Search Results (3,607)

The white rhinoceros (Ceratotherium simum) offers a unique model for investigating the genomic consequences of extreme demographic bottlenecks. However, the fragmented southern white rhinoceros genome assembly has limited chromosome-scale structural and evolutionary comparisons with the functionally extinct northern subspecies. Here, we report a chromosome-scale genome assembly for the southern white rhinoceros by integrating Oxford Nanopore Technology long-read sequencing, Illumina short-read polishing and high-throughput chromosome conformation capture (Hi-C) scaffolding. The final assembly spans 2.48 Gb and achieves a contig N50 of 42.06 Mb, representing a 452-fold improvement in contiguity over the previous assembly. In total, 2.46 Gb of sequence was anchored to 40 autosomes plus the X and Y chromosomes. Genome annotation identified 1.13 Gb of repetitive elements (45.7% of the assembly), 22,593 protein-coding genes, and 100.68 Mb of segmental duplications. Inspection of the major histocompatibility complex class II gene region further supported the local assembly and annotation reliability, revealing conserved gene composition and order between the southern and northern white rhinoceroses. Whole-genome comparison with the northern white rhinoceros assembly indicated extensive chromosome-scale synteny, along with localized structural variants between the two subspecies, including 111 inversions spanning 33.48 Mb and 497 translocations spanning 36.48 Mb. Furthermore, coalescent demographic reconstruction indicated asynchronous Pleistocene population dynamics for southern and northern white rhinoceroses, reflecting divergent responses to historical climate oscillations. Both subspecies also exhibit lower recent effective population sizes than estimated Pleistocene ancestral levels, underscoring persistent conservation concern. This assembly provides a useful resource for evaluating the genomic consequences of historical bottlenecks, informing future genomic-rescue plans, and strengthening the comparative framework for rhinoceros conservation and evolutionary genomics. Full article

As part of efforts to identify genes associated with Trichomonas vaginalis resistance to 5-nitroimidazole drugs, thirty cryopreserved T. vaginalis isolates were revived and grown using Diamond’s TYM medium. Minimum lethal concentrations (MLCs) for metronidazole (MTZ), tinidazole (TDZ), and secnidazole (SEC) were determined using a drug susceptibility assay. Transcriptome profiling was performed for 15 MTZ-sensitive (MTZ-S, MLC < 50 µg/mL) and 15 MTZ-resistant (MTZ-R, MLC ≥ 50 µg/mL) isolates using next-generation RNA sequencing. Bioinformatics analyses identified differentially expressed genes (DEGs). Among the MTZ-R isolates, six exhibited low MLCs of 50 µg/mL, five had intermediate MLCs between 100 and 200 µg/mL, and four had high MLCs ≥ 400 µg/mL. Differential gene expression analysis identified 28, 140, and 73 significantly altered genes in low-, intermediate-, and high-level MTZ resistance groups, respectively, with predominantly upregulated expression patterns. The SEC-resistant (SEC-R) isolates exhibited 136 differentially expressed genes, whereas the TDZ-resistant (TDZ-R) isolates showed minimal transcriptional changes. Focused analyses of iron transport pathways revealed reduced expression of ZIP-family iron import genes, particularly TvZIP4 (TVAG_273550), the strongest predictor of resistance in elastic-net modeling (AUC = 0.795). Resistant isolates also demonstrated coordinated upregulation of iron–sulfur cluster assembly and hydrogenosomal protein-import pathways. Weighted gene co-expression network analysis (WGCNA) identified multiple resistance-associated transcriptional modules correlated with MTZ and SEC MLCs. A comparative transcriptomic–proteomic analysis revealed concordant upregulation of iron–sulfur cluster machinery but discordant regulation of hydrogenosomal cargo proteins, likely supporting a post-transcriptional restriction model. These findings provide a broader mechanistic framework for understanding 5-nitroimidazole resistance in T. vaginalis and identifying candidate biomarkers and pathways that may support future therapeutic and diagnostic development. Full article

Programmable peptide hydrogels represent advanced supramolecular biomaterials featured with customizable molecular sequences and tunable self-assembly behaviors, which can biomimetically reconstruct the structural and microenvironmental complexity of native extracellular matrix. This review systematically elaborates the molecular engineering advances of programmable peptide hydrogels following a hierarchical logic from fundamental mechanisms to translational applications. We first interpret the intrinsic self-assembly mechanisms driven by non-covalent interactions and the regulatory effects of typical external microenvironmental stimuli. On this basis, we summarize core rational design principles, covering stimuli-responsive structural optimization, biofunctional modification, and the tunable regulation of physical properties, degradability and immunogenicity. Furthermore, we correlate multi-scale structural features (nanostructures, porous architecture and mechanical properties) with their versatile biomedical functions, and comprehensively discuss their cutting-edge applications in tissue regeneration, targeted drug and gene delivery, cell-mediated therapy, immunomodulation, and anti-infective treatment. Finally, we identify critical translational barriers including batch-to-batch inconsistency, immunogenic risks, and in vivo performance instability, and highlight future directions involving multi-stimuli-responsive systems, artificial intelligence-assisted design, computational modeling, and hybrid material construction. This work systematically clarifies the structure–property–function relationship of peptide hydrogels, and underscores their great potential as next-generation platforms for precision regenerative medicine and targeted disease intervention. Full article

Background/Objectives: Melophagus ovinus is an economically important ectoparasite of small ruminants with a broad global distribution. Although mitochondrial genomes are widely used in population genetic studies, the D-loop region of M. ovinus remains poorly characterized because its high AT content and repetitive structure complicate amplification, assembly, and sequencing. Methods: We sequenced the mitochondrial genome of M. ovinus collected from Qinghai using an integrative approach combining Illumina paired-end sequencing, targeted PCR amplification, and Nanopore long-read sequencing. Comparative genomic analysis was performed against published mitogenomes from Gansu (MH024396) and Xinjiang (NC_037368). Results: The Qinghai mitochondrial genome contained the typical 37 mitochondrial genes within a 14,728 bp conserved region. Comparative analysis revealed exceptionally high conservation (>99.6% sequence identity) among Qinghai, Gansu, and Xinjiang isolates outside the D-loop region. Notably, the D-loop exhibited length polymorphism, with different assembly strategies or samples yielding lengths ranging from 317 bp to 2385 bp. Targeted long-read sequencing of ten individuals identified a predominant D-loop variant of approximately 844 bp in nine samples and a markedly shorter variant of approximately 164 bp in one sample. The short variant was characterized by extensive deletions and a novel 45 bp insertion. Support for this variant was obtained from independent Illumina DNA-seq, RNA-seq, Nanopore sequencing, and de novo assembly analyses. Conclusions: This study provides preliminary evidence for D-loop structural heterogeneity in M. ovinus, suggesting remarkable length polymorphism and complex indel patterns that require further validation. These findings significantly expand the genomic resources available for this important veterinary parasite and establish a foundation for future population genetic and evolutionary studies. Full article

Contemporary iterations of avian phylogenies based on multiple genome sequence assemblies assign three major clades: Palaeognathae (mostly ratite birds), Galloanseres (land and waterfowl) and the largest group—Neoaves. The latter two are sister clades representing subdivisions of Neognathae, while Neoaves further subdivide into Columbaves (pigeons/doves/cuckoos/bustards, etc.), Mirandornithes (flamingos/grebes), Telluraves (“higher land birds”, including finches) and the newly recognized Elementaves (e.g., penguins/pelicans/hummingbirds/swifts/cranes/shorebirds). Molecular studies provide clade information, likely divergence timings and a framework from which gross genomic (chromosomal) changes may be mapped. In this review, we consider the patterns of chromosome change that have occurred throughout all avian clades thus far examined, citing studies from standard karyotyping through molecular cytogenetics to whole genome assemblies. Standard karyotyping led to the realization that most chromosomes (particularly the microchromosomes and dot chromosomes) could not be distinguished by classical means. Indeed, cross-species comparisons were difficult, even among the macrochromosomes, because of indistinct banding patterns. Based on fluorescence (or fluorescent) in situ hybridization (FISH), comparative genomics was thence progressed considerably by cross-species chromosome painting (Zoo-FISH) for the macrochromosomes and interspecific mapping of bacterial artificial chromosome (BAC) probes for the microchromosomes. A key finding was that the most studied species, the chicken, fortuitously, has a genomic organization somewhat akin to that of the ancestral karyotype and tends to be the standard from which all others are measured. A notable exception is the fusion of basal chromosome 4 with a smaller chromosome that convergently appears in some other Galliformes, at least one goose and one dove species. While some groups such as Falconiformes (falcons, etc.) and Psittaciformes (parrots, etc.) underwent extensive interchromosomal change, most, broadly speaking, retain a basic karyotype that differs little from bird to bird. Many, e.g., Passeriformes (finches, songbirds, etc.) and Columbiformes (pigeons, doves), do this despite multiple intrachromosomal rearrangements. The complete karyotype and fully established chromosome-level genome assembly of the chicken allow full integration of DNA sequence assembly with karyotype. They further permit cytogenetic studies to be performed using genome assemblies alone alongside cutting-edge long-read sequencing and optical mapping without the need for chromosome preparation. The classic ZW sex-determination system of birds is easily visible in most Neognathae species, but intrachromosomal change in the sex chromosomes is faster than in the autosomes; indeed, there are numerous examples of autosomal fusions and new sex chromosomes formed. Sex chromosomes aside, the classic avian karyotype represents a very successful mode of genome organization established before the emergence of the dinosaurs and perpetuated to this day in their only living descendants. Full article

Leaf nitrogen concentration (LNC) is an important indicator of Ginkgo nutritional status, but its hyperspectral estimation remains challenging because leaf spectra are high dimensional, strongly collinear, and affected by overlapping structural and biochemical signals. This study examined how spectral preprocessing, wavelength selection sequence, and regression model choice influence leaf scale Ginkgo LNC estimation, while separating simulation-assisted model development from measured sample-based prediction assessment. We assembled 717 field measured Ginkgo leaf spectra with corresponding laboratory measured LNC values and used PROSPECT-PRO simulated spectra only for wavelength screening or calibration augmentation, not as independent validation data. Three evaluation schemes were compared: measured-only analysis, simulated spectra-assisted wavelength selection followed by measured data calibration and testing, and simulated spectra-assisted wavelength selection and calibration followed by measured-only testing. The third scheme was used as the main inference framework because it retained an independent measured sample test boundary. Within this framework, multiple preprocessing methods, two wavelength selection sequences, and four regression models (PLSR, GPR, 1D-CNN, and DGP) were evaluated. MSC showed comparatively low error in the preprocessing comparison, and CARS-SPA identified a compact set of informative wavelengths concentrated mainly in the shortwave infrared region. Under the simulation-assisted calibration framework, the combination of MSC preprocessing, CARS-SPA wavelength selection, and DGP regression produced the lowest test error on the measured sample set (R² = 0.82; RMSE = 2.07 mg g⁻¹). These results indicate that Ginkgo LNC estimation depends on the combined choice of preprocessing method, wavelength selection strategy, and regression model, and provide a methodological reference for simulation-assisted hyperspectral modeling. Full article

Automating system-level nuclear thermal-hydraulic (T-H) model construction remains challenging because platform-specific API syntax, graph connectivity, parameter dependency ordering, and solver admissibility must be satisfied simultaneously. This study develops a closed-loop modeling framework on the SAFRI platform by combining supervised fine-tuning (SFT), a Plan-and-Act agent with retrieval-grounded parameter completion, and reinforcement learning based on group relative policy optimization (GRPO). The SFT stage uses a 6003-record domain corpus derived from expert-authored or expert-verified SAFRI modeling exemplars, while system-level generalization is evaluated on a held-out 50-case in-house evaluation set separated at the case-template level. At the component level, LoRA-adapted Qwen3-8B achieves 100% code accuracy, compared with 50% for zero-shot and 74% for one-shot prompting. At the system level, the SFT agent attains a 100% syntax success rate (SSR), 90% topology success rate (TSR), and 72.4% physical convergence rate (PCR), showing that local API correctness is insufficient for solver-valid model assembly. After GRPO training with schema, topology, physics, and sequence rewards, the full SAFRI-SFT-RL agent reaches a 100% SSR, 100% TSR, and 88.8% PCR on the in-house evaluation set, while an error self-healing loop resolves execution-time failures in an average of 2.3 corrective iterations. These results show that solver-grounded reinforcement learning is effective for closing the gap between syntactically correct script generation and physically convergent nuclear T-H model construction. Full article

Soil depth and habitat degradation can reshape fungal communities in salt-affected wetlands, but their effects on fungal ecological processes remain insufficiently understood. This study examined soil fungi in the Halahai Provincial Nature Reserve and adjacent converted farmland in the western Songnen Plain, Northeast China, where salt-affected meadow soils correspond mainly to Solonetz. Four habitat types—reed wetland, meadow steppe, degraded Suaeda saline patch, and converted farmland—were sampled at 0–20 cm and 20–40 cm soil depths. Soil properties, fungal diversity, taxonomic composition, environmental associations, niche breadth, assembly processes, and FUNGuild-based trophic modes were analyzed using ITS sequencing. Degraded Suaeda soils showed the strongest salinity–alkalinity stress, with pH values of 10.34–10.30 and electrical conductivity of 1.70–1.75 dS·m⁻¹. Fungal richness was highest in surface-converted farmland, with a Sobs value of 423.33, and lowest in deeper degraded Suaeda soil, with a Sobs value of 86.00. Ascomycota dominated most groups, especially degraded Suaeda soils, where its relative abundance reached 75.29–76.80%. ANOSIM confirmed significant community dissimilarity among habitat-depth groups (R = 0.56878, p = 0.001). Specialists accounted for 68.07% of fungal taxa, and stochastic processes, especially drift and dispersal limitation, contributed substantially to assembly. These results indicate that soil depth, salinity–alkalinity, and habitat conversion jointly regulate fungal community structure and ecological processes in degraded soda saline–alkali wetlands. Full article

This study aims to develop an efficient and accurate method for identifying joint parameters in assembled structures. A novel neural network-based joint identification framework is proposed. Frequency response function (FRF) datasets are generated by combining finite element simulation with frequency-domain substructure synthesis. The Uniform Manifold Approximation and Projection (UMAP) algorithm is employed for nonlinear dimensionality reduction in FRF sequences, preserving critical characteristics. A multilayer perceptron (MLP) network is then trained to regress joint parameters from the reduced-dimension FRF data. The necessity of the nonlinear dimensionality reduction within this joint identification framework is verified through comparison with the linear dimensionality reduction technique of principal component analysis (PCA). This methodology is implemented and validated using a tool–collet–holder system. Comparative studies with the global optimization method reveal that the proposed approach maintains superior identification accuracy while achieving significant improvements in computational efficiency across varying preload conditions. Furthermore, the identified joint parameters exhibit strong predictive capability when tested under tool/holder component changes, preload variations, and when coupled with a spindle, proving robustness under complex operational scenarios. This study provides a new technical pathway for the joint identification of assembly structure. Full article

TIDEs (therapeutic peptides, oligonucleotides, and related molecules) represent a rapidly expanding market that has gained significant momentum due to the recent success of Glucagon-like peptide-1 (GLP-1) receptor agonists for the treatment of obesity, diabetes and as cardiovascular and kidney diseases. Chemical synthesis remains the dominant manufacturing route for candidates containing approximately 10–40 amino acids and includes non-proteinogenic amino acids. Consequently, various combinations of solid-phase peptide synthesis (SPPS), liquid-phase peptide synthesis (LPPS), hybrid approaches, or tag-assisted peptide synthesis (TAPS) can be applied to achieve full-sequence assembly. However, identifying the most eco-efficient pathway through experimental trials alone is impractical because of the vast number of possible process combinations and the growing variety of green solvent alternatives. Therefore, process simulation studies—widely established in chemical engineering—must be adapted to the specific physicochemical characteristics of these large, multi-component molecules. This paper provides an overview of the current state of research and illustrates potential process improvements enabled by digital twin technologies as exemplified for the first manufacturing steps of tirzepatide. Full article

Accurate viral protein function annotation is essential for genomic surveillance, yet conventional retrieval-augmented generation (RAG) pipelines often fragment biological evidence into fixed-length text chunks, disrupting relationships among ORFs, annotations, structural domains, sequence motifs, residue mappings, and model-derived attention evidence. We propose ViroBioTree, a tree-structured biological evidence retrieval framework for downstream viral protein evidence review rather than a new primary annotation classifier. Built as an evidence organization layer on ViralMultiNet-derived ORF-level predictions and annotations, ViroBioTree converts sequence, annotation, structure, and attention evidence into typed biological nodes and traceable edges, then performs deterministic multi-channel recall, evidence-aware reranking, balanced TopK selection, rule-based verification, and node-cited report generation. In a demo benchmark, ViroBioTree achieved its strongest deterministic proxy performance on structure-explanation tasks, with Precision@K = 1.0, Recall@K = 1.0, and diversity = 0.52; these values reflect expected node-type and tag agreement rather than independent biological correctness. A bounded full-scale SARS-CoV-2 index contained 39,800 ORF rows, 80,000 attention records, 199,418 nodes, and 495,886 edges. In a stratified full20k diagnostic evaluation, ViroBioTree showed task-dependent advantages over LlamaIndex vector retrieval for conflict detection, evidence retrieval, and structure explanation, while LlamaIndex remained competitive or stronger for annotation-rich function annotation. A cross-family Influenza A Virus (IAV) diagnostic audit showed that the schema can represent IAV evidence namespaces while explicitly exposing missing formal ORF inputs, missing attention evidence, and unavailable residue/PDB assertions. Supplementary robustness, external sanity-check, diversity-risk, expert-evaluation, domain-tool positioning, and cross-family audit analyses supported traceability, report quality, and conservative evidence handling, but also showed that stable Precision@K under query perturbation does not necessarily imply stable retrieved evidence sets. ViroBioTree operates offline and deterministically, but does not address raw-read assembly, base calling, primary ORF prediction, or wet-lab validation. Its results should be interpreted as proxy and expert-reviewed evidence for traceable viral protein evidence retrieval and report generation rather than as direct validation of biological function annotation. Full article

In this study, we sequenced, assembled, and characterized the first complete chloroplast (cp) genome of Eutrema scapiflorum, an alpine species endemic to the Qinghai–Tibet Plateau (QTP). The assembled plastome is 153,041 bp in length and exhibits a typical quadripartite structure, comprising a large single-copy (LSC) region of 83,547 bp and a small single-copy (SSC) region of 17,506 bp, which are separated by two inverted repeats (IRs) of 25,994 bp each. Structurally, the genome encodes 132 unique genes, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Comparative analysis across eight species revealed that genome size variation is primarily driven by the SSC region. Notably, the IR/SC boundaries in E. scapiflorum are highly conserved, which contrasts with the significant IR expansion observed in Capsella tenella. Furthermore, simple sequence repeat (SSR) analysis identified 78 loci, predominantly mononucleotide A/T repeats located in intergenic spacers. Nucleotide diversity analysis pinpointed accD and ycf1 as the most variable genes. Selection pressure analysis indicated that most genes are under purifying selection, while seven protein-coding genes (ycf2, nadhE, cemA, clpP, psbH, ycf4, nadhB) exhibited signatures of positive selection (Ka/Ks > 1). Subsequently, phylogenomic analyses robustly resolved E. scapiflorum within the tribe Arabideae, showing its closest relationship to Alliaria petiolata. Divergence time estimation dated the split between E. scapiflorum and its closest relative to the middle Miocene (~17.57 Ma). Collectively, these findings provide crucial genomic resources and new insights into the structural evolution, phylogenetic placement, and potential adaptive mechanisms of this alpine species within the Brassicaceae family. Full article

Atypical Salmonella enterica strains that evade conventional detection pose significant challenges to food safety surveillance. A hydrogen sulfide (H₂S)-negative and serologically untypable S. enterica strain (SF1060) was detected by qPCR from cooked farmed mussels in Galicia, Spain, and characterized using phenotypic and genomic approaches. Despite typical biochemical profiles, SF1060 failed to produce black colonies on Xylose Lysine Deoxycholate (XLD) agar and lacked detectable somatic antigens by conventional serotyping. Hybrid genome assembly using nanopore and illumina sequencing yielded a closed chromosome and five plasmids. In silico analyses identified the strain as S. Senftenberg ST14. Comparative genomics revealed a chromosomal inversion at the rfb operon (encoding enzymes needed to synthesize deoxysugars and O antigens) mediated by IS5-family transposase ISEc68, which truncated the rfbD gene and separated the remaining rfb genes at rfbD, disrupting O-antigen biosynthesis, explaining the inconclusive phenotypic serotyping results. The phs operon responsible for H₂S production lacked premature stop codons, suggesting the H₂S-negative phenotype may result from an alternative mechanism. This study demonstrates how whole-genome sequencing resolves identification of atypical strains that fail culture-based detection and emphasizes the critical need for molecular surveillance methods in seafood safety programs, particularly in regions where atypical S. enterica variants may be endemic. Full article

Crop residue management strongly influences soil microbial communities, yet the mechanisms by which it regulates microbial co-occurrence network assembly across soil profiles remain poorly understood. Here, we investigated the effects of three straw management practices—no straw return (CK), straw burning (BS), and deep plowing with straw incorporation (DPS)—on soil physicochemical properties, microbial diversity, and co-occurrence network structure across multiple soil depths in a Mollisol of Northeast China. By integrating high-throughput sequencing, network analysis, and structural equation modeling (SEM), we explored the correlative relationships associated with microbial network assembly. DPS significantly correlates with higher soil organic carbon content, nutrient availability, and moisture content, particularly in subsoil layers. Under DPS, we obtained more complex and robust microbial networks characterized by higher connectivity and clustering. In contrast, under BS, we found reduced network complexity and stability. SEM may suggest the presence of distinct assembly mechanisms between microbial groups: bacterial network structure models responded to soil physicochemical properties, suggesting strong environmental filtering, whereas shifts in fungal network structures correlate with alpha diversity, highlighting the importance of biotic regulation. Notably, under the evaluated conditions, beta diversity was positively associated with network structural attributes across both groups, indicating potential links between community compositional variation and microbial co-occurrence patterns. These findings suggest that straw incorporation may be associated with shifts in microbial co-occurrence network attributes under the evaluated field conditions. However, the observed relationships are primarily correlative and based on statistical modeling approaches. The underlying ecological mechanisms linking soil properties, microbial diversity, and network structure require further validation through controlled biochemical, physiological, and experimental studies. This study provides additional ecological insights into soil microbial responses to residue management and highlights the potential role of residue management in shaping microbial network stability under the evaluated field conditions. Full article

To address the damage and failure of electromechanical structures such as Printed Circuit Board (PCB) modules and battery assemblies under multiple impacts, this study combined experimental and modeling approaches to quantitatively investigate the influence of target material mechanical properties on impact acceleration characteristics. Quasi-static tensile/compression tests, split-Hopkinson pressure bar dynamic compression tests, and sequential multiple-target impact experiments were conducted on nine metallic materials, providing constitutive parameters and impact response data. Variance analysis revealed that material type significantly affected acceleration characteristics (p ≤ 1.62 × 10⁻⁵), whereas the target position in the impact sequence was statistically insignificant (p ≥ 0.89). Quantitative prediction models were established for different acceleration characteristics: Ridge regression (α = 0.1) was employed for Peak 1–Peak 3, Duration 1, and Duration 3, while linear regression was used for Duration 2. The results quantitatively demonstrated that the elastic modulus was positively associated with both peak acceleration and duration, while dynamic compressive yield strength exhibited a significant negative influence. This work establishes a preliminary quantitative predictive framework that provides guidance for target material selection in sequential multiple-target impact experiments and offers an experimental approach for generating tunable overload responses in high-intensity impact testing of electromechanical components. Full article