bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sleep Traits and Hypothyroidism: A two-sample bidirectional Mendelian Randomization Study
Authors: Shi Yinli , Guo Ming , Wang Yuedan , Lin Yan , Zeng Guoduan , Wang Xu , Li Wenting , Wu Mianhua , Li Bo 
Published: August 2023

Abstract

Background: While the link between hypothyroidism and disturbed sleep patterns has been recognized, the available data are inconsistent, making it difficult to establish causality. This study aimed to investigate the causal relationship between certain sleep traits and hypothyroidism.
Methods: Using publicly available genomewide association study (GWAS) data, we applied linkage disequilibrium score regression (LDSC) to identify genetic associations between hypothyroidism and various sleep traits. Two-sample Mendelian randomization (MR) analysis was then conducted to assess the causal relationship between aberrant sleep features and the risk of hypothyroidism. The IVW, MR-Egger regression, weighted median, and weighted mode methods were used. To detect level polymorphism and outliers, MR-Egger regression and MR-PRESSO methods were employed.
Results: A genetic association between hypothyroidism and nap during the day and getting up in morning (rg=-0.0982, p=0.0007; rg=-0.101, p=0.0001). In addition, a causal relationship between hypothyroidism and sleep duration (IVW, OR 1.5208, 95%CI: 0.1082-0.7304, P=0.0082) and getting up in morning (IVW, OR 1.8375, 95%CI: 0.3717-0.8452, P=4.73×10-7). Furthermore, the reverse MR analysis did not reveal any causal link between hypothyroidism and aberrant sleep traits.
Conclusion: MR analysis demonstrated a causal link between hypothyroidism and certain aberrant sleep traits. Sleep duration should be considered as a potential factor in disease models for improving sleep quality and reducing the risk of hypothyroidism.
High-performanceintelligent Models for Faster Ailments Extraction Over the Big Healthcare Data
Authors: Reddy K Nageswara , Narasimhulu K , K RAJENDRA PRASAD , Kumar Y. Jeevan Nagendra , Basha M Suleman 
Published: August 2023

Abstract
Today, predictions for social use are being made in the growing field of social recommended applications. Twitter is a popular platform because it allows millions of users to express their opinions. One of the most emerging areas of study in social mining for large datasets is healthcare prediction. Applying topic models to healthcare data allows for the derivation of predictive insights. An illness or a symptom of a certain health issue is called an ailment. Condition-based evaluation of millions of tweets is performed using the assistance of ailment topic aspect models. The present topic models, which are Latent Semantic Indexing (LSI), Latent Dirichlet Allocation (LDA), and Probabilistic LSI (PLSI), are used for an evaluation of medical outcomes for any one of the ailments' aspects restrictions. Except for adverse effects evaluations of therapies, the state-of-the-art ailments topic aspect model (ATAM) solves the issues and provides healthcare findings for the essential features of ailments data. In order to provide healthcare outcomes over a huge quantity of medical data, ATAM's scalability efficiency is compromised. This paper presents intelligent and highly computational extended ATAM that operates in a distributed environment to solve the scaling issue. Its technique is developed on a multi-node Hadoop system's distributed environment for scalable results. Experiments have been carried out using lakhs of tweets on health and diseases to highlight comparisons between the currently used high-performance models and those recommended.
A causative role for periarticular skeletal muscle weakness in the progression of joint damage and pain in OA
Authors: Kim Ju-Ryoung , Pham Thi Hong Nhung , Kim Hyun Ah 
Published: August 2023

Abstract
Although OA is regarded as a disease of the articular cartilage, recent research has demonstrated alterations in periarticular muscles that surround the affected joint. Here, we investigated changes in periarticular muscle during the progression of osteoarthritis (OA), as well as the cause-and-effect relationship between muscle weakness and OA, in a mouse model of OA by destabilization of the medial meniscus (DMM). Pathological phenotypes in the periarticular muscles were assessed in the early and late stages of OA by DMM. OA pathology and pain behavior in the mice after DMM induction were examined in response to periarticular muscle weakness induced by multiple rounds of barium chloride injections. The examinations were also performed in myostatin knockout mice with strengthened muscle phenotypes by muscle hypertrophy. Morphological alterations in the TA and quadriceps in DMM mice included variations in muscle-fiber size, aberrant ECM deposition, inflammatory cell infiltration, and decreased muscle mass. Periarticular muscle fibers isolated from DMM mice showed reductions in myoblast cell number and myogenic capacity, as well as the proliferation of satellite cells. DMM + muscle injury mice also showed exacerbated joint degeneration compared to the DMM vehicles. Myostatin knockout mice were characterized by attenuated OA and the complete abrogation of pain behavior after DMM. Our results suggest a causative role for muscle weakness in the progression of OA and pain.
Remnant cholesterol and the risk of diabetic nephropathy progression to end-stage kidney disease in patients with type 2 diabetes mellitus: A longitudinal cohort study
Authors: Zhao Yuancheng , Zou Yutong , Wu Yucheng , Yang Jia , Xiao Xiang , Ju Xuegui , Yang Qing , Lang Yanlin , Liu Kai , Liu Fang 
Published: August 2023

Abstract
Aim
Remnant cholesterol has been investigated as a predictor for the progression of DN in type 1 diabetes mellitus patients, as well as the incidence of DN in type 2 diabetes mellitus (T2DM) patients. This study aimed to evaluate the longitudinal relationship between baseline remnant cholesterol and kidney outcomes using a Chinese T2DM with biopsy-confirmed DN cohort.
Methods
We included 334 patients with T2DM and biopsy-confirmed DN during 2010–2019 West China Hospital T2DM-DN cohort. Remnant cholesterol was defined by Martin-Hopkins equation. Patients were divided into four groups based on the median (IQR) remnant cholesterol concentration at the time of renal biopsy. The kidney outcome was defined as ESKD. The relationship between remnant cholesterol and kidney outcome was analyzed using the Kaplan‒Meier method and Cox regression analysis.
Results
The mean age was 51.1 years, and 235 (70%) were men. During follow-up, a total of 121 (36.2%) patients reached ESKD. The Kaplan‒Meier analysis showed that patients in the highest quartile (quartile 4) group had lower cumulative renal survival (log-rank test, p = 0.033) and shorter median renal survival time [34.0 (26.4–41.6) vs 55.0 (29.8–80.2) months] than patients in the lowest quartile (quartile 1) group. By univariate analysis, the high remnant cholesterol group was associated with a higher risk of progression to ESKD. Moreover, the risk of progression to ESKD in the highest quartile was still 2.857-fold (95% CI 1.305–6.257, p = 0.009) higher than that in the lowest quartile, and one-SD increase of remnant cholesterol was associated with a higher risk (HR = 1.424, 95% CI 1.075–1.886, p = 0.014) of progression to ESKD, after adjusted for confounding factors.
Conclusions
High remnant cholesterol is independently associated with a higher risk of ESKD in patients with T2DM-DN, and it may be a new noninvasive marker of ESKD.
Clinical relevance:
Calculated remnant cholesterol has the advantages of being economical and clinically accessible. Moreover, to our knowledge, there are no longitudinal cohort studies for investigating the risk of progression of T2DM-DN to ESKD. In our study, higher remnant cholesterol was associated with a higher risk of ESKD in patients with T2DM-DN, and it may be a new noninvasive predictor of ESKD.
Influence of Meteorological Variables and Air Pollutants on Fog/ Smog Formation in Seven Major Cities of Indo –Gangetic Plain
Authors: Lakra Kanchan , Avishek Kirti 
Published: August 2023

Abstract

The Indo-Gangetic Plains (IGP) of the Indian subcontinent during winters experience widespread fog episodes. The low visibility is not only attributed to meteorological conditions but also to the increased levels of pollution in the region. The study was carried out for Tier 1 and Tier II cities of the IGP of India, including Kolkata, Amritsar, Patiala, Hisar, Delhi, Patna, and Lucknow. This work analyzes data from a period of 33 years (1990–2023) employing the Mann-Kendall Theil-Sen slope to determine the trends in fog occurrence; the relation between fog and meteorological parameters using multiple linear regressions. Furthermore, the identification of the most relevant fog (visibility) - impacting factors from a set of both meteorological factors and air pollutants using step-wise regression. All cities indicated a trend in the number of foggy days except for Kolkata. The multiple regression analysis reveals relatively low associations between fog occurrences and meteorological factors (30–59%) although the association was stronger when air pollution levels were taken into account (60–91%). Relative Humidity and PM10 has the most influence in formation. Overall, the study provides comprehensive insights into fog trends by incorporating meteorological data and air pollution analysis. The findings highlight the significance of acknowledging both meteorological and pollution factors to understand and mitigate the impacts of reduced visibility. Hence, this information can guide policymakers, urban planners, and environmental management agencies in developing effective strategies to manage fog-related risks and improve air quality.
The potential role of Omentin-1 in Obesity-Related Metabolic Dysfunction-Associated Steatotic Liver Disease: Evidence from translational studies
Authors: Salvoza Noel , Giraudi Pablo , Gazzin Silvia , Bonazza Deborah , Palmisano Silvia , de Manzini Nicolò , Zanconati Fabrizio , Raseni Alan , Sirianni Francesca , Tiribelli Claudio , Rosso Natalia 
Published: August 2023

Abstract

BackgroundObesity, characterized by visceral adipose tissue (VAT) expansion, is closely associated with metabolic dysfunction-associated steatotic liver disease (MASLD). Recent research has highlighted the crucial role of the adipose tissue-liver axis in the development of MASLD to its progressive form, metabolic dysfunction-associated steatohepatitis (MASH). In this study, we investigated the potential role of omentin-1, a novel adipokine expressed by VAT, in obesity-related MASLD pathogenesis.MethodsThroughin silicoanalysis of differentially expressed genes in VAT from obese patients with and without MASH, we identified omentin-1 as a significant candidate. To validate our findings, we measured omentin-1 levels in VAT and plasma of lean controls and obese patients with biopsy-proven MASLD. Additionally, we assessed omentin-1 expression in the VAT of a juvenile mice MASLD model.In vitroandex vivostudies were conducted to investigate the effects of omentin-1 on MASLD-related mechanisms, including steatosis, inflammation, ER stress, and oxidative stress. We also analyzed the impact of D-glucose and insulin on VAT omentin-1 levelsex vivo.ResultsCompared to the lean group, the obese groups exhibited significantly lower VAT and plasma levels of omentin-1. Interestingly, within the MASH group, fibrosis did not affect omentin-1 levels. Likewise, VAT of mice fed with high-fat diet, showing histological signs of MASH showed decreased omentin-1 levels as com-pared to their control diet counterpart.In vitroexperiments on fat-laden human hepatocytes revealed that omentin-1 did not affect steatosis but significantly reduced TNF-α levels, ER stress, and oxidative stress. Similar results were obtained usingex vivoVAT explants from obese patients upon omentin-1 supplementation. Furthermore, omentin-1 decreased the expression ofNF-κBmRNA, bothin vitroandex vivo.Ex vivoVAT explants showed that D-glucose and insulin significantly reduced omentin-1 mRNA expression and protein levels.ConclusionsCollectively, our findings suggest that reduced omentin-1 levels contribute to the development of MASLD. Omentin-1 supplementation mitigates inflammation, ER stress, and oxidative stress, probably via inhibiting the NF-κB pathway and might also play a role in the regulation of glucose and insulin metabolism. Further research is warranted to explore omentin-1 as a potential therapeutic target and/or biomarker for MASLD.
Evaluation of groundwater quality in the Takelsa basin (Northeastern Tunisia) for irrigation and drinking suitability using water quality index
Authors: Dhouioui Sabra , Mzali Houcem , Hafsa Kalthoum 
Published: August 2023

Abstract
Groundwater serves as a vital freshwater resource in various regions worldwide. However, the combination of climate change, population growth, intensive agricultural and industrial practices, as well as the proliferation of drilled water wells, has resulted in declining water table levels and deterioration in physico-chemical water quality. This study aims to investigate the hydrogeochemical parameters (concentration of major ions: magnesium (Mg), calcium (Ca), potassium (K), sodium (Na), bicarbonate (HCO3), nitrate (NO3), sulfate (SO4), and chloride (Cl)), pH, Total Dissolved Solids (TDS), and electric conductivity (EC)) to discern the main geochemical processes and origin of groundwater salinity. The findings from the analysis of groundwater samples indicate the prevalence of Na-Cl and Cl-SO4-Ca facies. The mineralization of water is influenced by the dissolution of evaporites (halite, anhydrite, and gypsum), anthropogenic activities (nitrate contamination), and ion exchange processes. Moreover, the Water Quality Index (WQI) calculated from the percentage of sodium (%Na) and the Sodium Adsorption Ratio (SAR) demonstrates that the groundwater in the Takelsa basin is suitable for irrigation purposes but unsuitable for drinking. Furthermore, detailed geological mapping of the Takelsa basin, along with comprehensive field lithostratigraphic cross-sections, has enabled the following outcomes: 1) determination of a new basin structure; 2) identification of various water reservoirs within the Saouaf formation; and 3) characterization of aquifer geometry and features.
Boundary Negotiating Artifacts to Envision the Desired Research Data Infrastructure toward Reproducibility in Data-Intensive Science
Authors: Jeng Wei , Yang Yu-Ju , Chen Hong-Chun , Yang Yi-Jie , Shih Yi-Ru 
Published: August 2023

Abstract
New data-intensive research paradigms and surging volumes of research data have amplified the need for more effective systems of data curation, management, and sharing. This methodological paper focuses on the development and implementation of a workshop protocol aimed at enabling researchers in various sub-disciplines of data-intensive fields to achieve consensus about data-sharing and reproducibility practices. As such, it addresses a key gap in our understanding of how researchers from those sub-disciplines negotiate and reach consensus on disciplinary practices, which is crucially important to the design of research-data infrastructure and data-management support services. Specifically, we first convened a design-thinking workshop, attended by 17 principal investigators from the field of data-intensive health science, which simulated the identification and solution of real-life research problems in a multidisciplinary context. A key plank of our methodology is its use of boundary-negotiating artifacts as a conceptual model to delineate and analyze the artifacts (e.g., Post-its and other notes) that were created and used during the workshop. This approach provided insights into the development and evolution of common practices in the participants’ workplaces. Then, to validate and extend our methodology, we applied the workshop protocol to two additional case studies, respectively involving 30 academic librarians and 13 criminologists. The results confirm the potential applicability and adaptability of our approach to even more data-intensive disciplines, and provide insights that should be valuable to a range of stakeholders including but not limited to national funders, memory institutions, and research establishments.
Disulfidptosis-related signature to guide the prognosis prediction and treatment in hepatocellular carcinoma
Authors: Zhou Yuanzhi , Chen Wenwen , Zhang Xu , Ma Jiaxin , Li Yarui , Song Yiqun , Lu Guifang , Ren Mudan , Yin Yan , He Shuixiang 
Published: August 2023

Abstract
Disulfidptosis, a new cell death process, is tightly linked to the tumor appearance and development. This research established a five-gene disulfidptosis-related signature (DRS) model and a nomogram to comprehensively assess patient prognosis in HCC patients. We identified two clusters, low DRS score group and high DRS score group, significantly different in overall survival and tumor microenvironment (immunoassay and mutational profile). Moreover, HCC patients in high DRS score group responded less favorably than those in low DRS score group to the current first-line therapies (TACE and sorafenib) but were more sensitive to most standard chemotherapy drugs suggesting that patients who are resistant to first-line medications may benefit from trial use of traditional chemotherapy medicines. As well, in vitro experiments showed that a path for the treatment of HCC patient with a worse prognosis may be provided by the ability of phloretin to cause the death of high SLC7A11 expression HCC cells.
Researching how to match supply and demand for ecosystem services based on multi-source data: A Case Study in the Hexi Region, China
Authors: Zhang Xuebin , Li Xuehong , Wang Ziyang , Liu Yue , Yao Litang 
Published: August 2023

Abstract
To achieve the best management of the ecosystem and sustainable socioeconomic development, it is crucial to clarify the matching relationship between the supply and demand of ecosystem services (ESs). Therefore, four types of ESs were chosen for the Hexi region in this study: food supply, carbon sequestration, water yield, windbreak and sand fixation. This study evaluated the supply-demand and matching relationships between various ecosystem services tapping into the InVEST model, the supply-demand ratio of ecosystem services, and the four-quadrant model. It also analyzed the supply-demand ratio of comprehensive ecosystem services and their cold and hot spots. The findings suggest that (1) the overall ESs supply showed an increasing trend, with a spatial pattern of “high in the southeast and low in the northwest”. The demand for food supply and carbon sequestration services has been increasing annually, while the demand for water production and wind and sand prevention services has been declining. The demand space is characterized by a layout similar to the distribution of population, production and living areas, and ecologically vulnerable areas; (2) From the perspective of quantity matching, with the exception of windbreak and sand fixation services which are in short supply, all others are in a state of oversupply. Regrading spatial matching, all ESs are primarily dominated by low-low spatial matching zones, with large areas concentrated in the northwest desert region; (3) The supply-demand ratio of overall ESs shows a fluctuating upward trend. The proportion of cold spots and sub-cold spots, which are mainly concentrated in the northwest region, accounts for more than 50%, while that of hot spots and sub-hot spots is relatively small and mainly appears in the Qilian Mountains of the southern region and a few oasis areas.
The role of perfusion, grey matter and behavioural phenotypes in the data-driven classification of cognitive syndromes
Authors: Vipin Ashwati , Lee Bernett Teck Kwong , Kumar Dilip , Soo See Ann , Leow Yi Jin , Ghildiyal Smriti , En Faith Phemie Lee Hui , Hilal Saima , Kandiah Nagaendran 
Published: August 2023

Abstract
BACKGROUND
The use of structural and perfusion brain imaging in combination with behavioural information in the prediction of cognitive syndromes using a data-driven approach remains to be explored. Here, we thus examined the contribution of brain structural and perfusion imaging and behavioural features to the existing classification of cognitive syndromes using a data-driven approach.
METHODS
Study participants belonged to the community-based Biomarker and Cognition Cohort Study in Singapore who underwent neuropsychological assessments, structural-functional MRI and blood biomarkers. Participants had a diagnosis of cognitively normal (CN), subjective cognitive impairment (SCI), mild cognitive impairment (MCI) and dementia. Cross-sectional structural and cerebral perfusion imaging, behavioural scale data including mild behaviour impairment checklist, Pittsburgh Sleep Quality Index and Depression, Anxiety and Stress scale data were obtained.
RESULTS
373 participants (mean age 60.7 years; 56% female sex) with complete data were included. Principal component analyses demonstrated that no single modality was informative for the classification of cognitive syndromes. However, multivariate glmnet analyses revealed a specific combination of frontal perfusion and temporo-frontal grey matter volume were key protective factors while severity of mild behaviour impairment interest sub-domain and poor sleep quality were key at-risk factors contributing to the classification of CN, SCI, MCI and dementia (p < 0.0001). Moreover, the glmnet model showed best classification accuracy in differentiating between CN and MCI cognitive syndromes (AUC = 0.704; sensitivity = 0.698; specificity = 0.637).
CONCLUSIONS
Brain structure, perfusion and behavioural features are important in the classification of cognitive syndromes and should be incorporated by clinicians and researchers. These findings illustrate the value of using multimodal data when examining syndrome severity and provide new insights into how cerebral perfusion and behavioural impairment influence classification of cognitive syndromes.
Response of Some Sugar beets cultivars to Organic fertilizers under South Sinai Conditions.
Authors: Abdelaziz Mahmoud Abdelsalam 
Published: August 2023

Abstract
Background: Sugar beets-winter is the primary sugar planting technique in arid Egypt, This study's major goal was to increase the growth of sugar beetroot cultivars in an arid region by applying organic fertilizers. It will be easier to increase crop performance under salinity if we have a superior grasp in terms of the molecular and physiological mechanisms driving salt acceptance.
Results: The sustainability of sugar beets, a novel crop in this region, is still unknown. Consequently, a field experiment four sugar beets cultivars (Casupia-Salama-Sahar and Faten) under three organic fertilization (0, 11.905, and 23.810 ton/ha). Field data were used to incorporate the capacity of 17 morphological, yield-related, and physiological features as indicators for detecting salt tolerant, net ecosystem economic advantages, and economic benefits.
Conclusions: Salama cultivar significantly surpassed other studied cultivars by 8.5%. The organic fertilization considerable impact on application rate, facilitate the elements and reduce the damage of the salts. Taking into account modifications to the organic fertilization traces, the Salama cultivar with (23.810 ton/ha), which produced the greatest net benefits to the ecosystem in terms of both economic and ecological advantages, and a 167 % Salama greater net economic benefits to the ecosystem than with the status quo Casupia cultivar and Organic Fertilization application rate (0 ton/ha), employing a comprehensive approach that combines Salama cultivar and Organic Fertilization application contributes to improvements sustainable sugar beets production systems in the El-Tur area, South Sinai, Egypt and places with comparable ecological characteristics.