Antimicrobial Agents and Chemotherapy

Numerous factors may influence the optimal rollout of new gonococcal antibiotics. We compared eight rollout strategies using a gonorrhea transmission model and ranked strategies by the number of gonococcal infections and clinically useful antibiotic lifespan. Rankings were most sensitive to the starting ceftriaxone resistance prevalence and screening frequency.

Urinary tract infections (UTIs) are among the most common infectious diseases worldwide, with Escherichia coli being the predominant uropathogen. The increasing prevalence of extended-spectrum beta-lactamase (ESBL)-producing strains and their association with fluoroquinolone resistance pose a significant challenge to empirical therapy, particularly in community settings. The aim of this study was to determine the epidemiology and predictive factors associated with ESBL-producing E. coli and its concomitant fluoroquinolone resistance in community-acquired clinical isolates. A retrospective cross-sectional study was conducted analyzing 244 clinical E. coli isolates. Demographic and microbiological data were collected, including age, sex, sample type, and antibiotic susceptibility. Associations between variables and ESBL production were assessed using Pearsons chi-squared test, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Of the isolates, 165 (68%) were ESBL-producing. A significant association was observed between age group and ESBL production (p < 0.001), with the highest frequency in the 20-39 age group. Most ESBL-positive isolates were obtained from women (73%), although odds ratio (OR) analysis suggested a non-significant trend toward a higher probability in men (OR = 1.29; 95% CI: 0.72-2.31). High rates of fluoroquinolone resistance were identified among the ESBL-producing isolates, with 30% resistance to levofloxacin and 35% to ciprofloxacin (p < 0.001). Urine samples showed the highest concentration of ESBL-positive isolates, with a significant association between sample type and resistance (p < 0.001). The high prevalence of ESBL-producing E. coli and its concomitant resistance to fluoroquinolones highlight a critical challenge for the empirical treatment of urinary tract infections in Mexico, underscoring the need to strengthen antimicrobial use management and local surveillance strategies.

BackgroundThe Toto Bora trial tested whether a course of azithromycin reduced rates of re-hospitalization or death in the 6 months following hospitalization among Kenyan children. We hypothesized that azithromycin would reduce enteric bacteria and increase carriage of macrolide resistance in the subsequent 3 months. MethodsKenyan children (1-59 months) hospitalized and subsequently discharged for non-traumatic conditions provided fecal samples before and 3 months after randomization to a 5-day course of azithromycin or placebo. Quantitative PCR identified enteropathogens and AMR-conferring genes in fecal samples. Generalized estimating equations assessed the impact of the randomization arm on pathogen and resistance gene detection, accounting for baseline presence and site. ResultsAmong 1,393 baseline stools, 12.4% had at least one bacterial enteropathogen, 94.7% had at least one macrolide-resistance gene, and 92.6% had at least one beta-lactamase-resistance gene identified. At month 3, children randomized to azithromycin had a 6.1% higher likelihood of carrying a macrolide resistance gene compared to placebo (adjusted prevalence ratio [aPR], 1.06; 95% CI, 1.04-1.08; P<0.001). Specifically, azithromycin randomization was associated with a higher relative prevalence of erm(B) (aPR, 1.09 [95% CI, 1.04-1.15]; P=0.001), erm(C) (aPR, 1.23 [95% CI, 1.14-1.31]; P<0.001), msr(A) (aPR, 1.14 [95% CI, 1.04-1.25]; P=0.007), and msr(D) (aPR, 1.07 [95% CI, 1.03-1.11]; P=0.001). There was no difference in overall bacterial pathogen prevalence (18.9% vs 17.3%) between randomization arms, but a slightly lower proportion of children had Shigella after randomization in the azithromycin arm (3% vs. 5%, aPR, 0.79 [95% CI, 0.62, 1.01]; P=0.063). InterpretationAzithromycin at hospital discharge was associated with higher carriage of macrolide-resistance-conferring genes in the post-discharge period compared with placebo, without significant declines in enteric pathogen carriage other than modest changes to Shigella. The potential benefits and risks of empiric azithromycin need to be considered, as children are increasingly exposed to this broad-spectrum antibiotic.

ObjectivesAntimicrobial resistance (AMR) in Gram-negative pathogens is driven by complex and coordinated molecular mechanisms that remain incompletely characterized. This study integrated phenotypic, genomic, and quantitative proteomic analyses to characterize multidrug-resistant (MDR) and extensively drug-resistant (XDR) Gram-negative bacteria circulating in an intensive care unit (ICU) in Northeastern Brazil. MethodsA total of 259 Gram-negative isolates collected between 2019 and 2021 underwent species identification, antimicrobial susceptibility testing, and targeted qPCR for resistance genes. Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa representing susceptible, MDR, and XDR phenotypes were selected for whole-genome sequencing and label-free quantitative proteomics. Differential protein abundance was assessed using Limma with |log2FC| > 1 and p < 0.05. ResultsK. pneumoniae (47%), A. baumannii (24%), and P. aeruginosa (21%) predominated. Carbapenem resistance reached 44%, 93%, and 61%, respectively, and MDR/XDR phenotypes occurred in >30% of isolates. Genomic analyses revealed dense resistomes with coexisting {beta}-lactamases (blaKPC, blaNDM, blaCTX-M, OXA) and widespread efflux systems. Proteomic profiling demonstrated phenotype-associated differences in outer membrane proteins, transport systems, regulatory proteins, and metabolic pathways. XDR isolates showed additional enrichment of envelope remodeling proteins, stress response mechanisms, and proteostasis-associated factors. ConclusionsMDR and XDR Gram-negative ICU pathogens exhibit coordinated resistance architecture characterized by accumulation of resistance genes and adaptive proteomic remodeling. Integrated multi-omics approaches provide mechanistic insight into antimicrobial resistance and support improved surveillance and therapeutic strategies. What is known?O_LIAntimicrobial resistance is a priority and a serious problem in global health, resulting in high rates of morbidity and mortality. C_LIO_LIKlebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa are on the World Health Organizations (WHO) priority list as major causes of morbidity and mortality worldwide. C_LIO_LIClassical characterization of susceptibility and resistance phenotypes does not capture the complexity of antimicrobial resistance and hampers effective control measures and actions to minimize the evolutionary dynamics of resistance in these bacteria. C_LI What is new?O_LIThe study characterizes the phenotypic pattern of antimicrobial susceptibility, the presence and sequencing of the resistome and virulome, and analyzes the label-free quantitative proteome of susceptible, MDR, and XDR phenotypes in strains of K. pneumoniae, A. baumannii, and P. aeruginosa circulating in hospital ICUs in Brazil. C_LIO_LIMDR and XDR gram-negative phenotypes are associated with a dense resistome, with widespread dissemination of beta-lactamase genes (bla_KPC, bla_NDM, bla_CTX-M, and OXA) and RND-type (MEXs) and acrAB-tolC efflux pumps, without changes in virulence genes. C_LIO_LIProteomic analysis demonstrated increased production of beta-lactamases, components of efflux pump systems, outer membrane protein synthesis, protection for oxidative stress mechanisms, proteins for iron acquisition, and systemic regulators. XDR strains additionally showed enhanced remodeling of the cell envelope, activation of proteostasis, and metabolic adaptation. C_LI

Phage therapeutics are re-emerging as adjuncts or alternatives to antibiotics and their clinical translation will be enhanced with production methods that minimise downstream processing. We evaluated whether an endotoxin-reduced E. coli strain developed for production of recombinant proteins, ClearColi(R), can serve as a useful, safe phage production host without compromising yield and whether targeted receptor complementation can expand its utility. The parent strain BL21(DE3), and its lipid A modified derivative, ClearColi(R), were compared with respect to infection and generation of phage. Across a panel of 31 phage, a similar host range was observed between BL21(DE3) and ClearColi(R). To expand host range ompC was genetically engineered into the chromosome of ClearColi(R), thereby adding OmpC-dependent phage to its production capacity. Production metrics were broadly comparable between the hosts; efficiency of plating and final titres for representative phage were not significantly different; burst size varied by phage but without consistent host bias. Endotoxin activity in ClearColi(R)-propagated lysates was reduced by over 1000-fold relative to BL21(DE3), reaching the low hundreds of endotoxin units (EU) versus hundreds of thousands for BL21(DE3). Intravesical administration of ClearColi(R)-derived phage (LUC4) into pigs elicited no clinical abnormalities and no significant increases in circulating cytokines up to 48 hours after administration. ClearColi(R) allows efficient production of diverse phage with low endotoxin, reducing the requirement for downstream processing. Although its minimal LPS reduces its capacity for producing some LPS-dependent phage and its growth is slower than BL21(DE3), requiring optimisation for maximal phage titre, the safety and simplified manufacturing process support further development of endotoxin modified strains for phage production. Impact statementAntibiotic resistance is a current global problem and treatments based on phage and phage products already have a proven track record with particular bacterial infections, especially in the urinary tract. While progress is being made on in vitro phage synthesis, large scale bacteriophage preparations require a bacterial host for production, consequently toxic components in the initial lysate need to be removed or significantly diluted for safe clinical use. This is a study of the potential to utilise an endotoxin-reduced E. coli strain, ClearColi(R), to produce safer phage therapeutics. Such endotoxin modified strains should minimise the processing steps required and reduce overall production costs of a phage preparation. The research demonstrates that the endotoxin-reduced strain was able to produce a wide range of phage and for studied examples at phage titres equivalent to the more toxic parent strain. We also show that the strain can be modified to increase its host range and confirm the very low endotoxicity of basic phage lysates produced by the strain. Replicating this process to engineer additional low-toxicity bacterial production strains will accelerate the development of safer, more cost-effective phage therapeutics.

BackgroundChemokine receptor type 5 (CCR5) is expressed on hepatic stellate cells (HSCs), which, together with fibroblasts, are major producers of extracellular matrix during liver fibrosis. Leronlimab is a humanized IgG4{kappa} monoclonal antibody that binds to CCR5. The objective of the present study was to evaluate the antifibrotic effects of leronlimab in three independent preclinical studies using two mouse models of liver fibrosis. MethodsIn STAM (Stelic Animal Model) model 1, leronlimab was administered at doses of 5 or 10 mg/kg/week for 3 weeks. STAM model 2 was conducted as a confirmatory study to validate the antifibrotic effect observed with the 10 mg/kg/week dose in STAM model 1. In a third study, a carbon tetrachloride (CCl)-induced liver fibrosis mouse model was used to evaluate leronlimab administered at 10 mg/kg/week for 3 weeks. An isotype-matched control antibody was included in all studies for comparison. Evaluations included liver enzymes and histological assessment of liver fibrosis. ResultsIn STAM model 1, leronlimab at 10 mg/kg/week significantly reduced fibrosis area compared with the isotype control (p = 0.0005). These findings were confirmed in STAM model 2 (p < 0.0001). Consistent antifibrotic effects were also observed in the CCl-induced liver fibrosis model (p = 0.0006). ConclusionsCollectively, these preclinical results demonstrate that CCR5 blockade by leronlimab is associated with a significant reduction of established liver fibrosis in multiple mouse models and support further evaluation of leronlimab as a potential therapeutic option, either as monotherapy or in combination regimens, for chronic liver diseases with fibrosis.

Bacillus paranthracis was formally defined as a species in 2017, after decades of carrying the name "emetic B. cereus" based on cereulide production and clustering within B. cereus sensu lato phylogenetic group III. Commonly associated with foodborne intoxication, reports rarely link B. paranthracis to non-foodborne clinical illness. As such, the new taxonomy and close resemblance of the name to the biothreat pathogen Bacillus anthracis cause confusion in diagnostic and public health settings. To address this issue, B. paranthracis clinical strains (n=20) from the CDC collection were tested with microbiological methods used for identification of B. anthracis and antimicrobial susceptibility testing. Some B. paranthracis phenotypes were similar to B. anthracis, however others were inconsistent across strains. Like B. anthracis: 3 strains tested capsule positive, 5 were non-hemolytic on blood agar, and 9 non-motile. All B. paranthracis strains were resistant to gamma phage lysis, which differentiated them from B. anthracis. Treatment regimens for B. paranthracis infections are not well established, as antimicrobial therapy is not indicated for emetic intoxication caused by B. paranthracis. Notably, six B. paranthracis strains had elevated minimal inhibitory concentrations to anthrax-recommended antibiotics: one for ciprofloxacin, three for doxycycline and tetracycline, and two for clindamycin. Rapid MinION sequencing was assessed for antimicrobial resistance detection prediction but had limited value when using PiMA v.1. These microbiological observations and susceptibility profiles of B. paranthracis expand our understanding of this pathogen, strengthening our ability to differentiate this bacterium from B. anthracis to improve diagnosis and patient outcomes. IMPORTANCEThis study describes in vitro characterization of 20 archived clinical strains of B. paranthracis, an opportunistic pathogen identified more frequently in recent reports. Our findings highlight phenotypic differences and similarities between B. paranthracis and B. anthracis using standard microbiological methods and drug susceptibility profiling. We also assess a rapid B. anthracis specific MinION long read genome sequencing workflow with B. paranthracis. This report highlights the overlapping morphological features shared by B. paranthracis and B. anthracis to improve future laboratory diagnosis and strengthen anthrax preparedness. This article will effectively reach an audience of public health professionals and microbiologists strengthening anthrax preparedness.

Abstract Background Timely diagnosis of tuberculosis and drug resistance remains a cornerstone of effective disease control. Multiplex open molecular platforms capable of simultaneously detecting Mycobacterium tuberculosis complex (MTBc), non-tuberculous mycobacteria (NTM), and resistance to first-line anti-tuberculosis drugs could streamline diagnostic pathways. Methods We conducted a laboratory-based evaluation of two multiplex real-time PCR assays (MTBc/NTM R-Gene and MTB-RIF/INH R-Gene) using 300 well-characterized samples, including 150 MTBc-positive culture isolates (including rifampicin-resistant, isoniazid-resistant, and drug-susceptible strains) and 150 MTBc-negative samples (50 NTM isolates and 100 mycobacteria-negative specimens). Composite reference standards included culture, MPT64 antigen testing, and line probe assay corroborated by phenotypic drug susceptibility testing for resistance profiling, with NTM speciation performed using a dedicated line probe assay. DNA extraction was performed using the QIAamp DNA Mini Kit (QIAGEN, Germany), followed by amplification on a real-time PCR platform according to manufacturer instructions. The diagnostic performance was assessed against composite reference standards. Results The analytical performance for detecting MTBc demonstrated 100% sensitivity and specificity (150/150). NTM detection showed 70.0% sensitivity (35/50) and a specificity of 100%, highlighting limitations in coverage of NTM species. Rifampicin resistance was detected with a sensitivity of 96.0% (48/50) and specificity of 100%, whereas isoniazid resistance detection was 100% sensitive and specific (50/50). Agreement with established reference standards was high ({kappa}=0.76-1.00) within this analytical context. Interpretation This analytical validation demonstrates that multiplex open real-time PCR assays can accurately and simultaneously detect MTBc, NTM, and rifampicin and isoniazid resistance using culture isolates. While these platforms offer potential advantages in flexibility and expanded resistance profiling, additional studies on clinical diagnostic accuracy, cost-effectiveness analyses, and operational feasibility are required to determine their practical utility and programmatic impact in high-burden settings

BackgroundAn upsurge in Streptococcus pyogenes infections 2022-2023 highlighted potential benefits of point-of-care tests (POCT) to support clinical pathways, prevent outbreaks, and optimise antibiotic use. ObjectivesWe conducted a pilot research study in a west London paediatric emergency department (ED) to determine whether a molecular POCT had potential to alter management in children who were also having a conventional throat swab taken for culture. MethodsChildren <16 years presenting to ED who had a throat swab requested by a clinician were invited to have a second swab taken for research purposes only. Clinical management was unaffected by the research swab result, which was processed using a molecular POCT that was not approved for use in the host NHS Trust. ResultsPrevalence of streptococcal infection was low during the study (May 2023-June 2025); swab positivity in symptomatic children was 12.8% (6/47). Overall, 38/49 (77.6%) participants who had throat swabs received antibiotics. Of those children recommended to receive antibiotics, 29/38 (76.3%) had a negative POCT. Mean time to reporting of positive throat swab culture results was 3.67 days (range 3-5 days) leading to occasional delay in treatment, although POCT identified positive results within minutes. ConclusionAntibiotic use was frequent and could be avoided or stopped by use of a rule out POCT in over three-quarters of children in the ED, if suspicion of S. pyogenes is the main driver for prescribing. POCT were easy to process and produced immediate results compared with culture, in theory enabling timely decision-making and avoiding treatment delay.

Gingival inflammation is associated with dysbiotic oral biofilms characterized by reduced nitrate-reducing capacity and diminished nitric oxide (NO) bioavailability. While dietary nitrate has been shown to influence oral microbial activity, the effects of sustained, localized nitrate delivery on oral biofilm ecology and gingival inflammation remain incompletely defined. In this randomized, double-blind, placebo-controlled trial, 30 adults with gingival bleeding were assigned to receive localized prebiotic nitrate (~0.989 mmol per dose) or placebo for 21 days. The primary outcome was mean bleeding on probing (mBOP). Secondary outcomes included modified Gingival Index (mGI), Quigley-Hein plaque index (QHPI), salivary nitrite (as a proxy for NO bioavailability), oral pH, and microbiome composition assessed by 16S rRNA gene sequencing. Prebiotic nitrate supplementation formulation delivered in a slow-release chewing gum significantly reduced mBOP (25.7% to 15.3%; p = 0.0002) compared to placebo chewing gum. Salivary nitrite levels and oral pH increased, indicating enhanced nitrate metabolism. Microbiome analysis demonstrated enrichment of nitrate-reducing taxa, including Rothia mucilaginosa and Neisseria spp., and a relative reduction in inflammation-associated genera such as Prevotella and Porphyromonas. Localized prebiotic nitrate formula delivered in a functional chewing gum was associated with reduced gingival inflammation and shifts in oral microbiome composition consistent with enhanced nitrate-reducing capacity critical in nitric oxide formation. These findings support a role for biofilm-directed nutritional modulation as a non-antimicrobial approach for managing gingival inflammation and improving nitric oxide bioavailability.

West Nile virus (WNV) is the causative agent of fatal West Nile encephalitis. To date, no human vaccine against WNV has been approved. Adjuvants are important for developing effective and affordable vaccines that enhance the immunogenicity and decrease the required antigen doses. In this study, we assessed the efficacy of AddaS03, a synthetic adjuvant analogous to AS03, in a WNV subunit vaccine composed of soluble recombinant envelope protein (sEnv). Using a passive immunization mouse model, we defined the neutralizing antibody titer threshold required for protection against lethal WNV infections and applied this threshold as a surrogate marker to evaluate adjuvant efficacy. AddaS03-adjuvanted formulations elicited markedly higher neutralizing antibody titers compared to Alhydrogel adjuvant 2% (Alhydrogel), even at suboptimal antigen doses, and consistently exceeded the defined protective threshold titer. Moreover, in a sequential challenge mouse model, AddaS03-adjuvanted vaccines completely protected mice from symptomatic WNV infections, whereas Alhydrogel-adjuvanted vaccines failed to confer full protection. Collectively, these findings demonstrate that AddaS03 is a promising adjuvant for WNV subunit vaccine development and highlights the utility of a passive immunization model for defining protective antibody thresholds as a surrogate marker for vaccine evaluation.

Background: Mucormycosis is a rapidly progressive and often fatal invasive fungal infection caused by moulds in the order, Mucorales. Early diagnosis is essential for effective clinical management; however, conventional diagnostic approaches such as culture and histopathology are slow, insensitive, and require specialist mycological expertise. Although molecular methods are available for disease detection, they are not widely accessible. At present, no enzyme immunoassay (EIA) exists for the detection of mucormycosis. Methods: A murine IgG1 monoclonal antibody (mAb), FH12, was generated against extracellular polysaccharides (EPSs) produced by Mucorales pathogens during active growth. The antibody was characterised for specificity, epitope stability, and antigen localisation using ELISA, immunoblotting, and immunofluorescence techniques. The mAb was incorporated into a Sandwich-ELISA and evaluated using culture filtrates, purified EPSs spiked into human serum, and tissue homogenates from a patient with cutaneous mucormycosis caused by Lichtheimia ramosa. Results: mAb FH12 demonstrated pan-Mucorales specificity and no cross-reactivity with other clinically relevant yeasts and moulds. The epitope recognised by FH12 is periodate-insensitive and moderately heat-stable. The Sandwich-ELISA detected EPS antigens in human serum with limits of detection ranging from pg/mL to low ng/mL levels, and successfully identified the EPS biomarker in patient tissue homogenates. Conclusion: The FH12-based Sandwich-ELISA shows high sensitivity and specificity, and has the potential to be used as a laboratory-based adjunct diagnostic test for the detection of mucormycosis in humans.

Foodborne illness is a significant public health concern worldwide. Shiga toxin-producing Escherichia coli and Campylobacter species are recognized as important zoonotic bacterial pathogens contributing to human infections through the food chain, particularly via foods of animal origin. Although goat meat is in high demand in the southern region of Thailand, studies on foodborne pathogens in this livestock species remain limited. The current study aimed to (i) determine the antimicrobial susceptibility of Campylobacter spp. and STEC isolated from goats, and (ii) analyze the genetic relationships among Campylobacter spp. And E. coli O157 isolates obtained from different sources. Campylobacter jejuni and C. coli isolates were characterized based on sequences of seven housekeeping genes using the Achtman multilocus sequence typing scheme. For E. coli O157:H7, core genome multilocus sequence typing analysis was performed using whole-genome sequencing data. Genetic diversity was observed among C. jejuni, whereas a clonal population structure was detected in C. coli and E. coli O157:H7. Overlapping genetic characteristics were observed between C. jejuni isolates from goats and those previously reported in livestock and humans in Thailand. Among Campylobacter species, resistance to fluoroquinolones, including ciprofloxacin and nalidixic acid, was observed, whereas resistance to fosfomycin was most frequently detected in Shiga toxin-producing E. coli. Tetracycline-resistant isolates were identified in both Campylobacter species and Shiga toxin-producing E. coli at moderate levels. A multidrug-resistant pattern was observed only in C. coli, whereas no multidrug-resistant C. jejuni or Shiga toxin-producing E. coli isolates were detected. These findings indicate that healthy goats may serve as potential reservoirs of zoonotic pathogens and antimicrobial resistance in southern Thailand, where goat meat is frequently consumed.

This pilot study assessed the composition and diversity of the urinary microbiome from clinically confirmed UTI samples using 16S rRNA sequencing, whilst also exploring inter-individual variability of microbial community structure. We examined ten urine samples from patients with culture-positive UTIs. Demographic and clinical metadata, including age, sex, body mass index (BMI), diabetes status and recent antibiotic exposure was recorded per sample. Metagenomic DNA was extracted from microbial samples and sequenced to generate genus-level taxonomic profiling through 16S rRNA gene sequencing. Relative abundance tables were generated for each of the samples to identify dominant bacterial genera within each sample and summarize cohort level microbial patterns. To evaluate within-sample richness and evenness, alpha diversity indices (Shannon, Simpson, observed features and Chao1) were computed; beta diversity was measured using Bray-Curtis dissimilarity with principal coordinates analysis (PCoA) for graphical representation. The studys findings revealed the sex and moderate clinical diversity of the study sample; all samples were confirmed as having been taken from a UTI patient and exhibited a wide level of heterogeneity regarding the microbial composition of each urine sample. Overall, Pseudomonas was the dominant genus present, however, specific samples had approximately 50% of their microbiomes composed of Klebsiella, Proteus, and Escherichia species as well as approximately 25% of their total microbes were made up of Burkholderia spp., which are closely related to the genus of interest used during the course of this study. The observed alpha diversity of each sample displayed considerable variation for the included samples with a continuum of samples ranging from a single dominant microbe to a highly diverse mixed population producing a highly diverse polymicrobial population/bacterial composition, with some ratios of individual taxa to collective taxa of many samples repeatedly illustrating the exact nature of the specimen. Furthermore, a significant degree of Beta diversity was found between the patients, providing compelling evidence of identifiable differences among urinary microbiomes between patients with UTI. This pilot project provides a clear indication of the diversity and overall heterogeneity of urinary microbiota found in the UTI patients studied. In addition, the results of this study support the notion that the ecological complexities present within a urinary microbiome cannot necessarily be established through conventional culture methods, and that combined with molecular techniques such as 16S rRNA sequencing of bacterial DNA could be used to quantify and characterize the ecologic condition of urinary microbiota separate from the traditional high prevalence of identifiable uropathogens.

BackgroundTuberculosis (TB) remains a leading cause of infectious disease mortality worldwide, and treatment failure contributes to ongoing transmission, drug resistance, and poor clinical outcomes. Artificial intelligence and machine learning approaches have attracted growing interest for predicting tuberculosis treatment outcomes, but the literature is heterogeneous and lacks a comprehensive synthesis. MethodsWe conducted a systematic review and meta-analysis of studies that developed or validated machine learning models to predict TB treatment failure. We searched PubMed/MEDLINE and Embase from January 2000 to October 2025. Studies were eligible if they developed, validated, or implemented an artificial intelligence or machine learning model for the prediction of TB treatment failure or a closely related poor outcome in patients receiving anti-TB treatment. Risk of bias was assessed using the Prediction model Risk Of Bias Assessment Tool. Random-effects meta-analysis was performed to pool area under the curve values, with subgroup analyses and meta-regression to explore heterogeneity. ResultsThirty-four studies were included in the systematic review, of which 19 reported area under the curve values suitable for meta-analysis (total participants, 100,790). Studies were published between 2014 and 2025, with 91% published from 2019 onward. Tree-based methods were the most common algorithm family (52.9%), and multimodal models integrating three or more data types were used in 41.2% of studies. The pooled area under the curve was 0.836 (95% confidence interval 0.799-0.868), with substantial heterogeneity (I{superscript 2} = 97.9%). In subgroup analyses, studies including HIV-positive participants showed lower discrimination (pooled area under the curve 0.748) compared to those excluding them (0.924). Only eight studies (23.5%) performed external validation, and only one study (2.9%) was rated as low risk of bias overall, primarily due to methodological concerns in the analysis domain. Eggers test suggested publication bias (p = 0.024). Major evidence gaps included underrepresentation of high-burden countries, HIV-affected populations, social determinants, pediatric TB, and extrapulmonary disease. ConclusionsMachine learning models for predicting TB treatment failure show promising discrimination but are not yet ready for routine clinical implementation. Performance varies substantially across populations and settings, and methodological limitations, including inadequate validation, poor calibration assessment, and high risk of bias, limit confidence in current estimates. Future research should prioritize rigorous external validation, calibration assessment, and development in underrepresented populations, particularly HIV-affected and high-burden settings. Author SummaryTB kills over a million people annually. While curable, treatment failure remains common and drives ongoing transmission and drug resistance. Researchers increasingly use artificial intelligence and machine learning to predict which patients will fail treatment, but it is unclear if these models are ready for clinical use. We reviewed 34 studies including nearly 1.1 million participants from 22 countries. On average, models correctly distinguished patients who would fail treatment from those who would not 84% of the time, a performance generally considered good. However, this average hid enormous variation. Models developed in populations including HIV-positive people performed substantially worse, suggesting prediction is harder with HIV co-infection. Worryingly, only one study used high-quality methods; 97% had serious flaws in handling missing data, checking calibration, or testing in new populations. Only eight studies validated their models in different settings. To conclude, we found that machine learning is promising in predicting TB treatment failure, but it is not ready for clinical use. Researchers should prioritize validation in high-burden settings, include social determinants, and improve methodological rigor before these tools can help patients.

Type 2 diabetes mellitus (T2DM) is a progressive metabolic disorder characterized by persistent hyperglycemia, insulin resistance, and chronic low-grade inflammation. Despite the widespread use of established therapies such as metformin, long-term glycemic control remains suboptimal, and disease progression is often not adequately prevented. This highlights the need for novel therapeutic strategies that address both metabolic dysfunction and the underlying immunometabolic components of the disease. In this study, GLX10 (GLXM100) was evaluated as a novel immune modulator in a high-fat diet (HFD) and low-dose streptozotocin (STZ)-induced rat model of T2DM over a 91-day period. Glycemic outcomes were assessed using terminal random blood glucose and oral glucose tolerance testing (OGTT), with glucose exposure quantified by area under the curve (AUC 0-120). Complementary in vitro investigations were performed in hepatic and macrophage cell models to assess cytocompatibility, nitric oxide production, and modulation of pro-inflammatory cytokines, including IL-6 and TNF-. GLX10 treatment resulted in a significant reduction in random blood glucose levels and a marked improvement in glucose tolerance compared to diabetic control animals. Importantly, GLX10 demonstrated greater improvement in OGTT AUC compared to metformin under the same experimental conditions, indicating enhanced dynamic glucose regulation. In vitro, GLX10 maintained viability in normal hepatic cells while significantly suppressing nitric oxide production and inflammatory cytokine outputs in macrophages, supporting a favorable safety and immune profile. Collectively, these findings demonstrate that GLX10 exerts robust antidiabetic activity through a dual mechanism involving metabolic regulation and suppression of inflammatory signaling. The integration of in vivo efficacy with supportive in vitro safety and mechanistic data provides a strong preclinical foundation and supports the further development of GLX10 as a promising therapeutic candidate for T2DM.

Background and AimsThe rising incidence of Crohns disease (CD) in Westernized countries has been linked to changes in diet and increased consumption of food additives, yet the mechanisms by which these factors fuel intestinal inflammation remain unclear. Adherent-invasive Escherichia coli (AIEC), a pathobiont involved in CD pathogenesis, lacks a clear genetic hallmark but exhibits intestinal colonization and virulence traits, raising questions about the evolutionary forces promoting its emergence among select individuals. Here, we investigated how chronic exposure to two common dietary emulsifiers, carboxymethylcellulose (CMC) and polysorbate 80 (P80), along with host inflammation, drives AIEC genomic evolution and pathogenic potential. MethodsWild-type and Il10-deficient mice were monocolonized with AIEC and chronically exposed to CMC, P80, or water. Bacterial isolates were collected and analyzed for genomic diversification, mutations, and phenotype both in vitro and in vivo. ResultsEmulsifiers accelerated AIEC genomic diversification and selected for mutations linked to increased motility, invasion, and pro-inflammatory activity. Moreover, dietary emulsifier-evolved strains displayed a marked fitness advantage in vivo, outcompeting their counterparts in murine hosts, with the greatest advantage observed when evolution occurred under inflammatory conditions. Notably, evolutionary pathways and phenotypic outcomes were shaped by both emulsifier and the hosts inflammatory status, highlighting synergy between diet and host genetics in fostering pro-inflammatory pathobionts. ConclusionThese findings provide an evolutionary framework connecting modern dietary habits to the emergence of pathogenic AIEC strains, and underscore the importance of dietary interventions in individuals at risk for inflammatory bowel disease.

Background Tuberculosis (TB) remains a critical public health challenge, with two-thirds of the global TB burden in ten Asian countries. Social vulnerabilities, comorbidities, health inequity, multi-dimensional poverty, malnutrition, and barriers to healthcare access continue to fuel TB epidemic. Inability to detect asymptomatic and sub-clinical TB, combined with passive approach in service delivery and overreliance on smear microscopy, leads to delayed diagnosis, a substantial burden of undetected cases, and continuing TB transmission in the communities. In such a context, the introduction and scale-up of active case-finding approaches - including community-based TB screening using highly sensitive screening tools and novel rapid diagnostics - becomes a strategic priority to interrupt transmission. The growing availability of multiple screening and diagnostic options makes evidence-based decision-making increasingly complex. Methods To estimate the potential epidemiological impact and cost implications of scaling up TB diagnostics and community-based screening in ten high-burden Asian countries, we constructed a mathematical model and evaluated multiple intervention scenarios. We then assessed and compared four service delivery models: 1) digital ultraportable chest x-ray (UPCXR) & Xpert/Truenat in community, 2) digital UPCXR in community and Xpert/Truenat at health facilities, 3) digital UPCXR in community and near point of care (nPOC) at health facilities, 4) nPOC in community & Xpert/Truenat at health facilities - for total investment required and projected health benefits for their cost-effectiveness. Results and conclusions The modelling study indicated that strengthening health facility capacity (with enhanced TB screening, expanded molecular diagnostics, reduced loss to follow-up, private sector standard of care, leading to increased treatment coverage & quality of active disease treatment and reduced post-treatment relapse, scale-up of TB preventive treatment (TPT), and provision of nutritional support to 80% of TB patients and their household contacts) can significantly reduce TB incidence and mortality; however, community-wide mass screening remains essential to achieving TB elimination targets . Targeted screening of vulnerable populations demonstrated greater cost-effectiveness than untargeted screening approaches. Achieving the End TB goals will ultimately require an effective TB vaccine with high population-level coverage. AI-enabled digital UPCXR-based screening combined with Xpert/Truenat testing at the community level demonstrated maximum epidemiological impact potential, while the most cost-efficient model is Digital UPCXR in the community combined with nPOC testing at health facilities. An investment of USD 12.7 billion over the next five years in community-level implementation of digital UPCXR and molecular diagnostics could avert an additional 9.8 million TB cases and 1.9 million deaths across ten Asian countries over a ten-year horizon.

Tuberculosis (TB) is prevalent in Uganda and overlaps with a high rate of HIV/TB coinfection. While nearly all hospital-based TB cases in Kampala, the capital of Uganda, show clear TB symptoms, 30% or more of undiagnosed TB cases found through active screening are asymptomatic. Additionally, the host risk factors for TB in Kampala cannot be distinguished from environmental risk factors. These TB-specific challenges are just part of the complexity, especially in areas with high HIV/AIDS burden. Data science techniques, especially Artificial Intelligence (AI) and Machine Learning (ML) algorithms, could help untangle this complexity by identifying factors related to the host, pathogen, and environment, which are difficult to explain or predict with traditional/conventional methods. In this project, we will use health data science approaches (AI/ML) to identify factors driving TB transmission within households and reasons for anti-TB treatment failure. We will utilize the computational resources at Makerere University and available demographic, clinical, and laboratory data from TB patients and their contacts to develop AI and ML algorithms. These will aim to: (1) identify patients at baseline (month 0) unlikely to convert their sputum or culture results by months 2 and 5, thus at risk of failing TB treatment; (2) identify household contacts of TB cases who are at risk of developing TB disease, as well as contacts who may resist TB infection despite repeated exposure to M. tuberculosis. Achieving these objectives will provide evidence that data science methods are effective for early detection of potential TB cases and high-risk patients, thereby helping to reduce TB transmission in the community. The study protocol received approval from the School of Biomedical Sciences IRB, protocol number SBS-2023-495.

Vaccine adjuvants are critical for enhancing immune responses and sustaining antibody production. Although their safety profiles are well established, assessments have largely focused on metabolic and excretory organs such as the liver and kidneys, with limited attention to the heart. Here, we systematically evaluated the cardiac effects of five representative adjuvants in mice: alum, MF59, AS03, Sigma Adjuvant Systems, and lipid A. None of the adjuvants impaired baseline cardiac contractile function. Notably, lipid A uniquely enhanced mitochondrial respiratory capacity in rat and human induced pluripotent stem cell-derived cardiomyocytes and promoted mitochondrial membrane hyperpolarization. We next examined its therapeutic potential in a doxorubicin (Dox)-induced heart failure model characterized by mitochondrial dysfunction. Co-administration of lipid A with influenza hemagglutinin (HA) antigen significantly ameliorated cardiac dysfunction. In parallel, lipid A prevented the Dox-induced decline in anti-HA antibody titers, an effect associated with preservation of splenic B cell populations. Collectively, these findings reveal a previously unappreciated cytoprotective dimension of lipid A, demonstrating that it not only potentiates immune responses but also counteracts chemotherapy-induced functional decline by enhancing mitochondrial activity.