bluuebunny/crossref_metadata_2025_split huggingface dataset:
Peer mentoring experience on becoming a good doctor: student perspectives
Authors: Mohd Shafiaai Mohd Syameer Firdaus , Kadirvelu Amudha , Pamidi Narendra 
Published: December 2020

AbstractBackgroundPASS is a peer-led structured academic mentoring program designed to provide academic assistance for new students in their transition from college to university studies and also for students struggling in certain units. This study aims to establish acquired skills by peer leaders associated with peer-led mentoring via the PASS program, and to explore the role played by these acquired skills in their journey to become a successful doctor.MethodsStudy participants were forty selected second-year undergraduate medical students at Monash University Malaysia with commendable examination results. Validated pre-test and post-test questionnaires were administered to explore changes in the level of communication, leadership, professional, and pedagogical skills before and after participation in peer mentoring program. Qualitative analysis of focused group interviews was performed by an independent investigator to identify how the skills developed as a peer mentor may help with becoming a good doctor. Major themes were identified with the thematic-analysis approach.ResultsThirty-eight students completed the pre-test and post-test questionnaires. Peer leaders reported improvement in oral and written skills for teaching; increased confidence to give constructive feedback; better stress management; efficient time management; improved interpersonal skills; and enhanced problem-solving and critical thinking capabilities. Eight major themes were identified from the interview and peer leaders reported positive experience of working in diverse environments and shouldering of responsibilities.ConclusionsPeer-led mentoring provides a good opportunity for medical students to shoulder responsibilities as a leader and offers an experience of managing a team of their peers and juniors which in turn may enhance their communication, interpersonal, and leadership skills.
Anganwadi worker time use in Madhya Pradesh, India: a cross-sectional study
Authors: Jain Anoop , Walker Dilys M. , Avula Rasmi , Diamond-Smith Nadia , Gopalakrishnan Lakshmi , Menon Purnima , Nimmagadda Sneha , Patil Sumeet R. , Fernald Lia C. H. 
Published: December 2020

AbstractBackgroundAnganwadi Workers (AWWs) are a group of 1.4 million community health workers that operate throughout rural India as a part of the Integrated Child Development Services program. AWWs are responsible for disseminating key health information regarding nutrition, family planning, and immunizations to the women and children in their catchment area, while maintaining detailed registers that track key beneficiary data, updates on health status, and supply inventory beneficiaries. There is a need to understand how AWWs spend their time on all of these activities given all of their responsibilities, and the factors that are associated with their time use.MethodsThis cross-sectional study conducted in Madhya Pradesh, collected time use data from AWWs using a standard approach in which we asked participants how much time they spent on various activities. Additionally, we estimated a logistic regression model to elucidate what AWW characteristics are associated with time use.ResultsWe found that AWWs spend substantial amounts of time on administrative tasks, such as filling out their paper registers. Additionally, we explored the associations between various AWW characteristics and their likelihood of spending the expected amount of time on preschool work, filling out their registers, feeding children, and conducting home visits. We found a positive significant association between AWW education and their likelihood of filling out their registers.ConclusionsAWWs spend substantial amounts of time on administrative tasks, which could take away from their ability to spend time on providing direct care. Additionally, future research should explore why AWW characteristics matter and how such factors can be addressed to improve AWWs’ performance and should explore the associations between Anganwadi Center characteristics and AWW time use.
A microplanning model to improve door-to-door health service delivery: the case of Seasonal Malaria Chemoprevention in Sub-Saharan African villages
Authors: Ouédraogo André Lin , Zhang Julie , Tinto Halidou , Valéa Innocent , Wenger Edward A. 
Published: December 2020

Abstract
Background
Malaria incidence has plateaued in Sub-Saharan Africa despite Seasonal Malaria Chemoprevention’s (SMC) introduction. Community health workers (CHW) use a door-to-door delivery strategy to treat children with SMC drugs, but for SMC to be as effective as in clinical trials, coverage must be high over successive seasons.

Methods
We developed and used a microplanning model that utilizes population raster to estimate population size, generates optimal households visit itinerary, and quantifies SMC coverage based on CHWs’ time investment for treatment and walking. CHWs’ performance under current SMC deployment mode was assessed using CHWs’ tracking data and compared to microplanning in villages with varying demographics and geographies.

Results
Estimates showed that microplanning significantly reduces CHWs’ walking distance by 25%, increases the number of visited households by 36% (p < 0.001) and increases SMC coverage by 21% from 37.3% under current SMC deployment mode up to 58.3% under microplanning (p < 0.001). Optimal visit itinerary alone increased SMC coverage up to 100% in small villages whereas in larger or hard-to-reach villages, filling the gap additionally needed an optimization of the CHW ratio.

Conclusion
We estimate that for a pair of CHWs, the daily optimal number of visited children (assuming 8.5mn spent per child) and walking distance should not exceed 45 (95% CI 27–62) and 5 km (95% CI 3.2–6.2) respectively. Our work contributes to extend SMC coverage by 21–63% and may have broader applicability for other community health programs.
Sphenodontian phylogeny and the impact of model choice in Bayesian morphological clock estimates of divergence times and evolutionary rates
Authors: Simões Tiago R. , Caldwell Michael W. , Pierce Stephanie E. 
Published: December 2020

AbstractBackgroundThe vast majority of all life that ever existed on earth is now extinct and several aspects of their evolutionary history can only be assessed by using morphological data from the fossil record. Sphenodontian reptiles are a classic example, having an evolutionary history of at least 230 million years, but currently represented by a single living species (Sphenodon punctatus). Hence, it is imperative to improve the development and implementation of probabilistic models to estimate evolutionary trees from morphological data (e.g., morphological clocks), which has direct benefits to understanding relationships and evolutionary patterns for both fossil and living species. However, the impact of model choice on morphology-only datasets has been poorly explored.ResultsHere, we investigate the impact of a wide array of model choices on the inference of evolutionary trees and macroevolutionary parameters (divergence times and evolutionary rates) using a new data matrix on sphenodontian reptiles. Specifically, we tested different clock models, clock partitioning, taxon sampling strategies, sampling for ancestors, and variations on the fossilized birth-death (FBD) tree model parameters through time. We find a strong impact on divergence times and background evolutionary rates when applying widely utilized approaches, such as allowing for ancestors in the tree and the inappropriate assumption of diversification parameters being constant through time. We compare those results with previous studies on the impact of model choice to molecular data analysis and provide suggestions for improving the implementation of morphological clocks. Optimal model combinations find the radiation of most major lineages of sphenodontians to be in the Triassic and a gradual but continuous drop in morphological rates of evolution across distinct regions of the phenotype throughout the history of the group.ConclusionsWe provide a new hypothesis of sphenodontian classification, along with detailed macroevolutionary patterns in the evolutionary history of the group. Importantly, we provide suggestions to avoid overestimated divergence times and biased parameter estimates using morphological clocks. Partitioning relaxed clocks offers methodological limitations, but those can be at least partially circumvented to reveal a detailed assessment of rates of evolution across the phenotype and tests of evolutionary mosaicism.
A cluster-based analysis evaluating the impact of comorbidities in fibrotic interstitial lung disease
Authors: Wong Alyson W. , Lee Tae Yoon , Johannson Kerri A. , Assayag Deborah , Morisset Julie , Fell Charlene D. , Fisher Jolene H. , Shapera Shane , Gershon Andrea S. , Cox Gerard , Halayko Andrew J. , Hambly Nathan , Manganas Helene , Sadatsafavi Mohsen , Wilcox Pearce G. , To Teresa , Marcoux Veronica , Khalil Nasreen , Kolb Martin , Ryerson Christopher J. 
Published: December 2020

Abstract
Background
Comorbidities are frequent and have been associated with poor quality of life, increased hospitalizations, and mortality in patients with interstitial lung disease (ILD). However, it is unclear how comorbidities lead to these negative outcomes and whether they could influence ILD disease progression. The goal of this study was to identify clusters of patients based on similar comorbidity profiles and to determine whether these clusters were associated with rate of lung function decline and/or mortality.

Methods
Patients with a major fibrotic ILD (idiopathic pulmonary fibrosis (IPF), fibrotic hypersensitivity pneumonitis, connective tissue disease-associated ILD, and unclassifiable ILD) from the CAnadian REgistry for Pulmonary Fibrosis (CARE-PF) were included. Hierarchical agglomerative clustering of comorbidities, age, sex, and smoking pack-years was conducted for each ILD subtype to identify combinations of these features that frequently occurred together in patients. The association between clusters and change in lung function over time was determined using linear mixed effects modeling, with adjustment for age, sex, and smoking pack-years. Kaplan Meier curves were used to assess differences in survival between the clusters.

Results
Discrete clusters were identified within each fibrotic ILD. In IPF, males with obstructive sleep apnea (OSA) had more rapid decline in FVC %-predicted (− 11.9% per year [95% CI − 15.3, − 8.5]) compared to females without any comorbidities (− 8.1% per year [95% CI − 13.6, − 2.7]; p = 0.03). Females without comorbidities also had significantly longer survival compared to all other IPF clusters. There were no significant differences in rate of lung function decline or survival between clusters in the other fibrotic ILD subtypes.

Conclusions
The combination of male sex and OSA may portend worse outcomes in IPF. Further research is required to elucidate the interplay between sex and comorbidities in ILD, as well as the role of OSA in ILD disease progression.
Intrahepatic cholangiocarcinoma induced M2-polarized tumor-associated macrophages facilitate tumor growth and invasiveness
Authors: Yuan Hui , Lin Zelong , Liu Yingjun , Jiang Yuchuan , Liu Ke , Tu Mengxian , Yao Nan , Qu Chen , Hong Jian 
Published: December 2020

Abstract
Background
M2-polarized tumor-associated macrophages (M2-TAMs) have been shown to correlate with the progression of various cancers, including intrahepatic cholangiocarcinoma (ICC). However, the interactions and mechanism between M2 macrophages and ICC are not completely clear. We aimed to clarify whether M2 macrophages promote the malignancy of ICC and its mechanism.

Methods
Two progressive murine models of ICC were used to evaluate the alterations in different macrophage populations and phenotypes. Furthermore, we assessed M2 macrophage infiltration in 48 human ICC and 15 normal liver samples. The protumor functions and the underlying molecular mechanisms of M2 macrophages in ICC were investigated in an in vitro coculture system.

Results
We found that the number of M2 macrophages was significantly higher in ICC tissues than in normal bile ducts in the two murine models. M2 macrophage infiltration was highly increased in peritumoral compared with intratumoral regions and normal liver (p < 0.01). ICC cells induced macrophages to differentiate into the M2-TAM phenotype, and coculture with these M2 macrophages promoted ICC cell proliferation, invasion and epithelial–mesenchymal transition (EMT) in vitro. Mechanistically, M2-TAM-derived IL-10 promoted the malignant properties of ICC cells through STAT3 signaling. Furthermore, blockade of IL-10/STAT3 signaling partly rescued the effects of M2 macrophages on ICC.

Conclusion
Our results indicated that M2-polarized macrophages induced by ICC promote tumor growth and invasiveness through IL-10/STAT3-induced EMT and might be a potential therapeutic target for ICC.
RRM2 protects against ferroptosis and is a tumor biomarker for liver cancer
Authors: Yang Yueyue , Lin Jiafei , Guo Susu , Xue Xiangfei , Wang Yikun , Qiu Shiyu , Cui Jiangtao , Ma Lifang , Zhang Xiao , Wang Jiayi 
Published: December 2020

Abstract
Background
Ferroptosis is the process of cell death triggered by lipid peroxides, and inhibition of glutathione (GSH) synthesis leads to ferroptosis. Liver cancer progression is closely linked to ferroptosis suppression. However, the mechanism by which inhibition of GSH synthesis suppresses potential ferroptosis of liver cancer cells and whether ferroptosis-related liver cancer biomarkers have a promising diagnostic value remain unknown.

Methods
Ribonucleotide reductase regulatory subunit M2 (RRM2) levels were measured using an enzyme linked immunosorbent assay (ELISA), quantitative RT-PCR (qPCR), immunoblotting (IB) and immunochemistry (IHC). Cell viability and cell death were measured by a CellTiter-Glo luminescent cell viability assay and staining with SYTOX Green followed by flow cytometry, respectively. Metabolites were measured using the indicated kits. The Interaction between glutathione synthetase (GSS) and RRM2 was measured using immunofluorescence (IF), co-immunoprecipitation (co-IP) and the proximal ligation assay (PLA). The diagnostic value was analyzed using the area under the receiver operating characteristic curve (AUC-ROC). Bioinformatics analysis was performed using the indicated database.

Results
RRM2 showed specifically elevated levels in liver cancer and inhibited ferroptosis by stimulating GSH synthesis via GSS. Mechanistically, phosphorylation of RRM2 at the Threonine 33 residue (T33) was maintained at normal levels to block the RRM2–GSS interaction and therefore protected RRM2 and GSS from further proteasome degradation. However, under ferroptotic stress, RRM2 was dephosphorylated at T33, thus the RRM2–GSS interaction was promoted. This resulted in the translocation of RRM2 and GSS to the proteasome for simultaneous degradation. Clinically, serum RRM2 was significantly associated with serum alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma glutamyl transpeptidase (γ-GT), albumin (ALB) and total bilirubin. The AUC-ROC for the combination of RRM2 with AFP was 0.947, with a sensitivity of 88.7% and a specificity of 97.0%, which indicates better diagnostic performance compared to either RRM2 or AFP alone.

Conclusion
RRM2 exerts an anti-ferroptotic role in liver cancer cells by sustaining GSH synthesis. Serum RRM2 will be useful as a biomarker to evaluate the degree to which ferroptosis is suppressed and improve diagnostic efficiency for liver cancer.
Prevention of re-establishment of malaria: historical perspective and future prospects
Authors: Nasir S. M. Ibraheem , Amarasekara Sachini , Wickremasinghe Renu , Fernando Deepika , Udagama Preethi 
Published: December 2020

AbstractPrevention of re-establishment (POR) refers to the prevention of malaria outbreak/epidemic occurrence or preventing re-establishment of indigenous malaria in a malaria-free country. Understanding the effectiveness of the various strategies used for POR is, therefore, of vital importance to countries certified as “malaria-free” or to the countries to be thus certified in the near future. This review is based on extensive review of literature on both the POR strategies and elimination schemes of countries, (i) that have reached malaria-free status (e.g. Armenia, Mauritius, Sri Lanka), (ii) those that are reaching pre-elimination stage (e.g. South Korea), and (iii) countries at the control phase (e.g. India). History has clearly shown that poorly implemented POR programmes can result in deadly consequences (e.g. Sri Lanka); conversely, there are examples of robust POR programmes that have sustained malaria free status that can serve as examples to countries working toward elimination. Countries awaiting malaria elimination status should pre-plan their POR strategies. Malaria-free countries face the risk of resurgence mostly due to imported malaria cases; thus, a robust passenger screening programme and cross border collaborations are crucial in a POR setting. In addition, sustained vigilance, and continued funding for the national anti-malarial campaign programme and for related research is of vital importance for POR. With distinct intrinsic potential for malaria in each country, tailor-made POR programmes are built through continuous and robust epidemiological and entomological surveillance, particularly in countries such as Sri Lanka with increased receptivity and vulnerability for malaria transmission. In summary, across all five countries under scrutiny, common strengths of the POR programmes are (i) a multipronged approach, (ii) strong passive, active, and activated passive case detection, (iii) Indoor residual spraying (IRS), and (iv) health education/awareness programmes.
DNA methylation of insulin-like growth factor 2 and H19 cluster in cord blood and prenatal air pollution exposure to fine particulate matter
Authors: Wang Congrong , Plusquin Michelle , Ghantous Akram , Herceg Zdenko , Alfano Rossella , Cox Bianca , Nawrot Tim S. 
Published: December 2020

Abstract
Background
The IGF2 (insulin-like growth factor 2) and H19 gene cluster plays an important role during pregnancy as it promotes both foetal and placental growth. We investigated the association between cord blood DNA methylation status of the IGF2/H19 gene cluster and maternal fine particulate matter exposure during fetal life. To the best of our knowledge, this is the first study investigating the association between prenatal PM2.5 exposure and newborn DNA methylation of the IGF2/H19.

Methods
Cord blood DNA methylation status of IGF2/H19 cluster was measured in 189 mother-newborn pairs from the ENVIRONAGE birth cohort (Flanders, Belgium). We assessed the sex-specific association between residential PM2.5 exposure during pregnancy and the methylation level of CpG loci mapping to the IGF2/H19 cluster, and identified prenatal vulnerability by investigating susceptible time windows of exposure. We also addressed the biological functionality of DNA methylation level in the gene cluster.

Results
Prenatal PM2.5 exposure was found to have genetic region-specific significant association with IGF2 and H19 during specific gestational weeks. The association was found to be sex-specific in both gene regions. Functionality of the DNA methylation was annotated by the association to fetal growth and cellular pathways.

Conclusions
The results of our study provided evidence that prenatal PM2.5 exposure is associated with DNA methylation in newborns’ IGF2/H19. The consequences within the context of fetal development of future phenotyping should be addressed.
DeepFlower: a deep learning-based approach to characterize flowering patterns of cotton plants in the field
Authors: Jiang Yu , Li Changying , Xu Rui , Sun Shangpeng , Robertson Jon S. , Paterson Andrew H. 
Published: December 2020

Abstract
Background
Flowering is one of the most important processes for flowering plants such as cotton, reflecting the transition from vegetative to reproductive growth and is of central importance to crop yield and adaptability. Conventionally, categorical scoring systems have been widely used to study flowering patterns, which are laborious and subjective to apply. The goal of this study was to develop a deep learning-based approach to characterize flowering patterns for cotton plants that flower progressively over several weeks, with flowers distributed across much of the plant.

Results
A ground mobile system (GPhenoVision) was modified with a multi-view color imaging module, to acquire images of a plant from four viewing angles at a time. A total of 116 plants from 23 genotypes were imaged during an approximately 2-month period with an average scanning interval of 2–3 days, yielding a dataset containing 8666 images. A subset (475) of the images were randomly selected and manually annotated to form datasets for training and selecting the best object detection model. With the best model, a deep learning-based approach (DeepFlower) was developed to detect and count individual emerging blooms for a plant on a given date. The DeepFlower was used to process all images to obtain bloom counts for individual plants over the flowering period, using the resulting counts to derive flowering curves (and thus flowering characteristics). Regression analyses showed that the DeepFlower method could accurately (R2 = 0.88 and RMSE = 0.79) detect and count emerging blooms on cotton plants, and statistical analyses showed that imaging-derived flowering characteristics had similar effectiveness as manual assessment for identifying differences among genetic categories or genotypes.

Conclusions
The developed approach could thus be an effective and efficient tool to characterize flowering patterns for flowering plants (such as cotton) with complex canopy architecture.