Angiogenesis-related lncRNAs index: A predictor for CESC prognosis, immunotherapy efficacy, and chemosensitivity.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is a common gynecologic tumor and patients with advanced and recurrent disease usually have a poor clinical outcome. Angiogenesis is involved in the biological processes of tumors and can promote tumor growth and invasion. In this paper, we created a signature for predicting prognosis based on angiogenesis-related lncRNAs (ARLs). This provides a prospective direction for enhancing the efficacy of immunotherapy in CESC patients. We screened seven OS-related ARLs by univariate and multivariate regression analyses and Lasso analysis and developed a prognostic signature at the same time. Then, we performed an internal validation in the TCGA-CESC cohort to increase the precision of the study. In addition, we performed a series of analyses based on ARLs, including immune cell infiltration, immune function, immune checkpoint, tumor mutation load, and drug sensitivity analysis. Our created signature based on ARLs can effectively predict the prognosis of CESC patients. To strengthen the prediction accuracy of the signature, we built a nomogram by combining signature and clinical features.

hdWGCNA and Cellular Communication Identify Active NK Cell Subtypes in Alzheimer's Disease and Screen for Diagnostic Markers through Machine Learning.

BACKGROUND: Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative disorder, presenting a significant challenge to global health. Its hallmark pathological features include the deposition of ß-amyloid plaques and the formation of neurofibrillary tangles. Given this context, it becomes imperative to develop an early and accurate biomarker model for AD diagnosis, employing machine learning and bioinformatics analysis. METHODS: In this study, single-cell data analysis was employed to identify cellular subtypes that exhibited significant differences between the diseased and control groups. Following the identification of NK cells, hdWGCNA analysis and cellular communication analysis were conducted to pinpoint NK cell subset with the most robust communication effects. Subsequently, three machine learning algorithms-LASSO, Random Forest, and SVM-RFE-were employed to jointly screen for NK cell subset modular genes highly associated with AD. A logistic regression diagnostic model was then designed based on these characterized genes. Additionally, a protein-protein interaction (PPI) networks of model genes was established. Furthermore, unsupervised cluster analysis was conducted to classify AD subtypes based on the model genes, followed by the analysis of immune infiltration in the different subtypes. Finally, Spearman correlation coefficient analysis was utilized to explore the correlation between model genes and immune cells, as well as inflammatory factors. RESULTS: We have successfully identified three genes (RPLP2, RPSA, and RPL18A) that exhibit a high association with AD. The nomogram based on these genes provides practical assistance in diagnosing and predicting patients' outcomes. The interconnected genes screened through PPI are intricately linked to ribosome metabolism and the COVID-19 pathway. Utilizing the expression of modular genes, unsupervised cluster analysis unveiled three distinct AD subtypes. Particularly noteworthy is subtype C3, characterized by high expression, which correlates with immune cell infiltration and elevated levels of inflammatory factors. Hence, it can be inferred that the establishment of an immune environment in AD patients is closely intertwined with the heightened expression of model genes. CONCLUSION: This study has not only established a valuable diagnostic model for AD patients but has also delved deeply into the pivotal role of model genes in shaping the immune environment of individuals with AD. These findings offer crucial insights into early AD diagnosis and patient management strategies.

Corrigendum: Machine learning to construct sphingolipid metabolism genes signature to characterize the immune landscape and prognosis of patients with uveal melanoma.

[This corrects the article DOI: 10.3389/fendo.2022.1056310.].

New perspectives on migraine treatment: a review of the mechanisms and effects of complementary and alternative therapies.

Migraine is a prevalent and disabling neurovascular disorder, with women being more susceptible, characterized by unilateral throbbing headache, often accompanied by nausea and vomiting, and often associated with various comorbidities such as brain and cardiovascular diseases, which can have a serious impact on quality of life. Although nonsteroidal anti-inflammatory drugs (NSAIDs) are the main first-line medications for the treatment of pain, long-term use often leads to side effects and drug addiction, which emphasizes the need to investigate alternative pain management strategies with fewer adverse effects. Complementary and alternative medicine is a viable pain intervention often used in conjunction with traditional medications, including acupuncture, herbs, moxibustion, transcutaneous electrical stimulation, bio-supplements, and acupressure, which offer non-pharmacological alternatives that are now viable pain management options. This review focuses on the mechanistic doctrine of migraine generation and the role and potential mechanisms of Complementary and Alternative Therapies (CAT) in the treatment of migraine, summarizes the research evidences for CAT as an adjunct or alternative to conventional therapies for migraine, and focuses on the potential of novel migraine therapies (calcitonin gene-related peptide (CGRP) antagonists and pituitary adenylyl cyclase-activating peptide (PACAP) antagonists) with the aim of evaluating CAT therapies as adjunctive or alternative therapies to conventional migraine treatment, thereby providing a broader perspective on migraine management and the design of treatment programs for more effective pain management.

Machine Learning Prediction of Prediabetes in a Young Male Chinese Cohort with 5.8-Year Follow-Up.

The identification of risk factors for future prediabetes in young men remains largely unexamined. This study enrolled 6247 young ethnic Chinese men with normal fasting plasma glucose at the baseline (FPGbase), and used machine learning (Mach-L) methods to predict prediabetes after 5.8 years. The study seeks to achieve the following: 1. Evaluate whether Mach-L outperformed traditional multiple linear regression (MLR). 2. Identify the most important risk factors. The baseline data included demographic, biochemistry, and lifestyle information. Two models were built, where Model 1 included all variables and Model 2 excluded FPGbase, since it had the most profound effect on prediction. Random forest, stochastic gradient boosting, eXtreme gradient boosting, and elastic net were used, and the model performance was compared using different error metrics. All the Mach-L errors were smaller than those for MLR, thus Mach-L provided the most accurate results. In descending order of importance, the key factors for Model 1 were FPGbase, body fat (BF), creatinine (Cr), thyroid stimulating hormone (TSH), WBC, and age, while those for Model 2 were BF, white blood cell, age, TSH, TG, and LDL-C. We concluded that FPGbase was the most important factor to predict future prediabetes. However, after removing FPGbase, WBC, TSH, BF, HDL-C, and age were the key factors after 5.8 years.

Acupuncture therapy on myofascial pain syndrome: a systematic review and meta-analysis.

Purpose: Traditional Chinese medicine (TCM) therapies, especially acupuncture, have received increasing attention in the field of pain management. This meta-analysis evaluated the effectiveness of acupuncture in the treatment of myofascial pain syndrome. Methods: A comprehensive search was conducted across a number of databases, including PubMed, Cochrane Library, WOS, CNKI, WANFANG, Sinomed, and VIP. Furthermore, articles of studies published from the inception of these databases until November 22, 2023, were examined. This systematic review and meta-analysis encompassed all randomized controlled trials (RCTs) on acupuncture for myofascial pain syndromes, without language or date restrictions. Based on the mean difference (MD) of symptom change, we critically assessed the outcomes reported in these trials. The quality of evidence was assessed using the Cochrane Risk of Bias Tool. The study is registered with PROSPERO under registration number CRD42023484933. Results: Our analysis included 10 RCTs in which 852 patients were divided into two groups: an acupuncture group (427) and a control group (425). The results of the study showed that acupuncture was significantly more effective than the control group in treating myofascial pain syndromes, which was reflected in a greater decrease in VAS scores (MD = -1.29, 95% [-1.65, -0.94], p < 0.00001). In addition, the improvement in PRI and PPI was more pronounced in the acupuncture group (PRI: MD = -2.04, 95% [-3.76, -0.32], p = 0.02) (PPI: MD = -1.03, 95% [-1.26, -0.79], p < 0.00001) compared to the control group. These results suggest that acupuncture is effective in reducing myofascial pain. It is necessary to further study the optimal acupoints and treatment time to achieve the best therapeutic effect. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023484933.

SpyGlass guided PDT for advanced intraductal papillary mucinous neoplasm of the bile tract: A case report and literature review.

Intraductal papillary mucinous neoplasm of the bile tract is a rare biliary tumor characterized by mucin growth within the bile duct. In the early stages, it often presents without significant obstruction, this often leads to its discovery in the advanced stages. We report a case of a 63-year-old female with an intraductal papillary mucinous neoplasm of the bile duct (IPMN-B). The patient had a history of intrahepatic bile duct stones and biliary ascariasis. She gradually developed symptoms such as jaundice and intermittent fever before admission, and a bile duct biopsy confirmed the diagnosis of IPMN-B. Currently, endoscopic photodynamic therapy (PDT) is considered an effective treatment for bile duct cancer. In this case, we performed two sessions of PDT guided by SpyGlass. The patient experienced complete remission postoperatively, and there has been no evidence of tumor recurrence or metastasis in the three years following the procedure.