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Genome-wide characterization of NOD-like receptor genes links NLR repertoire evolution to spleen immune responses after Aeromonas hydrophila challenge in the Chinese spiny frog (Quasipaa spinosa).

NOD-like receptors (NLRs) are cytosolic pattern-recognition receptors that detect pathogen-associated and damage-associated molecular patterns and mediate innate immune signaling in vertebrates. However, the genomic repertoire, evolutionary diversification, and infection-associated expression of NLR genes remain poorly defined in non-model amphibians. In this study, 66 NLR genes were identified from the Chinese spiny frog (Quasipaa spinosa) genome and designated as QsNLR1-QsNLR66. These genes were unevenly distributed across chromosomes and were classified into three phylogenetic groups, with most members exhibiting conserved motif architectures. Gene duplication analysis indicated that dispersed duplication was the main contributor to QsNLR expansion. Synteny analysis detected five conserved orthologous gene pairs between Q. spinosa and Pelophylax nigromaculatus, suggesting partial conservation of NLR genomic organization between the two amphibians. Ka/Ks analysis showed that several duplicated gene pairs, including NLRC3-like/QsNLR36 and NLRC3-like/QsNLR50, exhibited Ka/Ks ratios greater than one, suggesting potential sequence divergence after duplication. Spleen RNA sequencing (RNA-seq) after Aeromonas hydrophila challenge revealed enrichment of immune-related Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Weighted gene co-expression network analysis linked several QsNLRs to infection-associated modules, among which QsNLR57 was co-expressed with CYBB, ADAM17, SPI1, and HK2. RT-qPCR using time-matched phosphate-buffered saline (PBS) controls showed distinct temporal patterns, with stronger induction of QsNLR29, QsNLR57, and QsNLR66 and weaker or delayed responses of QsNLR50 and QsNLR56. These results characterize the NLR repertoire of Q. spinosa and identify infection-associated QsNLR candidates for future studies of antibacterial immunity in amphibians.

Animals

miRNA-mediated control of TLR-NLR interplay in the uterus: A hidden corner of recurrent pregnancy loss.

Toll-like receptors (TLRs) and NOD-like receptors (NLRs) are crucial pattern recognition receptors that initiate inflammatory responses and immunological activation upon detecting pathogen- or damage-associated molecular patterns (PAMPs/DAMPS) in the female reproductive tract, thereby maintaining homeostasis and supporting pregnancy success. Their signaling pathways play a significant role in reproductive disorders by mediating the immune response to various pathogenic stimuli. Recurrent pregnancy loss (RPL), defined as the natural ending of two or more pregnancies before 24 weeks of gestation, approximately half of these patients remain idiopathic without precise prognostic, diagnostic, and therapeutic plans. Emerging data point that microRNAs are essential for immunological control in the female reproductive tract. MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to mRNA and preventing translation into protein. miRNAs play a role in many biological processes, including the development and differentiation of trophoblasts, the activation and implantation of embryos, immune tolerance, and the receptivity of the endometrium during implantation. Given their capacity to regulate up to 30 % of the human genome, miRNAs offer a promising avenue for understanding the immunopathogenesis of pregnancy complications. Recent research has detected differential expression of specific miRNAs in reproductive system pathologies. This review focuses on microRNAs and their association with idiopathic recurrent miscarriage, a condition characterized by considerable heterogeneity. Future studies identifying the precise mechanisms linking miRNA-mediated immune dysregulation in RPL immunopathogenesis could open the way for novel personalized therapeutic and diagnostic strategies.

Female

In silico prediction method for plant Nucleotide-binding leucine-rich repeat- and pathogen effector interactions.

Plant Nucleotide-binding leucine-rich repeat (NLR) proteins play a crucial role in effector recognition and activation of Effector triggered immunity following pathogen infection. Genome sequencing advancements have led to the identification of a myriad of NLRs in numerous agriculturally important plant species. However, deciphering which NLRs recognize specific pathogen effectors remains challenging. Predicting NLR-effector interactions in silico will provide a more targeted approach for experimental validation, critical for elucidating function, and advancing our understanding of NLR-triggered immunity. In this study, NLR-effector protein complex structures were predicted using AlphaFold2-Multimer for all experimentally validated NLR-effector interactions reported in literature. Binding affinities- and energies were predicted using 97 machine learning models from Area-Affinity. We show that AlphaFold2-Multimer predicted structures have acceptable accuracy and can be used to investigate NLR-effector interactions in silico. Binding affinities for 58 NLR-effector complexes ranged between -8.5 and -10.6 log(K), and binding energies between -11.8 and -14.4 kcal/mol-1, depending on the Area-Affinity model used. For 2427 "forced" NLR-effector complexes, these estimates showed larger variability, enabling identification of novel NLR-effector interactions with 99% accuracy using an Ensemble machine learning model. The narrow range of binding energies- and affinities for "true" interactions suggest a specific change in Gibbs free energy, and thus conformational change, is required for NLR activation. This is the first study to provide a method for predicting NLR-effector interactions, applicable to all pathosystems. Finally, the NLR-Effector Interaction Classification (NEIC) resource can streamline research efforts by identifying NLRs important for plant-pathogen resistance, advancing our understanding of plant immunity.

Plant Proteins

Comparison of the predictive performance of systemic immune-inflammation index and neutrophil-to-lymphocyte ratio for three-month poor functional outcome in ischemic stroke: a systematic review and meta-analysis.

INTRODUCTION: Ischemic stroke (IS) is a leading cause of global mortality and disability. Early and accurate prognosis is crucial for patient management. The neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) are emerging inflammatory biomarkers; however, their relative predictive value for three-month poor functional outcome (modified Rankin Scale [mRS]&#x2009;>&#x2009;2) remains uncertain. METHODS: We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library up to 20 July 2025, adhering to PRISMA guidelines. Observational studies reporting the association of SII or NLR with three-month poor outcome were included. Study quality was evaluated using the Newcastle-Ottawa Scale. Area under the curve (AUC), odds ratios (OR), and standardized mean differences (SMD) were pooled using random-effects models in Stata 16.0. RESULTS: Twenty-one studies involving 7520 IS patients were analysed. NLR demonstrated marginally superior discriminative ability compared to SII (AUC 0.71, 95% CI: 0.67-0.76 vs. 0.68, 95% CI: 0.64-0.71), though this difference was not statistically significant. Elevated NLR was significantly associated with poor outcome (OR = 1.26, 95% CI: 1.17-1.37, p&#x2009;<&#x2009;.001), whereas SII was not (OR = 1.00, 95% CI: 1.00-1.00, p&#x2009;=&#x2009;.384). Both markers showed moderate effect sizes (SMD: NLR = 0.69, SII = 0.72; p&#x2009;<&#x2009;.001). NLR performed better in non-intervention and Chinese subgroups, while SII exhibited consistent AUC values across treatment and ethnic subgroups. CONCLUSION: NLR and SII are accessible prognostic markers in IS. NLR demonstrates superior accuracy and a significant association with poor outcome, while SII shows greater stability across patient subgroups. Both may assist in risk stratification, in resource-limited settings.

Humans

Diverse haplotypes at a complex Solanum americanum locus confer resistance to Phytophthora infestans and P. capsici.

Plants encounter diverse pathogens and have evolved a two-layered innate immune system to detect pathogen molecules and activate defense mechanisms that restrict infection. Most cloned plant Resistance (R) genes encode NLR immune receptors. NLR genes are often found in clusters of paralogs with sequence and copy number variation; whether these NLR clusters evolve in response to single or multiple pathogens has been unclear. We report here the isolation of a Phytophthora capsici resistance gene, Rpc2, along with a novel P. infestans resistance gene, Rpi-amr5, from two Solanum americanum accessions. These orthologous genes reside in the Rpi-amr1 cluster, which has previously been associated with resistance to P. infestans. By screening RXLR effector libraries of P. infestans and P. capsici, we identified multiple effectors recognised by both NLRs. Our findings highlight the complexity of NLR clusters and evolution driven by interactions with multiple pathogens. This work will underpin efforts to elevate resistance against Phytophthora pathogens and enhances our understanding of NLR evolution.

Journal Article

Association of time-averaged systemic immune-inflammation indices with in-hospital mortality after intracerebral hemorrhage: a retrospective study.

BACKGROUND: Systemic inflammation plays a central role in secondary brain injury following intracerebral hemorrhage (ICH). Although inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) are linked to poor outcomes, their associations with mortality are commonly assumed to be linear, potentially overlooking nonlinear patterns where mortality risk rises steeply at higher levels. METHODS: We conducted a retrospective study using the MIMIC-IV database, including 440 patients with non-traumatic ICH who were alive and remained in the ICU for at least 72&#xa0;h after admission. Mean NLR, SII, and SIRI were calculated from measurements obtained during this period. Multivariable logistic regression and restricted cubic spline (RCS) analyses were applied to assess their independent and nonlinear associations with in-hospital mortality. Model discrimination and calibration were internally validated using 1,000 bootstrap resamples. RESULTS: The in-hospital mortality rate was 26.1%. After multivariable adjustment, NLR and SIRI remained independently associated with mortality. Patients in the highest SIRI quartile had the highest risk of death (aOR&#xa0;=&#xa0;5.12; 95% CI: 2.57-12.24; p&#xa0;<&#xa0;0.001). RCS analysis revealed a significant nonlinear association between SIRI and mortality (p-nonlinearity&#xa0;<&#xa0;0.05), showing a steep risk increase at higher SIRI levels. Adding SIRI to the base model provided a modest improvement in discrimination (AUC 0.762 to 0.785, p&#xa0;=&#xa0;0.045) and significantly improved risk reclassification (cNRI&#xa0;=&#xa0;0.4778, p&#xa0;<&#xa0;0.001; IDI&#xa0;=&#xa0;0.0240, p&#xa0;=&#xa0;0.0151). CONCLUSIONS: Among patients with ICH who met the 72-hour eligibility criterion, higher 72-hour average SIRI was independently associated with in-hospital mortality. As a time-averaged measure, SIRI should be interpreted as a dynamic marker integrating the initial inflammatory state and the early clinical course rather than as a purely baseline prognostic factor. Although adding SIRI to the base model modestly improved discrimination and risk reclassification, it should be considered a candidate prognostic marker requiring external validation before clinical application.

Humans

The Arabidopsis TIRome informs the design of artificial TIR (Toll/interleukin-1 receptor) domain proteins.

The TIR (Toll/interleukin-1 receptor) domain is an ancient protein module that functions in immune and cell death responses across the Tree of Life. TIR domains encoded by plants and prokaryotes function as enzymes to produce diverse small molecule immune signals. Plant genomes can encode hundreds of TIR-domain containing proteins-many of which confer important agricultural disease resistance as TIR-NLR (nucleotide-binding, leucine-rich repeat) immune receptors. Despite their importance, how natural variation influences TIR enzymatic output and immunity-associated cell death is largely unexplored. We assayed a complete collection of the TIR domains of Arabidopsis thaliana Col-0 (the "AtTIRome") to explore variation in TIR metabolite production and cell death signaling. Roughly half of the AtTIRome triggered cell death in transient assays. Artificial TIR proteins designed based on consensus sequences of the AtTIRome's cell death phenotypic classes revealed polymorphisms controlling variation in TIR cell death elicitation and metabolite production. Structure-function analyses of artificial TIRs revealed that natural variation in the "BB-loop", a flexible region overlying the catalytic pocket, determines differences in function across Arabidopsis TIR-containing proteins. We further demonstrate that artificial TIRs are functional on an NLR chassis and that BB-loop variation can tune the activity of a natural TIR-NLR protein. These findings shed light on the diversity of TIR outputs and reveal methods to design and engineer TIR-based immune receptors.

Arabidopsis

Tobamoviruses: Advances in Molecular Biology, Host Interactions and Integrated Disease Management.

Tobamoviruses (viruses in the genus Tobamovirus, family Virgaviridae) lead to major yield losses in economically important crops around the world. In this review, we go beyond the canonical gene expression framework by integrating recent discoveries of reverse open reading frames (rORFs) on the negative-strand RNA. These rORFs have only been experimentally validated in cucumber green mottle mosaic virus (CGMMV), with predicted sequence-conserved homologs across a subset of the genus, including TMV, ToBRFV, and PMMoV. However, they are not universally present in all tobamoviruses. We systematically dissect the infection cycle-from disassembly and replication to cell-to-cell and systemic movement-with an emphasis on the host factors hijacked at each stage. We synthesize current understanding of plant antiviral immunity, focusing on RNA silencing and NLR receptor-mediated resistance as two pillars of defense, along with the transcription factors and microRNAs that orchestrate these responses. We critically evaluate the experimental evidence for both plant defenses and viral counter-strategies, noting that many mechanistic models derive from limited model systems. We further characterize host genetic resistance and susceptibility factors applicable to crop breeding. These resources include dominant NLR and non-NLR resistance, as well as recessive resistance derived from modified host susceptibility genes. We address how viral mutations, recombination and fitness trade-offs undermine resistance durability. We then evaluate their practical deployment through conventional breeding, the exploitation of quantitative resistance, and genome editing, and outline associated agronomic drawbacks and regulatory constraints. Using ToBRFV as a case study, we analyze its epidemiological traits and assess the current arsenal of surveillance tools, from field diagnostics to remote sensing. Finally, we survey management strategies across a spectrum of maturity. Some approaches, including sanitation protocols and conventionally bred resistant cultivars, have proven effective under field conditions. The first dsRNA-based biopesticide has recently been registered in China, while other biological control agents and low-risk chemical approaches remain largely at the experimental stage. We also discuss the bottlenecks that impede lab-to-field transition and highlight promising solutions such as precision breeding and evolution-oriented cultivar deployment. By bridging molecular virology, epidemiology, and integrated disease management, this review provides a critical, bench-to-field framework for the sustainable control of tobamoviruses.

TMV

Pan-analysis of intra- and inter-species diversity reveals a group of highly variable immune receptor genes in rice.

Plant immune receptors and their natural variations play a central role in combating disease-causing pathogens. These immune receptors include intracellular nucleotide-binding leucine-rich repeat (LRR) receptors (NLRs) and cell-surface pattern recognition receptors (PRRs) that can be further classified as receptor-like proteins (RLPs) and receptor-like kinases (RLKs). Although the NLRome has been characterized, the repertoire and extent of diversity of PRRome remain undetermined in rice. In this study, we examined the diversity of immune receptor genes using high-quality genomes of 309 rice accessions from 8 species within the genus Oryza. A total of 376&#x2009;310 immune receptor genes were identified, including 149&#x2009;592 NLR-coding genes and 226&#x2009;718 PRR coding genes. Shannon entropy analysis revealed a set of immune receptors that display significant intra-species and inter-species diversity in rice. In general, RLPs are more variable than RLKs, while NLRs and LRR-RLPs are more variable than LRR-RLKs. Additionally, NLR and PRR genes exhibit contrasting shoot/root expression patterns, with NLRs generally skewed towards root expression. Furthermore, we found that the size of the LRR-RLK gene families correlates with local annual precipitation, suggesting a stronger selection pressure on LRR-RLK genes in rice accessions grown under wet conditions than dry conditions. In sum, this pan-genomic analysis not only reveals the extensive diversity of the immune receptor repertoires in rice but also provides potential target genes for improving disease resistance in rice.

Oryza

The Annotated Blueprint: Integrated Functional Genomic Resources for a model Tetraploid Wheat Triticum turgidum cv. Kronos.

Triticum turgidum cv. Kronos is a tetraploid wheat cultivar that underpins one of the richest community platforms for functional genomics. Over the past decade, about 3,000 exome- and promoter-capture datasets, linked to mutagenized seed stocks, and transcriptomic and phenotypic resources have accumulated, yet the absence of a reference genome has constrained their impact. Here, we present a chromosome-scale reference genome of Kronos with high-confidence annotations, including manual curation of over 1,000 disease resistance (NLR) genes. This reference revealed previously hidden NLR diversity and clarified their genomic organization at chromosomal ends. Re-analysis of exome- and promoter-capture datasets enabled high-resolution mutation discovery in genes and regulatory regions that were previously inaccessible, uncovering the full standing variation present in Kronos mutant lines. We further re-curated transcriptomic and small RNA datasets, generating improved, genome-wide maps of microRNAs and phasiRNAs important for wheat development. Collectively, these resources elevate Kronos to reference quality and establish it as a versatile platform for functional and translational wheat research.

Journal Article

Blood-based proteomic profiling reveals context-dependent changes in BCL2-associated signaling during taxane therapy in breast cancer patients.

The quality of life for many cancer survivors is compromised due to severe, long-lasting side effects of chemotherapy. As part of a pilot, prospective, non-interventional study to examine the side effects of chemotherapy in breast cancer patients, we examined the change in protein expression in blood collected from patients before and after treatment with taxanes for 12&#x2009;weeks. Protein expression was measured with reverse phase proteomic arrays (RPPA), which revealed divergent changes in apoptosis, senescence, and calcium signaling-related proteins depending on treatment setting (neoadjuvant vs. adjuvant). The largest change identified was BCL2 (B-cell lymphoma 2), a founding member of the BCL2 family of proteins that regulate apoptosis. Other proteins regulated by BCL2, including RB1 (retinoblastoma protein 1) and NLRP3 (NLR family pyrin domain containing 3) changed significantly over the course of treatment. These differences are consistent with intracellular calcium signaling dysregulation and activation of stress-response pathways that overlap with senescent-associated secretory phenotype (SASP)-like signaling, which has been implicated in cancer recurrence. To contextualize these observations, we generated Kaplan-Meier survival curves using publicly available proteomics data from The Cancer Proteome Atlas (TCPA). This work aims to demonstrate how blood-based proteomics can serve as a non-invasive method to monitor systemic physiological shifts during cancer therapy, offering a framework for generating hypotheses about chemotherapy timing and long-term outcomes.

Humans

Brain stem afferents to visual cortical areas 17, 18 and 19 in the cat, demonstrated by horseradish peroxidase.

The origins of brain stem projections to the cytoarchitectonically different areas 17, 18 and 19 of the cat's visual cortex were studied following small horseradish peroxidase (HRP) injections. Labelled cells were counted in a dopaminergic nucleus (nucleus linearis rostralis (NLR)), other catecholaminergic nuclei (locus coeruleus, parabrachialis nuclei and nucleus subcoeruleus) and serotonergic nuclei (nucleus raphe dorsalis (NRD) and nucleus centralis superior (NCS)). Area 18 receives afferents from more locus coeruleus cells than either of areas 17 or 19. The number of labelled cells in the catecholaminergic nuclei far exceeds that in the serotonergic nuclei.

Afferent Pathways

Association of Lung Quantitative CT Scan Textures With Systemic Inflammation and Mortality in COPD.

BACKGROUND: COPD is characterized by persistent inflammation that is responsible for remodeling the bronchovascular bundles (BVBs), which may lead to poor quality of life. Quantitative CT (QCT) scan textures of the lung can capture local disease patterns of inflammation and related respiratory morbidity. RESEARCH QUESTION: Are BVB textures, obtained from the adaptive multiple feature method, associated with systemic inflammation, morbidity, and mortality in COPD? STUDY DESIGN AND METHODS: We analyzed data from the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS; n = 2,981) and the Genetic Epidemiology of COPD (COPDGene) study (n = 10,305). The predictors included 2 QCT scan biomarkers, the BVB and CT density gradient (CTDG) textures, age, sex, BMI, race, smoking status, pack-years of smoking, CT scan-detected emphysema, and square root of the wall area of a hypothetical airway with a 10-mm lumen perimeter (Pi10). Outcomes included plasma biomarker concentrations from Meso Scale Discovery proteomics assays and CBC counts, both as markers of inflammation, along with FEV1, FEV1 to FVC ratio, St. George's Respiratory Questionnaire score, 6-minute walk distance, and modified Medical Research Council dyspnea scale score. Associations of these QCT scan textures with FEV1 decline and all-cause mortality also were investigated. RESULTS: Increased BVB texture was associated significantly with elevated neutrophil and monocyte counts and the neutrophil to lymphocyte ratio, independent of clinical covariates, CT scan-detected emphysema, and Pi10. Elevated CTDG was associated with increased neutrophil count, NLR, and tumor necrosis factor &#x3b1;. Increased CTDG and BVB textures also were associated with a lower FEV1 and 6-minute walk distance. CTDG at baseline was also associated with decline in FEV1 at the 5-year follow-up in the COPDGene study. We observed a significant association of both BVB texture (SPIROMICS: hazard ratio [HR], 1.084 [95% CI, 1.035-1.135; P < .001]; COPDGene: HR, 1.106 [95% CI, 1.080-1.131; P < .001]) and CTDG texture (SPIROMICS: HR, 1.033 [95% CI, 1.003-1.064; P = .03]; COPDGene: HR, 1.079 [95% CI, 1.061-1.096; P < .001]) with all-cause mortality independent of CT scan-detected emphysema and Pi10. INTERPRETATION: QCT scan textures may provide imaging evidence of the spatial heterogeneity of lung inflammation and overall disease burden in COPD. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; Nos.: NCT01969344 (SPIROMICS) and NCT00608764 (COPDGene); URL: www. CLINICALTRIALS: gov.

Humans

Diagnostic accuracy of bronchoalveolar lavage fluid-based testing for pulmonary cryptococcosis: A systematic review and meta-analysis.

BACKGROUND: Pulmonary cryptococcosis(PC) presents diagnostic challenges because of its non-specific clinical and radiological manifestations. Bronchoalveolar lavage fluid (BALF)-based testing, which includes latex agglutination (LA) and lateral flow assay (LFA), offers a minimally invasive diagnostic method, yet its pooled diagnostic accuracy remains unclear. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Scopus from inception to May 2026. Studies evaluating BALF-based testing for PC with extractable 2 &#xd7; 2 data were included. The methodological quality of relevant studies was assessed by the QUADAS-2 tool. Pooled sensitivity, specificity, likelihood ratios, and diagnostic odds ratio (DOR) were estimated using a bivariate random-effects model. Subgroup analyses were performed by testing method and reference standard type. Heterogeneity was evaluated through paired forest plots, HSROC visualization, and exploratory bivariate meta-regression. RESULTS: The pooled sensitivity was 0.87 (95% CI: 0.81-0.91), and the specificity was 0.99 (95% CI: 0.982 - 0.995). The pooled positive likelihood ratio (PLR) was 88.00 (95% CI: 47.39 - 163.42), the negative likelihood ratio (NLR) was 0.13 (95% CI: 0.09 -0.20), and the DOR was 658.50 (95% CI: 285.36-1519.55). No significant threshold effect or publication bias was detected. Exploratory meta-regression suggested a possible assay-method effect in the joint model (P = 0.03), mainly driven by specificity (P = 0.01). CONCLUSIONS: The study demonstrates the high accuracy of CrAg in BALF for the diagnosis of pulmonary cryptococcosis, supporting its role as an important adjunctive diagnostic tool, particularly when tissue biopsy is not feasible or rapid results are needed. Larger prospective studies with standardized protocols are needed to validate these estimates.

Humans

Recent gene duplication and structural remodeling drive rapid lineage-specific gene family evolution in plants.

Gene duplication promotes the generation of novel gene functions and trait diversity across species. Here, we present DupHIST, a computational pipeline that reconstructs the hierarchical timing of gene duplications by integrating maximum likelihood (ML)-based phylogeny with substitution-derived timing via statistical smoothing. Applied to over 4.5 million genes from 114 plant genomes, we successfully inferred duplication histories across nearly 130,000 orthogroups. This large-scale analysis showed that 53.0% of genes arose from recent, lineage-specific duplications, with high concentrations in particular multi-copy families. Among these, NLR, C48, and P450 families exemplified how recently duplicated genes undergo rapid stepwise structural remodeling. This process was primarily driven by small-scale mutations, including insertions, deletions, and frameshifts, that rapidly accumulated shortly after duplication. By resolving the precise duplication order, we reconstructed these architectural changes, thereby enabling both the inference of putative ancestral structures and the exploration of functional diversification arising from structural remodeling. Structure-based clustering further uncovered that recently duplicated, uncharacterized genes retain core domain structures resembling known functional proteins even across phylogenetically distant species lacking sequence homology. Our findings reveal that recent gene duplications and subsequent structural remodeling represent a widespread and lineage-specific force driving rapid diversification of gene families in plants.

Gene duplication history

Diagnostic and prognostic value of fibroblast growth factor 23 in acute kidney injury: systematic review and meta-analysis.

Background: Acute kidney injury (AKI) is associated with high mortality and adverse outcomes. Fibroblast growth factor 23 (FGF23) has emerged as a potential biomarker for AKI; however, its diagnostic and prognostic utility remains inconsistent.Methods: We conducted a systematic review and meta-analysis of studies evaluating circulating intact FGF23 (iFGF23) or C-terminal FGF23 (cFGF23) (PROSPERO: CRD42022302659). PubMed, EMBASE, CNKI, and Wanfang databases were searched through June 9, 2026. QUADAS-2 was used for quality assessment. A random-effects bivariate model pooled sensitivity, specificity, positive/negative likelihood ratio (PLR/NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (SROC AUC).Results: Twenty-three studies were included: 17 diagnostic, 6 prognostic (one addressing both). For AKI diagnosis, the pooled sensitivity was 0.79 (95% CI 0.73-0.86), specificity 0.82 (95% CI 0.75-0.89), PLR 4.40 (95% CI 2.59-6.21), NLR 0.25 (95% CI 0.16-0.34), DOR 17.49 (95% CI 8.67-35.16), and SROC AUC 0.87 (95% CI 0.81-0.92). Substantial heterogeneity was observed (I2 = 67%), with iFGF23 demonstrating higher accuracy than cFGF23 (AUC 0.91 vs 0.81). For AKI mortality, pooled sensitivity was 0.77 (95% CI 0.69-0.84), specificity 0.76 (95% CI 0.70-0.82), DOR 10.89 (95% CI 6.86-17.30), and SROC AUC 0.77 (95% CI 0.70-0.83). Significant heterogeneity was noted (I2 = 86.2% for sensitivity, 80.4% for specificity). No significant publication bias was detected.Conclusions: Circulating FGF23 exhibits moderate-to-high diagnostic and moderate prognostic performance in AKI, though interpretation is limited by substantial heterogeneity. It may serve as a complementary biomarker for risk stratification, pending further validation with standardized protocols.

Humans

Graph-based pan-genome reveals structural and functional diversity across oil palm domestication gradients.

BACKGROUND: Oil palm (Elaeis guineensis Jacq.), the world's most land-efficient oil crop, underpins global vegetable oil supply yet faces mounting constraints from limited expansion, climate stress, and disease pressure. These challenges highlight the urgent need for genomic resources that capture species-wide diversity to support sustainable improvement. While recent reference assemblies have advanced trait discovery, single linear genomes fail to represent the full spectrum of structural and gene-content variation, limiting resolution of agronomic alleles. RESULTS: Here, we constructed a graph-based pan-genome from 30 diverse oil palm assemblies representing wild, semi-domesticated, and commercial accessions. We characterized structural variants, gene presence-absence variation, and copy-number gains, with focusing on functional stratification and resistance gene dynamics. The graph-based pan-genome revealed extensive structural and gene-content variation, including a large conserved core, complemented by shell and unique fractions enriched or biased toward regulatory, stress-responsive, and defense-related functions. Structural variation and duplication-derived copy-number gains contributed substantially to gene-content diversity, with semi-domesticated accessions exhibiting the greatest variability. Resistance gene repertoires showed contrasting patterns: receptor-like kinases remained comparatively stable, whereas the CNL subclass of NLR genes contributed disproportionately to shell-genome variation and duplication-associated turnover. CONCLUSIONS: This graph-based pan-genome provides a curated multi-assembly reference and comparative framework for oil palm genomics. By capturing structural variants, gene-content variations, copy-number gains, and resistance gene dynamics across domestication gradients, it establishes a foundation for future pan-GWAS analysis, functional genomics, and molecular breeding strategies aimed at improving resilience and productivity in this globally important crop.

Arecaceae

Reduced mean platelet volume (MPV) as an inflammatory marker in Chinese women with polycystic ovary syndrome: a case-control study.

BACKGROUND: Low-grade chronic inflammation is observed in women with polycystic ovary syndrome (PCOS). A recent genome-wide association study (GWAS) suggested that several inflammation marker levels were altered in the blood routine tests in PCOS patients and such changes were associated with variant gene clusters. Therefore, inflammatory marker alterations in the blood routine tests are significant and might be involved in the onset as well as progression of PCOS. Compared with other markers, these inflammatory markers in the blood routine tests are less expensive and easier to detect. Very few studies have evaluated the changes in platelet indicators like platelet count and mean platelet volume (MPV) in Chinese women with PCOS. The aim of the study was to investigate the changes in platelet-related inflammatory indices in Chinese women with PCOS. METHODS: The study included 299 women aged 18&#x2013;47 with PCOS and 481 healthy women as the control group. We conducted propensity score matching to refine our dataset, utilizing the &#x2018;Matching&#x2019; package in R to match cases with the disease to controls. Correlation analyses were performed using Pearson correlation analysis. Partial correlation analysis was used to analyse the correlation between MPV and the indicators after adjusting for age, body mass index (BMI) and waist circumference (WC). Binary logistic regression (forward-wald) was used to evaluate if the relationship between MPV and PCOS was independent of obesity, insulin resistance (IR), and hyperandrogenism. RESULTS: After matching the age, BMI, and WC of the two groups, high-sensitivity CRP (hs-CRP), white blood cell counts (WBCs), lymphocytes, platelets and great platelet count (GPC) were significantly higher (P&#x2009;=&#x2009;0.007, 0.022, 0.011, 0.014, and 0.000, respectively), and mean platelet volume (MPV) and platelet distribution width (PDW) were significantly lower in PCOS patients compared with the control group (P&#x2009;=&#x2009;0.000, 0.016, respectively). Neutrophils, neutrophil-to-lymphocyte ratio (NLR), and platelet hematocrit (PCT) did not show statistically significant differences between the two groups (P&#x2009;=&#x2009;0.196, 0.480, 0.646, respectively). Decreased MPV was independently associated with the occurrence of PCOS (P&#x2009;=&#x2009;0.005, OR&#x2009;=&#x2009;0.770, 95% CI, 0.641&#x2013;0.925). MPV was negatively correlated with total testosterone (TT), free testosterone (FT) and total cholesterol (CHOL) levels after correcting for age and obesity (r = -0.149, P&#x2009;=&#x2009;0.000; r = -0.093, P&#x2009;=&#x2009;0.010; r = -0.081, P&#x2009;=&#x2009;0.025; respectively). CONCLUSIONS: Chinese PCOS patients have significantly reduced MPV as an inflammatory indicator independent of obesity, IR, and dyslipidemia.

Humans