bluuebunny/crossref_metadata_2025 huggingface dataset:
mmSIM: an open toolbox for accessible structured illumination microscopy
Authors: Russell Craig T. , Shaw Michael
Published: April 2021

Since the first practical super-resolution structured illumination fluorescence microscopes (SIM) were demonstrated more than two decades ago, the method has become increasingly popular for a wide range of bioimaging applications. The high cost and relative inflexibility of commercial systems, coupled with the conceptual simplicity of the approach and the desire to exploit and customize existing hardware, have led to the development of a large number of home-built systems. Several detailed hardware designs are available in the scientific literature, complemented by open-source software tools for SIM image validation and reconstruction. However, there remains a lack of simple open-source software to control these systems and manage the synchronization between hardware components, which is critical for effective SIM imaging. This article describes a new suite of software tools based on the popular Micro-Manager package, which enable the keen microscopist to develop and run a SIM system. We use the software to control two custom-built, high-speed, spatial light modulator-based SIM systems, evaluating their performance by imaging a range of fluorescent samples. By simplifying the process of SIM hardware development, we aim to support wider adoption of the technique.

This article is part of the Theo Murphy meeting issue ‘Super-resolution structured
illumination microscopy (part 1)’.
Niche-specific adaptation of Lactobacillus helveticus strains isolated from malt whisky and dairy fermentations
Authors: Kido Yoshihiko , Maeno Shintaro , Tanno Hiroki , Kichise Yuko , Shiwa Yuh , Endo Akihito
Published: April 2021

Lactobacillus helveticus

is a well characterized lactobacillus for dairy fermentations that is also found in malt whisky fermentations. The two environments contain considerable differences related to microbial growth, including the presence of different growth inhibitors and nutrients. The present study characterized

L. helveticus

strains originating from dairy fermentations (called milk strains hereafter) and malt whisky fermentations (called whisky strains hereafter) by in vitro phenotypic tests and comparative genomics. The whisky strains can tolerate ethanol more than the milk strains, whereas the milk strains can tolerate lysozyme and lactoferrin more than the whisky strains. Several plant-origin carbohydrates, including cellobiose, maltose, sucrose, fructooligosaccharide and salicin, were generally metabolized only by the whisky strains, whereas milk-derived carbohydrates, i.e. lactose and galactose, were metabolized only by the milk strains. Milk fermentation properties also distinguished the two groups. The general genomic characteristics, including genomic size, number of coding sequences and average nucleotide identity values, differentiated the two groups. The observed differences in carbohydrate metabolic properties between the two groups correlated with the presence of intact specific enzymes in glycoside hydrolase (GH) families GH1, GH4, GH13, GH32 and GH65. Several GHs in the milk strains were inactive due to the presence of stop codon(s) in genes encoding the GHs, and the inactivation patterns of the genes encoding specific enzymes assigned to GH1 in the milk strains suggested a possible diversification manner of

L. helveticus

strains. The present study has demonstrated how

L. helveticus

strains have adapted to their habitats.
Genetic determinants of interventricular septal anatomy and the risk of ventricular septal defects and hypertrophic cardiomyopathy
Authors: Yu Mengyao , Harper Andrew R. , Aguirre Matthew , Pittman Maureen , Tcheandjieu Catherine , Amgalan Dulguun , Grace Christopher , Goel Anuj , Farrall Martin , Xiao Ke , Engreitz Jesse , Pollard Katherine , Watkins Hugh , Priest James R.
Published: April 2021

Background

The interventricular septum (IVS) plays a primary role in cardiovascular physiology and a large proportion of genetic risk remains unexplained for structural heart disease involving the IVS such as hypertrophic cardiomyopathy (HCM) and ventricular septal defects (VSD).

Objectives

We sought to develop a reproducible proxy of IVS structure from standard medical imaging, discover novel genetic determinants of IVS structure, and relate these loci to two rare diseases of the IVS.

Methods

We performed machine learning to estimate the cross-sectional area of the interventricular septum (IVS.csad) obtained from the 4-chamber view of cardiac MRI in 32,219 individuals from the UK Biobank. Using these extracted measurement of IVS.csad we performed phenome-wide association to relate this proxy measure to relevant clinical phenotypes, followed by genome-wide association studies and Mendelian Randomization.

Results

Automated measures of IVS.csad were highly accurate, and strongly correlated with anthropometric measures, blood pressure, and diagnostic codes related to cardiovascular physiology. A Single nucleotide polymorphism in the intron ofCDKN1Awas associated with IVS.csad (rs2376620, Beta 8.4 mm2, 95% confidence intervals (CI) 5.8 to 11.0, p=2.0e-10), and a common inversion incorporatingKANSL1predicted to disrupt local chromatin structure was associated with an increase in IVS.csad (Beta 8.6 mm2, 95% CI 6.3-10.9, p=1.3e-13). Mendelian Randomization suggested that inheritance of a larger IVS.csad was causal for HCM (Beta 2.45 log odds ratio (OR) HCM per increase in SD of IVS.csad, standard error (SE) 0.48, pIVW = 2.8e-7) while inheritance of a smaller IVS.csad was causal for VSD (Beta −2.06 log odds ratio (OR) VSD per decrease in SD of IVS.csad, SE 0.75, pIVW = 0.006)

Conclusion

Automated derivation of the cross sectional area of the IVS from the 4-chamber view allowed discovery of loci mapping to genes related to cardiac development and Mendelian disease. Inheritance of a genetic liability for either large or small interventricular septum, appears to confer risk for HCM or VSD respectively, which suggests that a considerable proportion of risk for structural and congenital heart disease may be localized to the common genetic determinants of cardiovascular anatomy.
Stress and Depression in the Workplace of Educators in the Philippines
Authors: Orlanda-Ventayen Caren Casama , Ventayen Randy Joy Magno
Published: April 2021

Workplace Stress and depression should be treated properly in order to maintain productive teaching as the noblest profession. Unmanaged stress and depression could lead to a serious outcome that affects the happy environment in the classroom. Thus, managing stress and avoiding depression in the workplace is one of the important situations that a teacher should aim in order to succeed. This study aims to determine the level of workplace stress and depression of the educators in the Philippines by gathering their profile, workplace stress, and the state of depression. A correlation was investigated if there is a significant difference in the profile to the workplace stress and state of depression. Based on the result of the study, teachers sometimes experience stress in the workplace, while some experience depression at some point in time. It is recommended that teachers should understand how to practice stress management and avoiding depression.
Learning from the resilience of hospitals and their staff to the COVID-19 pandemic: a scoping review
Authors: Traverson Lola , Stennett Jack , Mathevet Isadora , Zacarias Amanda Correia Paes , de Sousa Karla Paz , Andrade Andrea , Zinszer Kate , Ridde Valéry
Published: April 2021

Background

The COVID-19 pandemic has brought huge strain on hospitals worldwide. It is crucial that we gain a deeper understanding of hospital resilience in this unprecedented moment. This paper aims to report the key strategies and recommendations in terms of hospitals and professionals’ resilience to the COVID-19 pandemic, as well as the quality and limitations of research in this field at present.

Methods

We conducted a scoping review of evidence on the resilience of hospitals and their staff during the COVID-19 crisis in the first half of 2020. The Stephen B. Thacker CDC Library website was used to identify papers meeting the eligibility criteria, from which we selected 65 publications. After having extracted data, we presented the results synthesis using an “effects-strategies-impacts” resilience framework.

Results

We found a wealth of research rapidly produced in the first half of 2020, describing different strategies used to improve hospitals’ resilience, particularly in terms of 1) planning, management, and security, and 2) human resources. Research focuses mainly on interventions related to healthcare workers’ well-being and mental health, protection protocols, space reorganization, personal protective equipment and resources management, work organization, training, e-health and the use of technologies. Hospital financing, information and communication, and governance were less represented in the literature.

Conclusion

The selected literature was dominated by quantitative descriptive case studies, sometimes lacking consideration of methodological limitations. The review revealed a lack of holistic research attempting to unite the topics within a resilience framework. Research on hospitals resilience would benefit from a greater range of analysis to draw more nuanced and contextualized lessons from the multiple specific responses to the crisis. We identified key strategies on how hospitals maintained their resilience when confronted with the COVID-19 pandemic and a range of recommendations for practice.
NeMoR: a New Method Based on Data-Driven for Neonatal Mortality Rate Forecasting
Authors: Beluzo Carlos Eduardo , Alves Luciana Correia , Arruda Natália Martins , Sepetauskas Cátia , Silva Everton , Carvalho Tiago
Published: April 2021

Reduction in child mortality is one of the United Nations Sustainable Development Goals for 2030. In Brazil, despite recent reduction in child mortality in the last decades, the neonatal mortality is a persistent problem and it is associated with the quality of prenatal, childbirth care and social-environmental factors. In a proper health system, the effect of some of these factors could be minimized by the appropriate number of newborn intensive care units, number of health care units, number of neonatal incubators and even by the correct level of instruction of mothers, which can lead to a proper care along the prenatal period. With the intent of providing knowledge resources for planning public health policies focused on neonatal mortality reduction, we propose a new data-driven machine leaning method forNeonatalMortalityRate forecasting calledNeMoR, which predicts neonatal mortality rates for 4 months ahead, usingNeoDeathForecast, a monthly base time series dataset composed by these factors and by neonatal mortality rates history (2006-2016), having 57,816 samples, for all 438 Brazilian administrative health regions. In order to build the model, Extra-Tree, XGBoost Regressor, Gradient Boosting Regressor and Lasso machine learning regression models were evaluated and a hyperparameters search was also performed as a fine tune step. The method has been validated using São Paulo city data, mainly because of data quality. On the better configuration the method predicted the neonatal mortality rates with a Mean Square Error lower than 0.18. Besides that, the forecast results may be useful as it provides a way for policy makers to anticipate trends on neonatal mortality rates curves, an important resource for planning public health policies.

Graphical Abstract

Highlights

Proposition of a new data-driven approach for neonatal mortality rate forecast, which provides a way for policy-makers to anticipate trends on neonatal mortality rates curves, making a better planning of health policies focused on NMR reduction possible;

a method for NMR forecasting with a MSE lower than 0.18;

an extensive evaluation of different Machine Learning (ML) regression models, as well as hyperparameters search, which accounts for the last stage in NeMoR;

a new time series database for NMR prediction problems;

a new features projection space for NMR forecasting problems, which considerably reduces errors in NRM prediction.
Role of non-aerosols activities in the transmission of SARS-Cov-2 infection among health care workers
Authors: Paris Christophe , Tadié Emilie , Heslan Christopher , Gary-Bobo Pierre , Oumary Sitty , Sitruk Anaïs , Wild Pascal , Tattevin Pierre , Thibault Vincent , Garlantezec Ronan
Published: April 2021

Background

Since the emergence of SARS-CoV-2, health care workers (HCWs) have been on the front line in caring for COVID-19 patients. Better knowledge of risk factors for SARS-CoV-2 infection is crucial for the prevention of disease among this population.

Methods

We conducted a seroprevalence survey among HCWs in a French university hospital after the first wave (May-June 2020), based on a validated lateral flow immuno-assay test (LFIAT) for SARS-CoV-2. Demographic characteristics as well as data on the working characteristics of COVID-19 and non-COVID-19 wards and 23 care activities were systematically recorded. The effectiveness of protective equipment was also estimated, based on self-declaration of mask use. SARS-CoV-2 IgG status was modelled by multiple imputations approach, accounting for the performance of the test and data on serum validation ELISA immunoassay.

Findings

Among the 3,234 enrolled HCWs, the prevalence of SARS-CoV-2 IgG was 3.8%. Contact with relatives or HCWs who developed COVID-19 were risk factors for SARS-CoV-2 infection, but not contact with COVID-19 patients. In multivariate analyses, suboptimal use of protective equipment during naso-pharyngeal sampling, patient mobilisation, clinical and eye examination was associated with SARS-CoV-2 infection. In addition, patients washing and dressing and aerosol-generating procedures were risk factors for SARS-CoV-2 infection with or without self-declared appropriate use of protective equipment.

Interpretation

Main routes of transmission of SARS-CoV-2 IgG among HCWs were i) contact with relatives or HCWs with COVID-19, ii) close or prolonged contact with patients, iii) aerosol-generating procedures.
COVID-19 pandemic: Analyzing of spreading behavior, the impact of restrictions and prevention measures in Germany and Japan
Authors: Bracke Stefan , Puls Alicia , Inoue Masato
Published: April 2021

In December 2019, the world was confronted with the outbreak of the respiratory disease COVID-19. The COVID-19 epidemic evolved at the beginning of 2020 into a pandemic, which continues to this day. The incredible speed of the spread and the consequences of the infection had a worldwide impact on societies and health systems. Governments enforced many measures to control the COVID-19 pandemic: Restrictions (e.g. lockdown), medical care (e.g. intensive care) and medical prevention (e.g. hygiene concept). This leads to a different spreading behavior of the COVID-19 pandemic, depending on measures. Furthermore, the spreading behavior is influenced by culture and geographical impacts. The spreading behavior of COVID-19 related to short time intervals can be described by Weibull distribution models, common in reliability engineering, in a sound way. The interpretation of the model parameters allows the assessment of the COVID-19 spreading characteristics. This paper shows results of a research study of the COVID-19 spreading behavior depending on different pandemic time phases within Germany and Japan. Both countries are industrial nations, but have many differences with respect to historical development, culture and geographical conditions. Consequently, the chosen government measures have different impacts on the control of the COVID-19 pandemic. The research study contains the analyses of different pandemic time intervals in Germany and Japan: The breakout phase in spring 2020 and subsequently following waves until winter season 2020/2021.
Selective attention is insensitive to reward and to dopamine in Parkinson’s disease
Authors: Pilgrim Matthew , Andy Ou Zhen-Yi , Sharp Madeleine
Published: April 2021

Patients with Parkinson’s disease exhibit reduced reward sensitivity in addition to early cognitive deficits, among which attention impairments are common. Attention allocation is controlled at multiple levels and recent work has shown that reward, in addition to its role in the top-down goal-directed control of attention, also guides the automatic allocation of attention resources, a process thought to rely on striatal dopamine. Whether Parkinson’s patients, due to their striatal dopamine loss, suffer from an inability to use reward information to guide the allocation of their attention is unknown. To address this question, we tested Parkinson’s patients (n=43) ON and OFF their dopaminergic medication, and compared them to a group of older controls (n=31). We used a standard two-phase attention capture task in which subjects were first implicitly trained to make colour-reward associations. In the second phase, the previously reward-associated colours were used as distractors in a visual search task. We found that patients did not use reward information to modulate their attention; they were similarly distracted by the presence of low and high-reward distractors. However, contrary to our predictions, we did not find evidence that dopamine modulated this inability to use reward to guide attention allocation. Additionally, we found slightly increased overall distractibility in Parkinson’s patients compared to older controls, but interestingly, the degree of distractibility was not influenced by dopamine replacement. Our results suggest that loss of reward-guided attention allocation may contribute to early attention deficits and raise the possibility that this inability to prioritize cognitive resource allocation could contribute to executive deficits more broadly in Parkinson’s disease.
Effects of high dosage methamphetamine on glutamatergic neurotransmission in the nucleus accumbens and prefrontal cortex
Authors: Mishra Devesh , Pena-Bravo Jose I , Ghee Shannon M , Berini Carole , Reichel Carmela M , Lavin Antonieta
Published: April 2021

Rationale

Methamphetamine (METH) induces changes in the glutamatergic system and elicits cellular alterations in the cortico-accumbens circuit.

Objective

While there is a body of literature on the effects of METH on dopaminergic transmission, there is a gap in knowledge regarding the effects of a high dose of METH on synaptic glutamatergic neurotransmission, specifically in brain regions involved in goal directed behavior (nucleus accumbens core; NAc core) and executive functions (prefrontal cortex;PFC).

Methods

In order to fill that gap we assessed synaptic glutamatergic transmission using a well established METH administration regime (4 × 4 mg/kg ip at 2 hr intervals) followed by 7 days of abstinence. Rats were then sacrificed and whole cell and field recordings were performed in the NAc core and medial PFC.

Results

METH treatment elicited a significant decrease in paired pulse ratio in NAc core and a significant increase in AMPA/NMDA ratio driven by increases in AMPA currents. On the other hand, there were no significant changes in measures of synaptic glutamate in the PFC.

Conclusion

These results suggest that a high dose of METH treatment followed by a period of abstinence elicits significant increases in indices of glutamatergic transmission in the NAc core with no detectable changes in mPFC, denoting that neurons and glutamate terminals in this limbic region have a higher susceptibility to a neurotoxic METH regime.
Predicting functional effect of missense variants using graph attention neural networks
Authors: Zhang Haicang , Xu Michelle S. , Chung Wendy K. , Shen Yufeng
Published: April 2021

Accurate prediction of damaging missense variants is critically important for interpreting genome sequence. While many methods have been developed, their performance has been limited. Recent progress in machine learning and availability of large-scale population genomic sequencing data provide new opportunities to significantly improve computational predictions. Here we describe gMVP, a new method based on graph attention neural networks. Its main component is a graph with nodes capturing predictive features of amino acids and edges weighted by coevolution strength, which enables effective pooling of information from local protein context and functionally correlated distal positions. Evaluated by deep mutational scan data, gMVP outperforms published methods in identifying damaging variants inTP53, PTEN, BRCA1, andMSH2. Additionally, it achieves the best separation ofde novomissense variants in neurodevelopmental disorder cases from the ones in controls. Finally, the model supports transfer learning to optimize gain- and loss-of-function predictions in sodium and calcium channels. In summary, we demonstrate that gMVP can improve interpretation of missense variants in clinical testing and genetic studies.
Prefusion conformation of SARS-CoV-2 receptor-binding domain favours interactions with human receptor ACE2
Authors: Kumawat Nitesh , Tucs Andrejs , Bera Soumen , Chuev Gennady N. , Fedotova Marina V. , Tsuda Koji , Kruchinin Sergey E. , Sljoka Adnan , Chakraborty Amit
Published: April 2021

A new coronavirus pandemic COVID-19, caused by Severe Acute Respiratory Syndrome coronavirus (SARS-CoV-2), poses a serious threat across continents, leading the World Health Organization to declare a Public Health Emergency of International Concern. In order to block the entry of the virus into human host cells, major therapeutic and vaccine design efforts are now targeting the interactions between the SARS-CoV-2 spike (S) glycoprotein and the human cellular membrane receptor angiotensin-converting enzyme, hACE2. By analyzing cryo-EM structures of SARS-CoV-2 and SARS-CoV-1, we report here that the homotrimer SARS-CoV-2 S receptor-binding domain (RBD) that binds with hACE2 has expanded in size, undergoing a large conformational change relative to SARS-CoV-1 S protein. Protomer with the up-conformational form of RBD, which binds with hACE2, exhibits higher intermolecular interactions at the RBD-ACE2 interface, with differential distributions and the inclusion of specific H-bonds in the CoV-2 complex. Further interface analysis has shown that interfacial water promotes and stabilizes the formation of CoV-2/hACE2 complex. This interaction has caused a significant structural rigidification, favoring proteolytic processing of S protein for the fusion of the viral and cellular membrane. Moreover, conformational dynamics simulations of RBD motions in SARS-CoV-2 and SARS-CoV-1 point to the role in modification in the RBD dynamics and their likely impact on infectivity.
A systematic review on Multisystem Inflammatory Syndrome in Children (MIS-C) with COVID-19: Development of a scoring system for clinical diagnosis
Authors: Surve Suchitra V , Joseph Shaini , Gajbhiye Rahul K , Mahale Smita D , Modi Deepak N
Published: April 2021

Background

There is growing evidence of Multisystem Inflammatory Syndrome in Children (MIS-C) resembling Kawasaki disease in children infected with SARS-CoV-2. The review was undertaken to evaluate the case definition, the spectrum of clinical presentations and current management practices in children with COVID-19 presenting with or without MIS-C.

Methods

The individual patient data from 119 studies accounting for 333 children were analyzed. We devised a scoring system as per WHO criteria to classify the patients as MIS-C or without MIS-C. A score of 3 was given for the presence of fever (>24h) and a score of 1 for lab-confirmed diagnosis of SARS-CoV-2. Additionally, a score of 1 was given for a) rash or conjunctivitis or muco-cutaneous inflammation signs, b) hypotension or shock, c) diarrhea, vomiting or abdominal pain, d) features of myocardial dysfunction as determined by abnormal eco-cardiography or elevated Troponin or N-terminal pro B-type Natriuretic Peptide (NT-proBNP), e) evidence of coagulopathy as evidenced by elevated levels of prothrombin time PT, partial thromboplastin time PTT or D-dimer, f) laboratory evidence of inflammation as determined by elevated erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP) or procalcitonin. A negative score of (−3) was given when there was a diagnosis of sepsis, staphylococcal or streptococcal shock syndrome. Based on these criteria, a minimum score of 6 was essential to classify the child as MIS-C.

Results

Based on this score, 18% (52/289) of cases were identified to be MIS-C. A greater proportion of children with MIS-C had cardiac involvement (MIS-C 80% vs Non-MIS-C 20%) and gastrointestinal involvement (MIS-C 71% vs Non-MIS-C 12%). Lymphopenia was commonly reported in MIS-C (MIS-C 54.2% vs Non-MIS-C 29.7%). In addition to routine inflammatory markers, significantly greater proportion of children with MIS-C had elevated Ferritin, LDH, Fibrinogen and IL-6. Children with MIS-C were less likely to have respiratory symptoms like cough (MIS-C 25% vs Non-MIS-C 75%) and rhinorrhea (MIS-C 4% vs Non-MIS-C 22.8%). A greater proportion of children with MIS-C required intensive care and aggressive treatment; and mortality rates were also higher in MIS-C group (MIS-C 10% vs Non-MIS-C 1%).

Conclusion

The children with COVID-19 having cardiac and/or gastrointestinal involvement are more likely to develop MIS-C. The children with MIS-C have higher mortality rates. The scoring system developed herein will aid clinicians in patient diagnosis and timely management.
Cross-classification between self-rated health and health status: longitudinal analyses of all-cause mortality and leading causes of death in the UK
Authors: Mutz Julian , Lewis Cathryn M.
Published: April 2021

Background

Risk stratification is an important public health priority that is central to clinical decision making and resource allocation. The aim of the present study was to examine how different combinations of self-rated and objective health status predict (i) all-cause mortality and (ii) cause-specific mortality from leading causes of death in the UK.

Methods

The UK Biobank study recruited >500,000 participants, aged 37-73, between 2006–2010. The health cross-classification examined incorporated self-rated health (poor, fair, good or excellent) and health status derived from medical history and current disease status, including 81 cancer and 443 non-cancer illnesses. We examined all-cause mortality and six specific causes of death: ischaemic heart disease, cerebrovascular disease, influenza and pneumonia, dementia and Alzheimer’s disease, chronic lower respiratory disease and malignant neoplasm.

Results

Analyses included>370,000 middle-aged and older adults with a median follow-up of 11.75 (IQR = 1.4) years, yielding 4,320,270 person years of follow-up. Compared to excellent self-rated health and favourable health status, all other levels of the health cross-classification were associated with a greater risk of mortality, with hazard ratios ranging from 1.22 (95% CI 1.15-1.29,pBonf.< 0.001) for good self-rated health and favourable health status to 7.14 (95% CI 6.70-7.60,pBonf.< 0.001) for poor self-rated health and unfavourable health status.

Conclusions

Our findings highlight that self-rated health captures additional health-related information and should be more widely assessed across settings. The cross-classification between health status and self-rated health represents a straightforward metric for risk stratification, with applications to population health, clinical decision making and resource allocation.
Regional opening strategies with commuter testing and containment of new SARS-CoV-2 variants in Germany
Authors: Kühn Martin J. , Abele Daniel , Binder Sebastian , Rack Kathrin , Klitz Margrit , Kleinert Jan , Gilg Jonas , Spataro Luca , Koslow Wadim , Siggel Martin , Meyer-Hermann Michael , Basermann Achim
Published: April 2021

Background

Despite the vaccination process in Germany, a large share of the population is still susceptible to SARS-CoV-2. In addition, we face the spread of novel variants. Until we overcome the pandemic, reasonable mitigation and opening strategies are crucial to balance public health and economic interests.

Methods

We model the spread of SARS-CoV-2 over the German counties by a graph-SIR-type, metapopulation model with particular focus on commuter testing. We account for political interventions by varying contact reduction values in private and public locations such as homes, schools, workplaces, and other. We consider different levels of lockdown strictness, commuter testing strategies, or the delay of intervention implementation. We conduct numerical simulations to assess the effectiveness of the different intervention strategies after one month. The virus dynamics in the regions (German counties) are initialized randomly with incidences between 75-150 weekly new cases per 100,000 inhabitants (red zones) or below (green zones) and consider 25 different initial scenarios of randomly distributed red zones (between 2 and 20 % of all counties). To account for uncertainty, we consider an ensemble set of 500 Monte Carlo runs for each scenario.

Results

We find that the strength of the lockdown in regions with out of control virus dynamics is most important to avoid the spread into neighboring regions. With very strict lockdowns in red zones, commuter testing rates of twice a week can substantially contribute to the safety of adjacent regions. In contrast, the negative effect of less strict interventions can be overcome by high commuter testing rates. A further key contributor is the potential delay of the intervention implementation. In order to keep the spread of the virus under control, strict regional lockdowns with minimum delay and commuter testing of at least twice a week are advisable. If less strict interventions are in favor, substantially increased testing rates are needed to avoid overall higher infection dynamics.

Conclusions

Our results indicate that local containment of outbreaks and maintenance of low overall incidence is possible even in densely populated and highly connected regions such as Germany or Western Europe. While we demonstrate this on data from Germany, similar patterns of mobility likely exist in many countries and our results are, hence, generalizable to a certain extent.
Feedforward mechanisms of masking in mouse V1
Authors: Barbera Dylan , Priebe Nicholas J. , Glickfeld Lindsey L.
Published: April 2021

Sensory neurons not only encode stimuli that align with their receptive fields but are also modulated by context. For example, the responses of neurons in mouse primary visual cortex (V1) to gratings of their preferred orientation are modulated by the presence of superimposed orthogonal gratings (“plaids”). The effects of this modulation can be diverse: some neurons exhibit cross-orientation suppression while other neurons have larger responses to a plaid than its components. We investigated whether these diverse forms of masking could be explained by a unified circuit mechanism. We report that the suppression of cortical activity does not alter the effects of masking, ruling out cortical mechanisms. Instead, we demonstrate that the heterogeneity of plaid responses is explained by an interaction between stimulus geometry and orientation tuning. Highly selective neurons uniformly exhibit cross-orientation suppression, whereas in weakly-selective neurons masking depends on the spatial configuration of the stimulus, with effects transitioning systematically between suppression and facilitation. Thus, the diverse responses of mouse V1 neurons emerge as a consequence of the spatial structure of the afferent input to V1, with no need to invoke cortical interactions.
6-Month Follow Up of 8679 Hospitalized COVID-19 Patients in Germany: A Nationwide Cohort Study
Authors: Günster Christian , Busse Reinhard , Spoden Melissa , Rombey Tanja , Schillinger Gerhard , Hoffmann Wolfgang , Weber-Carstens Steffen , Schuppert Andreas , Karagiannidis Christian
Published: April 2021

Background

Data on long-term outcomes of hospitalized COVID-19 patients are scarce.

Objective

To provide a detailed account of hospitalized COVID-19 patients until 180 days after their initial hospitalization.

Design

Nationwide cohort study using claims data from the German Local Health Care Funds, the health insurer of one-third of the German population.

Setting

Germany.

Patients

Adult patients hospitalized in Germany between Feb 1 and April 30, 2020 with PCR-confirmed COVID-19 and a related principal diagnosis.

Measurements

Patient characteristics and ventilation status, in-hospital, 30-, 90- and 180- day mortality measured from admission, and 180-day readmission measured from discharge. Multivariable logistic regression model of independent risk factors for 180-day mortality.

Results

Of 8679 patients (median age, 72 years), 2161 (24.9%) died during the index hospitalization. 30-day mortality was 23.9% (2073/8679), 90-day mortality 27.9% (2425/8679), and 180-day mortality 29.6% (2566/8679). The latter was 52.3% (1472/2817) for patients aged ≥ 80 years, and 53.0% for patients who had been ventilated invasively (853/1608). Risk factors for 180-day mortality included coagulopathy, BMI ≥ 40, and age. Female sex was a protective factor. Of 6235 patients discharged alive, 1668 patients were readmitted a total of 2551 times within 180 days, resulting in an overall readmission rate of 26.8%.

Limitations

We could not stratify patients by ICU treatment as it is not coded separately. Furthermore, we cannot exclude residual confounding in our analysis of risk factors nor determine causality between risk factors and long-term mortality given the observational nature of this study.

Conclusion

This nationwide cohort study of hospitalized COVID-19 patients in Germany found considerable long-term mortality and readmission rates, especially among patients with coagulopathy. Close follow-up after hospital discharge may improve long-term outcome.
The urgency of resuming disrupted dog rabies vaccination campaigns: a modeling and cost-effectiveness analysis
Authors: Kunkel Amber , Jeon Seonghye , Joseph Haim C , Dilius Pierre , Crowdis Kelly , Meltzer Martin I. , Wallace Ryan
Published: April 2021

OBJECTIVE

Dog vaccination is a cost-effective approach to preventing human rabies deaths. In Haiti, the 2019 dog vaccination campaign did not include the capital city, and the 2020 campaign was cancelled because of COVID-19 lockdown restrictions and redirection of funds. We estimated the number of human lives that could be saved by resuming dog vaccination in 2021 compared to 2022 and compared the cost-effectiveness of these two scenarios.

METHODS

We modified a previously published rabies transmission and economic model to estimate trends in dog and human rabies cases in Haiti from 2005-2025. We compared model outputs to surveillance data on human rabies deaths from 2005-2020 and animal rabies cases from 2018-2020. We then estimated the human health and cost implications of restarting dog vaccination programs in either 2021 or 2022.

FINDINGS

Model predictions and animal surveillance data from Haiti both suggest a 5-to 8-fold increase in animal rabies cases has occurred in the capital city between Fall 2019 and Fall 2020. We estimate that restarting dog vaccination in Haiti in 2021 compared to 2022 could save 285 human lives and prevent 6,541 human rabies exposures over a five-year period and may decrease program costs due to reduced need for human post-exposure prophylaxis.

CONCLUSIONS

A one-year delay in resuming dog vaccination in Haiti, from 2021 to 2022, could cost hundreds of lives over the next 5 years. Interruptions in dog vaccination campaigns before elimination is achieved can lead to significant human rabies epidemics if not promptly resumed.
A Novel Evidence-Based Predictor Tool for Hospitalization and Length of Stay: Insights from COVID19 Patients in New York City
Authors: Halabi Maan El , Feghali James , Tallón de Lara Paulino , Narasimhan Bharat , Ho Kam , Saabiye Joseph , Huang Judy , Osorio Georgina , Mathew Joseph , Wisnivesky Juan , Steiger David
Published: April 2021

Background

Coronavirus disease 2019 (COVID-19) has evolved into a true global pandemic infecting more than 30 million people worldwide. Predictive models for key outcomes have the potential to optimize resource utilization and patient outcome as outbreaks continue to occur worldwide. We aimed to design and internally validate a web-based calculator predictive of hospitalization and length of stay (LOS) in a large cohort of COVID-19 positive patients presenting to the Emergency Department (ED) in a New York City health system.

Methods

The study cohort consisted of consecutive adult (>18 years) patients presenting to the ED of one of the Mount Sinai Health System hospitals between March, 2020 and April, 2020 who were diagnosed with COVID-19. Logistic regression was utilized to construct predictive models for hospitalization and prolonged (>3 days) LOS. Discrimination was evaluated using area under the receiver operating curve (AUC). Internal validation with bootstrapping was performed, and a web-based calculator was implemented.

Results

The cohort consisted of 5859 patients with a hospitalization rate of 65% and a prolonged LOS rate of 75% among hospitalized patients. Independent predictors of hospitalization included older age (OR=6.29; 95% CI [1.83-2.63], >65 vs. 18-44), male sex (OR=1.35 [1.17-1.55]), chronic obstructive pulmonary disease (OR=1.74; [1.00-3.03]), hypertension (OR=1.39; [1.13-1.70]), diabetes (OR=1.45; [1.16-1.81]), chronic kidney disease (OR=1.69; [1.23-2.32]), elevated maximum temperature (OR=4.98; [4.28-5.79]), and low minimum oxygen saturation (OR=13.40; [10.59-16.96]). Predictors of extended LOS included older age (OR=1.03 [1.02-1.04], per year), chronic kidney disease (OR=1.91 [1.35-2.71]), elevated maximum temperature (OR=2.91 [2.40- 3.53]), and low minimum percent oxygen saturation (OR=3.89 [3.16-4.79]). AUCs of 0.881 and 0.770 were achieved for hospitalization and LOS, respectively. A calculator was made available under the following URL: https://covid19-outcome-prediction.shinyapps.io/COVID19_Hospitalization_Calculator/

Conclusion

The prediction tool derived from this study can be used to optimize resource allocation, guide quality of care, and assist in designing future studies on the triage and management of patients with COVID-19.
Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity
Authors: LeBlanc VG , Trinh DL , Aslanpour S , Hughes M , Livingstone D , Blough MD , Cairncross JG , Chan JA , Kelly JJ , Marra MA
Published: April 2021

Glioblastomas (GBMs) are aggressive primary malignant brain tumors characterized by extensive levels of inter- and intra-tumor genetic and phenotypic heterogeneity. Patient-derived organoids (PDOs) have recently emerged as useful models to study such heterogeneity. Here, we present bulk exome as well as single-cell genome and transcriptome profiles of primaryIDHwild type GBMs from ten patients, including two recurrent tumors, as well as PDOs and brain tumor-initiating cell (BTIC) lines derived from these patients. We find that PDOs are genetically similar to and variably retain gene expression characteristics of their parent tumors. At the phenotypic level, PDOs appear to exhibit similar levels of transcriptional heterogeneity as their parent tumors, whereas BTIC lines tend to be enriched for cells in a more uniform transcriptional state. The datasets introduced here will provide a valuable resource to help guide experiments using GBM-derived organoids, especially in the context of studying cellular heterogeneity.
Senolytics and the compression of late-life mortality
Authors: Kowald Axel , Kirkwood Thomas B L
Published: April 2021

Senescent cells play an important role in mammalian ageing and in the etiology of age-related diseases. Treatment of mice with senolytics – drugs that selectively remove senescent cells – causes an extension of median lifespan but has little effect on maximum lifespan. Postponement of some mortality to later ages, without a corresponding increase in maximum mortality, can be termed ‘compression of mortality’. When we fit the standard Gompertz mortality model to the survival data following senolytic treatment, we find an increase in the slope parameter, commonly described as the ‘actuarial ageing rate’. These observations raise important questions about the actions of senolytic treatments and their effects on health and survival, which are not yet sufficiently understood. To explore how the survival data from senolytics experiments might be explained, we combine recent exploration of the evolutionary basis of cellular senescence with theoretical consideration of the molecular processes that might be involved. We perform numerical simulations of senescent cell accumulation and senolytic treatment in an ageing population. The simulations suggest that while senolytics diminish the burden of senescent cells, they may also impair the general repair capacity of the organism, leading to a faster accumulation post-treatment of new senescent cells. Our results suggest a framework to address the benefits and possible side effects of senolytic therapies, with the potential to aid the design of optimal treatment regimens.
Uncertainty drives deviations in normative foraging decision strategies
Authors: Kilpatrick Zachary P , Davidson Jacob D , Hady Ahmed El
Published: April 2021

Nearly all animals forage, as it is essential to acquire energy for survival through efficient search and resource harvesting. Patch exploitation is a canonical foraging behavior, but a systematic treatment of how animals cope with uncertainty is lacking. To address these shortcomings, we develop a normative theory of patch foraging decisions, proposing mechanisms by which foraging behaviors emerge in the face of uncertainty. Our model foragers statistically and sequentially infer patch resource yields using Bayesian updating based on their resource encounter history. A decision to leave a patch is triggered when the certainty of the patch type or the estimated yield of the patch fall below a threshold. The timescale over which uncertainty in resource availability persists strongly impacts behavioral variables like patch residence times and decision rules determining patch departures. When patch depletion is slow, as in habitat selection, departures are characterized by a reduction of uncertainty, suggesting the forager resides in a low-yielding patch. Uncertainty leads patch-exploiting foragers to overharvest (underharvest) patches with initially low (high) resource yields in comparison to predictions of the marginal value theorem. These results extend optimal foraging theory and motivate a variety of behavioral experiments investigating patch foraging behavior.
A comparative analysis of computational tools for the prediction of epigenetic DNA methylation from long-read sequencing data
Authors: Pai Shruta Sandesh , Mathew Aimee Rachel , Anindya Roy
Published: April 2021

Recent development of Oxford Nanopore long-read sequencing has opened new avenues of identifying epigenetic DNA methylation. Among the different epigenetic DNA methylations, N6-methyladenosine is the most prevalent DNA modification in prokaryotes and 5-methylcytosine is common in higher eukaryotes. Here we investigated if N6-methyladenosine and 5-methylcytosine modifications could be predicted from the nanopore sequencing data. Using publicly available genome sequencing data ofSaccharomyces cerevisiae, we compared the open-access computational tools, including Tombo, mCaller, Nanopolish and DeepSignal for predicting 6mA and 5mC. Our results suggest that Tombo and mCaller can predict DNA N6-methyladenosine modifications at a specific location, whereas, Tombo dampened fraction, Nanopolish methylation likelihood and DeepSignal methylation probability have comparable efficiency for 5-methylcytosine prediction from Oxford Nanopore sequencing data.
A Phylogenetic Independent Contrast Method under the Ornstein-Uhlenbeck Model and its Applications in Correlated Evolution
Authors: Liang Cong , Deng Yingjun
Published: April 2021

Abstract

Phylogenetic comparative methods are essential in studying the evolution of traits across a phylogeny. Felsenstein’s phylogenetic independent contrast (PIC) method and the generalized least squares (GLS) regression were often utilized to study whether evolutionary changes between traits were correlated. However, a neutral Brownian model is assumed in the PIC method, which impacts the performance of the PIC method when the trait is subject to adaptation. In recent years, the Ornstein-Uhlenbeck (OU) model has attracted increasing attention in studying the evolution of traits with stabilizing selection. In this study, we extended Felsenstein’s PIC method under the OU model, which we termed OU-PIC. We simulated trait evolution under the OU model on phylogenetic trees with 8, 10, and 55 species. Compared to the PIC method, the OU-PIC method with correct stabilizing selection parameters achieved an appropriate type I error rate, the highest test power, and the lowest mean squared error. We presented a concise proof of the intrinsic connection between the OU-PIC and the generalized least squares (GLS) regression method in evaluating correlated evolution under the OU model. The OU-PIC method has a broad range of applications when trait evolution could be sufficiently modeled by the OU process. Compared with other phylogenetic comparative methods, OU-PIC avoids the inverse of the covariance matrix and would facilitate the analysis of correlated evolution on large phylogenies.
SIX1 Reprograms Myogenic Transcription Factors to Maintain the Rhabdomyosarcoma undifferentiated state
Authors: Hsu Jessica Y. , Danis Etienne P. , Nance Stephanie , O’Brien Jenean , Wessells Veronica M. , Goodspeed Andrew E. , Talbot Jared C. , Amacher Sharon L. , Jedlicka Paul , Black Joshua C. , Costello James C. , Durbin Adam D. , Artinger Kristin B. , Ford Heide L.
Published: April 2021

Rhabdomyosarcoma (RMS) is a pediatric skeletal muscle sarcoma characterized by the expression of the myogenic-lineage transcription factors (TF) MYOD1 and MYOG. Despite high expression of these TFs, RMS cells fail to terminally differentiate, suggesting the presence of factors that alter their function. Here, we demonstrate that the developmental TF, SIX1, is highly expressed in RMS and is critical to maintain a muscle progenitor-like state. SIX1 loss induces terminal differentiation of RMS cells into myotube-like cells and dramatically impedes tumor growthin vivo. We show that SIX1 maintains the RMS undifferentiated state by controlling enhancer activity and MYOD1 occupancy at loci more permissive to tumor growth over terminal muscle differentiation. Finally, we demonstrate that a gene signature derived from SIX1 loss correlates with differentiation status in RMS and predicts RMS progression in human disease. Our findings demonstrate a master regulatory role for SIX1 in the repression of RMS differentiation via genome-wide alterations in MYOD1-mediated transcription.

Highlights

SIX1 prevents differentiation in RMS while it promotes differentiation during normal development

FN-RMS are highly dependent on SIX1 for growth in both zebrafish and mouse xenograft models

Loss of SIX1 alters the transcriptional landscape of RMS cells, inducing a growth to differentiation switch

SIX1 knockdown in FN-RMS causes reduced super enhancer-based activity at stem-related genes and enhanced MYOD1 binding to differentiation loci, resulting in the activation of a myogenic differentiation program

A gene signature derived from SIX1 loss strongly correlates with myogenic differentiation status and is predictive of advanced RMS.