bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross-Sectoral Comparisons of Process Quality Indicators of Health Care Across Residential Regions Using Restricted Mean Survival Time
Authors: Šinkovec Hana , Gall Walter , Heinze Georg 
Published: October 2024

Background:
Practice guidelines recommend patient management based on scientific evidence. Quality indicators gauge adherence to such recommendations and assess health care quality. They are usually defined as adverse event rates, which may not fully capture guideline adherence over time.

Methods:
For assessing process indicators where compliance to the recommended treatment can be assessed by evaluating a patient's trace in linked routine databases, we propose using restricted mean survival time or restricted mean time lost, which are applicable even in competing risk situations. We demonstrate their application by assessing the compliance of patients with acute myocardial infarction (AMI) to high-power statins over 12 months in Austria’s political districts, using pseudo-observations and employing causal inference methods to achieve regional comparability.

Results:
We analyzed the compliance of 31,678 AMI patients from Austria’s 116 political districts with index AMI between 2011 and 2015. The results revealed considerable compliance variations across districts but also plausible spatial similarities.

Conclusions:
Restricted mean survival time and restricted mean time lost provide interpretable estimates of patients’ expected time in compliance (lost), well-suited for risk-adjusted entity comparisons in the presence of (measurable) confounding, censoring, and competing risks.
18F-THK5351 PET Is Superior to Conventional MRI in Identifying Inflammatory Lesions by Imaging Astrogliosis in 2 Cases of Neurosyphilis
Authors: Kotani Risa , Hatano Keiko , Ishibashi Kenji , Iwata Atsushi 
Published: October 2024

Abstract

18F-labeled THK5351 PET can visualize ongoing astrogliosis by estimating monoamine oxidase B levels and can be used as a neuroinflammation marker for identifying inflammatory lesions by imaging astrogliosis. Assessment of its performance is of interest, especially when compared with conventional MRI. Here, we present 2 cases of neurosyphilis, in which 18F-THK5351 PET identified inflammatory lesions by imaging astrogliosis, whereas MRI had difficulty detecting the lesions. Hence, this study suggests that 18F-THK5351 PET is superior to conventional MRI in identifying inflammatory lesions and that this feature of 18F-THK5351 can provide insights into the pathophysiology of neurosyphilis in living patients.
Application of 3D-Slicer Software in the Treatment of Gliomas
Authors: Liu Jinkai , Wang Bing 
Published: October 2024

Purpose:
To explore the application of 3D-Slicer multimodal image fusion technology in the surgical treatment of gliomas.

Method:
A retrospective analysis of clinical data from 48 cases of intracranial gliomas treated with 3D-Slicer multimodal image fusion technology from September 2021 to February 2023. Preoperative cranial CT, MRI, TOF-MRA, DTI, and MRV sequence examinations were completed. DICOM format medical imaging data were processed using the 3D-Slicer software. Multimodal fusion and 3-dimensional reconstruction of the tumor and surrounding structures were conducted to clarify the relationship between the tumor and surrounding structures. The surgery path was simulated through 3D virtual visualization images, enabling precise preoperative planning and assisting in surgical treatment.

Results:
Out of 48 patients, complete tumor resection was achieved in 45 cases. One case encountered severe postoperative cerebral edema, no infections were reported, 1 patient had slightly reduced muscle strength after surgery compared with before, and no cases of severe neurological function damage or surgical death were recorded.

Conclusion:
3D-Slicer multimodal image fusion technology can assist in detailed preoperative planning for the surgical treatment of intracranial glioma, reducing surgical complications, improving the rate of total tumor resection, and reducing postoperative complications.
Financial Toxicity in Complex Gastrointestinal Surgery and Correlation with Patient Reported Outcomes
Authors: Young Lindsey , Vergara Rosemary , Henriquez John , Fong Alvis , Al-Assil Talal , Shebrain Saad , Munene Gitonga 
Published: October 2024

Objectives:
To describe financial toxicity (FT) in patients who have undergone gastrointestinal (GI) surgery and its correlation with patients’ emotional (EWB) and social well-being (SWB).

Background:
FT describes the financial burden associated with treatment and its impact on patient outcomes. Few prior studies have examined FT in gastrointestinal surgery and its impact on patient quality of life.

Methods:
Patients who underwent gastrointestinal surgery at our institution were assessed for FT with a validated instrument between Jan 2022 and Jan 2023. EWB and SWB were assessed with a validated instrument. Risk factors for FT were determined using a multivariable model. The correlation between FT and patient EWB and SWB was assessed using Pearson correlation.

Results:
188 patients were surveyed, the majority had pancreatic resections (n = 90, 47.9%), 59 (31.4%) patients experienced FT. On multivariable analysis, categories associated with increased likelihood of exhibiting financial toxicity included single marital status and not receiving chemotherapy and/or radiation therapy, with odds ratio (95% C.I) of [3.02 (1.07, 8.51), P=.037] and [3.86 (1.3, 11.44), P=.015) respectively. Higher EWB and SWB scores directly correlated with higher FT scores.

Conclusion:
Patients undergoing complex gastrointestinal surgery often experience financial toxicity that affects patient reported outcomes. Financial toxicity is associated with identifiable pre-operative factors that can be utilized to screen patients for interventions that may mitigate some of the harmful effects of FT.
What Are the Most Popular Articles in Urogynecology and Who Is Disseminating Them
Authors: Williams Stephanie Nicole , Fitzgerald Jocelyn 
Published: October 2024

Importance
This research describes which articles published in Urogynecology are garnering the most attention online. Understanding which articles are having the largest impact in the online community has become increasingly important due to the exponential increase in the use of social media on the internet.

Objective
The Altmetric Attention Score (AAS) is a quantitative and qualitative measure of the articles’ online attention in social media and news outlets, blogs, and reference managers. The aim of this study was to provide an analysis of those accessing and sharing the 100 most popular articles published in Urogynecology.

Study Design
This was a retrospective descriptive analysis. Using Dimensions, a “linked research knowledge system,” data about each article’s demographics on Twitter and other media sources was extracted from each of the articles within Urogynecology with the highest AAS. No articles were excluded. The articles were categorized by topic and metrics of online sharing were compared among categories.

Results
Fifteen categories were created. Sexual health and education articles had the highest average Altmetric scores per article and reached the highest impressions per article and had the highest average follower count per Twitter user. On average, social justice in medicine had the highest number of tweets per article. Tweets were most often composed by members of the public (58%) compared with health care practitioners (14%), researchers (13%), and science communicators (12%).

Conclusions
Sexual health and education articles had the highest average AAS and impressions on Twitter. We observed a difference in which articles are being shared most among the general public and health care professionals. The general public comprised a majority of those sharing articles online regardless of category. Additionally, there may be a disparity in research, its funding, and online scientific communications within the field of urogynecology.
Variation in Overactive Bladder Treatment Type by Social Determinants of Health
Authors: Muñoz Jaclyn M. , Kim Edward K. , Andy Uduak U. , Mumford Sunni L. , Harvie Heidi S. 
Published: October 2024

Importance
There is limited understanding of the relationship between social determinants of health (SDOH) and types of overactive bladder/urgency urinary incontinence (OAB/UUI) treatments.

Objectives
Our objective was to determine if OAB/UUI treatment type differs by SDOH, including insurance and estimated median household income (EMHI).

Study Design
This was a cross-sectional study of adult patients assigned female at birth with OAB/UUI, identified from 2017 to 2022 within a tertiary academic health system. The primary outcome was any OAB/UUI treatment provision. Secondary outcomes included specific treatments and specialty care. We examined associations between SDOH and OAB/UUI treatments using univariable analysis and multivariable logistic regression.

Results
Among 33,002 patients with OAB/UUI, 15.4% received treatment. Treatment provision was associated with American Indian/Alaska Native or Black/African American race, Latina ethnicity, Medicaid, low-income Medicare, or Medicare Advantage (vs private insurance) and EMHI ranging from $26,500 to $100,000 (compared with EMHI >$100,000). Patients with Black/African American race, Medicaid or no insurance, and EMHI ≤$80,000 had higher odds of anticholinergic prescription and lower odds of β3-agonist prescription. Advanced therapy was associated with traditional Medicare, Medicare Advantage, and EMHI $26,500–$100,000 and negatively associated with Asian race. Specialty care was associated with Black/African American race, Medicaid, Medicare Advantage, no insurance, and EMHI ≤$80,000.

Conclusions
Overactive bladder/urgency urinary incontinence treatment provision was associated with American Indian/Alaska Native and Black/African American race, Latina ethnicity, Medicaid, low-income Medicare, or Medicare Advantage insurance. Patients with Black/African American race and with lower EMHI had higher odds of receiving anticholinergic therapy and lower odds of receiving β3-agonist medication, despite higher likelihood of specialty care.
Measurement Matters: A Metrological Approach to Renal Preimplantation Biopsy Evaluation to Address Uncertainty in Organ Selection
Authors: Ayorinde John O.O. , Loizeau Xavier , Bardsley Victoria , Thomas Spencer Angus , Romanchikova Marina , Samoshkin Alex , Pettigrew Gavin J. 
Published: October 2024

Background.
Preimplantation biopsy combines measurements of injury into a composite index to inform organ acceptance. The uncertainty in these measurements remains poorly characterized, raising concerns variability may contribute to inappropriate clinical decisions.

Methods.
We adopted a metrological approach to evaluate biopsy score reliability. Variability was assessed by performing repeat biopsies (n = 293) on discarded allografts (n = 16) using 3 methods (core, punch, and wedge). Uncertainty was quantified using a bootstrapping analysis. Observer effects were controlled by semi-blinded scoring, and the findings were validated by comparison with standard glass evaluation.

Results.
The surgical method strongly determined the size (core biopsy area 9.04 mm2, wedge 37.9 mm2) and, therefore, yield (glomerular yield r = 0.94, arterial r = 0.62) of each biopsy. Core biopsies yielded inadequate slides most frequently. Repeat biopsy of the same kidney led to marked variation in biopsy scores. In 10 of 16 cases, scores were contradictory, crossing at least 1 decision boundary (ie, to transplant or to discard). Bootstrapping demonstrated significant uncertainty associated with single-slide assessment; however, scores were similar for paired kidneys from the same donor.

Conclusions.
Our investigation highlights the risks of relying on single-slide assessment to quantify organ injury. Biopsy evaluation is subject to uncertainty, meaning each slide is better conceptualized as providing an estimate of the kidney’s condition rather than a definitive result. Pooling multiple assessments could improve the reliability of biopsy analysis, enhancing confidence. Where histological quantification is necessary, clinicians should seek to develop new protocols using more tissue and consider automated methods to assist pathologists in delivering analysis within clinical time frames.
ORCO: Ollivier-Ricci Curvature-Omics — an unsupervised method for analyzing robustness in biological systems
Authors: Simhal Anish K. , Weistuch Corey , Murgas Kevin , Grange Daniel , Zhu Jiening , Oh Jung Hun , Elkin Rena , Deasy Joseph O. 
Published: October 2024

AbstractAlthough recent advanced sequencing technologies have improved the resolution of genomic and proteomic data to better characterize molecular phenotypes, efficient computational tools to analyze and interpret the large-scale omic data are still needed. To address this, we have developed a network-based bioinformatic tool called Ollivier-Ricci curvature-omics (ORCO). ORCO incorporates gene interaction information with omic data into a biological network, and computes Ollivier-Ricci curvature (ORC) values for individual interactions. ORC, an edge-based measure, indicates network robustness and captures global gene signaling changes in functional cooperation using a consistent information passing measure, thereby helping identify therapeutic targets and regulatory modules in biological systems. This tool can be applicable to any data that can be represented as a network. ORCO is an open-source Python package and publicly available on GitHub athttps://github.com/aksimhal/ORC-Omics.
InteracTor: A new integrative feature extraction toolkit for improved characterization of protein structural properties
Authors: Silva Jose Cleydson F. , Schuster Layla , Sexson Nick , Kirst Matias , Resende Marcio F. R. , Dias Raquel 
Published: October 2024

AbstractUnderstanding the structural and functional diversity of protein families is crucial for elucidating their biological roles. Traditional analyses often focus on primary and secondary structures, which include amino acid sequences and local folding patterns like alpha helices and beta sheets. However, primary and secondary structures alone may not fully represent the complex interactions within proteins. To address this limitation, we developed a new algorithm (InteracTor) to analyze proteins by extracting features from their three-dimensional (3D) structures. The toolkit extracts interatomic interaction features such as hydrogen bonds, van der Waals interactions, and hydrophobic contacts, which are crucial for understanding protein dynamics, structure, and function. Incorporating 3D structural data and interatomic interaction features provides a more comprehensive understanding of protein structure and function, potentially enhancing downstream predictive modeling capabilities. By using the extracted features in Mutual Information scoring (MI), Principal Component Analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE), Uniform Manifold Approximation and Projection (UMAP), and hierarchical clustering analysis as use cases, we identified clear separations among protein structural families, highlighting distinct functional aspects. Our analysis revealed that interatomic interaction features were more informative than protein secondary structure features, providing insights into potential structural and functional properties. These findings underscore the significance of considering tertiary structure in protein analysis, offering a robust framework for future studies aiming at enhancing the capabilities of models for protein function prediction and drug discovery.
T-scope V4: miniaturized microscope for optogenetic tagging in freely behaving animals
Authors: Wang Yuteng , Vergara Pablo , Hasegawa Satoshi , Tomita Naoki , Cherasse Yoan , Naoi Toshie , Sakurai Takeshi , Sugaya Yuki , Kano Masanobu , Sakaguchi Masanori 
Published: October 2024

AbstractA miniaturized microscope (i.e., miniscope) enables the imaging of neuronal activity using calcium sensors while simultaneously manipulating that activity using opsins in freely moving animals. However, many miniscopes use light-emitting diodes with broadband emission, leading to unintentional opsin stimulation by light intended solely for calcium sensor activation (a phenomenon referred to as “biological crosstalk”). To address this issue, we previously developed a miniscope including a port for chosen light sources, such as lasers, by restructuring the open-source UCLA Miniscope v3. However, targeting the same neuronal soma for both excitable opsin stimulation and calcium sensor imaging remained a challenge. Here, we integrated features from the UCLA Miniscope v4 into our new T-scope V4 miniscope. In optogenetic tagging experiments, we demonstrated that a 445-nm blue laser can be used to image neuronal activity with the calcium sensor GCaMP6s without inadvertently stimulating the ChrimsonR opsin, allowing for simultaneous neuronal activity imaging and manipulation in freely moving mice. Thus, the T-scope V4 can serve as a powerful tool for probing causal relationships between neuronal activity and its function in living animals.HighlightsWe developed the T-scope V4 that integrates features of the UCLA Miniscope v4This miniscope prevents “biological crosstalk” between sensors and opsinsThis tool can help probe causal brain-behavior relationships in living animals
R3DFEM: an R package for running the 3D-CMCC-FEM model
Authors: Vangi Elia , Dalmonech Daniela , Collalti Alessio 
Published: October 2024

AbstractForest ecosystems account for about one-third of the Earth’s land area, and monitoring their structure and dynamics is essential for understanding the land’s carbon cycle and their role in the greenhouse gas balance. In this framework, process-based forest models (PBFMs) allow studying, monitoring and predicting forest growth and dynamics, capturing spatial and temporal patterns of carbon fluxes and stocks. The ‘Three Dimensional-Coupled Model Carbon Cycle - Forest Ecosystem Module’ (3D-CMCC-FEM) is a well-known eco-physiological, biogeochemical, biophysical process-based model, able to simulate energy, carbon, water and nitrogen fluxes and their allocation in homogeneous and heterogenous forest ecosystem. The model is specifically designed to represent forest stands, from simple ones to those with complex structures, involving several cohorts competing for light and other resources in a prognostic way. Currently, the model is implemented in C-language, which can be challenging for the broad public to use, and thus limiting its applications. In this paper, we present the open-source R package ‘R3DFEM’ which introduces efficient methods for: i) generating and handling input data needed for the model initialization; ii) running model simulations with different set up and exploring input; and iii) plotting output data. The functions in the R-package are designed to be user-friendly and intended for all R users with little to advanced coding skills, who aim to perform simulations using the 3D-CMCC-FEM. Here we present the package and its functionalities using some real case study and model applications.
Improving the reliability of molecular string representations for generative chemistry
Authors: Reboul Etienne , Wefers Zoe , Waldispühl Jérôme , Taly Antoine 
Published: October 2024

AbstractGenerative chemistry has seen rapid development recently. However, models based on string representations of molecules still rely largely on SMILES1and SELFIES2that have not been developed for this context. The goal of this study is to first analyze the difficulty encountered by a small generative model when using SMILES and SELF- IES. Our study found that SELFIES and canonical SMILES3are not fully reliable representations, i.e. do not ensure both the viability and fidelity of samples. Viable samples represent novel, unique molecules with correct valence, while fidelity ensures the accurate reproduction of chemical properties from the training set. In fact, 20% of the samples generated using Canonical SMILES as input representation do not corre-spond to valid molecules. At variance, samples generated using SELFIES less faithfully reproduce the chemical properties of the training dataset.As a mitigation strategy of the previously identified problems we have developed data augmentation procedures for both SELFIES and SMILES. Simplifying the com-plex syntax of SELFIES yielded only marginal improvements in stability and overall fidelity to the training set. For SMILES, we developed a stochastic data augmentation procedure called ClearSMILES, which reduces the vocabulary size needed to represent a SMILES dataset, explicitly represents aromaticity via Kekuĺe SMILES,3and reduces the effort required by deep learning models to process SMILES. ClearSMILES reduced the error rate in samples by an order of magnitude, from 20% to 2.2%, and improved the fidelity of samples to the training set.
Data-driven evaluation of suitable immunogens for improved antibody selection
Authors: Waury Katharina , Kvartsberg Hlin , Zetterberg Henrik , Blennow Kaj , Teunissen Charlotte E. , Abeln Sanne 
Published: October 2024

ABSTRACTAntibodies are indispensable in laboratory and clinical applications due to their high specificity and affinity for protein antigens. However, selecting the right protein fragments as immunogens for antibody production remains challenging. Leveraging the Human Protein Atlas, this study systematically evaluates immunogen properties aiming to identify key factors that influence their suitability. Antibodies were classified as successful or unsuccessful based on standardized validation experiments, and the structural and functional properties of their immunogens were analyzed. Results indicated that longer immunogens often resulted in more successful but less specific antibodies. Shorter immunogens (50 residues or fewer) with disordered or unfolded regions at the N- or C-terminus and long coil stretches, were more likely to generate successful antibodies. Conversely, immunogens with high beta sheet content, multiple secondary structure elements, transmembrane regions, or disulfide bridges were associated with poorer antibody performance. Post-translational modification sites within immunogens appeared to mark beneficial regions for antibody generation. To support antibody selection, a novel R package, immunogenViewer, was developed, enabling researchers to easily apply these insights when immunogen sequences are disclosed. By providing a deeper understanding of immunogen suitability, this study promotes the development of more effective antibodies, ultimately addressing issues of reproducibility and reliability in antibody-based research. The findings are highly relevant to the research community, as end-users often lack control over the immunogen selection process in antibody production.