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In recent years, "lying flat" has been enthusiastically pursued by young people in China, and it is worth studying its cause and social impact. However, there is still a lack of measurement tools that can scientifically evaluate an individual's tendency for "lying flat." In this study, a 6-item "Lying Flat" Tendency Scale was developed and cross-validated for reliability and validity in different samples from China. The findings demonstrated that the scale showed good internal consistency in three different samples; both exploratory factor analysis and confirmatory factor analysis supported the single dimension model of the scale, indicating good construct validity; the LFTS total score was negatively correlated with the satisfaction of basic psychological needs, happiness index, and positive emotions, and was positively correlated with negative emotions; simultaneously, the LFTS total score was also significantly positively correlated with the choice of "lying flat" behavior in the simulated situation. These results show that the scale has good validity and reliability, and can be used as a measuring tool for subsequent empirical research. It will help to promote the development of empirical research on the phenomenon of "lying flat", help to understand the causes and consequences of "lying flat" more deeply, and also help to find effective ways to help young people break out of the "lying flat" dilemma. [ABSTRACT FROM AUTHOR]

Background: Progranulin (GRN) mutations in frontotemporal dementia (FTD) have been less frequently reported in China than in Western countries. Objective: This study reports a novel GRN mutation and summarizes the genetic and clinical features of patients with GRN mutations in China. Methods: Comprehensive clinical, genetic, and neuroimaging examinations were conducted on a 58-year-old female patient diagnosed with semantic variant primary progressive aphasia. A literature review was also conducted and clinical and genetic features of patients with GRN mutations in China were summarized. Results: Neuroimaging revealed marked lateral atrophy and hypometabolism in the left frontal, temporal, and parietal lobes. The patient was negative for pathologic amyloid and tau deposition by positron emission tomography. A novel heterozygous 45-bp deletion (c.1414-14_1444delCCCTTCCCCGCCAGGCTGTGTGCTGCGAGGATCGCCAGCACTGCT) was detected by whole-exome sequencing of the patient's genomic DNA. Nonsense-mediated mRNA decay was presumed to be involved in the degradation of the mutant gene transcript. The mutation was deemed pathogenic according to American College of Medical Genetics and Genomics criteria. The patient had a reduced plasma GRN level. In the literature, there were reports of 13 Chinese patients – mostly female – with GRN mutations; the prevalence was 1.2% –2.6% and patients mostly had early disease onset. Conclusion: Our findings expand the mutation profile of GRN in China, which can aid the diagnosis and treatment of FTD. [ABSTRACT FROM AUTHOR]

What is Known and Objective? In China, patients with drug-induced liver injury (DILI) are commonly treated with one or more types of hepatoprotective drugs, despite a lack of evidence. We performed this study to investigate the association between the treatment pattern of DILI, including withdrawal of suspected drugs and use of hepatoprotective drugs, and recovery following DILI. Methods. A retrospective study was conducted at a tertiary hospital in Central China. Data of patients with a diagnosis of DILI hospitalized between January 2015 and December 2020 were collected through the Electronic Medical Records System. We excluded cases that did not meet the biochemical criteria of DILI and had a Roussel Uclaf Causality Assessment Method score of less than 3. Univariate and multivariate logistic regression models were used to analyze the association between treatment patterns and clinical outcomes. Results and Discussion. In total, 699 patients were included. Suspected drugs were discontinued in 619 patients (88.6%). 693 patients (99.1%) were treated with hepatoprotective drugs, among whom only 14.7% patients received monotherapy with hepatoprotective drugs. Recovery following DILI was seen in 593 cases (84.8%). By multivariate analysis, the number of hepatoprotective drugs combined did not show significance (p = 0.363), while the withdrawal of suspected drugs was associated with recovery following DILI (p = 0.015). What is New and Conclusion. The withdrawal of suspected drugs is associated with the recovery following DILI, and hepatoprotective drug combinations do not contribute to better outcomes than monotherapy. The findings indicate that DILI patients should stop suspected drugs as soon as possible and the combination therapy of hepatoprotective drugs is unnecessary. [ABSTRACT FROM AUTHOR]

Background: Seeking online health information (OHI) has become a common practice globally. The information seekers could face health risks if they are not proficient in OHI literacy. The OHI-seeking behaviors and skills of Chinese college students, the largest proportion of college students in the world, are understudied. This study was aimed to describe OHI-seeking behaviors and skills of college students in Guangdong, China.Methods: College students in the Guangdong province with OHI-seeking experience were invited via WeChat, QQ, and Sina Weibo using QR code posters and flyers for participation in this online anonymized questionnaire-based study. Data on demographics, OHI literacy, information resources, search approaches, and behaviors were collected. The relationship between perceived OHI literacy and high-risk behaviors was investigated by bivariate logistic regression analysis.Results: Respondents were 1203 college students with a mean age of 20.6 years, females (60.2%), and undergraduates (97.2%). They sought health information via websites (20.3%), WeChat (2.6%), or both (77.1%). Baidu was the main search engine, and baike.baidu.com (80.3%), Zhihu.com (48.4%), and Zhidao.baidu.com (35.8%) were top three among 20 searched websites for information about self-care (80.7%), general health (79.5%), disease prevention (77.7%), self-medication (61.2%), family treatment (40.9%), drugs (37.7%), western medications (26.6%), hospitals (22.7%), physicians (21.4%), and Traditional Chinese Medicine (15.6%). Despite most respondents (78%) lacked confidence in the evidence quality and satisfaction with the results, only 32.4% further consulted doctors. Many (> 50%) would recommend the retrieved information to others. About 20% experienced hacking/Internet fraud. Cronbach's alpha for the internal consistency of OHI literacy was 0.786. Bivariate logistic regression analysis showed that students who believed they can judge the evidence level of OHI were more likely to self-diagnose (OR = 2.2, 95%CI, 1.6-3.1) and look for drug usage (OR = 3.1, 95%CI, 1.9-5.0).Conclusions: This study reveals Chinese college students' heavy reliance on OHI to manage their own and others' health without sufficient knowledge/skills to identify misinformation and disinformation. The apparent risky information-seeking behaviors of Chinese college students warrant the provision of regulated, accurate, and actionable health information; assurance of cybersecurity; and health information literacy promotion in colleges by concerned authorities. [ABSTRACT FROM AUTHOR]

• A deep learning algorithm is used to build a comprehensive drought monitoring model. • Multi-source remote sensing data is processed as input data. • The comprehensive drought model has good applicability in the monitoring of meteorological drought and agricultural drought. • The model successfully monitored a drought process in Henan Province, China. • This study provides a new method for the comprehensive assessment of regional drought. Drought is a popular scientific issue in global climate change research. Accurate monitoring of drought has important implications for the sustainable development of regional agriculture in the context of increasingly complex global climate change. Deep learning is a widely used technique in the field of artificial intelligence. However, ongoing on drought monitoring using deep learning is relatively scarce. In this paper, the various hazard factors in drought development were comprehensively considered based on satellite data including Moderate Resolution Imaging Spectroradiometer (MODIS) and tropical rainfall measuring mission (TRMM) as multi-source remote sensing data. By using the deep learning technique, a comprehensive drought monitoring model was constructed and tested in Henan Province of China as an example. The results showed that the comprehensive drought model has good applicability in the monitoring of meteorological drought and agricultural drought. There was a significant positive correlation between the drought indicators of the model output and the comprehensive meteorological drought index (CI) measured at the site scale. The consistency rate of the drought grade of the two models was 85.6% and 79.8% for the training set and the test set, respectively. The correlation coefficient between the drought index of the model and the standard precipitation evapotranspiration index (SPEI) was between 0.772 and 0.910 (P < 0.01), which indicated a strong level of significance. The correlation coefficient between the drought index of the model and the soil relative moisture at a 10 cm depth was greater than 0.550 (P < 0.01), and there was a good correlation between them. This study provides a new method for the comprehensive assessment of regional drought. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to explore snacking behavior and perspectives on healthy and unhealthy food choices among adolescents in Mainland China.Design/methodology/approach Four focus-group interviews were conducted. Altogether 24 participants were recruited in Changsha, a second-tier city in China, through a convenience sampling process. They were asked to report their snacking behaviors, identify whether certain snacks are healthy or unhealthy and elaborate on factors affecting food choices.Findings Snacking was prevalent among the participants. The most frequently consumed snacks included fruit, milk and instant noodles. Participants’ evaluations for the healthiness of foods were based on the actual nutritional values of those foods, the effects on growth and body weight and word-of-mouth. Choice of snack was driven mainly by taste, image, convenience and health consciousness.Research limitations/implications The finding was based on a non-probability sample. The paper also did not explore the contexts where snacks were consumed.Practical implications Parents can make healthy snacks more accessible at home and at schools. Educators can teach adolescents how to read food labels. Schools can increase the availability of healthy snacks on campus. Social marketers can promote healthy snacks by associating them with fun and high taste.Originality/value This is the first paper on snacking behaviors among adolescents conducted in a second-tier city in China using focus-group methodology. [ABSTRACT FROM AUTHOR]

• Satellite LAI scheme can provide more accurate vegetation dynamic information. • Satellite LAI scheme improved LST simulation in Noah-MP land surface model. • Mechanism of LAI on LST simulation was revealed by energy budget analysis in model. Leaf area index (LAI) is essential for modelling the land surface temperature (LST) and related energy budget in the land surface models (LSMs). Due to the lack of a parameterization scheme based on satellite LAI data, it is unclear whether satellite LAI data can improve the performance of Noah with multi-parameterization (Noah-MP) LSM to model LST in China land data assimilation system (CLDAS). Here, by using satellite LAI data reconstructed by the advanced deep learning method, we established a new vegetation scheme based on satellite data for the Noah-MP LSM in the CLDAS. We quantitatively evaluated simulation effects of different vegetation schemes including the parameter table scheme (TAB), the dynamic vegetation scheme (DVEG), and the satellite LAI data scheme (OBS), on modelling LAI, LST and their related energy budget in China from 2016 to 2018. We found that except for the cropland, the LAI of the vegetation in growing season observed by satellite was lower than that simulated by the Noah-MP LSM. Validations based on the automatic weather stations in the vegetation-covered area showed that compared with the TAB and DVEG scheme, the OBS scheme improved the negative bias and high unbiased root mean square error (ubRMSE) of simulated LST. Compared with the TAB and DVEG scheme, the optimal improvements of the OBS scheme for annual mean bias and annual mean ubRMSE were 0.32 °C and 0.17 °C, respectively. We further revealed the mechanism of LAI on LST simulation in the Noah-MP LSM by decomposed temperature metric method. With the adoption of the new satellite LAI-based scheme, the absorbed radiation (SW), sensible heat flux (H), latent heat flux (LE), and ground heat flux (G) simulated by the Noah-MP LSM tend to change in different directions, leading to an overall increase in the net energy absorbed by the surface, which is consistent with the LST changes. The LAI changes of dense vegetation affect the LST simulation mainly through the competition of the absorbed shortwave radiation and turbulent heat fluxes. Due to the influence of exposed soil, the LAI changes of sparse vegetation mainly affect the LST simulation mainly through the interaction of the absorbed shortwave radiation and ground heat flux. Our study highlighted that the application of satellite LAI data has the potential to improve simulations of multiple land surface processes in the Noah-MP LSM. [ABSTRACT FROM AUTHOR]

Land cover type is a key parameter for simulating surface processes in many land surface models (LSMs). Currently, the widely used global remote sensing land cover products cannot meet the requirements of LSMs for classification systems, physical definition, data accuracy, and space-time resolution. Here, a new fusion method was proposed to generate land cover data for LSMs by fusing multi-source remote sensing land cover data, which was based on improving Dempster-Shafer evidence theory with mathematical models and knowledge rules optimization. The new method has the ability to deal with seriously disagreement information, thereby improving the robustness of the theory. The results showed the new method can reduce the disagreement between input data and realized the conversion of multiple land cover classification systems to into a single land cover classification system. China Fusion Land Cover data (CFLC) in 2015 generated by the new method maintained the classification accuracy of the China land use map (CNLULC), which is based on visual image interpretation and further enriched land cover classes of input data. Compared with Geo-Wiki observations in 2015, the overall accuracy for CFLC is higher than other two global land cover data. Compared with the observations, the 0–10 cm soil moisture simulated by the CFLC in Noah–MP LSM during the growing season in 2014 had better performance than that simulated by initial land cover data and MODIS land cover data. Our new method is highly portable and generalizable to generate higher quality land cover data with a specific land cover classification system for LSMs by fusing multiple land cover data, providing a new approach to land cover mapping for LSMs. [ABSTRACT FROM AUTHOR]

Riverine water and sediment discharge drive global material circulation and energy transfer, and they are crucial to the biogeochemical cycle. We investigated the changes in water-sediment fluxes in six major rivers from north to south in China from the mid-1950s to 2020 under the influence of climate change and human activities, and quantified the contributions of these specific influencing factors to water-sediment flux changes. Results showed that streamflow of the Songhua, Liao and Yellow rivers decreased significantly (p < 0.05). The sediment load of all rivers reduced significantly (p < 0.01) except the Songhua River. Streamflow or sediment fluxes to the oceans have increased or stabilized since around 2000, and the terrestrial sediment yielding center in China has shifted southward from the Yellow River to the Yangtze and Pearl rivers. The contribution of precipitation to the streamflow and sediment load changes decreased from north to south across the six rivers. From the mid-1950s to 2020, the underlying land surface change was the dominant contributor (>70 %) to reducing streamflow in the Songhua and Yellow rivers, while climate change (>50 %) was responsible for decreased streamflow in the Liao and Huai rivers. The sediment load reduction of the six rivers was attributed mainly to human activities. Among them, dam construction, human water consumption and catchment land surface change have reduced the total sediment load into the sea by 49 %, 25 % and 19 %, respectively. These results highlight that north-south variability in water and sediment flux are driven by both natural and anthropogenic forcing agents., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)