bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perception and Emotional Experiences of Infant Feeding Among Women Living With HIV in a High-Income Setting: A Longitudinal Mixed Methods Study
Authors: Moseholm Ellen , Fetters Michael D. , Aho Inka , Mellgren Åsa , Johansen Isik S. , Katzenstein Terese L. , Pedersen Gitte , Storgaard Merete , Weis Nina 
Published: October 2023

Background:The recommendation of breastfeeding avoidance for women living with HIV in high-income settings may be influenced by cultural beliefs and come at an emotional cost. This multicenter, longitudinal, convergent mixed methods study aimed to compare differences in attitudes, concerns, and experiences surrounding breastfeeding in women living with HIV of Nordic and non-Nordic origin.Setting:High-income setting.Methods:Pregnant women living with HIV in the Nordic countries Denmark, Finland, and Sweden were recruited in 2019–2020. Quantitative data on attitudes surrounding infant feeding were assessed using the Positive Attitudes Concerning Infant Feeding questionnaire completed in the third trimester (T1), and 3 (T2) and 6 (T3) months postpartum. Women who completed the survey were also invited to participate in semistructured interviews at T1 and T3. The findings from the quantitative survey and qualitative interviews were brought together through merging to assess for concordance, complementarity, expansion, or discordance between the data sets and to draw metainferences.Results:In total, 44 women completed the survey, of whom 31 also participated in qualitative interviews. The merged analyses identified three overarching domains representing commonalities across the quantitative and qualitative data: emotional impact, justifying not breastfeeding, and coping strategies. Not being able to breastfeed was emotionally challenging. Cultural expectations influenced the women's experiences and the strategies they used to justify their infant feeding choice.Conclusions:For women living with HIV in Nordic countries not breastfeeding was a complex, multilayered process substantially influenced by social and cultural expectations.
Brief Report: Ryan White Participation Increased the Prevalence of COVID-19 Vaccination Among People Living with HIV in Michigan
Authors: Convery Christine , Diesel Jill , Brantley Antoine , Miller Jennifer , Karram Sarah 
Published: October 2023

Introduction:
People living with HIV (PLWH) have higher prevalence of adverse COVID-19 outcomes, and many reside in socially vulnerable communities. Our aim was to evaluate how engagement in HIV care may increase vaccination likelihood.

Methods:
Michigan HIV surveillance data were extracted from the Enhanced HIV/AIDS Reporting System and matched at the person-level to COVID-19 vaccination records from the Michigan Care Improvement Registry (through December 31, 2021 [n = 15,537]). Based on residential census tract, we classified PLWH into quartiles (<25th percentile [least vulnerable], 25th to <50th, 50th to <75th, ≥75th [most vulnerable]) of the 2018 CDC Social Vulnerability Index. Using log binomial regression, we estimated the relative prevalence of COVID-19 vaccine series initiation among PLWH by quartile of social vulnerability and Ryan White participation; models were adjusted for covariates.

Results:
By December 31, 2021, 67% of PLWH in Michigan had initiated a COVID-19 vaccine series; 47% resided in an area deemed most vulnerable and 54% had participated in Ryan White services. Compared with PLWH in the most vulnerable quartile, those who resided in least vulnerable quartiles had higher prevalence of vaccine initiation (Prevalence Ratio [95% Confidence Interval]: 1.67 [1.50 to 1.86]). Participants in Ryan White had greater prevalence of initiation (1.52 [1.42 to 1.62]) compared with those who were not participants; initiation remained higher when adjusted for covariates including social vulnerability quartile.

Conclusions:
Ryan White participation was associated with increased COVID-19 vaccine initiation regardless of community-level vulnerability. Wraparound services may be key in vaccine promotion interventions in this vulnerable population.
Bone SPECT/CT in Advanced Diffuse Tenosynovial Giant Cell Tumor of the Wrist
Authors: Lampe Nina A. , Strobel Klaus , Pallaver Armin , Hany Thomas F. , Grünig Hannes 
Published: October 2023

Abstract
Tenosynovial giant cell tumor, previously known as pigmented villonodular synovitis, is a benign low-grade fibrohistiocytic proliferation with hemosiderin deposits in synovial joints. Mostly affecting the knee, it can also manifest in other synovial joints, infrequently also in the wrist. Tenosynovial giant cell tumor typically causes intense radionuclide uptake in all phases in planar bone scintigraphy, making a differentiation from other bone tumors or osteomyelitis difficult, especially in cases associated with extensive bone destruction. We present a case of an unusually advanced and extended tenosynovial giant cell tumor of the wrist in bone scintigraphy, SPECT/CT, radiograph, and MRI.
EEG Based Oculographic Analysis of Epileptic Nystagmus
Authors: Acar Aybuke , Zampino Anthony , Fotedar Neel 
Published: October 2023

AbstractEpileptic nystagmus (EN) is a subtle seizure semiology, most commonly seen in seizures originating in the posterior cortical regions. EN is broadly categorized into type I and type II. Type I EN consists of contralateral repetitive saccadic eye movements alternating with post-saccadic slow drifts with an overall contralateral deviation. Type II EN is characterized by ipsilateral slow drift alternating with contralateral corrective saccades. In this article, we report a method to perform oculographic analysis of eye movements using EEG only. We used this method to classify the type of EN in three patients with parieto-occipital seizures.In all three patients, the ictal EEG demonstrated repetitive saccadic eye movements, directed contralateral to the seizure onset zone. With prolonged time constant, we were able to identify this eye movement pattern as EN with distinct slow and fast phases. We were able to further characterize the type of EN as type I and type II. In all three patients, the direction of EN (direction of fast phase or saccades) was contralateral to the seizure onset zone.EN can be easily missed on video-electroencephalography (vEEG) recordings because of various reasons. Our study demonstrates a systematic method of eye movement analysis on EEG, which can be used to not only identify EN as seizure semiology but also classify it, without requiring additional electrodes.
Investigating Racial Disparities in Drug Prescriptions for Patients with Endometriosis
Authors: Kashyap Aparajita , Aziz Maryam , Sun Tony Y. , Lipsky-Gorman Sharon , Opoku-Anane Jessica , Elhadad Noémie 
Published: October 2023

AbstractBackgroundEndometriosis is a chronic disease with a long time to diagnosis and several known comorbidities that requires a range of treatments including of pain management and hormone-based medications. Racial disparities specific to endometriosis treatments are unknown.ObjectiveWe aim to investigate differences in patterns of drug prescriptions specific to endometriosis management in Black and White patients prior to diagnosis and after diagnosis of endometriosis and compare these differences to racial disparities established in the general population.Study DesignWe conduct a retrospective cohort study using observational health data from the IBM MarketScan® Multi-state Medicaid dataset. We identify a cohort of endometriosis patients consisting of women between the ages of 15 and 49 with an endometriosis-related surgical procedure and a diagnosis code for endometriosis within 30 days of this procedure. Cohort is further restricted to patients with at least 3 years of continuous observation prior to diagnosis.We identify a non-endometriosis cohort of women between the ages of 15 and 49 with no endometriosis diagnosis and at least 1 year of continuous observation. We compare prevalence of prescriptions across selected drug classes for Black vs. White endometriosis patients. We further examine prevalence differences in the non-endometriosis cohort and prevalence differences pre- and post-diagnosis in the endometriosis cohort.ResultsThe endometriosis cohort comprised 16,372 endometriosis patients (23.3% Black, 66.0% White). Of the 28 drug classes examined, 17 were prescribed significantly less in Black patients compared to 21 in non-endometriosis cohort (n=3,663,904), and 4 were prescribed significantly more in Black patients compared to 6 in the non-endometriosis cohort. Of the 17 drugs prescribed more often in White patients, 16 have larger disparities pre-diagnosis than post-diagnosis.ConclusionsOur analysis identified significant differences in medication prescriptions between White and Black patients with endometriosis, notably in hormonal treatments, pain management, and treatments for common endometriosis co-morbidities. Racial disparities in drug prescriptions are well established in healthcare, and better understanding these disparities in the specific context of chronic reproductive conditions and chronic pain is important for increasing equity in drug prescription practices.
Integration of Expression QTLs with fine mapping via SuSiE
Authors: Zhang Xiangyu , Jiang Wei , Zhao Hongyu 
Published: October 2023

AbstractGenome-wide association studies (GWASs) have achieved remarkable success in associating thousands of genetic variants with complex traits. However, the presence of linkage disequilibrium (LD) makes it challenging to identify the causal variants. To address this critical gap from association to causation, many fine mapping methods have been proposed to assign well-calibrated probabilities of causality to candidate variants, taking into account the underlying LD pattern. In this manuscript, we introduce a statistical framework that incorporates expression quantitative trait locus (eQTL) information to fine mapping, built on the sum of single-effects (SuSiE) regression model. Our new method, SuSiE2, connects two SuSiE models, one for eQTL analysis and one for genetic fine mapping. This is achieved by first computing the posterior inclusion probabilities (PIPs) from an eQTL-based SuSiE model with the expression level of the candidate gene as the phenotype. These calculated PIPs are then utilized as prior inclusion probabilities for risk variants in another SuSiE model for the trait of interest. By leveraging eQTL information, SuSiE2enhances the power of detecting causal SNPs while reducing false positives and the average size of credible sets by prioritizing functional variants within the candidate region. The advantages of SuSiE2over SuSiE are demonstrated by simulations and an application to a single-cell epigenomic study for Alzheimer’s disease. We also demonstrate that eQTL information can be used by SuSiE2to compensate for the power loss because of an inaccurate LD matrix.Author summaryGenome-wide association studies (GWASs) have proven powerful in detecting genetic variants associated with complex traits. However, there are challenges in distinguishing the causal variants from other variants strongly correlated with them. To better identify causal SNPs, many fine mapping methods have been proposed to assign well-calibrated probabilities of causality to candidate variants. We introduce a statistical framework that incorporates expression quantitative trait locus (eQTL) information to fine mapping, which can improve the accuracy and efficiency of association studies by prioritizing functional variants within the risk genes before evaluating the causation. Our new fine mapping framework, SuSiE2, connects two sum of single-effects (SuSiE) models, one for eQTL analysis and one for genetic fine mapping. The posterior inclusion probabilities from an eQTL-based SuSiE model are utilized as prior inclusion probabilities for risk variants in another SuSiE model for the trait of interest. Through simulations and a real data analysis focused on Alzheimer’s disease, we demonstrate that SuSiE2improves fine mapping results by simultaneously increasing statistical power, controlling the type I error rate, and reducing the average size of credible sets.
Excitatory and Inhibitory neurochemical markers of anxiety in young females
Authors: Johnstone Nicola , Kadosh Kathrin Cohen 
Published: October 2023

AbstractBetween the ages of 10-25 years the maturing brain is sensitive to a multitude of changes, including neurochemical variations in metabolites. Of the different metabolites, gamma-aminobutyric acid (GABA) has long been linked neurobiologically to anxiety symptomology, which begins to manifest in adolescence. To prevent persistent anxiety difficulties into adulthood, we need to understand the maturational trajectories of neurochemicals and how these relate to anxiety levels during this sensitive period. We used magnetic resonance spectroscopy in a sample of younger (aged 10-11) and older (aged 18-25) females to estimate GABA and glutamate levels in brain regions linked to emotion regulation processing, as well as a conceptually distinct control region. Within the Bayesian framework, we found that GABA increased, and glutamate decreased with age, negative associations between anxiety and glutamate and GABA ratios in the dorsolateral prefrontal cortex, and a positive relationship of GABA with anxiety levels. The results support the neural over-inhibition hypothesis of anxiety based on GABAergic activity.
Development of an Integrated Sample Amplification Control for Salivary Point-of-Care Pathogen Testing
Authors: Sritong Navaporn , Ngo Winston Wei , Ejendal Karin F. K. , Linnes Jacqueline C. 
Published: October 2023

AbstractBackgroundThe COVID-19 pandemic has led to a rise in point-of-care (POC) and home-based tests, but concerns over usability, accuracy, and effectiveness have arisen. The incorporation of internal amplification controls (IACs), essential control for translational POC diagnostics, could mitigate false-negative and false-positive results due to sample matrix interference or inhibition. Although emerging POC nucleic acid amplification tests (NAATs) for detecting SARS-CoV-2 show impressive analytical sensitivity in the lab, the assessment of clinical accuracy with IACs is often overlooked. In some cases, the IACs were run spatially, complicating assay workflow. Therefore, the multiplex assay for pathogen and IAC is needed.ResultsWe developed a one-pot duplex reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) assay for saliva samples, a non-invasive and simple collected specimen for POC NAATs. The ORF1ab gene of SARS-CoV-2 was used as a target and a human 18S ribosomal RNA in human saliva was employed as an IAC to ensure clinical reliability of the RT-LAMP assay. The optimized assay could detect SARS-CoV-2 viral particles down to 100 copies/μL of saliva within 30 minutes without RNA extraction. The duplex RT-LAMP for SARS-CoV-2 and IAC is successfully amplified in the same reaction without cross-reactivity. The valid results were easily visualized in triple-line lateral flow immunoassay, in which two lines (flow control and IAC lines) represent valid negative results and three lines (flow control, IAC, and test line) represent valid positive results. This duplex assay demonstrated a clinical sensitivity of 95%, specificity of 100%, and accuracy of 96% in 30 clinical saliva samples.SignificanceIACs play a crucial role in ensuring user confidence with respect to the accuracy and reliability of at-home and POC molecular diagnostics. We demonstrated the multiplex capability of SARS-COV-2 and human18S ribosomal RNA RT-LAMP without complicating assay design. This generic platform can be extended in a similar manner to include human18S ribosomal RNA IACs into different clinical sample matrices.
Cooperativity, information gain, and energy cost during early LTP in dendritic spines
Authors: Karbowski Jan , Urban Paulina 
Published: October 2023

AbstractWe investigate a mutual relationship between information and energy during early phase of LTP induction and maintenance in a large-scale system of mutually coupled dendritic spines with discrete internal states and probabilistic dynamics within the framework of nonequilibrium stochastic thermodynamics. In order to analyze this computationally intractable stochastic multidimensional system, we introduce a pair approximation, which allows us to reduce the spine dynamics into a lower dimensional manageable system of closed equations. It is found that the rates of information gain and energy attain their maximal values during an initial period of LTP (i.e. during stimulation), and after that they recover to their baseline low values, as opposed to a memory trace that lasts much longer. This suggests that learning phase is much more energy demanding than the memory phase. We show that positive correlations between neighboring spines increase both a duration of memory trace and energy cost during LTP, but the memory time per invested energy increases dramatically for very strong positive synaptic cooperativity, suggesting a beneficial role of synaptic clustering on memory duration. In contrast, information gain after LTP is the largest for negative correlations, and energy efficiency of that information generally declines with increasing synaptic cooperativity. We also find that dendritic spines can use sparse representations for encoding of long-term information, as both energetic and structural efficiencies of retained information and its lifetime exhibit maxima for low fractions of stimulated synapses during LTP. Moreover, we find that such efficiencies drop significantly with increasing the number of spines. In general, our stochastic thermodynamics approach provides a unifying framework for studying, from first principles, information encoding and its energy cost during learning and memory in stochastic systems of interacting synapses.
Specificity and promiscuity of JAK recruitment regulates pleiotropy of cytokine-receptor signaling
Authors: Zoler Eyal , Meyer Thomas , Bellón Junel Sotolongo , Sun Boyue , Piehler Jacob , Schreiber Gideon 
Published: October 2023

AbstractPromiscuous binding of different Janus kinases (JAKs) to class I/II cytokine receptors has been reported, yet its role in signaling is unclear. To systematically explore JAK pairing in type I interferon (IFN-I) signaling, we generated an artificial IFN-I receptor (AIR) by replacing the extracellular domains of IFNAR1 and IFNAR2 with anti mEGFP and mCherry nanobodies. The heterodimeric AIR restored near-native IFN-I activity, while the homomeric variant of IFNAR2 (AIR-dR2) initiated much weaker signaling despite harboring docking sites for signal transducer and activator of transcription (STAT) proteins. AIR-dR1 was signaling inactive, yet, pulldown uncovered its ICD to bind both TYK2 and JAK1. To further investigate the roles of JAKs on the receptors, knockout (KO) JAK1, JAK2, TYK2, and JAK2/TYK2 were generated. JAK1 KO led to complete loss of IFN-I signaling, which was partially restored by TYK2 overexpression. TYK2 KO cells retained partial activity, which was elevated by JAK1 overexpression, suggesting both JAKs to partially substitute each other. Conversely, JAK2 KO only moderately impacted the biological activity of IFN-Is, even in JAK2/TYK2 KO cells. Live cell micropatterning confirmed promiscuous binding of JAK1, JAK2 and TYK2 to IFNAR1 and IFNAR2, in line with an AlphaFold model that shows JAKs interchangeability on IFNAR ICDs. Similar promiscuity of JAK binding was observed for TPOR and GHR but not EPOR, accompanied by different downstream signaling activity. The competitive binding of JAKs to cytokine receptors together with the highly diverse absolute and relative JAK expression levels can account for cell type-dependent signaling pleiotropy observed for cytokine receptors.One Sentence SummaryPromiscuous and interchangeable binding of JAKs to cytokine receptors enables cell type-specific pleiotropic signaling.
The high of higher education: interactivity its influence and effectiveness on virtual communities
Authors: Srivastava Kajal , Siddiqui Masood H. , Kaurav Rahul Pratap Singh , Narula Sumit , Baber Ruturaj 
Published: October 2023

PurposeAmidst the COVID-19 pandemic, education has shifted to online teaching and learning. Interactivity is a crucial tool used to make online education effective. This study empirically examines the role of interactivity in higher education and its influence on students' behavioral outcomes, specifically focusing on soft skills and personality upgradation.Design/methodology/approachA quasi-experimental research design was carried out for post-graduate students undergoing a business communication course from four major institutions. For analysis, t-test, confirmatory factor analysis (CFA) and partial least squares structural equation modeling (PLS-SEM) have been employed. Experimental research has established the causal relationship between interactivity, personality and soft skill upgradation (SSU).FindingsIt was found that the theoretical structural model has a rational model-fit validity. Resultantly, practitioners may use prior knowledge of virtual community (VC) members to enhance web interactivity, thereby increasing social identity and social bonds in a group for more meaningful and effective delivery of online courses.Research limitations/implicationsThe major limitations lie in its context-dependent nature, predominantly influenced by the pandemic-induced mandatory online learning. The study's cross-sectional design also inhibits its ability to assess goal-directed behaviors over time, necessitating further longitudinal research.Originality/valueThe study is one of the pioneering pieces of research that examines the role of pre-defined grouping and enhanced web interactivity in VCs in the context of online learning, especially during the COVID-19 pandemic. Integrating theories of web interactivity, social bond theory (SBT) and social identity theory (SIT) provides a novel understanding of cognitive and social influences that drive meaningful online discussions and their impacts on knowledge enhancement and personality development. Its findings have implications for the design of effective online learning environments and e-learning pedagogy, contributing to the growing domain of information and communication technology (ICT)-enabled education.
A subgrid model with multiple relaxation time for lattice Boltzmann method based on the Cartesian grid
Authors: Qiu Aoxiang , Sang Weimin , Zhou Feng , Li Dong 
Published: October 2023

Purpose The paper aims to expand the scope of application of the lattice Boltzmann method (LBM), especially in the field of aircraft engineering. The traditional LBM is usually applied to incompressible flows at a low Reynolds number, which is not sufficient to satisfy the needs of aircraft engineering. Devoted to tackling the defect, the paper proposes a developed LBM combining the subgrid model and the multiple relaxation time (MRT) approach. A multilayer adaptive Cartesian grid method to improve the computing efficiency of the traditional LBM is also employed.Design/methodology/approach The subgrid model and the multilayer adaptive Cartesian grid are introduced into MRT-LBM for simulations of incompressible flows at a high Reynolds number. Validated by several typical flow simulations, the numerical methods in this paper can efficiently study the flows under high Reynolds numbers.Findings Some numerical simulations for the lid-driven flow of cavity, flow around iced GLC305, LB606b and ONERA-M6 are completed. The paper presents the investigation results, indicating that the methods are accurate and effective for the separated flow after icing.Originality/value LBM is developed with the addition of the subgrid model and the MRT method. A numerical strategy is proposed using a multilayer adaptive Cartesian grid method and its treatment of boundary conditions. The paper refers to innovative algorithm developments and applications to the aircraft engineering, especially for iced wing simulations with flow separations.