DPT Laboratories

Cholera is a life-threatening diarrheal disease caused by Vibrio cholerae, with recurring outbreaks in Iraq, including the Kurdistan Region. Despite its endemic nature, outbreaks have primarily been reported by the health sector without comprehensive molecular epidemiological investigations. Limited studies have characterized outbreak dynamics, prevalence, and antimicrobial resistance, hindering effective public health interventions. This study aimed to analyze the prevalence, molecular characteristics, and antibiotic resistance of V. cholerae isolates from the 2023 outbreak in Sulaymaniyah, Kurdistan, Iraq. A total of 1200 diarrheic stool samples were collected from Shar Hospital between July and October 2023. Bacterial isolation was performed using microbiological methods and automated VITEK 2 analysis, followed by serological identification (O1 and O139 antisera) and 16S rRNA gene sequencing. Antibiotic susceptibility testing (AST) was conducted to assess resistance patterns. The outbreak prevalence was 0.015%, with the highest infection rate in August (0.009%). The overall infection rate was 28.91% (347/1200), with the most affected age groups being 19–33 years (27.66%) and 34–48 years (26.22%). Infection was more common in females (55.6%) than males (44.4%). Phylogenetic analysis revealed high genetic similarity to the V. cholerae Kuwait1 strain, suggesting potential introduction from southern Iraq, possibly due to an influx of tourists. Furthermore, antibiotic susceptibility testing revealed that all V. cholerae isolates were susceptible to most tested antibiotics; however, complete resistance (100%) was observed against amikacin, amoxicillin, amoxiclav, nalidixic acid, and trimethoprim, with partial resistance (30%) to tetracycline. Cholera remains a major public health concern in Kurdistan, particularly in Sulaymaniyah, due to recurrent outbreaks. Molecular techniques provided crucial insights into outbreak tracking and genetic relatedness, while AST profiling highlighted the urgent need for revised treatment guidelines. Strengthening water sanitation, continuous antimicrobial resistance monitoring, and targeted public health interventions are essential for preventing future outbreaks.

Background Potassium binders mitigate hyperkalemia, allowing patients to maintain their renin-angiotensin-aldosterone-system inhibitor (RAASi) treatment. This study characterized patients treated with first- or second-generation potassium binders, usage patterns and their effectiveness in reducing potassium levels, and changes in RAASi treatment in a Swedish population-based study. Methods A National Cohort included patients who had record of a treatment episode with a first-generation or second-generation potassium binder between 2018 and 2022. A Mid-Sweden Cohort included patients from the National Cohort who also had a record of a potassium measurement within the 60 days prior to beginning potassium binder treatment. Comorbidities, prior medication use, persistence with potassium binder treatment, subsequent changes in potassium levels and RAASi treatment were evaluated. Persistence was analyzed using the Kaplan-Meier estimator and changes in potassium levels were assessed using linear mixed-effects models. Results 23,892 treatment episodes involving 14,235 patients (mean age 70 years, 33% women) were followed in the National Cohort, and 4860 episodes involving 3179 patients (mean age 72 years, 34% women) in the Mid-Sweden Cohort. Patients treated with second-generation potassium binders had more comorbidities and higher median persistence with treatment compared to those on first-generation potassium binders, 112.5 (95% CI:112.5-117.5) vs. 87.5 (95% CI: 87.5–87.5) days in the National Cohort; 165.5 (95% CI: 121.0-198.0) vs. 97.6 (95% CI: 87.5–110.0) days in the Mid-Sweden Cohort. Both first- and second-generation potassium binders reduced potassium levels from baseline by day 15, 5.7 [95% CI: 4.5–6.8] mmol/L to 4.7 [95% CI: 3.6–5.9] mmol/L and 5.5 (95% CI: 4.3–6.7) mmol/L to 4.9 (95% CI: 3.8–6.1) mmol/L, respectively. Dose reduction or discontinuation of renin-angiotensin system inhibitors (RASi) or mineralocorticoid receptor antagonists (MRAs) was found in 31.4% and 47.7%, respectively, within 120 days of initiating therapy. Conclusion Both potassium binders effectively reduced potassium levels, but frequent discontinuation or dose reduction of RAASi therapy were still observed during this period. The adjustments of RAASi therapy, despite the achievement of normokalemia within 15 days, may be premature and warrants careful reconsideration to ensure optimal patient outcomes.

Background and aims Body fat is a key body composition parameter monitored in soccer. Identifying reliable alternatives to laboratory techniques for assessing body fat during the competitive period is essential. This study aimed to evaluate the cross-sectional and longitudinal validity of anthropometric prediction equations in elite female soccer players. Methods Eighteen female soccer players (age: 26.6 [3.8] years; height: 168 [6.3] cm; body mass: 64.1 [7.4] kg; body mass index: 22.7 [1.9] kg/m²) from an Italian Serie A team were assessed at four time points during a competitive season. Fat mass was estimated using anthropometric equations by Evans and Warner and compared to dual-energy X-ray absorptiometry (DXA), which served as the reference method. Results Cross-sectional agreement analysis revealed a bias of -4.5% with Warner’s equation, while Evans’s equation showed no bias compared to DXA, with coefficient of determination (R²) values of 0.69 and 0.70, respectively. Both methods showed a negative association (Evans: r = -0.53, Warner: r = -0.63) when the difference between the values and the mean with DXA were correlated. Longitudinal agreement analysis showed no significant differences in fat mass changes between the anthropometric equations and DXA, with R² values ranging from 0.68 to 0.83. The 95% limits of agreement between the methods for individual changes in fat mass ranged from − 3.3 to 3.2%. Furthermore, no significant changes (p > 0.05) in fat mass were observed over the season with any method. Conclusions At the group level, Evans’s equation provides valid estimates of fat mass, whereas it may overestimate values in players with low body fat and underestimate them in those with high fat mass. The Warner equation showed the same trend as Evans at the individual level, also resulting in poor accuracy at the group level. Despite this, both anthropometric equations are valid alternatives to DXA for monitoring fat mass changes during the season, with Evans’s equation showing superior overall performance.

Vitiligo is a common skin disorder involving depigmentation. A 308-nm excimer laser and piperine were shown to be useful for the treatment of vitiligo. The aim of this study was to investigate the effect of a 308-nm excimer laser combined with piperine in the treatment of vitiligo and the molecular mechanism by which this treatment promotes melanin synthesis through regulation of the paracrine activity of keratinocytes (KCs). In this study, cells and animals were treated with a 308-nm excimer laser and piperine. ELISA, Western blot analysis, immunofluorescence and RT‒qPCR were used to measure the levels of proteins and genes, and EdU, Transwell, and flow cytometric assays were used to assess cell proliferation and apoptosis. Treatment with the 308-nm excimer laser combined with piperine promoted KCs secretion of cytokines related to melanin production, restrained the secretion of proinflammatory cytokines, elevated the level of PTEN, decreased the level of PDK1, inhibited the phosphorylation of Akt, and facilitated the phosphorylation of GSK3b. After coculture of melanocytes (MCs) with KCs supernatant, the proliferation and migration of MCs increased, the apoptosis of MCs decreased, and the expression of melanin synthesis-related genes increased. Moreover, compared with the 308-nm excimer laser or piperine alone, the combined treatment had a more significant effect. Moreover, inhibiting PTEN weakened the effect of the combined treatment. Animal experiments revealed that a 308-nm excimer laser combined with piperine had a therapeutic effect on vitiligo. After combined treatment, the number of CD8 + T cells decreased, and the PTEN/PDK1/GSK3b pathway was activated, which increased melanin synthesis and alleviated the progression of vitiligo. In conclusion, a 308-nm excimer laser combined with piperine regulates KCs paracrine activity through the PTEN/PDK1/GSK3b molecular axis, promotes MCs proliferation and melanin synthesis, and alleviates the progression of vitiligo, which provides new targets for the clinical treatment of vitiligo.

Breast cancer remains a significant global health challenge, emphasizing the pressing need for innovative therapeutic approaches. Our thorough research investigates the potential of mesoporous polydopamine nanoparticles (MPDA) as a targeted treatment for breast cancer. Meticulously crafted, these nanoparticles were loaded with honokiol (HK), which is a natural product, and then coated with functionalized hyaluronic acid (HA) to boost their ability to target breast cancer cells that overexpress CD44 receptors. The deep penetrating and photothermal (PTT) composite nanosystem combined with low-dose metformin (Met) improves the efficacy of synergetic therapy against breast tumors. The designed nanosystem exhibited exceptional biocompatibility and stability, suggesting its suitability for therapeutic use. Our in vitro studies demonstrated that the nanosystem precisely targeted and penetrated breast cancer cells, resulting in significant cell death. Additionally, in vivo studies showed that the nanosystem markedly inhibited tumor growth compared to the control group. This tumor-inhibiting effect was due to the combined action of the encapsulated HK, free Met, and the photothermal effect induced by near-infrared laser irradiation. This combination potently stimulates the expression of cleaved caspase-3 and cleaved PARP proteins, ultimately triggering cell apoptosis and effectively curbing tumor proliferation. Our research not only underscores the promising potential of nanoparticles for targeted breast cancer therapy but also sets the stage for further exploration and development of novel nanomedicine-based therapeutic strategies.

Upon stimulation and activation, mast cells (MCs) release soluble mediators, including histamine, proteases, and cytokines. These mediators are often stored within cytoplasmic granules in MCs and may be released in a granulated form. The secretion of cytokines and chemokines occurs within hours following activation, with the potential to result in chronic inflammation. In addition to their role in allergic inflammation, MCs are components of the tumor microenvironment (TME). MicroRNAs (miRNAs) are small RNA molecules that do not encode proteins, but regulate post-transcriptional gene expression by binding to the 3’ non-coding regions of mRNAs. This plays a crucial role in the function of MC, including the key processes of MC proliferation, maturation, apoptosis, and activation. It has been demonstrated that miRNAs are also present in extracellular vesicles (EVs) secreted by MCs. EVs derived from MCs mediate intercellular communication by carrying miRNAs, affecting various diseases including allergic diseases, intestinal disorders, neuroinflammation, and tumors. These findings provide important insights into the therapeutic mechanisms and targets of miRNAs in MCs that affect diseases. This review discusses the relevance of miRNA production by MCs in regulating their own activity and the effect of miRNAs putatively produced by other cells in the control of MC activity and their participation in selected pathologies.

Background Previous studies have established a correlation between elevated levels of remnant cholesterol (RC) and the occurrence of type 2 diabetes mellitus (T2D) as well as insulin resistance (IR); however, the precise nature of these associations remains incompletely elucidated. This study aimed to evaluate the relationships between RC and IR, as well as RC and T2D, and to determine the extent to which IR mediated the relationship between RC and T2D. Methods This was an observational study that utilized cross-sectional methods to examine the general population in the National Health and Nutrition Examination Survey (NHANES) 1999–2020. The participants were divided into 4 groups according to the RC quartiles. The outcome was the prevalence of IR and T2D. Survey-weighted binary logistic regression analysis was used to analyze the associations, and the restricted cubic spline (RCS) curve was used to further analyze the nonlinear relationship. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic performance, and the areas under the curves (AUC) of RC, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) were compared using the DeLong test. The mediating effect of IR on the relationship between RC and T2D was evaluated through mediation analysis. Results A total of 23,755 participants (46.02 ± 18.48 years, 48.8% male) were included in our study. Higher RC levels were significantly associated with increased prevalence of both IR and T2D. After adjusting for potential confounders, logistic regression analysis showed that higher RC quartiles were associated with the increased prevalence of IR [Quartile 4 vs. Quartile 1: odds ratio (OR) (95% confidence interval, CI): 1.65 (1.41–1.94), p < 0.001] and T2D [Quartile 4 vs. Quartile 1: OR (95% CI): 1.24 (1.03–1.50), p = 0.024]. RCS analysis revealed two distinct nonlinear relationships: one between RC levels and the prevalence of IR (nonlinear p < 0.001), and another between RC levels and the prevalence of T2D (nonlinear p < 0.001). ROC curve analysis demonstrated that RC had the highest discriminative ability, significantly outperforming LDL-C, HDL-C, and TG in predicting both IR and T2D risk (all P < 0.001 by DeLong test). Mediation analysis revealed that IR significantly mediated the relationship between RC and T2D, with approximately 54.1% of the effect of RC on T2D being indirect through IR. Conclusions Higher RC level was associated with increased prevalence of IR and T2D. IR mediated 54.1% of the association between RC and T2D, suggesting that managing IR could be crucial in reducing the risk of T2D in individuals with elevated RC levels.

Bacterial vaginosis (BV) is an abnormal gynecological condition caused by the overgrowth of specific bacteria in the vagina. This study aims to develop a novel method for BV detection by integrating surface-enhanced Raman scattering (SERS) with machine learning (ML) algorithms. Vaginal fluid samples were classified as BV positive or BV negative using the BVBlue Test and clinical microscopy, followed by SERS spectral acquisition to construct the data set. Preliminary SERS spectral analysis revealed notable disparities in characteristic peak features. Multiple ML models were constructed and optimized, with the convolutional neural network (CNN) model achieving the highest prediction accuracy at 99%. Gradient-weighted class activation mapping (Grad-CAM) was used to highlight important regions in the images for prediction. Moreover, the CNN model was blindly tested on SERS spectra of vaginal fluid samples collected from 40 participants with unknown BV infection status, achieving a prediction accuracy of 90.75% compared with the results of the BVBlue Test combined with clinical microscopy. This novel technique is simple, cheap, and rapid in accurately diagnosing bacterial vaginosis, potentially complementing current diagnostic methods in clinical laboratories. IMPORTANCE The accurate and rapid diagnosis of bacterial vaginosis (BV) is crucial due to its high prevalence and association with serious health complications, including increased risk of sexually transmitted infections and adverse pregnancy outcomes. Although widely used, traditional diagnostic methods have significant limitations in subjectivity, complexity, and cost. The development of a novel diagnostic approach that integrates SERS with ML offers a promising solution. The CNN model’s high prediction accuracy, cost-effectiveness, and extraordinary rapidity underscore its significant potential to enhance the diagnosis of BV in clinical settings. This method not only addresses the limitations of current diagnostic tools but also provides a more accessible and reliable option for healthcare providers, ultimately enhancing patient care and health outcomes.

Lead is a pervasive environmental contaminant with significant health risks, particularly to children. It is known for its neurotoxic and immunotoxic effects, causing developmental, cognitive, and behavioral impairments. Despite extensive research, the mechanisms of lead toxicity remain unclear. Cytokines, which are critical in immune response and inflammation, have emerged as potential biomarkers for lead toxicity. The recent Centers for Disease Control and Prevention (CDC) update to the blood lead reference value (BLRV) to 3.5 µg/dL emphasizes the need to explore novel biomarkers and mechanisms. The study involved 100 healthy children aged 1 to 5 years, divided into two groups based on BLRV: elevated (≥ 3.5 µg/dL) and low (< 3.5 µg/dL). The research consisted of two phases: discovery and validation. Plasma samples were analyzed using RayBio® Human Cytokine Antibody Arrays and Enzyme-linked immunosorbent assay (ELISA) for cytokine levels. Ethical approval was obtained, and statistical analyses included t-tests, chi-squared tests, pearson correlations, and multivariate logistic regression. Protein-protein interaction (PPI), Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to explore the roles of significant differentially expressed proteins (DEPs). No significant differences in age, gender, or BMI between the two groups, but BLRV levels were significantly higher in the elevated BLRV group compared to the low BLRV group. In the discovery phase, significant changes in cytokine expression were identified, including increased levels of IL-6, IL-8, and IL-17, and decreased levels of BDNF, BMP-4, IGF-1, IL-7, IL-10, and Leptin. These findings were validated in the second phase using ELISA. Significant positive correlations were found between BLRV and IL-6, IL-8, and IL-17. Negative correlations were observed with BDNF, BMP-4, IGF-1, IL-7, IL-10, and Leptin. Multivariate regression confirmed that BLRV significantly affects these cytokine levels. PPI networks revealed that DEPs had strong interactions with multiple proteins, indicating their central role in lead toxicity. GO and KEGG analyses highlighted pathways related to neurotoxicity and inflammatory responses, including “negative regulation of myotube differentiation,” “neurotrophin signaling pathway,” and “alcoholism.” This study provides insights into the role of cytokines as biomarkers for lead toxicity and offers a comprehensive analysis of the mechanisms involved. The findings underscore the importance of early detection and intervention based on updated BLRV thresholds. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-81215-2.

One of the most applied procedures for the determination of trace analytes in complex matrices is QuEChERS (an acronym for Quick, Easy, Cheap, Effective, Rugged, and Safe). QuEChERS procedures include an extraction step followed by a dispersive solid-phase extraction (dSPE) for analytes cleaning-up from the matrix components. A challenging task in QuEChERS procedures is extracting and determining pesticides from samples of high fat such as milk samples. This challenge induced the innovation of new adsorbents for the clean-up step such as Z-Sep Plus® and EMR-Lipid® to enable removal of fatty matrix components without affecting the recovery of hydrophobic analytes. This work aims to apply experimental design to optimize the combined application of both QuEChERS clean-up adsorbents; Z-Sep Plus® and EMR-Lipid® in addition to other QuEChERS parameters in the determination of eight pesticides: hexachlorocyclohexane, dichlorodiphenyldichloroethane, dichlorodiphenyltrichloroethane, primiphos ethyl, diazinon, malathion, endrin, and dimethoate in milk matrix. This was augmented by optimization of GC–MS/MS and UPLC-MS/MS to detect and determine analytes in extracts. The experimental design of QuEChERS procedure enabled the optimization of Z-Sep Plus®- and EMR-Lipid®-added adsorbent amounts with other method parameters to enable the maximum recovery of analytes. Furthermore, the optimized methods enabled low detection limits of the studied pesticides within a short analysis time (28 min for GC and 12 min for LC methods, respectively). The procedure was validated according to European SANTE/11312/2021 Guideline. Quantitation limit ranged from 1.7 to 3.2 ng/mL for GC–MS/MS method and from 1.7 to 3 ng/mL for UPLC-MS/MS method. Greenness assessment of the methods followed four approaches indicating an excellent value of greenness for the proposed methods. Furthermore, 45 real milk samples collected from the Egyptian market were tested with the developed procedure for the presence of pesticides.

Whole genome sequencing (WGS) potentially represents a rapid approach for antimicrobial resistance genotype-to-phenotype prediction. However, the challenge still exists to predict fully minimum inhibitory concentrations (MICs) and antimicrobial susceptibility phenotypes based on WGS data. This study aimed to establish an artificial intelligence-based computational approach in predicting antimicrobial susceptibilities of multidrug-resistant Acinetobacter baumannii from WGS and gene expression data. Antimicrobial susceptibility testing (AST) was performed using the broth microdilution method for 10 antimicrobial agents. In silico multilocus sequence typing (MLST), antimicrobial resistance genes, and phylogeny based on cgSNP and cgMLST strategies were analyzed. High-throughput qPCR was performed to measure the expression level of antimicrobial resistance (AMR) genes. Most isolates exhibited a high level of resistance to most of the tested antimicrobial agents, with the majority belonging to the IC2/CC92 lineage. Phylogenetic analysis revealed undetected transmission events or local outbreaks. The percentage agreements between AMR phenotype and genotype ranged from 70.08% to 89.96%, with the coefficient of agreement (κ) extending from 0.025 and 0.881. The prediction of AST employed by deep neural network models achieved an accuracy of up to 98.64% on the testing data set. Additionally, several linear regression models demonstrated high prediction accuracy, reaching up to 86.15% within an error range of one gradient, indicating a linear relationship between certain gene expressions and the corresponding antimicrobial MICs. In conclusion, neural network-based predictions could be used as a tool for the surveillance of antimicrobial resistance in multidrug-resistant A. baumannii.

In response to the COVID-19 pandemic, the Iranian government swiftly implemented immediate and decisive measures to control the spread of the infection. This study aims to demonstrate the impact of restriction measure on air pollution, also to highlight the potential variability in results that can arias from different methodological approach. A comprehensive dual-approach assessment was conducted to evaluate the effect of the lockdown measures on criteria air pollutants. Firstly, a traditional approach compared air quality during the pandemic period with baseline conditions from 2013 to 2019. Secondly, observed air pollution values during different periods with varying restrictions in 2020 were compared with expected values. This comprehensive analysis allows for a robust comparison and quantification of the impact of different lockdown measures in Ahvaz. The study revealed significant changes in air pollutant concentrations in Ahvaz during 2020, with variations observed across different pollutants. Notable reductions were observed in O3 levels, particularly in November (-54.44% compared to the baseline) and December (-63.58% compared to expected values). Decreases in CO levels were observed in multiple months, while substantial reductions in PM10 and PM2.5 were observed during various periods. Inconsistencies in the magnitudes and directions of changes were found when comparing baseline and forecasted values. The overall stringency index showed an inverse association with changes in O3, NO2, and CO, with international travel controls and restrictions on internal movement having significant impacts. This study provides valuable insights into the impact of COVID-19 lockdown measures on air pollution in Ahvaz, Iran, using a comprehensive dual-approach assessment. The findings highlight the effectiveness of these measures in reducing specific criteria air pollutants and emphasize the importance of implementing appropriate strategies for air quality management during similar public health emergencies.

The excessive presence of antibiotics such as Oxytetracycline (OTC) in the wastewater has increased health problems due to their toxic impact on the aquatic ecosystem. Therefore, their removal has become an important topic. This study aims to produce high surface area-activated carbon derived from low-cost and environmentally friendly barley lignocellulosic wastes to remove OTC from aqueous solutions. The synthesized barley wastes-activated carbon (BW-AC) was characterized using Fourier-Transform Infrared spectroscopy, Thermal Gravimetric Analysis, X-ray diffraction analysis, N2 adsorption/desorption isotherms, and Scanning Electron Microscopy. A Central Composite Design under the Response Surface Methodology (CCD-RSM) was applied to optimize the operational parameters (adsorbent dosage, pH, OTC initial concentration, and contact time) affecting the adsorption capacity as the response factor. The optimum condition of OTC adsorption by BW-AC was the adsorbent dosage of 16.25 mg, pH of 8.25, initial concentration of 62.50 mg/L, and contact time of 23.46 min. An analysis of variance (ANOVA) was performed to investigate the significance of the designed quadratic model and evaluate the parameters interactions. The linear regression coefficient (R²) of 0.975 shows a good correlation between predicted and actual results. The adsorption isotherms were used to determine the contaminant distribution over the adsorbent surface, and the equilibrium data was best described by the Freundlich isotherm due to the R² value of 0.99 compared to other isotherms and β parameter of 0.23 in Redlich-Peterson equation. Moreover, the n value of 1.25 in Freundlich equation and E value of 0.31 in Dubinin–Radushkevich equation indicates a physical nature of adsorption process. According to the equations results, the maximum adsorption capacity of BW-AC for OTC removal was 500 mg/g, based on the Langmuir isotherm equation. In addition, the thermodynamic studies indicated an endothermic process based on the 0.31 value of ΔH° and spontaneous nature due to the negative amount of ΔG° within the temperature range of 288–318 K. Consequently, the prepared BW-AC can be deemed as a highly effective adsorbent with a large surface area, resulting in significant capacity for removing OTC. This synthesized BW-AC can serve as an environmentally friendly adsorbent for affordable wastewater treatment and is poised to make valuable contributions to future research in this field.

Gate set tomography (GST) characterizes the process matrix of quantum logic gates, along with measurement and state preparation errors in quantum processors. GST typically requires extensive data collection and significant computational resources for model estimation. We propose a more efficient GST approach for qudits, utilizing the qudit Hadamard and virtual Z gates to construct fiducials while assuming virtual Z gates are error-free. Our method reduces the computational costs of estimating characterization results, making GST more practical at scale. We experimentally demonstrate the applicability of this approach on a superconducting transmon qutrit. Published by the American Physical Society 2024

IgA antibodies play an important role in mucosal immunity. However, there is still no effective way to consistently boost mucosal IgA responses, and the factors influencing these responses are not fully understood. We observed that colonization with the murine intestinal symbiotic protozoan Tritrichomonas musculis (T.mu) boosted antigen-specific mucosal IgA responses in wild-type C57BL/6 mice. This enhancement was attributed to the accumulation of free arachidonic acid (ARA) in the intestinal lumen, which served as a signal to stimulate the production of antigen-specific mucosal IgA. When ARA was prevented from undergoing its downstream metabolic transformation using the 5-lipoxygenase inhibitor zileuton or by blocking its downstream biological signaling through genetic deletion of the Leukotriene B4 receptor 1 (Blt1), the T.mu-mediated enhancement of antigen-specific mucosal IgA production was suppressed. Moreover, both T.mu transfer and dietary supplementation of ARA augmented the efficacy of an oral vaccine against Salmonella infection, with this effect being dependent on Blt1. Our findings elucidate a tripartite circuit linking nutrients from the diet or intestinal microbiota, host lipid metabolism, and the mucosal humoral immune response.

Purpose Visceral adiposity is a significant risk factor for severe COVID-19. However, the impact of the Chinese visceral adiposity index (CVAI) on the efficacy of SARS-CoV-2 vaccines remains poorly understood. This study aims to explore the impact of CVAI on the production of neutralizing antibodies (NAb) in inactivated SARS-CoV-2 vaccines and the potential mechanism, thereby optimizing vaccination guidance. Methods In this cross-sectional study, 206 health workers (completed two SARS-CoV-2 vaccination on February 8th and March 10th, 2021, respectively) were recruited. All baseline anthropometric parameters of the participants were collected, and venous blood samples were obtained 6 weeks later to measure peripheral innate immune cells, inflammatory cytokines, and NAb titers against SARS-CoV-2. CVAI were calculated according to the formula and divided participants into two groups depending on CVAI median. Results The median NAb titer among healthcare workers was 12.94 AU/mL, with an efficacy of 87.86% for the SARS-CoV-2 vaccine. NAb titers were lower in the CVAI dysfunction group than in the CVAI reference group (median: 11.40 AU/mL vs 15.57 AU/mL), the hsCRP levels (median: 0.50 mg/L vs 0.30 mg/L) and peripheral monocyte count (mean: 0.47 × 10⁹/L vs 0.42 × 10⁹/L) in the CVAI dysfunction group were higher than in the CVAI reference group. Additionally, CVAI showed positive correlations with hsCRP, monocytes, lymphocytes, and B-lymphocytes, and a negative correlation with NAb titers. Conclusion CVAI may inhibit SARS-CoV-2 neutralizing antibody expression through inducing immune dysfunction and chronic inflammation. Thus, more attention should be paid to the vaccination for high CVAI population to improve the effectiveness of vaccination, which could provide more robust support for COVID-19 epidemic prevention and control.

Background National treatment guidelines of China evolving necessitates population-level surveillance of transmitted drug resistance (TDR) to inform or update HIV treatment strategies. Methods We analyzed the demographic, clinical, and virologic data obtained from people with HIV (PWH) residing in 31 provinces of China who were newly diagnosed between 2018 and 2023. Evidence of TDR was defined by the World Health Organization list for surveillance of drug resistance mutations. Results Among the 22 124 PWH with protease and reverse transcriptase sequences, 965 (4.36%; 95% CI, 4.1–4.63) had at least 1 TDR mutation. The most frequent TDR mutations were nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations (2.39%; 95% CI, 2.19%–2.59%), followed by nucleoside reverse transcriptase inhibitor mutations(1.35%; 95% CI, 1.2%–1.5%) and protease inhibitor mutations (1.12%; 95% CI, .98%–1.26%). The overall protease and reverse transcriptase TDR increased significantly from 4.05% (95% CI, 3.61%–4.52%) in 2018 to 5.39% (95% CI, 4.33%–6.57%) in 2023. A low level of integrase strand transfer inhibitor TDR was detected in 9 (0.21%; 95% CI, .1%–.38%) of 4205 PWH. Conclusions Presently, the continued use of NNRTI-based first-line antiretroviral therapy regimen for HIV treatment has been justified.

Purpose Tuberculosis (TB) remains a major health threat worldwide, and the spread of drug-resistant (DR) TB impedes the reduction of the global disease burden. Ebselen (EbSe) targets bacterial thioredoxin reductase (bTrxR) and causes an imbalance in the redox status of bacteria. Previous work has shown that the synergistic action of bTrxR and sensitization to common antibiotics by EbSe is a promising strategy for the treatment of DR pathogens. Thus, we aimed to evaluate whether EbSe could enhance anti-TB drugs against Mycobacterium marinum (M. marinum) which is genetically related to Mycobacterium tuberculosis (Mtb) and resistant to many antituberculosis drugs. Methods Minimum inhibitory concentrations (MIC) of isoniazid (INH), rifampicin (RFP), and streptomycin (SM) against M. marinum were determined by microdilution. The Bliss Independence Model was used to determine the adjuvant effects of EbSe over the anti-TB drugs. Thioredoxin reductase activity was measured using the DTNB assay, and its effects on bacterial redox homeostasis were verified by the elevation of intracellular ROS levels and intracellular GSH levels. The adjuvant efficacy of EbSe as an anti-TB drug was further evaluated in a mouse model of M. marinum infection. Cytotoxicity was observed in the macrophage cells Raw264.7 and mice model. Results The results reveal that EbSe acts as an antibiotic adjuvant over SM on M. marinum. EbSe + SM disrupted the intracellular redox microenvironment of M. marinum by inhibiting bTrxR activity, which could rescue mice from the high bacterial load, and accelerated recovery from tail injury with low mammalian toxicity. Conclusion The above studies suggest that EbSe significantly enhanced the anti-Mtb effect of SM, and its synergistic combination showed low mammalian toxicity in vitro and in vivo. Further efforts are required to study the underlying mechanisms of EbSe as an antibiotic adjuvant in combination with anti-TB drug MS.

Introduction Both the incidence and mortality rates associated with methicillin-resistant Staphylococcus aureus (MRSA) have progressively increased worldwide. A nucleic acid testing system was developed in response, enabling swift and precise detection of Staphylococcus aureus (S. aureus) and its MRSA infection status. This facilitates improved prevention and control of MRSA infections. Methods In this work, we introduce a novel assay platform developed by integrating Pyrococcus furiosus Argonaute (PfAgo) with recombinase polymerase amplification (RPA), which was designed for the simultaneous detection of the nuc and mecA genes in MRSA. Results This innovative approach enables visual MRSA detection within 55 mins, boasting a detection limit of 10² copies/μL. Characterized by its high specificity, the platform accurately identifies MRSA infections without cross-reactivity to other clinical pathogens, highlighting its unique capability for S. aureus infection diagnostics amidst bacterial diversity. Validation of this method was performed on 40 clinical isolates, demonstrating a 95.0% accuracy rate in comparison to the established Vitek2-COMPACT system. Discussion The RPA-PfAgo platform has emerged as a superior diagnostic tool, offering enhanced sensitivity, specificity, and identification efficacy for MRSA detection. Our findings underscore the potential of this platform to significantly improve the diagnosis and management of MRSA infection.

The exosomes derived from modified mesenchymal stem cells are a promising treatment for osteoarthritis (OA). The aim of this study was to explore the therapeutic effects of SOX9-overexpressing human umbilical cord mesenchymal stem cells (hucMSCs) exosomes on OA and their potential mechanisms. SOX9 was overexpressed in hucMSCs, and the exosomes derived from these modified hucMSCs were isolated (Exos SOX9 ). An IL-1β-stimulated OA chondrocytes model and a surgically induced OA rat model were established. These models were subsequently treated with the prepared exosomes. Western blot results indicated that the Exos SOX9 markedly enhanced the synthesis of cartilage extracellular matrix and inhibited its degradation in vitro. Histological, imaging, immunohistochemical, and chip analysis demonstrated that the Exos SOX9 markedly alleviated OA progression and decreased serum inflammatory markers in OA rats. Furthermore, the autophagy/Wnt signaling axis served as a potential target pathway for the Exos SOX9 in both in vivo and in vitro studies. Consequently, the Exos SOX9 may alleviate OA by simultaneously inhibiting the Wnt pathway and inducing autophagy. The findings indicate that the Exos SOX9 may represente a promising approach for cell-free therapy in OA.