Effects of weight loss on QTc in people with obesity: a systematic review and meta-analysis.

BACKGROUND AND AIMS: Overweight and obesity have been found to exhibit a statistically significant increase in corrected QT interval (QTc), a major contributing factor to sudden death. However, the influence of widely used weight loss strategies including diet, exercise, anti-obesity drugs, and bariatric surgery on QTc remains inconsistent. Therefore, the present systematic review and meta-analysis aim to quantitatively analyse and evaluate the effect of weight loss on QTc in obese patients after diet control with exercise intervention and anti-obesity drugs, as well as bariatric surgery. METHODS: Twenty randomised controlled trials (RCT) and observational studies were included in the meta-analysis on the effects of weight loss on QTc. The fixed-effects model was employed in the RCTs, and the random-effects model was employed due to the presence of statistical heterogeneity among observational studies. Subgroup analysis was conducted to understand the differences in distinct weight loss methods and follow-up time. RESULTS: Overall, the QTc of people with obesity after weight loss was shorter than that before (mean difference (MD) = 21.97 ms, 95% confidence interval (CI) = 12.42, 31.52, p < .0001). Subgroup analysis restricted to seven included studies whose intervention was diet control with exercise showed a decrease of QTc with statistical significance (MD = 9.35 ms, 95%CI = 2.56, 37.54, p = .007). In the remaining 11 studies, bariatric surgery was the weight loss method. The results also showed a shortening of QTc after surgery, and the difference was statistically significant (MD = 29.04 ms, 95%CI = -16.46, 41.62, p < .00001). A statistically significant difference in QTc shortening at 6 months compared to pre-operation values was further observed (MD = -31.01 ms, 95%CI = -2.89, -59.12, p = .03). The shortening of QTc at 12 months of follow-up was also significantly different from that before surgery (MD = 36.47 ms, 95%CI = 14.17, 58.78, p < .00001). Moreover, the differences became more pronounced as the follow-up time extended. CONCLUSIONS: We demonstrate that weight loss links to a shortened QTc, without considering the means of weight loss. Bariatric surgery has been found to result in a greater reduction in QTc.

Losartan alleviates renal fibrosis by inhibiting the biomechanical stress-induced epithelial-mesenchymal transition of renal epithelial cells.

Angiotensin receptor blockers (ARBs) have been reported to be beneficial of renal fibrosis, but the molecular and cellular mechanisms are still unclear. In this study, we investigated the effectiveness and relevant mechanism of ARBs in alleviating renal fibrosis, especially by focusing on biomechanical stress-induced epithelial to mesenchymal transition (EMT) of renal epithelial cells. Unilateral ureteral obstruction (UUO) renal fibrosis model was established in mice by ligating the left ureter, and then randomly received losartan at a low dose (1 mg/kg) or a regular dose (3 mg/kg) for 2 weeks. Compared to the control, histological analysis showed that losartan treatment at either a low dose or a regular dose effectively attenuated renal fibrosis in the UUO model. To further understand the mechanism, we ex vivo loaded primary human renal epithelial cells to 50 mmHg hydrostatic pressure. Western blot and immunostaining analyses indicated that the loading to 50 mmHg hydrostatic pressure for 24 h significantly upregulated vimentin, ß-catenin and α-SMA, but downregulated E-cadherin in renal epithelial cells, suggesting the EMT. The addition of 10 or 100 nM losartan in medium effectively attenuated the EMT of renal epithelial cells induced by 50 mmHg hydrostatic pressure loading. Our in vivo and ex vivo experimental data suggest that losartan treatment, even at a low dose can effectively alleviate renal fibrosis in mouse UUO model, at least partly by inhibiting the biomechanical stress-induced EMT of renal epithelial cells. A low dose of ARBs may repurpose for renal fibrosis treatment.

Triptolide exposure induces oxidative stress and decreases oocyte quality in mouse.

Triptolide is a major active ingredient isolated from the traditional Chinese medicine Tripterygium wilfordii, which has anti-inflammatory, anti-cancer, and immunomodulatory effects. However, in clinical studies, triptolide has toxic side effects on the heart, kidney, liver and reproductive organs. With respect to female reproductive toxicity, damaging effects of triptolide on the ovary have been reported, but it has remained unknown whether oocytes are affected by triptolide. Therefore, this study established a concentration gradient of triptolide exposure in mice using 0 (control), 30, 60, and 90 µg triptolide/kg body weight/day administered by gavage. Triptolide administration for 28 d reduced body weight and ovarian weight and affected the developmental potential of oocytes. The triptolide-treated group exhibited meiotic failure of oocytes due to impaired spindle assembly, chromosome alignment, and tubulin stability. Triptolide was also found to induce mitochondrial dysfunction, autophagy and early apoptosis, iron homeostasis, and abnormal histone modifications. These adverse effects could be associated with oxidative stress induced by triptolide. In conclusion, our findings suggest detrimental effects of triptolide on mouse oocytes and, thus, on female reproduction.

Left abdominal wall proliferative myositis resection and patch repair: A case report.

BACKGROUND: Proliferative myositis is a rare benign tumor that is typically self-limiting and does not become malignant. It can be cured by simple resection without reported recurrence. Due to its rapid growth, hard structure and ill-defined borders, it can however be mistaken for malignant tumors such as sarcomas. CASE SUMMARY: We investigate the case of a 64-year-old male with proliferative myositis of the abdominal wall, who was preoperatively administered a needle aspiration biopsy and given a simple excision and patch repair. We then compared it with other similar cases to determine the effectiveness of this treatment method. CONCLUSION: Resection with follow-up observation has shown to be an effective treatment method for proliferative myositis. To avoid unnecessarily extended or destructive resection, a thorough and conclusive diagnosis is crucial, which requires adequate imaging and pathological knowledge.

Identification of Aging-Related Genes Associated with Prognostic Value and Immune Microenvironment Characteristics in Diffuse Large B-Cell Lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a complex invasive tumour that occurs mainly among the elderly. Therefore, we analysed the relationship between ageing-related genes (AG) and DLBCL prognosis. Datasets related to DLBCL and human AGs were downloaded and screened from the Gene Expression Omnibus (GEO) database and HAGR website, respectively. LASSO and Cox regression were used to analyse AGs in the dataset and construct an AG predictive model related to DLBCL prognosis. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment were used to analyse the function of the AG predictive model. The immune microenvironment and immune cell infiltration in DLBCL and their relationship with the AG prediction model were also analysed. After the analysis, 118 AGs were identified as genes related to DLBCL prognosis. Using the LASSO and Cox regression analyses, 9 AGs (PLAU, IL7R, MYC, S100B, IGFBP3, NR3C1, PTK2, TBP, and CLOCK) were used to construct an AG prognostic model. In the training and verification sets, this model exhibited excellent predictive ability for the prognosis of patients with DLBCL who have different clinical characteristics. Further analysis revealed that the high- and low-risk groups of the AG prognostic model were significantly correlated with immune cell infiltration and tumour microenvironment in DLBCL. Functional enrichment analysis also showed that the genes in the AG model were associated with immune-related functions and pathways. In conclusion, we constructed an AG model with a strong predictive function in DLBCL, with the ability to predict the prognosis of patients with different clinical features. This model provides new ideas and potential therapeutic targets for the study of the pathogenesis of DLBCL.

Corrigendum: Seven Glycolysis-Related Genes Predict the Prognosis of Patients With Pancreatic Cancer.

[This corrects the article DOI: 10.3389/fcell.2021.647106.].

Seven Glycolysis-Related Genes Predict the Prognosis of Patients With Pancreatic Cancer.

Objectives: To identify the key glycolysis-related genes (GRGs) in the occurrence and development of pancreatic ductal carcinoma (PDAC), and to construct a glycolysis-related gene model for predicting the prognosis of PDAC patients. Methodology: Pancreatic ductal carcinoma (PDAC) data and that of normal individuals were downloaded from the TCGA database and Genotype-Tissue Expression database, respectively. GSEA analysis of glycolysis-related pathways was then performed on PDAC data to identify significantly enriched GRGs. The genes were combined with other patient's clinical information and used to construct a glycolysis-related gene model using cox regression analysis. The model was further evaluated using data from the validation group. Mutations in the model genes were subsequently identified using the cBioPortal. In the same line, the expression levels of glycolysis related model genes in PDAC were analyzed and verified using immunohistochemical images. Model prediction for PDAC patients with different clinical characteristics was then done and the relationship between gene expression level, clinical stage and prognosis further discussed. Finally, a nomogram map of the predictive model was constructed to evaluate the prognosis of patients with PDAC. Results: GSEA results of the training set revealed that genes in the training set were significantly related to glycolysis pathway and iconic glycolysis pathway. There were 108 differentially expressed GRGs. Among them, 29 GRGs were closely related to prognosis based on clinical survival time. Risk regression analysis further revealed that there were seven significantly expressed glycolysis related genes. The genes were subsequently used to construct a predictive model. The model had an AUC value of more than 0.85. It was also significantly correlated with survival time. Further expression analysis revealed that CDK1, DSC2, ERO1A, MET, PYGL, and SLC35A3 were highly expressed in PDAC and CHST12 was highly expressed in normal pancreatic tissues. These results were confirmed using immunohistochemistry images of normal and diseases cells. The model could effectively evaluate the prognosis of PDAC patients with different clinical characteristics. Conclusion: The constructed glycolysis-related gene model effectively predicts the occurrence and development of PDAC. As such, it can be used as a prognostic marker to diagnose patients with PDAC.

Combining Bioinformatics Techniques to Study the Key Immune-Related Genes in Abdominal Aortic Aneurysm.

Approximately 13,000 people die of an abdominal aortic aneurysm (AAA) every year. This study aimed to identify the immune response-related genes that play important roles in AAA using bioinformatics approaches. We downloaded the GSE57691 and GSE98278 datasets related to AAA from the Gene Expression Omnibus database, which included 80 AAA and 10 normal vascular samples. CIBERSORT was used to analyze the samples and detect the infiltration of 22 types of immune cells and their differences and correlations. The principal component analysis showed significant differences in the infiltration of immune cells between normal vascular and AAA samples. High proportions of CD4+ T cells, activated mast cells, resting natural killer cells, and 12 other types of immune cells were found in normal vascular tissues, whereas high proportions of macrophages, CD8+ T cells, resting mast cells, and six other types of immune cells were found in AAA tissues. In the selected samples, we identified 39 upregulated (involved in growth factor activity, hormone receptor binding, and cytokine receptor activity) and 133 downregulated genes (involved in T cell activation, cell chemotaxis, and regulation of immune response mediators). The key differentially expressed immune response-related genes were screened using the STRING database and Cytoscape software. Two downregulated genes, PI3 and MAP2K1, and three upregulated genes, SSTR1, GPER1, and CCR10, were identified by constructing a protein-protein interaction network. Functional enrichment of the differentially expressed genes was analyzed, and the expression of the five key genes in AAA samples was verified using quantitative polymerase chain reaction, which revealed that MAP2K1 was downregulated in AAA, whereas SSTR1, GEPR1, and CCR10 were upregulated; there was no significant difference in PI3 expression. Our study shows that normal vascular and AAA samples can be distinguished via the infiltration of immune cells. Five genes, PI3, MAP2K1, SSTR1, GPER1, and CCR10, may play important roles in the development, diagnosis, and treatment of AAA.

Using Machine Learning Modeling to Explore New Immune-Related Prognostic Markers in Non-Small Cell Lung Cancer.

OBJECTIVE: To find new immune-related prognostic markers for non-small cell lung cancer (NSCLC). METHODS: We found GSE14814 is related to NSCLC in GEO database. The non-small cell lung cancer observation (NSCLC-OBS) group was evaluated for immunity and divided into high and low groups for differential gene screening according to the score of immune evaluation. A single factor COX regression analysis was performed to select the genes related to prognosis. A prognostic model was constructed by machine learning, and test whether the model has a test efficacy for prognosis. A chip-in-chip non-small cell lung cancer chemotherapy (NSCLC-ACT) sample was used as a validation dataset for the same validation and prognostic analysis of the model. The coexpression genes of hub genes were obtained by pearson analysis and gene enrichment, function enrichment and protein interaction analysis. The tumor samples of patients with different clinical stages were detected by immunohistochemistry and the expression difference of prognostic genes in tumor tissues of patients with different stages was compared. RESULTS: By screening, we found that LYN, C3, COPG2IT1, HLA.DQA1, and TNFRSF17 is closely related to prognosis. After machine learning, we constructed the immune prognosis model from these 5 genes, and the model AUC values were greater than 0.9 at three time periods of 1, 3, and 5 years; the total survival period of the low-risk group was significantly better than that of the high-risk group. The results of prognosis analysis in ACT samples were consistent with OBS groups. The coexpression genes are mainly involved B cell receptor signaling pathway and are mainly enriched in apoptotic cell clearance. Prognostic key genes are highly correlated with PDCD1, PDCD1LG2, LAG3, and CTLA4 immune checkpoints. The immunohistochemical results showed that the expression of COPG2IT1 and HLA.DQA1 in stage III increased significantly and the expression of LYN, C3, and TNFRSF17 in stage III decreased significantly compared with that of stage I. The experimental results are consistent with the previous analysis. CONCLUSION: LYN, C3, COPG2IT1, LA.DQA1, and NFRSF17 may be new immune markers to judge the prognosis of patients with non-small cell lung cancer.

A signature of 18 immune-related gene pairs to predict the prognosis of pancreatic cancer patients.

Pancreatic cancer is one of the most lethal malignancies. With the promising prospects conveyed by immunotherapy in cancers, we aimed to construct an immune-related gene pairs (IRGPs) signature to predict the prognosis of pancreatic cancer patients. We downloaded clinical and transcriptional data of pancreatic cancer patients from The Cancer Genome Atlas data set as the training group and GSE57495 data set as the verification group. We filtered immune-related transcriptional data by IMMPORT. With the assistance of lasso penalized Cox regression, we constructed our prognostic IRGPs signature and divided all samples into high-/low-risk groups by receiver operating characteristic curve for further comparisons. The comparisons between high- and low-risk groups including survival rate, multivariate, and univariate Cox proportional-hazards analysis, infiltration of immune cells, and Gene Set Enrichment Analysis (GSEA). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) are facilitated to analyze the proceedings in which our IRGPs signature may involve in. The results revealed that 18 IRGPs were defined as our prognostic signature. The prognostic value of this IRGPs signature was verified from the GSE57495 data set. We further demonstrated the independent prognostic value of this IRGPs signature. The contents of six immune cells between high-/low-risk groups were different, which was associated with the progression of diverse cancers. Results from GO, KEGG, and GSEA revealed that this IRGPs signature was involved in extracellular space, immune response, cancer pathways, cation channel, and gated channel activities. Evidently, this IRGPs signature will provide remarkable value for the therapy of pancreatic cancer patients.

29 immune-related genes pairs signature predict the prognosis of cervical cancer patients.

To screen the key immune genes in the development of cervical cancer, construct immune related gene pairs (IRGPs), and evaluate their influence on the prognosis of cervical cancer. Tumor Genome Atlas (TCGA) database and geo database were downloaded as training set and validation set respectively, and immune related gene data were downloaded from immport. IRGPs model is established by machine learning, and the model is analyzed and evaluated. Using the Uclcan to analyze the immune genes expression in cervical cancer, and to further explore the association with the expression level and the clinical stage and prognosis of cervical cancer. According to the analysis of training set, we identified 29 IRGPs as key gene pairs and constructed the model. The AUC value of the model was greater than 0.9, and the model group survival rate was conspicuous different (P < 0.001). The reliability of the model was confirmed in the validation group. Our IRGPs play an important role in the occurrence and development of cervical cancer, and can be used as a prognostic marker and potential new target of cervical cancer.

Abnormal immunity of non-survivors with COVID-19: predictors for mortality.

BACKGROUND: The number of coronavirus disease 2019 (COVID-19) cases has rapidly increased all over the world. Specific information about immunity in non-survivors with COVID-19 is scarce. This study aimed to analyse the clinical characteristics and abnormal immunity of the confirmed COVID-19 non-survivors. METHODS: In this single-centered, retrospective, observational study, we enrolled 125 patients with COVID-19 who were died between January 13 and March 4, 2020 in Renmin Hospital of Wuhan University. A total of 414 randomly recruited patients with confirmed COVID-19 who were discharged from the same hospital during the same period served as control. The demographic, clinical characteristics and laboratory findings at admission, and treatment used in these patients were collected. The immunity-related risk factors associated with in-hospital death were tested by logistic regression models and Receiver Operating Characteristic (ROC) curve. RESULTS: Non-survivors (70 years, IQR: 61.5-80) were significantly older than survivors (54 years, IQR: 37-65) (P <  0.001). 56.8% of non-survivors was male. Nearly half of the patients (44.9%) had chronic medical illness. In non-survivors, hypertension (49.6%) was the most common comorbidity, followed by diabetes (20.0%) and coronary heart disease (16.0%). The common signs and symptoms at admission of non-survivors were fever (88%), followed by cough (64.8%), dyspnea (62.4%), fatigue (62.4%) and chest tightness (58.4%). Compared with survivors, non-survivors had higher white blood cell (WBC) count (7.85 vs 5.07 × 109/L), more elevated neutrophil count (6.41 vs 3.08 × 109/L), smaller lymphocyte count (0.69 vs 1.20 × 109/L) and lower platelet count (172 vs 211 × 109/L), raised concentrations of procalcitonin (0.21 vs 0.06 ng/mL) and CRP (70.5 vs 7.2 mg/L) (P < 0.001). This was accompanied with significantly decreased levels of CD3+ T cells (277 vs 814 cells/µl), CD4+ T cells (172 vs 473 cells/µl), CD8+ T cells (84 vs 262.5 cells/µl, P < 0.001), CD19+ T cells (88 vs 141 cells/µl) and CD16+ 56+ T cells (79 vs 128.5 cells/µl) (P < 0.001). The concentrations of immunoglobulins (Ig) G (13.30 vs 11.95 g/L), IgA (2.54 vs 2.21 g/L), and IgE (71.30 vs 42.25 IU/ml) were increased, whereas the levels of complement proteins (C)3 (0.89 vs 0.99 g/L) and C4 (0.22 vs 0.24 g/L) were decreased in non-survivors when compared with survivors (all P < 0.05). The non-survivors presented lower levels of oximetry saturation (90 vs 97%) at rest and lactate (2.40 vs 1.90 mmol/L) (P < 0.001). Old age, comorbidity of malignant tumor, neutrophilia, lymphocytopenia, low CD4+ T cells, decreased C3, and low oximetry saturation were the risk factors of death in patients with confirmed COVID-19. The frequency of CD4+ T cells positively correlated with the numbers of lymphocytes (r = 0.787) and the level of oximetry saturation (r = 0.295), Whereas CD4+ T cells were negatively correlated with age (r =-0.323) and the numbers of neutrophils (r = - 0.244) (all P < 0.001). CONCLUSIONS: Abnormal cellular immunity and humoral immunity were key features of non-survivors with COVID-19. Neutrophilia, lymphocytopenia, low CD4+ T cells, and decreased C3 were immunity-related risk factors predicting mortality of patients with COVID-19.

Hyperthermia-triggered UK release nanovectors for deep venous thrombosis therapy.

Deep vein thrombosis (DVT) is a common and lethal complication of surgery. In the clinic, thrombolytic drugs are primarily used for treating DVT. However, the utilization of thrombolytic drugs is limited due to the risk of urokinase (UK)-related hemorrhagic complications. In this paper, a binary eutectic phase-change fatty acid composed of lauric acid and stearic acid was used to block the pores of gold-mesoporous silica core-shell nanoparticles, so as to deliver thrombolytic drugs. The eutectic mixture has a well-defined melting point at 39.2 °C, which can be used as a biocompatible phase-change material for hyperthermia-triggered drug release. The prepared system presents remarkable photothermal effects due to the gold nanoparticles and quick drug release in response to near-infrared irradiation (NIR). In addition, localized hyperthermia could also enhance the lysis of the thrombus. The thrombolytic effect of this system was evaluated in vitro and in vivo. Herein, a rabbit femoral vein thrombosis model was first built for imitating thrombolysis in vivo. The B-ultrasound was then used to monitor the changes in the thrombus after treatment. The results indicated that the reported system could be potentially used to deliver thrombotic drugs in the clinic.

lncRNA-XLOC_012370 Promotes the Development of Pancreatic Cancer and Inactivates the NF-κB Pathway Through miR-140-5p.

Pancreatic cancer is a high incidence, high degree of malignancy, and high mortality in the digestive system tumor. The incidence of pancreatic cancer in China has increased nearly six folds in the past 20 years, ranking fifth in the mortality rate of malignant tumors, so it is particularly important to actively explore clinical indicators with better diagnostic significance for pancreatic cancer. LncRNA performs an essential regulatory function in the occurrence, development, and metastasis of many kinds of tumors, playing both a carcinogenic role and a tumor suppressor gene. Here, we demonstrated the function and mechanism of LncRNA-XLOC_012370 in the development of pancreatic cancer. In our research, the abnormal upregulation of XLOC_012370 was observed in pancreatic cancer patients' tumor tissues. XLOC_012370 was related to tumor stage, lymph node metastasis, and overall survival. Silencing of XLOC_012370 prevented the proliferation, migration, and invasion via the NF-κB signal pathway. Further, miR-140-5p was identified as the target and downstream of XLOC_012370 and involved in pancreatic cancer progression. In vivo, knockdown of XLOC_012370 inhibited tumor growth via the NF-κB signal pathway. In conclusion, lncRNA-XLOC_012370 is closely related to some malignant clinicopathological features and prognosis of pancreatic cancer. Thus the miR-140-5p/NF-κB signal pathway might represent a promising treatment strategy to combat pancreatic cancer.

Influence of the number and substitution position of phenyl groups on the aggregation-enhanced emission of benzene-cored luminogens.

The influence of the number and substitution position of phenyl groups on the aggregation-enhanced emission of benzene-cored luminogens is unambiguously revealed.

Facile synthesis of the naturally cytotoxic triterpenoid saponin Patrinia-glycoside B-II and its conformer.

The first chemical synthesis of the natural triterpenoid saponin Patrinia-glycoside B-II, namely oleanolic acid 3-O-α-L-rhamnopyranosyl-(1→2)-[ß-D-gluco-pyranosyl-(1→3)]-α-L-arabinopyranoside, has been accomplished in a linear 11-step sequence 11 with 9.4% overall yield. The abnormal 1C4 conformation of the arabinose residue was found to occur via conformational fluctuation during preparation of the intermediates. Molecular mechanism and quantum chemistry calculations showed that Patrinia-glycoside B-II and its conformer 1 cannot interconvert under normal conditions. Preliminary structure-activity relationships studies indicated that the 4C1 chair conformation of the arabinose residue in the unique α-L-rhamnopyranosyl-(1→2)-α-L-arabinopyranosyl disaccharide moiety is one of the chief positive factors responsible for its cytotoxic activity against tumors.

[Study of the relationship between the micro-lymphatic vessel density and invasion and metastasis in gastric carcinoma].

AIM: To investigate the relationship between the micro-lymphatic vessel density (LMVD) and invasion and metastasis in gastric carcinoma. METHODS: The expression of LYVE-1 in 52 cases of gastric carcinoma was detected by immunohistochemical SP method, by which the LMVD was calculated. RESULTS: The lymphangiogenesis was shown in peritumoral tissue in gastric carcinoma. LMVD of gastric carcinoma was higher than that of normal gastric tissue (P<0.05). LMVD with lymphatic metastasis was higher than that without lymphatic metastasis (P<0.05); LMVD with big tumor (diameter >5 cm) was higher than that with small tumor (diameter <5 cm) (P<0.05); LMVD with serosal invasion was higher than that without serosal invasion (P<0.05). CONCLUSION: LMVD is closely related to lymph node metastasis, tumor size and invasive depth, which is helpful to determine the prognosis of gastric cancer and treatment program evaluation.

Design, synthesis, and anti-tumor evaluation of novel symmetrical bis-benzimidazoles.

A novel symmetrical bis-benzimidazole was designed as DNA minor groove binder. Molecular modeling study showed that it could dock into the minor groove of DNA. Several derivatives were synthesized and confirmed by IR, MS, and (1)H NMR. All these novel compounds were screened for cytotoxic activity on SKOV-3, HeLa, and BGC-823 cell lines in vitro. Some compounds showed IC(50)s in the single-digit micromolar range for cytotoxicity in several tumor cell lines.