Identification of hub genes in papillary thyroid carcinoma: robust rank aggregation and weighted gene co-expression network analysis.

BACKGROUND: Papillary thyroid carcinoma (PTC), which is the most common endocrine malignancy, has been steadily increasing worldwide in incidence over the years, while mechanisms underlying the pathogenesis and diagnostic for PTC are incomplete. The purpose of this study is to identify potential biomarkers for diagnosis of PTC, and provide new insights into pathogenesis of PTC. METHODS: Based on weighted gene co-expression network analysis, Robust Rank Aggregation, functional annotation, GSEA and DNA methylation, were employed for investigating potential biomarkers for diagnosis of PTC. RESULTS: Black and turquoise modules were identified in the gene co-expression network constructed by 1807 DEGs that from 6 eligible gene expression profiles of Gene Expression Omnibus database based on Robust Rank Aggregation and weighted gene co-expression network analysis. Hub genes were significantly down-regulated and the expression levels of the hub genes were different in different stages in hub gene verification. ROC curves indicated all hub genes had good diagnostic value for PTC (except for ABCA6 AUC = 89.5%, the 15 genes with AUC > 90%). Methylation analysis showed that hub gene verification ABCA6, ACACB, RMDN1 and TFPI were identified as differentially methylated genes, and the decreased expression level of these genes may relate to abnormal DNA methylation. Moreover, the expression levels of 8 top hub genes were correlated with tumor purity and tumor-infiltrating immune cells. These findings, including functional annotations and GSEA provide new insights into pathogenesis of PTC. CONCLUSIONS: The hub genes and methylation of hub genes may as potential biomarkers provide new insights for diagnosis of PTC, and all these findings may be the direction to study the mechanisms underlying of PTC in the future.

Ethnicity and survival in bladder cancer: a population-based study based on the SEER database.

BACKGROUND: Bladder cancer is the most common cancer in the urinary system and the fourth most common cancer in males. This study aimed to examine differences in the survival of bladder cancer patients of different ethnicities. METHOD: We used the SEER database to obtain data pertaining to bladder cancer patients from 2010 to 2015. Univariate and multivariate Cox proportional hazards regression analyses were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between ethnicity and death. Kaplan-Meier survival and nomogram analyses were used to compare survival differences among patients with different ethnicities. RESULTS: Among 101,364 bladder cancer patients, 90,910 were white, 5893 were black, 337 were American Indian/Alaska Native (AIAN), and 4224 were Asian or Pacific Islander (API). Our multivariate analysis identified differences between different ethnicities. Compared to the API group, the AIAN (HR = 1.31, 95% CI = 1.09-1.57, P < 0.001), black (HR = 1.56, 95% CI = 1.46-1.67, P < 0.001), and white (HR = 1.18, 95% CI = 1.12-1.25, P < 0.001) groups showed lower survival probabilities. Based on data from all Kaplan-Meier survival curves, there was no significant difference in survival between the black and AIAN groups, but the survival of these two races was worse than that of the white and API groups. We also used a nomogram to estimate patient survival and validated its predictive value. CONCLUSION: Our results suggest that ethnic differences exist in patients with bladder cancer, that the survival of black and AIAN bladder cancer patients is worse than that of other ethnicities and that the survival of API patients is the best. The significant prognostic factors of overall survival, which include age, sex, ethnicity, summary stage, American Joint Committee on Cancer stage, surgery type, and histologic type, should be applied to bladder cancer patient prognostication.

The predictive accuracy of CT radiomics combined with machine learning in predicting the invasiveness of small nodular lung adenocarcinoma.

Background: Conventionally, the judgment of whether small pulmonary nodules are invasive is mainly made by thoracic surgeons according to the chest computed tomography (CT) features of patients. However, there are limits to how much useful information can be obtained from this approach. A large number of feature information was extracted from CT images by CT radiomics. The machine learning algorithm was used to construct models based on radiomic characteristics to predict the invasiveness of lung adenocarcinoma (LUAD) with a good prediction accuracy. Methods: A total of 416 patients with pathologically confirmed preinvasive lesions and LUAD after video-assisted thoracoscopic surgery (VATS) in the Department of Thoracic Surgery of the First People's Hospital of Yunnan Province from February 2020 to February 2022 were retrospectively analyzed. According to random classification, patients were divided into 2 groups. The RadCloud platform was used to extract radiomics features, and the most relevant radiomics features were selected by continuous dimension reduction method. Then, 6 machine learning algorithms were used to establish and verify the prediction model of small lung nodular adenocarcinoma invasiveness. Receiver operating characteristic (ROC) curve and area under curve (AUC) were used to evaluate the predictive performance. Results: There were 78 cases of pre-invasive lesions and 226 cases of invasive lesions in the training group, and 34 cases of pre-invasive lesions and 78 cases of invasive lesions in the validation group. In the training group, the AUC values of the 6 models were all more than 0.914, the 95% confidence interval (CI) was 0.857-1.00, the sensitivity was equal or more than 0.87, and the specificity was equal or more than 0.85. In the validation group, the AUC values of the 6 models were all equal or more than 0.732, the 95% CI was 0.651-1.00, the sensitivity was equal or more than 0.7, and the specificity was more than 0.77. Conclusions: Machine learning algorithms were used to construct models to predict the invasiveness of small nodular LUAD based on radiomics features, which it could provide more evidence for doctors to make diagnoses and more personalized treatment plans for patients.

A Shortcut to the Optimization of Cellulase Production Using the Mutant Trichoderma reesei YC-108.

Trichoderma reesei YC-108, a strain isolated by a kind of newly invented plate was found to over produce cellulase and it was then used as a cellulase producer. To get the maximum amount of cellulase, the combination of the medium ingredients, which has a profound influence on metabolic pathway was optimized using response surface methodology. The optimum composition was found to be 24.63 g/L wheat bran, 30.78 g/L avicel, and 19.16 g/L soya-bean cake powder. By using the optimized medium, the filter paper activity (FPA) increased nearly five times to 15.82 IU/mL in a 30 L stirred fermenter, carboxymethyl cellulase activity (CMCase) was increased from 83.02 to 628.05 IU/mL and the CMCase/FPA ratio was nearly doubled compared with the parent strain at initial medium.

Comparison of two preoperative positioning techniques and unpositioning methods in non-intubated video-assisted thoracoscopic surgery.

Background: Using the non-intubated video-assisted thoracoscopic surgery (VATS) approach for small pulmonary nodules (SPNs) can accelerate patients' postoperative recovery. However, locating the SPNs intraoperatively by palpation can be difficult for thoracic surgeons. The advantages of using different preoperative positioning materials are different, especially for pulmonary-nodule-location-needle (P-N-L-N) and the microcoil. This retrospective study analyzed the advantages of two preoperative positioning techniques for VATS under non-intubation anesthesia. Methods: The data were collected for a total of 150 patients with pulmonary nodules who underwent non-intubated VATS at the First People's Hospital of Yunnan Province from January 2018 to January 2021. The patients were divided into a preoperative positioning group (including a P-N-L-N group and microcoil group) and an unlocalized group. These included patients were all compliant with surgical guidelines and were suitable for preoperative localization. Their intraoperative and postoperative indicators were compared, and among these indicators, the operative time, number of postoperative drainage days, postoperative total drainage volume, postoperative discharge time was efficacy group and the intraoperative blood loss was safety group. Results: Preoperative localization helped surgeons to explore nodules faster intraoperatively and remove SPNs precisely under non-intubated VATS. But the advantages of using different preoperative positioning materials are different. Positioning with either microcoil or P-N-L-N resulted in less operation time (P-N-L-N group: 94.90±28.42 min, microcoil group: 112.80±28.6 min, P<0.05), less intraoperative blood loss (P-N-L-N group: 35.80±21.17 mL, microcoil group: 75.00±65.22 mL, P<0.001) and less postoperative thoracic drainage volume (P-N-L-N group: 64.90±181.96 mL, microcoil group: 648.52±708.81 mL, P<0.001). However, the postoperative discharge time (P-N-L-N group: 5.02±1.35 days, microcoil group: 5.40±2.79 days, P=0.38) and postoperative drainage time(P-N-L-N group: 2.58±1.70 days, microcoil group: 3.18±2.49 days, P=0.16) was not statistically significant. Positioning with P-N-L-N seemed to have a better auxiliary effect for non-intubated VATS, suggesting its use can assist surgeons to determine the location of the lesion more accuracy intraoperatively. There was no significant difference in the pathological results among the groups. Conclusions: Localization of SPNs is beneficial in non-intubated VATS, and the use of P-N-L-N was more effective than the microcoil in reducing operative time, intraoperative blood loss, postoperative total drainage volume, and postoperative discharge time.

Clinical Outcomes of Tanezumab With Different Dosages for Patient With Osteoarthritis: Network Meta-Analysis.

Background: Osteoarthritis (OA) high disability rate will increase as people getting older, and is the most prevalent form of arthritis in the future. This study identified the clinical effects of optimum doses of tanezumab for patients with OA. Method: Three electronic databases were searched up until January 15, 2021. The mean difference (MD) or odds ratio (OR) was considered an effect measure. The design-by-treatment interaction model was adopted for network meta-analyses. Analyses were conducted using WinBUGS 1.4.3 and R 4.0.5 software. Results: nine publications with 10 studies were included. Compared with placebo in network meta-analysis, except the outcomes of Western Ontario and McMaster Universities Osteoarthritis (WOMAC) stiffness subscale and joints replaced, all dosages of tanezumab in the other effectiveness outcome were superior to placebo, and the difference was statistically significant. However, there was no statistical difference among all different doses of tanezumab. Compared with placebo, except the outcomes of adverse events (AEs) and AEs of abnormal peripheral sensation, all different dosages of tanezumab weren't superior to placebo in the other effectiveness outcome, and the difference was statistically significant. The 10 mg of tanezumab with highest SUCRA had the best effect, but it was associated with a higher safety event. Compared with placebo, except the outcomes of WOMAC stiffness subscale and joints replaced, all dosages of tanezumab in the other effectiveness outcome were superior to placebo, and the difference was statistically significant. Compared with placebo, except for the outcomes of AEs and AEs of abnormal peripheral sensation, all dosages of tanezumab in the other effectiveness outcome were superior to placebo, and the difference was statistically significant. Other direct comparisons showed no statistical difference. Conclusion: This study recommended that clinicians should give priority to the treatment of OA patients with a low dose of 2.5 mg according to the patient's condition and actual situation. If the effect using tanezumab with 2.5 mg is not satisfactory, the increase up to 10 mg should be carefully pondered, because of a more unbalanced risk/benefit ratio.

Comparative Efficacy and Acceptability of Pharmaceutical Management for Adults With Post-Traumatic Stress Disorder: A Systematic Review and Meta-Analysis.

The current clinical guidelines on post-traumatic stress disorder (PTSD) recommend selective serotonin reuptake inhibitors (SSRIs) and serotonin and norepinephrine reuptake inhibitors (SNRIs) of drugs. However, there is uncertainty about the efficacy of other drugs and selecting which treatments work best for which patients. This meta-analysis evaluated efficacy and acceptability of pharmaceutical management for adults with PTSD. Randomized-controlled trials, which reported active comparators and placebo-controlled trials of pharmaceutical management for adults with PTSD, from the Ovid Medline, EMBase, CENTRAL, PsycINFO, Ovid Health and Psychosocial Instruments, and ISIWeb of Science, were searched until June 21, 2019. In terms of efficacy, all active drugs demonstrated superior effect than placebo (SMD = -0.33; 95% CI, -0.43 to -0.23). The medications were superior to placebo in reducing the symptom of re-experiencing, avoidance, hyperarousal, depression, and anxiety. For acceptability, medicine interventions for PTSD showed no increase in all-cause discontinuation compared with placebo. Nevertheless, in terms of safety, medicine interventions indicated a higher risk of adverse effect compared with placebo (RR = 1.47, 95% CI: 1.24 to 1.75). Compared with placebo, the SSRIs and atypical antipsychotics drugs had significant efficacy whether in patients with severe or extremely severe PTSD status. However, only atypical antipsychotics (SMD = -0.29, 95% CI: -0.48 to -0.10) showed superior efficacy than placebo in veterans. Medication management could be effective in intervention of PTSD, which demonstrated a sufficient improvement in the core symptoms. This meta-analysis supports the status of SSRIs and SNRIs as recommended pharmacotherapy. However, patients with different clinical characteristics of PTSD should consider individualized drug management.