Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Viral sequence constraints”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

413 records · Page 5Linked to original sources
PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗
PubMed2026

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans↗
PubMed2026

Complete genome sequence of the Anaplasma phagocytophilum clinical isolate NCH-1.

Anaplasma phagocytophilum is an obligate intracellular gram-negative bacterium and etiologic agent of human granulocytic anaplasmosis. A. phagocytophilum genomic sequencing has historically been performed via short-read platforms. Our optimized bacterial isolation protocol combined with Nanopore sequencing produced a single, closed 1,481,805 bp circular A. phagocytophilum strain NCH-1 chromosome.

Anaplasma phagocytophilum↗
PubMed2026

Epigenetic Gene Networks Governing Immune State Transitions Across the Lifespan.

Immune function across development, tissue repair, aging, and disease depends not only on signaling pathways but also on epigenetic architectures that determine whether coordinated transcriptional programs can be accessed and resolved. Increasing evidence indicates that epigenetic gene networks regulate the accessibility and reversibility of semi-stable immune states, shaping plastic, homeostatic, reparative, and degenerative configurations. We propose the concept of epigenetic transition windows, defined as temporally and contextually restricted intervals during which epigenetic constraints are relaxed, permitting coordinated and reversible transitions between immune states. During development, these windows are broad and support immune tolerance and adaptive plasticity. In adulthood they become spatially and temporally restricted, preserving stability while enabling conditional adaptation. With aging, they progressively narrow, contributing to chronic inflammation, impaired repair, and increased vulnerability to neurodegeneration. Conversely, pathological persistence of regulatory permissiveness may underlie immune evasion and sustained plasticity in cancer. We outline operational genomic readouts for quantifying transition windows, including chromatin accessibility variance, enhancer switching dynamics, reversibility metrics, and cross-cell coordination indices, and derive experimentally testable predictions that distinguish this model from pathway-centric or damage-centric explanations. By reframing immune dysfunction as a failure of regulated state transition rather than excessive signaling alone, this framework integrates inflammaging, trained immunity, immune resolution failure, and tumor immune escape within a unified regulatory architecture and provides a systems-level perspective on immune adaptability across the lifespan.

Epigenesis, Genetic↗
PubMed2026

Draft genome sequence of Enterococcus casseliflavus strain MBBL_MP4 isolated from healthy bovine milk.

We report the draft genome sequence of Enterococcus casseliflavus MBBL_MP4, recovered from healthy bovine milk. The 3.45-Mbp genome assembly comprises 27 contigs and indicates low pathogenic potential, with no acquired antimicrobial resistance or known virulence genes. This genome provides a valuable resource for the genomic characterization of bovine-associated E. casseliflavus.

Enterococcus casseliflavus↗
PubMed2026

Human endogenous retroviruses leading to autoimmune diseases.

Human endogenous retroviruses (HERVs) comprise approximately 8% of the human genome and were long regarded as inert remnants of ancestral retroviral infections. Increasing evidence indicates that HERVs are active genomic elements capable of influencing transcriptional programs, modulating immune responses, and contributing to disease pathogenesis. Under physiological conditions, HERV expression is tightly controlled by epigenetic mechanisms; however, infections, chronic inflammation, aging, and diverse environmental stimuli can promote HERV reactivation. HERV-derived RNAs and proteins engage innate immune sensors and trigger antiviral-like responses through mechanisms of viral mimicry, leading to activation of type I interferon and other inflammatory pathways. HERV dysregulation has been associated with disease-relevant immune pathways. This review summarizes recent advances linking HERVs to autoimmune disease pathogenesis and discusses their potential translational relevance as biomarkers and therapeutic targets.

Humans↗
PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗
PubMed2026

Targeted sequencing reveals a distinct genetic alteration landscape in oral multiple primary squamous cell carcinomas.

OBJECTIVE: Oral multiple primary cancers (MPCs) are associated with poor clinical outcomes, yet their genomic characteristics remain insufficiently understood. DESIGN: Fifty-four formalin-fixed paraffin-embedded (FFPE) tumor samples from 30 patients with oral MPCs were analyzed using high-depth targeted sequencing of a customized 14-gene panel derived from prior whole-exome sequencing data. Detected alterations were analyzed after removal of synonymous mutations. RESULTS: Non-silent genomic alterations were identified in 59.3% (32/54) of samples, involving 19 patients. A total of 70 variant loci across 13 genes were detected. AKAP13 was the most frequently mutated gene at both the sample (22.2%, 12/54), with recurrent mutations observed across multiple patients. In contrast, TP53 mutations occurred at a substantially lower frequency (11.1%, 6/54). Marked inter- and intra-patient mutational heterogeneity was observed. CONCLUSIONS: FFPE-based targeted sequencing enabled an initial characterization of genomic alterations in oral MPCs. Recurrent alterations in AKAP13, GLI2, JMJD1C, and DNAH8, together with the relatively low frequency of TP53 alterations, identify candidate genomic features for further investigation and provide a basis for future studies of the molecular basis of oral MPCs.

Humans↗
PubMed2026

Long-term efficacy of cognitive behavioural therapy for insomnia (CBT-I) on depressive symptoms: A systematic review and meta-analysis of randomised controlled trials.

Depressive symptoms are common in individuals with persistent insomnia. Previous meta-analyses of randomised controlled trials (RCTs) showed that cognitive behavioural therapy for insomnia (CBT-I) can reduce depressive symptoms at post-treatment. However, the long-term maintenance of these improvements has never been systematically examined. To fill-in this gap, we conducted a systematic review and meta-analysis of the long-term (&#x2265;3 months) effects of CBT-I on depressive symptoms. The review was registered in PROSPERO (CRD420251146061). Only RCTs in adults with insomnia were considered. Pubmed, Scopus, Psycinfo, CINAHL, and Medline were searched up to 12 September 2025 with no predefined time constraints. From 5359 records initially retrieved, we included 53 articles reporting on 13,608 individuals. After outliers removal, random effects meta-analysis showed that CBT-I was superior to control conditions in reducing depressive symptoms at 3 [k&#x202f;=&#x202f;29, d&#x202f;=&#x202f;-.35, [95% CI: -.49 to -.21], p&#x202f;<&#x202f;.001], 6 [k&#x202f;=&#x202f;29, d&#x202f;=&#x202f;-.32, [95% CI: -.59 to -.05], p&#x202f;=&#x202f;.018], and 12 [k&#x202f;=&#x202f;10, d&#x202f;=&#x202f;-.25, [95% CI: -.39 to -.12], p&#x202f;<&#x202f;.001] months follow-ups. Results demonstrate that the effects of CBT-I on depressive symptoms are sustained throughout the year following treatment, although effects may decline over time.

Humans↗
PubMed2026

Teaching Engagement and Caregiving Help in the Intensive Care Unit (TEACH-ICU) Scale: Content Validity.

BACKGROUND: Having family members provide care to their loved ones in the intensive care unit (ICU) is a beneficial yet seldom implemented approach. For family members to perform caregiving, nurses must be willing to teach, and such willingness is a developing area of research. OBJECTIVES: To adapt an instrument validated in family members, the Family Willingness for Caregiving Scale, to address nurses' willingness to teach family members caregiving skills. METHODS: Purposive and snowball sampling were used to recruit 10 expert ICU nurses through the American Association of Critical-Care Nurses' research website and social media platforms. The researchers conducted cognitive interviews with the nurses to address the instrument's content validity. RESULTS: The scale was refined based on the participants' feedback. Items were deleted, added, and revised. Furthermore, scale instructions were adjusted to emphasize the willingness to teach families of patients receiving mechanical ventilation. Qualitative themes emerged related to barriers to family engagement, including time constraints, patient acuity, and nurse and family characteristics. CONCLUSIONS: Content validity of the scale was assessed, with future research aimed at pilot testing and evaluating construct validity before using the scale as a research instrument. Practical implications include using the scale as an evaluation tool to determine nurses' willingness to teach family members about caregiving. After evaluation, various strategies could be incorporated to enhance family engagement in adult ICUs.

Humans↗
PubMed2026

Synchronicity of parent-child sleep and potential mechanisms: A systematic review and meta-analysis.

Existing evidence indicates that parent and child circadian rhythms are associated, but studies have mainly examined factors affecting child sleep health. This systematic review addressed two questions: a) is there a synchronous relationship between parent and offspring sleep? and b) what are the potential mechanisms? PubMed, Embase, PsychINFO, and Scopus were searched from inception to April 2025. Forty-six studies comprising over 100000 parent-child dyads across 16 countries were included. Results showed small-to-moderate parent-child synchronicity in sleep duration (r&#x202f;=&#x202f;0.18, 95% CI [0.14, 0.23]), sleep efficiency (r&#x202f;=&#x202f;0.30, 95% CI [0.19, 0.41]), bedtime (r&#x202f;=&#x202f;0.34, 95% CI [0.20, 0.46]), and wake up time (r&#x202f;=&#x202f;0.48, 95% CI [0.24, 0.66]), with stronger effects observed in mother-child dyads. Synchronicity in sleep continuity was moderate, whereas associations in sleep satisfaction were small and non-significant. Mechanisms included genetic and hormonal factors, bedtime routines, shared environments, and attachment. These findings are consistent with family systems theory's premise that sleep is a relational phenomenon. Observed synchronicity in sleep timing may partly reflect shared external constraints like work and school schedules. Most studies were cross-sectional, limiting causal or directional conclusions. Future research should adopt standardized methodologies and longitudinal designs to clarify mechanistic pathways.

Humans↗
PubMed2025

Diagnostic and clinical utility of exome sequencing and chromosomal microarray in children with GDD/iD: a meta-analysis.

BACKGROUND: Global developmental delay/intellectual disability (GDD/ID) is among the most common neurodevelopmental disorders, with up to half of cases are attributed to genetic factors. Chromosome microarray (CMA) has traditionally been the primary genetic test for idiopathic GDD/ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) have recently emerged, substantially increasing diagnostic yields in these populations. METHODS: We conducted a comprehensive literature search of PubMed, Scopus, EMBASE, and the Cochrane Library from inception to April 29, 2025. Studies reporting the diagnostic utility of these tests in children with GDD/ID were included and analyzed. RESULTS: A total of 102 studies, comprising 55,752 children, were reviewed. The pooled diagnostic yield of WES was 0.37 (95% CI: 0.33-0.41; I2 = 93%), significantly higher than that of CMA at 0.19 (95% CI: 0.16-0.21; I2 = 95%). Subgroup analyses showed that WES yielded significantly higher diagnostic rates than CMA in both same-sample comparisons (OR = 2.27, 95% CI: 1.08-4.78) and different-sample comparisons (OR = 1.65, 95% CI: 1.15-2.37). Only one study evaluated WGS, reporting a diagnostic yield of 0.27. Meta-regression revealed a significant association between CMA diagnostic yield and the proportion of male participants (p&#x2009;<&#x2009;0.01), but not with WES. No significant difference in diagnostic utility was observed between isolated GDD/ID and GDD/ID with comorbidities. CONCLUSION: In children with unexplained GDD/ID, WES demonstrates superior diagnostic and clinical utility compared to CMA. Incorporating WES as a first-line investigation in the diagnostic evaluation of GDD/ID may be warranted.

Humans↗
PubMed2026

Comprehensive analysis of mRNA-microRNA-lncRNA expression profiles in post-traumatic elbow heterotopic ossification using RNA sequencing and experimental validation.

BACKGROUND: This study aimed to profile the molecular signatures of post-traumatic elbow heterotopic ossification (HO) to identify key regulators and potential therapeutic targets. METHODS: Total RNA from post-traumatic elbow HO tissues (n=4) and normal bone tissues (n=6) was subjected to high-throughput sequencing to identify differentially expressed mRNAs (DEGs), microRNAs (DEMs), and lncRNAs (DELs). Bioinformatics analyses included Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction network construction, and transcription factor (TF)-microRNA-mRNA network analysis. The expression trends of four most upregulated and four most downregulated DEGs were validated by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: We identified 2,138 DEGs, 40 DEMs, and 905 DELs. DEGs were significantly enriched in biological process "bone mineralization," cellular component "plasma membrane," molecular function "integrin binding," and pathways including PI3K-Akt, NF-&#x3ba;B, JAK-STAT, and TNF signaling pathways. Hub genes with high connectivity included MMP9, IL6, MMP3, CTSK, and BGLAP. Integrated network analysis highlighted the transcription factor JUN and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b). The qRT-PCR results confirmed the expression trends of selected DEGs. CONCLUSIONS: This study, for the first time, profiled the differentially expressed mRNAs, microRNAs, and lncRNAs in post-traumatic elbow HO using high-throughput RNA sequencing. These findings provide valuable insights into the molecular mechanisms of HO following elbow trauma. The identified hub genes (MMP9, IL6, MMP3, CTSK, and BGLAP), key TF (JUN), and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b) may serve as potential therapeutic targets for preventing and treating post-traumatic elbow HO.

Humans↗
PubMed2026

The cold case of state transition 7 (stt7) mutants of Chlamydomonas reinhardtii, solved by whole-genome sequencing.

The process of State Transitions (ST) corresponds to an STT7 kinase-driven redistribution of the transmembrane LHCII antenna proteins between Photosystem II (PSII) and Photosystem I (PSI), which results from changes in their phosphorylation state. For the past two decades, two LHCII-kinase mutants, stt7-1 and stt7-9, have been instrumental in the study of STs in Chlamydomonas reinhardtii, the former being a null mutant for the kinase but quasi-sterile in crosses, while the latter, although fertile, has a leaky phenotype. Using long-read sequencing, this study further characterized the genetic lesions of the stt7 mutant strains through whole-genome reconstruction and de novo chromosome assembly. In addition, two new stt7 null mutants were generated, one derived by crosses from the original stt7-1 and one obtained by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (Cas9) technology. This work provides a comprehensive genomic characterization of the original stt7-1 null mutant, revealing extensive chromosomal rearrangements and high levels of aneuploidy, associated with increased cell size and meiotic dysfunction. Reassessment of their physiology and genetic backgrounds highlights the need for caution in interpreting genetic information. We thus produced more reliable null mutants for the LHCII-kinase, amenable to genetic crosses for the study of STs in a variety of genetic backgrounds.

Chlamydomonas reinhardtii↗
PubMed2026

Complete genome sequence of multidrug-resistant Salmonella enterica subsp. enterica serovar Enteritidis SD191 isolated from chicken liver, harboring a novel imipenem resistance mechanism.

We present the complete genome sequence of Salmonella enterica subsp. enterica serovar Enteritidis SD191 isolated from Gallus gallus liver in China, harboring plasmid pSE191. The genome reveals multiple antibiotic resistance mechanisms and phenotypic imipenem resistance without canonical genes.

antibiotic resistance↗
PubMed2026

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (&#x3a8;) represents one of the most abundant and conserved RNA modifications. &#x3a8; provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of &#x3a8; sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel &#x3a8; site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA &#x3a8;-site prediction. The &#x3a8; modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA &#x3a8;-site prediction. Meta-PseU offers a new framework for robust &#x3a8;-site identification by using long sequences.

Pseudouridine↗