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A ϕ570 mm alloy ingot was utilized as the electrode for vacuum arc remelting， and a ϕ660 mm vacuum arc remelting ingot was prepared through the three stages of arc initiation， stabilized melting， and thermal capping. The melting process lasted a total of 860 minutes.The distribution of inclusions in the industrial ingot of vacuum arc remelting GH4742 alloy and its characteristic positions （crown， shelf and skin） was analyzed by field emission scanning electron microscope and inclusion automatic scanning system. The results of the study showed that there were four main types of inclusions in GH4742 alloy vacuum arc remelting ingots， including Ti（C，N）， LaAlO3-Ti（C，N）， Ti（C，N）-（Ti，Nb，Mo）C， and LaAlO3-Ti（C，N）-（Ti，Nb，Mo）C. The size of inclusions was mainly dominated by small-sized inclusions less than 3 μm. From the center to the edge， the size of inclusions gradually decreased and the number density gradually increased. The largest size of inclusions was observed at the middle center of the ingot， with a maximum average size of 4.14 μm. The lowest number of inclusions was observed at the bottom center of the ingot with a number density of 13.23 N/mm2. The aggregated oxide inclusions were distributed in the ingot crown， skin and shelf， which were formed when the oxides dislodged from the electrodes move to the edges of the ingot under the action of the flow field of the molten pool and are captured by the solidified regions at the edges.

Abstract Background Observational data indicates a connection between emotional discomfort, such as anxiety and depression, and uterine fibroids (UFs). However, additional investigation is required to establish the causal relationship between them. Hence, we assessed the reciprocal causality between four psychological disorders and UFs utilizing two-sample Mendelian randomization (MR). Methods To evaluate the causal relationship between four types of psychological distress (depressive symptoms, severe depression, anxiety or panic attacks, mood swings) and UFs, bidirectional two-sample MR was employed, utilizing single nucleotide polymorphisms (SNPs) associated with these conditions. Both univariate MR (UVMR) and multivariate MR (MVMR) primarily applied inverse variance weighted (IVW) as the method for estimating potential causal effects. Complementary approaches such as MR Egger, weighted median, simple mode, and weighted mode were utilized to validate the findings. To assess the robustness of our MR results, we conducted sensitivity analyses using Cochran’s Q-test and the MR Egger intercept test. Results The results of our UVMR analysis suggest that genetic predispositions to depressive symptoms (Odds Ratio [OR] = 1.563, 95% Confidence Interval [CI] = 1.209–2.021, P = 0.001) and major depressive disorder (MDD) (OR = 1.176, 95% CI = 1.044–1.324, P = 0.007) are associated with an increased risk of UFs. Moreover, the IVW model showed a nominally significant positive correlation between mood swings (OR: 1.578; 95% CI: 1.062–2.345; P = 0.024) and UFs risk. However, our analysis did not establish a causal relationship between UFs and the four types of psychological distress. Even after adjusting for confounders like body mass index (BMI), smoking, alcohol consumption, and number of live births in the MVMR, the causal link between MDD and UFs remained significant (OR = 1.217, 95% CI = 1.039–1.425, P = 0.015). Conclusions Our study presents evidence supporting the causal relationship between genetic susceptibility to MDD and the incidence of UFs. These findings highlight the significance of addressing psychological health issues, particularly depression, in both the prevention and treatment of UFs.

Background: Multiple empirical investigations have indicated a connection between asthma and adverse pregnancy outcomes (APOs). Nevertheless, the effects of asthma on APOs remain uncertain. Methods: We performed bi-directional Univariable Mendelian randomization (UVMR) analyses using combined information obtained from genome-wide association studies (GWAS) data that is publicly accessible. The principal approach used to analyze the causal association between asthma or age when diagnosed and APOs was the inverse variance weighted (IVW) method. The two types of data regarding exposure originate from the IEU Open GWAS project, which includes 56,167 and 47,222 European asthma patients, respectively. The data of four APOs were acquired via the GWAS dataset of the FinnGen collaboration. In addition, we implemented multivariable Mendelian randomization (MVMR), controlling for confounding factors such as smoking status, frequent drinking, body mass index (BMI), and live birth quantity. Furthermore, we executed several meticulous sensitivity studies to ascertain the reliability of our MR results. Results: Following the implementation of the Bonferroni adjustment, the UVMR assessment revealed that in the IVW model, asthma was significantly linked to an elevated risk of spontaneous abortion (SA) (odds ratio [OR]: 1.115; 95 % confidence interval [CI]: 1.031–1.206; P = 0.006) and gestational diabetes mellitus (GDM) (OR: 1.125; 95 % CI: 1.037–1.220; P = 0.005). However, there was no causal correlation between asthma and preterm birth (PTB) (OR: 0.979; 95 % CI: 0.897–1.068; P = 0.629) or preeclampsia (PE) (OR: 1.059; 95 % CI: 0.951–1.179; P = 0.297). After adjusting for confounding factors, including smoking status, frequent drinking, BMI, and live birth quantity, the MVMR analysis shows a statistically significant causal relationship between asthma and SA or GDM. Furthermore, our investigation's findings did not reveal a substantial correlation between the age of asthma onset based on genetics and the likelihood of SA or GDM. The inverse MR outcomes indicate a lack of causal connection linking APOs to the incidence of asthma. The validity of these findings were verified by sensitivity analyses. Conclusions: The evidence provided by this study proves that genetically determined asthma is linked to a higher likelihood of SA and GDM. Further research is required to examine potential pathways. However, no conclusive evidence has been found to support the increased risk of SA and GDM in early asthma diagnosis or the interaction between asthma and PTB or PE, indicating that confounding factors may affect the results of previous observational studies.

BackgroundIn recent years, the prevalence of obesity has continued to increase as a global health concern. Numerous epidemiological studies have confirmed the long-term effects of exposure to ambient air pollutant particulate matter 2.5 (PM2.5) on obesity, but their relationship remains ambiguous.MethodsUtilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings.ResultsThe UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881–21.968; PFDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244–2.776; PFDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092–5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106–2.841; PFDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269–3.022; PFDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34–4.649; PFDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025–0.89; PFDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21.ConclusionOur MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.

Cytotoxicity assays are crucial for assessing the efficacy of drugs in killing cancer cells and determining their potential therapeutic value. Measurement of the effect of drug concentration, which is an influence factor on cytotoxicity, is of great importance. This paper proposes a cytotoxicity assay using microwave sensors in an end-point approach based on the detection of the number of live cells for the first time. In contrast to optical methods like fluorescent labeling, this research uses a resonator-type microwave biosensor to evaluate the effects of drug concentrations on cytotoxicity by monitoring electrical parameter changes due to varying cell densities. Initially, the feasibility of treating cells with ultrapure water for cell counting by a microwave biosensor is confirmed. Subsequently, inhibition curves generated by both the CCK-8 method and the new microwave biosensor for various drug concentrations were compared and found to be congruent. This agreement supports the potential of microwave-based methods to quantify cell growth inhibition by drug concentrations.