bluuebunny/crossref_metadata_2025 huggingface dataset:
Dispersion of a new coronavirus SARS-CoV-2 by airlines in 2020: Temporal estimates of the outbreak in Mexico
Authors: Cruz-Pacheco G , Bustamante-Castañeda J.F , Caputo J.G , Jiménez-Corona ME , Ponce-de-León S
Published: March 2020

On January 23, 2020, China imposed a quarantine on the city of Wuhan to contain the SARS-CoV-2 outbreak. Regardless of this measure the new infection has spread to several countries around the world. Here, we developed a method to study the dissemination of this infection by the airline routes and we give estimations of the time of arrival of the outbreaks to the different cities.

In this work we show an analysis of the dispersion of this infection to other cities by airlines based on the classic model the Kermack and McKendrick complemented with diffusion on a graph composed of nodes which represent the cities and edges which represent the airline routes. We do several numerical simulations to estimate the date of arrival to different cities starting the infection at Wuhan, China and to show the robustness of the estimation respect to changes in the epidemiological parameters and to changes on the graph. we use Mexico City as an example. In this case, our estimate of the arrival time is between March 20 and March 30, 2020. This analysis is limited to the analysis of dispersion by airlines, so this estimate should be taken as an overestimate since the infection can arrive by other means.

This model estimates the arrival of the infectious outbreak to Mexico between March 20 and March 30. This estimation gives a time period to implement and strengthen preventive measures aimed at the general population, as well as to strengthen hospital infrastructure and training of human resources in health.
Risk assessment of progression to severe conditions for patients with COVID-19 pneumonia: a single-center retrospective study
Authors: Zeng Lijiao , Li Jialu , Liao Mingfeng , Hua Rui , Huang Pilai , Zhang Mingxia , Zhang Youlong , Shi Qinlang , Xia Zhaohua , Ning Xinzhong , Liu Dandan , Mo Jiu , Zhou Ziyuan , Li Zigang , Fu Yu , Liao Yuhui , Yuan Jing , Wang Lifei , He Qing , Liu Lei , Qiao Kun
Published: March 2020

Background

Management of high mortality risk due to significant progression requires prior assessment of time-to-progression. However, few related methods are available for COVID-19 pneumonia.

Methods

We retrospectively enrolled 338 adult patients admitted to one hospital between Jan 11, 2020 to Feb 29, 2020. The final follow-up date was March 8, 2020. We compared characteristics between patients with severe and non-severe outcome, and used multivariate survival analyses to assess the risk of progression to severe conditions.

Results

A total of 76 (31.9%) patients progressed to severe conditions and 3 (0.9%) died. The mean time from hospital admission to severity onset is 3.7 days. Age, body mass index (BMI), fever symptom on admission, co-existing hypertension or diabetes are associated with severe progression. Compared to non-severe group, the severe group already demonstrated, at an early stage, abnormalities in biomarkers indicating organ function, inflammatory responses, blood oxygen and coagulation function. The cohort is characterized with increasing cumulative incidences of severe progression up to 10 days after admission. Competing risks survival model incorporating CT imaging and baseline information showed an improved performance for predicting severity onset (mean time-dependent AUC = 0.880).

Conclusions

Multiple predisposition factors can be utilized to assess the risk of progression to severe conditions at an early stage. Multivariate survival models can reasonably analyze the progression risk based on early-stage CT images that would otherwise be misjudged by artificial analysis.
Selecting donors for faecal microbiota transplantation in ulcerative colitis
Authors: de Leeuw Marcel A. , Duval Manuel X.
Published: March 2020

Background

Inflammatory bowel disease (IBD) is a set of conditions characterized by non-infectious chronic inflammation of the gastrointestinal tract. These primarily include Crohn’s disease (CD), ulcerative colitis (UC) and indeterminate colitis. Fecal microbiota transplantation (FMT) has proven to be an effective treatment for some patients with active UC. There is currently no procedure allowing to predict the patients’ response and to select the most adequate donor(s).

Aim

Investigate microbiome characteristics in association with responder/non-responder status and develop selection criteria for donor samples to be used for UC FMT.

Methods

Available UC longitudinal FMT microbiome data sets were in part combined and reanalyzed, with focus on species level changes in the microbiota, using state-of-the-art 16S analysis routines.

Results

We predicted antibiotic resistance to be higher in non-responders (p=0.0064). Microbiomes of UC FMT responder donors have higher phylogenetic diversity (p=0.0026) and a higher proportion of facultative anaerobes (p=3.3E-5) as compared to non-responder donors. We predicted succinate and histamine to be increased in non-responder donors and non-responders, respectively. Sialic acid catabolism was also predicted to be increased in non-responder donors. Tryptamine and indole-3-acetaldehyde were predicted to be increased in responder donors.

Conclusions

Our findings contribute to the establishment of selection criteria for UC FMT donor samples and composition guidelines for future synthetic microbial communities. Our results suggest that oxidative stress resistant facultative anaerobes are important for the establishment of an anaerobic environment and a successful UC FMT therapy. Several metabolites can be tested for additional optimization or prioritization of stool bank samples for UC FMT. Our results question the usefulness of antibiotics based preparation of the gut, prior to FMT.
The early scientific literature response to the novel Coronavirus outbreak: who published what?
Authors: Gori Davide , Boetto Erik , Fantini Maria Pia
Published: March 2020

Introduction

Recent events highlight how emerging and re-emerging pathogens are becoming global challenges for public health. In December 2019, a novel coronavirus has emerged. This has suddenly turned out into global health concern.

Objectives

Aim of this research is to focus on the bibliometric aspects in order to measure what is published in the first 30-days of a global epidemic outbreak

Methods

We searched PubMed database in order to find all relevant studies in the first 30-days from the first publication.

Results

From the initial 442 identified articles, 234 were read in-extenso. The majority of papers come from China, UK and USA. 63.7% of the papers were commentaries, editorials and reported data and only 17.5% of the sources used data directly collected on the field. Topics mainly addressed were “epidemiology”, “preparedness” and “generic discussion”. NNR showed a reduction for both the objectives assessed from January to February.

Conclusions

“Diagnosis” and effective preventive and therapeutic measures were the fields in which more research is still needed. The vast majority of scientific literature in the first 30-days of an epidemic outbreak is based on reported data rather than primary data. Nevertheless, the scientific statements and public health decisions rely on these data.

Strengths of our study

This is the first bibliometric research in Pubmed Database on the first 30 days of publications regarding the novel Coronavirus (SARS-nCoV-2) outbreak of 2019.

The vast majority of publication in the first 30-days of an epidemic outbreak are reported data or comments, and only a small fraction of the papers have directly collected data.

Limitations of our study

Our research is only PubMed based. It ill be auspicable to consult more than one relevant database in future papers.

In addition, we excluded non-English publications leading to a potential bias due to the fact that the outbreak started in China.
Evolution of Service Metrics and Utilisation of Evidence-Based Outcome Measures in Anterior Cruciate Ligament Reconstruction Rehabilitation: An Observational Review of Two Cohorts in a Public Hospital Physiotherapy Department
Authors: Tuckerman Kirby , Potts Wendy , Ebrahimi Milad , Scholes Corey , Nelson Mark
Published: March 2020

Objective

Determine in patients undergoing supervised rehabilitation post ACL reconstruction in a public hospital, whether a new model of care incorporating a phase-based program, compared to standard care, increased physiotherapist utilisation of outcome measures, improved service metrics such as attendance and rehabilitation completion rates, as well as increased self-reported knee function and activity levels.

Methods

Patients attending outpatient physiotherapy after ACL reconstruction at a metropolitan public hospital (N = 132) were included in retrospective chart review to assess utilisation of outcomes such as quadriceps and hamstrings strength assessment, patient attendance and rehabilitation completion. Phone followup (minimum one year) was conducted to retrieve patient-reported measures of knee function (IKDC) and activity (Tegner Activity Scale). Patients were categorised by rehabilitation model of care (contemporary - time based [N = 93] vs new - phase based [N = 39]) and logistic regression used to assess the influence of patient factors and model of care on outcomes.

Results

Patients included for analysis were aged 25 years at surgery (IQR 20.3 - 30.8), with 42.4% of non-Australia country of origin. Compliance was equivalent between models of care and completion rates (formally discharged by therapist) were low (30-38%). The probability of a patient receiving strength assessment was significantly associated with model of care, sex, BMI and the number of sessions attended. The probability of a patient being recorded as discharged from the program was significantly associated with the model of care, as well as the duration and number of sessions.

Conclusion

The transition to a new model of care incorporating a phase-based rehabilitation program increased physiotherapist utilisation of certain evidence-based outcome measures, increased total duration of rehabilitation and increased the total number of sessions attended. Despite this, rehabilitation completion rates remained low, and no change was demonstrated with respect to self-reported knee function and activity levels.

Level of evidence

III, retrospective case-control study
Negligible Risk of the COVID-19 Resurgence Caused by Work Resuming in China (outside Hubei): a Statistical Probability Study
Authors: Zhao Kedong , Long Cheng , Wang Yan , Zeng Tieyong , Fu Xinmiao
Published: March 2020

The COVID-19 outbreak in China appears to reach the late stage since late February 2020, and a stepwise restoration of economic operations is implemented. Risk assessment for such economic restoration is of significance. Here we estimated the probability of COVID-19 resurgence caused by work resuming in typical provinces/cities, and found that such probability is very limited (<5% for all the regions except Beijing). Our work may inform provincial governments to make risk level-based, differentiated control measures.
Forecasting the Worldwide Spread of COVID-19 based on Logistic Model and SEIR Model
Authors: Zhou Xiang , Ma Xudong , Hong Na , Su Longxiang , Ma Yingying , He Jie , Jiang Huizhen , Liu Chun , Shan Guangliang , Zhu Weiguo , Zhang Shuyang , Long Yun
Published: March 2020

Background

With the outbreak of coronavirus disease 2019 (COVID-19), a sudden case increase in late February 2020 led to deep concern globally. Italy, South Korea, Iran, France, Germany, Spain, the US and Japan are probably the countries with the most severe outbreaks. Collecting epidemiological data and predicting epidemic trends are important for the development and measurement of public intervention strategies. Epidemic prediction results yielded by different mathematical models are inconsistent; therefore, we sought to compare different models and their prediction results to generate objective conclusions.

Methods

We used the number of cases reported from January 23 to March 20, 2020, to estimate the possible spread size and peak time of COVID-19, especially in 8 high-risk countries. The logistic growth model, basic SEIR model and adjusted SEIR model were adopted for prediction. Given that different model inputs may infer different model outputs, we implemented three model predictions with three scenarios of epidemic development.

Results

When comparing all 8 countries’ short-term prediction results and peak predictions, the differences among the models were relatively large. The logistic growth model estimated a smaller epidemic size than the basic SERI model did; however, once we added parameters that considered the effects of public health interventions and control measures, the adjusted SERI model results demonstrated a considerably rapid deceleration of epidemic development. Our results demonstrated that contact rate, quarantine scale, and the initial quarantine time and length are important factors in controlling epidemic size and length.

Conclusions

We demonstrated a comparative assessment of the predictions of the COVID-19 outbreak in eight high-risk countries using multiple methods. By forecasting epidemic size and peak time as well as simulating the effects of public health interventions, the intent of this paper is to help clarify the transmission dynamics of COVID-19 and recommend operation suggestions to slow down the epidemic. It is suggested that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviors are critical to slow down the epidemic.
Vitamin B12 and Risk of Diabetes: New insight from Cross-Sectional and Longitudinal Analyses of the China Stroke Primary Prevention Trial (CSPPT)
Authors: Liu Lishun , Huang Xiao , Wang Binyan , Song Yun , Lin Tengfei , Zhou Ziyi , Wang Zhuo , Wei Yaping , Guo Huiyuan , Chen Ping , Yang Yan , Ling Wenhua , Li Youbao , Qin Xianhui , Tang Genfu , Liu Chengzhang , Li Jianping , Zhang Yan , Zalloua Pierre , Wang Xiaobin , Huo Yong , Zhang Hao , Xu Xiping
Published: March 2020

Introduction

Previous studies in mostly Western populations, have yielded conflicting findings on the association of vitamin B12 with diabetes risk, in part, due to differences in study design and population characteristics. This study sought to examine the vitamin B12 – diabetes association in Chinese hypertensive adults by both cross-sectional and longitudinal analyses.

Research Design and Methods

This report included a total of 16699 participants from the China Stroke Primary Prevention Trial (CSPPT), with pertinent baseline and follow-up data. Diabetes mellitus (DM) was defined as either physician-diagnosed diabetes, the use of glucose-lowering drugs, or fasting blood glucose (FBG) ≥7.0 mmol/L. New-onset diabetes was defined as any new case of onset diabetes during the follow-up period or fasting blood glucose (FBG) ≥7.0 mmol/L at the exit visit.

Results

At baseline, there were 1872 (11.2%) diabetic patients; less than 1.5% had clinical B12 deficiency (<148.0 pmol/L). Over a median follow-up period of 4.5 years, there were 1589 (10.7%) cases of new-onset diabetes. Cross-sectional analyses showed a positive association between baseline vitamin B12 levels and FBG levels (β=0.18, 95%CI 0.15-0.21) and diabetes (OR=1.42, 95%CI 1.33-1.51). However, longitudinal analyses showed no association between baseline vitamin B12 and new-onset diabetes or changes in FBG levels. Among a subset of the sample (N=4366) with both baseline and exit B12 measurements, we found a positive association between an increase in B12 and an increase in FBG.

Conclusions

In this large Chinese hypertensive population mostly sufficient with vitamin B12, parallel cross-sectional and longitudinal analyses provided new insight into the conflicting findings of previous studies, and these results underscore the need for future studies to consider both baseline vitamin B12 and its longitudinal trajectory in order to better elucidate the role of vitamin B12 in the development of diabetes. Such findings, would have important clinical and public health implications.
“The more I fear about COVID-19, the more I wear medical masks”: A survey on risk perception and medical masks’ uses
Authors: Duc Huynh Toan Luu
Published: March 2020

The legal behaviors in using medical masks in public have been finally promulgated by the Vietnamese Government after 47 days since the WHO declared the Public Health Emergency of International Concern (PHEIC) due to the COVID-19 pandemic. From a sample of 345 Vietnamese respondents aged from 15 to 47 years, this brief note found that the risk perception of COVID-19 danger significantly increases the likelihood of wearing the medical masks. In addition, there is a weak evidence about the differences in age under the COVID-19 outbreaks. More noticeably, those who use masks before COVID-19 pandemic tend to maintain their behaviors. Our results offer the insightful into Vietnamese citizens’ responses in terms of using medical masks; even the uses of this method are still controversial. Our results are robust by performing Exploratory Factor Analysis for five features and further regressions.
Temperature dependence of COVID-19 transmission
Authors: Notari Alessio
Published: March 2020

The recent coronavirus pandemic follows in its early stages an almost exponential expansion, with the number of cases as a function of time reasonably well fit byN(t) ∝eαt, in many countries. We analyze the rateαin different countries, choosing as a starting point in each country the first day with 30 cases and fitting for the following 12 days, capturing thus the early exponential growth in a rather homogeneous way. We look for a link between the rateαand the average temperatureTof each country, in the month of the epidemic growth. We analyze abaseset of 42 countries, which developed the epidemic at an earlier stage, anintermediateset of 88 countries and anextendedset of 125 countries, which developed the epidemic more recently. Fitting with a linear behaviorα(T), we find increasing evidence in the three datasets for a decreasing growth rate as a function ofT, at 99.66%C.L., 99.86%C.L. and 99.99995% C.L. (p-value 5 10−7, or 5σdetection) in thebase, intermediateandextendeddataset, respectively. The doubling time is expected to increase by 40% 50%, going from 5° C to 25° C. In thebaseset, going beyond a linear model, a peak at about (7.7 ± 3.6)°Cseems to be present in the data, but such evidence disappears for the larger datasets. Moreover we have analyzed the possible existence of a bias: poor countries, typically−located in warm regions, might have less intense testing. By excluding countries below a given GDP per capita from the dataset, we find that this affects our conclusions only slightly and only for theextendeddataset. The significance always remains high, with ap-value of about 10−310−4or less. Our findings give hope that, for northern hemisphere countries, the growth rate should significantly decrease as a result of both warmer weather and lockdown policies. In general the propagation should be hopefully stopped by strong lockdown, testing and tracking policies, before the arrival of the next cold season.
A deductive approach to modeling the spread of COVID-19
Authors: Mishra Pranav , Mishra Shekhar
Published: March 2020

Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), previously known as 2019-nCoV, is responsible for the atypical pneumonia pandemic designated as Coronavirus Disease 2019 (COVID-19). The number of cases continues to grow exponentially reaching 492,000 people in 175 countries as of March 25, 2020. 22,169 people (∼4.5%) infected with SARS-COV-2 virus have died. We have developed an exponential regression model using the COVID-19 case data (Jan 22 – Mar 22, 2020). Our primary model uses designated Phase 1 countries, who exceed 2500 cases on Mar 22. The model is then applied to Phase 2 countries: those that escaped the initial Phase 1 global expansion of COVID-19. With the exception of stabilizing countries (South Korea, Japan, and Iran) all Phase 1 countries are growing exponentially, as per I2500(t) = 120.4 × e0.238t, with a rate, r = 0.238 ± 0.068. Excluding China, the BRICS developing nations and Australia are in Phase 2. Case data from Phase 2 countries are following the model derived from Phase 1 countries. In the absence of measures employed to flatten the curve including social distancing, quarantine, and healthcare expansion, our model projects over 274,000 cases and 12,300 deaths in the US by Mar 31. India can expect 123,000 cases by April 16. By flattening the curve to the growth rate of stabilizing countries (r = 0.044 ± 0.062), the US would prevent 8,500 deaths by Mar 31, and India would prevent 5,500 deaths by April 16.
A model to forecast regional demand for COVID-19 related hospital beds
Authors: Ferstad Johannes O. , Gu Angela , Lee Raymond Y. , Thapa Isha , Shin Andrew Y. , Salomon Joshua A. , Glynn Peter , Shah Nigam H. , Milstein Arnold , Schulman Kevin , Scheinker David
Published: March 2020

COVID-19 threatens to overwhelm hospital facilities throughout the United States. We created an interactive, quantitative model that forecasts demand for COVID-19 related hospitalization based on county-level population characteristics, data from the literature on COVID-19, and data from online repositories. Using this information as well as user inputs, the model estimates a time series of demand for intensive care beds and acute care beds as well as the availability of those beds. The online model is designed to be intuitive and interactive so that local leaders with limited technical or epidemiological expertise may make decisions based on a variety of scenarios. This complements high-level models designed for public consumption and technically sophisticated models designed for use by epidemiologists. The model is actively being used by several academic medical centers and policy makers, and we believe that broader access will continue to aid community and hospital leaders in their response to COVID-19.

LINK TO ONLINE MODEL

https://surf.stanford.edu/covid-19-tools/covid-19/
Telomere length and chromosomal instability for predicting individual radiosensitivity and risk via machine learning
Authors: Luxton Jared J. , McKenna Miles J. , Lewis Aidan M. , Taylor Lynn E. , Jhavar Sameer G. , Swanson Gregory P. , Bailey Susan M.
Published: March 2020

The ability to predict a cancer patient’s response to radiotherapy and risk of developing adverse late health effects would greatly improve personalized treatment regimens and individual outcomes. Telomeres represent a compelling biomarker of individual radiosensitivity and risk, as exposure can result in dysfunctional telomere pathologies that coincidentally overlap with many radiation-induced late effects, ranging from degenerative conditions like fibrosis and cardiovascular disease to proliferative pathologies like cancer. Here, telomere length was longitudinally assessed in a cohort of fifteen prostate cancer patients undergoing Intensity Modulated Radiation Therapy (IMRT) utilizing Telomere Fluorescencein situHybridization (Telo-FISH). To evaluate genome instability and enhance predictions for individual patient risk of secondary malignancy, chromosome aberrations were also assessed utilizing directional Genomic Hybridization (dGH) for high-resolution inversion detection. We present the first implementation of individual telomere length data in a machine learning model, XGBoost, trained on pre-radiotherapy (baseline) andin vitroexposed (4 Gy γ-rays) telomere length measures, to predict post-radiotherapy telomeric outcomes, which together with chromosomal instability provide insight into individual radiosensitivity and risk for radiation-induced late effects.
Longitudinal assessment of mycotoxin co-exposures in exclusively breastfed infants
Authors: Braun Dominik , Schernhammer Eva , Marko Doris , Warth Benedikt
Published: March 2020

Early-life development of infants may be critically affected by man-made or natural contaminants including mycotoxins. However, data on the occurrence of food contaminants in breast milk is scarce and prohibits a comprehensive exposure and risk assessment for mothers and their infants.

Here, we present a longitudinal exposure assessment over the first 211 days of a single newborn girl (study A) by measuring multiple mycotoxins in milk. Eighty-seven consecutive breast milk samples were obtained from the newborn’s mother living in Austria and following a regular mixed diet. Mycotoxins were analyzed by utilizing a highly sensitive LC-MS/MS approach covering 29 mycotoxins and key metabolites. In addition to this longitudinal study, three mothers provided breast milk samples each on five consecutive days, for a preliminary comparison of inter-day and inter-individual variation in exposures (study B). Study A revealed that mycotoxin occurrence in breast milk was limited to the emerging mycotoxins alternariol monomethyl ether (AME), beauvericin (BEA), enniatins (A, A1, B, B1) and to ochratoxin A (OTA), which is regulated in commercial infant food. These mycotoxins were, if present, mostly detected at very low concentrations (<10 ng/L), except AME which exceeded this concentration on two distinct days by a factor of 3x and 5x. Overall, longitudinal results indicated chronic low-dose exposure to the detected mycotoxins. Other regulated mycotoxins including the carcinogenic aflatoxins or the estrogenic zearalenone and their biotransformation products were absent in all tested samples. Study B confirmed the results of study A, with minimal inter-day and inter-individual variation. In addition, a preliminary correlation of OTA levels occurring in breast milk and matched urine samples was found (r=0.64, p=0.034) in study B. Based on the data set obtained in study A, exposure of the infant was estimated. Exposure estimates of individual mycotoxins were on average below 1 ng/kg body weight per day.

Our preliminary findings suggest that recommended maximum daily intake levels might not be exceeded in the Austrian population. However, exposure is likely to be higher in populations with lower food safety standards. In the light of co-occurrence of several emerging mycotoxins in breast milk, future studies should address low-dose mixture effects. This also includes other environmental contaminants which may be present in this bio-fluid and should involve an exposome-scale risk assessment. All these efforts must be intended to minimize exposure of mothers and infants in a window of high susceptibility.
The Stochastic Resonance model of auditory perception: A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition
Authors: Schilling Achim , Tziridis Konstantin , Schulze Holger , Krauss Patrick
Published: March 2020

Stochastic Resonance (SR) has been proposed to play a major role in auditory perception, and to maintain optimal information transmission from the cochlea to the auditory system. By this, the auditory system could adapt to changes of the auditory input at second or even sub-second timescales. In case of reduced auditory input, somatosensory projections to the dorsal cochlear nucleus would be disinhibited in order to improve hearing thresholds by means of SR. As a side effect, the increased somatosensory input corresponding to the observed tinnitus-associated neuronal hyperactivity is then perceived as tinnitus. In addition, the model can also explain transient phantom tone perceptions occurring after ear plugging, or the Zwicker tone illusion. Vice versa, the model predicts that via stimulation with acoustic noise, SR would not be needed to optimize information transmission, and hence somatosensory noise would be tuned down, resulting in a transient vanishing of tinnitus, an effect referred to as residual inhibition.
Brain structures associated with reading and their abnormalities in dyslexia: a whole-brain analysis
Authors: Kujala T. , Thiede A. , Palo-oja P. , Virtala P. , Laasonen M. , Numminen J. , Sihvonen A. J.
Published: March 2020

Developmental dyslexia (DD) is a highly prevalent neurodevelopmental disorder, which often has a devastating influence on the individual’s academic achievement and career. Research on the neural origins of DD has continued for half a century, yielding, however, inconsistent results. The current study was set out to determine abnormalities of grey and white matter volumes in adults with DD and to shed light on neural architectures associated with reading and related skills. To this end, we conducted a whole-brain voxel based morphometry following current recommendations on analysis approaches, coupled with rigorous neuropsychological testing, to characterize the associations between neuroanatomy and skills vital for reading in DD. We found decreased volumes of grey matter in DD, comprising a left-hemispheric network including superior temporal and inferior frontal gyri, insula, the limbic system, and basal ganglia, and white matter, including the right middle temporal gyrus and hippocampus, as well as the right precuneus. These results are both consistent with the most robust previous findings on cortical abnormalities in DD and yield novel insight to the role of subcortical structures in DD, scarcely studied so far. Crucially, areas with decreased grey matter in DD overlapped with brain areas associated with technical reading skills. This supports the conclusion that the grey matter regions that we identified to have a low volume in DD are associated with the core areas vital for reading.
Durable Changes to Airway Mucus and Fluid Secretion Following Cholinergic Challenge
Authors: Liao Yan Shin J. , Collins Emily N. , Guevara Maria Valentina , Schurmann Veronica , Atanasova Kalina R. , Bravo Laura , Sponchiado Mariana , Hoegger Mark J. , Reznikov Leah R.
Published: March 2020

Purpose

Mucus abnormalities are central to the pathophysiology of several chronic airway diseases. Mucus secretion and clearance are regulated, in part, by cholinergic innervation. Prolonged cholinergic stimulation may contribute to mucus abnormalities in disease. Thus, we tested the hypothesis that prolonged cholinergic stimulation gives rise to lasting mucus abnormalities in airways.

Methods

We delivered aerosolized bethanechol, a cholinergic agonist, to pig airways. Forty-eight hours later, we measured mucus secretion and mucociliary transport in tracheal segmentsex vivo. Tracheal and bronchoalveolar lavage concentrations of the major secreted mucus glycoproteins, mucin5B (MUC5B) or mucin5AC (MUC5AC), were measured with ELISA and antibody labeling. Pig airway epithelia were cultured at the air-liquid interface and treated with bethanechol for forty-eight hours. Stimulated fluid secretion was measured with reflected microscopy and Ussing chambers were used to measure ion transport.

Results

Airways from bethanechol-challenged pigs exhibited sheet-like mucus films, which were not associated with a greater abundance of MUC5AC or MUC5B. Epithelia treated with bethanechol had diminished fluid secretion and decreased Cl-transport. However, mucus and fluid alterations were not associated with impaired mucociliary transport.

Conclusions

These data suggest that cholinergic transmission induces sustained alterations in airway mucus properties. Such defects might compound and/or contribute to persistent mucus phenotypes found after the resolution of airway inflammation.
Internal control for process monitoring of clinical metagenomic next-generation sequencing of urine samples
Authors: Janes Victoria A. , van der Laan Jennifer S. , Matamoros Sébastien , Mende Daniel R. , de Jong Menno D. , Schultsz Constance
Published: March 2020

Background

Process control for clinical metagenomic next-generation sequencing (mNGS) is not yet widely applied, while technical sources of bias are plentiful. We present an easy-to-use internal control (IC) method focussing on technical process control applied to metagenomics in clinical diagnostics.

Methods

DNA of nine urine samples was sequenced in the absence and presence ofThermus thermophilusDNA as IC in incremental concentrations (0.5-2-5%). Between aliquots of each sample, we compared the IC relative abundance (RA), and afterin silicosubtraction of IC reads, the microbiota and the RA of pathogens. The optimal IC spike-in concentration was defined as the lowest concentration still detectable in all samples.

Results

The RA of IC correlated linearly with the spiked IC concentration (r2=0.99). IC added in a concentration of 0.5% of total DNA concentration was detectable in all samples, regardless of human/bacterial composition and afterin silicoremoval gave the smallest difference in RA of pathogens compared to the unspiked aliquot of the sample. The microbiota of sample aliquots sequenced in the presence and absence of IC was highly similar afterin silicoremoval of IC reads (median BC-dissimilarity per sample of 0.059), provided samples had sufficient bacterial read counts.

Conclusion

T. thermophilusDNA at a percentage of 0.5% of the total DNA concentration can be applied for the process control of mNGS of urine samples. We demonstrated negligible alterations in sample microbial composition afterin silicosubtraction of IC sequence reads. This approach contributes toward implementation of mNGS in the clinical microbiology laboratory.
Evaluating COVID-19 Public Health Messaging in Italy: Self-Reported Compliance and Growing Mental Health Concerns
Authors: Barari Soubhik , Caria Stefano , Davola Antonio , Falco Paolo , Fetzer Thiemo , Fiorin Stefano , Hensel Lukas , Ivchenko Andriy , Jachimowicz Jon , King Gary , Kraft-Todd Gordon , Ledda Alice , MacLennan Mary , Mutoi Lucian , Pagani Claudio , Reutskaja Elena , Roth Christopher , Slepoi Federico Raimondi
Published: March 2020

Purpose

The COVID-19 death-rate in Italy continues to climb, surpassing that in every other country. We implement one of the first nationally representative surveys about this unprecedented public health crisis and use it to evaluate the Italian government’ public health efforts and citizen responses.

Findings

(1) Public health messaging is being heard. Except for slightly lower compliance among young adults, all subgroups we studied understand how to keep themselves and others safe from the SARS-Cov-2 virus. Remarkably, even those who do not trust the government, or think the government has been untruthful about the crisis believe the messaging and claim to be acting in accordance. (2) The quarantine is beginning to have serious negative effects on the population’s mental health.

Policy Recommendations

Communications should move from explaining to citizens that they should stay at home to what they can do there. We need interventions that make staying following public health protocols more desirable, such as virtual social interactions, online social reading activities, classes, exercise routines, etc. — all designed to reduce the boredom of long term social isolation and to increase the attractiveness of following public health recommendations. Interventions like these will grow in importance as the crisis wears on around the world, and staying inside wears on people.
An alternative workflow for molecular detection of SARS-CoV-2 - escape from the NA extraction kit-shortage, Copenhagen, Denmark, March 2020
Authors: Fomsgaard Anna S. , Rosenstierne Maiken W.
Published: March 2020

The World Health Organisation has declared a pandemic caused by the newly discovered SARS-CoV-2. Due to growing demand for reagents used for SARS-CoV-2 RNA extraction for subsequent molecular diagnostics, there is a worldwide risk of kit- and/or reagent-shortages for extraction. With a detection sensitivity of 97.4% (95% CI=86.2-99.9%), we describe a simple, fast, alternative workflow for molecular detection of SARS-CoV-2, where samples are simply heat-processed for 5 minutes at 98°C prior to the RT-qPCR reaction.
A COVID-19 Infection Risk Model for Frontline Health Care Workers
Authors: Dy Louie Florendo , Rabajante Jomar Fajardo
Published: March 2020

The number of confirmed COVID-19 cases admitted in hospitals is continuously increasing in the Philippines. Frontline health care workers are faced with imminent risks of getting infected. In this study, we formulate a theoretical model to calculate the risk of being infected in health care facilities considering the following factors: the average number of encounters with a suspected COVID-19 patient per hour; interaction time for each encounter; work shift duration or exposure time; crowd density, which may depend on the amount of space available in a given location; and availability and effectiveness of protective gears and facilities provided for the frontline health care workers. Based on the simulation results, a set of risk assessment criteria is proposed to classify risks as ‘low’, ‘moderate’, or ‘high’. We recommend the following: (i) decrease the rate of patient encounter per frontline health care worker, e.g., maximum of three encounters per hour in a 12-hour work shift duration; (ii) decrease the interaction time between the frontline health care worker and the patients, e.g., less than 40 minutes for the whole day; (iii) increase the clean and safe space for social distancing, e.g., maximum of 10% crowd density, and if possible, implement compartmentalization of patients; and/or (iv) provide effective protective gears and facilities, e.g., 95% effective, that the frontline health care workers can use during their shift. Moreover, the formulated model can be used for other similar scenarios, such as identifying infection risk in public transportation, school classroom settings, offices, and mass gatherings.
Gestational-age-dependent development of the neonatal metabolome
Authors: Ernst Madeleine , Rogers Simon , Lausten-Thomsen Ulrik , Björkbom Anders , Laursen Susan Svane , Courraud Julie , Børglum Anders , Nordentoft Merete , Werge Thomas , Mortensen Preben Bo , Hougaard David M , S.Cohen Arieh
Published: March 2020

Background

Prematurity is a severe pathophysiological condition associated with increased morbidity and mortality; however, little is known about the gestational-age-dependent development of the neonatal metabolome.

Methods

Using an untargeted liquid chromatography tandem mass spectrometry (LC-MS/MS) metabolomics protocol we measured over 6000 metabolites in 148 neonatal heel prick dried blood spots retrieved from the Danish Neonatal Screening Biobank. Using a combination of state-of-the-art metabolome mining tools, including mass spectral molecular networking (GNPS), unsupervised substructure discovery (MS2LDA) andin silicostructure annotation, we retrieved chemical structural information at a broad level for over 4000 (60%) metabolites and assessed their relation to gestational age.

Results

A total of 744 (∼12%) metabolites were significantly correlated with gestational age (false-discovery-rate-adjustedP< 0.05), whereas 93 metabolites were strongly predictive of gestational age, explaining on average 37% of the variance. Using a custom algorithm based on hypergeometric testing we identified 17 molecular families (230 metabolites) overrepresented with metabolites correlating with gestational age (P< 0.01). Metabolites significantly related to gestational age included bile acids, carnitines, polyamines, amino-acid-derived compounds, nucleotides, dipeptides as well as treatment-related metabolites such as antibiotics and caffeine.

Conclusions

Carnitines, bile acids, as well as amino acid-derived compounds are known to be affected by the gut microbiota, whereas polyamines such as spermine and spermidine may play an important role in regulating (epithelial) cell growth. Our findings reveal for the first time the gestational-age-dependent development of the neonatal blood metabolome and suggest that gut microbial and gestational-age-dependent metabolic maturation may be monitored during newborn screening.
Potential roles of social distancing in mitigating the spread of coronavirus disease 2019 (COVID-19) in South Korea
Authors: Park Sang Woo , Sun Kaiyuan , Viboud Cécile , Grenfell Bryan T. , Dushoff Jonathan
Published: March 2020

On January 20, 2020, the first COVID-19 case was confirmed in South Korea. After a rapid outbreak, the number of incident cases has been consistently decreasing since early March; this decrease has been widely attributed to its intensive testing. We report here on the likely role of social distancing in reducing transmission in South Korea. Our analysis suggests that transmission may still be persisting in some regions.
In Vivo Localization of Deep Brain Implants in Mice
Authors: Király Bálint , Balázsfi Diána , Horváth Ildikó , Solari Nicola , Sviatkó Katalin , Lengyel Katalin , Birtalan Eszter , Máthé Domokos , Szigeti Krisztián , Hangya Balázs
Published: March 2020

Electrophysiology provides a direct readout of neuronal activity at a temporal precision only limited by the sampling rate. However, interrogating deep brain structures, implanting multiple targets or aiming at unusual angles still poses significant challenges even for expert operators, and errors are only discovered by post-hoc histological reconstruction. Here, we propose a method combining the high-resolution information about bone landmarks provided by micro-CT scanning with the soft tissue contrast of the MRI, which allowed us to precisely localize electrodes and optic fibers in mice in vivo. This enables arbitrating the success of implantation directly after surgery with a precision comparable to the gold standard histological reconstruction. Adjustment of the recording depth with electrode microdrives or early termination of unsuccessful experiments saves many working hours, while fast 3-dimensional feedback helps surgeons to avoid systematic errors. Increased aiming precision will allow more precise targeting of small or deep brain nuclei and multiple targeting of specific cortical layers.
Introductory gestures before songbird vocal displays are shaped by learning and biological predispositions
Authors: Kalra Shikha , Yawatkar Vishruta , James Logan S , Sakata Jon T , Rajan Raghav
Published: March 2020

Introductory gestures are present at the beginning of many animal displays. For example, lizards start their head-bobbing displays with introductory push-ups and animal vocal displays begin with introductory notes. Songbirds also begin their vocal displays by repeating introductory notes (INs) before producing their learned song and these INs are thought to reflect motor preparation. Between individuals of a given species, the acoustic structure of INs and the number of times INs are repeated before song varies considerably. While similar variation in songs between individuals is known to be a result of learning, whether INs are also learned remains poorly understood. Here, using natural and experimental tutoring with male zebra finches, we show that mean IN number and IN acoustic structure are learned from a tutor, independent of song learning. We also reveal biological predispositions in IN production; birds artificially tutored with songs lacking INs still repeated a short-duration syllable, thrice on average, before their songs. Overall, these results show that INs, just like elements in song, are shaped both by learning and biological predispositions and suggest multiple, independent, learning processes underlying the acquisition of complex vocal displays.
Bipartite network analysis of ant-task associations reveals task groups and absence of colonial daily activity
Authors: Fujioka Haruna , Okada Yasukazu , Abe Masato S.
Published: March 2020

Social insects are one of the best examples of complex self-organised systems exhibiting task allocation. How task allocation is achieved is the most fascinating question in behavioural ecology and complex systems science. However, it is difficult to comprehensively characterise task allocation patterns due to behavioural complexity, such as the individual variation, context dependency, and chronological variation. Thus, it is imperative to quantify individual behaviours and integrate them into colony levels. Here, we applied bipartite network analyses to characterise individual-behaviour relationships. We recorded the behaviours of all individuals with verified age in ant colonies and analysed the individual-behaviour relationship at the individual, module, and network levels. Bipartite network analysis successfully detected the module structures, illustrating that certain individuals performed a subset of behaviours (i.e., task groups). We confirmed age polyethism by comparing age between modules. Additionally, to test the daily rhythm of the executed tasks, the data were partitioned between daytime and nighttime, and a bipartite network was re-constructed. This analysis supported that there was no daily rhythm in the tasks performed. These findings suggested that bipartite network analyses could untangle complex task allocation patterns and provide insights into understanding the division of labour.
A Comprehensive Survey of Mutations in Oesophageal Carcinoma Reveals Recurrent Neoantigens as Potential Immunotherapy Targets
Authors: Chen Chao , Liu Songming , Xiong Heng , Zhang Xi , Li Bo
Published: March 2020

This study was aimed to investigate the mutations in Esophageal Carcinoma (EC) for recurrent neoantigen identification. A total of 733 samples with whole exome sequencing (WES) mutation data and 1153 samples with target region sequencing data were obtained from 7 published studies and GENIE database. Common HLA-I and HLA-II genotypes in both TCGA cohort and Chinese were used to predict the probability of ‘public’ neoantigens in the dataset. Based on the integrated data, we not only obtained the most comprehensive EC mutation landscape so far, but also found 253 mutation sites which could be identified in at least 3 or more patients, including,TP53p.R248Q,PIK3CAp.E545K,PIK3CAp.E542K,KRASp.G12D,PIK3CAp.H1047R andTP53p.C83F. These mutations can be recognized by multiple common HLA molecules (HLA-A11:01, HLA-B57:01, HLA-A03:01, DRB1-0301, DRB1-1202, et al.) in Chinese and TCGA cohort as potential public neoantigens. Overall, our analysis provides some potential targets for EC immunotherapy.