bluuebunny/crossref_metadata_2025 huggingface dataset:
When everything changes at once: finding a new normal after genome duplication
Authors: Bomblies Kirsten
Published: November 2020

Whole-genome duplication (WGD), which leads to polyploidy, is implicated in adaptation and speciation. But what are the immediate effects of WGD and how do newly polyploid lineages adapt to them? With many studies of new and evolved polyploids now available, along with studies of genes under selection in polyploids, we are in an increasingly good position to understand how polyploidy generates novelty. Here, I will review consistent effects of WGD on the biology of plants, such as an increase in cell size, increased stress tolerance and more. I will discuss how a change in something as fundamental as cell size can challenge the function of some cell types in particular. I will also discuss what we have learned about the short- to medium-term evolutionary response to WGD. It is now clear that some of this evolutionary response may ‘lock in’ traits that happen to be beneficial, while in other cases, it might be more of an ‘emergency response’ to work around physiological changes that are either deleterious, or cannot be undone in the polyploid context. Yet, other traits may return rapidly to a diploid-like state. Polyploids may, by re-jigging many inter-related processes, find a new, conditionally adaptive, normal.
Plasmids shape the diverse accessory resistomes of Escherichia coli ST131
Authors: Decano Arun Gonzales , Tran Nghia , Al-Foori Hawriya , Al-Awadi Buthaina , Campbell Leigh , Ellison Kevin , Mirabueno Louisse Paolo , Nelson Maddy , Power Shane , Smith Genevieve , Smyth Cian , Vance Zoe , Woods Caitriona , Rahm Alexander , Downing Tim
Published: November 2020

The human gut microbiome includes beneficial, commensal and pathogenic bacteria that possess antimicrobial resistance (AMR) genes and exchange these predominantly through conjugative plasmids.

Escherichia coli

is a significant component of the gastrointestinal microbiome and is typically non-pathogenic in this niche. In contrast, extra-intestinal pathogenic

E. coli

(ExPEC) including ST131 may occupy other environments like the urinary tract or bloodstream where they express genes enabling AMR and host cell adhesion like type 1 fimbriae. The extent to which commensal

E. coli

and uropathogenic ExPEC ST131 share AMR genes remains understudied at a genomic level, and we examined this here using a preterm infant resistome. We found that individual ST131 had small differences in AMR gene content relative to a larger shared resistome. Comparisons with a range of plasmids common in ST131 showed that AMR gene composition was driven by conjugation, recombination and mobile genetic elements. Plasmid pEK499 had extended regions in most ST131 Clade C isolates, and it had evidence of a co-evolutionary signal based on protein-level interactions with chromosomal gene products, as did pEK204 that had a type IV fimbrial pil operon. ST131 possessed extensive diversity of selective type 1, type IV, P and F17-like fimbriae genes that was highest in subclade C2. The structure and composition of AMR genes, plasmids and fimbriae vary widely in ST131 Clade C and this may mediate pathogenicity and infection outcomes.
Remotididymella ageratinae sp. nov. and Remotididymella anemophila sp. nov., two novel species isolated from the invasive weed Ageratina adenophora in PR China
Authors: Yang Ai-Ling , Chen Lin , Fang Kai , Dong Xing-Fan , Li Yu-Xuan , Zhang Han-Bo , Yu Ze-Fen
Published: November 2020

To determine if Ageratina adenophora can accumulate diverse pathogens from surrounding native plants, we intensively sampled fungal communities, including endophytes, leaf spot pathogens and canopy air fungi, associated with Ag. adenophora as well as native plants in its invasive range. In total, we collected 4542 foliar fungal strains from 10 geographic sites, including 1340 from healthy leaves of Ag. adenophora, 2051 from leaf spots of Ag. adenophora and 1151 from leaf spots of 56 species of native plants and crops. Taxonomically, the common fungal genera included Colletotrichum, Diaporthe, Alternaria, Nemania, Xylaria, Neofusicoccum, Nigrospora, Epicoccum, Gibberella, Pestalotiopsis, Irpex, Schizophyllum and Clonostachys. We also isolated the cultivable fungi from 12 air samples collected from six areas in Yunnan Province, PR China. Among the total of 1255 air fungal isolates, the most common genera were Cladosporium, Trichoderma and Epicoccum. Among them, two new Remotididymella species, Remotididymella ageratinae from leaf spot of Ag. adenophora and Remotididymella anemophila from canopy air of Ag. adenophora were found. The two species showed both asexual and sexual reproductive structures. The conidia of R. ageratinae and R. anemophila are larger than those of R. anthropophila and R. destructiva. The size of ascospores of R. ageratinae and R. anemophila also differ from R. bauhiniae. Phylogenetic analysis of the combined ITS, LSU rRNA, rpb2 and tub2 sequences showed that R. ageratinae and R. anemophila each formed a distinct clade, separated from all species previously described in Remotididymella and confirmed them as new species belonging to Remotididymella. Full descriptions of R. ageratinae and R. anemophila are provided in this study.
The origin and past demography of murine astrovirus 1 in laboratory mice
Authors: Su Chia-Ming , Cheng Ying-Chien , Wang Hurng-Yi , Hsieh Chia-Hung , Wan Cho-Hua
Published: November 2020

Astroviruses are non-enveloped, positive-sense, ssRNA viruses and often associated with gastrointestinal diseases. Murine astrovirus (MuAstV) was first confirmed in a laboratory mouse colony in 2011. Although infected mice do not present significant clinical symptoms, the virus might interfere with research results. A recent surveillance has shown that MuAstV is highly prevalent in laboratory mice. The aims of the present study were to identify and characterize MuAstV strains as well as to investigate the prevalence rate of viral RNA in laboratory mice in Taiwan, and to estimate the origin and past population demography of MuAstVs. Based on molecular surveillance, MuAstV RNA was detected in 45.7 % of laboratory mice (48/105) from seven of nine colonies. Three fully sequenced MuAstV strains, MuAstV TW1, TW2 and TW3, exhibited 89.1−94.4 % and 89.1–90.0 % nucleotide identities with the reference strains MuAstV STL1 and STL2, respectively. Phylogenetic analyses of the partial regions of the RNA-dependent RNA polymerase (RdRp) and capsid protein (CP) genes of 18 Taiwan strains along with other astroviruses revealed that there are three distinct lineages of mouse astrovirus, MuAstV1, MuAstV2 and mouse astrovirus JF755422. The mutation rates of MuAstV1 were 2.6×10−4 and 6.2×10−4 substitutions/site/year for the RdRp and CP regions, respectively. Based on the above molecular clock, the colonization of MuAstV1 in laboratory mice was between 1897 and 1912, in good agreement with the establishment of ‘modern’ laboratory mouse facilities. Since its initial infection, the population size of MuAstV1 has increased 15–60-fold, probably consistent with the increased use of laboratory mice. In conclusion, MuAstV1 has been associated with modern laboratory mice since the beginning, and its influence on research results may require further investigation.
Paediatric bacterial meningitis in the USA: outcomes and healthcare resource utilization of nosocomial versus community-acquired infection
Authors: Adil Syed M. , Hodges Sarah E. , Charalambous Lefko T. , Kiyani Musa , Liu Beiyu , Lee Hui-Jie , Parente Beth A. , Perfect John R. , Lad Shivanand P.
Published: November 2020

Introduction. Paediatric bacterial meningitis remains a costly disease, both financially and clinically.

Hypothesis/Gap Statement. Previous epidemiological and cost studies of bacterial meningitis (BM) have largely focused on adult populations or single pathogens. There have been few recent, large-scale studies of pediatric BM in the USA.

Aim. We examined healthcare resource utilization (HCRU) and associated morbidity and mortality of community-acquired versus nosocomial bacterial infections in children across the USA.

Methodology. The IBM MarketScan Research databases were used to identify patients <18 years old admitted to USA hospitals from 2008 to 2015 with a primary diagnosis of BM. Cases were categorized as either community-acquired or nosocomial. HCRU, post-diagnosis neurosurgical procedures, 30-day in-hospital mortality, and complications were compared between groups. Multivariable regression adjusted for sex, age and Gram staining was used to compare costs of nosocomial versus community-acquired infections over time.

Results. We identified 1928 cases of paediatric BM without prior head trauma or neurological/systemic complications. Of these, 15.4 % were nosocomial and 84.6 % were community-acquired infections. After diagnostic lumbar puncture (37.1 %), the most common neurosurgical procedure was placement of ventricular catheter (12.6 %). The 30-day complication rates for nosocomial and community-acquired infections were 40.5 and 45.9 %, respectively. The most common complications were hydrocephalus (20.8 %), intracranial abscess (8.8 %) and cerebral oedema (8.1 %). The 30-day in-hospital mortality rates for nosocomial and community-acquired infections were 2.7 and 2.8 %, respectively.

Median length of admission was 14.0 days (Q1: 7 days, Q3: 26 days). Median 90-day cost was $40 861 (Q1: $11 988, Q3: $114,499) for the nosocomial group and $56 569 (Q1: $26 127, Q3: $142 780) for the community-acquired group. In multivariable regression, the 90-day post-diagnosis total costs were comparable between groups (cost ratio: 0.89; 95 % CI: 0.70 to 1.13), but at 2 years post-diagnosis, the nosocomial group was associated with 137 % higher costs (CR: 2.37, 95 % CI: 1.51 to 3.70).

Conclusion. In multivariable analysis, nosocomial infections were associated with significantly higher long-term costs up to 2 years post-infection. Hydrocephalus, intracranial epidural abscess and cerebral oedema were the most common complications, and lumbar punctures and ventricular catheter placement were the most common neurosurgical procedures. This study represents the first nation-wide, longitudinal comparison of the outcomes and considerable HCRU of nosocomial versus community-acquired paediatric BM, including characterization of complications and procedures contributing to the high costs of these infections.
Hogwash: three methods for genome-wide association studies in bacteria
Authors: Saund Katie , Snitkin Evan S.
Published: November 2020

Bacterial genome-wide association studies (bGWAS) capture associations between genomic variation and phenotypic variation. Convergence-based bGWAS methods identify genomic mutations that occur independently multiple times on the phylogenetic tree in the presence of phenotypic variation more often than is expected by chance. This work introduces hogwash, an open source R package that implements three algorithms for convergence-based bGWAS. Hogwash additionally contains two burden testing approaches to perform gene or pathway analysis to improve power and increase convergence detection for related but weakly penetrant genotypes. To identify optimal use cases, we applied hogwash to data simulated with a variety of phylogenetic signals and convergence distributions. These simulated data are publicly available and contain the relevant metadata regarding convergence and phylogenetic signal for each phenotype and genotype. Hogwash is available for download from GitHub.
Genomic analysis of trimethoprim-resistant extraintestinal pathogenic Escherichia coli and recurrent urinary tract infections
Authors: Li Dmitriy , Reid Cameron J. , Kudinha Timothy , Jarocki Veronica M. , Djordjevic Steven P.
Published: November 2020

Urinary tract infections (UTIs) are the most common bacterial infections requiring medical attention and a leading justification for antibiotic prescription. Trimethoprim is prescribed empirically for uncomplicated cases. UTIs are primarily caused by extraintestinal pathogenic

Escherichia coli

(ExPEC) and ExPEC strains play a central role in disseminating antimicrobial-resistance genes worldwide. Here, we describe the whole-genome sequences of trimethoprim-resistant ExPEC and/or ExPEC from recurrent UTIs (67 in total) from patients attending a regional Australian hospital from 2006 to 2008. Twenty-three sequence types (STs) were observed, with ST131 predominating (28 %), then ST69 and ST73 (both 7 %). Co-occurrence of trimethoprim-resistance genes with genes conferring resistance to extended-spectrum β-lactams, heavy metals and quaternary ammonium ions was a feature of the ExPEC described here. Seven trimethoprim-resistance genes were identified, most commonly dfrA17 (38 %) and dfrA12 (18 %). An uncommon dfrB4 variant was also observed. Two blaCTX-M
variants were identified – blaCTX-M-15
(16 %) and blaCTX-M-14
(10 %). The former was always associated with dfrA12, the latter with dfrA17, and all blaCTX-M
genes co-occurred with chromate-resistance gene chrA. Eighteen class 1 integron structures were characterized, and chrA featured in eight structures; dfrA genes featured in seventeen. ST131 H30Rx isolates possessed distinct antimicrobial gene profiles comprising aac(3)-IIa, aac(6)-Ib-cr, aph(3′)-Ia, aadA2, blaCTX-M-15
, blaOXA-1 and dfrA12. The most common virulence-associated genes (VAGs) were fimH, fyuA, irp2 and sitA (all 91 %). Virulence profile clustering showed ST131 H30 isolates carried similar VAGs to ST73, ST405, ST550 and ST1193 isolates. The sole ST131 H27 isolate carried molecular predictors of enteroaggregative

E. coli

/ExPEC hybrid strains (aatA, aggR, fyuA). Seven isolates (10 %) carried VAGs suggesting ColV plasmid carriage. Finally, SNP analysis of serial UTI patients experiencing worsening sequelae demonstrated a high proportion of point mutations in virulence factors.
Comprehensive genome analyses of Sellimonas intestinalis, a potential biomarker of homeostasis gut recovery
Authors: Muñoz Marina , Guerrero-Araya Enzo , Cortés-Tapia Catalina , Plaza-Garrido Angela , Lawley Trevor D. , Paredes-Sabja Daniel
Published: November 2020

Sellimonas intestinalis

is a Gram-positive and anaerobic bacterial species previously considered as uncultivable. Although little is known about this

Lachnospiraceae

family member, its increased abundance has been reported in patients who have recovered from intestinal homeostasis after dysbiosis events. In this context, the aim of the present study was to take advantage of a massive in vitro culture protocol that allowed the recovery of extremely oxygen-sensitive species from faecal samples, which led to isolation of

S. intestinalis

. Whole genome analyses of 11 

S

.

intestinalis

genomes revealed that this species has a highly conserved genome with 99.7 % 16S rRNA gene sequence similarity, average nucleotide polymorphism results >95, and 50.1 % of its coding potential being part of the core genome. Despite this, the variable portion of its genome was informative enough to reveal the existence of three lineages (lineage-I including isolates from Chile and France, lineage-II from South Korea and Finland, and lineage-III from China and one isolate from the USA) and evidence of some recombination signals. The identification of a cluster of orthologous groups revealed a high number of genes involved in metabolism, including amino acid and carbohydrate transport as well as energy production and conversion, which matches with the metabolic profile previously reported for microbiota from healthy individuals. Additionally, virulence factors and antimicrobial resistance genes were found (mainly in lineage-III), which could favour their survival during antibiotic-induced dysbiosis. These findings provide the basis of knowledge about the potential of

S. intestinalis

as a bioindicator of intestinal homeostasis recovery and contribute to advancing the characterization of gut microbiota members with beneficial potential.
Central and peripheral nervous system complications of COVID-19: A prospective tertiary center cohort with 3-month follow-up
Authors: Nersesjan Vardan , Amiri Moshgan , Lebech Anne-Mette , Roed Casper , Mens Helene , Russel Lene , Fonsmark Lise , Berntsen Marianne , Sigurdsson Sigurdur Thor , Carlsen Jonathan , Langkilde Annika , Martens Pernille , Løbner Lund Eva , Hansen Klaus , Jespersen Bo , Folke Marie Norsker , Meden Per , Hejl Anne-Mette , Wamberg Christian , Benros Michael E. , Kondziella Daniel
Published: November 2020

Objective

To systematically describe CNS and PNS complications in hospitalized COVID-19 patients.

Methods

We conducted a prospective, consecutive, observational study of adult patients from a tertiary referral center with confirmed COVID-19. All patients were screened daily for neurological and neuropsychiatric symptoms during admission, at discharge and at 3-month follow-up. We classified complications as caused by SARS-CoV-2 neurotropism, immune-mediated or critical illness-related.

Results

From April-September 2020, we enrolled 61 consecutively admitted COVID-19 patients, 35 (57%) of whom were referred to ICU for respiratory failure. Evaluation revealed a higher frequency of CNS/PNS symptoms in ICU patients compared to non-ICU patients. The most common CNS complication was encephalopathy (n=22, 36.1%), which was severe in 13 patients (GCS≤12), including 8 with akinetic mutism. Length of ICU admission was an independent predictor of encephalopathy (OR=1.23). Other CNS complications included ischemic stroke, a biopsy-proven acute necrotizing encephalitis, and transverse myelitis. The most common PNS complication was critical illness polyneuromyopathy (13.1%), with prolonged ICU stay as independent predictor (OR=1.14). Treatment-related PNS complications included meralgia paresthetica. Of 41 complications in total, 3 were classified as para/post-infectious. The remainder included cases secondary to critical illness or other causes (n=34) or without sufficient investigations (n=4). Cerebrospinal fluid was negative for SARS-CoV-2 RNA in all 5 patients investigated.

Conclusions

CNS/PNS complications were common in hospitalized COVID-19 patients, particularly in ICU patients, and often attributable to critical illness. In cases with COVID-19 as the primary cause for neurological disease, there were no signs of viral neurotropism, but laboratory changes suggested autoimmune-mediated mechanisms.
A Predictive Internet-Based Model for COVID-19 Hospitalization Census
Authors: Turk Philip , Tran Thao , Rose Geoff , McWilliams Andy
Published: November 2020

The COVID-19 pandemic has strained hospital resources and necessitated the need for predictive models to forecast patient care demands in order to allow for adequate staffing and resource allocation. Recently, other studies have looked at associations between Google Trends data and the number of COVID-19 cases. Expanding on this approach, we propose a vector error correction model (VECM) for the number of COVID-19 patients in a healthcare system (Census) that incorporates Google search term activity and healthcare chatbot scores. The VECM provided a good fit to Census and very good forecasting performance as assessed by hypothesis tests and mean absolute percentage prediction error. Although our study and model have limitations, we have conducted a broad and insightful search for candidate Internet variables and employed rigorous statistical methods. We have demonstrated the VECM can potentially be a valuable component to a COVID-19 surveillance program in a healthcare system.
LoopDetect: Comprehensive feedback loop detection in ordinary differential equation models
Authors: Baum Katharina , Wolf Jana
Published: November 2020

The dynamics of ordinary differential equation (ODE) models strongly depend on the model structure, in particular the existence of positive and negative feedback loops. LoopDetect offers user-friendly detection of all feedback loops in ODE models in three programming languages frequently used to solve and analyze them: MATLAB, Python, and R. The developed toolset accounts for user-defined model parametrizations and states of the modelled variables and supports feedback loop detection over ranges of values. It generates output in an easily adaptable format for further investigation.

Availability and Implementation

LoopDetect is implemented in R, Python 3 and MATLAB. It is freely available athttps://cran.r-project.org/web/packages/LoopDetectR/,https://pypi.org/project/loopdetect/,https://de.mathworks.com/matlabcentral/fileexchange/81928-loopdetect/(GPLv3 or BSD license).

Contact

katharina.baum@hpi.de
The impact of the coronavirus disease 2019 (COVID-19) outbreak on hospital admissions for alcohol-related liver disease and pancreatitis in Japan: a time-series analysis
Authors: Itoshima Hisashi , Shin Jung-ho , Takada Daisuke , Morishita Tetsuji , Kunisawa Susumu , Imanaka Yuichi
Published: November 2020

Background

During the coronavirus disease 2019 (COVID-19) pandemic, there have been health concerns related to alcohol use and misuse. Therefore, the World Health Organization cautioned that alcohol consumption during the pandemic might have a negative impact. The aim of this study was to examine the population-level change in cases of alcohol-related liver disease and pancreatitis that required admission during the COVID-19 outbreak.

Methods

We included patients aged 18 years or older who were hospitalized between July 2018 and June 2020 using Diagnostic Procedure Combination data, an administrative database in Japan, and counted the admission cases whose primary diagnosis was alcohol-related liver disease or pancreatitis. We defined the period from April 2020, when the Japanese government declared a state of emergency, as the beginning of the COVID-19 outbreak. The rate ratio (RR) of admissions with alcohol-related liver disease or pancreatitis per 1,000 admissions was tested using interrupted time series analysis. In addition, excess admissions for alcohol-related liver disease or pancreatitis were calculated.

Results

Overall admissions were 3,026,389 cases, and a total of 10,242 admissions for alcohol-related liver disease or pancreatitis occurred from 257 hospitals. The rate of admissions per 1,000 admissions during the COVID-19 outbreak period (April 2020 to June 2020) had a 1.2 times increase compared with the pre-outbreak period (July 2018 to March 2020) for cases of alcohol-related liver disease or pancreatitis (RR: 1.22, 95%Confidence interval [CI]: 1.12 to 1.33). The COVID-19 pandemic caused about 214.75 (95%CI: 178.78 to 249.72) excess admissions for alcohol-related liver disease or pancreatitis based on predictions from our model.

Conclusion

The COVID-19 outbreak might have resulted in increased hospital admissions for alcohol-related liver disease or pancreatitis.
Removing weekly administrative noise in the daily count of COVID-19 new cases. Application to the computation of Rt
Authors: Alvarez Luis , Colom Miguel , Morel Jean-Michel
Published: November 2020

The way each country counts and reports the incident cases of SARS-CoV-2 infections is strongly affected by the “weekend effect”. During the weekend, fewer tests are carried out and there is a delay in the registration of cases. This introduces an “administrative noise” that can strongly disturb the calculation of trend estimators such as the effective reproduction numberR(t). In this work we propose a procedure to correct the incidence curve and obtain a better fit between the number of infected and the one expected using the renewal equation. The classic way to deal with the administrative noise is to invoke its weekly period and therefore to filter the incidence curve by a seven days sliding mean. Yet this has three drawbacks: the first one is a loss of resolution. The second one is that a 7-day mean filter hinders the estimate of the effective reproduction numberR(t) in the last three days before present. The third drawback of a mean filter is that it implicitly assumes the administrative noise to be additive and time invariant. The present study supports the idea that the administrative is better dealt with as being both periodic and multiplicative. The simple method that derives from these assumptions amount to multiplying the number of infected by a correcting factor which depends on the day of the week. This correcting factor is estimated from the incidence curve itself. The validity of the method is demonstrated by its positive impact on the accuracy of an the estimates ofR(t). To exemplify the advantages of the multiplicative periodic correction, we apply it to Sweden, Germany, France and Spain. We observe that the estimated administrative noise is country dependent, and that the proposed strategy manages to reduce it noise considerably. An implementation of this technique is available atwww.ipol.im/ern, where it can be tested on the daily incidence curves of an extensive list of states and geographic areas provided by the European Centre for Disease Prevention and Control.
Globally Local: Hyper-local Modeling for Accurate Forecast of COVID-19
Authors: Gopalakrishnan Vishrawas , Pethe Sayali , Kefayati Sarah , Srinivasan Raman , Hake Paul , Deshpande Ajay , Liu Xuan , Hoang Etter , Davila Marbelly , Bianco Simone , Kaufman James H.
Published: November 2020

Multiple efforts to model the epidemiology of SARS-CoV-2 have recently been launched in support of public health response at the national, state, and county levels. While the pandemic is global, the dynamics of this infectious disease varies with geography, local policies, and local variations in demographics. An underlying assumption of most infectious disease compartment modeling is that of a well mixed population at the resolution of the areas being modeled. The implicit need to model at fine spatial resolution is impeded by the quality of ground truth data for fine scale administrative subdivisions. To understand the trade-offs and benefits of such modeling as a function of scale, we compare the predictive performance of a SARS-CoV-2 modeling at the county, county cluster, and state level for the entire United States. Our results demonstrate that accurate prediction at the county level requires hyper-local modeling with county resolution. State level modeling does not accurately predict community spread in smaller sub-regions because state populations are not well mixed, resulting in large prediction errors. As an important use case, leveraging high resolution modeling with public health data and admissions data from Hillsborough County Florida, we performed weekly forecasts of both hospital admission and ICU bed demand for the county. The repeated forecasts between March and August 2020 were used to develop accurate resource allocation plans for Tampa General Hospital.

2010 MSC

92-D30, 91-C20
Adverse effects of remdesivir, hydroxychloroquine, and lopinavir/ritonavir when used for COVID-19: systematic review and meta-analysis of randomized trials
Authors: Izcovich Ariel , Siemieniuk Reed AC , Bartoszko Jessica J , Ge Long , Zeraatkar Dena , Kum Elena , Khamis Assem M. , Rochwerg Bram , Agoritsas Thomas , Chu Derek K , McLeod Shelley L , Mustafa Reem A , Vandvik Per O , Brignardello-Petersen Romina
Published: November 2020

Introduction

In an attempt to improve outcomes for patients with coronavirus disease 19 (COVID-19), several drugs, such as remdesivir, hydroxychloroquine (with or without azithromycin), and lopinavir/ritonavir, have been evaluated for treatment. While much attention focuses on potential benefits of these drugs, this must be weighed against their adverse effects.

Methods

We searched 32 databases in multiple languages from 1 December 2019 to 27 October 2020. We included randomized trials if they compared any of the drugs of interest to placebo or standard care, or against each other. A related world health organization (WHO) guideline panel selected the interventions to address and identified possible adverse effects that might be important to patients. Pairs of reviewers independently extracted data and assessed risk of bias. We analyzed data using a fixed-effects pairwise meta-analysis and assessed the certainty of evidence using the GRADE approach.

Results

We included 16 randomized trials which enrolled 8226 patients. Compared to standard care or placebo, low certainty evidence suggests that remdesivir may not have an important effect on acute kidney injury (risk difference [RD] 8 fewer per 1000, 95% confidence interval (CI): 27 fewer to 21 more) or cognitive dysfunction/delirium (RD 3 more per 1000, 95% CI: 12 fewer to 19 more). Low certainty evidence suggests that hydroxychloroquine may increase the risk of serious cardiac toxicity (RD 10 more per 1000, 95% CI: 0 more to 30 more) and cognitive dysfunction/delirium (RD 33 more per 1000, 95% CI: 18 fewer to 84 more), whereas moderate certainty evidence suggests hydroxychloroquine probably increases the risk of diarrhoea (RD 106 more per 1000, 95% CI: 48 more to 175 more) and nausea and/or vomiting (RD 62 more per 1000, 95% CI: 23 more to 110 more) compared to standard care or placebo. Low certainty evidence suggests lopinavir/ritonavir may increase the risk of diarrhoea (RD 168 more per 1000, 95% CI: 58 more to 330 more) and nausea and/or vomiting (RD 160 more per 1000, 95% CI: 100 more to 210 more) compared to standard care or placebo.

Conclusion

Hydroxychloroquine probably increases the risk of diarrhoea and nausea and/or vomiting and may increase the risk of cardiac toxicity and cognitive dysfunction/delirium. Remdesivir may have no effect on risk of acute kidney injury or cognitive dysfunction/delirium. Lopinavir/ritonavir may increase the risk of diarrhoea and nausea and/or vomiting. These findings provide important information to support the development of evidence-based management strategies for patients with COVID-19.
Bifocal tACS Enhances Visual Motion Discrimination by Modulating Phase Amplitude Coupling Between V1 and V5 Regions
Authors: Salamanca-Giron Roberto F. , Raffin Estelle , Zandvliet Sarah Bernardina , Seeber Martin , Michel Christoph M. , Sauseng Paul , Huxlin Krystel R. , Hummel Friedhelm C.
Published: November 2020

Visual motion discrimination involves reciprocal interactions in the alpha band between the primary visual cortex (V1) and the mediotemporal area (V5/MT). We investigated whether modulating alpha phase synchronization using individualized multisite transcranial alternating current stimulation (tACS) over V5 and V1 regions would improve motion discrimination. We tested 3 groups of healthy subjects: 1) an individualized In-Phase V1alpha-V5alphatACS (0° lag) group, 2) an individualized Anti-Phase V1alpha-V5alphatACS (180° lag) group and 3) a sham tACS group. Motion discrimination and EEG activity were compared before, during and after tACS. Performance significantly improved in the Anti-Phase group compared to that in the In-Phase group at 10 and 30 minutes after stimulation. This result could be explained by changes in bottom-up alpha-V1 gamma-V5 phase-amplitude coupling. Thus, Anti-Phase V1alpha-V5alphatACS might impose an optimal phase lag between stimulation sites due to the inherent speed of wave propagation, hereby supporting optimized neuronal communication.

IMPACT STATEMENT

Alpha multisite (V1 and V5) tACS influences global motion discrimination and integration

Phase-amplitude coupling is associated with visual performance

Multisite Anti-Phase stimulation of strategic visual areas (V1 and V5) is associated with connectivity changes in the visual cortex and thus, associated with changes in direction acuity
Reinforcing neuron extraction and spike inference in calcium imaging using deep self-supervised learning
Authors: Li Xinyang , Zhang Guoxun , Wu Jiamin , Zhang Yuanlong , Zhao Zhifeng , Lin Xing , Qiao Hui , Xie Hao , Wang Haoqian , Fang Lu , Dai Qionghai
Published: November 2020

Calcium imaging is inherently susceptible to detection noise especially when imaging with high frame rate or under low excitation dosage. We developed DeepCAD, a self-supervised learning method for spatiotemporal enhancement of calcium imaging without requiring any high signal-to-noise ratio (SNR) observations. Using this method, detection noise can be effectively suppressed and the imaging SNR can be improved more than tenfold, which massively improves the accuracy of neuron extraction and spike inference and facilitate the functional analysis of neural circuits.
Photostimulation of lymphatic clearance of red blood cells from the mouse brain after intraventricular hemorrhage
Authors: Li Dong-Yu , Liu Shao-Jun , Yu Ting-Ting , Liu Zhang , Sun Si-Lin , Bragin Denis , Navolokin Nikita , Kurths Jürgen , Glushkovskaya-Semyachkina Oxana , Zhu Dan
Published: November 2020

Intraventricular hemorrhage (IVH) is the most fatal form of brain injury, yet a therapy directed at ameliorating intraventricular clot is very limited. There is accumulating evidence that an augmentation of the meningeal lymphatic (MLVs) functions might be a promising therapeutic target for IVH. In particular, the photostimulation (PS) of MLVs could be promising for non-invasive therapy of IVH via PS of clearance of red blood cells (RBCs) from the brain via MLVs. Indeed, we uncover that PS has therapeutic effects on IVH in mice reducing the mortality, improving the emotional status, accelerating the RBCs evacuation from the ventricles and increasing the ICP recovery. Our findings strongly suggest that the PS-mediated stimulation of drainage and clearing functions of MLVs can be a novel bedside, readily applicable and commercially viable technologies for treatment of IVH. These pilot results open new horizons in a non-invasive therapy of IVH via PS stimulation of regenerative lymphatic mechanisms.
MegaGO: a fast yet powerful approach to assess functional similarity across meta-omics data sets
Authors: Verschaffelt Pieter , Van Den Bossche Tim , Gabriel Wassim , Burdukiewicz Michał , Soggiu Alessio , Martens Lennart , Renard Bernhard Y. , Schiebenhoefer Henning , Mesuere Bart
Published: November 2020

The study of microbiomes has gained in importance over the past few years, and has led to the fields of metagenomics, metatranscriptomics and metaproteomics. While initially focused on the study of biodiversity within these communities the emphasis has increasingly shifted to the study of (changes in) the complete set of functions available in these communities. A key tool to study this functional complement of a microbiome is Gene Ontology (GO) term analysis. However, comparing large sets of GO terms is not an easy task due to the deeply branched nature of GO, which limits the utility of exact term matching. To solve this problem, we here present MegaGO, a user-friendly tool that relies on semantic similarity between GO terms to compute functional similarity between two data sets. MegaGO is highly performant: each set can contain thousands of GO terms, and results are calculated in a matter of seconds. MegaGO is available as a web application athttps://megago.ugent.beand installable via pip as a standalone command line tool and reusable software library. All code is open source under the MIT license, and is available athttps://github.com/MEGA-GO/.
The reward-complexity trade-off in schizophrenia
Authors: Gershman Samuel J. , Lai Lucy
Published: November 2020

Action selection requires a policy that maps states of the world to a distribution over actions. The amount of memory needed to specify the policy (the policy complexity) increases with the state-dependence of the policy. If there is a capacity limit for policy complexity, then there will also be a trade-off between reward and complexity, since some reward will need to be sacrificed in order to satisfy the capacity constraint. This paper empirically characterizes the trade-off between reward and complexity for both schizophrenia patients and healthy controls. Schizophrenia patients adopt lower complexity policies on average, and these policies are more strongly biased away from the optimal reward-complexity trade-off curve compared to healthy controls. How-ever, healthy controls are also biased away from the optimal trade-off curve, and both groups appear to lie on the same empirical trade-off curve. We explain these findings using a cost-sensitive actor-critic model. Our empirical and theoretical results shed new light on cognitive effort abnormalities in schizophrenia.
Tysserand - Fast and accurate reconstruction of spatial networks from bioimages
Authors: Coullomb Alexis , Pancaldi Vera
Published: November 2020

Networks provide a powerful framework to analyze spatial omics experiments. However, we lack tools that integrate several methods to easily reconstruct networks for further analyses with dedicated libraries. In addition, choosing the appropriate method and parameters can be challenging.

We proposetysserand, a Python library to reconstruct spatial networks from spatially resolved omics experiments. It is intended as a common tool to which the bioinformatics community can add new methods to reconstruct networks, choose appropriate parameters, clean resulting networks and pipe data to other libraries.

Availability and implementation

tysserandsoftware and tutorials with a Jupyter notebook to reproduce the results are available athttps://github.com/VeraPancaldiLab/tysserand

Supplementary information

Supplementary data are available atBioarxivonline.
Mandibular morphology, task specialization, and bite mechanics inPheidoleants (Hymenoptera: Formicidae)
Authors: Klunk C.L. , Argenta M.A. , Casadei-Ferreira A. , Economo E.P. , Pie M.R.
Published: November 2020

The remarkable ecological and evolutionary success of ants was associated with the evolution of reproductive division of labor, in which sterile workers perform most colony tasks whereas reproductives become specialized in reproduction. In some lineages, the worker force became further subdivided into morphologically distinct subcastes (e.g. minor vs. major workers), allowing for the differential performance of particular roles in the colony. However, the functional and ecological significance of morphological differences between subcastes is not well understood. Here, we applied Finite Element Analysis (FEA) to explore the functional differences between major and minor ant worker mandibles. Analyses were carried out on mandibles of twoPheidolespecies, a dimorphic ant genus. In particular, we test whether major mandibles evolved to minimize stress when compared to minors using combinations of tooth and masticatory margin bites under strike and pressure conditions. Majors performed better in pressure conditions yet, contrary to our expectations, minors performed better in strike bite scenarios. Moreover, we demonstrate that even small morphological differences in ant mandibles might lead to substantial differences in biomechanical responses to bite loading. These results also underscore the potential of FEA to uncover biomechanical consequences of morphological differences within and between ant worker castes.
Simplified and unified access to cancer proteogenomic data
Authors: Lindgren Caleb M. , Adams David W. , Kimball Benjamin , Boekweg Hannah , Tayler Sadie , Pugh Samuel L. , Payne Samuel H.
Published: November 2020

Comprehensive cancer datasets recently generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) offer great potential for advancing our understanding of how to combat cancer. These datasets include DNA, RNA, protein, and clinical characterization for tumor and normal samples from large cohorts in many different cancer types. The raw data are publicly available at various Cancer Research Data Commons. However, widespread re-use of these datasets is also facilitated by easy access to the processed quantitative data tables. We have created a Python package,cptac, which is a data API that distributes the finalized processed CPTAC datasets in a consistent, up-to-date format. This consistency makes it easy to integrate the data with common graphing, statistical, and machine learning packages for advanced analysis. Additionally, consistent formatting across all cancer types promotes the investigation of pan-cancer trends. The data API structure of directly streaming data within a programming environment enhances reproducibility. Finally, with the accompanying tutorials, this package provides a novel resource for cancer research education.
ION-Decoding: A Single-channel Interactive Offline Neural Decoding Algorithm for a large number of neurons
Authors: Rastegari Mohsen , Marateb Hamid Reza
Published: November 2020

Researchers have widely used extracellular recordings as a technique of paramount importance due to its wide usage in cognitive studies, health technologies, and prosthetics and orthotics research. To extract the required information from this technique, a critical and crucial step, called spike sorting, must be performed on the recorded signal. By this method, it is possible to analyze a single neuron (single-unit activity) and investigate its specifications, such as the firing rates and the number of action potentials (spikes) of an individual neuron. Here we introduce a novel idea of a user-friendly interactive, offline, and unsupervised algorithm called ION-Decoding. This platform extracts and aligns the spikes using a high-resolution alignment method, and the clusters can be atomically identified and manually edited. The entire procedure is performed using the minimum number of adjustable parameters, and cluster merging was performed in a smart, intuitive way. The ION-Decoding algorithm was evaluated by a benchmark dataset, including 95 simulations of two to twenty neurons from 10 minutes simulated extracellular recordings. There was not any significant relationship between the number of missed clusters with the quality of the signal (i.e., the signal-to-noise ratio (SNR)) by controlling the number of neurons in each signal (p_value=0.103). Moreover, the number of extra clusters was not significantly dependent on the parameter SNR (p_value=0.400). The accuracy of the classification method was significantly associated with the decomposability index (DI) (p_value<0.001). A number of 77% of the neurons with the DI higher than 20 had the classification accuracy higher than 80%. The ION-Decoding algorithm significantly outperformed Wave_Clus in terms of the number of hits (p_value=0.017). However, The Wave_Clus algorithm significantly outperformed the ION-Decoding algorithm when the false-positive error (FP) was considered (p_value=0.001). The ION-Decoding is thus a promising single-channel spike sorting algorithm. However, our future focuses on the improvement of the cluster representative identification and FP error reduction.
The gut bacteria of an invasive amphibian respond to the dual challenges of range-expansion and parasite attack
Authors: Zhou Jia , Nelson Tiffanie Maree , Rodriguez Lopez Carlos , Zhou Shao Jia , Ward-Fear Georgia , Stuart Katarina C. , Shine Richard , Rollins Lee Ann
Published: November 2020

Gut bacterial communities influence, and are influenced by, the behaviour and ecology of their hosts. Those interactions have been studied primarily in humans and model organisms, but we need field research to understand the relationship between an organism’s gut bacteria and its ecological challenges, such as those imposed by rapid range expansion (as in invasive species) and the presence of host-manipulating parasites. Cane toads (Rhinella marina) provide an excellent model system in this respect, because the species’ ongoing colonization of Australia has enforced major changes in phenotypic traits (including behaviour), and lungworm parasites (Rhabdias pseudosphaerocephala) modify host gut function in ways that enhance the viability of lungworm larvae. We collected female toads from across the species’ invasive range and studied their morphology, behaviour, parasite infection status and gut bacterial community. Range-coreversusrange-edge toads differed in morphology, behaviour, gut bacterial composition and predicted gut bacterial function but did not differ in the occurrence of parasite infection nor in the intensity of infection. Toads infected with lungworms differed from uninfected conspecifics in gut bacterial composition and diversity. Our study demonstrates strong associations between gut bacterial community and host ecology and behaviour.
Probing the aggregated effects of purifying selection per individual on 1,380 medical phenotypes in the UK biobank
Authors: Vy Ha My T. , Jordan Daniel M. , Balick Daniel J. , Do Ron
Published: November 2020

Understanding the relationship between natural selection and phenotypic variation has been a long-standing challenge in human population genetics. With the emergence of biobank-scale datasets, along with new statistical metrics to approximate strength of purifying selection at the variant level, it is now possible to correlate a proxy of individual relative fitness with a range of medical phenotypes. We calculated a per-individual deleterious load score by summing the total number of derived alleles per individual after incorporating a weight that approximates strength of purifying selection. We assessed four methods for the weight, including GERP, phyloP, CADD, and fitcons. By quantitatively tracking each of these scores with the site frequency spectrum, we identified phyloP as the most appropriate weight. The phyloP-weighted load score was then calculated across 15,129,142 variants in 335,161 individuals from the UK Biobank and tested for association on 1,380 medical phenotypes. After accounting for multiple test correction, we observed a strong association of the load score amongst coding sites only on 27 traits including body mass, adiposity and metabolic rate. We further observed that the association signals were driven by common variants (derived allele frequency > 5%) with high phyloP score (phyloP > 2). Finally, through permutation analyses, we showed that the load score amongst coding sites had an excess of nominally significant associations on many medical phenotypes. These results suggest a broad impact of deleterious load on medical phenotypes and highlight the deleterious load score as a tool to disentangle the complex relationship between natural selection and medical phenotypes.

Author summary

This study aims to augment our understanding between the complex relation between natural selection and human phenotypic variation. We developed a load score to approximate the relative fitness of an individual and correlate it with a set of medical phenotypes. Association tests between the load score amongst coding sites and 1,380 phenotypes in a sample of 335,161 individuals from the UK Biobank showed a strong association with 27 traits including body mass, adiposity and metabolic rate. Furthermore, an excess of nominal associations at suggestive levels was observed between the load score amongst coding sites and medical phenotypes than would be expected under a null model. These results suggest that the aggregate effect of deleterious mutations as measured by the load score has a broad effect on human phenotypes.