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Microbial signal profiles and organism-level concordance between plasma metagenomic sequencing and blood culture in suspected bloodstream infection.

Plasma metagenomic next-generation sequencing (mNGS) and blood culture detect different components of the microbial signal and frequently produce discordant organism reports. We characterized microbial signal class, report-derived burden, organism-level concordance, and independent clinical attribution in a retrospective, single-center, episode-level cohort. Among 329 episodes with evaluable plasma mNGS reports, 315 had blood culture performed; 232 were mNGS positive/culture negative and 53 were positive by both methods. In the 232 discordant episodes, the recorded routine-care diagnosis classified 124 as bloodstream infection (BSI) and 108 as non-BSI. Nonviral signals were present in 78.2% and 42.6%, respectively (P&#x2009;<&#x2009;0.001), and median maximum report-derived sequence counts were 98.5 and 11.5 (P&#x2009;<&#x2009;0.001). Two laboratory physicians then independently reviewed source records using structured criteria while masked to the recorded BSI label and mNGS organism and sequence-count information. Initial agreement for the five-category BSI assessment was 97.6% (Cohen's kappa, 0.960). Within the mNGS-positive/culture-negative subgroup, adjudicated BSI likelihood showed a modest ordinal association with report burden (Spearman rho&#x2009;=&#x2009;0.190; P&#x2009;=&#x2009;0.004), while mNGS organisms were considered supported in 1 episode, plausible in 158, unlikely or contaminant in 72, and unresolved in 1. Among 53 dual-positive episodes, 33 (62.3%) shared at least one species, but only 5 (9.4%) had complete species-set concordance. Plasma mNGS and blood culture therefore frequently generated non-equivalent organism sets. Signal class and report burden contributed graded contextual evidence, but organism-level attribution required clinical review and orthogonal microbiology rather than binary positivity alone.

Humans

Divergent trajectories of genome architecture and chromosome evolution in ferns and angiosperms.

Ferns and angiosperms represent the two largest vascular plant lineages but exhibit striking genomic and ecological contrasts. We investigated whether differences in genome size, chromosome architecture, GC content, and stomatal traits reveal divergent evolutionary trajectories between these lineages. We assembled the most comprehensive dataset to date, integrating genome size, chromosome number and size, GC content, and stomatal traits for over 1100 fern species and compared it with an extensive angiosperm dataset. Ferns exhibited markedly lower variability and c. 16-fold slower rates of chromosome size evolution than angiosperms. A persistent positive relationship between genome size and chromosome number in ferns suggests limited cytological post-polyploid diploidization. While ferns generally possess larger stomata, this difference disappears after accounting for genome size, indicating that nucleotypic constraints, rather than lineage-specific physiology, dictate stomatal dimensions. Both groups share a unimodal GC-genome size relationship peaking at c. 14 Gbp. Larger fern chromosomes imply lower genome-wide recombination rates, potentially limiting genetic reshuffling and adaptive potential. Our results highlight fundamentally divergent evolutionary trajectories, likely shaped by meiotic symmetry in ferns and meiotic asymmetry, possibly centromere drive, and post-polyploid diploidization in angiosperms, defining the functional and genomic landscapes of these lineages across deep evolutionary timescales.

Genome, Plant

Single-cell RNA sequencing provides further insights into the immunostimulatory action of freeze-dried Lactiplantibacillus plantarum on Penaeus vannamei shrimp.

Immunostimulation through dietary interventions opened new avenues in developing disease control and prevention tools for shrimp aquaculture. We have previously shown that feeding with freeze-dried Lactiplantibacillus plantarum (LAB) increased disease resistance of Penaeus vannamei against both Vibrio parahaemolyticus and white spot syndrome virus (WSSV) based on bulk RNA sequencing of shrimp gills. This tissue participates in ion transport and serves as a first line of defense against environmental stressors and pathogenic infections. However, characterization of their cell composition and functions remains limited. Here, we implemented a single-cell RNA sequencing approach to further gather insights into how feeding with freeze-dried LAB modulates host immunity which may not be evident with bulk RNA sequencing approach. A total of five clusters with unique transcriptional signatures were identified, corresponding to pillar cells, septal cells, and sessile hemocytes. Pseudo-bulk analyses at global- and cluster-levels showed differential expression of genes related to host immunity and metabolism. We further revealed how overall transcriptomic changes are not exclusively caused by gene expression changes but may also be driven by cell population dynamics. This study highlighted how single-cell RNA sequencing approach may shed light on the mechanisms of action of immunostimulants which may be masked in bulk transcriptome analyses.

Animals

Integrated exome and mitochondrial genome sequencing reveals the genetic landscape of primary mitochondrial diseases: findings from a large Tunisian cohort.

Primary mitochondrial diseases are a heterogeneous group of neurometabolic disorders recognized as the most common metabolic genetic diseases. They manifest at any age, affecting any tissue or organ, especially those with high energy demands, and are caused by pathogenic variants in both mitochondrial and nuclear genomes. Here, we aimed to describe the genetic spectrum of a Tunisian pediatric cohort with suspected mitochondrial diseases. We recruited 47 unrelated families who underwent exome sequencing as a first-tier test followed by whole mitochondrial genome sequencing for unsolved cases. Dedicated bioinformatic pipelines and prediction tools were used to determine the potential disease-causing variants. Sanger sequencing confirmed the presence and segregation within parents. For the newly identified variants, structural modeling was conducted to study the impact of these variants on protein structure and motions. Dual genome sequencing yielded a molecular diagnosis in 33/47 families (70%) and 18/47 (38%) showed disease-causing variants in genes encoding mitochondrial proteins. Among them, four families disclosed novel variants in FASTKD2, SERAC1 and GATB, which were supported by in-depth in silico and structural analyses demonstrating their deleterious effect. The remaining families (32%, 15/47) disclosed other metabolic and neurological disorders. An exome-first strategy delivers a high diagnostic yield in Tunisia, where consanguinity remains high and simultaneously captures mitochondrial and non-mitochondrial etiologies. Mitochondrial sequencing remains indispensable in the case of an inconclusive exome. Thus, our data expand the clinical and genetic spectrum of primary mitochondrial diseases in Tunisia, an underrepresented and admixed population.

Humans

Protein isolation markedly enhances in vitro digestibility, nutritional quality, and bioactivity of fungal mycelial proteins.

Fungal mycelial proteins are promising sustainable protein sources, yet their nutritional utilization is often limited by structural constraints. This study systematically evaluated the effects of protein isolation on the proteomic composition, gastrointestinal digestion behavior, amino acid utilization, and bioactivity of Pleurotus citrinopileatus mycelial proteins. Quantitative proteomics identified 3591 proteins, of which 3374 were shared between mycelial flour (PCMF) and protein isolate (PCMPI), indicating that PCMPI primarily represents the soluble proteome fraction. In vitro digestion revealed that PCMPI exhibited significantly higher digestibility (93.98%) than PCMF (42.98%) (p&#xa0;<&#xa0;0.05), reaching levels comparable to whey protein isolate. Enhanced enzymatic accessibility in PCMPI promoted rapid peptide generation during the gastric phase and efficient amino acid release during the intestinal phase, resulting in higher peptide (634.76&#xa0;mg/g) and free amino acid levels (341.69&#xa0;mg/g) at the digestion endpoint. Consequently, PCMPI achieved a balanced amino acid profile with a PDCAAS of 1.0. Moreover, its digestion products exhibited stronger antioxidant activity (IC&#x2085;&#x2080;&#xa0;=&#xa0;8.36&#xa0;mg/mL) and ACE inhibitory activity (IC&#x2085;&#x2080;&#xa0;=&#xa0;15.65&#xa0;mg/mL) compared with PCMF. Mechanistically, protein isolation disrupted the cell wall matrix, shifting digestion from a structure-limited to an accessibility-driven regime. Collectively, these findings demonstrate that protein isolation markedly enhances the digestibility, nutritional quality, and functional potential of mycelial proteins, supporting their application as high-value sustainable protein ingredients.

Digestion

Diagnostic value of plasma cell-free DNA metagenomic next-generation sequencing in patients with suspected infections and exploration of clinical scenarios-a retrospective study from a single center.

BACKGROUND: Plasma cell-free DNA metagenomic next-generation sequencing (mNGS) is a non-invasive comprehensive method for the etiological diagnosis of various infectious diseases. However, research on the early diagnosis and real-world clinical impact of plasma mNGS in patients with suspected infection are still limited. MATERIALS AND METHODS: This study retrospectively included 140 patients with suspected infections who underwent early plasma mNGS and conventional culture testing. Referring to the clinical diagnosis of infectious diseases, the diagnostic performance of plasma mNGS and culture tests was compared, and the application scenarios and clinical effects of plasma mNGS were evaluated. RESULTS: The positive rate of plasma mNGS was significantly higher than that of culture methods (55.71% vs 25.10%, p&#x2009;<&#x2009;0.001) and blood cultures (55.71% vs 12.86%, p&#x2009;<&#x2009;0.001). Regarding clinical diagnosis, the sensitivity of plasma mNGS was significantly higher than that of culture (58.27% vs 37.80%, p&#x2009;=&#x2009;0.002). The combination of mNGS and culture achieved a higher detection sensitivity (69.29%), especially in patients with multi-site co-infections (73.68%) and blood infections (73.17%). Plasma mNGS demonstrated higher sensitivity in patients with procalcitonin (PCT) index > 5&#x2009;ng/ml or human neutrophil lipocalin (HNL) index > 200&#x2009;ng/ml. In terms of treatment, a total of 69 patients (54.33%) benefited from plasma mNGS. CONCLUSION: This study highlights the significant improvement in pathogen detection performance by combining conventional culture with plasma mNGS detection, especially in patients with multi-site co-infections and blood infections. Early use of plasma mNGS as an adjunct to culture can better guide clinicians to initiate appropriate anti-infective therapy.

Humans

Mapping antibody sequences and effector functions across spatial niches.

Antibodies are fundamental to human health but can also drive pathology. Each antibody has a molecular specificity, encoded by their clonally heritable B cell receptor (BCR). Recent advances in spatial transcriptomics coupled with repertoire sequencing have enabled capturing antibody-secreting cells (ASCs) and their clonal BCR within their tissue microenvironment. However, our understanding of antibody production niches remains limited. Furthermore, where antibodies are produced can be distinct from where antibodies exert their effector function. Here, we propose a conceptual spatial framework to distinguish between 'antibody production niches', defined by the ASC, BCR, and niche composition, versus 'antibody functional niches', composed of the antibody, antigen, and effector landscape. We then examine the possibilities and challenges to map and link antibody-encoding sequences and antibody effector functions using current and emerging technologies. Combined, we argue that integrating spatial sequence data with the antibody functional context is essential to decode the architecture of antibody-mediated immunity.

Humans

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans

LitCTL1: A novel C-type lectin involved in the mucosal and cellular immunity of the common periwinkle Littorinalittorea.

C-type lectins (CTLs) are vital pattern-recognition receptors (PRRs) that mediate innate immune responses in mollusks, yet their characterization in Caenogastropoda, the largest gastropod group, remains limited. This study characterizes LitCTL1, a novel secreted single-domain C-type lectin from the common periwinkle, Littorina littorea. The 199-amino acid polypeptide contains a conserved carbohydrate recognition domain with canonical QPD and WND motifs and is predicted to form a homodimer. Uniquely, LitCTL1 was localized in both circulating hemocytes and mucus-secreting epithelial cells of the foot, mantle, and hypobranchial gland - the first report of such dual localization for a molluscan lectin, linking systemic and mucosal defense. Expression analysis revealed that LitCTL1 is constitutively expressed in hemocytes. Functional assays with recombinant LitCTL1 demonstrated its role as a potent opsonin with hemagglutinating activity, significantly enhancing hemocyte spreading and the phagocytosis of zymosan. Genomic analysis reveals that LitCTL1 belongs to a rapidly diversifying, genus-specific expansion distinct from conserved perlucin-like lineages. These results identify LitCTL1 as a key effector molecule in both systemic and mucosal innate immunity, likely reflecting an evolutionary adaptation to the microbial challenges of the intertidal environment.

Animals

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti

Diving Deeper Into Mechanisms of Acrylamide-Induced Toxicity: RNA Sequencing Reveals Transcriptomic Alteration and Retrotransposon Expression in Drosophila melanogaster.

Given the inevitability of human and animal exposure to acrylamide, there is increasing concern regarding its potential health risks. While a number of molecular mechanisms have been proposed, the complexity of acrylamide toxicological pathways and interactions remains incompletely characterized. In this study, we employed a transcriptomic approach to investigate the transcriptional responses of Drosophila melanogaster following exposure to acrylamide (100&#x2009;mg/kg). Our analysis identified 634 differentially expressed genes (DEGs), with 362 upregulated and 272 downregulated. Functional analysis revealed these DEGs are enriched in pathways related to reproduction, detoxification, cellular and metabolic processes, signaling, synaptic formation and organization. Notably, acrylamide exposure upregulated the expression of tau and beta-amyloid protein precursor-like genes, both implicated in Alzheimer's disease pathology. An aversive memory test further demonstrated that acrylamide impaired the short-term memory of treated flies. Additionally, acrylamide-induced toxicity altered the expression of nine long terminal repeat retrotransposons, belonging to the gypsy and pao superfamilies. By exploring the potential role of transposable element activity in acrylamide-mediated toxicity, this study provides novel insights into the molecular mechanisms underlying its effects. Collectively, these findings offer a more comprehensive understanding of the mechanisms and pathways associated with the toxic action and detoxification of acrylamide in D. melanogaster.

Animals

Cost-Effectiveness and the Economics of Genomic Testing and Molecularly Matched Therapies.

Cost-effectiveness analysis of precision oncology can help guide value-driven care. Next-generation sequencing is increasingly cost-efficient over single gene testing because diagnostic algorithms require multiple individual gene tests to determine biomarker status. Matched targeted therapy is often not cost-effective due to the high cost associated with drug treatment. However, genomic profiling can promote cost-effective care by identifying patients who are unlikely to benefit from therapy. Additional applications of genomic profiling such as universal testing for hereditary cancer syndromes and germline testing in patients with cancer may represent cost-effective approaches compared with traditional history-based diagnostic methods.

Humans

An allograft inflammatory factor enhances sperm viability by modulating intracellular calcium in oyster Crassostrea gigas.

As an important aquaculture bivalve, the Pacific oyster Crassostrea gigas faces severe constraints in artificial reproduction, where low sperm motility often leads to fertilization failure and limits the sustainable development of the oyster aquaculture industry. In the present study, the variation of sperm from different oyster individuals was observed, and high-quality sperm possessed intact, elongated flagella with no structural abnormalities, while low-quality sperm showed shortened flagella with frequent tangling or coiling defects. Transcriptomic analysis comparing high- and low-quality sperm revealed significantly reduced expression of genes associated with sperm motility and release (CgAIF1, CgAchR, CgSEX), sperm quality and development (CgEP4, CgIFi2b), and cryoprotection (CgISPs) in low-quality sperm. Notably, an allograft inflammatory factor (designed as CgAIF1) encoding EF-hand domain, known as Ca2+ binding activity, was among the most significantly downregulated in low-motility sperm. CgAIF1 is highly expressed in haemocytes, ganglia, and gonads of oysters. Incubation with the recombinant AIF1 protein (rCgAIF1) significantly improved sperm curvilinear velocity, thereby enhancing the overall motility of C. gigas sperm. Furthermore, rCgAIF1 incubation increased intracellular Ca2+ levels (2.13-fold at 30&#xa0;min, 2.71-fold at 60&#xa0;min) and superoxide dismutase (SOD) activity (1.44-fold at 30&#xa0;min, 1.24-fold at 60&#xa0;min) in sperm, suggesting potential roles in calcium homeostasis regulation and antioxidant defense. In conclusion, this study demonstrates that CgAIF1 significantly enhances motility of oyster sperm, providing a scientific basis for artificial breeding and seed production in oyster aquaculture.

Animals

Whole-transcriptome RNA sequencing and ceRNA network analyses provide novel insights into the antibacterial immune response of Hippocampus abdominalis against Vibrio harveyi.

Long non-coding RNAs (lncRNAs) stand as newly-arisen molecular types that exert regulatory effects, able to operate as competitive endogenous RNAs (ceRNAs) to engage microRNAs (miRNAs) in interaction, resulting in the recovery of target mRNA expression and activity. Increasing evidences indicate that the ceRNA network affects various biological processes in mammals, including development, cellular differentiation, metabolism, immune response, and disease pathogenesis. In teleost fish, the lncRNA-miRNA-mRNA regulatory networks have been reported occasionally. However, up to now, the roles of lncRNAs in the big-belly seahorse (Hippocampus abdominalis) remains unclear. In this study, we reported for the first time, via whole-transcriptome RNA sequencing, the lncRNA mediated ceRNA regulatory network in Vibrio harveyi-infected H. abdominalis. A total of 4197 differentially expressed mRNAs (DE-mRNAs), 1317 DE-lncRNAs, and 183 DE-miRNAs were identified. Furthermore, the crosstalk between miRNAs and lncRNAs as well as between miRNAs and mRNAs was inferred based on the negative correlations between miRNAs and their target lncRNAs/mRNAs. A core immune associated lncRNA-miRNA-mRNA putative regulatory network was thus constructed, comprising 211 lncRNA-miRNA and 224 mRNA-miRNA pairs. In conclusion, our findings provide an integrative overview of the ceRNA regulatory networks on the underlying immune responses to V. harveyi infection in the big-belly seahorse, and offer a solid theoretical foundation for the comparative immunological research of teleost fish.

Animals

Prenatal exome sequencing of fetuses with central nervous system anomalies based on prenatal ultrasound and magnetic resonance imaging diagnosis: A retrospective cohort study with a systematic review and meta-analysis.

INTRODUCTION: Fetal central nervous system (CNS) abnormalities have diverse etiologies, with genetic factors as a major contributor. Prenatal exome sequencing (ES) is a powerful tool for precise molecular diagnosis of CNS anomalies, but its diagnostic yield varies among studies. This study aimed to evaluate the additional diagnostic yield of prenatal ES compared with chromosomal microarray analysis (CMA) in fetuses with CNS anomalies detected by prenatal imaging. MATERIAL AND METHODS: We collected ES results from fetuses diagnosed with CNS anomalies by prenatal imaging (2019-2024) who had negative results. Subgroup analyses assessed phenotype-specific ES diagnostic yield for associated genes and variants. A systematic review and meta-analysis incorporating our data and published studies further explored the association between phenotype and diagnostic yield. RESULTS: In the cohort study of 219 cases, ES identified pathogenic/likely pathogenic single nucleotide variations in 36 cases (16%). The highest diagnostic yield of ES was in cases with multisystem malformations (25%, 14/55), followed by multiple CNS anomalies (15%, 2/13) and isolated CNS anomalies (13%, 20/151). The most commonly identified isolated CNS anomaly was agenesis of the corpus callosum (31%, 5/16). Neural tube defects with urogenital anomalies were associated with a positive ES finding in 57% (4/7) of cases. The meta-analysis of 989 cases from 22 studies showed a pooled diagnostic yield of ES of 27% (95% CI, 21%-34%). The highest diagnostic yield of ES was in cases of corpus callosum anomalies with facial abnormalities (75%, 8/11) and neural tube defects with urogenital malformations (80%, 12/15). The diagnostic yield of ES for three or more CNS abnormalities was 43% (95% CI, 31%-58%), significantly higher than that for only two abnormalities (10%, 95% CI, 4%-18%). No significant difference in diagnostic yield was found between cases identified by prenatal MRI combined with ultrasound (27%, 95% CI, 20%-36%) and those identified by ultrasound alone (25%, 95% CI, 17%-35%). CONCLUSIONS: ES provided a significantly higher diagnostic yield than CMA for fetal CNS abnormalities, with diagnostic yields varying by phenotype. The systematic review and meta-analysis confirmed that the complexity and combination of malformations are key factors associated with differences in ES diagnostic yield.

Humans

Low-salinity stress alters growth, histology, physiology, and transcriptomic profiles of the gills and antennal glands in Macrobrachium rosenbergii.

Salinity is a major abiotic constraint in freshwater aquaculture of the giant freshwater prawn Macrobrachium rosenbergii, yet the coordinated roles of the gills and antennal glands, the two primary osmoregulatory organs in decapod crustaceans, under low-salinity stress remain poorly characterized. Here, we integrated histological, physiological, and transcriptomic analyses to characterize the adaptive responses of M. rosenbergii to acute (96&#xa0;h) and chronic (8&#xa0;weeks) exposure to salinity 5. Chronic low-salinity stress significantly impaired growth performance and decreased the survival rate. Acute stress induced thinning of the gill filaments, partial disorganization of pillar cells, and dilation of the intermicrovillar space in the antennal glands, whereas chronic stress caused gill vacuolization, cuticle thinning, and adaptive folding of antennal gland microvilli. In parallel, acute exposure significantly decreased hemolymph sodium and potassium ion concentrations but increased magnesium ion concentration, whereas chronic exposure increased hemolymph sodium and potassium ion concentrations, upregulated gill Na+/K+-ATPase activity, and enhanced hepatopancreatic antioxidant capacity. Transcriptomic analyses revealed distinct tissue-specific responses. Under acute stress, the gills preferentially activated pathways associated with cytoskeletal remodeling, motor proteins, and tight junctions, whereas chronic acclimation shifted the transcriptional response toward the renin-angiotensin system and glutathione metabolism. In the antennal glands, acute stress rapidly activated the renin secretion pathway, whereas chronic exposure promoted membrane remodeling by enriching pathways related to lipid and glycan metabolism. These findings reveal tissue-specific functional differentiation and synergistic coordination between the gills and antennal glands that underpin M. rosenbergii's adaptive response to low-salinity stress.

Animals

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning