Background. Thioredoxin-1 (Trx-1) is a small redox protein, which plays an important role in many biological processes. Although increased expression of Trx-1 in various solid tumors has been reported, the prognostic significance and function of Trx-1 in human gastric cancer (GC) are still unclear. Here, we investigated the clinical and prognostic significance of Trx-1 expression and the function and mechanism of Trx-1 in human GC. Methods. We analyzed Trx-1 mRNA expression from the GEO database and Trx-1 protein expression in 144 GC tissues using immunohistochemistry. Effects of Trx-1 on GC cell were assessed in vitro and in vivo through Trx-1 knockdown or overexpression. The antitumor effects of the Trx-1 inhibitor, PX-12, on GC cells were investigated. PTEN and p-AKT expressions were evaluated by Western blotting. Results. Increased Trx-1 expression was found in GC tissues and associated with poor prognosis and aggressive clinicopathological characteristics in patients with GC. High Trx-1 expression predicted poor prognosis, and its expression was an independent prognostic factor for overall survival of GC patients. Knockdown of Trx-1 expression inhibited GC cell growth, migration, and invasion in vitro and tumor growth and lung metastasis in vivo. Conversely, overexpression of Trx-1 promoted GC cell growth, migration, and invasion. We also found that PX-12 inhibited GC cell growth, migration, and invasion. Overexpression of Trx-1 caused a decrease in PTEN and increase in p-AKT levels whereas silencing Trx-1 caused an increase in PTEN and decrease in p-AKT levels in GC cells. Inhibition of AKT signaling pathway by MK2206 also inhibited GC cell growth, migration, and invasion. Conclusion. Our results indicate that Trx-1 may be a promising prognostic indicator and therapeutic target for GC patients.

Background: It has been proven that the ratio of albumin to globulin (A/G) is a typical biomarker for monitoring inflammation and nutritional status. But the potential role of A/G in stroke-associated pneumonia (SAP) after acute ischemic stroke (AIS) remained unknown.Patients and methods: Following inclusion criteria, 5,173 AIS patients were included and segmented into SAP (n = 897) and non-SAP (n = 4,276) groups. The differences in variables between groups were compared. The logistic regression model was used to determine the association between A/G and SAP, and a forest plot was drawn.Results: Compared with the non-SAP group, the SAP group had a lower A/G level (P < 0.001). Then, A/G was divided into quartiles. In comparison to Q3 (A/G = 1.25–1.39), logistic regression revealed that patients with a lower A/G (A/G ≤ 1.09) had a higher risk of SAP (OR = 1.96, 95% CI, 1.56–2.46, P < 0.001). On the contrary, those with a higher A/G (A/G ≥ 1.4) had a lower SAP risk (OR = 0.73, 95% CI, 0.54–0.97, P = 0.029).Conclusion: The study revealed that a low A/G level was associated with an increased SAP risk. Appropriate preventative measures for SAP should be taken in AIS patients with a low A/G level.

Background: The relationship between serum uric acid (SUA) level and diabetic peripheral neuropathy (DPN) remains controversial. We aimed to investigate the association between SUA level and DPN and evaluate the effects of SUA level on nerve conduction function via electromyography in patients with type 2 diabetes (T2DM), stratified by gender and age. Methods: This cross-sectional study included 647 inpatients with T2DM from the First Affiliated Hospital of Wenzhou Medical University between February 2017 and October 2020. The diagnosis of DPN was confirmed according to the Toronto Expert Consensus. Clinical data, SUA level, and nerve conduction parameters were obtained from electronic medical records. Results: A total of 647 patients with T2DM were included, and 471 patients were diagnosed with DPN. The level of SUA was higher in the DPN group than in the Non-DPN group (330.58 ± 99.67 vs. 309.16 ± 87.04, p < 0.05). After adjustment, a higher SUA level was associated with the presence of DPN [odds ratio (OR) 1.003, 95% confidence interval (CI), 1.001–1.005; p = 0.017]. The area under the curve for the prediction of DPN was 0.558 (95% CI, 0.509–0.608; p = 0.022), and the optimized cut-off of SUA level was 297.5 µmol/L. The SUA > 297.5 µmol/L level was independently associated with DPN in the male subgroup (OR 2.507, 95% CI, 1.405–4.473; p = 0.002) rather than in the female subgroup. Besides, SUA > 297.5 µmol/L was independently associated with DPN in the younger subgroup (age < 65 years) (OR 2.070, 95% CI, 1.278–3.352; p = 0.003) rather than in the older subgroup. In multiple linear regression analysis, SUA was significantly correlated with certain nerve conduction study parameters in the all patients group, and was also observed in the male and younger subgroups. Conclusions: Elevated SUA was independently associated with poorer nerve conduction functions, and hyperuricemia was also significantly associated with a higher risk of developing DPN in T2DM patients, especially in male and younger patients.

Background and Purpose: Diabetic peripheral neuropathy (DPN) leads to ulceration, noninvasive amputation, and long-term disability. This study aimed to develop and validate a nomogram for forecasting the probability of DPN in type 2 diabetes mellitus patients. Methods: From February 2017 to May 2021, 778 patients with type 2 diabetes mellitus were included in this study. We confirmed the diagnosis of DPN according to the Toronto Expert Consensus. Patients were randomly divided into a training cohort (n = 519) and a validation cohort (n = 259). In the training cohort, univariate and multivariate logistic regression analyses were performed, and a simple nomogram was built using the stepwise method. The receiver operating characteristic (ROC), calibration curve, and decision curve analysis were computed in order to validate the discrimination and clinical value of the nomogram model. Results: About 65.7% and 72.2% of patients were diagnosed with DPN in the training and validation cohorts. We developed a novel nomogram to predict the probability of DPN based on the parameters of age, gender, duration of diabetes, body mass index, uric acid, hemoglobin A1c, and free triiodothyronine. The areas under the curves (AUCs) of the nomogram model were 0.763 in the training cohort and 0.755 in the validation cohort. The calibration plots revealed well-fitted accuracy between the predicted and actual probability in the training and validation cohorts. Decision curve analysis confirmed the clinical value of the nomogram. In subgroup analysis, the predictive ability of the nomogram model was strong. Conclusions: The nomogram of age, gender, duration of diabetes, body mass index, uric acid, hemoglobin A1c, and free triiodothyronine may assist clinicians with the early identification of DPN in patients with type 2 diabetes mellitus.

The immune microenvironment plays a critical role in tumor biology. As a critical feature of cancers, stemness is acknowledged as a contributor to the development of drug resistance in gastric cancers (GCs). Long non-coding RNAs (lncRNAs) have been revealed to participate in this process. In this study, we aimed to develop a stemness-related lncRNA signature (SRLncSig) with guiding significance for immunotherapy. Three cohorts (TCGA, Zhongshan, and IMvigor210) were enrolled for analysis. A list of stemness-related lncRNAs (SRlncRNAs) was collected by co-expression strategy under the threshold of coefficient value >0.35 and p-value < 0.05. Cox and Lasso regression analysis was further applied to find out the SRlncRNAs with prognosis-predictive value to establish the SRLncSig in the TCGA cohort. IPS and TIDE algorithms were further applied to predict the efficacy of SRLncSig in TCGA and Zhongshan cohorts. IMvigor210 was composed of patients with clinical outcomes of immunotherapy. The results indicated that SRLncSig not only was confirmed as an independent risk factor for GCs but also identified as a robust indicator for immunotherapy. The patient with a lower SRLncSig score was more likely to benefit from immunotherapy, and the results were highly consistent in three cohorts. In conclusion, our study not only could clarify the correlations between stemness and immunotherapy in GC patients but also provided a model to guide the applications of immunotherapy in clinical practice.