Microorganisms

Background: Oral dysbiosis has been associated with oral squamous cell carcinoma (OSCC); however, most microbiome studies rely on 16S ribosomal RNA (rRNA) gene sequencing, limiting species-level taxonomic resolution. Methods: Dental plaque, saliva, and tumor tissue samples from 10 patients with OSCC and dental plaque and saliva samples from 10 healthy controls were analyzed in this exploratory cross-sectional study. DNA was extracted and subjected to shotgun metagenomic sequencing using the Illumina MiSeq platform. Sequence reads were quality filtered with fastp, taxonomically classified using Kraken2 v2.1.3, and species-level abundances were re-estimated with Bracken v2.9 following the removal of human reads and low abundance taxa. Relative abundances were compared using the Mann Whitney U test with the Benjamini Hochberg false discovery rate correction, while the Bray Curtis principal coordinate analysis was used as an exploratory approach to visualize microbial community patterns. Results: Shotgun metagenomic sequencing revealed distinct bacterial community profiles across the oral microenvironment. Dental plaque exhibited the highest taxonomic diversity and relative abundance. The control plaque was enriched in Streptococcus koreensis, Capnocytophaga sp. oral taxon 878, Treponema sp. Marseille Q4132, and Leptotrichia sp. oral taxon 498, whereas the plaque from patients with OSCC showed a higher relative abundance of Pyramidobacter piscolens, Parvimonas parva, and Gemella sanguinis. Salivary samples displayed lower diversity and a more homogeneous composition, predominantly comprising Capnocytophaga endodontalis, Prevotella jejuni, Aggregatibacter aphrophilus, and Gemella sanguinis. The tumor tissue showed relatively higher abundance of Sellimonas catena, Escherichia coli, Solobacterium moorei, and Lacrimispora sp. HJ 01. Conclusions: This exploratory study provides species-level characterization of the oral microbiome across multiple oral microenvironments in OSCC and generates hypotheses for future integrative metagenomic and functional studies investigating the potential contribution of oral bacterial communities to OSCC pathogenesis.

Plant growth-promoting bacterial endophytes represent a sustainable strategy for enhancing agricultural productivity while reducing reliance on synthetic fertilizers and pesticides. This study focused on the genomic and functional characterization of two endophytic bacterial strains, R11F and R19M, isolated from bean and maize roots, respectively. Comparative analyses based on 16S rRNA gene sequences, average nucleotide identity (ANI), and genome-to-genome distance calculations (GGDC) classified both isolates as Pseudomonas palleroniana. Comparative genomic analyses revealed highly conserved genomes containing genes associated with plant colonization, phosphate solubilization, stress adaptation, heavy metal resistance, and hydrocarbon degradation. Genome mining further identified 17 and 18 biosynthetic gene clusters (BGCs) in R11F and R19M, respectively, including non-ribosomal peptide synthetases (NRPS), pyoverdine, NRP-metallophores, RiPP-like compounds, arylpolyenes, {beta}-lactones, terpenes, NAGGN, and hydrogen cyanide. Strain-specific BGCs associated with syringomycin and viscosin biosynthesis were identified in R11F, whereas R19M harbored clusters related to asplenin and kolossin biosynthesis. In vitro assays confirmed indole production, phosphate solubilization, and siderophore production, as well as the ability of both strains to grow in nitrogen-free medium. Both strains significantly inhibited the growth of Fusarium oxysporum, Phytophthora cinnamomi, and Colletotrichum gloeosporioides. Furthermore, plant inoculation assays demonstrated host-dependent growth promotion, with R11F showing the most consistent improvements in plant growth parameters in tomato, wheat, and lentil. Overall, the integration of comparative genomics and experimental validation demonstrates that P. palleroniana R11F and R19M possess complementary traits associated with plant growth promotion, pathogen suppression, saline stress adaptation, and bioremediation.

Background: Refractory and macrolide-resistant Mycoplasma pneumoniae pneumonia (MPP) has emerged as a major challenge in pediatric respiratory medicine, amplified by the post-2023 resurgence. However, a systematic overview of the research landscape specific to treatment-refractory and drugresistant disease in children remains lacking. Methods: Research articles and reviews on pediatric refractory or macrolide-resistant MPP published between 2000 and 2025 were retrieved from OpenAlex using Boolean searches. After screening, 2,286 records were quantitatively analyzed for annual output, contributing countries/institutions, thematic clusters, and citation-burst dynamics using Python. Results: Annual publications grew exponentially, with a pronounced surge after 2023 (n=378 in 2025). China produced the highest volume (45.1%) but recorded fewer citations per publication than the US, Japan, and Canada. The literature resolved into four clusters: macrolide resistance/molecular basis, epidemiology, etiology/co-infection, and refractory disease management. Burst analysis showed an evolution from earlier fronts like 23S rRNA mutations and azithromycin to recent emerging trends like pandemic-related co-circulation, genotype surveillance, and co-infection. Conclusions: Research on pediatric refractory and resistant MPP is expanding rapidly, shifting in emphasis from etiologic descriptions toward resistance mechanisms and clinical management. Standardizing the treatment of macrolide-unresponsive disease and post-pandemic epidemiological surveillance represent the principal directions for future work. Keywords: Mycoplasma pneumoniae; children; macrolide resistance; refractory pneumonia; bibliometric analysis; research trends

The global dissemination of antimicrobial resistance is increasingly driven by bacterial clones combining antimicrobial resistance with enhanced virulence and environmental adaptability. Escherichia coli sequence type 131 (ST131) has historically been regarded as a major disseminator of the extended-spectrum {beta}-lactamase (ESBL) blaCTX-M-15. However, the emergence of E. coli ST1193 carrying blaCTX-M-15 may represent an ongoing shift in the epidemiology of this resistance determinant. Here, we investigated the prevalence, genomic characteristics, virulence and antimicrobial resistance potential of ST1193 in comparison with ST131. A total of 1,136 E. coli isolates were recovered from touristic and non-touristic environments, hospital-associated samples, and aircraft toilets in Guadeloupe. Isolates were whole-genome sequenced and analysed for antimicrobial resistance and virulence determinants. Additionally, publicly available genomic data comprising 1,215 blaCTX-M-15-positive ST131 and ST1193 isolates were analysed to assess temporal and geographical trends. ST1193 was significantly associated with aircraft-associated samples and exhibited a higher antimicrobial resistance gene burden than ST131, while maintaining a comparable virulence factor content. Analysis of publicly available genomes revealed similar temporal emergence patterns for blaCTX-M-15-positive ST1193 and ST131, with ST1193 showing a more recent distribution and a higher number of deposited isolates in recent years, consistent with a potential ongoing clonal replacement. Comparative genomic analysis identified numerous virulence and adaptation-associated genes shared between both sequence types, while ST1193 additionally carried distinct determinants, including components of the transmissible locus of stress tolerance. Furthermore, quinolone resistance-associated mutations were strongly linked to blaCTX-M-15 carriage, particularly among ST1193 isolates. Together, these findings identify E. coli ST1193 as an emerging high-risk clone with substantial potential for blaCTX-M-15 dissemination. Its association with aircraft-associated samples further highlights the potential role of air travel in long-distance transmission and underscores the need to reconsider current surveillance strategies focused predominantly on ST131.

The global prevalence of Extended-spectrum {beta}-lactamase-producing Enterobacterales (ESBL-E) colonization is increasing. However, it is unclear whether ESBL-E persist and if that is associated with an altered gut microbial ecology especially in early life where the developing microbiome may not provide the same colonization resistance as in adults. In this study, we collected longitudinal infant gut microbiome samples at delivery and in the nonclinical home setting in Chicago, Illinois, U.S.A, aiming to disentangle how genetic factors pertaining to the ESBL-E, as well as the surrounding gut ecology, influences persistence in the infant gut microbiome. We observed not only a higher-than-expected prevalence of ESBL-E in healthy infant gut microbiomes, but also a trend of ESBL-E persistence once colonized. Microbial communities showed higher dissimilarity between ESBL-E positive and negative infant gut microbiome at earlier time points. Although dissimilarity decreased over time, we present evidence that ESBL-E persist even when traditional detection methods are negative.

Next-generation sequencing (NGS) of the prokaryotic 16S rRNA gene revolutionized gut microbiome research two decades ago. However, short read lengths remain an inherent limitation of platforms such as the widely used Illumina platforms (2 x 150-300 bp). Recent advances in Oxford Nanopore Technologies (ONT) flow cell chemistry (R10.4.1) have substantially improved sequencing accuracy. Combined with a custom multiple-primer strategy that comprehensively targets 16S rRNA gene variants to generate near-full-length amplicons, this approach enables read-by-read taxonomic classification, a feature not feasible with short-read sequencing platforms. Although our multiple-primer strategy could enable parallel sequencing of more than 18,000 samples (192 x 96), current flow cell capacity offers sufficient sequencing depth for approximately 1,000-1,500 samples. To validate the scalability and our per-read classification pipeline, we show that more than a thousand human fecal microbiome samples spiked with two bacterial strains (Imtechella halotolerans and Allobacillus halotolerans), not otherwise present in human fecal samples, can be successfully sequenced on a single flow cell, achieving a per-molecule error rate sufficient for direct per-read classification and at an adequate read depth for downstream analysis. This level of scalability significantly reduces per-sample costs, making the approach more accessible to a broader research community. To embrace these advancements, we have developed RubyRed, a pipeline that processes raw sequencing data and assigns taxonomic classifications on a per-read basis. Using spike-in references (I. halotolerans and A. halotolerans), we demonstrate high mean single-read sequencing accuracy (99% and 98.9%, respectively), with the majority of reads exceeding the canonical threshold required for species-level taxonomic classification based on the 16S rRNA gene.

Background Severe acute respiratory infections (SARI) strain healthcare systems. Sentinel surveillance remains central to SARI monitoring, but routinely collected hospital discharge data offer a scalable, population-wide complement. In Finland, national registers now enable register-based surveillance, yet SARI case definitions remain unevaluated. Aim To evaluate whether routinely collected electronic health records can support register-based SARI surveillance and establish a national case definition. Methods We conducted a retrospective register-based study linking inpatient discharge data from the Finnish Care Register for Health Care (Hilmo) and laboratory-confirmed pathogen notifications from the National Infectious Diseases Register (NIDR). Admissions were aggregated into hospitalisation episodes using generic and pathogen-specific respiratory ICD-10 codes and linked to laboratory-confirmed respiratory pathogens within an admission-centred window. We assessed the impact of diagnostic coding position, laboratory linkage windows and alternative case definitions on age distribution, seasonality and epidemic trend detection. Results We included 145,435 respiratory hospitalisation episodes. Laboratory confirmations clustered around admission, and a -7-to-+3-day window was selected; 51,498 (35.4%) had a linked laboratory confirmation. Specific primary-position diagnoses preserved clear seasonality and age distributions consistent with SARI epidemiology, whereas secondary-position diagnoses showed attenuated seasonality. A combined case definition incorporating specific primary diagnoses and laboratory-supported syndromic episodes produced stable epidemic curves while improving sensitivity over laboratory confirmation alone. Conclusion National discharge and laboratory registers can support robust SARI surveillance in Finland when case definitions are carefully designed. A combined register-based definition balances specificity, sensitivity and feasibility, complementing sentinel surveillance and integrated respiratory monitoring. Keywords Severe acute respiratory infection (SARI); surveillance; electronic health records; ICD-10; case definition; Finland

Motivation: With the scaling frequency and intensity of extreme heat events across the globe, it is critical for public institutions to develop early detection systems and continuous monitoring of these events and their impacts. In Brazil, Rio de Janeiro was the first city to publish its heat protocol, with the Rio Heat Dashboard as a central component of this system. Implementation: The dashboard was implemented using R/Shiny and integrates climatic and health data from multiple sources. General features: The application comprises real-time heat exposure monitoring and automatic alert level classification, which is monitored daily by multiple municipal actors and supports activation of actions specified in the heat protocol. It also features a health impact module, which lists each heat event and its impact on mortality, and primary care and emergency visits. Availability: The source for full reproducibility is available through https://github.com/joaohmorais/RioHeatDashboard.

Machine-learning models of the human microbiome are trained mostly on stool samples from single cohorts, limiting cross-body-site representation and cross-study generalization. Progress is constrained less by algorithms than by the absence of a harmonized multi-body-site corpus carrying the technical metadata needed to model, rather than ignore, batch structure. Here we release Corpusome, a harmonized two-tier cross-body-site human microbiome corpus for representation learning: a harmonized corpus of 187,546 human microbiome samples integrating standardized profiles from curatedMetagenomicData, the American Gut Project, and the EBI MGnify platform. Corpusome follows a two-tier design preserving both functional depth and cross-body-site breadth: a shotgun tier (22,588 samples, 93 studies) with species- and pathway-level profiles, and a 16S tier (164,958 samples, from a full pull of 708 MGnify studies) with genus-level profiles extending coverage to oral, skin, respiratory, and urogenital sites. It spans six body sites and two modalities, with harmonized metadata for batch-aware modelling. Body-site signal exceeds technical/source variance in the 16S tier by approximately 2.4-fold.

Background The COVID-19 pandemic substantially altered respiratory pathogen circulation worldwide. However, longitudinal analyses of changes in respiratory pathogen ecology across the pandemic and post-pandemic periods remain limited. Methods We analyzed 19,968 respiratory samples tested with the BioFire(R) FilmArray(R) Respiratory Panel at a hospital in Tokyo, Japan, between January 2020 and March 2026. We evaluated temporal changes in pathogen circulation, age-specific epidemiology, co-detection patterns, pairwise pathogen associations, and clinical parameters. Results At least one respiratory pathogen was detected in 27.8% of tests. Respiratory pathogens resurged asynchronously following the relaxation of COVID-19-related public health measures. Influenza virus circulation remained markedly suppressed until late 2022 before re-emerging in successive large seasonal epidemics, whereas other pathogens, including RSV, human metapneumovirus, and Mycoplasma pneumoniae, exhibited distinct resurgence patterns. Pathogen distributions also varied by age. Human rhinovirus/enterovirus remained predominant among young children, whereas SARS-CoV-2 predominated among older adults. Co-detection occurred in 14.0% of positive specimens and was significantly more frequent in younger patients. Pairwise analysis identified both positive and negative pathogen associations; however, the patterns varied across age groups and study periods. Conclusions Respiratory pathogen circulation changed substantially during the transition from the COVID-19 pandemic to the post-pandemic period, with pathogen-specific, age- and period-dependent patterns. Continued surveillance is warranted to determine how respiratory pathogen circulation will evolve and to inform infection control strategies in the post-pandemic era.

Background. The clinical course of coronavirus disease 2019 (COVID-19), and the ability to anticipate which patients will require intensive care, were poorly characterized in Central Asia during the first pandemic wave. We aimed to describe the clinical features of hospitalized COVID-19 patients at the Tashkent State Medical University, Uzbekistan, and to identify risk factors for intensive care unit (ICU) admission. Methods. In this single-centre cross-sectional study, we reviewed the records of 2500 consecutive patients hospitalized between 11 April and 8 August 2020. Patients were grouped as asymptomatic or symptomatic, and symptomatic patients were compared by ICU versus non-ICU status. Groups were compared with chi-square or Fisher's exact and Mann-Whitney U tests. Univariable and multivariable logistic regression identified risk factors for ICU admission. Results. Of 2500 patients (median age 36 years; 60.9% male), 989 (39.6%) were asymptomatic and 1511 (60.4%) symptomatic. In total, 129 (5.2%) were admitted to the ICU and 38 (1.5%) died. ICU patients were older (median 56 vs 40.5 years) and more often had bilateral pneumonia, oxygen desaturation and cardiometabolic comorbidity. In the multivariable model (AUC 0.82), the independent predictors of ICU admission were ischemic heart disease (aOR 4.20), shortness of breath (aOR 3.22), hypertensive heart disease (aOR 2.93) and male sex (aOR 2.00). Conclusions. Older age, cardiometabolic comorbidity and respiratory compromise identified patients at high ICU risk. As one of the first clinical COVID-19 descriptions from Uzbekistan, these data provide a baseline for preparedness in Central Asia.

H5N1 clade 2.3.4.4b avian influenza A viruses pose a significant threat to wild animal populations, domesticated animals, and potentially, the human population. For H5N1s to infect and transmit among mammalian species, mutations for improved utilization of mammalian receptors and enhanced replication at the lower temperatures of the upper respiratory tract need to be acquired. A human H1N1pdm09-like virus was compared to H5N1 genotypes B3.13 and D1.1 for replication at 33{o}C, 37{o}C, and 39{o}C - temperatures consistent with the upper and lower respiratory tract in humans, and dairy cow udder tissue. All H5N1 viruses had increased plaque sizes on MDCK cells at 37{o}C and 39{o}C compared to H1N1pdm09. In primary, differentiated human nasal and bronchial epithelial cultures, all H5N1 viruses show restricted infectious virus production compared to H1N1 at 33{o}C. While H5N1 D1.1 also showed restricted replication at 37{o}C and 39{o}C, the H5N1 B3.13 replicated to nearly equivalent titers as H1N1pdm09. All H5N1 viruses demonstrated similar cell tropism in cells from the upper and lower respiratory tract, infecting more ciliated than non-ciliated cells relative to H1N1pdm09. H1N1, H5N1 B3.13 D1.1 infection induced similar innate immune factors, with nasal epithelial cells producing higher levels compared to bronchial epithelial cells. These data suggest that genotype B3.13 and D1.1 H5N1 viruses show different temperature dependent replication patterns compared to H1N1pdm09.

Antimicrobial resistance is a public health challenge, driving the need for rapid, cost-effective diagnostic support tools. Artificial intelligence (AI) may enable prediction of susceptibility to untested antibiotics from known susceptibility results, but prospective clinical validation is required before routine use. We evaluated an AI-based decision support method, trained on invasive isolates from the European Surveillance System (TESSy), for prediction of antibiotic susceptibility in clinical Escherichia coli urine isolates. The evaluation included 99 E. coli isolates from urine samples with diversity in age, sex, and antibiotic susceptibility. Predictions were evaluated for 14 antibiotics using patient metadata and susceptibility results for 4-8 antibiotics as input. Prediction uncertainty was handled using conformal prediction, allowing abstention when confidence was insufficient. EUCAST disk diffusion test results were used as reference and genomic sequence data was used to explore mechanisms of the AI performance. Without conformal prediction, 84% of predictions were correct when susceptibility results of six antibiotics were used to predict susceptibility to eight additional antibiotics. Across all predictions generated using susceptibility results for six antibiotics as input, the major and very major error rates were 19% and 12%, respectively. Prediction errors varied between antibiotics and were associated with certain phenotypic and genotypic resistance patterns. Conformal prediction reduced errors but increased abstentions; at confidence levels of 90%, 95%, and 97.5%, the model abstained in 9.6%, 14%, and 22% of instances. The method showed promising performance, but its clinical use remains limited and may require diagnostic data beyond susceptibility test results and demographic variables.

Background Using a population-based cohort from the Calgary Health Zone (CHZ), Canada, we integrated longitudinal antimicrobial susceptibility and prescribing data with the whole genome sequences of five major pathogens. We aimed to assess how antimicrobial resistance (AMR) responds to prescribing changes and determine which bacterial strains shape these dynamics. Methods We analysed antibiotic prescribing rates, clinical and genomic data from 7,271 Staphylococcus aureus, 1,609 Enterococcus faecalis, 801 Enterococcus faecium, 11,363 Escherichia coli, and 2,319 Klebsiella pneumoniae isolates, associated with bacteraemia episodes in the CHZ between 2006-2022. Genomic clusters (referred to as strains) were identified using StrainGST and assigned to known sequence types (STs) or clonal complexes (CCs). Strain-level incidence, stratified by community-onset (isolates collected [&le;]48h after admission) and hospital-onset (>48h after admission), AMR phenotypes, and prescribing rates were modelled using negative-binomial and binomial regression. Temporal trends were quantified using average annual percentage change (AAPC). Findings Between 2010-2022, fluoroquinolone prescribing declined in both community (AAPC=-6.8% [95% CI -8.1, -5.4]; p<0.0001) and hospital settings (AAPC=-5.1% [-6.5, -3.7]; p<0.0001). This was accompanied by a significant reduction in fluoroquinolone resistance among Gram-positive species. Specifically, S aureus bacteraemia resistant to clinically important antibiotics, cloxacillin, ciprofloxacin, erythromycin, and clindamycin, declined from 2006 to 2022, mostly in hospital-onset cases (AAPC=-16.0%, [-19.3%, -12.7%], p<0.0001). In E coli, ceftriaxone and ciprofloxacin resistance were clustered in ST131 and the emerging ST1193; the latter increased steadily, particularly in community-onset cases (AAPC=17.7%, [0.0%, 30.0%], p<0.0001). CTX-M-27-producing E coli ST131 strains increased (AAPC=23.8%, [17.4%, 30.5%], p<0.0001) between 20082022, while CTX-M-14-producing E coli ST131 declined (AAPC=-15.9%, [-21.3%, -10.2%], p<0.0001) between 2013-2022. These trends were paralleled by an increase in community cephalosporin prescribing (AAPC=7.3%, [4.2%, 10.5%], p<0.0001) between 2010-2022. For K pneumoniae, hypervirulent ST23 was most common (N=88) with an increasing trend in incidence (AAPC=3.0%, [-2.8%, 9.2%]) between 2006-2019. Conclusions The contrasting resistance trends between Gram-positive and Gram-negative species underscore the complexity of AMR control efforts. Effective strategies will require stewardship efforts targeting multiple drug classes, genomic surveillance for emerging resistant strains, and interventions extending beyond hospital settings.

Background Rural-urban disparities in SARS-CoV-2 infection epidemiology remain poorly quantified and understood in Zambia despite differences in healthcare access, services and preventive interventions. This study examined the geographical distribution and associated factors of SARS-CoV-2 cases across selected rural and urban districts of Zambia. Methods A convergent mixed-methods study comprised of quantitative survey and qualitative interviews was conducted in; Ndola (Urban), Kafue (Peri-urban) and Lufwanyama (Rural). The proximate determinant framework guided variable selection and interpretation. Quantitative combined (Hospital-surveillance data with community survey), while qualitative included In-depth interviews. Participants were sampled using multistage sampling technique. Quantitative data were analysed using STATA version 17, while qualitative data were analysed thematically. Findings were integrated through triangulation. Results A total of 528 participants were included, with a median age 31 years (15-71). Overall SARS-CoV-2 positivity was 12.6%, varying across rural (16.5%), peri-urban (14.9%), and urban (9.9%) settings, though residence was not associated with infection (P<0.132). Participants aged [&ge;]49 years had significantly higher odds of infection (aOR=8.78; 95% CI:1.15-66.99), whereas secondary education (aOR=0.37; 95% CI:0.16-0.86) and hospital-based testing (aOR=0.37; 95% CI:0.15-0.92) were associated with lower odds of infection. Vaccine uptake was highest in urban areas but was not independently associated with infection. Qualitative findings revealed marked rural-urban differences in perceived susceptibility, testing access, vaccine decision-making, and adherence to preventive measures, explaining several quantitative observations. Conclusion SARS-CoV-2 infection across rural and urban settings in Zambia was influenced by demographic, behavioral, and health-system factors rather than geographic residence alone. These findings highlight the need for context-specific prevention strategies, equitable access to testing, strengthened community surveillance, and targeted risk communication to improve preparedness and response for future respiratory disease outbreaks.

Background: Pulmonary arterial hypertension (PAH) is a serious disease with poor prognosis, especially in infants or preterm babies and there is still no optimal treatment for this disease. Noradrenalin (NE) is a vasoactive mediator which is released by sympathetic ganglion. According to previous studies, NE/1-adrenoreceptors is not only in regulating normal physiologic responses, but also in the pathogenesis of PAH. However, the mechanisms of NE in PAH are not fully understood. Methods: Human PASMC (PASMC) was used in this study. Cell viability assay and Wound healing assay were used to evaluate the proliferation and migration of PASMC. Immunoprecipitation and western blots analysis were used to investigate the mechanisms which involved in NE-induced PASMC proliferation. Results: We investigated that NE could induce human PASMC proliferation and migration. Furthermore, we first find that endothelin 1 (ET-1) signaling pathway plays an important role in NE-induced PASMC proliferation. ET1 is a critical molecular which is known for regulating cell growth and migration. We investigated that NE could increase NE-1 secretion, further enhancing ET-1 bind to its receptors. For further clarifying the downstream signals in NE/ET-1 induced PASMC proliferation, we detected the phosphorylation and expression levels of ERK and JNK. Conclusions: By combining the results from ours and previous studies, we believed that JNK/c-jun pathway may play an important role in NE-induced PASMC proliferation. Key Words: Noradrenaline; Pulmonary Arterial Hypertension; Pulmonary Artery Smooth Muscle Cells; Endothelin-1; JNK/c-Jun Signaling.

Motivation: The Interactive Tree of Life (iTOL) is widely used to display and annotate phylogenetic trees, but managing its format-sensitive annotation files impede reproducible high-throughput analyses. Among the maintained Python packages and versions evaluated, none combined template generation, taxonomic monophyly assessment and iTOL batch operations. Results: PyiTOL validates inputs, generates 31 iTOL template schemas (22 accepted by the live batch uploader), performs LCA-based monophyly classification with nested-monophyly detection, sampling-completeness states and polyphyletic subgroup decomposition, plus API upload and session replay. On a topology-constructed benchmark, all calls matched prespecified labels for 4,389 groups; on a 700-genome tree, binary mono/non-mono calls agreed with ETE4 for 409 genera; 17,294 GTDB R232 genera were processed in about 17 s. Availability and Implementation: PyiTOL 1.0.3 (Python [&ge;]3.10; Linux, macOS and Windows) is MIT-licensed at https://github.com/ZengZichao/PyiTOL and archived with test data at Zenodo (https://doi.org/10.5281/zenodo.22106806).

Background: Case fatality reflects the quality and timeliness of clinical care for leptospirosis, yet no study has examined it at a national level in the Dominican Republic (DR), where leptospirosis is endemic. We describe the case fatality rate (CFR) of leptospirosis in the DR between 2012 and 2026 and identify associations with mortality. Methods: We conducted an analytical cross-sectional study, using national surveillance records merged with a discharge-condition extract via a composite key. We calculated CFR with Wilson 95% confidence intervals among 5,412 valid cases (suspected, probable, or confirmed) reported from January 2012 through June 2026. We compared proportions with Pearson's chi-square test, assessed annual trend with ordinary least squares linear regression, and fitted multivariable logistic regression models to account for confounding. Results: Overall CFR was 8.5% (460/5,412), with no significant annual trend (p=0.372). CFR was higher in men than women (p < 0.001) and increased significantly with age (p < 0.001). Male gender (OR: 1.79; 95%CI: 1.18-2.73) and pre-existing comorbidity (OR: 1.76; 95% CI: 1.21- 2.57) were independent predictors of death. Clinical complications were the strongest predictor in the adjusted model (OR: 3.16; 95%CI: 2.17-4.61), attenuating the gender effect. CFR varied widely by province (2.43-22.22%) and correlated negatively with incidence at the province level (p = 0.066). Conclusions: Leptospirosis case fatality is concentrated among men, people with comorbidity, and those who develop clinical complications. These national, long-term findings can help prioritize clinical and surveillance resources as extreme weather events are expected to intensify across the Caribbean.

Background: Sleeve gastrectomy is the most frequently performed bariatric procedure worldwide but is associated with the development of de novo gastroesophageal reflux disease (GERD). Hiatal hernia has been identified as a relevant anatomical factor in postoperative reflux, although most studies evaluate it dichotomously without analyzing whether its size influences GERD risk. The aim was to evaluate the association between preoperative hiatal hernia size and de novo GERD after sleeve gastrectomy. Methods: Retrospective, single - center, observational study of patients undergoing sleeve gastrectomy at Hospital Central Norte de Petroleos Mexicanos (2018 - 2025). Demographic and clinical characteristics, endoscopic classification of hiatal hernia size (small <2 cm, medium 2.1 - 4 cm, large >4 cm), and evidence of de novo GERD were analyzed using descriptive statistics, Fisher's exact test, odds ratio (=R) estimation with 95% confidence intervals (CI), and binary logistic regression. Statistical significance was set at p<0.05. Results: Fiftysix patients were included (mean age 48.3 {+/-} 8.1 years; 67.9% male). Hiatal hernia classification was conclusive in 46 patients (82.1%): 63.0% no hernia, 4.3% small, 30.4% medium, and 2.2% large. De novo GERD occurred in 14.0% of patients without preexisting GERD (6/43). No significant association was found between hiatal hernia size and de novo GERD (Fisher p=0.515). In the reduced logistic model, neither hiatal hernia (medium/large vs. absent/small; OR 3.47; 95% CI 0.50 - 29.43; p=0.207) nor age (OR 1.02; 95% CI 0.90 - 1.13; p=0.754) was significantly associated. No evaluated factor (sex, smoking, alcohol, age) reached significance. Conclusions: In this cohort, no statistically significant association was demonstrated between preoperative hiatal hernia size and de novo GERD after sleeve gastrectomy; however, the low number of events limits the ability to exclude a clinically relevant association. These findings are compatible with a multifactorial mechanism rather than with the isolated presence of this finding. Prospective studies with larger sample sizes and standardized reflux assessment instruments are required to confirm these results.

Background: Early trophic feeding promotes gut maturation, feeding tolerance, and growth in preterm neonates. However, delays remain common despite recommendations for initiation within 24 hours of birth, especially in resource-limited settings. Evidence on feeding initiation timing and predictors among Ethiopian preterm neonates is limited. Objective: To determine time to trophic feeding initiation and identify predictors among preterm neonates admitted to Adama Hospital Medical College, Ethiopia. Methods: A hospital-based retrospective cohort study was performed on 436 randomly chosen preterm neonates admitted to NICU. Data extraction was performed using a structured checklist. Time to trophic feeding initiation was analyzed using Kaplan-Meier estimates, log-rank tests, and bivariable and multivariable Cox regression models . Adjusted hazard ratios with 95% CIs were reported. Results:The sample comprised 416 preterm neonates, of whom 311 (74.8%) started trophic feeding during follow-up, and 105 (25.2%) were censored. The rate of initiation of trophic feeding was 1.92 per 100 person-hours (95% CI 1.72 to 2.15). Median time to initiation was 42 hours (interquartile range 24 to 50). Independent predictors of feeding initiation were determined by multivariable analysis and included gestational age, birth weight, maternal anaemia, respiratory distress syndrome and necrotising enterocolitis. Neonates born at 34-36 weeks had earlier initiation than those born at <34 weeks (AHR 1.39; 95 % CI 1.09 to 1.78). Similarly, neonates with a birth weight of [&ge;]1500 g had an earlier initiation than those with a birth weight of <1500 g (AHR 1.41; 95% CI 1.04 to 1.91). Delayed initiation was associated with maternal anaemia (AHR 0.70; 95% CI 0.51-0.95), respiratory distress syndrome (AHR 0.67; 95% CI 0.51-0.88) and necrotising enterocolitis (AHR 0.48; 95% CI 0.33-0.69). Conclusions: Delayed trophic feeding remains common among preterm neonates. Standardized feeding protocols, strengthened maternal care, and individualized nutrition strategies are needed to improve neonatal outcomes in study area.