bluuebunny/crossref_metadata_2025 huggingface dataset:
An effect assessment of Airborne particulate matter pollution on COVID-19: A multi-city Study in China
Authors: Wang Bo , Liu Jiangtao , Fu Shihua , Xu Xiaocheng , Li Lanyu , Ma Yueling , Zhou Ji , Yaoc Jinxi , Liu Xingrong , Zhang Xiuxia , He Xiaotao , Yan Jun , Shi Yanjun , Ren Xiaowei , Niu Jingping , Luo Bin , zhang Kai
Published: April 2020

Objective

Coronavirus disease 2019 (COVID-19) is a serious infectious disease, which has caused great number of deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution on COVID-19 across China.

Methods

In this study, we obtained confirmed cases of COVID-19, the data of airborne ambient PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10), ambient temperature (AT), absolute humidity (AH) and migration scale index (MSI) in 72 cities of China (excluded Wuhan city) on a daily basis, each of which confirmed more than 50 cases from January 20th to March 2nd, 2020. We applied a two-stage analysis. Generalized additive models with quasi-Poisson distribution was first fitted to estimate city-specific effects of PM10 and PM2.5 on daily confirmed COVID-19 cases while controlling AT, AH and MSI. Then, we used meta-analysis to generate the pooled effect estimates from city-specific results.

Results

During the study period, there were a total of 24 939 COVID-19 cases, most of which were reported in Hubei Province. In our meta-analysis, we found each 10 μg/m3 increase in concentration of PM2.5 and PM10 in single day lag (from lag 0 to lag 7 and lag 14) were positively associated with confirmed cases of COVID-19, not including PM10 at lag 5, lag 6 and lag 7, and PM2.5 at lag 5, lag 6. Similar trend was also found in different cumulative lag days (from lag 01 to lag 07 and lag 014). The effects of PM2.5 and PM10 on daily COVID-19 confirmed cases are statistically significant for three cumulative lag periods over 3, 7 and 14 days with the greatest effect over 14 days. The estimated RRs of which were 1.64 (95% CIs: 1.47, 1.82) and 1.47 (95% CIs: 1.34, 1.61) with each 10 μg/m3 increase in concentrations of PM2.5 and PM10, respectively. In addition, we found that the effects of PM2.5 on daily confirmed cases were greater than PM10 in all included lag days.

Conclusions

This nationwide study suggests that airborne PM pollution likely increases the risk of getting COVID-19 in China.
Do latitude and ozone concentration predict Covid-2019 cases in 34 countries?
Authors: Alipio Mark M.
Published: April 2020

In this paper, I used multivariate linear regression analysis to determine if latitude and ozone concentration predict Covid-2019 cases in 34 countries worldwide. Data pertaining to Covid-2019 cases were extracted from Worldometer. Ozone concentration levels were taken from the open-access database of World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Latitude of specific area where measurement took place was also provided in the database. Preliminary Kendall rank correlation test revealed that Covid-2019 incidence was positively and significantly related to ozone concentration; however, incidence was not significantly related to latitude. Using multivariate linear regression, a statistically significant link between ozone concentration and Covid-2019 incidence in 34 countries was established; however, I found no statistical association between latitude and Covid-2019 incidence refuting previous claims. Prompt health actions should be developed for areas with high ozone concentration in the present and possibly, future outbreaks; however, extensive laboratory analysis should be conducted to further confirm the findings of the study. Nevertheless, the results of this study could serve as a basis for further clinical and large-scale studies.
A Simple Colorimetric Molecular Detection of Novel Coronavirus (COVID-19), an Essential Diagnostic Tool for Pandemic Screening
Authors: Annamalai Pazhanimuthu , Kanta Madhu , Ramu Pazhanivel , Ravi Baskar , Veerapandian Kokilavani , Srinivasan Rengarajan
Published: April 2020

The recent outbreak of the newly emerged novel coronavirus (SARS-CoV-2) presents a big challenge for public health laboratories as virus isolates are not available while there is an increasing evidence that the epidemic is more widespread than initially thought, as well as spreading internationally across borders through travellers does already happen warranting a methodology for the rapid detection of the infection to control SARS-CoV-2. Aim: We intended to develop and deploy a robust and rapid diagnostic methodology using LAMP assay for use in point of care settings to detect SARS-COV-2 infection. Methodology: In the present study, we have developed a validated rapid diagnostic procedure to detect SARS-CoV-2 using LAMP assay, its design relying on isothermal amplification of the nucleic acids of the SARS-CoV-2. Results: The LAMP assay developed detects SARS-CoV-2 infection rapidly with high sensitivity and reliability. The data generated by LAMP assay were comparable and at par with the data generated by real-time PCR method. Conclusion: The present study demonstrates that the LAMP assay developed was a rapid, reliable, sensitive and cost effective method to detect SARS-CoV-2 infection in a point of care as well as in laboratory settings.
Should contact bans be lifted in Germany? A quantitative prediction of its effects
Authors: Donsimoni Jean Roch , Glawion René , Plachter Bodo , Weiser Constantin , Wälde Klaus
Published: April 2020

Many countries consider the lifting of restrictions of social contacts (RSC). We quantify the effects of RSC for Germany. We initially employ a purely statistical approach to predicting prevalence of COVID19 if RSC were upheld after April 20. We employ these findings and feed them into our theoretical model. We find that the peak of the number of sick individuals would be reached already mid April. The number of sick individuals would fall below 1,000 at the beginning of July. When restrictions are lifted completely on April 20, the number of sick should rise quickly again from around April 27. A balance between economic and individual costs of RSC and public health objectives consists in lifting RSC for activities that have high economic benefits but low health costs. In the absence of large-scale representative testing of CoV-2 infections, these activities can most easily be identified if federal states of Germany adopted exit strategies that differ across states.
Probabilistic modelling of effects of antibiotics and calendar time on transmission of healthcare-associated infection
Authors: Laager Mirjam , Cooper Ben S , Eyre David W
Published: April 2020

Healthcare-associated infection and antimicrobial resistance are major concerns. However, the extent to which antibiotic exposure affects transmission and detection of infections such as MRSA is unclear. Additionally, temporal trends are typically reported in terms of changes in incidence, rather than analysing underling transmission processes. We present a data-augmented Markov chain Monte Carlo approach for inferring changing transmission parameters over time, screening test sensitivity, and the effect of antibiotics on detection and transmission. We expand a basic model to allow use of typing information when inferring sources of infections. Using simulated data, we show that the algorithms are accurate, well-calibrated and able to identify antibiotic effects in sufficiently large datasets. We apply the models to study MRSA transmission in an intensive care unit in Oxford, UK with 7924 admissions over 10 years. We find that falls in MRSA incidence over time were associated with decreases in both the number of patients admitted to the ICU colonised with MRSA and in transmission rates. In our inference model, the data were not informative about the effect of antibiotics on risk of transmission or acquisition of MRSA, a consequence of the limited number of possible transmission events in the data. Our approach has potential to be applied to a range of healthcare-associated infections and settings and could be applied to study the impact of other potential risk factors for transmission. Evidence generated could be used to direct infection control interventions.
Chaos, Percolation and the Coronavirus Spread: the Italian case
Authors: Bonasera Aldo , Bonasera G. , Zhang Suyalatu
Published: April 2020

A model based on chaotic maps and turbulent flows is applied to the spread of Coronavirus for each Italian region in order to obtain useful information and help to contrast it. We divide the regions into different risk categories and discuss anomalies. The worst cases are confined between the Appenine and the Alps mountain ranges but the situation seem to improve closer to the sea. The Veneto region gave the most efficient response so far and some of their resources could be diverted to other regions, in particular more tests to the Lombardia, Liguria, Piemonte, Marche and V. Aosta regions, which seem to be worst affected. We noticed worrying anomalies in the Lazio, Campania and Sicilia regions to be monitored. We stress that the number of fatalities we predicted on March 12 has been confirmed daily by the bulletins. This suggests a change of strategy in order to reduce such number maybe moving the weaker population (and negative to the virus test) to beach resorts, which should be empty presently. The ratio deceased/positives on April 4, 2020 is 5.4% worldwide, 12.3% in Italy, 1.4% in Germany, 2.7% in the USA, 10.3% in the UK and 4.1% in China. These large fluctuations should be investigated starting from the Italian regions, which show similar large fluctuations.
No evidence of clinical efficacy of hydroxychloroquine in patients hospitalised for COVID-19 infection and requiring oxygen: results of a study using routinely collected data to emulate a target trial
Authors: Mahévas Matthieu , Tran Viet-Thi , Roumier Mathilde , Chabrol Amélie , Paule Romain , Guillaud Constance , Gallien Sébastien , Lepeule Raphael , Szwebel Tali-Anne , Lescure Xavier , Schlemmer Frédéric , Matignon Marie , Khellaf Medhi , Crickx Etienne , Terrier Benjamin , Morbieu Caroline , Legendre Paul , Dang Julien , Schoindre Yoland , Pawlotski Jean-Michel , Michel Marc , Perrodeau Elodie , Carlier Nicolas , Roche Nicolas , de Lastours Victoire , Mouthon Luc , Audureau Etienne , Ravaud Philippe , Godeau Bertrand , Costedoat-Chalumeau Nathalie
Published: April 2020

Background

Treatments are urgently needed to prevent respiratory failure and deaths from coronavirus disease 2019 (COVID-19). Hydroxychloroquine (HCQ) has received worldwide attention because of positive results from small studies.

Methods

We used data collected from routine care of all adults in 4 French hospitals with documented SARS-CoV-2 pneumonia and requiring oxygen ≥ 2 L/min to emulate a target trial aimed at assessing the effectiveness of HCQ at 600 mg/day. The composite primary endpoint was transfer to intensive care unit (ICU) within 7 days from inclusion and/or death from any cause. Analyses were adjusted for confounding factors by inverse probability of treatment weighting.

Results

This study included 181 patients with SARS-CoV-2 pneumonia; 84 received HCQ within 48 hours of admission (HCQ group) and 97 did not (no-HCQ group). Initial severity was well balanced between the groups. In the weighted analysis, 20.2% patients in the HCQ group were transferred to the ICU or died within 7 days vs 22.1% in the no-HCQ group (16 vs 21 events, relative risk [RR] 0.91, 95% CI 0.47–1.80). In the HCQ group, 2.8% of the patients died within 7 days vs 4.6% in the no-HCQ group (3 vs 4 events, RR 0.61, 95% CI 0.13–2.89), and 27.4% and 24.1%, respectively, developed acute respiratory distress syndrome within 7 days (24 vs 23 events, RR 1.14, 95% CI 0.65–2.00). Eight patients receiving HCQ (9.5%) experienced electrocardiogram modifications requiring HCQ discontinuation.

Interpretation

These results do not support the use of HCQ in patients hospitalised for documented SARS-CoV-2-positive hypoxic pneumonia.
Risk Assesment of nCOVID-19 Pandemic In India: A Mathematical Model And Simulation
Authors: Biswas Swarnava , Mukherjee Moumita
Published: April 2020

The entire world is now eventually locked down due to the outbreak of nCOVID-19 corona virus outbreak. The fast and relentless spread nCOVID-19 has basically segmented the populace only into merely into three classes, such as susceptible, infected and recovered compartments. Adapting the classical SEIR-type epidemic modelling framework, the direct person-to-person contact transmission is taken as the direct route of transmission of nCOVID-19 pandemic. In this research, the authors have developed a model of the nation-wide trends of the outburst of the nCOVID-19 infection using an SEIR Model. The SEIR dynamics are expressed using ordinary differential equations. The creators initially determined the parameters of the model from the accessible day by day information for Indian States dependent on around 35 days history of diseases, recuperations and deaths. The determined parameters have been amassed to extend future patterns for the Indian subcontinent, which is right now at a beginning time in the contamination cycle. The novelty of the study lies in the prediction of both the pessimistic and optimistic mathematical model based comprehensive analysis of nCOVID-19 infection spreading, for two different conditions: (a) if lockdown gets withdrawn and (b) if lockdown continues as a whole. If the complete lockdown in India is withdrawn on 14th April 2020, as a whole, then from the simulation, the authors have predicted that the infected population will flare-up to a large extent, suddenly, however, gradual or zone specific withdrawal would be more effective solution. This study also suggested some possible way-out to get rid of this situation by providing a trade-off between ‘ flattening of the curve” as well as “less economic turbulence. The projections are intended to provide a base/ action plan for the socio-economic counter measures to alleviate nCOVID-19.
Antibiotic stewardship in premature infants: a systematic review
Authors: Rajar Polona , Saugstad Ola D. , Berild Dag , Dutta Anirban , Greisen Gorm , Lausten-Thomsen Ulrik , Mande Sharmila S. , Nangia Sushma , Petersen Fernanda C. , Dahle Ulf R. , Haaland Kirsti
Published: April 2020

Antibiotic treatment in premature infants is often empirically prescribed, and practice varies widely among otherwise comparable neonatal intensive care units. Unnecessary and prolonged antibiotic treatment is documented in numerous studies. Recent research shows serious side effects and suggests long-term adverse health effects in prematurely born infants exposed to antibiotics in early life. One preventive measure to reduce unnecessary antibiotic exposure is implementation of antibiotic stewardship programs. We reviewed the literature on implemented antibiotic stewardship programs focusing on premature infants. Six academic databases were systematically searched and eleven articles met inclusion criteria. Articles were grouped according to common area of stewardship actions; 1) Focus on reducing initiation of antibiotic therapy, 2) Focus on shortening duration of antibiotic therapy, 3) Various infrastructural stewardship implementations. The studies differed in their cohort composition and measured outcomes. We provide an overview of the reduction in antibiotic use achieved. Antibiotic stewardship programs are effective especially when they use a multifactorial approach and are tailored to premature infants. Implementation of antibiotic stewardship programs targeting premature infants should be considered in all neonatal intensive care units. The Norwegian Research Council (project number 273833) and the Olav Thon Foundation supported the study.
Potency and timing of antiviral therapy as determinants of duration of SARS CoV-2 shedding and intensity of inflammatory response
Authors: Goyal Ashish , Cardozo-Ojeda  , Fabian E. , Schiffer Joshua T.
Published: April 2020

Treatments are desperately needed to lower the hospitalization and case fatality rates of SARS CoV-2 infection. In order to meaningfully impact the COVID-19 pandemic, promising antiviral therapies must be identified within the next several months. However, the number of clinical trials that can be performed in this timeframe is limited. We therefore developed a mathematical model which allows projection of all possible therapeutic approaches. Our model recapitulates off-treatment viral dynamics and predicts a three-phase immune response. Addition of treatment with remdesivir, hydroxychloroquine, neutralizing antibodies or cellular immunotherapy demonstrates that ifin vivodrug potency is high, then rapid elimination of virus is possible. Potent therapies dosed soon after peak viral load when infected people typically develop symptoms, are predicted to decrease shedding duration and intensity of the effector immune response, but to have little effect on viral area under the curve, which is driven by high levels of early SARS CoV-2 replication. Potent therapy dosed prior to peak viral load, when infection is usually pre-symptomatic, is predicted to be the only option to lower viral area under the curve. We also identify that clinically meaningful drug resistance is less likely to emerge with a highly potent agent that is dosed after peak viral load. Our results support an early test and treat approach for COVID-19, but also demonstrate the need to identify early viral shedding kinetic features that are the most predictive surrogates of clinical severity and transmission risk.

One Sentence Summary

We developed a mathematical model to predict the outcomes of different possible COVID-19 treatments.
Application of COVID-19 pneumonia diffusion data to predict epidemic situation
Authors: zhenguo Wu
Published: April 2020

Objective

To evaluate novel coronavirus pneumonia cases by establishing the mathematical model of the number of confirmed cases daily, and to assess the current situation and development of the epidemic situation, so as to provide a digital basis for decision-making.

Methods

The number of newly confirmed covid-19 cases per day was taken as the research object, and the seven-day average value (M) and the sequential value (R) of M were calculated to study the occurrence and development of covid-19 epidemic through the analysis of charts and data.

Results

M reflected the current situation of epidemic development; R reflected the current level of infection and the trend of epidemic development.

Conclusion

The current data can be used to evaluate the number of people who have been infected, and when R < 1, the peak of epidemic can be predicted.

Preface

In December 2019, a number of cases of pneumonia with unknown causes were found in some hospitals in Wuhan, Hubei province, China. On 11 March 2020, the director-general of the world health organization (WHO), Tedros Adhanom Ghebreyesus, announced that based on the assessment, WHO believes that the current outbreak of COVID-19 can be called a global pandemic. By early April 2020, there were more than one million confirmed cases worldwide.

COVID-19 has developed from sporadic cases to pandemic in a short period of 3 months. The analysis and research of its infectious data will help to prevent and control the next stage of epidemic prevention and other infectious diseases in the future.

In this paper, COVID-19 rounded average of seven days (M), and M’s ring ratio (R) are used to predict the current potential patients’ data, and the relative state of epidemic prevention and control is judged through the graphic features and characteristic data, so as to provide evidence for the prevention and control decisions.
Predicting metastasis with a novel biophysical cell-adhesion force technique
Authors: Gan Jessie , Zhihai Zhao , Miao Yu
Published: April 2020

Metastasis is widely accepted to be responsible for approximately 90% of all cancer deaths. Current research on metastasis prediction often centers on gene sequencing; however, these analyses must account for the complexity of gene regulation and rely on comprehensive datasets. To investigate the process from a simpler, non-genomic angle, some studies indicate differences in cell adhesion force, an important physical process in metastasizing cells. However, cell adhesion force methods tend to focus on cell population approaches and therefore have their drawbacks in cost or efficiency, rendering them impractical outside a research setting. In this work, we test a novel and inexpensive bead-pipette assay to investigate the adhesion forces of non-metastatic NIH3T3 cells and mutated RasV12 cells, a metastatic model cell line.

Control cells and RasV12 cells were evaluated with wound healing, spreading area, and focal adhesion (FA) analysis assays. Then cells were tested by the novel bead-pipette assay, which uses a fibronectin-coated bead and a glass micropipette to measure cell adhesion force using Hooke’s law.

The RasV12 cells had faster migration, polarized cell shape, and smaller FA area than control cells. The RasV12 cells also exerted higher adhesion forces than control cells and a potential force threshold was determined for distinguishing metastatic cells through a Receiver Operating Characteristic (ROC) curve. An ROC curve was computed for all other assays and the bead-pipette assay was shown to perform higher as a classifier than other assays.

The RasV12 cells had increased metastatic potential compared to control. The novel bead-pipette assay showed potential as a classifier for determining metastasizing cells from non-metastatic cells. With further work, it may serve as a clinical diagnostic tool for cancer patients or as a testbed to be used in the development of anti-metastatic drugs.
Mechanisms of a sustained anti-inflammatory drug response in alveolar macrophages unraveled with mathematical modeling
Authors: Nyman Elin , Lindh Maria , Lövfors William , Simonsson Christian , Persson Alexander , Eklund Daniel , Bäckström Erica , Fridén Markus , Cedersund Gunnar
Published: April 2020

Both initiation and suppression of inflammation are hallmarks of the immune response. If not balanced, the inflammation may cause extensive tissue damage, which is associated with common diseases, e.g. asthma and atherosclerosis. Anti-inflammatory drugs often come with severe side effects driven by high and fluctuating drug concentrations. To remedy this, drugs with sustained anti-inflammatory responses are desirable. However, we still lack a quantitative mechanistic understanding of such sustained effects. Here, we study the anti-inflammatory response to a common glucocorticoid drug, Dexamethasone. We find a sustained response 22 hours after drug removal. With hypothesis testing using mathematical modeling, we unravel the underlying mechanism – a slow release of Dexamethasone from the receptor-drug complex. The developed model is in agreement with time-resolved training and testing data, and is used to simulate hypothetical treatment schemes. This work opens up for a more knowledge-driven drug development, to find sustained anti-inflammatory responses and fewer side effects.
EllipTrack: A Global-Local Cell-Tracking Pipeline for 2D Fluorescence Time-Lapse Microscopy
Authors: Tian Chengzhe , Yang Chen , Spencer Sabrina L.
Published: April 2020

Time-lapse microscopy provides an unprecedented opportunity to monitor single-cell dynamics. However, tracking cells for long periods of time remains a technical challenge, especially for multi-day, large-scale movies with rapid cell migration, high cell density, and drug treatments that alter cell morphology/behavior. Here, we present EllipTrack, a global-local cell-tracking pipeline optimized for tracking such movies. EllipTrack first implements a global track-linking algorithm to construct tracks that maximize the probability of cell lineages, and then corrects tracking mistakes with a local track-correction module where tracks generated by the global algorithm are systematically examined and amended if a more probable alternative can be found. Through benchmarking, we show that EllipTrack outperforms state-of-the-art cell trackers and generates nearly error-free cell lineages for multiple large-scale movies. In addition, EllipTrack can adapt to time- and cell density-dependent changes in cell migration speeds, requires minimal training datasets, and provides a user-friendly interface. EllipTrack is available atgithub.com/tianchengzhe/EllipTrack.
A Novel Model of Pancreatic Cancer Dormancy Reveals Mechanistic Insights and a Dormancy Gene Signature with Human Relevance
Authors: Dudgeon Crissy , Harris Chris R. , Chen Ying , Ghaddar Bassel , Sharma Anchal , Shah Mihir M. , Roberts Arthur I. , Casabianca Anthony , Collisson Eric A. , Balachandran Vinod P. , Vertino Paula M. , De Subhajyoti , Carpizo Darren R.
Published: April 2020

Latent recurrences following curative-intent pancreatic cancer surgery is a major clinical problem thought to be due to the reactivation of dormant tumor cells that disseminate before the primary tumor has been removed. How dormancy is established and ultimately reversed to drive recurrence is poorly understood. Here we introduce a novel model of pancreatic cancer dormancy that mimics early and latent survival outcomes of resected patients. Using single-cell transcriptomics we compared primary, dormant, and reactivated tumor cells and found the primary and reactivated tumor cell transcriptomes clustered together with and away from the dormant tumor cells. Using a chromatin accessibility assay we found dormancy exhibits large scale changes in chromatin remodeling. Dormant tumor cells express cancer stem cell markers that are lost upon reactivation and are chemotherapy resistant. We identified a dormancy gene signature and investigated this in patients undergoing surgery for localized PC by isolating cells from the primary tumor and liver disseminated tumor cells (DTCs) for single-cell transcriptomics. We found the signature correlated with DTCs indicating that these cells are dormant at the time of surgery. The signature also identified CCL5 as a novel dormancy marker in PC. Mechanisms of PC dormancy include upregulation of the transcriptional repressor Dec2 which drives quiescence, monoallelic suppression of the mutant KRAS allele by DNA methylation, and immunoregulation. We conclude that PC dormancy is a highly plastic and heterogeneous cellular state governed by tumor cell autonomous and non-autonomous mechanisms.

One Sentence Summary

A novel model of resectable pancreatic cancer reveals pancreatic cancer dormancy is characterized by significant cellular plasticity, heterogeneity and chromatin remodeling
The covariance shift (C-SHIFT) algorithm for normalizing biological data
Authors: Chunikhina Evgenia , Logan Paul , Kovchegov Yevgeniy , Yambartsev Anatoly , Mondal Debashis , Morgun Andrey
Published: April 2020

Omics technologies are powerful tools for analyzing patterns in gene expression data for thousands of genes. Due to a number of systematic variations in experiments, the raw gene expression data is often obfuscated by undesirable technical noises. Various normalization techniques were designed in an attempt to remove these non-biological errors prior to any statistical analysis. One of the reasons for normalizing data is the need for recovering the covariance matrix used in gene network analysis. In this paper, we introduce a novel normalization technique, called the covariance shift (C-SHIFT) method. This normalization algorithm uses optimization techniques together with the blessing of dimensionality philosophy and energy minimization hypothesis for covariance matrix recovery under additive noise (in biology, known as the bias). Thus, it is perfectly suited for the analysis of logarithmic gene expression data. Numerical experiments on synthetic data demonstrate the method’s advantage over the classical normalization techniques. Namely, the comparison is made with rank, quantile, cyclic LOESS (locally estimated scatterplot smoothing), and MAD (median absolute deviation) normalization methods.
Color naming and categorization depend on distinct functional brain networks
Authors: Siuda-Krzywicka Katarzyna , Witzel Christoph , Bartolomeo Paolo , Cohen Laurent
Published: April 2020

Naming a color can be understood as an act of categorization, i.e. identifying it as a member of category of colors that are referred to by the same name. But are naming and categorization equivalent cognitive processes, and consequently rely on same neural substrates? Here, we used task and resting-state fMRI, as well as behavioral measures to identify functional brain networks that modulated naming and categorization of colors. Color naming and categorization response times were modulated by different resting state connectivity networks spanning from the color-sensitive regions in the ventro-occipital cortex. Color naming correlated with the connectivity between the left posterior color region, the left medial temporal gyrus, and the left angular gyrus; whereas color categorization involved the connectivity between the bilateral posterior color regions, the left frontal, right temporal and bilateral parietal areas. The networks supporting naming and categorization did not overlap, suggesting that the two processes rely on different neural mechanisms.

Significance

When we name a color, we also identify it as a member of a color category, e.g. blue or yellow. Are neural processes underlying color categorization equivalent to those of color naming? Here, we address this question by measuring how individual differences in color categorization and naming response times relate to the strength of functional connections in the brain. Color naming speed correlated with left-hemispheric connectivity between the color-sensitive visual regions and the anterior temporal lobe. Color categorization speed was modulated by a different brain network, encompassing bilateral color-sensitive visual areas, and high-level executive and semantic regions. Thus, color categorization and naming performance involved distinct, non-overlapping brain networks, suggesting that the two processes depend on different neural mechanisms.
Mitochondrial ROS1 increases mitochondrial fission and respiration in oral squamous cancer carcinoma
Authors: Chang Yu-Jung , Chen Kuan-Wei , Chen Linyi
Published: April 2020

IncreasedROS1oncogene expression has been implicated in the invasiveness of human oral squamous cell carcinoma (OSCC). The cellular distribution of ROS1 has long been assumed at the plasma membrane. However, a previous work reported a differential cellular distribution of mutant ROS1 derived from chromosomal translocation, resulting in increased carcinogenesis. We thus hypothesized that cellular distribution of up-regulated ROS1 in OSCC may correlate with invasiveness. We found that ROS1 can localize to mitochondria in the highly invasive OSCC and identified a mitochondria-targeting signal sequence in ROS1. We also demonstrated that ROS1 targeting to mitochondria is required for mitochondrial fission phenotype in the highly invasive OSCC cells. OSCC cells expressing high levels of ROS1 consumed more oxygen and had increased levels of cellular ATP levels. Our results also revealed that ROS1 regulates mitochondrial biogenesis and cellular metabolic plasticity. Together, these findings demonstrate that ROS1 targeting to mitochondria enhances OSCC invasion through regulating mitochondrial morphogenesis and cellular respiratory.

Summary Statement

This study discovers a new role for the ROS1 in mitochondrial fission and metabolic activities.
sureLDA: A Multi-Disease Automated Phenotyping Method for the Electronic Health Record
Authors: Ahuja Yuri , Zhou Doudou , He Zeling , Sun Jiehuan , Castro Victor M. , Gainer Vivian , Murphy Shawn N. , Hong Chuan , Cai Tianxi
Published: April 2020

Objective

A major bottleneck hindering utilization of electronic health record (EHR) data for translational research is the lack of precise phenotype labels. Chart review as well as rule-based and supervised phenotyping approaches require laborious expert input, hampering applicability to studies that require many phenotypes to be defined and labeledde novo. Though ICD codes are often used as surrogates for true labels in this setting, these sometimes suffer from poor specificity. We propose a fully automated topic modeling algorithm to simultaneously annotate multiple phenotypes.

Methods

sureLDA is a label-free multidimensional phenotyping method. It first uses the PheNorm algorithm to initialize probabilities based on two surrogate features for each target phenotype, and then leverages these probabilities to constrain the Latent Dirichlet Allocation (LDA) topic model to generate phenotype-specific topics. Finally, it combines phenotype-feature counts with surrogates via clustering ensemble to yield final phenotype probabilities.

Results

sureLDA achieves reliably high accuracy and precision across a range of simulated and real-world phenotypes. Its performance is robust to phenotype prevalence and relative informativeness of surogate versus non-surrogate features. It also exhibits powerful feature selection properties.

Discussion

sureLDA combines attractive properties of PheNorm and LDA to achieve high accuracy and precision robust to diverse phenotype characteristics. It offers particular improvement for phenotypes insufficiently captured by a few surrogate features. Moreover, sureLDA’s feature selection ability enables it to handle high feature dimensions and produce interpretable computational phenotypes.

Conclusion

sureLDA is well suited toward large-scale EHR phenotyping for highly multi-phenotype applications such as PheWAS.
An approach for long-term, multi-probe Neuropixels recordings in unrestrained rats
Authors: Luo Thomas Zhihao , Bondy Adrian G. , Gupta Diksha , Elliott Verity A. , Kopec Charles D. , Brody Carlos D.
Published: April 2020

The use of Neuropixels probes for chronic neural recordings is in its infancy and initial studies leave questions about long-term stability and probe reusability unaddressed. Here we demonstrate a new approach for chronic Neuropixels recordings over a period of months in freely moving rats. Our approach allows multiple probes per rat and multiple cycles of probe reuse. We found that hundreds of units could be recorded for multiple months, but that yields depended systematically on anatomical position. Explanted probes displayed a small increase in noise compared to unimplanted probes, but this was insufficient to impair future single-unit recordings. We conclude that cost-effective, multi-region, and multi-probe Neuropixels recordings can be carried out with high yields over multiple months in rats or other similarly sized animals. Our methods and observations may facilitate the standardization of chronic recording from Neuropixels probes in freely moving animals.
SpiderSeqR: an R package for crawling the web of high-throughput multi-omic data repositories for data-sets and annotation
Authors: Sozanska Anna M. , Fletcher Charles , Bihary Dóra , Samarajiwa Shamith A.
Published: April 2020

Abstract

More than three decades ago, the microarray revolution brought about high-throughput data generation capability to biology and medicine. Subsequently, the emergence of massively parallel sequencing technologies led to many big-data initiatives such as the human genome project and the encyclopedia of DNA elements (ENCODE) project. These, in combination with cheaper, faster massively parallel DNA sequencing capabilities, have democratised multi-omic (genomic, transcriptomic, translatomic and epigenomic) data generation leading to a data deluge in bio-medicine. While some of these data-sets are trapped in inaccessible silos, the vast majority of these data-sets are stored in public data resources and controlled access data repositories, enabling their wider use (or misuse). Currently, most peer reviewed publications require the deposition of the data-set associated with a study under consideration in one of these public data repositories. However, clunky and difficult to use interfaces, subpar or incomplete annotation prevent discovering, searching and filtering of these multi-omic data and hinder their re-purposing in other use cases. In addition, the proliferation of multitude of different data repositories, with partially redundant storage of similar data are yet another obstacle to their continued usefulness. Similarly, interfaces where annotation is spread across multiple web pages, use of accession identifiers with ambiguous and multiple interpretations and lack of good curation make these data-sets difficult to use. We have produced SpiderSeqR, an R package, whose main features include the integration between NCBI GEO and SRA databases, enabling an integrated unified search of SRA and GEO data-sets and associated annotations, conversion between database accessions, as well as convenient filtering of results and saving past queries for future use. All of the above features aim to promote data reuse to facilitate making new discoveries and maximising the potential of existing data-sets.

Availability

https://github.com/ss-lab-cancerunit/SpiderSeqR
Temporo-parietal brain regions are involved in higher order object perception
Authors: Nestmann Sophia , Wiesen Daniel , Karnath Hans-Otto , Rennig Johannes
Published: April 2020

Lesions to posterior temporo-parietal brain regions are associated with deficits in perception of global, hierarchical shapes, but also impairments in the processing of objects presented under demanding viewing conditions. Evidence from neuroimaging studies and lesion patterns observed in patients with simultanagnosia and agnosia for object orientation suggest similar brain regions to be involved in perception of global shapes and processing of objects in atypical (‘non-canonical’) orientation. In a localizer experiment, we identified individual temporoparietal brain areas involved in global shape perception and found significantly higher BOLD signals during the processing of non-canonical compared to canonical objects. In a multivariate approach, we demonstrated that posterior temporo-parietal brain areas show distinct voxel patterns for non-canonical and canonical objects and that voxel patterns of global shapes are more similar to those of objects in non-canonical compared to canonical viewing conditions. These results suggest that temporo-parietal brain areas are not only involved in global shape perception but might serve a more general mechanism of complex object perception. Our results challenge a strict attribution of object processing to the ventral visual stream by suggesting specific dorsal contributions in more demanding viewing conditions.

Highlights

Posterior temporo-parietal brain areas in the TPJ region that are involved in global shape perception are significantly involved in object perception

Individual global shape TPJ ROIs identified with a specific localizer experiment prefer objects in non-canonical over objects in canonical orientations

Univariate activations and multivariate voxel patterns in global shape TPJ ROIs distinguish canonical and non-canonical object presentations
The Medial Temporal Lobe Supports Mnemonic Discrimination For Event Duration
Authors: Muncy Nathan M. , Kirwan C. Brock
Published: April 2020

Time has an integral role in episodic memory and previous work has implicated the medial temporal lobe in both representing time and discriminating between similar memory traces. Here we developed a novel paradigm to test mnemonic discrimination for temporal duration, as previous temporal work has largely focused on order or maintaining information over time. Thirty-five healthy, young adults completed a continuous-recognition temporal discrimination task in which participants were tasked with detecting a change of stimulus duration on the order of 0.5 seconds and whole-brain high-resolution fMRI data were acquired during this process. Analyses of behavioral results indicate that participants were successful at detecting whether the stimulus duration changed. Further, fMRI analyses revealed that successful trial performance was associated with differential processes in the left entorhinal and perirhinal cortices. Specifically, the left entorhinal cortex was differentially engaged during encoding trials that preceded Target detection, and the left perirhinal cortex was differentially engaged during successful test phase Target and Lure detections. These findings suggest that the entorhinal cortex is involved in the encoding of temporal context information and that the perirhinal cortex is representing the conjunction of item and context during retrieval.
Charged Gram-positive species sequester and decrease the potency of pediocin PA-1 in mixed microbial settings
Authors: Trivedi Vikas D. , Nair Nikhil U.
Published: April 2020

Antimicrobial peptides (AMPs) have gained attention recently due to increasing antibiotic resistance amongst pathogens. Most AMPs are cationic in nature and their preliminary interactions with the negatively charged cell surface is mediated by electrostatic attraction. This is followed by pore formation, which is either receptor-dependent or -independent and leads to cell death. Typically, AMPs are characterized by their killing activity using bioactivity assays to determine host range and degree of killing. However, cell surface binding is independent from killing. Most of the studies performed to-date have attempted to quantify the peptide binding using artificial membranes. Here, we use the narrow-spectrum class IIa bacteriocin AMP pediocin PA-1 conjugated to a fluorescent dye as a probe to monitor cell surface binding. We developed a flow cytometry-based assay to quantify the strength of binding in target and non-target species. Through our binding assays, we found a strong positive correlation between cell surface charge and pediocin PA-1 binding. Interestingly, we also found inverse correlation between zeta potential and pediocin PA-1 binding, the correlation coefficient for which improved when only Gram-positives were considered. We also show the effect of the presence of protein, salt, polycationic species, and other non-target species on the binding of pediocin PA-1 to the target organism. We conclude that the of presence of highly charged non-target species, as well as solutes, can decrease the binding, and the apparent potency, of pediocin PA-1. Thus, these outcomes are highly significant to the use of pediocin PA-1 and related AMPs in mixed microbial settings such as those found in the gut microbiota.
An empirical comparison of univariate versus multivariate methods for the analysis of brain-behavior mapping
Authors: Ivanova Maria V. , Herron Timothy J. , Dronkers Nina F. , Baldo Juliana V.
Published: April 2020

Lesion symptom mapping (LSM) tools are used on brain injury data to identify the neural structures critical for a given behavior or symptom. Univariate lesion-symptom mapping (ULSM) methods provide statistical comparisons of behavioral test scores in patients with and without a lesion on a voxel by voxel basis. More recently, multivariate lesion-symptom mapping (MLSM) methods have been developed that consider the effects of all lesioned voxels in one model simultaneously. However, very little work has been done to empirically compare the advantages and disadvantages of these two different methods. In the current study, we provide a needed systematic comparison of 5 ULSM and 8 MLSM methods, using both synthetic and real data to identify the potential strengths and weaknesses of both approaches. We tested power and spatial precision of each LSM method for both single and dual (network type) anatomical target simulations across anatomical target location, sample size, noise level, and lesion smoothing. Additionally, we performed false positive simulations to identify the characteristics associated with each method’s spurious findings. Simulations showed no clear superiority of either ULSM or MLSM methods overall, but rather highlighted specific advantages of different methods. No single method produced a thresholded LSM map that exclusively delineated brain regions associated with the target behavior. Thus, different LSM methods are indicated, depending on the particular study design, specific hypotheses, and sample size. Overall, we recommend the use of both ULSM and MLSM methods in tandem to enhance confidence in the results: Brain foci identified as significant across both types of methods are unlikely to be spurious and can be confidently reported as robust results.
Modeling disease-correlated TUBA1A mutation in budding yeast reveals a molecular basis for tubulin dysfunction
Authors: Denarier E. , Ecklund K.H. , Berthier G. , Favier A. , Gory S. , Macedo L. De , Delphin C. , Andrieux A. , Markus S.M. , Boscheron C.
Published: April 2020

Malformations of cortical development (MCD) of the human brain are a likely consequence of defective neuronal migration, and/or proliferation of neuronal progenitor cells, both of which are dictated in part by microtubule-dependent transport of various cargoes, including the mitotic spindle. Throughout the evolutionary spectrum, proper spindle positioning depends on cortically anchored dynein motors that exert forces on astral microtubules emanating from spindle poles. A single heterozygous amino acid change, G436R, in the conserved TUBA1A α-tubulin gene was reported to account for MCD in patients. The mechanism by which this mutation disrupts microtubule function in the developing cerebral cortex is not understood. Studying the consequence of tubulin mutations in mammalian cells is challenging partly because of the large number of α-tubulin isotypes expressed. To overcome this challenge, we have generated a budding yeast strain expressing the mutated tubulin (Tub1G437Rin yeast) as one of the main sources of α-tubulin (in addition to Tub3, another α-tubulin isotype in this organism). Although viability of the yeast was unimpaired by this mutation, they became reliant on Tub3, as was apparent by the synthetic lethality of this mutant in combination withtub3Δ. We find that Tub1G437Rassembles into microtubules that support normal G1 activity, but lead to enhanced dynein-dependent nuclear migration phenotypes during G2/M, and a consequential disruption of spindle positioning. We find that this mutation impairs the interaction between She1 – a negative regulator of dynein – and microtubules, as was apparent from a yeast two-hybrid assay, a co-sedimentation assay, and from live cell imaging. We conclude that a weaker interaction between She1 and Tub1G437R-containing microtubules results in enhanced dynein activity, ultimately leading to the spindle positioning defect. Our results provide the first evidence of an impaired interaction between microtubules and a dynein regulator as a consequence of a tubulin mutation, and sheds light on a mechanism that may be causative of neurodevelopmental diseases.