bluuebunny/crossref_metadata_2025_split huggingface dataset:
Climate change education in public health and medical curricula in Australian and New Zealand Universities: a mixed methods study of barriers and areas for further action
Authors: Lal Aparna , Walsh Erin , Weatherell Ali , Slimings Claudia 
Published: June 2021

AbstractBackgroundThe World Health Organization deemed climate change and air pollution as the top threat to global health in 2019. The importance of climate for health is recognised by healthcare professionals, who need to be equipped to deliver environmentally sustainable healthcare and promote planetary health. There is some evidence that climate change and health is not strongly embedded in accredited master-level public health training programs and medical programs globally, however, the immersion of climate-health in Australian and New Zealand programs is unclear.ObjectivesTo explore the extent to which climate-health education is currently embedded into public health and medical curricula in Australia and New Zealand.MethodsEducators identified by their coordination, convenorship, or delivery into programs of public health and medicine at universities in Australia and New Zealand were invited to participate in a cross-sectional, exploratory mixed methods study. Participants completed an online quantitative survey and qualitative interviews regarding their experience in program and course delivery, and the prominence of climate-health content within program and course delivery. Quantitative surveys were analysed using descriptive statistics and qualitative interview content was analysed via a modified ground theory approach.ResultsThe response rate of the quantitative survey was 43.7% (21/48). Ten survey respondents also completed qualitative interviews. Quantitative results showed that epidemiologists were the most common experts involved in design and delivery of this curriculum, with a reliance on guest lecturers to provide updated content. Qualitative interviews highlighted the ad-hoc role of Indigenous-led content in this field, the barriers of time and resources to develop a coherent curriculum and the important role of high-level champions to drive the inclusion of climate change and planetary health.ConclusionThere is an urgent need to strengthen current support available for pedagogical leadership in the area of climate and broader environmental change teaching at universities.
A Patient-Reported Measure of Locomotor Function Derived from the Functional Assessment Questionnaire
Authors: Schwartz Michael H. , Aldahondo Nanette , MacWilliams Bruce A. 
Published: June 2021

AbstractBackgroundLocomotor function is often impaired in children diagnosed with cerebral palsy (CP). Improving locomotor function is a common goal of treatment. The current gold standard for assessing locomotor function in CP is the gross motor function measure (GMFM-66). The GMFM-66 requires an in-person assessment by a trained clinician. It would be useful to have a measure of function that is like the GMFM-66 but can be assessed through patient report.MethodsWe queried the clinical databases of two motion analysis centers (Gillette Children’s Specialty Healthcare and Shriners Hospital – Salt Lake City) for individuals with a diagnosis of cerebral palsy (CP) who were 18 years old or younger and had undergone instrumented clinical gait analysis that included the functional assessment questionnaire (FAQ). We computed the transformed FAQ (FAQt) as the weighted sum of the skills an individual was able to perform, where the weighting was the difficulty of the skills. We assessed concurrent and external validity of the FAQt by comparing it to the GMFM-66.ResultsThe FAQt exhibited strong concurrent and external validity. Linear regression showed that the GMFM-66 explained 54% of the variance in FAQt, and the linear fit was independent of center. The FAQt evolved with age in a manner similar to the GMFM-66, with higher functioning individuals, as measured by gross motor function classification system level, achieving higher levels of function at a higher rate and an earlier age compared to their lower functioning peers. The findings with respect to GMFM-66 did not depend on the center at which the data was acquired.ConclusionsThe FAQt demonstrates strong concurrent and external validity, making it a useful measure of locomotor function.
Quantitative definition of fever needs a change
Authors: Kumar Nitin , Kapoor Mayank , Panda Prasan Kumar , Singh Yogesh , Bhadoriya Ajeet Singh 
Published: June 2021

AbstractBackgroundThe age-old definition of fever was derived using cross-sectional population surveying utilizing old techniques without considering symptomatology. However, the diagnosis of fever must be made only in the presence of associated symptoms that can distinguish it from the mere asymptomatic physiologic rise of temperature. Association of the temperature values with the symptoms to define the cut-off for fever is need of the hour.MethodsA longitudinal study on the healthy population of Northen-India were followed-up over 1-year. Participants were advised for self-monitoring of oral temperature with a standard digital thermometer in either left or right sublingual pocket and record it in the thermometry diary. The study was considered complete if the participant had all the three phases of the study (i.e. non-febrile, febrile, and post-febrile phases) or completed the duration of the study.ResultsPer protocol analysis done for febrile participants (n=144, temperature recordings= 23851). The mean febrile phase temperature was 100.25 ± 1.440F. A temperature of 99.10F had maximum diagnostic accuracy for feeling feverish (98.2%), along with one (98.3%) or two (99%) associated symptoms. Summer and spring months showed higher temperatures (100.38 ± 1.44 v/s 99.80 ± 1.49, P<0.001), whereas no significant temperature difference could be noted amongst the gender.ConclusionsA revised cut-off for the temperature to decide fever is hereby proposed: 99.10F along with one or two associated symptoms. This is going to redefine fever in the modern era completely.
INCIDENCE OF VENOUS THROMBOTIC EVENTS AND EVENTS OF SPECIAL INTEREST IN A RETROSPECTIVE COHORT OF COMMERCIALLY-INSURED US PATIENTS
Authors: Weller Susan C. , Porterfield Laura , Davis John W. , Wilkinson Gregg S. , Chen Lu , Baillargeon Jacques 
Published: June 2021

ABSTRACTObjectiveTo estimate the US incidence of thrombotic events and related rare diagnoses.DesignClaims-based retrospective cohort study of incidence.SettingUS commercial health insurance administrative claims database.ParticipantsAdults 25-65 years of age between 2015 and 2019 with a minimum of 12 consecutive thrombosis-free months of continuous enrollment beginning 2014 were selected.Main OutcomesAge (10-year intervals) and sex stratum specific incidence rates per 100,000 person-years were determined for: venous thromboembolism (VTE), cerebral venous thrombosis (CVT), and other major venous thrombotic events, and events of special interest, including immune thrombocytopenic purpura (ITP), hemolytic-uremic syndrome (HUS), and heparin-induced thrombocytopenia (HIT).ResultsOf 13,249,229 enrollees (half female/male), incidence of venous thromboembolic events (DVT, PE, CVT, or other major venous thrombotic conditions) was 247.89 per 100,000 person-years (95% CI: 245.96, 249.84). Incidence of VTE was 213.79 with ICD codes alone (95% CI: 211.99, 215.59) and 127.18 (95% CI: 125.80, 128.58) when also requiring a filled anticoagulation prescription. Incidence was 6.37 for CVT (95% CI: 6.07, 6.69), 26.06 for ITP (95% CI: 25.44, 26.78), 0.94 for HUS (95% CI: 0.82, 1.06), and 4.82 for HIT (95% CI: 4.56, 5.10). The co-occurrence of CVT with either ITP or HIT (diagnoses within 14 days of one another) was 0.090 (95% CI: 0.06, 0.13). Incidence tended to increase with age and was higher for women under 55. Incidence for CVT, HUS, and CVT with ITP or HIT was higher for women in all age groups. Incidence of PE and CVT increased significantly over the five-year period, while DVT rates decreased.ConclusionsThese results are the first US estimates for incidence of thrombotic and rare events of interest in a large, commercially-insured US population. Findings provide a critically important reference for determining excess morbidity associated with COVID-19 and more generally for vaccine pharmacovigilance.BOX POINTSWhat is already known on this topic?Incidence of venous thromboembolic diagnoses vary by country and date.There have been improvements in the past decade in thromboprophylaxis (e.g., for deep vein thrombosis) and detection (e.g., for cerebral venous thrombosis), but there are no recent comprehensive estimates for the United States.What this study addsOur results document the US incidence of thrombotic and related rare diagnoses for the most recent five-year pre-pandemic period (2015-2019) in an insured population.
Rapid antifouling nanocomposite coating enables highly sensitive multiplexed electrochemical detection of myocardial infarction and concussion markers
Authors: Timilsina Sanjay S. , Durr Nolan , Yafia Mohamed , Sallum Hani , Jolly Pawan , Ingber Donald E. 
Published: June 2021

ABSTRACTHere we describe an ultra-fast (< 1 min) method for coating electrochemical (EC) sensors with an anti-fouling nanocomposite layer that can be stored at room temperature for months, which provides unprecedented sensitivity and selectivity for diagnostic applications. We leveraged this method to develop a multiplexed diagnostic platform for detection of biomarkers that could potentially be used to triage patients with myocardial infarction and traumatic brain injury using only 15 µL of blood. Single-digit pg/mL sensitivity was obtained within minutes for all the biomarkers tested in unprocessed human plasma samples and whole blood, which is much faster and at least 50 times more sensitive than traditional ELISA methods, and the signal was stable enough to be measured after one week of storage. The multiplexed EC sensor platform was validated by analyzing 22 patient samples, which demonstrated excellent correlation with reported clinical values.
Immunogenicity and reactogenicity of a heterologous COVID-19 prime-boost vaccination compared with homologous vaccine regimens
Authors: Schmidt Tina , Klemis Verena , Schub David , Mihm Janine , Hielscher Franziska , Marx Stefanie , Abu-Omar Amina , Schneitler Sophie , Becker Sören L. , Gärtner Barbara C. , Sester Urban , Sester Martina 
Published: June 2021

AbstractHeterologous priming with the ChAdOx1-nCoV-19 vector-vaccine followed by boosting with an mRNA-vaccine is currently recommended in Germany, although data on immunogenicity and reactogenicity are not available. Here we show that the heterologous regimen induced spike-specific IgG, neutralizing antibodies, and spike-specific CD4 T-cells, which were significantly more pronounced than after homologous vector boost, and higher or comparable in magnitude to the homologous mRNA regimens. Moreover, spike-specific CD8 T-cell levels after heterologous vaccination were significantly higher than after both homologous regimens. Cytokine expression profiling showed a predominance of polyfunctional T-cells expressing IFNγ, TNFα and IL-2 with subtle differences between regimens. Both recipients of the homologous vector-regimen and the heterologous vector/mRNA-combination were most affected by the priming vector-vaccination, whereas heterologous boosting was well tolerated and comparable to homologous mRNA-boosting. Taken together, heterologous vector-mRNA boosting induces strong humoral and cellular immune responses with acceptable reactogenicity profile. This knowledge will have implications for future vaccine strategies.
Similar Rates of AKI during the First Two Waves of COVID-19 in Northern Italy: a single-center study
Authors: Alfano Gaetano , Giovanella Silvia , Fontana Francesco , Milic Jovana , Ligabue Giulia , Giaroni Francesco , Ferri Camilla , Montali Martina , Melluso Andrea , Niccolò Morisi , Mori Giacomo , Magistroni Riccardo , Franceschini Erica , Bedini Andrea , Cuomo Giacomo , DiGaetano Margherita , Meschiari Marianna , Mussini Cristina , Cappelli Gianni , Guaraldi Giovanni 
Published: June 2021

AbstractIntroductionTwo waves of COVID-19 cases have overwhelmed most European countries during 2020. It is unclear if the incidence of acute kidney injury (AKI) has changed during the COVID-19 outbreaks. This study aims to evaluate the differences in incidence, risk factors and outcome of AKI in patients with SARS-CoV-2 infection during the first and second wave of COVID-19.MethodWe reviewed the health medical records of 792 consecutive patients with COVID-19 hospitalized at the University Hospital of Modena, Italy, from February 25 to December 14, 2020.ResultsAKI was diagnosed in 122 (15.4%) patients. Incidence of AKI remained steady rate during wave-1 (15.9%) and wave-2 (14.7%) (P=0.89). AKI patients were older (P=<0.001) and had a more severe respiratory impairment (PO2/FO2) (P=≤0.001) than their non-AKI counterparts. AKI led to a longer hospital stay (P=0.001), complicated with a higher rate of ICU admission. COVID-19-related AKI was associate with 59.7% of deaths during wave-1 and 70.6% during wave-2. At the end of the period of observation, 24% (wave-1) and 46.7% (wave-2) of survivors were discharged with a not fully recovered kidney function. Risk factors for AKI in patients with COVID-19 were diuretics (HR=5.3; 95%CI, 1.2-23.3; P=0.025) and cardiovascular disease (HR, 2.23; 95%CI, 1.05-5.1; P=0.036).ConclusionThe incidence of AKI (about 15%) remained unchanged during 2020, regardless of the trend of COVID-19. AKI occurred in patients with severe COVID-19 symptoms and was associated with a higher incidence of deaths than non-AKI patients. The risk factors of COVID-19-related AKI were diuretic therapy and cardiovascular disease.
Quantifying concordant genetic effects of de novo mutations on multiple disorders
Authors: Guo Hanmin , Hou Lin , Shi Yu , Jin Sheng Chih , Zeng Xue , Li Boyang , Lifton Richard P. , Brueckner Martina , Zhao Hongyu , Lu Qiongshi 
Published: June 2021

AbstractExome sequencing on tens of thousands of parent-proband trios has identified numerous deleterious de novo mutations (DNMs) and implicated risk genes for many disorders. Recent studies have suggested shared genes and pathways are enriched for DNMs across multiple disorders. However, existing analytic strategies only focus on genes that reach statistical significance for multiple disorders and require large trio samples in each study. As a result, these methods are not able to characterize the full landscape of genetic sharing due to polygenicity and incomplete penetrance. In this work, we introduce EncoreDNM, a novel statistical framework to quantify shared genetic effects between two disorders characterized by concordant enrichment of DNMs in the exome. EncoreDNM makes use of exome-wide, summary-level DNM data, including genes that do not reach statistical significance in single-disorder analysis, to evaluate the overall and annotation-partitioned genetic sharing between two disorders. Applying EncoreDNM to DNM data of nine disorders, we identified abundant pairwise enrichment correlations, especially in genes intolerant to pathogenic mutations and genes highly expressed in fetal tissues. These results suggest that EncoreDNM improves current analytic approaches and may have broad applications in DNM studies.
miR-544-3p mediates arthritis pain through regulation of FcγRI
Authors: Liu Yan , Jeon Sang-Min , Caterina Michael J. , Qu Lintao 
Published: June 2021

AbstractChronic or episodic joint pain is a major symptom in rheumatoid arthritis (RA) and its adequate treatment represents an unmet medical need. However, the cellular and molecular mechanisms underlying RA pain remain elusive. Non-coding microRNAs (miRNAs) have been implicated in the pathogenesis of RA as negative regulators of the stability or translation of specific target mRNAs. Yet, their significance in RA pain is still not well defined. We and other groups recently identified neuronally expressed FcγRI as a key driver of arthritis pain in mouse RA models. Thus, we tested the hypothesis that miRNAs that target and regulate neuronal FcγRI attenuate RA pain. Here, we show that miR-544-3p was robustly downregulated whereas FcγRI was significantly upregulated in the dorsal root ganglion (DRG) in mouse RA models. Intrathecal injection of miR-544-3p mimic attenuated established mechanical and heat hyperalgesia in a mouse model of collagen II-induced arthritis (CIA). Moreover, this effect was likely mediated, at least in part, by FcγRI since miR-544-3p mimic downregulated FcγRI in the DRG during arthritis and genetic deletion of FcγRI produced similar antihyperalgesic effects in the CIA model. This notion was further supported by a dual luciferase assay showing that miR-544-3p targeted FcγRI by directly binding to its 3’UTR. In addition, FcγRI expression in DRG neurons in vitro was downregulated by miR-544-3p mimic and upregulated by miR-544-3p inhibitor. In naïve mice, miR-544-3p mimic alleviated acute joint pain hypersensitivity induced by IgG immune complex (IgG-IC), whereas miR-544-3p inhibitor potentiated the pro-nociceptive behavioral effect of IgG-IC. These findings suggest that miR-544-3p causally participates in the maintenance of arthritis pain by targeting neuronal FcγRI, and thus define miR-544-3p as a new potential therapeutic target for treating RA pain.
Rapid Characterization of Human Serum Albumin Binding for Per- And Polyfluoroalkyl Substances Using Differential Scanning Fluorimetry
Authors: Jackson Thomas W. , Scheibly Chris M. , Polera M. E. , Belcher Scott M. 
Published: June 2021

AbstractPer- and polyfluoroalkyl substances (PFAS) are a diverse class of synthetic chemicals that accumulate in the environment. Many proteins, including the primary human serum transport protein albumin (HSA), bind PFAS. The predictive power of physiologically based pharmacokinetic modeling approaches are currently limited by a lack of experimental data defining albumin binding properties for most PFAS. A novel thermal denaturation assay was optimized to evaluate changes in thermal stability of HSA in the presence of increasing concentrations of known ligands and a structurally diverse set of PFAS. Assay performance was initially evaluated for fatty acids and HSA binding drugs ibuprofen and warfarin. Concentration response relationships were determined and dissociation constants (Kd) for each compound were calculated using regression analysis of the dose-dependent changes in HSA melting temperature. Estimated Kdvalues for HSA binding of octanoic acid, decanoic acid, hexadecenoic acid, ibuprofen and warfarin agreed with established values. The binding affinities for 24 PFAS that included perfluoroalkyl carboxylic acids (C4-C12), perfluoroalkyl sulfonic acids (C4-C8), mono- and polyether perfluoroalkyl ether acids, and polyfluoroalkyl fluorotelomer substances were determined. These results demonstrate the utility of this differential scanning fluorimetry assay as a rapid high through-put approach for determining the relative protein binding properties and identification of chemical structures involved in binding for large numbers of structurally diverse PFAS.
Deep learning models for identification of splice junctions across species
Authors: Dutta Aparajita , Singh Kusum Kumari , Anand Ashish 
Published: June 2021

AbstractDeep learning models like convolutional neural networks (CNN) and recurrent neural networks (RNN) have been frequently used to identify splice sites from genome sequences. Most of the deep learning applications identify splice sites from a single species. Furthermore, the models generally identify and interpret only the canonical splice sites. However, a model capable of identifying both canonical and non-canonical splice sites from multiple species with comparable accuracy is more generalizable and robust. We choose some state-of-the-art CNN and RNN models and compare their performances in identifying novel canonical and non-canonical splice sites in homo sapiens, mus musculus, and drosophila melanogaster.The RNN-based model named SpliceViNCI outperforms its counterparts in identifying splice sites from multiple species as well as on unseen species. SpliceViNCI maintains its performance when trained with imbalanced data making it more robust. We observe that all the models perform better when trained with more than one species. SpliceViNCI outperforms the counterparts when trained with such an augmented dataset. We further extract and compare the features learned by SpliceViNCI when trained with single and multiple species. We validate the extracted features with knowledge from the literature.
CCPE: Cell Cycle Pseudotime Estimation for Single Cell RNA-seq Data
Authors: Liu Jiajia , Yang Mengyuan , Zhao Weiling , Zhou Xiaobo 
Published: June 2021

AbstractThe rapid development of single-cell RNA-sequencing (scRNA-seq) technologies makes it possible to characterize cellular heterogeneity by detecting and quantifying transcriptional changes at the single-cell level. Pseudotime analysis enables to characterize the continuous progression of various biological processes, such as cell cycle. Cell cycle plays an important regulatory role in cell fate decisions and differentiation and is also often regarded as a confounder in scRNA-seq data analysis when analyzing the role of other factors on transcriptional regulation. Therefore, accurate prediction of cell cycle pseudotime and identify cell stages are important steps for characterizing the development-related biological processes, identifying important regulatory molecules and promoting the analysis of transcriptional heterogeneity. Here, we develop CCPE, a novel cell cycle pseudotime estimation method to characterize cell cycle timing and determine cell cycle phases from single-cell RNA-seq data. CCPE uses a discriminative helix to characterize the circular process and estimates pseudotime in the cell cycle. We evaluated the model performance based on a variety of simulated and real scRNA-seq datasets. Our results indicate that CCPE is an effective method for cell cycle estimation and competitive in various downstream analyses compared with other existing methods. CCPE successfully identified cell cycle marker genes and is robust to dropout events in scRNA-seq data. CCPE also has excellent performance on small datasets with fewer genes or cells. Accurate prediction of the cell cycle in CCPE effectively contributes to cell cycle effect removal across cell types or conditions.