bluuebunny/crossref_metadata_2025 huggingface dataset:
Update on Idiopathic Canalicular Inflammatory Disease (ICID): Outcomes With Addition of Topical Cyclosporine and the Modified Treatment Protocol
Authors: Ali Mohammad Javed , Bothra Nandini
Published: April 2020

Purpose:

The objective of this study is to present clinical outcomes with addition of topical cyclosporine while managing cases of “idiopathic canalicular inflammatory disease” and to propose a modified treatment protocol.

Methods:

Prospective case series of 88 canaliculi of 44 eyes of 22 patients diagnosed as “idiopathic canalicular inflammatory disease” at a tertiary care Dacryology service over a period of 2 years. All the patients were diagnosed based on the published major and minor criteria and each of the canaliculus was clinically staged. All patients were treated initially with a combination of topical cyclosporine (0.05%) and rapidly tapering topical steroids followed by punctal dilatation and placement of mini-monoka stents after control of inflammation. Monoka stents were extubated at 6 weeks and the cyclosporine was continued for at least up to 3 months beyond the extubation of stents. Patient demographics, investigations, response to cyclosporine, management modalities, recurrence of inflammation, anatomical and functional outcomes were analyzed.

Results:

Eighty-eight canaliculi were diagnosed to have idiopathic canalicular inflammatory disease during the study period. There was a female preponderance (77%, 17/22) and the mean age at presentation was 51 years. All patients presented with bilateral epiphora (mean duration 4.5 months) without any discharge. Staging revealed 18, 27, 24, and 19 canaliculi were involved with stages 1–4, respectively. The mean duration of cyclosporine use was 5.7 months. All patients except 3 (19/22) underwent monoka dilatation. Complete anatomical and functional resolution were noted in 62% (55/88), of which 12 puncta and canaliculi, all stage 1 (13.6%, 12/88) showed complete resolution with cyclosporine alone. Relentless disease progression to stage 5 was noted in 30% (26/88) of the puncta and canaliculi. All the younger patients (<30 years, 13.6%, 3/22) demonstrated poor outcomes.

Conclusions:

The addition of topical cyclosporine is beneficial in controlling inflammation and disease downstaging in patients with idiopathic canalicular inflammatory disease. The current modified treatment protocol salvages majority of the canaliculi.
Unintentional Manganese Delivery in Neonatal Parenteral Nutrition
Authors: Sauberan Jason B. , Katheria Anup C.
Published: April 2020

Iatrogenic manganese (Mn) neurotoxicity is a safety concern in neonates receiving parenteral nutrition (PN). Prior studies suggest Mn contamination of PN ingredients represents an unintended source of Mn delivery. In order to determine the relative contribution of unsourced Mn to total Mn exposure in neonatal PN, this study measured Mn concentrations in neonatal PN solutions using inductively coupled plasma mass spectrometry. Solutions prepared using a standard fixed dose neonatal multiple trace element product were compared with test solutions prepared using individual trace element ingredients not including Mn. The standard solutions (n = 6) contained a mean (SD) Mn concentration of 56.63 μg/L (0.94), compared with 6.04 μg/L (0.39) in the test solutions without added Mn (n = 6). This study suggests that neonatal PN contains significant quantities of Mn not intentionally added during PN preparation. Further studies are needed to identify individual ingredient sources of unintentional Mn, and the feasibility of Mn omission strategies.
Equivalent Survival of p53 Mutated Endometrial Endometrioid Carcinoma Grade 3 and Endometrial Serous Carcinoma
Authors: Brett Mary Anne , Atenafu Eshetu G. , Singh Nilanchali , Ghatage Prafull , Clarke Blaise A. , Nelson Gregg S. , Bernardini Marcus Q. , Köbel Martin
Published: April 2020

TP53 status is the most important prognostic biomarker in endometrial carcinoma. We asked the question whether p53 mutated endometrial endometrioid carcinomas grade 3 (EEC3) or endometrial serous carcinomas (ESC), the latter ubiquitously harboring TP53 mutation, have different outcomes. TP53 mutation status was assessed by surrogate p53 immunohistochemistry on 326 EEC3 and ESC from 2 major cancer centers in Canada. Mutant-type p53 expression, including overexpression, complete absence, or cytoplasmic expression, was distinguished from the wild-type pattern. Statistical associations with clinico-pathological parameter, other key biomarkers, and survival analyses were performed. P53 mutant-type immunohistochemistry was observed in all 126 ESC and in 47/200 (23.5%) EEC3. ESC and p53 mutated EEC3 had an unfavorable outcome compared with p53 wild-type EEC3 (hazard ratio=2.37, 95% confidence interval=1.48–3.80, P=0.003, hazard ratio=2.19, 95% confidence interval=1.16–4.12, P=0.016, respectively) in multivariable analyses adjusted for age, stage, center, and presence of lymph-vascular invasion. There was no significant difference in survival between ESC and p53 mutated EEC3 in multivariable analysis. Furthermore, p53 mutated EEC3 and ESC almost completely overlapped in univariate survival analysis when mismatch repair (MMR)-deficient cases were excluded, which suggests that EEC3 harboring combined MMR deficiency and TP53 mutations behave more according to the MMR status. Significant differences between p53 mutated MMR-proficient EEC3 and ESC in PTEN and p16 expression status remained. p53 mutated, MMR-proficient EEC3 and ESC have overlapping survival significantly different from p53 wild-type EEC3, which justifies a similar treatment with current non-targeted standard therapy. Although this is so, separate classification should continue due to biological differences that will become important for future targeted therapy.
Cultivable Bacteria in Urine of Women With Interstitial Cystitis: (Not) What We Expected
Authors: Jacobs Kristin M. , Price Travis K. , Thomas-White Krystal , Halverson Thomas , Davies Abigail , Myers Deborah L. , Wolfe Alan J.
Published: April 2020

Objective

Multiple studies show cultivatable bacteria in urine of most women. The existence of these bacteria challenges interstitial cystitis (IC)/painful bladder syndrome (PBS) diagnosis, which presumes a sterile bladder. The aims of this study were (1) to compare the female bladder microbiomes in women with IC/PBS and unaffected controls and (2) to correlate baseline bladder microbiome composition with symptoms.

Methods

This cross-sectional study enrolled 49 IC/PBS and 40 controls. All provided catheterized urine samples and completed validated questionnaires. A subset of the IC/PBS cohort provided voided and catheterized urine samples. All samples from both cohorts were assessed by the expanded quantitative urine culture (EQUC) protocol; a subset was assessed by 16S rRNA gene sequencing.

Results

Of the IC/PBS cohort, 49.0% (24/49) were EQUC positive; in these EQUC-positive samples, the most common urotypes were Lactobacillus (45.8%) and Streptococcus (33.3%). Of the controls, 40.0% were EQUC positive; of these EQUC-positive samples, the most common urotype was Lactobacillus (50.0%). The urotype distribution was significantly different (P < 0.05), as 16% of the IC/PBS cohort, but 0% of controls, were Streptococcus urotype (P < 0.01). Symptom-free IC/PBS participants were less likely to be EQUC positive (12.5%) than IC/PBS participants with moderate or severe symptoms (68.8% and 46.2%) and the control cohort (60%; P < 0.05).

Conclusion

Lactobacillus was the most common urotype. However, the presence of Lactobacillus did not differ between cohorts, and it did not impact IC/PBS symptom severity. Bacteria were not isolated from most participants with active IC/PBS symptoms. These findings suggest that bacteria may not be an etiology for IC/PBS.
United States Special Operations Command fatality study of subcommands, units, and trends
Authors: Kotwal Russ S. , Mazuchowski Edward L. , Howard Jeffrey T. , Janak Jud C. , Harcke Howard T. , Montgomery Harold R. , Butler Frank K. , Holcomb John B. , Eastridge Brian J. , Gurney Jennifer M. , Shackelford Stacy A.
Published: April 2020

BACKGROUND

Death from injury occurs predominantly in prehospital settings. Injury prevention and prehospital care of military forces is the responsibility of combatant commanders. Medical examiner and trauma systems should routinely study fatalities and inform commanders of mortality trends.

METHODS

Data reported on US Special Operations Command (USSOCOM) fatalities who died while performing duties from September 11, 2001, to September 10, 2018, were reevaluated to compare subcommands, units, and trends. Injury was assessed by mechanism, severity, operational posture, and survivability. Death was assessed by manner, cause, classification, mechanism, and preventability.

RESULTS

Of 614 USSOCOM fatalities (median age, 30 years; male, 98.5%), 67.6% occurred in the Army command, of which 49.2% occurred in the Special Forces command. Battle injury accounted for 60.1% of USSOCOM fatalities. Most battle-injured fatalities in each subcommand had nonsurvivable injuries and nonpreventable deaths. For each subcommand except Marine Corps, fatalities with nonsurvivable injuries sustained injuries primarily while mounted. By subcommand, the primary cause of death for fatalities with nonsurvivable injuries was blast for Army (57.6%), multiple/blunt force for Navy (60.0%), gunshot wound for Air Force (55.6%), and split between blast (50.0%) and gunshot wound (50.0%) for Marine Corps. For each subcommand except Air Force, fatalities with potentially survivable-survivable injuries sustained injuries primarily while dismounted, and the mechanism of death was primarily hemorrhage plus other mechanism or hemorrhage alone. Hemorrhage only mechanism of death was surpassed over time by complex multimechanism death. Potential for injury survivability and death preventability was greatest during early and later years of conflict.

CONCLUSION

Organizational differences in mortality characteristics and trends were identified from which commanders can refine efforts to prevent and treat injury and improve survival. Fatality analyses inform operational risk matrices and advance casualty prevention and response efforts. Prevention, assessment, and treatment strategies must evolve to reduce death from hemorrhage plus coexisting mechanisms.

LEVEL OF EVIDENCE

Performance Improvement and Epidemiological, level IV.
Tranexamic acid in pediatric combat trauma requiring massive transfusions and mortality
Authors: Hamele Mitchell , Aden James K. , Borgman Matthew A.
Published: April 2020

BACKGROUND

Tranexamic acid (TXA) has been demonstrated to decrease mortality in adult trauma, particularly in those with massive transfusions needs sustained in combat injury. Limited data are available for the efficacy of TXA in pediatric trauma patients outside of a single combat support hospital in Afghanistan.

METHODS

The Department of Defense Trauma Registry was queried for trauma patients younger than 18 years from Iraq and Afghanistan requiring 40 mL/kg or greater of blood product within 24 hours of injury. Burns and fatal head traumas were excluded. Primary outcome was in-hospital mortality. Secondary outcomes were hospital, ventilator, and intensive care unit–free days, as well as total blood product volume.

RESULTS

Among those pediatric patients receiving massive transfusions, those who received TXA were less likely to die in hospital (8.5% vs. 18.3%). Patients who received TXA and those who did not have similar hospital-free days (19 vs. 20), ventilator-free days (27 vs. 27), and intensive care unit–free days (25 vs. 24). Those who received TXA had higher 24-hour blood product administration (100 mL/kg vs. 75 mL/kg). None of our results rose to the level of statistical significance. The TXA administration significantly reduced odds of death on logistic regression (odds ratio, 0.35; 95% confidence interval, 0.123–0.995; p = 0.0488).

CONCLUSION

Use of TXA in pediatric patients with combat trauma requiring massive transfusions trended toward a significant improvement in in-hospital mortality (p = 0.055). This mortality benefit is similar to that seen in adult studies and a less well characterized cohort in another pediatric study suggesting TXA administration confers mortality benefit in massively transfused pediatric combat trauma victims.

LEVEL OF EVIDENCE

Evidence (retrospective cohort), Level IV
Disparity in Accessibility to and Prognosis of Kidney Transplantation According to Economic Inequality in South Korea: A Widening Gap After Expansion of Insurance Coverage
Authors: Park Sehoon , Park Gi Chan , Park Jina , Kim Ji Eun , Yu Mi-yeon , Kim Kwangsoo , Park Minsu , Kim Yong Chul , Kim Dong Ki , Joo Kwon Wook , Kim Yon Su , Lee Hajeong
Published: April 2020

Background.

Nationwide studies on the effects of wealth inequality on kidney transplantation are rare, particularly in a country with an expanded National Health Insurance Service and in Asian countries.

Methods.

In this nationwide, population-based cohort study, we reviewed the national claims database of Korea in which details of nationwide health insurance are provided. From 2007 to 2015, 9 annual cohorts of end-stage renal disease patients were included. The annual financial statuses were collected and stratified into 5 subgroups in each year: the aided group in which insurance fee was waived and the 4 other groups divided by quartiles of their medical insurance fee. Time trends of incidence proportion of kidney transplantation among end-stage renal disease patients in each year were initially assessed. The risk of graft failure, both including death-censored graft failure and death with a functioning graft, was analyzed as a prognostic outcome within the transplant recipients.

Results.

Significant disparity in the accessibility of kidney transplantation was present, and it was further widening, particularly from 2009 in which the National Health Insurance Service started to cover desensitized kidney transplantation. Desensitized or preemptive transplantation was less common in the poorest group who were more frequently receiving transplantation after 5 years of dialysis in the latter years. The prognosis of kidney transplantation was significantly worse in the poorer people, and this disparity also worsened during the study period.

Conclusions.

Prominent disparity regarding accessibility to and prognosis of kidney transplantation was observed in Korea according to wealth inequality, and this disparity was worsening.
Comprehensive evaluation system for stability of multiple dams in a uranium tailings reservoir: based on the TOPSIS model and bow tie model
Authors: Jiang Fuliang , Wu Haonan , Liu Yong , Chen Guan , Guo Jintao , Wang Zhe
Published: April 2020

The main purposes of this study are to analyse the evaluation of tailings dam stability under multiple factors and prevent accidents more effectively by proposing a composite risk analysis model. The evaluation model combining the TOPSIS model and bow tie model is presented in this paper. Firstly, a new formula was adopted to calculate the integrated weights based on the subjective and objective weights and the theory of the TOPSIS model was introduced. Secondly, taking a uranium tailings reservoir in south China as an example, the index values and constant weights of the 10 dams are determined according to eight aspects of accumulating dam crest elevation, dam slope, mechanical properties, seepage capacity, topographical conditions, flood control capacity, rainstorm resistance capacity and earthquake resistance capacity. Thirdly, the fitting degree between the stability and ideal solution of each dam is calculated by using the TOPSIS model. The stability fitting degree of the 10 dams is 76%, 93%, 82%, 90%, 66%, 79%, 85%, 96%, 32%, 89% in sequence. This result shows that among the 10 dams, the 9
#
dam ranks the lowest in stability. The actual results are in good consistency with those calculated by the TOPSIS model, which can provide a scientific and reliable new idea for the safety of other multi-index comprehensive evaluations. It is worth mentioning that it can still maintain high accuracy of dam stability evaluation under multiple indexes and multiple dams. Also, the comprehensive evaluation model proposed in this paper can more effectively reflect the subtle differences between similar evaluation objects. Fourthly, safety barriers from both the cause of the accident and the consequences was established by using the bow tie model to block the path of the accident, and to propose safety measures to make the evaluation system more complete.
Magnetic nanoparticles assisted dispersive liquid–liquid microextraction of chloramphenicol in water samples
Authors: Saad Salwani Md , Aling Nur Afiqah , Miskam Mazidatulakmam , Saaid Mardiana , Mohamad Zain Nur Nadhirah , Kamaruzaman Sazlinda , Raoov Muggundha , Mohamad Hanapi Nor Suhaila , Wan Ibrahim Wan Nazihah , Yahaya Noorfatimah
Published: April 2020

This work describes the development of a new methodology based on magnetic nanoparticles assisted dispersive liquid–liquid microextraction (DLLME-MNPs) for preconcentration and extraction of chloramphenicol (CAP) antibiotic residues in water. The approach is based on the use of decanoic acid as the extraction solvent followed by the application of MNPs to magnetically retrieve the extraction solvent containing the extracted CAP. The coated MNPs were then desorbed with methanol, and the clean extract was analysed using ultraviolet–visible spectrophotometry. Several important parameters, such as the amount of decanoic acid, extraction time, stirring rate, amount of MNPs, type of desorption solvent, salt addition and sample pH, were evaluated and optimized. Optimum parameters were as follows: amount of decanoic acid: 200 mg; extraction time: 10 min; stirring rate: 800 rpm; amount of MNPs: 60 mg; desorption solvent: methanol; salt: 10%; and sample pH, 8. Under the optimum conditions, the method demonstrated acceptable linearity (
R
2
= 0.9933) over a concentration range of 50–1000 µg l
–1
. Limit of detection and limit of quantification were 16.5 and 50.0 µg l
–1
, respectively. Good analyte recovery (91–92.7%) and acceptable precision with good relative standard deviations (0.45–6.29%,
n
= 3) were obtained. The method was successfully applied to tap water and lake water samples. The proposed method is rapid, simple, reliable and environmentally friendly for the detection of CAP.
Can N95 respirators be reused after disinfection? And for how many times?
Authors: Liao Lei , Xiao Wang , Zhao Mervin , Yu Xuanze , Wang Haotian , Wang Qiqi , Chu Steven , Cui Yi
Published: April 2020

The Coronavirus Disease 2019 (COVID-19) pandemic has led to a major shortage of N95 respirators, which are essential to protecting healthcare professionals and the general public who may come into contact with the virus. Thus, it is essential to determine how we can reuse respirators and other personal protection in these urgent times. We investigated multiple commonly used and easily deployable, scalable disinfection schemes on media with particle filtration efficiency of 95%. Among these, heating (≤85 °C) under various humidities (≤100% RH) was the most promising, nondestructive method for the preservation of filtration properties in meltblown fabrics as well as N95-grade respirators. Heating can be applied up to 50 cycles (85 °C, 30% RH) without observation in the degradation of meltblown filtration performance. Ultraviolet (UV) irradiation was a secondary choice which was able to withstand 10 cycles of treatment and showed small degradation by 20 cycles. However, UV can also potentially impact the material strength and fit of respirators. Finally, treatments involving liquids and vapors require caution, as steam, alcohol, and household bleach may all lead to degradation of the filtration efficiency, leaving the user vulnerable to the viral aerosols.
Trading accuracy for speed over the course of a decision
Authors: Derosiere Gerard , Thura David , Cisek Paul , Duque Julie
Published: April 2020

Humans and other animals often need to balance the desire to gather sensory information (to make the best choice) with the urgency to act, facing a speed-accuracy tradeoff (SAT). Given the ubiquity of SAT across species, extensive research has been devoted to understanding the computational mechanisms allowing its regulation at different timescales, including from one context to another, and from one decision to another. However, animals must frequently change their SAT on even shorter timescales –i.e., over the course of an ongoing decision – and little is known about the mechanisms that allow such rapid adaptations. The present study aimed at addressing this issue. Human subjects performed a decision task with changing evidence. In this task, subjects received rewards for correct answers but incurred penalties for mistakes. An increase or a decrease in penalty occurring halfway through the trial promoted rapid SAT shifts, favoring speeded decisions either in the early or in the late stage of the trial. Importantly, these shifts were associated with stage-specific adjustments in the accuracy criterion exploited for committing to a choice. Those subjects who decreased the most their accuracy criterion at a given decision stage exhibited the highest gain in speed, but also the highest cost in terms of performance accuracy at that time. Altogether, the current findings offer a unique extension of previous work, by suggesting that dynamic changes in accuracy criterion allow the regulation of the SAT within the timescale of a single decision.

New and noteworthy

Extensive research has been devoted to understanding the mechanisms allowing the regulation of the speed-accuracy tradeoff (SAT) from one context to another and from one decision to another. Here, we show that humans can voluntarily change their SAT on even shorter timescales –i.e., over the course of a decision. These rapid SAT shifts are associated with dynamic adjustments in the accuracy criterion exploited for committing to a choice.
An “Infodemic”: Leveraging High-Volume Twitter Data to Understand Public Sentiment for the COVID-19 Outbreak
Authors: Medford Richard J. , Saleh Sameh N. , Sumarsono Andrew , Perl Trish M. , Lehmann Christoph U.
Published: April 2020

Background

Twitter has been used to track trends and disseminate health information during viral epidemics. On January 21, 2020, the CDC activated its Emergency Operations Center and the WHO released its first situation report about Coronavirus disease 2019 (COVID-19), sparking significant media attention. How Twitter content and sentiment has evolved in the early stages of any outbreak, including the COVID-19 epidemic, has not been described.

Objective

To quantify and understand early changes in Twitter activity, content, and sentiment about the COVID-19 epidemic.

Design

Observational study.

Setting

Twitter platform.

Participants

All Twitter users who created or sent a message from January 14th to 28th, 2020.

Measurements

We extracted tweets matching hashtags related to COVID-19 and measured frequency of keywords related to infection prevention practices, vaccination, and racial prejudice. We performed a sentiment analysis to identify emotional valence and predominant emotions. We conducted topic modeling to identify and explore discussion topics over time.

Results

We evaluated 126,049 tweets from 53,196 unique users. The hourly number of COVID-19-related tweets starkly increased from January 21, 2020 onward. Nearly half (49.5%) of all tweets expressed fear and nearly 30% expressed surprise. The frequency of racially charged tweets closely paralleled the number of newly diagnosed cases of COVID-19. The economic and political impact of the COVID-19 was the most commonly discussed topic, while public health risk and prevention were among the least discussed.

Conclusion

Tweets with negative sentiment and emotion parallel the incidence of cases for the COVID-19 outbreak. Twitter is a rich medium that can be leveraged to understand public sentiment in real-time and target public health messages based on user interest and emotion.

Funding

None.
Autocatalytic Model for Covid-19 Progression in a Country
Authors: Chernyshev Anatoly
Published: April 2020

Herewith we present a computational model for the forecasting of cumulative diagnosed cases of Covid-19 pneumonia within a country. The only explicit parameter of the model is the population density. The implicit parameter is a moving average ambient temperature, currently integrated into the kinetic constants. Other finer details pertaining to the mechanism of the pathogen SARS-CoV-2 spread within a given region are implicitly manifested in the exponent parameters derived from the non-linear fitting of the published data on Covid-19 occurrence. The performance of the model is demonstrated on a few selected countries, and on the Diamond Princess cruising ship outbreak. The model might be used as an aiding tool for the policy makers regarding the decisions on the containment measures and quarantine regime required.
COVID-19 diagnosis prediction in emergency care patients: a machine learning approach
Authors: de Moraes Batista André Filipe , Miraglia João Luiz , Rizzi Donato Thiago Henrique , Porto Chiavegatto Filho Alexandre Dias
Published: April 2020

The coronavirus disease (COVID-19) pandemic has increased the necessity of immediate clinical decisions and effective usage of healthcare resources. Currently, the most validated diagnosis test for COVID-19 (RT-PCR) is in shortage in most developing countries, which may increase infection rates and delay important preventive measures. The objective of this study was to predict the risk of positive COVID-19 diagnosis with machine learning, using as predictors only results from emergency care admission exams. We collected data from 235 adult patients from the Hospital Israelita Albert Einstein in São Paulo, Brazil, from 17 to 30 of March, 2020, of which 102 (43%) received a positive diagnosis of COVID-19 from RT-PCR tests. Five machine learning algorithms (neural networks, random forests, gradient boosting trees, logistic regression and support vector machines) were trained on a random sample of 70% of the patients, and performance was tested on new unseen data (30%). The best predictive performance was obtained by the support vector machines algorithm (AUC: 0.85; Sensitivity: 0.68; Specificity: 0.85; Brier Score: 0.16). The three most important variables for the predictive performance of the algorithm were the number of lymphocytes, leukocytes and eosinophils, respectively. In conclusion, we found that targeted decisions for receiving COVID-19 tests using only routinely-collected data is a promising new area with the use of machine learning algorithms.
Predict the next moves of COVID-19: reveal the temperate and tropical countries scenario
Authors: Hasan Neaz A. , Haque Mohammad Mahfujul
Published: April 2020

The spread of COVID-19 engulfs almost all the countries and territories of the planet, and infections and fatality are increasing rapidly. The first epi-center of its’ massive spread was in Wuhan, Hubei province, China having a temperate weather, but the spread has got an unprecedented momentum in European temperate countries mainly in Italy and Spain (as of March 30, 2020). However, Malaysia and Singapore and the neighboring tropical countries of China got relatively low spread and fatality that created a research interest on whether there are potential impacts of weather condition on COVID-19 spread. Adopting the SIR (Susceptible Infected Removed) deviated model to predict potential cases and death in the coming days from COVID-19 was done using the secondary and official sources of data. This study shows that COVID-19 spread and fatality tend to be high across the world but compared to tropical countries, it is going to be incredibly high in the temperate countries having lower temperature (7-16°C) and humidity (80-90%) in last March. However, some literature predicted that this might not to be true, rather irrespective of weather conditions there might be a continuous spread and death. Moreover, a large number of asymptotic COVID-19 carrier in both temperate and tropical countries may re-outbreak in the coming winter. Therefore, a comprehensive global program with the leadership of WHO for testing of entire population of the world is required, which will be very useful for the individual states to take proper political action, social movement and medical services.
Community responses during early phase of the COVID-19 epidemic: a cross-sectional study
Authors: Delshad Mohammad Hossein , Pourhaji Fatemeh , Pourhaji Fahimeh , Ghanbarizadeh Saeed Reza , Zarmehri Hassan Azhdari , Bazrafshan Edris , Gholian-Aval Mahdi
Published: April 2020

Community responses are important for outbreak management during the early phase when preventive interventions are the major options. Therefore, this study aims to examine the behavioral responses of the community during the early phase of the COVID-19 epidemic in the Razavi Khorasan Province of Iran. A cross-sectional online survey was proceeded after confirmed COVID-19 in Iran. The population of the study was 500 residents of Razavi Khorasan areas were randomly surveyed. The research tool was demographic and risk perception questionnaire and Anxiety was assessed using the 7-item GAD Scale. The data analyzed using the SPSS statistical version (V.20). The means of age participants was 31.9±11.9. The mean GAD-7 scores were 6.4±5.2 and 92.4% had moderate or severe anxiety (GAD-7 score ≥10). Many respondents reported their health status were very good or good (62.2 %; 311/500). About a quarter of them had respiratory symptoms in the past 14 days and experienced 20% of them travelled outside the Razavi Khorasan Province in the previous. Risk perception toward COVID-19 in the community of the Razavi Khorasan Province was moderate. Most participants are alert to disease progression. This study suggested timely behavioral assessment of the community is beneficial and effective to inform next intervention, and risk communication strategies in epidemic disease.
COVID-19 higher induced mortality in Chinese regions with lower air quality
Authors: Pansini Riccardo , Fornacca Davide
Published: April 2020

COVID-19 has spread in all continents in a span of just over three months, escalating into a pandemic that poses several humanitarian as well as scientific challenges. We here investigated the geographical expansion of the infection and correlate it with the annual indexes of air quality observed from the Sentinel-5 satellite orbiting around China, Italy and the U.S.A. Controlling for population size, we find more viral infections in those areas afflicted by Carbon Monoxide (CO) and Nitrogen Dioxide (NO2). Higher mortality was also correlated with poor air quality, namely with high PM2.5, CO and NO2 values. In Italy, the correspondence between poor air quality and SARS-CoV-2 appearance and induced mortality was the starkest. Similar to smoking, people living in polluted areas are more vulnerable to SARS-CoV-2 infections and induced mortality. This further suggests the detrimental impact climate change will have on the trajectory of future epidemics.

Significance

We found a significant correlation between levels of air quality and COVID-19 spread and mortality in China, Italy and the United States. Despite the infection being still ongoing at a global level, these correlations are relatively robust not being influenced by varying population densities. Living in an area with low air quality seems to be a risk factor for becoming infected and dying from this new form of coronavirus.
Neural basis of common-pool resources exploitation
Authors: Martinez-Saito Mario , Andraszewicz Sandra , Klucharev Vasily , Rieskamp Jörg
Published: April 2020

Why do people often exhaust unregulated common (shared) natural resources but manage to preserve similar private resources? To answer this question, in the present work we combine a neurobiological, economic, and cognitive modeling approach. Using functional magnetic resonance imaging on 50 participants, we show that sharp depletion of common and private resources is associated with deactivation of the ventral striatum, a brain region involved in the valuation of outcomes. Across individuals, when facing a common resource, ventral striatal activity is anti-correlated with resource preservation (less harvesting), whereas with private resources the opposite pattern is observed. This indicates that neural value signals distinctly modulate behavior in response to the depletion of common versus private resources. Computational modeling suggest that over-harvesting of common resources is facilitated by the modulatory effect of social comparison on value signals. In sum, the results provide an explanation of people’s tendency to over-exploit unregulated common natural resources.
Load adaptation of endocytic actin networks
Authors: Kaplan Charlotte , Kenny Sam J. , Chen Xuyan , Schöneberg Johannes , Sitarska Ewa , Diz-Muñoz Alba , Akamatsu Matthew , Xu Ke , Drubin David G.
Published: April 2020

Clathrin-mediated endocytosis (CME) robustness under elevated membrane tension is maintained by actin assembly-mediated force generation. However, whether more actin assembles at endocytic sites in response to increased load, as has been observed in lamellipodia, has not previously been investigated. Here actin network ultrastructure at CME sites was examined under low and high membrane tension. Actin and N-WASP spatial organization indicate that actin polymerization initiates at the base of clathrin-coated pits and that the network then grows away from the plasma membrane. Actin network height at individual CME sites was not coupled to coat shape, raising the possibility that local differences in mechanical load feedback on assembly. By manipulating membrane tension and Arp2/3 complex activity we tested the hypothesis that actin assembly at CME sites increases in response to elevated load. Indeed, in response to elevated membrane tension, actin grew higher, resulting in greater coverage of the clathrin coat, and CME slowed. When membrane tension was elevated and the Arp2/3 complex was inhibited, shallow clathrin-coated pits accumulated, indicating that this adaptive mechanism is especially crucial for coat curvature generation. We propose that actin assembly increases in response to increased load to ensure CME robustness over a range of plasma membrane tensions.
Optical Aberration Correction via Phase Diversity and Deep Learning
Authors: Krishnan Anitha Priya , Belthangady Chinmay , Nyby Clara , Lange Merlin , Yang Bin , Royer Loic A.
Published: April 2020

In modern microscopy imaging systems, optical components are carefully designed to obtain diffraction-limited resolution. However, live imaging of large biological samples rarely attains this limit because of sample induced refractive index inhomogeneities that create unknown temporally variant optical aberrations. Importantly, these aberrations are also spatially variant, thus making it challenging to correct over wide fields of view. Here, we present a framework for deep-learning based wide-field optical aberration sensing and correction. Our model consists of two modules which take in a set of three phase-diverse images and (i) estimate the wavefront phase in terms of its constituent Zernike polynomial coefficients and (ii) perform blind-deconvolution to yield an aberration-free image. First, we demonstrate our framework on simulations that incorporate optical aberrations, spatial variance, and realistic modelling of sensor noise. We find that our blind deconvolution achieves a 2-fold improvement in frequency support compared to input images, and our phase-estimation achieves a coefficient of determination (r2) of at least 80% when estimating astigmatism, spherical aberration and coma. Second, we show that our results mostly hold for strongly varying spatially-variant aberrations with a 30% resolution improvement. Third, we demonstrate practical usability for light-sheet microscopy: we show a 46% increase in frequency support even in imaging regions affected by detection and illumination scattering.
Comparing Metapopulation Dynamics of Infectious Diseases under Different Models of Human Movement
Authors: Citron Daniel T. , Guerra Carlos A. , Dolgert Andrew J. , Wu Sean L. , Henry John M. , Sánchez C Héctor M. , Smith David L.
Published: April 2020

Newly available data sets present exciting opportunities to investigate how human population movement contributes to the spread of infectious diseases across large geographical distances. It is now possible to construct realistic models of infectious disease dynamics for the purposes of understanding global-scale epidemics. Nevertheless, a remaining unanswered question is how best to leverage the new data to parameterize models of movement, and whether one’s choice of movement model impacts modeled disease outcomes. We adapt three well-studied models of infectious disease dynamics, the SIR model; the SIS model; and the Ross-Macdonald model, to incorporate either of two candidate movement models. We describe the effect that the choice of movement model has on each disease model’s results, finding that in all cases there are parameter regimes where choosing one movement model instead of another has a profound impact on epidemiological outcomes. We further demonstrate the importance of choosing an appropriate movement model using the applied case of malaria transmission and importation on Bioko Island, Equatorial Guinea, finding that one model produces intelligible predictions ofR0while the other produces nonsensical results.

Significance Statement

Newly available large-scale datasets of human population movement represent an opportunity to model how diseases spread between different locations. Combining infectious disease models with mechanistic models of host movement enables studies of how movement drives disease transmission and importation. Here we explore in what ways modeled epidemiological outcomes may be sensitive to the modeler’s choice of movement model structure. We use three different mathematical models of disease transmission to show how a model’s epidemiological predictions can change dramatically depending on the chosen host movement model. We find these different outcomes are robust to using the same data sources to parameterize each candidate model, which we illustrate using an example of real-world malaria transmission and importation in Bioko Island, Equatorial Guinea.
Explaining the “Bomb-Like” Dynamics of COVID-19 with Modeling and the Implications for Policy
Authors: Lin Gary , Strauss Alexandra T. , Pinz Maxwell , Martinez Diego A. , Tseng Katie K. , Schueller Emily , Gatalo Oliver , Yang Yupeng , Levin Simon A. , Klein Eili Y. ,   For the CDC MInD-Healthcare Program
Published: April 2020

Using a Bayesian approach to epidemiological compartmental modeling, we demonstrate the “bomb-like” behavior of exponential growth in COVID-19 cases can be explained by transmission of asymptomatic and mild cases that are typically unreported at the beginning of pandemic events due to lower prevalence of testing. We studied the exponential phase of the pandemic in Italy, Spain, and South Korea, and found theR0to be 2.56 (95% CrI, 2.41-2.71), 3.23 (95% CrI, 3.06-3.4), and 2.36 (95% CrI, 2.22-2.5) if we use Bayesian priors that assume a large portion of cases are not detected. Weaker priors regarding the detection rate resulted inR0values of 9.22 (95% CrI, 9.01-9.43), 9.14 (95% CrI, 8.99-9.29), and 8.06 (95% CrI, 7.82-8.3) and assumes nearly 90% of infected patients are identified. Given the mounting evidence that potentially large fractions of the population are asymptomatic, the weaker priors that generate the highR0values to fit the data required assumptions about the epidemiology of COVID-19 that do not fit with the biology, particularly regarding the timeframe that people remain infectious. Our results suggest that models of transmission assuming a relatively lowerR0value that do not consider a large number of asymptomatic cases can result in misunderstanding of the underlying dynamics, leading to poor policy decisions and outcomes.
Estimating number of cases and spread of Coronavirus disease 2019 (COVID-19) in the United Kingdom using critical care admissions, February to March 2020
Authors: Jit Mark , Jombart Thibaut , Nightingale Emily S , Endo Akira , Abbott Sam ,   LSHTM Centre for Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Edmunds W John
Published: April 2020

An exponential growth model was fitted to critical care admissions from multiple surveillance databases to determine likely COVID-19 case numbers and growth in the United Kingdom from 16 February – 23 March 2020, after which a national lockdown occurred. We estimate that on 23 March, there were 102,000 (median; 95% credible interval 54,000 - 155,000) new cases and 320 (211 - 412) new critical care reports, with 464,000 (266,000 – 628,000) cumulative cases since 16 February.
A Bayesian Logistic Growth Model for the Spread of COVID-19 in New York
Authors: Bliznashki Svetoslav
Published: April 2020

We use Bayesian Estimation for the logistic growth model in order to estimate the spread of the coronavirus epidemic in the state of New York. Models weighting all data points equally as well as models with normal error structure prove inadequate to model the process accurately. On the other hand, a model with larger weights for more recent data points and with t-distributed errors seems reasonably capable of making at least short term predictions.
On predicting the novel COVID-19 human infections by using Infectious Disease modelling method in the Indian State of Tamil Nadu during 2020
Authors: Ayubali Arsath Abbasali , Satheesh Sara Roshini
Published: April 2020

Since the introduction of the novel Corona Virus (The COVID-19) to the Chinese city Wuhan in the Hubei province during the late December 2019, the effectiveness of the deadly disease, its human infection, spreading severity and the mortality rate of the infection has been an issue of debate. The outbreak of the virus along the time has become a massive threat to the global public health security and has been declared as a pandemic. Accounting the radical number of increases in the infected cases and the death due to COVID-19 infections around the globe, there is a need to predict the infections among the people by making proper optimization and using various Infectious Disease modelling (IDM) methods, in order to challenge the outcome. In comparison with previous diseases like SARS and Ebola viruses, the new corona virus (COVID-19) infections are infectious during the incubation period. In addition to that, naturally produced droplets from humans (e.g. droplets produced by breathing, talking, sneezing, coughing) and Person-to-person contact transmission are reported to be the foremost ways of transmission of novel corona virus. By considering the above two factors, a modified SEIR (Susceptibility-Exposure-Infection-Recovery) method have been used for predicting the spread of the infections in the state of Tamil Nadu which is located in the southern part of India. Further, we have utilized the current surveillance data from Health and Family Welfare Department – Government of Tamil Nadu to accurately predict the spreading trend of the infection on a state level.
Increased Detection coupled with Social Distancing and Health Capacity Planning Reduce the Burden of COVID-19 Cases and Fatalities: A Proof of Concept Study using a Stochastic Computational Simulation Model
Authors: Ghosh Pramit , Basheer Salah , Paul Sandip , Chakrabarti Partha , Sarkar Jit
Published: April 2020

Objective

In absence of any vaccine, the Corona Virus Disease 2019 (COVID-19) pandemic is being contained through a non-pharmaceutical measure termed Social Distancing (SD). However, whether SD alone is enough to flatten the epidemic curve is debatable. Using a Stochastic Computational Simulation Model, we investigated the impact of increasing SD, hospital beds and COVID-19 detection rates in preventing COVID-19 cases and fatalities.

Research Design and Methods

The Stochastic Simulation Model was built using the EpiModel package in R. As a proof of concept study, we ran the simulation on Kasaragod, the most affected district in Kerala. We added 3 compartments to the SEIR model to obtain a SEIQHRF (Susceptible-Exposed-Infectious-Quarantined-Hospitalised-Recovered-Fatal) model.

Results

Implementing SD only delayed the appearance of peak prevalence of COVID-19 cases. Doubling of hospital beds couldn’t reduce the fatal cases probably due to its overwhelming number compared to the hospital beds. Increasing detection rates could significantly flatten the curve and reduce the peak prevalence of cases (increasing detection rate by 5 times could reduce case number to half).

Conclusions

An effective strategy to contain the epidemic spread of COVID-19 in India is to increase detection rates in combination with SD measures and increase in hospital beds.

HIGHLIGHTS

Increased Detection of COVID-19 cases must accompany Social Distancing and Health Capacity Planning to reduce the burden of cases and fatalities.

Interruptive Social Distancing is an effective alternative to continuous Social Distancing.

Given the overwhelming burden of COVID-19 fatalities, there is immediate need of co-ordination with the Private Healthcare Sector.

COVID-19 cases will be peaking after May, 2020 giving us time for Healthcare Capacity Building in the government and private sector both.
Tissue-specific multiOMICs analysis of atrial fibrillation
Authors: Assum Ines , Krause Julia , Scheinhardt Markus O. , Müller Christian , Hammer Elke , Börschel Christin S. , Völker Uwe , Conradi Lenard , Geelhoed Bastiaan , Zeller Tanja , Schnabel Renate B. , Heinig Matthias
Published: April 2020

Genome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, novel multiOMICs approaches are needed for deciphering the underlying molecular networks. Here, we integrated genomics, transcriptomics, and proteomics of human atrial tissue which allowed for identifying widespread effects of genetic variants on both transcript (cis eQTL) and protein (cis pQTL) abundance. We further established a novel targeted trans QTL approach based on polygenic risk scores to identify candidates for AF core genes. Using this approach, we identified two trans eQTLs and four trans pQTLs for AF GWAS hits, and elucidated the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multiOMICs method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization.