Distribution, source apportionment, and ecological risk assessment of soil antibiotic resistance genes in urban green spaces.

Urban green spaces play a crucial role in cities by providing near-natural environments that greatly impacts the health of residents. However, these green spaces have recently been scrutinized as potential reservoirs of antibiotic resistance genes (ARGs), posing significant ecological risks. Despite this concern, our understanding of the distribution, sources, and ecological risks associated with ARGs remains limited. In this study, we investigated the spatial distribution of soil ARGs using spatial interpolation and auto-correlation analysis. To apportion the source of soil ARGs in urban green spaces of Tianjin, Geo-detector method (GDM) was employed. Furthermore, we evaluated the ecological risk posed by ARGs employing risk quotients (RQ). The results of our study showed a significantly higher abundance of Quinolone resistance genes in the soil of urban green spaces in Tianjin. These genes were mainly found in the northwest, central, and eastern regions of the city. Our investigation identified three main factors contributing to the presence of soil ARGs: antibiotic production, precipitation, livestock breeding, and hospital. The results of ecological risk in RQ value showed a high risk associated with Quinolone resistance genes, followed by Aminoglycoside, Tetracycline, Multidrug, MLSB, Beta Lactam, Sulfonamide, and Chloramphenicol. Mantel-test and correlation analysis revealed that the ecological risk of ARGs was greatly influenced by soil properties and heavy metals. This study provides a new perspective on source apportionment and the ecological risk assessment of soil ARGs in urban green spaces.

Blood and CSF findings of cellular immunity in anti-NMDAR encephalitis.

OBJECTIVES: To investigate the immunopathogenic mechanisms of anti-N-methyl-D-aspartate receptor encephalitis (NMDAR-E) by characterizing the changes of immune cells in both peripheral blood (PB) and cerebrospinal fluid (CSF) of patients with NMDAR-E. METHODS: Cytology and flow cytometry were used to explore and compare different immunological parameters in PB and CSF of patients with NMDAR-E, viral encephalitis (VE) and healthy volunteers. Moreover, different models were established to assess the possibility of identifying NMDAR-E patients based on PB and CSF parameters. RESULTS: The neutrophil counts and monocyte-to-lymphocyte ratios (MLR) in PB are higher in NMDAR-E patients than in both VEs and controls (P < 0.001, respectively), while the percentages of CD3 + T, CD4 + T lymphocytes, and the leukocytes count in CSF were lower in NMDAR-Es than in VEs (P < 0.01, respectively). The higher percentages of CD8 + T cells in blood and CSF were both correlated with more severe NMDAR-E (P < 0.05, respectively). The poor neurological status group had significantly higher PB leukocytes but lower CSF leukocyte count (P < 0.05). Longitudinal observations in patients with NMDAR-E showed a decreasing trend of leukocyte count, neutrophils count, neutrophil-to-monocyte ratios (NMR), and neutrophil-to-lymphocyte ratios (NLR) with the gradual recovery of neurological function. CONCLUSIONS: The expression patterns of T lymphocyte subsets were different in patients with NMDAR-E and viral encephalitis. The changing trends of leukocyte and lymphocyte populations in peripheral blood and cerebrospinal fluid may provide clues for the diagnosis of different types of encephalitides, including NMDARE, and can be used as immunological markers to assess and predict the prognosis.

Microplastics could alter invasive plant community performance and the dominance of Amaranthus palmeri.

The increase in alien plant invasions poses a major threat to global biodiversity and ecosystem stability. However, the presence of microplastics (MPs) as an environmental stressor could impact the interactions between invasive and native species in an invasive plant community. Nevertheless, the community alterations and underlying mechanisms resulting from these interactions remain unclear. Herein, we systematically investigated the impacts of polyethylene (PE) and polypropylene (PP) on invasive plant communities invaded by Amaranthus palmeri through soil seed bank. The results illustrated that MPs markedly declined community height and biomass, and altered community structure, low-dose MPs could prominently increase community invasion resistance, but reduced community stability. The niche width and niche overlap of A. palmeri and S. viridis declined when exposed to high-dose MPs, but MPs elicited a significant rise in the niche width of S. salsa. PP had the potential to reduce the diversity of invasive plant community. Structural equation model revealed that PP addition could change soil total phosphorus content, thereby leading to a reduction of the community stability. Our study helps to fill the knowledge gap regarding the effects of MPs on invasive plant communities and provide new perspectives for invasive plant management.

Biochar may alter plant communities when remediating the cadmium-contaminated soil in the saline-alkaline wetland.

It is thought remediating cadmium pollution with biochar can affect plant traits. However, the potential impact of this practice on plant communities is poorly understood. Here, we established natural-germinated plant communities using soil seed bank from a saline-alkaline wetland and applied a biochar treatment in Cd-polluted wetland soil. The outcomes illustrated that Juglans regia biochar (JBC), Spartina alterniflora biochar (SBC), and Flaveria bidentis biochar (FBC) promoted exchangeable Cd transform into FeMn oxide bound Cd. Additionally, most biochar addition reduced species abundance, root-shoot ratio, biomass, diversity, and community stability, yet enhanced community height. Among all treatments, the 5 % SBC demonstrated the most significant reduction in species abundance, biomass, species richness and functional richness. Specifically, it resulted in a reduction of 92.80 % in species abundance, 73.80 % in biomass, 66.67 % in species richness, and 95.14 % in functional richness compared to the CK. We also observed changes in root morphological traits and community structure after biochar addition. Soil pH, salinity, and nutrients played a dominant role in shaping plant community. These findings have implications for biodiversity conservation, and the use of biochar for the remediation of heavy metals like cadmium should be approached with caution due to its potential negative impacts on plant communities.

A comprehensive method of source apportionment and ecological risk assessment of soil heavy metals: A case study in Qingyuan city, China.

The study combined multiple models to provide a deeper understanding to soil heavy metal contamination and source information, which are essential for controlling pollution and reducing human health risks. In this study, the agricultural soils were collected from the Qingyuan City of China as an example. The multiple models (APCS/MLR, PMF, and GDM) were used to identify and quantitatively apportion the main sources of heavy metal pollution in the area. The results showed that Cu (56.4 %), Ni (70.9 %), B (44.5 %), and Cr (72.8 %) were associated with natural sources, such as soil parent material and soil-forming processes. However, Pb (41.2 %), Zn (61.8 %), Hg (67.0 %), and Cd (69.6 %) were associated with agricultural activities, atmospheric deposition, vehicle exhaust emissions, and vehicle tires, while Mo, Se, and Mn were possibly derived from natural sources, including rock weathering and soil parent materials. Additionally, the network of environmental analysis revealed that soil microbes are far more sensitive to soil heavy metal pollution than herbivores, vegetation, and carnivores. This study can serve as a guideline for reducing the ecological and health risks associated with heavy metals in soil by controlling their preferential sources. Environmental implication Combining multiple models is more effective approach to wide understanding of heavy metal contamination and source information, which is essential for controlling pollution and reducing human health risks. Based on multiple models (APCS/MLR, PMF, and GDM) and network environ analysis, a comprehensive method for apportioning soil heavy metal sources and assessing ecological risk had been provided. Further, the present study can be a guideline for reducing ecological and health risks by heavy metals in soil by controlling preferential sources.

Genome-wide association study of tuberculosis in the western Chinese Han and Tibetan population.

Tuberculosis (TB) remains a serious global public health threat. Accumulated evidence has demonstrated that human susceptibility to TB has a strong genetic basis. And different susceptibility single nucleotide polymorphisms (SNP) have been reported in different studies. To gain greater insight into the host susceptibility to TB, we perform a two-stage genome-wide association study to identify the susceptible loci of TB. In the discovery stage, 3116 (1532 TB patients and 1584 healthy controls) and 439 (211 TB patients and 228 healthy controls) individuals were genome-wide genotyped from a western Chinese Han and Tibetan population, respectively. Based on the additive genetic model, we discovered 14 and three independent loci that had potential associations with TB susceptibility in the Chinese Han and Tibetan populations, respectively (p < 1 × 10-5). Furthermore, we conducted an imputation-based meta-analysis on another two East Asia cohorts to replicate our findings. We identified one independent locus harbored by the human leukocyte antigen (HLA) class II genes that was genome-wide significantly associated with TB (lead SNP rs111875628 with a p-value of 2.20 × 10-9). Our findings suggest a novel mechanism of the interaction with the HLA class II genes and reinforce the importance of the HLA class II alleles in response to TB.

In situ electrodeposition of bismuth oxide nanowires @MWNT on the carbon fiber microelectrode for the sensitively electrochemical detection of folic acid.

A microminiaturized electrochemical device, BiO@CNW/CFE was fabricated based on the in situ co-electrodeposition of bismuth oxide nanowires (BiNWs) and multi-walled carbon nanotubes (MWNTs) on the surface of carbon fiber electrode (CFE). The nanostructure of BiNWs could bind MWNTs on the surface of CFE during the precipitation of bismuth at the potential of -1.1 V. The vimineous nanostructure of BiO@CNW improved the surface area and electrochemical activity of the microelectrode. With the low background noise, folic acid (FA) can be detected sensitively by BiO@CNW/CFE based on the electrochemical reduction via the method of square wave voltammetry. The linear range of FA in sodium acetate-acetic acid buffer was achieved in the range of 5.00 nM-200 nM, the detection limit was estimated to be 0.63 nM. The recoveries of FA in human serum and artificial cerebral spinal fluid were between 99% and 103%, which indicates BiO@CNW/CFE was a reliable sensor for the detection of FA in biological samples.

Genetic architecture of tuberculosis susceptibility: A comprehensive research synopsis, meta-analyses, and epidemiological evidence.

To date, many studies have been conducted to investigate associations between variants and tuberculosis risk; however, the results have been inconclusive. Here, we systematically provide a summary of the understanding of the genetic architecture of tuberculosis susceptibility. We searched PubMed, Embase and Web of Science to identify genetic association studies of tuberculosis published through October 31, 2021. We conducted meta-analyses for the genetic association with tuberculosis risk. We graded levels of cumulative epidemiological evidence of significant associations with risk of tuberculosis and false-positive report probability tests. We performed functional annotations for these variants using data from the Encyclopedia of DNA Elements (ENCODE) Project and other databases. We identified 703 eligible articles comprising 298,074 cases and 879,593 controls through screening a total of 24,398 citations. Meta-analyses were conducted for 614 genetic variants in 469 genes or loci. We found 39 variants that were nominally significantly associated with tuberculosis risk. Cumulative epidemiological evidence for a significant association was graded strong for 9 variants in or near 9 genes. Among them, 5 variants were associated with tuberculosis risk in at least three main ethnicity (African, Asian and White) which together explained approximately 9.59% of the familial relative risk of tuberculosis. Data from ENCODE and other databases suggested that 8 of these 9 genetic variants with strong evidence might fall within putative functional regions. Our study summarizes the current literature on the genetic architecture of tuberculosis susceptibility and provides useful data for designing future studies to investigate the genetic association with tuberculosis risk.

Chinese abnormal compound heterozygote spinocerebellar ataxia type 8: a case report.

CASE REPORTS: An elderly Chinese male patient was diagnosed with compound heterozygous spinocerebellar ataxia type 8; molecular diagnosis found that the (CTA)n(CTG)n repeat unit of his ATXN8/ATXN8OS gene was 134/93. The patient has a 6-year medical history, mainly manifested by ataxia, dysarthria, abnormal eye movements, and pyramidal signs. Magnetic resonance imaging (MRI) showed no obvious abnormalities in the medulla oblongata and cervical spinal cord except for cerebellar atrophy and sulci enlargement. There are heterozygous SCA8 individuals among his family members, but there are significant differences in their onset age and clinical manifestations. DISCUSSION AND CONCLUSION: This case reminds us that (CTA)n(CTG)n repeats are very prone to dynamic mutations in intergenerational inheritance, and the ATXN8/ATXN8OS gene penetrance is different in different SCA8 individuals, which suggests that genetic detection is of great importance.

Cytokine/chemokine levels in the CSF and serum of anti-NMDAR encephalitis: A systematic review and meta-analysis.

Objectives: To summarize the cytokine/chemokine levels of anti-N-methyl-Daspartate receptor encephalitis (NMDAR-E) and explore the potential role of these molecules and immune cells in the pathogenic mechanism. Methods: The PubMed, Cochrane Library, Embase, and Web of Science databases were searched for various articles that assessed the concentrations of cytokines/chemokines in the unstimulated cerebrospinal fluid (CSF) or serum of patients with NMDAR-E in this systematic review and meta-analysis. The standardized mean difference (SMD) and 95% confidence interval (CI) were calculated by Stata17.0. Results: A total of 19 articles were included in the systematic review from 260 candidate papers, and cytokine/chemokine levels reported in the CSF/serum were examined in each article. This meta-analysis included 17 eligible studies comprising 579 patients with NMDAR-E, 367 patients with noninflammatory neurological disorders, and 42 healthy controls from China, Spain, South Korea, Australia, Czechia, and Sweden. The results indicated that the levels of different cytokines interleukin (IL)-6, tumor necrosis factor (TNF)-α, IL-10, IL-13, IL-1ß, IL-12, and IL-17 and chemokine C-X-C motif ligand (CXCL)10 in the CSF were significantly higher in NMDAR-E patients with a large effect size. In addition, B cell activating factor (BAFF), CXCL13, and interferon (IFN)-γ levels in the CSF were higher in NMDAR-E patients with a middle effect size. In contrast, levels of IL-2 and IL-4 in the CSF and CXCL13 and BAFF in the serum did not show a significant difference between cases and controls. Conclusions: These analyses showed that the central immune response in NMDAR-E is a process that involves multiple immune cell interactions mediated by cytokines/chemokines, and T cells play an important role in the pathogenesis of immunity. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier (CRD42022342485).

Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19.

The worldwide pandemic of coronavirus disease 2019 (COVID-19) presents us with a serious public health crisis. To combat the virus and slow its spread, wider testing is essential. There is a need for more sensitive, specific, and convenient detection methods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Advanced detection can greatly improve the ability and accuracy of the clinical diagnosis of COVID-19, which is conducive to the early suitable treatment and supports precise prophylaxis. In this article, we combine and present the latest laboratory diagnostic technologies and methods for SARS-CoV-2 to identify the technical characteristics, considerations, biosafety requirements, common problems with testing and interpretation of results, and coping strategies of commonly used testing methods. We highlight the gaps in current diagnostic capacity and propose potential solutions to provide cutting-edge technical support to achieve a more precise diagnosis, treatment, and prevention of COVID-19 and to overcome the difficulties with the normalization of epidemic prevention and control.

Development and Validation of a LASSO Prediction Model for Better Identification of Ischemic Stroke: A Case-Control Study in China.

BACKGROUND: Timely diagnosis of ischemic stroke (IS) in the acute phase is extremely vital to achieve proper treatment and good prognosis. In this study, we developed a novel prediction model based on the easily obtained information at initial inspection to assist in the early identification of IS. METHODS: A total of 627 patients with IS and other intracranial hemorrhagic diseases from March 2017 to June 2018 were retrospectively enrolled in the derivation cohort. Based on their demographic information and initial laboratory examination results, the prediction model was constructed. The least absolute shrinkage and selection operator algorithm was used to select the important variables to form a laboratory panel. Combined with the demographic variables, multivariate logistic regression was performed for modeling, and the model was encapsulated within a visual and operable smartphone application. The performance of the model was evaluated on an independent validation cohort, formed by 304 prospectively enrolled patients from June 2018 to May 2019, by means of the area under the curve (AUC) and calibration. RESULTS: The prediction model showed good discrimination (AUC = 0.916, cut-off = 0.577), calibration, and clinical availability. The performance was reconfirmed in the more complex emergency department. It was encapsulated as the Stroke Diagnosis Aid app for smartphones. The user can obtain the identification result by entering the values of the variables in the graphical user interface of the application. CONCLUSION: The prediction model based on laboratory and demographic variables could serve as a favorable supplementary tool to facilitate complex, time-critical acute stroke identification.

Pulmonary alveolar proteinosis complicated with tuberculosis: A case report.

BACKGROUND: Pulmonary alveolar proteinosis (PAP) is a rare lung disease characterized by the accumulation of phospholipoproteinaceous material in the alveoli. Cases of PAP complicated with tuberculosis are much more complex and have rarely been well recorded. CASE SUMMARY: We describe a 21-year-old Han Chinese patient with suspicious lung infection associated with mild restrictive ventilatory dysfunction and diffusion reduction. High resolution computed tomography revealed a "crazy-paving" appearance and multiple pulmonary miliary nodules around the bronchi. Bronchoalveolar lavage demonstrated a small amount of periodic acid-Schiff positive proteinaceous materials. A serological test for the presence of a Mycobacterium tuberculosis antibody and an interferon-gamma release assay were both positive. The patient received a standard course of first-line anti-tuberculosis treatment after diagnostic bronchoalveolar lavage. To date, clinical remission has been achieved and maintained for five years. CONCLUSION: In summary, the diagnosis of PAP complicated with tuberculosis was supported by a combination of clinical manifestations, imaging, pulmonary function, laboratory examinations, bronchoalveolar lavage, etc. This case highlighted that diagnostic bronchoalveolar lavage in combination with anti-tuberculosis treatment is a safe and effective option for mild PAP patients with tuberculosis.

Development and Validation of a Predictive Model for Severe COVID-19: A Case-Control Study in China.

Background: Predicting the risk of progression to severe coronavirus disease 2019 (COVID-19) could facilitate personalized diagnosis and treatment options, thus optimizing the use of medical resources. Methods: In this prospective study, 206 patients with COVID-19 were enrolled from regional medical institutions between December 20, 2019, and April 10, 2020. We collated a range of data to derive and validate a predictive model for COVID-19 progression, including demographics, clinical characteristics, laboratory findings, and cytokine levels. Variation analysis, along with the least absolute shrinkage and selection operator (LASSO) and Boruta algorithms, was used for modeling. The performance of the derived models was evaluated by specificity, sensitivity, area under the receiver operating characteristic (ROC) curve (AUC), Akaike information criterion (AIC), calibration plots, decision curve analysis (DCA), and Hosmer-Lemeshow test. Results: We used the LASSO algorithm and logistic regression to develop a model that can accurately predict the risk of progression to severe COVID-19. The model incorporated alanine aminotransferase (ALT), interleukin (IL)-6, expectoration, fatigue, lymphocyte ratio (LYMR), aspartate transaminase (AST), and creatinine (CREA). The model yielded a satisfactory predictive performance with an AUC of 0.9104 and 0.8792 in the derivation and validation cohorts, respectively. The final model was then used to create a nomogram that was packaged into an open-source and predictive calculator for clinical use. The model is freely available online at https://severeconid-19predction.shinyapps.io/SHINY/. Conclusion: In this study, we developed an open-source and free predictive calculator for COVID-19 progression based on ALT, IL-6, expectoration, fatigue, LYMR, AST, and CREA. The validated model can effectively predict progression to severe COVID-19, thus providing an efficient option for early and personalized management and the allocation of appropriate medical resources.

Novel Long Non-coding RNA and LASSO Prediction Model to Better Identify Pulmonary Tuberculosis: A Case-Control Study in China.

INTRODUCTION: The insufficient understanding and misdiagnosis of clinically diagnosed pulmonary tuberculosis (PTB) without an aetiological evidence is a major problem in the diagnosis of tuberculosis (TB). This study aims to confirm the value of Long non-coding RNA (lncRNA) n344917 in the diagnosis of PTB and construct a rapid, accurate, and universal prediction model. METHODS: A total of 536 patients were prospectively and consecutively recruited, including clinically diagnosed PTB, PTB with an aetiological evidence and non-TB disease controls, who were admitted to West China hospital from Dec 2014 to Dec 2017. The expression levels of lncRNA n344917 of all patients were analyzed using reverse transcriptase quantitative real-time PCR. Then, the laboratory findings, electronic health record (EHR) information and expression levels of n344917 were used to construct a prediction model through the Least Absolute Shrinkage and Selection Operator algorithm and multivariate logistic regression. RESULTS: The factors of n344917, age, CT calcification, cough, TBIGRA, low-grade fever and weight loss were included in the prediction model. It had good discrimination (area under the curve = 0.88, cutoff = 0.657, sensitivity = 88.98%, specificity = 86.43%, positive predictive value = 85.61%, and negative predictive value = 89.63%), consistency and clinical availability. It also showed a good replicability in the validation cohort. Finally, it was encapsulated as an open-source and free web-based application for clinical use and is available online at https://ziruinptb.shinyapps.io/shiny/. CONCLUSION: Combining the novel potential molecular biomarker n344917, laboratory and EHR variables, this web-based prediction model could serve as a user-friendly, accurate platform to improve the clinical diagnosis of PTB.

Lithium cobalt phosphate electrode for the simultaneous determination of ascorbic acid, dopamine, and serum uric acid by differential pulse voltammetry.

Lithium cobalt phosphate (LCP) was prepared and modified on the surface of glassy carbon electrode (GCE) to fabricate the electrochemical sensor (LCP/GCE) for the simultaneous determination of ascorbic acid (AA), dopamine (DA), and serum uric acid (UA). The homogenous incorporation of carbon improved the conductivity of LCP. Benefiting from the small particle size distribution, LCP/GCE has a large active surface and responds to AA, DA, and UA sensitively and rapidly. For the simultaneous detection with differential pulse voltammetry the anodic peaks of AA, DA, and UA were well-separated and appeared at ~0 V, ~0.19 V, and ~ 0.33 V (vs. Ag/AgCl), respectively. The linear responses toward AA, DA, and UA were in the range 10 µM-8.0 mM, 10 nM-10 µM, and 0.020 µM-25 µM; the detection limits were estimated to be 8.10 µM, 7.50 nM, and 22.7 nM (S/N = 3), respectively. The excellent selectivity and reproducibility of LCP/GCE enable serum UA to be detected without the interference of AA and DA. The recoveries of DA and AA in the serum sample were in the range 95 to 111%. The results indicate that LCP has the potential to be developed as the sensing devices to be applied to in vitro diagnosis. The lithium-ion battery cathodic material, LCP with the excellent adsorption and catalytic behavior, was utilized to fabricate the electrochemical sensor for the sensitive and simultaneous detection of AA, DA, and UA, which achieved the low detection limits and the wide concentration ranges. LCP/GCE can be used for the quantitative detection of serum UA without the interference of DA and AA. In addition, the recoveries of DA and AA in human serum were satisfactory, which illustrate the reliability of LCP/GCE to be applied to in vitro diagnosis.

Potential Fluid Biomarkers and a Prediction Model for Better Recognition Between Multiple System Atrophy-Cerebellar Type and Spinocerebellar Ataxia.

OBJECTIVE: This study screened potential fluid biomarkers and developed a prediction model based on the easily obtained information at initial inspection to identify ataxia patients more likely to have multiple system atrophy-cerebellar type (MSA-C). METHODS: We established a retrospective cohort with 125 ataxia patients from southwest China between April 2018 and June 2020. Demographic and laboratory variables obtained at the time of hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) regression and logistic regression to construct a diagnosis score. The receiver operating characteristic (ROC) and decision curve analyses were performed to assess the accuracy and net benefit of the model. Also, independent validation using 25 additional ataxia patients was carried out to verify the model efficiency. Then the model was translated into a visual and operable web application using the R studio and Shiny package. RESULTS: From 47 indicators, five variables were selected and integrated into the prediction model, including the age of onset (AO), direct bilirubin (DBIL), aspartate aminotransferase (AST), eGFR, and synuclein-alpha. The prediction model exhibited an area under the curve (AUC) of 0.929 for the training cohort and an AUC of 0.917 for the testing cohort. The decision curve analysis (DCA) plot displayed a good net benefit for this model, and external validation confirmed its reliability. The model also was translated into a web application that is freely available to the public. CONCLUSION: The prediction model that was developed based on laboratory and demographic variables obtained from ataxia patients at admission to the hospital might help improve the ability to differentiate MSA-C from spinocerebellar ataxia clinically.

High Dose Steroids as First-Line Treatment Increased the Risk of In-Hospital Infections in Patients With Anti-NMDAR Encephalitis.

Objective: To address the effects of high dose steroids on in-hospital infection and neurologic outcome in anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis patients. Methods: We retrospectively reviewed the clinical data of anti-NMDAR encephalitis patients in West China Hospital, the Third Hospital of Mianyang and Mianyang Central Hospital between October 2011 and August 2020. The development of infections, inflammatory factors, neurologic outcome at discharge and risk factors for in-hospital infection were assessed in patients with and without high dose steroid therapy before and after immunotherapy. Least absolute shrinkage and selection operator (LASSO) regression and logistic regression models were established to assess risk factors for in-hospital infection. Results: A total of 278 patients with anti-NMDAR encephalitis were included in the study. Thirty-four patients received high dose methylprednisolone (IVMP) therapy only, 84 patients received intravenous immunoglobulin (IVIG) therapy, and 160 patients received IVIG and IVMP therapy. Compared with the IVIG group, IVIG + IVMP group had a higher infection rate (64.38% vs 39.29%, P < 0.001), a higher incidence of noninfectious complications (76.25% vs 61.90%, P = 0.018) and a higher modified Rankin Scale (mRS) score at discharge from the hospital (3 vs 2, P < 0.001). Inflammatory indicators, including white blood cell (WBC) count, neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII), were higher (9.93 vs 5.65, 6.94 vs 3.47 and 1.47 vs 0.70, respectively, P < 0.001) in the IVIG + IVMP group than in the IVIG group. Moreover, lymphocyte-to-monocyte ratio (LMR) was lower (2.20 vs 2.54, P = 0.047) in the IVIG + IVMP group. The LASSO model showed that mRS score on admission, seizure, body temperature, uric acid (URIC), cerebrospinal fluid immunoglobulin G (CSF IgG), NLR and LMR were risk factors for in-hospital infection. The prediction model exhibited an area under the curve (AUC) of 0.885. Conclusions: High dose steroids therapy was significantly associated with higher in-hospital infectious complication rates and a poor short-term prognosis in relatively severe anti-NMDAR encephalitis patients. The established prediction model might be helpful to reduce the risk of in-hospital infection.

Assessing the role of SH3RF1 and SH3RF2 polymorphisms in susceptibility to tuberculosis: A case-control study in the Han Chinese population.

BACKGROUND: Tuberculosis (TB) remains a major public health problem. SH3RF1 and SH3RF2 are candidate genes with multiple single-nucleotide polymorphisms (SNPs) that have the potential to participate in Mycobacterium infection via activation of the JNK signaling pathway. In this case-control study, we aimed to investigate the association of five SH3RF1 and SH3RF2 SNPs with susceptibility to TB in the Western Chinese population. METHODS: A total of 900 TB patients and 1534 healthy control subjects were enrolled in our study. All samples used were obtained from the Bio-Bank of resources of Tuberculosis Research in the Department of Laboratory Medicine, West China Hospital, Sichuan University, China. SNP genotyping was conducted using a commercial custom-by-design 2 × 48-Plex SNPscan Kit. RESULTS: The rs758037 variant of the SH3RF2 gene was found to be associated with decreased TB risk based on allelic effects (p = 0.00001, OR = 0.731, 95% CI = 0.641-0.833) and three genetic models (padd = 0.00001, pdom = 0.0003, prec = 0.0007) after the data were controlled for age and gender and underwent Bonferroni correction. The rs4913057 variant of the SH3RF2 gene was found to be associated with increased TB risk in a dominant model (p = 0.021, OR: 1.260, 95% CI: 1.065-1.490). No significant association was observed between other SNPs and TB risk. CONCLUSION: These findings indicate that polymorphisms in the SH3RF2 gene are involved in susceptibility to TB in the Western Chinese population.