bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of ABCB1 and CES1 Polymorphisms on Plasma Levels of Dabigatran and Risk of Hemorrhagic Complications in Ischemic Stroke Patients
Authors: Anna Olšerová , Petr Janský , Hana Magerová , Tereza Šrámková , Petra Kešnerová , Silvia Kmetonyová , Vlastimil Šulc , Hana Halmová , Martin Šrámek , Ivana Šarbochová , Jaroslava Paulasová-Schwabová , Kateřina Benešová , Jan Macek , Václav Maťoška , Aleš Tomek 
Published: March 2024

Background:
Dabigatran directly inhibits thrombin and is used in primary and secondary stroke prevention in individuals with nonvalvular atrial fibrillation. The prodrug dabigatran etexilate is absorbed by enteral P-glycoprotein (ABCB1) and then activated by hepatic and intestinal carboxylesterases (CES1) to produce active metabolites. Variations in dabigatran metabolism because of genetics may affect concentration levels and clinical outcomes.

Study Question:
We conducted a study to assess how polymorphisms in the CES1 (rs2244613) and ABCB1 (rs4148738) genes affect the through plasma level (cmin) of dabigatran and its correlation to clinical outcomes.

Study Design:
Retrospective multicentric study of consecutive patients on dabigatran therapy. Examination of CES1 rs2244613 and ABCB1 rs4148738 polymorphisms, cmin 12 hours after administration, clinical follow-up (ischemic stroke, major or clinically relevant hemorrhage, myocardial infarction, other thromboembolism, and death).

Measures and Outcomes:
A total of 432 patients received treatment for an average of 19.78 months (SD of 20.165). The sex distribution of the patients was 56.5% male, and the average age was 67.56 years (SD of 14.7). The ABCB1 variant genotype was present in 67.8% of patients, whereas 37.5% carried the CES1 polymorphism.

Results:
Compared with wild-type patients, patients with the CES1 variant had significantly lower dabigatran plasma levels (with a mean difference of 16.986; 95% confidence interval, 5.794–28.178 ng/mL, P = 0.003). We also found a significant risk of major bleeding in patients carrying the ABCB1 rs4148738 allele (hazard ratio = 1.99, confidence interval 95% 1.10 to 3.59, P = 0.024).

Conclusions:
The CES1 variant genotype rs2244613 is closely linked with reduced cmin of dabigatran. Carriers of the ABCB1 rs4148738 polymorphism exhibit a tendency toward higher plasma levels of dabigatran, which leads to a significantly increased risk of bleeding.
Melanoma—Modern Treatment for Metastatic Melanoma
Authors: Dimitrova Maya , Weber Jeffrey 
Published: March 2024

Abstract
Traditional chemotherapy has been ineffective in the treatment of metastatic melanoma. Until the use of checkpoint inhibitors, patients had very limited survival. Since the original US Food and Drug Administration approval of ipilimumab over a decade ago, the armamentarium of immunotherapeutic agents has expanded to include programmed cell death protein 1 and lymphocyte activation gene 3 antibodies, requiring a nuanced approach to the selection of frontline treatments, managing patients through recurrence and progression, and determining length of therapy. Herein, we review the existing evidence supporting current standard immunotherapy regimens and discuss the clinical decision-making involved in treating patients with metastatic melanoma with checkpoint inhibitors.
The Impact of Radiation on Nipple Symmetry After Bilateral Nipple-Sparing Mastectomy and Implant-Based Reconstruction
Authors: Brown Ciara A. , Carlson Grant W. 
Published: March 2024

Introduction
Radiation therapy can adversely affect outcomes of implant-based breast reconstruction, potentially complicating procedures like nipple-sparing mastectomy (NSM), which is increasingly popular in breast cancer management. This study aims to evaluate the impact of radiation on nipple symmetry in patients undergoing bilateral NSM with implant-based reconstruction.

Methods
We conducted a retrospective analysis using data from an Emory University review board-approved database. This encompassed bilateral NSMs coupled with immediate implant-based reconstructions. The BCCT.core software was employed to objectively measure nipple asymmetry preoperatively and postoperatively. Metrics, such as Breast Retraction Assessment values, upper nipple retraction, lower breast contour, and nipple to midline (NML) discrepancies were quantified. The study included 80 patients with a minimum of 1 year of follow-up; among them, 15 received radiation therapy (RT) while 65 did not.

Results
The reconstructions were divided into tissue expander, used in 39 cases (48.8%), and direct-to-implant (DTI), employed in 41 cases (51.2%). The DTIs were further categorized based on the location of the implant: 22 subpectoral and 19 prepectoral. Radiation was applied to 15 breasts, distributed among prepectoral DTI (4), subpectoral DTI (6), and tissue expander (5). Breast Retraction Assessment scores significantly differed between the nonirradiated and irradiated groups (1.49 vs 2.64, P < 0.0004). Nipple to midline differences and Upper Nipple Retraction also significantly varied postradiation, especially when comparing subpectoral and prepectoral implant placements.

Conclusions
Radiation therapy has a detrimental effect on nipple symmetry after bilateral NSM and implant-based reconstruction, with variations seen regardless of the implant's placement or the reconstructive technique utilized. Specifically, subpectoral reconstructions irradiated were prone to lateral nipple displacement, likely related to radiation-induced pectoralis muscle changes, while prepectoral irradiated reconstructions tended to have increased vertical displacement. These insights are crucial for patient education and surgical planning in the context of radiation and breast reconstruction.
ImageAssist
Authors: Golinko Michael S. , Abou-Ghanem Odette , Simard Michael , Caudill Mike , Pontell Matthew E. , O’Sick Nick , Oglesby Brandon , Arrieta Mark 
Published: March 2024

Statement of the Problem
Standardized medical photography of the face is a vital part of patient documentation, clinical evaluation, and scholarly dissemination. Because digital photography is a mainstay in clinical care, there is a critical need for an easy-to-use mobile device application that could assist users in taking a standardized clinical photograph. ImageAssist was developed to answer this need. The mobile application is integrated into the electronic medical record (EMR); it implements and automates American Society of Plastic Surgery/Plastic Surgery Research Foundation photographic guidelines with background deletion.

Initial Product Development
A team consisting of a craniofacial plastic surgeon and the Health Information Technology product group developed and implemented the pilot application of ImageAssist. The application launches directly from patients' chart in the mobile version of the EMR, EPIC Haiku (Verona, Wisconsin). Standard views of the face (90-degree, oblique left and right, front and basal view) were built into digital templates and are user selected. Red digital frames overlay the patients' face on the screen and turn green once standardized alignment is achieved, prompting the user to capture. The background is then digitally subtracted to a standard blue, and the photograph is not stored on the user's phone.

Early User experience
ImageAssist initial beta user group was limited to 13 providers across dermatology, ENT, and plastic surgery. A mix of physicians, advanced practice providers, and nurses was included to pilot the application in the outpatient clinic setting using Image Assist on their smart phone. After using the app, an internal survey was used to gain feedback on the user experience. In the first 2 years of use, 31 users have taken more than 3400 photographs in more than 800 clinical encounters. Since initial release, automated background deletion also has been functional for any anatomic area.

Conclusions
ImageAssist is a novel smartphone application that standardizes clinical photography and integrated into the EMR, which could save both time and expense for clinicians seeking to take consistent clinical images. Future steps include continued refinement of current image capture functionality and development of a stand-alone mobile device application.
ChatGPT in Urogynecology Research: Novel or Not?
Authors: Choueka David , Tabakin Alexandra L. , Shalom Dara F. 
Published: March 2024

Importance
ChatGPT (Chat Generative Pre-trained Transformer) is an artificial intelligence (AI) chatbot that provides human-like responses to text prompts. Little is known regarding ChatGPT’s ability to identify original research ideas in urogynecology.

Objective
Our objective was to evaluate the accuracy of ChatGPT in generating novel systematic review (SR) and research ideas in urogynecology.

Study Design
In this cross-sectional study, we asked ChatGPT to generate 10 novel SR ideas that have not yet been published for each of the following 5 topics: (1) urogynecology, (2) tension-free vaginal tape slings, (3) pessaries for pelvic organ prolapse, (4) beta-3 agonist use for overactive bladder, and (5) sexual function with genitourinary syndrome of menopause. Research idea novelty was assessed by cross-referencing PubMed and Scopus to determine if any prior publications existed.

Results
ChatGPT proposed 50 total SR ideas, including 10 for each prompt. Overall, ChatGPT showed 54% overall accuracy in developing novel SR ideas. Nonnovel SR ideas had a median of 19 (interquartile range, 8–35) published SRs on the suggested topic. When stratified by prompt type, 50% of general and 40–70% of specific urogynecology proposed SR ideas were found to be novel. There were no publications of any type identified for 7 of the 50 suggested ideas.

Conclusions
ChatGPT may be helpful for identifying novel research ideas in urogynecology, but its accuracy is limited. It is essential for those using ChatGPT to review existing literature to ensure originality and credibility. As AI transforms health care, we encourage all urogynecologists to familiarize themselves with popular AI platforms.
Cosmic mysteries and the hydrogen 21-cm line: bridging the gap with lunar observations
Authors: Fialkov A. , Gessey-Jones T. , Dhandha J. 
Published: March 2024

The hydrogen 21-cm signal is predicted to be the richest probe of the young Universe, including those eras known as the cosmic Dark Ages, the Cosmic Dawn (when the first star and black hole formed) and the Epoch of Reionization. This signal holds the key to deciphering processes that take place at the early stages of cosmic history. In this opinion piece, we discuss the potential scientific merit of lunar observations of the 21-cm signal and their advantages over more affordable terrestrial efforts. The Moon is a prime location for radio cosmology which will enable precision observations of the low-frequency radio sky. The uniqueness of such observations is that they will provide an unparalleled opportunity to test cosmology and the nature of dark matter using the Dark Ages 21-cm signal. No less enticing is the opportunity to obtain a much clearer picture of the Cosmic Dawn than that currently achievable from the ground, which will allow us to determine the properties of the first stars and black holes.This article is part of a discussion meeting issue ‘Astronomy from the Moon: the next decades (part 2)’.
Improving Diagnostic Precision: Urine Proteomics Identifies Promising Biomarkers for Necrotizing Enterocolitis
Authors: Mackay Stephen , Frazer Lauren C. , Bailey Grace K. , Miller Claire M. , Gong Qingqing , DeWitt Olivia N. , Good Misty 
Published: March 2024

AbstractBackgroundNecrotizing enterocolitis (NEC) is a severe intestinal disease that primarily impacts preterm infants. Current diagnostic tools are inadequate, so urine proteomics was performed for patients with and without NEC to identify putative biomarkers.Research design and methodsThe abundance of urinary proteins detected using an aptamer-based microarray was compared for infants with NEC (n=20) and controls, age-matched (n=8) or self-matched (n=12). Spearmanrcorrelation and hierarchical cluster analysis were performed. The area under the curve (AUC) was calculated for receiver operator characteristic curves (ROC).ResultsNinety-nine proteins differed in NEC vs. controls based on median fold change (Log2± 1.1) and significance (P< 0.05). Patterns of abundance were consistent for both types of matching, and samples clustered based on NEC severity. Two panels were built to differentiate between infants with and without NEC. Panel 1 included proteins associated with inflammation/NEC and produced by the intestinal epithelium (REG1B, REG3A, FABP2, DEFA5, AUC 0.90). Panel 2 consisted of proteins with the largest fold change between NEC vs. controls and the highest individual AUC values (REG1B, SSBP1, CRYZL1, ITM2B, IL36B, IL36RN, AUC 0.98).ConclusionsUrine proteins significantly differ between infants with and without NEC, which supports their potential as future biomarkers.Graphical abstract.Overview of study findings. Created with Biorender.com
Navigating primary health care challenges: Insights from older people with multimorbidity in Malawi
Authors: Kwaitana Duncan , Bates Maya Jane , Msowoya Esnath , Breevoort Dorothee van , Mildestvedt Thomas , Meland Eivind , Umar Eric 
Published: March 2024

AbstractThe global population is undergoing a significant surge in aging leading to increased susceptibility to various forms of progressive illnesses. This phenomenon significantly impacts both individual health and healthcare systems. Low and Middle Income Countries face particular challenges, as their Primary Health Care (PHC) settings often lack the necessary human and material resources to effectively address the escalating healthcare demands of the older people. This study set out to explore the experiences of older people living with progressive multimorbidity in accessing PHC services in Malawi. Between July 2022 and January 2023, a total of sixty in-depth interviews were conducted with dyads of individuals aged ≥50 years and their caregivers, and twelve healthcare workers in three public hospitals across Malawi’s three administrative regions. The study employed a stratified selection of sites, ensuring representation from rural, peri-urban, and urban settings, allowing for a comprehensive comparison of diverse perspectives. Guided by the Andersen-Newman theoretical framework, the study assessed the barriers, facilitators, and need factors influencing PHC service utilization by the older people. Three themes, consistent across all sites emerged, encompassing barriers, facilitators, and need factors respectively. The themes include: (1) clinic environment: inconvenient clinic setup, reliable PHC services and research in diabetic foods; (2) geographical factors: bad road conditions, lack of comprehensive PHC at local health facility and need for community approaches; and (3) social factors: encompassing use of alternative medicine, transport support, perceived health care benefit and support with startup capital for small-scale businesses. This research highlights the impact of multiple factors on the access to and utilization of PHC services among older individuals, emphasizing the urgent need for enhanced nationwide availability of such services. It strongly recommends a thorough investigation into successful practices implemented in diverse health facilities in Malawi, with a specific focus on addressing the unique healthcare needs of the older population.
OnSIDES (ON-label SIDE effectS resource) Database : Extracting Adverse Drug Events from Drug Labels using Natural Language Processing Models
Authors: Tanaka Yutaro , Chen Hsin Yi , Belloni Pietro , Gisladottir Undina , Kefeli Jenna , Patterson Jason , Srinivasan Apoorva , Zietz Michael , Sirdeshmukh Gaurav , Berkowitz Jacob , Brown Kathleen LaRow , Tatonetti Nicholas P. 
Published: March 2024

AbstractAdverse drug events (ADEs) are the fourth leading cause of death in the US and cost billions of dollars annually in increased healthcare costs. However, few machine-readable databases of ADEs exist, limiting the opportunity to study drug safety on a broader, systematic scale. Recent advances in Natural Language Processing methods, such as BERT models, present an opportunity to accurately extract relevant information from unstructured biomedical text. As such, we fine-tuned a PubMedBERT model to extract ADE terms from descriptive text in FDA Structured Product Labels for prescription drugs. With this model, we achieve an F1 score of 0.90, AUROC of 0.92, and AUPR of 0.95 at extracting ADEs from the labels’ “Adverse Reactions”. We further utilize this method to extract serious ADEs from labels’ “Boxed Warnings”, and ADEs specifically noted for pediatric patients. Here, we present OnSIDES (ON-label SIDE effectS resource), a compiled, computable database of drug-ADE pairs generated with this method. OnSIDES contains more than 3.6 million drug-ADE pairs for 3,233 unique drug ingredient combinations extracted from 47,211 labels. Additionally, we expand this method to extract ADEs from drug labels of other major nations/regions - Japan, the UK, and the EU - to build a complementary OnSIDES-INTL database. To present potential applications, we used OnSIDES to predict novel drug targets and indications, analyze enrichment of ADEs across drug classes, and predict novel ADEs from chemical compound structures. We conclude that OnSIDES can be utilized as a comprehensive resource to study and enhance drug safety.One Sentence SummaryOnSIDES is a large, comprehensive database of adverse drug events extracted from drug labels using natural language processing methods.
Evaluating the Portability of SepsisWatch: A Multi-Site External Validation of a Sepsis Machine Learning Model
Authors: Valan Bruno , Prakash Anusha , Ratliff William , Gao Michael , Muthya Srikanth , Thomas Ajit , Eaton Jennifer L. , Gardner Matt , Nichols Marshall , Revoir Mike , Tart Dustin , O’Brien Cara , Patel Manesh , Balu Suresh , Sendak Mark 
Published: March 2024

AbstractImportanceSepsis accounts for a substantial portion of global deaths and healthcare costs. Early detection using machine learning (ML) models offers a critical opportunity to improve care and reduce the burden of sepsis.ObjectiveTo externally validate the SepsisWatch ML model, initially developed at Duke University, in a community healthcare and assess its performance and clinical utility in early sepsis detection.DesignThis retrospective external validation study evaluated the performance of the SepsisWatch model in a new environment. Data from patient encounters at Summa Health’s emergency departments between 2020 and 2021 were used. The study analyzed the model’s ability to predict sepsis using a combination of static and dynamic patient data.SettingThe study was conducted at Summa Health, a nonprofit healthcare system in Northeast Ohio, covering two emergency departments (EDs) associated with acute care hospitals, and two standalone EDs.ParticipantsEncounters associated with adult patients in any of Summa Health’s four EDs were included. Encounters lasting <1 hour were excluded. Only the first 36 hours of each encounter were used in model evaluation.Intervention(s)/Exposure(s)The SepsisWatch model was used to predict sepsis based on patient data.Main Outcome(s) and Measure(s)The primary outcomes measured were the model’s area under the precision-recall curve (AUPRC), and area under the receiver operator curve (AUROC).ResultsThe study included 205,005 encounters from 101,584 unique patients. 54.7% (n = 112,223) patients were female and the mean age was 50 (IQR, [38,71]). The model demonstrated strong performance across the Summa Health system, with little variation across different sites. The AUROC ranged from 0.906 to 0.960, and the AUPRC ranged from 0.177 to 0.252 across the four sites.Conclusions and RelevanceThe external validation of the SepsisWatch model in a community health system setting confirmed its robust performance and portability across different geographical and demographic contexts. The study underscores the potential of advanced ML models in improving sepsis detection in both academic and community hospital settings, paving the way for prospective studies to measure the clinical and operational impact of such models in healthcare.
Benchmark calculations of fully heavy compact and molecular tetraquark states
Authors: Wu Wei-Lin , Chen Yan-Ke , Meng Lu , Zhu Shi-Lin 
Published: March 2024

We calculate the mass spectrum of the S-wave fully heavy tetraquark systems QQQ¯Q¯(Q=c,b) with both normal (JPC=0++,1+−,2++) and exotic (JPC=0+−,1++,2+−) C-parities using three different quark potential models (AL1, AP1, BGS). The exotic C-parity systems refer to the ones that cannot be composed of two S-wave ground heavy quarkonia. We incorporate the molecular dimeson and compact diquark-antidiquark spatial correlations simultaneously, thereby discerning the actual configurations of the states. We employ the Gaussian expansion method to solve the four-body Schrödinger equation, and the complex scaling method to identify the resonant states. The mass spectra in three different models qualitatively agree with each other. We obtain several resonant states with JPC=0++,1+−,2++,1++ in the mass region (6.92,7.30) GeV, some of which are good candidates of the experimentally observed X(6900) and X(7200). We also obtain several exotic C-parity zero-width states with JPC=0+− and 2+−. These zero-width states have no corresponding S-wave diquarkonium threshold and can only decay strongly to final states with P-wave quarkonia. With the notation T4Q,J(C)(M), we deduce from the root mean square radii that the X(7200) candidates T4c,0(+)(7173),T4c,2(+)(7214) and the state T4c,1(−)(7191) look like molecular states although most of the resonant and zero-width states are compact states.

Published by the American Physical Society
2024