Machine learning applications in healthcare clinical practice and research

Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.

Synthetic data as an investigative tool in hypertension and renal diseases research

There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient privacy.This is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension worldwide.However,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.

Harnessing artificial intelligence for identifying conflicts of interest in research

This editorial explores the transformative potential of artificial intelligence(AI)in identifying conflicts of interest(COIs)within academic and scientific research.By harnessing advanced data analysis,pattern recognition,and natural language processing techniques,AI offers innovative solutions for enhancing transparency and integrity in research.This editorial discusses how AI can automatically detect COIs,integrate data from various sources,and streamline reporting processes,thereby maintaining the credibility of scientific findings.

Geographical Engineering and Its Role in Promoting Integrated Geography Research

Throughout the contemporary Chinese history of geography,geographical engineering has consistently played a pivotal role as a fundamental scientific activity.It possesses its distinct ontological basis and value orientation,rendering it inseparable from being merely a derivative of geographical science or technology.This paper defines geographical engineering and introduces its development history through the lens of Chinese geographical engineering praxises.Furthermore,it is highlighted the logical and functional consistency between the theory of human-earth system and the praxis of geographical engineering.Six modern cases of geographical engineering projects are presented in detail to demonstrate the points and characteristics of different types of modern geographical engineering.Geographical engineering serves as an engine for promoting integrated geography research,and in response to the challenge posed by fragmented geographies,this paper advocates for an urgent revitalization of geographical engineering.The feasibility of revitalizing geographical engineering is guaranteed because it aligns with China’s national strategies.

Experimental research on grouser traction of deep-sea mining machine

The traction characteristics of the grouser, cutting the simulative soil of deepsea sediment, with different tooth widths, tooth heights, and ground pressures are studied with traction characteristic test apparatus. A traction-displacement model is obtained by combining the analysis of the cutting mechanism. The results show that the tractiondisplacement curves of grousers with different tooth widths, tooth heights, and ground pressures have the same changing trend, which matches the Wong traction model. Their sensitivity coefficient and shear modulus are slightly fluctuated. Therefore, the average values can be used as the traction model parameters. The maximum traction of the grouser with a two-side edge and a 10 mm tooth width increment changing with the tooth height and ground pressure can be determined according to the grousers with different tooth widths. By combining the traction model parameters, the traction-displacement curve of the grouser with a certain group values of tooth width, tooth height, and ground pressure can be predicted. Therefore, the slip of the mining machine can be prevented to improve the mining efficiency.

Research on Pressure Tight Sampling Technique of Deep-Sea Shallow Sediment—A New Approach to Gas Hydrate Investigation

Analyzed and calculated are pressure changes and body deformation of the sample inside of the corer in the process of sampling of deep-sea shallow sediment with a non-piston corer for gas hydrate investigation, Two conclusions are drawn： （1） the stress increments associated with the corer through the sampling process do not affect the stabilization of the gas hydrate; （2） the body deformation of the sample is serious and the ＂incremental filling ratio＂ （IFR） is less than unit, For taking samples with in-situ pressure and structure, combining with the design theories of the pressure tight corer, we have designed a kind of piston corer, named the gas hydrate pressure tight piston corer, Several tests on the sea have been conducted. Test results indicate that the piston corer has a good ability of taking sediment samples on the seafloor and maintaining their original in-situ pressure, meeting the requirement of exploration of gas hydrate in deep-sea shallow sediment layers.

Design and research on a variable ballast system for deep-sea manned submersibles

Variable ballast systems are necessary for manned submersibles to adjust their buoyancy.In this paper,the design of a variable ballast system for a manned submersible is described.The variable ballast system uses a super high pressure hydraulic seawater system.A super high pressure seawater pump and a deep-sea brushless DC motor are used to pump seawater into or from the variable ballast tank,increasing or decreasing the weight of the manned submersible.A magnetostrictive linear displacement transducer can detect the seawater level in the variable ballast tank.Some seawater valves are used to control pumping direction and control on-off states.The design and testing procedure for the valves is described.Finally,the future development of variable ballast systems and seawater hydraulic systems is projected.

Research on coupled thermo-hydro-mechanical dynamic response characteristics of saturated porous deep-sea sediments under vibration of mining vehicle

The excessive deformation of deep-sea sediments caused by the vibration of the mining machine will adversely affect the efficiency and safety of mining.Combined with the deep-sea environment,the coupled thermo-hydro-mechanical problem for saturated porous deep-sea sediments subject to the vibration of the mining vehicle is investigated.Based on the Green-Lindsay(G-L)generalized thermoelastic theory and Darcy’s law,the model of thermo-hydro-mechanical dynamic responses for saturated porous deep-sea sediments under the vibration of the mining vehicle is established.We obtain the analytical solutions of non-dimensional vertical displacement,excess pore water pressure,vertical stress,temperature,and change in the volume fraction field with the normal mode analysis method,and depict them graphically.The normal mode analysis method uses the canonical coordinate transformation to solve the equation,which can quickly decouple the equation by ignoring the modal coupling effect on the basis of the canonical mode.The results indicate that the vibration frequency has obvious influence on the vertical displacement,excess pore water pressure,vertical stress,and change in volume fraction field.The loading amplitude has a great effect on the physical quantities in the foundation,and the changes of the physical quantities increase with the increase in loading amplitude.

What Depth Should Deep-Sea Water be Pumped up from in the South China Sea for Medicinal Research?

In this study, seawater was pumped up from 150, 200, 300, 500 and 1000 m in the South China Sea and analyzed to make certain what depth should deep-sea water (DSW) be pumped up for medicinal usage. The pumping depth of DSW was determined on the basis of chemical ingredients. The analyses of inorganic elements and dissolved organic matter (DOM) were performed by inductively coupled plasma mass spectrometry (ICP-MS) and ultra performance liquid chromatography-mass spectrometry (UPLC-MS) respectively. The raw data were used for hierarchical cluster analysis (HCA) and principal component analysis (PCA). The results showed that seawater pumped up from 500 m and 1000 m was similar in their chemical ingredients, and was different from the seawater pumped up from other depths. These results indicated that seawater from more than 500 m depth had relatively stable chemical ingredients and could be used as DSW in the South China Sea.

Research funding and citations in papers of Nobel Laureates in Physics, Chemistry and Medicine, 2019-2020

Purpose:The goal of this study is a comparative analysis of the relation between funding(a main driver for scientific research)and citations in papers of Nobel Laureates in physics,chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole.Design/methodology/approach:This study utilizes a power law model to explore the relationship between research funding and citations of related papers.The study here analyzes 3,539 recorded documents by Nobel Laureates in physics,chemistry and medicine and a broader dataset of 183,016 documents related to the fields of physics,medicine,and chemistry recorded in the Web of Science database.Findings:Results reveal that in chemistry and medicine,funded researches published in papers of Nobel Laureates have higher citations than unfunded studies published in articles;vice versa high citations of Nobel Laureates in physics are for unfunded studies published in papers.Instead,when overall data of publications and citations in physics,chemistry and medicine are analyzed,all papers based on funded researches show higher citations than unfunded ones.Originality/value:Results clarify the driving role of research funding for science diffusion that are systematized in general properties:a)articles concerning funded researches receive more citations than(un)funded studies published in papers of physics,chemistry and medicine sciences,generating a high Matthew effect(a higher growth of citations with the increase in the number of papers);b)research funding increases the citations of articles in fields oriented to applied research(e.g.,chemistry and medicine)more than fields oriented towards basic research(e.g.,physics).Practical implications:The results here explain some characteristics of scientific development and diffusion,highlighting the critical role of research funding in fostering citations and the expansion of scientific knowledge.This finding can support decision-making of policymakers and R&D managers to improve the effectiveness in allocating financial resources in science policies to generate a higher positive scientific and societal impact.

Glucocorticoids-based prodrug design:Current strategies and research progress

Attributing to their broad pharmacological effects encompassing anti-inflammation,antitoxin,and immunosuppression,glucocorticoids(GCs)are extensively utilized in the clinic for the treatment of diverse diseases such as lupus erythematosus,nephritis,arthritis,ulcerative colitis,asthma,keratitis,macular edema,and leukemia.However,longterm use often causes undesirable side effects,including metabolic disorders-induced Cushing's syndrome(buffalo back,full moon face,hyperglycemia,etc.),osteoporosis,aggravated infection,psychosis,glaucoma,and cataract.These notorious side effects seriously compromise patients'quality of life,especially in patients with chronic diseases.Therefore,glucocorticoid-based advanced drug delivery systems for reducing adverse effects have received extensive attention.Among them,prodrugs have the advantages of low investment,low risk,and high success rate,making them a promising strategy.In this review,we propose the strategies for the design and summarize current research progress of glucocorticoid-based prodrugs in recent decades,including polymer-based prodrugs,dendrimer-based prodrugs,antibody-drug conjugates,peptide-drug conjugates,carbohydrate-based prodrugs,aliphatic acid-based prodrugs and so on.Besides,we also raise issues that need to be focused on during the development of glucocorticoid-based prodrugs.This review is expected to be helpful for the research and development of novel GCs and prodrugs.

General laws of funding for scientific citations:how citations change in funded and unfunded research between basic and applied sciences

Purpose:The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences.Design/methodology/approach:A power law model analyzes the relationship between research funding and citations of papers using 831,337 documents recorded in the Web of Science database.Findings:The original results reveal general characteristics of the diffusion of science in research fields:a)Funded articles receive higher citations compared to unfunded papers in journals;b)Funded articles exhibit a super-linear growth in citations,surpassing the increase seen in unfunded articles.This finding reveals a higher diffusion of scientific knowledge in funded articles.Moreover,c)funded articles in both basic and applied sciences demonstrate a similar expected change in citations,equivalent to about 1.23%,when the number of funded papers increases by 1%in journals.This result suggests,for the first time,that funding effect of scientific research is an invariant driver,irrespective of the nature of the basic or applied sciences.Originality/value:This evidence suggests empirical laws of funding for scientific citations that explain the importance of robust funding mechanisms for achieving impactful research outcomes in science and society.These findings here also highlight that funding for scientific research is a critical driving force in supporting citations and the dissemination of scientific knowledge in recorded documents in both basic and applied sciences.Practical implications:This comprehensive result provides a holistic view of the relationship between funding and citation performance in science to guide policymakers and R&D managers with science policies by directing funding to research in promoting the scientific development and higher diffusion of results for the progress of human society.

Global research trends and hotspots in overweight/obese comorbid with depression among children and adolescents: A bibliometric analysis

BACKGROUND Overweight/obesity combined with depression among children and adolescents(ODCA)is a global concern.The bidirectional relationship between depression and overweight/obesity often leads to their comorbidity.Childhood and adolescence represent critical periods for physical and psychological development,during which the comorbidity of overweight/obesity and depression may increase the risk of adverse health outcomes.AIM To evaluate the relationship between ODCA,we conduct a bibliometric analysis to aid in formulating prevention and treatment strategies.METHODS From 2004 to 2023,articles related to ODCA were selected using the Science Citation Index Expanded from the Web of Science Core Collection.Bibliometric analysis of relevant publications,including countries/regions,institutions,authors,journals,references,and keywords,was conducted using the online bibliometric analysis platforms,CiteSpace,VOSviewer,and bibliometrix.RESULTS Between 2004 and 2023,a total of 1573 articles were published on ODCA.The United States has made leading contributions in this field,with Harvard University emerging as the leading contributor in terms of research output,and Tanofsky being the most prolific author.The J Adolescent Health has shown significant activity in this domain.Based on the results of the keyword and reference analyses,inequality,adverse childhood experiences,and comorbidities have become hot topics in ODCA.Moreover,the impact of balancedrelated behavior and exploration of the biological mechanisms,including the potential role of key adipocytokines and lipokines,as well as inflammation in ODCA,have emerged as frontier topics.CONCLUSION The trend of a significant increase in ODCA publications is expected to continue.The research findings will contribute to elucidating the pathogenic mechanisms of ODCA and its prevention and treatment.

Research Progress and Prospects of Total Factor Productivity in the Construction Industry

The high-quality development of the construction industry fundamentally stems from the significant improvement of total factor productivity.Therefore,it is of crucial significance for promoting the development of the construction industry to a higher level by scientifically and accurately measuring the total factor productivity of the construction industry and deeply analyzing the influencing factors behind it.Based on a comprehensive consideration of research methods and influencing factors,this paper systematically reviews the existing relevant literature on total factor productivity in the construction industry,aiming to reveal the current research development trend in this field and point out potential problems.This effort aims to provide a solid theoretical foundation and valuable reference for further in-depth research,and jointly promote the continuous progress and development of total factor productivity research in the construction industry.

Experimental investigation of the inhibition of deep-sea mining sediment plumes by polyaluminum chloride

Deep-sea sediment disturbance may occur when collecting polymetallic nodules,resulting in the creation of plumes that could have a negative impact on the ecological environment.This study aims to investigate the potential solution of using polyaluminum chloride(PAC)in the water jet.The effects of PAC are examined through a self-designed simulation system for deep-sea polymetallic nodule collection and sediment samples from a potential deep-sea mining area.The experimental results showed that the optimal PAC dose was found to be 0.75 g/L.Compared with the test conditions without the addition of PAC,the presence of PAC leads to a reduction in volume,lower characteristic turbidity,smaller diffusion velocity,and shorter settling time of the plume.This indicates that PAC inhibits the entire development process of the plume.The addition of PAC leads to the flocculation of mm-sized particles,resulting in the formation of cm-sized flocs.The flocculation of particles decreases the rate of erosion on the seabed by around 30%.This reduction in erosion helps to decrease the formation of plumes.Additionally,when the size of suspended particles increases,it reduces the scale at which they diffuse.Furthermore,the settling velocity of flocs(around 10^(-2) m/s)is much higher that of compared to sediment particles(around 10^(-5) m/s),which effectively reduces the amount of time the plume remains in suspension.

Recent Ventures in Interdisciplinary Arctic Research:The ARCPATH Project

This paper celebrates Professor Yongqi GAO's significant achievement in the field of interdisciplinary studies within the context of his final research project Arctic Climate Predictions: Pathways to Resilient Sustainable Societies-ARCPATH(https://www.svs.is/en/projects/finished-projects/arcpath). The disciplines represented in the project are related to climatology, anthropology, marine biology, economics, and the broad spectrum of social-ecological studies. Team members were drawn from the Nordic countries, Russia, China, the United States, and Canada. The project was transdisciplinary as well as interdisciplinary as it included collaboration with local knowledge holders. ARCPATH made significant contributions to Arctic research through an improved understanding of the mechanisms that drive climate variability in the Arctic. In tandem with this research, a combination of historical investigations and social, economic, and marine biological fieldwork was carried out for the project study areas of Iceland, Greenland, Norway, and the surrounding seas, with a focus on the joint use of ocean and sea-ice data as well as social-ecological drivers. ARCPATH was able to provide an improved framework for predicting the near-term variation of Arctic climate on spatial scales relevant to society, as well as evaluating possible related changes in socioeconomic realms. In summary, through the integration of information from several different disciplines and research approaches, ARCPATH served to create new and valuable knowledge on crucial issues, thus providing new pathways to action for Arctic communities.

关于现阶段我国英文期刊办刊模式的思考——以Research等期刊为例

近年来,国内兴起了创办英文科技期刊热潮。本文以此为视角,分析了我国创办英文期刊现状及问题。通过查阅文献和新闻报道,以中国科协和美国科学促进会合作共同创办的英文期刊Research等近年来国内创办的高水平英文新刊为例,详细分析了案例从创刊到快速发展成为高影响力科技期刊的路径,主要包括选择办刊人才、明确办刊定位、组建编委会、邀约优质稿源、加大媒体宣传等,以期为正在筹备创办新刊的同行提供借鉴,也为相关部门决策提供建议参考。

Monitoring discharge from deep-sea mining ships via optical satellite observations

Deep-sea mining may disturb the water column environment,including the surface water and deep-sea,and these disturbances should be carefully treated.Remote sensing provides high-resolution and accurate long-term observations in the area around deep-sea mining.Discharge from mining ships can be identified within few days from satellite observations based on changes in reflectance.A pioneer twomonth experimental deep-sea mining cruise was conducted by The Metal Company in the eastern Pacific Ocean from September 15 to November 17,2022.A report from Greenpeace indicated incidents of surface discharge and leakage during this mining experiment.In this study,satellite observations captured a clear signal over the surface water from September 24 to October 28,indicating the location with discharged water from the mothership.The number of pixels where the potential discharged water was identified in the satellite imagery ranged from 4 to 13.The discharged water was transported by the combined effects of wind and currents,locating continuously to the downwind side of the mothership's mooring location.Remote sensing provides a timely and accurate monitoring system for tracking water discharge during deep-sea mining.

Integrated biomarker response to assess toxic impacts of iron and manganese on deep-sea mussel Gigantidas platifrons under a deep-sea mining activity scenario

Deep-sea mining activities can potentially release metals,which pose a toxicological threat to deep-sea ecosystems.Nevertheless,due to the remoteness and inaccessibility of the deep-sea biosphere,there is insufficient knowledge about the impact of metal exposure on its inhabitants.In this study,deep-sea mussel Gigantidas platifrons,a commonly used deep-sea toxicology model organism,was exposed to manganese(100,1000μg/L)or iron(500,5000μg/L)for 7 d,respectively.Manganese and iron were chosen for their high levels of occurrence within deep-sea deposits.Metal accumulation and a battery of biochemical biomarkers related to antioxidative stress in superoxide dismutase(SOD),catalase(CAT),malondialdehyde(MDA);immune function in alkaline phosphatase(AKP),acid phosphatase(ACP);and energy metabolism in pyruvate kinase(PK)and hexokinase(HK)were assessed in mussel gills.Results showed that deep-sea mussel G.platifrons exhibited a high capacity to accumulate Mn/Fe.In addition,most tested biochemical parameters were altered by metal exposure,demonstrating that metals could induce oxidative stress,suppress the immune system,and affect energy metabolism of deep-sea mussels.The integrated biomarker response(IBR)approach indicated that the exposure to Mn/Fe had a negative impact on deep-sea mussels,and Mn demonstrated a more harmful impact on deep-sea mussels than Fe.Additionally,SOD and CAT biomarkers had the greatest impact on IBR values in Mn treatments,while ACP and HK were most influential for the low-and high-dose Fe groups,respectively.This study represents the first application of the IBR approach to evaluate the toxicity of metals on deep-sea fauna and serves as a crucial framework for risk assessment of deep-sea mining-associated metal exposure.

Can ChatGPT evaluate research quality?

Purpose:Assess whether ChatGPT 4.0 is accurate enough to perform research evaluations on journal articles to automate this time-consuming task.Design/methodology/approach:Test the extent to which ChatGPT-4 can assess the quality of journal articles using a case study of the published scoring guidelines of the UK Research Excellence Framework(REF)2021 to create a research evaluation ChatGPT.This was applied to 51 of my own articles and compared against my own quality judgements.Findings:ChatGPT-4 can produce plausible document summaries and quality evaluation rationales that match the REF criteria.Its overall scores have weak correlations with my self-evaluation scores of the same documents(averaging r=0.281 over 15 iterations,with 8 being statistically significantly different from 0).In contrast,the average scores from the 15 iterations produced a statistically significant positive correlation of 0.509.Thus,averaging scores from multiple ChatGPT-4 rounds seems more effective than individual scores.The positive correlation may be due to ChatGPT being able to extract the author’s significance,rigour,and originality claims from inside each paper.If my weakest articles are removed,then the correlation with average scores(r=0.200)falls below statistical significance,suggesting that ChatGPT struggles to make fine-grained evaluations.Research limitations:The data is self-evaluations of a convenience sample of articles from one academic in one field.Practical implications:Overall,ChatGPT does not yet seem to be accurate enough to be trusted for any formal or informal research quality evaluation tasks.Research evaluators,including journal editors,should therefore take steps to control its use.Originality/value:This is the first published attempt at post-publication expert review accuracy testing for ChatGPT.