Search Results (8,219)

Foundation models are reshaping computational pathology by enabling scalable task-agnostic representations of histopathological whole-slide images (WSIs). Unlike earlier task-specific deep learning systems, pathology foundation models (PFMs) leverage massive whole-slide image repositories and self-supervised Vision Transformer architectures to achieve broad generalization and few-shot adaptability. Their evolution reflects a shift from weakly supervised approaches such as Clustering-Constrained Attention Multiple Instance Learning (CLAM) and hierarchical architectures such as Hierarchical Image Pyramid Transformer (HIPT) to large-scale efforts including foundation models, UNI, Virchow, Phikon, CONtrastive learning from Captions for Histopathology (CONCH), GigaPath, H-Optimus, Transformer-Based Pathology Image and Text Alignment Network (TITAN), and the Mayo Clinic Atlas. These models demonstrate impressive performance across diagnostic and prognostic benchmarks while also opening pathways for multimodal integration with genomics and clinical data. Yet significant barriers remain including inconsistent generalization across institutions, interpretability lagging behind clinical needs, and slow integration into routine laboratory workflows. Certain domains of anatomic pathology such as cytopathology, transplant pathology, frozen sections, and rare tumor subtypes remain particularly resistant to current models. Here, we review the development of PFMs, critically evaluate their strengths and limitations, and outline priorities for their safe and effective clinical translation. We argue that the next phase of PFM development will depend on rigorous benchmarking, pathologist-in-the-loop deployment, and multimodal fusion ensuring these models evolve from research tools into clinically robust systems. Full article

Duolang sheep, an indigenous breed of southern Xinjiang, are significant for their agricultural systems due to their adaptation to arid and semi-arid environments. This review integrates recent advancements in Duolang’s reproductive biology, genomic studies, and management strategies to address the breed’s reproductive efficiency under challenging ecological conditions. Reproductive traits such as puberty onset, estrous cycle characteristics, and seasonal breeding are influenced by complex genetic and several environmental factors. Numerous remarkable genomic findings highlight key loci related to fecundity, including the Booroola FecB mutation, as well as genes involved in steroidogenesis, folliculogenesis, and HPG axis regulation. Despite the genetic potential for increased prolificacy, Duolang sheep often exhibit low litter sizes, largely constrained by detrimental environmental factors and management practices. This review emphasizes the significance of integrating genetics, nutrition, and reproductive management to optimize productivity. Strategies such as nutritional flushing, hormone-based estrous synchronization, and selective breeding for increased litter size are discussed, with a focus on minimizing the risks associated with early puberty and lamb survival. Furthermore, the review explores the potential of genomic selection, marker-assisted breeding, and advanced reproductive technologies to enhance the breed’s performance. Finally, the review outlines future research directions, necessitating the development of genomic resources, precise breeding programs, and field trials on reproductive interventions to accelerate genetic gains in Duolang sheep. This integrated approach promises to improve reproductive outcomes, with implications for sustainable sheep production in Xinjiang and similar environments across the globe. Full article

BK and JC Polyomaviruses (BKPyV and JCPyV) are ubiquitous human pathogens capable of establishing lifelong, asymptomatic persistence in the majority of the global population. While decades of research have focused on their lytic replication cycles and the development of severe diseases, such as polyomavirus-associated nephropathy (PVAN) caused by BKPyV and progressive multifocal leukoencephalopathy (PML) caused by JCPyV, their primary evolutionary strategy is one of persistence rather than pathogenesis. This review shifts the perspective from a replication-centric framework towards an evolutionary persistence model, detailing the multi-layered host and viral determinants that maintain the homeostatic balance. At the cellular level, viral genomes are restricted by chromatinization into minichromosomes and host S-phase licensing. These constraints are reinforced by innate immune sensing and adaptive T-cell and antibody responses that curtail systemic dissemination while permitting periodic, low-level urinary shedding, which is essential for horizontal transmission. In addition to these host barriers, the viruses utilize intrinsic regulatory mechanisms to prevent excessive replication and immune detection, including the stable archetype non-coding control region (NCCR), viral microRNAs that downregulate early gene expression, and the small t antigen (STAg). Finally, we address unresolved questions regarding the full spectrum of cellular reservoirs, the molecular triggers of reactivation, and the ecological factors shaping their transmission routes. Understanding these maintenance mechanisms is crucial for refining clinical interventions and managing the rare, devastating transitions from silent persistence to lytic disease. Full article

Gliomas represent the most prevalent type of brain tumor, with their most aggressive variant, glioblastoma multiforme, associated with high mortality rates. Due to their elevated molecular heterogeneity, accurate classification of gliomas has presented significant challenges. Therefore, considerable effort has been dedicated to identifying relevant biomarkers that improve early diagnosis and unveil new areas for treatment. Advances in high-throughput sequencing technology have enabled public resources such as The Cancer Genome Atlas (TCGA) to provide large-scale data from various cancers, allowing researchers to perform more comprehensive analysis of this disease. In this study, we introduce MOHVAE-B, a comprehensive framework designed for the integration of multi-omics data and biomarker discovery using data from TCGA. MOHVAE-B employs a supervised hierarchical variational autoencoder integrated with SHAP-based interpretability to effectively integrate high-dimensional multi-omics data and extract the most influential features driving the model’s predictions. Subsequently, Bayesian Networks (BNs) are constructed to model conditional dependencies between the selected features, providing insights into their possible relations. Applied to the TCGA glioma cohorts, MOHVAE-B achieved a near-perfect AUC of $0.9993$ and successfully identified high-impact features related to glioma classification. For glioblastoma multiforme, this included six novel candidates: LINC02172, NACA2, LINC01114, HNRNPA1P48, PPIAL4G, and LINC01558. For low-grade gliomas, the model highlighted AMER2 as a promising marker. Across both cohorts, PMP2 stood out as a particularly strong candidate for a potential role in glioma pathogenesis. The constructed BNs provided an additional layer of validation, reinforcing NACA2 as a candidate of interest in glioma biology. Full article

Background: Hypermobile Ehlers–Danlos syndrome (hEDS), the most common EDS subtype, is characterized by chronic pain and joint laxity, yet no definitive causative genes or imaging-based diagnostic criteria have been established. This study investigated the genetic basis of hEDS using whole-exome sequencing (WES) and objectively evaluated ankle instability. Methods: We conducted an observational cohort study with a case–control comparison, including 22 patients and a three-generation Korean family (six individuals, four affected) diagnosed with hEDS by the 2017 criteria. WES was performed; ankle laxity was assessed by the anterior drawer test (ADT), stress ultrasonography, and stress radiography. Healthy young adults (n = 24, Beighton score < 5) from our previous study served as controls. Results: The hEDS cohort had a mean Beighton score of 8.5, with all participants reporting a family history of hypermobility and musculoskeletal complications. Family-based WES identified variants in CD44 (c.1516 + 1G > A), ITIH2 (c.783C > G), and ADAM21 (c.397C > T) in all affected individuals. In 22 unrelated patients, 114 variants in 103 candidate genes were identified; 17 patients harbored variants in genes from the same pathways as the family-derived causative genes. Compared with controls, the hEDS group showed significantly greater manual ADT grade, anterior talofibular ligament (ATFL) length at rest and under stress, dynamic ATFL change, anterior talar translation, and talar tilt. Conclusions: These findings provide molecular evidence that hEDS is a multifactorial disorder involving interconnected biological pathways, and confirm ankle instability as a clinically meaningful diagnostic feature. These complementary approaches may improve diagnostic accuracy and provide insights into the prognosis and therapeutic strategies for hEDS. Full article

Growing evidence links gut microbiota dysbiosis to neurodegenerative diseases (NDs) such as Alzheimer’s disease and Parkinson’s disease, yet the field remains dominated by correlational observations rather than experimentally validated causal mechanisms. In this hypothesis-generating Perspective, we propose that causal inference in microbiota-associated neurodegeneration may be strengthened by combining two complementary lenses: evolutionary biomedicine and microbial metabolism. Because evolutionary information carries intrinsic temporal and causal structure, it can provide biological prior knowledge for inferring causal mechanisms of diseases. Human Accelerated Regions (HARs), genomic loci conserved across mammals but rapidly divergent in the human lineage, offer an anchor for identifying human-specific host–microbe co-evolutionary units relevant to NDs. We further hypothesize that microbial metabolites represent one class of mechanistically testable intermediates linking host genetic background, gut microbial ecology, and neurodegenerative phenotypes. This integrated evolutionary-metabolic perspective offers a tractable path from correlation toward mechanism in gut microbiota–ND research. Full article

Background: As a transcription factor superfamily unique to plants, WRKY plays broad roles in both secondary development and secondary metabolic processes. Robinia pseudoacacia is renowned for its durable and naturally durable heartwood, which holds significant commercial value. However, their potential association with heartwood formation remains largely unexplored. Results: Leveraging published genomic data from Robinia pseudoacacia, we conducted a comprehensive bioinformatics analysis that identified 85 WRKY transcription factors. An uneven distribution across 11 chromosomes was observed for the RpWRKY genes, which were systematically named RpWRKY1 to RpWRKY85 according to their genomic locations, as determined by chromosomal localization. By conducting a phylogenetic comparison between RpWRKY and AtWRKY (from Arabidopsis thaliana), the RpWRKY family was categorized into three primary clades (I, II, and III), wherein group II was additionally partitioned into subgroups designated IIa through IIe. Conserved structural features and motif patterns were observed among members of each subgroup. Purifying selection was suggested by collinearity analysis as the primary evolutionary driver of RpWRKY, leading to structural and functional diversification. Finally, four candidate genes (RpWRKY78, RpWRKY45, RpWRKY50, RpWRKY80) potentially involved in heartwood formation regulation were identified through analysis of xylem tissue-specific expression patterns. Conclusions: For this economically important tree species, the present study not only provides the first systematic characterization of RpWRKY but also identifies potential regulators of heartwood development. Thus, the present study lays the groundwork for subsequent research aimed at uncovering the molecular processes that regulate heartwood development. Full article

Bringing a new drug to market is a complex, costly, and lengthy process, averaging $2.6 billion and about ten years of research and development. It involves multiple stages, from target discovery to post-approval monitoring, and relies heavily on innovation driven by collaboration among pharmaceutical sciences, biology, biochemistry, engineering, and artificial intelligence. Drug discovery can be divided into four main stages: target selection and validation; compound screening and optimization; preclinical studies; and clinical trials. First, researchers identify and validate a biological target associated with a disease using genomic, proteomic, and bioinformatic approaches. Next, potential compounds (“hits”) are identified through methods such as high-throughput and virtual screening, followed by iterative chemical optimization and functional testing. Promising candidates undergo preclinical in vivo studies to assess pharmacokinetics, pharmacodynamics, and toxicity. Clinical development proceeds in three phases: Phase I evaluates safety in healthy volunteers; Phase II assesses efficacy in patients; and Phase III confirms efficacy and safety in larger populations. After successful trials, regulatory agencies review the data for approval. While small molecules have long dominated due to their stability and oral bioavailability, biologics—such as monoclonal antibodies and mRNA-based therapies—have grown rapidly, highlighted by COVID-19 vaccine development and increasing FDA approvals. Full article

The ability to rapidly estimate bacterial numbers in a pure culture is an important research tool, often performed by measuring the optical density of the culture. However, this method is of limited use with mycoplasma cultures. Therefore, a new method for estimating Mycoplasma gallisepticum cell numbers in a pure culture was developed based on the fluorescent measurement of genomic DNA from lysed cells. Actual Mycoplasma gallisepticum counts obtained from either Color Change Units (CCU) or Colony Forming Units (CFU) were used to create equations to estimate mycoplasma concentration from either DNA concentration data obtained from lysed cells or optical density data from mycoplasma in media. The results suggest that calculated counts are slightly more accurate than those obtained from OD600 data. The results further show that calculating culture concentration using the DNA concentration has a wider range compared to using OD600 data. Results also showed that equations generated using one M. gallisepticum strain could work for a second M. gallisepticum strain. However, it was also shown that the equations were not accurate for a different mycoplasma strain. These results suggest that measuring DNA concentration from lysed mycoplasma cells can provide another useful tool for estimating mycoplasma culture concentrations. Full article

Breast cancer is prevalent and deadly, affecting women worldwide. Increasing research suggests that lysine lactylation (KLA) and DNA damage repair (DDR) play critical roles in tumor progression and that KLA and DDR are interconnected, as KLA can modulate DDR protein function, thereby influencing genome stability and drug response, while DDR signaling can reciprocally reshape lactate metabolism and KLA activity. In this study, we developed a novel prognostic gene signature (KLA and DDR index, KLDRI) based on KLA- and DDR-related genes. Model genes (PGK1, MORF4L2, RAD54B, RPA3, CCND2) were generated via LASSO-Cox regression. Patients were stratified into high- and low-risk groups according to KLDRI, the robust prognostic value of which was demonstrated via survival and validation analyses in the TCGA cohort and the METABRIC and GSE96058 cohorts, respectively. Tumor microenvironment analysis indicated an immunologically suppressed phenotype in high-risk patients, whereas low-risk patients exhibited an immune-inflamed microenvironment. Drug sensitivity analysis indicated reduced sensitivity to multiple chemotherapy and targeted therapy drugs in the high-risk group. Single-cell transcriptomic analysis revealed differential gene expression patterns between risk groups. A prognostic nomogram based on KLDRI was developed to predict overall survival. Furthermore, functional experiments demonstrated that RPA3 knockdown suppressed cancer cell proliferation and migration, sensitized cells to cisplatin treatment, and reduced global lactylation, which may serve as a novel biomarker and potential therapeutic target. These findings enhance our understanding of the interplay between KLA, DDR, and breast cancer progression, facilitating the development of personalized therapeutic strategies. Full article

The genus Desmidorchis Ehrenb. (Apocynaceae) is a characteristic component of the succulent flora of the Arabian Peninsula, where high levels of endemism and increasing environmental pressures highlight the need for integrated genomic and conservation research. This study assessed the conservation status of three ethnomedicinally important endemics—D. adenensis, D. arabica, and D. awdeliana—and characterizes their complete plastomes to resolve their evolutionary and temporal history. Conservation assessments were conducted following IUCN Red List criteria, and complete plastomes were sequenced and compared within a dataset of 15 subtribe Stapeliinae taxa. Comparative analyses examined the genome structure, divergence hotspots, repetitive sequences, codon usage bias, and selection pressure, while divergence times were estimated using fossil-calibrated molecular clock analyses. All three species were classified as Near Threatened (NT), primarily due to anthropogenic and environmental pressures. Plastome analyses revealed a highly conserved genome structure; however, hypervariable regions, particularly ycf1 and clpP1, exhibited elevated sequence divergence and phylogenetic informativeness. Simple sequence repeats (SSRs) were also identified as potentially informative features at the genus level. Codon usage and Ka/Ks analyses further indicated that most plastid protein-coding genes are under strong purifying selection, whereas only a few loci, particularly clpP1, showed comparatively elevated evolutionary rates. Phylogenomic analyses supported the monophyly of Desmidorchis, with molecular dating indicating recent Pleistocene diversification (~0.34–1.51 Ma), potentially associated with Quaternary climatic oscillations. Overall, this study provides an important genomic foundation for future taxonomic, evolutionary, and conservation studies of rare Arabian taxa. Full article

Somatic cell nuclear transfer (SCNT) in pigs has been a widely used technique for producing gene-edited pigs for biomedical research, yet its wide-spread application through serial cloning remains markedly limited. Unlike in mice, where the serial cloning can be sustained across numerous generations, in pigs it is usually limited to only a few rounds. Specifically, porcine serial cloning has not been reported beyond three consecutive generations in live-born offspring, with blastocyst development rates declining from approximately 4.4% in G1 to 1–5% in G2–G3, and live-birth cloning efficiency (offspring/recipient) dropping sharply with each successive round. Compelling evidence suggests that cumulative epigenetic instability, incomplete embryo genome activation, DNA methylation reprogramming, persistent donor-cell memory, and imprinting disruption collectively erode transcriptional integrity across generations. Although several manipulations, including epigenetic modifiers, transiently improved the early development, they failed to sustain the reprogramming across several generations. Here, we synthesize comparative advances in serial cloning across species and propose that species-specific differences in chromatin plasticity and cytoplasmic reprogramming capacity define a porcine “reprogramming ceiling”. Deciphering and overcoming this barrier will be critical for advancing sustainable livestock engineering, xenotransplantation and translational medicine biotechnology. Full article

Gene editing technology, a revolutionary tool in molecular biology, enables precise modifications of genomic sequences and gene expression patterns, thereby conferring desired traits to cells or organisms. Since 2014, CRISPR/Cas9 has rapidly become the most widely used gene editing method in agricultural animals due to its high editing efficiency. Subsequently, the development of novel gene editing systems, such as base editors and prime editors, has provided enhanced precision and reduced off-target effects. These advancements have facilitated the transition of gene editing from laboratory research to clinical and agricultural applications. Gene editing has been extensively utilized to enhance production traits, improve disease resistance, facilitate disease detection, and establish disease models. This review outlines the development of gene editing technologies, discusses the advantages and limitations of key gene editing tools, and explores their applications in poultry. Furthermore, it examines the challenges and future prospects of gene editing in animal husbandry, including off-target effects, ethical concerns, and technical complexities. Full article

Fungal infections represent an escalating global health challenge due to their increasing incidence, the emergence of multidrug-resistant pathogens, and the limited development of new antifungal agents. Therapeutic efficacy is compromised by mutations in drug targets, overexpression of efflux pumps, alterations in the ergosterol biosynthetic pathway, biofilm-associated tolerance, and extensive genomic plasticity. The growing prevalence of antifungal resistance and the limited availability of effective therapeutic options highlight the urgent need to strengthen epidemiological surveillance and accelerate research into innovative therapeutic strategies. In this review, we discuss the potential of lipid-based drug delivery systems (LDDSs) as a versatile strategy to optimize antifungal administration and overcome resistance mechanisms. Liposomes (LPs), solid lipid nanoparticles (SLNs), nanostructured lipid carriers (NLCs), and lipid nanoparticles (LNPs) offer high biocompatibility, efficient encapsulation of hydrophobic compounds, structural stability, and controlled drug release. Their nanoscale properties facilitate penetration into biofilms, promote intracellular uptake, and reduce the impact of efflux-mediated drug extrusion, thereby improving cellular penetration and circumventing resistance pathways. In addition, LDDSs increase bioavailability, reduce toxicity, and promote drug accumulation within poorly accessible tissue compartments. Overall, LDDSs represent a promising approach to expand the therapeutic arsenal against both superficial and invasive fungal infections, particularly those caused by multidrug-resistant pathogens. Full article

The buffalo is an important agricultural species due to its many productive characteristics, which encourage its use worldwide. Uncovering the processes of selective sweeps is critical for a comprehensive understanding of genomic mechanisms that influence phenotypic differentiation in buffalo. This study aims to refine signatures of selection in Bulgarian (BUL), Hungarian (HUN), and Romanian (ROM) buffalo breeds using runs of homozygosity (ROHs), the integrated haplotype score (iHS), the standardized log-ratio of the integrated site-specific extended haplotype homozygosity (EHH) between pairs of breeds test (Rsb), and cross-population EHH (XP-EHH) approaches. The SNP dataset of 160 genotypes from BUL, HUN, and ROM buffalo breeds was genotyped using the Axiom^® Buffalo Genotyping Array 90K from Affymetrix. By combining the ROH, iHS, Rsb, and XP-EHH methods, we identified many important genomic regions and candidate genes associated with milk production (SLC24A2, TMEM132C, and ALCAM), reproduction (CSMD1, NTS, PLIN2, GPC5, and FSHR), growth (MYOM2, CLN8, and RRAGA), immune response (METTL25, MLLT3, NAALADL2, and GAB2), and adaptation (ADAMTSL1) in BUL, HUN, and ROM buffalo breeds. Our findings highlighted selection signals and genes related to important economic traits in the BUL, HUN, and ROM buffalo breeds, providing promising candidate genes for further research and inclusion in conservation and selection plans for these breeds. Full article