Corrigendum: Positive association between blood ethylene oxide levels and metabolic syndrome: NHANES 2013-2020.

[This corrects the article DOI: 10.3389/fendo.2024.1365658.].

Positive association between blood ethylene oxide levels and metabolic syndrome: NHANES 2013-2020.

Purpose: The exposure of Ethylene oxide (EO) is linked to systemic inflammatory response and various cardiovascular risk factors. Hemoglobin's binding to ethylene oxide (HbEO) was used to measure serum EO level. This research aims to explore the association between metabolic syndrome (MetS) and HbEO, and between HbEO and components of metabolic syndrome. Method: This research included 1842 participants from 2013 to 2020 in National Health and Nutrition Examination Survey (NHANES) database. Weighted logistic regression models were used to analyze the relationship between HbEO and metabolic syndrome risk, using odds ratio (OR) and 95% confidence interval (CI). The restricted cubic spline plot explores whether there is a dose-response relationship between HbEO and MetS risk. Subgroup analysis was performed to analyze study heterogeneity. Results: Significant differences were found in gender, educational level, marital status, diabetes status and hypertension among different groups (P < 0.001, P = 0.007, P = 0.003, P < 0.001, P < 0.001, respectively). The serum HbEO level exhibited positive correlation with metabolic syndrome risk in Q2 level (OR=1.64, 1.04~2.48), Q3 level (OR=1.99, 1.29~3.08), and Q4 level (OR=2.89, 1.92~4.34). The dose-response association suggested a possible linear association between serum HbEO and metabolic syndrome risk (P-overall=0.0359, P-non-linear=0.179). L-shaped association was found between HbEO and the risk of MetS in female population, obese population and mid-age and elder population (P-overall<0.001, P-non-linear=0.0024; P-overall=0.0107, P-non-linear=0.0055 P-overall<0.001 P-non-linear=0.0157). Conclusion: This study indicates a linear correlation between MetS and HbEO, with MetS risk escalating as HbEO levels increase. The prevalence of MetS varies depending on BMI, age and gender, and these factors can also influence MetS prevalence when exposed to EO.

Whole-exome sequencing combined with postoperative data identify c.1614dup (CAMKK2) as a novel candidate monogenic obesity variant.

Early-onset obesity is a rising health concern influenced by heredity. However, many monogenic obesity variants (MOVs) remain to be discovered due to differences in ethnicity and culture. Additionally, patients with known MOVs have shown limited weight loss after bariatric surgery, suggesting it can be used as a screening tool for new candidates. In this study, we performed whole-exome sequencing (WES) combined with postoperative data to detect candidate MOVs in a cohort of 62 early-onset obesity and 9 late-onset obesity patients. Our findings demonstrated that patients with early-onset obesity preferred a higher BMI and waist circumference (WC). We confirmed the efficacy of the method by identifying a mutation in known monogenic obesity gene, PCSK1, which resulted in less weight loss after surgery. 5 genes were selected for further verification, and a frameshift variant in CAMKK2 gene: NM_001270486.1, c.1614dup, (p. Gly539Argfs*3) was identified as a novel candidate MOV. This mutation influenced the improvement of metabolism after bariatric surgery. In conclusion, our data confirm the efficacy of WES combined with postoperative data in detecting novel candidate MOVs and c.1614dup (CAMKK2) might be a promising MOV, which needs further confirmation. This study enriches the human monogenic obesity mutation database and provides a scientific basis for clinically accurate diagnosis and treatment.

Mendelian randomization study supports effect of gut microflora on fractures.

To investigate the possible causal relationship between intestinal microflora and fractures using Mendelian randomization (MR). A 2-sample MR study of gut microbiota and fractures was conducted using a weighted inverse variance analysis with tests for heterogeneity, horizontal pleiotropy, and sensitivity. A causal association between fracture risk and specific bacterial taxa was identified at various taxonomic levels: 2 (Bacteroidia, P = .0304; Deltaproteobacteria P = .0304) at the class level, 3 (Bacteroidales, P = .0428; Desulfovibrionales, P = .0428; Enterobacteriales, P = .0208) at the order level, 2 (FamilyXI, P = .0304; Enterobacteriaceae P = .0332) at the family level, and 1 (Alistipes, P = .0405) at the genus level. This study revealed a causal relationship between gut microflora and fracture risk, demonstrating that the effect of different flora taxa flora abundance on fracture risk differs. It provides a reference for further studies.

Projection-Angle-Sensor-Assisted X-ray Computed Tomography for Cylindrical Lithium-Ion Batteries.

X-ray computed tomography (XCT) has become a powerful technique for studying lithium-ion batteries, allowing non-destructive 3D imaging across multiple spatial scales. Image quality is particularly important for observing the internal structure of lithium-ion batteries. During multiple rotations, the existence of cumulative errors and random errors in the rotary table leads to errors in the projection angle, affecting the imaging quality of XCT. The accuracy of the projection angle is an important factor that directly affects imaging. However, the impact of the projection angle on XCT reconstruction imaging is difficult to quantify. Therefore, the required precision of the projection angle sensor cannot be determined explicitly. In this research, we selected a common 18650 cylindrical lithium-ion battery for experiments. By setting up an XCT scanning platform and installing an angle sensor to calibrate the projection angle, we proceeded with image reconstruction after introducing various angle errors. When comparing the results, we found that projection angle errors lead to the appearance of noise and many stripe artifacts in the image. This is particularly noticeable in the form of many irregular artifacts in the image background. The overall variation and residual projection error in detection indicators can effectively reflect the trend in image quality. This research analyzed the impact of projection angle errors on imaging and improved the quality of XCT imaging by installing angle sensors on a rotary table.

Causal association of metformin and osteoporosis: A 2-sample Mendelian randomization study.

To investigate the causal relationship between metformin use and osteoporosis and different subtypes of osteoporosis using a 2-sample Mendelian randomization method. Data from genome-wide association studies were analyzed, with the exposure factor being metformin and the outcome variables being osteoporosis and different subtypes. Mendelian randomization was performed using Inverse Variance Weighted (IVW), MR-Egger, and weight median (WM) methods, and heterogeneity tests, horizontal multivariate analyses, and sensitivity analyses were performed. The IVW method analysis with metformin and osteoporosis showed P = 1.53E-04, OR (95%CI) = 1.81E-02 (2.27E-02-1.44E-01); the IVW method analysis with metformin and postmenopausal osteoporosis with pathologic fracture showed P = 2.22E-01, OR (95%CI) = 4.89E-02 (3. 83E-04-6.23E + 00); the IVW method using metformin with osteoporosis with pathological fracture showed that P = 2.14E-01, OR (95%CI) = 1.64E + 00(5.78E-02-6.44E-04); the IVW method using metformin with pharmacological osteoporosis with pathological fracture showed that P = 9. 83E- 01, OR (95%CI) = 1.11E + 00 (3.99E-05-3.11E + 04); IVW method of metformin use and pharmacological osteoporosis showed that P = 5.99E-01, OR (95%CI) = 2.27E + 01 (2.00E-04-2.57E + 06); there is a causal relationship between metformin use and osteoporosis, but there is no causal relationship between metformin use and postmenopausal osteoporosis with pathological fracture, osteoporosis with pathological fracture, pharmacological osteoporosis, and pharmacological osteoporosis with pathological fracture, and metformin use is a protective factor for osteoporosis.