bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ensemble machine learning methods in screening electronic health records: A scoping review
Authors: Stevens Christophe AT , Lyons Alexander RM , Dharmayat Kanika I , Mahani Alireza , Ray Kausik K , Vallejo-Vaz Antonio J , Sharabiani Mansour TA 
Published: May 2023

Background Electronic health records provide the opportunity to identify undiagnosed individuals likely to have a given disease using machine learning techniques, and who could then benefit from more medical screening and case finding, reducing the number needed to screen with convenience and healthcare cost savings. Ensemble machine learning models combining multiple prediction estimates into one are often said to provide better predictive performances than non-ensemble models. Yet, to our knowledge, no literature review summarises the use and performances of different types of ensemble machine learning models in the context of medical pre-screening. Method We aimed to conduct a scoping review of the literature reporting the derivation of ensemble machine learning models for screening of electronic health records. We searched EMBASE and MEDLINE databases across all years applying a formal search strategy using terms related to medical screening, electronic health records and machine learning. Data were collected, analysed, and reported in accordance with the PRISMA scoping review guideline. Results A total of 3355 articles were retrieved, of which 145 articles met our inclusion criteria and were included in this study. Ensemble machine learning models were increasingly employed across several medical specialties and often outperformed non-ensemble approaches. Ensemble machine learning models with complex combination strategies and heterogeneous classifiers often outperformed other types of ensemble machine learning models but were also less used. Ensemble machine learning models methodologies, processing steps and data sources were often not clearly described. Conclusions Our work highlights the importance of deriving and comparing the performances of different types of ensemble machine learning models when screening electronic health records and underscores the need for more comprehensive reporting of machine learning methodologies employed in clinical research.
Mother's Experience with COVID-19 in Breastfeeding: A Phenomenological Study
Authors: Mufdlilah Mufdlilah , Kusuma Nur Intan , Suryaningsih Endang Koni 
Published: May 2023

Background The COVID-19 pandemic has disrupted mothers’ and children's access to essential health services. Concerns about the transmission of COVID-19 to infants resulted in strict procedures, which then caused delays in initial contact and breastfeeding. This delay then impacted the well-being of mothers and babies. Purpose This study aimed to explore the experience of mothers with COVID-19 in breastfeeding. This study was qualitative research with a phenomenological approach. Methods Participants were mothers with a confirmed history of COVID-19 during the breastfeeding period either in 2020, 2021, or 2022. Semi-structured in-depth interviews were conducted with 21 mothers. Data were analyzed using thematic analysis. Results Three themes were obtained: breastfeeding during the mother was confirmed COVID-19, changes in the mother's condition, and social support received by the mother. Based on this theme, it can be seen that mothers are temporarily separated from their newborns, which causes breastfeeding difficulties. Mothers confirmed to have COVID-19 in 2020 and 2021 appear to have more significant concerns about transmitting COVID-19, as indicated by the mother's decision not to breastfeed and to undergo separate isolation with the baby. Conclusion Mothers need support to continue to breastfeed. The benefits obtained from breastfeeding are far more significant than efforts to prevent transmission by separating mother and baby, so mothers should be encouraged to continue breastfeeding.
An Approach to Leadership Development and Patient Safety and Quality Improvement Education in the Context of Professional Identity Formation in Pre-Clinical Medical Students
Authors: Inayat Hamza , Torti Jacqueline , Hemmett Juliya , Lingard Lorelei , Chau Brandon , Inayat Ali , Elzinga Jason L. , Sultan Nabil 
Published: May 2023

Objectives Leadership and patient safety and quality improvement (PSQI) are recognized as essential parts of a physician's role and identity, which are important for residency training. Providing adequate opportunities for undergraduate medical students to learn skills related to these areas, and their importance, is challenging. Methods The Western University Professional Identity Course (WUPIC) was introduced to develop leadership and PSQI skills in second-year medical students while also aiming to instill these topics into their identities. The experiential learning portion was a series of student-led and physician-mentored PSQI projects in clinical settings that synthesized leadership and PSQI principles. Course evaluation was done through pre/post-student surveys and physician mentor semi-structured interviews. Results A total of 108 of 188 medical students (57.4%), and 11 mentors (20.7%), participated in the course evaluation. Student surveys and mentor interviews illustrated improved student ability to work in teams, self-lead, and engage in systems-level thinking through the course. Students improved their PSQI knowledge and comfort levels while also appreciating its importance. Conclusion The findings from our study suggest that undergraduate medical students can be provided with an enriching leadership and PSQI experience through the implementation of faculty-mentored but student-led groups at the core of the curricular intervention. As students enter their clinical years, their first-hand PSQI experience will serve them well in increasing their capacity and confidence to take on leadership roles.
Robust Damage Detection and Localization Under Complex Environmental Conditions Using Singular Value Decomposition-based Feature Extraction and One-dimensional Convolutional Neural Network
Authors: Zong Shengkang , Wang Sheng , Luo Zhitao , Wu Xinkai , Zhang Hui , Ni Zhonghua 
Published: May 2023

AbstractUltrasonic guided wave is an attractive monitoring technique for large-scale structures but is vulnerable to changes in environmental and operational conditions (EOC), which are inevitable in the normal inspection of civil and mechanical structures. This paper thus presents a robust guided wave-based method for damage detection and localization under complex environmental conditions by singular value decomposition-based feature extraction and one-dimensional convolutional neural network (1D-CNN). After singular value decomposition-based feature extraction processing, a temporal robust damage index (TRDI) is extracted, and the effect of EOCs is well removed. Hence, even for the signals with a very large temperature-varying range and low signal-to-noise ratios (SNRs), the final damage detection and localization accuracy retain perfect 100%. Verifications are conducted on two different experimental datasets. The first dataset consists of guided wave signals collected from a thin aluminum plate with artificial noises, and the second is a publicly available experimental dataset of guided wave signals acquired on a composite plate with a temperature ranging from 20°C to 60°C. It is demonstrated that the proposed method can detect and localize the damage accurately and rapidly, showing great potential for application in complex and unknown EOC.
Improvement of straw decomposition and rice growth through co-application of straw-decomposing inoculants and ammonium nitrogen fertilizer
Authors: Liu Wei , Tang Jichao , Zhang Dahong , Jiang Xun , Lu Bilin , Yang Wenjia 
Published: May 2023

Abstract
Background
The growth of rice is reduced by the slow decomposition of accumulated straw, which competes with rice for soil nitrogen nutrient. In recent year, straw-decomposing inoculants (SDIs) that can accelerate straw decomposition and ammonium nitrogen (N) fertilizer that can quickly generate available N is increasingly adopted in China. However, it is still unknown whether the N demand of straw decomposition and crop growth can be simultaneously met through the co-application of SDIs and ammonium N fertilizer.

Results
In this study, we investigated the effect of the co-application of SDIs and ammonium bicarbonate on decomposition rate of wheat straw, rice growth and rice yield over two consecutive years in rice-wheat rotation system. Compound fertilizer (A0) was used as control. The ratios of ammonium bicarbonate addition were 20% (A2), 30% (A3) and 40% (A4), respectively, without SDIs or with SDIs (IA2, IA3, IA4). Our results revealed that without SDIs, compared with A0, straw decomposition rate, rice growth and yield were improved under A2; However, under A3, rice yield was decreased due to the slow decomposition rate of straw and limited growth of rice during late growth stage. Combining SDIs and N fertilizer increased straw decomposition rate, rice growth rate and yield more than that of N fertilizer alone, especially under IA3. Compared with A0, straw decomposition rate, tiller number, aboveground biomass, leaf area index, root length, and nitrogen use efficiency were significantly increased by 16%, 8%, 27%, 12%, 17%, and 15% under IA3. Consequently, the average rice yield of IA3 was increased to 10,856 kg/ha, which was 13% and 9% higher, respectively, than of A0 and A2.

Conclusion
Our results indicated that ammonium bicarbonate application alone carried a risk of nutrient deficiency during late growth stage and yield decline. Therefore, the co-application of SDIs and 30% ammonium N fertilizer substitution can be a favorable practice to simultaneously accelerate straw decomposition and increase rice crop growth.
High expression of PPFIA1 in human esophageal squamous cell carcinoma correlates with tumor metastasis and poor prognosis
Authors: Gao Yongyin , Guan Lizhao , Jia Ran , Xiao Wanyi , Han Youming , Li Yue , Tang Peng , Yu Zhentao , Zhang Hongdian 
Published: May 2023

Abstract
Background
PTPRF interacting protein alpha 1 (PPFIA1) is reportedly related to the occurrence and progression of several kinds of malignancies. However, its role in esophageal squamous cell carcinoma (ESCC) is unclear. This current study investigated the prognostic significance and biological functions of PPFIA1 in ESCC.

Methods
Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), and Gene Expression Omnibus (GEO) were used to investigate PPFIA1 expression in esophageal cancer. The relationship between PPFIA1 expression and clinicopathological characteristics and patient survival was evaluated in GSE53625 dataset, and verified in the cDNA array based on qRT–PCR and tissue microarray (TMA) dataset based on immunohistochemistry. The impact of PPFIA1 on the migration and invasion of cancer cells were investigated by wound-healing and transwell assays, respectively.

Results
The expression of PPFIA1 was obviously increased in ESCC tissues versus adjacent esophageal tissues according to online database analyses (all P < 0.05). High PPFIA1 expression was closely related to several clinicopathological characteristics, including tumor location, histological grade, tumor invasion depth, lymph node metastasis, and tumor-node-metastasis (TNM) stage. High PPFIA1 expression was related to worse outcomes and was identified as an independent prognostic factor of overall survival in ESCC patients (GSE53625 dataset, P = 0.019; cDNA array dataset, P < 0.001; TMA dataset, P = 0.039). Downregulation of PPFIA1 expression can significantly reduce the migration and invasion ability of ESCC cells.

Conclusion
PPFIA1 is related to the migration and invasion of ESCC cells, and can be used as a potential biomarker to evaluate the prognosis of ESCC patients.
Psychometrics evaluation of the university student engagement inventory in online learning among Arab students
Authors: Sharif-Nia Hamid , Marôco João , Rahmatpour Pardis , Ghahrani Nassim , Muhammad Ibrahim Fatima , Mohammad Ibrahim Maryam , Kaveh Omolhoda 
Published: May 2023

Abstract
Aim
Student’ engagement is a predictor of various educational outcomes, and it is a key factor in perceived learning. This study aims to investigate the psychometric properties of University Student Engagement Inventory (USEI) among students of Arab universities.

Methods
In this cross-sectional methodological study 525 Arab university students participated. Data was collected from December 2020 to January 2021. The confirmatory factor analysis used for construct validity, reliability and Invariance analysis for Sex were evaluated.

Results
Confirmatory factor analysis indices confirmed the good model fit to the data (CFIscl=0.977, NFIscl=0.974, TLIscl=0.972, SRMR = 0.036, RMSEAscl=0.111, n = 525). All tested models showed strong invariance of the USEI between male and females. There was also evidence of convergent (AVE > 0.7 for all the scales) and discriminant validity (HTMT > 0.75 for all scales). Reliability evidence for the USEI measures in the sample of Arabic students was high (αordinal and ω above 0.86).

Conclusion
The results of this study support the validity and reliability of the USEI with 15 items and 3 factors and demonstrate the importance of students’ engagement in the learning process, academic progress, and self-directed learning.
Early sex-dependent differences in metabolic profiles of overweight and adiposity in young children: a cross-sectional analysis
Authors: Azab Sandi M , Shanmuganathan Meera , de Souza Russell J , Kroezen Zachary , Desai Dipika , Williams Natalie C , Morrison Katherine M , Atkinson Stephanie A , Teo Koon K , Azad Meghan B , Simons Elinor , Moraes Theo J , Mandhane Piush J , Turvey Stuart E , Subbarao Padmaja , Britz-McKibbin Philip , Anand Sonia S 
Published: May 2023

Abstract
Background
Childhood obesity is a global health concern and can lead to lifetime cardiometabolic disease. New advances in metabolomics can provide biochemical insights into the early development of obesity, so we aimed to characterize serum metabolites associated with overweight and adiposity in early childhood and to stratify associations by sex.

Methods
Nontargeted metabolite profiling was conducted in the Canadian CHILD birth cohort (discovery cohort) at age 5 years (n = 900) by multisegment injection-capillary electrophoresis-mass spectrometry. Clinical outcome was defined using novel combined measures of overweight (WHO-standardized body mass index ≥ 85th percentile) and/or adiposity (waist circumference ≥ 90th percentile). Associations between circulating metabolites and child overweight/adiposity (binary and continuous outcomes) were determined by multivariable linear and logistic regression, adjusting for covariates and false discovery rate, and by subsequent sex-stratified analysis. Replication was assessed in an independent replication cohort called FAMILY at age 5 years (n = 456).

Results
In the discovery cohort, each standard deviation (SD) increment of branched-chain and aromatic amino acids, glutamic acid, threonine, and oxoproline was associated with 20–28% increased odds of overweight/adiposity, whereas each SD increment of the glutamine/glutamic acid ratio was associated with 20% decreased odds. All associations were significant in females but not in males in sex-stratified analyses, except for oxoproline that was not significant in either subgroup. Similar outcomes were confirmed in the replication cohort, where associations of aromatic amino acids, leucine, glutamic acid, and the glutamine/glutamic acid ratio with childhood overweight/adiposity were independently replicated.

Conclusions
Our findings show the utility of combining measures of both overweight and adiposity in young children. Childhood overweight/adiposity at age 5 years has a specific serum metabolic phenotype, with the profile being more prominent in females compared to males.
The role and metabolic adaptations of neutrophils in premetastatic niches
Authors: Chen Enli , Yu Jing 
Published: May 2023

AbstractIt has been found that tumor cells create microenvironments in distant organs that promote their survival and growth in advance of their arrival. These predetermined microenvironments are referred to as “pre-metastatic niches”. Increasing attention is being paid to neutrophils’ role in forming the pre-metastatic niche. As major components of the pre-metastatic niche, tumor-associated neutrophils (TANs) play an important role in the formation of the pre-metastatic niche through communication with multiple growth factors, chemokines, inflammatory factors, and other immune cells, which together create a pre-metastatic niche well suited for tumor cell seeding and growth. However, how TANs modulate their metabolism to survive and exert their functions in the process of metastasis remains largely to be discovered. Accordingly, the objective of this review is to assess the role that neutrophils play in the formation of pre-metastatic niche and to explore the metabolism alteration of neutrophils in cancer metastasis. A better understanding of the role of TANs in pre-metastatic niche will help us discover new mechanisms of metastasis and develop new therapies targeting TANs.
An optimal spatial-filtering method derived from eigenvalue perturbation for extending the Courant-Friedrichs-Lewy stability limit
Authors: Miao Zhongzheng , Zhang Jinhai 
Published: May 2023

Explicit time-marching schemes are widely used in numerical simulations. However, their maximum time step is constrained by the Courant-Friedrichs-Lewy (CFL) stability limit. Two methods have been developed to extend this limit: (1) the eigenvalue perturbation method, which exhibits high numerical accuracy but incurs unaffordable memory demand and computational costs, even for middle-scale models, and (2) the spatial-filtering method, which can be implemented easily but results in significant numerical errors under large time steps. However, the intrinsic relationship between these two methods remains unknown. We reveal the intrinsic relationship between these two methods by considering the eigenvalue perturbation method for a homogeneous model. Using this relationship, we derive an analytical spatial filter for the homogeneous model and develop an optimal spatial filter for heterogeneous models. Compared to the classical spatial-filtering method, which removes all high-wavenumber components, our method retains all high-wavenumber components that contribute to wave propagation while eliminating other high-wavenumber components that cause instability. For the same numerical accuracy, the maximum time step allowed by the proposed method is approximately twice that of the classical spatial-filtering method. Compared to the eigenvalue perturbation method, our method can be used in large-scale models without additional memory consumption and computational cost. This can significantly accelerate the pseudospectral method with significantly larger time steps beyond the CFL stability limit, which is particularly promising for large-scale models with a fine grid.
Deficiency in hereditary hemorrhagic telangiectasia-associated Endoglin elicits hypoxia-driven heart failure in zebrafish
Authors: Lelièvre Etienne , Bureau Charlotte , Bordat Yann , Frétaud Maxence , Langevin Christelle , Jopling Chris , Kissa Karima 
Published: May 2023

ABSTRACT
Hereditary hemorrhagic telangiectasia (HHT) is a rare genetic disease caused by mutations affecting components of bone morphogenetic protein (BMP)/transforming growth factor-β (TGF-β) signaling in endothelial cells. This disorder is characterized by arteriovenous malformations that are prone to rupture, and the ensuing hemorrhages are responsible for iron-deficiency anemia. Along with activin receptor-like kinase (ALK1), mutations in endoglin are associated with the vast majority of HHT cases. In this study, we characterized the zebrafish endoglin locus and demonstrated that it produces two phylogenetically conserved protein isoforms. Functional analysis of a CRISPR/Cas9 zebrafish endoglin mutant revealed that Endoglin deficiency is lethal during the course from juvenile stage to adulthood. Endoglin-deficient zebrafish develop cardiomegaly, resulting in heart failure and hypochromic anemia, which both stem from chronic hypoxia. endoglin mutant zebrafish display structural alterations of the developing gills and underlying vascular network that coincide with hypoxia. Finally, phenylhydrazine treatment demonstrated that lowering hematocrit/blood viscosity alleviates heart failure and enhances the survival of Endoglin-deficient fish. Overall, our data link Endoglin deficiency to heart failure and establish zebrafish as a valuable HHT model.
Effectiveness of irinotecan plus trabectedin on a desmoplastic small round cell tumor patient-derived xenograft
Authors: Zuco Valentina , Pasquali Sandro , Tortoreto Monica , Percio Stefano , Doldi Valentina , Barisella Marta , Collini Paola , Dagrada Gian Paolo , Brich Silvia , Gasparini Patrizia , Fiore Marco , Casanova Michela , Frezza Anna Maria , Gronchi Alessandro , Stacchiotti Silvia , Ferrari Andrea , Zaffaroni Nadia 
Published: May 2023

ABSTRACT
This study exploited a novel patient-derived xenograft (PDX) of desmoplastic small round cell tumor (DSRCT), which reproduces histomorphological and molecular characteristics of the clinical tumor, to assess the activity of cytotoxic and targeted anticancer agents. Antitumor effect was moderate for doxorubicin, pazopanib and larotrectenib [maximum tumor volume inhibition (max TVI), 55-66%], while trabectedin had higher activity (max TVI, 82%). Vinorelbine, irinotecan and eribulin achieved nearly complete tumor growth inhibition (max TVI, 96-98%), although tumors regrew after the end of treatment. The combination of irinotecan with either eribulin or trabectedin resulted in complete responses, which were maintained until the end of the experiment for irinotecan plus trabectedin. Irinotecan-based combinations nearly abrogated the expression of proteins of the G2/M checkpoint, preventing cell entrance in mitosis, and induced apoptotic and necroptotic cell death. Consistently, irinotecan plus trabectedin resulted in reprogramming of DSCRT transcriptome, with downregulation of E2F targets, G2/M checkpoint and mitotic spindle gene sets. This study emphasizes the importance of patient-derived preclinical models to explore new treatments for DSRCT and fosters clinical investigation into the activity of irinotecan plus trabectedin.
Leader peptide or pro-segment mutants of renin are misrouted to mitochondria in autosomal dominant tubulointerstitial kidney disease
Authors: Schaeffer Céline , De Fusco Maurizio , Pasqualetto Elena , Scolari Caterina , Izzi Claudia , Scolari Francesco , Rampoldi Luca 
Published: May 2023

ABSTRACT
Autosomal dominant tubulointerstitial kidney disease (ADTKD), a rare genetic disorder characterised by progressive chronic kidney disease, is caused by mutations in different genes, including REN, encoding renin. Renin is a secreted protease composed of three domains: the leader peptide that allows insertion in the endoplasmic reticulum (ER), a pro-segment regulating its activity, and the mature part of the protein. Mutations in mature renin lead to ER retention of the mutant protein and to late-onset disease, whereas mutations in the leader peptide, associated with defective ER translocation, and mutations in the pro-segment, leading to accumulation in the ER-to-Golgi compartment, lead to a more severe, early-onset disease. In this study, we demonstrate a common, unprecedented effect of mutations in the leader peptide and pro-segment as they lead to full or partial mistargeting of the mutated proteins to mitochondria. The mutated pre-pro-sequence of renin is necessary and sufficient to drive mitochondrial rerouting, mitochondrial import defect and fragmentation. Mitochondrial localisation and fragmentation were also observed for wild-type renin when ER translocation was affected. These results expand the spectrum of cellular phenotypes associated with ADTKD-associated REN mutations, providing new insight into the molecular pathogenesis of the disease.