bluuebunny/crossref_metadata_2025_split huggingface dataset:
A critical review on polyvinylidene fluoride (PVDF)/zinc oxide (ZnO)-based piezoelectric and triboelectric nanogenerators
Authors: Shee Chirantan , Banerjee Swagata , Bairagi Satyaranjan , Baburaj Aiswarya , Naveen Kumar S K , Aliyana Akshaya Kumar , Mulvihill Daniel M , Alagirusamy R , Ali S Wazed 
Published: April 2024

Abstract
In this current energy crisis era, piezoelectric and triboelectric effects are emerging as promising technologies for energy harvesting. Polyvinylidene fluoride (PVDF) and its copolymers are well-known piezoelectric materials with high piezoelectric coefficients, which are widely used in flexible electronic devices. PVDF is also greatly utilized in the preparation of triboelectric layer due to its higher electronegative nature amongst common polymers. On the other hand, zinc oxide (ZnO) has been widely studied to investigate its multifunctional properties, including piezoelectricity, pyroelectricity and antibacterial activity. This versatile material can be prepared, using low cost and environmentally friendly routes, in various morphologies. Various research has already been performed to capture the synergistic effects of reinforcing ZnO within the PVDF polymeric matrix. This work first describes the basic principles of piezoelectric and triboelectric effects. Thereafter, the piezoelectric and triboelectric performances of PVDF and ZnO-based materials are briefly depicted based on their structures. Finally, the challenges and future scope associated with the mechanical energy harvesting from such materials are highlighted.
Renewable sources with virtual inertia penetration in multi area interconnected AGC using a modified MPC controller
Authors: Vidyarthi Prabhat Kumar , Kumar Ashiwani , Kumari Ankita , Kumar Aaryan 
Published: April 2024

Abstract
The challenge of controlling frequency deviation becomes more difficult as the complexity of a power plant increases. The robustness of the controller has a major impact on the stability of a complex power system (CPS). Due to the hybridization of CPS basic Automatic Generation Control (AGC) controllers (PID, FOPID, and TID), they are insufficient to give optimal performance to a plant. This requires a robust controller. So, a modified MPC controller has been proposed and evaluated by comparing it with several existing controllers, which gives optimal performance in terms of overshoot, undershoot, and settling time and improves its performance approximately 45%. This research discusses a combined AGC model and control for a three-area CPS, where each producing area consists of a thermal plant, a Diesel power plant, and a Solar Thermal Power Plant (STPP). The results of the modified MPC are superior to those of the basic controller compared to several existing controllers. An improved version of Sea-horse Optimization (SHO) has been proposed to optimize the different controller settings. The superiority of the SHO is shown by a comparison with some well-known, current meta-heuristic methods. The higher penetration levels of renewable energy sources (RESs) reduced system inertia which further deteriorate frequency response in CPS. To overcome these challenges, virtual inertia (VI) has been implemented with MPC. VI is applied to improve the performance of the AGC of the interconnected CPS along with emphasizing the nature of intermittent RESs of PV and wind energy. The thorough study findings provide compelling evidence for the effectiveness and efficiency of the recommended control strategies and also point to the possibility of applying them in actual power systems to improve stability and performance.
School racial/ethnic composition, effect modification by caring teacher/staff presence, and mid-/late-life depressive symptoms: findings from the Study of Healthy Aging in African Americans
Authors: Mobley Taylor M , Hayes-Larson Eleanor , Wu Yingyan , Peterson Rachel L , George Kristen M , Gilsanz Paola , Glymour M Maria , Thomas Marilyn D , Barnes Lisa L , Whitmer Rachel A , Mayeda Elizabeth Rose 
Published: April 2024

Abstract
For Black students in the United States, attending schools with a higher proportion of White students is associated with worse mental and physical health outcomes in adolescence/early adulthood. To our knowledge, no prior studies have evaluated the association between school racial/ethnic composition from kindergarten through grade 12 and later-life mental health. In a cohort of Black adults aged ≥50 years in Northern California who retrospectively reported (2017-2020) school racial/ethnic composition for grades 1, 6, 9, and 12, we assessed the association between attending a school with mostly Black students versus not and mid-/late-life depressive symptoms (8-item Patient-Reported Outcomes Measurement Information System (PROMIS) depression score, standardized to the 2000 US adult population) using age-, sex/gender-, southern US birth–, and parental education–adjusted generalized estimating equations, and assessed effect modification by the presence of a caring teacher/staff member. Levels of later-life depressive symptoms were lower among those who attended schools with mostly Black students in grades 1 and 6 (β = −0.12 [95% CI, −0.23 to 0.00] and β = −0.11 [95% CI, −0.22 to 0.00], respectively). In grade 6, this difference was larger for students without an adult at school who cared about them (β = −0.29 [95% CI, −0.51 to −0.07] vs β = −0.04 [95% CI, −0.17 to 0.09]). Among Black Americans, experiencing early schooling with mostly Black students may have later-life mental health benefits; this protective association appears more important for students without the presence of caring teachers/staff.
This article is part of a Special Collection on Mental Health.
GAUSS: a summary-statistics-based R package for accurate estimation of linkage disequilibrium for variants, Gaussian imputation, and TWAS analysis of cosmopolitan cohorts
Authors: Lee Donghyung , Bacanu Silviu-Alin 
Published: April 2024

Abstract

Motivation
As the availability of larger and more ethnically diverse reference panels grows, there is an increase in demand for ancestry-informed imputation of genome-wide association studies (GWAS), and other downstream analyses, e.g. fine-mapping. Performing such analyses at the genotype level is computationally challenging and necessitates, at best, a laborious process to access individual-level genotype and phenotype data. Summary-statistics-based tools, not requiring individual-level data, provide an efficient alternative that streamlines computational requirements and promotes open science by simplifying the re-analysis and downstream analysis of existing GWAS summary data. However, existing tools perform only disparate parts of needed analysis, have only command-line interfaces, and are difficult to extend/link by applied researchers.

Results
To address these challenges, we present Genome Analysis Using Summary Statistics (GAUSS)—a comprehensive and user-friendly R package designed to facilitate the re-analysis/downstream analysis of GWAS summary statistics. GAUSS offers an integrated toolkit for a range of functionalities, including (i) estimating ancestry proportion of study cohorts, (ii) calculating ancestry-informed linkage disequilibrium, (iii) imputing summary statistics of unobserved variants, (iv) conducting transcriptome-wide association studies, and (v) correcting for “Winner’s Curse” biases. Notably, GAUSS utilizes an expansive, multi-ethnic reference panel consisting of 32 953 genomes from 29 ethnic groups. This panel enhances the range and accuracy of imputable variants, including the ability to impute summary statistics of rarer variants. As a result, GAUSS elevates the quality and applicability of existing GWAS analyses without requiring access to subject-level genotypic and phenotypic information.

Availability and implementation
The GAUSS R package, complete with its source code, is readily accessible to the public via our GitHub repository at https://github.com/statsleelab/gauss. To further assist users, we provided illustrative use-case scenarios that are conveniently found at https://statsleelab.github.io/gauss/, along with a comprehensive user guide detailed in Supplementary Text S1.
MEG-PPIS: a fast protein–protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network
Authors: Ding Hongzhen , Li Xue , Han Peifu , Tian Xu , Jing Fengrui , Wang Shuang , Song Tao , Fu Hanjiao , Kang Na 
Published: April 2024

Motivation
Protein–protein interaction sites (PPIS) are crucial for deciphering protein action mechanisms and related medical research, which is the key issue in protein action research. Recent studies have shown that graph neural networks have achieved outstanding performance in predicting PPIS. However, these studies often neglect the modeling of information at different scales in the graph and the symmetry of protein molecules within three-dimensional space.

Results
In response to this gap, this article proposes the MEG-PPIS approach, a PPIS prediction method based on multi-scale graph information and E(n) equivariant graph neural network (EGNN). There are two channels in MEG-PPIS: the original graph and the subgraph obtained by graph pooling. The model can iteratively update the features of the original graph and subgraph through the weight-sharing EGNN. Subsequently, the max-pooling operation aggregates the updated features of the original graph and subgraph. Ultimately, the model feeds node features into the prediction layer to obtain prediction results. Comparative assessments against other methods on benchmark datasets reveal that MEG-PPIS achieves optimal performance across all evaluation metrics and gets the fastest runtime. Furthermore, specific case studies demonstrate that our method can predict more true positive and true negative sites than the current best method, proving that our model achieves better performance in the PPIS prediction task.

Availability and implementation
The data and code are available at https://github.com/dhz234/MEG-PPIS.git.
Exact solution for minimization of root mean square deviation with G-RMSD to determine molecular similarity
Authors: Nabika Tomohiro , Iwata Satoru , Satoh Hiroko 
Published: April 2024

Abstract
Generalized root mean square deviation (G-RMSD) is an optimization method for three-dimensional molecular similarity determination. It calculates the minimum value of RMSD among all the possible one-to-one matchings between the atoms and positions of the molecules. The first paper on G-RMSD introduced two approaches called alternating optimization (AO) and tangent space relaxation (TSR) methods, which give local optimum solutions. We propose here a new method of G-RMSD using a branch-and-bound method (BnB) on isometric transformations, called IsometryOpt, which is mathematically proven to give an exact G-RMSD index, i.e. this method can reach the global optimum solution. The performance of IsometryOpt was compared to AO and TSR, as well as the MatchFastOpt method. IsometryOpt shows better performance than MatchFastOpt for molecules with the same number of atoms. AO and TSR fail to reach exact values in some cases. We also have developed two improved methods to search for all possible matches of a substructure in one or more molecules. One is called IsometrySearch, which uses BnB on isometric transformations. The other is a variant version of MatchFPT, called MatchFPT-delta. Computer experiments indicate that MatchFPT-delta performs better than MatchFPT and IsometrySearch.
For Tuberculosis, Not “To Screen or Not to Screen?” but “Who?” and “How?”
Authors: Farhat Maha Reda , Jacobson Karen Rita 
Published: April 2024

AbstractActive case finding leveraging new molecular diagnostics and chest X-rays with automated interpretation algorithms is increasingly being developed for high-risk populations to drive down tuberculosis incidence. We consider why such an approach did not deliver a decline in tuberculosis prevalence in Brazilian prison populations and what to consider next.
Association Between Causative Pathogen and Occurrence of Infection-Related Glomerulonephritis in Infective Endocarditis
Authors: Shrestha Nabin K , Kanyo Emese C , Nakhoul Georges N , Herlitz Leal C , Gordon Steven M 
Published: April 2024

Abstract
Among patients with pathologically proven infective endocarditis, the association of pathogen with occurrence of infection-related glomerulonephritis (IRGN) was examined in 48 case patients with IRGN and 192 propensity score-matched controls. Bartonella was very strongly associated with IRGN (odds ratio, 38.2 [95% confidence interval, 6.7–718.8]; P &lt; .001); other microorganisms were not.
Genome editing and kidney health
Authors: Tavakolidakhrabadi Nadia , Aulicino Francesco , May Carl J , Saleem Moin A , Berger Imre , Welsh Gavin I 
Published: April 2024

ABSTRACT
Genome editing technologies, clustered regularly interspaced short palindromic repeats (CRISPR)-Cas in particular, have revolutionized the field of genetic engineering, providing promising avenues for treating various genetic diseases. Chronic kidney disease (CKD), a significant health concern affecting millions of individuals worldwide, can arise from either monogenic or polygenic mutations. With recent advancements in genomic sequencing, valuable insights into disease-causing mutations can be obtained, allowing for the development of new treatments for these genetic disorders. CRISPR-based treatments have emerged as potential therapies, especially for monogenic diseases, offering the ability to correct mutations and eliminate disease phenotypes. Innovations in genome editing have led to enhanced efficiency, specificity and ease of use, surpassing earlier editing tools such as zinc-finger nucleases and transcription activator-like effector nucleases (TALENs). Two prominent advancements in CRISPR-based gene editing are prime editing and base editing. Prime editing allows precise and efficient genome modifications without inducing double-stranded DNA breaks (DSBs), while base editing enables targeted changes to individual nucleotides in both RNA and DNA, promising disease correction in the absence of DSBs. These technologies have the potential to treat genetic kidney diseases through specific correction of disease-causing mutations, such as somatic mutations in PKD1 and PKD2 for polycystic kidney disease; NPHS1, NPHS2 and TRPC6 for focal segmental glomerulosclerosis; COL4A3, COL4A4 and COL4A5 for Alport syndrome; SLC3A1 and SLC7A9 for cystinuria and even VHL for renal cell carcinoma. Apart from editing the DNA sequence, CRISPR-mediated epigenome editing offers a cost-effective method for targeted treatment providing new avenues for therapeutic development, given that epigenetic modifications are associated with the development of various kidney disorders. However, there are challenges to overcome, including developing efficient delivery methods, improving safety and reducing off-target effects. Efforts to improve CRISPR-Cas technologies involve optimizing delivery vectors, employing viral and non-viral approaches and minimizing immunogenicity. With research in animal models providing promising results in rescuing the expression of wild-type podocin in mouse models of nephrotic syndrome and successful clinical trials in the early stages of various disorders, including cancer immunotherapy, there is hope for successful translation of genome editing to kidney diseases.
Pericardial agenesis: a case report of a rare congenital heart disease
Authors: Trimarchi Giancarlo , Zito Concetta , Pelaggi Giuseppe , Carerj Scipione , Di Bella Gianluca 
Published: April 2024

Abstract

Background
Pericardial agenesis is a rare congenital heart disease characterized by a variable clinical presentation.

Case summary
A 32-year-old man was sent by an occupational health physician to our health care centre because of pathological electrocardiogram (ECG). On transthoracic echocardiogram, we had some difficulty to obtain a good quality of four-chamber apical view that was shifted upper and laterally towards the left anterior axillary line. Nonetheless, an abnormal diastolic expansion of the apex of the left ventricle (LV) that had an otherwise normal systolic function was detected. A chest X-ray confirmed the leftward shift of the heart, with the elongation of the left border of cardiac silhouette and cardiac MRI, finally revealed the absence of left-sided pericardium associated with a leftward dislocation of the heart and a dysmorphism of the LV apex that appeared rounded and curved. The non-invasive work-up was completed with 48 h long Holter ECG that was unremarkable. The exercise test was also negative for both inducible myocardial ischaemia and arrhythmias. Patient was scheduled for loop-recorder implantation, and a 6-month clinical follow-up was advised.

Discussion
Pericardial agenesis is a rare congenital heart disease associated with an increased risk of cardiac arrhythmias and type A aortic dissection, however its clinical course could be also completely unremarkable. The diagnosis is challenging, and cardiac MRI remains the gold standard imaging modality. In complete left-sided and asymptomatic forms, no treatment is needed. Prognosis is not well established due to both the rarity of disease and extreme variability of clinical presentation.
Glucagon-like peptide-1 receptor agonists use and associations with outcomes in heart failure and type 2 diabetes: data from the Swedish Heart Failure and Swedish National Diabetes Registries
Authors: Wallner Markus , Biber Mattia Emanuele , Stolfo Davide , Sinagra Gianfranco , Benson Lina , Dahlström Ulf , Gudbjörnsdottir Soffia , Cosentino Francesco , Mol Peter G M , Rosano Giuseppe M C , Butler Javed , Metra Marco , Lund Lars H , Ferrannini Giulia , Savarese Gianluigi 
Published: April 2024

Abstract

Aims
To assess the use and associations with outcomes of glucagon-like peptide-1 receptor agonists (GLP-1 RA) in a real-world population with heart failure (HF) and type 2 diabetes mellitus (T2DM).

Methods and results
The Swedish HF Registry was linked with the National Diabetes Registry and other national registries. Independent predictors of GLP-1 RA use were assessed by multivariable logistic regressions and associations with outcomes were assessed by Cox regressions in a 1:1 propensity score-matched cohort. Of 8188 patients enrolled in 2017–21, 9% received a GLP-1 RA. Independent predictors of GLP-1 RA use were age &lt;75 years, worse glycaemic control, impaired renal function, obesity, and reduced ejection fraction (EF). GLP-1 RA use was not significantly associated with a composite of HF hospitalization (HHF) or cardiovascular (CV) death regardless of EF, but was associated with a lower risk of major adverse CV events (CV death, non-fatal stroke/transient ischaemic attack, or myocardial infarction), and CV and all-cause death. In patients with body mass index ≥30 kg/m2, GLP-1 RA use was also associated with a lower risk of HHF/CV death and HHF alone.

Conclusions
In patients with HF and T2DM, GLP-1 RA use was independently associated with more severe T2DM, reduced EF, and obesity and was not associated with a higher risk of HHF/CV death but with longer survival and less major CV adverse events. An association with lower HHF/CV death and HHF was observed in obese patients. Our findings provide new insights into GLP-1 RA use and its safety in HF and T2DM.
To block or not: why the British ruling elite enabled the Industrial Revolution during the 18th century
Authors: Gulsunar Emrah 
Published: April 2024

Abstract
This study explores why the ruling elite in 18th-century Britain not only allowed but actively supported industrialization. Economic rents, political power, and international competition are commonly cited as the reasons, but these explanations lack empirical evidence. By conducting a text analysis of parliamentary legislation and debates on the cotton industry, this study demonstrates that the ruling elite was primarily motivated by keeping unemployment low and sustaining the British economy’s international competitiveness. A favorable political system facilitated the realization of the elite’s objectives.
Accurate prediction equations for ventilatory thresholds in cardiometabolic disease when gas exchange analysis is unavailable: development and validation
Authors: Milani Juliana Goulart Prata Oliveira , Milani Mauricio , Machado Felipe Vilaça Cavallari , Wilhelm Matthias , Marcin Thimo , D’Ascenzi Flavio , Cavigli Luna , Keytsman Charly , Falter Maarten , Bonnechere Bruno , Meesen Raf , Braga Fabrício , Cipriano Graziella França Bernardelli , Cornelissen Veronique , Verboven Kenneth , Cipriano Junior Gerson , Hansen Dominique 
Published: April 2024

Abstract

Aims
To develop and validate equations predicting heart rate (HR) at the first and second ventilatory thresholds (VTs) and an optimized range-adjusted prescription for patients with cardiometabolic disease (CMD). To compare their performance against guideline-based exercise intensity domains.

Methods and results
Cross-sectional study involving 2868 CMD patients from nine countries. HR predictive equations for first and second VTs (VT1, VT2) were developed using multivariate linear regression with 975 cycle-ergometer cardiopulmonary exercise tests (CPET). ‘Adjusted’ percentages of peak HR (%HRpeak) and HR reserve (%HRR) were derived from this group. External validation with 1893 CPET (cycle-ergometer or treadmill) assessed accuracy, agreement, and reliability against guideline-based %HRpeak and %HRR prescriptions using mean absolute percentage error (MAPE), Bland–Altman analyses, intraclass correlation coefficients (ICC). HR predictive equations (R²: 0.77 VT1, 0.88 VT2) and adjusted %HRR (VT1: 42%, VT2: 77%) were developed. External validation demonstrated superiority over widely used guideline-directed intensity domains for %HRpeak and %HRR. The new methods showed consistent performance across both VTs with lower MAPE (VT1: 7.1%, VT2: 5.0%), ‘good’ ICC for VT1 (0.81, 0.82) and ‘excellent’ for VT2 (0.93). Guideline-based exercise intensity domains had higher MAPE (VT1: 6.8–21.3%, VT2: 5.1–16.7%), ‘poor’ to ‘good’ ICC for VT1, and ‘poor’ to ‘excellent’ for VT2, indicating inconsistencies related to specific VTs across guidelines.

Conclusion
Developed and validated HR predictive equations and the optimized %HRR for CMD patients for determining VT1 and VT2 outperformed the guideline-based exercise intensity domains and showed ergometer interchangeability. They offer a superior alternative for prescribing moderate intensity exercise when CPET is unavailable.