Validating core therapeutic targets for osteoporosis treatment based on integrating network pharmacology and informatics.

OBJECTIVE: Our goal was to find metabolism-related lncRNAs that were associated with osteoporosis (OP) and construct a model for predicting OP progression using these lncRNAs. METHODS: The GEO database was employed to obtain gene expression profiles. The WGCNA technique and differential expression analysis were used to identify hypoxia-related lncRNAs. A Lasso regression model was applied to select 25 hypoxia-related genes, from which a classification model was created. Its robust classification performance was confirmed with an area under the ROC curve close to 1, as verified on the validation set. Concurrently, we constructed a ceRNA network based on these genes to unveil potential regulatory processes. Biologically active compounds of STZYD were identified using the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP) database. BATMAN was used to identify its targets, and we obtained OP-related genes from Malacards and DisGeNET, followed by identifying intersection genes with metabolism-related genes. A pharmacological network was then constructed based on the intersecting genes. The pharmacological network was further integrated with the ceRNA network, resulting in the creation of a comprehensive network that encompasses herb-active components, pathways, lncRNAs, miRNAs, and targets. Expression levels of hypoxia-related lncRNAs in mononuclear cells isolated from peripheral blood of OP and normal patients were subsequently validated using quantitative real-time PCR (qRT-PCR). Protein levels of RUNX2 were determined through a western blot assay. RESULTS: CBFB, GLO1, NFKB2 and PIK3CA were identified as central therapeutic targets, and ADD3-AS1, DTX2P1-UPK3BP1-PMS2P11, TTTY1B, ZNNT1 and LINC00623 were identified as core lncRNAs. CONCLUSIONS: Our work uncovers a possible therapeutic mechanism for STZYD, providing a potential therapeutic target for OP. In addition, a prediction model of metabolism-related lncRNAs of OP progression was constructed to provide a reference for the diagnosis of OP patients.

Derivation and comprehensive analysis of ageing-related genes in intervertebral disc degeneration for prediction and immunology.

Intervertebral disc degeneration (IDD) is triggered primarily by ageing, a process characterized by intrinsic, multifaceted and progressive characteristics. Regarding the crucial senescence genes and underlying regulatory mechanisms leading to the etiology of IDD, there is still some uncertainty. In this study, we used gene expression patterns from the GEO database to create a diagnostic model of IDD using differential ageing-related genes (DARG). We examine the relative dynamics of immune cells by single-sample gene set. On the basis of transcription factor (TF) miRNA and miRNA-mRNA pairs, the regulatory network for transcription and post-transcriptional processes was built. The active therapeutic components and Chinese herbal remedies of the main ageing genes were investigated using a network pharmacology approach. 20 DARGs were combined to create a diagnostic model, and both the training and validation sets had an area under the ROC curve of 1. We found alterations in many cell types in IDD tissue, but mainly in activated dendritic cells, type 17 T helper cells, and mast cells. We identified a regulatory axis for STAT1/miR-4306/PPARA based on the correlations between gene expression and targeting. Active substances (Naringenin and Quercetin) and herbs (Aurantii fructus and Eucommiae cortex) targeting PPARA for the treatment of IDD were discovered through network pharmacology. These results provide a theoretical framework for identifying and treating IDD. For the first time, we were able to diagnose IDD patients using 20 ageing-related indicators. At the same time, TF-miRNA-mRNA in conjunction with network pharmacology enabled the identification of prospective therapeutic targets and pharmacological processes.

Potential superiority of periarticular injection in analgesic effect and early mobilization ability over femoral nerve block following total knee arthroplasty.

PURPOSE: Pain management after total knee arthroplasty (TKA) should permit early knee mobilization with minimal pain. Periarticular injection (PAI) with local anaesthetics has been recently discussed as a protocol of pain control. The purpose of this review of the literature was to evaluate the efficacy of PAI in comparison with femoral nerve block (FNB). METHODS: A literature search was performed in PubMed, EMBASE, the OVID database and the Cochrane Library databases. Risk of bias was assessed using the Cochrane collaboration tool. Outcomes of interest included narcotic consumption, pain score, early mobilization ability, length of stay and adverse effects or events. RESULTS: Research identified 918 articles, of which six with a total of 284 knees, met the inclusion criteria and were eligible for the current study. Conflicting evidence was found in terms of narcotic consumption on the postoperative day 1 and early mobilization ability. Total narcotic consumption, pain score in the first 2 days after surgery, length of stay and adverse effects or events showed no difference between two groups. Lower pain score on the day of surgery was detected after PAI. When compared to continuous FNB, patients in PAI group showed a tendency to achieving better ability of early mobilization. CONCLUSIONS: In consideration of its relatively simple practice and its potential in analgesic effects or early mobilization ability, PAI had superiority to FNB in the management of pain control after TKA. Before PAI could be widely used in clinical practice after TKAs, further investigations would be necessary to confirm or refute our observed results and to unify the protocol of PAI. LEVEL OF EVIDENCE: I.