BMC Microbiology

Malaria remains a severe health problem in endemic regions because people lack adequate diagnostic tools, leading to delayed medical care and elevated death rates. This research introduces a dual-mode artificial intelligence system that uses two complementary models to enhance malaria pre-screening and diagnosis. The patient-centered model uses multivariate logistic regression to analyze biosignals, including heart rate, body temperature, and oxygen saturation, collected through a wearable sensor prototype and a mobile interface for symptom analysis. The system enables patients to begin self-assessment to determine their level of need before scheduling a doctor's appointment. The clinician-centered model represents a customized convolutional neural network that uses annotated microscopy images of red blood cells to achieve 94.84% accuracy, 95.71% precision, 93.87% recall, 94.78% F1 score, and 0.84 Area Under Curve (AUC). The patient model achieved 94.6% accuracy and an AUC of 0.985 using a 70/30 train-test split. These systems work together to create a layered diagnostic system that can operate independently or together to detect malaria at an early stage, especially in areas with limited resources. The findings demonstrate that wearable biosignal data integration with image-based deep learning can produce dependable, scalable, and user-friendly systems for malaria pre-screening. Keywords - malaria diagnosis, artificial intelligence (AI), convolutional neural networks (CNN), wearable biosensors, multivariate logistic regression

Antimicrobial resistance (AMR) is an ever-increasing threat to population health. Industrial, environmental and societal factors are increasingly recognized as important contributors to AMR within communities. Here, we investigated the spatial distribution of AMR genes (ARGs) across Alberta, Canada and their association with socio-economic, immigration-related, and agro-industrial characteristics using municipal wastewater-based surveillance. We analyzed monthly wastewater metagenomes collected between March 2022 and March 2023 across eleven municipalities, representing 39% of Alberta's population. Integration with census data enabled multivariate analysis, revealing that municipal resistome profiles were strongly structured along income and immigration-related population gradients. ARGs spanning 14 resistance classes exhibited distinct distributional patterns across income and immigration gradients, including contrasting associations among beta-lactam, aminoglycoside, and macrolide-lincosamide-streptogramin ARGs, consistent with heterogeneous selection pressures across sub-populations. These findings demonstrate the capacity of longitudinal wastewater surveillance to identify persistent population-level resistome patterns and highlight the importance of incorporating sociodemographic context into AMR surveillance and mitigation strategies.

Background: Early-onset colorectal cancer (EOCRC) is increasing globally, particularly among Hispanic/Latino (H/L) populations, yet the contribution of tumor-colonizing microbiota to age-associated colorectal cancer (CRC) biology remains poorly understood. Most microbiome studies have focused on fecal communities or non-Hispanic populations, leaving the intratumoral microbial landscape of H/L patients largely unexplored. Methods: We performed an exploratory characterization of tumor-colonizing microbiota using whole-exome sequencing (WES) data from four primary colorectal tumors obtained from H/L patients treated at City of Hope, including two EOCRC (<50 years) and two late-onset colorectal cancer (LOCRC; [&ge;]50 years) cases. Following removal of host-derived sequences, microbial taxonomic profiling was conducted at the family, genus, and species levels, and microbial metabolic pathways were inferred. Clinical and pathological data were integrated to evaluate age-associated differences in microbial composition and predicted function. Results: Family-, genus-, and species-level analyses consistently demonstrated greater microbial diversity in LOCRC than EOCRC. LOCRC contained more than twice the number of unique bacterial families, nearly three times as many unique genera, and more than twice as many unique bacterial species. A conserved core microbiota, including Fusobacteriaceae, Prevotellaceae, Fusobacterium, and Prevotella, was identified across both age groups, whereas LOCRC was enriched in CRC-associated taxa including Fusobacterium nucleatum, Bacteroides fragilis, Parvimonas micra, Porphyromonas asaccharolytica, and Dialister pneumosintes. Species-level analyses revealed only a single shared bacterial species between EOCRC and LOCRC, indicating progressive microbial divergence with increasing taxonomic resolution. In contrast, functional profiling identified 11 predicted microbial metabolic pathways, of which nine were shared between age groups, two were unique to EOCRC, and none were exclusive to LOCRC. Core metabolic pathways involved in energy metabolism, amino acid biosynthesis, phospholipid metabolism, and central carbon metabolism exhibited comparable abundance across both groups, demonstrating substantial functional conservation despite pronounced taxonomic differences. Conclusions: Tumor-colonizing microbiota differ markedly between EOCRC and LOCRC in H/L patients, with late-onset tumors exhibiting substantially greater microbial richness and taxonomic complexity. Despite these compositional differences, microbial metabolic functions remain largely conserved, supporting the concept of functional redundancy within the colorectal tumor microenvironment (TME). Although exploratory, this proof-of-concept study provides one of the first characterizations of intratumoral microbiota in H/L EOCRC and establishes a foundation for larger multi-omics investigations aimed at identifying microbiome-based biomarkers and therapeutic targets for precision oncology.

Blood banks represent highly controlled healthcare environments where microbiological surveillance has traditionally focused on blood products rather than environmental microbial reservoirs. Despite their critical role in transfusion safety, the ecology of surface-associated microorganisms and the persistence traits that enable their long-term survival remain poorly understood. Here, we combined scanning electron microscopy, culture-based microbiology, phenotypic characterization, MALDI-TOF mass spectrometry, and whole-genome sequencing to investigate whether surfaces within a public blood bank facility constitute reservoirs of environmentally derived bacteria with enhanced persistence potential. Samples collected from a public blood bank in Tucuman, Argentina yielded 37 culturable bacterial isolates, predominantly Gram-positive environmental taxa together with a limited number of opportunistic Gram-negative species. More than 30% of the isolates exhibited multidrug resistance, while several strains displayed strong biofilm formation, amyloid-like fiber production, motility, and hemolytic activity, indicating multiple phenotypic strategies associated with long-term surface persistence. Whole-genome sequencing of six representative isolates confirmed species identity, identified genes related to antimicrobial resistance, adhesion, biofilm formation, stress adaptation, and cytotoxicity, and revealed frequent genotype-phenotype discordance, highlighting the importance of integrating genomic and phenotypic analyses. Notably, one isolate exhibited less than 92% average nucleotide identity with publicly available genomes, suggesting the presence of a previously undescribed environmental species. Thus, blood bank surfaces function as selective ecological niches favoring bacteria with persistence-associated traits rather than simply reflecting contamination from blood products. These microorganisms may constitute latent biosafety hazards if environmental barriers fail, particularly in facilities handling biological materials intended for vulnerable patients. Our results support the incorporation of integrated bioimaging, phenotypic characterization, and genome-resolved environmental surveillance into infection prevention strategies and transfusion biosafety programs within a One Health framework.

Histidine-rich protein 2 (HRP2)-based rapid diagnostic tests (RDTs) are central to malaria case management in Africa but fail when Plasmodium falciparum parasites lack the pfhrp2 or pfhrp3 genes. Widespread deletions have been reported in Eritrea, Ethiopia, and Djibouti, yet no systematic data have been available from Somalia. Between May and October 2023, we collected 7148 dried blood spot (DBS) samples from patients with suspected malaria attending eight health facilities across seven regions in Somalia. Field HRP2/pan-lactate dehydrogenase (LDH) RDTs and microscopy were performed, and DNA was extracted from 301 RDT-positive and 173 RDT-negative DBS samples. A multiplex quantitative PCR assay targeting pfldh, pfhrp2, and pfhrp3 was used to identify deletions in pfldh-positive samples lacking pfhrp2 or pfhrp3 amplification, with mixed infections inferred from delta cycle threshold ({Delta}Ct) differences. Of 474 analysed samples, 301 (4.2%, 95% CI 3.7-4.7) were RDT or microscopy positive, and 159 (33.5%) were confirmed pfldh-positive by qPCR. Among these, six (3.8%, 95% CI 1.4-8.1) carried pfhrp2 deletions and 59 (37.1%, 95% CI 29.6-45.1) carried pfhrp3 deletions. Eleven infections (6.9%, 95% CI 3.5-12.1) produced discordant RDT outcomes, HRP-/LDH+ or RDT-negative despite pfldh positivity. Deletions were most frequent in Dolow, Luq, and Bosaso. A single isolate carried the pfk13 R622I mutation, confirming the first report of the emergence of an artemisinin partial resistance-associated in Dolow, Gedo region, Somalia. Pfhrp2/3 deletions causing false RDT results remain low in Somalia and the confidence interval overlaps with the 5% policy threshold for changing RDTs, indicating uncertainty that warrants larger-scale assessment. Pfhrp3 deletions are widespread and compromise the diagnostic redundancy of HRP2-based tests. Most deletion-carrying parasites remain detectable through the pan-LDH line, minimising immediate clinical risk but leading to systematic misclassification of P. falciparum as non-falciparum malaria. These findings support the continued use of HRP2/Pan-LDH RDTs but highlight high risk areas and emphasise the need for periodic and expanded molecular surveillance for prevalence trends to guide timely future diagnostic policy.

Background and objectives Spontaneous bacterial peritonitis (SBP) is a life-threatening complication of cirrhosis with ascites, carrying one- and two-year mortality rates exceeding 70% and 80%, respectively. Fluoroquinolone prophylaxis is the cornerstone of SBP prevention. Real-world longitudinal data on prescribing practices and clinical outcomes from Indian tertiary care centers are sparse. We aimed to evaluate fluoroquinolone prescribing patterns, guideline adherence, and six-month clinical outcomes in SBP patients at a tertiary academic center in North India. Methods This was a pre-specified sub-analysis of a 15-month analytical longitudinal study at AIIMS Rishikesh. Adults (age >/=18 years) admitted with SBP and initiated on fluoroquinolone prophylaxis were enrolled consecutively and followed for six months. Prescribing practices were compared against EASL and AASLD recommendations. The primary outcome was the rate of guideline-directed prescribing. Secondary outcomes included clinical cure at discharge, six-month cure, relapse, regimen modification, adverse drug reactions, and treatment compliance. Categorical variables were compared by Fisher's exact test or chi-squared test (SPSS). Results Forty-eight SBP patients were included (mean age 44.75 +/- 11.94 years; 85.4% male). Guideline-directed fluoroquinolone prophylaxis was prescribed to all patients (100%). Norfloxacin 400 mg once daily was predominant (85.4%), followed by levofloxacin (10.4%) and moxifloxacin (4.2%). Cure at discharge was 85.4%. At six months, 64.6% maintained sustained cure and 22.9% relapsed. Regimen modification occurred in 22.9%, most commonly antimicrobial substitution. Nausea was the only adverse drug reaction (4.8%). Treatment compliance was 73.8%. No patient underwent therapeutic drug monitoring. Conclusions Fluoroquinolone prescribing for SBP prophylaxis at AIIMS Rishikesh was fully concordant with standard guidelines. Despite complete adherence, a relapse rate of 22.9% and frequent regimen modification underscore the limitations of long-term fluoroquinolone prophylaxis, likely reflecting emerging quinolone resistance. Strengthening antimicrobial stewardship is essential to sustain prophylaxis effectiveness in Indian tertiary care settings.

Abstract Background and Objective: To investigate the efficacy of a new, proprietary high-resistance potato starch as a prebiotic in comparison to inulin and a control. Methods: In this prospective study, an intervention of 9 g of resistant potato starch (RPS, Potatodaat), inulin, or accessible corn starch was given to participants with mild to moderate indigestion for 30 days. Short chain fatty acid (SCFA) levels, changes to the gut microbiome, and changes in clinical symptoms of indigestion were assessed as primary outcomes. Results: Subjects in the RPS (n = 22), inulin (n = 23), and accessible corn starch (n = 22) groups demonstrated similarity in age, sex, and baseline parameters. At 30 days, the groups experienced 21.1%, 6.29%, and 9.15% increases in stool butyrate, respectively. Clinical symptoms like indigestion and flatulence showed greater improvement with the use of RPS compared to the other two groups. Conclusion: Consumption of high resistance potato starch helps improve stool SCFA levels along with clinical symptoms related to digestion, showing its better prebiotic potential as compared to inulin and accessible corn starch. The new high-resistance potato starch can be considered an effective replacement for inulin.

Background: Urinary tract infection (UTI) is the most common secondary condition among people with spinal cord injury/disease (SCI/D). Intravesical Lacticaseibacillus rhamnosus GG (LGG) is an antibiotic-sparing approach to managing urinary symptoms. Objective: Determine the optimal number of doses of intravesical LGG for urinary symptom reduction. Design: Prospective, randomized, two-arm dosing trial. Setting: National recruitment with a local subsample providing urine samples in Washington, DC, USA. Participants: Adults with SCI/D and neurogenic lower urinary tract dysfunction (NLUTD) who use intermittent catheterization (IC); 177 enrolled and randomized (intention-to-treat), with 76 compliant instillers (39 low-dose, 37 high-dose) in the per-protocol analytic sample. Interventions: Two (2 doses/24 hours) or four (4 doses/36 hours) intravesical LGG regimens, self-initiated in response to cloudier or malodorous urine per the Self-Management Protocol using Probiotics (SMP-Pro). Main Outcome Measures: Primary: proportion achieving [&ge;]20% reduction on the Urinary Symptom Questionnaire for Neurogenic Bladder-Intermittent Catheter version (USQNB-IC). Secondary: urinary biomarkers (leukocyte esterase, nitrite, white blood cells, urinary neutrophil gelatinase-associated lipocalin [uNGAL]) and standard urine culture (SUC) in a local subsample. Results: By Day 2, 57.9% (63.8% low-dose; 51.2% high-dose) achieved [&ge;]20% total symptom reduction; high-dose success rose to 70.0% by Day 4. Thirty percent of high-dose participants did not respond at either time point and could not be distinguished from responders by demographics or urine biomarkers. Urinary biomarkers and SUC were unchanged pre- to post-instillation. No serious adverse events were adjudicated as attributable to intravesical LGG by an independent Data Safety Monitoring Board (DSMB). Conclusions: A two-dose course of intravesical LGG yields clinically meaningful symptom improvement in the majority of people with SCI/D and NLUTD who use IC; four doses benefits a meaningful subgroup of two-day non-responders, while a small cohort remains nonresponsive. These results provide preliminary dosing guidance and support progression to a definitive trial.

The increasing deployment of artificial intelligence (AI) assistive systems across healthcare, education, and organisational domains necessitates a deeper understanding of dispositional factors shaping trust and acceptance. This study investigated the Big Five personality traits as predictors of trust in and acceptance of AI assistive systems among a large adult sample (N = 380) in Makurdi Benue State. Anchored in the Technology Acceptance Model (TAM) developed by Davis (1989), the study examined both direct and indirect pathways linking personality traits to AI acceptance through trust. Participants completed standardised measures of the Big Five Inventory, Trust in AI Scale, and AI Acceptance Scale. Data were analysed using structural equation modelling (SEM) with maximum likelihood estimation. The hypothesised model demonstrated good fit indices (CFI = .84, TLI = .82, RMSEA = .05). Openness to experience ({beta} = .34, p < .001) and agreeableness ({beta} = .27, p < .01) significantly predicted trust in AI systems, which in turn strongly predicted AI acceptance ({beta} = .62, p < .001). Neuroticism negatively predicted trust ({beta} = -.29, p < .001), while conscientiousness showed a modest positive direct effect on acceptance ({beta} = .18, p < .05). Extraversion was not a significant direct predictor but exerted an indirect effect through trust. Mediation analysis confirmed that trust significantly mediated the relationship between personality traits and AI acceptance. The findings underscore the centrality of dispositional traits in shaping technological trust formation and highlight the psychological architecture underlying human AI interaction. These results contribute to social psychological theory and provide empirical guidance for designing personality sensitive AI systems to enhance user adoption and sustained engagement.

Background: Early detection of pancreatic ductal adenocarcinoma (PDAC) is critical. While faecal elastase-1 (FE-1) is a standard clinical marker for pancreatic function, its diagnostic accuracy for malignancy is limited. We sought to identify plasma metabolites that enhance FE-1 performance in symptomatic "at-risk" patients. Methods: Using the DEPEND cohort (CRUK C45617/A29908), plasma metabolomics was performed on patients with resectable PDAC (n=23) and healthy volunteers (n=24). Predictive modelling included feature selection and cross-validation, with further validation in an independent external cohort. Results: Citrulline was identified as significantly depleted in PDAC patients across discovery and validation cohorts. In isolation, Citrulline achieved an AUC of 0.86 (internal) and 0.88 (external validation). Standalone FE-1 demonstrated an AUC of 0.67. However, combining Citrulline and FE-1 significantly improved diagnostic performance, achieving a combined AUC of 0.96. Stratification revealed distinct metabolomic signatures associated with poorly differentiated tumours, suggesting a link to histological grade. Conclusions: Integrating Citrulline with FE-1 testing substantially improves PDAC detection in symptomatic patients. This non-invasive panel offers high diagnostic potential, though prospective validation is required to establish clinical cut-offs for routine practice.

Background and Aims The optimal treatment for first episodes and first recurrences of Clostridioides difficile infections (CDI) is unknown and there is emerging evidence for pulse and taper (P-T) regimens. Therefore, we sought to estimate the relative efficacy of treatment options. Methods MEDLINE and CENTRAL were searched from database inception to May 21, 2025 and unpublished conference abstracts were searched from recent infectious disease conferences. RCTs on the treatment of first episodes or first recurrences of CDI comparing fixed-dose or P-T regimens of fidaxomicin or vancomycin were included. The primary and secondary outcomes were 40- and 56-day CDI recurrence, respectively. A random-effects network meta-analysis on the risk ratio (RR) scale was conducted using a standard regimen (10-14 days) of vancomycin as the comparator. Treatments were ranked using the surface under the cumulative ranking curve (SUCRA). Results 8 RCTs were included comprising a total of 2181 patients. For 40-day recurrence, fidaxomicin P-T had the highest probability of ranking best (RR=0.10, 95%Confidence Interval [95%CI]=0.10-0.49, SUCRA=1.00), followed by vancomycin P-T (RR=0.49, 95%CI=0.32-0.76, SUCRA=0.61), fixed-dose fidaxomicin (RR=0.61, 95%CI=0.49-0.76, SUCRA=0.39), and, finally, fixed-dose of vancomycin (SUCRA=0.00). The treatments ranked in the same order for 56-day recurrence, though only 3 RCTs reported on this timepoint. Conclusion Vancomycin P-T, fidaxomicin P-T, and fixed-dose fidaxomicin were all superior to a fixed-dose vancomycin. Head-to-head comparative effectiveness RCTs are needed to quantify their relative effect sizes of and impact on long-term prevention of recurrent CDI.

Background: Oral care is a critical nursing intervention for mechanically ventilated patients in intensive care units because it reduces oral microbial colonization and contributes to the prevention of ventilator-associated pneumonia, a major cause of morbidity, prolonged hospitalization, and increased healthcare costs among critically ill patients. Despite the availability of evidence-based guidelines, gaps in nurses knowledge and inconsistent implementation of oral care practices remain challenges, particularly in low- and middle-income settings. Objective: This study aimed to assess the level of knowledge among intensive care unit nurses regarding oral care for mechanically ventilated patients at Tenwek Hospital, Kenya, determine factors influencing knowledge, and examine the relationship between nurses knowledge and selected demographic and professional characteristics. Methods: An analytical cross-sectional study design was employed. The study was conducted among intensive care unit nurses at Tenwek Hospital. A sample of 38 nurses was selected from a target population of 60 intensive care unit nurses using simple random sampling. Data were collected using a structured self-administered questionnaire assessing socio-demographic characteristics, knowledge of evidence-based oral care practices, awareness of guidelines, and factors influencing knowledge. Data were analyzed using descriptive statistics, chi-square tests, Pearson correlation, and logistic regression, with statistical significance set at probability value less than 0.05. Results: Thirty-five nurses participated, yielding a response rate of 92.1 percent. The findings demonstrated generally high knowledge levels regarding oral care practices for mechanically ventilated patients. Most nurses correctly identified recommended oral care frequency (88.6 percent), oral assessment before care (91.4 percent), suctioning before and after oral care (94.3 percent), and the role of oral care in preventing ventilator-associated pneumonia (97.1 percent). However, knowledge gaps were identified in areas such as toothbrushing practices and documentation of oral care procedures. Training, continuing professional education, availability of guidelines, workload, resources, supervision, and teamwork were identified as important factors influencing knowledge. The findings revealed that professional qualification (probability value equal to 0.02), intensive care unit experience (probability value equal to 0.030) and formal oral care training (probability value equal to 0.021) were significantly associated with nurses knowledge of oral care practices. Conclusion: Intensive care unit nurses at Tenwek Hospital demonstrated adequate knowledge of evidence-based oral care practices for mechanically ventilated patients. However, targeted educational interventions are required to address identified gaps and strengthen standardized oral care delivery. Continuous professional development, consistent use of guidelines, supportive supervision, and adequate resource provision are recommended to enhance patient safety and reduce preventable intensive care unit complications such as ventilator-associated pneumonia. Keywords: Intensive care unit nurses; Oral care; Mechanically ventilated patients; Ventilator-associated pneumonia; Nursing knowledge; Evidence-based practice

Introduction: Group interpersonal psychotherapy may improve outcomes beyond depressive symptoms, but evidence on functioning, social support, and household welfare remains limited. We examined these outcomes using mixed methods in a pilot cluster-randomized controlled trial of a six-week intervention in rural Uganda. Methods: Twenty-four villages were randomized to group interpersonal psychotherapy or enhanced care as usual. Eligible participants were female, aged at least 13 years, with Patient Health Questionnaire-9 scores of 10 or more. Outcomes were assessed at baseline, two weeks, and three months after treatment. Regression models used village-clustered standard errors. Exploratory sensitivity analyses compared controls with 33 intervention participants assessed independently of facilitators and after an honesty and confidentiality prompt. Fourteen interviews and three focus group discussions with 30 intervention participants were analysed thematically and integrated by outcome domain. Results: Of 292 randomized participants, 263 completed the three-month assessment. Intervention participants had lower anxiety scores than controls at three months (mean difference -7.18; p<0.001), higher subjective wellbeing (mean difference 3.70; p<0.001), lower disability scores (mean difference -1.01; p<0.001), greater perceived social support (difference 23.4 percentage points; p<0.001), and more meals reported for children in the previous 24 hours (mean difference 0.62; p<0.001). Household food insecurity was lower in the full-sample analysis (difference -23.3 percentage points; p=0.008), but not in the exploratory sensitivity analysis (difference 1.5 percentage points; p=0.883). Qualitative accounts described recovery as restored capacity to work, manage relationships, care for children, and respond to hardship despite material constraints. Conclusions: These preliminary findings suggest that group interpersonal psychotherapy may improve outcomes beyond depressive symptoms, although household welfare findings were less consistent. Larger trials with independent outcome assessment and longer follow-up are needed. Trial registration: The trial was retrospectively registered with the Pan African Clinical Trials Registry (PACTR202606549854263) on 29 June 2026.

Background: Antimicrobial resistance (AMR) disproportionately affects low- and middle-income countries (LMICs) such as Pakistan, where obstetric and gynaecological (OBGYN) patients carry high antibiotic exposure. Specialty-specific drug utilization data with concurrent stewardship audit remain scarce. This study evaluated antibiotic prescribing patterns, consumption metrics, and antimicrobial stewardship program (AMS) compliance in OBGYN inpatients at a public sector tertiary care hospital. Methods: A prospective cross-sectional study was conducted in OBGYN wards of Dow University Hospital, Karachi, from 1 September to 31 October 2025. Women receiving [&ge;]1 systemic antibiotic were included. Daily AMS rounds were conducted by an Infectious Diseases physician and pharmacist. Antibiotic consumption was measured as Defined Daily Doses (DDD) and Days of Therapy (DOT) per 1,000 patient-days (total = 821). Antibiotics were classified by WHO AWaRe (2023) framework. Results: Of 812 total admissions, 278 patients (34.2%) received [&ge;]1 antibiotic and were enrolled (205 obstetric, 73 gynaecological), generating 636 prescriptions (mean 2.29/patient). Surgical prophylaxis was the predominant documented indication (213, 33.5%); 65.1% carried no documented indication. By AWaRe classification, 53.6% were Access-group and 46.1% Watch-group. Ceftriaxone (38.4%) and metronidazole (36.8%) together represented 75.2% of prescriptions. Combined DDD/1,000 patient-days was 1,758.6 and DOT/1,000 patient-days was 1,852.7. AMS compliance was 0%. Conclusions: This study documents high antibiotic prescribing burden, near-universal documentation failure, and zero AMS compliance in OBGYN inpatients at a Pakistani public sector hospital. The predominance of Watch-group antibiotics and undocumented surgical prophylaxis highlights structural stewardship gaps. Findings support urgent need for institutional OBGYN antibiotic guidelines and structured pharmacist-led AMS programs.

Background: Children and young people (CYP) with intellectual disability (ID) frequently have co-occurring neurodevelopmental (ND) and mental health (MH) difficulties. While copy number variants (CNVs) are identified as an important aetiology of ID, it is unclear whether and how CNV risk scores predict ND and MH characteristics within the CNV-associated ID population. Methods: We analysed data from the UK-based IMAGINE-ID cohort of CYP (aged 4-19 years) with ID and clinically-reported CNVs (N = 1,640). CNVs were annotated with Gencode 19 in ENSEMBL to calculate CNV risk scores, including summed probability of loss-of-function intolerance (pLI) and dosage sensitivity. Multivariate regression models examined the prediction of CNV variables and inheritance on ND and MH characteristics, assessed via the Development and Well-Being Assessment (DAWBA). Post-hoc analyses explored CNV variable stratification (lower vs. higher range pLI). Results: Higher summed pLI scores (indexing CNV genes' intolerance to loss of function) unexpectedly predicted fewer MH difficulties and a lower likelihood of ND diagnoses, even after accounting for demographic factors and CNV inheritance. Post-hoc analyses identified a threshold effect. Within the lower pLI range, higher pLI scores were associated with greater MH difficulties, consistent with findings from population-based samples. In contrast, within the higher pLI range, higher pLI scores were associated with fewer MH difficulties (among individuals more likely to have severe ID). Conclusion: These findings challenge the assumption that CNV genomic "risk scores" universally predict ND and MH difficulties. Instead, within CNV-associated ID, complex relationships exist between CNV risk scores, inheritance and phenotypes. These insights emphasise the necessity of integrating genomic results with familial and developmental context to understand individual vulnerabilities and support needs.

Background Bloodstream infections are a major cause of mortality, yet the primary testing method, blood cultures, have low positivity (<10%) and turnaround times of 24 - 48 hours. Many are taken from patients at low risk of infection, while some bloodstream infections are diagnosed late or missed entirely. We aimed to develop and externally validate machine learning models to improve targeting of blood culture testing. Methods In this retrospective cohort study, we used routinely collected clinical and laboratory data available around culture collection from a large multi-site NHS trust (Oxford University Hospitals; Infections in Oxfordshire Research Database), between 1 January 2016 and 17 March 2025. All blood cultures taken from adults and children were included. XGBoost models were trained to predict pathogenic blood culture positivity using a temporal split (training before 1 January 2024; held-out test thereafter). External validation used emergency department data (between 1st May 2019 and 30th April 2024) from University College London Hospitals. An additional analysis examined blood culture reallocation towards the highest-risk untested admissions. Findings 294,064 cultures were included (positivity 5.6%). In the temporal hold-out test set (n=46,339), AUROC (Area Under the Receiver Operating Characteristic) was 0.853 (95% CI 0.846 - 0.860), rising to 0.876 in emergency department patients, and the model was well calibrated (slope 1.046). In external validation (n=37,326), AUROC was 0.847 (95% CI 0.839 - 0.856) with preserved calibration. In a simulated resource-neutral reallocation, replacing the 10,000 lowest-risk sent cultures with the highest-risk untested emergency admissions yielded 627 additional positive cultures (28.3% relative increase in yield). Performance was reduced when restricted to data available at the point of culture collection (AUROC 0.769, 95% CI 0.760 - 0.779). Interpretation An externally validated, well calibrated machine learning model built from broadly available, routinely collected data could improve blood culture yield without increasing testing volume, supporting resource-neutral diagnostic stewardship across NHS sites.

Executive function (EF) deficits are central features of schizophrenia and strongly influence long-term functional outcomes. Conventional cognitive assessments often lack ecological validity and cultural relevance. This study introduces the Luk Chup Augmented Reality (LCAR) tool a video guided, clay modeling task delivered through wearable AR that integrates culturally familiar activity with realtime neurophysiological monitoring. Thirty individuals diagnosed with schizophrenia (mean age = 38.9, SD. = 7.15 years) completed a series of modeling and memory tasks using LCAR while undergoing quantitative EEG (QEEG). Task duration and theta/beta power were analyzed across procedural and color shape memory phases. Memory phases took significantly longer to complete and were associated with decreased lateral prefrontal theta and increased frontal midline theta activity (Fz, Cz), indicating higher EF demand. A repeated-measures ANOVA revealed significant condition, site, and interaction effects on theta power. The LCAR tool shows promise as a culturally grounded, dual-mode assessment of EF in schizophrenia. It offers a novel integration of performance-based and neurophysiological metrics that may inform future interventions in psychiatric rehabilitation.

ABSTRACT Background Breastfeeding practices vary across populations and are influenced by a range of social-cultural, and healthcare-related factors. Evidence on early initiation of breastfeeding (EIBF) and exclusive breastfeeding (EBF) among indigenous communities in India remains limited. This study aimed to identify factors associated with EIBF and EBF among Bhumij mothers in eastern India. Method A community-based cross-sectional study of 306 Bhumij mother-child pairs was conducted in Purulia, West Bengal, India (2023-2024). Socio-demographic and breastfeeding-related data were collected through structured interviews and analysed using bivariate and multivariable logistic regression. Results Almost all children (99.3%) had been breastfed; 72.9% initiated breastfeeding within one hour of birth, and 65.2% were exclusively breastfed during the first six months. In multivariable analyses, mode of delivery, pre-lacteal feeding, and colostrum discarding were significantly associated with EIBF. Maternal knowledge of EBF was positively associated with EBF practice (adjusted OR: 6.14; 95% CI: 2.80-13.46). Maternal perception of milk production was also associated with EBF, with higher odds observed among mothers reporting adequate (adjusted OR: 6.12; 95% CI: 3.00-12.48) or profuse (adjusted OR: 7.71; 95% CI: 2.56-23.25) milk production compared with those reporting insufficient milk production. Conclusion This study provides evidence on breastfeeding practices among Bhumij mothers and identifies healthcare-related, maternal, and caregiving factors associated with EIBF and EBF. The findings contribute to the limited literature on infant feeding practices among indigenous populations in India and may inform breastfeeding promotion and nation-wide maternal-child health programmes in similar settings.

Background Oral care is a critical nursing intervention for mechanically ventilated patients in intensive care units (ICUs) and plays an important role in preventing ventilator-associated complications. However, variability in nurses' competency in oral care remains a concern, particularly in resource-limited settings. Objective To assess ICU nurses' competency in providing oral care to mechanically ventilated patients and determine factors associated with competency at Tenwek Hospital, Kenya. Methods An analytical cross-sectional study was conducted among ICU nurses at Tenwek Hospital. A total of 38 nurses were invited, and 35 participated, yielding a response rate of 92.1%. Data were collected using a structured questionnaire and an observational competency checklist. Descriptive statistics and inferential analysis, including chi-square tests and binary logistic regression, were performed using SPSS version 30. Statistical significance was set at p<0.05. Results ICU nurses demonstrated generally high competency in key oral care practices, including use of personal protective equipment (100%), suctioning before and after oral care (91.4%), and oral assessment (80.0%). However, gaps were identified in documentation of oral care (62.9%) and adherence to standardized protocols (65.7%). Formal oral care training was significantly associated with competency (OR=5.63, 95% CI: 1.78-17.81, p=0.002), as were professional qualification (p=0.030) and ICU experience (p=0.021). In multivariable analysis, oral care training (OR=3.01, p=0.006), ICU experience (OR=2.85, p=0.015), and availability of guidelines (OR=2.17, p=0.047) were independent predictors of competency. Conclusion ICU nurses at Tenwek Hospital demonstrate satisfactory competency in oral care for mechanically ventilated patients, although gaps remain in documentation and protocol adherence. Strengthening training, guideline availability, and institutional support systems is essential to improve consistency and quality of oral care practice. Keywords Intensive care unit; oral care; nursing competency; mechanically ventilated patients; ventilator-associated pneumonia; Kenya.

BACKGROUND: Artificial intelligence (AI) medical scribes rely on speech-to-text (STT) models for transcription. Evaluations of STT models in non-English settings remain scarce. We benchmarked ten STT models on medical consultations from Latin American (LatAm) Spanish and assessed whether fine-tuning improves transcription accuracy. METHODS: Ten YouTube videos depicting medical consultations. Human transcriptions were the ground truth. Five open-source models were evaluated: Whisper Large, Whisper Large v3, Whisper Large v3 Turbo, Voxtral Mini 3B, and Canary 1B v2; and so were five close-source models: gpt-4o-transcribe, gpt-4o-mini-transcribe, gemini-2.5-pro, Eleven Labs, and Assembly AI. Whisper Large v3 was fine-tuned. One video was withheld from training. Performance assessed using Word Error Rate (WER), Character Error Rate (CER), BLEU Score, ROUGE-L, BERT Score, and Semantic Similarity on the one withheld video. RESULTS: None of the fine-tuning iterations outperformed the vanilla Whisper Large v3. With the withheld video, Gemini-2.5-pro was the close-source model with the best performance in four of six metrics. In comparison to the close-source models, the fine-tuned model never outperformed the other models (withheld video); conversely, in comparison to the close-source models, the fine-tuned model showed better performance across metrics, for instance: BLEU score (63% vs to 58% for the second-ranking model), BERT (89% vs to 86%), and semantic similarity (89% vs to 83%), CER (19% vs 20%). CONCLUSIONS: Whisper Large v3 and its fine-tuned variant are the best open-source STT models for transcribing medical conversations in LatAm Spanish. These findings provide an evidence base for developing AI medical scribes tailored to Spanish-speaking LatAm.