonstrate that compared with mainstream state-of-the-art baseline models, FDR-Net achieves a peak recognition accuracy of 90.1% with substantially enhanced mAP_50-95 performance. Retaining lightweight characteristics, it exhibits superior performance in identifying incipient fine-grained lesions and strong adaptability to simulated complex aquaculture scenarios. Collectively, this study provides an efficient technical backbone for the rapid and precise detection of tilapia fine-grained lesions, offering a potential solution for precise disease management in tilapia farming. Full article

Phosphorus (P) deficiency severely limits the growth and yield of crop plants, and anthocyanin accumulation is a key adaptive physiological response to low-P stress. However, the role of MYB transcription factors in regulating anthocyanin biosynthesis under P-deficient conditions and the application of favorable haplotypes in foxtail millet low-P tolerance breeding remain unclear. Here, we performed genome-wide identification of SiMYB genes, elucidated their evolutionary characteristics, and identified key members regulating anthocyanin accumulation under P deficiency to provide genetic resources and a theoretical basis for foxtail millet molecular breeding aimed at improving nutrient use efficiency. Specifically, a total of 229 SiMYB genes were identified in the foxtail millet genome and classified into three subgroups, with the R2R3-MYB subfamily accounting for 59.8%. Phylogenetic and synteny analyses across 15 plant species revealed diverse divergence times and complex relationships, with 29 R2R3-MYB genes showing conserved collinearity with rice and maize orthologs. Association analysis using 196 foxtail millet accessions showed that 38 single nucleotide polymorphisms (SNPs) from 16 SiMYB genes were significantly associated with leaf anthocyanin content under P deficiency (p < 0.001). Notably, the SiMYB169 gene exhibited differential tissue expression and was highly upregulated in the leaves of a P-tolerant genotype after 24 h of P deficiency treatment. Furthermore, accessions carrying the favorable G allele of SiMYB169 showed significantly higher anthocyanin accumulation under P deficiency (p < 0.01). Network prediction analysis found that SiMYB169 interacted with key genes and multiple transcription factors in the biosynthesis pathway of anthocyanin. These findings highlight SiMYB169 as an evolutionarily conserved regulator that modulated anthocyanin biosynthesis under P-deficient conditions. Full article

Type 1 diabetes (T1D) is an autoimmune disease with a strong genetic component (~70% heritability). Early identification of individuals at risk is crucial for early intervention or risk assessment. Although polygenic risk scores (PRS) have shown promise in risk assessment, most current approaches remain constrained by linear assumptions and limited generalizability. We aimed to develop a neural network-driven classifier using T1D-associated single nucleotide polymorphisms (SNPs). In addition, we explored the inclusion of an entropy-derived feature as a complementary variable, representing the degree of genetic variability within an individual’s genotype profile across the 67 T1D-associated SNPs, to evaluate its potential additive contribution to the model performance. We analyzed genotype data from 11,909 individuals in the UK BioBank (546 T1D cases and 11,363 controls). Sixty-seven well-known SNPs associated with T1D were utilized as inputs to the model, using two distinct allele-encoding strategies. A feed-forward neural network was evaluated under varying case–control ratios through five-fold cross-validation. Performance was assessed using the area under the receiver operating characteristic curve (AUC) on a held-out test set and on an external European cohort as a validation cohort. Across five-fold cross-validation, the best configuration achieved a median AUC of 0.903. On the held-out UK Biobank test set, the model generalized well, with an AUC of 0.8889 (95% CI: 0.8516–0.9262). A probability-based risk framework, constructed using five risk groups (“very low”, “low”, “intermediate”, “high”, and “very high” risk), yielded a negative predictive value (NPV) of 98.9% for the “very low” risk group and a Positive Predicted Value (PPV) of 61.9% with a specificity of 97.3% for the “very high” risk group, assuming a 10% T1D prevalence. External validation in the German Diabetes Study reproduced clear case–control separation; for individuals with recent onset diabetes and glutamic acid decarboxylase antibodies (GADA+) vs. controls, specificity reached 91.9% in the “high” risk group (PPV of 94.3%) and 97.6% in the “very high” risk group (PPV of 95.7%). The proposed neural network reliably predicts T1D genetic risk using a compact SNP panel of 67 SNPs and maintains accuracy in both internal and external European cohorts. Its probabilistic output enables clinically interpretable risk thresholds, while entropy features contributed modestly to performance. These results demonstrate that a neural network-based approach achieves discriminative performance that is comparable to established T1D genetic risk models, while offering flexible probability-based risk stratification and architectural extensibility for future integration of additional features. Full article

The industrial application of starter cultures requires stable physiological and genetic performance. In this study, Streptococcus salivarius subsp. thermophilus and Lactobacillus delbrueckii subsp. bulgaricus were continuously subcultured. Physiological stability was assessed through colony morphology, fermentation activity, and growth profiling. Genetic stability was evaluated through comparative genomics of carbohydrate metabolism networks and single-nucleotide polymorphism (SNP) analysis. The results showed that after 2000 generations, the cellular morphology of the strains remained intact. Additionally, the strains exhibited enhanced growth performance and fermentation capability. The Gompertz model revealed that adapted S. thermophilus A37 and L. bulgaricus B29 exhibited shortened lag phases, increased maximum specific growth rates, and high stationary-phase cell densities. Phenotypic microarray and comparative genomics revealed that S. thermophilus mainly used mono- and disaccharides, with impaired ribose metabolism due to the absence of the rbsk gene in the pentose phosphate pathway. In contrast, L. bulgaricus metabolized diverse oligosaccharides, sugar alcohols, and plant-derived substrates. Additionally, it effectively catabolized ribose through the phosphoketolase pathway and possessed a trehalose degradation cluster. All strains exhibited genomic stability, with SNPs revealing fewer than 21 variations per isolate. This study provides an important theoretical foundation for evaluating the stability of fermentation starter cultures. Full article

The unique ecological gradients of Xinjiang have fostered a rich reservoir of genetic resources in local sheep populations. However, the population genetic structure, adaptive mechanisms to extreme environments, and the genetic basis underlying key economic traits of these breeds remain poorly understood. To address this gap, we performed whole-genome resequencing of 140 individuals from seven indigenous sheep populations—Altay, Bayinbuluke, Kazakh, Kirgiz, Bashibai, Turpan Black, and Yemule White—identifying 18,700,507 high-quality SNPs. Genetic diversity analyses revealed that all populations exhibited comparable levels of genetic diversity, with modest variation across breeds, with Turpan Black sheep exhibiting the highest observed heterozygosity (Ho = 0.3110) and proportion of polymorphic sites, whereas Kirgiz sheep showed comparatively lower values. Population structure analyses consistently indicated that geographic isolation is the primary driver of genetic differentiation, with Kirgiz sheep from the Pamir Plateau in southern Xinjiang displaying the greatest genetic distance relative to northern Xinjiang populations. By integrating multiple selection signature detection methods—including F_ST, π ratio, and XP-CLR—we found that genes under selection in Kirgiz sheep were significantly enriched in biological pathways related to stem cell pluripotency regulation (e.g., BMPR1B), DNA repair (e.g., DDB2), and neural development, thereby elucidating their unique genetic adaptations to high-altitude environments. In contrast, Turpan Black sheep appear to cope with heat stress through mechanisms involving basal transcriptional regulation (e.g., GTF2I), maintenance of protein homeostasis (e.g., DNAJB14), and melanin biosynthesis (e.g., MC1R). Furthermore, comparative analysis of body size identified a suite of candidate genes associated with growth and development (e.g., CUX1, KIT), which are primarily involved in transcriptional regulation, protein kinase activity, and the ubiquitin-mediated proteolytic system, thereby revealing a multi-layered genetic regulatory network governing body conformation. Collectively, this study provides a comprehensive genomic framework for understanding the genetic structure, adaptive evolution, and molecular basis of economically important traits in indigenous sheep breeds from Xinjiang, offering valuable candidate targets for future functional validation and precision breeding programs. Full article

To address the insufficient capability of YOLO-series models in representing structural information for foreign objects with diverse scales and morphologies, an improved algorithm named SSFE-YOLO is proposed. First, the Space-to-Depth Convolution (SPDConv) is adopted into the backbone network to preserve edge and texture details in shallow features during downsampling, thereby maintaining the integrity of critical target structures at the feature generation stage. Second, an adaptive receptive field enhancement module (ARFE) is designed by introducing parallel feature branches with varying receptive fields. This module performs adaptive fusion to bolster the structural perception of the network towards polymorphic foreign objects. Furthermore, a distribution-feature stable compensation module (DFSC) is designed to suppress feature distribution shifts caused by illumination variations and noise interference through structural consistency enhancement and stable distribution constraints, which significantly improves the stability of feature representation in complex environments. Finally, a dual-dimension optimized loss function (D${}^2$-OL) is constructed to achieve differentiated supervision for samples of varying quality and balanced optimization for multi-scale target detection by modulating the supervisory weights of feature layers and filtering effective training samples. Experimental results on a self-built mine conveyor belt dataset demonstrate that the proposed method achieves an mAP@0.5 of 90.5% and an mAP@0.5:0.95 of 59.1%, consistently outperforming mainstream models such as YOLOv8, YOLOv11, and YOLOv13. Simulation results indicate that the proposed approach effectively enhances the detection accuracy and robustness of foreign objects in mining environments, showcasing substantial potential for engineering applications. Full article

Background/Objectives: The Subo Merino sheep is a high-quality fine-wool breed developed through progressive hybridization, characterized by high wool yield and excellent wool quality. This study is designed to investigate the effects of two gene polymorphisms in Subo Merino sheep on wool traits, thereby providing critical theoretical and technical support for the breeding of high-quality fine-wool sheep. Methods: In this study, 944 one-year-old Subo Merino sheep were genotyped for coding regions of the BLTP1 and KIF27 genes using the Fluidigm BioMark™ HD system. Association between SNP loci and wool traits was analyzed via the least squares means method in SAS 9.4. Protein–protein interaction networks were constructed using the STRING database, and protein structures before and after mutation were predicted with SOPMA and SWISS-MODEL. Results: The results revealed that BLTP1 gene identified a missense mutation site SNP1, which resulted in a nucleotide change c.812 (C > T) and an amino acid change p.Pro271Leu. KIF27 gene identified a missense mutation site SNP2, which resulted in a nucleotide change c.3896 (T > C) and an amino acid change p.Met1299Thr. Association analysis showed that SNP1 had a significant effect on wool crimp number (CN) and staple length (SL) (p < 0.05), while SNP2 significantly affected live weight after shearing (LWAS) (p < 0.05). Protein structure prediction showed that mutations at SNP1 and SNP2 primarily led to changes in α-helix, extended chain, and random coil structures. Conclusions: These results suggest that SNP1 in BLTP1 and SNP2 in KIF27 could serve as potential molecular markers for wool traits in Subo Merino sheep. This study provides theoretical support and candidate gene targets for molecular marker-assisted breeding, contributing to genetic improvement and efficient breeding of this fine-wool breed. Full article

How many founders are required for insects and other organisms to establish new populations is a fundamental question in invasion biology. We investigated the population establishment process of a parasitoid wasp, Monodontomerus sp., which was first recorded in Japan in 2000. Field surveys conducted in this study showed that the parasitism rate has been increasing in recent years. Morphological and molecular analyses suggested that the parasitoid species is M. obscurus, or a closely related lineage derived from it, which newly invaded Japan. To examine genetic variation during the early stage of invasion, we developed microsatellite DNA markers and conducted population genetic analyses. The results revealed extremely low genetic diversity: most loci were monomorphic, polymorphism was restricted to loci with long repeat motifs, and the allele frequencies of these loci were dominated by single alleles. A minimum spanning network based on microsatellite genotypes exhibited a star-like pattern. These results based on genome-wide microsatellite data indicate that the present population was founded by very few individuals, most likely a single female or an effectively single genetic lineage, and novel genotypes arose through post-invasion mutations. Our study provides rare empirical evidence for single-female founding under natural conditions, and highlights how species-specific life-history and genetic systems can enable successful invasion despite extreme bottlenecks. Full article

As a major retrovirus threatening global poultry farming, Avian Leukosis Virus Subgroup J (ALV-J) has expanded its host range since discovery, extending from conventional broilers to layer chickens and native breeds. Its diverse oncogenic manifestations, including myeloid leukemia, hemangiomas, and tumors of immune and visceral organs, have led to increased mortality, reduced productivity, and substantial economic losses in the poultry industry. Based on the current body of literature, this review summarizes and synthesizes advances in the etiological characteristics, infection and pathogenic mechanisms, host resistance, and research progress in prevention and control of ALV-J. Accumulating evidence indicates that viral evolution driven by mutations and recombination—particularly in the env gene and LTR regions—plays a central role in host range expansion, tumor diversity, and immune evasion. Current studies consistently demonstrate that host resistance to ALV-J is a multifactorial process involving genetic polymorphism, innate immune responses, and cellular autonomous defense systems. In this context, recent advances in disease-resistant breeding highlight CRISPR-Cas9-mediated gene editing as a promising strategy for blocking viral entry or replication. Despite these advances, major gaps remain, including an incomplete understanding of virus–host interaction networks, limited insight into co-infection-mediated synergistic pathogenicity, the absence of effective vaccines, and insufficient large-scale epidemiological surveillance and purification systems. Addressing these challenges will be critical for the development of integrated prevention strategies and the sustainable control of ALV-J in poultry production. Full article

We report the crystallization and single-crystal X-ray analysis of the monohydrate hydrochloride salt of chloroquine(CQ), abbreviated CQHCl·H₂O, an antimalarial drug with the formula C₁₈H₂₆ClN₃. The crystal structure reveals a well-defined supramolecular architecture stabilized by an extensive hydrogen-bonding network involving CQH⁺ cations, chloride anions, and water molecules. Notably, this study provides the first crystallographic characterization of a monoprotonated chloroquine salt. Additionally, our findings demonstrate the feasibility of isolating pseudo-polymorphic forms of a commercially available CQ salt via heterogeneous crystallization. Full article

Background/Objectives: Carbapenem-resistant Acinetobacter baumannii (CRAB) is classified as an urgent-threat pathogen because of its resistance to nearly all available antibiotics, resulting in high morbidity and mortality rates. However, data on the molecular epidemiology of CRAB isolates in southern Thailand are limited. This study aimed to investigate the genomic epidemiology of CRAB isolates within a hospital network in lower southern Thailand. Methods: Whole-genome sequencing data of CRAB clinical isolates (n = 224) were obtained from a previous study. Additional isolates (n = 70) were included, for which genomic DNA was extracted and sequenced. In total, 294 isolates were collected from patients across seven hospitals in southern Thailand between 2019 and 2020. Their genomes were analyzed using several bioinformatic tools. Results: A high proportion of isolates were obtained from sputum samples of patients with CRAB infection or colonization. Sequence type (ST) 2 was the most frequent ST and was classified in the quadrant with high resistance and virulence. The Sankey diagram showed that ST2 was the dominant and most versatile CRAB lineage circulating across major hospitals, commonly associated with pneumonia, and that diverse resistance genes and plasmid combinations were dominated by bla_OXA-23. The core single-nucleotide polymorphism (SNP)-based phylogenetic tree revealed clades A1 (ST215), A2 (multiple STs), and B (ST2). Bloodstream, skin, and soft tissue infections were predominantly observed in clade B. Conclusions: Our analysis revealed widespread circulation of a high-risk ST2 CRAB lineage with enhanced resistance and virulence across hospital networks in the studied region, highlighting the importance of genomics-informed surveillance for controlling CRAB dissemination. Full article

Continuous human-mediated introduction of colonies and queens promotes genetic introgression and reshapes the genetic diversity and structure of local honeybee populations. According to reports, multiple non-native honeybee colonies and queens have been introduced into the DL region, leading to continuous genetic introgression. Here, we assessed the effects of continuous introgression on indigenous Apis cerana in the DL region using mtDNA and genome-wide SNP markers. We sequenced the mitochondrial tRNA ^leu-COII from 217 individuals sampled at 7 DL sites and identified 26 haplotypes defined by 18 polymorphic sites. The ΦST values indicated no internal differentiation within the Apis cerana populations in the DL region. Phylogenetic, network, ABBA-BABA test, and f3 statistic suggested introgression from both northern and southern sources. The f4-ratio indicates that approximately 16% of the ancestry in the DL group is derived from the Aba group. Genetic diversity varied widely within the DL region (Hd: 0.2907–0.8220; π: 0.0009–0.0038; K: 0.3140–1.3980), indicating different stages of introgression. The genetic structure within the DL group appears to be unstable, necessitating long-term monitoring of evolutionary processes and genetic diversity dynamics in A. c. cerana for further insights. Full article

Coal mine ventilation systems face coupled and systemic risks characterized by structural interconnection and disaster chain propagation. In order to accurately quantify and evaluate this overall system risk, this study presents a new method of risk assessment of the coal mine ventilation system based on fuzzy polymorphic Bayesian networks. This method effectively addresses the shortcomings of traditional assessment approaches in the probabilistic quantification of risk. A Bayesian network with 44 nodes was established from five dimensions: ventilation power, ventilation network, ventilation facilities, human and management factors, and work environment. The risk states were divided into multiple states based on the As Low As Reasonably Practicable (ALARP) metric. The probabilities of evaluation-type root nodes were calculated using fuzzy evaluation, and the subjective bias was corrected by introducing a reliability coefficient. The concept of distance compensation is proposed to flexibly calculate the probabilities of quantitative-type root nodes. Through the verification of the ventilation system of H Coal Mine in Shanxi, China, it is concluded that the high risk of the ventilation system is 18%, and the high-risk probability of the ventilation system caused by the external air leakage of the mine is the largest. The evaluation results are consistent with real-world conditions. The results can provide a reference for improving the safety of the ventilation systems. Full article

Enhancing wood properties, particularly fiber length (FL), represents a critical objective in Populus tomentosa breeding programs. However, the molecular mechanisms regulating these traits remain largely elusive. Here, an integrative analysis of the PtomiR171 family, uncovering substantial functional divergence among PtomiR171 family members and identified a PtomiR171a-PtoGRAS50 regulatory axis that may control cellulose-related gene expression and influence fiber development in P. tomentosa. Single-nucleotide polymorphism (SNP)-based association studies implicated the role of the PtomiR171a-PtoGRAS50 module in modulating FL. Combined with dual-luciferase reporter gene assay, real-time reverse transcription polymerase chain reaction (RT-qPCR), transcriptome and degradome analysis, PtomiR171a exerts a negative regulatory effect on PtoGRAS50, which is a key regulator of early xylem development. DNA affinity purification sequencing (DAP-seq) identified two downstream putative target genes of PtoGRAS50, both of which are involved in cellulose biosynthesis and metabolism. Unlike previous studies about miRNAs in P. tomentosa, this work narrows its scope to miR171 and elucidates the downstream regulatory module. Collectively, these findings elucidate a critical PtomiR171a-PtoGRAS50 regulatory axis, advancing our understanding of the genetic networks that orchestrate wood properties, deepening insights into FL modulation, and laying a foundation for the development of targeted genetic strategies to enhance wood quality in P. tomentosa. Full article