BACKGROUND: Currently, lung cancer is one of the malignant tumors with a high morbidity and mortality all over the world. However, the exact mechanisms underlying lung cancer progression remain unclear. The tumor necrosis factor receptor associated factor (TRAF) family members are cytoplasmic adaptor proteins, which function as both adaptor proteins and ubiquitin ligases to regulate diverse receptor signalings, leading to the activation of nuclear factor kappa-B (NF-κB), mitogen-activated protein kinase (MAPK) and interferon regulatory factor (IRF) signaling. The aim of this study was to investigate the expression of TRAFs in different tissues and cancer types, as well as its mRNA expression, protein expression, prognostic significance and functional enrichment analysis in non-small cell lung cancer (NSCLC), in order to provide new strategies for the diagnosis and treatment of NSCLC. METHODS: RNA sequencing data from the The Genotype-Tissue Expression database was used to analyze the expression patterns of TRAF family members in different human tissues. RNA sequencing data from the Cancer Cell Line Encyclopedia database was used to analyze the expression patterns of TRAF family members in different types of cancer cell lines. RNA sequencing data from the The Cancer Genome Atlas (TCGA) database was used to analyze the mRNA levels of TRAF family members across different types of human cancers. Immunohistochemistry (IHC) analyses from HPA database were used to analyze the TRAF protein levels in NSCLC [lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC)]. Overall survival analysis was performed by Log-rank test using original data from Kaplan-Meier Plotter database to evaluate the correlation between TRAF expressions and prognosis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on the TRAF family-related genes using RNA sequencing data from the TCGA database for NSCLC. The correlation between the expression levels of TRAF family members and the tumor immune microenvironment was analyzed using the ESTIMATE algorithm based on RNA sequencing data from the TCGA database. RESULTS: The TRAF family members exhibited significant tissue-specific expression heterogeneity. TRAF2, TRAF3, TRAF6 and TRAF7 were widely expressed in most tissues, while the expressions of TRAF1, TRAF4 and TRAF5 were restricted to specific tissues. The expressions of TRAF family members were highly specific among different types of cancer cell lines. In mRNA database of LUAD and LUSC, the expressions of TRAF2, TRAF4, TRAF5 and TRAF7 were significantly upregulated; while TRAF6 did the opposite; moveover, TRAF1 and TRAF3 only displayed a significant upregulation in LUAD and LUSC, respectively. Except for TRAF3, TRAF4 and TRAF7, other TRAF proteins displayed an obviously deeper IHC staining in LUAD and LUSC tissues compared with normal tissues. Additionally, patients with higher expression levels of TRAF2, TRAF4 and TRAF7 had shorter overall survival; while patients with higher expression levels of TRAF3, TRAF5 and TRAF6 had significantly longer overall survival; however, no significant difference had been observed between TRAF1 expression and the overall survival. TRAF family members differentially regulated multiple pathways, including NF-κB, immune response, cell adhesion and RNA splicing. The expression levels of TRAF family members were closely associated with immune cell infiltration and stromal cell content in the tumor immune microenvironment, with varying positive and negative correlations among different members. CONCLUSIONS TRAF family members exhibit highly specific expression differences across different tissues and cancer types. Most TRAF proteins exhibit upregulation at both mRNA and protein levels in NSCLC, whereas, only upregulated expressions of TRAF2, TRAF4 and TRAF7 predict worse prognosis. The TRAF family members regulate processes such as inflammation, immunity, adhesion and splicing, and influence the tumor immune microenvironment.
Humans ; Carcinoma, Non-Small-Cell Lung/pathology* ; Lung Neoplasms/mortality* ; Prognosis ; Gene Expression Regulation, Neoplastic ; Tumor Necrosis Factor Receptor-Associated Peptides and Proteins/metabolism*

Chloropicrin is a commonly used pesticide in agricultural production. The clinical manifestations of oral poisoning patients are complex, and the lesions involve multiple organs. At present, the specific pathogenic mechanism of such poisoning is not clear, and the treatment experience is insufficient, so there are certain difficulties in clinical diagnosis, treatment and treatment. In this paper, the data of a patient with oral chloropicrin poisoning treated in Yidu Central Hospital of Weifang City in April 2023 were summarized. The patient was admitted to our hospital for treatment in time, and his condition improved after Hemopurification, methylene blue reduction, organ support, infection prevention as well as other symptomatic support. Oral chlorophenol can cause lung damage, skin and mucous membrane damage, and may have certain effects on the nervous system and kidney. Early intervention, especially blood purification, is effective.

Individuals with type 1 diabetes or advanced type 2 diabetes suffer insufficient insulin secretion, leading to symptoms of hyperglycemia. To maintain the normal blood glucose levels, those people with diabetes must administer insulin multiple times a day. However, insulin requirements are influenced by several factors such as diet, exercise, and illness, combined with the narrow therapeutic index, making accurate insulin dosage challenging. Excessive insulin administration can even pose life-threatening risks. In addition, frequent daily insulin injections place considerable physiological and psychological burdens on patients. To tackle these challenges, researchers have embarked on the development of closed-loop insulin delivery systems. These systems adjust insulin dosages in real-time changes based on the patient’s blood glucose levels, therefore enhancing both the safety and effectiveness of insulin therapy. This review categorizes closed-loop insulin delivery systems into two types: electronic-based and material-based systems, based on their compositional attributes. The exploration of both types covers their components, developmental history, clinical applications, current pros and cons, and future directions. The relative strengths and limitations of these two categories of closed-loop insulin delivery systems are also compared and discussed.

Chloropicrin is a commonly used pesticide in agricultural production. The clinical manifestations of oral poisoning patients are complex, and the lesions involve multiple organs. At present, the specific pathogenic mechanism of such poisoning is not clear, and the treatment experience is insufficient, so there are certain difficulties in clinical diagnosis, treatment and treatment. In this paper, the data of a patient with oral chloropicrin poisoning treated in Yidu Central Hospital of Weifang City in April 2023 were summarized. The patient was admitted to our hospital for treatment in time, and his condition improved after Hemopurification, methylene blue reduction, organ support, infection prevention as well as other symptomatic support. Oral chlorophenol can cause lung damage, skin and mucous membrane damage, and may have certain effects on the nervous system and kidney. Early intervention, especially blood purification, is effective.

Background::T-cell-mediated immunity is crucial for the effective clearance of viral infection, but the T-cell-mediated immune responses that are induced by booster doses of inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in people living with human immunodeficiency virus (PLWH) remain unclear.Methods::Forty-five PLWH who had received antiretroviral therapy (ART) for more than two years and 29 healthy controls (HCs) at Beijing Youan Hospital were enrolled to assess the dynamic changes in T-cell responses between the day before the third vaccine dose (week 0) and 4 or 12 weeks (week 4 or week 12) after receiving the third dose of inactivated SARS-CoV-2 vaccine. Flow cytometry, enzyme-linked immunospot (ELISpot), and multiplex cytokines profiling were used to assess T-cell responses at the three timepoints in this study.Results::The results of the ELISpot and activation-induced marker (AIM) assays showed that SARS-CoV-2-specific T-cell responses were increased in both PLWH and HCs after the third dose of the inactivated SARS-CoV-2 vaccine, and a similar magnitude of immune response was induced against the Omicron (B.1.1.529) variant compared to the wild-type strain. In detail, spike-specific T-cell responses (measured by the ELISpot assay for interferon γ [IFN-γ] release) in both PLWH and HCs significantly increased in week 4, and the spike-specific T-cell responses in HCs were significantly stronger than those in PLWH 4 weeks after the third vaccination. In the AIM assay, spike-specific CD4 + T-cell responses peaked in both PLWH and HCs in week 12. Additionally, significantly higher spike-specific CD8 + T-cell responses were induced in PLWH than in HCs in week 12. In PLWH, the release of the cytokines interleukin-2 (IL-2), tumour necrosis factor-alpha (TNF-α), and IL-22 by peripheral blood mononuclear cells (PBMCs) that were stimulated with spike peptides increased in week 12. In addition, the levels of IL-4 and IL-5 were higher in PLWH than in HCs in week 12. Interestingly, the magnitude of SARS-CoV-2-specific T-cell responses in PLWH was negatively associated with the extent of CD8 + T-cell activation and exhaustion. In addition, positive correlations were observed between the magnitude of spike-specific T-cell responses (determined by measuring IFN-γ release by ELISpot) and the amounts of IL-4, IL-5, IL-2 and IL-17F. Conclusions::Our findings suggested that SARS-CoV-2-specific T-cell responses could be enhanced by the booster dose of inactivated COVID-19 vaccines and further illustrate the importance of additional vaccination for PLWH.

Chondroitin sulfate sodium is a sulphated glycosaminoglycan composed of repeating disaccharide units of D-glucuronic acid and N-acetyl-D-galactosamine,prepared from the cartilage tissue of land or marine animal by a specific extraction and purification process.Chondroitin sulfate sodium is considered to have anti-osteoarthritis effect and many other potential physiological activities.It has broad application prospects and development space in the fields of health food,cosmetics,and drugs.This paper reviews the preparation process of chondroitin sulfate sodium,development and problems of microbial synthesis technology and the research status of anti-osteoarthritis activity based on cells models,animal models and clinical randomized controlled trials(RCT).The limitations of current research are analyzed and corresponding strategies are proposed to provide reference for further standardization and development of chondroitin sulfate sodium.

Methamphetamine (METH) abuse is associated with significant neurotoxicity, high addiction potential, and behavioral abnormalities. Recent studies have identified a connection between the gut microbiota and METH-induced neurotoxicity and behavioral disorders. However, the underlying causal mechanisms linking the gut microbiota to METH pathophysiology remain largely unexplored. In this study, we employed fecal microbiota transplantation (FMT) and antibiotic (Abx) intervention to manipulate the gut microbiota in mice administered METH. Furthermore, we supplemented METH-treated mice with short-chain fatty acids (SCFAs) and pioglitazone (Pio) to determine the protective effects on gut microbiota metabolism. Finally, we assessed the underlying mechanisms of the gut-brain neural circuit in vagotomized mice. Our data provide compelling evidence that modulation of the gut microbiome through FMT or microbiome knockdown by Abx plays a crucial role in METH-induced neurotoxicity, behavioral disorders, gut microbiota disturbances, and intestinal barrier impairment. Furthermore, our findings highlight a novel prevention strategy for mitigating the risks to both the nervous and intestinal systems caused by METH, which involves supplementation with SCFAs or Pio.

Objective:To investigate the risk factors of surgical site infection (SSI) after colorectal surgery, and to establish and validate a risk prediction model nomogram.Methods:An observational study was conducted to retrospectively collect data of 6527 patients aged ≥16 years who underwent colorectal surgery in 56 domestic hospitals from March 1, 2021 to February 28, 2022 from the national Surgical Site Infection Surveillance network. The incidence of SSI after surgery was 2.3% (149/6527). According to the ratio of 7:3, 6527 patients were randomly divided into the modeling cohort (4568 cases) and the validation cohort (1959 cases), and there was no statistically significant difference between the two datasets ( P>0.05). Univariate analysis was performed using t test /Mann-Whitney U test /χ 2 test. Multivariate analysis was performed using binary logistic regression to establish a preliminary model and select variables using Lasso analysis to establish an optimized model nomogram. The discrimination and calibration of the model were evaluated by ROC curve, calibration curve, and Hosmer-Lemeshow test. AUC value>0.7 is considered a good discrimination of the model. The Bootstrap method (repeated self-sampling 1000 times) was used to verify the constructed model internally and externally to evaluate the accuracy of the constructed model. Results:Multivariate analysis showed that history of chronic liver disease (OR=3.626, 95%CI: 1.297-10.137, P<0.001) and kidney disease (OR=1.567,95%CI:1.042-2.357, P=0.038), surgical antibiotic prophylaxis (OR=1.564, 95%CI:1.038-2.357, P=0.035), and emergency surgery (OR=1.432,95%CI: 1.089-1.885, P=0.021), open surgery (OR=1.418, 95%CI:1.045-1.924, P=0.042), preoperative stoma (OR=3.310, 95%CI:1.542-7.105, P<0.001), postoperative stoma (OR=2.323,95%CI: 1.537-8.134, P<0.001), surgical incision type above grade II (OR=1.619,95%CI:1.097-2.375, P=0.014), and each unit increase in total bilirubin (OR=1.003,95%CI:-0.994-1.012, P=0.238), alanine aminotransferase (OR=1.006, 95%CI:1.001-1.011, P=0.032), blood urea nitrogen (OR=1.003,95%CI:0.995-1.011, P=0.310), blood glucose (OR=1.024, 95%CI:1.005-1.043, P=0.027), C-reactive protein (OR=1.007, 95%CI:1.003-1.011, P<0.001), length of incision (OR=1.042, 95%CI:1.002-1.087, P=0.031), surgical duration (OR=1.003,95%CI:1.001-1.005, P=0.017), and surgical blood loss (OR=1.001,95%CI: 1.000-1.002, P=0.045) were risk factors for SSI after colorectal surgery. Each unit increase in albumin level (OR=0.969,95%CI:0.941-0.998, P=0.036) was an independent protective factor for SSI after colorectal surgery. The area under the curve of the optimized model obtained by internal and external validation were 0.768 (95%CI: 0.723-0.813) and 0.753 (95%CI: 0.680-0.832), respectively. The predicted value of the calibration curve was basically consistent with the actual value. Conclusions:The risk prediction model for SSI after colorectal surgery constructed in this study has good discrimination and calibration. The nomogram created in this model can provide an evaluation basis for the observed rate and expected event rate of SSI after clinical colorectal surgery.

Objective:To examine the clinical value of rapid detection of drug-resistant bacteria by immunochromatography and the effects of rapid detection on the prognosis of patients with severe intra-abdominal infection complicated by carbapenem-resistant Enterobacteriaceae (CRE) bloodstream infection.Methods:This was a retrospective cohort study. We analyzed clinical data of 73 patients with severe abdominal infections with sepsis or septic shock complicated by CRE bloodstream infection admitted to the general surgery department of Jinling Hospital between February 2022 and February 2023. Patients were divided into a colloidal gold immunochromatographic assay (GICA) group (17 patients) and conventional testing group (56 patients) based on whether a GICA for CRE had been performed on the patients' first blood culture sample during the diagnosis and treatment process. There were no statistically significant differences between the GICA and conventional testing groups in age ([55.9±17.3] vs. [47.6±16.4] years), sex ([16 men vs. one woman ] vs. [41 men vs. 15 women]), median Charlson comorbidity index (3.0[2.0,4.0] vs. 3.0[2.0, 4.8]), septic shock (10 vs. 39), or acute kidney injury (8 vs. 40) (all P>0.05). Both groups routinely underwent traditional bacterial identification and drug susceptibility testing. Additionally, patients in the GICA group were tested directly for positive blood cultures using a GICA carbapenemase test kit. The main outcomes were mortality rates on Days 28 and 90 after the first identification of CRE bloodstream infection in both groups. We also compared the microbial clearance rate, duration of hospitalization and intensive care unit stay, and time from onset of CRE bloodstream infection to initiation of targeted and appropriate antibiotics between the two groups. Results:The rate of microbial clearance of bloodstream infection was significantly greater in the GICA group than in the conventional testing group (15/17 vs. 34/56 [60.7%], χ 2=4.476, P=0.034), whereas the 28-day mortality tended to be lower in the GICA than conventional testing group [5/17 vs. 44.6% [25/56], χ 2=1.250, P=0.264). The 90-day mortality (8/17 vs. 53.6% [30/56], χ 2=0.222, P=0.638), median duration of hospitalization (37.0 [18.0, 46.5] days vs. 45.5 [32.2, 64.8] days, Z=-1.867, P=0.062), and median duration of intensive care unit stay (18.0 [6.5, 35.0] days vs. 32.0 [5.0, 51.8] days, Z=-1.251, P=0.209). The median time between the onset of bloodstream infection and administration of antibiotics was 49.0 (38.0, 69.0) hours in the GICA group, which is significantly shorter than the 163.0 (111.8, 190.0) hours in the conventional testing group ( Z=-5.731, P<0.001). The median time between the onset of bloodstream infection and administration of appropriate antibiotics was 40.0 (34.0, 80.0) hours in the GICA group, which is shorter than in the conventional testing group (68.0 [38.2, 118.8]) hours; however, this difference is not statistically significant ( Z=-1.686, P=0.093). Conclusions:GICA can provide information on carbapenemase- producing pathogens faster than traditional drug sensitivity testing, enabling early administration of the optimal antibiotics. The strategy of 'carbapenemase detection first' for managing bacterial infection has the potential to improve prognosis of patients and reduce mortality rate.

Objective:To investigate the risk factors of surgical site infection (SSI) after colorectal surgery, and to establish and validate a risk prediction model nomogram.Methods:An observational study was conducted to retrospectively collect data of 6527 patients aged ≥16 years who underwent colorectal surgery in 56 domestic hospitals from March 1, 2021 to February 28, 2022 from the national Surgical Site Infection Surveillance network. The incidence of SSI after surgery was 2.3% (149/6527). According to the ratio of 7:3, 6527 patients were randomly divided into the modeling cohort (4568 cases) and the validation cohort (1959 cases), and there was no statistically significant difference between the two datasets ( P>0.05). Univariate analysis was performed using t test /Mann-Whitney U test /χ 2 test. Multivariate analysis was performed using binary logistic regression to establish a preliminary model and select variables using Lasso analysis to establish an optimized model nomogram. The discrimination and calibration of the model were evaluated by ROC curve, calibration curve, and Hosmer-Lemeshow test. AUC value>0.7 is considered a good discrimination of the model. The Bootstrap method (repeated self-sampling 1000 times) was used to verify the constructed model internally and externally to evaluate the accuracy of the constructed model. Results:Multivariate analysis showed that history of chronic liver disease (OR=3.626, 95%CI: 1.297-10.137, P<0.001) and kidney disease (OR=1.567,95%CI:1.042-2.357, P=0.038), surgical antibiotic prophylaxis (OR=1.564, 95%CI:1.038-2.357, P=0.035), and emergency surgery (OR=1.432,95%CI: 1.089-1.885, P=0.021), open surgery (OR=1.418, 95%CI:1.045-1.924, P=0.042), preoperative stoma (OR=3.310, 95%CI:1.542-7.105, P<0.001), postoperative stoma (OR=2.323,95%CI: 1.537-8.134, P<0.001), surgical incision type above grade II (OR=1.619,95%CI:1.097-2.375, P=0.014), and each unit increase in total bilirubin (OR=1.003,95%CI:-0.994-1.012, P=0.238), alanine aminotransferase (OR=1.006, 95%CI:1.001-1.011, P=0.032), blood urea nitrogen (OR=1.003,95%CI:0.995-1.011, P=0.310), blood glucose (OR=1.024, 95%CI:1.005-1.043, P=0.027), C-reactive protein (OR=1.007, 95%CI:1.003-1.011, P<0.001), length of incision (OR=1.042, 95%CI:1.002-1.087, P=0.031), surgical duration (OR=1.003,95%CI:1.001-1.005, P=0.017), and surgical blood loss (OR=1.001,95%CI: 1.000-1.002, P=0.045) were risk factors for SSI after colorectal surgery. Each unit increase in albumin level (OR=0.969,95%CI:0.941-0.998, P=0.036) was an independent protective factor for SSI after colorectal surgery. The area under the curve of the optimized model obtained by internal and external validation were 0.768 (95%CI: 0.723-0.813) and 0.753 (95%CI: 0.680-0.832), respectively. The predicted value of the calibration curve was basically consistent with the actual value. Conclusions:The risk prediction model for SSI after colorectal surgery constructed in this study has good discrimination and calibration. The nomogram created in this model can provide an evaluation basis for the observed rate and expected event rate of SSI after clinical colorectal surgery.