bluuebunny/crossref_metadata_2025 huggingface dataset:
Nowcasting and Forecasting the Spread of COVID-19 and Healthcare Demand in Turkey, A Modelling Study
Authors: Arslan Şeyma , Özdemir Muhammed Yusuf , Uçar Abdullah
Published: April 2020

Background

This study aims to estimate the total number of infected people, evaluate the effects of NPIs on the healthcare system, and predict the expected number of cases, deaths, hospitalizations due to COVID-19 in Turkey.

Methods

This study was carried out according to three dimensions. In the first, the actual number of infected people was estimated. In the second, the expected total numbers of infected people, deaths, hospitalizations have been predicted in the case of no intervention. In the third, the distribution of the expected number of infected people and deaths, and ICU and non-ICU bed needs over time has been predicted via a SEIR-based simulator (TURKSAS) in four scenarios.

Results

According to the number of deaths, the estimated number of infected people in Turkey on March 21 was 123,030. In the case of no intervention the expected number of infected people is 72,091,595 and deaths is 445,956, the attack rate is 88 · 1%, and the mortality ratio is 0·54%. The ICU bed capacity in Turkey is expected to be exceeded by 4·4-fold and non-ICU bed capacity by 3·21-fold. In the second and third scenarios compliance with NPIs makes a difference of 94,303 expected deaths. In both scenarios, the predicted peak value of occupied ICU and non-ICU beds remains below Turkey’s capacity.

Discussion

Predictions show that around 16 million people can be prevented from being infected and 94,000 deaths can be prevented by full compliance with the measures taken. Modelling epidemics and establishing decision support systems is an important requirement.
Using ICU data to improve the real-time estimation of the effective reproductive number of the COVID-19 epidemic in 9 European countries
Authors: Hurtado Samuel , Tinajero David
Published: April 2020

1.

We replicate a recent study by the Imperial College COVID-19 Response Team (Flaxman et al, 2020) that estimates both the effective reproductive number, Rt, of the current COVID-19 epidemic in 11 European countries, and the impact of different nonpharmaceutical interventions that have been implemented to try to contain the epidemic, including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, widescale social distancing including local and national lockdowns. The main indicator they use for measuring the evolution of the epidemic is the daily number of deaths by COVID-19 in each country, which is a better statistic than the number of identified cases because it doesn’t depend so much on the testing strategy that is in place in each country at each moment in time.

We improve on their estimation by using data from the number of patients in intensive care, which provides two advantages over the number of deaths: first, it can be used to construct a signal with less bias: as the healthcare system of a country reaches saturation, the mortality rate would be expected to increase, which would bias the estimates of Rtand of the impact of measures implemented to contain the epidemic; and second, it is a signal with less lag, as the time from onset of symptoms to ICU admission is shorter than the time from onset to death (on average, 7.5 days shorter). The intensive care signal we use is not just the number of people in ICU, as this would also be biased if the healthcare system has reached saturation (in this case, biased downwards, as admissions are no longer possible when all units are in use). Instead, we estimate the daily demand of intensive care, as the sum of two components: the part that is satisfied (new ICU admissions) and the part that is not (which results in excess mortality).

Thanks to the advantages of this ICU signal in terms of timeliness and bias, we find that most of the countries in the study have already reached Rt<1 with 95% confidence (Italy, Spain, Austria, Denmark, France, Norway and Switzerland, but not Belgium or Sweden), whereas the original methodology of Flaxman et al (2020), even with updated data, would only find Rt<1 with 95% confidence for Italy and Switzerland.
Multi-chain Fudan-CCDC model for COVID-19 – a revisit to Singapore’s case
Authors: Pan Hanshuang , Shao Nian , Yan Yue , Luo Xinyue , Wang Shufen , Ye Ling , Cheng Jin , Chen Wenbin
Published: April 2020

Background

COVID-19 has been impacting on the whole world critically and constantly since late December 2019. Rapidly increasing infections has raised intense world-wide attention. How to model the evolution of COVID-19 effectively and efficiently is of great significance for prevention and control.

Methods

We propose the multi-chain Fudan-CCDC model based on the original single-chain model in [8] to describe the evolution of COVID-19 in Singapore. Multi-chains can be considered as the superposition of several single chains with different characteristics. We identify parameters of models by minimizing the penalty function.

Results

The numerical simulation results exhibit the multichain model performs well on data fitting. Though unsteady the increments are, they could still fall within the range of ±25% fluctuation from simulation results. It is predicted by multi-chain models that Singapore are experiencing a nonnegligible risk of explosive outbreak, thus stronger measures are urgently needed to contain the epidemic.

Conclusion

The multi-chain Fudan-CCDC model provides an effective way to early detect the appearance of imported infectors and super spreaders and forecast a second outbreak. It can also explain the data in those countries where the single-chain model shows deviation from the data.
Importance of untested infectious individuals for the suppression of COVID-19 epidemics
Authors: Pérez-Reche Francisco J. , Forbes Ken J. , Strachan Norval J. C.
Published: April 2020

The impact of the extent of testing infectious individuals on suppression of COVID-19 is illustrated from the early stages of outbreaks in Germany, the Hubei province of China, Italy, Spain and the UK. The predicted percentage of untested infected individuals depends on the specific outbreak but we found that they typically represent 50% to 80% of the infected individuals. Even when unreported cases are taken into account, we estimate that less than 8% of the population would have been exposed to SARS-CoV-2 by 09/04/2020 in the analysed outbreaks. These levels are far below the 70-85% needed to ensure herd immunity and would predict a resurgence of infection if ongoing lockdowns in the outbreaks are fully lifted. We propose that partially lifted lockdowns together with early and thorough testing allowing for quick isolation of both symptomatic and asymptomatic cases could lead to suppression of secondary waves of COVID-19 epidemics.
The Prediction for the Outbreak of COVID-19 for 15 States in USA by Using Turning Phase Concepts as of April 10, 2020
Authors: Yuan George Xianzhi , Di Lan , Gu Yudi , Qian Guoqi , Qian Xiaosong
Published: April 2020

Based on a new concept called “Turning Period”, the goal of this report is to show how we can conduct the prediction for the outlook in the different stages for the battle with outbreak of COVID-19 currently in US, in particular, to identify when each of top 15 states in USA (basically on their populations) is going to enter into the stage that the outbreak of COVID-19 is under the control by the criteria such as daily change of new patients is less than 10% smoothly. Indeed, based on the data of April 10, 2020 with the numerical analysis, we are able to classify 15 states of US into the following four different categories for the Prevention and Control of Infectious Diseases Today and the main conclusion are:

First, staring around April 14, 20202, three states which are Washington State, Louisiana and Indiana are entering the stage that the outbreak of COVID-19 is under the control, which means daily change of new patients is less than 10% and the gamma is less than zero in general.

Second, staring aroundApril15, 20202, two states which are New Jersey, and New York are entering the stage that the outbreak of COVID-19 is under the control, which means daily change of new patients is less than 10% and the gamma is less than zero in general.

Third, staring aroundApril16, 20202, seven states which are California, Florida, Georgia (GA), Illinois, Maryland, Indiana, Michigan, and Pennsylvania are entering the stage that the outbreak of COVID-19 is under the control, which means daily change of new patients is less than 10% and the gamma is less than zero in general.

Fourth, staring aroundApril17, 20202, three states which are Texas, Massachusetts, and Connecticut are entering the stage that the outbreak of COVID-19 is under the control, which means daily change of new patients is less than 10% and the gamma is less than zero in general.

Finally, we want to reinforce that emergency risk management is always associated with the implementation of an emergency plan. The identification of the Turning Time Period is key to emergency planning as it provides a timeline for effective actions and solutions to combat a pandemic by reducing as much unexpected risk as soon as possible.
Text Classification Models for the Automatic Detection of Nonmedical Prescription Medication Use from Social Media
Authors: Mohammed Ali Al-Garadi , Yang Yuan-Chi , Cai Haitao , Ruan Yucheng , O’Connor Karen , Graciela Gonzalez-Hernandez , Perrone Jeanmarie , Sarker Abeed
Published: April 2020

Prescription medication (PM) misuse/abuse has emerged as a national crisis in the United States, and social media has been suggested as a potential resource for performing active monitoring. However, automating a social media-based monitoring system is challenging—requiring advanced natural language processing (NLP) and machine learning methods. In this paper, we describe the development and evaluation of automatic text classification models for detecting self-reports of PM abuse from Twitter. We experimented with state-of-the-art bi-directional transformer-based language models, which utilize tweet-level representations that enable transfer learning (e.g., BERT, RoBERTa, XLNet, AlBERT, and DistilBERT), proposed fusion-based approaches, and compared the developed models with several traditional machine learning, including deep learning, approaches. Using a public dataset, we evaluated the performances of the classifiers on their abilities to classify the non-majority “abuse/misuse” class. Our proposed fusion-based model performs significantly better than the best traditional model (F1-score [95% CI]: 0.67 [0.64-0.69] vs. 0.45 [0.42-0.48]). We illustrate, via experimentation using differing training set sizes, that the transformer-based models are more stable and require less annotated data compared to the other models. The significant improvements achieved by our best-performing classification model over past approaches makes it suitable for automated continuous monitoring of nonmedical PM use from Twitter.
Partial unlock for COVID-19-like epidemics can save 1-3 million lives worldwide
Authors: Shuler Robert L. , Koukouvitis Theodore , Suematsu Dyske
Published: April 2020

Background

A large percentage of deaths in an epidemic or pandemic can be due to overshoot of population (herd) immunity, either from the initial peak or from planned or unplanned exit from lockdown or social distancing conditions.

Objectives

We study partial unlock or reopening interaction with seasonal effects in a managed epidemic to quantify overshoot effects on small and large unlock steps and discover robust strategies for reducing overshoot.

Methods

We simulate partial unlock of social distancing for epidemics over a range of replication factor, immunity duration and seasonality factor for strategies targeting immunity thresholds using overshoot optimization.

Results

Seasonality change must be taken into account as one of the steps in an easing sequence, and a two step unlock, including seasonal effects, minimizes overshoot and deaths. It may cause undershoot, which causes rebounds and assists survival of the pathogen.

Conclusions

Partial easing levels, even low levels for economic relief while waiting on a vaccine, have population immunity thresholds based on the reduced replication rates and may experience overshoot as well. We further find a two step strategy remains highly sensitive to variations in case ratio, replication factor, seasonality and timing. We demonstrate a three or more step strategy is more robust, and conclude that the best possible approach minimizes deaths under a range of likely actual conditions which include public response.
A blueprint for the implementation of a validated approach for the detection of SARS-Cov2 in clinical samples in academic facilities
Authors: Sridhar Sushmita , Forrest Sally , Kean Iain , Young Jamie , Scott Josefin Bartholdson , Maes Mailis , Pereira-Dias Joana , Parmar Surendra , Routledge Matthew , Rivett Lucy , Dougan Gordon , Weekes Michael , Curran Martin , Goodfellow Ian , Baker Stephen
Published: April 2020

The COVID-19 pandemic is expanding at an unprecedented rate. As a result, diagnostic services are stretched to their limit, and there is a clear need for the provision of additional diagnostic capacity. Academic laboratories, many of which are closed due to governmental lockdowns, may be in a position to support local screening capacity by adapting their current laboratory practices. Here, we describe the process of developing a SARS-Cov2 diagnostic workflow in a conventional academic Containment Level 2 (CL2) laboratory. Our outline includes simple SARS-Cov2 deactivation upon contact, the methods for a quantitative real-time reverse transcriptase PCR (qRT-PCR) detecting SARS-Cov2, a description of process establishment and validation, and some considerations for establishing a similar workflow elsewhere. This was achieved under challenging circumstances through the collaborative efforts of scientists, clinical staff, and diagnostic staff to mitigate to the ongoing crisis. Within 14 days, we created a validated COVID-19 diagnostics service for healthcare workers in our local hospital. The described methods are not exhaustive, but we hope may offer support to other academic groups aiming to set up something comparable in a short time frame.
Chloroquine Kills Hair Cells in Zebrafish Lateral Line and Murine Cochlear Cultures: Implications for Ototoxicity
Authors: Davis Samantha N. , Wu Patricia , Camci Esra D. , Simon Julian A. , Rubel Edwin W , Raible David W.
Published: April 2020

Hearing and balance deficits have been reported during and following treatment with the antimalarial drug chloroquine. However, experimental work examining the direct actions of chloroquine on mechanoreceptive hair cells in common experimental models is lacking. This study examines the effects of chloroquine on hair cells using two common experimental models: the zebrafish lateral line and neonatal mouse cochlear cultures. Zebrafish larvae were exposed to varying concentrations of chloroquine phosphate or hydroxychloroquine for 1 hr or 24 hr, and hair cells assessed by antibody staining. A significant, dose-dependent reduction in the number of surviving hair cells was seen across conditions for both exposure periods. Hydroxycholroquine showed similar toxicity. In mouse cochlear cultures, chloroquine damage was specific to outer hair cells in tissue from the cochlear basal turn, consistent with susceptibility to other ototoxic agents. These findings suggest a need for future studies employing hearing and balance monitoring during exposure to chloroquine and related compounds, particularly with interest in these compounds as therapeutics against viral infections including coronavirus.
Molecular Assays of Pollen Use Consistently Reflect Pollinator Visitation Patterns in a System of Flowering Plants
Authors: James Aubrie R. M. , Geber Monica A. , Toews David P. L.
Published: April 2020

Determining how pollinators visit plants versus how they carry and transfer pollen is an ongoing project in pollination ecology. The differences between how pollinators visit flowers versus how they carry pollen can be appreciable, but the current tools for identifying the pollens that bees carry have different strengths and weaknesses when used for ecological inference. In this study we use three methods to better understand a system of congeneric, co-flowering plants in the genusClarkiaand their bee pollinators: observations of plant-pollinator contact in the field, and two different molecular methods to estimate the relative abundance of eachClarkiapollen in samples collected from pollinators. We use these methods to investigate if observations of plant-pollinator contact in the field correspond to the pollen bees carry; if individual bees carryClarkiapollens in predictable ways, based on previous knowledge of their foraging behaviors; and how the three approaches differ for understanding plant-pollinator interactions. We find that observations of plant-pollinator contact are generally predictive of the pollens that bees carry while foraging, and network topologies using the three different methods are statistically indistinguishable from each other. Results from molecular pollen analysis also show that while bees can carry multiple species ofClarkiaat the same time, they often carry one species of pollen. Our work contributes to the growing body of literature aimed at resolving how pollinators use floral resources. We suggest our novel relative amplicon quantification method as another tool in the developing molecular ecology and pollination biology toolbox.
Carbon Sequestration Potential of Oil Palm Plantations in Southern Philippines
Authors: Borbon Sheila Mae C. , Medina Michael Arieh P. , Patricio Jose Hermis P. , Toledo-Bruno Angela Grace
Published: April 2020

Aside from the greenhouse gas reduction ability of palm oil-based biofuel as alternative to fossil fuels, another essential greenhouse gas mitigation ability of oil palm plantation is in terms of offsetting anthropogenic carbon emissions through carbon sequestration. In this context, this study was done to determine the carbon sequestration potential of oil palm plantations specifically in two areas in Mindanao, Philippines. Allometric equation was used in calculating the biomass of oil palm trunk. Furthermore, destructive methods were used to determine the biomass in other oil palm parts (fronds, leaves, and fruits). Carbon stocks from the other carbon pools in the oil palm plantations were measured which includes understory, litterfall, and soil. Results revealed that the average carbon stock in the oil palm plantations is 40.33 tC/ha. Majority of the carbon stock is found in the oil palm plant (53%), followed by soil (38%), litterfall (6%), and understory, (4%). The average carbon sequestration rate of oil palm plants is estimated to be 4.55 tC/ha/year. It is advised that oil palm expansions should be done on grasslands and barren lands instead of forest lands to avoid incurring “carbon debts”. It is also recommended that oil palms should be mixed with shrub crops species to enhance soil organic carbon as well as increase the aboveground biomass in oil palm plantations.
Spatiotemporal functional interactivity among large-scale brain networks
Authors: Xu Nan , Doerschuk Peter C. , Keilholz Shella D. , Spreng R. Nathan
Published: April 2020

The macro-scale intrinsic functional network architecture of the human brain has been well characterized. Early studies revealed robust and enduring patterns of static connectivity, while more recent work has begun to explore the temporal dynamics of these large-scale brain networks. Little work to date has investigated directed connectivity within and between these networks, or the temporal patterns of afferent (input) and efferent (output) connections between network nodes. Leveraging a novel analytic approach, prediction correlation, we investigated the causal interactions within and between large-scale networks of the brain using resting-state fMRI. This technique allows us to characterize information transfer between brain regions in both the spatial (direction) and temporal (duration) scales. Using data from the Human Connectome Project (N=200) we applied prediction correlation techniques to four resting state fMRI runs (total TRs = 4800). Three central observations emerged. First, the strongest and longest duration connections were observed within the somatomotor, visual and dorsal attention networks. Second, the short duration connections were observed for high-degree nodes in the visual and default networks, as well as in hippocampus. Specifically, the connectivity profile of the highest-degree nodes was dominated by efferent connections to multiple cortical areas. Moderate high-degree nodes, particularly in hippocampal regions, showed an afferent connectivity profile. Finally, multimodal association nodes in lateral prefrontal brain regions demonstrated a short duration, bidirectional connectivity profile, consistent with this region’s role in integrative and modulatory processing. These results provide novel insights into the spatiotemporal dynamics of human brain function.
Distinct early IgA profile may determine severity of COVID-19 symptoms: an immunological case series
Authors: Dahlke Christine , Heidepriem Jasmin , Kobbe Robin , Santer René , Koch Till , Fathi Anahita , Ly My L. , Schmiedel Stefan , Seeberger Peter H. ,   ID-UKE COVID-19 study group, Addo Marylyn M. , Loeffler Felix F.
Published: April 2020

SARS-CoV-2 is the causative agent of COVID-19 and is a severe threat to global health. Patients infected with SARS-CoV-2 show a wide range of symptoms and disease severity, while limited data is available on its immunogenicity.

Here, the kinetics of the development of SARS-CoV-2-specific antibody responses in relation to clinical features and dynamics of specific B-cell populations are reported. Immunophenotyping of B cells was performed by flow cytometry with longitudinally collected PBMCs. In parallel, serum samples were analyzed for the presence of SARS-CoV-2-specific IgA, IgG, and IgM antibodies using whole proteome peptide microarrays. Soon after disease onset in a mild case, we observed an increased frequency of plasmablasts concomitantly with a strong SARS-CoV-2-specific IgA response. In contrast, a case with more severe progression showed a delayed, but eventually very strong and broad SARS-CoV-2-specific IgA response.

This case study shows that determining SARS-CoV-2-specific antibody epitopes can be valuable to monitor the specificity and magnitude of the early B-cell response, which could guide the development of vaccine candidates. Follow-up studies are required to evaluate whether the kinetics and strength of the SARS-CoV-2-specific IgA response could be potential prognostic markers of viral control.
COVID-19 Antibody Seroprevalence in Santa Clara County, California
Authors: Bendavid Eran , Mulaney Bianca , Sood Neeraj , Shah Soleil , Ling Emilia , Bromley-Dulfano Rebecca , Lai Cara , Weissberg Zoe , Saavedra-Walker Rodrigo , Tedrow Jim , Tversky Dona , Bogan Andrew , Kupiec Thomas , Eichner Daniel , Gupta Ribhav , Ioannidis John P.A. , Bhattacharya Jay
Published: April 2020

Background

Addressing COVID-19 is a pressing health and social concern. To date, many epidemic projections and policies addressing COVID-19 have been designed without seroprevalence data to inform epidemic parameters. We measured the seroprevalence of antibodies to SARS-CoV-2 in a community sample drawn from Santa Clara County.

Methods

On April 3-4, 2020, we tested county residents for antibodies to SARS-CoV-2 using a lateral flow immunoassay. Participants were recruited using Facebook ads targeting a sample of individuals living within the county by demographic and geographic characteristics. We estimate weights to adjust our sample to match the zip code, sex, and race/ethnicity distribution within the county. We report both the weighted and unweighted prevalence of antibodies to SARS-CoV-2. We also adjust for test performance characteristics by combining data from 16 independent samples obtained from manufacturer’s data, regulatory submissions, and independent evaluations: 13 samples for specificity (3,324 specimens) and 3 samples for sensitivity (157 specimens).

Results

The raw prevalence of antibodies to SARS-CoV-2 in our sample was 1.5% (exact binomial 95CI 1.1-2.0%). Test performance specificity in our data was 99.5% (95CI 99.2-99.7%) and sensitivity was 82.8% (95CI 76.0-88.4%). The unweighted prevalence adjusted for test performance characteristics was 1.2% (95CI 0.7-1.8%). After weighting for population demographics of Santa Clara County, the prevalence was 2.8% (95CI 1.3-4.7%), using bootstrap to estimate confidence bounds. These prevalence point estimates imply that 54,000 (95CI 25,000 to 91,000 using weighted prevalence; 23,000 with 95CI 14,000-35,000 using unweighted prevalence) people were infected in Santa Clara County by early April, many more than the approximately 1,000 confirmed cases at the time of the survey.

Conclusions

The estimated population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection may be much more widespread than indicated by the number of confirmed cases. More studies are needed to improve precision of prevalence estimates. Locally-derived population prevalence estimates should be used to calibrate epidemic and mortality projections.
Is the fit of N95 facial masks effected by disinfection? A study of heat and
UV disinfection methods using the OSHA protocol fit test
Authors: Price Amy , Cui Yi , Liao Lei , Xiao Wang , Yu Xuanze , Wang Haotian , Zhao Mervin , Wang Qiqi , Chu Steven , Chu Larry
Published: April 2020

The current COVID-19 pandemic has highlighted global supply chain
shortcomings in the US hospital delivery system, most notably personal
protective equipment (PPE) and COVID-19 is found on these masks ∼7 days. Recent
work from our group has shown two promising disinfection methods for N95 facial
masks, dry heat (hot air (75 °C, 30 min) and UVGI which is UVGI 254 nm, 8W, 30
min. Using N95 five models of N95 masks from three different manufacturers we
determined the following: 1) Hot air treated N95 masks applied over 5 cycles did
not degrade the fit of masks (1.5% change in fit factor, p = .67), 2) UVGI
treated N95 masks applied over 10 cycles were significantly degraded in fit and
did not pass quantitative fit testing using OSHA testing protocols on a human
model (−77.4% change in fit factor, p = .0002).

NOTE

We would like to share our results with the community as
soon as possible. Be mindful that this report is a pilot study and a
work in progress. We will have more results in the coming days and
weeks.

We recommend that hospital
policy and
procedures be respected
and adhered to. Do not use anything in your home to disinfect contaminated
equipment. Please do not heat your masks in a home oven!
Egg cannibalism by passion vine specialistDisonychaChevrolat beetles (Coleoptera: Chrysomelidae: Galerucinae: Alticini)
Authors: Morrison Colin R. , Armstrong Wyatt , Gilbert Lawrence
Published: April 2020

Cannibalistic behavior is now recognized to be an important component of nutritional ecology in both carnivorous and herbivorous species, including many beetle families (Englert and Thomas 1970; Beaver 1974; Dickinson 1992; Bartlett 1987; Alabiet al.2008). This habit was historically viewed by an incidental outcome of unnaturally crowded laboratory situations with little ecological importance (Fox 1975), but it is increasingly acknowledged that cannibalism represents a potentially advantageous behavior (Richardsonet al.2010). Here we report on multiple cases of egg cannibalism, or conspecific oophagy, by adults of two species of passion vine (PassifloraLinnaeus: Passifloraceae) specialist flea beetles in the genusDisonychaChevrolat (Coleoptera: Chrysomelidae: Galerucinae: Alticini). This is the first report of egg cannibalism from the Galerucinae, and to our knowledge, only the fourth report of egg cannibalism by adults in the Chrysomelidae; the other three reports are of adult Chrysomelinae species eating conspecific eggs (Dickinson 1992; McCauley 1992; Schrodet al.1996). We conclude this note with several questions raised by our observations, followed by a discussion that may contribute to explanations of this behavior.
Performance Evaluation of Markerless 3D Skeleton Pose Estimates with Pop Dance Motion Sequence
Authors: Labuguen Rollyn T. , Ingco Wally Enrico M. , Negrete Salvador Blanco , Kogami Tonan , Shibata Tomohiro
Published: April 2020

The evaluation of markerless pose estimation performed by OpenPose has been getting much attention from researchers of human movement studies. This work aims to evaluate and compare the output joint positions estimated by the OpenPose with a marker-based motion-capture data recorded on a pop dance motion. Although the marker-based motion capture can accurately measure and record the human joint positions, this particular set-up is expensive. The framework to compare the outputs of the markerless method to the ground truth marker-based joint remains unknown, especially for complex body motion. Synchronization, camera calibration, and 3D reconstruction by fusing the outputs of the markerless method (OpenPose) are discussed. In this case study, the comparison results illustrate that even if the markerless method expects to fail when the subject’s body parts are self-occluded, the average magnitude errors for each key points are less than 700 mm.
Blood RNA Profiles are Diagnostic for Severity in Human Acute Spinal Cord Injury
Authors: Kyritsis Nikos , Espin Abel Torres , Schupp Patrick G. , Huie J. Russell , Chou Austin , Duong-Fernandez Xuan , Thomas Leigh H. , Tsolinas Rachel E. , Hemmerle Debra D. , Pascual Lisa U. , Singh Vineeta , Pan Jonathan Z. , Talbott Jason F. , Whetstone William D. , Burke John F. , DiGiorgio Anthony M. , Weinstein Philip R. , Manley Geoffrey T. , Dhall Sanjay S. , Ferguson Adam R. , Oldham Michael C. , Bresnahan Jacqueline C. , Beattie Michael S.
Published: April 2020

Biomarkers of spinal cord injury (SCI) could help determine the severity of the injury and facilitate early critical care decision making. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared to healthy and trauma controls and in direct relation to SCI severity. Unsupervised co-expression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity.
Exome sequencing identifies ARID2 as a novel tumor suppressor in early-onset sporadic rectal cancer
Authors: Bala Pratyusha , Singh Anurag Kumar , Kavadipula Padmavathi , Kotapalli Viswakalyan , Sabarinathan Radhakrishnan , Bashyam Murali Dharan
Published: April 2020

Early-onset sporadic rectal cancer (EOSRC) is a unique and predominant colorectal cancer (CRC) subtype in India. In order to understand the tumorigenic process in EOSRC, we performed whole exome sequencing of 47 microsatellite stable EOSRC samples. Signature 1 was the predominant mutational signature in EOSRC, as previously shown in other CRC exome studies. More importantly, we identifiedTP53, KRAS, APC, PIK3R1andSMAD4as significantly mutated (q<0.1) andARID1AandARID2as near-significantly mutated (restricted hypothesis testing; q<0.1) candidate drivers. Unlike the other candidates, the tumorigenic potential ofARID2, encoding a component of the SWI/SNF chromatin remodeling complex, is largely unexplored in CRC. shRNA mediatedARID2knockdown performed in two different CRC cell lines resulted in significant alterations in transcript levels of cancer-related target genes. More importantly,ARID2knockdown promoted several tumorigenic features including cell viability, proliferation, ability to override contact inhibition of growth, and migration besides significantly increasing tumor formation ability in nude mice. The observed gain in tumorigenic features were rescued upon ectopic expression ofARID2. Analyses of the TCGA CRC dataset revealed poorer survival in patients withARID2alterations. We therefore proposeARID2as a novel tumor suppressor in CRC.
Deciphering cellular transcriptional alterations in Alzheimer’s disease brains
Authors: Wang Xue , Allen Mariet , Li Shaoyu , Quicksall Zachary S. , Patel Tulsi A. , Carnwath Troy P. , Reddy Joseph S. , Carrasquillo Minerva M. , Lincoln Sarah J. , Nguyen Thuy T. , Malphrus Kimberly G. , Dickson Dennis W. , Crook Julia E. , Asmann Yan W. , Ertekin-Taner Nilüfer
Published: April 2020

Large-scale brain bulk-RNAseq studies identified molecular pathways implicated in Alzheimer’s disease (AD), however these findings can be confounded by cellular composition changes in bulk-tissue. To identify cell intrinsic gene expression alterations of individual cell types, we designed a bioinformatics pipeline and analyzed three AD and control bulk-RNAseq datasets of temporal and dorsolateral prefrontal cortex from 685 brain samples. We detected cell-proportion changes in AD brains that are robustly replicable across the three independently assessed cohorts. We applied three different algorithms including our in-house algorithm to identify cell intrinsic differentially expressed genes in individual cell types (CI-DEGs). We assessed the performance of all algorithms by comparison to single nucleus RNAseq data. We identified consensus CI-DEGs that are common to multiple brain regions. Despite significant overlap between consensus CI-DEGs and bulk-DEGs, many CI-DEGs were absent from bulk-DEGs. Consensus CI-DEGs and their enriched GO terms include genes and pathways previously implicated in AD or neurodegeneration, as well as novel ones. We demonstrated that the detection of CI-DEGs through computational deconvolution methods is promising and highlight remaining challenges. These findings provide novel insights into cell-intrinsic transcriptional changes of individual cell types in AD and may refine discovery and modeling of molecular targets that drive this complex disease.
Cholinergic modulation of membrane properties of calyx terminals in the vestibular periphery
Authors: Ramakrishna Yugandhar , Manca Marco , Sadeghi Soroush G.
Published: April 2020

Vestibular nerve afferents are divided into regular and irregular groups based on the variability of interspike intervals in their resting discharge. Most afferents receive inputs from bouton terminals that contact type II hair cells as well as from calyx terminals that cover the basolateral walls of type I hair cells. Calyces have an abundance of different subtypes of KCNQ (Kv7) potassium channels and muscarinic acetylcholine receptors (mAChRs) and receive cholinergic efferent inputs from neurons in the brainstem. We investigated whether mAChRs affected membrane properties and firing patterns of calyx terminals through modulation of KCNQ channel activity. Patch clamp recordings were performed from calyx terminals in central regions of the cristae of the horizontal and anterior canals in 13 – 18 day old Sprague-Dawley rats. KCNQ mediated currents were observed as voltage sensitive currents with slow kinetics (activation and deactivation), resulting in spike frequency adaptation so that calyces at best fired a single action potential at the beginning of a depolarizing step. Activation of mAChRs by application of oxotremorine methiodide or inhibition of KCNQ channels by linopirdine dihydrochloride decreased voltage activated currents by ∼30%, decreased first spike latencies by ∼40%, decreased spike thresholds by ∼50%, and resulted in continuous firing during depolarizing steps. Interestingly, some of the calyces showed spontaneous discharge in the presence of these drugs. Together, these findings suggest that cholinergic efferents can modulate the response properties and encoding of head movements by afferents.
Invasion of homogeneous and polyploid populations in nutrient-limiting environments
Authors: Kimmel Gregory J. , Dane Mark , Heiser Laura , Altrock Philipp M. , Andor Noemi
Published: April 2020

Breast cancer progresses in a multistep process from primary tumor growth and stroma invasion to metastasis. Progression is accompanied by a switch to an invasive cell phenotype. Nutrient-limiting environments promote chemotaxis with aggressive morphologies characteristic of invasion. It is unknown how co-existing cells differ in their response to nutrient limitations and how this impacts invasion of the metapopulation as a whole. We integrate mathematical modeling with microenvironmental perturbation-data to investigate invasion in nutrient-limiting environments inhabited by one or two cancer cell subpopulations. Hereby, subpopulations are defined by their energy efficiency and chemotactic ability. We estimate the invasion-distance traveled by a homogeneous population. For heterogeneous populations, our results suggest that an imbalance between nutrient efficacy and chemotactic superiority accelerates invasion. Such imbalance will spatially segregate the two populations and only one type will dominate at the invasion front. Only if these two phenotypes are balanced do the two subpopulations compete for the same space, which decelerates invasion. We investigate ploidy as a candidate biomarker of this phenotypic heterogeneity to discern circumstances when inhibiting chemotaxis amplifies internal competition and decelerates tumor progression, from circumstances that render clinical consequences of chemotactic inhibition unfavorable.

Significance

A better understanding of the nature of the double-edged sword of high ploidy is a prerequisite to personalize combination-therapies with cytotoxic drugs and inhibitors of signal transduction pathways such as MTOR-Is.
A facile method of mapping HIV-1 neutralizing epitopes using chemically masked cysteines and deep sequencing
Authors: Datta Rohini , Chowdhury Rohan Roy , Manjunath Kavyashree , Hanna Luke Elizabeth , Varadarajan Raghavan
Published: April 2020

Identification of specific epitopes targeted by neutralizing antibodies is essential to advance epitope-based vaccine design strategies. We report a facile methodology for rapid epitope mapping of neutralizing antibodies (NAbs) against HIV-1 Envelope (Env) at single residue resolution, using Cys labeling, viral neutralization assays and deep sequencing. This was achieved by the generation of a library of Cys mutations in Env glycoprotein on the viral surface, covalent labeling of the Cys residues using a Cys reactive label that masks epitope residues, followed by infection of the labeled mutant virions in mammalian cells in the presence of NAbs. Env gene sequencing from NAb-resistant viruses was used to accurately delineate epitopes for the NAbs VRC01, PGT128 and PGT151. These agreed well with corresponding experimentally determined structural epitopes previously inferred from NAb:Env structures. HIV-1 infection is associated with complex and polyclonal antibody responses, typically composed of multiple antibody specificities. Deconvoluting the epitope specificities in a polyclonal response is a challenging task. We therefore extended our methodology to map multiple specificities of epitopes targeted in polyclonal sera, elicited in immunized animals as well as in an HIV-1 infected elite neutralizer capable of neutralizing Tier-3 pseudoviruses with high titers. The method can be readily extended to other viruses for which convenient reverse genetics or lentiviral surface display systems are available.
Asian wild apples threatened by gene flow from domesticated apples and by their pestified pathogen
Authors: Feurtey Alice , Guitton Ellen , De Gracia Coquerel Marie , Duvaux Ludovic , Shiller Jason , Bellanger Marie-Noëlle , Expert Pascale , Sannier Mélanie , Caffier Valérie , Giraud Tatiana , Cam Bruno Le , Lemaire Christophe
Published: April 2020

Massive gene flow between crops and their wild relatives may threaten the genetic integrity of wild species. Such threats are now well documented, but little is known about indirect consequences involving the spillover of crop pathogens to wild plants or introgression between crop and wild pathogens. To address these questions, we used population genetics approaches, demographic inference and pathogenicity tests on host-pathogen pairs composed of wild or domesticated apple trees of Central Asia and their fungal pathogen,Venturia inaequalis, itself showing differentiated agricultural-type and wild-type populations. We confirmed the occurrence of gene flow from cultivated to wild apple trees in Asian forests, threatening the Asian wild apple genetic integrity. SNP markers and demographic modeling revealed the occurrence of a secondary contact followed by hybridization between agricultural-type and wild-type fungal pathogen populations, and the dispersal of the agricultural-type pathogen in wild forests. We detected a SNP predicting the ability of the fungus to parasitize the different host populations, which induced an early stop codon in a gene coding for a small secreted protein in the agricultural-type fungal population, thus representing a putative avirulence gene which function loss would enable to parasitize cultivated apples. Pathogenicity tests in fact revealed the pestification ofV. inaequalis, with higher virulence of the agricultural-type population on both wild and domesticated trees. Our findings highlight the threat posed by cultivating a crop near its center of origin, with the invasion of a pestified pathogen on wild plants and introgression in the wild-type pathogen.
Forest production efficiency increases with growth temperature
Authors: Collalti A. , Ibrom A. , Stockmarr A. , Cescatti A. , Alkama R. , Fernández-Martínez M. , Matteucci G. , Sitch S. , Friedlingstein P. , Ciais P. , Goll D.S. , Nabel J.E.M.S. , Pongratz J. , Arneth A. , Haverd V. , Prentice I.C.
Published: April 2020

Introductory paragraph

We present a global analysis of the relationship of forest production efficiency (FPE) to stand age and climate, based on a large compilation of data on gross primary production and either biomass production or net primary production. FPE is important for both forest production and atmospheric carbon dioxide uptake. Earlier findings – FPE declining with age – are supported by this analysis. However, FPE also increases with absolute latitude, precipitation and (all else equal) with temperature. The temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature. It implies top-down regulation of forest carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate.
Cancer SIGVAR: A semi-automated interpretation tool for germline variants of hereditary cancer-related genes
Authors: Li Hong , Liu Shuixia , Wang Shuangying , Zeng Quanlei , Chen Yulan , Fang Ting , Zhang Yi , Zhou Ying , Zhang Yu , Wang Kaiyue , Yan Zhangwei , Qiang Cuicui , Xu Meng , Chai Xianghua , Yuan Yuying , Huang Ming , Zhang Hongyun , Xiong Yun
Published: April 2020

The American College of Medical Genetics and Genomics and the Association for Molecular Pathology published guidelines in 2015 for the clinical interpretation of Mendelian disorder sequence variants based on 28 criteria. ClinGen Sequence Variant Interpretation (SVI) Working Groups have developed many adaptations or refinements of these guidelines to improve the consistency of interpretation. We combined the most recent adaptations to expand the criteria from 28 to 48 and developed a tool called Cancer SIGVAR to help healthcare workers and genetic counselors interpret the clinical significance of cancer germline variants, which is critical for the clinical diagnosis and treatment of hereditary cancer. Our tool can accept VCF files as input and realize fully automated interpretation based on 21 criteria and semi-automated interpretation based on 48 criteria. We validated our tool on the ClinVar and CLINVITAE benchmark databases for the accuracy of fully automated interpretation, achieving an average consistency for pathogenic and benign assessment up to 93.40% and 82.54%, respectively. We compared Cancer SIGVAR with a similar tool, InterVar, and analyzed the main differences in criteria and implementation. In addition, to verify the performance of semi-automated interpretation based on 48 criteria, we selected 911 variants from two benchmark databases and reached an average classification consistency of 98.35%. Our findings highlight the need to optimize automated interpretation tools based on constantly updated guidelines.
Identification of a Novel Picorna-like Virus in Coconut Rhinoceros Beetles (Oryctes rhinoceros)
Authors: Etebari Kayvan , Shelomi Matan , Furlong Michael J.
Published: April 2020

A novel Picorna-like virus, tentatively named Oryctes rhinoceros Picorna-like virus 1 (OrPV1), was identified in coconut rhinoceros beetle (Oryctes rhinoceros) larvae in Taiwan. The complete genome sequence consisted of 9,665 nucleotides with a polyA tail and included one open reading frame. Conserved structural domains such as Picornavirus capsid protein, RNA helicase, Peptidase and RNA-dependent RNA polymerase (RdRp) were identified through Pfam domain searches. The genome shares approximately 28% identity with other unclassified picornavirals that infect honey bees (Darwin bee virus 2, Bundaberg bee virus 5, and Sacbrood virus) and a recently reported virus from Asian lady beetle (Harmonia axyridis virus 1). We did not detect this virus in any other geographical populations ofO. rhinoceroscollected from the South Pacific Islands and the Philippines. Analysis of the deduced RdRp amino acid sequences showed that the virus clustered with other Picorna-like viruses and separated from other members of family Dicistroviridae and Iflaviridae.
Insect herbivory on urban trees: Complementary effects of tree neighbours and predation
Authors: Stemmelen Alex , Paquette Alain , Benot Marie-Lise , Kadiri Yasmine , Jactel Hervé , Castagneyrol Bastien
Published: April 2020

Insect herbivory is an important component of forest ecosystems functioning and can affect tree growth and survival. Tree diversity is known to influence insect herbivory in natural forest, with most studies reporting a decrease in herbivory with increasing tree diversity. Urban ecosystems, on the other hand, differ in many ways from the forest ecosystem and the drivers of insect herbivory in cities are still debated.

We monitored 48 urban trees from five species – three native and two exotic – in three parks of Montreal (Canada) for leaf insect herbivory and predator activity on artificial larvae, and linked herbivory with both predation and tree diversity in the vicinity of focal trees.

Leaf insect herbivory decreased with increasing tree diversity and with increasing predator attack rate.

Our findings indicate that tree diversity is a key determinant of multitrophic interactions between trees, herbivores and predators in urban environments and that managing tree diversity could contribute to pest control in cities.

This article has been peer-reviewed and recommended byPeer Community in Ecologyhttps://doi.org/10.24072/pci.ecology.100061