The role of neutrophil percentage to albumin ratio in predicting 1-year mortality in elderly patients with hip fracture and external validation.

Objectives: This study aimed to investigate the association between the neutrophil percentage to albumin ratio (NPAR) on the day of admission and mortality 1 year after surgery in elderly patients with hip fractures. Methods: Clinical characteristics and blood markers of inflammation were retrospectively collected from October 2016 to January 2022 in elderly patients with hip fractures at two different regional tertiary medical centers. It is divided into a training set and an external validation set. Multivariate Nomogram models such as NPAR were constructed using the least absolute shrinkage and selection operator (LASSO) regression results and multi-factor logistic regression analysis. In addition, multivariate Cox regression analysis and Kaplan-Meier survival curves were used to explore the relationship between NPAR values and mortality within 1 year in elderly patients with hip fractures. The predictive performance of the Nomogram was evaluated using the concordance index (C Index) and receiver operating characteristic curve (ROC) and validated by Bootstrap, Hosmer-Lemesow goodness of fit test, calibration curve, decision curve, and clinical impact curve analysis. Results: The study included data from 1179 (mean age, 80.34 ± 8.06 years; 61.4[52.1%] male) patients from the Guangzhou Red Cross Hospital affiliated with Jinan University and 476 (mean age, 81.18 ± 8.33 years; 233 [48.9%] male) patients from the Xiaogan Central Hospital affiliated with Wuhan University of Science and Technology. The results showed that NPAR has good sensitivity and specificity in assessing patients' prognosis 1 year after surgery. Multivariate logistic regression models based on influencing factors such as NPAR have good discrimination and calibration ability (AUC=0.942, 95% CI:0.927-0.955; Hosmer-Lemeshow test: P >0.05). Kaplan-Meier survival curves for the training and validation sets showed that patients in the high NPAR group had a higher mortality rate at 1 year compared to the low NPAR group (P< 0.001). Multivariate Cox regression showed that high NPAR values were an independent risk factor for death within 1 year in elderly hip fracture patients (P< 0.001, HR =2.38,95%CI:1.84-3.08). Conclusion: Our study showed that NPAR levels were significantly higher in patients who died within 1 year after surgery in both the training and validation sets. NPAR has good clinical value in assessing 1-year postoperative prognosis in elderly patients with hip fractures.

Identification of aging-related biomarkers and immune infiltration characteristics in osteoarthritis based on bioinformatics analysis and machine learning.

Background: Osteoarthritis (OA) is a degenerative disease closely related to aging. Nevertheless, the role and mechanisms of aging in osteoarthritis remain unclear. This study aims to identify potential aging-related biomarkers in OA and to explore the role and mechanisms of aging-related genes and the immune microenvironment in OA synovial tissue. Methods: Normal and OA synovial gene expression profile microarrays were obtained from the Gene Expression Omnibus (GEO) database and aging-related genes (ARGs) from the Human Aging Genomic Resources database (HAGR). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO), and Gene set variation analysis (GSVA) enrichment analysis were used to uncover the underlying mechanisms. To identify Hub ARDEGs with highly correlated OA features (Hub OA-ARDEGs), Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning methods were used. Furthermore, we created diagnostic nomograms and receiver operating characteristic curves (ROC) to assess Hub OA-ARDEGs' ability to diagnose OA and predict which miRNAs and TFs they might act on. The Single sample gene set enrichment analysis (ssGSEA) algorithm was applied to look at the immune infiltration characteristics of OA and their relationship with Hub OA-ARDEGs. Results: We discovered 87 ARDEGs in normal and OA synovium samples. According to functional enrichment, ARDEGs are primarily associated with inflammatory regulation, cellular stress response, cell cycle regulation, and transcriptional regulation. Hub OA-ARDEGs with excellent OA diagnostic ability were identified as MCL1, SIK1, JUND, NFKBIA, and JUN. Wilcox test showed that Hub OA-ARDEGs were all significantly downregulated in OA and were validated in the validation set and by qRT-PCR. Using the ssGSEA algorithm, we discovered that 15 types of immune cell infiltration and six types of immune cell activation were significantly increased in OA synovial samples and well correlated with Hub OA-ARDEGs. Conclusion: Synovial aging may promote the progression of OA by inducing immune inflammation. MCL1, SIK1, JUND, NFKBIA, and JUN can be used as novel diagnostic biomolecular markers and potential therapeutic targets for OA.

Cancer drug therapy and stochastic modeling of "nano-motors".

BACKGROUND: Controlled inhibition of kinesin motor proteins is highly desired in the field of oncology. Among other interventions, there exists "targeted chemotherapeutic regime/options" of selective Eg5 competitive and allosteric inhibitors, inducing cancer cell apoptosis and tumor regression with improved safety profiles. RESEARCH QUESTION: Though promising, such studies are still under clinical trials, for the discovery of efficient and least harmful Eg5 inhibitors. The aim of this research was to bridge the computational modeling approach with drug design and therapy of cancer cells. METHODS: A computational model, interfaced with the clinical data of "Eg5 dynamics" and "inhibitors" via special functions, is presented in this article. Comparisons are made for the drug efficacy, and the threshold values are predicted through numerical simulations. RESULTS: Results are obtained to depict the dynamics induced by ispinesib, when used as an inhibitor of kinesin Eg5, on cancer cell lines.

Role of key players in paradigm shifts of prostate cancer bone metastasis.

The decreased bone mineral density and compromised bone strength predispose individuals to skeletal osteoporosis. Both prostate cancer and bone metastasis caused by cancer invasion have remained a great challenge to researchers. With the advancement in the fields of biochemistry and biomechanics, the molecular mechanisms that make prostate cancer metastasize to bone have recently been identified, and they provide new molecular targets for drug development. Many biochemical by-products have been identified to help in understanding the interaction between the bone and the tumor. Enhanced clinical management of patients with bone metastases was reported during the past decade; however, the anticipated risk and the response to the therapy are still challenging to assess. In this review, the key players that play a dominant role in secondary osteoporosis are addressed. An attempt is made to provide the readers with a clear understanding of the communication pathways between each of the cell types involved in this vicious cycle. Furthermore, the role of Wnts, sclerostin, RANKL, PTHrP, and their respective clinical studies are addressed in this study.