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Associations between Geriatric Nutrition Risk Index,bone mineral density and body composition in type 2 diabetes patients

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World Journal of Diabetes 2024年第3期15卷 403-417页

作者： xiao-xiao Zhu kai-Feng Yao Hai-Yan huang Li-Hua Wang Department of Pediatrics The Second Affiliated Hospital of Nantong UniversityFirst People’s Hospital of Nantong CityNantong 226001Jiangsu ProvinceChina Department of Nursing The Second Affiliated Hospital of Nantong UniversityFirst People’s Hospital of Nantong CityNantong 226001Jiangsu ProvinceChina Department of Endocrinology The Second Affiliated Hospital of Nantong UniversityFirst People’s Hospital of Nantong CityNantong 226001Jiangsu ProvinceChina

BACKGROUND Type 2 diabetes mellitus(T2DM),a fast-growing issue in public health,is one of the most common chronic metabolic disorders in older individuals.Osteoporosis and sarcopenia are highly prevalent in T2DM patients and may result in fractures and disabilities.In people with T2DM,the association between nutrition,sarcopenia,and osteoporosis has rarely been explored.AIM To evaluate the connections among nutrition,bone mineral density(BMD)and body composition in patients with T2DM.METHODS We enrolled 689 patients with T2DM for this cross-sectional study.All patients underwent dual energy X-ray absorptiometry(DXA)examination and were categorized according to baseline Geriatric Nutritional Risk Index(GNRI)values calculated from serum albumin levels and body weight.The GNRI was used to evaluate nutritional status,and DXA was used to investigate BMD and body composition.Multivariate forward linear regression analysis was used to identify the factors associated with BMD and skeletal muscle mass index.RESULTS Of the total patients,394 were men and 295 were women.Compared with patients in tertile 1,those in tertile 3 who had a high GNRI tended to be younger and had lower HbA1c,higher BMD at all bone sites,and higher appendicular skeletal muscle index(ASMI).These important trends persisted even when the patients were divided into younger and older subgroups.The GNRI was positively related to ASMI(men:r=0.644,P<0.001;women:r=0.649,P<0.001),total body fat(men:r=0.453,P<0.001;women:r=0.557,P<0.001),BMD at all bone sites,lumbar spine(L1-L4)BMD(men:r=0.110,P=0.029;women:r=0.256,P<0.001),FN-BMD(men:r=0.293,P<0.001;women:r=0.273,P<0.001),and hip BMD(men:r=0.358,P<0.001;women:r=0.377,P<0.001).After adjustment for other clinical parameters,the GNRI was still significantly associated with BMD at the lumbar spine and femoral neck.Additionally,a low lean mass index and higherβ-collagen special sequence were associated with low BMD at all bone sites.Age was negatively correlated with ASMI,whereas weight was positively correlated w

关键词： Geriatric Nutrition Risk Index Bone mineral density Skeletal muscle mass Type 2 diabetes

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T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma

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World Journal of Gastrointestinal Oncology 2024年第3期16卷 819-832页

作者： Hui-Da Zheng Qiao-Yi huang Qi-Ming huang xiao-Ting Ke kai Ye Shu Lin Jian-Hua Xu Department of Gastrointestinal Surgery The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou 362000Fujian ProvinceChina Department of Gynaecology and Obstetrics The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou 362000Fujian ProvinceChina Department of Computed Tomography/Magnetic Resonance Imaging The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou 362000Fujian ProvinceChina Centre of Neurological and Metabolic Research The Second Affiliated Hospital of Fujian Medical UniversityQuanzhou 362000Fujian ProvinceChina Group of Neuroendocrinology Garvan Institute of Medical ResearchSydneyNSW 2010Australia

BACKGROUND The study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported yet.Developing a non-invasive model to predict the differentiation grade of CRC is of great value.AIM To develop and validate machine learning-based models for predicting the differ-entiation grade of CRC based on T2-weighted images(T2WI).METHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023.Patients were randomly assigned to a training cohort(n=220)or a validation cohort(n=95)at a 7:3 ratio.Lesions were delineated layer by layer on high-resolution T2WI.Least absolute shrinkage and selection operator regression was applied to screen for radiomic features.Radiomics and clinical models were constructed using the multilayer perceptron(MLP)algorithm.These radiomic features and clinically relevant variables(selected based on a significance level of P<0.05 in the training set)were used to construct radiomics-clinical models.The performance of the three models(clinical,radiomic,and radiomic-clinical model)were evaluated using the area under the curve(AUC),calibration curve and decision curve analysis(DCA).RESULTS After feature selection,eight radiomic features were retained from the initial 1781 features to construct the radiomic model.Eight different classifiers,including logistic regression,support vector machine,k-nearest neighbours,random forest,extreme trees,extreme gradient boosting,light gradient boosting machine,and MLP,were used to construct the model,with MLP demonstrating the best diagnostic performance.The AUC of the radiomic-clinical model was 0.862(95%CI:0.796-0.927)in the training cohort and 0.761(95%CI:0.635-0.887)in the validation cohort.The AUC for the radiomic model was 0.796(95%CI:0.723-0.869)in the training cohort and 0.735(95%CI:0.604-0.866)in the validation cohort.The clinical model achieved an AUC of 0.751(95%CI:0.661-0.842)in the training cohort and

关键词： Radiomics Colorectal cancer Differentiation grade Machine learning T2-weighted imaging

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A micro-crosslinked amphoteric hydrophobic association copolymer as high temperature-and salt-resistance fluid loss reducer for water-based drilling fluids

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Petroleum Science 2024年第3期21卷 1980-1991页

作者： Jian Li Yu-Xi Ji xiao-xiao Ni kai-He Lv Xian-Bin huang Jin-Sheng Sun School of Petroleum Engineering China University of Petroleum(East China) Key Laboratory of Unconventional Oil & Gas Development China University of Petroleum(East China) Inspection and Testing Center of Huabei Oil Field Company PetroChina Drilling Fluid Research Institute CNPC Engineering Technology R&D Company Limited

During ultradeep oil and gas drilling, fluid loss reducers are highly important for water-based drilling fluids, while preparing high temperature-and salt-resistance fluid loss reducers with excellent rheology and filtration performance remains a challenge. Herein, a micro-crosslinked amphoteric hydrophobic association copolymer(i.e., DADC) was synthesized using N,N-dimethyl acrylamide, diallyl dimethyl ammonium chloride, 2-acrylamido-2-methylpropane sulfonic acid, hydrophobic monomer, and pentaerythritol triallyl ether crosslinker. Due to the synergistic effects of hydrogen bonds, electrostatic interaction, hydrophobic association, and micro-crosslinking, the DADC copolymer exhibited outstanding temperature-and salt-resistance. The rheological experiments have shown that the DADC copolymer had excellent shear dilution performance and a certain degree of salt-responsive viscosity-increasing performance. The DADC copolymer could effectively adsorb on the surface of bentonite particles through electrostatic interaction and hydrogen bonds, which bring more negative charge to the bentonite, thus improving the hydration and dispersion of bentonite particles as well as the colloidal stability of the drilling fluids. Moreover, the drilling fluids constructed based on the DADC copolymer exhibited satisfactory rheological and filtration properties(FLHTHP= 12 m L) after aging at high temperatures(up to200°C) and high salinity(saturated salt) environments. Therefore, this work provided new insights into designing and fabricating high-performance drilling fluid treatment agents, demonstrating good potential applications in deep and ultradeep drilling engineering.

关键词： Fluid loss reducer Temperature- and salt-resistance Hydrophobic association Amphoteric Micro-crosslinking

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Adaptive learning-based optimal tracking control system design and analysis of a disturbed nonlinear hypersonic vehicle model

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Science China Technological Sciences 2024年第6期67卷 1893-1906页

作者： AN kai WANG ZhenGuo huang Wei National University of Defense Technology Hypersonic Technology Laboratory

We propose an adaptive learning-based optimal control scheme for height-velocity control models considering model uncertainties and external disturbances of hypersonic winged-cone vehicles. The longitudinal nonlinear model is first established and transformed into the control-oriented error equations, and the control scheme is organized by a steady-compensation combination. To overcome and eliminate the impact of model uncertainties and external disturbances, an adaptive radial basis function neural network(RBFNN) is designed by a q-gradient approach. Taking the height-velocity error system with estimated uncertainties into account, the adaptive learning-based optimal tracking control(ALOTC) scheme is proposed by combining the critic-only adaptive dynamic programming(ADP) framework and parameter optimization of system settling time. Furthermore,a novel weight update law is proposed to satisfy the online iteration requirements, and the algorithm convergence and closedloop stability are discussed by the Lyapunov theory. Finally, four simulation cases are provided to prove the effectiveness,accuracy, and robustness of the proposed scheme for the hypersonic longitudinal control system.

关键词： optimal tracking control adaptive dynamic programming RBFNN hypersonic vehicle

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Machine learning with active pharmaceutical ingredient/polymer interaction mechanism:Prediction for complex phase behaviors of pharmaceuticals and formulations

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Chinese Journal of Chemical Engineering 2024年第2期66卷 263-272页

作者： kai Ge Yiping huang Yuanhui Ji Jiangsu Province Hi-Tech Key Laboratory for Biomedical Research School of Chemistry and Chemical EngineeringSoutheast UniversityNanjing 211189China

The high throughput prediction of the thermodynamic phase behavior of active pharmaceutical ingredients(APIs)with pharmaceutically relevant excipients remains a major scientific challenge in the screening of pharmaceutical formulations.In this work,a developed machine-learning model efficiently predicts the solubility of APIs in polymers by learning the phase equilibrium principle and using a few molecular descriptors.Under the few-shot learning framework,thermodynamic theory(perturbed-chain statistical associating fluid theory)was used for data augmentation,and computational chemistry was applied for molecular descriptors'screening.The results showed that the developed machine-learning model can predict the API-polymer phase diagram accurately,broaden the solubility data of APIs in polymers,and reproduce the relationship between API solubility and the interaction mechanisms between API and polymer successfully,which provided efficient guidance for the development of pharmaceutical formulations.

关键词： Multi-task machine learning Density functional theory Hydrogen bond interaction Miscibility Solubility

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Long-lived lunar volcanism sustained by precession-driven core-mantle friction

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National Science Review 2024年第2期11卷 114-123页

作者： Shuoran Yu xiao xiao Shengxia Gong Nicola Tosi Jun huang Doris Breuer Long xiao Dongdong Ni State Key Laboratory of Lunar and Planetary Sciences Macau University of Science and Technology Planetary Science Institute State Key Laboratory of Geological Processes and Mineral Resources School of Earth Sciences China University of Geosciences CAS Key Laboratory of Planetary Sciences Shanghai Astronomical Observatory Institute of Planetary Research German Aerospace Centre(DLR)

Core-mantle friction induced by the precession of the Moon's spin axis is a strong heat source in the deep lunar mantle during the early phase of a satellite's evolution, but its influence on the long-term thermal evolution still remains poorly explored. Using a one-dimensional thermal evolution model, we show that core-mantle friction can sustain global-scale partial melting in the upper lunar mantle until ～3.1 Ga, thus accounting for the intense volcanic activity on the Moon before ～3.0 Ga. Besides, core-mantle friction tends to suppress the secular cooling of the lunar core and is unlikely to be an energy source for the long-lived lunar core dynamo. Our model also favours the transition of the Cassini state before the end of the lunar magma ocean phase(～4.2 Ga), which implies a decreasing lunar obliquity over time after the solidification of the lunar magma ocean. Such a trend of lunar obliquity evolution may allow volcanically released water to be buried in the lunar regolith of the polar regions. As a consequence, local water ice could be more abundant than previously thought when considering only its accumulation caused by solar wind and comet spreading.

关键词： Moon precession orbit volcanism

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Role of biochar in raising blue carbon stock capacity of salt marshes

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Pedosphere 2024年第1期34卷 19-22页

作者： Yuzhou huang Xi xiao Ocean College Zhejiang UniversityZhoushan 316021China Key Laboratory of Marine Ecological Monitoring and Restoration Technologies of the Ministry of Natural Resources of China Shanghai 201306China Donghai Laboratory Zhoushan 316021China Ocean Academy Zhejiang UniversityZhoushan 316021China Key Laboratory of Watershed Non-point Source Pollution Control and Water Eco-security of Ministry of Water Resources College of Environmental and Resources SciencesZhejiang UniversityHangzhou 310058China

Salt marshes are an important blue carbon ecosystem, with surprisingly fast carbon accumulation rates that are 40 times higher than those of terrestrial forests. In recent decades, salt marshes have suffered great degradation and loss all over the world. The idea to enhance carbon stock in salt marshes(so-called blue carbon) using biochar (so-called black carbon) has recently been proposed. Although experiments and observations remain limited, significant enhancements in soil organic carbon and plant growth have been documented in most case studies. However, due to the limited number of observations and their relatively short time window ranging from months to less than one year, there still exists a knowledge gap regarding the process, mechanism, and effect of biochar in enhancing carbon stock in salt marshes. Future research is urgently needed in the following perspectives:1) exploring the relationship between carbon stock enhancement efficiency and biochar properties, 2) optimizing the physical and chemical properties of biochar to boost its efficiency, and 3)studying the in-situ responses of complex carbon pools to biochar addition, especially under tidal conditions and over a longer period of time.

关键词： soil stock char

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Predicting Hurricane Evacuation Decisions with Interpretable Machine Learning Methods

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International Journal of Disaster Risk Science 2024年第1期15卷 134-148页

作者： Yuran Sun Shih‑kai huang Xilei Zhao Department of Civil and Coastal Engineering University of FloridaGainesvilleFL 32611USA Department of Emergency Management and Public Administration Jacksonville State UniversityJacksonvilleAL 36265USA

Facing the escalating effects of climate change,it is critical to improve the prediction and understanding of the hurricane evacuation decisions made by households in order to enhance emergency management.Current studies in this area often have relied on psychology-driven linear models,which frequently exhibited limitations in practice.The present study proposed a novel interpretable machine learning approach to predict household-level evacuation decisions by leveraging easily accessible demographic and resource-related predictors,compared to existing models that mainly rely on psychological factors.An enhanced logistic regression model(that is,an interpretable machine learning approach) was developed for accurate predictions by automatically accounting for nonlinearities and interactions(that is,univariate and bivariate threshold effects).Specifically,nonlinearity and interaction detection were enabled by low-depth decision trees,which offer transparent model structure and robustness.A survey dataset collected in the aftermath of Hurricanes Katrina and Rita,two of the most intense tropical storms of the last two decades,was employed to test the new methodology.The findings show that,when predicting the households’ evacuation decisions,the enhanced logistic regression model outperformed previous linear models in terms of both model fit and predictive capability.This outcome suggests that our proposed methodology could provide a new tool and framework for emergency management authorities to improve the prediction of evacuation traffic demands in a timely and accurate manner.

关键词： Artifcial Intelligence(AI) Decision-making modeling Hurricane evacuation Interpretable machine learning Nonlinearity and interaction detection

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Decouple charge transfer reactions in the Li-ion battery

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Journal of Energy Chemistry 2024年第5期92卷 759-798页

作者： Yuxuan Bai Qiu-An huang kai Wu Jiujun Zhang Institute for Sustainable Energy/College of Sciences Shanghai UniversityShanghai 200444China Ningde Contemporary Innovation Laboratory Contemporary Amperex Technology Co.LimitedNingde 352100FujianChina

In the development of Li-ion batteries(LIBs)with high energy/power density,long cycle-life,fast charging,and high safety,an insight into charge transfer reactions is required.Although electrochemical impedance spectroscopy(EIS)is regarded as a powerful diagnosis tool,it is not a direct but an indirect measurement.With respect to this,some critical questions need to be answered:(i)why EIS can reflect the kinetics of charge transfer reactions;(ii)what the inherent logical relationship between impedance models under different physical scenes is;(iii)how charge transfer reactions compete with each other at multiple scales.This work aims at answering these questions via developing a theory framework so as to mitigate the blindness and uncertainty in unveiling charge transfer reactions in LIBs.To systematically answer the above questions,this article is organized into a three-in-one(review,tutorial,and research)type and the following contributions are made:(i)a brief review is given for impedance model development of the LIBs over the past half century;(ii)an open source code toolbox is developed based on the unified impedance model;(iii)the competive mechanisms of charge transfer reactions are unveiled based on the developed EIS-Toolbox@LIB.This work not only clarifies theoretical fundamentals,but also provides an easy-to-use open source code for EIS-Toolbox@LIB to optimize fast charge/discharge,mitigate cycle aging,and improve energy/power density.

关键词： Electrochemical impedance spectroscopy Unified impedance model Charge transfer reactions Solid/electrolyte diffusion Porous electrode EIS-Toolbox@LIB

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WNT7A promotes tumorigenesis of head and neck squamous cell carcinoma via activating FZD7/JAK1/STAT3 signaling

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International Journal of Oral Science 2024年第1期16卷 85-96页

作者： Qingling huang Yi xiao Ting Lan Youguang Lu Li huang Dali Zheng Department of Biochemistry and Molecular Biology School of Basic Medical SciencesFujian Medical UniversityFuzhouChina Fujian Key Laboratory of Oral Diseases School and Hospital of StomatologyFujian Medical UniversityFuzhouChina Department of Preventive Dentistry School and Hospital of StomatologyFujian Medical UniversityFuzhouChina Department of Dentistry The First Affiliated Hospital of Fujian Medical UniversityFuzhouChina

Wnt signaling are critical pathway involved in organ development, tumorigenesis, and cancer progression. WNT7A, a member of the Wnt family, remains poorly understood in terms of its role and the underlying molecular mechanisms it entails in head and neck squamous cell carcinoma (HNSCC). According to the Cancer Genome Atlas (TCGA), transcriptome sequencing data of HNSCC, the expression level of WNT7A in tumors was found to be higher than in adjacent normal tissues, which was validated using Real-time RT-PCR and immunohistochemistry. Unexpectedly, overexpression of WNT7A did not activate the canonical Wnt-β-catenin pathway in HNSCC. Instead, our findings suggested that WNT7A potentially activated the FZD7/JAK1/STAT3 signaling pathway, leading to enhanced cell proliferation, self-renewal, and resistance to apoptosis. Furthermore, in a patient-derived xenograft (PDX) tumor model, high expression of WNT7A and phosphorylated STAT3 was observed, which positively correlated with tumor progression.These findings underscore the significance of WNT7A in HNSCC progression and propose the targeting of key molecules within the FZD7/JAK1/STAT3 pathway as a promising strategy for precise treatment of HNSCC.

关键词： WNT squamous tumorigenesis

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