bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of a low-cost, environment friendly perovskite solar cell with synergic effect of graphene oxide-based HTL and CH3NH3GeI3 as ETL
Authors: Chaudhary Akhilesh Kumar , Verma Sudhanshu , Chauhan R K 
Published: August 2023

Abstract
This research explores a novel, environment friendly perovskite solar cell (PSC) featuring a lead-free CH3NH3SnI3 absorber layer, capitalizing on tin’s analogous electronic configuration and chemical properties to lead. Tin-based perovskite exhibits similar optoelectronic features to lead-based perovskite, such as high absorption coefficient and long carrier diffusion length and tin’s higher abundance than lead renders it a cost-effective and promising alternative for PSCs. The proposed PSC employs an FTO/CH3NH3GeI3/CH3NH3SnI3/GO/C structure, incorporating graphene oxide (GO) as the hole transport layer (HTL) and CH3NH3GeI3 as the electron transport layer (ETL). Graphene oxide, renowned for its exceptional electrical conductivity and low processing costs, enables efficient hole transfer, while the use of CH3NH3GeI3 as ETL not only ensures seamless electron transfer due to its compatible crystallographic structure with CH3NH3SnI3 but also mitigates interface defects, making it a critical aspect of the design. Carbon is used as the back contact, providing a cost-effective option to increase sustainability. The absorber layer parameters, such as the thickness of the absorber layer and acceptor density, are optimized. The effects of defect density, interface defects of HTL/absorber and ETL/absorber, as well as series and shunt resistance, are also analyzed. By optimizing absorber layer parameters, the solar cell attains a power conversion efficiency (PCE) of 24.11% and a fill factor exceeding 85% within the visible light spectrum range, showcasing the potential for a high-performance, environment friendly, and cost-effective solar cell substitute. Device simulations were performed using the SCAPS-1D tool.
Gender- and Age-Related Characterization of Lip Morphology: A Three-Dimensional Analysis in a Chinese Population
Authors: Yang Yuyan , Zhang Mengyuan , Jin Lin , Long Xiao , Zeng Ang , Yu Nanze , Wang Xiaojun 
Published: August 2023

Abstract

Background
Establishing facial anthropometric reference values is essential for diagnosis of deformity, assessment of aging, and planning for aesthetic and reconstructive treatment.

Objectives
This study aimed to provide detailed perioral anthropometric data in relation to sex and age in Chinese persons with a standardized 3-dimensional protocol.

Methods
Three-dimensional facial photographs were obtained of 60 male and 64 female healthy Chinese participants ages 20 to 35 and 50 to 65 years old, as well as 2 acromegaly patients, with the VECTRA 3D camera. A standardized evaluation was performed to locate 37 perioral landmarks and generate corresponding measurements, including 26 linear distances, 5 ratios, 2 curvatures, 4 areas, and 9 angles. Measurements of different age groups and of different genders were compared, as were measurements of healthy individuals with those of acromegaly patients.

Results
Sex discrepancy was noted in philtrum length, width, and area, lip width, and vermilion and cutaneous upper lip area; these were larger in Chinese males than females. However, vermilion heights were similar in both genders. With age, philtrum and cutaneous upper lip height and area, lip width, and angles related to cupid's bow significantly increased, whereas vermilion height and mouth corner angles decreased, and philtrum width, vermilion areas, and lip protrusion remained unchanged. Compared to healthy Chinese patients, acromegaly patients had a larger value for most measurements. Perioral rejuvenation based on detailed 3-dimensional anthropometry showed good results.

Conclusions
Chinese males have wider but not thicker lips than females, and aging features thin, flattened, and wide vermilions with a lengthened philtrum in both genders. These data can serve as a reference standard for disease diagnosis, aesthetic procedures, and reconstructive lip surgeries.

Level of Evidence: 4
AntiRef: reference clusters of human antibody sequences
Authors: Briney Bryan 
Published: August 2023

Abstract

Motivation
Genetic biases in the human antibody repertoire result in publicly available antibody sequence datasets that contain many duplicate or highly similar sequences. Available datasets are further skewed by the predominance of studies focused on specific disease states, primarily cancer, autoimmunity, and a small number of infectious diseases that includes HIV, influenza, and SARS-CoV-2. These biases and redundancies are a barrier to rapid similarity searches and reduce the efficiency with which these datasets can be used to train statistical or machine-learning models. Identity-based clustering provides a solution; however, the extremely large size of available antibody sequence datasets makes such clustering operations computationally intensive and potentially out of reach for many scientists and researchers who would benefit from such data.

Results
Antibody Reference Clusters (AntiRef), which is modeled after UniRef, provides clustered datasets of filtered human antibody sequences. Due to the modular nature of recombined antibody genes, the clustering thresholds used by UniRef for general protein sequences are suboptimal for antibody clustering. Starting with an input dataset of ∼451M full-length, productive human antibody sequences, AntiRef provides reference datasets clustered at a range of antibody-optimized identity thresholds. AntiRef90 is one-third the size of the input dataset and less than half the size of the non-redundant AntiRef100.

Availability and implementation
AntiRef datasets are available on Zenodo (zenodo.org/record/7474336). All code used to generate AntiRef is available on GitHub (github.com/briney/antiref). The AntiRef versioning scheme (current version: v2022.12.14) refers to the date on which sequences were retrieved from OAS.
Pretrained transformer models for predicting the withdrawal of drugs from the market
Authors: Mazuz Eyal , Shtar Guy , Kutsky Nir , Rokach Lior , Shapira Bracha 
Published: August 2023

Abstract

Motivation
The process of drug discovery is notoriously complex, costing an average of 2.6 billion dollars and taking ∼13 years to bring a new drug to the market. The success rate for new drugs is alarmingly low (around 0.0001%), and severe adverse drug reactions (ADRs) frequently occur, some of which may even result in death. Early identification of potential ADRs is critical to improve the efficiency and safety of the drug development process.

Results
In this study, we employed pretrained large language models (LLMs) to predict the likelihood of a drug being withdrawn from the market due to safety concerns. Our method achieved an area under the curve (AUC) of over 0.75 through cross-database validation, outperforming classical machine learning models and graph-based models. Notably, our pretrained LLMs successfully identified over 50% drugs that were subsequently withdrawn, when predictions were made on a subset of drugs with inconsistent labeling between the training and test sets.

Availability and implementation
The code and datasets are available at https://github.com/eyalmazuz/DrugWithdrawn.
Coherent pathway enrichment estimation by modeling inter-pathway dependencies using regularized regression
Authors: Jablonski Kim Philipp , Beerenwinkel Niko 
Published: August 2023

AbstractMotivationGene set enrichment methods are a common tool to improve the interpretability of gene lists as obtained, for example, from differential gene expression analyses. They are based on computing whether dysregulated genes are located in certain biological pathways more often than expected by chance. Gene set enrichment tools rely on pre-existing pathway databases such as KEGG, Reactome, or the Gene Ontology. These databases are increasing in size and in the number of redundancies between pathways, which complicates the statistical enrichment computation.ResultsWe address this problem and develop a novel gene set enrichment method, called pareg, which is based on a regularized generalized linear model and directly incorporates dependencies between gene sets related to certain biological functions, for example, due to shared genes, in the enrichment computation. We show that pareg is more robust to noise than competing methods. Additionally, we demonstrate the ability of our method to recover known pathways as well as to suggest novel treatment targets in an exploratory analysis using breast cancer samples from TCGA.Availability and implementationpareg is freely available as an R package on Bioconductor (https://bioconductor.org/packages/release/bioc/html/pareg.html) as well as on https://github.com/cbg-ethz/pareg. The GitHub repository also contains the Snakemake workflows needed to reproduce all results presented here.
metGWAS 1.0: an R workflow for network-driven over-representation analysis between independent metabolomic and meta-genome-wide association studies
Authors: Khan Saifur R , Obersterescu Andreea , Gunderson Erica P , Razani Babak , Wheeler Michael B , Cox Brian J 
Published: August 2023

Abstract

Motivation
The method of genome-wide association studies (GWAS) and metabolomics combined provide an quantitative approach to pinpoint metabolic pathways and genes linked to specific diseases; however, such analyses require both genomics and metabolomics datasets from the same individuals/samples. In most cases, this approach is not feasible due to high costs, lack of technical infrastructure, unavailability of samples, and other factors. Therefore, an unmet need exists for a bioinformatics tool that can identify gene loci-associated polymorphic variants for metabolite alterations seen in disease states using standalone metabolomics.

Results
Here, we developed a bioinformatics tool, metGWAS 1.0, that integrates independent GWAS data from the GWAS database and standalone metabolomics data using a network-based systems biology approach to identify novel disease/trait-specific metabolite-gene associations. The tool was evaluated using standalone metabolomics datasets extracted from two metabolomics-GWAS case studies. It discovered both the observed and novel gene loci with known single nucleotide polymorphisms when compared to the original studies.

Availability and implementation
The developed metGWAS 1.0 framework is implemented in an R pipeline and available at: https://github.com/saifurbd28/metGWAS-1.0.
MULGA, a unified multi-view graph autoencoder-based approach for identifying drug–protein interaction and drug repositioning
Authors: Ma Jiani , Li Chen , Zhang Yiwen , Wang Zhikang , Li Shanshan , Guo Yuming , Zhang Lin , Liu Hui , Gao Xin , Song Jiangning 
Published: August 2023

Abstract

Motivation
Identifying drug–protein interactions (DPIs) is a critical step in drug repositioning, which allows reuse of approved drugs that may be effective for treating a different disease and thereby alleviates the challenges of new drug development. Despite the fact that a great variety of computational approaches for DPI prediction have been proposed, key challenges, such as extendable and unbiased similarity calculation, heterogeneous information utilization, and reliable negative sample selection, remain to be addressed.

Results
To address these issues, we propose a novel, unified multi-view graph autoencoder framework, termed MULGA, for both DPI and drug repositioning predictions. MULGA is featured by: (i) a multi-view learning technique to effectively learn authentic drug affinity and target affinity matrices; (ii) a graph autoencoder to infer missing DPI interactions; and (iii) a new “guilty-by-association”-based negative sampling approach for selecting highly reliable non-DPIs. Benchmark experiments demonstrate that MULGA outperforms state-of-the-art methods in DPI prediction and the ablation studies verify the effectiveness of each proposed component. Importantly, we highlight the top drugs shortlisted by MULGA that target the spike glycoprotein of severe acute respiratory syndrome coronavirus 2 (SAR-CoV-2), offering additional insights into and potentially useful treatment option for COVID-19. Together with the availability of datasets and source codes, we envision that MULGA can be explored as a useful tool for DPI prediction and drug repositioning.

Availability and implementation
MULGA is publicly available for academic purposes at https://github.com/jianiM/MULGA/.
Clinical features and imaging characteristics in achiasmia
Authors: Pilat Anastasia , McLean Rebecca J , Vanina Anna , Dineen Robert A , Gottlob Irene 
Published: August 2023

Abstract
Achiasmia is a rare visual pathway maldevelopment with reduced decussation of the axons in the optic chiasm. Our aim was to investigate clinical characteristics, macular, optic nerve and brain morphology in achiasmia. A prospective, cross-sectional, observational study of 12 participants with achiasmia [8 males and 4 females; 29.6 ± 18.4 years (mean ± standard deviation)] and 24 gender-, age-, ethnicity- and refraction-matched healthy controls was done. Full ophthalmology assessment, eye movement recording, a high-resolution spectral-domain optical coherence tomography of the macular and optic disc, five-channel visual-evoked responses, eye movement recordings and MRI scans of the brain and orbits were acquired. Achiasmia was confirmed in all 12 clinical participants by visual-evoked responses. Visual acuity in this group was 0.63 ± 0.19 and 0.53 ± 0.19 for the right and left eyes, respectively; most participants had mild refractive errors. All participants with achiasmia had see-saw nystagmus and no measurable stereo vision. Strabismus and abnormal head position were noted in 58% of participants. Optical coherence tomography showed optic nerve hypoplasia with associated foveal hypoplasia in four participants. In the remaining achiasmia participants, macular changes with significantly thinner paracentral inner segment (P = 0.002), wider pit (P = 0.04) and visual flattening of the ellipsoid line were found. MRI demonstrated chiasmatic aplasia in 3/12 (25%), chiasmatic hypoplasia in 7/12 (58%) and a subjectively normal chiasm in 2/12 (17%). Septo-optic dysplasia and severe bilateral optic nerve hypoplasia were found in three patients with chiasmic aplasia/hypoplasia on MRI. In this largest series of achiasmia patients to date, we found for the first time that neuronal abnormalities occur already at the retinal level. Foveal changes, optic nerve hypoplasia and the midline brain anomaly suggest that these abnormalities could be part of the same spectrum, with different manifestations of events during foetal development occurring with varying severity.
Short-term percutaneous mechanical circulatory support: no promise without positioning!
Authors: Balthazar Tim , Van Mieghem Nicolas M , Raes Matthias , Van Loo Ines , Verbrugge Frederik H 
Published: August 2023

Abstract
Short-term percutaneous mechanical circulatory support by a micro-axial flow pump is increasingly used to support the left ventricle in cardiogenic shock. After a correct indication and placement, appropriate device management in the cardiac intensive care unit is vital to ensure optimal pump function and adequate haemodynamic support. A key element hereby is a correct percutaneous ventricular assist device (pVAD) position. This review explains how an optimal left-sided pVAD position can be achieved and maintained, focusing on the correct insertion depth and rotational angle. Useful imaging techniques, placement and replacement manoeuvres, and monitoring options through the console are discussed. The frequently encountered problem of mal-rotation towards the mitral valve, which may cause suction alarms, haemolysis, aortic regurgitation, and inadequate haemodynamic support, is explained. Finally, a practical bedside approach to assess pVAD position and discern suction alarms due to mal-positioning from haemodynamic problems is proposed.
Comparative genome analysis of the freshwater fungus Filosporella fistucella indicates potential for plant-litter degradation at cold temperatures
Authors: Vasconcelos Rissi Daniel , Ijaz Maham , Baschien Christiane 
Published: August 2023

Abstract
Freshwater fungi play an important role in the decomposition of organic matter of leaf litter in rivers and streams. They also possess the necessary mechanisms to endure lower temperatures caused by habitat and weather variations. This includes the production of cold-active enzymes and antifreeze proteins. To better understand the physiological activities of freshwater fungi in their natural environment, different methods are being applied, and genome sequencing is one in the spotlight. In our study, we sequenced the first genome of the freshwater fungus Filosporella fistucella (45.7 Mb) and compared the genome with the evolutionary close-related species Tricladium varicosporioides (48.2 Mb). The genomes were annotated using the carbohydrate-active enzyme database where we then filtered for leaf-litter degradation-related enzymes (cellulase, hemicellulase, laccase, pectinase, cutinase, amylase, xylanase, and xyloglucanase). Those enzymes were analyzed for antifreeze properties using a machine-learning approach. We discovered that F. fistucella has more enzymes to participate in the breakdown of sugar, leaf, and wood than T. varicosporioides (855 and 719, respectively). Filosporella fistucella shows a larger set of enzymes capable of resisting cold temperatures than T. varicosporioides (75 and 66, respectively). Our findings indicate that in comparison with T. varicosporioides, F. fistucella has a greater capacity for aquatic growth, adaptability to freshwater environments, and resistance to low temperatures.
Associations Between Change in Kidney Functioning, Age, Race/Ethnicity, and Health Indicators in the Health and Retirement Study
Authors: Zhao Erfei , Ailshire Jennifer , Kim Jung Ki , Wu Qiao , Crimmins Eileen M 
Published: August 2023

Abstract

Background
The aging process is accompanied by decline in kidney functioning. It remains unknown to what extent age-related decline in kidney functioning can be attributed to health indicators, and whether rate of decline differs across sociodemographic groups.

Methods
Using data from the Health and Retirement Study from 2006/2008 through 2014/2016, we estimated kidney functioning trajectories, determined by cystatin C, among adults aged over 51 over 8 years. We evaluated the role of age, health conditions/behaviors, and genetics in the decline and also examined sociodemographic differentials.

Results
Kidney function declined with age and accelerated at older ages, even after adjusting for health conditions/behaviors and genetic differences (eg, 0.019 mg/L annual increase in cystatin C among 70–79 compared to 0.007 mg/L among 52–59 at baseline). Decline occurred faster among those with uncontrolled diabetes (0.008, p = .009), heart conditions (0.007, p &lt; .000), and obesity (0.005, p = .033).Hispanic participants (0.007, p = .039) declined faster than non-Hispanic White persons due to diabetes, heart conditions, and obesity; non-Hispanic Black participants had worse baseline kidney functioning (0.099, p &lt; .000), but only one fourth of this Black–White difference was explained by investigated risk factors. People with higher education experienced slower decline (−0.009, p = .004).

Conclusions
Age was a significant predictor of decline in kidney functioning, and its association was not fully explained by health conditions/behaviors, or genetics. Better management of diabetes, heart conditions, and obesity is effective in slowing this decline. Baseline differences in kidney functioning (eg, between non-Hispanic White and Black persons; those with and without hypertension) suggest disparities occur early in the life course and require early interventions.
Pain, Physical Demands at Work, and Future Work Expectations Among Older Adults in the United States
Authors: Andrasfay Theresa , Fennell Gillian , Crimmins Eileen 
Published: August 2023

Abstract

Background and Objectives
In the United States, pain is becoming increasingly prevalent among older adults at the same time as policies are incentivizing work longer. Given that pain and physically demanding jobs are both linked to early retirement and they often go hand-in-hand, it is important to assess how the unique effects of pain and physical work demands may interact in predicting future work expectations.

Research Design and Methods
Using Health and Retirement Study data (1998, 2004, 2010, and 2016 waves), we assess how pain and physical job demands influence future work expectations of 10,358 adults at midlife (ages 51–56), after accounting for sociodemographic, job, health, and financial characteristics.

Results
Compared to men with no pain, activity-interfering pain was associated with low expectations of full-time work past 62 regardless of job demands, while noninterfering pain was associated with 62% higher odds (odds ratio [OR] = 1.62, 95% confidence interval [CI]: 1.35–1.93) of expecting not to work full-time past age 62 only among those with physically demanding jobs. Having both interfering pain and a physically demanding job was associated with increased odds of expecting not to work full-time past age 65 for men (OR = 1.25, 95% CI: 1.06–1.47) and past age 62 for women (OR = 1.18, 95% CI: 1.00–1.39).

Discussion and Implications
The co-occurrence of physically demanding work with pain—particularly activity-interfering pain—is associated with low expectations of full-time work past ages 62 and 65 for adults at midlife. Working longer may be feasible for older adults whose pain does not interfere with work, but unrealistic for individuals facing both pain and physically demanding work.
Participatory Research Approaches in Alzheimer’s Disease and Related Dementias Literature: A Scoping Review
Authors: Reyes Laurent , Scher Clara J , Greenfield Emily A 
Published: August 2023

Abstract

Background and Objectives
Given the increase in methodological pluralism in research on brain health, cognitive aging, and neurodegenerative diseases, this scoping review aims to provide a descriptive overview and qualitative content analysis of studies stating the use of participatory research approaches within Alzheimer’s disease and related dementias (ADRD) literature globally.

Research Design and Methods
We conducted a systematic search across four multidisciplinary databases (CINAHL, SCOPUS, PsycInfo, PubMed) for peer-reviewed, English-language studies addressing ADRD that explicitly described their use of a participatory research approach. We employed a systematic process for selecting articles that yielded a final sample of 163 studies. Data from articles were analyzed to chart trends from 1990 to 2022 in terminology, descriptions, application of participatory approaches, and the extent and nature of partnerships with nonacademics.

Results
Results demonstrated geographic differences in the use of stated approaches between North America—where community-based participatory research predominates—and Europe, where Action Research is most common. We further found that only 73% of papers in this systematic review had identifiable definitions or descriptions of the participatory approach used. Findings also showed that 14% of articles demonstrated no evidence of engaged partnership beyond activities typical of research participants, while 23% of articles identified partnering with people with dementia, and an additional 16% reported partnerships with members from Indigenous, Black, Asian, or Latinx communities.

Discussion and Implications
This scoping review identifies three areas in need of greater attention in ADRD literature using participatory research approaches. First, findings indicate the importance of strengthening the use, transparency, and rigor of participatory methods. Second, results suggest the need for greater inclusion of historically marginalized groups who are most affected by ADRD as research partners. Finally, the findings highlight the need for integrating social justice values of participatory approaches into research project designs.