bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of a novel telehealth device for dietary cognitive behavioral intervention in overweight or obesity care
Authors: Fang Yi-Ya , Lee Jia-In , Wu Nai-Yuan , Chang Chiao-I , Huang Meng-Chuan , Lee Chun-Ying , Huang Jui-Yen , Lee Gwo Giun Chris , Chen Cheng-Sheng 
Published: April 2023

AbstractObesity has become a major public health issue which relate to numerous physical problems and highly comorbid with depression and anxiety. Recently, some studies of technology-based interventions for weight reduction emerged to overcome the barriers from time, cost and distance. Mood component and eating behavior related to obesity are less discussed so far with technology-based intervention though. This pilot study was aimed to investigate the effect of telehealth assisted intervention on weight reduction, mood status, and eating behavior change under a smartphone application (app) with novel 3D food picture recognition and incorporated with cognitive behavioral training programs. Adult aged 30–60 years old with overweight were recruited and randomly assigned to control-first group and intervention-first group. In period 1, control-first group had regular life and intervention-first group underwent app intervention; in period 2, two groups went crossover. Body composition and psychological/behavioral questionnaires were collected at baseline, end of period 1, and end of period 2. Nonparametric statistics was performed for data analyzing. A total of 20 participants were enrolled. In control-first group, there were statistically significant reduction in body weight (− 0.55 kg,p = 0.02) and change of body weight percentage (− 0.6%,p = 0.02) after App use. In intervention-first group, the fat percentage decreased by 0.4% after App use in period 1, and increased by 0.05% in period 2. The integrated crossover data revealed that subjects of App group had significant improvements in mindful eating behavior. This pilot study showed the effectiveness in using CogniNU app for weight control and eating behavior. The difference of short-term and long-term effectiveness of technology-based weight control intervention deserves more investigation in the future.Clinical Trial Registration: ISRCTN16082909.
Control of white mold (Sclerotinia sclerotiorum) through plant-mediated RNA interference
Authors: Walker Philip L. , Ziegler Dylan J. , Giesbrecht Shayna , McLoughlin Austein , Wan Joey , Khan Deirdre , Hoi Vanessa , Whyard Steve , Belmonte Mark F. 
Published: April 2023

AbstractThe causative agent of white mold, Sclerotinia sclerotiorum, is capable of infecting over 600 plant species and is responsible for significant crop losses across the globe. Control is currently dependent on broad-spectrum chemical agents that can negatively impact the agroecological environment, presenting a need to develop alternative control measures. In this study, we developed transgenic Arabidopsis thaliana (AT1703) expressing hairpin (hp)RNA to silence S. sclerotiorum ABHYDROLASE-3 and slow infection through host induced gene silencing (HIGS). Leaf infection assays show reduced S. sclerotiorum lesion size, fungal load, and ABHYDROLASE-3 transcript abundance in AT1703 compared to wild-type Col-0. To better understand how HIGS influences host–pathogen interactions, we performed global RNA sequencing on AT1703 and wild-type Col-0 directly at the site of S. sclerotiorum infection. RNA sequencing data reveals enrichment of the salicylic acid (SA)-mediated systemic acquired resistance (SAR) pathway, as well as transcription factors predicted to regulate plant immunity. Using RT-qPCR, we identified predicted interacting partners of ABHYDROLASE-3 in the polyamine synthesis pathway of S. sclerotiorum that demonstrate co-reduction with ABHYDROLASE-3 transcript levels during infection. Together, these results demonstrate the utility of HIGS technology in slowing S. sclerotiorum infection and provide insight into the role of ABHYDROLASE-3 in the A. thaliana–S. sclerotiorum pathosystem.
STEP-COVID: a pilot study of a prenatal intervention for pregnant women during the COVID-19 pandemic
Authors: Berthelot Nicolas , Garon-Bissonnette Julia , Drouin-Maziade Christine , Bergeron Vanessa , Sériès Thibaut 
Published: April 2023

AbstractThe COVID-19 pandemic has been associated with a global increase in psychological distress in pregnant women. This study evaluated the effects of STEP-COVID, a six-session mentalization-based prenatal group program offered online during the COVID-19 pandemic. The 100 participants were allocated to STEP-COVID or to the natural trajectory of prenatal care. Pre- and post-intervention assessments included measures of psychological distress, post-traumatic symptoms and positive affectivity. Perception of change during pregnancy on resilience-promoting factors was also assessed at post-intervention. A significant decrease in psychological distress and post-traumatic symptoms and an increase in positive affectivity were observed in participants in the intervention condition, whereas only post-traumatic symptoms improved in the control condition. Women who participated in STEP-COVID also reported greater changes during pregnancy on resilience-promoting factors than women in the control condition. Results hold promise for buffering the effect of the pandemic on the mental health of pregnant women using brief online interventions. Clinical trial registration: NCT05419167 (15/06/2022)
High levels of burnout among health professionals treating COVID-19 patients in two Nile basin countries with limited resources
Authors: EL Dabbah Noha Ahmed , Elhadi Yasir Ahmed Mohammed 
Published: April 2023

AbstractBurnout syndrome is a real cause for concern in African health facilities. Healthcare professionals (HCPs) burnout is considered a great public health problem and especially during pandemics as several physical and emotional stressors on this population can lead to increased burnout. This study aimed to investigate the frequency and associated factors of occupational burnout among HCPs working at COVID-19 isolation facilities in Egypt and Sudan. This is important to summarize lessons learned and inform relevant interventions for future pandemic responses. A cross-sectional survey was conducted among frontline HCPs from May 2021 to July 2021. An online, anonymous, self-administered questionnaire was used for data collection. Occupational burnout was estimated using the Oldenburg Burnout Inventory. A total of 362 HCPs participated in the study and were equally recruited from Egypt (181) and Sudan (181) with a mean age of (31.84 ± 8.32) years. More than half of HCPs were females (60%) and physicians (58.3%). Most HCPs included in the study had high levels of work disengagement (75.4%) and emotional exhaustion (98.6%). Burnout syndrome was present in 75% of the HCPs with 77% among Egyptian HCPs and 71% among Sudanese HCPs. Multivariate logistic regression was used to determine predictors of burnout, working hours per week were the parameters associated with burnout syndrome among Egyptian HCPs; while for Sudanese HCPs, these were age and number of days off. The study revealed a high level of burnout syndrome among HCPs working at COVID-19 isolation facilities in both Egypt and Sudan. Appropriate actions should be taken to preserve the mental health status of HCPs through the establishment of effective and efficient coping strategies.
Utilizing EEG and fNIRS for the detection of sleep-deprivation-induced fatigue and its inhibition using colored light stimulation
Authors: Shoaib Zeshan , Akbar Arbab , Kim Eung Soo , Kamran Muhammad Ahmad , Kim Jun Hyun , Jeong Myung Yung 
Published: April 2023

AbstractDrowsy driving is a common, but underestimated phenomenon in terms of associated risks as it often results in crashes causing fatalities and serious injuries. It is a challenging task to alert or reduce the driver’s drowsy state using non-invasive techniques. In this study, a drowsiness reduction strategy has been developed and analyzed using exposure to different light colors and recording the corresponding electrical and biological brain activities. 31 subjects were examined by dividing them into 2 classes, a control group, and a healthy group. Fourteen EEG and 42 fNIRS channels were used to gather neurological data from two brain regions (prefrontal and visual cortices). Experiments shining 3 different colored lights have been carried out on them at certain times when there is a high probability to get drowsy. The results of this study show that there is a significant increase in HbO of a sleep-deprived participant when he is exposed to blue light. Similarly, the beta band of EEG also showed an increased response. However, the study found that there is no considerable increase in HbO and beta band power in the case of red and green light exposures. In addition to that, values of other physiological signals acquired such as heart rate, eye blinking, and self-reported Karolinska Sleepiness Scale scores validated the findings predicted by the electrical and biological signals. The statistical significance of the signals achieved has been tested using repeated measures ANOVA and t-tests. Correlation scores were also calculated to find the association between the changes in the data signals with the corresponding changes in the alertness level.
High-throughput image analysis with deep learning captures heterogeneity and spatial relationships after kidney injury
Authors: McElliott Madison C. , Al-Suraimi Anas , Telang Asha C. , Ference-Salo Jenna T. , Chowdhury Mahboob , Soofi Abdul , Dressler Gregory R. , Beamish Jeffrey A. 
Published: April 2023

AbstractRecovery from acute kidney injury can vary widely in patients and in animal models. Immunofluorescence staining can provide spatial information about heterogeneous injury responses, but often only a fraction of stained tissue is analyzed. Deep learning can expand analysis to larger areas and sample numbers by substituting for time-intensive manual or semi-automated quantification techniques. Here we report one approach to leverage deep learning tools to quantify heterogenous responses to kidney injury that can be deployed without specialized equipment or programming expertise. We first demonstrated that deep learning models generated from small training sets accurately identified a range of stains and structures with performance similar to that of trained human observers. We then showed this approach accurately tracks the evolution of folic acid induced kidney injury in mice and highlights spatially clustered tubules that fail to repair. We then demonstrated that this approach captures the variation in recovery across a robust sample of kidneys after ischemic injury. Finally, we showed markers of failed repair after ischemic injury were correlated both spatially within and between animals and that failed repair was inversely correlated with peritubular capillary density. Combined, we demonstrate the utility and versatility of our approach to capture spatially heterogenous responses to kidney injury.
Association of beverage consumption with subclinical atherosclerosis in a Spanish working population
Authors: Muñoz-Cabrejas Ainara , Laclaustra Martín , Guallar-Castillón Pilar , Sánchez-Recio Raquel , Jarauta Estíbaliz , Casasnovas José Antonio , Moreno-Franco Belén 
Published: April 2023

AbstractBeverages play a substantial role meeting water, calorie, and nutrient requirements; however, they are presented as being major contributors to the current obesity epidemic. Although, the relationship between beverage consumption and metabolic risk factors for cardiovascular disease (CVD) in adults has been frequently studied, its association with subclinical atherosclerosis is of increased interest. We studied the association of beverage consumption with the presence of peripheral subclinical atherosclerosis among Spanish workers. We performed a cross-sectional study of 2089 middle-aged males, with a mean age of 50.9 (SD 3.9), and without CVD, carried out in the Aragon Workers’ Health Study (AWHS). A food frequency questionnaire was used to measure beverage consumption of low-fat milk, coffee and tea (unsweetened), whole-fat milk, sugar-sweetened beverages, bottled fruit juice, artificially-sweetened beverages and 100% fruit juice. Atherosclerotic plaques were measured by ultrasound (in carotid arteries, and in femoral arteries). Atherosclerotic plaque was defined as a focal structure protruding ≥ 0.5 mm into the lumen, or reaching a thickness ≥ 50% of the surrounding intima-media thickness. As statistical analysis, we use logistic regression models, simultaneously adjusted for all beverage groups. As results, unsweetened coffee was the beverage most associated with peripheral subclinical atherosclerosis with an odds ratio (OR) of 1.25 (1.10–1.41), and 1.23 (1.09–1.40) 100g/day] for carotid, and femoral territories respectively. Moreover, subclinical atherosclerosis was positively associated with whole-fat milk [OR 1.10 (1.02–1.18) 100 g/day] in the femoral territory. The association was protective for low-fat milk in the carotid territory [OR 0.93 (0.88–0.99) 100g/day]. There was also a protective association with bottled fruit juices in the femoral territory [0.84 (0.74–0.94) 100g/day]. Our results suggest a detrimental association with the consumption of coffee, as well as with whole-fat milk and the presence of subclinical atherosclerosis. Therefore, an element of prudence excluding water and low-fat milk, must be applied when recommending beverage consumption.
Feature-based attention warps the perception of visual features
Authors: Chapman Angus F. , Chunharas Chaipat , Störmer Viola S. 
Published: April 2023

AbstractSelective attention improves sensory processing of relevant information but can also impact the quality of perception. For example, attention increases visual discrimination performance and at the same time boosts apparent stimulus contrast of attended relative to unattended stimuli. Can attention also lead to perceptual distortions of visual representations? Optimal tuning accounts of attention suggest that processing is biased towards “off-tuned” features to maximize the signal-to-noise ratio in favor of the target, especially when targets and distractors are confusable. Here, we tested whether such tuning gives rise to phenomenological changes of visual features. We instructed participants to select a color among other colors in a visual search display and subsequently asked them to judge the appearance of the target color in a 2-alternative forced choice task. Participants consistently judged the target color to appear more dissimilar from the distractor color in feature space. Critically, the magnitude of these perceptual biases varied systematically with the similarity between target and distractor colors during search, indicating that attentional tuning quickly adapts to current task demands. In control experiments we rule out possible non-attentional explanations such as color contrast or memory effects. Overall, our results demonstrate that selective attention warps the representational geometry of color space, resulting in profound perceptual changes across large swaths of feature space. Broadly, these results indicate that efficient attentional selection can come at a perceptual cost by distorting our sensory experience.
The impact of physicochemical features of carbon electrodes on the capacitive performance of supercapacitors: a machine learning approach
Authors: Mishra Sachit , Srivastava Rajat , Muhammad Atta , Amit Amit , Chiavazzo Eliodoro , Fasano Matteo , Asinari Pietro 
Published: April 2023

AbstractHybrid electric vehicles and portable electronic systems use supercapacitors for energy storage owing to their fast charging/discharging rates, long life cycle, and low maintenance. Specific capacitance is regarded as one of the most important performance-related characteristics of a supercapacitor’s electrode. In the current study, Machine Learning (ML) algorithms were used to determine the impact of various physicochemical properties of carbon-based materials on the capacitive performance of electric double-layer capacitors. Published experimental datasets from 147 references (4899 data entries) were extracted and then used to train and test the ML models, to determine the relative importance of electrode material features on specific capacitance. These features include current density, pore volume, pore size, presence of defects, potential window, specific surface area, oxygen, and nitrogen content of the carbon-based electrode material. Additionally, categorical variables as the testing method, electrolyte, and carbon structure of the electrodes are considered as well. Among five applied regression models, an extreme gradient boosting model was found to best correlate those features with the capacitive performance, highlighting that the specific surface area, the presence of nitrogen doping, and the potential window are the most significant descriptors for the specific capacitance. These findings are summarized in a modular and open-source application for estimating the capacitance of supercapacitors given, as only inputs, the features of their carbon-based electrodes, the electrolyte and testing method. In perspective, this work introduces a new wide dataset of carbon electrodes for supercapacitors extracted from the experimental literature, also giving an instance of how electrochemical technology can benefit from ML models.
Familial risk for depression is associated with reduced P300 and late positive potential to affective stimuli and prolonged cardiac deceleration to unpleasant stimuli
Authors: Moretta Tania , Messerotti Benvenuti Simone 
Published: April 2023

AbstractDespite evidence of abnormal affective processing as a key correlate of depression, specific attentional mechanisms underlying processing of emotions in familial risk for depression have yet to be investigated in a single study. To this end, the amplitude of the P300 and late positive potential (LPP) complex and cardiac deceleration were assessed during the passive viewing of affective pictures in 32 individuals who had family history of depression (without depressive symptoms) and in 30 controls (without depressive symptoms and family history of depression). Individuals with familial risk for depression revealed reduced P300-LPP amplitudes in response to pleasant and unpleasant stimuli relative to controls, and comparable P300-LPP amplitudes in response to pleasant and neutral stimuli. Controls, but not individuals with familial risk for depression, reported cardiac deceleration during the viewing of pleasant vs. neutral and unpleasant stimuli in the 0–3 s time window. Also, only individuals with familial risk for depression showed a prolonged cardiac deceleration in response to unpleasant vs. neutral stimuli. Overall, the present study provides new insights into the characterization of emotion-related attentional processes in familial risk for depression as potential vulnerability factors for the development of the disorder.
Bee venom as an alternative for antibiotics against Staphylococcus aureus infections
Authors: Sameh Ahmed , Gouda Amr A. , Elmligy Esraa , Hatem Hossam , Sadek Salma S. , Ahmed Osama , El Amir Azza 
Published: April 2023

AbstractThe misuse of antibiotics has led to antibiotic-resistant bacterial strains, making it even harder to combat and eliminate their infections. Staphylococcus aureus causes various adverse infections and diseases, including skin abscesses, bloodstream infections, pneumonia, and joint infections. In this study, we aimed to test the cytotoxic and antibacterial effects of bee venom-loaded chitosan nanoparticles (BV-loaded CS-NPs) in comparison to gamma-irradiated BV and native BV from Apis mellifera. The physiochemical characterizations of our treatments were determined by Fourier Transform Infrared Spectroscopy (FTIR), Transmission Electron Microscope (TEM), zeta-potential, release rate, and Encapsulation Efficiency (EE). Our study was conducted on both levels, in-vitro and in-vivo. For the in-vitro study, a bacterial model of Staphylococcus aureus with an ATCC number of 6538 was grown in tryptic soy agar (TSA) medium, and the inhibition zones of our drug candidates were measured with the appropriate statistical analysis performed. For the in-vivo study, levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), Creatinine, Urea, and interleukin 6 (IL-6) were analyzed. BV-loaded CS-NPs showed relatively better results than the other alternatives, which are native BV and gamma-irradiated BV. The results showed that the antibacterial effect of BV-loaded CS-NPs was greater than the alternatives. Furthermore, its cytotoxic effect was far less than the native and irradiated bee venom. These outcomes ensure that loading BV on CS-NPs makes it a promising drug candidate for an antibiotic alternative with minimal cytotoxicity and enhanced antibacterial activity.
Onthodiplogaster japonica n. gen., n. sp. (Rhabditida: Diplogastridae) isolated from Onthophagus sp. (Coleoptera: Scarabaeidae) from Japan
Authors: Kanzaki Natsumi , Ikeda Yuya , Shinya Ryoji 
Published: April 2023

AbstractA diplogastrid nematode was isolated from a dung beetle, Onthophagus sp., collected from a rotten mushroom in Kyoto, Japan. The species is characterised by its cheilostomatal shape, separated into 12 narrow plates (rugae), deep stegostom, large ellipsoidal amphids, conical female tail and characteristic receptaculum seminis in the female. Based on its phylogenetic status and stomatal composition, the species is typologically similar to two other diplogastrid genera, Neodiplogaster and Mononchoides. The species can be distinguished from these two genera by the size and shape of the amphid (small pore in Neodiplogaster), female tail shape (long and filiform in Mononchoides) and presence of receptaculum seminis (absence in the two nominal genera), and is described as a monotypic member of a new genus, Onthodiplogaster japonica n. gen., n. sp. Observation of feeding behaviour suggested that O. japonica n. gen., n. sp. does not show clear stomatal dimorphism or polymorphism, which is found in its close relatives, but the species can feed on nematodes (predation), fungi and bacteria. This monomorphic omnivory possibly represents its habitat of dung and other rotten materials, where the environment is biologically divergent, and its condition changes rapidly.