bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reliability of skinfold measurements and body fat prediction depends on the rater's experience: a cross-sectional analysis comparing expert and novice anthropometrists
Authors: Machado Dalmo Roberto Lopes , Silva Leonardo Santos Lopes da , Vaquero-Cristóbal Raquel , Rosa Victor Carvalheiro , Júnior Marcio Fernando Tasinafo , Santos André Pereira dos , Abdalla Pedro Pugliesi , Mazzonetto Lisa Fernanda , Oliveira Alcivandro Sousa , Mota Jorge , Marcos-Pardo Pablo Jorge 
Published: June 2024

Abstract

In this study, we aimed to identify the variability among anthropometrists with varying levels of experience and its effects on the final interpretations of body composition estimates. Were implied 25 male university students, aged between 18 and 30 years. Skinfold measurements of eight body regions were obtained by two anthropometrists: an expert (more than 20 years of experience) and a novice (initial basic training). The same calibrated adipometer was used to verify the %fat. The results showed that the expert technical error of measurements (TEM) was below the tolerated limits (< 5%) for all skinfold measurements, while the novice exceeded the rater (> 7.5%) for the iliac crest and abdominal skinfolds. The inter-evaluator reliabilities were good for triceps, subscapular, and calf skinfolds; moderate for iliac crest, abdominal, and thigh skinfolds; but poor for biceps skinfolds. Some TEM novice measurements were 2 to 4 times higher than expert. The Bland & Altman analysis showed that inter-evaluator reliabilities were good for triceps, subscapular, and calf (p < 0.001). However, the inter-evaluator reliabilities were moderate for iliac crest, abdominal, and thigh (p < 0.001), and poor for biceps (p = 0.07). There was a significant impact on the predicted %fat, with estimates up to 55.12% higher by the novice compared to the expert. Conclusively, low reliability in estimating body fat emphasizes the importance of measurement training. Measurements by anthropometrists with low expertise levels are unreliable even with standardized protocols and equally calibrated instruments.
Shockwave lithotripsy paves the way for drug coated balloon in calcific in- stent restenosis: a case report
Authors: Zaalouk Sedky , Elwany Mostafa 
Published: June 2024

Abstract

Background
Drug-coated balloons (DCB) have been well-studied as a modality of percutaneous intervention (PCI) for the management of in-stent restenosis (ISR) in numerous trials. Proper lesion preparation has been the Achilles heel for DCB and is essentially the cornerstone for its proper use. Shockwave intravascular lithotripsy (IVL) is considered one of the safe and effective techniques for cracking heavy coronary artery calcifications (CAC) to allow proper stent expansion. There have been a few reports illustrating the safety and efficacy of the use of IVL technology to achieve satisfactory stent expansion in heavily calcific ISR.
Case presentation
In this report, we are presenting a resistant calcific ISR in a post coronary artery bypass surgery (CABG) patient which was successfully managed by IVL followed by DCB.
Conclusions
IVL followed by PCI using DCB has been shown to be safe and effective in cases of ISR with dense CAC. The technique needs to be further assessed by more studies to be adopted on a wider scale.
The association of energy, macronutrients, and food sources consumption at dinner versus breakfast with obesity: The National Health and Nutrition Examination Survey (NHANES), 2003-2016
Authors: hou wanying , wang weiqi , sun changhao 
Published: June 2024

Abstract

Background
This study aimed to investigate the association of the difference of dietary consumption (energy, macronutrients, and foods) at dinner versus breakfast with obesity among U.S adults.
Subjects/Methods:
This study adopted the data from the National Health and Nutrition Examination Survey (2003–2016), involving a total of 27911 participants. The differences in the ratio of total energy and three macronutrients with six subgroups at dinner versus breakfast (ΔRatio) were categorized into quartiles. The differences in the consumption of 17 types of food at dinner versus breakfast (ΔFoods) were considered as continuous variables. Body Mass Index (BMI) and Waist circumference (WC) were used to define general obesity (30.0 ≤ BMI < 40.0), morbid obesity (BMI ≥ 40.0), and abdominal obesity (WC > 102 cm for men or WC > 88 cm for women). Multiple logistic and linear regression models were developed.
Results:
After a variety of covariates were adjusted, participants in the highest quartile (higher energy/macronutrient intake at dinner than breakfast) of ΔRatio in terms of energy, fat, saturated fatty acids (SFA), and unsaturated fatty acids (USFA) was positively associated with morbid obesity compared with those in the lowest quartile (ORΔRatio of energy 1.27, 95%CI 1.01;1.61; ORΔRatio of fat 1.27, 95%CI 1.01;1.60; ORΔRatio of SFA 1.27, 95%CI 1.01;1.59; ORΔRatio of USFA 1.28, 95%CI 1.02;1.59). The highest quartile of ΔRatio of low-quality carbohydrate led to higher odds of abdominal obesity (ORΔRatio of low−quality carbohydrate 1.16; 95%CI 1.03–1.31). Meanwhile, ΔRatio of low-quality carbohydrates was significantly positively associated with BMI (coefficient: 0.562, 95%CI: 0.217–0.907). ΔFoods including whole fruits, other starchy vegetables, added sugars, poultry, dairy, and nuts were positively associated with obesity.
Conclusions:
This study indicated that among US adults, higher intake of energy, macronutrients (low-quality carbohydrate, fat, SFA, and USFA), and foods (whole fruits, other starchy vegetables, added sugars, poultry, dairy, and nuts) at dinner than breakfast was associated with higher odds of having obesity. In conclusion, this study emphasized the importance of diet quality and meal-timing in the prevention of obesity.
Computational modeling of insect odorant receptors: A comparative analysis of Template-based and Alphafold modeling
Authors: Jabeen Amara , Oakeshott John , Lee Siu Fai , Ranganathan Shoba , Taylor Phillip W. 
Published: June 2024

Abstract

Insects rely on odorant receptors (ORs) to detect and respond to volatile environmental cues, so the ORs are attracting increasing interest as potential targets for pest control. However, experimental analysis of their structures and functions faces significant challenges. Computational methods such as template-based modeling (TBM) and Alphafold2 (AF) could facilitate the structural characterisation of ORs. This study first showed that both models accurately predicted the structural fold of MhOR5, a jumping bristletail OR with known experimental 3D structures, although accuracy was higher in the extracellular region of the protein and binding mode of their cognate ligands with TBM. The two approaches were then compared for their ability to predict the empirical binding evidence available for OR-odorant complexes in two economically important fruit fly species, Bactrocera dorsalis and B. minax. Post-simulation analyses including binding affinities, complex and ligand stability and receptor-ligand interactions (RLIs) revealed that TBM performed better than AF in discriminating between binder and non-binder complexes. TBM’s superior performance is attributed to hydrophobicity-based helix-wise multiple sequence alignment (MSA) between available insect OR templates and the ORs for which the binding data were generated. This MSA identified conserved residues and motifs which could be used as anchor points for refining the alignments.
Promoting the mental health and well-being of vulnerable youth through art: A descriptive qualitative study
Authors: Simons Kyra , Mendrek Adrianna , Piché Jasmine , Bernier Megan , Léger-Goodes Terra , Malboeuf-Hurtubise Catherine 
Published: June 2024

Abstract

Background: Children in rural communities represent some of the most vulnerable populations in Canada, posing implications for their mental health and well-being, particularly regarding their access to mental health services. Art-based interventions are accessible, but not thoroughly validated.
Aim:The purpose of this project was to offer an art-based intervention for a very specific population benefiting from an after-school program in rural Quebec.
Methods: Youth in Quebec, Canada, took part in a 7-week art-based intervention. A descriptive design was implemented to examine the implications this intervention had on students, particularly their mental health and well-being.
Results:The majority of students described enjoying the intervention, many stating it had a positive impact on their lives. Students reported feeling positively during art-making and expressed interest in taking part in follow-up research.
Discussion: Positive experiences with the present intervention support existing literature regarding the effectiveness of art-based methods for youth populations.
Numerical and parametric study of the thermal performance of a latent storage unit
Authors: Sebbar El Hassan , Labtira Abdelkrim 
Published: June 2024

Abstract

Latent heat storage is an advanced technology with advantages for heating and cooling systems, including load displacement, flexibility, and energy savings. By accumulating thermal energy efficiently during low-demand periods and using it during high-demand periods. This reduces environmental impact, and financial savings, and increases system reliability. This work aims to study numerically a latent heat storage system. This system consists of a tank filled with a phase-change material (PCM); the tank is crossed by a heat transfer fluid to charge the PCM with thermal energy. this process follows the evolution of the PCM temperature and the tank outlet temperature during the charging period. A thorough parametric study analyzes the thermal and dynamic performance of the system and studies the effect of several parameters, including tank height, HTF mass flow rate, PCM layer thickness, and the amount of energy stored during charge. The system was modeled using computational fluid dynamics (CFD) to simulate PCM phase change phenomena. Validation of the numerical model showed excellent agreement with experimental results. It was observed that a higher mass flow rate leads to a shorter storage time and lower stored energy, with values of 19.2563 kWh for a flow rate of 0.6 kg/s and 20.1642 kWh for a flow rate of 0.4 kg/s.
Expression and regulation of SETBP1 in the song system of male zebra finches (Taeniopygia guttata) during singing
Authors: Grönberg Dana Jenny , Carvalho Sara Luisa Pinto , Dernerova Nikola , Norton Phillip , Wong Maggie , mendoza ezequiel 
Published: June 2024

Abstract

Rare de novo heterozygous loss-of-function SETBP1 variants lead to a neurodevelopmental disorder characterized by speech deficits, indicating a potential involvement of SETBP1 in human speech. However, the expression pattern of SETBP1 in brain regions associated with language remains poorly understood, along with the underlying molecular mechanisms linking it to speech. In this study, we examined SETBP1 expression in the brain of male zebra finches, a well-established model for studying vocal production learning. We demonstrated that zebra finch SETBP1 exhibits a greater number of exons and isoforms compared to its human counterpart. We characterized a SETBP1 antibody and showed that SETBP1 colocalized with FoxP1, FoxP2, and Parvalbumin in key song nuclei. Moreover, SETBP1 expression in neurons in Area X is significantly higher in zebra finches singing alone, than those singing courtship song to a female, or non-singers. Importantly, we found a distinctive neuronal protein expression of SETBP1 and FoxP2 in Area X only in zebra finches singing alone, but not in the other conditions. We demonstrated SETBP1´s regulatory role on FoxP2 promoter activity in vitro. Taken together, these findings provide compelling evidence for SETBP1 expression in brain regions to be crucial for vocal learning and its modulation by singing behavior.
Lightweight design of inner hub of coated steel strapping machine based on topology optimization
Authors: Li Xihan , Wei Yulan , Zhang Qingzhu , Shen Hua , Gao Weiqian , Ding KunYing 
Published: June 2024

Abstract

Aiming at the current situation of the demand for low energy consumption, long life and high efficiency of the coated steel bar strapping machine, topology optimization and orthogonal test method are combined to carry out lightweight research on the inner hub of the strapping machine. Based on the results of the static analysis, and taking the minimum structural flexibility as the research objective, the optimized dimensions are designed and the topology optimization model of the inner hub is established, the orthogonal test is simulated by ANSYS, and the least-squares regression equation is established to obtain the optimized mathematical model of the inner hub. The static analysis of the optimized inner hub model is carried out, and the comparison results show that the weight is reduced by 23.06% under the requirement of meeting the working needs of the inner hub.
Neuritin attenuates neuroinflammation and apoptosis in early brain injury after subarachnoid hemorrhage via endoplasmic reticulum stress-related inflammatory pathways
Authors: Ren Kunhao , Dai Linzhi , Zhang Hao , He Yaowen , Liu Bin , Hu Youjie , Ma Ketao , Tian Weidong , Zhao Dong 
Published: June 2024

Abstract

Neuroinflammation is a key destructive pathophysiological process in early brain injury (EBI) following subarachnoid hemorrhage (SAH). Recent studies have discovered that endoplasmic reticulum stress-related inflammatory pathways include the IRE1α-TRAF2-NF-κB pathway, PERK-eIF2α-NF-κB pathway, and ATF6-AKT -NF-κB pathway leading to neuroinflammatory response. Neuritin is a neurotrophin that is involved in neuronal plasticity and regeneration. Studies have suggested that Neuritin has a vital role in reducing neuroinflammation, and can also decrease the expression of proteins related to endoplasmic reticulum stress following SAH. This suggests that Neuritin could be a potential therapeutic target for SAH and other neurological conditions. However, the regulatory mechanisms of Neuritin in ER stress-related inflammatory pathways after SAH are not yet fully understood. In this work, we discovered that the activation of ER stress-related inflammatory pathways leads to neuroinflammation, which further aggravates neuronal apoptosis after SAH. Our findings indicate that Neuritin overexpression play a neuroprotective role by inhibiting IRE1α-TRAF2-NF-κB pathway, PERK-eIF2α-NF-κB pathway, and ATF6-AKT-NF-κB pathway associated with endoplasmic reticulum stress. These inhibitory effects on neuroinflammation ultimately reduce nerve cell apoptosis.
Gis Based Hydrological Modelling for Urban Flood Simulation Using Soil and Water Assessment Tool (SWAT)
Authors: Jawale Priyanka , Thube A. D. 
Published: June 2024

Abstract

This study presents a comprehensive approach to flood analysis using GIS-based hydrological modeling, particularly focusing on the application of the Soil and Water Assessment Tool (SWAT) in the urban area of the Mula River, Wakad watershed. The (QSWAT) tool, which is the SWAT interface for QGIS, has been used in this study. By examining data spanning nearly three decades, valuable insights are provided into the trends and impacts of land-use changes on flood scenarios. The study area encompasses a delineated watershed and sub-basin parameters, comprising slope orientation, digital elevation model (DEM), soil classification and land cover. The principal objective is to formulate a runoff model leveraging a geospatial database to evaluate the influence of land-use class alterations on QSWAT outputs at the sub basin level. QSWAT, renowned as a river basin model, is leveraged to assess the ramifications of management decisions on water resources. This investigation illustrates the application of QSWAT for stream flow simulation in an experimental basin, employing daily and hourly rainfall observations to appraise the impact of rainfall resolution on model efficacy. The catchment area for this watershed covers an estimated drainage area of 603.446 hectares, divided into 28 sub-basins. It is observed that the trend in average annual rainfall is on the rise over time. The maximum surface runoff observed is 3206 mm, with an average annual surface runoff of 117.89 mm. Analysis reveals that surface runoff does not adhere to a specific pattern, but the frequency of flood occurrences is escalating over time. In summary, the QSWAT model effectively simulated and forecasted flow, offering insights into dynamics of urban flooding and highlights the importance of proactive measures in mitigating flood risks.
Associations between HIV infection status, psychosocial factors, and adjuvant endocrine therapy adherence among South African women with early-stage breast cancer
Authors: O'Neil Daniel S , Blanchard Charmaine L , Joffe Maureen , Antoni Michael , Ream Molly , Mmoledi Keletso Constance , Mkwanazi Nontlantla , Shandukani Victor , Ruff Paul 
Published: June 2024

Abstract

Purpose: We aimed to evaluate for associations between HIV status, psychosocial factors, and adjuvant endocrine therapy (AET) adherence in South African (SA) women with estrogen receptor positive (ER+) breast cancer (BC).Methods: We enrolled South African women with early-stage ER + BC in remission and prescribed tamoxifen or an aromatase inhibitor to the prospective observational study. We performed AET pill counts at enrollment, 12 weeks, and 24 weeks, and calculated adherence ratios of pills consumed between visits to days between visits. Women completed questionnaires on social support, attitude towards medication, health literacy, self-efficacy, mental health, and AET toxicity. We collected household wealth data. We used hierarchical linear (HLM) and structural equation modelling (SEM) to compare adherence ratios between women with and without HIV while adjusting for psychosocial factors.Results: We collected adherence data from 239 women, 63 (26.4%) with co-morbid HIV. Comparing women with and without HIV, median AET adherence ratio was 0.88 vs 0.89, respectively (HLM p = 0.31). In our SEM model for the full cohort, mental health, healthcare savvy, and side effect burden latent variables were not significantly associated with adherence. In the subgroup of women living with HIV, lower SES quintile (β 0.04, SE 0.02, p = 0.08) and poorer mental health (β -0.02, SE 0.01, p = 0.10) showed trends toward association with adherence.Conclusions: HIV status is not predictive of AET adherence among SA women with ER + BC, though decreasing SES status and increasing mental health symptoms are marginally associated with adherence in women with BC and HIV.
A low resource simulation-based training package leads to increased knowledge and skill retention post Basic Emergency Obstetric and Neonatal Care in rural Tanzania: A Quasi-experimental research design
Authors: Matovelo Dismas , Brenner Jennifer L. , Singhal Nalini , NettelAguirre Alberto , Ndaboine Edgar , Shabani Girles , Subi Leonard , Sigalet Elaine 
Published: June 2024

Abstract

Background: Neonatal and Maternal mortality remain alarmingly high in rural areas like Kwimba Tanzania. The Basic Emergency Obstetric and Neonatal Care (BEmONC) training program aims to decrease these rates by improving healthcare provider knowledge and skill. Literature supports improvement in knowledge and skill immediately after training, but skill decay is reported as early as 1 month if healthcare providers are not afforded further facility-based opportunities to practice. The purpose of this study was to examine a low-cost resource option, a simulation package, for its impact on retention of knowledge and skills over a one-year period.
Methods: A quasi-experimental research design was used to test the intervention; 5-day BEmONC training plus a facility-based simulation package: (1) low dose high frequency peer to peer simulation practice using peer cards and (3) clinical mentorship. Participants were midwives/nurses, clinical officers, and medical officers from local hospitals and health centers in Kwimba, Tanzania. Facilities were purposely assigned to one of the two clusters. After initial BEmONC training. Cluster A was supported with the simulation package whereas access to the simulation package was delayed until after the 6-month assessment for Cluster B. Knowledge and skill were analyzed using the training program OSCE’s at baseline, post workshop, at 6 months and at 12 months using the r core statistics; p-values < 0.05 were considered statistically significant.
Results: All participants demonstrated significant knowledge and skill improvements post-initial workshop. At 6 months, Cluster A’s aggregate skill scores were significantly higher than Cluster B, who showed skill decay. At 12 months, aggregate skill scores between Cluster A and Cluster B were similar.
Conclusion: There was a significant relationship between clusters receiving component two and three of the interventions and retention of skill sets at 6 and 12 months. This is the first study to report skill retention at 12 months after BEmONC training. Peer learning using detailed peer learning cards, with mentorship visits by the clinical expert every 3 months is a low resource educational option that in this context supported skill retention. More research is needed to assess generalizability and link like initiatives with clinical outcomes.
Carbon Emission Prediction and Emission Reduction Analysis of Wastewater Treatment Plant Based on Machine Learning and Deep Learning
Authors: Liu Fangqin , Ding Ning , Zheng Guanghua , Xu Jiangrong 
Published: June 2024

Abstract

Accurate accounting and prediction of carbon emissions from sewage treatment plants is the basis for exploring low-carbon sewage treatment plants and measures to reduce pollution and carbon emissions. Although carbon emission prediction models have been widely used in construction, transportation and other fields, research in the field of wastewater treatment is still lacking, and the existing research is mostly limited to the prediction of carbon emissions from a single link or energy consumption, which makes it difficult to control the carbon emissions of the whole plant as a whole in order to realize the carbon emission reduction of the whole plant. This study proposes a hybrid prediction framework based on machine learning and deep learning, which integrates multiple algorithms and has strong adaptability and generalization ability. The pre-framework uses Pearson correlation coefficient to select feature values, constructs a combined prediction model based on the selected features using support vector machine (SVR) and artificial neural network (ANN), and optimizes the model parameters and structure using Gray Wolf Optimization (GWO) algorithm. The results show that the model has stronger prediction performance compared with other prediction models, with a mean absolute percentage error (MAPE) of 0.49% and an R2 of 0.9926. In addition, this study establishes six future development scenarios based on the historical data trends and policy outlines, which provide recommendations for the development of carbon emission reduction measures for wastewater treatment plants. This study can provide a reference for exploring efficient carbon management and achieving carbon neutrality in wastewater treatment plants.