bluuebunny/crossref_metadata_2025_split huggingface dataset:
Edentulism and quality of life in the Salvadoran population: a cross-sectional study
Authors: Escobar Guillermo Alfonso Aguirre , Cartagena Francisco José Rivas , de González Wendy Yesenia Escobar , de Rodríguez Katleen Argentina Aguirre , Pérez Manuel Bravo , Mesa Francisco , Siciliano Ana Lourdes Pérez 
Published: March 2024

Abstract

The impact of edentulism on quality of life was determined in 3322 users of the Public Health System of El Salvador aged 15 to > 60 years. Edentulism was determined by clinical examination using the Oral Impact on Daily Performance scale. We used χ2 tests and set the significance threshold at p < 0.05. The calculation of percentages, means, and standard deviations and multiple regression analysis were performed with SPSS v. 26.0. Partial edentulism in the upper jaw was present in 2269 people (68.24%), partial edentulism in the lower jaw was present in 2408 people (72.42%) and complete edentulism was observed in 67 people (2.02%). There were significant sex differences and a relationship between sex and quality of life (p < 0.004); the self-perception of severe/very severe impacts was greater in women. People without education or with primary or secondary education only were the most affected (p < 0.05). Tooth loss increases with age, affecting quality of life in a severe/very severe manner. Complete edentulism had greater impacts on quality of life in terms of eating (25.64%), speaking (21.15%), and socializing/enjoying contact with people (10.90%). A severe/very severe impact on quality of life of teeth lost was reported mainly by those over 60 years of age, with an average of 11 missing posterior teeth, 6 missing anterior teeth and 13 missing teeth per patient. Those missing up to 6 anterior teeth were 5.78 times more likely to perceive severe/very severe impacts on quality of life than those without any missing teeth. Edentulism affected the quality of life of those examined, especially the loss of upper anterior teeth.
Genetically proxied therapeutic inhibition of kidney function drug targets and type 2 diabetes in Africans: A Mendelian randomization study
Authors: Diawara Abdoulaye , Traore Mariam , Diabaté Oudou , Kintu Christopher , Saeed Ali Awadallah , Abiola Julianah Ore , Cisse Cheickna , Traore Kassim , Wele Mamadou , Nash Oyekanmi , Doumbia Seydou O. , Abbas Talib Yusuf , Shaffer Jeffrey G. , Diakité Mahamadou , Fatumo Segun , Soremekun Opeyemi 
Published: March 2024

Abstract

Background:
Despite the growing number of treatments available for diabetics, many people fail to achieve their therapeutic goals. The complexity of diabetes prevention and control exacerbates the situation in low-income countries. These complexities include genetic factors, social, and financial burdens. Strategies for optimizing coverage for new drugs and clinical therapies for type 2 diabetes mellitus (T2DM) have focused on dual-use approaches for new or off-label indications. This study aimed to determine whether inhibition of kidney function drug targets have adverse effect on T2DM.
Methods: A two-sample Mendelian randomization (MR) study was conducted based on genetic variants located in or near genes (in 300 kilobyte windows) for encoding significant drug targets. We used summary statistics of eGFR GWAS (n=80,027) of African ancestry individuals and GWAS datasets of T2DM (n=4,347 Africans in South Africa, Nigeria, Ghana and Kenya), to predict the effects of drug exposure on T2DM risk.
Results: Genetically predicted inhibition of vascular endothelial growth factor A (VEGFA) and Ras homolog enriched in brain (RHEB) were associated with higher odds of T2DM incidence (OR, 2.66; 95% CI 1.34–3.78, and OR, 2.25; 95% CI, 1.34–3.28, respectively). Genetically predicted inhibition of SLC22A2 and inhibition of CLDN14 were not associated with T2DM occurrence (OR, 0.95; 95% CI, 0.61-1.48 and OR, 1.56; 0.71–2.20, respectively).
Interpretation: Our results suggest VEGFA inhibitors and RHEB inhibitors drugs may increase the risk or exacerbate T2DM risk in Africans, hence a need for closely monitoring the safety and efficacy of anti-diabetic drugs in the African population.
Preserving Trust in the Doctor-Patient Interaction: Unveiling the Interactive Positive Evolutionary Process of Doctor-Patient Trust through fNIRS Evidence
Authors: Liu Yuting , Liu Yu , Zhang Mingming , Wang Pei 
Published: March 2024

Abstract

Background: Effective doctor-patient interaction plays a crucial role in fostering trust between doctors and patients. This study aimed to construct an interactive positive evolution model of doctor-patient trust by incorporating key influencing factors (interaction needs and interaction modes) in the doctor-patient interaction context, drawing from the interpersonal trust model. This new model includes three trust stages: the bounded rational trust stage, the knowledge-based trust stage, and the identification-based trust stage.
Methods: To validate the efficacy of the new model, interactive empirical experiments were conducted using functional near-infrared spectroscopy (fNIRS).
Results: The behavior and fNIRS results revealed that the knowledge-based trust stage, characterized by mutual understanding, exhibited higher levels of doctor-patient trust, accompanied by increased inter-brain synchronization in the left inferior frontal gyrus, compared to the bounded rational trust stage. Furthermore, the identification-based trust stage, characterized by mutual positive feedback, demonstrated the highest levels of doctor-patient trust, with increased inter-brain synchronization observed in the bilateral temporoparietal junction and the right inferior frontal gyrus. Especially, the inter-brain synchronization results in the left temporoparietal junction region were positively correlated with the doctor’s trust.
Conclusions: Therefore, we confirmed the effectiveness of the interactive, positive evolution model of doctor-patient trust and provided neural evidence that predicts the development of doctor-patient trust. This trust model offers valuable guidance for both medical student education and patient education, illuminating the path toward more effective and empathetic healthcare practices.
Distribution of mental health diagnoses in relation to sexual orientation and gender dysphoria in a late adolescent community population
Authors: Gerdner Arne , Skoog Therése , Kapetanovic Sabina , Claesdotter-Knutsson Emma , Askelöf Susanna , Håkansson Anders 
Published: March 2024

Abstract
Background Few population studies have assessed the prevalence of various psychiatric disorders separately for sexual minority groups, and none in an adolescent population. Given the increased mental health problems in sexual minority groups combined, the present study aimed to describe prevalence of mental disorders in separate minority groups in community-recruited adolescents in Sweden.Methods The present study is based on two waves (at 17 and 18 years of age) of a longitudinal cohort study (N = 949; 56% girls). Diagnostic data of 20 mental health disorders (psychiatric, substance use, and addictive behavior disorders) for each group of sexual orientation (asexual, homosexual, bisexual, and heterosexual) and gender dysphoria are reported, based on structured screening and subsequent diagnostic procedures.Results The largest prevalence of mental health disorders were detected in homosexual girls and in bisexuals of both genders. Among asexual individuals, and among homosexual boys, none of the participants fulfilled the mental health disorders assessed. Gender dysphoria was associated with a moderately higher number of mental health disorders.Conclusion Mental health services, both in specialized psychiatry and in community-based services targeting the mental health of adolescents, may need a particular focus on the screening and treatment of mental health disorders in bisexual individuals and in female homosexual individuals. Further research with larger samples is essential to better understand mental health in asexual individuals, young male homosexuals, and transgender populations.
Integrating geospatial data and multi-criteria analysis for mapping and evaluating the mineralization potential in the Dschang pluton (Western Cameroon)
Authors: Fozing Eric Martial , Jules Tcheumenak Kouémo , Sâga Sawadogo , Boris Chako Tchamabé , Ousmanou Safianou , Staelle Foka Koagne , Madeleine Nguimezap Marie , Maurice kwékam 
Published: March 2024

Abstract
Investigating lithological units and potential hydrothermal alteration areas using remote sensing, geographic information systems (GIS) and statistical analysis are indeed an essential method for geological exploration. In this research, we developed an algorithm for the identification and delineation of rock units and hydrothermal alteration mineral deposits in the Dschang area using multiple set of criteria derived from Landsat 9 OLI and ASTER data using False Color Composites (FCC), Band Ratios (BRs), Principal Component Analysis (PCA), Spectral Angle Mapper (SAM), and fuzzy-logic overlay methods. The multiple methods applied on these datasets clearly identified orthogneiss, granites and basalts and showed iron-oxides, ferrous, hydroxyl-bearing/carbonate, argillic, phyllic and propylitic mineral properties. The fuzzy overlay map identified domains depending on their mineralization prospective, serving as fundamental tool for prospective mineral deposit evaluation investigation, which was produced by merging band ratios and PC's alteration markers labelled very good and excellent and encompasses 0.8–0.9 and 0.9-1.0 respectively. From the statistical analysis of geochemical data point of view, the calcic and alkaline-calcic, strongly metaluminous to hyperaluminous I-type character of the Dschang granitoids proves their parent magma was fertile for mineralization in Rare Earths, Cu, Sn, Mo, and Zn. In addition, lineaments analysis illustrated the presence of three structural directions in the Dschang area (ENE-WSW to NE-SW, N-S to NNE-SSW, and NW-SE). The innovative aspect of this research is the integration and processing of Landsat 9 OLI, ASTER, and statistical analysis of previous geochemical data and investigation data, which allows for the identification of rock units and potentially mineralized rock formations and defining exploration targets.
Investigating the effect of Transactional Analysis training on the quality of life and marital intimacy of women with unplanned pregnancy
Authors: Cheraghi Zohre , Azar Fereshteh Farzan , Mehrabi Fatemeh 
Published: March 2024

Abstract
Introduction:
Unplanned pregnancy has adverse maternal-fetal and family consequences. This study aims to investigate the effect of Transactional Analysis (TA) training on the quality of life and marital intimacy of women with unwanted pregnancies.
Methods
In a semi-experimental study of pre-test and post-test types with a control group, among 250 volunteer women with unplanned pregnancies referring to Kausar Clinic in Arak city, 64 people were randomly assigned into two control and intervention groups. The intervention group received eight two-hour Transactional Analysis training on quality of life and marital intimacy. World Health Organization quality of life questionnaire - short form and Bagarozi marital intimacy questionnaire were completed by two groups before and immediately after the end of the intervention. Data were analyzed by chi-square, independent t and paired t tests in Spss version 26 software.
Results
The average age of participants was 31.2 ± 4.9 years. The results showed that there was no significant difference between the mean quality of life and total and all dimensions of marital intimacy scores of the intervention group and the control group before the intervention (Ƥ<0.005). A better increase in the quality of life in the intervention group (60.16 ± 5.6) compared to the control group (39.59 ± 5.46) and an increase in the average total score (intervention 283.14 ± 7.92 to control 186.81 ± 7.34) and all dimensions of marital intimacy in the intervention group were significant compared to the control group (Ƥ=0.001).
Conclusion
The results of the present study showed that Transactional Analysis training improved the quality of life and marital intimacy of women with unwanted pregnancies.
IL-6 as potential predictive biomarker of febrile seizures
Authors: Papež Jan , Česká Katarína , Loja Tomáš , Šána Jiří , Večeřa Marek , Jabandžiev Petr , Aulicka Stefania , Aulická Štefania 
Published: March 2024

Abstract

Background
Febrile seizures are the most common type of convulsions in children. Fever is induced by cytokines release during infection. Recent studies focusing on the identification of a possible role of cytokines in pathogenesis of febrile seizures have contributed conflicting results. Moreover, most of these studies investigated only a few cytokines, such as IL-1β, IL-6 and TNFα. The aim of this study was to investigate multiple cytokine-chemokine profiles that could be potentially associated with the development of febrile seizures.
Methods
Twenty-four febrile seizure cases (febrile seizure group) and two matched control groups were included in this study. Children with febrile illness without convulsion (febrile control group) and children without seizures and without fever (healthy control group) served as control groups. We investigated serum levels of IL-1β, IL-6, IL-8, IL-10, IL-18, CXCL10/IP-10, CCL2/MCP-1, CXCL13/BLC, TNFα, and fractalkine/CXC3CL1 in all children included in the study.
Results
The analysis of serum samples revealed a significant elevation of IL-6 (p = 0.0042) in the FS group compared to the febrile controls. Significantly higher levels of cytokines were also found in the FS group compared to healthy controls in IL-10 (p = 0.0039), TNFα (p = 0.0091) and MCP-1 (p = 0.0039).
Conclusion
Our study supports the hypothesis that IL-6 is involved in the pathogenesis of febrile seizures. We supposed that IL-6 could become a potential biomarker of the development of febrile seizures in children with febrile disease. This knowledge could be used in clinical practice to identify children at risk of developing of febrile convulsions.
Recent C4 vegetation decline is imprinted in atmospheric carbon isotopes
Authors: Lavergne Aliénor , Harrison Sandy , Atsawawaranunt Kamolphat , Dong Ning , Prentice Iain 
Published: March 2024

Abstract
How changes in the abundance and distribution of C3 and C4 plants are influencing the terrestrial carbon cycle is still unclear. Here, we use a simple C3/C4 distribution model based on optimality principles to investigate the impact of climate-related changes in C3 and C4 plants on global gross primary production (GPP) and atmospheric carbon isotopic discrimination (Δ13C). We estimate that the fraction of total C4 plants including natural grasslands and crops has decreased from 17.6% to 14.4% over 1982–2016, despite an increase in the fraction of C4 crops, reflecting the declining competitive ability of C4 photosynthesis as atmospheric CO2 concentrations increased. When ignoring this decline, the model predicts a strong increase in global GPP (18.6 ± 2.1 PgC) and slight increase in Δ13C (0.003 ± 0.001‰ ppm-1). However, when considering this decline, the increase in global GPP is slightly reduced (16.5 ± 1.8 PgC) and that of Δ13C increased (0.014 ± 0.001‰ ppm-1). The rate of Δ13C increase is consistent with independent atmospheric estimates but greater than that derived from another C4 distribution model. We conclude that the magnitude of the decrease in global atmospheric δ13CO2 can be partly explained by global changes in the distribution of C3/C4 plants.
The role of various physiological and bioelectrical parameters for estimating the Weight Status in Infants and Juveniles cohort from the Southern Cuba Region: A Machine Learning Study
Authors: Luna Taira Batista , Bello Jose Luis García , Carbonell Agustín Garzón , Montoya Ana de la Caridad Román , Lafargue Alcibíades Lara , Ciria Hector Manuel Camué , Zulueta Yohandys A. 
Published: March 2024

Abstract

Objective
This work is aimed to develop a machine learning predictions of weigh status derived from bioimpedance measurements and other physical parameters of healthy infant juvenile cohort from the Oncological Hospital, Santiago de Cuba, Cuba.
Methods
The volunteers were selected between 2002 and 2008, ranging in age between 2 to 18 years old. In total, 393 female and male infant and juvenile individuals are studied. The bioimpedance parameters are obtained by measuring standard tetrapolar whole-body configuration. A classification model are performed, followed by a prediction of other bioparameters influencing the weight status.
Results
The results obtained from the classification model indicate that fat-free mass, reactance, and corrected resistance primarily influence the weight status of the studied population. Specifically, the regression model demonstrates that other bioparameters derived from impedance measurements can be highly accurate in estimating weight status
Conclusion
The classification and regression predictive models developed in this work are of the great importance for accessing to the weigh status with high accuracy of younger individuals at the Oncological Hospital in Santiago de Cuba, Cuba.
Binding Affinity Prediction with 3D Machine Learning: Training Data and Challenging External Testing
Authors: Gómez-Tamayo Jose Carlos , Cao Lili , Ahmad Mazen , Tresadern Gary 
Published: March 2024

Abstract

Protein-ligand binding affinity prediction is one of the major challenges in computational assisted drug discovery. An active area of research uses machine learning (ML) models trained on 3D structures of protein ligand complexes to predict binding modes, discriminate active and inactives, or predict affinity. Methodological advances in deep learning, and artificial intelligence along with increased experimental data (3D structures and bioactivities) has led to many studies using different architectures, representation, and features. Unfortunately, many models do not learn details of interactions or the underlying physics that drive protein-ligand affinity, but instead just memorize patterns in the available training data with poor generalizability and future use. In this work we incorporate “dense”, feature rich datasets that contain up to several thousand analogue molecules per drug discovery target. For the training set, PDBbind dataset is used with enrichment from 8 internal lead optimization (LO) datasets and inactive and decoy poses in a variety of combinations. A variety of different model architectures was used and the model performance was validated using the binding affinity for 12 internal LO and 6 ChEMBL external test sets. Results show a significant improvement in the performance and generalization power, especially for virtual screening and suggest promise for the future of ML protein-ligand affinity prediction with a greater emphasis on training using datasets that capture the rich details of the affinity landscape.
Choline and its Metabolites Trimethylamine and Trimethylamine N-oxide Potentially Predict the Risk of Small Vulnerable Newborn and the Development of 1-Year Infants
Authors: Xiao Xiaoqiu , Lin Xiaojing , Li Kemeng , Wang Zhuyun , Chen Chang , He Xiaoling , Qi Hongbo , Baker Philip , Saffery Richard , Zhang Hua 
Published: March 2024

Abstract
Background: The concept of Small Vulnerable Newborns (SVN), encompassing small for gestational age (SGA), low birthweight (LBW), and preterm birth (PTB) has recently proposed [1, 2]. Collectively, these births represent the main cause of neonatal mortality and specific interventions to address SVN have great potential to improve maternal and infant outcomes. Choline is an essential nutrient for many aspects of fetal development and metabolism, but despite this, upwards of 90% of pregnant women fail to achieve recommend adequate intake [3]. At present, the role of choline deficiency in pregnancy on SVN risk remains unclear.
Methods: Here, we measured choline and its metabolites, TMA an TMAO by liquid chromatography-mass spectrometry (LC-MS/MS) in first (11-14 weeks), second (22-28 weeks), and third (32-34 weeks) trimester plasma of 1231 pregnant women from the Complex Lipids in Mothers and Babies (CLIMB) cohort to investigate the relationship between choline TMA, TMAO in pregnancy and the risk of SVN. We also explored the relationship of these measures with later infant developmental outcomes of SVN and non-SVN births including physical and brain development.
Results: Pregnant women with SVN births showed no differences in circulating choline throughout pregnancy but had significantly lower TMAO in the first two trimesters, and higher TMA in the third trimester, relative to non-SVN births. However, TMAO levels during pregnancy were positively correlated with the risk of SVN, while TMA levels were negatively correlated with the risk of LBW and PTB in SVN. Supporting findings included positive associationbetween TMAO during pregnancy and birth weight and birth length, while negative association between TMA and birth weight and birth length. In the receiver operating characteristic (ROC) curves, inclusion of choline and its metabolites TMA and TMAO during pregnancy in the models markedly increased the predictive performance for the model which contained traditional risk factors for SVN including age, body mass index, fasting blood glucose , one-hour postprandial blood glucose, two-hour postprandial blood glucose, and placental growth factor. Moreover, during pregnancy, the TMAO was not only positively correlated with fetal development, but also with the development of postnatal offspring at six months old and 1 year old, while TMA was the opposite.
Conclusions: The abnormal choline metabolism is potentially associated with the risk of SVN and the development of fetus and postnatal offspring, with particular attention paid to the opposite association between TMAO and TMA in offspring development, which may be an effective means of preventing SVN and ensuring healthy fetal development.
Analysis of expression status and relationship between senescence- related genes and pancreatic function-related genes in human islets of various ages
Authors: Imamura Hajime , Adachi Tomohiko , Miyamoto Daisuke , Kin Tatsuya , Yamashita Mampei , Matsushima Hajime , Hara Takanobu , Soyama Akihiko , Eguchi Susumu 
Published: March 2024

Abstract
Background
Although studies on senescence-related genes using human islets have been performed, the expression of senescence-related genes and their association with functional genes in islets remain insufficiently investigated. We aimed to determine whether and what types of senescent related genes are expressed in islets and identify their correlations with pancreatic function-related genes by using islets from individuals of various ages isolated for islet transplantation.
Methods
Islet from deceased donors of both sexes and different ages were used for analysis. The expression status of senescence-related genes (GLS1, IL-6, IL-8, p16, p21, and SA-β-gal) and pancreatic function-related genes (GCG and INS) was examined by RT-qPCR, and their relationships with age were investigated.
Results
We obtained isolated human islets from 18 deceased multiorgan donors. There was no correlation between donor age and each senescence-related gene. Regarding correlations between donor age and pancreatic function-related genes, age was positively correlated only with INS (r = 0.49, p = 0.03). Meanwhile, INS expression was not correlated with GLS1 (r = 0.23, p = 0.34), IL-6 (r=-0.06, p = 0.79), or IL-8 (r=-0.1, p = 0.12), but positively related with p16 (r = 0.89, p < 0.0001), p21 (r = 0.51, p = 0.02), and SA-β-gal (r = 0.52, p = 0.02).
Conclusion
We did show the functional potential of even aged islets, which were originally thought to be functionally impaired. We were unable to identify any senescence-related genes expressed in islets from various ages. Therefore, a new index would need to be established to evaluate not only actual chronological age but also organ- and cell-specific age.