bluuebunny/crossref_metadata_2025_split huggingface dataset:
Puckered in pioneer neurons coordinates the motor activity of the Drosophila embryo
Authors: Karkali Katerina , Vernon Samuel , Baines Richard , Panayotou George , Martin-Blanco Enrique 
Published: April 2023

Abstract
Central Nervous System (CNS) organogenesis is a complex process that obeys precise architectural rules. The impact that nervous system architecture may have on its functionality remains, however, relatively unexplored. To clarify this problem, we analyzed the development of the Drosophila embryonic Ventral Nerve Cord (VNC). VNC morphogenesis requires the tight control of Jun kinase (JNK) signaling, exerted in part via a negative feedback loop mediated by the dual specificity phosphatase Puckered, in a subset of pioneer neurons. Here we show that the JNK pathway autonomously regulates neuronal electrophysiological properties without affecting synaptic vesicle transport. Manipulating, during early embryogenesis, JNK signaling activity in pioneer neurons, directly influences their function as ‘organizers’ of VNC architecture and, moreover, uncovers a role in the coordination of the embryonic motor circuitry that is required for hatching. Together, our data reveal critical links, mediated by the control of the JNK signaling cascade by Puckered, between the structural organization of the VNC and its functional optimization.
Transcriptional landscape of intestinal environment in DSS-induced ulcerative colitis mouse model
Authors: Wen Yuefei , Li Chenyang , Huang Peng , Liu Zhigang , Liu Bin , He Yanjun 
Published: April 2023

Abstract
Ulcerative colitis (UC) is a chronic inflammatory disease that affects the colon and is becoming increasingly prevalent worldwide. To identify new diagnostic and therapeutic avenues for UC, we sequenced colons of UC mouse models and analyze their difference in expressed genes (DEGs), pathway, construct protein-protein interaction (PPI) and ceRNA networks. We identified novel DEGs include Tppp3, Saa3, Cemip, Pappa, Nr1d1, and found they enriched in cytokine-mediated signaling, extracellular matrix organization, extracellular structure organization, and external encapsulating structure organization, indicating that UC pathogenesis is significantly affected by the functional and clinically significant interactions between immune and non-immune cells and the extracellular matrix (ECM). Besides, several important nodes were found in Protein-protein interaction (PPI) network, such as Stat3, Il1b, Mmp3, and Lgals3, and found them involved in cytokine-mediated signaling pathway playing a critical role in inflammation. Additionally, ceRNA network analysis revealed the involvement of Smad7 lncRNA. The hub miRNAs in the ceRNA network were mmu-miR-17-5p, mmu-miR-93-5p, mmu-miR-20b-5p, mmu-miR-16-5p, and mmu-miR-106a-5p, while the hub mRNAs were Egln3, Plagl2, Sema7a, Arrdc3, and Stat3. These findings suggest that ceRNA networks play a role in the progression of UC and may aid in elucidating its pathogenesis.
TM4SF19-mediated brake of macrophage efferocytosis contributes to obesity-induced inflammation of adipose tissue
Authors: lee Yun-Hee , Choi Cheoljun , Jeong Yujin , Kim Minji , Choi Garam , Namgoong Sik , Jung Young Suk , Granneman James , Chung Yeonseok , Kim Jong , Choi Yoon Ha 
Published: April 2023

Abstract
Adipose tissue macrophages are critical players in obesity-induced inflammation and metabolic dysfunction. Here, we identify transmembrane 4 L six family member 19 (TM4SF19) as a gene upregulated in adipose tissue macrophages in obese states. We demonstrate that TM4SF19 is a lysosomal membrane protein that inhibits vacuolar H+-ATPase activity by interacting with its subunit ATP6V0B. In vitro gain- and loss-of-function assays in macrophages indicate that TM4SF19 reduces lysosomal acidification and impairs the clearance of dead fat cells. Single-nucleus RNA sequencing analysis indicates that TM4SF19 is specifically expressed in a subpopulation of Trem2 + lipid-associated macrophages, and global knockout reduces diet-induced obesity and recruitment of pro-inflammatory macrophages to adipose tissue. Moreover, global or macrophage-specific TM4SF19 knockout decreases the number of lipid-stressed adipocytes induced by high-fat feeding and restores tissue insulin sensitivity. Overall, these results suggest that TM4SF19-mediated control of lysosomal activity is a potential therapeutic target to resolve obesity-induced adipose tissue inflammation.
Gender-based violence among healthcare students: prevalence, description and associated factors
Authors: Tavolacci Marie-Pierre , Karmaly Alice , Gharbi-hamza Najla , Veber Benoit , Ladner Joel 
Published: April 2023

Abstract
The aims of the current study were to describe five types of gender-based violence (GBV) among healthcare students; and to identify factors associated with GBV. A cross-sectional study was conducted among voluntary healthcare students in France. Five types of GBV were noted: (1) damage to a person’s image due to a sexual connotation on social networks, (2) sexist remarks and behaviour, (3) comments with sexual connotations, (4) sexual assaults and (5) rape or attempted rape. One thousand one hundred and fifty-two students were included. The mean age was 20.8 years (SD = 2.26), 82.6% of students were women (0.4% non-binary). Since the beginning of their studies, 41.2% of students CI 95% [39.7–42.6] were exposed to at least one type of GBV: 15.8% among men CI 95% [13.2–18.4] and 46.0% CI 95% [44.4–47.6] among women (p < 0.001). After multivariate analysis, being a woman, LGBTQ+, a nurse, a physiotherapist student, having a job, living in a roommate and year of study were risk factors for GBV. GBV is so common at colleges and universities and can have such severe consequences for students that more work is needed to generate a culture change and ensure safe learning environments.
Patterns of Postnatal Weight Gain and its predictors among Preterm Very Low Birth Weight Neonates Born in Bahir-Dar Public Hospitals Retrospective Follow up Study, 2022
Authors: Ayehu Yihenew , Hailemeskel Solomon , Mekonen Jalane 
Published: April 2023

Abstract
Introduction: Postnatal weight gain in very low birth weight babies remains a challenge to the management of the neonatal period in low and middle income countries like Ethiopia, where no many feeding alternatives and follow up charts are available. Even though, extra-uterine growth retardation is a common problem in preterm, very low birth weight babies, there is lack of evidence in resource limited countries on patterns of postnatal weight gain. Therefore this study aimed to assess the Patterns of postnatal weight gain and its predictors among Preterm Very Low Birth Weight Infants Born in Bahir-Dar public hospitals neonatal care unit, 2022.Methods A Retrospective follow-up study was conducted among 206 neonates who were admitted to the neonatal intensive care unit of Bahir Dar city public hospitals for the last 2 years. The calculated sample sizes for each hospital were assigned proportionally. The actual data was collected through structured questionnaires and analyzed by using Stata14.0. Outcome variables were compared using log-binomial regression and reported using adjusted risk ratios (aRR) with 95% confidence intervals and P- value < 0.05 was considered statistically significant.Result The average postnatal weight gain among preterm very low birth weight neonates from regaining birth weight to discharge was 11.1g/kg/d and 85.4% CI (79.9-89.66) of neonates had poor postnatal weight gain at discharge. Preterm very low birth weight neonates delivered by SVD (aRR = 1.38, 95% CI :( 1.34–1.40), delivered after 34 weeks of gestation (aRR = 2.95, 95% CI: (1.62–5.39)), birth z-score >-1.29 (aRR = 3.17, 95% CI: (1.91–5.28)), first feed on the first day (aRR = 2.55, 95% CI: (1.19–5.47)), regaining birth weight within 14 days (aRR = 3.62, 95% CI: (1.45–9.03)) and neonates who had no respiratory distress syndrome (aRR = 3.27, 95% CI: (1.09–9.77) had statistical significant association with adequate postnatal weight gain.Conclusion According to the findings of this study postnatal weight gain for preterm very low birth weight neonates was lower than recommended weight gain by neonatal intensive care unit guideline of Ethiopia. Gestational age, mode of delivery, at birth z-score, initiation time of first feeding, time to regain birth weight and respiratory distress syndrome were factors associated with postnatal weight gain.
Endoplasmic reticulum activation of the caspase-12/9/3 cascade via ATG5 leads to sterogenic femoral head necrosis
Authors: Liu Wanlin , Jiang Boyong , Wang Lianjuan , Zhao Zhenqun , Gong Yulin 
Published: April 2023

Abstract
Programmed osteocyte death might be a pathogenesis of steroid-related avascular necrosis of the femoral head (SANFH). Autophagy-related gene 5 (ATG5) can activate the unfolded protein response pathway under endoplasmic reticulum stress (ERS) to participate in cell regulation, but the regulatory mechanism remains unclear. We examined the role of ERS in SANFH pathogenesis by studying the ATG5 participation mechanism in osteoblast apoptosis regulation to provide a theoretical basis for developing new SANFH therapeutic targets. Rat bone marrow mesenchymal stem cells cultured in vitro underwent osteogenic induction and alizarin red staining. The resultant osteoblasts were divided into Control, SANFH (methylprednisolone-treated), SANFH+ATG5 small interfering RNA (siRNA) (methylprednisolone-treated ATG5 siRNA transfection) groups. Beclin 1, MAP1LC3, ATG5, PERK, and caspase-3, -9, and -12 mRNA and protein expression levels were detected, the osteoblast survival rate was measured, and apoptosis was detected. The relationship between Beclin 1, MAP1LC3, ATG5, PERK, and caspase-3, -9, and -12 mRNA and protein expression levels and osteoblast apoptosis was analyzed. The SANFH group had enhanced expression of the autophagy-related genes Beclin 1 and MAP1LC3 and numerous autophagosomes were formed. Osteoblast injury stimulated ERS. ATG5 siRNA inhibited the glucocorticoid-induced osteoblast autophagy and ERS. The ER stimulated the caspase-12/9/3 cascade through ATG5 to enhance apoptosis and improve persistent ERS. The continuous action of methylprednisolone increased Beclin 1 and MAP1LC3 gene expression, resulting in bone cell injury and stimulating ERS. The ER activated the caspase-12/9/3 cascade via ATG5 under persistent and unchangeable ERS, leading to apoptosis and SANFH.
Exploring declared and taught curricula at a UK dental school through the lens of pulp management.
Authors: Brooks Laura , Edwards David , Field James , Ellis Janice 
Published: April 2023

Abstract
Introduction: This paper explores the declared and taught endodontic curriculum within an undergraduate dental programme in the UK, as part of a wider study which also investigates the learned curriculum. Management of the dental pulp was chosen due to the availability of clear internationally recognised guidelines.
Method: The declared curriculum was identified through existing course guides, seminar and practical session plans. The formal taught curriculum was identified by cataloguing all lectures, practical teaching sessions, seminars and handouts available to dental students. Questionnaires using clinical vignettes were used to explore the informal taught curriculum.
Results: Valid responses to the questionnaire were received from 25/40 (62.5%) clinical supervisors. Disparities between national guidelines, the declared and taught curriculum were primarily due to broad learning objectives and disparate information from lectures and supervising clinicians. Although the majority of formal teaching aligned with national guidelines, the main deviation occurred within the informal taught curriculum.
Conclusion: This study highlights disparities between current evidence-based guidelines, the declared and the taught curriculum in relation to pulp management in a UK dental school. Recommendations: all policies, procedures and protocols are updated and aligned to a contemporaneous evidence base annually, and engagement with clinical lecturers to enable more standardised teaching.
A Comparative Study of Classification Techniques and Imbalanced Data Treatment for Prediction of Software Faults
Authors: Bafna Rishabh , Jain Ridham , Malhotra Ruchika 
Published: April 2023

Abstract
Software Defect Prediction is one of the major challenges faced by software engineers across the world as software grows in size and function. It is the process of identifying error-prone modules in software before the testing phase, which helps with cost-cutting and saves time. The primary goal of this research is to compare the different data balancing techniques along with the popular classification models used for software fault prediction and optimize the best results. In this study, we have used the AEEEM dataset, along with mean value treatment and min-max scaling to pre-process data. Then dataset balancing is performed using class-weight-based, over-sampling, under-sampling, and hybridization techniques. The balanced datasets are now analyzed using 5 classification techniques: Random Forest Classifier, XGBoost, Support Vector Classifier, LightGBM, and Logistic Regression. Thus, a total of 25 combinations are accessed to find the best results using 10-fold cross-validation with f1-score and AUC as the performance metric. Further, the best methods are improved using feature selection. Finally, the best case is optimized using Optuna.
Comprehensive Assessment of Postoperative Recurrence and Survival in Patients with Cervical Cancer: Nomograms
Authors: Zhang Yu , Li Linrui , Jia Haodong , Qian Liting , Wu Qibing , Dong Jiangning 
Published: April 2023

Abstract

Background To investigate the value of nomograms based on clinical parameters, inflammatory indicators, intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and MRI-derived radiomics in predicting recurrence-free survival (RFS), disease-free survival (DFS), cancer-specific survival (CSS) and overall survival (OS) in cervical cancer patients after surgery.Methods A retrospective analysis of 181 cervical cancer patients operated at our hospital between January 2015 and January 2021 with continuous follow-up was completed. The parameters of IVIM-DWI and radiomics were measured, analyzed and screened. The logistic regression with LASSO regularization was used to calculate radiomics score (Rad-score). Multivariate Cox regression analysis was used to construct nomogram models for predicting postoperative RFS, DFS, CSS and OS in cervical cancer patients, with internal and external validation.Results Clinical stage, parametrial infiltration, internal irradiation, D-value and Rad-score were independent prognostic factors for RFS; Squamous cell carcinoma antigen, internal irradiation, D-value, f-value and Rad-score were independent prognostic factors for DFS; Maximum tumor diameter, lymph node metastasis, platelets, D-value and Rad-score were independent prognostic factors for CSS; Lymph node metastasis, systemic inflammation response index, D-value and Rad-score were independent prognostic factors for OS. The AUCs of each model predicting RFS, DFS, CSS and OS at 1, 3 and 5 years were 0.985, 0.929, 0.910 and 0.833, 0.818, 0.816 and 0.832, 0.863, 0.891 and 0.804, 0.812, 0.870, respectively.Conclusions Nomograms based on clinical and imaging parameters showed high clinical value in predicting postoperative RFS, DFS, CSS and OS of cervical cancer patients and can be used as prognostic markers.
Assessing the Qualitative and Quantitative Performance of Hostels and Mess for an HEI through Multi-Criteria Decision Making
Authors: PANWAR ANKITA , Pant Millie 
Published: April 2023

Abstract
Performance measurement of a unit or an organization is a concrete step for maintaining quality services and should be done periodically to assess the strengths and weaknesses of an organization. The assessment of performance depends on several criteria and is basically a multi-criterion decision-making (MCDM) problem for which various techniques are available in the literature. In the present study, the objective is to measure the performance of hostels and mess facilities of a Higher Educational Institute (HEI) through multi-criteria decision-making methods. On the basis of a survey conducted, a total of 13 criteria are identified which affect the performance of the hostel and mess. Two well-known MCDM techniques, data envelopment analysis (DEA) and analytic hierarchy process (AHP), are used for analyzing the results. While DEA is used for the quantitative analysis, AHP is used for the qualitative analysis. Further, the relevant performing factors for hostels and mess are also identified through AHP and sensitivity analysis-DEA (DEA-SA).
Machine learning-enabled early prediction of dimensional accuracy for complex products of investment casting
Authors: dong ruizhe , Wang Wenhu , Wang Yuanbin , Zhang tianren , Jiang Ruisiong , Cui Kang 
Published: April 2023

Abstract
For the foundry industry, predicting the dimensional accuracy of investment precision castings is vital yet challenging. In order to reduce cost loss caused by out-of-tolerance phenomena, this work develops a data-driven framework for estimating and screening early products based on machine learning techniques. The hollow turbine blade is analyzed as a typical case for the proposed framework. Initially, a database was compiled from the same production line of wax patterns and corresponding castings. Feature engineering techniques were employed to choose the most important characteristics and simplify inputs, employing reject rate analysis and decision tree analysis. Random forest regressors (RFRs) were chosen as the fundamental models after a sensible selection of machine learning algorithms. To enhance the performance of RFRs, the results suggested that the thickness distribution of the source material is another crucial element in determining the dimensional correctness of castings. Ultimately, a hybrid metaheuristic strategy incorporating RFR and dung beetle optimization was developed. The results showed that the proposed prediction model could minimize the error by 22.4% compared to conventional models, making it an valuable tool for early dimensional quality evaluation and guiding wall thickness control for hollow turbine blades.
Evaluation of Dimensional Stability of 3D-printed Dental Casts
Authors: Vincze Zsófia Éva , Kovács Zoltán Imre , Názár Vivien , Oskovics László , Vass Fanni , Borbély Judit , Márton Krisztina 
Published: April 2023

Abstract
Background The objective of this research was to investigate the change in dimensional stability of 3D printed dental model construction types with time. By comparing the models to each other, we sought to find the most suitable building technique based on causing the least deformation of the 3D printed model with time.Methods Four dental casts were printed at an angle of 0°, polymerizing every 50 µm using UV light with a wavelength of 405 nm. The four types of models were as follows: 2.5 mm wall thickness hollow (2,5 mm.H), 2 mm wall thickness hollow (2 mm.H), 2 mm wall thickness hollow with stabilization bars (2 mm.B), and 2 mm wall thickness with hollow with gypsum base (2 mm.G). Casts were digitized with a laboratory scanner (3Shape E3 Red E Scanner) after printing, to create the reference Standard Tessellation Language (STL) files. All models were stored under constant conditions (25°C and 50% humidity) and scanned again after 1 day and 1, 2 and 10 weeks. These scan data were compared to the reference STL file and were analysed by comparing the deformation in a surface fitting software (Geomagic Control X, 3D Systems). The results were statistically evaluated using paired Student’s t tests with the SPSS 23.0 software program. The significance level was set at p < 0.05.Results There were significant differences in dimensional stability after 10 weeks between the 2.5 mm.H(18,45 µm ± 7,661) and 2 mm.B(11,49 µm ± 2,648), p < 0.05; the 2 mm.H(13,81 µm ± 3,18) and 2 mm.G(21,57 µm ± 1,897) p < 0.0001; and the 2 mm.B(11,49 µm ± 2,648) and 2 mm.G(21,57 µm ± 1,897) p < 0.0001 casts. The results suggest that the 2 mm.B casts experienced the least deformation.Conclusions For of all casts, the deformation stayed within the clinical acceptance range, but there were significant differences between the different building structures. Of this four structures, the 2 mm cast with a stabilization bar (2 mm.B) showed the best results.
Applying a convolutional neural network as a statistical method to evaluate the correlation between diabetic retinopathy and diabetic nephropathy
Authors: Li Tao , Tang Juan , Gao Jiayou , Su Xingpin , Lv Jing , Zhai Yuanwei , Qi Xing , Dai Chuanqiang , Liu Guogang , Zhou Yan , lin Sheng , Wang Huaguo , Liu Zejiang , Lin Zhiwu , Liao Qingsan , Li Jiaman 
Published: April 2023

Abstract
Objective At present, there is no consensus on the relationship between diabetic nephropathy (DN) and diabetic retinopathy (DR), and there is a lack of imaging data to prove the correlation between them. Therefore, we aimed to investigate the common risk factors for DN and DR in patients with type 2 diabetes and used Emission Computed Tomography(ECT) imaging technology and clinical test criteria to assess the correlation between DR and DN.Purpose The convolutional neural network was employed to observe and detect pathological changes in DR and DN images. And further analyze the correlation between DR and DN through clinical test data.Results In this study, we discovered that with the aggravation of DR, SCR, BUN and ACR gradually increased while GFR decreased. The incidence of DN in the non-DR, mild-NPDR, moderate-NPDR, severe-NPDR and PDR groups was 4.17%, 28.33%, 55%, 75.83% and 91.67%, respectively. Multivariate linear regression analysis showed that duration of T2D, smoking, HbA1c, TC, TG, HDL-c, LDL-c, UAlb, Scr, BUN, UAlb, ACR, GFR, ACR and GFR were independent risk factors for DR. Renal dynamic ECT imaging analysis demonstrated that with the aggravation of DR, renal blood flow perfusion gradually decreased, thus resulting in a decrease in renal filtration function. In T2D patients, DR and DN show a linear aggravation relationship, and hypercholesterolemia and renal dysfunction are common risk factors for DR and DN.Conclusion The convolutional neural network provides a more accurate, efficient and easier way to analyze DR and DN images. Early screening of the renal function index in DR patients using ECT imaging technology will help to identify and prevent DN as early as possible.
Targeting Sex Determination to Suppress Mosquito Populations
Authors: Akbari Omar , Li Ming , Kandul Nikolay , Sun Ruichen , Yang Ting , Benetta Elena Dalla , Brogan Daniel , antoshechkin igor , C Héctor Sánchez , Zhan Yin Peng , DeBeaubien Nicolas , Loh YuMin , Su Matthew , Montell Craig , Marshall John 
Published: April 2023

Abstract
Each year, hundreds of millions of people are infected with arboviruses such as dengue, yellow fever, chikungunya, and Zika, which are all primarily spread by the notorious mosquito Aedes aegypti. Traditional control measures have proven insufficient, necessitating innovations. In response, here we generate a next generation CRISPR-based precision-guided sterile insect technique (pgSIT) for Aedes aegypti that disrupts genes essential for sex determination and fertility, producing predominantly sterile males that can be deployed at any life stage. Using mathematical models and empirical testing, we demonstrate that released pgSIT males can effectively compete with, suppress, and eliminate caged mosquito populations. This versatile species-specific platform has the potential for field deployment to control wild populations, safely curtailing disease transmission.