Clinical Significance of Sarcopenia in Elderly Patients Undergoing Endoscopic Submucosal Dissection: A Systematic Review and Meta-analysis.

BACKGROUND AND AIMS: As global life expectancy rises and gastrointestinal tumor incidence increases, more elderly patients are undergoing endoscopic submucosal dissection (ESD) for tumor treatment. The current situation highlights the importance of sarcopenia assessment before ESD. This systematic review and meta-analysis aim to assess sarcopenia's role in predicting post-ESD adverse outcomes in the elderly. METHODS: We conducted a systematic review and meta-analysis to investigate the impact of sarcopenia on the prognosis of elderly patients undergoing ESD treatment. A comprehensive search was conducted across three databases (PubMed, Embase, Web of Science). We were using NEWCASTLE-OTTAWA ASSESSMENT SCALE for risk of bias assessment. The data were synthesized using Review Manager 5.3. RESULTS: A total of 9 reports were identified, analyzing 7 indicators, with a combined sample size of 6044. Through a series of analyses, we have derived several highly credible research findings: the overall OR and 95% CI for gastric and colorectal post-ESD perforation between sarcopenia and nonsarcopenia groups were 1.34 [0.92, 1.97], for CTCAE grade > 2 was 2.65 [1.45, 4.82], for upper gastrointestinal post-ESD pneumonia were 1.97 [1.30, 2.99], and for gastric post-ESD mortality within 5 years were 2.96 [1.33, 6.58]. CONCLUSIONS: Sarcopenia is a risk factor for increased incidence of complications (CTCAE > 2) after undergoing gastric and colorectal ESD, increased pneumonia rates, and higher mortality rates within five years following gastric ESD treatment in elderly patients. However, sarcopenia does not lead to an increased perforation rate in elderly patients undergoing gastric and colorectal ESD treatments. Registration and protocol: The protocol for this study was registered on the Open Science Framework in 2024 https://doi.org/10.17605/OSF.IO/7B2CZ . We also conducted pre-registration on PROSPERO (CRD42024532547).

Sarcopenia among treated cancer patients before and after neoadjuvant chemotherapy: a systematic review and meta-analysis of high-quality studies.

BACKGROUND: Neoadjuvant chemotherapy, used to shrink tumors before surgery, is increasingly applied in clinical practice. However, retrospective studies indicate that it may increase sarcopenia rates and consequently result in an elevated occurrence rate of postoperative severe complications such as severe surgical incision infection, severe respiratory failure, and severe postoperative hemorrhage, especially in the elderly population. Currently, no systematic analysis examines the association between neoadjuvant chemotherapy and sarcopenia. This study aims to fill this gap with a comprehensive meta-analysis focused on this critical aspect of the field. METHODS: A systematic literature search was conducted in the PubMed and Web of Science databases from their inception to January 2024. The included studies encompassed patients who received neoadjuvant chemotherapy and underwent computed tomography (CT) scans both before and after treatment to calculate skeletal muscle index (SMI) or categorize them for the presence of sarcopenia. The determination of sarcopenia status was based on well-established and validated threshold criteria. Data extraction was performed independently by two reviewers. A meta-analysis was employed to estimate the pooled odds ratio (OR) and its corresponding 95% confidence interval (95% CI) to assess the risk of neoadjuvant chemotherapy-induced muscle reduction. RESULTS: In the 14 studies with complete categorical variable data, comprising 1853 patients, 773 patients were identified as having sarcopenia before neoadjuvant treatment and 941 patients had sarcopenia after neoadjuvant therapy. The OR and its 95% CI was calculated as 1.51 [1.31, 1.73]. Among these, 719 patients had digestive system cancer, with 357 patients having sarcopenia before neoadjuvant treatment and 447 patients after, resulting in an OR of 1.74 [1.40, 2.17]. In the remaining 1134 patients with non-digestive system cancers, 416 were identified as having sarcopenia before neoadjuvant treatment, and 494 patients had sarcopenia after, with an OR of 1.37 [1.15, 1.63]. Additionally, in seven studies with complete continuous variable data, including 1228 patients, the mean difference in the change of SMI before and after neoadjuvant treatment was - 1.13 [- 1.65, - 0.62]. After excluding low-quality small-sample studies with fewer than 50 patients, the same trend was observed in the analysis. CONCLUSION: The risk of muscle reduction significantly increases in cancer patients after neoadjuvant chemotherapy and digestive system cancers tend to have a higher risk of developing sarcopenia post-treatment compared to non-digestive system cancers.

Novel role of lncRNAs regulatory network in papillary thyroid cancer.

Papillary thyroid cancer (PTC) is the most common endocrine malignancy. The incidence of PTC has increased annually worldwide. Thus, PTC diagnosis and treatment attract more attention. Noncoding RNAs (lncRNAs) play crucial roles in PTC progression and act as prognostic biomarkers. Moreover, microRNAs (miRNAs) and epithelial-mesenchymal transition (EMT)-associated proteins have potential biomarkers for diagnosing and treating PTC. However, the correlation of lncRNAs with miRNAs and EMT-associated proteins needs further clarification. The present review highlights the recent advances of lncRNAs in PTC. We significantly summarized the two molecular regulatory mechanisms in PTC progress, including lncRNAs-miRNAs-protein signaling axes and lncRNAs-EMT pathways. This review will help our understanding of the association between lncRNAs and PTC and may assist us in evaluating the prognosis for PTC patients. Taken together, targeting the lncRNAs regulatory network has promising applications in diagnosing and treating PTC.

Near-infrared fluorophores methylene blue for targeted imaging of the stomach in intraoperative navigation.

Near-infrared (NIR) fluorescence imaging-guided surgery is increasingly concerned in gastrointestinal surgery because it can potentially improve clinical outcomes. This new technique can provide intraoperative image guidance for surgical margin evaluation and help surgeons examine residual lesions and small tumors during surgery. NIR fluorophores methylene blue (MB) is a promising fluorescent probe because of its safety and intraoperative imaging in the clinic. However, whether MB possesses the potential to perform intraoperative navigation of the stomach and gastric tumors needs to be further explored. Therefore, the current study mainly validated MB's usefulness in animal models' intraoperative imaging of stomach and gastric tumors. NIR fluorophores MB can exhibit specific uptake by the gastric epithelial cells and cancer cells. It is primarily found that MB can directly target the stomach in mice. Interestingly, MB was applied for the NIR imaging of gastric cancer cell xenografts, suggesting that MB cannot specifically target subcutaneous and orthotopic gastric tumors in xenograft models. Thus, it can be concluded that MB has no inherent specificity for gastric tumors but specificity for gastric tissues. Apparently, MB-positive and negative NIR imaging are meaningful in targeting gastric tissues and tumors. MB is expected to represent a helpful NIR agent to secure precise resection margins during the gastrectomy and resection of gastric tumors.

A Probabilistic Bayesian Parallel Deep Learning Framework for Wind Turbine Bearing Fault Diagnosis.

The technology of fault diagnosis helps improve the reliability of wind turbines. Difficulties in feature extraction and low confidence in diagnostic results are widespread in the process of deep learning-based fault diagnosis of wind turbine bearings. Therefore, a probabilistic Bayesian parallel deep learning (BayesianPDL) framework is proposed and then achieves fault classification. A parallel deep learning (PDL) framework is proposed to solve the problem of difficult feature extraction of bearing faults. Next, the weights and biases in the PDL framework are converted from deterministic values to probability distributions. In this way, an uncertainty-aware method is explored to achieve reliable machine fault diagnosis. Taking the fault signal of the gearbox output shaft bearing of a wind turbine generator in a wind farm as an example, the diagnostic accuracy of the proposed method can reach 99.14%, and the confidence in diagnostic results is higher than other comparison methods. Experimental results show that the BayesianPDL framework has unique advantages in the fault diagnosis of wind turbine bearings.