Journal of Clinical Microbiology

Effective filtration and concentration of stool specimens is an essential pre-analytical step for reducing fecal debris and improving organism recovery using microscopy-based ova and parasite (O&P) examination. This study evaluated three commercially available fecal sedimentation-based filtration/concentration systems, ParaPak SpinCon (Meridian Bioscience), Mini Parasep SF (Apacor), and the newly-available ParadeviceReingenuity), for qualitative parasite detection and workflow logistics using conventional and artificial intelligence (AI)-assisted microscopy. Forty clinical stool specimens (20 parasite-positive and 20 parasite-negative) were processed with the 3 devices, and the resultant 120 wet mount and 120 trichrome stained smear preparations were examined using conventional microscopy. Trichrome-stained slides were also scanned at 40x magnification using a Hamamatsu NanoZoomerS360 flatbed digital slide scanner and images were analyzed using the Techcyte Fusion Human Fecal Trichrome AI algorithm. Positive and indeterminate digital findings were confirmed by conventional glass slide microscopy. Slides and digital images were reviewed in a blinded manner. Concordance was assessed among the 360 initial evaluations (microscopy and AI-assisted), and discrepant parasitology results were resolved through re-review and specimen reprocessing as needed. Final qualitative agreement across slide/image evaluations using all three concentration systems was 100%. Minor discrepancies in protozoan and white/red blood cell detection/identification were noted in 5 and 7 cases, respectively, and likely reflected sampling and observer variability. While the three concentration systems produced equivalent qualitative results, the Paradevice and Mini Parasep SF offered the most streamlined workflows. These findings support the Paradevice and Mini Parasep SF as efficient, analytically equivalent systems that are compatible with traditional and AI-assisted O&P workflows.

Background Coeliac disease (CD) diagnosis on duodenal biopsies is limited by interobserver variability. We have previously demonstrated pathologist-level performance with our artificial intelligence (AI) model for the histopathological diagnosis of adult CD, but not in paediatric practice. As paediatric CD screening programmes expand internationally, accurate and scalable diagnostic tools are needed. We investigated whether an AI model trained exclusively on adult whole-slide images (WSIs) can generalise to paediatric CD diagnosis across independent centres. Methods A training and validation dataset of 9,958 WSIs from 8,421 adult patients (961 CD) from five centres was used to develop an ensemble of multiple-instance learning models using features from a foundation model. Testing was performed on 708 consecutive paediatric patients (86 CD) from two centres (Edinburgh and Southampton) not included in training. Model calibration was assessed, and probability outputs were grouped into clinically interpretable categories. Findings In adult cross-validation, the AI model achieved an area under the receiver operating characteristic curve (AUC) of 98.7%, sensitivity of 84.9%, specificity of 99.0%, and negative predictive value (NPV) of 98.1%. On testing (paediatric) datasets, performance remained high (AUC 98.8%, sensitivity 80.2%, specificity 98.4%, NPV 97.3%). Restricting analysis to predictions outside the intermediate-probability range (predicted CD probability <10% or [&ge;]65%; 85.3% of cases) improved sensitivity to 100% and specificity to 98.7%. No misclassifications were observed among high-confidence predictions (<2% or [&ge;]85%; 66.0% of cases). The expected calibration error was 0.03. Performance improved significantly when biopsies from both duodenal sites (bulb [D1] and descending [D2/3]) were considered. Interpretation Our AI model, trained on adult biopsies, generalises to paediatric CD diagnosis across centres and scanner platforms. Well-calibrated probability outputs provide clinically interpretable measures of diagnostic confidence and could support safe identification of CD-negative biopsies within defined thresholds. These findings demonstrate the feasibility of applying adult-derived AI models in paediatric populations and reinforce the importance of multi-site (D1 & D2) biopsy sampling.

Introduction: Synthetic oligopeptides provide a rapid and cost-efficient approach to developing antibodies and diagnostics for emerging viral variants. Methods: This study computationally and experimentally characterized a synthetic peptide analog of the SARS-CoV-2 spike subdomain 2 major disulfide loop (SD2MDL), designated S621 (CPVAIHADQLTPTWRVYSTC). Binding affinity was computationally estimated using the Heuristic Affinity Prediction Tool for Immune Complexes (HAPTIC), while experimental validation was performed using enzyme-linked immunosorbent assay (ELISA) with rabbit-derived antipeptide antibodies. Clinical diagnostic accuracy testing was done using plasma samples from RT-PCR-confirmed COVID-19 patients and pre-COVID-19 controls. Results: S621 demonstrated nanomolar binding affinity (Kdapp = 1.14 nM) and high avidity (3.67 nM), closely matching HAPTIC predictions (3.54 nM). Diagnostic evaluation yielded a sensitivity of 89.92% and specificity of 27.79%, corresponding to an overall accuracy of 71.79%. Discussion: These findings demonstrate that a single synthetic peptide derived from a conserved spike subdomain can function as a high-affinity surrogate for full-length antigens, supporting its potential application in rapid peptide-based immunodiagnostics.

Background Thalassemia is one of the most common monogenic disorders worldwide, current screening strategies combining hematological testing with molecular assays still carry a risk of missed diagnoses and undesirable efficiency, particularly for complex structural variants and rare mutations. Methods In this prospective double-blind, multicenter cohort study of 3,842 participants (3,362 pregnant women and 480 male partners), we conducted a head-to-head comparison to systematically evaluate the incremental clinical value and detection performance of single-molecule nanopore sequencing in thalassemia (SMITH) against conventional hematological testing and next-generation sequencing (NGS). Findings The overall concordance rate between NGS and SMITH was 98.6% (3789/3842). The discrepant cases (n=53) were directly attributed to the superior detection capabilities of SMITH, which successfully identified complex structural rearrangements-including 45 -globin gene triplications and four HK alleles-that were missed by NGS. Furthermore, SMITH accurately detected four rare variants (c.134_135insT/, c.-22(C>T)/, {beta}N/{beta}c.316-290delinsAGGGCAATAATTT and {beta}3.5 kb deletion/{beta}N ) and resolved ten trans and three cis configurations within the globin gene allele. Clinically, these technical advantages translated to a 9.3% (5/54) increase in the detection rate of high-risk prenatal couples, effectively preventing one birth affected by moderate-to-severe thalassemia. Additionally, SMITH corrected a diagnostic discrepancy in one case (HK vs. -3.7), sparing the couple from an unnecessary invasive procedure. Interpretation Our findings demonstrate that SMITH provides a powerful platform for resolving globin gene rearrangements, detecting rare variants, and enabling direct haplotype phasing. By effectively eliminating diagnostic blind spots, SMITH is expected to become an optimal method for thalassemia prevention programs. Funding This study was supported by Chinese National Natural Science Foundation Projects 81760037 and 82271894.

Background: In resource-limited settings, a critical bottleneck in cervical cancer prevention is the lack of practical strategies to triage high-risk human papillomavirus (HR-HPV)- positive women. Therefore, this study aimed to develop and internally validate a genotype-specific risk stratification model. Methods: A cross-sectional study enrolled 555 women in Cameroon. Data collection integrated cervical cytology and HPV genotyping using Abbott m2000rt and Sacace multiplex systems. An iterative modeling approach with bootstrap validation was used to develop the model and address model instability. HR-HPV genotypes were transformed into a hierarchical risk variable due to sparsity and integrated with significant predictors. The final model was translated into a scoring system, and the risk gradients and performances were evaluated at two thresholds. Data was analyzed using SPSS 27.0. Results: The mean age was 44.8 years, and the prevalence of HR-HPV was 26.5% (147/555). The final model, incorporating HPV categories, age, and tobacco, demonstrated moderate discriminative ability (AUC=0.702, 0.642-0.762) with a good calibration (Hosmer-Lemeshow {chi}{superscript 2}=4.05, p=0.399). The scoring system assigned women to risk groups based on their total scores which produced a clear monotonic risk gradient; the observed probability of high-grade lesions/cancer ranged from 15% (score 0) to >65% (score [&ge;]4). At a conservative threshold ([&ge;]4 points), 4.7% (26/555) of women were classified as high-risk, concentrating 46% (6/13) of cancers (positive predictive value[PPV]=58%) while a sensitive threshold ([&ge;]3 points) had 16.8% (93/555) high-risk, concentrating 77% (10/13) cancers (PPV=38%). Both thresholds maintained a high negative predictive value (>95%). Conclusion: This bootstrap-validated, risk-stratification tool is a proof-of-concept in resource limited settings that assigns HR-HPV-positive women to distinct management pathways using three variables. After refining through a longitudinal study and external validation, this scoring system can improve the efficiency of cervical cancer screening programs in low-resource settings.

Objective: Clinical phenotyping methods that rely on clinical and informatics expertise can be time-intensive and costly. We tested both manual and highly automated approaches using electronic health record (EHR) data to identify an FDA Sentinel Initiative health outcome of interest, acute pancreatitis. Materials and Methods: We trained and evaluated machine learning algorithms using EHR data with two approaches: a custom approach that included manually curated features and trained on outcomes data validated with medical record review, and a highly automated approach that greatly simplifies and automates feature engineering and relies on low-cost silver-standard outcomes for model training. Results: Custom algorithms using manually curated structured claims data discriminated cases from non-cases with a high degree of accuracy (cv-AUC 0.89 [95%CI 0.84-0.94]); the inclusion of natural language processing (NLP)-derived covariates from clinical notes increased performance slightly (cv-AUC 0.91[95%CI 0.86-0.97]). The automated algorithm trained on the outcome count of diagnosis codes performed less well (AUC 0.80 [95% CI 0.75-0.85]) but improved using maximum lipase value as an outcome (AUC 0.88 [95% CI 0.84-0.92]). At a positive predictive value of 90%, the custom algorithm had a sensitivity of 92%, the automated algorithm trained on diagnosis code count had a sensitivity of 45%, and the automated algorithm trained on maximum lipase value had a sensitivity of 84%. However, a prediction rule derived by clinicians during chart review was nearly as accurate (maximum lipase value [&ge;] 3 times upper limit of normal; AUC 0.86, PPV 85%, sensitivity 92%). Discussion: Machine learning algorithms with manually curated structured data and NLP features trained on validated outcomes data successfully identified validated events. Use of an outcome in the automated model based on specific phenotype knowledge (maximum lipase value) allowed for performance similar to the custom model and with considerably less resources.

Background Pediatric immunizations for Respiratory Syncytial Virus (RSV), including monoclonal antibodies for infants and vaccines for pregnant people, have become broadly available and can prevent severe RSV outcomes in infants. However, quantifying the impact of RSV immunization in prevention of severe pediatric illness at the population-level is limited by lack of RSV case surveillance data. The Massachusetts Department of Public Health (DPH) conducted a modeling analysis using routine public health surveillance data to estimate the state-level impact of new RSV immunization products on Emergency Department (ED) visits and hospitalizations in Massachusetts for highest risk pediatric groups. Methods A scenario projection tool, called R.Scenario.Vax, was utilized to simulate RSV-associated ED hospital encounters by age group in the context of newly available immunizations. ED visit and hospitalization data from the National Syndromic Surveillance Program (NSSP) during the time period 10/08/2017--10/19/2024 were analyzed, scaled to account for changes in RSV testing practices over time and missing encounter volume in historic data, and utilized to inform model fit of a "typical" RSV season. RSV immunization data from the Massachusetts Immunization Information System (MIIS) for the 2023--2024 and 2024--2025 RSV seasons informed high and moderate pediatric RSV immunization coverage scenarios and their impact was compared to a counterfactual reference scenario of no new immunizations. Median projections were quantitatively and qualitatively compared to observed 2024--2025 season data. Percent reduction in hospital encounters and encounters averted per 10,000 population were calculated for each scenario as compared to the reference. Results Projections for the youngest at-risk age groups showed significantly lower RSV-associated ED visits and hospitalizations during the 2024--2025 season for both high and moderate immunization coverage scenarios. Median projections for infants under 6 months old in the highest coverage scenario, wherein nearly all infants were immunized, showed 72.6% lower ED visits and 73.4% lower hospitalizations when compared to the reference scenario, equating to 262 ED visits and 85 hospitalizations averted per 10,000 population. Conclusions Our results support the use of modeling methods for public health insights and suggest that RSV immunizations for infant populations result in significantly lower RSV-related ED encounters in Massachusetts.

Summary Background Persistent transmission from relapsing Plasmodium vivax infections threatens malaria elimination programs in the Asia-Pacific and Americas. Tools to identify people at risk of relapse are urgently required. We aimed to validate a panel of eight P. vivax serological biomarkers for predicting future relapses. Methods In this observational study, soldiers returning from malaria-endemic Papua to non-endemic East Java, Indonesia, were screened at enrolment using antibody measurement (Luminex) and trained random forest classification algorithms, then followed for 6 months. Active case detection was performed fortnightly by microscopy. Algorithms classified soldiers as recently infected (last nine months) and thus at risk of relapse, based on anti-vivax antibody measurements at enrolment. Findings Between December 2018 and July 2022, 592 soldiers were enrolled, with 553 completing follow-up; 119 experienced a P. vivax relapse. Of these, 102 were correctly classified as at risk of relapse at enrolment, corresponding to 86% sensitivity and 86% specificity, with an AUC of 0.92. Interpretation P. vivax serological biomarkers can identify people at risk of relapse with high sensitivity and specificity and could be used as a novel public health intervention, P. vivax serological testing and treatment (PvSeroTAT), to reduce relapse-driven transmission.

Background Artemisinin derivatives are central to first-line treatment of both uncomplicated and severe Plasmodium falciparum malaria. Emerging artemisinin partial resistance in East Africa threatens to spread across the continent. Methods In two cross-sectional studies in Zambia in 2024, we genotyped the artemisinin resistance-associated gene Pfkelch13. In Kaoma, western Zambia, we evaluated the percentage of patients with day-3 parasite positivity following treatment with artemisinin-based combination therapy, and ex vivo parasite susceptibility to dihydroartemisinin (the active metabolite of artemisinin). We also assessed longitudinal changes in Pfkelch13 mutation prevalence in Kaoma using isolates collected from 2018 through 2026. Results We identified a novel mutation, Pfkelch13 A724E, in 52% (113 of 217) of isolates from Western Province, 51% (94 of 184) of isolates from North-Western Province, and 11.7% (229 of 1,949) of isolates country-wide. In Kaoma, 28% (21 of 75) of patients carrying Pfkelch13 A724E mutant parasites before treatment were parasite positive on day 3, compared with 0% (0 of 23) of patients with the wild-type allele (P=0.003). Within day-3 positive patients, the proportion of A724E mutant parasites increased significantly after treatment (P = 0.013). The prevalence of Pfkelch13 A724E in Kaoma increased steadily from 0% (95% confidence interval [CI], 0 to 22%) in 2018 to 79% (95% CI, 73 to 85%) in 2026. Conclusions A novel Pfkelch13 mutation conferring partial resistance to artemisinin is spreading in Zambia. Additional clinical evaluations are urgently needed in the region. (Funded by the Gates Foundation, INV-048316).

Vaccines to prevent infant group B streptococcus (GBS) disease are advancing, with licensure likely based on safety and immunologic endpoints rather than clinical efficacy data. This approach requires robust, generalisable serological thresholds of risk reduction (SToRRs). We combined data from six case-control studies in Europe and Africa to define SToRRs for early-onset (EOD) and late-onset (LOD) GBS disease. Across diverse epidemiological and healthcare settings, anti-capsular polysaccharide IgG concentrations were consistently higher in infants who remained disease free than in those who developed disease. Higher antibody concentrations were required to reduce the risk of EOD than LOD, and higher concentrations were required for serotype Ia than for serotype III. This study provides a quantitative framework to support correlates-based evaluation and potential licensure of maternal GBS vaccines.

Background: The World Health Organization has expanded its recommendations for prophylactic Ebola vaccination for at-risk populations. Durable vaccine-induced immunity is important for sustaining outbreak preparedness in regions with recurrent Ebola virus disease (EVD). We assessed five-year persistence of vaccine-induced immune responses in adults and children from the PREVAC trial. Methods: Two large randomised phase 2 trials (NCT02876328), in adults and children aged [&ge;]1 year, were conducted in four west African countries. Participants were randomly assigned to placebo or to one of three Ebola vaccine strategies: Ad26.ZEBOV followed by MVA-BN-Filo at 56 days; rVSV{Delta}G-ZEBOV-GP followed by placebo; or rVSV{Delta}G-ZEBOV-GP followed by a homologous booster dose at 56 days. After 12 months of follow-up, the primary results were published, participants unblinded to their vaccine assignment, and follow-up continued for 60 months. After Month 24, placebo group recipients were offered active vaccination. Anti Ebola virus glycoprotein Immunoglobulin G (IgG) concentrations were measured for 5 years. Findings: 1401 adults and 1401 children were initially randomized, and 1315 (93.9%) adults and 1322 (94.4%) children attended at least one long-term visit. Retention was high, with 95% followed beyond 1 year and 83% completion at 5-year follow-up. For the three vaccine strategies, antibody geometric mean concentrations (GMC) declined modestly between Months 12 and 24, followed by a stable plateau from Months 24 to 60. At Month 60, antibody GMC were higher in the rVSV-based groups (1099 and 1216 EU/ml for adults; 1982 and 2347 EU/ml for children) than in the Ad26.ZEBOV, MVA-BN-Filo group (252 adults and 645 EU/ml children). Antibody persistence at Month 60 was heterogeneous, varying by age, sex, country, and baseline IgG concentration. Interpretation: Licensed Ebola vaccines induced sustained antibody responses in adults and children for up to 5 years. While the protective antibody level is unknown, these data demonstrate long-lasting immune responses from currently employed vaccine strategies.

Objective: To characterize pregnancy outcomes and menstrual irregularities in Mexican women with systemic lupus erythematosus (SLE) and identify clinical factors associated with adverse pregnancy outcomes and early-onset menopause. Methods: We conducted a cross-sectional study of women with SLE enrolled in the Mexican Lupus Registry (LupusRGMX) between May 2021 and September 2024. Clinical and reproductive data were collected using standardized questionnaires. Menopause was defined as the absence of menstruation for [&ge;]12 consecutive months, and early menopause as onset before age 40. Univariable and multivariable logistic regression analyses were used to identify factors associated with pregnancy complications and early menopause. Results: A total of 210 women were included. Median age was 38 years (IQR 29-46) and median disease duration was 4 years (IQR 1-10). Among women with a history of pregnancy (47%), full-term delivery predominated (61%), while pregnancy loss occurred in 26% and preterm delivery in 13%. Pregnancy complications were reported in 9.6%, most commonly preeclampsia (6.7%). Younger maternal age was independently associated with pregnancy complications (OR 0.89, 95% CI 0.83-0.95) and adverse outcomes (OR 0.95, 95% CI 0.92-0.98). Higher disease activity was associated with complications in univariable analysis. Most pregnancies (68.3%) occurred before diagnosis. Early menopause was observed in 6.2% and independently associated with longer disease duration and older age. Conclusion: Younger maternal age was independently associated with adverse pregnancy outcomes, whereas disease activity showed an association in univariable analysis. Most pregnancies occurred prior to SLE diagnosis. Early menopause was associated with longer disease duration, suggesting impact of cumulative disease burden on ovarian function.

Introduction Reducing delays in leprosy case detection is essential for achieving global leprosy targets. Accurate measurement of these delays and their determinants relies largely on patient-reported data, as routine health records are often inadequate. The leprosy case detection delay (CDD) questionnaire, developed under the Post Exposure Prophylaxis for Leprosy (PEP4LEP) project, has been validated in Ethiopia, Mozambique, Tanzania, and Indonesia. However, it has not been adapted or validated for Nigeria or any major Nigerian indigenous language. This study aimed to culturally adapt and validate the CDD questionnaire for Igbo-speaking populations in Nigeria. Methodology/Principal Findings The CDD questionnaire underwent a standardized cross-cultural adaptation process. Content validity was assessed using item- and scale-level content validity indices, while construct validity was evaluated through hypothesis testing. Reproducibility was assessed using test-retest and inter-rater reliability; agreement using the Bland-Altman method and the Wilcoxon Signed-Rank test; reliability using Spearmans rank correlation coefficient and the Intraclass Correlation Coefficient (ICC); and internal consistency using Cronbachs alpha. Data were collected through face-to-face interviews with persons affected by leprosy at two time points separated by at least two weeks. Participants (n=100) had a mean age of 45.1 years (SD=18.7). Mean CDD was 77.2 months at baseline and 77.9 months at retest. The instrument demonstrated excellent content validity (I-CVI/S-CVI: 0.90-1.00), good internal consistency (Cronbachs =0.77), and excellent test-retest reliability (ICC=0.996, 95% CI: 0.994-0.997). Test and retest measurements were highly correlated ({rho}=0.985, p<0.001), with no evidence of systematic change over time (p=0.864). Seventy-two percent of participants reported identical CDD values across assessments. All items from the original English version were retained without modification. Conclusion/Significance The Igbo version of the CDD questionnaire demonstrated good validity and reliability and is suitable for assessing leprosy case detection delay among Igbo-speaking populations in Nigeria

Background: Reliable inference of Plasmodium vivax recurrence states - relapse, recrudescence and reinfection (the ``3Rs'') - improves estimates of antimalarial efficacy. The R package Pv3Rs features a Bayesian model designed for P. vivax molecular correction, i.e., using parasite genetic data to infer recurrence states. The model is an extension of a prototype built to analyse microsatellite data from the Vivax History (VHX) and Best Primaquine Dose (BPD) trials. Methods: We re-analysed data from 212 VHX and BPD trial participants (493 recurrences) using Pv3Rs, comparing results with those from the prototype and with genetic relatedness estimated using Dcifer, a tool for estimating relatedness based on identity-by-descent. Posterior recurrence state probabilities were computed using both uniform and time-to-event priors: artificial but equal prior probabilities facilitate posterior interpretation, while time-to-event priors leverage all available information and enable re-computation of failure rates. Relatedness estimates were used to identify and correct instances of model misspecification. Results: The Pv3Rs model generated posterior probabilities for all recurrences and was able to jointly model data on all episodes per participant for 89% of participants, compared with 73% using the prototype. Recurrence state probabilities were broadly consistent across methods, though the Pv3Rs model elevated reinfection probabilities slightly. Relatedness estimates exposed various outliers consistent with half-sibling parasites and/or genotyping errors. Outlier correction impacted some per-participant failure probabilities, but reinfection-adjusted radical-cure failure rates of high-dose primaquine remained near 3%, in line with previous findings. Conclusion: Re-analysis of VHX and BPD P. vivax genetic data restates earlier reinfection-adjusted efficacy estimates. It demonstrates the increased computational capability and misspecification sensitivity of Pv3Rs, highlighting a need for careful analyses. Using relatedness-based diagnostics alongside model-based inference, we were able to harness the advantages of model-based inference and provide a framework for future P. vivax molecular correction.

Background Healthcare-associated infections pose a major burden to neonatal health worldwide and remain difficult to track in low-resource hospitals because patient movement data and pathogen genomic data are rarely integrated into actionable transmission models. Existing approaches are often restricted to specific settings, highly structured electronic health records (EHRs), or analyses focused on either patient movements or pathogen characteristics alone. To address this gap, we developed PathoPath, an open-source integrative modelling platform, and evaluated its utility in a high burden paediatric hospital in Dhaka, Bangladesh. Methods PathoPath is an open-source R package that combines electronic health records with whole genome sequencing data to generate contact networks from direct and indirect contacts using minimal structured inputs. We retrospectively applied PathoPath to 373 cases of Klebsiella pneumoniae species complex (KpSC) infection identified in 2021 at the largest paediatric referral hospital in Dhaka, Bangladesh. Ward level patient movement trajectories were used to reconstruct contact networks, and genomic data from isolates from children <60 days were integrated to identify probable dissemination of bacterial clones and antimicrobial resistance plasmids. Findings PathoPath identified 750 direct contacts among 317 patients, forming 25 connected components, with the largest including 93 patients. KpSC infections were identified across 21 of 37 wards, with the neonatal intensive care unit accounting for 77.9% of all cases. Integration of genomic and network data distinguished sustained clustering of ST147 from multiple probable inter-clonal dissemination events involving IncFII plasmids carrying blaNDM-5 and/or blaOXA-181 within ST16. Four dominant sequence types accounted for 65.6% of sequenced isolates, and carbapenemase genes were detected in 95.8%. Interpretation PathoPath reconstructs hospital-wide contact networks and integrates them with pathogen genomics to map probable dissemination of pathogens and antimicrobial resistance using minimal structured clinical data. It could support more targeted infection prevention and control in hospitals where granular digital records are not available.

Use of fungal mycelia, which has antiviral properties, constitutes a novel strategy for addressing existing and newly emerging viral diseases. We evaluated safety and feasibility of fungal mycelia (Fomitopsis officinalis and Trametes versicolor, FoTv) for treatment of COVID-19 and assessed its antiviral effects and potential to reduce symptoms. In a randomized, double-blind, placebo-controlled, dual site (UCSD/UCLA medical centers) clinical trial we examined non-hospitalized patients who contracted mild-to-moderate COVID-19 [&le;] 96 hours, and experienced symptom onset [&le;] nine days, before enrollment. FoTv was safe, well-tolerated, and feasible for COVID-19 treatment. Minor differences in biochemical markers were observed between groups (26 FoTv, 24 Placebo). FoTv significantly reduced the number and severity of symptoms, particularly sore throat/cough, and in vitro SARS-CoV-2 (pseudovirus) cellular infection. In conclusion, FoTv was safe and reduced COVID-19 symptoms and cellular viral infection. Future studies should investigate therapeutic benefits of fungal mycelia for SARS-CoV-2 and other viruses. Clinicaltrials.gov registration:NCT04667247.

Flow cytometry can establish T cell clonality by detecting a restricted expression pattern of the T cell receptor (TCR) {beta} constant region (TRBC), expressed in association with CD3. However, T cell neoplasms frequently lose surface expression of the CD3/TCR complex, posing a challenge to demonstrating T cell lineage and clonality. To address this challenge, here we present a 12-color flow cytometry panel, called cytoTCR, to characterize cytoplasmic expression of CD3/TCR complex components. We apply cytoTCR to 38 patient specimens with immunophenotypically abnormal T cell populations, demonstrating this approach can efficiently establish T cell lineage and clonality in challenging T cell neoplasms that have lost surface CD3 expression. While we show that natural killer (NK)-lineage neoplasms can express cytoplasmic CD3 at similar levels to T cells, we show that absent expression of cytoplasmic TCR components by mature lymphocytes can help confirm NK cell lineage. We demonstrate that cytoTCR can detect cytoplasmic TRBC-restriction in challenging cases of null-phenotype anaplastic large cell lymphoma, which lack surface expression of pan-T cell antigens. In cases of T-lymphoblastic leukemia, cytoTCR shows that cytoplasmic TRBC expression matches the expected developmental stage of the leukemia. Finally, we use cytoTCR to characterize atypical cCD3-CD7- T cells in a patient with a history of T-lymphoblastic leukemia as well as recent CAR-T therapy, showing that this atypical population is polytypic and represents CAR-T product rather than residual disease. Our study presents a broadly applicable flow cytometric approach to simultaneously assess T cell lineage and clonality in suspected T lineage populations with absent surface CD3 expression.

Background Tuberculosis remains the leading infectious cause of death worldwide. In the WHO African region, declining incidence has coincided with antiretroviral therapy (ART) scale-up, though whether this reflects reduced progression to disease or reduced transmission is unclear. We evaluated how ART and symptom status influence within-household Mycobacterium tuberculosis complex (MTBC) transmission risk. Methods We conducted a case-contact household study in rural South Africa, enrolling index adults with bacteriologically-confirmed pulmonary tuberculosis. MTBC immunoreactivity was measured in all child household contacts (aged 2-14 years) as a proxy measure of within-household transmission. We assessed the influence of index person ART status and symptom status, and explored effect-measure modification of the association between index person HIV status and transmission risk by sex. Results Among 755 child contacts of 296 index persons, effective ART was not associated with within-household MTBC transmission risk (risk ratio [RR], 1.07; 95% CI, 0.66-1.74). Among PLHIV engaged in ART care, WHO TB four-symptom screen (WHO4SS) status was not associated with transmission risk (RR, 0.80; 95% CI, 0.43-1.47), although absence of reported cough reduced risk (RR, 0.61; 95% CI, 0.38-0.96). A pronounced interaction between sex and HIV status was observed: HIV-negative women had the highest within-household MTBC transmission risk (30.5% vs. 14.3% in women with HIV) whereas risks were similar between HIV-positive and HIV-negative men. Conclusions We found no evidence that effective ART or WHO4SS status influenced within-household MTBC transmission risk, though confidence intervals were wide. Absence of reported cough was associated with lower risk, and transmission risk was highest among child contacts of HIV-negative women. These findings suggest reported cough is a useful marker of transmission risk and that routine tuberculosis screening within ART care may reduce transmission from PLHIV; intensified efforts are nonetheless needed to achieve earlier tuberculosis detection in HIV-negative individuals.

Background One in four surgical patients carries a drug allergy label, of which an estimated 90% are incorrect. Avoidance of first-choice drug therapies may lead to worse postoperative outcomes. We sought to determine the nature and extent of any association between drug allergy labels and postoperative complications. Methods A multicentre observational study in 21 NHS hospitals. Eligible patients were 18 years or older, undergoing common surgical procedures: primary hip or knee replacement; internal fixation of closed long bone fracture; colorectal resection; trans-urethral resection of prostate or bladder tumour; caesarean section; hysterectomy. Exclusion criteria: use of antibiotics in the two weeks prior to surgery, previous participation in the study. Primary outcome was postoperative complications within 30 days following surgery, a composite outcome comprising: all postoperative infections, anastomotic leak, acute respiratory distress syndrome, myocardial infarction, postoperative bleed, pulmonary embolism, stroke, antimicrobial side effects, death. Results Among 13,646 patients, 3924 (29%) carried greater than or equal to1 drug allergy labels. Labelled patients were more likely to develop postoperative complications (989/3924 (25%) vs 1926/9722 (20%); OR 1.21 [1.10-1.34]; p<0.001). They were more likely to develop surgical site infections (337/3924 (9%) vs 760/9722 (8%); OR 1.19 [1.03 -1.38]; p<0.018), and any postoperative infection (750/3924 (19%) vs 1472/9722 (15%); OR 1.24 [1.11-1.38] p<0.001). Labelled patients experienced increased risk of allergic drug reactions (31/3924 (0.01%) vs 29/9722 (<0.01%); OR 3.00 [1.77-5.09]; p<0.001), but no increase in mortality. Conclusions Drug allergy labels are common, but often incorrect. Labelled patients experience worse postoperative outcomes, including infective and non-infective complications and increased risk of allergic drug reactions. Trial registration Registered with ISRCTN registry, ISRCTN15775657.

Objective: The study aimed to describe the challenges, best practices, and lessons learned during meningitis vaccination campaigns conducted in the context of COVID-19 in Cameroon in 2020. Results: During the prevention campaigns, 3,460 individuals were selected. All were tested before the campaign (100%). Eight cases were positive, representing a positivity rate of 0.23% (8/3,460). The campaign was carried out using a fixed strategy in health facilities and prisons and a fixed-temporary strategy in communities. Most health areas received sufficient quantities of COVID-19 equipment for some items and insufficient quantities for others. No screening was done during or after the campaign. The main difficulties encountered were compliance with social distancing and the continuous wearing of gowns. The challenges faced were the screening of actors and the use of personal protective equipment. Lessons learned: aspects related to COVID-19 impacted the speed of the campaign. Vaccination coverage ranged from 91% to 140% in prisons on the one hand, and from 35% to 112% in the health areas surrounding prisons on the other. The campaign in the context of COVID-19 was effective. Compliance with barrier measures was not optimal due to difficulties encountered with aspects such as social distancing, continuous wearing of gowns, screening of participants during and after the campaign, and insufficient personal protective equipment.