Background Ageing traits and frailty are important health issues in modern medicine. Evidence supporting the causal effects of tobacco smoking on various ageing traits is required. Methods This study performed Mendelian randomization (MR) analysis instrumenting 377 genetic variants associated with being an ever‐smoker at a genome‐wide significance level to test the causal estimates from tobacco smoking. The outcome data were obtained from 337 138 white British ancestry participants from the UK Biobank. Leucocyte telomere length, appendicular lean mass index, subjective walking pace, handgrip strength, and wristband accelerometry‐determined physical activity degree were collected as ageing‐related outcomes. Summary‐level MR analysis was performed using the inverse variance‐weighted method and pleiotropy‐robust MR methods, including weighted median and MR‐Egger. Observational association between the outcome traits and phenotypically being an ever‐smoker was also investigated. Results Summary‐level MR analysis indicated that a higher genetic predisposition for tobacco smoking was significantly associated with shorter leucocyte telomere length (twofold increase in prevalence of smoking towards standardized Z‐score, −0.041 [−0.054, −0.028]), lower appendicular lean mass index (−0.007 [−0.010, −0.005]), slower walking pace (ordinal category, −0.047 [−0.054, −0.033]) and lower time spent on moderate‐to‐vigorous physical activity (hours per week, −0.39 [−0.56, −0.23]). The causal estimates were non‐significant towards handgrip strength phenotype (kg, 0.074 [−0.055, 0.204]). Pleiotropy‐robust MR results generally supported the main causal estimates. The observational findings also showed significant association between being an ever‐smoker and the ageing traits. Conclusions Genetically predicted and observational tobacco smoking status are significantly associated with poor ageing phenotypes. Healthcare providers may continue to reduce tobacco use, which may be helpful in reducing the burden of ageing and frailty.

Thermoplastic polyurethanes (TPUs) with different hard segment length has been prepared from a fixed molar ratio of poly(tetramethylene ether glycol), 4,4'-diphenylmethane diisocyanate, and 1,4-butanediol by different polymerization procedures. Results reveal that the on-set temperature of exotherms (T cc ) due to the crystallization of hard segments by cooling the TPUs from melt and the peak temperature of endotherms due to the melting of hard segments (T mh ) by heating the TPUs increased and levelled off with increasing the hard segment length of TPUs. It has also been observed that soft segment glass transition temperature (T gs ) of TPU decreased slightly with increasing the hard segment length, which explains less mixing of soft segments and hard segments. In tensile measurement of TPUs, strain hardening is observed with increasing the hard segment length, which is attributed to the strain induced crystallization of soft segments.

Interleukins (ILs), key cytokine family of inflammatory response, are closely associated with kidney function. However, the causal effect of various ILs on kidney function needs further investigation. Here we show two-sample summary-level Mendelian randomization (MR) analysis that examined the causality between serum IL levels and kidney function. Genetic variants with strong association with serum IL levels were obtained from a previous genome-wide association study meta-analysis. Summary-level data for estimated glomerular filtration rate (eGFR) were obtained from CKDGen database. As a main MR analysis, multiplicative random-effects inverse-variance weighted method was performed. Pleiotropy-robust MR analysis, including MR-Egger with bootstrapped error and weighted median methods, were also implemented. We tested the causal estimates from nine ILs on eGFR traits. Among the results, higher genetically predicted serum IL-1 receptor antagonist level was significantly associated with higher eGFR values in the meta-analysis of CKDGen and the UK Biobank data. In addition, the result was consistent towards eGFR decline phenotype of the outcome database. Otherwise, nonsignificant association was identified between other genetically predicted ILs and eGFR outcome. These findings support the clinical importance of IL-1 receptor antagonist-associated pathway in relation to kidney function in the general individuals, particularly highlighting the importance of IL-1 receptor antagonist.

Background Hyperlactatemia occurs frequently in critically ill patients, and this pathologic condition leads to worse outcomes in several disease subsets. Herein, we addressed whether hyperlactatemia is associated with the risk of mortality in patients undergoing continuous renal replacement therapy (CRRT) due to acute kidney injury. Methods A total of 1,661 patients who underwent CRRT for severe acute kidney injury were retrospectively reviewed between 2010 and 2020. The patients were categorized according to their serum lactate levels, such as high (≥ 7.6 mmol/l), moderate (2.1–7.5 mmol/l) and low (≤ 2 mmol/l), at the time of CRRT initiation. The hazard ratios (HRs) for the risk of in-hospital mortality were calculated with adjustment of multiple variables. The increase in the area under the receiver operating characteristic curve (AUROC) for the mortality risk was evaluated after adding serum lactate levels to the Sequential Organ Failure Assessment (SOFA) and the Acute Physiology and Chronic Health Evaluation (APACHE) II score-based models. Results A total of 802 (48.3%) and 542 (32.6%) patients had moderate and high lactate levels, respectively. The moderate and high lactate groups had a higher risk of mortality than the low lactate group, with HRs of 1.64 (1.22–2.20) and 4.18 (2.99–5.85), respectively. The lactate-enhanced models had higher AUROCs than the models without lactates (0.764 vs. 0.702 for SOFA score; 0.737 vs. 0.678 for APACHE II score). Conclusions Hyperlactatemia is associated with mortality outcomes in patients undergoing CRRT for acute kidney injury. Serum lactate levels may need to be monitored in this patient subset.

Background: Since chronic kidney disease (CKD) is caused by genetic and environmental factors, biomarker development through metabolomic analysis, which reflects gene-derived downstream effects and host adaptation to the environment, is warranted. Methods: We measured the metabolites in urine samples collected from 789 patients at the time of kidney biopsy and from urine samples from 147 healthy subjects using nuclear magnetic resonance (NMR). The composite outcome was defined as a 30% decline in estimated glomerular filtration rate (eGFR), doubling of serum creatinine levels, or end-stage kidney disease. Results: Among the 28 candidate metabolites, we identified 7 metabolites showing 1) good discrimination between healthy controls and patients with stage 1 CKD and 2) a consistent change in pattern from controls to patients with advanced-stage CKD. Among the 7 metabolites, betaine, choline, glucose, fumarate, and citrate showed significant associations with the composite outcome after adjustment for age, sex, eGFR, the urine protein-creatinine ratio, and diabetes. Furthermore, adding choline, glucose, or fumarate to traditional biomarkers, including eGFR and proteinuria, significantly improved the ability of the net reclassification improvement (P<0.05) and integrated discrimination improvement (P<0.05) to predict the composite outcome. Conclusion: Urinary metabolites, including betaine, choline, fumarate, citrate, and glucose, were found to be significant predictors of the progression of CKD. As a signature of kidney injury-related metabolites, it would be warranted to monitor to predict the renal outcome.