Risk Factors and Clinical Significance of Ankylosing Spondylitis Combined with Early-Onset Coronary Heart Disease.

Objective: To explore the risk factors contributing to the development of premature coronary artery disease (PCAD) in patients with ankylosing spondylitis (AS) and assess the clinical implications of this association. Methods: The study used a retrospective analysis design to investigate the risk factors and clinical significance of ankylosing spondylitis (AS) combined with early-onset coronary heart disease (AS-PCAD). A total of 80 patients diagnosed with AS and coronary heart disease who were admitted to the hospital between February 2019 and February 2022 were included in the analysis. The patients were divided into two groups based on the age of onset of coronary heart disease - the PCAD group (n=42, mean age 41.48±2.69 years) and the non-early-onset coronary heart disease (NPCAD) group (n=38, mean age 69.13±4.50 years). Relevant clinical data, including demographics, medical history, laboratory results, and imaging findings, were extracted from electronic health records. Binary logistic regression analysis was employed to identify risk factors influencing the incidence of AS-PCAD. The study aimed to uncover the distinctive clinical features and risk factors associated with AS patients who experience early-onset coronary heart disease, in order to guide diagnosis and treatment strategies for this patient population. Results: The results of the study revealed several notable findings. Significant differences were observed between the PCAD and NPCAD groups in terms of age and age at AS onset (P < .05). Specifically, patients in the PCAD group had a younger mean age at AS onset compared to the NPCAD group (41.48±2.69 years vs 69.13±4.50 years, respectively). Additionally, the two groups exhibited statistically significant differences in several laboratory parameters. Levels of C-reactive protein (CRP) were found to be markedly higher in the PCAD group compared to the NPCAD group (P < .05). Hemoglobin levels and the prevalence of anemia also showed significant variations between the two cohorts (both P < .05). Importantly, the binary logistic regression analysis identified two key risk factors that independently influenced the incidence of PCAD in AS patients: younger age at AS onset and elevated levels of C-reactive protein. Conclusions: The key findings of this study underscore the heightened risk of premature coronary artery disease in patients with ankylosing spondylitis, particularly those with a younger age of AS onset and elevated levels of systemic inflammation as marked by C-reactive protein. These results have important clinical implications. Identifying AS patients at increased risk for PCAD, based on factors such as younger disease onset and higher inflammatory burden, enables targeted screening and early intervention strategies. Comprehensive cardiovascular risk assessment and management should be an integral part of the care approach for this patient population. Early recognition of PCAD risk, followed by aggressive management of modifiable risk factors and implementation of appropriate therapeutic measures, can help mitigate the burden of premature cardiovascular complications in individuals with ankylosing spondylitis.

Development and validation of a machine learning-based model for postoperative ischemic stroke in middle-aged and elderly patients with hip or knee arthroplasty.

Postoperative ischemic stroke in middle-aged and elderly patients with hip or knee arthroplasty remains a major postoperative challenge, little is known about its incidence and risk factors. This study sought to create a nomogram for precise prediction of ischemic stroke after hip or knee arthroplasty. Discharge data of all middle-aged and elderly patients undergoing primary hip or knee arthroplasty from May 2013 to October 2020 were queried. These patients were then followed up over time to determine their risk of ischemic stroke. Clinical parameters and blood biochemical features were analyzed by the use of univariable and multivariable generalized logistic regression analysis. A nomogram to predict the risk of ischemic stroke was constructed and validated with bootstrap resampling. Eight hundred twenty-eight patients were included for analysis; Fifty-one were diagnosed with ischemic stroke. After final regression analysis, age, the neutrophil-to-lymphocyte ratio (NLR), a standard deviation of red blood cell distribution width, American Society of Anesthesiologists, low-density lipoprotein, and diabetes were identified and were entered into the nomogram. The nomogram showed an area under the receiver operating characteristic curve of 0. 841 (95% confidence interval [CI], 0.809-0.871). The calibration curves for the probability of ischemic stroke showed optimal agreement between the probability as predicted by the nomogram and the actual probability (Hosmer-Lemeshow test: P = .818). We developed a practical nomogram that can predict the risk of ischemic stroke for middle-aged and elderly patients with hip or knee arthroplasty. This model has the potential to assist clinicians in making treatment recommendations.

[Expression of glycerol dehydrogenase gene in Escherichia coli by codon optimization].

OBJECTIVE: To improve expression level of glycerol dehydrogenase gene gldA in Escherichia coli by means of codon optimization. METHODS: For immediately downstream region of initiation codon in gldA, we designed optimized sequence by choosing higher AT-content synonymous, in order that this region's AT-content was increased without changing the corresponding amino acids. Then we had wild gene gldA-WT site-directed mutagenesis depending on mega-primers PCR, so that physically optimized gene gldA-4 was acquired. We cloned gldA-4 into pET-32a(+) to construct expression plasmid pET-gldA4, which was transformed into Escherichia coli BL21 (DE3) for gaining engineering bacteria E. coli-4, by contrast engineering bacteria involved gldA-WT named E. coli-WT. After E. coli-4 and E. coli-WT were fermented in shake flasks,we measured enzyme activities of expression products with glycerol as substrate. RESULTS: Four gldA-4's bases in the second, fifth and sixth codon were different with gldA-WT, so AT-content of the optimized gene was up to 80.0% higher than the wild gene's 53.3%. Furthermore, enzyme activity of E. coli-4's crude extract was 191.3 U/mL more three times than E. coli-WT's 48.3 U/mL. CONCLUSION: This optimization scheme was quick and easy, but indeed increased dehydrogenase's activity. It possible becomes a universal method to improve heterogenous expression level of target genes.