bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mapping insecticide resistance in mosquitoes to aid malaria control
Authors: Moyes Catherine L. , Athinya Duncan Kobia , Seethaler Tara , Battle Katherine , Sinka Marianne , Hadi Melinda P. , Hemingway Janet , Coleman Michael , Hancock Penelope A. 
Published: April 2020

AbstractMalaria vector control may be compromised by resistance to insecticides in vector populations. Actions to mitigate against resistance rely on surveillance using standard susceptibility tests, but there are large gaps in the monitoring data. Using a published geostatistical ensemble model, we have generated maps that bridge these gaps and consider the likelihood that resistance exceeds recommended thresholds. Our results show that this model provides more accurate next-year predictions than two simpler approaches. We have used the model to generate district-level maps for the probability that pyrethroid resistance in Anopheles gambiae s.l. exceeds the World Health Organization (WHO) thresholds for susceptibility and confirmed resistance. In addition, we have mapped the three criteria for the deployment of piperonyl butoxide-treated nets that mitigate against the effects of metabolic resistance to pyrethroids. This includes a critical review of the evidence for presence of cytochrome P450-mediated metabolic resistance mechanisms across Africa. The maps for pyrethroid resistance are available on the IR Mapper website where they can be viewed alongside the latest survey data.Significance StatementMalaria control in Africa largely relies on the use of insecticides to prevent mosquitoes from transmitting the malaria parasite to humans, however, these mosquitoes have evolved resistance to these insecticides. To manage this threat to malaria control, it is vital that we map locations where the prevalence of resistance exceeds thresholds defined by insecticide resistance management plans. A geospatial model and data from Africa are used to predict locations where thresholds of resistance linked to specific recommended actions are exceeded. This model is shown to provide more accurate next-year predictions than two simpler approaches. The model is used to generate maps that aid insecticide resistance management planning and that allow targeted deployment of interventions that counter specific mechanisms of resistance.
Modeling risk of infectious diseases: a case of Coronavirus outbreak in four countries
Authors: Islam Md. Mazharul , Islam Md. Monirul , Hossain Md. Jamal , Ahmed Faroque 
Published: April 2020

AbstractBackgroundThe novel coronavirus (2019-nCOV) outbreak has been a serious concern around the globe. Since people are in tremor due to the massive spread of Coronavirus in the major parts of the world, it requires to predict the risk of this infectious disease. In this situation, we develop a model to measure the risk of infectious disease and predict the risk of 2019-nCOV transmission by using data of four countries—US, Australia, Canada and China.MethodsThe model underlies that higher the population density, higher the risk of transmission of infectious disease from human to human. Besides, population size, case identification rate and travel of infected passengers in different regions are also incorporated in this model.ResultsAccording to the calculated risk index, our study identifies New York State in United States (US) to be the most vulnerable area affected by the novel Coronavirus. Besides, other areas (province/state/territory) such as Hubei (China, 2nd), Massachusetts (US, 3rd), District of Columbia (US, 4th), New Jersey (US, 5th), Quebec (Canada, 20th), Australian Capital Territory (Australia, 29th) are also found as the most risky areas in US, China, Australia and Canada.ConclusionThe study suggests avoiding any kind of mass gathering, maintaining recommended physical distances and restricting inbound and outbound flights of highly risk prone areas for tackling 2019-nCOV transmission.
Patient-collected tongue, nasal, and mid-turbinate swabs for SARS-CoV-2 yield equivalent sensitivity to health care worker collected nasopharyngeal swabs
Authors: Tu YP , Jennings R , Hart B , Cangelosi GA , Wood RC , Wehber K , Verma P , Vojta D , Berke EM 
Published: April 2020

ABSTRACTBackgroundCurrent testing for SARS-CoV-2 requires health care workers to collect a nasopharyngeal (NP) sample from a patient. NP sampling requires the use of personal protective equipment that are in limited supply, is uncomfortable for the patient, and reduces clinical efficiency. This study explored the equivalency of patient-collected tongue, anterior nares (nasal), and mid-turbinate (MT) samples to health care worker-collected NP samples for detecting SARS-CoV-2.MethodsPatients presenting to five urgent care facilities with symptoms indicative of an upper respiratory infection provided self-collected samples from three anatomic sites along with a health care worker-collected NP sample. Using NP as the comparator, sensitivities and one-sided 95% confidence intervals for the tongue, nasal, and MT samples for detection of SARS-CoV-2 were calculated.ResultsThe sensitivity for detecting SARS-CoV-2 in patient-collected tongue, nasal, and mid-turbinate samples was 89.8% (95% CI: 80.2 -100.0), 94.0 (95% CI: 84.6-100.0) and 96.2 (95% CI: 87.7-100.0), respectively. Among samples yielding positive results, cycle threshold (Ct) values (a measure of viral load) had correlation coefficients of 0.48, 0.78, and 0.86 between the NP samples and the tongue, nasal, and MT samples, respectively.ConclusionsPatient-collected nasal and MT samples demonstrated high sensitivity for SARS-CoV-2 detection using health care worker-collected NP samples as the comparator. Among patients testing positive with NP samples, nasal and MT Ct values demonstrated high correlations with those Ct values of the NP samples. Patient-collected nasal or MT sampling may improve efficiency for COVID-19 testing while reducing the risk of exposure of the health workforce.
Estimation of the Final Size of the COVID-19 Epidemic in Pakistan
Authors: Syed F. , Sibgatullah S. 
Published: April 2020

AbstractThe COVID-19 infections in Pakistan are spreading at an exponential rate and a point may soon be reached where rigorous prevention measures would need to be adopted. Mathematical models can help define the scale of an epidemic and the rate at which an infection can spread in a community. We used an SIR model to predict the magnitude of the COVID-19 epidemic in Pakistan and compared the numbers with the reported cases on the national database. Our results indicate that Pakistan could hit peak number of infectious cases on May 26th, 2020 and by June 24th, 2020, 90% of the population will have become infected with the virus if policy interventions seeking to curb this infection are not adopted aggressively.
Predicting Whom to Test is More Important Than More Tests - Modeling the Impact of Testing on the Spread of COVID-19 Virus By True Positive Rate Estimation
Authors: Rodriguez Paul 
Published: April 2020

AbstractI estimate plausible true positive (TP) rates for the number of COVID-19 tests per day, most relevant when the number of test is on the same order of magnitude as number of infected persons. I then modify a standard SEIR model to model current growth patterns and detection rates in South Korea and New York state. Although reducing transmission rates have the largest impact, increasing TP rates by ∼10% in New York can have an impact equal to adding tens of thousands of new tests per day. Increasing both TP rates and tests per day together can have significant impacts and likely be more easily sustained than social distancing restrictions. Systematic and standardized data collection, even beyond contact tracking, should be ongoing and quickly made available for research teams to maximize the efficacy of testing.
Potent Antiviral Activities of Type I Interferons to SARS-CoV-2 Infection
Authors: Mantlo Emily , Bukreyeva Natalya , Maruyama Junki , Paessler Slobodan , Huang Cheng 
Published: April 2020

AbstractThe ongoing historic outbreak of COVID-19 not only constitutes a global public health crisis, but also carries a devastating social and economic impact. The disease is caused by a newly identified coronavirus, Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). There is an urgent need to identify antivirals to curtail the COVID-19 pandemic. Herein, we report the remarkable sensitivity of SARS-CoV-2 to recombinant human interferons α and β (IFNα/β). Treatment with IFN-α at a concentration of 50 international units (IU) per milliliter drastically reduces viral titers by 3.4 log or over 4 log, respectively, in Vero cells. The EC50of IFN-α and IFN-β treatment is 1.35 IU/ml and 0.76 IU/ml, respectively, in Vero cells. These results suggest that SARS-CoV-2 is more sensitive than many other human pathogenic viruses, including SARS-CoV. Overall, our results demonstrate the potent efficacy of human Type I IFN in suppressing SARS-CoV-2 infection, a finding which could inform future treatment options for COVID-19.
Reduction of lymphocyte at early stage elevates severity and death risk of COVID-19 patients: a hospital-based case-cohort study
Authors: Fei Jun , Fu Lin , Li Ying , Xiang Hui-Xian , Xiang Ying , Li Meng-Die , Liu Fang-Fang , Xu De-Xiang , Zhao Hui 
Published: April 2020

AbstractBackground and objectiveSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-induced coronavirus disease 2019 (COVID-19) has been pandemic worldwide. Several reports observed a reduction of lymphocytes among COVID-19 patients. However, clinical significance of lymphocyte reduction in COVID-19 patients remains unclear. The objective of this study was to analyze the association between lymphocyte reduction at early stage and the prognosis of COVID-19 patients.MethodsAll 192 hospitalized patients with COVID-19 were enrolled. Electronic medical records, including demographic data, clinical characteristics, comorbidities and exposure history, were collected. Biochemical indexes on admission and chest computed tomography (CT) were detected. Patient’s prognosis was followed up.ResultsOn admission, 84 (43.8%) patients suffered from lymphocyte reduction among COVID-19 patients. The count and percentage of lymphocytes on admission were lower among more than seventy-year-old patients than those of younger patients. Multivariate logistic regression revealed that older age was a risk factor of lymphocyte reduction. Of interest, chest CT score, a key marker of lung injury, was increased among COVID-19 patients with lymphocyte reduction. By contrast, PaCO2, SpO2 and oxygenation index, several respiratory function markers, were decreased in COVID-19 patients with lymphocyte reduction. Moreover, TBIL and DBIL, two markers of hepatic injury, creatinine and urea nitrogen, two indices of renal function, and creatine kinase, AST and LDH, three myocardial enzymes, were elevated in COVID-19 patients with lymphocyte reduction. Among 84 COVID-19 patients with lymphocyte reduction, 32.1% died. Fatality rate was obviously higher in COVID-19 patients with lymphocyte reduction than those with normal lymphocyte (RR=5.789, P<0.001).ConclusionOlder COVID-19 patients are more susceptible to lymphocyte reduction. Lymphocyte reduction at early stage aggravates the severity of multiple organ injuries and elevates death risk of COVID-19 patients.
A Model of Supply-Chain Decisions for Resource Sharing with an Application to Ventilator Allocation to Combat COVID-19
Authors: Mehrotra Sanjay , Rahimian Hamed , Barah Masoud , Luo Fengqiao , Schantz Karolina 
Published: April 2020

AbstractWe present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency is to be allocated. The entities (states) may share the critical resource with a different state under a risk-averse condition. The model is applied to study the allocation of ventilator inventory in the COVID-19 pandemic by FEMA to different US states. Findings suggest that if less than 60% of the ventilator inventory is available for non-COVID-19 patients, FEMA’s stockpile of 20,000 ventilators (as of 03/23/2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non-COVID-19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top-most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (till 05/31/20) is about 232,000 ventilator days, with a peak shortfall of 17,200 ventilators on 04/19/2020. Results are also reported for a worst-case where the demand is at the upper limit of the 95% confidence interval.
Predictions for COVID-19 Outbreak in India using epidemiological models
Authors: Ranjan Rajesh 
Published: April 2020

AbstractCOVID-19 data from India is compared against several countries as well as key states in the US with a major outbreak, and it is found that the basic reproduction number R0 for India is in the expected range of 1.4-3.9. Further, the rate of growth of infections in India is very close to that in Washington and California. Exponential and classic susceptible-infected-recovered (SIR) models based on available data are used to make short and long-term predictions on a daily basis. Based on the SIR model, it is estimated that India will enter equilibrium by the end of May 2020 with the final epidemic size of approximately 13,000. However, this estimation will be invalid if India enters the stage of community transmission. The impact of social distancing, again with the assumption of no community transmission, is also assessed by comparing data from different geographical locations.
A novel cohort analysis approach to determining the case fatality rate of COVID-19 and other infectious diseases
Authors: Narayanan Charit Samyak 
Published: April 2020

AbstractAs the Coronavirus contagion develops, it is increasingly important to understand the dynamics of the disease. Its severity is best described by two parameters: its ability to spread and its lethality. Here, we combine a mathematical model with a cohort analysis approach to determine the range of case fatality rates (CFR). We use a logistical function to describe the exponential growth and subsequent flattening of COVID-19 CFR that depends on three parameters: the final CFR (L), the CFR growth rate (k), and the onset-to-death interval (t0). Using the logistic model with specific parameters (L, k and t0), we calculate the number of deaths each day for each cohort. We build an objective function that minimizes the root mean square error between the actual and predicted values of cumulative deaths and run multiple simulations by altering the three parameters. Using all of these values, we find out which set of parameters returns the lowest error when compared to the number of actual deaths. We were able to predict the CFR much closer to reality at all stages of the viral outbreak compared to traditional methods. This model can be used far more effectively than current models to estimate the CFR during an outbreak, allowing for better planning. The model can also help us better understand the impact of individual interventions on the CFR. With much better data collection and labeling, we should be able to improve our predictive power even further.
Common Fronto-temporal Effective Connectivity in Humans and Monkeys
Authors: Rocchi Francesca , Oya Hiroyuki , Balezeau Fabien , Billig Alexander J. , Kocsis Zsuzsanna , Jenison Rick , Nourski Kirill V. , Kovach Christopher K. , Steinschneider Mitchell , Kikuchi Yukiko , Rhone Ariane E. , Dlouhy Brian J. , Kawasaki Hiroto , Adolphs Ralph , Greenlee Jeremy D.W. , Griffiths Timothy D. , Howard Matthew A. , Petkov Christopher I. 
Published: April 2020

ABSTRACTCognitive pathways supporting human language and declarative memory are thought to have uniquely evolutionarily differentiated in our species. However, cross-species comparisons are missing on site-specific effective connectivity between regions important for cognition. We harnessed a new approach using functional imaging to visualize the impact of direct electrical brain stimulation in human neurosurgery patients. Applying the same approach with macaque monkeys, we found remarkably comparable patterns of effective connectivity between auditory cortex and ventro-lateral prefrontal cortex (vlPFC) and parahippocampal cortex in both species. Moreover, in humans electrical tractography revealed rapid evoked potentials in vlPFC from stimulating auditory cortex and speech sounds drove vlPFC, consistent with prior evidence in monkeys of direct projections from auditory cortex to vocalization responsive regions in vlPFC. The results identify a common effective connectivity signature that from auditory cortex is equally direct to vlPFC and indirect to the hippocampus (via parahippocampal cortex) in human and nonhuman primates.HighlightsPrivileged human auditory to inferior frontal connectivity, linked to monkeysCommon auditory to parahippocampal effective connectivity in both speciesGreater lateralization in human effective connectivity, more symmetrical in monkeysHuman fronto-temporal network function rooted in evolutionarily conserved signatureeTOC short summaryFunctional connectivity between regions crucial for language and declarative memory is thought to have substantially differentiated in humans. Using a new technique to similarly visualize directional effective connectivity in humans and monkeys, we found remarkably comparable connectivity patterns in both species between fronto-temporal regions crucial for cognition.
Spike timing in the attention network predicts behavioral outcome prior to target selection
Authors: Fiebelkorn Ian C. , Kastner Sabine 
Published: April 2020

ABSTRACTThere has been little evidence linking changes in spiking activity that occur prior to a spatially predictable target (i.e., prior to target selection) to behavioral outcomes, despite such preparatory changes being widely assumed to enhance the sensitivity of sensory processing. We simultaneously recorded from frontal and parietal nodes of the attention network, while macaques performed a spatial-cueing task. When anticipating a spatially predictable target, different patterns of coupling between spike timing and oscillatory phase in local field potentials—but not changes in spike rate—were predictive of different behavioral outcomes. These behaviorally relevant differences in local and between-region synchronization occurred among specific cell types that were defined based on their sensory and motor properties, providing insight into the mechanisms underlying enhanced sensory processing prior to target selection. We propose that these changes in neural synchronization reflect differential, anticipatory engagement of the network nodes and functional units that shape attention-related sampling.
ERG orchestrates chromatin interactions to drive prostate cell fate reprogramming
Authors: Li Fei , Yuan Qiuyue , Di Wei , Xia Xinyi , Liu Zhuang , Mao Ninghui , Li Lin , Li Chunfeng , He Juan , Li Yunguang , Guo Wangxin , Zhang Xiaoyu , Zhu Yiqin , Aji Rebiguli , Wang Shangqian , Chi Ping , Carver Brett , Wang Yong , Chen Yu , Gao Dong 
Published: April 2020

AbstractWhile cancer is commonly perceived as a disease of dedifferentiation, the hallmark of early stage prostate cancer is paradoxically the loss of more plastic basal cells and the abnormal proliferation of more differentiated secretory luminal cells. However, the mechanism of prostate cancer pro-luminal differentiation is largely unknown. Through integrating analysis of the transcription factors (TFs) from 806 human prostate cancers, we have identified that ERG highly correlated with prostate cancer luminal subtyping. ERG overexpression in luminal epithelial cells inhibits its normal plasticity to transdifferentiate into basal lineage and ERG supersedes PTEN-loss which favors basal differentiation. ERG knock-out disrupted prostate cell luminal differentiation, whereas AR knock-out had no such effects. Trp63 is a known master regulator of prostate basal lineage. Through analysis of 3D chromatin architecture, we found that ERG binds and inhibits the enhancer activity and chromatin looping of a Trp63 distal enhancer, thereby silencing its gene expression. Specific deletion of the distal ERG binding site resulted in the loss of ERG-mediated inhibition of basal differentiation. Thus, ERG orchestrates chromatin interactions and regulates prostate cell lineage toward pro-luminal program, as its fundamental role on lineage differentiation in prostate cancer initiation.
Bats are key hosts in the radiation of mammal-associated Bartonella bacteria
Authors: McKee Clifton D. , Bai Ying , Webb Colleen T. , Kosoy Michael Y. 
Published: April 2020

AbstractBats are notorious reservoirs of several zoonotic diseases and may be uniquely tolerant of infection among mammals. Broad sampling has revealed the importance of bats in the diversification and spread of viruses and eukaryotes to other animal hosts. Vector-borne bacteria of the genus Bartonella are prevalent and diverse in mammals globally and recent surveys have revealed numerous Bartonella lineages in bats. We assembled a sequence database of Bartonella strains, consisting of nine genetic loci from 209 previously characterized lineages and 121 new cultured strains from bats, and used these data to perform the most comprehensive phylogenetic analysis of Bartonella to date. This analysis included estimation of divergence dates using a molecular clock and ancestral reconstruction of host associations and geography. We estimate that Bartonella began infecting mammals 62 million years ago near the Cretaceous-Paleogene boundary. Additionally, the radiation of particular Bartonella clades correlate strongly to the timing of diversification and biogeography of mammalian hosts. Bats were inferred to be the ancestral hosts of all mammal-associated Bartonella and appear to be responsible for the early geographic expansion of the genus. We conclude that bats have had a deep influence on the evolutionary radiation of Bartonella bacteria and their spread to other mammalian orders. These results support a ‘bat seeding’ hypothesis that could explain similar evolutionary patterns in other mammalian parasite taxa. Application of such phylogenetic tools as we have used to other taxa may reveal the general importance of bats in the ancient diversification of mammalian parasites.Significance statementDiscovering the evolutionary history of infectious agents in animals is important for understanding the process of host adaptation and the origins of human diseases. To clarify the evolution of the Bartonella genus, which contains important human pathogens, we performed phylogenetic analysis on a broad diversity of Bartonella strains, including novel strains from bats. Our results indicate that Bartonella clades diversified along with their mammal hosts over millions of years. Bats appear to be especially important in the early radiation and geographic dispersal of Bartonella lineages. These patterns are consistent with research indicating a chiropteran origin of important human viruses and eukaryotic parasites, suggesting that bats may play a unique role as historical sources of infections to other hosts.