New predictive models and indices for screening MAFLD in school-aged overweight/obese children.

Currently, most predictions of metabolic-associated fatty liver disease (MAFLD) in school-aged children utilize indicators that usually predict nonalcoholic fatty liver disease (NAFLD). The present study aimed to develop new predictive models and predictors for children with MAFLD, which could enhance the feasibility of MAFLD screening programs in the future. A total of 331 school-aged overweight/obese children were recruited from six primary schools in Ningbo city, China. Hepatic steatosis and fibrosis were detected with controlled attenuation parameter (CAP) and liver stiffness measurement (LSM), respectively. Machine learning methods were adapted to build a set of variables to predict MAFLD in children. Then, the area under the curve (AUC) of multiple models and indices was compared to predict pediatric MAFLD. Compared with non-MAFLD children, children with MAFLD had more obvious metabolic disturbances, as they had higher anthropometric indicators, alanine aminotransferase, fasting plasma glucose, and inflammation indicators (white blood cell count, hemoglobin, neutrophil count) (all P < 0.05). The optimal variables for all subjects selected by random forest (RF) were alanine aminotransferase, uric acid, insulin, and BMI. The logistic regression (LR) model performed best, with AUC values of 0.758 for males and 0.642 for females in predicting MAFLD. LnAI-BMI, LnAI, and LnAL-WHtR were approving indices for predicting pediatric MAFLD in all participants, boys and girls individually. CONCLUSIONS: This study developed LR models and sex-specific indices for predicting MAFLD in overweight/obese children that may be useful for widespread screening and identification of children at high risk of MAFLD for early treatment. WHAT IS KNOWN: • Most of the indicators predicting pediatric MAFLD are derived from the predictive indicators for NAFLD, but the diagnostic criteria for MAFLD and NAFLD are not exactly the same. • The accuracy of predictors based on routine physical examination and blood biochemical indicators to diagnose MAFLD is limited. WHAT IS NEW: • This study developed indicators based on routine examination parameters that have approving performance for MAFLD, with AUC values exceeding 0.70.

The effects of quercetin on immunity, antioxidant indices, and disease resistance in zebrafish (Danio rerio).

The main purpose of this study was to evaluate the immunity, antioxidant indices, and disease resistance of quercetin in zebrafish (Danio rerio). A total of 630 fish were assigned to 21 tanks with 30 fish/tank, and they were exposed to 0, 0.01, 0.1, 1, 10, 100, and 1000 µg/L quercetin, respectively, for 56 days. Results indicated that the immune indices including acid phosphatase (ACP), myeloperoxidase (MPO), lysozyme activities, and Complement 3 (C3), C4, IgM contents were significantly higher in 1 µg/L quercetin group than these parameters in the control group (P < 0.05). TNF-α and IL-8 mRNA expressions significantly decreased as the levels of quercetin increased up to 1 µg/L and increased thereafter (P < 0.05). 1 and 10 µg/L quercetin groups showed significantly lower TNF-α and IL-8 mRNA levels than the quercetin-free group. Transforming growth factor-ß and IL-10 mRNA levels showed an obviously opposite trend with TNF-α expression. The SOD, GPX, CAT, T-AOC activities, and SOD and GPX gene expression in the liver were enhanced with increasing quercetin up to 1 µg/L, and decreased thereafter. MDA contents were affected by quercetin, in which 1 and 10 µg/L quercetin had a significantly lower level than that of the control group (P < 0.05). Defensin and Leap-II mRNA expression in the liver were the highest for fish exposed to 1 µg/L quercetin. The fish that exposed to 1 µg/L quercetin also showed a significantly higher survival rate than these of fish exposed to 0, 0.01, and 1000 µg/L quercetin (P < 0.05). In conclusion, the optimal level of quercetin promotes immunostimulant properties, antioxidant indices, and disease resistance of zebrafish.

[Effects of wearing a mask on oxygenation of subjects with spontaneous breathing during supplementary oxygen through facemask].

During the COVID-19 epidemic, our national guidelines have suggested that surgical patients should wear a mask to decrease the potential transmission of COVID-19 in the operating room, as long as the condition allows. However, so far, there is no study to discuss the influence of wearing a mask on the ventilation and blood oxygenation status in patients of spontaneous breathing with supplementary oxygen through an anesthetic facemask. This is a before-after study in the same patient, and 10 healthy volunteers were recruited, by testing the arterial blood gas parameters at key time points before and after oxygen inhalation to evaluate the effects of two different supplementary oxygen methods ('disposable medical mask + anesthetic facemask' and 'anesthetic facemask only') on the oxygenation of subjects. Our data demonstrated whether wearing a disposable medical mask or not could effectively increase the oxygen supply of the subjects compared with the basic value before oxygen inhalation; however, compared with the group without mask, the arterial oxygen partial (PaO 2) reduced significantly at each time points when subjects wearing a disposable medical mask. There was no significant difference in other parameters, and our data showed that age growth and smoking had no significant effects on the difference of PaO 2 between the groups with and without masks. This study demonstrates effective oxygen supplementation through anesthetic facemask in subjects with spontaneous breathing who is wearing a disposable medical mask, whose pulse oxygen saturation and arterial oxygen saturation can reach 100% rapidly, and this provides a theoretical basis for the management of patients with disseminated respiratory diseases to wear masks in the operating room; however, the rate and amount of PaO 2 increase are both decreased as compared to those who is not wearing a disposable medical mask during supplementary oxygenation. Whether this difference will affect the clinical outcome needs further study.

Comparative analysis of the genomes of two field isolates of the rice blast fungus Magnaporthe oryzae.

Rice blast caused by Magnaporthe oryzae is one of the most destructive diseases of rice worldwide. The fungal pathogen is notorious for its ability to overcome host resistance. To better understand its genetic variation in nature, we sequenced the genomes of two field isolates, Y34 and P131. In comparison with the previously sequenced laboratory strain 70-15, both field isolates had a similar genome size but slightly more genes. Sequences from the field isolates were used to improve genome assembly and gene prediction of 70-15. Although the overall genome structure is similar, a number of gene families that are likely involved in plant-fungal interactions are expanded in the field isolates. Genome-wide analysis on asynonymous to synonymous nucleotide substitution rates revealed that many infection-related genes underwent diversifying selection. The field isolates also have hundreds of isolate-specific genes and a number of isolate-specific gene duplication events. Functional characterization of randomly selected isolate-specific genes revealed that they play diverse roles, some of which affect virulence. Furthermore, each genome contains thousands of loci of transposon-like elements, but less than 30% of them are conserved among different isolates, suggesting active transposition events in M. oryzae. A total of approximately 200 genes were disrupted in these three strains by transposable elements. Interestingly, transposon-like elements tend to be associated with isolate-specific or duplicated sequences. Overall, our results indicate that gain or loss of unique genes, DNA duplication, gene family expansion, and frequent translocation of transposon-like elements are important factors in genome variation of the rice blast fungus.

Deep learning models for predicting the survival of patients with hepatocellular carcinoma based on a surveillance, epidemiology, and end results (SEER) database analysis.

Hepatocellular carcinoma (HCC) is a common malignancy with poor survival and requires long-term follow-up. Hence, we collected information on patients with Primary Hepatocellular Carcinoma in the United States from the Surveillance, Epidemiology, and EndResults (SEER) database. We used this information to establish a deep learning with a multilayer neural network (the NMTLR model) for predicting the survival rate of patients with Primary Hepatocellular Carcinoma. HCC patients pathologically diagnosed between January 2011 and December 2015 in the SEER (Surveillance, Epidemiology, and End Results) database of the National Cancer Institute of the United States were selected as study subjects. We utilized two deep learning-based algorithms (DeepSurv and Neural Multi-Task Logistic Regression [NMTLR]) and a machine learning-based algorithm (Random Survival Forest [RSF]) for model training. A multivariable Cox Proportional Hazards (CoxPH) model was also constructed for comparison. The dataset was randomly divided into a training set and a test set in a 7:3 ratio. The training dataset underwent hyperparameter tuning through 1000 iterations of random search and fivefold cross-validation. Model performance was assessed using the concordance index (C-index), Brier score, and Integrated Brier Score (IBS). The accuracy of predicting 1-year, 3-year, and 5-year survival rates was evaluated using Receiver Operating Characteristic (ROC) curves, calibration plots, and Area Under the Curve (AUC). The primary outcomes were the 1-year, 3-year, and 5-year overall survival rates. Models were developed using DeepSurv, NMTLR, RSF, and Cox Proportional Hazards regression. Model differentiation was evaluated using the C-index, calibration with concordance plots, and risk stratification capability with the log-rank test. The study included 2197 HCC patients, randomly divided into a training cohort (70%, n = 1537) and a testing cohort (30%, n = 660). Clinical characteristics between the two cohorts showed no significant statistical difference (p > 0.05). The deep learning models outperformed both RSF and CoxPH models, with C-indices of 0.735 (NMTLR) and 0.731 (DeepSurv) in the test dataset. The NMTLR model demonstrated enhanced accuracy and well-calibrated survival estimates, achieving an Area Under the Curve (AUC) of 0.824 for 1-year survival predictions, 0.813 for 3-year, and 0.803 for 5-year survival rates. This model's superior calibration and discriminative ability enhance its utility for clinical prognostication in Primary Hepatocellular Carcinoma. We deployed the NMTLR model as a web application for clinical practice. The NMTLR model have potential advantages over traditional linear models in prognostic assessment and treatment recommendations. This novel analytical approach may provide reliable information on individual survival and treatment recommendations for patients with primary liver cancer.

Lifestyle intervention in children with obesity and nonalcoholic fatty liver disease (NAFLD): study protocol for a randomized controlled trial in Ningbo city (the SCIENT study).

BACKGROUND: The increasing prevalence of childhood obesity has become an urgent public health problem, evidence showed that intervention for childhood obesity bring enormous health benefits. However, an effective individualized intervention strategy remains to be developed, and the accompanying remission of related complications, such as nonalcoholic fatty liver disease (NAFLD), needs to be assessed. This study aimed to develop an m-Health-assisted lifestyle intervention program targeting overweight/obese children and assess its effectiveness on indicators of adiposity and NAFLD. METHODS: This is a cluster-randomized controlled trial that conducted in children with overweight/obesity in Ningbo city, Zhejiang Province, China. Students in Grade 3 (8-10 years old) were recruited from six primary schools, with three be randomized to intervention group and three to usual practice group. The intervention program will last for one academic year and consists of health education, dietary guidance, and physical activity reinforcement. This program is characterized by encouraging four stakeholders, including School, Clinic, famIly, and studENT (SCIENT), to participate in controlling childhood obesity, assisted by m-Health technology. Assessments will be conducted at baseline and 3 months, 9 months, 24 months, and 36 months after baseline. The primary outcome will be the differences between the two groups in students' body mass index and fatty liver index at the end of the intervention (9 months after baseline). During the implementation process, quality control methods will be adopted. DISCUSSION: The program will test the effectiveness of the m-Health-assisted lifestyle intervention on children with obesity and NAFLD. The results of this study will provide evidence for establishing effective lifestyle intervention strategy aimed at childhood obesity and NAFLD and may help develop guidelines for the treatment of obesity and NAFLD in Chinese children. TRIAL REGISTRATION: Clinicaltrials.gov NCT05482191. Registered on July 2022.

Establish a noninvasive model to screen metabolic dysfunction-associated steatotic liver disease in children aged 6-14 years in China and its applications in high-obesity-risk countries and regions.

Background: The prevalence of metabolic-associated steatotic liver disease (MASLD) is rising precipitously among children, particularly in regions or countries burdened with high prevalence of obesity. However, identifying those at high risk remains a significant challenge, as the majority do not exhibit distinct symptoms of MASLD. There is an urgent need for a widely accepted non-invasive predictor to facilitate early disease diagnosis and management of the disease. Our study aims to 1) evaluate and compare existing predictors of MASLD, and 2) develop a practical screening strategy for children, tailored to local prevalence of obesity. Methods: We utilized a school-based cross-sectional survey in Beijing as the training dataset to establish predictive models for screening MASLD in children. An independent school-based study in Ningbo was used to validate the models. We selected the optimal non-invasive MASLD predictor by comparing logistic regression model, random forest model, decision tree model, and support vector machine model using both the Beijing and Ningbo datasets. This was followed by serial testing using the best performance index we identified and indices from previous studies. Finally, we calculated the potential MASLD screening recommendation categories and corresponding profits based on national and subnational obesity prevalence, and applied those three categories to 200 countries according to their obesity prevalence from 1990 to 2022. Findings: A total of 1018 children were included (NBeijing = 596, NNingbo = 422). The logistic regression model demonstrated the best performance, identifying the waist-to-height ratio (WHtR, cutoff value ≥0.48) as the optimal noninvasive index for predicting MASLD, with strong performance in both training and validation set. Additionally, the combination of WHtR and lipid accumulation product (LAP) was selected as an optimal serial test to improve the positive predictive value, with a LAP cutoff value of ≥668.22 cm × mg/dL. Based on the obesity prevalence among 30 provinces, three MASLD screening recommendations were proposed: 1) "Population-screening-recommended": For regions with an obesity prevalence ≥12.0%, where MASLD prevalence ranged from 5.0% to 21.5%; 2) "Resources-permitted": For regions with an obesity prevalence between 8.4% and 12.0%, where MASLD prevalence ranged from 2.3% to 4.4%; 3) "Population-screening-not-recommended": For regions with an obesity prevalence <8.4%, where MASLD prevalence is difficult to detect using our tool. Using our proposed cutoff for screening MASLD, the number of countries classified into the "Population-screening-recommended" and "Resources-permitted" categories increased from one and 11 in 1990 to 95 and 28 in 2022, respectively. Interpretation: WHtR might serve as a practical and accessible index for predicting pediatric MASLD. A WHtR value ≥0.48 could facilitate early identification and management of MASLD in areas with obesity prevalence ≥12.0%. Furthermore, combining WHtR ≥0.48 with LAP ≥668.22 cm × mg/dL is recommended for individual MASLD screening. Moreover, linking these measures with population obesity prevalence not only helps estimate MASLD prevalence but also indicates potential screening profits in regions at varying levels of obesity risk. Funding: This study was supported by grants from Capital's Funds for Health Improvement and Research (Grant No. 2022-1G-4251), National Natural Science Foundation of China (Grant No. 82273654), Major Science and Technology Projects for Health of Zhejiang Province (Grant No. WKJ-ZJ-2216), Cyrus Tang Foundation for Young Scholar 2022 (2022-B126) and Sino-German Mobility Programme (M-0015).

Comparison of MAFLD and NAFLD Characteristics in Children.

BACKGROUND & AIMS: An international panel proposed a diagnostic framework for metabolic-associated fatty liver disease (MAFLD) in children. The aim was to compare the clinical features of MAFLD and nonalcoholic fatty liver disease (NAFLD) in children. METHODS: The characteristic differences between NAFLD and MAFLD in children were compared with the National Health and Nutrition Examination Survey (NHANES) 2017-2018 in the U.S. and the Comprehensive Prevention Project for Overweight and Obese Adolescents (CPOOA) study in China. RESULTS: In NHANES 2017-2018, regardless of which criteria were implemented, participants with hepatic steatosis were more likely to have higher BMI z-scores, a higher prevalence of hypertension or higher metabolic indices and higher non-invasive liver fibrosis scores (all p < 0.05). The cases diagnosed by those two definitions had a similarity of over 75%. More obese children were diagnosed with MAFLD than NAFLD (p < 0.001). However, approximately 19% of children with NAFLD present with normal weight and fasting glucose levels and cannot be diagnosed with MAFLD. The CPOOA study excluded viral infected liver disease and certain kinds of congenital causes of liver steatosis patients, resulting in children with NAFLD being identical with MAFLD children. CONCLUSIONS: Most clinical features were similar between children with MAFLD and children with NAFLD, and more than 75% of children with NAFLD can also be diagnosed with MAFLD. However, approximately 19% of children with NAFLD cannot be categorized as MAFLD. Therefore, to gain greater benefits from renaming NAFLD to MAFLD in pediatrics, the prevalence of different causes of hepatic steatosis in children needs to be understood.

Associations between exposure to ambient particulate matter and advanced liver fibrosis in Chinese MAFLD patients.

BACKGROUND & AIMS: Liver fibrosis is an important feature in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). This study aimed to explore the association between long-term ambient particulate matter (PM) exposure and advanced liver fibrosis (ALF) in MAFLD participants. METHODS: A cross-sectional study of 23170 adults recruited from 33 provinces of China from 2010 to 2020. ALF was detected using the nonalcoholic fatty liver disease fibrosis score (NFS). The annual average levels of particulate matter with aerodynamic diameters of ≤ 1 µm (PM1), ≤ 2.5 µm (PM2.5) and ≤ 10 µm (PM10) were calculated using validated spatiotemporal models. Generalized additive models were applied to analyze the association between PM and ALF in patients with MAFLD. RESULTS: One-year exposure to higher levels of all PM was found to increase the risk of ALF, with odds ratios (ORs) of 1.10 (95% CI 1.06-1.14), 1.05 (1.03-1.07), and 1.03(1.02-1.04) for each 10 µg/m3 increase in PM1, PM2.5 and PM10, respectively. With the dissection of the impact of PM1 in PM2.5, PM2.5 in PM10 and PM1 in PM10, we found that PM2.5 had a stronger impact on ALF (both Pinteraction＜0.05) in comparison with PM1 and PM10. CONCLUSIONS: Long-term exposure to PM is associated with ALF in patients with MAFLD, with PM2.5 playing a dominant role.

The influence of adjunctive traditional Chinese medicine therapy on survival in primary liver cancer: a real-world study based on electronic medical records.

Background: Traditional Chinese medicine (TCM) effectively improves the survival rate and quality of life of primary liver cancer patients, but high-level evidence is lacking. Patients and methods: Patients were selected from 5 tertiary hospitals in Henan Province, China. Two thousand sixty-seven patients with primary liver cancer were included in the study. The electronic medical records (EMRs) of the patients were collected. Patients who received adjunctive TCM treatment and underwent treatment cumulative time for more than 1 month were classified as the TCM intervention cohort. Patients who did not receive adjunctive TCM treatment or underwent treatment cumulative time for less than 1 month were classified as the non-TCM intervention cohort. The main outcome indicators were the survival rate and overall survival time. The propensity score inverse probability weighting method was used to balance the differences between the groups. Results: The primary cohort comprised 2,067 patients, including 462 patients who received adjunctive TCM treatment and 1,605 patients who did not receive adjunctive TCM treatment. The results of the Kaplan‒Meier survival curve indicated that the survival rate and median survival time of the exposure group before and after propensity score weighting were greater than those of the control group (p < 0.0001). Univariate Cox regression analysis after propensity score weighting showed that adjunctive TCM treatment was an independent protective factor for survival [regression coefficient = -0.215, hazard ratio (HR) = 0.8066, 95% confidence interval (CI) (0.6609-0.9844)]. Conclusion: Adjuvant treatment with TCM has a protective effect on the prognosis of patients with primary liver cancer; it can reduce the mortality and prolong the survival time.

Thermal-inert and ohmic-contact interface for high performance half-Heusler based thermoelectric generator.

Unsatisfied electrode bonding in half-Heusler devices renders thermal damage and large efficiency loss, which limits their practical service at high temperatures. Here, we develop a thermodynamic strategy to screen barrier layer elements. Theoretically, we found that the interface between VIIB elements and half-Heuslers possesses near-zero interfacial reaction energy and large atomic diffusion barrier. Experimentally, such an interphase proves to be the atomic direct bonding and has high thermal stability at 1073 K, leading to ideal ohmic contact. Such thermally inert and ohmic contact interface enable modules stably to work at elevated temperature up to 1100 K, which releases the peak performance of half-Heuslers and in turn boosts the energy conversion efficiencies to the records of 11.1% and 13.3% for half-Heusler single-stage and half-Heusler/Bi2Te3 segmented modules. This design strategy provides a feasible solution for the high-temperature half-Heusler generators and gives enlightenment for other package interconnection design of electronic devices.

Low Temperature Joining and High Temperature Application of Segmented Half Heusler/Skutterudite Thermoelectric Joints.

A low temperature joining process has been developed to fabricate segmented half Heusler/skutterudite thermoelectric joints, and high temperature service behavior of the joints has been studied. The microstructure and electrical resistance across the joint before and after aging were investigated. The joint is well bonded and no cracks appear at the interfaces of the joint before and after aging, which can attribute to the formation of high melting point intermetallic compounds. The electrical resistance crosses the bonding layer smoothly and the contact resistance is low. These results show the process is effective, and promising for preparation of segmented thermoelectric devices.

Peroxisomal fission is induced during appressorium formation and is required for full virulence of the rice blast fungus.

Peroxisomes are involved in various metabolic processes and are important for virulence in different pathogenic fungi. How peroxisomes rapidly emerge in the appressorium during fungal infection is poorly understood. Here, we describe a gene, PEF1, which can regulate peroxisome formation in the appressorium by controlling peroxisomal fission, and is required for plant infection in the rice blast fungus Magnaporthe oryzae. Targeted deletion of PEF1 resulted in a reduction in virulence and a delay in penetration and invasive growth in host cells. PEF1 was particularly expressed during appressorial development, and its encoding protein was co-localized with peroxisomes during appressorial development. Compared with the massive vesicle-shaped peroxisomes formed in the wild-type appressorium, the Δpef1 mutant could only form stringy linked immature peroxisomes, suggesting that PEF1 was involved in peroxisomal fission during appressorium formation. We also found that the Δpef1 mutant could not utilize fatty acids efficiently, which can improve significantly the expression level of PEF1 and induce peroxisomal fission. As expected, the Δpef1 mutant showed reduced intracellular production of reactive oxygen species (ROS) during appressorium formation and induced ROS accumulation in host cells during infection. Taken together, PEF1-mediated peroxisomal fission is important for fungal infection by controlling the number of peroxisomes in the appressorium.