bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dual mTORC1/mTORC2 inhibition as a Host-Directed Therapeutic Target in Pathologically Distinct Mouse Models of Tuberculosis
Authors: Tasneen Rokeya , Mortensen Deborah S. , Converse Paul J. , Urbanowski Michael E. , Upton Anna , Fotouhi Nader , Nuermberger Eric , Hawryluk Natalie 
Published: February 2021

AbstractEfforts to develop more effective and shorter-course therapies for tuberculosis have included a focus on host-directed therapy (HDT). The goal of HDT is to modulate the host response to infection, thereby improving immune defenses to reduce the duration of antibacterial therapy and/or the amount of lung damage. As a mediator of innate and adaptive immune responses involved in eliminating intracellular pathogens, autophagy is a potential target for HDT in tuberculosis. BecauseMycobacterium tuberculosismodulates mammalian target of rapamycin (mTOR) signaling to impede autophagy, pharmacologic mTOR inhibition could provide effective HDT. mTOR exists within two distinct multiprotein complexes, mTOR complex-1 (mTORC1) and mTOR complex-2 (mTORC2). Rapamycin and its analogs only partially inhibit mTORC1. We hypothesized that novel mTOR kinase inhibitors blocking both complexes would have expanded therapeutic potential. We compared the effects of two mTOR inhibitors: rapamycin and the orally available mTOR kinase domain inhibitor CC214-2, which blocks both mTORC1 and mTORC2, as adjunctive therapies against murine TB, when added to the first-line regimen (RHZE) or the novel bedaquiline-pretomanid-linezolid (BPaL) regimen. Neither mTOR inhibitor affected lung CFU counts after 4-8 weeks of treatment when combined with BPaL or RHZE. However, addition of CC214-2 to BPaL and RHZE was associated with significantly fewer relapses in C3HeB/FeJ compared to addition of rapamycin and, in RHZE-treated mice, resulted in fewer relapses compared to RHZE alone. Therefore, CC214-2 and related mTOR kinase inhibitors may be more effective candidates for HDT than rapamycin analogs and may have the potential to shorten the duration of TB treatment.
Plasma pharmacokinetics of high dose oral versus intravenous rifampicin in patients with tuberculous meningitis: a randomized controlled trial
Authors: Wasserman Sean , Davis Angharad , Stek Cari , Chirehwa Maxwell , Botha Stephani , Daroowala Remy , Bremer Marise , Maxebengula Mpumi , Koekemoer Sonya , Goliath Rene , Jackson Amanda , Crede Thomas , Naude Jonathan , Szymanski Patryk , Vallie Yakoob , Moosa Muhammed S , Wiesner Lubbe , Black John , Meintjes Graeme , Maartens Gary , Wilkinson Robert J 
Published: February 2021

ABSTRACTBackgroundHigher doses of intravenous rifampicin may improve outcomes in tuberculous meningitis but is impractical in high burden settings. We hypothesized that plasma rifampicin exposures would be similar between oral 35 mg/kg and intravenous 20 mg/kg, which has been proposed for efficacy trials in tuberculous meningitis.Materials and methodsWe performed a randomized parallel group pharmacokinetic study nested within a clinical trial of intensified antimicrobial therapy for tuberculous meningitis. HIV-positive participants with tuberculous meningitis were recruited from South African hospitals and randomized to one of three rifampicin dosing groups: standard (oral 10 mg/kg), high dose (oral 35 mg/kg), and intravenous (intravenous 20 mg/kg). Intensive pharmacokinetic sampling was done on day 3. Data were described using non-compartmental analysis and exposures compared by geometric mean ratio (GMR).ResultsForty-six participants underwent pharmacokinetic sampling (standard dose, n = 17; high dose oral, n= 15; IV, n = 14). Median CD4 count was 130 cells/mm3 (IQR 66 −253). Geometric mean AUC0-∞ was 47.7 µg·h/mL (90% CI, 33.2 – 68.5) for standard dose; 322.3 µg·h/mL (90% CI,234.6 – 442.7) for high dose; and 214.6 µg·h/mL (90% CI, 176.2 – 261.2) for intravenous. High dose oral dosing achieved higher rifampicin exposure than intravenous: AUC0-∞ GMR 0.67 (90% CI, 0.46 −1.0); however, Cmax GMR was 1.11 (90% CI, 0.81 – 1.59), suggesting equivalence.ConclusionsPlasma rifampicin exposure was similar with high dose oral and intravenous administration. Findings support oral rifampicin dosing in future tuberculous meningitis trials.
A Method for Machine Learning Generation of Realistic Synthetic Datasets for Validating Healthcare Applications
Authors: Arvanitis Theodoros N. , White Sean , Harrison Stuart , Chaplin Rupert , Despotou George 
Published: February 2021

ABSTRACTBackgroundDigital health applications can improve quality and effectiveness of healthcare, by offering a number of tools to patients, professionals, and the healthcare system. Introduction of new technologies is not without risk, and digital health applications are often considered a medical device. Assuring their safe operation requires, amongst others, clinical validation, which needs large datasets to test their application in realistic clinical scenarios. Access to such datasets is challenging, due to concerns about patient privacy. Development of synthetic datasets, which will be sufficiently realistic to test digital applications, is seen as a potential alternative, enabling their deployment.ObjectiveThe aim of work was to develop a method for the generation of realistic synthetic datasets, statistically equivalent to real clinical datasets, and demonstrate that Generative Adversarial Network based approach is fit for purpose.MethodA generative adversarial network was implemented and trained, in a series of six experiments, using numerical and categorical variables from three clinically relevant datasets, including ICD-9 and laboratory codes from the MIMIC III dataset. A number of contextual steps provided the success criteria for the synthetic dataset.ResultsThe approach created a synthetic dataset that exhibits very similar statistical characteristics with the real dataset. Pairwise association of variables is very similar. A high degree of Jaccard similarity and a successful K-S test further support this.ConclusionsThe proof of concept of generating realistic synthetic datasets was successful, with the approach showing promise for further work.
Inclusion of cycle threshold (CT) values when reporting SARS-CoV-2 RT-PCR results improves clinical Interpretation in suspected and confirmed COVID-19
Authors: Coyle Peter V. , Molawi Naema Hassan Al , Kacem Mohamed Ali Ben Hadj , Kahlout Reham Awni El , Kuwari Einas Al , Khal Abdullatif Al , Gilliani Imtiaz , Jeremijenko Andrew , Saeb Hatoun , Thani Sheikh Mohammad Al , Bertollini Roberto , Rahim Hanan F. Abdul , Chemaitelly Hiam , Tang Patrick , Latif Ali Nizar , Kaabi Saad Al , AlMaslamani Muna A. Rahman S. , Morris Brendan David , Al-Ansari Nasser , Kaleeckal Anvar Hassan , Raddad Laith J. Abu 
Published: February 2021

IntroductionThe Cycle Threshold (CT) value in Real-time Polymerase Chain Reaction (RT-PCR) is where a target specific amplification signal becomes detectable and can infer viral load, risk of transmission and recovery in SARS-CoV-2 infections. Adoption into routine practice is however uncommon.Gap StatementThe lack of inclusion of CT values when reporting SARS-CoV-2 RT-PCR results in routine practice.AimTo use CT values when reporting SARS-CoV-2 RT-PCR results in Qatar to aid clinical interpretation and patient management.MethodologyRoutine CT values across 3 different RT-PCR platforms were reviewed for concordance at presentation and clearance in patients with COVID-19. An Indicative Threshold of CT 30 based on viral clearance kinetics categorized low and high CT values.ResultsThere was very high Correlation and Kappa Score agreement between the different gene targets in each platform (p<0.001). Using the Indicative Threshold it was possible to autoverify and add average CT values and append Interpretive Comments to all RT-PCR reports. The new reporting algorithm impacted immediately and safely on: physician interpretation of SARS-CoV-2 results; patient management; staff surveillance protocols; length of stay in quarantine; a redefinition of patient recovery.ConclusionIncorporation of CT values into routine practice is possible across different RT-PCR platforms and adds useful information for patient management. The use of an Indicative Threshold and interpretive comments improves clinical interpretation of the result and could be a model for reporting other respiratory infections. The current accepted practice of withholding CT values should be reviewed by the profession, accreditation bodies and regulators.
Returning to nursing during the COVID-19 pandemic: experiences and needs of re-entering nurses
Authors: Noorland Sofie A. , Hoekstra Trynke , Kok Maarten O. 
Published: February 2021

AbstractAimAssessing the needs and experiences of re-entering nurses during the COVID-19 pandemic.BackgroundDuring the COVID-19 outbreak in the Netherlands, thousands of former nurses have returned to nursing to support healthcare staff. After a period of absence and with little time to prepare, these former nurses re-entered during a challenging, uncertain and rapidly evolving pandemic. Little is known about the experiences and needs of these re-entering nurses.DesignQualitative studyMethodsWe conducted semi-structured interviews with 20 purposively selected nurses who had re-entered nursing during the first wave of the COVID-19 pandemic in the Netherlands. Interviews were transcribed verbatim and analysed via thematic content analysis. This study followed the COREQ guidelines.ResultsParticipants mentioned that a lack of a clear job description led to unclarity about the kind of tasks that re-entering nurses were expected and allowed to perform. This unclarity was especially notable in the newly established COVID-19 departments. Re-entering nurses mentioned to wish for an easily accessible mentorship structure and an individualised and practical training program. Re-entering nurses felt supported by a positive team dynamic, which was shaped by the sense of urgency and relevance of their work and helped them deal with stressful experiences.ConclusionThe results indicate that a rapid and safe return to nursing during a pandemic could be facilitated by: a clear description of roles and responsibilities; an individualised assessment determining the competences and knowledge disparities of re-entering nurses; practical training focussing on competencies needed during a pandemic; and a collaborative mentorship structure to guide re-entering nurses.Relevance to clinical practiceThe rapid recruitment of former nurses to mitigate an acute shortage of qualified nurses could play a vital role during a pandemic. To deploy these nurses effectively, safely and sustainably, it is important to address the needs of these re-entering nurses.What does this paper contribute towards the wider global clinical community?This research showed the need to prepare a flexible individualised training programme which could support re-entering nurses during crisis situations, such as a pandemic.A responsive mentorship structure helps to provide support to re-entering nurses in a dynamic, uncertain and rapidly evolving situation.In a rapidly evolving situation, it is essential to continue to create clarity about the roles and responsibilities of re-entering nurses.
Mandatory public health measures for COVID-19 are associated with improved mortality, equity and economic outcomes
Authors: Lundberg Brita E. , McDonald Kathyrn 
Published: February 2021

AbstractWe review approaches to the COVID-19 pandemic in a systematic way by comparing countries/states representative of the mandatory vs. voluntary approach to non-pharmaceutical interventions in Europe and the US. We use a comparative tabular format to examine differences in mortality, economic impact and equity between regions with mandatory versus voluntary policies. Mandatory shelter-in-place policies were associated with 3 to 4 fold lower population adjusted mortality in the US model and 11 fold lower in the European one. We conclude that voluntary policies are less effective, based on historical precedent and the current analysis. Moreover, effects on health equity mirrored the increased mortality outcomes of voluntary policies and there was no apparent economic benefit associated with voluntary measures.
The association of CREBRF variant rs373863828 with body composition in adult Samoans
Authors: Hawley Nicola L. , Duckham Rachel L. , Carlson Jenna C. , Naseri Take , Reupena Muagututia Sefuiva , Lameko Viali , Pomer Alysa , Wetzel Abigail , Selu Melania , Lupematisila Vaimoana , Unasa Folla , Vesi Lupesina , Fatu Tracy , Unasa Seipepa , Faasalele-Savusa Kima , Viali Satupaitea , Rivara Anna C. , Russell Emily M. , Deka Ranjan , Kershaw Erin E. , Minster Ryan L. , Weeks Daniel E. , McGarvey Stephen T. 
Published: February 2021

AbstractObjectiveThe minor allele of rs373863828, a missense variant in CREBRF, is associated with higher BMI but lower odds of type 2 diabetes in Pacific Islanders.MethodsTo test if this protective effect operates through metabolically favorable body fat distribution, we examined the association of the minor A allele with body composition, measured using dual-energy x-ray absorptiometry (DXA), in a cross-sectional study of n=421 Samoan adults.ResultsWe replicated our earlier finding that this allele was associated with higher weight and BMI, although it was statistically significant only in women. There was no significant association of genotype with percent body fat, visceral adiposity or fat distribution, although in women, the A allele was associated with greater total fat mass (p=0.02), android (p=0.009) and trunk fat (p=0.01). In both sexes, age- and height-adjusted average lean mass was significantly greater per copy of the A allele: 2.16 kg/copy in women and 1.73 kg/copy in men.ConclusionsThese data do not support a primary role of fat distribution in mediating the association between rs373863828 genotype and type 2 diabetes risk. We suggest an alternative hypothesis: those with the A allele may more efficiently regulate blood glucose because of their greater absolute lean mass.
Noncommunicable Diseases, Sociodemographic Vulnerability, and the Risk of Mortality in Hospitalized Children and Adolescents with COVID-19 in Brazil: A Syndemic in Play
Authors: Sousa Braian Lucas Aguiar , Maria Brentani Alexandra Valeria , Ribeiro Cecilia Claudia Costa , Dolhnikoff Marisa , Ellero Grisi Sandra Josefina Ferraz , Ferrer Ana Paula Scoleze , Ferraro Alexandre Archanjo 
Published: February 2021

AbstractBackgroundAlthough many studies identify the presence of comorbidities and socioeconomic vulnerabilities as risk factors for worse COVID-19 outcomes, few have addressed this issue in children. We aimed to study how these factors have impacted COVID-19 mortality in Brazilian children and adolescents.MethodsThis is an observational study using publicly available data from the Brazilian Ministry of Health. We studied 5,857 patients younger than 20 years old, all of them hospitalized with laboratory-confirmed COVID-19. We used multilevel mixed-effects generalized linear models to study mortality, stratifying the analysis by age, region of the country, presence of noncommunicable diseases, ethnicity, and socioeconomic development.FindingsIndividually, most of the comorbidities included were risk factors. Having more than one comorbidity increased almost tenfold the risk of death (OR 9·67 95%CI 6·89-13·57). Compared to White children, Indigenous, Pardo (mixed), and East Asian had a significantly higher risk of mortality. We also found a regional effect (higher mortality in the North), and a socioeconomic effect (higher mortality among children from less socioeconomically developed municipalities).InterpretationBesides the impact of comorbidities, we identified ethnic, regional, and socioeconomic effects shaping the mortality of children hospitalized with COVID-19 in Brazil. Putting these findings together, we propose that there is a syndemic among COVID-19 and noncommunicable diseases, driven and fostered by large-scale sociodemographic inequalities. Facing COVID-19 in Brazil must also include addressing these structural issues. Our findings also identify risk groups among children that should be prioritized for public health measures, such as vaccination.FundingNone.
Development of a new Aerosol Barrier Mask for mitigation of spread of SARS-CoV-2 and other infectious pathogens
Authors: Karam Karam Abi , Hota Piyush , Mora S. Jimena , Lowell Amelia , McKay Kelly , Xian Xiaojun , Patel Bhavesh , Forzani Erica 
Published: February 2021

AbstractThe COVID-19 pandemic has caused huge impact on public health and significantly changed our lifestyle. This is due to the fast airborne oro-nasal transmission of SARS-CoV-2 from the infected individuals. The generation of liquid aerosolized particles occurs when the COVID-19 patients speak, sing, cough, sneeze, or simply breathe. We have developed a novel aerosol barrier mask (ABM) to mitigate the spread of SARS-CoV-2 and other infectious pathogens. This Aerosol Barrier Mask is designed for preventing SARS-CoV-2 transmission while transporting patients within hospital facilities. This mask can constrain aerosol and droplet particles and trap them in a biofilter, while the patient is normally breathing and administrated with medical oxygen. The system can be characterized as an oxygen delivery and mitigation mask which has no unfiltered exhaled air dispersion. The mask helps to prevent the spread of SARS-CoV-2, and potentially other infectious respiratory pathogens and protects everyone in general, especially healthcare professionals.
Clinician Readiness to Adopt A.I. for Critical Care Prioritisation
Authors: Kennedy Georgina , Gallego Blanca 
Published: February 2021

AbstractThere is a wide chasm between what has been shown to be feasible in the application of artificial intelligence to data from the electronic medical record, and what is currently available. The reasons for this are complex and understudied, and vary across technical, ethical and sociocultural domains. This work addresses the gap in the literature for studies that determine the readiness of clinical end-users to adopt such tools and the way in which they are perceived to affect clinical practice itself.In this study, we present a novel, credible AI system for predicting in-patient deterioration to likely end users. We gauge their readiness to adopt this technology using a modified version of the technology adoption model.Users are found to be moderately positive towards the potential introduction of this technology in their workflow, although they demonstrate particular concern for the appropriateness of the clinical setting into which it is deployed.
Development of an exosomal gene signature to detect residual disease in dogs with osteosarcoma using a novel xenograft platform and machine learning
Authors: Makielski Kelly M. , Donnelly Alicia J. , Khammanivong Ali , Scott Milcah C. , Ortiz Andrea R. , Galvan Dana C. , Tomiyasu Hirotaka , Amaya Clarissa , Ward Kristi , Montoya Alexa , Garbe John R. , Mills Lauren J. , Cutter Gary R. , Fenger Joelle M. , Kisseberth William C. , O’Brien Timothy D. , Weigel Brenda J. , Spector Logan G. , Bryan Brad A. , Subramanian Subbaya , Modiano Jaime F. 
Published: February 2021

AbstractOsteosarcoma has a guarded prognosis. A major hurdle in developing more effective osteosarcoma therapies is the lack of disease-specific biomarkers to predict risk, prognosis, or therapeutic response. Exosomes are secreted extracellular microvesicles emerging as powerful diagnostic tools. However, their clinical application is precluded by challenges in identifying disease-associated cargo from the vastly larger background of normal exosome cargo. We developed a method using canine osteosarcoma in mouse xenografts to distinguish tumor-derived from host-response exosomal mRNAs. The model allows for the identification of canine osteosarcoma-specific gene signatures by RNA sequencing and a species-differentiating bioinformatics pipeline. An osteosarcoma-associated signature consisting of five gene transcripts (SKA2, NEU1, PAF1, PSMG2, and NOB1) was validated in dogs with spontaneous osteosarcoma by qRT-PCR, while a machine learning model assigned dogs into healthy or disease groups. Serum/plasma exosomes were isolated from 53 dogs in distinct clinical groups (“healthy”, “osteosarcoma”, “other bone tumor”, or “non-neoplastic disease”). Pre-treatment samples from osteosarcoma cases were used as the training set and a validation set from post-treatment samples was used for testing, classifying as “osteosarcoma–detected” or “osteosarcoma–NOT detected”. Dogs in a validation set whose post-treatment samples were classified as “osteosarcoma–NOT detected” had longer remissions, up to 15 months after treatment. In conclusion, we identified a gene signature predictive of molecular remissions with potential applications in the early detection and minimal residual disease settings. These results provide proof-of-concept for our discovery platform and its utilization in future studies to inform cancer risk, diagnosis, prognosis, and therapeutic response.Abstract Figure
A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genusPopulus
Authors: Conde Daniel , Triozzi Paolo M. , Balmant Kelly M. , Doty Andria L. , Miranda Mariza , Boullosa Anthony , Schmidt Henry W. , Pereira Wendell J. , Dervinis Christopher , Kirst Matias 
Published: February 2021

ABSTRACTSingle-cell transcriptome analysis has been extensively applied in humans and animal models to uncover gene expression heterogeneity between the different cell types of a tissue or an organ. It demonstrated its capability to discover the key regulatory elements that determine cell fate during developmental programs such as brain or heart development. Single-cell analysis requires the isolation and labeling of the messenger RNA (mRNA) derived from each cell. These challenges were primarily addressed in mammals by developing microfluidic-based approaches. For plant species whose cells contain cell walls, these approaches have generally required the generation of isolated protoplasts. Many plant tissues’ secondary cell wall hinders enzymatic digestion required for individual protoplast isolation, resulting in an unequal representation of cell types in a protoplast population. This limitation is especially critical for cell types located in the inner layers of a tissue or the inner tissues of an organ. Consequently, single-cell RNA sequencing (scRNA-seq) studies using microfluidic approaches in plants have mainly been restricted toArabidopsisroots, for which well-established procedures of protoplast isolation are available. Here we present a simple alternative approach to generating high-quality protoplasts from plant tissue by characterizing the mRNA extracted from individual nuclei instead of whole cells. We developed the protocol using two different plant materials with varying cellular complexity levels and cell-wall structure,Populusshoot apices, and more lignified stems. Using the 10× Genomics Chromium technology, we show that this procedure results in intact mRNA isolation and limited leakage, with a broad representation of individual cell transcriptomes.