bluuebunny/crossref_metadata_2025 huggingface dataset:
Excess deaths during the Covid-19 pandemic: An international comparison
Authors: Docherty Kieran F. , Butt Jawad H. , de Boer Rudolf A. , Dewan Pooja , Køber Lars , Maggioni Aldo P. , McMurray John J.V. , Solomon Scott D. , Jhund Pardeep S.
Published: April 2020

Background

With the global pandemic of coronavirus disease 2019 (Covid-19) there has been disruption to normal clinical activity in response to the increased demand on health services. There are reports of a reduction in non-Covid-19 emergency presentations. Consequentially, there are concerns that deaths from non-Covid-19 causes could increase. We examined recent reported population-based mortality rates, compared with expected rates, and compared any excess in deaths with the number of deaths attributed to Covid-19.

Methods

National agency and death registration reports were searched for numbers of deaths attributed to Covid-19 and overall mortality that had been publicly reported by 06 May 2020. Data on the number of deaths attributed to Covid-19, the total number of deaths registered in the population and the historical average over at least 3 years were collected. Data were available for 4 European countries (England & Wales, Scotland, Netherlands and Italy) and New York State, United States of America.

Results

There was an increase in observed, compared with expected, mortality in Scotland (+68%), England and Wales (+74%), the Netherlands (+58%), Italy (+39%) and New York state (+49%). Of these deaths, only 73% in Scotland, 71 % in England and Wales, 53% in the Netherlands, 54% in Italy and 79% in New York state were attributed to Covid-19 leaving a number of excess deaths not attributed to Covid-19. In the 5-week period of study, Scotland, 10% of the excess of deaths were attributed to dementia/Alzheimer’s disease and 7% to cardiovascular causes.

Conclusion

A substantial proportion of excess deaths observed during the current COVID-19 pandemic are not attributed to COVID-19 and may represent unrecognised deaths due to Covid-19, an excess of deaths due to other causes, or both. The impact of Covid-19 on mortality and morbidity from other causes needs to be quantified and addressed in public health planning.
Military participation in health security: analysis of Joint External Evaluation mission reports and National Action Plans for Health Security
Authors: Forshey Brett M. , Woodward Alexandra K. , Sanchez Jose L. , Petzing Stephanie R.
Published: April 2020

Militaries across the world play an important but at times poorly defined and underappreciated role in global health security. For example, they are often called upon to support civilian authorities in humanitarian crises and to provide routine healthcare for civilians. Furthermore, military personnel are a unique population in a health security context, as they are highly mobile and often deploy to austere settings domestically and internationally, which may increase exposure to infectious diseases. Despite the role of militaries, few studies have systematically evaluated the involvement of militaries in global health security activities, including the Global Health Security Agenda (GHSA). To address this shortcoming, we analyzed Joint External Evaluation (JEE) mission reports (n=91) and National Action Plans for Health Security (n=11) that had been completed as of October 2019 (n=91) to determine the extent to which military organizations have been involved in the evaluation process, country military contributions to health security are accounted for, and specific recommendations are provided for the country’s military. For JEE reports, military involvement was highest for the “Respond” core area (73%) but much lower for the Prevent (36%) and Detect (30%) core areas. Similarly, 73% of NAPHS documents mentioned military involvement in the Respond core area, compared to 27% and 36% for Prevent and Detect, respectively. Additionally, only 26% of JEE reports provide recommendations for the military in any of the core areas. Our results indicate the need to more fully incorporate military roles and contributions into the GHSA framework and other health security activities in order to improve national capabilities to prevent, detect, and respond to infectious disease threats.
Multi-level modeling of early COVID-19 epidemic dynamics in French regions and estimation of the lockdown impact on infection rate
Authors: Prague Mélanie , Wittkop Linda , Collin Annabelle , Dutartre Dan , Clairon Quentin , Moireau Philippe , Thiébaut Rodolphe , Hejblum Boris P.
Published: April 2020

We developed a multi-level model of the French COVID-19 epidemic at the regional level. We rely on a global extended Susceptible-Exposed-Infectious-Recovered (SEIR) mechanistic model as a simplified representation of the average epidemic process, with the addition of region specific random effects. Combining several French public datasets on the early dynamics of the epidemic, we estimate region-specific key parameters conditionally on this mechanistic model through Stochastic Approximation Expectation Maximization (SAEM) optimization usingMonolixsoftware. We thus estimate the basic reproductive numbers by region before lockdown (with a national average at 2.81 with 95% Confidence Interval [2.58; 3.07]), attack rates (i.e. percentages of infected people) over time per region which range between 1.9% and 9.9% as of May 11th, 2020, and the impact of nationwide lockdown on the infection rate which decreased the transmission rate by 76% towards reproductive numbers ranging from 0.63 to 0.73 at the end of lockdown across regions. These results confirm the low population immunity, the strong effect of the lockdown on the dynamics of the epidemics and the need for further intervention when lifting the lockdown to avoid an epidemic rebound.
Risk of COVID-19 and long-term exposure to air pollution: evidence from the first wave in China
Authors: Zheng Pai , Liu Yonghong , Song Hongbin , Wu Chieh-Hsi , Li Bingying , Kraemer Moritz U.G. , Tian Huaiyu , Yan Xing , Zheng Yuxin , Stenseth Nils Chr. , Dye Christopher , Jia Guang
Published: April 2020

People with chronic obstructive pulmonary disease, cardiovascular disease or hypertension have a high risk of severe coronavirus disease 2019 (COVID-19). Long-term exposure to air pollution, especially PM2.5, has also been associated with COVID-19 mortality. We collated individual-level data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average levels of air pollutants as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the time of emergency response. Other variables included census, smoking prevalence, climate, and socio-economic data from 324 cities in China. We adjusted for human mobility and socio-economic factors, and found that an increase in long-term NO2 or PM2.5 may correspond to an increase in the number of COVID-19 cases and severe infections. However, the linkage might also be affected by the confounding factor of population size because of the predefined correlation between population size and air pollution. The results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings of this paper (and other previous studies that have given ambiguous results) indicate that a more definitive analysis is needed of the link between COVID-19 and air pollution.
Data-driven modeling reveals a universal dynamic underlying the COVID-19 pandemic under social distancing
Authors: Marsland Robert , Mehta Pankaj
Published: April 2020

We show that the COVID-19 pandemic under social distancing exhibits universal dynamics. The cumulative numbers of both infections and deaths quickly cross over from exponential growth at early times to a longer period of power law growth, before eventually slowing. In agreement with a recent statistical forecasting model by the IHME, we show that this dynamics is well described by the erf function. Using this functional form, we perform a data collapse across countries and US states with very different population characteristics and social distancing policies, confirming the universal behavior of the COVID-19 outbreak. We show that the predictive power of statistical models is limited until a few days before curves flatten, forecast deaths and infections assuming current policies continue and compare our predictions to the IHME models. We present simulations showing this universal dynamics is consistent with disease transmission on scale-free networks and random networks with non-Markovian transmission dynamics.
Prediction of the COVID-19 Epidemic Trends Based on SEIR and AI Models
Authors: Feng Shuo , Feng Zebang , Ling Chen , Chang Chen , Feng Zhongke
Published: April 2020

The outbreak of novel coronavirus-caused pneumonia (COVID-19) in Wuhan has attracted worldwide attention. To contain its spread, China adopted unprecedented nationwide interventions on January 23. We sought to show how these control measures impacted the containment of the epidemic. We proposed an SEIR(Susceptible-Exposed-Infectious-Removed) model to analyze the epidemic trend in Wuhan and use the AI model to analyze the epidemic trend in non-Wuhan areas. We found that if the closure was lifted, the outbreak in non-Wuhan areas of mainland China would double in size. Our SEIR and AI model was effective in predicting the COVID-19 epidemic peaks and sizes. The implementation of control measures on January 23, 2020, was indispensable in reducing the eventual COVID-19 epidemic size.
Comparison of videolaryngoscope & direct laryngoscope for intubation in critically ill patients: A Bayesian meta-analysis
Authors: Maitra Souvik , Som Anirban , Bhattacharjee Sulagna
Published: April 2020

Purpose

To identify the benefit of video laryngoscope (VL) over direct laryngoscope (DL) for intubation in the intensive care unit (ICU)

Material & Methods

Randomized controlled trials (RCTs) comparing VL with DL for intubation in ICU by was conducted in conventional frequentist methodology and also incorporated of the previous evidences from observational studies in Bayesian methodology.

Results

Data of 1464 patients from six RCTs have been included in this meta-analysis. In conventional meta-analysis of RCTs, first attempt intubation success rate was similar between VL and DL group [p=0.39]. Rate of esophageal intubation was significantly less with VL [p=0.03] and glottic visualization was significantly improved with VL in comparison to DL [p=0.009]. Time to intubation was similar in both the group [p=0.48]. When evidences from a meta-analysis of observational studies incorporated in Bayesian model, first attempt intubation success is significantly higher with VL [posterior median log OR (95% credible interval) 0.50 (0.06, 1.00)].

Conclusion

Evidences from both observational studies and RCTs synthesized in Bayesian methodology suggest that use of VL for endotracheal intubation in critically patients may be associated with higher first intubation success when compared to DL.
Methylphenidate use and restorative treatment in 13,000 young adults with ADHD
Authors: Schermann Haggai , Schiffmann Nathan , Ankory Ran , Shlaifer Amir , Yavnai Nirit , Yoffe Victoria , Natapov Lena
Published: April 2020

Objective

To assess a dose-response effect of methylphenidate use on restorative treatment needs, which served as an indicator of caries.

Subjects and Methods

This study is a retrospective cohort of military recruits aged 18-25 who served for 12 to 48 months between 2005 and 2017. The cohort included 6,875 subjects with ADHD who received treatment with methylphenidate, 6,729 subjects with ADHD who had no prescriptions for methylphenidate, and 200,000 healthy controls. The outcome was normative treatment needs: having at least one recommendation for restorative treatment during the study period.

Results

Frequency of recommendation for restorative treatment among the treated, the untreated and the control groups was 24%, 22% and 17%, respectively (p<0.0001). On multivariate analysis, the dose-response association between methylphenidate use and the odds of having at least one restorative treatment was confirmed (OR=1.006 for each additional 1 gr of methylphenidate; 95% CI [1.004:1.009]).

Conclusions

Subjects with ADHD who receive chronic treatment with methylphenidate have higher restorative treatment needs than subjects with untreated ADHD and healthy controls. Our results show that chronic methylphenidate medication among young adults leads to an elevated need for restorative treatment and implies a significant impact on oral health.
Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach
Authors: Jelodar Hamed , Wang Yongli , Orji Rita , Huang Hucheng
Published: April 2020

Internet forums and public social media, such as online healthcare forums, provide a convenient channel for users (people/patients) concerned about health issues to discuss and share information with each other. In late December 2019, an outbreak of a novel coronavirus (infection from which results in the disease named COVID-19) was reported, and, due to the rapid spread of the virus in other parts of the world, the World Health Organization declared a state of emergency. In this paper, we used automated extraction of COVID-19–related discussions from social media and a natural language process (NLP) method based on topic modeling to uncover various issues related to COVID-19 from public opinions. Moreover, we also investigate how to use LSTM recurrent neural network for sentiment classification of COVID-19 comments. Our findings shed light on the importance of using public opinions and suitable computational techniques to understand issues surrounding COVID-19 and to guide related decision-making.
DeepViral: infectious disease phenotypes improve prediction of novel virus–host interactions
Authors: Liu-Wei Wang , Kafkas Şenay , Chen Jun , Dimonaco Nicholas , Tegnér Jesper , Hoehndorf Robert
Published: April 2020

Motivation

Infectious diseases from novel viruses have become a major public health concern. Rapid identification of virus–host interactions can reveal mechanistic insights into infectious diseases and shed light on potential treatments. Current computational prediction methods for novel viruses are based mainly on protein sequences. However, it is not clear to what extent other important features, such as the symptoms caused by the viruses, could contribute to a predictor. Disease phenotypes (i.e., signs and symptoms) are readily accessible from clinical diagnosis and we hypothesize that they may act as a potential proxy and an additional source of information for the underlying molecular interactions between the pathogens and hosts.

Results

We developed DeepViral, a deep learning based method that predicts protein–protein interactions (PPI) between humans and viruses. Motivated by the potential utility of infectious disease phenotypes, we first embedded human proteins and viruses in a shared space using their associated phenotypes and functions, supported by formalized background knowledge from biomedical ontologies. By jointly learning from protein sequences and phenotype features, DeepViral significantly improves over existing sequence-based methods for intra- and inter-species PPI prediction. Lastly, we propose a novel experimental setup to realistically evaluate prediction methods for novel viruses.

Availability

https://github.com/bio-ontology-research-group/DeepViral

Contact

robert.hoehndorf@kaust.edu.sa
Genomic, geographic and temporal distributions of SARS-CoV-2 mutations
Authors: Yang Hsin-Chou , Chen Chun-houh , Wang Jen-Hung , Liao Hsiao-Chi , Yang Chih-Ting , Chen Chia-Wei , Lin Yin-Chun , Kao Chiun-How , Liao James C.
Published: April 2020

The COVID-19 pandemic is the most significant public health issue in recent history. Its causal agent, SARS-CoV-2, has evolved rapidly since its first emergence in December 2019. Mutations in the viral genome have critical impacts on the adaptation of viral strains to the local environment, and may alter the characteristics of viral transmission, disease manifestation, and the efficacy of treatment and vaccination. Using the complete sequences of 1,932 SARS-CoV-2 genomes, we examined the genomic, geographic and temporal distributions of aged, new, and frequent mutations of SARS-CoV-2, and identified six phylogenetic clusters of the strains, which also exhibit a geographic preference in different continents. Mutations in the form of single nucleotide variations (SNVs) provide a direct interpretation for the six phylogenetic clusters. Linkage disequilibrium, haplotype structure, evolutionary process, global distribution of mutations unveiled a sketch of the mutational history. Additionally, we found a positive correlation between the average mutation count and case fatality, and this correlation had strengthened with time, suggesting an important role of SNVs on disease outcomes. This study suggests that SNVs may become an important consideration in virus detection, clinical treatment, drug design, and vaccine development to avoid target shifting, and that continued isolation and sequencing is a crucial component in the fight against this pandemic.

Significance Statement

Mutation is the driving force of evolution for viruses like SARS-CoV-2, the causal agent of COVID-19. In this study, we discovered that the genome of SARS-CoV-2 is changing rapidly from the originally isolated form. These mutations have been spreading around the world and caused more than 2.5 million of infected cases and 170 thousands of deaths. We found that fourteen frequent mutations identified in this study can characterize the six main clusters of SARS-CoV-2 strains. In addition, we found the mutation burden is positively correlated with the fatality of COVID-19 patients. Understanding mutations in the SARS-CoV-2 genome will provide useful insight for the design of treatment and vaccination.
Comparison of commercial RT-PCR diagnostic kits for COVID-19
Authors: van Kasteren Puck B. , van der Veer Bas , van den Brink Sharon , Wijsman Lisa , de Jonge Jørgen , van den Brandt Annemarie , Molenkamp Richard , Reusken Chantal B.E.M. , Meijer Adam
Published: April 2020

The final months of 2019 witnessed the emergence of a novel coronavirus in the human population. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has since spread across the globe and is posing a major burden on society. Measures taken to reduce its spread critically depend on timely and accurate identification of virus-infected individuals by the most sensitive and specific method available, i.e. real-time reverse transcriptase PCR (RT-PCR). Many commercial kits have recently become available, but their performance has not yet been independently assessed.

The aim of this study was to compare basic analytical and clinical performance of selected RT-PCR kits from seven different manufacturers (Altona Diagnostics, BGI, CerTest Biotec, KH Medical, PrimerDesign, R-Biopharm AG, and Seegene).

We used serial dilutions of viral RNA to establish PCR efficiency and estimate the 95% limit of detection (LOD95%). Furthermore, we ran a panel of SARS-CoV-2-positive clinical samples (n=16) for a preliminary evaluation of clinical sensitivity. Finally, we used clinical samples positive for non-coronavirus respiratory viral infections (n=6) and a panel of RNA from related human coronaviruses to evaluate assay specificity.

PCR efficiency was ≥96% for all assays and the estimated LOD95% varied within a 6-fold range. Using clinical samples, we observed some variations in detection rate between kits. Importantly, none of the assays showed cross-reactivity with other respiratory (corona)viruses, except as expected for the SARS-CoV-1 E-gene.

We conclude that all RT-PCR kits assessed in this study may be used for routine diagnostics of COVID-19 in patients by experienced molecular diagnostic laboratories.
Stroma secreted IL6 selects for “stem-like” population and alters pancreatic tumor microenvironment by reprogramming metabolic pathways
Authors: Kesh Kousik , Garrido Vanessa T , Doesch Austin , Durden Brittany , Gupta Vineet K , Sharma Nikita S , Lyle Michael , Nagathihalli Nagaraj , Merchant Nipun , Saluja Ashok , Banerjee Sulagna
Published: April 2020

Pancreatic adenocarcinoma is a devastating disease with an abysmal survival rate of 9%. A robust fibro-inflammatory and desmoplastic stroma, characteristic of pancreatic cancer, contributes to the challenges in developing viable therapeutic strategies in this disease. Apart from constricting blood vessels and preventing efficient drug delivery to the tumor, the stroma also contributes to aggressive biology of the cancer along with its immune-evasive microenvironment. In this study, we show that in pancreatic tumors, the developing stroma increases tumor initiation frequency in pancreatic cancer cells in vivo by enriching for CD133+ aggressive “stem-like” cells. Additionally, the stromal fibroblasts secrete IL6 as the major cytokine, increases glycolytic flux in the pancreatic tumor cells and increases lactate efflux in the microenvironment via activation of the STAT signaling pathway. We also show that the secreted lactate favors activation of M2 macrophages in the tumor microenvironment, which excludes CD8+ T-cells in the tumor. Our data additionally confirms that treatment of pancreatic tumors with anti-IL6 antibody results in tumor regression as well as decreased CD133+ population within the tumor. Furthermore, inhibiting the lactate efflux in the microenvironment reduces M2 macrophages, and makes pancreatic tumors more responsive to anti-PD1 therapy. This suggests that stromal IL6 driven metabolic reprogramming plays a significant role in the development of an immune evasive microenvironment. In conclusion, our study shows that targeting the metabolic pathways affected by stromal IL6 can make pancreatic tumors amenable to checkpoint inhibitor therapy.
The safety profile of Bald’s eyesalve for the treatment of bacterial infections
Authors: Anonye Blessing O , Nweke Valentine , Furner-Pardoe Jessica , Gabrilska Rebecca , Rafiq Afshan , Ukachukwu Faith , Bruce Julie , Lee Christina , Unnikrishnan Meera , Rumbaugh Kendra P. , Snyder Lori AS , Harrison Freya
Published: April 2020

The rise in antimicrobial resistance has prompted the development of alternatives, such as plant-derived compounds, to combat bacterial infections. Bald’s eyesalve, a remedy used in the Early Medieval period, has previously been shown to have efficacy againstStaphylococcus aureusgrown in anin vitromodel of soft tissue infection. This remedy also had bactericidal activity against methicillin-resistantS. aureus(MRSA) in a chronic mouse wound. However, the safety profile of Bald’s eyesalve has not yet been demonstrated, and this is vital before testing in humans. Here, we determined the safety potential of Bald’s eyesalve usingin vitro,ex vivo, andin vivomodels representative of skin or eye infections. We also confirmed that Bald’s eyesalve is active against an important eye pathogen,Neisseria gonorrhoeae. Low levels of cytotoxicity were observed in eyesalve-treated cell lines representative of skin and immune cells. Results from a bovine corneal opacity and permeability test demonstrated slight irritation to the cornea that resolved within 10 minutes. The slug mucosal irritation assay revealed that a low level of mucus was secreted by slugs exposed to eyesalve, indicating mild mucosal irritation. We obtained promising results from mouse wound closure experiments; no visible signs of irritation or inflammation were observed. Our results suggest that Bald’s eyesalve could be tested further on human volunteers to assess safety for topical application against bacterial infections.

Importance

Alternative treatment for bacterial infections are needed to combat the ever increasing repertoire of bacteria resistant to antibiotics. A medieval plant-based remedy, Bald’s eyesalve, shows promise as a substitute for the treatment of these infections. For any substance to be effective in the treatment of bacterial infections in humans, it is important to consider the safety profile. This is a key consideration in order to have the necessary regulatory approval. We demonstrate the safety profile of Bald’s eyesalve using a variety of models, including whole-organ and whole-animal models. Our results show that Bald’s eyesalve is mildly toxic to cultured human cells, but potentially suitable for patch tests on healthy human volunteers to assess safety for later clinical trials. Our work has the potential to transform the management of diseases caused by bacterial infections, such as diabetic foot ulcers, through topical application of a natural product cocktail based on Bald’s eyesalve.
Modular output circuits of the fastigial nucleus mediate diverse motor and nonmotor functions of the cerebellar vermis
Authors: Fujita Hirofumi , Kodama Takashi , Lac Sascha du
Published: April 2020

The cerebellar vermis, long associated with axial motor control, has been implicated in a surprising range of neuropsychiatric disorders and cognitive and affective functions. Remarkably little is known, however, about the specific cell types and neural circuits responsible for these diverse functions. Here, using single-cell gene expression profiling and anatomical circuit analyses of vermis output neurons in the mouse fastigial (medial cerebellar) nucleus, we identify five major classes of glutamatergic projection neurons distinguished by gene expression, morphology, distribution, and input-output connectivity. Each fastigial cell type is connected with a specific set of Purkinje cells and inferior olive neurons and in turn innervates a distinct collection of downstream targets. Transsynaptic tracing indicates extensive disynaptic links with cognitive, affective, and motor forebrain circuits. These results indicate that diverse cerebellar vermis functions are mediated by modular synaptic connections of distinct fastigial cell types which differentially coordinate posturomotor, oromotor, positional-autonomic, orienting, and vigilance circuits.
Physiology of PNS axons relies on glycolytic metabolism in myelinating Schwann cells
Authors: Deck Marie , Van Hameren Gerben , Campbell Graham , Bernard-Marissal Nathalie , Devaux Jérôme , Berthelot Jade , Lattard Alise , Médard Jean-Jacques , Gautier Benoît , Quintana Patrice , Chao de la Barca Juan Manuel , Reynier Pascal , Lenaers Guy , Chrast Roman , Tricaud Nicolas
Published: April 2020

Despite the lactate shuttle theory, how glial cells support axonal metabolism and function remains unclear. Lactate production is a common occurrence following anaerobic glycolysis in muscles. However, several other cell types, including some stem cells, activatezd macrophages and tumor cells, can produce lactate in presence of oxygen and cellular respiration, using Pyruvate Kinase 2 (PKM2) to divert pyruvate to lactate dehydrogenase. We show here that PKM2 is also upregulated in mature myelinating Schwann cells (mSC) of mouse sciatic nerve. Deletion of this isoform in PLP-expressing cells in mice leads to a deficit of lactate in mSC and in peripheral nerves. This had no detectable consequences on the myelin sheath. However, mutant mice developed a peripheral neuropathy. Peripheral nerve axons of mutant mice failed to maintain lactate homeostasis upon activity, resulting in an impaired production of mitochondrial ATP. Action potential propagation was not altered but axonal mitochondria transport was slowed down, muscle axon terminals retracted and motor neurons displayed cellular stress. Additional reduction of lactate availability through dichloroacetate treatment, which diverts pyruvate to mitochondrial oxidative phosphorylation, further aggravated motor dysfunction in mutant mice. Thus, lactate production through aerobic glycolysis is essential in mSC for the long-term maintenance of peripheral nerve axon physiology and function.
3D SYNAPTIC ORGANIZATION OF THE RAT CA1 AND ALTERATIONS INDUCED BY COCAINE SELF-ADMINISTRATION
Authors: Blazquez-Llorca L. , Miguéns M. , Montero-Crespo M. , Selvas A. , Gonzalez-Soriano J. , Ambrosio E. , DeFelipe J.
Published: April 2020

The hippocampus plays a key role in contextual conditioning and has been proposed as an important component of the cocaine addiction brain circuit. To gain knowledge about cocaine-induced alterations in this circuit, we used Focused Ion Beam milling/Scanning Electron Microscopy (FIB/SEM) to reveal and quantify the 3D synaptic organization of thestratum radiatumof rat CA1, under normal circumstances and after cocaine-self administration (SA). Most synapses are asymmetric (excitatory), macular-shaped, and in contact with spine heads. After cocaine-SA, the size and complexity of both asymmetric and symmetric (inhibitory) synapses increased but no changes were observed in the synaptic density.

This work constitutes the first detailed report on the 3D synaptic organization in thestratum radiatumof the CA1 field of cocaine-SA rats. Our data contribute to the elucidation of the normal and altered synaptic organization of the hippocampus, which is crucial for better understanding the neurobiological mechanisms underlying cocaine addiction.
Detection of Gray Mold Infection in Plants Using a Multispectral Imaging System
Authors: Scarboro Clifton G. , Ruzsa Stephanie M. , Doherty Colleen J. , Kudenov Michael W.
Published: April 2020

Gray mold disease caused by the fungusBotrytis cinereadamages many crop hosts worldwide and is responsible for heavy economic losses. Early diagnosis and detection of the disease would allow for more effective crop management practices to prevent outbreaks in field or greenhouse settings. Furthermore, having a simple, non-invasive way to quantify the extent of gray mold disease is important for plant pathologists interested in quantifying infection rates. In this paper, we design and build a multispectral imaging system for discriminating between leaf regions, infected with gray mold, and those that remain unharmed on a lettuce (Lactuca spp.)host. First, we describe a method to select two optimal (high contrast) spectral bands from continuous hyperspectral imagery (450-800 nm). We then built a system based on these two spectral bands, located at 540 and 670 nm. The resultant system uses two cameras, with a narrow band-pass spectral filter mounted on each, to measure the multispectral reflectance of a lettuce leaf. The two resulting images are combined using a normalized difference calculation that produces a single image with high contrast between the leaves’ infected and healthy regions. A classifier was then created based on the thresholding of single pixel values. We demonstrate that this simple classification produces a true positive rate of 95.25% with a false positive rate of 9.316%.
The Mechanics of Temporal Interference Stimulation
Authors: Cao Jiaming , Doiron Brent , Goswami Chaitanya , Grover Pulkit
Published: April 2020

We utilize single neuron models to understand mechanisms behind Temporal Interference (TI) stimulation (also called “Interferential Stimulation”). We say that a neuron exhibits TI stimulation if it does not fire for a high-frequency sinusoidal input, but fires when the input is a low-frequency modulation of the high-frequency sinusoid (specifically that generated by addition of two high frequency sinusoids with a small difference in their frequencies), while the maximum amplitude is kept the same in both cases. Our key observation – that holds for both FitzHugh-Nagumo and Hodgkin-Huxley neuron models – is that for neuron models that do exhibit TI stimulation, a high frequency pure sinusoidal input results in a current balance between inward and outward currents. This current balance leads to a subthreshold periodic orbit that keeps the membrane potential from spiking for sinusoidal inputs. However, the balance is disturbed when the envelope of the sinusoids is modulated with a high slope: the fast-changing envelope activates fast depolarizing currents without giving slow outward currents time to respond. This imbalance causes the membrane potential to build up, causing the neuron to fire. This mechanistic understanding can help design current waveforms for neurons that exhibit TI stimulation, and also help classify which neuron-types may or may not exhibit TI stimulation.
In silicodesign of Multi-epitope-based peptide vaccine against SARS-CoV-2 using its spike protein
Authors: Mitra Debarghya , Pandey Janmejay , Jain Alok , Swaroop Shiv
Published: April 2020

SARS-CoV-2 has been efficient in ensuring that many countries are brought to a standstill. With repercussions ranging from rampant mortality, fear, paranoia, and economic recession, the virus has brought together countries to look at possible therapeutic countermeasures. With prophylactic interventions possibly months away from being particularly effective, a slew of measures and possibilities concerning the design of vaccines are being worked upon. We attempted a structure-based approach utilizing a combination of epitope prediction servers and Molecular dynamic (MD) simulations to develop a multi-epitope-based subunit vaccine that involves the two subunits of the spike glycoprotein of SARS-CoV-2 (S1 and S2) coupled with a substantially effective chimeric adjuvant to create stable vaccine constructs. The designed constructs were evaluated based on their docking with Toll-Like Receptor (TLR) 4. Our findings provide an epitope-based peptide fragment that can be a potential candidate for the development of a vaccine against SARS-CoV-2. Recent experimental studies based on determining immunodominant regions across the spike glycoprotein of SARS-CoV-2 indicate the presence of the predicted epitopes included in this study.
Identification of Plitidepsin as Potent Inhibitor of SARS-CoV-2-Induced Cytopathic Effect after a Drug Repurposing Screen
Authors: Rodon Jordi , Muñoz-Basagoiti Jordana , Perez-Zsolt Daniel , Noguera-Julian Marc , Paredes Roger , Mateu Lourdes , Quiñones Carles , Erkizia Itziar , Blanco Ignacio , Valencia Alfonso , Guallar Víctor , Carrillo Jorge , Blanco Julià , Segalés Joaquim , Clotet Bonaventura , Vergara-Alert Júlia , Izquierdo-Useros Nuria
Published: April 2020

There is an urgent need to identify therapeutics for the treatment of Coronavirus diseases 2019 (COVID-19). Although different antivirals are given for the clinical management of SARS-CoV-2 infection, their efficacy is still under evaluation. Here, we have screened existing drugs approved for human use in a variety of diseases, to compare how they counteract SARS-CoV-2-induced cytopathic effect and viral replicationin vitro.Among the potential 72 antivirals tested herein that were previously proposed to inhibit SARS-CoV-2 infection, only 18% had an IC50below 25 μM or 102IU/mL. These included plitidepsin, novel cathepsin inhibitors, nelfinavir mesylate hydrate, interferon 2-alpha, interferon-gamma, fenofibrate, camostat along the well-known remdesivir and chloroquine derivatives. Plitidepsin was the only clinically approved drug displaying nanomolar efficacy. Four of these families, including novel cathepsin inhibitors, blocked viral entry in a cell-type specific manner. Since the most effective antivirals usually combine therapies that tackle the virus at different steps of infection, we also assessed several drug combinations. Although no particular synergy was found, inhibitory combinations did not reduce their antiviral activity. Thus, these combinations could decrease the potential emergence of resistant viruses. Antivirals prioritized herein identify novel compounds and their mode of action, while independently replicating the activity of a reduced proportion of drugs which are mostly approved for clinical use. Combinations of these drugs should be tested in animal models to inform the design of fast track clinical trials.
Within-population sperm competition intensity does not predict asymmetry in conpopulation sperm precedence
Authors: Garlovsky Martin D. , Yusuf Leeban H. , Ritchie Michael G. , Snook Rhonda R.
Published: April 2020

Postcopulatory sexual selection can generate coevolutionary arms races between the sexes resulting in the rapid coevolution of reproductive phenotypes. As traits affecting fertilisation success diverge between populations postmating prezygotic barriers to gene flow may evolve. Conspecific sperm precedence is a form of such isolation thought to evolve early during speciation yet has mostly been studied between species. Here we show conpopulation sperm precedence betweenDrosophila montanapopulations. Using genomic data to estimate divergence times and patterns of gene flow between populations, we show gene flow has played a considerable role during divergence. We find conpopulation sperm precedence is asymmetric and is concordant with asymmetry in non-competitive postmating prezygotic reproductive isolation. These results suggest these phenomena have a shared mechanism, but we show that this asymmetry is unrelated to the strength of postcopulatory sexual selection acting within populations. We tested whether overlapping foreign and coevolved ejaculates within the female reproductive tract altered fertilisation success but found no effect. Our results show that neither time since divergence nor sperm competitiveness predicts the strength of postmating prezygotic reproductive isolation. We suggest that divergence of postcopulatory phenotypes resulting in postmating prezygotic isolation is potentially driven by cryptic female choice, or mutation order divergence.
Universality of cell differentiation trajectories revealed by a reconstruction of transcriptional uncertainty landscapes from single-cell transcriptomic data
Authors: Gao Nan Papili , Gandrillon Olivier , Páldi András , Herbach Ulysse , Gunawan Rudiyanto
Published: April 2020

We employed our previously-described single-cell gene expression analysis CALISTA (Clustering And Lineage Inference in Single-Cell Transcriptional Analysis) to evaluate transcriptional uncertainty at the single-cell level using a stochastic mechanistic model of gene expression. We reconstructed a transcriptional uncertainty landscape during cell differentiation by visualizing single-cell transcriptional uncertainty surface over a two dimensional representation of the single-cell gene expression data. The reconstruction of transcriptional uncertainty landscapes for ten publicly available single-cell gene expression datasets from cell differentiation processes with linear, single or multi-branching cell lineage, reveals universal features in the cell differentiation trajectory that include: (i) a peak in single-cell uncertainty during transition states, and in systems with bifurcating differentiation trajectories, each branching point represents a state of high transcriptional uncertainty; (ii) a positive correlation of transcriptional uncertainty with transcriptional burst size and frequency; (iii) an increase in RNA velocity preceeding the increase in the cell transcriptional uncertainty. Finally, we provided biological interpretations of the universal rise-then-fall profile of the transcriptional uncertainty landscape, including a link with the Waddington’s epigenetic landscape, that is generalizable to every cell differentiation system.
Mosquitoes (Diptera:Culicidae) in an indigenous settlement of the Magdalena State, Colombia
Authors: Parra-Henao Gabriel , Perdomo Erick , Carrasquilla Deibys , Torres Emy , Perez Celenny , Molina Jose Luis
Published: April 2020

Studies directed to investigate ecological parameters of mosquitoes populations allows to establish the risk of vector borne diseases transmission and to bring recommendations for health authorities about prevention, surveillance and control. We report some ecological aspects of mosquitoes populations in a region of Colombia. Quarterly sampling was done. For mosquito catching CDC and Shannon traps were used. Diversity and abundance indexes estimation was done. A total of 1071 mosquitoes belonging to four genera and 10 species were collected. The most abundant species wereCx quinquefasciatus(22.6%),Ae. aegypti(20.08%),Ae. scapularis(12.3%),Ae. angustivittatus(9%) andAn. albimanus(8.0%). The finding ofCx pedroi, Ae. scapularis,,Cx. nigripalpus, Cx. quinquefasciatus, Cx. declarator, Ma. titillans, andPs. feroxpreviously reported as arbovirus vectors warns about the possibility of transmission in the zone and the finding ofAn. albimanus, also warns about the risk for malaria transmission in the area.
MaxHiC: robust estimation of chromatin interaction frequency in Hi-C and capture Hi-C experiments
Authors: Alinejad-Rokny Hamid , Modegh Rassa Ghavami , Rabiee Hamid R. , Rezaie Narges , Tam Kin Tung , Forrest Alistair R. R.
Published: April 2020

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions, and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than random (background) interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools and demonstrate using published Hi-C and capture Hi-C datasets that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, and 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and more likely to link known regulatory features than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distribution only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C and capture Hi-C data.

Author summary

MaxHiC is a robust machine learning based tool for identifying significant interacting regions from both Hi-C and capture Hi-C data. All the current existing models are designed for either Hi-C or capture Hi-C data, however we developed MaxHiC to be applicable for both Hi-C and capture Hi-C libraries (two different models have been used for Hi-C and capture Hi-C data). MaxHiC is also able to analyse very deep Hi-C libraries (e.g., MicroC) without any computational issues. MaxHiC significantly outperforms current existing tools in terms of enrichment of interactions between known regulatory regions as well as biologically relevant interactions.
Succinct dynamic variation graphs
Authors: Eizenga Jordan M. , Novak Adam M. , Kobayashi Emily , Villani Flavia , Cisar Cecilia , Heumos Simon , Hickey Glenn , Colonna Vincenza , Paten Benedict , Garrison Erik
Published: April 2020

Motivation

Pangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic data sets can be challenging to work at. These challenges have impeded progress in this field.

Results

Here we present a stack of two C++ libraries,libbdsgandlibhandlegraph, which use a simple, field-proven interface, designed to expose elementary features of these graphs while preventing common graph manipulation mistakes. The libraries also provide a Python binding. Using a diverse collection of pangenome graphs, we demonstrate that these tools allow for efficient construction and manipulation of large genome graphs with dense variation. For instance, the speed and memory usage is up to an order of magnitude better than the prior graph implementation in the vg toolkit, which has now transitioned to usinglibbdsg’s implementations.

Availability

libhandlegraphandlibbdsgare available under an MIT License fromhttps://github.com/vgteam/libhandlegraphandhttps://github.com/vgteam/libbdsg.

Contact

erik.garrison@ucsc.edu
Shifting Baselines: Physiological legacies contribute to the response of reef coral to frequent heat waves
Authors: Wall Christopher B. , Ricci Contessa A. , Wen Alexandra D. , Ledbetter Bren E. , Klinger Delania E. , Mydlarz Laura D. , Gates Ruth D. , Putnam Hollie M.
Published: April 2020

Global climate change is altering coral reef ecosystems. Notably, marine heat waves are producing widespread coral bleaching events that are increasing in frequency, with projections for annual bleaching events on reefs worldwide by mid-century.

The response of corals to elevated seawater temperatures can be modulated by abiotic factors at site of origin and dominant endosymbiont type, which can result in a shift in multiple coral traits and drive physiological legacy effects that influence the trajectory of reef corals under subsequent thermal stress events. It is critical, therefore, to evaluate the potential for shifting physiological and cellular baselines driven by these factors inin situbleaching (and recovery) events. Here, we use the back-to-back regional bleaching events of 2014 and 2015 in the Hawaiian Islands and subsequent recovery periods to test the hypothesis that coral multivariate trait space (here termed physiotype, sensu (Van Straalen, 2003) shift in multiple bleaching events, modulated by both environmental histories and symbiotic partnerships (Symbiodiniaceae).

Despite fewer degree heating weeks in the first-bleaching event relative to the second (7vs. 10), bleaching severity in a dominant reef building coral on Hawaiian reefs,Montipora capitata, was greater (~70%vs. 50% bleached cover) and differences due to environmental history (reef site) were more pronounced. Melanin, an immune cytotoxic response, provided an initial defense during the first event, potentially priming antioxidant activity, which peaked in the second-bleaching event (i.e., a legacy effect). While magnitude of bleaching differed, immune response patterns were shared among corals harboring heat-sensitive and heat-tolerant Symbiodiniaceae. This supports a pattern of increased constitutive immunity in corals resulting from repeat bleaching events, with greater specialized enzymes (catalase, peroxidase, superoxide dismutase) and attenuated melanin synthesis.

This study demonstrates bleaching events have implications for reef corals beyond shaping their ecological assemblages. These events can change the magnitude and/or identity of response variables contributing to physiotype, thus generating physiological legacies carried over into the future. Quantifying baseline coral physiotypes and tracking their shifts will be critical to understanding and forecasting the effects of increased bleaching frequency on coral biology and ecology in the Anthropocene.