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PubMed2026

Multi-omics reveal microbial functional traits and antifungal metabolites associated with lower Pseudogymnoascus destructans loads in bat cave soils.

White-nose syndrome, caused by Pseudogymnoascus destructans (Pd), is a major fungal disease threatening hibernating bats. Cave soils can serve as environmental reservoirs for Pd, yet the microbial and biochemical mechanisms underlying naturally low Pd burdens in some cave environments remain poorly understood. Here, we integrated soil microbiome profiling, metagenomics, metabolomics, multi-omics network analysis, and in vitro validation to investigate the ecological and functional basis of differential Pd loads in hibernating bat caves in Northeast China. The three caves shared cold, humid, and weakly acidic microenvironments, but differed significantly in electrical conductivity, soil water content, nutrient availability, and extracellular enzyme activities. Soil microbial communities showed significant inter-cave variation in composition, diversity, and niche breadth, with stochastic processes contributing substantially to community assembly. Environmental variables, particularly pH and Pd load, were important predictors of microbial community structure. Functional analyses revealed that the low-Pd Gezi Cave was enriched in genes associated with organic carbon degradation, nitrogen input and retention, and secondary metabolism. Metabolomic profiling further identified cave-specific metabolite signatures, among which Biochanin A, 4-Hydroxybenzaldehyde, Vanillin, and Arachidonic acid were negatively correlated with Pd loads. Integrated pathway and network analyses showed that differential genes and metabolites jointly mapped to secondary metabolite biosynthesis, aminobenzoate degradation, and flavonoid degradation pathways, forming a microbe-metabolite-functional gene coupling network involving key taxa such as Rhodococcus, Pseudorhodoplanes, and Rhodoplanes. In vitro assays confirmed that 4-Hydroxybenzaldehyde, Coumarin, and Vanillin inhibited Pd growth. Structural equation modelling further indicated that environmental heterogeneity was associated with variation in Pd loads through microbial functional attributes and metabolite profiles. These findings suggest that naturally low-Pd cave soils are associated with coordinated environmental filtering, microbial functional specialization, and antifungal metabolite production, providing mechanistic insight into microbial and biochemical constraints on Pd persistence in cave reservoirs.

Animals↗

PubMed2026

Bioprospecting microbial genomes to expand the biocatalytic toolbox of rubber oxygenases.

A set of rubber oxygenases was discovered through phylogenetic analysis and AI-based structural modeling of complexes of the putative enzymes with a substrate mimicking cis-1,4-polyisoprene. Sixteen candidate proteins were selected from thermophilic microorganisms, all sequence-related to the Latex clearing protein from Streptomyces sp. K30 (LcpK30). Sequence truncation and solubility tags were then evaluated to enhance protein expression, with the SUMO tag proving to be the most effective. Including LcpK30, nine heme-containing oxygenases were successfully expressed in E. coli NEB 10-beta cells, purified (35-157 mg L-1 yield) and characterized. Steady-state kinetics revealed significant rubber latex-degrading properties for six of them, with the truncated SUMO-fused LcpK30 (SUMO-LcpK30T) showing activity in agreement with literature. Notably, the catalytic efficiencies of all the expressed homologs lay within one order of magnitude and the oxygenase from Thermomonospora echinospora was found to be particularly promising in terms of activity, especially at high latex concentrations (more than 1% w/v). The analysis of reaction mixtures by both HPLC and HPLC-MS confirmed the oxidation of cis-1,4-polyisoprene to form the expected isoprenoid oligomers (n = 2-12), whose distribution was consistent with the usual endo-type cleavage pattern in all but one case. This bioprospecting effort afforded a platform of new rubber-degrading enzymes with diverse efficiencies and product profiles, capable of adapting to targeted applications.

Oxygenases↗

PubMed2026

Meta-analysis of growth and inactivation kinetics of Legionella.

Quantitative risk assessments intended to inform evidence-based water management plans and public health targets for Legionella in engineered water systems are constrained by fragmented and heterogeneous growth and inactivation kinetics. We conducted a meta-analysis of 25 growth and 39 thermal- and chemical-inactivation studies, fitting microbial persistence models to harmonize parameters. Nonlinear models outperformed first-order formulations, indicating that lag phases and resistant or protected subpopulations are central to Legionella persistence. Random forest analysis identified environmental and methodological drivers of variability based on 226 growth rates and reduction times for thermal (209) and chemical (135) inactivation. Growth was primarily governed by temperature, nutrient availability, and compatible Legionella-host pairings; thermal inactivation by quantification method, temperature, and turbidity; and chemical inactivation by inoculum size, disinfectant type, concentration, and host-associations. Accordingly, temperature-dependent growth parameters and exposure metrics for heat, free-chlorine, and monochloramine, expressed as TT (Temperature×time) and CT (Concentration×time), were derived as condition-specific inputs for predictive models. Growth optima around 37-40 °C, together with lag-time estimates, indicate that hot-water temperature setbacks and energy-saving practices may favor Legionella proliferation under repeated or prolonged lukewarm exposure. Culture- and viability-based TT differences highlight the need to consider viable‑but-non-culturable persistence in monitoring programs. CT comparisons suggest monochloramine may be advantageous because of its lower apparent sensitivity to host-associated protection. Although limited by restricted experimental conditions, the findings show that predictive models should account for microbial ecology, water matrix effects, and quantification endpoints. Future kinetic studies should prioritize realistic multi-host systems, strain pre-adaptation, complementary viability measurements, and standardized protocols and reporting to ensure reproducibility and enable robust system-level predictive modeling.

Legionella↗

PubMed2026

Mechanisms of high-humidity hot air impingement blanching (HHAIB) on microbial counts, functional properties, phenolic profile transformation, and volatile compounds in celery stalks (Apium graveolens L.).

In this study, celery stalks were pretreated with different durations (0-150 s) of high-humidity hot air impingement blanching (HHAIB), followed by far-infrared radiation assisted pulsed vacuum freeze-drying (FIR-PVFD) at 60, 65, and 70 °C. The effects of HHAIB on the physicochemical properties, composition and transformation of phenolic compounds, volatile components, and antioxidant capacity of FIR-PVFD-dried celery stalks were systematically investigated. The results showed that HHAIB not only effectively reduced the counts of total mesophilic aerobic bacteria (TMAB) and total yeast and mold (TYM), but also decreased the relative activities of polyphenol oxidase (PPO) and lipoxygenase (LOX) by more than 91% after 90 s of treatment. HHAIB altered the cellular structure of celery stalks, shortened the drying time by 29.33-41.43%, and improved their hydration properties. HHAIB pretreatment promoted the conversion of bound phenolics to free phenolics in celery stalks, with significant increases in the contents of p-coumaric acid, apigenin, graveobioside A, and other components. The total free phenolic content increased by 56.99%, thus HHAIB enhanced the antioxidant activity. An electronic nose and sensory evaluation revealed that HHAIB-pretreated celery stalks better retained the characteristic herbal and pungent notes. GC-MS results indicated that HHAIB treatment optimized the aroma profile by regulating the contents and composition of terpenes, aldehydes, ketones, alcohols, and aromatic compounds.

Apium↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Cooperative anaerobic catabolism of chlorinated organic compounds: implications for sustainable bioremediation.

Biodegradation research historically followed a reductionist approach focused on axenic (pure) cultures capable of catabolizing the specific contaminant(s) of interest. While this approach has substantially advanced our understanding of the microbiology, physiology, biochemistry, and genetics of contaminant degradation under laboratory conditions, it does not capture the complexity of natural and engineered environments. During in situ bioremediation, microbiomes are exposed to mixtures of contaminants, and microbial interactions profoundly influence contaminant transformation and fate. In anoxic environments, degradation of chlorinated compounds is often sustained by metabolic cooperation among taxonomically and physiologically distinct microorganisms. Through the exchange of metabolites such as hydrogen, formate, acetate, and other nutrients, microbial populations establish interdependent networks that overcome thermodynamic and physiological constraints, enabling self-sustaining systems of contaminant transformations that would be inefficient or impossible with individual organisms. We highlight examples of microbial interactions that underpin anaerobic catabolism of chlorinated contaminants, including systems resulting in self-sustained anaerobic bioremediation.

Biodegradation, Environmental↗

PubMed2026

Longitudinal Prediction of Retinal Sensitivity Based on Disease Progression Quantified From Optical Coherence Tomography in Geographic Atrophy.

PURPOSE: The purpose of this study was to analyze the association between disease progression of geographic atrophy (GA) from optical coherence tomography (OCT) with retinal sensitivity (RS) in microperimetry (MP) over a 2-year follow-up period. METHODS: This is a longitudinal analysis of the OAKS Phase-III clinical trial. Both study and fellow eyes with GA that underwent imaging with the Spectralis OCT and consecutive MP examination were eligible. Pointwise quantification of ellipsoid zone (EZ) thickness, EZ and retinal pigment epithelium (RPE) loss from OCT volumes was correlated with localized RS. A longitudinal predictive model using a Markov Chain framework was implemented to predict RS change over time based on OCT biomarkers. The modeling of morphological and functional progression was based on the fellow-eye cohort. RESULTS: A total of 39,681 MP points from 406 patients were analyzed. In the fellow eye cohort, baseline (BSL) EZ thickness was positively associated with RS (0.3 decibel [dB]/µm, P < 0.001). Decrease in EZ thickness between visits during follow-up was significantly associated with decrease in RS (0.1 dB / 1 µm change). RS was significantly lower in MP points within EZ loss during follow-up compared with MP points within the retina with measurable EZ (P < 0.001). The largest functional decline was observed within RPE loss, also associated with the highest probability of absolute scotoma (P < 0.001). Morphological progression to EZ and RPE loss was influenced by EZ thickness and the morphology of adjacent MP points (P < 0.001). CONCLUSIONS: Two exploratory endpoints were developed, namely quantification of EZ thickness and loss, and localized RS within high-risk OCT areas. RS decline during follow-up is associated with automatically quantified disease progression in OCT.

Humans↗

PubMed2025

New insights into soil amendment: Impact of humic acid on typical antibiotic resistance in agricultural soil.

Humic acid (HA) addition can improve agricultural soil, but little is known about how it affects the soil resistome. In this study, we used selective agar plate combined with quantitative PCR (qPCR) and 16S rRNA gene sequencing to investigate how HA influences antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs) in soil contaminated with erythromycin and kanamycin. 0.1 % HA reduced the abundance of culturable erythromycin-resistant bacteria (ERB), while promoting the growth of kanamycin-resistant bacteria (KRB). Lysinibacillus and Paenibacillus were the dominant genera in ERB and KRB, respectively, governing the changes in their abundances. At this concentration, the Lysinibacillus abundance in ERB decreased from 96.74 % to 70.57 %. Meanwhile, that of Paenibacillus in KRB increased from 33.40 % to 77.44 %. The copy number of ermF decreased after HA addition, while that of ermB increased. Furthermore, 0.1 % HA significantly reduced the copy number and relative abundance of aadA1 and aac(6')-Ib (aka aacA4)-03 in the soil. Changes in these two types of ARB and ARGs were primarily driven by shifts in the microbial community structure. Soil physicochemical properties, particularly increased organic matter (OM), altered the absolute abundance of ermB. Meanwhile, changes in intI1 abundance determined the risk associated with aadA1 and aac(6')-Ib (aka aacA4)-03. These findings emphasize the dual role of HA in the dissemination of antibiotic resistance in agricultural soils and highlight the necessity of considering dose-dependent effects when applying HA as a soil amendment.

Soil Microbiology↗

PubMed2026

Depth-dependent microbial succession and interspecies hydrogen transfer drive pit mud maturation in Chinese strong-flavor baijiu fermentation.

Microbial communities in fermentation pit mud play a key role in determining the quality of Chinese strong-flavor baijiu (CSFB). However, the ecological processes underlying pit mud maturation across spatial and temporal scales remain unclear. In this study, amplicon sequencing and metagenomic analyses were employed to investigate the taxonomic succession, community assembly, and metabolic functions of bacterial and archaeal communities during the transition from fresh pit mud (FPM) to new pit mud (NPM) and old pit mud (OPM). A pronounced depth-dependent succession pattern was observed, with 4 cm representing a critical ecological boundary separating distinct community structures and maturation trajectories. During surface-layer maturation, community assembly shifted from stochastic to deterministic processes, accompanied by homogeneous selection and increasing network complexity. In contrast, stochastic processes remained dominant throughout deep-layer maturation. Metagenomic analyses revealed a functional transition from lactate and acetate production, primarily associated with Lactobacillus in FPM and NPM, to butyrate and caproate production associated with Clostridium and Caproiciproducens in OPM. This functional transition was accompanied by enhanced amino acid metabolism, which was associated with the enrichment of Proteiniphilum and Aminobacterium. Notably, methanogen-mediated interspecies hydrogen transfer (IHT) emerged as a key ecological feature during pit mud maturation. In OPM, IHT networks primarily involving Methanobacterium and Methanosarcina linked methanogenesis with reverse β-oxidation through diverse hydrogen-transfer pathways, reinforcing metabolic interactions underlying caproate production. These findings provide new insights into the ecological mechanisms underlying pit mud maturation and offer a theoretical basis for the directed cultivation of high-quality pit mud in CSFB production.

Hydrogen↗

PubMed2026

Transformation of antibiotics mediated by iron-bearing minerals: A review.

Iron-bearing minerals are ubiquitous in water, sediments and soil, where their surface chemical properties and redox activity can play an important role in degradation of trace antibiotics. This review systematically summarizes the roles of various iron-bearing minerals in chemical transformation and microbial degradation of antibiotics and reaction mechanisms involved, and refines the critical idea for iron-driven control of antibiotics with trace level in natural environment. Overall, antibiotics removal in the presence of iron-bearing minerals involves combination of adsorption, surface oxidative degradation, photo-induced degradation, Fenton-like reaction and microbial degradation. Adsorption of antibiotics by Fe(III)-minerals involves electrostatic interaction, complexation, H-bonding, π-π interaction and hydrophobic interaction. Adsorbed antibiotics form complexes with Fe(III)-minerals, undergoing electron transfer to generate radical intermediates, subsequently generating final products through hydroxylation, dealkylation, and deamination. Additionally, Fe(III)-minerals can be excited to produce electrons and holes under sunlight and to produce antibiotics-degrading hydroxyl radical through O2 reduction, H2O oxidation and ligand-to-metal charge transfer. Reduced iron minerals can activate oxygen to participate in Fenton-like degradation reactions. Finally, antibiotics are mainly removed by bio-driven Fenton reaction and direct enzyme biodegradation. The presence of iron-bearing minerals can promote antibiotics microbial degradation by providing nutrients for microorganisms or by changing microbial activity and microbial community structure. Existing problems and future research directions are identified. New insights for application of iron-bearing minerals in transformation of antibiotics are proposed. The work aims to suggest new methods and insights for pollution control and remediation of emerging contaminants including trace antibiotics in the natural environment.

Anti-Bacterial Agents↗

PubMed2026

Performance of Automated Hematology Analyzer Criteria in Detecting Peripheral Blood Smear Abnormalities: A Systematic Literature Review.

OBJECTIVES: Criteria for visual examination of stained peripheral blood smear (PBS) differ among institutions in the United States and internationally. In an effort to standardize review criteria, the International Consensus Group for Hematology Review (ICGHR) proposed in 2005 a consensus list of rules for CBC findings that should trigger a review of automated cell counter results and potentially lead to further testing or blood smear review. The primary aim of this paper is to report on the published literature in the past 20 years regarding PBS review criteria and their ability to identify relevant peripheral blood abnormalities. METHODS: We performed a systematic review of the published literature from 2005 to 2025 to investigate and summarize PBS review criteria and performance in the context of automated hematology analyzers in clinical laboratories. RESULTS: Of 5351 citations, 68 studies met our search criteria. These studies included 22 countries and all major hematology analyzer manufacturers. Marked variability was observed in study populations, analyzer flagging criteria, details of PBS visual review, definitions of a "positive" smear, and approaches to statistical data analysis. Across studies, the blast flag sensitivity ranged from 18% to 100% while the blast flag specificity ranged from 17% to 100%. Wide ranges in sensitivity/specificity were also seen for atypical and/or abnormal lymphocyte flags across studies. For studies analyzing the same patient population, less striking variation was seen across instruments. CONCLUSIONS: This systematic review provides a 20-year overview of the literature, highlighting significant variability in PBS review criteria, dependence on study design and hematology analyzer, and the importance of developing harmonized evidence-based guidelines.

Humans↗

PubMed2026

Accelerated Diagnostic Pathways for Suspected Acute Coronary Syndrome in Practice: A Randomized Trial of 0/1-Hour vs 0/3-Hour Troponin Testing.

BACKGROUND: For suspected acute coronary syndrome (ACS), guidelines recommend using high-sensitivity troponins (hs-cTn) in accelerated diagnostic pathways (ADPs) with 0/1-hour recommended over 0/3-hour ADP. However, implementation of these ADPs, with universal use of hs-cTns, has not been directly compared in randomized trials OBJECTIVES: This study sought to compare the efficiency and safety of the European Society of Cardiology (ESC) 0/1-hour and a 0/3-hour ADP when implemented in real-world clinical practice. METHODS: This pragmatic, randomized, noninferiority implementation trial compared the safety and efficiency of clinician decision making using these 2 pathways. To prevent incorporation bias, an independent hs-cTnI was used for formal adjudication using the fourth universal definition of myocardial infarction (MI). Efficiency was judged by the proportion of patients discharged within 4 hours. The safety endpoint was major adverse cardiac events (MACE) within 30 days (adjudicated index or representation type 1 MI, cardiovascular death, and urgent coronary revascularization) for those who were considered not to have ACS and discharged. The noninferiority margin, for absolute difference in sensitivity, between the ESC 0/1-hour and the 0/3-hour ADP was set at 3%, assessed with a 1-sided 97.5% CI. RESULTS: From December 2021 to July 2024, of 13,983 screened 3,543 individual patients with suspected ACS were recruited and consented from 2 major emergency departments in North-West England, with 100% follow-up achieved for all representations to any national hospital. The median age was 60 years (IQR: 49.5-70.5 years), 53% were men, 6.7%, and 7.6% had adjudicated index type 1 MI and MACE within 30 days, respectively. The turnaround time from sample to result for central laboratory hs-cTnT was 81 minutes (IQR: 69-101 minutes). The proportion of patients discharged within 4 hours was relatively low and did not differ substantially (21.8% vs 19.2%, P = 0.07). In addition, the 0/1-hour pathway was noninferior for safety, in patients discharged, compared with the 0/3-hour pathway, absolute difference in sensitivity was +4.2% (1-sided 97.5% CI: -2.5) in favor of the 0/1-hour pathway. The calculated sensitivities were 93.7% (95% CI: 88.4%-97.1%) vs 89.5% (95% CI: 82.7%-94.3%), respectively. CONCLUSIONS: Implementation of the ESC 0/1-hour pathway failed to discharge significantly more patients within 4 hours of presentation compared with the 0/3-hour ADP. In addition, The ESC 0/1-hour was noninferior to the 0/3-hour hs-cTn pathway for safety of discharge, although safety for both pathways was less than that imputed by observational studies. This trial demonstrates that perceived benefits to emergency department efficiency of a reduced sampling interval are mitigated by central laboratory turnaround times as well as system constraints. (Pragmatic Randomised Trial of the ESC 0/1 Versus 0/3 Hour Troponin Pathway [MACROS2]; NCT05322395).

Acute Coronary Syndrome↗

PubMed2026

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗

PubMed2026

Effects of acute hypoxia followed by reoxygenation on intestinal histomorphology, oxidative stress and hypoxia signaling biomarkers, and microbiota in pikeperch (Sander lucioperca).

In aquatic environments, natural and anthropogenic factors commonly reduce dissolved oxygen (DO) and trigger hypoxia, which threatens the health and survival of aquatic organisms. As an important economic fish species in China, pikeperch (Sander lucioperca) is extremely sensitive to hypoxia. However, there are relatively few reports on how hypoxia and reoxygenation affect its intestinal physiology and microbial community. Three treatment groups were set for pikeperch: normoxia (DO = 8.5 ± 0.5 mg/L), 48 h hypoxia (DO = 2.5 ± 0.1 mg/L), and reoxygenation (48 h hypoxia followed by 6 h reoxygenation at normal DO), to evaluate alterations in intestinal histopathology, tight junction gene expression, oxidative stress, hypoxia signaling molecules and intestinal microbiota composition. The results showed that hypoxia significantly decreased muscularis thickness by approximately 32.5% and reduced the expression of tight junction genes (Occludin, Claudin2, and ZO-2). Moreover, hypoxia significantly increased oxidative stress index levels (GSH-Px, CAT, and MDA), markedly upregulated the expression of Bax, Caspase3, and HIF-1α, while significantly downregulating the expression of Bcl-2, Egln1, and Egln2. Notably, reoxygenation elicited partial compensatory effects against these hypoxia-induced changes. 16S rRNA sequencing analysis revealed that hypoxic stress altered the intestinal microbial community composition of pikeperch and increased its diversity. In the hypoxia group, the abundance of the phylum Bacillota, along with the genera Halomonas and Acinetobacter, was significantly elevated, whereas in the reoxygenation group, the genus Lactobacillus increased approximately 180-fold. The results indicated that hypoxia caused intestinal oxidative damage, cell apoptosis, and intestinal microbiota dysbiosis in pikeperch, while short-term reoxygenation achieved partial recovery from these hypoxia-triggered intestinal injuries. The present research provides valuable references for in-depth exploration of the molecular mechanisms behind the response of pikeperch to acute hypoxia and reoxygenation stress, while also offering a novel perspective to understand the mechanism by which hypoxia impacts intestinal health in fish.

Animals↗

PubMed2026

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established clinical risk stratification tools. However, reported performance is heterogeneous and the relative contribution of model architecture and feature dominance remains unclear. METHODS: We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy systematic review and diagnostic meta-analysis of studies evaluating ML models for intracranial aneurysm rupture discrimination. PubMed, Embase and CENTRAL were searched to February 2026. Sensitivity and specificity were pooled using a bivariate random-effects model, with summary receiver operating characteristic curves generated across training, internal testing and external validation datasets. Models were compared with regression-based approaches and Population, Hypertension, Age, Size of aneurysm, Earlier subarachnoid haemorrhage, Site of aneurysm (PHASES) scores. Subgroup and meta-regression analyses explored associations between algorithm family and feature domain. RESULTS: Sixty-two retrospective cohorts (29 709 patients 209 models) met the inclusion criteria. In training datasets, pooled sensitivity and specificity for ML were 0.81 (95% CI 0.75 to 0.85) and 0.83 (0.80-0.86), with an area under the curve (AUC) of 0.878, exceeding PHASES (AUC 0.667). In testing datasets, ML retained higher discrimination (AUC 0.837) than regression models (0.806) and PHASES (0.646). In external validation, sensitivity was preserved (0.82), but specificity declined (0.66). Deep learning demonstrated the highest AUCs (training and testing). Incorporation of haemodynamic or radiomic features improved pooled discrimination relative to morphology alone. Evidence of small-study effects and mostly unclear Prediction Model Risk Of Bias Assessment Tool ratings were observed. CONCLUSIONS: ML approaches demonstrate higher pooled discrimination for aneurysm rupture status than conventional risk scores in retrospective datasets, but reduced external validation specificity and heterogeneity limit confidence for clinical translation. Prospective, externally validated, calibrated models are required before integration into routine cerebrovascular risk stratification.

Humans↗

PubMed2026

Microbial allies in a cotton pest: A descriptive account of associated microbiota dynamics in Dysdercus cingulatus across development.

BACKGROUND: Hemipteran insects harbour several symbiotic partners, mainly bacteria, which play pivotal roles for hosts like dietary provision, support overall physiology, xenobiotic degradation and manipulate/regulate behaviour. Most of these symbionts usually reside and operate from the digestive tracts of the animals. Cotton is one of the major cash crops in India and Dysdercus cingulatus (D. cingulatus) though a secondary pest, is causing significant destruction of cotton bolls, poor lint quality and reduce oil content of seeds. Premature opening of cotton bolls often leads to bacterial and fungal infections, thus resulting in extensive economic loss worldwide. D. cingulatus is a hemimetabolous insect that comprises of developmental stages like egg, nymph (5 instar stages), and adult. The present work explored the ontogeny specific diversity in the associated microbiota and predicted their probable functional inputs in D. cingulatus. RESULTS: The data obtained using 16S rRNA gene sequencing (NovaSeq 6000) revealed presence of members of Proteobacteria (65.83%), Firmicutes (24%), Actinobacteria (10%) phyla throughout the ontogeny of D. cingulatus. Highest alpha diversity of these symbiotic bacteria was recorded in the third instar nymphs in contrast to rest of the developmental stages. Among all the observed genera, Stenotrophomonas, Hungatella and Glutamicibacter were predominant from egg to adult stages. MicFunPred, a tool used for predicting the probable functional inputs of these symbionts, hinted at their probable stage specific contribution in crucial biochemical pathways such as polyketide biosynthesis, ascorbate/aldarate metabolism, pentose phosphate and glyoxylate cycles, steroid hormone and peptidoglycan biosynthesis, and glycolysis/pyruvate metabolism. CONCLUSIONS: The primary investigations on the ontogenetic composition and diversity of associated microbiota, suggest dynamic shifts in D. cingulatus, concurrent with their probable functions/roles in the host development and metabolism. To the best of our knowledge, this is the first report on symbiotic microbiota variation across the developmental stages of D. cingulatus that provides preliminary descriptive observations that may guide future functional and experimental investigations into microbiota-based pest management.

Animals↗

PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗

PubMed2026

Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.

Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.

Bacillus↗