bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of a stakeholder-driven, self-contained electronic informed consent platform for trio-based genomic research studies
Authors: Norton Bethany Y , Liu James , Lewis Sara A , Magee Helen , Kruer Tyler N , Dinh Rachael , Bakhtiari Somayeh , Nordlie Sandra H. , Shetty Sheetal , Heim Jennifer , Nishiyama Yumi , Arango Jorge , Johnson Darcy , Seabrooke Lee , Shub Mitchell , Rosenberg Robert , Shusterman Michele , Wisniewski Stephen , Cooper Blair , Rothwell Erin , Fahey Michael C , Shrader M. Wade , Lennon Nancy , Oleszek Joyce , Pierce Wendy , Fleming Hannah , Belthur Mohan , Tinto Jennifer , Noritz Garey , Glader Laurie , Steffan Kelsey , Walker William , Grenard Deborah , Aravamuthan Bhooma , Bjornson Kristie , Joseph Malin , Gross Paul , Kruer Michael C ,   the Cerebral Palsy Research Network.
Published: May 2024

ABSTRACTIncreasingly long and complex informed consents have yielded studies demonstrating comparatively low participantcomprehensionandsatisfactionwith traditional face-to-face approaches. In parallel, interest in electronic consents for clinical and research genomics has steadily increased, yet limited data are available for trio-based genomic discovery studies. We describe the design, development, implementation, and validation of an electronic iConsent application for trio-based genomic research deployed to support genomic studies of cerebral palsy. iConsent development incorporated stakeholder perspectives including researchers, patient advocates, institutional review board members, and genomic data-sharing considerations. The iConsent platform integrated principles derived from prior electronic consenting research and elements of multimedia learning theory. Participant comprehension was assessed in an interactive teachback format. The iConsent application achieved nine of ten proposed desiderata for effective patient-focused electronic consenting for genomic research.Overall, participants demonstrated highcomprehensionandretentionof key human subjects’ considerations. Enrollees reported high levels ofsatisfactionwith the iConsent, and we found that participantcomprehension, iConsentclarity,privacy protections, andstudy goal explanationswere associated with overallsatisfaction. Although opportunities exist to optimize iConsent, we show that such an approach is feasible, can satisfy multiple stakeholder requirements, and can realize high participantsatisfactionandcomprehensionwhile increasing study reach.
A case-control study evaluating CT signs of xiphoid process associated with xiphodynia
Authors: Ono Ryosuke , Horibata Ken 
Published: May 2024

AbstractObjectivesTo investigate whether CT signs of the xiphoid process, such as xiphisternal angle and evidence of soft tissue compression, are useful for diagnosing xiphodynia.DesignA case-control study within a cohort.Setting/ParticipantsParticipants included 1560 individuals who visited a small urban hospital in Japan for chest or abdominal pain between January 2021 and September 2023. Those who underwent CT examinations including the xiphoid process were selected. Nine individuals diagnosed with xiphodynia were assigned to the case group, while 321 individuals diagnosed with other causes of pain were assigned to the control group.InterventionsThe xiphisternal angle, evidence of soft tissue compression anterior to the xiphoid process, anatomical features at the tip of the xiphoid process, and anatomical morphology of the xiphoid process were compared between the two groups.ResultsThere was no significant difference in the xiphisternal angle between the two groups. No significant differences were observed in evidence of soft tissue compression anterior to the xiphoid process or anatomical features at the tip of the xiphoid process. New anatomical signs reveal that in approximately 70% of cases, the xiphoid process curves forward and then backward.ConclusionsThe xiphoid process sternal angle is not useful for diagnosing xiphodynia. The curvature of the xiphoid process is frequently observed regardless of the presence of xiphodynia.
Integrating Genetic Ancestry into Clinical Care: Accuracy, Utility, and Stakeholder Views
Authors: Prettyman Jessica , Hoffmann Thomas J , Biswas Sawona , Rajkovic Aleksandar 
Published: May 2024

ABSTRACTPURPOSEThis study aimed to evaluate the concordance of genetic ancestry reports from different providers, assess the accuracy of genetic ancestry compared to self-identified race and ethnicity (SIRE), and explore patient and provider perspectives on the potential utility and integration of genetic ancestry data into the electronic health record (EHR).METHODSGenetic ancestry results from two commercial providers and two 3rd-party analyses were compared for concordance using data from 451 participants in the UCSF 3D Health Study. Genetic ancestry was also compared to SIRE. Surveys were administered to gather perspectives on genetic ancestry testing, its accuracy, and potential integration into the EHR.RESULTSThe overall mean concordance between the two commercial providers was 58.41%. Ancestry from one provider had the highest concordance with SIRE, ranging from 80.05% to 94.78% across different thresholds. The majority of participants and providers were neutral regarding the integration of genetic ancestry into the EHR.CONCLUSIONSignificant discordance exists between genetic ancestry reports from different providers, highlighting the need for standardization in the calculation of genetic ancestry. While participants and providers acknowledge the potential utility of genetic ancestry in personalized medicine, concerns regarding data privacy, accuracy, and the potential for discrimination must be addressed before integration into the EHR.
Sex-differences in reporting of statin-associated diabetes mellitus to the US Food and Drug Administration
Authors: Kao David P , Martin James , Aquilante Christina , Shalowitz Elise L , Leyba Katarina , Kudron Elizabeth , Reusch Jane EB , Regensteiner Judith G. 
Published: May 2024

ABSTRACTObjectiveDetermine whether statin-associated DM is reported more frequently in women than men in post-marketing adverse drug event (ADE) surveillance.DesignRetrospective pharmacovigilance analysisData sourcePublicly available FDA Adverse Event Reporting System (FAERS) from January 1997 through December 2023.SettingReal-world spontaneously reported ADEs in the United States.ParticipantsCommunity patients reporting statin ADEs during the study period.Interventions/exposuresAdverse drug event reports that included at least one statin.Main outcome measuresProportional reporting ratio to identify increased rates of statin-associated DM events in women and men compared with all other medications, and reporting odds ratio to compare reporting rates in women vs. men.ResultsA total of 18,294,814 ADEs were reported during the study period. Among statin-associated ADEs, 14,897/519,209 (2.9%) reports mentioned DM in women compared with 7,412/489,453 (1.5%) in men, which were both significantly higher than background (0.6%). Statins were primary-or secondary-suspected cause of the ADE significantly more often in women than men (59.8 vs. 28.7%), and reporting rates were disproportionately higher in women than in men for all statins. (reporting odds ratio 1.9 [95% CI 1.9-2.0]). The largest difference in reporting of statin-associated DM between women and women was observed with atorvastatin.ConclusionsAnalysis post-marketing spontaneous ADE reports demonstrated a higher reporting rate of DM-associated with statin use compared to other medications with a significantly higher reporting rate in women compared to men. Future studies should consider mechanisms of statin-associated DM moderated by sex.
Feature Selection Using Lasso Regression Enhances Deep Learning Model Performance For Diagnosis Of Lung Cancer from Transcriptomic Data
Authors: Guha Souvik 
Published: May 2024

AbstractCancer is a genetic disease where gene mutations are pivotal in disease initiation and pathophysiology. The gene expression profile follows a specific pattern exclusive to each cancer which can be utilized for early and accurate diagnosis. Microarray techniques have emerged as powerful tools capable of simultaneously capturing the expression profiles of thousands of genes. However, because of the high dimensionality of the produced transcriptome data, analysis of the resulting datasets is challenging. Recent advancements in Artificial Intelligence (AI) techniques like Machine Learning (ML) and Deep Learning can be instrumental in efficiently processing these high-dimensional datasets. LASSO-regression is a ML technique that can help to rank the features which could help in feature selection leading to dimensionality reduction. Deep Learning is one of the most sophisticated ML techniques that can process high-dimensional data owing to the presence of more number of hidden layers in its neural network. We designed a Deep Neural Network (DNN) classifier model fused with a LASSO-based significant feature extractor for classifying the gene expression dataset containing a total of 51 samples of which 24 samples are of lung cancer patients and the remaining 27 samples are of normal individuals. A LASSO regression model was implemented to identify the genes that played a significant role in the classification. These significant gene expressions were then fed into a convergent Deep Neural Architecture. The classifier was trained with 70% data and the rest 30% was used for validation. The proposed classifier proved to provide better classification as compared to LASSO regression and DNN used individually. The two classes were classified with an average accuracy of 96.25%, average precision of 99.67%, average specificity of 99.45% and average sensitivity of 91.73% measured over thirty independent assessments. In some cases, the model was able to obtain a classification accuracy of 100%. This could open the path to early and better diagnosis of cancers from transcriptome data.
Muscle Contraction is Essential for Tendon Healing and Muscle Function Recovery after Achilles Tendon Rupture and Surgical Repair
Authors: Yoneno Moe , Minegishi Yuki , Takahashi Haruna , Takahata Kei , Miyamoto Himari , Usami Yuna , Kokubun Takanori 
Published: May 2024

AbstractIncomplete tendon healing and postponed muscle weakness after Achilles tendon rupture and surgical repair lead to poor performance in patient activities. Although the effectiveness of postoperative early functional rehabilitation has been proven, the priority and each effect of specific methods in early rehabilitation remain unclear. We hypothesized early muscle contraction exercises without joint motion would promote tendon healing and prevent calf muscle atrophy; in contrast, early static stretching after surgical repair would not contribute to tendon healing and induce calf muscle atrophy. C57Bl/6 mice underwent Achilles tendon rupture and suture repair, followed by different methods of post-surgery interventions: a non-exercise group, a Static stretching group, and an Electrical muscle stimulation group. 3 and 5 weeks after surgery, we assessed ex vivo tendon mechanical properties, collagen fiber alignment, and histological muscle properties. Electrical Muscle Stimulation restored the recovery of tendon mechanical properties and muscle strength more quickly than Static stretching. Static stretching had no additional effect on them compared to the non-exercise. Our results suggested that calf muscle contraction was essential as a post-surgery early functional rehabilitation to load tensile forces on tendons and improve Achilles tendon healing. Additionally, early muscle contractions naturally promote restoring muscle function after the rupture, but further research is needed to optimize muscle contraction protocols.Statement of Clinical SignificanceThis study shows the importance of selecting appropriate exercise modalities to resolve imperfections in tendon healing and muscle recovery. The establishment of proper rehabilitation is expected to improve post-surgery outcomes.Study DesignA controlled laboratory study.
Towards accesible brain-tumor classification at the point of care: Nanopore methylation sequencing from Formalin-Fixed Paraffin-Embedded (FFPE) pathology samples
Authors: Feinberg-Gorenshtein Galina , Grunwald Assaf , Vermeulen Carlo , Mark Nurit Gal , Maman Lena Shinderman , Shihrur Keren , Hameiri-Grossman Michal , Michaeli Orly , Fichman Suzanna , Natan Abraham , Siegal Tali , Yust-Katz Shlomit , Weiss Hanna , Levi-Barda Adva , Konen Osnat , Kershenovich Amir , de Ridder Jeroen , Toledano Helen , Birger Yehudit , Izraeli Shai , Ebenstein Yuval 
Published: May 2024

AbstractOxford Nanopore Technology (ONT) based methylation sequencing is increasingly recognized for its rapid and accurate classification of brain tumors. A process that is crucial for optimal patient treatment. However, widespread clinical utility is currently limited by the need for fresh-frozen biopsies and not the standard-of-care formalin-fixed, paraffin-embedded (FFPE) samples. Our study explores the impact of FFPE on DNA methylation and presents a developed and validated protocol for ONT-based FFPE tumor classification. We present a practical solution for precise brain tumor diagnoses in routine clinical settings and facilitating timely treatment decisions at the point of care and without interfering with operating room standards.
“Real-time county-aggregated wastewater-based estimates for SARS-CoV-2 effective reproduction numbers”
Authors: Ravuri Sindhu , Burnor Elisabeth , Routledge Isobel , Linton Natalie , Thakur Mugdha , Boehm Alexandria , Wolfe Marlene , Bischel Heather N. , Naughton Colleen C. , Yu Alexander T. , White Lauren A. , León Tomás M. 
Published: May 2024

ABSTRACTBackgroundThe effective reproduction number (Re) serves as a metric of population-wide, time-varying disease spread. During the COVID-19 pandemic,Rewas primarily estimated from clinical surveillance data streams (Rcc), which have varied in quality and representativeness due to changes in testing volume, test-seeking behavior, and resource constraints. DerivingRefrom alternative data sources such as wastewater could inform future public health responses.ObjectivesWe estimated county-aggregated, sewershed-restricted wastewater-based SARS-CoV-2Re(Rww) from May 1, 2022 to April 30, 2023 for five counties in California of varying population sizes, clinical testing rates, demographics, proportions surveilled by wastewater, and sampling frequencies to validate the reliability ofRwwas a real-time disease surveillance metric.MethodsWe produced both instantaneous and cohort sewershed-restrictedReusing smoothed and deconvolved wastewater concentrations. We then population-weighted and aggregated these sewershed-level estimates to arrive at county-levelRe. Using mean absolute error (MAE), Spearman’s rank correlation (ρ), confusion matrix classification, and cross-correlation analyses, we compared the timing and trajectory of twoRwwmodels to: (1) a publicly available, county-level ensemble ofRccestimates, and (2) a county-aggregated, sewershed-restrictedRcc.ResultsBothRwwmodels demonstrated high concordance with traditionalRccestimates, as indicated by low mean absolute errors (MAE ≤ 0.09), significant positive Spearman correlation (Spearman ρ ≥ 0.66, p < 0.001), and high confusion matrix classification accuracy (≥ 0.81). The relative timings ofRwwandRccwere less clear, with cross-correlation analyses suggesting strong associations for a wide range of temporal lags that varied by county andRwwmodel type.DiscussionThisReestimation methodology provides a generalizable, robust, and operationalizable framework for estimating county-levelRww. Our results support the additional use ofRwwas an epidemiological tool for surveillance. Based on this research, we produced publicly availableRwwnowcasts for the California Communicable diseases Assessment Tool (https://calcat.covid19.ca.gov/cacovidmodels/).
Topography and environmental deficiencies are associated with chikungunya virus exposure in urban informal settlements in Brazil
Authors: Travis Catherine , Argibay Hernán , Pellizzaro Maysa , de Oliveira Daiana Santos , Santana Roberta , Almerinda G. Palma Fabiana , Lustosa Ricardo , Souza Fábio Neves , Alzate López Yeimi Alexandra , Reis Mitermayer Galvão , Ko Albert I. , Diggle Peter J. , Begon Michael , Costa Federico , Eyre Max T. , Khalil Hussein 
Published: May 2024

AbstractBackgroundChikungunya virus (CHIKV) is an arbovirus with a significant global public health burden. Delineating the specific contributions of individual behaviour, household structure and the natural and built environment to CHIKV transmission is important for mitigating risk but challenging in urban informal settlements due to their heterogeneous environments. The aim of this study was to quantify variation in CHIKV seroprevalence between and within four urban communities in a large Brazilian city, and identify the respective contributions of individual, household and environmental factors for seropositivity.Methodology/Principal FindingsA cross-sectional serological survey was conducted in four low-income communities in Salvador, Brazil in 2018 to collect individual, household and CHIKV IgG serology data for 1217 participants. Fine-scale community mapping of high-risk environmental features and remotely sensed environmental data were used to improve characterisation of the microenvironment close to the household. We categorised risk factors into three dimensions - individual, household, and environmental and used binomial mixed-effect models to identify associations with CHIKV seropositivity. CHIKV seroprevalence was 4.8%, 6.1% and 4.3% in three communities and 22.6% in one community which had a distinct topographical profile. The only individual dimension variable associated with seropositivity was male sex (OR 1.67, 95% CI 1.11 - 2.36), but several environmental variables, including living in a house on a steep hillside, at medium to high elevations, and with surface water nearby, were associated with higher seropositivity.Conclusions/SignificanceOur findings indicate that CHIKV exposure risk can vary significantly between nearby communities and at fine spatial scales within communities, and is likely to be driven more strongly by the availability of mosquito breeding sites rather than human exposure patterns. They suggest that environmental deficiencies and topography, a proxy for several environmental processes including the degree of urbanisation and flooding risk, may play an important role in driving risk at both of these scales.
Implementation of a mobile app (iMPAKT) for improving person-centredness in nursing and midwifery practice: Protocol for a multi-methods evaluation study
Authors: O’Connor Sean R , Brown Donna , Cleland Ian , Wilson Valerie , McCance Tanya V 
Published: May 2024

ABSTRACTThe iMPAKT App has been developed as a digital tool for implementing and measuring person- centredness in nursing and midwifery practice. Despite its potential usefulness for the collection of person-centred measures, appropriate strategies are required to enhance the implementation of the app. To better understand the factors affecting adoption and maintenance, this protocol describes a multi-methods study to examine the experience of using the iMPAKT App in different contexts and settings. A convergent, multiple-methods approach will be used. Nurses and midwifes working in teams at different study sites in the UK and Australia will use the app during two, six-week cycles of data collection. Qualitative interviews and focus groups, guided by the Consolidated Framework for Implementation Research (CFIR) will be used to explore individual responses, views and experiences around acceptability and engagement with the app, and to examine variations in contexts. Quantitative data will be gathered on the number of person-centred measures recorded during the data collection cycles and using the System Usability Scale. Results will help to develop an understanding of the determinants and processes underpinning successful implementation, and inform further research to develop tailored implementation strategies, aimed at facilitating large scale collection of data on person- centred measures using the iMPAKT App.
Using Generative AI to Simulate Patient History-Taking in a Problem-Based Learning Tutorial: A Mixed-Methods Study
Authors: Mool Allison , Schmid Jacob , Johnston Thomas , Thomas William , Fenner Emma , Lu Kevin , Gandhi Raya , Western Adam , Seabold Brendan , Smith Kodi , Patterson Zachary , Feldt Hannah , Vollmer Daniel , Nallaveettil Roshan , Fanelli Anthony , Schmillen Logan , Tischkau Shelley , Cianciolo Anna T. , Benedict Pinckney , Selinfreund Richard 
Published: May 2024

AbstractBackgroundMedical educators who implement problem-based learning (PBL) strive to balance realism and feasibility when simulating patient cases, aiming to stimulate collaborative group discussion, engage students’ clinical reasoning, motivate self-directed learning, and promote the development of actionable scientific understanding. Recent advances in generative artificial intelligence (AI) offer exciting new potential for patient simulation in PBLMethodThis study used a between-groups, mixed-methods approach to (1) form a comprehensive picture of Year 2 medical student interactions with a generative AI-simulated patient in a PBL tutorial, as compared to interactions with multimedia patient case materials; and (2) triangulate on the impact these interactions had on learning. Two groups of students (N = 13) gathered patient history information from a generative AI-enabled, 3D-animated avatar (AI condition). Two other student groups (N = 13) gathered patient history information from a multimedia database using keyword searching (Electronic PBL Module [ePBLM] condition). We used descriptive observation to explore student interactions with both forms of the simulated patient, and we quantitatively compared students’ perceptions of their learning experience and recall of patient history information across conditions.ResultsStudents in the AI condition rated their present, AI-augmented PBL learning experience—particularly its clinical accuracy and teamwork aspects—significantly higher than they rated their previous PBL learning experiences using ePBLMs. Recall of patient history information did not differ between conditions. Descriptive observation indicated that the AI avatar presented case content accurately, with an appropriate amount of information provided in response to students’ questions. Students were highly engaged as a group in taking a history from the avatar. However, although students used language suggestive of anthropomorphizing of the AI (e.g., gender pronouns), they appeared to orient to it as an augmented “question bank” for gathering patient history information, using a questioning strategy akin to querying an ePBLM.DiscussionOptimizing AI implementation to stimulate clinical reasoning and patient communication skills in PBL could include (1) starting early, perhaps in Year 1, before an alternative interactional framework can take hold; (2) orienting students to the AI to help them understand its capabilities; and (3) encouraging “play” with or “discovery learning” of the AI’s capabilities.