Whole-body magnetic resonance imaging at 0.05 Tesla.

Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.

Maternal Dietary Cholesterol and Egg Intake during Pregnancy and Large-for-Gestational-Age Infants: A Prospective Cohort Study.

BACKGROUND: Cholesterol plays a vital role in fetal growth and development during pregnancy. There remains controversy over whether pregnant females should limit their cholesterol intake. OBJECTIVES: The objective of this study was to investigate the association between maternal dietary cholesterol intake during pregnancy and infant birth weight in a Chinese prospective cohort study. METHODS: A total of 4146 mother-child pairs were included based on the Jiangsu Birth Cohort study. Maternal dietary information was assessed with a semiquantitative food-frequency questionnaire. Birth weight z-scores and large-for-gestational-age (LGA) infants were converted by the INTERGROWTH-21st neonatal weight-for-gestational-age standard. Poisson regression and generalized estimating equations were employed to examine the relationships between LGA and maternal dietary cholesterol across the entire pregnancy and trimester-specific cholesterol intake, respectively. RESULTS: The median intake of maternal total dietary cholesterol during the entire pregnancy was 671.06 mg/d, with eggs being the main source. Maternal total dietary cholesterol and egg-sourced cholesterol were associated with an increase in birth weight z-score, with per standard deviation increase in maternal total and egg-sourced dietary cholesterol being associated with an increase of 0.16 [95% confidence interval (CI): 0.07, 0.25] and 0.06 (95% CI: 0.03, 0.09) in birth weight z-score, respectively. Egg-derived cholesterol intake in the first and third trimesters was positively linked to LGA, with an adjusted relative risk of 1.11 (95% CI: 1.04, 1.18) and 1.09 (95% CI: 1.00, 1.18). Compared with mothers consuming ≤7 eggs/wk in the third trimester, the adjusted relative risk for having an LGA newborn was 1.37 (95% CI: 1.09, 1.72) for consuming 8-10 eggs/wk and 1.45 (95% CI: 1.12, 1.86) for consuming >10 eggs/wk (P-trend = 0.015). CONCLUSIONS: Maternal total dietary cholesterol intake, as well as consuming over 7 eggs/wk during pregnancy, displayed significant positive relationships with the incidence of LGA, suggesting that mothers should avoid excessive cholesterol intake during pregnancy to prevent adverse birth outcomes.

RBM3 enhances the stability of MEF2C mRNA and modulates blood-brain barrier permeability in AD microenvironment.

Blood-brain barrier (BBB) changes are acknowledged as early indicators of Alzheimer's disease (AD). The permeability and integrity of the BBB rely significantly on the essential role played by the tight junction proteins (TJPs) connecting endothelial cells. This study found the reduced RNA binding motif protein 3 (RBM3) expression in brain microvascular endothelial cells (BMECs) incubated with Aß1-42. This downregulation of RBM3 caused a decrease in the levels of ZO-1 and occludin and increased the permeability of BBB cell model in AD microenvironment. Myocyte enhancer factor 2C (MEF2C) expression was also inhibited in BMECs incubated with Aß1-42. A decrease in MEF2C expression led to increased permeability of BBB cell model in AD microenvironment and reductions in the levels of ZO-1 and occludin. Further analysis of the underlying mechanism revealed that RBM3 binds to and stabilizes MEF2C mRNA. MEF2C binds to the promoters of ZO-1 and occludin, enhancing their transcriptional activities and modulating BBB permeability. RBM3 increases the stability of MEF2C mRNA and subsequently modulates BBB permeability through the paracellular pathway of TJPs. This may provide new insights for AD research.

Transformer fault diagnosis method based on SMOTE and NGO-GBDT.

In order to improve the accuracy of transformer fault diagnosis and improve the influence of unbalanced samples on the low accuracy of model identification caused by insufficient model training, this paper proposes a transformer fault diagnosis method based on SMOTE and NGO-GBDT. Firstly, the Synthetic Minority Over-sampling Technique (SMOTE) was used to expand the minority samples. Secondly, the non-coding ratio method was used to construct multi-dimensional feature parameters, and the Light Gradient Boosting Machine (LightGBM) feature optimization strategy was introduced to screen the optimal feature subset. Finally, Northern Goshawk Optimization (NGO) algorithm was used to optimize the parameters of Gradient Boosting Decision Tree (GBDT), and then the transformer fault diagnosis was realized. The results show that the proposed method can reduce the misjudgment of minority samples. Compared with other integrated models, the proposed method has high fault identification accuracy, low misjudgment rate and stable performance.

Selective deletion of E3 ubiquitin ligase FBW7 in VE-cadherin-positive cells instigates diffuse large B-cell lymphoma in mice in vivo.

During the maturation of hematopoietic stem/progenitor cells (HSPCs) to fully differentiated mature B lymphocytes, developing lymphocytes may undergo malignant transformation and produce B-cell lymphomas. Emerging evidence shows that through the endothelial-hematopoietic transition, specialized endothelial cells called the hemogenic endothelium can differentiate into HSPCs. However, the contribution of genetic defects in hemogenic endothelial cells to B-cell lymphomagenesis has not yet been investigated. Here, we report that mice with endothelial cell-specific deletion of Fbw7 spontaneously developed diffuse large B-cell lymphoma (DLBCL) following Bcl6 accumulation. Using lineage tracing, we showed that B-cell lymphomas in Fbw7 knockout mice were hemogenic endothelium-derived. Mechanistically, we found that FBW7 directly interacted with Bcl6 and promoted its proteasomal degradation. FBW7 expression levels are inversely correlated with BCL6 expression. Additionally, pharmacological disruption of Bcl6 abolished Fbw7 deletion-induced B-cell lymphomagenesis. We conclude that selective deletion of E3 ubiquitin ligase FBW7 in VE-cadherin positive endothelial cells instigates diffuse large B-cell lymphoma via upregulation of BCL6 stability. In addition, the mice with endothelial cell-specific deletion of Fbw7 provide a valuable preclinical platform for in vivo development and evaluation of novel therapeutic interventions for the treatment of DLBCL.

Implementation and Validation of an OpenMM Plugin for the Deep Potential Representation of Potential Energy.

Machine learning potentials, particularly the deep potential (DP) model, have revolutionized molecular dynamics (MD) simulations, striking a balance between accuracy and computational efficiency. To facilitate the DP model's integration with the popular MD engine OpenMM, we have developed a versatile OpenMM plugin. This plugin supports a range of applications, from conventional MD simulations to alchemical free energy calculations and hybrid DP/MM simulations. Our extensive validation tests encompassed energy conservation in microcanonical ensemble simulations, fidelity in canonical ensemble generation, and the evaluation of the structural, transport, and thermodynamic properties of bulk water. The introduction of this plugin is expected to significantly expand the application scope of DP models within the MD simulation community, representing a major advancement in the field.

Choice Preference of Middle-Aged and Elderly People on Integrated Medical Services and Elderly Care Model: A Cross-Sectional Study.

Facing the increasingly severe aging situation, China has started to implement the "integrated medical services and elderly care (IMSEC)" policy, which covers a variety of IMSEC models. However, there is currently little research on middle-aged and elderly people's choice preference for these IMSEC models and their associated factors. Through the face-to-face questionnaire method, the choice preference of middle-aged and elderly people aged 45 years and over in Zhejiang Province, China, to the IMSEC model is explored. Through the multinomial logistic regression model, the influencing factors of choice preference are analyzed. A total of 1034 people are included in 2022. Their choice preference for the 4 major types of IMSEC models are Home IMSEC model (48.07%), Community IMSEC model (23.79%), Institutional IMSEC model (21.76%), and Internet Plus IMSEC model (6.38%). "C1. Home elderly care and contracted with a family doctor" is the most chosen subtype, accounting for 34.53%. The rural elderly are more likely to choose "Home IMSEC model" (OR(95%CI) = 2.977(1.343-6.601)). Elderly people with relatively large life care needs are more likely to choose "Institutional IMSEC model" (OR(95%CI) = 1.114(1.042-1.190)). Moreover, age, education, and self-reported health status are also influencing factors of choice preference. The government should focus on promoting the development of the "Home IMSEC model" and increase the promotion of "Internet Plus IMSEC model." In addition, the life care service capacity and spiritual comfort capacity of IMSEC institutions, as well as the medical service capacity of the community, need to be enhanced.

DP/MM: A Hybrid Model for Zinc-Protein Interactions in Molecular Dynamics.

Zinc-containing proteins are vital for many biological processes, yet accurately modeling them using classical force fields is hindered by complicated polarization and charge transfer effects. This study introduces DP/MM, a hybrid force field scheme that utilizes a deep potential model to correct the atomic forces of zinc ions and their coordinated atoms, elevating them from MM to QM levels of accuracy. Trained on the difference between MM and QM atomic forces across diverse zinc coordination groups, the DP/MM model faithfully reproduces structural characteristics of zinc coordination during simulations, such as the tetrahedral coordination of Cys4 and Cys3His1 groups. Furthermore, DP/MM allows water exchange in the zinc coordination environment. With its unique blend of accuracy, efficiency, flexibility, and transferability, DP/MM serves as a valuable tool for studying structures and dynamics of zinc-containing proteins and also represents a pioneering approach in the evolving landscape of machine learning potentials for molecular modeling.

Clinical impact of sarcopenia for overweight or obese patients with colorectal cancer.

BACKGROUND: Sarcopenia, overweight and obesity are all dynamic changes in body composition, which may have a negative effect on the prognosis for patients with colorectal cancer. The aim of this study was to investigate the predictive role of sarcopenia on overweight or obese patients with colorectal cancer. METHODS: We conducted an observative study on the population of overweight or obese patients with colorectal cancer who underwent curative surgeries in two centers between 2015 and 2021. They were grouped by the presence of sarcopenia. Propensity score match analysis was used to balance the baseline of clinicopathologic characteristics of the two groups. Then, the postoperative outcomes between the two groups were compared. Independent risk factors were evaluated for complications using univariate and multivariate analysis. RESULTS: Of 827 patients enrolled, 126 patients were matched for analysis. Patients with sarcopenia had a higher incidence of total complication and medical complications, a higher rate of laparoscopic surgery performed and higher hospitalization costs. Old age (≥65 years, P = 0.012), ASA grade (III, P = 0.008) and sarcopenia (P = 0.036) were independent risk factors for total complications. ASA grade (III, P = 0.002) and sarcopenia (P = 0.017) were independent risk factors for medical complications. CONCLUSIONS: Sarcopenia was prevalent among overweight or obese patients with colorectal cancer and was associated with negative postoperative outcomes. Early recognition of changes in body composition could help surgeons be well prepared for surgical treatment for overweight or obese patients.

Establishment and validation of novel nomograms to predict muscle quality in colorectal cancer patients.

OBJECTIVES: The skeletal muscle mass index and skeletal muscle radiodensity have promise as specific diagnostic indicators for muscle quality. However, the difficulties in measuring low skeletal muscle mass index and low skeletal muscle radiodensity limit their use in routine clinical practice, impeding early screening and diagnosis. The objective of this study is to develop a nomogram that incorporates preoperative factors for predicting low skeletal muscle mass index and low skeletal muscle radiodensity. METHODS: A total of 1692 colorectal cancer patients between 2015 and 2021 were included. The patients were randomly divided into a training cohort (n = 1353) and a validation cohort (n = 339). Nomogram models were calibrated using the area under the curve, calibration curves, and the Hosmer-Lemeshow test to assess their predictive ability. Finally, a decision curve was applied to assess the clinical usefulness. RESULTS: In a prediction model for low skeletal muscle mass index, age, body mass index, and grip strength were incorporated as variables. For low skeletal muscle radiodensity, age, sex, body mass index, serum hemoglobin level, and grip strength were included as predictors. In the training cohort, the area under the curve value for low skeletal muscle mass index was 0.750 (95% CI, 0.726-0.773), whereas for low skeletal muscle radiodensity, it was 0.763 (95% CI, 0.739-0.785). The Hosmer-Lemeshow test confirmed that both models fit well in both cohorts. Decision curve analysis was applied to assess the clinical usefulness of the model. CONCLUSIONS: The incorporation of preoperative factors into the nomogram-based prediction model represents a significant advancement in the muscle quality assessment. Its implementation has the potential to early screen patients at risk of low skeletal muscle mass index and low skeletal muscle radiodensity.

Comorbidities in congenital heart disease: different patterns in childhood and adulthood.

BACKGROUND: Existing studies were no exploration of the association between congenital heart disease (CHD) in children and comorbidities. This study was to assess the prevalence and number of comorbidities in CHD among children and adults, and to compare the comorbidity patterns by children and adults using association rule analysis. METHODS: Patients identified by the International Classification of Diseases, Ninth Revision (ICD-9) code in the Medical Information Mart for Intensive Care III (MIMIC-III) 2001-2012 and MIMIC-IV 2008-2018 were included in this cross-sectional study. Association rule analysis was used to explore associations between CHD and comorbidities in children and adults using values of support (%), confidence (%), and lift. RESULTS: Among 60,400 eligible patients, 1.54% of adults had CHD and 0.83% of adults had CHD with at least one comorbidity, 13.79% had CHD and 12.37% had CHD with at least one comorbidity in children. The most common comorbidities were circulatory system diseases (53.78%), endocrine diseases (35.76%), and respiratory system diseases (23.46%) in adults with CHD, and the most common comorbidities were perinatal diseases (87.50%) in children with CHD. The comorbidity rate was 90.19% and 56.68% in children and adults, respectively. In children, perinatal diseases, circulatory system diseases, and endocrine diseases had the highest prevalence. The incidence of circulatory system diseases, perinatal diseases and endocrine diseases in CHD adults was confidence = 31.56%, 36.11%, and 23.23%, respectively. Perinatal diseases were common comorbidities among all CHD severity groups in children and adults. CONCLUSION: The prevalence of comorbidities in children with CHD was higher than that in adults with CHD. The most common comorbidities were perinatal diseases and endocrine diseases among children and adults with CHD, respectively. Our study provided insights into comorbidity patterns in children and adults with CHD.

Development and validation of a novel food exchange system for Chinese pregnant women.

BACKGROUND: The dietary nutritional status of pregnant women is critical for maintaining the health of both mothers and infants. Food exchange systems have been employed in the nutritional guidance of patients in China, although their application in the dietary guidance of healthy pregnant women is quite limited. This study aimed to develop a novel food exchange system for Chinese pregnant women (NFES-CPW) and evaluate the relative validation of its application. METHODS: NFES-CPW covers approximately 500 types of food from ten categories and has more elaborate food portion sizes. It established a recommendation index for guiding food selection and used energy, water content, and protein as the exchange basis to balance the supply of energy and important nutrients throughout pregnancy. Furthermore, dietitians used the NFES-CPW and traditional food exchange system to generate new recipes based on the sample recipe. There were 40 derived recipes for each of the two food exchange methods. The food consumption, energy, and key nutrients of each recipe were calculated, and the differences between the two food exchange systems were compared using the Wilcoxon rank sum test or the Chi-square test. RESULTS: The results revealed that compared to those derived from traditional food exchange system, the NFES-CPW derived recipes had a better dietary structure, as evidenced by the intakes of whole-grain cereals, beans excluding soybeans, potatoes, fruits, fish, shrimp and shellfish, as well as eggs (P < 0.05), which were more conducive to reaching the recommended range of balanced dietary pagoda. After calculating energy and nutrients, although these two food exchange systems have similar effects on the dietary energy and macronutrient intake of pregnant women, the intake of micronutrients in NFES-CPW derived recipes was significantly higher than that from the traditional food exchange system, which was more conducive to meeting the dietary requirements of pregnant women. The outstanding improvement are primarily vitamin A, vitamin B2, folic acid, vitamin B12, vitamin C, calcium, iron, and iodine (P < 0.05). Moreover, when compared to recipes obtained from the traditional food exchange system, the error ranges of energy and most nutrients were significantly reduced after employing the NFES-CPW. CONCLUSIONS: Therefore, NFES-CPW is an appropriate tool that adheres to Chinese dietary characteristics and can provide suitable dietary guidance to pregnant women.

MG-SIN: Multigraph Sparse Interaction Network for Multitask Stance Detection.

Stance detection on social media aims to identify if an individual is in support of or against a specific target. Most existing stance detection approaches primarily rely on modeling the contextual semantic information in sentences and neglect to explore the pragmatics dependency information of words, thus degrading performance. Although several single-task learning methods have been proposed to capture richer semantic representation information, they still suffer from semantic sparsity problems caused by short texts on social media. This article proposes a novel multigraph sparse interaction network (MG-SIN) by using multitask learning (MTL) to identify the stances and classify the sentiment polarities of tweets simultaneously. Our basic idea is to explore the pragmatics dependency relationship between tasks at the word level by constructing two types of heterogeneous graphs, including task-specific and task-related graphs (tr-graphs), to boost the learning of task-specific representations. A graph-aware module is proposed to adaptively facilitate information sharing between tasks via a novel sparse interaction mechanism among heterogeneous graphs. Through experiments on two real-world datasets, compared with the state-of-the-art baselines, the extensive results exhibit that MG-SIN achieves competitive improvements of up to 2.1% and 2.42% for the stance detection task, and 5.26% and 3.93% for the sentiment analysis task, respectively.

Preference between Chinese and Western medicines for hypertension treatment: Evidences based on Chinese population aged ≥ 45 years.

Hypertension is one of the chronic diseases that threaten the health of the elderly population. This study aims to explore the treatment and medication preferences in Chinese elderly patients (≥45 years old) with hypertension, and to investigate the relevant influencing factors. A cross-sectional design was adopted. Utilizing the data from the public database CHARLS 2018, the factors influencing the treatment and medication preference among the elderly hypertensive patients were explored with multinomial logistic regression models. A total of 6588 hypertensive patients aged ≥ 45 years were included in this study, of which 5135 (77.94%) received treatment. Besides, 4939 (96.18%) chose oral medication, which was the most preferred treatment for these patients. The proportion of patients who chose "oral medication only" increased with age, but decreased with educational level and self-reported health. Patients with higher educational levels were more likely to choose other modalities of treatment. In particular, patients with better self-reported health were more willing to try traditional Chinese medication (TCM). Lower income group without medical insurance preferred to choose "Chinese medicine only." Patients aged ≥ 75 years, urban residents, and those with 2 or more chronic diseases were more willing to try combined Chinese and Western medicines. Patients' preference for TCM therapy was correlated positively with the provincial economic welfare factor, and negatively with the provincial medical and social welfare factors. During treatment of patients with hypertension, clinicians should pay attention to their preferences and formulate personalized regimens for them, in order to improve their compliance with treatment. Additionally, the government should steadily improve the local medical benefits, thereby facilitating the promotion and application of local TCM services.

Exploring the mechanism of aloe-emodin in the treatment of liver cancer through network pharmacology and cell experiments.

Objective: Aloe-emodin (AE) is an anthraquinone compound extracted from the rhizome of the natural plant rhubarb. Initially, it was shown that AE exerts an anti-inflammatory effect. Further studies revealed its antitumor activity against various types of cancer. However, the mechanisms underlying these properties remain unclear. Based on network pharmacology and molecular docking, this study investigated the molecular mechanism of AE in the treatment of hepatocellular carcinoma (HCC), and evaluated its therapeutic effect through in vitro experiments. Methods: CTD, Pharmmapper, SuperPred and TargetNet were the databases to obtain potential drug-related targets. DisGenet, GeneCards, OMIM and TTD were used to identify potential disease-related targets. Intersection genes for drugs and diseases were obtained through the Venn diagram. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of intersecting genes were conducted by the website of Bioinformatics. Intersection genes were introduced into STRING to construct a protein-protein interaction network, while the Cytoscape3.9.1 software was used to visualize and analyze the core targets. AutoDock4.2.6 was utilized to achieve molecular docking between drug and core targets. In vitro experiments investigated the therapeutic effects and related mechanisms of AE. Results: 63 overlapped genes were obtained and GO analysis generated 3,646 entries by these 63 intersecting genes. KEGG analysis mainly involved apoptosis, proteoglycans in cancer, TNF signaling pathway, TP53 signaling pathway, PI3K-AKT signaling pathway, etc. AKT1, EGFR, ESR1, TP53, and SRC have been identified as core targets because the binding energies of them between aloe-emodin were less than -5 kcal/Mol.The mRNA and protein expression, prognosis, mutation status, and immune infiltration related to core targets were further revealed. The involvement of AKT1 and EGFR, as well as the key target of the PI3K-AKT signaling pathway, indicated the importance of this signaling pathway in the treatment of HCC using AE. The results of the Cell Counting Kit-8 assay and flow analysis demonstrated the therapeutic effect of AE. The downregulation of EGFR, PI3KR1, AKT1, and BCL2 in mRNA expression and PI3KR1, AKT,p-AKT in protein expression confirmed our hypothesis. Conclusion: Based on network pharmacology and molecular docking, our study initially showed that AE exerted a therapeutic effect on HCC by modulating multiple signaling pathways. Various analyses confirmed the antiproliferative activity and pro-apoptotic effect of AE on HCC through the PI3K-AKT signaling pathway. This study revealed the therapeutic mechanism of AE in the treatment of HCC through a novel approach, providing a theoretical basis for the clinical application of AE.

Home/Community-Based Medical and Elderly Care Services Utilization in China: A Cross-Sectional Study from the Middle-Aged and Elderly Population.

Few studies have analyzed the acceptance of home/community-based medical and elderly care services in China. Therefore, we conducted a cross-sectional study to describe the acceptance of five services among people aged ≥ 45 years in the China mainland, and their influencing factors. The data were obtained from the database China Health and Retirement Longitudinal Study 2018. For each service, a binary logistics regression was adopted. A total of 9719 people were included, of whom 20.12% received services. The numbers of recipients (acceptance rates) of the five services, namely, comprehensive aged care services, regular physical examinations, onsite visits, health management, and entertainment, were 107 (1.10%), 1640 (16.87%), 323 (3.32%), 156 (1.61%), and 245 (2.52%), respectively. About 4% of people had received two or more services. The elderly aged 65-74 and those who were satisfied with the local medical services had higher acceptance of services. Urban hukou having health insurance, two or more chronic diseases, provincial economic welfare, and social welfare were positively associated with the acceptance of regular physical examination services. It is suggested that the government should gradually improve satisfaction with local medical services, and pay more attention to the needs of elderly people aged 65-74 for all kinds of home/community-based medical and elderly care services.

Deep learning enabled fast 3D brain MRI at 0.055 tesla.

In recent years, there has been an intensive development of portable ultralow-field magnetic resonance imaging (MRI) for low-cost, shielding-free, and point-of-care applications. However, its quality is poor and scan time is long. We propose a fast acquisition and deep learning reconstruction framework to accelerate brain MRI at 0.055 tesla. The acquisition consists of a single average three-dimensional (3D) encoding with 2D partial Fourier sampling, reducing the scan time of T1- and T2-weighted imaging protocols to 2.5 and 3.2 minutes, respectively. The 3D deep learning leverages the homogeneous brain anatomy available in high-field human brain data to enhance image quality, reduce artifacts and noise, and improve spatial resolution to synthetic 1.5-mm isotropic resolution. Our method successfully overcomes low-signal barrier, reconstructing fine anatomical structures that are reproducible within subjects and consistent across two protocols. It enables fast and quality whole-brain MRI at 0.055 tesla, with potential for widespread biomedical applications.

Impact of Replacing Soft Drinks with Dairy Products on Micronutrient Intakes of Chinese Preschool Children: A Simulation Study.

At present, energy surplus and micronutrient deficiency coexist in preschool children in China. The low intake of dairy products accompanied by an increased consumption of soft drinks in this age group reveals some of the reasons for this phenomenon. The purpose of this study was to evaluate the improvement of key micronutrients in preschool children by quantifying the dietary nutritional gap before and after simulating the use of dairy products instead of equal amounts of soft drinks. In the cross-sectional dietary intake survey of infants and young children in China (2018-2019), 676 preschool children aged 3-6 years were randomly selected. Four days of dietary data were collected through an online diary for simulation. The individual intake of soft drinks was substituted at a corresponding volume by soymilk, cow's milk, or formulated milk powder for preschool children (FMP-PSC). In these three models, the simulated nutrient intake and nutrient inadequacy or surplus were compared with the actual baseline data of the survey. The results of this study indicated that all three models made the nutrient intakes of this group more in line with the recommendations. For the whole population, the replacement of soymilk improved the intake of zinc (from 4.80 to 4.85 mg/d), potassium (from 824.26 to 836.82 mg/d), vitamin A (from 211.57 to 213.92 µg retinol activity equivalent/d), and vitamin B9 (from 115.94 to 122.79 µg dietary folate equivalent/d); the simulation of cow's milk improved the intake of calcium (from 311.82 to 330.85 mg/d), zinc (from 4.80 to 4.87 mg/d), potassium (from 824.26 to 833.62 mg/d), vitamin A (from 211.57 to 215.12 µg retinol activity equivalent/d), vitamin B2 (from 0.53 to 0.54 mg/d), and vitamin B12 (from 1.63 to 1.67 µg/d); and the substitution of FMP-PSC improved the intake of calcium (from 311.82 to 332.32 mg/d), iron (from 9.91 to 9.36 mg/d), zinc (from 4.80 to 4.96 mg/d), potassium (from 824.26 to 828.71 mg/d), vitamin A (from 211.57 to 217.93 µg retinol activity equivalent/d), vitamin B2 (from 0.53 to 0.54 mg/d), vitamin B9 (from 115.94 to 118.80 µg RA dietary folate equivalent/d), and vitamin B12 (from 1.63 to 1.70 µg/d). Therefore, correct nutritional information should be provided to parents and preschool children. In addition to changing the consumption behavior of soft drinks, it is also necessary to have a diversified and balanced diet. When necessary, the use of food ingredients or nutritional fortifiers can be encouraged.

DeePMD-kit v2: A software package for deep potential models.

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.

Investigation on the Coaxial-Annulus-Argon-Assisted Water-Jet-Guided Laser Machining of Hard-to-Process Materials.

In this study, the novel coaxial-annulus-argon-assisted (CAAA) atmosphere is proposed to enhance the machining capacity of the water-jet-guided laser (WJGL) when dealing with hard-to-process materials, including ceramic matrix composites (CMCs) and chemical-vapor-deposition (CVD) diamond. A theoretical model was developed to describe the two-phase flow of argon and the water jet. Simulations and experiments were conducted to analyze the influence of argon pressure on the working length of the WJGL beam, drainage circle size, and extreme scribing depth on ceramic matrix composite (CMC) substrates. A comparative experiment involving coaxial annulus and helical atmospheres revealed that the coaxial annulus atmosphere disrupts the water jet proactively, while effectively maintaining the core velocity within the confined working length and enhancing the processing capability of the WJGL beam. Single-point percussion drilling experiments were performed on a CMC substrate to evaluate the impact of machining parameters on hole morphology. The maximum depth-to-width ratio of the groove and depth-to-diameter ratio of the hole reached up to 41.2 and 40.7, respectively. The thorough holes produced by the CAAAWJGL demonstrate superior roundness and minimal thermal damage, such as fiber drawing and delamination. The average tensile strength and fatigue life of the CMCs specimens obtained through CAAAWJGL machining reached 212.6 MPa and 89,463.8 s, exhibiting higher machining efficiency and better mechanical properties compared to femtosecond (194.2 MPa; 72,680.2 s) and picosecond laser (198.6 MPa; 80,451.4 s) machining. Moreover, groove arrays with a depth-to-width ratio of 11.5, good perpendicularity, and minimal defects on a CVD diamond were fabricated to highlight the feasibility of the proposed machining technology.