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Background We aimed to explore the causal relationship between blood metabolites and the risk of visceral obesity, as measured by visceral adipose tissue (VAT). Methods Summary statistics for 486 blood metabolites and total, as well as sex-stratified, MRI-derived VAT measurements, adjusted for body mass index (BMI) and height, were collected from previous genome-wide association studies (GWAS). A two-sample Mendelian Randomization (MR) design was used. Comprehensive evaluation was further conducted, including sensitivity analysis, linkage disequilibrium score (LDSC) regression, Steiger test, and metabolic pathway analysis. Results After multiple testing correction, arachidonate (20:4n6) has been implicated in VAT accumulation (β = 0.35, 95%CI:0.18–0.52, P  < 0.001; FDR = 0.025). Additionally, several blood metabolites were identified as potentially having causal relationship (FDR < 0.10). Among them, lysine (β = 0.67, 95%CI: 0.28–1.06, P  < 0.001; FDR = 0.074), proline (β = 0.30, 95%CI:0.13–0.48, P  < 0.001; FDR = 0.082), valerate (β = 0.50, 95%CI:0.23–0.78, P  < 0.001, FDR = 0.091) are associated with an increased risk of VAT accumulation. On the other hand, glycine (β=-0.21, 95%CI: -0.33–0.09), P  < 0.001, FDR = 0.076) have a protective effect against VAT accumulation. Most blood metabolites showed consistent trends between different sexes. Multivariable MR analysis demonstrated the effect of genetically predicted arachidonate (20:4n6) and proline on VAT remained after accounting for BMI and glycated hemoglobin (HbA1c). There is no evidence of heterogeneity, pleiotropy, and reverse causality. Conclusion Our MR findings suggest that these metabolites may serve as biomarkers, as well as for future mechanistic exploration and drug target selection of visceral obesity.

The exponential growth of encrypted network traffic poses significant challenges for detecting malicious activities online. The scale of emerging malicious traffic is significantly smaller than that of normal traffic, and the imbalanced data distribution poses challenges for detection. However, most existing methods rely on single-category features for classification, which struggle to detect covert malicious traffic behaviors. In this paper, we introduce a novel semi-supervised approach to identify malicious traffic by leveraging multimodal traffic characteristics. By integrating the sequence and topological information inherent in the traffic, we achieve a multifaceted representation of encrypted traffic. We design two independent neural networks to learn the corresponding sequence and topological features from the traffic. This dual-feature extraction enhances the model’s robustness in detecting anomalies within encrypted traffic. The model is trained using a joint strategy that minimizes both the reconstruction error from the autoencoder and the classification loss, allowing it to effectively utilize limited labeled data alongside a large amount of unlabeled data. A confidence-estimation module enhances the classifier’s ability to detect unknown attacks. Finally, our method is evaluated on two benchmark datasets, UNSW-NB15 and CICIDS2017, under various scenarios, including different training set label ratios and the presence of unknown attacks. Our model outperforms other models by 3.49% and 5.69% in F1 score at labeling rates of 1% and 0.1%, respectively.

Purpose Muscle Quality Index (MQI), defined as the muscle strength per unit of muscle mass, is considered an emerging indicator of health and physical function. This study aims to explore the relationship between MQI and the risk of depression among non-elderly US adults. Methods This cross-sectional study collected data from participants aged between 20 and 59 years old, utilizing the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014. The MQI was calculated by dividing the handgrip strength (HGS, kg) by the arm and appendicular skeletal muscle mass (ASM, kg). Depression assessments were conducted using the Patient Health Questionnaire (PHQ-9). The relationship between MQI and the risk of depression was explored by weighted logistic regression, smooth curve fitting, and subgroup analyses. Results A total of 4773 participants were included in this study. After adjusting for confounding factors, low MQI levels were identified as an independent risk factor for depression (OR = 0.800, 95%CI:0.668–0.957, P  = 0.015). Smooth curve fitting analysis indicated a nonlinear relationship. Subgroup analysis did not identify any specific populations. Conclusions Higher MQI levels were closely associated with a lower risk of depression among non-elderly US adults. MQI could enhance our understanding of the link between muscle and depression and might serve as a simple functional measure for evaluating and predicting depression.

Purpose The ratio of non-high-density lipoprotein cholesterol (non-HDL-c) to high-density lipoprotein cholesterol (HDL-c) (NHHR) is a novel comprehensive lipid index. The aim of this study was to investigate the relationship between the NHHR and the prevalence of hyperuricaemia (HUA) in the adult population of the U.S. Methods This cross-sectional study collected data from the National Health and Nutrition Examination Survey (NHANES) (2007–2018). HUA was defined as a serum uric acid (SUA) concentration ≥ 7 mg/dL in men and ≥ 6 mg/dL in women. Multivariate logistic regression models and the restricted cubic spline (RCS) method were applied to examine the relationship between the NHHR and the risk of developing HUA. Subgroup analyses and interaction tests were also performed. Results The prevalence of HUA increased with increasing NHHR values (9.01% vs. 13.38% vs. 17.31% vs. 25.79%, P  < 0.001). The NHHR was independently correlated with the risk of developing HUA (OR = 1.10, 95% CI: 1.05–1.16; P  < 0.001). Furthermore, the risk of developing HUA was significantly greater among individuals with the highest NHHR quartile than among those with the lowest NHHR quartile (OR = 1.94, 95% CI: 1.62–2.33; P  < 0.001). This relationship was consistent across subgroups. According to the RCS analysis, an inverted U-shaped relationship existed between the NHHR and the risk of developing HUA. Conclusions The NHHR was closely associated with an increased risk of developing HUA. Further studies on the NHHR could be beneficial for preventing and treating HUA.

Purpose Remnant cholesterol (RC) is an independent risk factor for cardiovascular diseases. The objective of this study is to assess the correlation between RC levels and trouble sleeping among U.S. adults. Methods This study analyzed data from 14,617 adults enrolled in the National Health and Nutrition Examination Survey (NHANES), calculating RC by subtracting both high‐density and low‐density lipoprotein cholesterol (HDL‐c and LDL‐c) from total cholesterol (TC). Trouble sleeping was identified through self‐report history. The relationship between RC and trouble sleeping was explored through logistic regression, restricted cubic spline (RCS), and mediation analysis. Results The prevalence of trouble sleeping escalates with increasing RC levels. Adjusting for potential confounders, higher RC levels were significantly associated with an increased risk of trouble sleeping [OR (95% CI): 1.30 (1.13–1.49), p < 0.001]. A linear relationship was identified through RCS analysis. Moreover, depression was found to partially mediate the relationship between RC and trouble sleeping. Conclusions Trouble sleeping is associated with increased RC levels. The causal relationship requires additional investigation. Remnant cholesterol was positively and linearly associated with self‐reported trouble sleeping in U.S. adults, and depression partially mediated this relationship. Monitoring remnant cholesterol may help identify individuals at higher risk of sleep problems and related cardiometabolic consequences.

Purpose The Composite Dietary Antioxidant Index (CDAI) is a novel, inclusive measure for evaluating the antioxidant potential of diets. We aim to explore the link between the CDAI and abdominal aortic calcification (AAC) in U.S. adults aged ≥ 40 years. Methods This cross-sectional study collected dietary and AAC data for individuals aged ≥ 40 years from the 2013–2014 National Health and Nutrition Examination Survey (NHANES) database. The CDAI was calculated using six dietary antioxidants. AAC was evaluated using a semi-quantitative scoring system known as AAC-24, with an AAC score greater than 6 as severe AAC (SAAC). To examine the association between CDAI and AAC, including SAAC, liner/logistic regression analyses and smooth curve fitting were applied. Results A total of 2,640 participants were included in this study, and significant decreases in AAC score and SAAC prevalence were observed with ascending CDAI levels ( P  < 0.01). After adjusting for confounding factors, a clear link was established between the CDAI and both AAC score (β = -0.083, 95% CI -0.144–0.022, P  = 0.008) and SAAC (OR = 0.883, 95% CI 0.806–0.968, P  = 0.008), respectively. Further smooth curve fitting indicated a negative correlation between CDAI and both AAC score and SAAC. Conclusions Dietary antioxidant consumption, as quantified by the CDAI, shows an inverse relationship with AAC risk. Additional longitudinal and intervention studies are essential.

Background This study aimed to investigate the association between central sensitivity to thyroid hormones and all-cause mortality in euthyroid patients with chronic kidney disease (CKD). Methods ​Data on thyroid function indicators and all-cause mortality for CKD patients were extracted from the NHANES database (2007–2012). Central sensitivities to thyroid hormones were mainly evaluated by Thyroid Feedback Quantile-based Index (TFQI). The Kaplan–Meier method, Cox proportional hazards regression model and subgroup analysis were performed to explore the potential associations between thyroid hormone sensitivity and all-cause mortality. Results A total of 1303 euthyroid CKD patients were enrolled in this study. After a median follow-up of 115 months, 503 participants died. The Kaplan-Meier analysis demonstrated significant variations in survival rates among different levels of TFQI ( P  = 0.0015). Cox regression analysis showed that increased levels of TFQI were independent risk factors for all-cause mortality after adjusting for multiple confounding factors (HR = 1.40, 95% CI 1.10–1.79, P  = 0.007). Subgroup analysis did not reveal any significant variation in the association between TFQI and all-cause mortality between the subgroups assessed ( P for interaction > 0.05). Conclusion Our study suggests that impaired thyroid hormone sensitivity might be linked to increased mortality in euthyroid CKD patients. Further research is needed to confirm and explore this association.

N1-methyladenosine (m1A) RNA methylation is critical for regulating mRNA translation; however, its role in the development, progression, and immunotherapy response of head and neck squamous cell carcinoma (HNSCC) remains largely unknown. Using Tgfbr1 and Pten conditional knockout (2cKO) mice, we found the neoplastic transformation of oral mucosa was accompanied by increased m1A modification levels. Analysis of m1A-associated genes identified TRMT61A as a key m1A writer linked to cancer progression and poor prognosis. Mechanistically, TRMT61A-mediated tRNA-m1A modification promotes MYC protein synthesis, upregulating programmed death-ligand 1 (PD-L1) expression. Moreover, m1A modification levels were also elevated in tumors treated with oncolytic herpes simplex virus (oHSV), contributing to reactive PD-L1 upregulation. Therapeutic m1A inhibition sustained oHSV-induced antitumor immunity and reduced tumor growth, representing a promising strategy to alleviate resistance. These findings indicate that m1A inhibition can prevent immune escape after oHSV therapy by reducing PD-L1 expression, providing a mutually reinforcing combination immunotherapy approach.

With the increasing global requirements for environmental protection, refrigerants with ODP of 0 and low GWP are widely concerned and applied. In this paper, the CFD numerical method simulates the R134a centrifugal compressor directly replaced by R1234yf and R1234ze(E). The results show that at the same compressor rotational speed, using R1234yf to replace R134a directly can obtain a higher cooling capacity, but it reduces COP by about 12.5%; using R1234ze(E) to replace R134a directly reduces the cooling capacity under partial working conditions, the COP is reduced by about 7.0%. When the evaporation temperature, condensation temperature, and cooling capacity are the same, compared with the R134a unit, the COP of the R1234ze(E) unit is reduced by about 5.14%, and it is reduced by about 8.93% for the R1234yf unit. For the R134a centrifugal chiller, the drop-in replacement of R134a with R1234ze(E) can obtain better system performance compared with R1234yf.

Plasma cell mastitis (PCM) is a nonbacterial breast inflammation with severe and intense clinical manifestation, yet treatment methods for PCM are still rather limited. Although the mechanism of PCM remains unclear, mounting evidence suggests that the dysregulation of immune system is closely associated with the pathogenesis of PCM. Drug combinations or combination therapy could exert improved efficacy and reduced toxicity by hitting multiple discrete cellular targets. We have developed a knowledge graph architecture toward immunotherapy and systematic immunity that consists of herbal drug-target interactions with a novel scoring system to select drug combinations based on target-hitting rates and phenotype relativeness. To this end, we employed this knowledge graph to identify an herbal drug combination for PCM and we subsequently evaluated the efficacy of the herbal drug combination in clinical trial. Our clinical data suggests that the herbal drug combination could significantly reduce the serum level of various inflammatory cytokines, downregulate serum IgA and IgG level, reduce the recurrence rate, and reverse the clinical symptoms of PCM patients with improvements in general health status. In summary, we reported that an herbal drug combination identified by knowledge graph can alleviate the clinical symptoms of PCM patients. We demonstrated that the herbal drug combination holds great promise as an effective remedy for PCM, acting through the regulation of immunoinflammatory pathways and improvement of systematic immune level. In particular, the herbal drug combination could significantly reduce the recurrence rate of PCM, a major obstacle to PCM treatment. Our data suggests that the herbal drug combination is expected to feature prominently in future PCM treatment. C. Liu's lab was supported by grants from the Public Health Science and Technology Project of Shenyang (grant: 22-321-32-18); Y. Yang's laboratory was supported by the National Natural Science Foundation of China (grant: 81874301), the Fundamental Research Funds for Central University (grant: DUT22YG122), and the Key Research project of 'be Recruited and be in Command' in Liaoning Province (2021JH1/10400050). NCT05530226.