Molecular insights for an anti-osteoporotic properties of Litsea glutinosa on Saos-2 cells: An in-vitro approach

Cowpea isoflavones enhance the osteoblast differentiation and antioxidant capacity in synergy with vitamin D and β-carotene: A mechanistic in vitro study

Background: Osteoporosis (OS) is a pathological condition that makes bones susceptible to fractures by affecting the balance between bone formation and resorption. Recent literature uncovered the possible potential of bioactive compounds with antioxidant mechanisms to counter the issue. Cowpea (CP) isoflavones based on our previous study, vitamin D and natural antioxidant β-carotene for its pleotropic protective effects were assessed alone and in combination. Aim: The study aims to assess the antioxidant and osteoblast differentiation abilities of cowpea isoflavones alone and in combination of vitamin D (VD) and β-carotene (BC) in the human osteosarcoma cell line Saos2. Methods: Saos2 cells were maintained in cell culture conditions and concentrations of CP extract (genistein  +  daidzein), BC and VD required to increase cell proliferation were estimated using MTT assay. Upon treating cells with the EC50 concentrations, lysates were prepared and levels of alkaline phosphatase (ALP) and osteocalcin were evaluated using ELISA. Oxidative stress parameters and osteoblast differentiation markers were evaluated. Results: CP extract (genistein  +  daidzein), BC and VD concentrations which enhanced the cell proliferation rate were determined and elevated levels of ALP and osteocalcin upon treatment was observed. Anti-oxidant stress parameters studied showed an increase in cells upon treatment compared to control. Significant alterations in levels of protein involved in osteoblast differentiation are observed upon treatment. Conclusion: Cowpea isoflavones has shown a significant activity against OS by elevating antioxidant parameters and inducing osteoblast differentiation in the present study.

Multi-omics Analysis to Identify Key Immune Genes for Osteoporosis based on Machine Learning and Single-cell Analysis

OBJECTIVE

Osteoporosis is a severe bone disease with a complex pathogenesis involving various immune processes. With the in-depth understanding of bone immune mechanisms, discovering new therapeutic targets is crucial for the prevention and treatment of osteoporosis. This study aims to explore novel bone immune markers related to osteoporosis based on single-cell and transcriptome data, utilizing bioinformatics and machine learning methods, in order to provide novel strategies for the diagnosis and treatment of the disease.

METHODS

Single cell and transcriptome data sets were acquired from Gene Expression Omnibus (GEO). The data was then subjected to cell communication analysis, pseudotime analysis, and high dimensional WGCNA (hdWGCNA) analysis to identify key immune cell subpopulations and module genes. Subsequently, ConsensusClusterPlus analysis was performed on the key module genes to identify different diseased subgroups in the osteoporosis (OP) training set samples. The immune characteristics between subgroups were evaluated using Cibersort, EPIC, and MCP counter algorithms. OP's hub genes were screened using 10 machine learning algorithms and 113 algorithm combinations. The relationship between hub genes and immunity and pathways was established by evaluating the immune and pathway scores of the training set samples through the ESTIMATE, MCP-counter, and ssGSEA algorithms. Real-time fluorescence quantitative PCR (RT-qPCR) testing was conducted on serum samples collected from osteoporosis patients and healthy adults.

RESULTS

In OP samples, the proportions of bone marrow-derived mesenchymal stem cells (BM-MSCs) and neutrophils increased significantly by 6.73% (from 24.01% to 30.74%) and 6.36% (from 26.82% to 33.18%), respectively. We found 16 intersection genes and four hub genes (DND1, HIRA, SH3GLB2, and F7). RT-qPCR results showed reduced expression levels of DND1, HIRA, and SH3GLB2 in clinical blood samples of OP patients. Moreover, the four hub genes showed positive correlations with neutrophils (0.65-0.90), immature B cells (0.76-0.92), and endothelial cells (0.79-0.87), while showing negative correlations with myeloid-derived suppressor cells (negative 0.54-0.73), T follicular helper cells (negative 0.71-0.86), and natural killer T cells (negative 0.75-0.85).

CONCLUSION

Neutrophils play a crucial role in the occurrence and development of osteoporosis. The four hub genes potentially inhibit metabolic activities and trigger inflammation by interacting with other immune cells, thereby significantly contributing to the onset and diagnosis of OP.

Ethnomedicinal Uses, Phytochemistry, and Therapeutic Potentials of Litsea glutinosa (Lour.) C. B. Robinson: A Literature-Based Review

Litsea glutinosa (Lour.) C. B. Robinson, belonging to the family Lauraceae, is a multipurpose and fast-growing evergreen or deciduous tree that has been traditionally used for numerous purposes such as treatment for diarrhea, dysentery, abdominal pain, indigestion, gastroenteritis, edema, traumatic injuries, colds, arthritis, asthma, diabetes, pain relief, and poignant sexual power. This study aimed to summarize the chemical reports, folk values, and phytopharmacological activities of L. glutinosa, based on available information screened from diverse databases. An up-to-date electronic-based search was accomplished to obtain detailed information, with the help of several databases such as Google Scholar, Scopus, SpringerLink, Web of Science, ScienceDirect, ResearchGate, PubMed, ChemSpider, Elsevier, BioMed Central, and the USPTO, CIPO, INPI, Google Patents, and Espacenet, using relevant keywords. Outcomes advocate that, up to the present time, alkaloids, glycosides, and terpenoids are abundant in, and the most bioactive constituents of, this natural plant. Results demonstrated that L. glutinosa has various remarkable biological activities, including antioxidant, anti-inflammatory, anti-microbial, anticancer, antipyretic, anti-diabetic, analgesic, hepatoprotective, and wound-healing activity. One study revealed that L. glutinosa exhibited significant aphrodisiac and anti-infertility activity. Nevertheless, no clinical studies have been cited. Taken together, L. glutinosa may be one of the significant sources of bioactive constituents that could potentially lead to different effective pharmacological activities. On the other hand, future research should focus on clinical studies and several toxicity evaluations, such as sub-chronic toxicity, teratogenicity, and genotoxicity.

Prognostic analysis and validation of diagnostic marker genes in patients with osteoporosis

Backgrounds

As a systemic skeletal dysfunction, osteoporosis (OP) is characterized by low bone mass and bone microarchitectural damage. The global incidences of OP are high.

Methods

Data were retrieved from databases like Gene Expression Omnibus (GEO), GeneCards, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Gene Expression Profiling Interactive Analysis (GEPIA2), and other databases. R software (version 4.1.1) was used to identify differentially expressed genes (DEGs) and perform functional analysis. The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression and random forest algorithm were combined and used for screening diagnostic markers for OP. The diagnostic value was assessed by the receiver operating characteristic (ROC) curve. Molecular signature subtypes were identified using a consensus clustering approach, and prognostic analysis was performed. The level of immune cell infiltration was assessed by the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm. The hub gene was identified using the CytoHubba algorithm. Real-time fluorescence quantitative PCR (RT-qPCR) was performed on the plasma of osteoporosis patients and control samples. The interaction network was constructed between the hub genes and miRNAs, transcription factors, RNA binding proteins, and drugs.

Results

A total of 40 DEGs, eight OP-related differential genes, six OP diagnostic marker genes, four OP key diagnostic marker genes, and ten hub genes (TNF, RARRES2, FLNA, STXBP2, EGR2, MAP4K2, NFKBIA, JUNB, SPI1, CTSD) were identified. RT-qPCR results revealed a total of eight genes had significant differential expression between osteoporosis patients and control samples. Enrichment analysis showed these genes were mainly related to MAPK signaling pathways, TNF signaling pathway, apoptosis, and Salmonella infection. RT-qPCR also revealed that the MAPK signaling pathway (p38, TRAF6) and NF-kappa B signaling pathway (c-FLIP, MIP1β) were significantly different between osteoporosis patients and control samples. The analysis of immune cell infiltration revealed that monocytes, activated CD4 memory T cells, and memory and naïve B cells may be related to the occurrence and development of OP.

Conclusions

We identified six novel OP diagnostic marker genes and ten OP-hub genes. These genes can be used to improve the prognostic of OP and to identify potential relationships between the immune microenvironment and OP. Our research will provide insights into the potential therapeutic targets and pathogenesis of osteoporosis.