Journal of Immunological Methods

Multiplex bead-based immunoassays (MIAs) are promising tools for simultaneously detecting humoral immunity to multiple targets, potentially playing a crucial role in serosurveillance and vaccine response assessments. However, evaluation of assay performance is paramount prior to widespread use. This study presents a performance evaluation of a pan-filovirus MIA through characterization of the analytical range for the EBOV glycoprotein (GP) target and assessments of assay precision and antigen discrimination. The precision of the MIA was evaluated by comparing the detection of anti-filovirus antibodies at two independent laboratory sites: the University of Hawaii, Honolulu (UH), and the Institut National de Recherche Biomedicale (INRB) in Kinshasa, Democratic Republic of the Congo (DRC). Forty-six samples from Yambuku, DRC, including Ebola virus Disease (EVD) survivors and close contacts, were tested at both sites. Additionally, 858 samples were tested in DRC before and after vaccination with a prophylactic EVD vaccine, ERVEBO. Results demonstrated low variability between laboratories, with intra-assay and inter-laboratory coefficients of variation below predefined thresholds for all filovirus targets included in the multiplex panel. Analyte correlations between sites were high (r2=0.86-0.92). Longitudinal analysis detected increased EBOV GP reactivity following vaccination, while reactivity to non-vaccine filovirus antigens remained stable, consistent with minimal cross-reactivity in a vaccinated cohort. These findings suggest that this pan-filovirus MIA produces reproducible results across distinct laboratory settings and may serve as a useful tool for comparative serologic investigations, serosurveillance, and evaluation of EBOV vaccine-associated antibody responses. IMPORTANCE STATEMENTThis study investigates the functionality and intra-laboratory consistency of a novel multiplex bead-based immunoassay with pan-filovirus targets. As part of the evaluation process, the feasibility of using the assay in resource-limited settings was demonstrated in the Democratic Republic of the Congo. This assay holds significant promise as a tool for detecting filovirus-specific antibody responses. By leveraging its multiplex capabilities, it may be used for widespread serosurveillance of high-consequence pathogens, including the pan-filovirus antigens such as Ebolavirus and Marburg virus already incorporated in the assay, as well as other targets of interest.

Celiac disease (CD) is strongly associated with specific HLA DQ heterodimers, formed by HLA DQA1 and HLA DQB1 proteins. In particular DQ2.5 (DQB1*02 associated to DQA1*05) and DQ8 (DQB1*03:02 with DQA1*03) are present in virtually all celiac patients. HLA DQB1*02 is considered the main single genetic susceptibility marker and has been reported in 90 to 95% of CD patients. However, the distribution of these alleles may vary across populations, potentially impacting the performance of genetic screening strategies. In this study, we evaluated the prevalence of HLA DQ2.5 and DQ8 genotypes in celiac patients (n = 41) and an unbiased general population cohort (n = 60) from San Luis, Argentina, using a PCR-based genotyping approach. In addition, we assessed the feasibility of a simplified saliva direct PCR protocol for large scale testing. Overall, 95.1% of CD patients carried DQ2.5 and/or DQ8. Notably, 41.5% of patients were DQ8(+)/DQ2.5(-), and 36.6% lacked the DQB1*02 allele, indicating that DQB1*02 based screening alone would have reduced sensitivity in this population. In the general population, 53.3% of individuals carried CD associated genotypes, with a markedly higher prevalence of DQ8 compared to European cohorts. Genotype distributions deviated from Hardy Weinberg equilibrium in CD patients but not in the general population. We show that DQB1*03:02 is a reliable proxy for DQ8, allowing simplification of genotyping strategies, whereas DQA1*05 typing remains essential to discriminate DQ2.5 from other lower risk DQB1*02 carrying heterodimers. We also describe a saliva direct PCR approach showing a performance comparable to purified DNA based assays. These findings highlight the importance of population specific genetic data for optimizing CD screening strategies and foster the development of simplified, cost effective genotyping approaches for large scale applications.

1Sex steroid hormones are not exclusively localised in the circulation and can be found in numerous extragonadal tissues, in concentrations unrelated to the circulating fraction. Existing methodology to measure intramuscular steroid hormone concentrations includes both immune-based assays and liquid chromatography-mass spectrometry (LC-MS), the gold standard for hormone measurements. To date, no LC-MS based methods validation has been published on the measurement of intramuscular sex steroid hormones, despite clear biological relevance. Here, we describe the development and validation of a simple, high-throughput LC-MS Orbitrap method for the measurement of 10 intramuscular sex steroid hormones, including pregnenolone, progesterone, dehydroepiandrosterone, androstenedione, testosterone, epitestosterone, dihydrotestosterone, oestrone, oestradiol, and oestriol. In brief, isotope labelled standards were added to 5-6 milligrams of lyophilised muscle tissue, homogenised and extracted with ethyl acetate. The extracts were dried down and sequentially derivatised with 1-methylimidazole-2-sulfonyl chloride and hydroxylamine hydrochloride to target both the phenolic hydroxyl groups and ketone groups. The limit of detection was 1.0 {+/-} 1.0 pg/mg (range 0.36 - 3.26 pg/mg), with a R2 > 0.99 for all analytes. Matrix effects were 90-110% for all analytes except for dihydrotestosterone (143.6%), and precision was <10 CV% for all analytes in the presence of a muscle matrix. Our method allows for 20-40 samples to be prepared in [~]4 h, with a sample data acquisition time of 13 minutes. Moreover, our method provides the opportunity for specific analysis of steroid hormone concentrations in skeletal muscle, allowing target tissue specificity instead of relying on proxy measures from the circulation.

Tuberculosis screening is not mandatory for prospective tissue donors. In 2021 and 2023, two different bone allograft products caused nationwide tuberculosis outbreaks. We assessed the morbidity and mortality of the second outbreak and reviewed donor and tissue screening to identify deficiencies. Thirty-six people residing in nine states received the product during spinal and dental procedures. Twenty-seven recipients had tuberculosis infection, 11 had microbiologic or imaging evidence of tuberculosis disease, and two died from tuberculosis within 12 months of outbreak detection. Another recipient died from tuberculosis nearly 3 years after product implantation. The bone donor died of pneumonia and septic shock. Polymerase chain reaction testing of the product before and after distribution did not detect Mycobacterium tuberculosis. Mycobacterial culture was not performed until after outbreak detection, when M. tuberculosis was isolated from 2 of 6 unused product units. This outbreak demonstrates persistent gaps in tissue transplant safety. Appropriate selection of donors and mycobacterial culture of donated tissues could reduce but not eliminate the risk of M. tuberculosis transmission. Therefore, it is important that clinicians monitor tissue recipients and promptly report adverse events to tissue establishments and health authorities.

Objective: To characterize genome-wide DNA methylation patterns associated with sepsis using the Infinium Methylation EPIC v2.0 platform and to evaluate the feasibility of pooled methylation profiling in a pilot critical care cohort. Design: Single-center pilot epigenome-wide association study using pooled whole-blood genomic DNA and pool-level bioinformatic analysis. Setting: Academic medical center. Patients: Fifty critically ill adults enrolled within 48 hours of illness onset and 20 healthy controls. Interventions: None. Measurements and Main Results: Critically ill patients required mechanical ventilation and/or vasopressor support. Sepsis was defined according to Sepsis-3 criteria. Seventy individual samples were organized into 14 intended pools of 5 individuals each: 7 sepsis pools, 3 critically ill non-septic pools, and 4 healthy-control pools. One critically ill non-septic pool was excluded because of poor DNA quality, yielding 13 analyzable pools. For the primary pooled comparison, 7 sepsis pools were compared with 6 non-sepsis comparator pools comprising 2 critically ill non-septic and 4 healthy-control pools. After quality control and preprocessing with SeSAMe, 876,094 CpG sites were retained. The initial pool-level screen identified 170,897 candidate differentially methylated regions. Application of stringent secondary filters (false discovery rate <= 1%, absolute delta-beta >= 7.5%, and >= 5 CpGs per region) yielded a high-confidence subset with marked directional skewing, including 155 hypomethylated and 32 hypermethylated regions in sepsis. Differentially methylated region-associated genes were enriched in myeloid leukocyte activation, myeloid leukocyte-mediated immunity, defense response to bacterium, neutrophil granule biology, and hematopoietic cell lineage pathways. Additional signals involved microRNA-associated targets, ribosome biogenesis, RNA processing, long noncoding RNAs, and previously uncharacterized loci. Conclusions: In this pilot pooled EPIC v2.0 study, sepsis was associated with a biologically coherent, predominantly hypomethylated methylation signature enriched in myeloid and host-defense pathways. These findings support the feasibility of pooled methylation profiling for discovery-oriented sepsis biobank studies but should be interpreted as hypothesis-generating given the pool-level design, limited effective sample size, heterogeneous comparator group, and lack of direct validation against individual-level methylation profiles.

BackgroundTubulitis is a defining histologic feature of T cell-mediated rejection (TCMR), while glomerulitis is often characteristic of antibody mediated rejection (AMR). Histologic quantification of tubulitis and glomerulitis using Banff criteria is subject to interobserver variability. Bulk transcriptomic assays (e.g., MMDx) have introduced molecular correlations of tubulitis with TCMR and glomerulitis with AMR, but lack spatial resolution. MethodsWe applied a web-based platform, FUSION (Functional Unit State Identification in Whole Slide Images), to a cohort of 8 cases (n=2 per condition) with kidney allograft biopsy samples acute TCMR, active AMR, chronic active AMR, and no rejection (control). The machine-learning (ML) platform enabled integrated visualization and analysis of spatial transcriptomics (10x Genomics Visium v2) together with high-resolution whole-slide histology. ResultsTranscriptomics-derived immune cell proportions within AI-segmented tubular and glomerular regions were used to generate spatial Banff t- and g-scores. Derived t-scores showed full concordance with pathologist scores in both acute TCMR cases; g-scores showed concordance in 2 of 4 AMR cases, with discordant cases characterized by low absolute immune signal near the classification boundary. ConclusionsWe demonstrate the feasibility of using AI-based FTU segmentation integrated with spatial transcriptomics-derived immune cell proportions to generate spatially informed t- and g-scores aligned with Banff criteria, with full concordance in severe rejection and partial concordance in mild rejection. This approach lays the foundation for validated, spatial transcriptomics-augmented t-scores and g-scores that enhance diagnostic precision, reduces inter-observer variability among renal pathologists, and support potential clinical adoption.

BackgroundShigella flexneri 2a (SF2a) and 6 (SF6) are two of the most common S. flexneri serotypes. They have distant O-specific polysaccharide (O-SP) structures. Previous studies showed no cross-reactivity or cross-protection between the two serotypes in a guinea pig model of infection. However, partial cross-reactivity and cross-protection were reported in humans immunized with a SF2a lattice-type conjugate vaccine candidate comprising the chemically detoxified lipopolysaccharide (LPS) attached to recombinant Pseudomonas aeruginosa Exoprotein A (rEPA). ObjectivesThis study aimed at deciphering the possible cross-reactivity with heterologous SF6 strains of antibodies induced in humans by SF2a-TT15, a sun-type SF2a conjugate vaccine candidate featuring a non-O-acetylated synthetic oligosaccharide (OS) as surrogate of the detoxified LPS. Special focus was on the impact of the O-SP non-stoichiometric O-acetylation on cross-reactivity. MethodsSerum IgG antibody titers to LPSs from SF6 strains harboring different degrees of O-SP O-acetylation, and from Escherichia coli O147 (EC147) which shares an identical but non-O-acetylated O-SP with SF6, were measured by ELISA in 63 serum samples of volunteers receiving 2 {micro}g and 10 {micro}g OS doses of SF2a-TT15 or placebo in the frame of a phase I clinical study. Antibody in-lymphocyte-supernatants (ALS), avidity, and serum bactericidal activity (SBA) were measured in a subset of volunteers. ResultsSF2a-TT15 induced cross-reacting IgG antibodies to all SF6 LPSs and EC147 LPS. A [&ge;]4-fold rise in anti-SF6 IgG titers was more frequent with the 10 {micro}g dose than with 2 {micro}g (50% vs 22%, p=0.045). Cross-reactivity rate was higher with the low O-acetylated SF6 O-SP than with the high O-acetylated one (50% versus 21%, p<0.05). Anti-SF6 responses correlated with homologous anti-SF2a LPS responses. Similar cross-reactivity was detected in ALS samples at day 7 after vaccination. Cross-reacting antibodies were partially functional against the heterologous SF6 parental strains, as shown by bactericidal activity and increased avidity. ConclusionsSF2a-TT15 induces stronger SF6 cross-reactive IgG responses than the previously tested detoxified O-acetylated SF2a LPS-rEPA conjugate. While both serotypes are included in most multivalent Shigella vaccine candidates, cross-reactivity and cross-protection between SF2a and SF6 could enhance the immunogenicity and efficacy of a Shigella multivalent vaccine candidate, particularly in infants in low- and middle-income countries, the primary target population for a Shigella vaccine.

Human milk contains structurally diverse glycans with key roles in shaping infant development, yet analytical constraints limit characterisation from low-volume samples. Glycosaminoglycans (GAGs), including chondroitin sulphate (CS), are understudied due to existing protocols requiring sample volumes of at least 5 mL and lengthy extraction steps prior to instrumental analysis. This study establishes a workflow for quantifying CS disaccharides from 25 {micro}L of human milk, enabling analysis of samples previously inaccessible to GAG profiling, such as those collected as salvage samples from neonatal intensive care units. For CS quantification, the CS is first enzymatically depolymerised using chondroitinase ABC to release repeating disaccharide units. Matrix complexity is reduced via two rounds of acetonitrile-based protein and lipid precipitation. Disaccharides are separated by hydrophilic interaction liquid chromatography and detected using a Triple Quadrupole Mass Spectrometer, providing robust sensitivity for all CS disaccharides. Method development and validation were performed using pooled mature human milk from term infants. This workflow facilitates detection of all CS disaccharides, with low but reproducible recoveries for total CS. Low- and high-level spike recoveries were 41.3% (RSDr 7.5%, RSDiR 15.9%) and 43.7% (RSDr 24.4%, RSDiR 27.9%), respectively. Despite modest absolute accuracy, precision remained sufficient to make relative comparison of CS concentrations between samples. This method expands the analytical toolkit for human milk glycomics, enabling same day preparation and CS profiling from sample volumes that are 200 times smaller than prior work, supporting future investigations into GAG-mediated functions in early life. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/723732v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@176dffborg.highwire.dtl.DTLVardef@16ae4ccorg.highwire.dtl.DTLVardef@d333c2org.highwire.dtl.DTLVardef@1eb3216_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO Schematic of sample preparation protocol 25 L of human milk is combined with lyase enzymes and TRIS buffer containing the internal standard prior to incubation. Samples then undergo multiple rounds of centrifugation and refrigeration before analysis via LC-MS/MS. Made using BioRender.com. Glycan nomenclature following Varki et al., 2015. C_FIG

BackgroundCytokines are immunomodulatory proteins that play central roles in regulating immune responses and represent attractive targets for cancer therapy. However, as single agents, cytokines have shown limited clinical benefit due to systemic toxicities and a short in vivo half-life. Our group has focused on engineering fusion cytokines (fusokines) that couple two cytokines into a single biologic to reprogram immune cell responses by enforcing non-canonical receptor engagement and signaling. A chimeric IL-6/IL-1{beta} fusokine was engineered to test the hypothesis that enforced co-engagement of IL-6 and IL-1{beta} signaling pathways would confer a gain-of-function phenotype in T cells and promote robust anti-tumor immunity. Here, we describe the immunomodulatory properties of IL6/1 fusokine and a method to deliver this fusokine to produce inhibition of ovarian tumor growth in a pre-clinical mouse model. MethodsLentiviral vectors encoding murine or human IL6/1 were designed using Vector Builder and expressed in either HEK293, CHO or ID8-F3 (p53-/-) cells depending on the downstream experiment to be conducted. IL6/1 expression was validated by ELISA and flow cytometry. Effects of human IL6/1 (hIL6/1) on T cell function (proliferation, memory phenotype, activation induced apoptosis) were monitored by flow cytometry. For in vivo studies, ID8-F3 murine ovarian cancer cells expressing mouse IL6/1 (mIL6/1) were administered intraperitoneally (I.P.) as a cell-based therapy to C57BL/6 female mice bearing established ID8-F3 luciferase tumors. Tumor progression was monitored by bioluminescence (BLI) imaging, and overall survival was evaluated. ResultshIL6/1 significantly enhanced T cell survival and selectively promoted activation and expansion of CD45RO memory T cells. mIL6/1 expressing ID8-F3 cells (ID8IL6/1) demonstrated stable transduction and sustained cytokine secretion. In vivo, ID8IL6/1 cell therapy significantly reduced tumor growth and improved overall survival compared to control groups, with 2 of 8 mice achieving complete tumor clearance. ConclusionThese findings indicate that IL6/1 fusokine enhances T cell survival and proliferation while promoting memory responses. Engineered cancer cells (ID8-F3) expressing mIL6/1 fusokine induced a strong anti-tumor response when delivered as a therapeutic vaccine in ovarian cancer mouse model. What is already known on this topicO_LIFusokines are a class of bifunctional proteins designed to achieve synergistic immune modulation. Previous studies in our lab have shown fusokine exhibit gain-of-function immunomodulating activity. Individually, IL-6 and IL-1{beta} are recognized for their roles in promoting T-cell proliferation and effector function. However, the potential for a fused IL-6/1 fusokine to reprogram the immune system and elicit a superior anti-tumor response in vivo in ovarian cancer model is not yet studied. C_LI What this study addsO_LIThis study develops a novel fusion cytokine (fusokine), combining IL-6 and IL-1{beta}, and demonstrate robust activation of T cells. In a preclinical ovarian cancer model, engineered cancer cells expressing IL6/1 used as a therapeutic vaccine showed significant tumor reduction and improved overall survival. C_LI How this study might affect research, practice or policyO_LIThis study demonstrates that in comparison to individual cytokines, fusokines have greater potential to activate T cell function and when delivered as a cell therapy, achieve clear therapeutic efficacy in an ovarian cancer model. Further translational and clinical studies may enable the development of novel and more effective fusokine cell therapy approaches for patients with ovarian cancer. C_LI

Cystic echinococcosis (CE), caused by the larval stage of Echinococcus granulosus, remains a significant public health and veterinary problem in endemic regions. Although chemotherapy and control programs exist, the development of complementary immunotherapeutic tools is increasingly needed. This study evaluated the generation and functional activity of hyperimmune serum (HIS) produced in three adult male castrated llamas (Lama glama) immunized with antigenic material derived from protoscoleces (PSCs) of the parasite. Sera collected after each of the first six immunizations were assessed by ELISA to quantify antigen-specific IgG responses, and their biological effects were tested in vitro using viable PSCs. Motility was measured using video-assisted paired-image scoring across serial serum dilutions (1:2-1:2048), and the methylene blue exclusion assay was used to assess viability. Hyperimmune serum produced a clear, reproducible, dose-dependent inhibition of PSC motility and viability. Higher titers of early inoculations reduced motility by 70-85%, while sera from the fifth and sixth inoculations achieved complete suppression. Naive serum and PBS controls showed no inhibitory effect. ELISA titers strongly correlated with biological activity, indicating that higher humoral responses predicted functional inhibition. These findings demonstrate the feasibility of generating potent anti-Echinococcus granulosus polyclonal antibodies in camelids and support their potential application in passive immunization strategies. The study establishes a foundation for future development of llama-derived immunobiological reagents, including nanobody-based tools, for the control of cystic echinococcosis.

Metastasis remains the major cause of cancer-related mortality, and circulating tumor cells (CTCs) are both candidate liquid-biopsy biomarkers and plausible intermediates of metastatic dissemination. Because CTCs are extremely rare in peripheral blood, platform comparisons have often focused solely on recovery. That focus is insufficient for applications that depend on the quality of the recovered material, including single-cell profiling, short-term culture, and functional testing. Here, we compared four CTC isolation approaches: TellDx CTC System, Genesis System, RosetteSep, and flow cytometry, using spike-in experiments in human blood. Capture efficiency was evaluated across all four platforms; purity was assessed for TellDx, Genesis, and RosetteSep; and post-isolation GFP signal persistence in culture was assessed for TellDx and Genesis as an exploratory proxy for short-term post-isolation preservation. Under the conditions tested, TellDx showed the highest recovery (88.1% {+/-} 3.7%), followed by Genesis (40.6% {+/-} 12.1%), RosetteSep (36.5% {+/-} 9.0%), and flow cytometry (7.6% {+/-} 4.5%). TellDx also showed the highest purity score (3.76), whereas Genesis (2.25) and RosetteSep (2.09) did not differ substantially. In the short-term culture assay, TellDx-derived samples retained a higher normalized GFP signal than Genesis-derived samples at 48 h and 72 h. To synthesize these readouts, we propose the Recovery Performance Index (RPI), a composite score integrating recovery, purity, and post-isolation signal persistence. Within this experimental framework, TellDx achieved the highest RPI. These data support two conclusions. First, platform benchmarking for CTC workflows benefits from multidimensional evaluation rather than recovery alone. Second, under this spike-in model and within the specific workflows used here, TellDx performed best among the platforms tested. The principal contribution of this study is therefore the establishment of a practical benchmarking framework that can be expanded in future work using clinical samples, multiple CTC phenotypes, and orthogonal viability assays.

ObjectivesThis study aimed to develop and validate machine learning models to predict in-hospital mortality among systemic lupus erythematosus (SLE) patients using administrative claims data in a tertiary referral center in Indonesia. MethodsWe conducted a retrospective cohort study of 327 SLE hospital admissions between January 2019 and June 2025. Predictor variables included demographics, hospitalisation characteristics, and the ten most frequent comorbidities. We developed Logistic Regression, Random Forest, and Extreme Gradient Boosting (XGBoost) models. Class imbalance was addressed using the Synthetic Minority Over-sampling Technique. ResultsThe overall in-hospital mortality rate was 7.7%. While models achieved comparable discrimination (Area Under the Curve ~0.71), XGBoost was selected for its superior sensitivity (0.93) compared to Logistic Regression (0.80) and Random Forest (0.97). Feature importance analysis revealed pneumonia as the most significant predictor, followed by acute kidney failure and length of stay. Hypoalbuminemia and hyponatremia were also identified as key prognostic markers. ConclusionsMachine learning models utilising registry-based administrative data effectively stratify mortality risk in hospitalised SLE patients with high sensitivity. The dominance of pneumonia and renal failure as predictors underscores the critical need for aggressive infection control and renal monitoring in this population.

Background Oropouche virus (OROV) is an emerging vector-borne virus with rapidly expanding geographic range, increasing case counts, and growing evidence of severe outcomes including neuroinvasive disease and vertical transmission. Because OROV infection presents with nonspecific febrile illness that overlaps clinically with other viruses including dengue, zika, and chikungunya, accurate molecular diagnostics are essential for patient care and surveillance. Yet existing assays rely on single genomic targets and are vulnerable to detection failure as the virus evolves and reassorts. Methodology/Principal Findings To support diagnostic capacity, we developed and clinically validated a multiplexed qPCR assay targeting three regions of the OROV S segment, incorporating redundancy to preserve sensitivity across viral diversity while enabling robust clinical interpretation. The multiplex also includes an assay targeting RNaseP as an internal sample control to ensure adequate sample processing. We evaluated assay performance using both historical and contemporary OROV strains and validated the assay on contrived serum, plasma, and cerebrospinal fluid samples, assessing linearity, limit of detection (LOD), accuracy, specificity, precision, and sample stability. The assay met or exceeded all predefined acceptance criteria for clinical testing and achieved an LOD as low as 6 copies per reaction for contemporary outbreak strains. We further implemented a logic-based interpretation matrix that reduced false-positive risk while maintaining sensitivity near the analytical LOD. Conclusions/Significance Our assay sensitively and specifically detects OROV RNA in serum, plasma, and cerebrospinal fluid while incorporating safeguards against viral evolution and reassortment. The assay has been approved for use by CLIA at Nexus Medical Labs in 49 U.S. states, expanding access to timely OROV diagnostics in the United States and providing a durable framework for molecular detection of reassorting, rapidly evolving viruses as OROV continues to spread into new regions.

IntroductionErgosterol-targeting azoles are widely used in the treatment of Candida albicans infection. In addition to direct antifungal activity, azoles are known to enhance neutrophil-mediated killing of C. albicans, but the underlying mechanisms remain unclear, particularly whether ergosterol depletion directly modulates host immune responses. Gap StatementIt remains unknown whether reduced ergosterol levels alone, independent of broader disruption to sterol biosynthesis and fungal morphogenesis, influence neutrophil antifungal activity. AimThis study aimed to determine how genetic disruption of late-stage ergosterol biosynthesis affects neutrophil-mediated responses to C. albicans. MethodologyDoxycycline-repressible GRACE mutants targeting late-stage ergosterol biosynthesis genes (ERG4, ERG5, ERG3 and ERG28) were co-incubated with primary human neutrophils. Fungal survival, oxidative burst, phagocytosis, neutrophil extracellular trap (NET) formation and cell wall composition were assessed. ResultsAll ergosterol-deficient strains induced elevated neutrophil reactive oxygen species (ROS) production; however, only ERG4 depletion was associated with enhanced fungal clearance. This phenotype correlated with increased phagocytosis and reduced NET formation. Cell wall analysis revealed no changes in total chitin or mannan content but demonstrated significantly increased surface exposure of {beta}-1,3-glucan in ERG4-depleted cells. ConclusionThese findings indicate that disruption of late-stage ergosterol biosynthesis, particularly via ERG4, enhances neutrophil antifungal responses and is associated with increased {beta}-glucan exposure. This study highlights a potential role for ergosterol in immune evasion and suggests that targeting terminal steps of the pathway may improve host-mediated clearance of C. albicans.

Tickborne diseases are a significant burden in many parts of the world. In the upper Midwestern United States, Lyme disease is the most common tickborne disease. It is carried by Ixodes scapularis. This vector can also transmit the pathogens causing anaplasmosis, babesiosis, ehrlichiosis, and several more tickborne diseases in this region. There is also concern for other tick species, such as Amblyomma americanum, that are expanding their ranges northward. We launched a citizen science passive tick surveillance program in 2024 to investigate tick species ranges in the upper Midwest, as well as the pathogens carried by I. scapularis. We received over 12,000 ticks in the first two years of this program, primarily from Wisconsin. While we received submissions of adult A. americanum outside of their endemic range, we did not see evidence of establishment in our study area. We measured pathogen prevalence in adult female I. scapularis (n=707) and observed 51% positivity for Borrelia burgdorferi, 9% for Babesia microti, 9% for Anaplasma phagocytophilum, and 3% for Ehrlichia muris eauclairensis. Multiple pathogens were identified in 14% of tested specimens, and significant associations were observed between B. burgdorferi and B. microti, and B. burgdorferi and E. muris eauclairensis. Pathogen prevalences varied across time and geography. Our results can begin to inform risk assessment for tickborne diseases in our region. A non-technical version of this document with interactive maps is available here: https://storymaps.arcgis.com/stories/8008c9d710b5400599f3c6cf88b2c546 Our online data dashboard is available here: redcap.link/TICS

Background Erythema nodosum leprosum (ENL) is a severe inflammatory complication of lepromatous leprosy characterised by recurrent inflammatory episodes often requiring prolonged immunosuppression. The severity of ENL can be quantified using the validated and reliable ENLIST ENL Severity Scale (EESS). The longitudinal course of ENL and how it is captured using standardised severity measures has not been well described. We prospectively evaluated the changes in ENL severity over time using the EESS in a randomised clinical trial. Methods We conducted a post-hoc analysis of participants enrolled in the Methotrexate and Prednisolone Study in ENL, an international multicentre randomised controlled trial conducted in Ethiopia, India, Indonesia, and Nepal. Adults with severe ENL (EESS score [&ge;]9) were followed for 60 weeks with repeated EESS assessments. Longitudinal trajectories were analysed using mixed-effects regression models. Item-level analyses characterised the clinical phenotype captured by the scale. Associations between EESS score, prednisolone exposure, and dermatology-specific health-related quality of life measured using the Dermatology Life Quality Index (DLQI) were examined. Findings A total of 135 participants contributed 1,958 EESS assessments. Mean EESS declined rapidly during the first four weeks of treatment (-2.10 points/week; 95% CI -2.36 to -1.84; p<0.001), increased modestly during reduction in corticosteroid dose (weeks 4-20), and gradually declined thereafter. Severe ENL (EESS score [&ge;]9) occurred in 20.6% of visits and was characterised primarily by pain and cutaneous inflammatory manifestations. Participants who required additional prednisolone had persistently higher EESS scores and showed limited improvement compared with those who did not receive additional prednisolone. Longitudinal EESS scores were strongly correlated with the DLQI score (Spearmans {rho}=0.75; p<0.001). Conclusion The EESS captures clinically meaningful changes in ENL severity, aligns with treatment decisions, and reflects patient-reported severity over time. These findings support the use of the EESS as a robust tool for monitoring ENL severity in both clinical research and routine care.

In view of the outstanding progress of machine learning (ML) and growing cost of health systems, it is a current challenge to incorporate artificial intelligence tools into actual medical practice. Here we explored the feasibility and reliability of using machine learning to perform an important immunological investigation that currently requires experienced biologists : Anti-nuclear cytoplasmic antibodies (ANCAs) are important markers for vasculitis and they may be evidenced by microscopic examination of cells labeled with patients' sera. The use of a reliable ML classifier to discriminate between positive and negative samples would increase the rapidity and decrease the cost of immunofluorescence-based ANCA detection. Here, we tested seven well-documented ML algorithms, ranging from simple models such as k nearest neighbors to more complex convolutional neural networks involving millions of adjustable parameter. We studied the feasibility and reliability of classifying 1114 serum samples that had been collected for about 3 years and assayed with conventional procedure. We compared four strategies consisting of assaying either whole microscope fields or individual cell images, and natural images or histograms. The following conclusions were obtained : (i) Several different strategies allowed us to build models stable enough to discriminate between positive and negative samples collected during about 27 months, with a comparison to human classification yielding a kappa index of about 0.7, that may be considered as fairly good and intermediate between the performance of junior and senior biologists. (ii) Simpler ML models combined with theoretical thinking might provide the most rapid and efficient way of developing a reliable test within the framework of a single institution. (iii) In addition, the interpretability of the simplest model provided some theoretical insight into important classification parameters. (iv) An important point and caveat is that the multiplicity and versatility of currently available tools make it an essential requirement to test repeatedly a given model, that must be chosen as simple as possible, to achieve a reliability compatible with medical use. It is concluded that our study provides a strong incentive to incorporate ML tools in well defined medical tests, which might reduce the risk of human errors and pave the way to fully automatic procedures.

Aptamers are single stranded DNA or RNA molecules selected for their high affinity and specificity to bind target molecules, similar to antibodies. They are commonly selected through the SELEX process, which involves the iterative exposure of a random sequence library to a target and retaining the sequences showing good binding properties. To improve Lyme disease detection, we propose designing aptamers that specifically bind to the CspZ protein on the surface of Borrelia burgdorferi, the bacterium responsible for the disease. Starting with a SELEX process consisting of thirteen rounds, from which selected in vitro sequence candidates have emerged, we aim to propose a holistic process that selects in silico new sequence candidates that are further validated experimentally. Our approach relies on 1) using Machine Learning (ML) techniques, specifically a Restricted Boltzmann Machine (RBM), to digitally replicate the last round of the SELEX process, 2) integrating insights from text analysis methods, such as word2vec and n-grams, into the RBM model trained on the final-round SELEX dataset to represent and compare newly generated sequences with in vitro candidates, 3) selecting in silico sequences with strong potential to bind to CspZ protein, 4) experimentally validating the selected in silico sequences of step 3. Our holistic approach combines biological insights with statistical models to improve the efficiency and outcome of the SELEX process. We enhance the RBM model, designed to replicate the distribution of the final SELEX round, by integrating geometric representations of sequences, which is especially advantageous when dealing with limited datasets relative to the vast sequence space. In addition, it provides in silico sequence candidates with strong binding properties.

Manual colony counting remains the rate-limiting, operator-dependent step in culture-based food microbiology quality control (QC). Automated colony analysis using machine learning (ML) offers the potential to standardise, accelerate, and improve the traceability of this process. However, systematic multi-method validation data for AI-based platforms against recognised international standards remain scarce. We conducted a prospective, multi-study validation of the Reshape Smart Incubator which is an automated imaging and ML-based colony analysis system, across eight ISO microbiological reference methods. In total, 887 plates were analysed, spanning qualitative (presence/absence) detection of Listeria spp. (ISO 11290-1) and Salmonella spp. (ISO 6579), and quantitative enumeration of total viable count (ISO 4833), Bacillus cereus (ISO 7932), Enterobacteriaceae (ISO 21528), coagulase-positive Staphylococci (ISO 6888), yeasts and moulds (ISO 21527), and lactic acid bacteria (ISO 15214). Automated results were benchmarked against the consensus of three or more trained technicians. The platform achieved 100% agreement with manual assessment for all both qualitative detection methods (ISO 11290-1, ISO 6579) with zero false positives and zero false negatives. For quantitative enumeration, agreement ranged from 92.97% (ISO 15214, n=122, using ISO-aligned {+/-}10%/>30 CFU thresholds) to 98.46% (ISO 21528, n=130). Where discrepancies occurred, they largely coincided with plates showing high inter-technician variability. Precision testing demonstrated a coefficient of variation of 5.88% and a mean standard deviation of 0.44 CFU for low-count plates. This study presents a comprehensive multi-ISO validation of an AI-based colony analysis system to date. The AI models demonstrated performance comparable to or exceeding that of trained human technicians across a broad range of microbiological targets, agar types, and colony morphologies, thereby supporting their use as a validated and traceable alternative to manual plate reading in accredited food microbiology quality control laboratories.

PurposeGlasdegib is a Sonic Hedgehog (SHH) pathway inhibitor used for treating newly diagnosed acute myeloid leukemia in elders or patients unfit for intensive chemotherapy. This study sought to demonstrate growth inhibition and increased apoptosis of B-cell acute lymphoblastic leukemia (B-ALL) in vitro under glasdegib, alone and combined with inotuzumab, using a novel co-culture system and validated chemosensitivity testing model to determine whether glasdegib with and without inotuzumab may represent a promising treatment strategy in B-ALL. MethodsSeven blood and marrow samples from B-ALL patients were co-cultured with HS-5 stromal cells in a co-culturing system designed to mimic the tumor microenvironment to maintain B-ALL cell viability for chemosensitivity testing under glasdegib and inotuzumab. ResultsCo-culturing improved B-ALL viability from four to nine days. Dosage-dependent responses to glasdegib were consistent among B-ALL samples on day four based on culture viability, and varied based on expressions of SSH genes GLI1, GLI3, SMO, and PTCH1. Combination with inotuzumab had varied effects on treatment response. ConclusionCo-culturing B-ALL cells with HS-5 stromal cells improves B-ALL growth and viability. Glasdegib with and without inotuzumab treatments impact the viability of co-cultured B-ALL cells by day four. SHH gene expressions suggest different B-ALL patients may be sensitive or resistant to glasdegib and inotuzumab.