bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning to differentiate pulmonary hypertension due to left heart disease from pulmonary arterial hypertension
Authors: Swinnen Katleen , Verstraete Kenneth , Baratto Claudia , Hardy Laura , De Vos Maarten , Topalovic Marko , Claessen Guido , Quarck Rozenn , Belge Catharina , Vachiery Jean-Luc , Janssens Wim , Delcroix Marion 
Published: July 2023

Background and aimsPulmonary hypertension due to left heart disease (PH-LHD) is the most frequent form of PH. As differential diagnosis with pulmonary arterial hypertension (PAH) has therapeutic implications, it is important to accurately and noninvasively differentiate PH-LHD from PAH before referral to PH centres. The aim was to develop and validate a machine learning (ML) model to improve prediction of PH-LHD in a population of PAH and PH-LHD patients.MethodsNoninvasive PH-LHD predictors from 172 PAH and 172 PH-LHD patients from the PH centre database at the University Hospitals of Leuven (Leuven, Belgium) were used to develop an ML model. The Jacobs score was used as performance benchmark. The dataset was split into a training and test set (70:30) and the best model was selected after 10-fold cross-validation on the training dataset (n=240). The final model was externally validated using 165 patients (91 PAH, 74 PH-LHD) from Erasme Hospital (Brussels, Belgium).ResultsIn the internal test dataset (n=104), a random forest-based model correctly diagnosed 70% of PH-LHD patients (sensitivity: n=35/50), with 100% positive predicted value, 78% negative predicted value and 100% specificity. The model outperformed the Jacobs score, which identified 18% (n=9/50) of the patients with PH-LHD without false positives. In external validation, the model had 64% sensitivity at 100% specificity, while the Jacobs score had a sensitivity of 3% for no false positives.ConclusionsML significantly improves the sensitivity of PH-LHD prediction at 100% specificity. Such a model may substantially reduce the number of patients referred for invasive diagnostics without missing PAH diagnoses.
Staying in or out? COVID-19-induced healthcare utilization avoidance and associated socio-demographic factors in rural India
Authors: Oduro Michael Safo , Peprah Prince , Morgan Anthony Kwame , Agyemang-Duah Williams 
Published: July 2023

Abstract
Background
Although evidence on healthcare utilization avoidance during COVID-19 pandemic is emerging, such knowledge is limited in rural settings. An effective policy to the COVID-19 shocks and stresses in rural settings require empirical evidence to inform the design of health policies and programmes. To help overcome this evidence gap and also contribute to policy decisions, this study aimed at examining COVID-19-induced healthcare utilization avoidance and associated factors in rural India.

Methods
This study used the third-round data from the COVID-19-Related Shocks in Rural India survey conducted between 20-24 September, 2020 across six states. The outcome variable considered in this study was COVID-19-induced healthcare utilization avoidance. Multivariable Binary Logistic Regression Model via Multiple Imputation was used to assess the factors influencing COVID-19-induced healthcare utilization avoidance.

Results
Data on 4,682 respondents were used in the study. Of this, the prevalence of COVID-19-induced healthcare utilization avoidance was 15.5% in rural India across the six states. After adjusting for relevant covariates, participants from the Bihar State have significantly higher likelihood of COVID-19-induced healthcare utilization avoidance compared to those from the Andhra Pradesh. Also, participants whose educational level exceeds high school, those who use government hospital/clinic, engage in daily wage labour in agriculture have significantly higher odds of COVID-19-induced healthcare utilization avoidance compared to their counterparts.

Conclusion
Our study revealed that state of residence, type of health facility used, primary work activity and educational level were associated with COVID-19-induced healthcare utilization avoidance in rural India. The findings suggest that policy makers and public health authorities need to formulate policies and design interventions that acknowledge socioeconomic and demographic factors that influence healthcare use avoidance.
Serum IL-23 significantly decreased in obese patients with psoriatic arthritis six months after a structured weight loss intervention
Authors: Landgren A. J. , Jonsson C. A. , Bilberg A. , Eliasson B. , Torres L. , Dehlin M. , Jacobsson L. T. H. , Gjertsson I. , Larsson I. , Klingberg E. 
Published: July 2023

Abstract
Introduction
Patients with psoriatic arthritis (PsA) are frequently obese. We have previously shown decreased disease activity in patients with PsA with a body mass index (BMI) ≥ 33 kg/m2 following weight loss treatment with Very Low Energy Diet (VLED), resulting in a median weight loss of 18.6% at six months (M6) after baseline (BL). In this study we assessed the effects of VLED on cytokines and adipokines at M6 in the same patients with PsA and controls (matched on sex, age and weight).

Methods
VLED (640 kcal/day) during 12 or 16 weeks, depending on BL BMI < 40 or ≥ 40 kg/m2, was taken and followed by an energy-restricted diet. Cytokines and adipokines were measured with Magnetic Luminex Assays at BL and M6.

Results
Serum interleukin (IL)-23, (median (interquartile range) 0.40 (0.17–0.54) ng/mL vs. 0.18 (0.10–0.30) ng/mL, p < 0.001) and leptin (26.28 (14.35–48.73) ng/mL vs. 9.25 (4.40–16.24) ng/mL, p < 0.001) was significantly decreased in patients with PsA. Serum total (tot)-adiponectin and high molecular weight (HMW) adiponectin increased significantly. Similar findings were found in controls. Also, in patients with PsA, ∆BMI was positively correlated with ∆IL-23 (rS = 0.671, p < 0.001). In addition, significant positive correlations were found between ΔBMI and ΔDisease Activity Score (DAS28CRP), ΔCRP, Δtumor necrosis factor (TNF)-α, ΔIL-13, ∆IL-17 and Δleptin, and negative correlations between ΔBMI and Δtot-adiponectin.

Conclusions
Weight loss was associated with decreased levels of leptin and cytokines, in particular IL-23. These findings may partly explain the anti-inflammatory effect of weight reduction in PsA.

Trial registration
ClinicalTrials.gov identifier: NCT02917434, registered on September 21, 2016, retrospectively registered.
Machine learning for predicting diabetes risk in western China adults
Authors: Li Lin , Cheng Yinlin , Ji Weidong , Liu Mimi , Hu Zhensheng , Yang Yining , Wang Yushan , Zhou Yi 
Published: July 2023

Abstract
Objective
Diabetes mellitus is a global epidemic disease. Long-time exposure of patients to hyperglycemia can lead to various type of chronic tissue damage. Early diagnosis of and screening for diabetes are crucial to population health.

Methods
We collected the national physical examination data in Xinjiang, China, in 2020 (a total of more than 4 million people). Three types of physical examination indices were analyzed: questionnaire, routine physical examination and laboratory values. Integrated learning, deep learning and logistic regression methods were used to establish a risk model for type-2 diabetes mellitus. In addition, to improve the convenience and flexibility of the model, a diabetes risk score card was established based on logistic regression to assess the risk of the population.

Results
An XGBoost-based risk prediction model outperformed the other five risk assessment algorithms. The AUC of the model was 0.9122. Based on the feature importance ranking map, we found that hypertension, fasting blood glucose, age, coronary heart disease, ethnicity, parental diabetes mellitus, triglycerides, waist circumference, total cholesterol, and body mass index were the most important features of the risk prediction model for type-2 diabetes.

Conclusions
This study established a diabetes risk assessment model based on multiple ethnicities, a large sample and many indices, and classified the diabetes risk of the population, thus providing a new forecast tool for the screening of patients and providing information on diabetes prevention for healthy populations.
The efficacy of prophylactic metoclopramide in preventing nausea and vomiting in patients with acute pain treated with intravenous tramadol: a randomized double-blinded, placebo-controlled trial
Authors: Sriwiset Haruethai , Lokeskrawee Thanin , Patumanond Jayanton , Wongyikul Pakpoom , Phinyo Phichayut 
Published: July 2023

Abstract
Objective
To examine the clinical efficacy of prophylactic metoclopramide in reducing the incidence of nausea and vomiting in emergency department (ED) patients with acute pain who were treated with intravenous tramadol.

Results
We conducted a single-center randomized, double-blinded, placebo-controlled trial. A total of 99 ED patients presented with acute pain were recruited. Sixty-four patients were randomized, 31 patients in the treatment arm and 33 in the control arm. Overall, there were no significant differences in baseline characteristics between treatment arm and control arm. Only one patient within each arm reported having nausea symptom. No patients reported vomiting episode. There was no statistically significant difference in the proportion of patients with nausea or vomiting symptoms between the two groups (3.2% in the treatment arm vs. 3.0% in the control arm, p = 1.000). The administration of prophylactic metoclopramide may not provide additional benefit in reducing the occurrence of nausea and/or vomiting episode in ED patients with acute pain treated with intravenous tramadol.
Trial registration Randomized clinical trial TCTR20220525001; registration date: 21 October 2021. Retrospectively registered.
Acquired SERPINC1/antithrombin deficiency during oral contraceptive consumption: a case report
Authors: Denora D. , Di Rosa M. V. , Altamura N. , Pellicori F. , Vinci P. , Sisto U. G. , Spanò F. , Di Girolamo F. G. , Fiotti N. , Biolo G. 
Published: July 2023

Abstract
Background
SERPINC1 is a glycoprotein that regulates blood coagulation. SERPINC1 congenital or acquired deficiencies represent a significant risk factor for thromboembolic disease. SERPINC1 acquired defects are observed in very few cases and can occur in many clinical conditions such as treatment with l-asparaginase or oral contraceptive (particularly estrogen derivatives), but these conditions are not routinely investigated.

Case presentation
A 50-year-old Caucasian woman who took gestodene 75 µg/ethinylestradiol 20 µg as oral contraceptive, was sent to our thrombophilia clinic because, on thrombophilia testing, a reduction of SERPINC1 (74%) and a slight increase in circulating D-dimer and homocysteine were found. We investigated triggers of such SERPINC1 reduction, and identified gestodene 75 µg/ethinylestradiol 20 µg use as the most likely candidate. Two months after the discontinuation of the oral contraceptive, SERPINC1 value returned to normal (92%) and D-dimer and homocysteine were normalized.

Conclusion
Each patient has a different sensitivity to contraceptive use. Genetic (or epigenetic) regulation of anticoagulant proteins might account for a different rate of consumption of anticoagulant proteins as oral contraceptives and probably determine the susceptibility to thrombotic events.
PPARγ-dependent hepatic macrophage switching acts as a central hub for hUCMSC-mediated alleviation of decompensated liver cirrhosis in rats
Authors: Yao Yunqi , Zhang Lin , Cheng Fuyi , Jiang Qingyuan , Ye Yixin , Ren Yushuang , He Yuting , Su Dongsheng , Cheng Lin , Shi Gang , Dai Lei , Deng Hongxin 
Published: July 2023

Abstract
Background
Decompensated liver cirrhosis (DLC), a terminal-stage complication of liver disease, is a major cause of morbidity and mortality in patients with hepatopathies. Human umbilical cord mesenchymal stem cell (hUCMSC) therapy has emerged as a novel treatment alternative for the treatment of DLC. However, optimized therapy protocols and the associated mechanisms are not entirely understood.

Methods
We constructed a DLC rat model consistent with the typical clinical characteristics combined use of PB and CCL4. Performing dynamic detection of liver morphology and function in rats for 11 weeks, various disease characteristics of DLC and the therapeutic effect of hUCMSCs on DLC in experimental rats were thoroughly investigated, according to ascites examination, histopathological, and related blood biochemical analyses. Flow cytometry analysis of rat liver, immunofluorescence, and RT-qPCR was performed to examine the changes in the liver immune microenvironment after hucMSCs treatment. We performed RNA-seq analysis of liver and primary macrophages and hUCMSCs co-culture system in vitro to explore possible signaling pathways. PPARγ antagonist, GW9662, and clodronate liposomes were used to inhibit PPAR activation and pre-exhaustion of macrophages in DLC rats’ livers, respectively.

Results
We found that changing the two key issues, the frequency and initial phase of hUCMSCs infusion, can affect the efficacy of hUCMSCs, and the optimal hUCMSCs treatment schedule is once every week for three weeks at the early stage of DLC progression, providing the best therapeutic effect in reducing mortality and ascites, and improving liver function in DLC rats. hUCMSCs treatment skewed the macrophage phenotype from M1-type to M2-type by activating the PPARγ signaling pathway in the liver, which was approved by primary macrophages and hUCMSCs co-culture system in vitro. Both inhibition of PPARγ activation with GW9662 and pre-exhaustion of macrophages in DLC rats’ liver abolished the regulation of hUCMSCs on macrophage polarization, thus attenuating the beneficial effect of hUCMSCs treatment in DLC rats.

Conclusions
These data demonstrated that the optimal hUCMSCs treatment effectively inhibits the ascites formation, prolongs survival and significantly improves liver structure and function in DLC rats through the activation of the PPARγ signaling pathway within liver macrophages. Our study compared the efficacy of different hUCMSCs infusion regimens for DLC, providing new insights on cell-based therapies for regenerative medicine.
The product quality inspection scheme based on software-defined edge intelligent controller in industrial internet of things
Authors: Hu Pengfei , He Chunming , Zhu Yiming , Li Tianhui 
Published: July 2023

AbstractThe Industrial Internet of Things (IIoT) enables the improvement of the productivity and intelligent level of factory. The procedure of product quality inspection has generally adopted machine intelligence algorithms instead of manual operation to improve efficiency. In this paper, we propose a product quality inspection system scheme based on software-defined edge intelligent controller (SD-EIC). By adopting the software definition and resource virtualization technologies, the hardware platform of SD-EIC is designed to support the real-time control tasks and non-real-time edge computing tasks at the same time. To this end, we propose the scheme and architecture of product quality inspection system based on SD-EIC. Multiple virtual controllers and virtual edge computing nodes are constructed on a set of SD-EIC hardware platform to realize the integrated deployment of the real-time control for terminal devices and the AI model reasoning of product defect recognition algorithm based on machine vision respectively. In addition, the management and control scheme of product quality inspection system based on industrial information model is proposed. By constructing the semantic-based digital twin information model of terminal device, the flexible adjustment and parameter configuration of terminal device are realized to meet the demands of flexible production and manufacturing. The proposed product quality inspection system solution can effectively improve the utilization of hardware resources and the efficiency of product quality inspection, and reduce the overall deployment cost of the system. It can flexibly adapt to product diversity and different industrial scenarios.
Soaring migrants flexibly respond to sea-breeze in a migratory bottleneck: using first derivatives to identify behavioural adjustments over time
Authors: Becciu Paolo , Troupin David , Dinevich Leonid , Leshem Yossi , Sapir Nir 
Published: July 2023

Abstract
Background
Millions of birds travel every year between Europe and Africa detouring ecological barriers and funnelling through migratory corridors where they face variable weather conditions. Little is known regarding the response of migrating birds to mesoscale meteorological processes during flight. Specifically, sea-breeze has a daily cycle that may directly influence the flight of diurnal migrants.

Methods
We collected radar tracks of soaring migrants using modified weather radar in Latrun, central Israel, in 7 autumns between 2005 and 2016. We investigated how migrating soaring birds adjusted their flight speed and direction under the effects of daily sea-breeze circulation. We analysed the effects of wind on bird groundspeed, airspeed and the lateral component of the airspeed as a function of time of day using Generalized Additive Mixed Models. To identify when birds adjusted their response to the wind over time, we estimated first derivatives.

Results
Using data collected during a total of 148 days, we characterised the diel dynamics of horizontal wind flow relative to the migration goal, finding a consistent rotational movement of the wind blowing towards the East (morning) and to the South-East (late afternoon), with highest crosswind speed around mid-day and increasing tailwinds towards late afternoon. Airspeed of radar detected birds decreased consistently with increasing tailwind and decreasing crosswinds from early afternoon, resulting in rather stable groundspeed of 16–17 m/s. In addition, birds fully compensated for lateral drift when crosswinds were at their maximum and slightly drifted with the wind when crosswinds decreased and tailwinds became more intense.

Conclusions
Using a simple and broadly applicable statistical method, we studied how wind influences bird flight through speed adjustments over time, providing new insights regarding the flexible behavioural responses of soaring birds to wind conditions. These adjustments allowed the birds to compensate for lateral drift under crosswind and reduced their airspeed under tailwind. Our work enhances our understanding of how migrating birds respond to changing wind conditions during their long-distance journeys through migratory corridors.
Acoustic accelerometer transmitters and their growing relevance to aquatic science
Authors: Lennox Robert J. , Eldøy Sindre H. , Dahlmo Lotte S. , Matley Jordan K. , Vollset Knut Wiik 
Published: July 2023

AbstractThere has recently been great interest in the use of accelerometers onboard electronic transmitters to characterise various aspects of the ecology of wild animals. We review use cases and outline how these tools can provide opportunities for studying activity and survival, exercise physiology of wild animals, the response to stressors, energy landscapes and conservation planning tools, and the means with which to identify behaviours remotely from transmitted data. Accelerometer transmitters typically send data summaries to receivers at fixed intervals after filtering out static acceleration and calculating root-mean square error or overall dynamic body action of 2- or 3-axis acceleration values (often at 5–12.5 Hz) from dynamic acceleration onboard the tag. Despite the popularity of these transmitters among aquatic ecologists, we note that there is wide variation in the sampling frequencies and windows used among studies that will potentially affect the ability to make comparisons in the future. Accelerometer transmitters will likely become increasingly popular tools for studying finer scale details about cryptic species that are difficult to recapture and hence not suitable for studies using data loggers. We anticipate that there will continue to be opportunities to adopt methods used for analysing data from loggers to datasets generated from acceleration transmitters, to generate new knowledge about the ecology of aquatic animals.
Effect of grain size on amorphization mechanism and kinetics of bridgmanite in shocked meteorites
Authors: Nishi Masayuki , Jin Si , Kawano Katsutoshi , Kuwahara Hideharu , Yamada Akihiro , Kawaguchi Shogo , Mori Yuki , Sakaiya Tatsuhiro , Kondo Tadashi 
Published: July 2023

AbstractBridgmanite formation and amorphization in shocked meteorites constrain the pressure and temperature conditions during planetary impact. However, the effect of the bridgmanite grain size on its amorphization kinetics is still unclear. Here, the amorphization mechanism and kinetics of fine-grained polycrystalline bridgmanite were studied at high temperatures up to 1080 K. High-temperature time-resolved synchrotron X-ray diffraction measurements showed that significant volume expansion due to temperature-induced amorphization caused static stress, which then hindered amorphization progress. Further, the temperature required for the amorphization of fine-grained bridgmanite (~ 1 μm) was found to be approximately 100 K higher than that required for the amorphization of coarse-grained samples (> 10 μm). We also noted that amorphization preferentially commenced at the twin planes and subgrain boundaries of bridgmanite grains, resulting in lower amorphization temperatures for the coarse-grained samples. The limited number of such specific locations in fine-grained natural bridgmanite suggested that grain boundary amorphization may be the dominant mechanism for bridgmanite amorphization in shocked meteorites. This unique amorphization kinetics would support the preservation of bridgmanite during the post-shock annealing in the shocked meteorite. Although bridgmanite amorphization starts easily at temperatures above ~ 420 K, a small amount of bridgmanite grains can survive at temperatures above 800 K by the effect of amorphization-induced stress.
Study of power-law activity distributions in a spiking neural network model
Authors: Cho Myoung Won , Choi M. Y. 
Published: July 2023

Abstract
Neuronal avalanches are cascades of bursts of activity observed primarily in the superficial cortical layers, the distribution of which fits a power law well. Motivated by the observation, we study how a power-law activity distribution emerges in a spiking neural network model. Specifically, we clarify the fundamentals of the phenomenon by applying a general theory of scale-free behavior, introduced to explain the power-law degree distribution in a brain network, and disclose that two kinds of fluctuations in spiking dynamics serve as the essential mechanism for the phenomenon. It is shown that the scale-free behavior arises from a Markov process or a Fokker-Planck diffusion in one dimension and how the power-law exponent of the activity distribution is determined depending on several factors, including the time bin. Finally, we also explain the scale-free behavior observed in the statistics of activity lifetimes.