bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improvement of Electronic Health Record Integrated Transition Planning Tools in Primary Care
Authors: Rusley Jack , Tomaszewski Kathy , Kim Julia , Robinson Larnce , Rose Kadi-Ann , Aronin Caroline , Molloy Matthew , Arrington-Sanders Renata 
Published: May 2020

Introduction:
The transition from pediatric to adult care is under-studied in primary care. Electronic health record-integrated transition planning tools (ETPTs) can facilitate the transition. We tested whether ETPTs and clinician reminders increase the frequency of transition discussions during adolescent well-visits.

Methods:
In an academic adolescent medicine primary care practice serving a predominantly African American, Medicaid-insured population, we developed 4 ETPTs—readiness assessment, plan template, information handout, and diagnosis code. We used Plan-Do-Study-Act quality improvement cycles to implement ETPTs and measure outcomes. Each cycle added a new layer of clinician support: (1) ETPT training, (2) visual reminders, (3) incentives, and (4) daily reminders. The primary outcome was the proportion of well-visits in which “any ETPT use” occurred. We collected data via chart review and used run charts and regression analyses with multiple comparisons to detect differences between cycles. Clinicians-provided feedback was elicited.

Results:
Any ETPT use increased from 0% to 45% between baseline and cycle 4. The odds of any ETPT use was ten times larger in cycle 4 compared to cycle 1 (odds ratio 10.09, 95% confidence interval 2.29–44.44, P = 0.002) and 22 times larger in cycle 4 than cycle 2 (odds ratio 21.99, 95% confidence interval 3.96–122.00, P < 0.001). Clinicians identified time constraints and lack of sociocultural relevance as barriers to uptake.

Conclusions:
Daily reminders combined with training and visual reminders were effective in increasing the use of ETPTs in primary care. Future interventions should adapt existing transition tools to the needs of target populations and create regular reminders to facilitate uptake.
Urinary Reflux Into the Prostate Gland and Seminal Vesicles
Authors: Hekimsoy Turkay , Gorur Gozde Daglioz , Isgoren Serkan , Uslu Hande , Demir Hakan 
Published: May 2020

Abstract
A 64-year-old man with lung cancer underwent 18F-FDG PET/CT for restaging, which demonstrated intense 18F-FDG uptake in the right lobe of prostate gland and seminal vesicles, indicating a potential prostate cancer. In 68Ga-PSMA PET/CT, intense uptake in the right lobe of prostate gland and seminal vesicles was also observed but decreased in postmictional delayed images. Magnetic resonance imaging showed high signal intensity of urine in the same areas of uptakes. 18F-FDG and 68Ga-PSMA PET/CT findings in the prostate gland and seminal vesicles were considered to be a result of urinary reflux possibly because of the patient’s previous transurethral resection.
Contractility and Myofibrillar Content in Skeletal Muscle are Decreased During Post-Sepsis Recovery, But Not During the Acute Phase of Sepsis
Authors: Crowell Kristen T. , Lang Charles H. 
Published: May 2020

ABSTRACT
Convalescence in humans after severe sepsis occurs over weeks to months and is associated with prolonged functional disabilities and impaired quality-adjusted survival. While much is known regarding the acute early phase of sepsis, there is a knowledge gap pertaining to restoration of muscle mass and function after elimination of the septic nidus. We used a sepsis-recovery model—where cecal-ligation-puncture (CLP) was performed in adult male mice followed 24 h later by removal of the cecum and antibiotic treatment—to assess changes in the abundance of muscle contractile proteins and function during the acute phase of sepsis (24 h post-CLP) and during the recovery phase (day 10 post-CLP). Although body weight and food consumption decreased acutely with sepsis, both had normalized by day 10; however, extensor digitorum longus mass remained decreased 10%. During acute sepsis, there were few contractile defects or significant changes in contractile proteins. In contrast, during sepsis recovery, specific maximum isometric twitch and specific maximum tetanic force were decreased ≈50%, compared with time-matched pair-fed controls, and defects were independent of the concomitant reduction in muscle mass. Force generation in sepsis-recovery mice was decreased 30% with increasing stimulus frequency. Contractile defects during sepsis-recovery were associated with 50% to 90% reductions in thin filament (troponin T, troponin I, tropomyosin, α-sarcomeric actin), thick filament (myosin heavy and myosin light chains), Z-disc (α-actinin 3), and M-band (myomesin-2) proteins, but no change in the intermediate filaments desmin and vimentin. During sepsis recovery, myofibrillar protein synthesis did not differ from control, but synthesis of sarcoplasmic proteins was increased 60%. These data suggest intrinsic defects in muscle contractile function exist during the recovery phase of sepsis and may negatively impact convalescence.
Arachidonic Acid-Dependent Pathway Inhibition in Platelets: its Role in Multiple Injury-Induced Coagulopathy and the Potential Mechanisms
Authors: Tang Yao , Huang Sunhua , Lin Wenhao , Wen Ke , Lin Zhexuan , Han Ming 
Published: May 2020

ABSTRACT

Background:
Our previous study demonstrated the types of platelet dysfunction varied at early stage (∼3 h) in trauma-induced coagulopathy (TIC) caused by different types of injuries. And arachidonic acid (AA)-dependent pathway inhibition in platelet seemed to be specific for TIC caused by multiple injury (MI). The aim of this research was to further study AA-dependent pathway inhibition in platelets in a rat model of TIC caused by MI and to explore its potential mechanisms.

Methods:
Sprague-Dawley rat model of TIC caused by MI was established. We used thrombelastography with platelet mapping as a measure of platelet function to assess the inhibitory extent of AA-dependent activation pathway. Flow cytometry was used to determine the expression of activation-dependent granular protein P-selectin (CD62P). In addition, the plasma levels of 6-Keto-prostaglandin F1 alpha (6-Keto-PGF1α), Prostaglandin E2, and Thromboxane B2 were assessed by enzyme-linked immuno sorbent assay.

Results:
The inhibition rate of AA-dependent pathway after injury was significantly higher than that of control. The maximum amplitude decreased in the MI group, compared with that of control. The percentage of CD62P expression in the MI group was remarkably lower than that of control after AA treatment. The plasma concentrations of 6-Keto-PGF1α and PGE2 increased in the MI group.

Conclusion:
Platelets inhibition was observed in TIC caused by MI at early stage after injury, which might be partially attributed to AA-dependent activation pathway dysfunction. The increase of plasma Prostacyclin and PGE2 levels may contribute to the inhibition process.
Applying Principles From Aviation Safety Investigations to Root Cause Analysis of a Critical Incident During a Simulated Emergency
Authors: Imach Sebastian , Eppich Walter , Zech Alexandra , Kohlmann Thorsten , Prückner Stephan , Trentzsch Heiko 
Published: May 2020

Summary Statement
Safety investigations in aviation aim to identify potential root causes. They use structured techniques to analyze information from flight data and cockpit voice recorders. Full-scale medical simulations using audiovisual recordings provide similar possibilities. During a simulated cardiac arrest, an incident related to use of the defibrillator (automated external defibrillator) occurred with emergency medical services (EMS) providers. Treatment interventions and dialogs during the incident were extracted from audiovisual recordings and transferred into a transcript of events.
Knowing indicated treatment measures, the team adhered to automated external defibrillator voice prompts rather than follow their own assessment. Cardiopulmonary resuscitation was on hold for 72% of the time. Time to first defibrillation was delayed by 2:17 minutes. Transcript allowed us to identify faulty decision-making, loss of leadership, and automation bias as possible root causes. Use of RCA methodology during medical simulation improves understanding of critical incidents and can contribute to training of EMS personnel and education of instructors.
Visual statistical learning and integration of perceptual priors are intact in Attention Deficit Hyperactivity Disorder
Authors: Richards Katie L. , Karvelis Povilas , Lawrie Stephen M. , Seriès Peggy 
Published: May 2020

AbstractDeficits in statistical learning and predictive processing could in principle explain inattention and distractibility in attention deficit hyperactivity disorder (ADHD).To test this, we evaluated whether adults diagnosed with ADHD (n = 17) differed from controls (n = 30) in implicitly learning and using low-level perceptual priors to guide sensory processing. We used a visual statistical learning task in which participants had to estimate the direction of coherently moving dots. Unbeknown to the participants, two directions were more frequently presented than the others, creating an implicit bias (prior) towards those directions. This task had previously revealed differences in autistic spectrum disorder and schizophrenia.Both groups acquired the prior expectations for the most frequent directions and, except for some subtle differences over time, there were no group difference in how much the priors influenced performance. This suggests that ADHD symptoms do not stem from difficulties in developing and/or using perceptual priors.Statement of RelevanceSchizophrenia, autistic spectrum disorder (ASD), and more recently anxiety and depression have all been described in terms of disturbances in predictive coding or Bayesian inference – a general mechanism for how incoming sensory information is integrated with prior knowledge and how such prior knowledge is learnt. In theory, Attention deficit hyperactivity disorder (ADHD) is also associated with a range of sensory processing differences that could be understood within the Bayesian inference framework. However, to our knowledge, there has been no experimental work explicitly testing differences in Bayesian inference in ADHD so far.Here we found the acquisition and use of the low-level perceptual priors to be intact in ADHD, compared to controls.Our study shows for the first time that the learning and use of low-level Bayesian priors are not impaired in ADHD, contrary to what has been described in other neurodevelopmental disorders.
Multilevel Integrated Model with a Novel Systems Approach (MIMANSA) for Simulating the Spread of COVID-19
Authors: Welling Arpita , Patel Abhilasha , Kulkarni Padmaj , Vaidya Vinay G. 
Published: May 2020

AbstractDue to the spread of the coronavirus, public health officials grapple with multiple issues such as recommending a lockdown, contact tracing, promoting the use of masks, social distancing, frequent handwashing, as well as quarantining. It is even more challenging to find the optimal combination of these factors without the use of a suitable mathematical model.In this paper, we discuss a novel systems approach to building a model for simulating the spread of COVID-19. The model, MIMANSA, divides an individual’s in-person social interactions into three areas, namely home, workplace, and public places. The model tracks the in-person interactions and follows the virus spread. When a new silent carrier is created, the model automatically expands and builds a new layer in the network.MIMANSA has four control mechanisms, namely the exposure, infection rate, lockdown, and quarantining. MIMANSA differentiates between virus-infected patients, silent carriers, and healthy carriers. It can consider variations in virus activity levels of asymptomatic patients, varying the exposure to the virus, and varying the infection rate depending on the person’s immunity. MIMANSA can simulate scenarios to study the impact of many different conditions simultaneously. It could assist public health officials in complex decision making, enable scientists in projecting the SARS-CoV-2 virus spread and aid hospital administrators in the management of beds and equipment.MIMANSA is trained and validated using the data from the USA and India. Our results show that MIMANSA forecasts the number of COVID-19 cases in the USA, and India within a 3% margin of error.
Atrophy of the Nucleus Basalis of Meynert predicts the progression of gait variability in Parkinson’s disease
Authors: Wilkins Kevin B. , Parker Jordan E. , Bronte-Stewart Helen M. 
Published: May 2020

AbstractParkinson’s disease (PD) is a systemic brain disorder where the cortical cholinergic network begins to degenerate early in the disease process. Readily accessible, quantitative, and specific behavioral markers of the cortical cholinergic network are lacking. Although degeneration of the dopaminergic network may be responsible for deficits in cardinal motor signs, the control of gait is a complex process and control of higher-order aspects of gait, such as gait variability, may be influenced by cognitive processes attributed to cholinergic networks. We investigated whether swing time variability, a metric of gait variability that is independent from gait speed, was a quantitative behavioral marker of cortical cholinergic network integrity in PD. Twenty-two individuals with PD and twenty-nine age-matched controls performed a validated stepping-in-place (SIP) task to assess swing time variability off all therapy. The PD cohort also underwent structural MRI scans to measure gray matter volume of the Nucleus Basalis of Meynert (NBM), the key node in the cortical cholinergic network. Swing time variability was also measured ON subthalamic nucleus (STN) deep brain stimulation (DBS) in PD individuals. A subset of eleven individuals with PD completed the SIP task again off all therapy after three years of continuous DBS. Clinical motor assessments were performed for each condition. Swing time variability was significantly greater (i.e., worse) in PD compared to controls and greater swing time variability was related to greater atrophy of the NBM. STN DBS significantly improved cardinal motor signs but did not improve swing time variability. Swing time variability worsened in PD, off therapy, after three years of continuous STN DBS, and NBM atrophy predicted the degree of increase. In contrast, cardinal motor signs did not progress. These results demonstrate that swing time variability is a reliable marker of cortical cholinergic health, and support a framework in which higher-order aspects of gait control in PD are reliant on the cortical cholinergic system, in contrast to other motor aspects of PD that rely on the dopaminergic network.
Preventive efficacy of a tenofovir alafenamide fumarate nanofluidic implant in SHIV-challenged nonhuman primates
Authors: Pons-Faudoa Fernanda P. , Sizovs Antons , Shelton Kathryn A. , Momin Zoha , Bushman Lane R. , Xu Jiaqiong , Chua Corrine Ying Xuan , Nichols Joan E. , Hawkins Trevor , Rooney James F. , Marzinke Mark A. , Kimata Jason T. , Anderson Peter L. , Nehete Pramod N. , Arduino Roberto C. , Ferrari Mauro , Sastry K. Jagannadha , Grattoni Alessandro 
Published: May 2020

AbstractPre-exposure prophylaxis (PrEP) using antiretroviral oral drugs is effective at preventing HIV transmission when individuals adhere to the dosing regimen. Tenofovir alafenamide (TAF) is a potent antiretroviral drug, with numerous long-acting (LA) delivery systems under development to improve PrEP adherence. However, none has undergone preventive efficacy assessment. Here we show that LA TAF using a novel subcutaneous nanofluidic implant (nTAF) confers partial protection from HIV transmission. We demonstrate that sustained subcutaneous delivery through nTAF in rhesus macaques maintained tenofovir diphosphate concentration at a median of 390.00 fmol/106peripheral blood mononuclear cells, 9 times above clinically protective levels. In a non-blinded, placebo-controlled rhesus macaque study with repeated low-dose rectal SHIVSF162P3challenge, the nTAF cohort had a 62.50% reduction (95% CI: 1.72% to 85.69%;p=0.068) in risk of infection per exposure compared to the control. Our finding mirrors that of tenofovir disoproxil fumarate (TDF) monotherapy, where 60.00% protective efficacy was observed in macaques, and clinically, 67.00% reduction in risk with 86.00% preventive efficacy in individuals with detectable drug in the plasma. Overall, our nanofluidic technology shows potential as a subcutaneous delivery platform for long-term PrEP and provides insights for clinical implementation of LA TAF for HIV prevention.
DCI: Learning Causal Differences between Gene Regulatory Networks
Authors: Belyaeva Anastasiya , Squires Chandler , Uhler Caroline 
Published: May 2020

AbstractSummaryDesigning interventions to control gene regulation necessitates modeling a gene regulatory network by a causal graph. Currently, large-scale expression datasets from different conditions, cell types, disease states and developmental time points are being collected. However, application of classical causal inference algorithms to infer gene regulatory networks based on such data is still challenging, requiring high sample sizes and computational resources. Here, we propose an algorithm that efficiently learns the differences in gene regulatory mechanisms between different conditions. Our difference causal inference (DCI) algorithm infers changes (i.e., edges that appeared, disappeared or changed weight) between two causal graphs given gene expression data from the two conditions. This algorithm is efficient in its use of samples and computation since it infers the differences between causal graphs directly without estimating each possibly large causal graph separately. We provide a user-friendly Python implementation of DCI and also enable the user to learn the most robust difference causal graph across different tuning parameters via stability selection. Finally, we show how to apply DCI to bulk and single-cell RNA-seq data from different conditions and cell states, and we also validate our algorithm by predicting the effects of interventions.Availability and implementationAll algorithms are freely available as a Python package athttp://uhlerlab.github.io/causaldag/dciContactcuhler@mit.edu
A rat epigenetic clock recapitulates phenotypic aging and co-localizes with heterochromatin-associated histone modifications
Authors: Levine Morgan , McDevitt Ross , Meer Margarita , Perdue Kathy , Di Francesco Andrea , Meade Theresa , Farrell Colin , Thrush Kyra , Wang Meng , Dunn Christopher , Pellegrini Matteo , de Cabo Rafael , Ferrucci Luigi 
Published: May 2020

ABSTRACTAging has been shown to be a strong driver of DNA methylation changes, leading to the development of robust biomarkers in humans and more recently, in mice. This study aimed to generate a novel epigenetic clock in rats—a model with unique physical, physiological, and biochemical advantages for studying mammalian aging. Additionally, we incorporated behavioral data, unsupervised machine learning, and network analysis to identify epigenetic signals that not only track with age, but also relate to phenotypic aging and reflect higher-order molecular aging changes. We used DNAm data from reduced representation bisulfite sequencing (RRBS) to train an epigenetic age (DNAmAge) measure in Fischer 344 CDF (F344) rats. In an independent sample of n=32 F344 rats, we found that this measure correlated with age at (r=0.93), and related to physical functioning (5.9e-3), after adjusting for age and differential cell counts. DNAmAge was also found to correlate with age in C57BL/6 mice (r=0.79), and was decreased in response to caloric restriction (CR), such that the longer the animal was on a CR diet, the greater the decrease in DNAm. We also observed resetting of DNAm when kidney and lung fibroblasts when converted to induced pluripotent stem cells (iPSCs). Using weighted gene correlation network analysis (WGCNA) we identified two modules that appeared to drive our DNAmAge measure. These two modules contained CpGs in intergenic regions that showed substantial overlap with histone marks H3K9me3, H3K27me3, and E2F1 transcriptional factor binding. In moving forward, our ability to unravel the complex signals linking DNA methylation changes to functional aging would require experimental studies in model systems in which longitudinal epigenetic changes can be related to other molecular and physiological hallmarks of aging.
Chest MRI of patients with COVID-19: a retrospective case study
Authors: Vasilev Yu.A. , Sergunova K.A. , Bazhin A.V. , Masri A.G. , Vasileva Yu.N. , Semenov D.S. , Kudryavtsev N.D. , Panina O.Yu. , Khoruzhaya A.N. , Zinchenko V.V. , Akhmad E.S. , Petraikin A.V. , Vladzymyrskyy A.V. , Midaev A.V. , Morozov S.P. 
Published: May 2020

ABSTRACTDuring the pandemic of COVID-19, computed tomography showed its effectiveness in diagnosis of coronavirus infection. However, ionizing radiation during CT studies causes concern for patients who require dynamic observation, as well as for examination of children and young people. For this retrospective study, we included 15 suspected for COVID-19 patients who were hospitalized in April 2020, Russia. There were 4 adults with positive polymerase chain reaction (PCR) test for COVID-19. All patients underwent MRI examinations using MR-LUND PROTOCOL: Single-shot Fast Spin Echo (SSFSE), LAVA 3D and IDEAL 3D, EPI diffusion-weighted imaging (DWI) and Fast Spin Echo (FSE) T2WI without using respiratory or any other trigger. 3 patients also had CT scan performed. In 5 (33,3%) patients, detected lesioins were visualized on T2WI and DWI simultaneously. At the same time, 4 (26.7%) patients revealed lung tissue changes only on T2WI (P(McNemar)= 0,125, OR= 0,00 (95%), kappa=0,500). Pulmonary changes on MRI were also analyzed depending on their localization. In those patients who had CT scan, the changes were comparable to MRI. MRI of the lungs can detect features of viral pneumonia and assess severity of lung damage. The method can be used to diagnose COVID-19. These data may be applicable for interpreting other studies, such as thoracic spine MRI, detecting signs of viral pneumonia of asymptomatic patients. The current study was limited by a small sample size and absence of chest CT scans of all patients.
COVID-19 healthcare demand projections: Arizona
Authors: Gel Esma S. , Jehn Megan , Lant Timothy , Muldoon Anna R. , Nelson Trisalyn , Ross Heather M. 
Published: May 2020

AbstractBeginning in March 2020, the United States emerged as the global epicenter for COVID-19 cases. In the ensuing weeks, American jurisdictions attempted to manage disease spread on a regional basis using non-pharmaceutical interventions (i.e., social distancing), as uneven disease burden across the expansive geography of the United States exerted different implications for policy management in different regions. While Arizona policymakers relied initially on state-by-state national modeling projections from different groups outside of the state, we sought to create a state-specific model using a mathematical framework that ties disease surveillance with the future burden on Arizona’s healthcare system. Our framework uses a compartmental system dynamics model using a SEIRD framework that accounts for multiple types of disease manifestations for the COVID-19 infection, as well as the observed time delay in epidemiological findings following public policy enactments. We use a bin initialization logic coupled with a fitting technique to construct projections for key metrics to guide public health policy, including exposures, infections, hospitalizations, and deaths under a variety of social reopening scenarios.