bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pandemic Lock-down, Isolation, and Exit Policies Based on Machine Learning Predictions
Authors: Evgeniou Theodoros , Fekom Mathilde , Ovchinnikov Anton , Porcher Raphael , Pouchol Camille , Vayatis Nicolas 
Published: May 2020

The widespread lockdowns imposed in many countries at the beginning of the COVID-19 pandemic elevated the importance of research on pandemic management when medical solutions such as vaccines are unavailable. We present a framework that combines a standard epidemiological SEIR (susceptible-exposed-infected-removed) model with an equally standard machine learning classification model for clinical severity risk, defined as an individual’s risk needing intensive care unit (ICU) treatment if infected. Using COVID-19-related data and estimates for France as of spring 2020, we then simulate isolation and exit policies. Our simulations show that policies considering clinical risk predictions could relax isolation restrictions for millions of the lowest-risk population months earlier while consistently abiding by ICU capacity restrictions. Exit policies without risk predictions, meanwhile, would considerably exceed ICU capacity or require the isolation of a substantial portion of population for over a year in order to not overwhelm the medical system. Sensitivity analyses further decompose the impact of various elements of our models on the observed effects.Our work indicates that predictive modelling based on machine learning and artificial intelligence could bring significant value to managing pandemics. Such a strategy, however, requires governments to develop policies and invest in infrastructure to operationalize personalized isolation and exit policies based on risk predictions at scale. This includes health data policies to train predictive models and apply them to all residents, as well as policies for targeted resource allocation to maintain strict isolation for high-risk individuals.
Mathematical model describing CoViD-19 in São Paulo State, Brazil – Evaluating isolation as control mechanism and forecasting epidemiological scenarios of release
Authors: Yang Hyun Mo , Junior Luis Pedro Lombardi , Castro Fabio Fernandes Morato , Yang Ariana Campos 
Published: May 2020

AbstractWe formulated a mathematical model considering young (below 60 years old) and elder (above 60 years) subpopulations to describe the introduction and dissemination of new coronavirus epidemics in the São Paulo State, Brazil. From the data collected in São Paulo State, we estimated the model parameters and calculated the basic reproduction number asR0= 6.828. Considering isolation as a control mechanism, we varied the releasing proportions of young and elder persons to assess their epidemiological impacts. The best scenarios were release of young persons, but maintaining elder persons isolated. To avoid the collapse of the health care system, the isolation must be at least 80%.
Public knowledge, attitudes and practices towards COVID-19: A cross-sectional study in Malaysia
Authors: Azlan Arina Anis , Hamzah Mohammad Rezal , Sern Tham Jen , Ayub Suffian Hadi , Mohamad Emma 
Published: May 2020

AbstractIn an effort to mitigate the outbreak of COVID-19, many countries have imposed drastic lockdown, movement control or shelter in place orders on their residents. The effectiveness of these mitigation measures is highly dependent on cooperation and compliance of all members of society. The knowledge, attitudes and practices people hold toward the disease play an integral role in determining a society’s readiness to accept behavioural change measures from health authorities. The aim of this study was to determine the knowledge levels, attitudes and practices toward COVID-19 among the Malaysian public. A cross-sectional online survey of 4,850 Malaysian residents was conducted between 27th March and 3rd April 2020. The survey instrument consisted of demographic characteristics, 13 items on knowledge, 3 items on attitudes and 3 items on practices, modified from a previously published questionnaire on COVID-19. Descriptive statistics, chi-square tests, t-tests and one-way analysis of variance (ANOVA) were conducted. The overall correct rate of the knowledge questionnaire was 80.5%. Most participants held positive attitudes toward the successful control of COVID-19 (83.1%), the ability of Malaysia to conquer the disease (95.9%) and the way the Malaysian government was handling the crisis (89.9%). Most participants were also taking precautions such as avoiding crowds (83.4%) and practising proper hand hygiene (87.8%) in the week before the movement control order started. However, the wearing of face masks was less common (51.2%). This survey is among the first to assess knowledge, attitudes and practice in response to the COVID-19 pandemic in Malaysia. The results highlight the importance of consistent messaging from health authorities and the government as well as the need for tailored health education programs to improve levels of knowledge, attitudes and practices.
Lack of Evidence for a Reduced Late Positive Potential in Major Depressive Disorder
Authors: Nikolin Stevan , Chand Nicholas , Martin Donel , Rushby Jacqueline , Loo Colleen K. , Boonstra Tjeerd W. 
Published: May 2020

ABSTRACTBackgroundIndividuals with major depressive disorder (MDD) present with deficits in emotional reactivity. Conflicting models have been proposed to explain this effect. We sought to test the emotional context insensitivity hypothesis, which suggests that reactivity to positive and negatively-valenced emotional stimuli is blunted in depression, in a preregistered study.MethodsForty-one depressed participants and 41 age- and gender-matched healthy controls were presented a series of unpleasant and neutrally-valenced pictures in a passive view paradigm while acquiring electroencephalography (EEG). The late positive potential (LPP), an EEG correlate of emotional reactivity, was compared between groups using mixed-effects repeated-measures models and exploratory cluster-based permutation tests. A sensitivity analysis was performed to assess the robustness of LPP findings by reanalysing the LPPs using 22 EEG pipelines from studies identified in the literature.ResultsWe found no difference in LPP amplitudes between MDD and healthy individuals using the preregistered analysis pipeline. The sensitivity analysis revealed that the magnitude and direction of LPP effect sizes were affected by the analysis pipeline. Exploratory permutation analyses revealed an electrode cluster that showed a significant reduction in the LPP for MDD participants while viewing unpleasant pictures.ConclusionsThese results do not provide evidence in support of the emotional context insensitivity hypothesis, except for the exploratory data-driven approach. Methodological differences, in particular in the analysis pipeline, contribute to the heterogeneity of LPP modulation in depression. A standardised approach to quantify EEG correlates of emotional reactivity is needed to evaluate alternative models of emotional reactivity in depression.
A systematic review and meta-analysis to evaluate the clinical outcomes in COVID -19 patients on angiotensin converting enzyme inhibitors or angiotensin receptor blockers
Authors: Grover Abhinav , Oberoi Mansi 
Published: May 2020

AbstractIntroductionAngiotensin converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) share their target receptor site with the SARS-CoV-2 virus, that may cause ACE2 receptor upregulation which raised concerns regarding ACEI and ARB use in COVID-19 patients. However, many medical professional societies recommended their continued use given the paucity of clinical evidence but there is need for an updated systematic review of latest clinical studies.MethodsA search was conducted on PubMed, Google Scholar, EMBASE and various preprint servers for studies comparing clinical outcomes and mortality in COVID-19 patients on ACEI and/or ARB and a meta-analysis was performed.ResultsA total of sixteen studies were included for review and meta-analysis. There were conflicting findings reported in several studies as Meng J. et al, Liu Y. et al, Feng Y. et al, Zhang P. et al, Mancia G. et al and Reynolds H.R. et al reported that patients on ACE inhibitors/ARB had lower rates of severe outcomes whereas Richardson S. et al reported higher rates of invasive ventilation and intensive care unit (ICU) admissions in patients on ACE inhibitors/ARB as compared to non-users. Similarly, there were conflicting results in the rate of mortality reported in the various studies. Meng J. et al, Li J. et al, Zhang P. et al, Yang G. et al, Zeng Z. et al and Andrew Ip et al reported lower rates of mortality in ACE inhibitors/ARB users versus non-users whereas Richardson S. et al and Guo T. et al reported higher rates of mortality. In a pooled analysis of 9 studies, there was a statistically significant reduction (OR = 0.86, 95% CI = 0.75-0.99, I2 = 53.25, p value = 0.03) in the odds of death in those on ACEI/ARB as compared to patients not on ACEI/ARB. In a pooled analysis of five studies, there was a statistically non-significant reduction (OR = 0.90, 95% CI: 0.63-1.23, I2=70.36) in the odds of developing severe disease in patients on ACEI/ARB versus non-users.ConclusionIt is concluded that ACEI and ARB should be continued in COVID-19 patients. Additionally, the individual patient factors like ACE2 polymorphisms which might confer higher risk of adverse outcomes need to be evaluated further.
Does weather affect the growth rate of COVID-19, a study to comprehend transmission dynamics on human health
Authors: Sil Arjun , Kumar Vanapalli Naveen 
Published: May 2020

AbstractThe undefendable outbreak of novel coronavirus (SARS-COV-2) lead to a global health emergency due to its higher transmission rate and longer symptomatic duration, created a health surge in a short time. Since Nov 2019 the outbreak in China, the virus is spreading exponentially everywhere. The current study focuses on the relationship between environmental parameters and the growth rate of COVID-19. The statistical analysis suggests that the temperature changes retarded the growth rate and found that −6.28°C and +14.51°C temperature is the favorable range for COVID-19 growth. Gutenberg-Richter’s relationship is used to estimate the mean daily rate of exceedance of confirmed cases concerning the change in temperature. Temperature is the most influential parameter that reduces the growth at the rate of 13–16 cases/day with a 1°C rise in temperature.
Pericyte-derived fibrotic scarring is conserved across diverse central nervous system lesions
Authors: Dias David O. , Kalkitsas Jannis , Kelahmetoglu Yildiz , Estrada Cynthia P. , Tatarishvili Jemal , Ernst Aurélie , Huttner Hagen B. , Kokaia Zaal , Lindvall Olle , Brundin Lou , Frisén Jonas , Göritz Christian 
Published: May 2020

AbstractFibrotic scar tissue limits central nervous system regeneration in adult mammals. The extent of fibrotic tissue generation and distribution of stromal cells across different lesions in the brain and spinal cord has not been systematically investigated in mice and humans. Furthermore, it is unknown whether scar-forming stromal cells have the same origin throughout the central nervous system and in different types of lesions. In the current study, we compared fibrotic scarring in human pathological tissue and corresponding mouse models of penetrating and non-penetrating spinal cord injury, traumatic brain injury, ischemic stroke, multiple sclerosis and glioblastoma. We show that the extent and distribution of stromal cells are specific to the type of lesion and, in most cases, similar between mice and humans. Employingin vivolineage tracing, we report that in all mouse models developing fibrotic tissue, the primary source of scar-forming fibroblasts is a discrete subset of perivascular cells, termed type A pericytes.We uncover pericyte-derived fibrosis as a conserved mechanism that may be explored as a therapeutic target to improve recovery after central nervous system lesions.
Causal role for sleep-dependent reactivation of learning-activated sensory ensembles for fear memory consolidation
Authors: Clawson Brittany C. , Pickup Emily J. , Enseng Amy , Geneseo Laura , Shaver James , Gonzalez-Amoretti John , Zhao Meiling , York A. Kane , Jiang Sha , Aton Sara J. 
Published: May 2020

AbstractLearning-activated engram neurons play a critical role in memory recall. An untested hypothesis is that these same neurons play an instructive role in offline memory consolidation. Here we show that a visually-cued fear memory is consolidated during post-conditioning sleep in mice. We then use TRAP (targeted recombination in active populations) to genetically label or optogenetically manipulate primary visual cortex (V1) neurons responsive to the visual cue. Following fear conditioning, mice respond to activation of this visual engram population in a manner similar to visual presentation of fear cues. Cue-responsive neurons are selectively reactivated in V1 during post-conditioning sleep. Mimicking visual engram reactivation optogenetically leads to increased representation of the visual cue in V1. Optogenetic inhibition of the engram population during post-conditioning sleep disrupts consolidation of fear memory. We conclude that selective sleep-associated reactivation of learning-activated sensory populations serves as a necessary instructive mechanism for memory consolidation.
Bacillus thuringiensisbioinsecticides induce developmental defects in non-targetDrosophila melanogasterlarvae
Authors: Nawrot-Esposito Marie-Paule , Babin Aurélie , Pasco Matthieu , Poirié Marylène , Gatti Jean-Luc , Gallet Armel 
Published: May 2020

AbstractBioinsecticides made from the bacteriumBacillus thuringiensis(Bt) are the best-selling bioinsecticide worldwide. AmongBtbioinsecticides, those based on the strainBt var. kurstaki(Btk) are widely used in farming to specifically control pest lepidopteran larvae. Although there is much evidence of the lack of acute lethality ofBtkproducts for non-target animals, only scarce data are available on their potential non-lethal developmental adverse effects. Using doses that could be reached in the field upon sprayings, we have shown thatBtkproducts impair growth and developmental time of the non-target dipteranDrosophila melanogaster. These effects are mediated by the synergy betweenBtkbacteria andBtkinsecticidal toxins, which induces a significant apoptosis of larval enterocytes, resulting in a decreased intestinal capacity to digest proteins. The harmful effects can be mitigated by a protein-rich diet or by adding the probiotic bacteriumLactobacillus plantaruminto the food. Finally, we showed that the larval midgut maintain its integrity uponBtkaggression thanks to both the flattening of surviving enterocytes and the generation of new immature cells arising from the adult midgut precursor cells.
Continued and Serious Lockdown Could Minimize Many Newly Transmitted Cases of COVID-19 in the U.S.: Wavelets, Deterministic Models, and Data
Authors: Srinivasa Rao Arni S.R. , Krantz Steven G. 
Published: May 2020

SummaryAll the newly reported COVID-19 cases of April in the U.S. have not acquired the virus in the same month. We estimate that there was an average of 29,000/day COVID-19 cases in the U.S. transmitted from infected to susceptible during April 1–24, 2020 after adjusting for under-reported and under-diagnosed. We have provided model-base d predictions of COVID-19 for the low and high range of transmission rates and with varying degrees of preventive measures including the lockdowns. We predict that even if 10% of the susceptible and 20 % of the infected who were not identified as of April 23, 2020, do not adhere to proper care or do not obey lockdown, then by the end of May and by end of June 50,000 and 55,000 new cases will emerge, respectively. These values for the months of May and June with worse adherence rates of 50% by susceptible and infected (but not identified) will be 251,000 and 511,000, respectively. Continued and serious lockdown measures could bring this average daily new cases to a further low at 4,300/day to 8,000/day in May.
COVID-19 in breast cancer patients: a cohort at the Institut Curie hospitals in the Paris area
Authors: Vuagnat Perrine , Frelaut Maxime , Ramtohul Toulsie , Basse Clémence , Diakite Sarah , Noret Aurélien , Bellesoeur Audrey , Servois Vincent , Hequet Delphine , Laas Enora , Kirova Youlia , Cabel Luc , Pierga Jean-Yves ,   Institut Curie Breast Cancer and COVID Group, Bozec Laurence , Paoletti Xavier , Cottu Paul , Bidard François-Clément 
Published: May 2020

AbstractBackgroundCancer patients have been reported to be at higher risk of COVID-19 complications and deaths. We report the characteristics and outcome of patients diagnosed with COVID-19 during breast cancer treatment at Institut Curie hospitals (ICH, Paris area, France).MethodsAn IRB-approved prospective registry was set up at ICH for all breast cancer patients with COVID-19 symptoms or radiologic signs.ResultsAmong 15,600 patients actively treated for early or metastatic breast cancer during the last 4 months at ICH, 76 patients with suspected COVID-19 infection were included in the registry and followed. Fifty-nine of these patients were diagnosed with COVID-19 based on viral RNA testing or typical radiologic signs: 37/59 (63%) COVID-19 patients were treated for metastatic breast cancer, and 13/59 (22%) of them were taking corticosteroids daily. Common clinical features mostly consisted of fever and/or cough, while ground-glass opacities were the most common radiologic sign at diagnosis. We found no association between prior radiation therapy fields or extent of radiation therapy sequelae and extent of COVID-19 lung lesions. Twenty-eight of these 59 patients (47%) were hospitalized and 6 (10%) were transferred to an intensive care unit. At the time of analysis, 45/59 (76%) patients were recovering or had been cured, 10/59 (17%) were still followed and 4/59 (7%) had died from COVID-19. All 4 patients who died had significant non-cancer comorbidities. In univariate analysis, hypertension and age (>70) were the two factors associated with a higher risk of intensive care unit admission and/or death.ConclusionsThis prospective registry analysis suggests that the COVID-19 mortality rate in breast cancer patients depends more on comorbidities than prior radiation therapy or current anti-cancer treatment. Special attention must be paid to comorbidities when estimating the risk of severe SARS-CoV-2 infection in breast cancer patients.
Prevalence of Chronic Hepatitis B and C in Malaysia- results from a community-based screening campaign
Authors: Lim ZZ , Teo JS , Tan AC , Siam Tan Soek , Mohamed Rosmawati , Goh KL , Jaya Fauziah , Senamjit K , Aun Azlida Che’ , Said Rosaida , Lim EK , Shahar Hamiza , Muhammad Radzi AH , Poh Tee Hoi , Seng Tan Soon , Menon Jayaram , Menon Rena , Lim TO 
Published: May 2020

AbstractIntroductionThe epidemiology of hepatitis, which is apparently endemic in Asia, is still poorly documented in Malaysia. Available statistics are modelled estimates based on expert input or estimated from small studies on special populations. We therefore determined the prevalence of chronic hepatitis B and C in Malaysia based on a large sample data from a screening campaign.MethodsA total of 10,914 subjects participated in the hepatitis screening campaign in 2018 and 2019. A low-cost Point-of-care test, which has previously been validated, was used to screen for HBsAg and anti-HCV. All screen positive subjects were recalled to undergo confirmatory serology tests and nucleic acid tests.ResultsWe estimated 1.17% or 238,971 Malaysian adults aged 20 or older had chronic HBV, while only 0.74% or 151,144 adults had chronic HCV. Young adults below age 30 years had very low prevalence of HBV (0.09%). Women had lower prevalence of HBV and HCV, Chinese had the highest prevalence of HBV while Malay had the highest prevalence of HCV.ConclusionYoung adults seems to be protected from HBV perhaps owing to the introduction of universal HBV vaccination since 1989. Chronic HBV however remains prevalent in older adults especially among the Chinese. Chronic HCV is uncommon in Malaysia.
A clinical and biological framework on the role of visceral fat tissue and leptin in SARS-CoV-2 infection related respiratory failure
Authors: van der Voort Peter HJ , Moser Jill , Zandstra Durk F , Kobold Anneke C Muller , Knoester Marjolein , Calkhoven Cornelis F. , Hamming Inge , van Meurs Matijs 
Published: May 2020

AbstractObesity is a risk factor for SARS-CoV-2 infected patients to develop respiratory failure. Leptin produced in visceral fat might play a role in the deterioration to mechanical ventilation. A cross sectional study was performed. The mean BMI was 31 kg/m2 (range 24.8 – 48.4) for the 31 SARS-CoV-2 ventilated patients and 26 kg/m2 (range 22.4-33.5) for the 8 controls. SARS-CoV-2 infected patients with a similar BMI as control patients appear to have significantly higher levels of serum leptin. The mean leptin level was 21.2 (6.0-85.2) vs 5.6 (2.4-8.2) ug/L for SARS-CoV-2 and controls respectively (p=0.0007). With these findings we designed a clinical and biological framework that explains clinical observations. The ACE2 utilization by the virus leads to local pulmonary inflammation due to ACE2-ATII disbalance. This is enhanced by an increase in leptin production induced by SARS-CoV-2 infection of visceral fat. Leptin receptors in the lungs are now more activated to enhance local pulmonary inflammation. This adds to the pre-existent chronic inflammation in obese patients. Visceral fat, lung tissue and leptin production play an interconnecting role. This insight can lead the way to further research and treatment.
Machine Learning for Pattern Detection in Cochlear Implant FDA Adverse Event Reports
Authors: Crowson Matthew G. , Hamour Amr , Lin Vincent , Chen Joseph M. , Chan Timothy C. Y. 
Published: May 2020

ABSTRACTImportanceThe United States Food & Drug Administration (FDA) passively monitors medical device performance and safety through submitted medical device reports (MDRs) in the Manufacturer and User Facility Device Experience (MAUDE) database. These databases can be analyzed for patterns and novel opportunities for improving patient safety and/or device design.ObjectivesThe objective of this analysis was to use supervised machine learning to explore patterns in reported adverse events involving cochlear implants.DesignThe MDRs for the top three CI manufacturers by volume from January 1st 2009 to August 30th 2019 were retained for the analysis. Natural language processing was used to measure the importance of specific words. Four supervised machine learning algorithms were used to predict which adverse event narrative description pattern corresponded with a specific cochlear implant manufacturer and adverse event type - injury, malfunction, or death.SettingU.S. government public database.ParticipantsAdult and pediatric cochlear patients.ExposureSurgical placement of a cochlear implant.Main Outcome MeasureMachine learning model classification prediction accuracy (% correct predictions).Results27,511 adverse events related to cochlear implant devices were submitted to the MAUDE database during the study period. Most adverse events involved patient injury (n = 16,736), followed by device malfunction (n = 10,760), and death (n = 16). Submissions to the database were dominated by Cochlear Corporation (n = 13,897), followed by MedEL (n = 7,125), and Advanced Bionics (n = 6,489). The random forest, linear SVC, naïve Bayes and logistic algorithms were able to predict the specific CI manufacturer based on the adverse event narrative with an average accuracy of 74.8%, 86.0%, 88.5% and 88.6%, respectively.Conclusions & RelevanceUsing supervised machine learning algorithms, our classification models were able to predict the CI manufacturer and event type with high accuracy based on patterns in adverse event text descriptions.Level of evidence3