Introduction: Hepatocellular carcinoma (HCC) is a liver cancer. In contrast, ferroptosis is a novel iron-dependent and ROS reliant type of cell death that is observed under various disease conditions.Methods and analysis: RNA sequencing data from HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Ferroptosis-related long non-coding RNAs (lncRNAs) were screened by Pearson correlation analysis. Patients were randomized into training or testing sets in a 1:1 ratio. They were constructed in the training set using univariate-Lasso and multivariate Cox regression analysis and further tested for prognostic values in the testing set. Four lncRNAs were identified. Kaplan-Meier analysis showed that patients in the high-risk group had a worse prognosis than those in the low-risk group. Following differentially expressed genes analysis of these two groups. Functional analysis showed association with oxidative stress response. Cox regression analyses showed that risk score was an independent prognostic indicator. Receiver operating characteristic curve (ROC) and decision curve analysis demonstrated the accuracy of prediction. Four ferroptosis-related lncRNAs based on differential expression of HCC were screened by bioinformatic methods to construct a prognostic risk model and accurately predict the prognosis of HCC patients. Four lncRNAs may have a potential role in the anti-tumor immune process and serve as therapeutic targets for HCC. To lay the foundation for subsequent studies.Abbreviations: CC = cellulose component, DCA = decision curve analysis, DEG = differentially expressed gene, FC = fold change, FDR = false discovery rate, lncRNA = long non-coding RNA, GO = gene ontology, HCC = hepatocellular carcinoma, KEGG = Kyoto Encyclopedia of Genes and Genomes, Lasso = least absolute shrinkage and selection operator, ROC = receiver operating characteristic curve, TCGA = The Cancer Genome Atlas.

Introduction: Since conflicting evidence from systematic reviews and meta-analyses (SRs/MAs) on the effectiveness of acupuncture in the treatment of postpartum depression is observed. To systematically collate, appraise and synthesize the evidence from these SRs/MAs, an overview will be performed, and this study is an overview protocol. Methods and analysis: Eight databases will be searched: Medicine, Web of science, Cochrane Library, Embase, China National Knowledge Infrastructure, SinoMed, VIP, and Wanfang Data. SRs/MAs of acupuncture on postpartum depression will be included. Literature screening, data extraction, and evaluation of the review quality will be performed by 2 independent reviewers. The methodological quality, reporting quality, and evidence quality will be assessed using the assessment of multiple systematic reviews-2 tool, the preferred reporting items for systematic reviews and meta-analyses checklists, and the grading of recommendations, assessment, development, and evaluation system, respectively. The results will be presented in the context of the topic and the objects of the overview. This study will help bridge the implementation gap between clinical evidence and its translation in clinical application, identify flaws in research and guide future high-quality study.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing coronavirus disease , has been devastated by COVID-19 in an increasing number of countries and health care systems around the world since its announcement of a global pandemic on 11 March 2020. During the pandemic, emerging novel viral mutant variants have caused multiple outbreaks of COVID-19 around the world and are prone to genetic evolution, causing serious damage to human health. As confirmed cases of COVID-19 spread rapidly, there is evidence that SARS-CoV-2 infection involves the central nervous system (CNS) and peripheral nervous system (PNS), directly or indirectly damaging neurons and further leading to neurodegenerative diseases (ND), but the molecular mechanisms of ND and CVOID-19 are unknown. We employed transcriptomic profiling to detect several major diseases of ND: Alzheimer 's disease (AD), Parkinson' s disease (PD), and multiple sclerosis (MS) common pathways and molecular biomarkers in association with COVID-19, helping to understand the link between ND and COVID-19. There were 14, 30 and 19 differentially expressed genes (DEGs) between COVID-19 and Alzheimer 's disease (AD), Parkinson' s disease (PD) and multiple sclerosis (MS), respectively; enrichment analysis showed that MAPK, IL-17, PI3K-Akt and other signaling pathways were significantly expressed; the hub genes (HGs) of DEGs between ND and COVID-19 were CRH, SST, TAC1, SLC32A1, GAD2, GAD1, VIP and SYP. Analysis of transcriptome data suggests multiple co-morbid mechanisms between COVID-19 and AD, PD, and MS, providing new ideas and therapeutic strategies for clinical prevention and treatment of COVID-19 and ND. Abbreviations: ACE2 = angiotensin-converting enzyme 2, AD = Alzheimer's disease, BBB = blood-brain barrier, CNS = central nervous system, COVID-19 = coronavirus disease, DEGs = differentially expressed genes, GO = gene ontology, GRN = gene regulatory network, HG = hub gene, KEGG = Kyoto Encyclopedia of Genes and Genomes, miRNA = micro RNA, MS = multiple sclerosis, ND = neurodegenerative diseases, PD = Parkinson's disease, PPI = protein-protein interaction network, SARS-CoV-2 = syndrome coronavirus 2, TFS = transcription factors.