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*

Patients with new-onset atrial fibrillation in sepsis have a high mortality rate and poor prognosis. At present, the pathogenesis of new-onset atrial fibrillation in sepsis has not been fully elucidated. Studies have shown that both sepsis and atrial fibrillation are closely related to NOD-like receptor protein 3 (NLRP3). NLRP3 inflammasome can not only induce the activation of caspase-1 and the subsequent release of cellular pro-inflammatory factors, but also participate in the occurrence and development of sepsis and promote the occurrence and development of atrial fibrillation. It is concluded that the NLRP3 inflammasome may play an important role in the occurrence and development of new-onset atrial fibrillation in sepsis. This paper summarized the current research progress on the structure and function of the NLRP3 inflammasome, its role in sepsis, its mechanism in promoting atrial fibrillation, the relationship between the NLRP3 inflammasome and new-onset atrial fibrillation in sepsis, the feasibility of studying new-onset atrial fibrillation in sepsis, and potential therapeutic targets for new-onset atrial fibrillation in sepsis. This review aims to provide a theoretical basis for future research on the mechanisms by which the NLRP3 inflammasome promotes new-onset atrial fibrillation in sepsis and possible therapeutic targets.

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.

Methamphetamine (Meth) abuse can cause serious mental disorders, including anxiety and depression. The gut microbiota is a crucial contributor to maintaining host mental health. Here, we aim to investigate if microbiota participate in Meth-induced mental disorders, and the potential mechanisms involved. Here, 15 mg/kg Meth resulted in anxiety- and depression-like behaviors of mice successfully and suppressed the Sigma-1 receptor (SIGMAR1)/BDNF/TRKB pathway in the hippocampus. Meanwhile, Meth impaired gut homeostasis by arousing the Toll-like receptor 4 (TLR4)-related colonic inflammation, disturbing the gut microbiome and reducing the microbiota-derived short-chain fatty acids (SCFAs). Moreover, fecal microbiota from Meth-administrated mice mediated the colonic inflammation and reproduced anxiety- and depression-like behaviors in recipients. Further, SCFAs supplementation optimized Meth-induced microbial dysbiosis, ameliorated colonic inflammation, and repressed anxiety- and depression-like behaviors. Finally, Sigmar1 knockout (Sigmar1^-/-) repressed the BDNF/TRKB pathway and produced similar behavioral phenotypes with Meth exposure, and eliminated the anti-anxiety and -depression effects of SCFAs. The activation of SIGMAR1 with fluvoxamine attenuated Meth-induced anxiety- and depression-like behaviors. Our findings indicated that gut microbiota-derived SCFAs could optimize gut homeostasis, and ameliorate Meth-induced mental disorders in a SIGMAR1-dependent manner. This study confirms the crucial role of microbiota in Meth-related mental disorders and provides a potential preemptive therapy.

OBJECTIVE: To study the development of surgical robots at home and abroad in recent years. METHODS: Through a large number of literature review and analysis, the qualification approval and technical function characteristics of domestic and foreign surgical robots from January 2019 to July 2022 were analyzed. RESULTS: The related situations of 39 surgical robots were analyzed and reported, and the shortcomings and future development direction of the current surgical robots were summarized. CONCLUSIONS The development of surgical robots in China is now in a rapid development stage. At present, surgical robots generally have the disadvantages of high cost, lack of tactile feedback (force feedback), large size, large space occupation and difficult to move. In the future, it will develop towards intelligent, miniaturized, remote, open and low-cost.
China ; Robotics ; Robotic Surgical Procedures

BACKGROUND: T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibition motif domains (TIGIT), an inhibitory receptor expressed on T cells, plays a dysfunctional role in antiviral infection and antitumor activity. However, it is unknown whether TIGIT expression on T cells influences the immunological effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inactivated vaccines. METHODS: Forty-five people living with HIV (PLWH) on antiretroviral therapy (ART) for more than two years and 31 healthy controls (HCs), all received a third dose of a SARS-CoV-2 inactivated vaccine, were enrolled in this study. The amounts, activation, proportion of cell subsets, and magnitude of the SARS-CoV-2-specific immune response of TIGIT + CD4 + and TIGIT + CD8 + T cells were investigated before the third dose but 6 months after the second vaccine dose (0W), 4 weeks (4W) and 12 weeks (12W) after the third dose. RESULTS: Compared to that in HCs, the frequency of TIGIT + CD8 + T cells in the peripheral blood of PLWH increased at 12W after the third dose of the inactivated vaccine, and the immune activation of TIGIT + CD8 + T cells also increased. A decrease in the ratio of both T naïve (T N ) and central memory (T CM ) cells among TIGIT + CD8 + T cells and an increase in the ratio of the effector memory (T EM ) subpopulation were observed at 12W in PLWH. Interestingly, particularly at 12W, a higher proportion of TIGIT + CD8 + T cells expressing CD137 and CD69 simultaneously was observed in HCs than in PLWH based on the activation-induced marker assay. Compared with 0W, SARS-CoV-2-specific TIGIT + CD8 + T-cell responses in PLWH were not enhanced at 12W but were enhanced in HCs. Additionally, at all time points, the SARS-CoV-2-specific responses of TIGIT + CD8 + T cells in PLWH were significantly weaker than those of TIGIT - CD8 + T cells. However, in HCs, the difference in the SARS-CoV-2-specific responses induced between TIGIT + CD8 + T cells and TIGIT - CD8 + T cells was insignificant at 4W and 12W, except at 0W. CONCLUSIONS TIGIT expression on CD8 + T cells may hinder the T-cell immune response to a booster dose of an inactivated SARS-CoV-2 vaccine, suggesting weakened resistance to SARS-CoV-2 infection, especially in PLWH. Furthermore, TIGIT may be used as a potential target to increase the production of SARS-CoV-2-specific CD8 + T cells, thereby enhancing the effectiveness of vaccination.
Humans ; Antibodies, Viral ; CD8-Positive T-Lymphocytes ; COVID-19/complications* ; COVID-19 Vaccines/immunology* ; HIV Infections/complications* ; Receptors, Immunologic ; SARS-CoV-2

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine can induce a potent cellular and humoral immune response to protect against SARS-CoV-2 infection. However, it was unknown whether SARS-CoV-2 vaccination can induce effective natural killer (NK) cell response in people living with human immunodeficiency virus (PLWH) and healthy individuals. METHODS: Forty-seven PLWH and thirty healthy controls (HCs) inoculated with SARS-CoV-2 inactivated vaccine were enrolled from Beijing Youan Hospital in this study. The effect of SARS-CoV-2 vaccine on NK cell frequency, phenotype, and function in PLWH and HCs was evaluated by flow cytometry, and the response of NK cells to SARS-CoV-2 Omicron Spike (SARS-2-OS) protein stimulation was also evaluated. RESULTS: SARS-CoV-2 vaccine inoculation elicited activation and degranulation of NK cells in PLWH, which peaked at 2 weeks and then decreased to a minimum at 12 weeks after the third dose of vaccine. However, in vitro stimulation of the corresponding peripheral blood monocular cells from PLWH with SARS-2-OS protein did not upregulate the expression of the aforementioned markers. Additionally, the frequencies of NK cells expressing the activation markers CD25 and CD69 in PLWH were significantly lower than those in HCs at 0, 4 and 12 weeks, but the percentage of CD16 + NK cells in PLWH was significantly higher than that in HCs at 2, 4 and 12 weeks after the third dose of vaccine. Interestingly, the frequency of CD16 + NK cells was significantly negatively correlated with the proportion of CD107a + NK cells in PLWH at each time point after the third dose. Similarly, this phenomenon was also observed in HCs at 0, 2, and 4 weeks after the third dose. Finally, regardless of whether NK cells were stimulated with SARS-2-OS or not, we did not observe any differences in the expression of NK cell degranulation markers between PLWH and HCs. CONCLUSION s:SARS-CoV-2 vaccine elicited activation and degranulation of NK cells, indicating that the inoculation of SARS-CoV-2 vaccine enhances NK cell immune response.
Humans ; COVID-19 Vaccines/therapeutic use* ; COVID-19 ; SARS-CoV-2 ; Killer Cells, Natural ; HIV Infections ; Antibodies, Viral

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 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.

Background Hand-arm vibration disease (HAVD) is a chronic progressive disease caused by long-term exposure to hand-transmitted vibration, but the mechanism by which vibration affects peripheral vascular function of fingers is not completely clear. Objective To study the association between vasoactive factors and HAVD, and to screen specific indicators for its early diagnosis and prevention. Methods Judgmental sampling method was used to select workers with (HAVD group) and without HAVD (vibration contact group), and non-hand-transmitted vibration operation workers (control group), with 60 workers in each group. The levels of leukotriene B4 (LTB4), vascular endothelial growth factor (VEGF), 5-hydroxy tryptamine (5-HT), interleukin-1β (IL-1β), and calcitonin gene-related peptide (CGRP) in plasma of the three groups were measured by enzyme-linked immunosorbent assay. The association between vasoactive factors and HAVD was analyzed using logistic regression, and the diagnostic HAVD indicators were screened by receiver operator characteristic (ROC) curve of a multivariate model indicator \begin{document}$ \widehat{Y} $\end{document}. Results The hand symptom rates of the HAVD group, the vibration contact group, and the control group were 26.7%, 66.7%, and 96.7% respectively, with a significant difference (P<0.05). The levels of LTB4, 5-HT, IL-1β, and CGRP in the HAVD group were the highest followed by the vibration contact group, and lowest levels were in the control group (P<0.05). There was no significant difference in the VEGF level among the three groups (P>0.05). The logistic regression results showed that higher levels of LTB4 (OR=1.048, 95%CI: 1.022-1.076), 5-HT (OR=1.011, 95%CI: 1.004-1.018), IL-1β (OR=1.148, 95%CI: 1.071-1.230), and CGRP (OR=1.055, 95%CI: 1.008-1.104) were associated with a higher risk of HAVD (P<0.05). The order of the potential indicators' area under the ROC curve from high to low was:\begin{document}$ \widehat{Y} $\end{document} (0.969) > IL-1β (0.907) > LTB4 (0.876) > 5-HT (0.858) > CGRP (0.836). Conclusion The expression levels of LTB4, 5-HT, IL-1β, and CGRP are altered with occupational exposure in hand-transmitted vibration operations and may be associated with HAVD; VEGF is not found to be associated with HAVD. The accuracy of early screening for HAVD can be improved by combining the monitoring of various biochemical indicators.