bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dissociable dorsal medial prefrontal cortex ensembles are necessary for cocaine seeking and fear conditioning in mice
Authors: Liu Shuai , Nawarawong Natalie , Liu Xiaojie , Liu Qing-song , Olsen Christopher M. 
Published: March 2024

AbstractThe dmPFC plays a dual role in modulating drug seeking and fear-related behaviors. Learned associations between cues and drug seeking are encoded by a specific ensemble of neurons. This study explored the stability of a dmPFC cocaine seeking ensemble over two weeks and its influence on persistent cocaine seeking and fear memory retrieval. In the first series of experiments, we trained TetTag mice in cocaine self-administration and tagged strongly activated neurons with EGFP during the initial day 7 cocaine seeking session. Subsequently, a follow-up seeking test was conducted two weeks later to examine ensemble reactivation between two seeking sessions via c-Fos immunostaining. In the second series of experiments, we co-injected viruses expressing TRE-cre and a cre-dependent inhibitory PSAM-GlyR into the dmPFC of male and femalec-fos-tTA mice to enable “tagging” of cocaine seeking ensemble or cued fear ensemble neurons with an inhibitory chemogenetic receptors. Then we investigated their contribution to subsequent cocaine seeking and fear recall during inhibition of the tagged ensemble by administering uPSEM792s (0.3 mg/kg), a selective ligand for PSAM-GlyR. In both sexes, there was a positive association between the persistence of cocaine seeking and the proportion of reactivated EGFP+ neurons within the dmPFC. More importantly, inhibition of the cocaine seeking ensemble suppressed cocaine seeking, but not recall of fear memory, while inhibition of the fear ensemble reduced conditioned freezing but not cocaine seeking. The results demonstrate that cocaine and fear recall ensembles in the dmPFC are stable, but largely exclusive from one another.
Chromosome-level Subgenome-awarede novoAssembly ofSaccharomyces bayanusProvides Insight into Genome Divergence after Hybridization
Authors: Gardner Cory , Chen Junhao , Hadfield Christina , Lu Zhaolian , Debruin David , Zhan Yu , Donlin Maureen J. , Lin Zhenguo , Ahn Tae-Hyuk 
Published: March 2024

AbstractInterspecies hybridization is prevalent in various eukaryotic lineages and plays important roles in phenotypic diversification, adaption, and speciation. To better understand the changes that occurred in the different subgenomes of a hybrid species and how they facilitated adaptation, we completed chromosome-levelde novoassemblies of all 16 pairs chromosomes for a recently formed hybrid yeast,Saccharomyces bayanusstrain CBS380 (IFO11022), using Nanopore MinION long-read sequencing. Characterization ofS. bayanussubgenomes and comparative analysis with the genomes of its parent species,S. uvarumandS. eubayanus,provide several new insights into understanding genome evolution after a relatively recent hybridization. For instance, multiple recombination events between the two subgenomes have been observed in each chromosome, followed by loss of heterozygosity (LOH) in most chromosomes in nine chromosome pairs. In addition to maintaining nearly all gene content and synteny from its parental genomes,S. bayanushas acquired many genes from other yeast species, primarily through the introgression ofS. cerevisiae, such as those involved in the maltose metabolism. In addition, the patterns of recombination and LOH suggest an allotetraploid origin ofS. bayanus. The gene acquisition and rapid LOH in the hybrid genome probably facilitated its adaption to maltose brewing environments and mitigated the maladaptive effect of hybridization.
Risk factors for breast cancer subtypes by race and ethnicity: A scoping review of the literature
Authors: Hurson Amber N , Ahearn Thomas U , Koka Hela , Jenkins Brittany D , Harris Alexandra R , Roberts Sylvia , Fan Sharon , Franklin Jamirra , Butera Gisela , Keeman Renske , Jung Audrey Y , Middha Pooja , Gierach Gretchen L , Yang Xiaohong R , Chang-Claude Jenny , Tamimi Rulla M , Troester Melissa A , Bandera Elisa V , Abubakar Mustapha , Schmidt Marjanka K , Closas Montserrat Garcia- 
Published: March 2024

ABSTRACTBackgroundBreast cancer is comprised of distinct molecular subtypes. Studies have reported differences in risk factor associations with breast cancer subtypes, especially by tumor estrogen receptor (ER) status, but their consistency across racial and ethnic populations has not been comprehensively evaluated.MethodsWe conducted a qualitative, scoping literature review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews to investigate consistencies in associations between 18 breast cancer risk factors (reproductive, anthropometric, lifestyle, and medical history) and risk of ER-defined subtypes in women who self-identify as Asian, Black or African American, Hispanic or Latina, or White. We reviewed publications between January 1, 1990 and July 1, 2022. Etiologic heterogeneity evidence (convincing, suggestive, none, or inconclusive) was determined by expert consensus.ResultsPublications per risk factor ranged from 14 (benign breast disease history) to 66 (parity). Publications were most abundant for White women, followed by Asian, Black or African American, and Hispanic or Latina women. Etiologic heterogeneity evidence was strongest for parity, followed by age at first birth, post-menopausal BMI, oral contraceptive use, and estrogen-only and combined menopausal hormone therapy. Evidence was limited for other risk factors. Findings were consistent across racial and ethnic groups, although the strength of evidence varied.ConclusionThe literature supports etiologic heterogeneity by ER for some established risk factors that are consistent across race and ethnicity groups. However, in non-White populations evidence is limited. Larger, more comparable data in diverse populations is needed to better characterize breast cancer etiologic heterogeneity.
Exploring Early Perceptions and Experiences of ChatGPT in Pediatric Critical Care: A Qualitative Study Among Healthcare Professionals
Authors: Temsah Mohamad-Hani , Abouammoh Noura , Alsatrawi Mohammed , Almazyad Mohammed , Aljamaan Fadi , Vargas-Gutierrez Mariella , Hay Rebecca , Al-Jelaify Muneera , Alabdulkreem Wejdan , Assiri Nawal , Muaygil Ruaim , Altamimi Ibraheem , Alshahrani Fatimah S. , Alhasan Khalid , Malki Khalid H. , Jamal Amr , Al-Tawfiq Jaffar A. , Al-Eyadhy Ayman 
Published: March 2024

AbstractThis qualitative inquiry explores the initial impressions and firsthand encounters of healthcare professionals (HCPs) with ChatGPT, a Generative Pre-trained Transformer, within Pediatric Intensive Care Units (PICUs). Through focus group discussions held at a tertiary academic center, a diverse cadre of HCPs was engaged to ascertain their awareness, utilization patterns, perceived advantages, and apprehensions regarding ChatGPT. The analysis revealed three primary themes: understanding and ease of use of ChatGPT, its practical applications in clinical workflows for critically ill children and information retrieval, and the ethical considerations associated with its deployment. While participants praised ChatGPT for its engaging interface and potential to streamline tasks and provide prompt information, notable reservations surfaced regarding its limitations, particularly in medical accuracy, currency of data, and ethical implications. The findings suggest a cautious optimism towards integrating Generative Artificial Intelligence (GAI), like ChatGPT, in pediatric critical care, highlighting the need for balanced, informed, and transparent applications, with ongoing evaluation of GAI technologies in pediatric healthcare settings.
Decoding Prodromal Parkinson’s Disease: Clinical Differences between Isolated Hyposmia and REM Sleep Behavior Disorder
Authors: Banerjee Luke Vikram , Pasquini Jacopo , Henderson Robin , Pavese Nicola , Anderson Kirstie N 
Published: March 2024

AbstractBackgroundThe prodromal phase of Parkinson’s disease (PD), much like the disease itself, displays marked heterogeneity, with varied rates of progression and symptom severities. A detailed clinical characterization of prodromal subgroups may provide useful insights for both clinical and research settings.ObjectivesTo compare clinical assessments in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and those with isolated hyposmia.MethodsA cross-sectional study was conducted on 191 patients with iRBD, 213 patients with isolated hyposmia and 150 healthy controls recruited in the Parkinson’s Progression Markers Initiative. The earliest available assessment for each participant was selected. Our analysis investigated and compared the Montreal Cognitive Assessment, Scales for Outcomes in Parkinson’s Disease Autonomic Dysfunction (SCOPA-AUT) and Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Parts I, II and III scores across the three groups. To assess differences, after adjusting for age and sex, we employed permutations testing. We further investigated the specific question items that contributed most significantly to the observed variations between the groups.ResultsWe found significant differences between the healthy control group and a combined prodromal group across all assessment categories, with prodromal participants displaying poorer scores. For between prodromal groups comparison, significant differences emerged in SCOPA-AUT and MDS-UPDRS Part I scores, with the iRBD group presenting with more severe scores.ConclusionOur study highlights that even in the premotor stage of PD, clinical distinctions exist in terms of autonomic burden between individuals with iRBD and those with isolated hyposmia.
COGNITIVE ASSESSMENT WITH COGNIVUECLARITY®: PSYCHOMETRIC PROPERTIES AND ENHANCED NORMATIVE RANGES IN A DIVERSE POPULATION
Authors: Galvin James E. , Chang Lun-Ching , Estes Paul , Harris Heather M. , Fung Ernest 
Published: March 2024

ABSTRACTBackgroundDetecting cognitive impairment in clinical practice is challenging as most instruments do not perform well in diverse samples of older adults. These same instruments are often used for eligibility into clinical trials making it difficult to recruit minoritized adults into Alzheimer’s disease (AD) studies. CognivueClarity®is an FDA-cleared computerized cognitive screening platform using adaptive psychophysics to detect cognitive impairment.ObjectiveTest the ability of CognivueClarityto detect cognitive impairment in a diverse community sample compared with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).MethodsThis study enrolled 452 participants across 6 US study sites and completed both CognivueClaritydevice and RBANS. Psychometric properties and exploratory factor analysis of CognivueClaritywere explored and comparisons against RBANS across different age, sex, education, and ethnoracial groups were conducted.ResultsParticipants had a mean age of 47.9±16.1 years (range: 18-85), 63.6% were female, 45.9% had<12 years of education, 31.2% were African American and 9.2% were Hispanic. CognivueClarityhad strong internal consistency, test-retest and minimal practice effects. A 4-factor structure (Memory, Attention, Visuomotor, and Discrimination) had excellent goodness of fit. Normalizing age effects improved performance. Race and education effects were similar to those seen with RBANS. CognivueClarityhad strong correlation with RBANS.ConclusionsOur study supports the use of CognivueClarityas an easy-to-use, brief, and valid cognitive assessment that can be used for identifying individuals with likely cognitive impairment in the clinical setting and those who could be candidates for AD research studies.
Identifying Psychosis Episodes in Psychiatric Admission Notes via Rule-based Methods, Machine Learning, and Pre-Trained Language Models
Authors: Hua Yining , Blackley Suzanne V. , Shinn Ann K. , Skinner Joseph P. , Moran Lauren V. , Zhou Li 
Published: March 2024

ABSTRACTEarly and accurate diagnosis is crucial for effective treatment and improved outcomes, yet identifying psychotic episodes presents significant challenges due to its complex nature and the varied presentation of symptoms among individuals. One of the primary difficulties lies in the underreporting and underdiagnosis of psychosis, compounded by the stigma surrounding mental health and the individuals’ often diminished insight into their condition. Existing efforts leveraging Electronic Health Records (EHRs) to retrospectively identify psychosis typically rely on structured data, such as medical codes and patient demographics, which frequently lack essential information. Addressing these challenges, our study leverages Natural Language Processing (NLP) algorithms to analyze psychiatric admission notes for the diagnosis of psychosis, providing a detailed evaluation of rule-based algorithms, machine learning models, and pre-trained language models. Additionally, the study investigates the effectiveness of employing keywords to streamline extensive note data before training and evaluating the models. Analyzing 4,617 initial psychiatric admission notes (1,196 cases of psychosis versus 3,433 controls) from 2005 to 2019, we discovered that the XGBoost classifier employing Term Frequency-Inverse Document Frequency (TF-IDF) features derived from notes pre-selected by expert-curated keywords, attained the highest performance with an F1 score of 0.8881 (AUROC [95% CI]: 0.9725 [0.9717, 0.9733]). BlueBERT demonstrated comparable efficacy an F1 score of 0.8841 (AUROC [95% CI]: 0.97 [0.9580, 0.9820]) on the same set of notes. Both models markedly outperformed traditional International Classification of Diseases (ICD) code-based detection methods from discharge summaries, which had an F1 score of 0.7608, thus improving the margin by 0.12. Furthermore, our findings indicate that keyword pre-selection markedly enhances the performance of both machine learning and pre-trained language models. This study illustrates the potential of NLP techniques to improve psychosis detection within admission notes and aims to serve as a foundational reference for future research on applying NLP for psychosis identification in EHR notes.
Burden of Disease of Respiratory Syncytial Virus in Older Adults and Adults Considered at High Risk of Severe Infection
Authors: Abrams Elissa , Doyon-Plourde Pamela , Davis Phaedra , Lee Liza , Rahal Abbas , Brousseau Nicholas , Siu Winnie , Killikelly April 
Published: March 2024

AbstractBackgroundVaccine products for adults have increased interest in understanding Canada’s respiratory syncytial virus (RSV) burden in older adults and adults considered at high risk of severe infection.ObjectiveTo characterize the burden of RSV disease in Canada by joint analysis of the published literature and hospitalization data from a healthcare administrative database.MethodsElectronic databases of published literature were searched to identify studies and systematic reviews reporting data on outpatient visits, hospitalizations, intensive care unit (ICU) admissions and deaths associated with RSV infection in adults. For the hospitalization data analysis, hospital discharge records were extracted from the Canadian Institute of Health Information (CIHI) Discharge Abstract Database (DAD) for all patients admitted to an acute care facility for RSV infection defined by ICD-10 codes from 2010-2020 and 2021-2023.ResultsOverall, 26 studies, including 7 systematic reviews, were identified and summarized in the rapid review. Evidence suggests that medically attended RSV respiratory tract infections (RTI) are frequent causing 4.7 to 7.8% of symptomatic RTI in adults 60 years of age and older. Incidence of RSV RTI increases with age and presence of underlying medical conditions, such as cardiorespiratory disease, diabetes, and immunocompromising conditions. This trend was consistently observed across all RSV clinical outcomes of interest (i.e., hospitalization, ICU admission and death). Patients who reside in long-term care or other chronic care facilities have higher likelihood of severe clinical outcomes (i.e., ICU admission, receiving mechanical ventilation and/or death) compared to patients with other living situations upon hospital admission. Approximately 10% of older adults hospitalized with RSV infection require ICU admission. Although data are limited, evidence suggests that case fatality ratio (CFR) among those admitted to hospital varies between 5 and 10%. Some evidence suggests that RSV burden may be close to influenza burden in older adults. In general, the results from the Canadian hospitalization data support the rapid review findings Rates of hospitalization, ICU admission and death associated with RSV all increased with age, with 16% of hospitalizations resulting in ICU admission and with an in-hospital CFR of 9%.ConclusionIn adults, risk of severe RSV outcomes in general increases with increasing age and presence of comorbidities.
Study Protocol for the Artificial Intelligence-Driven Evaluation of Structural Heart Diseases Using Wearable Electrocardiogram (ID-SHD)
Authors: Aminorroaya Arya , Dhingra Lovedeep Singh , Pedroso Camargos Aline , Vasisht Shankar Sumukh , Khunte Akshay , Sangha Veer , Sen Sounok , McNamara Robert L , Haynes Norrisa , Oikonomou Evangelos K , Khera Rohan 
Published: March 2024

ABSTRACTIntroductionPortable devices capable of electrocardiogram (ECG) acquisition have the potential to enhance structural heart disease (SHD) management by enabling early detection through artificial intelligence-ECG (AI-ECG) algorithms. However, the performance of these AI algorithms for identifying SHD in a real-world screening setting is unknown. To address this gap, we aim to evaluate the validity of our wearable-adapted AI algorithm, which has been previously developed and validated for detecting SHD from single-lead portable ECGs in patients undergoing routine echocardiograms in the Yale New Haven Hospital (YNHH).Research Methods and AnalysisThis is the protocol for a cross-sectional study in the echocardiographic laboratories of YNHH. The study will enroll 585 patients referred for outpatient transthoracic echocardiogram (TTE) as part of their routine clinical care. Patients expressing interest in participating in the study will undergo a screening interview, followed by enrollment upon meeting eligibility criteria and providing informed consent. During their routine visit, patients will undergo a 1-lead ECG with two devices - one with an Apple Watch and the second with another portable 1-lead ECG device. With participant consent, these 1-lead ECG data will be linked to participant demographic and clinical data recorded in the YNHH electronic health records (EHR). The study will assess the performance of the AI-ECG algorithm in identifying SHD, including left ventricular systolic dysfunction (LVSD), valvular disease and severe left ventricular hypertrophy (LVH), by comparing the algorithm’s results with data obtained from TTE, which is the established gold standard for diagnosing SHD.Ethics and DisseminationAll patient EHR data required for assessing eligibility and conducting the AI-ECG will be accessed through secure servers approved for protected health information. Data will be maintained on secure, encrypted servers for a minimum of five years after the publication of our findings in a peer-reviewed journal, and any unanticipated adverse events or risks will be reported by the principal investigator to the Yale Institutional Review Board, which has reviewed and approved this protocol (Protocol Number: 2000035532).
A survey of experts to identify methods to detect problematic studies: Stage 1 of the INSPECT-SR Project
Authors: Wilkinson Jack , Heal Calvin , Antoniou George A , Flemyng Ella , Avenell Alison , Barbour Virginia , Bordewijk Esmee M , Brown Nicholas J L , Clarke Mike , Dumville Jo , Grohmann Steph , Gurrin Lyle C. , Hayden Jill A , Hunter Kylie E , Lam Emily , Lasserson Toby , Li Tianjing , Lensen Sarah , Liu Jianping , Lundh Andreas , Meyerowitz-Katz Gideon , Mol Ben W , O’Connell Neil E , Parker Lisa , Redman Barbara , Seidler Anna Lene , Sheldrick Kyle , Sydenham Emma , Dahly Darren L , van Wely Madelon , Bero Lisa , Kirkham Jamie J 
Published: March 2024

AbstractBackgroundRandomised controlled trials (RCTs) inform healthcare decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesise all RCTs which have been conducted on a given topic. This means that any of these ‘problematic studies’ are likely to be included, but there are no agreed methods for identifying them. The INSPECT-SR project is developing a tool to identify problematic RCTs in systematic reviews of healthcare-related interventions. The tool will guide the user through a series of ‘checks’ to determine a study’s authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion.MethodsWe assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorised these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list.ResultsExtensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool.ConclusionsA comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool.
Assessing the Seasonality of Lab Tests Among Patients with Alzheimer’s Disease and Related Dementias in OneFlorida Data Trust
Authors: Han Wenshan , Bhasuran Balu , Muse Victorine Patricia , Brunak Søren , Lin Lifeng , Hanna Karim , Huang Yu , Bian Jiang , He Zhe 
Published: March 2024

AbstractAbout 1 in 9 older adults over 65 has Alzheimer’s disease (AD), many of whom also have multiple other chronic conditions such as hypertension and diabetes, necessitating careful monitoring through laboratory tests. Understanding the patterns of laboratory tests in this population aids our understanding and management of these chronic conditions along with AD. In this study, we used an unimodal cosinor model to assess the seasonality of lab tests using electronic health record (EHR) data from 34,303 AD patients from the OneFlorida+ Clinical Research Consortium. We observed significant seasonal fluctuations—higher in winter in lab tests such as glucose, neutrophils per 100 white blood cells (WBC), and WBC. Notably, certain leukocyte types like eosinophils, lymphocytes, and monocytes are elevated during summer, likely reflecting seasonal respiratory diseases and allergens. Seasonality is more pronounced in older patients and varies by gender. Our findings suggest that recognizing these patterns and adjusting reference intervals for seasonality would allow healthcare providers to enhance diagnostic precision, tailor care, and potentially improve patient outcomes.