The genomes of pathogenic bacteria typically encode a diverse array of virulence factors, which constitute the fundamental basis for resisting host immunity and establishing infection. Given the high energetic cost of virulence gene expression, pathogens must precisely orchestrate the activation and silencing of these genes in accordance with the infection process, thereby flexibly executing diverse biological functions within the constraints of their energy budget. To sustain efficient infection, pathogens have evolved multiple mechanisms governing gene expression, enabling them to maintain competitive advantages over both their hosts and microbial competitors across diverse niches. Pseudomonas plecoglossicida is an important Gram-negative pathogen in aquaculture that combines strong environmental adaptability with host invasiveness. It frequently causes explosive epidemics such as visceral white spot disease, inflicting substantial economic losses, and represents one of the principal pathogens threatening the sustainability of aquaculture. An in-depth dissection of its complex virulence mechanisms and hierarchical regulatory networks will provide critical molecular insights into the dynamic interplay between P. plecoglossicida and its hosts. Accordingly, this review focuses on the key virulence factors of P. plecoglossicida, including secretion systems (the type III secretion system and its effector PP_ExoU, and the fish-pathogen-specific type VI secretion system T6SS-1), extracellular products, the flagellar system, metal nutrient acquisition systems, and outer membrane barriers, together with their hierarchical regulatory networks comprising sigma factors, two-component systems, quorum sensing, the second messenger cyclic di-GMP, and small RNAs. We summarize the core functions of these virulence factors and dissect the molecular mechanisms by which this pathogen senses environmental signals and modulates virulence expression, aiming to provide a theoretical basis for the development of novel antivirulence strategies and therapeutic interventions.
This mini-review synthesizes four decades of Mexican fusariosis literature, organizing cases into four clinical categories: ocular, superficial/cutaneous, invasive/disseminated, and central nervous system (CNS) disease. It identified significant gaps in national surveillance, molecular diagnostics, antifungal susceptibility testing, access to effective therapies, specialized mycology infrastructure, and highlights the urgent need for a coordinated clinical mycology network in Mexico. Fusariosis, caused by Fusarium species, presents a broad clinical spectrum, from keratitis and onychomycosis in immunocompetent individuals to disseminated disease in those with hematologic conditions. In Mexico, most reported cases stem from clinical case reviews rather than systematic national surveillance. Exceptions include a 10-year retrospective study published in 2023, and a Fusarium solani meningitis outbreak in Durango and Matamoros during 2022–2023, which together represent the largest global clusters of healthcare-associated fungal meningitis including an antifungal-resistant isolate in Matamoros that required investigational treatments such as Fosmanogepix. Keratitis by Fusarium spp. is the most documented manifestation, with 380 cases reported, most of them in clinical centers for diagnosis in Ciudad de Mexico, where F. solani predominated and ocular trauma was the primary risk factor. Additionally, 49 cases of invasive fusariosis have been reported across six states, mainly linked to burn injuries and hematological malignancies. Collectively, this review provides a national framework for understanding fusariosis and informs future research and public health strategies to address this emerging threat.
The debate between post-treatment Lyme disease syndrome (PTLDS) and chronic Lyme disease (CLD) reflects different views about the causes and treatment of persistent symptoms attributed to Lyme disease, including symptoms that continue after recommended antibiotic treatment. This study examines how competing positions in the controversy draw on different scientific evidence domains, and how findings from those domains are extended into broader clinical and mechanistic claims. We analysed a 2000–2024 literature corpus using a prompt-optimised three-model large language model ensemble to classify abstracts by stance, theme and model-derived study design. We then conducted targeted full-text audits of selected retreatment and treatment-duration trials, and preclinical persistence studies. Across the higher-volume evidence domains, model-derived claim orientations differed by study-design tier. Observational studies and commentaries showed PTLDS-oriented distributions, whereas case reports or series, animal models, and in vitro studies showed CLD-oriented distributions. The smaller RCT and guideline tiers were also PTLDS-oriented, but the small numbers and wide confidence intervals made this direction uncertain. The clinical trial audit showed that some trials reported short-term or symptom-specific improvements, while the interpretation of these findings depended on their durability, endpoint consistency, eligibility criteria, treatment burden, and safety. The citation-conditioned preclinical audit identified findings that support several candidate mechanisms and generate hypotheses for further study, but these findings did not by themselves establish viable infection as the cause of persistent human symptoms or demonstrate the efficacy of prolonged antimicrobial treatment. The findings show a recurring distinction between mechanism-level evidence and the evidence needed to establish patient-level causation or durable clinical benefit. They map how these different forms of evidence are distributed and translated across the PTLDS–CLD literature.
BackgroundEarly identification and precise prognosis of sepsis are of great significance. Traditional biomarkers, such as procalcitonin (PCT) and lactate (Lac), do not reflect the immune dysregulation at the center of sepsis pathophysiology. Interferon - γ -induced protein 10 (IP-10) is an important chemokine for septic immune dysregulation responses and may have good predictive value. Our research aims to establish and validate a clinically applicable nomogram that combines IP-10 and conventional clinical parameters to predict the 28-day mortality in septic patients in the emergency department (ED).MethodsThis study recruited 655 patients who met the criteria of sepsis 3.0 from the ED of Beijing Chao-Yang Hospital from November 2023 to May 2025. A total of 580 patients were analyzed and randomly divided into the training group and the validation group in a 7:3 ratio. The variable selection in this study was conducted using the Least Absolute Shrinkage and Selection Operator (LASSO) regression, and our research employed multivariate logistic regression to determine independent predictors of 28-day mortality. The study scientifically evaluated nomogram using receiver operating characteristic (ROC) curves, calibration plots, Decision Curve Analysis (DCA), and Clinical Impact Curves (CIC).ResultsAmong the 580 patients, the 28-day mortality rate was 12.9% (75 non-survivors). Multivariate analysis identified five independent risk factors: IP-10 (OR = 1.978, 95% CI: 1.964-1.992), Sequential Organ Failure Assessment (SOFA) score (OR = 1.526, 95% CI: 1.365-1.758), Lac (OR = 1.447, 95% CI: 1.281-1.711), PCT (OR = 1.562, 95% CI: 1.341-1.924), and Acute Physiology and Chronic Health Evaluation II (APACHE II) score (OR = 1.658, 95% CI: 1.515-1.840). The nomogram showed excellent discriminatory ability. The area under the curve (AUC) of the training set and validation set was 0.952 (95% CI: 0.930-0.974) and 0.946 (95% CI: 0.911-0.981), respectively. Calibration was satisfactory, and DCA/CIC analyses confirmed that within the risk threshold range, the clinical net benefit was significant.ConclusionIt is the first time to develop and validate a prognostic nomogram model for 28-day mortality based on IP-10 and clinical parameters in septic patients in the ED. This tool may assist clinicians in early risk stratification and clinical decision-making.
The evolutionary origin of vertebrate adaptive immunity has been a longstanding problem in evolutionary biology. The diversified proteins that orchestrate this complex system are present throughout the jawed vertebrates but are absent in extant jawless vertebrates and invertebrates. From work initially carried out in the sea lamprey (Petromyzon marinus) and subsequently extended to other lampreys and hagfishes, we now know that, instead of immunoglobulin domain-based receptors, jawless vertebrates have leucine-rich repeat-based variable lymphocyte receptors (VLRs). Like immunoglobulins (Igs) and T cell receptors (TCRs), these proteins are somatically diversified in lymphocyte-like cells. Of the six VLR loci described in the sea lamprey (VLRA-VLRF), five are expressed exclusively as transmembrane receptors on T-like lymphocytes (VLRA and VLRC-VLRF). Here we focus on VLRB which, like jawed vertebrate immunoglobulins, is expressed both as a cell surface receptor on B-like cells and as a secreted, polyvalent VLRB antibody. Although little is known about the mucosal functions of VLR antibodies, VLRB-expressing cells diversify in gut-associated lymphopoietic tissues and are present in the gut epithelium and other regions of the intestine. We discuss what is known about VLRB and some future directions for understanding its gut-associated functions in relation to what is known in the jawed vertebrates.
BackgroundPulmonary mucormycosis is a life-threatening fungal infection with a mortality rate exceeding 50%, and diabetes mellitus is one of its strongest risk factors. However, the molecular mechanisms linking diabetes to impaired pulmonary innate immunity remain poorly understood.MethodsA streptozotocin-induced type 1 diabetes (T1D) mouse model was used to investigate host responses to intratracheal Cunninghamella bertholletiae infection. Genetic Axl deficiency, pharmacological Axl inhibition with BGB324, histopathological analyses, and ex vivo and in vitro macrophage assays were performed to define the role of the Gas6/Axl axis in antifungal immunity.ResultsT1D mice exhibited rapid mortality after pulmonary C. bertholletiae infection, accompanied by markedly impaired early neutrophil recruitment. Elevated lung and serum levels of growth arrest-specific protein 6 (Gas6) were intrinsic features of the diabetic state and correlated with blood glucose levels. Genetic ablation or pharmacological blockade of Axl restored macrophage chemokine responses, increased neutrophil recruitment into the airspace, reduced fungal burden, and significantly improved survival in T1D mice. Mechanistically, the Gas6/Axl axis directly suppressed fungus-induced chemokine production by alveolar macrophages, establishing a pre-existing state of innate immune hyporesponsiveness before infection.ConclusionsThese findings identify the Gas6/Axl axis as a mechanistic link between diabetes and impaired pulmonary innate immunity. Targeting this pathway may represent a promising host-directed therapeutic strategy for pulmonary mucormycosis in patients with diabetes.
BackgroundSepsis-associated encephalopathy (SAE) is a common complication of sepsis. Its underlying mechanisms remain incompletely understood, and effective treatments are still lacking. Recent studies have shown that the microbiota-gut-brain axis may play a key role in the pathogenesis of SAE, but its potential mechanisms have not yet been clarified.MethodsIn this study, we used a lipopolysaccharide (LPS)-induced zebrafish endotoxemia model and systematically characterized microbiota–gut–brain axis-associated alterations using multi-omics profiling combined with histopathology, behavioral assessment, and blood–brain barrier integrity assays.ResultsOur results showed that LPS exposure induced intestinal inflammation and barrier disruption, neurovascular dysfunction, anxiety-like behavior, and impaired cognitive function in zebrafish. Gut microbiota profiling revealed marked compositional alterations, accompanied by widespread metabolic disturbances in intestinal and brain tissues. Brain transcriptomic analysis showed that the differentially expressed genes were closely associated with the PI3K-Akt signaling pathway, cell adhesion, and autophagy-related pathways. Cross-omics association analyses suggested potential associations among gut microbial dysbiosis, metabolic disturbances, and brain molecular responses.ConclusionThese findings suggest that disruption of the microbiota–gut–brain axis may contribute to LPS-induced SAE-like neurobehavioral abnormalities and provide a basis for further mechanistic and therapeutic studies.
BackgroundLimited by small sample size, single-institution design, and insufficient comprehensive external validation across heterogeneous healthcare systems, no study to date has systematically validated the predictive performance of machine learning models for sepsis occurrence in an intensive care unit (ICU) population with concomitant pulmonary fibrosis through multiple large-scale databases.MethodsThis retrospective multi-database study utilized two large databases to establish and validate a machine learning model for predicting the probability of sepsis occurrence in ICU patients with pulmonary fibrosis. In this study, 542 patients from the MIMIC-IV database were divided into a training set (381 patients) and an internal validation set (161 patients) in a 7:3 ratio, and external validation was performed on the MIMIC-III (186 patients) database. Six machine learning algorithms were employed: Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Logistic Regression (LR), Lightweight Gradient Boosting Machine (LightGBM), Support Vector Machine (SVM), and Artificial Neural Network (ANN). Baseline variables were screened using least absolute shrinkage and selection operator (Lasso) regression to identify potential predictors. The interpretability of the model was evaluated using Shapley Additive Explanations (SHAP) analysis.ResultsThe entire cohort consisted of 728 ICU patients with pulmonary fibrosis. We identified nine consistently crucial clinical characteristics, including gender, dementia, pneumonia, antibiotics, nephrotoxic drugs, glucocorticoids, sequential organ failure assessment (Sofa) score, red blood cell distribution width, and total serum calcium. The ANN algorithm performed optimally, with an area under the curve (AUC) of 0.878 in the training set, 0.837 in the internal validation set, and 0.857 in the MIMIC-III external validation set. SHAP analysis indicated that Sofa was the most influential predictor, followed by antibiotics and pneumonia. Additionally, a web tool was developed to facilitate the prediction of sepsis probability in clinical practice.ConclusionsThis study is the first to develop and validate a machine learning model for predicting sepsis in ICU patients with pulmonary fibrosis across multiple databases. The ANN model, combined with SHAP interpretability, provides a reliable decision-making tool for clinical decision support, and its consistency has been verified in two databases, including our internal validation cohort.
Colorectal cancer (CRC) is one of the most common malignancies worldwide and a leading cause of cancer-related mortality. The gut microbiome has attracted growing attention because of its involvement in CRC initiation and progression, early detection, prognostic evaluation, and therapeutic response. However, CRC microbiome studies continue to face inconsistent findings and limited reproducibility, partly because of differences in specimen type. Directly comparing microbial signals from fecal, mucosal, and intratumoral samples may therefore bias mechanistic interpretation and mislead clinical translation. From a spatial-niche perspective, this review summarizes the distinct characteristics, formation mechanisms, interrelationships, and clinical implications of fecal, mucosal, and intratumoral microbiota during CRC progression. We further propose a “seed bank–colonizers–specialized populations” model to conceptualize the continuous but non-equivalent hierarchy among these niches. By providing a clearer spatially stratified framework, this review aims to help move CRC microbiome research beyond descriptive associations toward precision-oriented applications supported by mechanistic interpretability, reproducible evidence, and clinical translatability.
Tuberculosis is a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb). As primary host cells targeted by Mtb, macrophages play central roles in both innate and adaptive immunity. Accumulating evidence indicates that macrophage polarization is a key determinant of tuberculosis pathogenesis. In response to diverse microenvironmental cues, macrophages adopt functionally distinct polarization states, ranging from pro-inflammatory, microbicidal programs (M1-like) to anti-inflammatory, tissue-reparative programs (M2-like). These states differentially shape tuberculosis progression. Defining the remodeling of these context-dependent macrophage states is therefore critical for understanding Mtb infection, granuloma formation, and disease outcomes, as well as for guiding the development of next-generation vaccines, immunotherapies, and host-directed interventions. This Review synthesizes the molecular mechanisms underlying macrophage polarization during Mtb infection, integrates the bidirectional regulatory networks between pathogen-derived and host-derived factors, and highlights their roles in immune evasion, granuloma biology, and emerging therapeutic strategies in tuberculosis.
IntroductionMosquitoes (Diptera: Culicidae) are primary vectors of public health pathogens, yet their core viromes remain poorly characterized, particularly in Neotropical sylvatic lineages. This study investigated the RNA virome of multiple mosquito species across urban-to-forest gradients in São Paulo State, Brazil, including neglected sylvatic taxa such as Sabethes, Psorophora, Shannoniana, and Wyeomyia.MethodsThe RNA virome of multiple mosquito species was investigated across urban-to-forest gradients in São Paulo State, Brazil. Ecological analyses were performed to assess the effects of host taxonomy and environment on virome composition. Network analysis was conducted to investigate virus–host associations and viral sharing across ecological interfaces.ResultsOur analysis identified 919 viral contigs across 217 viral species and 37 distinct families, revealing a substantial fraction of “viral dark matter” with low amino acid identity (median < 40%) in predominantly sylvatic mosquito species. Although viral families containing known arboviruses, such as Flaviviridae, Phenuiviridae, and Peribunyaviridae, were detected, no high-consequence human pathogens were identified within the sensitivity limits of our sampling and sequencing depth. Ecological analyses demonstrated that virome composition was strongly structured by host taxonomy and environment (R2=0.570, p=0.001), with host species explaining 32.9% of the unique variance (PERMANOVA, R2=0.329, p=0.001), whereas ecotope played a secondary role (R2=0.029, p=0.001). Network analysis revealed a highly modular virus–host structure dominated by host-restricted specialists, with a limited number of bridge species facilitating viral sharing across ecological interfaces.DiscussionThese findings indicate that intrinsic mosquito biology is the main driver of viral community structure, while environmental gradients play a secondary role, and highlight the importance of host-associated processes in shaping viral diversity at the Neotropical forest–urban interface.
IntroductionKlebsiella pneumoniae is the most frequently encountered multidrug-resistant bacterial pathogen in humans, but its pathogenic effects on aquatic animals are not well documented. K. pneumoniae has recently been identified as a significant cause of death and illness in American bullfrogs (Rana catesbeiana). In the present study, the dominant bacteria were isolated from a diseased bullfrog with neurological signs in Hanchuan, Hubei Province, China.MethodsThe ZYRC75 isolate was identified by Gram staining, morphological observations, biochemical assays and 16S rRNA sequencing. Antimicrobial susceptibility testing and artificial infection testing were conducted to determine its resistance phenotype and pathogenicity. The whole genome of the ZYRC75 strain was also sequenced.ResultsThe isolate ZYRC75 was identified as K. pneumoniae and assigned to ST6839, a novel sequence type. It displayed multidrug resistance against penicillins (carbenicillin, piperacillin, ampicillin, penicillin), chloramphenicol, trimethoprim and tetracycline. Infection experiments confirmed the isolate exhibited significant pathogenicity in bullfrogs. ZYRC75 possessed a single circular chromosome of 5,454,922 bp, carrying 179 virulence‑related genes and 157 antimicrobial‑resistance genes.DiscussionThis investigation presents a detailed phenotypic and genomic profile of ZYRC75, revealing its antimicrobial resistance and virulence, and establishing a basis for future studies on the pathogenicity of K. pneumoniae.
BackgroundGut microbiota dysbiosis has been implicated in osteoarthritis (OA) through the gut–joint axis, but the clinical efficacy of gut microbiota-targeted interventions remains unclear. This systematic review and meta-analysis evaluated the effects of these interventions on clinical outcomes and inflammatory biomarkers in OA.MethodsPubMed, Embase, Web of Science, CNKI, and Wanfang were searched from inception to 20 January 2026 for randomized controlled trials (RCTs) of probiotics, prebiotics, synbiotics, or dietary modification in adults with OA. Primary outcomes were visual analog scale (VAS) pain, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, WOMAC function, and WOMAC total score; secondary outcomes included WOMAC stiffness, body weight, knee flexion angle, cartilage oligomeric matrix protein (COMP), high-sensitivity C-reactive protein (hs-CRP), erythrocyte sedimentation rate (ESR), interleukin (IL)-1β, and IL-6. Standardized mean differences (SMDs) with 95% CIs were pooled using random-effects models; risk of bias was assessed with RoB 2.0. Subgroup analyses, univariable meta-regression, trial sequential analysis (TSA), and GRADE were used to grade certainty.ResultsEighteen RCTs (2,080 participants) were included. Interventions reduced VAS pain (SMD = −0.66, 95% CI: −1.27 to −0.06, P = 0.03), WOMAC pain (SMD = −0.62, 95% CI: −0.97 to −0.27, P = 0.004), WOMAC function (SMD = −0.40, 95% CI: −0.64 to −0.17, P = 0.0006), and WOMAC total score (SMD = −0.78, 95% CI: −1.26 to −0.30, P = 0.009) and lowered hs-CRP, ESR, and IL-1β. WOMAC stiffness, WOMAC physical function, body weight, knee flexion angle, COMP, and IL-6 did not differ significantly. All 18 trials were rated “some concerns” overall on RoB 2.0. Probiotics showed larger effects than dietary interventions, with appreciable residual heterogeneity. Information accrual reached the required size only for WOMAC pain and WOMAC function; VAS pain, WOMAC total score, and hs-CRP were promising but not yet conclusive. GRADE certainty ranged from high (WOMAC function) to very low (VAS pain); unchanged COMP indicates no support for cartilage protection or disease modification.ConclusionGut microbiota-targeted interventions, particularly probiotics, may improve pain, physical function, and systemic inflammation in OA. The evidence is compatible with symptomatic benefit but does not support cartilage protection or disease modification. Because certainty ranges from high to very low and information accrual is incomplete for most outcomes, these findings are provisional pending larger standardized RCTs.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/home, identifier CRD42023472181.
IntroductionImmune checkpoint inhibitors (ICIs) have transformed the management of microsatellite instability-high/deficient mismatch repair (MSI-H/dMMR) colorectal cancer (CRC). However, a substantial proportion of patients exhibit primary resistance or eventually develop acquired resistance, highlighting the need for a better understanding of the biological mechanisms influencing therapeutic response. Increasing evidence suggests that the gut microbiome–immune axis is an important regulator of antitumor immunity through complex interactions among microbial communities, microbial metabolites, host immunity, and the tumor microenvironment.Main bodyThis narrative review summarizes current evidence regarding the role of the gut microbiome–immune axis in mediating primary and acquired resistance to immune checkpoint inhibition in MSI-H/dMMR CRC. We discuss the physiological interactions that maintain immune homeostasis and review the functional mechanisms through which alterations in microbial metabolic pathways, including short-chain fatty acids, bile acids, tryptophan-derived metabolites, inosine, and polyamines, may influence antitumor immune responses. We further examine microbial composition and functional biomarkers associated with immune checkpoint inhibitor response, together with emerging therapeutic strategies aimed at modulating the gut microbiome–immune axis, including dietary interventions, prebiotics, probiotics, selective antimicrobial approaches, fecal microbiota transplantation, live biotherapeutic products, and next-generation precision microbiome engineering. Finally, we discuss current translational challenges and future research priorities required for successful clinical implementation.ConclusionThe gut microbiome–immune axis represents a promising area of investigation for understanding resistance to immune checkpoint inhibition in MSI-H/dMMR CRC. While growing evidence supports its biological relevance, much of the current knowledge remains preclinical or is derived from early-phase clinical studies. Future progress will depend on mechanistic investigation, longitudinal multi-omic microbiome profiling, standardized methodologies, prospective biomarker validation, and the rational development of microbiome-directed therapeutic strategies to support precision immuno-oncology.
IntroductionThis study characterized gut microbial composition and fecal metabolomic profiles in hospitalized patients with Staphylococcus aureus infection (SAI) and explored their associations with inflammatory and organ-function indicators.MethodsThis single-center exploratory observational study included 16 hospitalized patients with microbiologically confirmed and clinically adjudicated SAI and 10 healthy controls (HCs). The first qualified fecal sample was collected within 7 days after microbiological confirmation. Fifteen patients had received antimicrobial treatment before sampling, whereas one had not; none of the HCs had received antibiotics before fecal collection. Gut microbiota were profiled by 16S rRNA sequencing, and fecal metabolites were analyzed by LC-MS/MS-based untargeted metabolomics. Genus-level differential abundance was assessed using ANCOM-BC2 with Benjamini-Hochberg correction and pseudo-count sensitivity analysis.ResultsAlpha-diversity indices were lower in the SAI group. Bray-Curtis PERMANOVA showed a statistically significant but modest group-associated difference in community composition (F = 2.8654, R² = 0.1067, P = 0.0001), whereas PERMDISP was not significant (P = 0.0885). ANCOM-BC2 identified four genera with robustly higher bias-corrected abundance in the SAI group: Corynebacterium, the [Clostridium] innocuum group, Enterococcus, and Eggerthella. Their effect directions remained positive in culture-confirmed and respiratory-infection-only analyses, although not all retained pseudo-count-robust significance. Untargeted metabolomics detected 2,956 features, including 2,491 with putative MS/MS-based annotations. Using VIP > 1 and raw P < 0.05, 381 candidate features were identified. Exploratory enrichment signals involved tryptophan, glutathione, sulfur, bile acid, amino acid, and lipid metabolism, but were not regarded as FDR-confirmed. No clinical-omics association remained significant after FDR correction.DiscussionHospitalized patients with SAI showed group-associated microbial and metabolic differences compared with HCs. However, because nearly all patients were sampled after antimicrobial exposure, these patterns cannot be separated from treatment, hospitalization, disease severity, and other clinical interventions. The findings are therefore preliminary and hypothesis-generating rather than S. aureus-specific signatures.
IntroductionDeletion of Listeria pathogenicity island 4 (LIPI-4) in Listeria monocytogenes (L. monocytogenes) impairs motility, disrupts flagellar assembly, and markedly upregulates the lmo0180 gene.MethodsIn this study, the Δlmo0180 single-gene deletion mutant and ΔLIPI-4/lmo0180 double-gene deletion mutant were constructed by homologous recombination. Bacterial motility was assessed, and flagellar biogenesis was observed by transmission electron microscopy. The adhesion, invasion, intracellular proliferation, and cell-to-cell spread capacities were compared across strains. Virulence was evaluated in a mouse model, and transcript levels of major virulence factors were quantified by quantitative real-time PCR.ResultsThe results showed that deletion of lmo0180 alone had no detectable effects on bacterial motility, flagellar formation, or virulence-related phenotypes. In contrast, LIPI-4 deletion enhanced biofilm formation and eliminated motility and flagellar assembly. Simultaneous deletion of LIPI-4 and lmo0180 restored bacterial motility, flaA gene expression, and partial restoration of flagellar assembly; however, the double mutant displayed significant reductions in adhesion, invasion, intracellular proliferation, and cell-to-cell spread in host cells. In vivo experiments consistently showed that mice infected with the ΔLIPI-4/lmo0180 mutant exhibited reduced bacterial loads and tissue damage. Compared with the ΔLIPI-4 strain that exhibited elevated transcript levels of PrfA-controlled virulence genes, the ΔLIPI-4/lmo0180 mutant exhibited downregulation of most such genes.DiscussionThese transcriptional changes may contribute to the attenuated virulence phenotype. Collectively, the study demonstrates that LIPI-4 and lmo0180 interact genetically to influence flagellar motility and virulence in L. monocytogenes, a finding that provides new insights into the pathogenic mechanisms of L. monocytogenes.
BackgroundMosquito-borne viral diseases pose an important public health threat due to their frequent outbreaks, similar early clinical manifestations, and potential for rapid transmission. Conventional diagnostic methods, such as virus isolation, serological assays and RT-qPCR, are reliable but may be limited by long turnaround time, cross-reactivity, laboratory equipment requirements and trained operators. Recombinase polymerase amplification (RPA)-based methods have emerged as promising tools for rapid detection of mosquito-borne viruses, but their overall diagnostic accuracy still requires comprehensive evaluation. This meta-analysis aimed to systematically evaluate the diagnostic performance of RPA-based assays for mosquito-borne virus detection.MethodsA systematic search of PubMed, Embase, Web of Science, Scopus and MEDLINE was conducted using search terms related to mosquito-borne viruses, RPA technology and diagnostic accuracy. Studies reporting sensitivity and specificity or providing sufficient data to construct 2 × 2 contingency tables were included. The methodological quality of included studies was assessed using QUADAS-2. R software was used for statistical analysis. A Bayesian bivariate random-effects model was applied to calculate pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and summary receiver operating characteristic (SROC) curve.ResultsTen studies involving 13 data sets in total were included in this meta-analysis. The pooled sensitivity and specificity of RPA-based assays were 0.96 (95% CrI: 0.92–0.98) and 0.99 (95% CrI: 0.98–1.00), respectively. The pooled PLR was 146.25 (95% CrI: 35.79–597.57), and the pooled NLR was 0.05 (95% CrI: 0.02–0.10). The area under the SROC curve was 0.987 (95% CrI: 0.972–0.995), suggesting excellent overall diagnostic performance. Subgroup analyses showed that RPA-based assays maintained good diagnostic accuracy in both CRISPR-based and non-CRISPR groups, as well as in DENV and non-DENV subgroups. No significant publication bias was detected by Deeks’ funnel plot asymmetry test.ConclusionRPA-based assays showed good diagnostic accuracy for mosquito-borne virus detection, with high pooled sensitivity, specificity and AUC. These findings suggest that RPA-based methods may provide a useful technical choice for rapid case identification and public health response. Nevertheless, the limited number of included studies, methodological limitations and insufficient real-world evidence warrant cautious interpretation. More high-quality prospective studies are still needed to confirm their practical feasibility and application value in clinical and public health settings.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD420261380107.
BackgroundDental caries, primarily driven by Streptococcus mutans (S. mutans) biofilms, remains a formidable clinical challenge due to the protective extracellular polymeric substance (EPS) matrix and the limited efficacy of conventional antibiotics.MethodsTo address this, we report a biomimetic photothermal nanoplatform (FWA NPs) featuring a hierarchical, urchin-like multi-spiked architecture, synthesized via the co-assembly of ferrocene-tryptophan conjugates and in situ biomineralized gold nanoparticles.ResultsBenefiting from this unique topological structure, FWA NPs maximize interfacial interactions with bacterial membranes and exhibit enhanced near-infrared absorption, achieving a remarkable photothermal conversion efficiency of 54.4%. Under 808 nm near-infrared (NIR) irradiation, this rapid and localized heat generation induced efficient eradication of S. mutans, which manifested as a dramatic reduction in bacterial colonies from ~107 to ~105 CFU/mL and irreversible membrane damage characterized by massive surface wrinkling, localized collapse, and membrane rupture. Additionally, FWA NPs reduced the survival rate of S. mutans biofilms to approximately 10%, Crucially, FWA NPs demonstrated excellent biocompatibility with a hemolysis rate of approximately 1% for red blood cells and a relative survival rate of 90% for normal cells.ConclusionBy synergistically integrating topological advantages with highly efficient energy conversion, this rationally designed nanoplatform offers a highly effective, non-antibiotic therapeutic paradigm for combating biofilm-associated oral infections and mitigating the global threat of antimicrobial resistance.
BackgroundFusobacterium nucleatum (F. nucleatum) is increasingly recognized as a key pathobiont in colorectal cancer (CRC), driving tumor progression through immune evasion, inflammation, and metabolic reprogramming. Nevertheless, a comprehensive bibliometric analysis of the literature on F. nucleatum and CRC remains a gap in the current research landscape. Here, we integrate bibliometric trend analysis with a narrative synthesis of key mechanistic insights. Unlike traditional narrative reviews, this study systematically quantifies global research trends, collaboration networks, and thematic evolution using integrated bibliometric tools (CiteSpace, VOSviewer, and Bibliometrix).MethodsThis study employed bibliometric analysis to explore the current status of research related to F. nucleatum and CRC. Publications from 2000 to 2025 were retrieved from the Web of Science Core Collection (WOSCC) and Scopus. We used VOSviewer, CiteSpace and Bibliometrix to visualize countries, institutions, authors, keywords, journals and references. Statistical analysis was conducted using Microsoft Office Excel.ResultsThe annual number of publications and their relative percentages concerning F. nucleatum and CRC exhibited a steady upward trend from 2009 to 2025, with China (n=708), the United States (n=584), and Italy(n=119) dominating the field. Harvard University and Shanghai Jiao Tong University emerged as leading institutions, while Yu Jun and Shuji Ogino were the most prolific authors. Keyword analysis identified 7 clusters. The most popular journal in this field is Gut. Limitations include potential selection bias from using only two databases (WOSCC and Scopus) and restriction to English-language publications.ConclusionOur research provides a comprehensive overview of the research trends and key focal areas in the study of F. nucleatum and CRC. The analysis results show that the annual publication volume in this field has steadily increased, indicating that researchers’ attention to this topic has grown continuously. Future research directions suggested by the literature include further exploration of F. nucleatum-targeted therapies, biomarker validation, and multi-omics approaches, although these remain at an early stage.
BackgroundUlcerative colitis (UC) is a chronic inflammatory bowel disease characterized by intestinal immune dysregulation and mucosal barrier dysfunction. Macrophages play central roles in gut immunity, yet their metabolic reprogramming and heterogeneity in UC remain insufficiently characterized.MethodsWe integrated single-cell RNA sequencing (scRNA-seq), bulk transcriptomics, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (LASSO, SVM-RFE, and Random Forest) to identify candidate macrophage-associated metabolic regulators in UC. Pseudotime trajectory, CellChat, and functional enrichment analyses were used to assess differentiation, intercellular interactions, and pathway involvement. Diagnostic performance was evaluated using ROC curves and validated in independent datasets. Experimental validation was performed using Hematoxylin and Eosin (H&E) staining for histopathological assessment and Western blotting for protein expression analysis.ResultsscRNA-seq identified 505 macrophage-specific genes, with pseudotime analysis suggesting differentiation branches marked by RGCC and FOSL2. Transcriptomic profiling revealed 1,058 differentially expressed genes, enriched in TNF, epithelial–mesenchymal transition, and NF-κB pathways. Six macrophage-associated immunometabolic genes (CYBB, CR1, INPP5D, CTSH, IFI16, and NCF4) were identified through WGCNA and machine learning analyses. These genes were strongly correlated with macrophage infiltration and cytokine signaling, showing high diagnostic performance (AUC > 0.98), although potential overfitting cannot be fully excluded. Consensus clustering stratified UC patients into two molecular subtypes, with Cluster 1 exhibiting a proinflammatory phenotype. H&E staining confirmed characteristic mucosal inflammation and epithelial damage in UC tissues, while Western blotting validated the upregulation of the six key regulators in UC tissues.ConclusionThis multi-omics analysis identifies six macrophage metabolic regulators (CYBB, CR1, INPP5D, CTSH, IFI16, and NCF4) with potential diagnostic relevance in UC. Experimental validation provides supportive evidence for their association with macrophage-related immunometabolic alterations in UC.
