bluuebunny/crossref_metadata_2025_split huggingface dataset:
The microbial exometabolome: ecological resource and architect of microbial communities
Authors: Douglas Angela E. 
Published: March 2020

All microorganisms release many metabolites, collectively known as the exometabolome. The resultant multi-way cross-feeding of metabolites among microorganisms distributes resources, thereby increasing total biomass of the microbial community, and promotes the recruitment and persistence of phylogenetically and functionally diverse taxa in microbial communities. Metabolite transfer can also select for evolutionary diversification, yielding multiple closely related but functionally distinct strains. Depending on starting conditions, the evolved strains may be auxotrophs requiring metabolic outputs from producer cells or, alternatively, display loss of complementary reactions in metabolic pathways, with increased metabolic efficiency. Metabolite cross-feeding is widespread in many microbial communities associated with animals and plants, including the animal gut microbiome, and these metabolic interactions can yield products valuable to the host. However, metabolite exchange between pairs of intracellular microbial taxa that share the same host cell or organ can be very limited compared to pairs of free-living microorganisms, perhaps as a consequence of host controls over the metabolic function of intracellular microorganisms. Priorities for future research include the development of tools for improved quantification of metabolite exchange in complex communities and greater integration of the roles of metabolic cross-feeding and other ecological processes, including priority effects and antagonistic interactions, in shaping microbial communities.This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.
Understanding the evolution of interspecies interactions in microbial communities
Authors: Gorter Florien A. , Manhart Michael , Ackermann Martin 
Published: March 2020

Microbial communities are complex multi-species assemblages that are characterized by a multitude of interspecies interactions, which can range from mutualism to competition. The overall sign and strength of interspecies interactions have important consequences for emergent community-level properties such as productivity and stability. It is not well understood how interspecies interactions change over evolutionary timescales. Here, we review the empirical evidence that evolution is an important driver of microbial community properties and dynamics on timescales that have traditionally been regarded as purely ecological. Next, we briefly discuss different modelling approaches to study evolution of communities, emphasizing the similarities and differences between evolutionary and ecological perspectives. We then propose a simple conceptual model for the evolution of interspecies interactions in communities. Specifically, we propose that to understand the evolution of interspecies interactions, it is important to distinguish between direct and indirect fitness effects of a mutation. We predict that in well-mixed environments, traits will be selected exclusively for their direct fitness effects, while in spatially structured environments, traits may also be selected for their indirect fitness effects. Selection of indirectly beneficial traits should result in an increase in interaction strength over time, while selection of directly beneficial traits should not have such a systematic effect. We tested our intuitions using a simple quantitative model and found support for our hypotheses. The next step will be to test these hypotheses experimentally and provide input for a more refined version of the model in turn, thus closing the scientific cycle of models and experiments.This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.
Chitinasiproducens palmae gen. nov., sp. nov., a new member of the family Burkholderiaceae isolated from leaf tissues of oil palm (Elaeis guineensis Jacq.)
Authors: Madhaiyan Munusamy , See-Too Wah-Seng , Ee Robson , Saravanan Venkatakrishnan Sivaraj , Wirth Joseph S. , Alex Tan Hian Hwee , Lin Cai , Kim Soo-Jin , Weon Hang-Yeon , Kwon Soon-Wo , Whitman William B. , Ji Lianghui 
Published: March 2020

A Gram-stain-negative, aerobic, rod-shaped, leaf-associated bacterium, designated JS23T, was isolated from surface-sterilized leaf tissue of an oil palm grown in Singapore and was investigated by polyphasic taxonomy. Phylogenetic analyses based on 16S rRNA gene sequences and 180 conserved genes in the genome of several members of

Burkholderiaceae

revealed that strain JS23T formed a distinct evolutionary lineage independent of other taxa within the family

Burkholderiaceae

. The predominant ubiquinone was Q-8. The primary polar lipids were phosphatidylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, and an unidentified aminophospholipid. The major fatty acids were C16 : 0, summed feature 3 (C16 : 1
ω7c /C16 : 1
ω6c) and summed feature 8 (C18 : 1
ω7c /C18 : 1
ω6c). The size of the genome is 5.36 Mbp with a DNA G+C content of 66.2 mol%. Genomic relatedness measurements such as average nucleotide identity, genome-to-genome distance and digital DNA–DNA hybridization clearly distinguished strain JS23T from the closely related genera

Burkholderia

,

Caballeronia

,

Mycetohabitans

,

Mycoavidus

,

Pandoraea

,

Paraburkholderia

,

Robbsia

and

Trinickia

. Furthermore, average amino acid identity values and the percentages of conserved proteins, 56.0–68.4 and 28.2–45.5, respectively, were well below threshold values for genus delineation and supported the assignment of JS23T to a novel genus. On the basis of the phylogenetic, biochemical, chemotaxonomic and phylogenomic evidence, strain JS23T is proposed to represent a novel species of a new genus within the family

Burkholderiaceae

, for which the name Chitinasiproducens palmae gen. nov., sp. nov., is proposed with the type strain of JS23T (= DSM 27307T=KACC 17592T).
Preprint server use in kidney disease research: a rapid review
Authors: Vlasschaert Caitlyn , Giles Cameron , Hiremath Swapnil , Lanktree Matthew B. 
Published: March 2020

AbstractPurpose of reviewPreprint servers including arXiv and bioRxiv have disrupted the scientific communication landscape by providing rapid access to pre--peer reviewed research. MedRxiv is a recently launched free online repository for preprints in the health sciences. We sought to summarize potential benefits and risks to preprint server use, from both the researcher and end--user perspective, and evaluate the uptake of preprint servers in the nephrology community.Sources of InformationWe performed a rapid review of articles describing preprint servers and their use. We approached the 20 highest impact nephrology journals regarding their policy towards the use of preprint servers. We evaluated the average time from study completion to publication of impactful articles in nephrology. Finally, we evaluated the number of nephrology articles submitted to preprint servers.FindingsTo date over 600 kidney--related articles have been uploaded to bioRxiv and medRxiv. The average time from study completion to publication was over 10 months. 16 of the top 20 nephrology journals currently accept research submitted to a preprint server. Transparency and collaboration, visibility and recognition, and rapid dissemination of results were identified as benefits of preprint servers. Concerns exist regarding the potential risk of non--peer reviewed medical research being publicly available.LimitationsPreprint servers remain a recent phenomenon in health sciences and their long-- term impact on the medical literature remains to be seen.ImplicationsThe quantity of research submitted to preprint servers is likely to continue to grow. The model for dissemination of research results will need to adapt to incorporate preprint servers.
High incidence of asymptomatic SARS-CoV-2 infection, Chongqing, China
Authors: Tao Yang , Cheng Panke , Chen Wen , Wan Peng , Chen Yaokai , Yuan Guodan , Chen Junjie , Huo Da , Guan Ge , Sun Dayu , Tan Ju , Yang Guanyuan , Zeng Wen , Zhu Chuhong 
Published: March 2020

SummaryBackgroundSARS-CoV-2 has been a global pandemic, but the emergence of asymptomatic patients has caused difficulties in the prevention of the epidemic. Therefore, it is significant to understand the epidemiological characteristics of asymptomatic patients with SARS-CoV-2 infection.MethodsIn this single-center, retrospective and observational study, we collected data from 167 patients with SARS-CoV-2 infection treated in Chongqing Public Health Medical Center (Chongqing, China) from January to March 2020. The epidemiological characteristics and variable of these patients were collected and analyzed.Findings82.04% of the SARS-CoV-2 infected patients had a travel history in Wuhan or a history of contact with returnees from Wuhan, showing typical characteristics of imported cases, and the proportion of severe Covid-19 patients was 13.2%, of which 59% were imported from Wuhan. For the patients who was returnees from Wuhan, 18.1% was asymptomatic patients. In different infection periods, compared with the proportion after 1/31/2020, the proportion of asymptomatic patient among SARS-CoV-2 infected patient was higher(19% VS 1.5%). In different age groups, the proportion of asymptomatic patient was the highest(28.6%) in children group under 14, next in elder group over 70 (27.3%). Compared with mild and common Covid-19 patients, the mean latency of asymptomatic was longer (11.25 days VS 8.86 days), but the hospital length of stay was shorter (14.3 days VS 16.96 days).ConclusionThe SARS-CoV-2 prevention needs to focus on the screening of asymptomatic patients in the community with a history of contact with the imported population, especially for children and the elderly population.
ACE-2 Expression in the Small Airway Epithelia of Smokers and COPD Patients: Implications for COVID-19
Authors: Leung Janice M. , Yang Chen X. , Tam Anthony , Shaipanich Tawimas , Hackett Tillie-Louise , Singhera Gurpreet K. , Dorscheid Delbert R. , Sin Don D. 
Published: March 2020

AbstractIntroductionCoronavirus disease 2019 (COVID-19) is a respiratory infection caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This virus uses the angiotensin converting enzyme II (ACE-2) as the cellular entry receptor to infect the lower respiratory tract. Because individuals with chronic obstructive pulmonary disease (COPD) are at increased risk of severe COVID-19, we determined whether ACE-2 expression in the lower airways was related to COPD and cigarette smoking.MethodsUsing RNA-seq, we determined gene expression levels in bronchial epithelia obtained from cytologic brushings of 6th to 8th generation airways in individuals with and without COPD. We eternally validated these results from two additional independent cohorts, which used microarray technologies to measure gene expression levels from 6th to 12th generation airways.ResultsIn the discovery cohort (n=42 participants), we found that ACE-2 expression levels were increased by 48% in the airways of COPD compared with non-COPD subjects (COPD=2.52±0.66 log2 counts per million reads (CPM) versus non-COPD= 1.70±0.51 CPM, p=7.62×10−4). There was a significant inverse relationship between ACE-2 gene expression and FEV1% of predicted (r=-0.24; p=0.035). Current smoking also significantly increased ACE-2 expression levels compared with never smokers (never current smokers=2.77±0.91 CPM versus smokers=1.78±0.39 CPM, p=0.024). These findings were replicated in the two eternal cohorts.ConclusionsACE-2 expression in lower airways is increased in patients with COPD and with current smoking. These data suggest that these two subgroups are at increased risk of serious COVID-19 infection and highlight the importance of smoking cessation in reducing the risk.
Effectiveness and safety of antiviral or antibody treatments for coronavirus
Authors: Rios Patricia , Radhakrishnan Amruta , Antony Jesmin , Thomas Sonia , Muller Matthew , Straus Sharon E. , Tricco Andrea C. 
Published: March 2020

ABSTRACTBackgroundTo identify safe and effective medical countermeasures (e.g., antivirals/antibodies) to address the current outbreak of a novel coronavirus (COVID-19)MethodsComprehensive literature searches were developed by an experienced librarian for MEDLINE, EMBASE, the Cochrane Library, and biorxiv.org/medrxiv.org; additional searches for ongoing trials and unpublished studies were conducted in clinicaltrials.gov and the Global Infectious Diseases and Epidemiology Network (GIDEON). Title/abstract and full-text screening, data abstraction, and risk of bias appraisal were carried out by single reviewers.Results54 studies were included in the review: three controlled trials, 10 cohort studies, seven retrospective medical record/database studies, and 34 case reports or series. These studies included patients with severe acute respiratory syndrome (SARs, n=33), middle east respiratory syndrome (MERS, n=16), COVID-19 (n=3), and unspecified coronavirus (n=2). The most common treatment was ribavirin (n=41), followed by oseltamivir (n=10) and the combination of lopinavir/ritonavir (n=7). Additional therapies included broad spectrum antibiotics (n=30), steroids (n=39) or various interferons (n=12). No eligible studies examining monoclonal antibodies for COVID-19 were identified. One trial found that ribavirin prophylactic treatment statistically significantly reduced risk of MERS infection in people who had been exposed to the virus. Of the 21 studies reporting rates of ICU admission in hospitalized SARS or MERS patients, none reported statistically significant results in favour of or against antiviral therapies. Of the 40 studies reporting mortality rates in hospitalized SARS or MERS patients, one cohort study (MERS) and one retrospective study (SARS) found a statistically significant increase in the mortality rate for patients treated with ribavirin. Eighteen studies reported potential drug-related adverse effects including gastrointestinal symptoms, anemia, and altered liver function in patients receiving ribavirin.ConclusionThe current evidence for the effectiveness and safety of antiviral therapies for coronavirus is inconclusive and suffers from a lack of well-designed prospective trials or observational studies, preventing any treatment recommendations from being made. However, it is clear that the existing body of evidence is weighted heavily towards ribavirin (41/54 studies), which has not shown conclusive evidence of effectiveness and may cause harmful adverse events so future investigations may consider focusing on other candidates for antiviral therapy.
Role of meteorological temperature and relative humidity in the January-February 2020 propagation of 2019-nCoV in Wuhan, China
Authors: Alvarez-Ramirez Jose , Meraz Monica 
Published: March 2020

AbstractIdentified in December 2019, the 2019-nCoV emerged in Wuhan, China, and its spread increased rapidly, with cases arising across Mainland China and several other countries. By January 2020, the potential risks imposed by 2019-nCoV in human health and economical activity were promptly highlighted. Considerable efforts have been devoted for understanding the transmission mechanisms aimed to pursue public policies oriented to mitigate the number of infected and deaths. An important question requiring some attention is the role of meteorological variables (e.g., temperature and humidity) in the 2019-nCoV transmission. Correlations between meteorological temperature and relative humidity with the number of daily confirmed cases were explored in this work for the epicenter city of Wuhan, China for the period from 29 January to March 6, 2020. Long-term trend of temperature and relative humidity was obtained with a 14-days adjacent-averaging filter, and lagged correlations of the number of daily confirmed cases were explored. The analysis showed negative correlations between temperatures with the number of daily confirmed cases. Maximum correlations were found for 6-day lagged temperatures, which is likely reflecting the incubation period of the virus. It was postulated that the indoor crowding effect is responsible of the high incidence of 2019-nCoV cases, where low absolute humidity and close human contact facilitate the transport of aerosol droplets.
Scalable Surrogate Deconvolution for Identification of Partially-Observable Systems and Brain Modeling
Authors: Singh Matthew F. , Wang Anxu , Braver Todd S. , Ching ShiNung 
Published: March 2020

AbstractFor many biophysical systems, direct measurement of all state-variables,in – vivois not-feasible. Thus, a key challenge in biological modeling and signal processing is to reconstruct the activity and structure of interesting biological systems from indirect measurements. These measurements are often generated by approximately linear time-invariant (LTI) dynamical interactions with the hidden system and may therefore be described as a convolution of hidden state-variables with an unknown kernel. In the current work, we present an approach termed surrogate deconvolution, to directly identify such coupled systems (i.e. parameterize models). Surrogate deconvolution reframes certain nonlinear partially-observable identification problems, which are common in neuroscience/biology, as analytical objectives that are compatible with almost any user-chosen optimization procedure. We show that the proposed technique is highly scalable, low in computational complexity, and performs competitively with the current gold-standard in partially-observable system estimation: the joint Kalman Filters (Unscented and Extended). We show the benefits of surrogate deconvolution for model identification when applied to simulations of the Local Field Potential and blood oxygen level dependent (BOLD) signal. Lastly, we demonstrate the empirical stability of Hemodynamic Response Function (HRF) kernel estimates for Mesoscale Individualized NeuroDynamic (MINDy) models of individual human brains. The recovered HRF parameters demonstrate reliable individual variation as well as a stereotyped spatial distribution, on average. These results demonstrate that surrogate deconvolution promises to enhance brain-modeling approaches by simultaneously and rapidly fitting large-scale models of brain networks and the physiological processes which generate neuroscientific measurements (e.g. hemodynamics for BOLD fMRI).
Estimating the reproduction number of COVID-19 in Iran using epidemic modeling
Authors: Sahafizadeh Ebrahim , Sartoli Samaneh 
Published: March 2020

AbstractBackgroundAs reported by Iranian governments, the first cases of coronavirus (COVID-19) infections confirmed in Qom, Iran on February 19, 2020 (30 Bahman 1398). The number of identified cases afterward increased rapidly and the novel coronavirus spread to all provinces of the country. This study aimed to fit an epidemic model to the reported cases data to estimate the basic reproduction number (R0) of COVID-19 in Iran.MethodsWe used data from February 21, 2020, to April 21, 2020, on the number of cases reported by Iranian governments and we employed the SIR (Susceptible-Infectious-Removed) epidemic spreading model to fit the transmission model to the reported cases data by tuning the parameters in order to estimate the basic reproduction number of COVID-19 in Iran.ResultsThe value of reproduction number was estimated 4.86 in the first week and 4.5 in the second week. it decreased from 4.29 to 2.37 in the next four weeks. At the seventh week of the outbreak the reproduction number was reduced below one.ConclusionsThe results indicate that the basic reproduction number of COVID-19 was significantly larger than one in the early stages of the outbreak. However, implementing social distancing and preventing travelling on Nowruz (Persian New Year) effectively reduced the reproduction number. Although the results indicate that reproduction number is below one, it is necessary to continue social distancing and control travelling to prevent causing a second wave of outbreak.
Effectiveness and cost-effectiveness of public health measures to control COVID-19: a modelling study
Authors: Wang Qiang , Shi Naiyang , Huang Jinxin , Cui Tingting , Yang Liuqing , Ai Jing , Ji Hong , Xu Ke , Ahmad Tauseef , Bao Changjun , Jin Hui 
Published: March 2020

AbstractBackgroundThe Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first reported in China, which caused a respiratory disease known as Coronavirus Disease 2019 (COVID-19). Since its discovery, the virus has spread to over 160 countries and claimed more than 9800 deaths. This study aimed to assess the effectiveness and cost-effectiveness of various response public health measures.MethodsThe stochastic agent-based model was used to simulate the process of COVID-19 outbreak in scenario I (imported one case) and II (imported four cases) with a series of public health measures, involving the personal protection, isolation-and-quarantine, gathering restriction, and community containment. The virtual community was constructed following the susceptible-latent-infectious-recovered framework. The epidemiological and economic parameters derived from the previous literature and field investigation. The main outcomes included avoided infectors, cost-effectiveness ratios (CERs), and incremental cost-effectiveness ratios (ICERs). The sensitivity analyses were undertaken to assess uncertainty.ResultsIn scenario I and II, the isolation-and-quarantine averted 1696 and 1990 humans infected respectively at the cost of US$12 428 and US$58 555, both with negative value of ICERs. The joint strategy of personal protection and isolation-and-quarantine could avert one more case than single isolation-and-quarantine with additional cost of US$166 871 and US$180 140 respectively. The effectiveness of isolation-and-quarantine decreased as lowering quarantine probability and increasing delay-time. Especially in scenario II, when the quarantine probability was less than 25%, the number of infections raised sharply; when the quarantine delay-time reached six days, more than a quarter of individuals would be infected in the community. The strategy including community containment could protect more lives and was cost-effective, when the number of imported cases was no less than 65, or the delay-time of quarantine was more than five days, or the quarantine probability was below 25%, based on current assumptions.ConclusionsThe isolation-and-quarantine was the most cost-effective intervention. However, personal protection and isolation-and-quarantine was the optimal strategy averting more infectors than single isolation-and-quarantine. Certain restrictions should be considered, such as more initial imported cases, longer quarantine delay-time and lower quarantine probability.
Modelling the Potential Health Impact of the COVID-19 Pandemic on a Hypothetical European Country
Authors: Wilson Nick , Barnard Lucy Telfar , Kvalsvig Amanda , Verrall Ayesha , Baker Michael , Schwehm Markus 
Published: March 2020

AbstractA SEIR simulation model for the COVID-19 pandemic was developed (http://covidsim.eu) and applied to a hypothetical European country of 10 million population. Our results show which interventions potentially push the epidemic peak into the subsequent year (when vaccinations may be available) or which fail. Different levels of control (via contact reduction) resulted in 22% to 63% of the population sick, 0.2% to 0.6% hospitalised, and 0.07% to 0.28% dead (n=6,450 to 28,228).