bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global Achievement of Maternal Health-Related Sustainable Development Goals Targets Among Women Exposed to Intimate Partner Violence
Authors: Refaat Amany 
Published: April 2023

Abstract
Health-related Sustainable Development Goal (SDG 3) aims to ensure healthy lives. This study investigates the influence of Intimate Partner Violence (IPV) on achieving maternal health related SDG3 targets among exposed women globally.
Methodology: This study used secondary data analysis of Domestic Violence Modules from the latest Demographic and Health Surveys (DHS) of 40 countries. IPV was defined by women ever exposed to emotional, physical, severe, or sexual violence from the spouse. Achieving maternal health related SDG3 targets among women was measured by: Proportion of births attended by skilled health personnel; Antenatal care (women received antenatal care eight or more times from any provider); and the need for family planning satisfied with modern methods. The influence of IPV was estimated through adjusted OR after controlling for socioeconomic factors using binary logistic regression.
Results: Exposure to IPV was among one-third of the women (37%) mainly physical (29%) and emotional (24%). Adjusted OR with 95%CI for the influence of IPV on women’s utilization of skilled birth attendants was 0.81 (0.79-0.83)); having eight or more antenatal care visits 0.61 (0.59-0.63); and the needs for family planning with modern methods satisfied was 0.85 (0.83-0.87). Achievement of maternal health services was among 57% of the women. Women exposed to IPV were less to achieve maternal health services (50% VS 61%) with adjusted OR 0.71; 95%CI: 0.70-0.73 and it was not confounded by the positive effect of socioeconomic factors.
Conclusion & Recommendation: Exposure to IPV had a statistically significant negative influence on all the maternal health related SDG3 services among women. Programs working in facilitating the achievement of the SDGs related maternal health targets should include prevention of women’s exposure to IPV and support for those who are exposed to it.
Circular RNA as new serum metabolic biomarkers in patients with Premature Ovarian Insufficiency
Authors: Wang Zhuoya , Zheng Yuqi , Zhong Caiting , Ou Yuyang , Feng Yihui , Lin Yu , Zhao Ying 
Published: April 2023

Abstract
Objective
Quantitative Real-time PCR (qPCR) is used to detect the differential expression of Circular RNAs in patients of Premature Ovarian Insufficiency (POI), in order to explore the new biomarkers of POI that can be detected from blood as soon as possible.
Methods
The study collected plasma samples from 30 patients in POI group and 30 normal people group that meet the inclusion criteria, who visited the gynecology clinic of The First Affiliated Hospital of Guangzhou University of Chinese Medicine from July 2019 to December 2020. Then circRNAs in plasmawere extracted for qPCR validation.
Results
1. qPCR technology was performed on hsa_circRNA_008901 and hsa_circRNA_403959, and it was found that the levels of both were considerably downregulated in POI group. Clinical evaluation showed that both hsa_circRNA_008901 and hsa_circRNA_403959 have good diagnostic value for POI.
2. According to miRNA Regulatory Element (MRE) analysis, the predicted target miRNAs of hsa_circRNA_008901 are: hsa-miR-548c-3p, hsa-miR-924, hsa-miR-4677-5p, hsa-miR-6786 -3p and hsa-miR-7974; the predicted target miRNAs of hsa_circRNA_403959 are: hsa-miR-1207-5p, hsa-miR-4691-5p, hsa-miR-4763-3p, hsa-miR-6807-5p and hsa -miR-7160-5p.
Conclusion
Compared with the normal group, the expression levels of hsa_circRNA_008901 and hsa_circRNA_403959 in the POI group were downregulated, suggesting that these two circRNAs may be potential biomarkers of POI. Bioinformatics analysis indicated that hsa_circRNA_008901 and hsa_circRNA_403959 may regulate their binding miRNA through the action form of “molecular sponge", and then regulate the signaling pathway regulated by miRNA, and ultimately affect the disease progression of POI.
Association Between the miR-100 rs1834306 A&gt;G SNP and Susceptibility to Vascular Malformation in Southern Chinese Children
Authors: Liu Zhenyin , Guitao Wu , Xi Lin , Hua Jiang 
Published: April 2023

Abstract
Background:Vascular malformation was related to genes and resulted in functional and morphologic anomalies. Genetic variations affecting development of vessel endothelial cells are unclear. Therefore, this study aimed to investigated the potential value of miR-100 rs1834306 A>G SNP as a marker of susceptibility to vascular malformation.
Methods:In this case–control study in southern Chinese children, we collected samples from 1158 controls and 1113 patients with vascular malformation. TaqMan genotyping of miR-100 rs1834306 A>G was performed by real-time fluorescent quantitative polymerase chain reaction.
Result:Multivariate logistic regression analysis showed that there was no significant association between the presence of the miR-100 rs1834306 A>G polymorphism and susceptibility to vascular malformation by evaluating the values of pooled odds ratios and 95% confidence intervals. Similarly, among different sites, rs1834306 A>G was also not associated with vascular malformation.
Conclusion:Our results suggest that the miR-100 rs1834306 A>G polymorphism is not associated with susceptibility to vascular malformation in southern Chinese children. These results need to be further confirmed by investigating a more diverse ethnic population of patients with vascular malformation.
New strategy for the synthesis of photo-crosslinkable polyalphaolefin resins and related biocompatible three-dimensional networks
Authors: Kheljani Somayyeh Sadat Afi , Didehban Khadijeh , Atai Mohammad , Chen Changle , Bahri-Laleh Naeimeh 
Published: April 2023

AbstractIn this research, functionalization of the easily available polyalphaolefin (PAO) based resins is accomplished by the copolymerization of 1-decene with 9-decenol through a facile cationic polymerization route. The resultantCo-oligomerwas further functionalized with acryloyl chloride to furnishMacromerproduct. The exact microstructure of synthesized and modified resins was explored via H-NMR, FTIR and GPC analytical methods. The PAO chains contain roughly 20 monomeric units in which three polymerizable C = C moieties could be embedded. The crosslinking ofMacromervia visible light irradiation in the presence of a photo-initiator system provided final fabricate. The effect of photo-initiator content on the cross-linking kinetics of the resin wasexplored using shrinkage strain measurement. The resulted three dimensional PAO (3D-PO) revealed hydrophilic nature with water contact angel of 65° and excellent cell viability of 93% in the MTT assay. This strategy starts from easily available α-olefin based monomers, employs a facile cationic polymerization procedure, enables modulation of the functional groups in theMacromerbackbone in order to make it photo-polymerizable, and holds great potential for tissue engineering applications.
Predictive Minisci and P450 Late Stage Functionalization with Transfer Learning
Authors: King-Smith Emma , Faber Felix , Reilly Usa , Sinitskiy Anton , Yang Qingyi , Liu Bo , Hyek Dennis , Lee Alpha 
Published: April 2023

Abstract
Structural diversification of lead molecules is a key component of drug discovery to explore chemical space. Late stage functionalizations (LSFs) are versatile methodologies capable of installing functional handles on richly decorated intermediates to deliver numerous diverse products in a single reaction. Predicting the regioselectivity of LSF is still an open challenge in the field. Numerous efforts from chemoinformatics and machine learning (ML) groups have made significant strides in this area. However, it is arduous to isolate and characterize the multitude of LSF products generated, limiting available data and hindering pure ML approaches. We report the development of an approach that combines a message passing neural network and 13C NMR-based transfer learning to predict the atom-wise probabilities of functionalization. We validated our model retrospectively and with a series of prospective experiments, showing that it accurately predicts the outcomes of Minisci-type and P450 transformations, outperforming state-of-the-art Fukui-based reactivity indices.
Exploring Immune-Related Gene Expression Up To The First 24-Hour For Predicting Sepsis Outcomes Based On Comprehensive Bioinformatics Analysis And Machine Learning
Authors: Deng Huiyin , Li Jiuyi , Shah Abid Ali , Huang Lingkun , Ge Lite , Ouyang Wen 
Published: April 2023

Abstract
Background: Host immune dysregulation participates in the prognosis of sepsis with high morbidity and mortality. Our study aimed to identify the roles of immuneassociated genes during sepsis progression and to predict sepsis survival up to 24 h at diagnosis, which may help plan future individualized treatments.
Methods: GSE54514, GSE57065, and GSE95233 datasets were downloaded from the Gene Expression Omnibus (GEO) database for early identification of differentially expressed IRGs between sepsis patients and healthy controls. Candidate IRGs significantly associated with sepsis survival were obtained by univariate logistic
regression analysis. Gene signatures of these IRGs were further selected by Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest Algorithm (RFA). The correlation between signature genes and prognosis was analyzed.Furthermore, signature IRGs were further validated by quantitative PCR (qPCR) on the whole blood of septic patients and an external COVID-19 dataset and candidate drug were predicted.
Results: HLA.DPA1, IL18RAP, MMP9, RNASE3, S100P, and PTX3 were found
significantly differentially expressed starting very early after sepsis infection and persisting for up to 5 days, and their formed IRG score had a satisfactory predictive value on sepsis outcome. Furthermore, our validation showed that these six IRGs were
also significantly dysregulated in both an external COVID-19 dataset and sepsis patients. Finally, 10 potential compounds were predicted to have targeted these genes.
Conclusion: Our study developed a prognostic modeling tool for sepsis survival based on IRG expression profiles, and has the capacity for early prediction of sepsis outcomes via monitoring the immunogenomic landscape, and possibly the individualized therapies for sepsis survival.
Effect of Surface Treatment on Photoanode substrate Using Titanium Foil for DSSC Application
Authors: Ismail Izad Syahrul Ariffin Mohd , Shafiee Farah Nabilah , Hamidon Mohd Nizar , Shafie Suhaidi 
Published: April 2023

Abstract
After many attempts for Dye Sensitized Solar Cell (DSSC) efficiency improvement which mainly concentrated on electrode materials, sensitizers, and electrolytes, however there are only a few reports that have focused on the improvement of the interface between substrate material and semiconductor material. Therefore, the main objective of this work is to investigate the effect of surface treatment to the DSSC power conversion efficiency (η%) by employing different steps in pre-treatment process using sandpaper and hydrogen peroxide (H2O2) on Titanium (Ti) foil photoanode substrate. The substrates were labelled as Untreated (substrate was cleaned without sandpaper scratching and H2O2 pre-treatment), Scratched (undergone sandpaper scratching without H2O2 pre-treatment) and H2O2 Treated (Pre-treatment with both sandpaper scratching and H2O2) respectively. The Ti foil sheet resistance of each treatment process was measured using four-point probe. The morphological surface of substrates were determined using Field Emission Scanning Electron Microscopy (FESEM) whereas the elemental analysis was obtained from Energy Dispersive X-Ray (EDX). The morphological images show that the surface roughness increased after each pre-treatment process, resulting in the decrease in the sheet resistance value which contributes to a better electron transfer process, thus leading to improvement on DSSC efficiency (η%). This is proven from the I-V characteristics analysis where the H2O2 Treated Ti foil shows an impressive improvement with the highest efficiency (η%) of 1.12%.
Interactive Curriculum Learning Decreases and Homogenizes Motor Variability
Authors: Sungeelee Vaynee , Loriette Antoine , Sigaud Olivier , Caramiaux Baptiste 
Published: April 2023

Abstract
One of the challenges of technology-assisted motor learning is how to adapt practice to facilitate learning. Random practice has been shown to promote long-term learning. However, it does not adapt to the learner's specific learning requirements. Previous attempts to adapt learning consider the skill level of learners from past training sessions. This study investigates the effects of personalizing practice in real time, through a Curriculum Learning approach, where a curriculum of tasks is built by considering consecutive performance differences for each task. 12 participants were allocated to each of three training conditions in an experiment which required performing a steering task to drive a cursor in an arc channel. The Curriculum Learning approach was compared to two other conditions: random practice and another adaptive practice, which does not consider the learning evolution. The Curriculum Learning practice outperformed the random practice in effectively decreasing movement variability at post-test and outperformed both the random practice and the adaptive practice on transfer tests. The adaptation of Curriculum Learning practice also made learners' skills more uniform. Based on these findings, we anticipate that future research will explore the use of Curriculum Learning in interactive training tools to support motor skill learning, such as rehabilitation.
Correlation analysis of sarcopenia, osteoporosis, and vertebral fragility fracture in patients with liver cirrhosis using QCT
Authors: li Yuncheng , Zhai Jian , Zhu Chao , Zhang Qian , Lv Lei , Li Pei , Yu Hongqing 
Published: April 2023

Abstract
Background Sarcopenia, osteoporosis (OP), and vertebral fragility fractures were common in patients with LC. This study aimed to investigate the correlation between sarcopenia, OP, and vertebra fragility fracture in patients with liver cirrhosis (LC) using quantitative computed tomography (QCT).Methods Participants included 365 patients with LC and 130 age- and gender-matched controls who underwent an abdominal noncontrast CT scans at our Hospital from July 2019 to September 2022. The skeletal muscle area at the L3 vertebra (SMA-L3), muscle fat infiltration in posterior muscle groups at the L3 vertebra (MFI-L3), and lumbar bone mineral density (BMD) were measured using QCT Pro software. The skeletal muscle index at the L3 vertebra (SMI-L3) was SMA-L3/height². Sarcopenia was diagnosed based on SMI-L3 < 50cm²/m² (male), SMI-L3 < 39cm²/m² (female).Results Patients with LC had lower SMI-L3 and lumbar BMD than controls (P < 0.05), along with the higher prevalence of OP (26.00% vs. 16.20%), fracture (18.60% vs. 9.20%), and MFI-L3 than controls (P < 0.05). In patients with LC, logistic regression analysis indicated that age, Child-Pugh C, and OP were risk factors for sarcopenia (P < 0.05), while body mass index (BMI) was a protective factor (P < 0.001). Furthermore, female, age, sarcopenia, and fracture were risk factors for OP (P < 0.05), and age and OP were risk factors for fracture (P < 0.001).Conclusions Our study further extended the application value of QCT without additional patient exposure to ionizing radiation including assessment of BMD and muscle tissue. Sarcopenia, OP, and vertebral fragility fractures were closely correlated with each other.
Handling the Class Imbalance Problem using an improved Sine Cosine Algorithm for Optimal Instance Selection
Authors: Moorthy Rajalakshmi Shenbaga , S Arikumar K , Prathiba Sahaya Beni , Gadekallu Thippa Reddy , Baza Mohamed , Srivast Gautam , Alshahrani Hani 
Published: April 2023

Abstract
Class imbalance is a significant problem that is biased, exhibiting excellent performance towards the majority classes in the dataset while inhibiting inferior performance toward minority classes. When dealing with real-world issues, in particular healthcare problems, this kind of biased nature affects classification accuracy. Thus, a class imbalance is a danger that directly affects the effectiveness of any classification algorithm. The Improved Binary Sine Cosine Algorithm (IBSCA) has been used in this work to identify the subset of the majority class in the best possible way. The proposed IBSCA makes some enhancements over the conventional Binary Sine Cosine Algorithm (BSCA) to address the issue of premature convergence with the local optimal solutions. Intending to improve the classification accuracy for unbalanced datasets, the proposed IBSCA seeks to identify the optimal collection of instances from the majority class. The advised IBSCA uses a random agent’s location, which tends to devote considerable time to exploration to find the best possible set of instances. By using the geometric Mean (G-Mean) and F-Score to describe the fitness function, the proposed IBSCA aims to solve the multi-objective optimization issue. The most crucial metrics for assessing how well a classifier performs on skewed datasets are G-Meanand F-Score. Additionally, a V-shaped transfer function is used to handle the discrete nature of the class imbalance issue. On 18 datasets with different imbalance ratios taken from the KEEL repository, experimentation is conducted. Comparisons are made between the suggested IBSCA and the traditional BSCA, Binary Particle Swarm Optimization (BPSO), and Binary GreyWolf Optimization (BGWO). Additionally, the performance of the suggested IBSCA is evaluated against the top outcomes from different research papers. Metrics like Sensitivity, F-Score, G-Mean, and Area under Curve (AUC) show that the suggestedIBSCA outperforms the current algorithms. The statistical findings also demonstrate that the suggested IBSCA is more efficient than the other conventional algorithms.
Furan-Dihydroquinazolinone based Fluorescent Nanoprobe for Selective Recognition of 4-nitrophenol: A Spectofluorimetric Approach
Authors: Wakshe Saubai B. , Dongare Pravin R. , Gore Anil H. , Mote Gurunath V. , Anbhule Prashant V. , Kolekar Govind B. 
Published: April 2023

Abstract
Fluorescent organic nanoparticles (FONPs) have attracted much attention as a practicable and effective platform for detection applications. The present article describes the preparation of FONPs derived from the quinazolinone-based 2-(furan-2-yl)-2,3-dihydroquinazolin-4(1H)-one derivative FHDQ. Self-assembly of FHDQ in an aqueous medium resulted in the formation of FONPs through H-type aggregation and showed excellent fluorescence properties. The presence of other coexisting species solutions had no effect on the selective fluorescence quenching observed with the addition of 4-nitrophenol. The photophysical properties, i.e., UV absorbance, fluorescence emission, and lifetime measurements together with zeta particle sizer, support excited-state complex formation followed by a dynamic fluorescence quenching phenomenon in the emission of FDHQNPs. In the concentration range of 0 to 36 μg.mL⁻1, the detection limit of this turn-off sensor FDHQNPs against 4-NP was determined to be 0.01611 μM. Finally, the practicability of the FDHQNPs for the analysis of 4-NP in environmental samples was demonstrated.
The effect of body mass index at cancer diagnosis on survival of patients with squamous cell head and neck carcinoma
Authors: Pastorino Roberta , Marafon Denise Pires , Hoxhaj Ilda , Grossi Adriano , Giraldi Luca , Rondinò Antonella , Cadoni Gabriella , Polesel Jerry , Serraino Diego , Vecchia Carlo La , Garavello Werner , Canova Cristina , Richiardi Lorenzo , Lissowska Jolanta , Pandics Tamas , Dudding Tom , Ness Andy , Thomas Steve , Pring Miranda , Kelsey Karl , McClean Michael , Bradshaw Patrick T. , Zhang Zuo-Feng , Morgenstern Hal , Rozek Laura , Wolf Gregory T. , Olshan Andrew F. , Liu Geoffrey , Hung Rayjean J. , Vilensky Marta , de Carvalho Marcos Brasilino , Lopez Rossana Veronica Mendonza , Wunsch-Filho Victor , Boffetta Paolo , Hashibe Mia , Lee Yuan-Chin Amy , Boccia Stefania 
Published: April 2023

Abstract
The aim of this study is to investigate the prognostic role of body mass index (BMI) and survival from head and neck cancer (HNC). We performed a pooled analysis of studies included in the International Head and Neck Cancer Epidemiology consortium in order to investigate the prognostic role of BMI and survival from HNC. We used Cox proportional hazards models to estimate the adjusted hazard ratios (HR) for overall survival and HNC-specific survival, by cancer site. The study included 10,177 patients from 10 studies worldwide. Underweight patients had lower overall survival (HR = 1.69, 95%CI: 1.31–2.19) respect to those having normal weight with consistent results across the HNC sites. Overweight and obese patients with oropharyngeal cancers had a favourable HNC-specific survival (HR = 0.50 (95%CI: 0.33–0.75) and HR = 0.51 (95%CI: 0.36–0.72), respectively). Among ever smokers overweight and obese patients showed a favourable HNC-specific survival (HR = 0.69 (95%CI: 0.56–0.86) and HR = 0.70 (95%CI: 0.61–0.80)). Our findings show that high BMI values at cancer diagnosis predict the survival rates in smoking patients with HNC. This association may be explained by residual confounding, reverse causation, and collider stratification bias, but may also suggest that a nutritional reserve may help patients survive HNC cancer.
Decision-making pathways for contraceptive use among refugee and host populations in Adjumani district, Uganda.
Authors: Achola Roselline , Orach Christopher Garimoi , Nabiwemba Elizabeth , Atuyambe Lynn M. 
Published: April 2023

Abstract

Introduction
Contraceptive use is known to have a positive impact on maternal and child health outcomes, but it is still low especially in low-income countries. Contraceptive use is even lower among people in humanitarian situations. This study explored the decision-making processes towards use or non-use of contraceptives by people in humanitarian situations to inform program design for uptake.
Methods
A qualitative exploratory study was conducted among women of reproductive age (15-49 years) living in any of the three refugee settlements of Pagirinya, Nyumanzi, and Mirieyi and the surrounding host communities in Adjumani district, Uganda. Data were collected using 49 in-depth interviews (IDIs), 11 Key Informant Interviews (KIIs,) and 20 Focus Group Discussions (FGDs). Inductive thematic analysis was done with the aid of Atlas ti. Version 14.
Results
This study found that the decision-making processes entailed linear and nonlinear internalized cognitive and contextual processes involving four dynamic pathways. While following the linear pathway, participants reported starting with 1) idea inception, then followed through to 2) cognitive processing, 3) consultation, and 4) decision-making to either use or not use contraception. Complex linear pathway happened when participants did not go through consultation but straight to decision making. However, participants who followed non-linear pathway continuously went back to cognitive processing. Some women after consultation, or those already using and those not using contraceptives, decided to go back to cognitive processing to reconsider their current positions. This study found that some women who started off not using contraceptives ended up using, while some who started off using contraception ended up dropping out. There were also events that defied established pathway where women were forced to get off contraception by their spouses.
Conclusions
This study showed dynamic decision-making processes involving both internal and external environments as triggers to decision-making for contraceptive use. Interventions to increase contraceptive use should target both users and significant others who influence the decision for use particularly among refugees.