Prevalence and risk factors of sarcopenia in idiopathic pulmonary fibrosis: a systematic review and meta-analysis

BackgroundSarcopenia often occurs as a comorbidity in many diseases which ultimately affects patient prognosis. However, it has received little attention in patients with idiopathic pulmonary fibrosis (IPF). This systematic review and meta-analysis aimed at determining the prevalence and risk factors of sarcopenia in patients with IPF.MethodsEmbase, MEDLINE, Web of Science, and Cochrane databases were searched using relevant MeSH terms until December 31, 2022. The Newcastle-Ottawa Scale (NOS) was used for quality assessment and data analysis were performed using Stata MP 17.0 (Texas, USA). A random effects model was adopted to account for differences between articles, and the I2 statistic was used to describe statistical heterogeneities. Overall pooled estimates obtained from a random effects model were estimated using the metan command. Forest plots were generated to graphically represent the data of the meta-analysis. Meta-regression analysis was used for count or continuous variables. Egger test was used to evaluate publication bias and, if publication bias was observed, the trim and fill method was used.Main resultsThe search results showed 154 studies, and five studies (three cross-section and two cohort studies) with 477 participants were finally included. No significant heterogeneity was observed among studies included in the meta-analysis (I2 = 16.00%) and our study's publication bias is low (Egger test, p = 0.266). The prevalence of sarcopenia in patients with IPF was 26% (95% CI, 0.22–0.31). The risk factors for sarcopenia in patients with IPF were age (p = 0.0131), BMI (p = 0.001), FVC% (p < 0.001), FEV1% (p = 0.006), DLco% (p ≤ 0.001), and GAP score (p = 0.003).ConclusionsThe pooled prevalence of sarcopenia in patients with IPF was 26%. The risk factors for sarcopenia in IPF patients were age, BMI, FVC%, FEV1%, DLco%, and GAP score. It is important to identify these risk factors as early as possible to improve the life quality of patients with IPF

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

A BWM-TOPSIS Hazardous Waste Inventory Safety Risk Evaluation

Hazardous waste can cause severe environmental pollution if not disposed of properly, which in turn can seriously affect the sustainable development of the entire ecology and will inevitably bring disaster to companies. However, because of limited available disposal capacity, it is often difficult to safely dispose of hazardous waste, meaning that it must be kept as passive inventory. For the passive inventory of hazardous waste, risk evaluation of safe operation of the inventory is crucial and urgently needs to be resolved. Based on this, this paper focuses on the risk management of hazardous waste inventory of waste-producing companies and proposes a risk evaluation system for safely dealing with hazardous waste inventory, which expands the scope of inventory safety management and provides guidance to companies on developing appropriate measures to ensure hazardous waste inventory safety. First, the risk evaluation index system for hazardous waste inventory is constructed from equipment, management level, nature of hazardous waste and operational aspects. Then, the best worst method (BWM) is employed to calculate the criteria weights and the technique for order performance by similarity to ideal solution (TOPSIS) is employed to rank the alternatives. Finally, risk evaluation on four waste-producing companies was conducted using the developed method. The results show that Case Company 4 has the greatest risk of hazardous waste inventory, which should be reduced by improving storage method and the amount of hazardous waste. It was found that the proposed evaluation system was effective for hazardous waste inventory safety risk assessments and that the designed index system could assist companies improve their hazardous waste inventory management

Broadband spatial self-phase modulation and ultrafast response of MXene Ti3C2Tx (T=O, OH or F)

Two-dimensional layered materials (2DLM) have become the subject of intensive research in various applications such as electronics, photonics and optoelectronics due to their unique physical properties. As a new class of 2DLM, MXenes have attracted great interest due to their superior performance in a wide variety of applications such as batteries, supercapacitors, catalysts, electronics and optics. Here, we have investigated the broadband spatial self-phase modulation (SSPM) and ultrafast response of the MXene Ti3C2Tx (T=O, OH or F) experimentally. The MXene Ti3C2Tx exhibited the broadband nonlinear optical response via SSPM from 400 nm to ~1 μm under the ultrafast laser excitation, and ultrafast carrier characteristics with an ultrafast recovery time with femtosecond transient absorption spectroscopy. The experimental results have shown that the MXenes have the broadband nonlinear optical response, which can lay a foundation for the application prospect for the MXene-based ultrafast optoelectronic devices

Glycyl‐l‐histidyl‐l‐lysine‐Cu2+ rescues cigarette smoking‐induced skeletal muscle dysfunction via a sirtuin 1‐dependent pathway

Abstract Background Skeletal muscle dysfunction is an important co‐morbidity in patients with chronic obstructive pulmonary disease (COPD) and is significantly associated with increased mortality. Oxidative stress has been demonstrated an important trigger for COPD‐related skeletal muscle dysfunction. Glycine‐histidine‐lysine (GHK) is an active tripeptide, which is a normal component of human plasma, saliva, and urine; promotes tissue regeneration; and acts as an anti‐inflammatory and antioxidant properties. The purpose of this study was to determine whether GHK is involved in COPD‐related skeletal muscle dysfunction. Methods The plasma GHK level in patients with COPD (n = 9) and age‐paired healthy subjects (n = 11) were detected using reversed‐phase high‐performance liquid chromatography. The complex GHK with Cu (GHK‐Cu) was used in in vitro (C2C12 myotubes) and in vivo experiments (cigarette smoking [CS]‐exposure mouse model) to explore the involvement of GHK in CS‐induced skeletal muscle dysfunction. Results Compared with healthy control, plasma GHK levels were decreased in patients with COPD (70.27 ± 38.87 ng/mL vs. 133.0 ± 54.54 ng/mL, P = 0.009). And plasma GHK levels in patients with COPD were associated with pectoralis muscle area (R = 0.684, P = 0.042), inflammatory factor TNF‐α (R = −0.696, P = 0.037), and antioxidative stress factor SOD2 (R = 0.721, P = 0.029). GHK‐Cu was found to rescue CSE‐induced skeletal muscle dysfunction in C2C12 myotubes, as evidenced by increased expression of myosin heavy chain, reduced expression of MuRF1 and atrogin‐1, elevated mitochondrial content, and enhanced resistance to oxidative stress. In CS‐induced muscle dysfunction C57BL/6 mice, GHK‐Cu treatment (0.2 and 2 mg/kg) reduces CS‐induced muscle mass loss (skeletal muscle weight (1.19 ± 0.09% vs. 1.29 ± 0.06%, 1.40 ± 0.05%; P < 0.05) and muscle cross‐sectional area elevated (1055 ± 552.4 μm2 vs. 1797 ± 620.9 μm2, 2252 ± 534.0 μm2; P < 0.001), and also rescues CS‐induced muscle weakness, indicated by improved grip strength (175.5 ± 36.15 g vs. 257.6 ± 37.98 g, 339.1 ± 72.22 g; P < 0.01). Mechanistically, GHK‐Cu directly binds and activates SIRT1(the binding energy was −6.1 kcal/mol). Through activating SIRT1 deacetylation, GHK‐Cu inhibits FoxO3a transcriptional activity to reduce protein degradation, deacetylates Nrf2 and contribute to its action of reducing oxidative stress by generation of anti‐oxidant enzymes, increases PGC‐1α expression to promote mitochondrial function. Finally, GHK‐Cu could protect mice against CS‐induced skeletal muscle dysfunction via SIRT1. Conclusions Plasma glycyl‐l‐histidyl‐l‐lysine level in patients with chronic obstructive pulmonary disease was significantly decreased and was significantly associated with skeletal muscle mass. Exogenous administration of glycyl‐l‐histidyl‐l‐lysine‐Cu2+ could protect against cigarette smoking‐induced skeletal muscle dysfunction via sirtuin 1

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care