bluuebunny/crossref_metadata_2025 huggingface dataset:
Introductory gestures before songbird vocal displays are shaped by learning and biological predispositions
Authors: Kalra Shikha , Yawatkar Vishruta , James Logan S , Sakata Jon T , Rajan Raghav
Published: January 2021

Numerous animal displays begin with introductory gestures. For example, lizards start their head-bobbing displays with introductory push-ups, and many songbirds begin their vocal displays by repeating introductory notes (INs) before producing their learned song. Among songbirds, the acoustic structure and the number of INs produced before song vary considerably between individuals in a species. While similar variation in songs between individuals is a result of learning, whether variations in INs are also due to learning remains poorly understood. Here, using natural and experimental tutoring with male zebra finches, we show that mean IN number and IN acoustic structure are learned from a tutor. Interestingly, IN properties and how well INs were learned, were not correlated with the accuracy of song imitation and only weakly correlated with some features of songs that followed. Finally, birds artificially tutored with songs lacking INs still repeated vocalizations that resembled INs, before their songs, suggesting biological predispositions in IN production. These results demonstrate that INs, just like song elements, are shaped both by learning and biological predispositions. More generally, our results suggest mechanisms for generating variation in introductory gestures between individuals while still maintaining the species-specific structure of complex displays like birdsong.
Trophic consequences of terrestrial eutrophication for a threatened ungulate
Authors: Serrouya Robert , Dickie Melanie , Lamb Clayton , van Oort Harry , Kelly Allicia P. , DeMars Craig , McLoughlin Philip D. , Larter Nicholas C. , Hervieux Dave , Ford Adam T. , Boutin Stan
Published: January 2021

Changes in primary productivity have the potential to substantially alter food webs, with positive outcomes for some species and negative outcomes for others. Understanding the environmental context and species traits that give rise to these divergent outcomes is a major challenge to the generality of both theoretical and applied ecology. In aquatic systems, nutrient-mediated eutrophication has led to major declines in species diversity, motivating us to seek terrestrial analogues using a large-mammal system across 598 000 km2of the Canadian boreal forest. These forests are undergoing some of the most rapid rates of land-use change on Earth and are home to declining caribou (Rangifer tarandus caribou) populations. Using satellite-derived estimates of primary productivity, coupled with estimates of moose (Alces alces) and wolf (Canis lupus) abundance, we used path analyses to discriminate among hypotheses explaining how habitat alteration can affect caribou population growth. Hypotheses included food limitation, resource dominance by moose over caribou, and apparent competition with predators shared between moose and caribou. Results support apparent competition and yield estimates of wolf densities (1.8 individuals 1000 km−2) above which caribou populations decline. Our multi-trophic analysis provides insight into the cascading effects of habitat alteration from forest cutting that destabilize terrestrial predator–prey dynamics. Finally, the path analysis highlights why conservation actions directed at the proximate cause of caribou decline have been more successful in the near term than those directed further along the trophic chain.
Ovotestes suggest cryptic genetic influence in a reptile model for temperature-dependent sex determination
Authors: Whiteley Sarah L. , Georges Arthur , Weisbecker Vera , Schwanz Lisa E. , Holleley Clare E.
Published: January 2021

Sex determination and differentiation in reptiles is complex. Temperature-dependent sex determination (TSD), genetic sex determination (GSD) and the interaction of both environmental and genetic cues (sex reversal) can drive the development of sexual phenotypes. The jacky dragon (
Amphibolurus muricatus
) is an attractive model species for the study of gene–environment interactions because it displays a form of Type II TSD, where female-biased sex ratios are observed at extreme incubation temperatures and approximately 50 : 50 sex ratios occur at intermediate temperatures. This response to temperature has been proposed to occur due to underlying sex determining loci, the influence of which is overridden at extreme temperatures. Thus, sex reversal at extreme temperatures is predicted to produce the female-biased sex ratios observed in
A. muricatus
. The occurrence of ovotestes during development is a cellular marker of temperature sex reversal in a closely related species
Pogona vitticeps
. Here, we present the first developmental data for
A. muricatus
, and show that ovotestes occur at frequencies consistent with a mode of sex determination that is intermediate between GSD and TSD. This is the first evidence suggestive of underlying unidentified sex determining loci in a species that has long been used as a model for TSD.
The effect of optic flow cues on honeybee flight control in wind
Authors: Baird Emily , Boeddeker Norbert , Srinivasan Mandyam V.
Published: January 2021

To minimize the risk of colliding with the ground or other obstacles, flying animals need to control both their ground speed and ground height. This task is particularly challenging in wind, where head winds require an animal to increase its airspeed to maintain a constant ground speed and tail winds may generate negative airspeeds, rendering flight more difficult to control. In this study, we investigate how head and tail winds affect flight control in the honeybeeApis mellifera, which is known to rely on the pattern of visual motion generated across the eye—known as optic flow—to maintain constant ground speeds and heights. We find that, when provided with both longitudinal and transverse optic flow cues (in or perpendicular to the direction of flight, respectively), honeybees maintain a constant ground speed but fly lower in head winds and higher in tail winds, a response that is also observed when longitudinal optic flow cues are minimized. When the transverse component of optic flow is minimized, or when all optic flow cues are minimized, the effect of wind on ground height is abolished. We propose that the regular sidewards oscillations that the bees make as they fly may be used to extract information about the distance to the ground, independently of the longitudinal optic flow that they use for ground speed control. This computationally simple strategy could have potential uses in the development of lightweight and robust systems for guiding autonomous flying vehicles in natural environments.
INDUCTION AND ORIENTATION PRACTICES AND PERCEIVED EFFECT ON HEALTH WORK FORCE PERFORMANCE AND SATISFACTION IN PUBLIC HOSPITALS OF ILUBABOUR ZONE, OROMIA REGIONAL STATE, SOUTH WEST ETHIOPIA, 2018: FACILITY BASED CROSS SECTIONAL STUDY DESIGN WAS EMPLOYED
Authors: Ayana Sisay Siraj , Alaro Tesfamichael , Gebissa Feyera
Published: January 2021

Background

Successful orientation speeds up the adaptation process by helping new employees feel comfortable in the organization and by making them more productive on the job. In today’s world most organization are recognizing that this type of simple generic orientation is not enough, a more complex employee orientation or on boarding process is required.

Objective

To assess induction and orientation practices and perceived effect on health work force performance and satisfaction in public hospitals of Ilubabour zone, Oromia regional state, south west Ethiopia, 2018.

Methods

A Facility based cross sectional study was conducted by using both quantitative and qualitative methods. Quantitative data was collected by self-administered questionnaire and qualitative data was collected by in-depth interview with purposefully selected key informants using interviewer guide. The sample sizes for quantitative data were calculated by using single population proportion formula. Accordingly, a total of 403 samples were drawn from the source population by stratified sampling technique. Qualitative data of in-depth interview was transcribed, and thematically analyzed and triangulated with quantitative findings.

Results

Out of 388 only 135(34 %) respondents have attended induction and orientation training while assignment to different new responsibilities. The finding from key informants revealed that they take even for less than one day or an hour. Regarding the practices held during the training; only proper welcoming them to the organization and department was practiced, the rest practices like sharing the organization vision, involving senior leaders and post training evaluation was responded that they were exercised poorly within the organizations. Only 53.1% responded that induction and orientation training have perceived effect on employee Performance while 46.7% of respondents do not. About 55.7% respondents said that induction and orientation training have perceived effect on employees’ job satisfaction and the remaining responded to have no effect on employee’s satisfaction.

Conclusion

Generally, the induction and orientation practice was poor so as the supportive supervision and post training evaluation. More than half of the respondents perceived that it has effect on performance and satisfaction and the rest did not understand its specific effects.
Issues of Random Sampling with Rapid Antigen Tests for COVID-19 Diagnosis: A Special Reference to Kalmunai RDHS Division
Authors: Razmy AM , Junaideen SM
Published: January 2021

Random sampling from the community and performing the rapid antigen test has become a debatable issue during this COVID-19 pandemic. This writing analyzes the concerns using the data from Kalmunai RDHS Division, Sri Lanka, related to COVID-19 and shows the issues of random sampling in a community wherein the incident rate is small. Therefore, suitable sampling protocol is to be developed for performing rapid antigen test for COVID-19 diagnosis.
BAYESIAN GROUP TESTING WITH DILUTION EFFECTS
Authors: Tatsuoka Curtis , Chen Weicong , Lu Xiaoyi
Published: January 2021

Summary

A Bayesian framework for group testing under dilution effects has been developed, using latticebased models. This work has particular relevance given the pressing public health need to enhance testing capacity for COVID-19 and future pandemics, and the need for wide-scale and repeated testing for surveillance under constantly varying conditions. The proposed Bayesian approach allows for dilution effects in group testing and for general test response distributions beyond just binary outcomes. It is shown that even under strong dilution effects, an intuitive group testing selection rule that relies on the model order structure, referred to as the Bayesian halving algorithm, has attractive optimal convergence properties. Analogous look-ahead rules that can reduce the number of stages in classification by selecting several pooled tests at a time are proposed and evaluated as well. Group testing is demonstrated to provide great savings over individual testing in the number of tests needed, even for moderately high prevalence levels. However, there is a trade-off with higher number of testing stages, and increased variability. A web-based calculator is introduced to assist in weighing these factors and to guide decisions on when and how to pool under various conditions. High performance distributed computing methods have also been implemented for considering larger pool sizes, when savings from group testing can be even more dramatic.
Genomics of Aminoglycoside Resistance in Pseudomonas aeruginosa Bloodstream Infections at a United States Academic Hospital
Authors: Atassi Giancarlo , Scheetz Marc , Nozick Sophia , Rhodes Nathaniel J. , Murphy-Belcaster Megan , Murphy Katherine R , Ozer Egon A. , Hauser Alan R.
Published: January 2021

Pseudomonas aeruginosa is a frequent cause of antibiotic-resistant infections. Although P. aeruginosa is intrinsically resistant to many antimicrobial agents, aminoglycosides are active against this organism in the absence of acquired resistance determinants and mutations. However, genes encoding aminoglycoside modifying enzymes (AMEs) are found in many strains that are resistant to these agents. We examined the prevalence of phenotypic resistance to the commonly used aminoglycosides gentamicin, tobramycin, and amikacin in a collection of 227 P. aeruginosa bloodstream isolates collected over two decades from a single U.S. academic medical institution. Resistance to these antibiotics was relatively stable over this time period. High-risk clones ST111 and ST298 were initially common but decreased in frequency over time. Whole genome sequencing identified relatively few AME genes in this collection compared to the published literature; only 14% of isolates contained an AME gene other than the ubiquitous aph(3’)-IIb. Of those present, only ant(2”)-Ia was associated with phenotypic resistance to gentamicin or to tobramycin. One extensively drug-resistant strain, PS1871, contained 5 AME genes, most of which were part of clusters of antibiotic resistance genes embedded within transposable elements. These findings suggest that AME genes play a relatively minor role in aminoglycoside resistance at our institution but that multidrug-resistant strains remain a problem.
The management of Moderate Acute Malnutrition (MAM) in children aged 6-59 months: A systematic review and meta-analysis
Authors: Gluning I , Kerac M , Bailey J , Bander A , Opondo C
Published: January 2021

Background

Malnutrition is a leading cause of morbidity and mortality in children aged under five years, especially in low- and middle-income countries (LMICs). Although severe acute malnutrition (SAM) is considered the most serious form of malnutrition, moderate acute malnutrition (MAM) affects greater numbers globally and, unlike SAM, guidelines lack a robust evidence-base. This systematic review and meta-analysis assessed the evidence for lipid-based nutrient supplements (LNS), fortified-blended-flours (FBF) and nutrition counselling, in the treatment of MAM.

Methods

Five databases were systematically searched for studies conducted in LMICs that compared the effectiveness of food-based products versus any comparator group in promoting recovery from MAM in children aged 6-59 months. Where appropriate, pooled estimates of effect were estimated using random-effects meta-analyses.

Results

A total of thirteen trials were identified for inclusion. All used active controls rather than ‘standard care’, which is often minimal in most settings. There was evidence of increased probability of recovery (as assessed by gaining normal weight-for-height and/or MUAC) among children treated with LNS compared to children treated with FBF (RR 1·05, 95%CI 1·01-1·09, p=0·009). Treatment with an LNS was also associated with a lower risk of persistent MAM at the end of treatment compared with a FBF (RR 0·82, 95%CI 0·71-0·95, p=0·007).

Conclusion

Based on a relatively small number of studies mainly from Africa, LNS are superior to FBF in improving anthropometric recovery from MAM. The true benefit of MAM treatment may be underestimated due to all studies using active controls rather than usual care which is minimal.

More high-quality evidence is needed to evaluate nutrition education/counselling alone as a MAM intervention. Studies should also assess a wider range of outcomes including body composition, morbidity and development – not weight-gain alone.
Sword of Damocles or choosing well. Population genetics sheds light into the future of the COVID-19 pandemic and SARS-CoV-2 new mutant strains
Authors: García de Alcañíz J. G. , López-Rodas V. , Costas E.
Published: January 2021

An immense scientific effort has been made worldwide due to Covid-19’s pandemic magnitude. It has made possible to identify almost 300,000 SARS-CoV-2 different genetic variants, connecting them with clinical and epidemiological findings. Among this immense data collection, that constitutes the biggest evolutionary experiment in history, is buried the answer to what will happen in the future. Will new strains, more contagious than the current ones or resistant to the vaccines, arise by mutation? Although theoretic population genetics is, by far, the most powerful tool we have to do an accurate prediction, it has been barely used for the study of SARS-CoV-2 due to its conceptual difficulty. Having in mind that the size of the SARS-CoV-2 population is astronomical we can apply a discrete treatment, based on the branching process method, Fokker-Plank equations and Kolmogoroff’s forward equations, to calculate the survival likelihood through time, to elucidate the likelihood to become dominant genotypes and how long will this take, for new SARS-CoV-2 mutants depending on their selective advantage. Results show that most of the new mutants that will arise in the SARS-CoV-2 meta-population will stay at very low frequencies. However, some few new mutants, significantly more infectious than current ones, will still emerge and become dominant in the population favoured by a great selective advantage. Far from showing a “mutational meltdown”, SARS-CoV-2 meta-population will increase its fitness becoming more infective. There is a probability, small but finite, that new mutants arise resistant to some vaccines. High infected numbers and slow vaccination programs will significantly increase this likelihood.
Development of Predictive Risk Models for All-cause Mortality in Pulmonary Hypertension using Machine Learning
Authors: Zhou Jiandong , Wong Ka Hei Gabriel , Lee Sharen , Liu Tong , Kit Leung Keith Sai , Jeevaratnam Kamalan , Yung Cheung Bernard Man , Kei Wong Ian Chi , Zhang Qingpeng , Tse Gary
Published: January 2021

Background

Pulmonary hypertension, a progressive lung disorder with symptoms such as breathlessness and loss of exercise capacity, is highly debilitating and has a negative impact on the quality of life. In this study, we examined whether a multi-parametric approach using machine learning can improve mortality prediction.

Methods

A population-based territory-wide cohort of pulmonary hypertension patients from January 1, 2000 to December 31, 2017 were retrospectively analyzed. Significant predictors of all-cause mortality were identified. Easy-to-use frailty indexes predicting primary and secondary pulmonary hypertension were derived and stratification performances of the derived scores were compared. A factorization machine model was used for the development of an accurate predictive risk model and the results were compared to multivariate logistic regression, support vector machine, random forests, and multilayer perceptron.

Results

The cohorts consist of 2562 patients with either primary (n=1009) or secondary (n=1553) pulmonary hypertension. Multivariate Cox regression showed that age, prior cardiovascular, respiratory and kidney diseases, hypertension, number of emergency readmissions within 28 days of discharge were all predictors of all-cause mortality. Easy-to-use frailty scores were developed from Cox regression. A factorization machine model demonstrates superior risk prediction improvements for both primary (precision: 0.90, recall: 0.89, F1-score: 0.91, AUC: 0.91) and secondary pulmonary hypertension (precision: 0.87, recall: 0.86, F1-score: 0.89, AUC: 0.88) patients.

Conclusion

We derived easy-to-use frailty scores predicting mortality in primary and secondary pulmonary hypertension. A machine learning model incorporating multi-modality clinical data significantly improves risk stratification performance.
The Socioeconomic Impact of COVID-19 in Urban Informal Settlements
Authors: Gil Diego , Domínguez Patricio , Undurraga Eduardo A. , Valenzuela Eduardo
Published: January 2021

The COVID-19 pandemic has reached almost every corner of the world. Without a pharmaceutical solution, governments have been forced to implement regulations and public policies to control social behavior and prevent the spread of the virus. There is dramatic evidence of the social and economic effects of these measures and their disparate impact on vulnerable communities. Individuals living in urban informal settlements are in a structurally disadvantaged position to cope with a health crisis such as the COVID-19 pandemic. This paper examines the socioeconomic impact of the crisis brought by the pandemic in informal settlements in Chile. We use a three-wave panel study to compare the situation in informal settlements before and during the health crisis. We show that households living in informal settlements are paying a high toll. Their employment loss is dramatic, substantially larger than the loss reported in the general population, and has particularly affected the inmigrant population. We also find that the pandemic has triggered neighborhood cooperation within the settlements. Targeted government assistance programs have reached these communities; however, this group’s coverage is not enough to counteract the magnitude of the crisis. Our results suggest that governments, the non-profit sector, and the community need to urgently provide economic support and protections to individuals living in informal settlements and consider this opportunity for long-term improvements in these marginalized communities.

Highlights

Governments have implemented large-scale non-pharmaceutical interventions to control the spread of the COVID-19 pandemic

These measures have had dramatic social and economic effects on the population, particularly affecting vulnerable communities

Individuals living in urban informal settlements are in a structurally disadvantaged position to cope with this crisis

Using panel data, we document a dramatic employment loss among informal settlements dwellers, substantially larger than the general population

The pandemic has also triggered neighborhood cooperation within the settlements as well as targeted government assistance, but not enough to counteract the magnitude of the economic loss
Meta-Analysis of Robustness of COVID-19 Diagnostic Kits During Early Pandemic
Authors: Shanmugam Chandrakumar , Behring Michael , Luthra Vishwas , Leal Sixto M , Diffalha Sameer Al , Varambally Sooryanarayana , Netto George J , Manne Upender
Published: January 2021

Background

Accurate detection of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is necessary to mitigate the coronavirus disease-19 (COVID-19) pandemic. However, the test reagents and assay platforms are varied and may not be sufficiently robust to diagnose COVID-19.

Methods

We reviewed 85 studies (21,530 patients), published from five regions of the world, to highlight issues involved in the diagnosis of COVID-19 in the early phase of the pandemic, following the standards outlined in the PRISMA statement. All relevant articles, published up to May 31, 2020, in PubMed, BioRiXv, MedRiXv, and Google Scholar, were included. We evaluated the qualitative (9749 patients) and quantitative (10,355 patients) performance of RT-PCR and serologic diagnostic tests for real-world samples, and assessed the concordance (5,538 patients) between methods in meta-analyses.

Results

The RT-PCR tests exhibited heterogeneity in the primers and reagents used. Of 1,957 positive RT-PCR COVID-19 participants, 1,585 had positive serum antibody (IgM +/- IgG) tests (sensitivity 0.81, 95%CI 0.66-.90). While 3,509 of 3581 participants RT-PCR negative for COVID-19 were found negative by serology testing (specificity 0.98, 95%CI 0.94-0.99). The chemiluminescent immunoassay exhibited the highest sensitivity, followed by ELISA and lateral flow immunoassays. Serology tests had higher sensitivity and specificity for laboratory-approval than for real-world reporting data.

Conclusions

The robustness of the assays/platforms is influenced by variability in sampling and reagents. Serological testing complements and may minimize false negative RT-PCR results. Lack of standardized assay protocols in the early phase of pandemic might have contributed to the spread of COVID-19.
Exposure to glucagon-like peptide 1 receptor (GLP-1R) agonists reduces glaucoma risk
Authors: Sterling Jacob K. , Hua Peiying , Dunaief Joshua L. , Cui Qi N. , VanderBeek Brian L.
Published: January 2021

Importance

Glucagon-like peptide-1 receptor (GLP-1R) agonists regulate blood glucose and are commonly used to treat Type II Diabetes Mellitus. Recent work has shown that treatment with the novel GLP-1R agonist, NLY01, decreased retinal neuroinflammation and glial activation to rescue retinal ganglion cells in an animal model of glaucoma.

Objective

In this study, we used an insurance claims database to examine whether GLP-1R agonist exposure impacts glaucoma risk.

Design, Setting, and Participants

A retrospective cohort of adult patients who initiated a new GLP-1R agonist (i.e., exenatide, liraglutide, albiglutide, dulaglutide, semaglutide, or lixisenatide) was 1:3 age, gender, race, active diabetes medication classes, and year of index date matched to a cohort of patients who initiated a different class of oral diabetic medication during their time in the database. Exclusion occurred for <2 years in the database, age <18 years old, no visit to an eyecare provider prior to the index date, a prior diagnosis of glaucoma, glaucoma suspect, or ocular hypertension, or prior glaucoma medication, procedure, or surgery. Diabetes severity was assessed using hemoglobin A1c and the Diabetes Complications Severity Index (DCSI), a validated metric based on six categories of diabetic complications. Inverse probability of treatment weighting (IPTW) was used within a multivariable Cox proportional hazard regression model to test the association between GLP-1R agonist exposure and the primary outcome. IPTW was derived from a propensity score model based on the DCSI, HbA1c, demographic factors and other systemic health conditions.

Exposure

Glucagon-like peptide 1 receptor agonist.

Main Outcomes and Measures

New diagnosis of primary open angle glaucoma, glaucoma suspect, or low tension glaucoma.

Results

Cohorts were comprised of 1,961 new users of GLP-1R agonists matched to 4,371 unexposed controls. After IPTW, age was the only covariate imbalanced (SMD >0.1) between cohorts. Ten new diagnoses of glaucoma (0.51%) were present in the GLP-1R agonist cohort compared to 58 (1.33%) in the unexposed controls. After adjustment, GLP-1R exposure conferred a reduced hazard of 0.54 (95%CI: 0.35-0.85, P =0.007), suggesting that GLP-1R agonists reduce the risk for glaucoma.

Conclusions and Relevance

GLP-1R agonist use was associated with a statistically significant hazard reduction for a new glaucoma diagnosis. Our findings support further investigations into the use of GLP-1R agonists in glaucoma prevention.
TRACT revisited: an algebraic solution for determining overall rotational correlation times from cross-correlated relaxation rates
Authors: Robson Scott A. , Dağ Çağdaş , Wu Hongwei , Ziarek Joshua J.
Published: January 2021

Accurate rotational correlation times (τc) are critical for quantitative analysis of fast timescale NMR dynamics. As molecular weights increase, the classic derivation ofτcusing transverse and longitudinal relaxation rates becomes increasingly unsuitable due to the non-trivial contribution of remote dipole-dipole interactions to longitudinal relaxation. Derivations using cross-correlated relaxation experiments, such as TRACT, overcome these limitations but are erroneously calculated in 65% of the citing literature. Herein, we developed an algebraic solutions to the Goldman relationship that facilitate rapid, point-by-point calculations for straightforward identification of appropriate spectral regions where global tumbling is likely to be dominant. The rigid-body approximation of the Goldman relationship has been previously shown to underestimate TRACT-based rotational correlation time estimates. This motivated us to develop a second algebraic solution that employs a simplified model-free spectral density function including an order parameter term that could, in principle, be set to an average backbone S2≈ 0.9 to further improve the accuracy ofτcestimation. These solutions enabled us to explore the boundaries of the Goldman relationship as a function of the H-N internuclear distance (r), difference of the two principal components of the axially-symmetric15N CSA tensor (ΔδN), and angle of the CSA tensor relative to the N-H bond vector (θ). We hope our algebraic solutions and analytical strategies will increase the accuracy and application of the TRACT experiment.
Modeling and Simulation: A study on predicting the outbreak of COVID-19 in Saudi Arabia
Authors: Msmali Ahmed , Mutum Zico , Mechai Idir , Ahmadini Abdullah
Published: January 2021

The novel coronavirus (Covid-19) infection has resulted in an ongoing pandemic affecting health system and economy of more than 200 countries around the world. Mathematical models are used to predict the biological and epidemiological trends of an epidemic and develop methods for controlling it. In this work, we use mathematical model perspective to study the role of behavior change in slowing the spread of the COVID-19 disease in Saudi Arabia. The real-time updated data from 1st May 2020 to 8th January 2021 is collected from Saudi Ministry of Health, aiming to provide dynamic behaviors of the pandemic in Saudi Arabia. During this period, it has infected 297,205 people, resulting in 6124 deaths with the mortality rate 2.06 %. There is weak positive relationship between the spread of the infection and mortality (R2 =0.412). We use Susceptible-Exposed-Infection-Recovered (SEIR) mode, the logistic growth model and with special focus on the exposed, infection and recovery individuals to simulate the final phase of the outbreak. The results indicate that social distancing, good hygienic conditions, and travel limitation are the crucial measures to prevent further spreading of the epidemic.
Electronic Computer-Based Model of Combined Ventilation Using a New Medical Device
Authors: Ramos Matias , Giambastiani Roberto Orofino , Riva Diego , Biancolini María Fernanda , Lugones Ignacio
Published: January 2021

Introduction

The increased demand for mechanical ventilation caused by the SARS-CoV-2 pandemic could generate a critical situation where patients may lose access to mechanical ventilators. Combined ventilation, in which two patients are ventilated simultaneously but independently with a single ventilator has been proposed as a life-saving bridge while waiting for new ventilators availability. New devices have emerged to facilitate this task and allow individualization of ventilatory parameters in combined ventilation. In this work we run computer-based electrical simulations of combined ventilation. We introduce an electrical model of a proposed mechanical device which is designed to individualize ventilatory parameters, and tested it under different circumstances.

Materials and Methods

With an electronic circuit simulator applet, an electrical model of combined ventilation is created using resistor-capacitor circuits. A device is added to the electrical model which is capable of individualizing the ventilatory parameters of two patients connected to the same ventilator. Through computational simulation, the model is tested in different scenarios with the aim of achieving adequate ventilation of two subjects under different circumstances: 1) two identical subjects; 2) two subjects with the same size but different lung compliance; and 3) two subjects with different sizes and compliances. The goal is to achieve the established charge per unit of size on each capacitor under different levels of end-expiratory voltage (as an end-expiratory pressure analog). Data collected included capacitor charge, voltage, and charge normalized to the weight of the simulated patient.

Results

Simulations show that it is possible to provide the proper charge to each capacitor under different circumstances using an array of electrical components as equivalents to a proposed mechanical device for combined ventilation. If the pair of connected capacitors have different capacitances, adjustments must be made to the source voltage and/or the resistance of the device to provide the appropriate charge for each capacitor under initial conditions. In pressure control simulation, increasing the end-expiratory voltage on one capacitor requires increasing the source voltage and the device resistance associated with the other simulated patient. On the other hand, in the volume control simulation, it is only required to intervene in the device resistance.

Conclusions

Under simulated conditions, this electrical model allows individualization of combined mechanical ventilation.
Validating quantitative PCR assays for cell-free DNA detection without DNA extraction: Exercise induced kinetics in systemic lupus erythematosus patients
Authors: Neuberger Elmo W.I. , Brahmer Alexandra , Ehlert Tobias , Kluge Katrin , Philippi Keito F.A. , Boedecker Simone C. , Weinmann-Menke Julia , Simon Perikles
Published: January 2021

Circulating cell-free DNA (cfDNA) has been investigated as a screening tool for many diseases. To avoid expensive and time-consuming DNA isolation, direct quantification PCR assays can be established. However, rigorous validation is required to provide reliable data in the clinical and non-clinical context. Considering International Organization for Standardization, as well as bioanalytical method validation guidelines we provide a comprehensive procedure to validate assays for cfDNA quantification from unpurified blood plasma. A 90 and 222 bp assay was validated to study the kinetics of cfDNA after exercise in patients with systemic lupus erythematosus. The assays showed ultra-low limit of quantification (LOQ) with 0.47 and 0.69 ng/ml, repeatability ≤ 11.6% (95% CI: 8.1–20.3), and intermediate precision ≤ 12.1% (95% CI: 9.2-17.7). Incurred sample reanalysis confirmed the precision of the procedure. The additional consideration of pre-analytical factors shows that centrifugation speed and temperature do not change cfDNA concentrations. In SLE patients cfDNA increases ∼2 fold after all out walking exercise, normalizing after 60 min of rest. The established assays allow reliable and cost-efficient quantification of cfDNA in minute amounts of plasma in the clinical setting and can be used as a standard to control pre-analytical factors including cfDNA losses during purification.
Modelling the Long-Term Effects of Covid-19 Cancer Services Disruption on Patient Outcome in Scotland
Authors: Figueroa Jonine D , Gray Ewan , Maeda Yasuko , Hall Peter S , Mackean Melanie , Elder Kenneth , Din Farhat V N , Dunlop Malcolm G , Weller David
Published: January 2021

Background

Modelling the long-term effects of disruption of cancer services and minimising any excess cancer mortality due to the Covid-19 pandemic is of great importance. Here we adapted a stage-shift model to inform service planning decisions within NHS Scotland for the ‘‘Detect Cancer Early’ tumours, breast, colorectal and lung cancer which represent 46% of all cancers diagnosed in Scotland.

Methods & Data

Lung, colorectal and breast cancer incidence data for years 2017-18 were obtained from Public Health Scotland Cancer Quality Performance Indicators (QPI), to define a baseline scenario. The most current stage-specific 5-year survival data came from 2009-2014 national cancer registry and South East Scotland Cancer Network (SCAN) QPI audit datasets. The Degeling et al., inverse stage-shift model was adapted to estimate changes in stage at diagnosis, excess mortality and life-years lost from delays to diagnosis and treatment due to Covid-19-related health services disruption. Three and 6-month periods of disruption were simulated to demonstrate the model predictions.

Results

Approximately, 1-9% reductions in stage I/II presentations leading up to 2-10% increases in stage III/IV presentations are estimated across the three cancer types. A 6-month period of service disruption is predicted to lead to excess deaths at 5 years of 32.5 (31.1, 33.9) per 1000 cases for lung cancer, 16.5 (7.9, 24.3) for colorectal cancer and 31.6 (28.5, 34.4) for breast cancer.

Conclusions

Disruption of cancer diagnostic services can lead to significant excess deaths in following years. Increasing diagnostic and capacity for cancer services to deal with the backlog of care are needed. Real time monitoring of incidence and referral patterns over the disruption and post-disruption period to reduce excess deaths including more rapid incidence data by stage and other key tumour/clinical characteristics at presentation for key cancer cases (on a quarterly basis). Real time monitoring in cancer care and referral patterns should help inform what type of interventions are needed to reduce excess mortality and whether different population subgroups require public health messaging campaigns. Specific mitigation measures can be the subject of additional modelling analysis to assess the benefits and inform service planning decision making.
Leaf Aqueous Extract ofManilkara hexandrainfluenced Glucose Metabolism in fish: An observation withLabeo rohitaFingerlings as model organism
Authors: Dutta Sumana , Chowdhury Debnarayan , Das Ria , Das Jayashri , Ghosh Poulomi , Ghosh Koushik , Ray Sanjib
Published: January 2021

Manilkara hexandra(Roxb.) Dubard (common name Khirni, family: Sapotaceae) is an evergreen traditionally used medicinal plant. The present study aimed to see the effects of leaf aqueous extract ofM. hexandra(LAEMH) on digestive and glucose metabolic enzyme action and serum glucose level in rohu,Labeo rohita, fingerlings. Experimental fish were fed a basal diet (Group I), and diets supplemented with LAEMH at 300 mg (Group II) and 600 mg (Group III) kg−1body weight. A significant reduction in serum glucose was noticed in the treated groups when compared with the control group. The reduced amylase activity was noticed in the treated fingerlings in a dose-dependent manner. However, lipase and protease activities didn’t differ significantly among the experimental groups. Reduced serum glucose level might be correlated with the decline in the activity of digestive amylase in fish. Group II (3.35±0.19 U) and Group III (3.49±0.13 U) were recorded with reduced glucose-6-phosphatase activities than the control group (4.4±0.39 U). Moreover, the study revealed a decline in fructose-1,6-phosphatase activities in the treated groups in comparison to the control group. The decline in the activities of the metabolic enzymes might be associated with the non-availability of glucose owing to reduced activity of the digestive amylase in the treated groups. In conclusion, the present study established the hypoglycaemic effect of the leaf aqueous extract ofM. hexandrain a fish model.
Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays
Authors: Chen Ao , Liao Sha , Cheng Mengnan , Ma Kailong , Wu Liang , Lai Yiwei , Qiu Xiaojie , Yang Jin , Li Wenjiao , Xu Jiangshan , Hao Shijie , Wang Xin , Lu Huifang , Chen Xi , Liu Xing , Huang Xin , Lin Feng , Li Zhao , Hong Yan , Fu Defeng , Jiang Yujia , Peng Jian , Liu Shuai , Shen Mengzhe , Liu Chuanyu , Li Quanshui , Yuan Yue , Zheng Huiwen , Wang Zhifeng , Wang Zhaohui , Huang Xin , Xiang Haitao , Han Lei , Qin Baoming , Guo Pengcheng , Cánoves Pura Muñoz- , Thiery Jean Paul , Wu Qingfeng , Zhao Fuxiang , Li Mei , Kuang Haoyan , Hui Junhou , Wang Ou , Lu Haorong , Wang Bo , Liu Shiping , Ni Ming , Zhang Wenwei , Mu Feng , Yin Ye , Yang Huanming , Lisby Michael , Cornall Richard J. , Mulder Jan , Uhlen Mathias , Esteban Miguel A. , Li Yuxiang , Liu Longqi , Xu Xun , Wang Jian
Published: January 2021

Spatially resolved transcriptomic technologies are promising tools to study cell fate decisions in a physical microenvironment, which is fundamental for enhancing our knowledge of mammalian development. However, the imbalance between resolution, transcript capture and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation mammalian embryos. Here, we combined DNA nanoball (DNB) patterned arrays and tissue RNA capture to create SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq). This approach allows transcriptomic profiling of large histological sections with high resolution and sensitivity. We have applied Stereo-seq to study the kinetics and directionality of transcriptional variation in a time course of mouse organogenesis. We used this information to gain insight into the molecular basis of regional specification, neuronal migration and differentiation in the developing brain. Furthermore, we mapped the expression of a panel of developmental disease-related loci on our global transcriptomic maps to define the spatiotemporal windows of tissue vulnerability. Our panoramic atlas constitutes an essential resource to investigate longstanding questions concerning normal and abnormal mammalian development.
Attenuation of Hyperalgesia and Allodynia by some Phenolic Acids in Paclitaxel Induced Neuropathy
Authors: Pawar Shubhangi H. , Upaganlawar Aman B. , Upasani Chandrashekhar D.
Published: January 2021

Paclitaxel, an anticancer drug induced neuropathy is widely used animal model to evaluate new drugs in neuropathy. As oxidative stress is key contributor in pathogenesis of neuropathy, many phenolic acids with antioxidant potential are proven as neuroprotective. So,present work undertaken to evaluate effect of syringic acid and sinapic acid in paclitaxel induced neuropathy. We evaluated effect on mechanical and thermal hyperalgesia and allodynia which are vital signs of neuropathy. 4 weeks treatment by different doses of syringic acid and sinapic acid shown significant protective effect on hyperalgesia and allodynia in dose dependant manner assessed by Randello Selitto, hot plate, cold plate and Von Frey filament test. As these phenolic acids attenuates hyperalgesia and allodynia in neuropathy, can be therapeutically used in combination with current treatment of neuropathy.

Summary statement

Hyperlagesia and allodynia are major signs of neuropathy and this article focus on reduction of hyperalgesia and allodynia by syringic and sinapic acid in neuropathy induced by paclitaxel.
Temporal Trends in COVID-19 associated AKI from March to December 2020 in New York City
Authors: Dellepiane Sergio , Vaid Akhil , Jaladanki Suraj K , Paranjpe Ishan , Coca Steven , Fayad Zahi A , Charney Alexander W , Bottinger Erwin P , He John Cijiang , Glicksberg Benjamin S , Chan Lili , Nadkarni Girish
Published: January 2021

Acute Kidney Injury (AKI) is among the most common complications of Coronavirus Disease 2019 (COVID-19). Throughout 2020 pandemic, the clinical approach to COVID-19 has progressively improved, but it is unknown how these changes have affected AKI incidence and severity. In this retrospective analysis, we report the trend over time of COVID-19 associated AKI and need of renal replacement therapy in a large health system in New York City, the first COVID-19 epicenter in United States.
COVID-19 in 823 Transplant patients: A Systematic Scoping Review
Authors: Emara Moataz Maher , Elsedeiq Mahmoud , Elmorshedi Mohamed , Neamatallah Hamed , Abdelkhalek Mostafa , Yassen Amr , Nabhan Ashraf
Published: January 2021

Background

Management of COVID-19 in transplant patients is a big challenge. Data on immunosuppression management, clinical picture, and outcomes are lacking.

Objectives

To summarize the current literature on COVID-19 in transplant patients especially the data regarding the immunosuppression protocols, clinical presentation, and outcomes.

Search strategy

A systematic search of MEDLINE, EBSCO, CENTRAL, CINAHL, LitCovid, Web of Science, and Scopus electronic databases. The references of the relevant studies were also searched. The search was last updated on June 3, 2020.

Selection Criteria

Primary reports of solid organ transplant patients who developed COVID-19. An overlap of cases in different reports was checked.

Data collection and analysis

A descriptive summary of immunosuppression therapy (before and after COVID-19), clinical presentation (symptoms, imaging, laboratory, and disease severity), management (oxygen therapy, antiviral, and antibacterial), major outcomes (Intensive care admission, invasive mechanical ventilation, acute kidney injury), and mortality.

Main results

We identified 74 studies reporting 823 cases of solid organ transplantation with COVID-19. Among 372 patients, 114 (30.6%) were mild COVID-19, 101 (27.2%) moderate, and 157 (42.2%) severe or critical.

Major outcomes included intensive care unit admission, invasive ventilation, and acute kidney injury, which occurred in 121 (14.7%), 97 (11.8%), and 63 (7.7%) of patients, respectively. Mortality was reported in 160 (19.4%) patients. Missing individual data hindered making clinical correlations.

Conclusion

COVID-19 in solid organ transplant patients probably has a more disease severity, worse major outcomes (Intensive care admission, invasive ventilation, acute kidney injury), and higher mortality than in non-transplant patients.
State-of-the-Art Risk Models for Diabetes, Hypertension, Visual Diminution, and COVID-19 Severity in Mexico
Authors: Amaya Heladio , Enciso Jennifer , Meizner Daniela , Pentland Alex , Noriega Alejandro
Published: January 2021

BACKGROUND

Diabetes and hypertension are among top public health priorities, particularly in low and middle-income countries where their health and socioeconomic impact is exacerbated by the quality and accessibility of health care. Moreover, their connection with severe or deadly COVID-19 illness has further increased their societal relevance. Tools for early detection of these chronic diseases enable interventions to prevent high-impact complications, such as loss of sight and kidney failure. Similarly, prognostic tools for COVID-19 help stratify the population to prioritize protection and vaccination of high-risk groups, optimize medical resources and tests, and raise public awareness.

METHODS

We developed and validated state-of-the-art risk models for the presence of undiagnosed diabetes, hypertension, visual complications associated with diabetes and hypertension, and the risk of severe COVID-19 illness (if infected). The models were estimated using modern methods from the field of statistical learning (e.g., gradient boosting trees), and were trained on publicly available data containing health and socioeconomic information representative of the Mexican population. Lastly, we assembled a short integrated questionnaire and deployed a free online tool for massifying access to risk assessment.

RESULTS

Our results show substantial improvements in accuracy and algorithmic equity (balance of accuracy across population subgroups), compared to established benchmarks. In particular, the models: i) reached state-of-the-art sensitivity and specificity rates of 90% and 56% (0.83 AUC) for diabetes, 80% and 64% (0.79 AUC) for hypertension, 90% and 56% (0.84 AUC) for visual diminution as a complication, and 90% and 60% (0.84 AUC) for development of severe COVID disease; and ii) achieved substantially higher equity in sensitivity across gender, indigenous/non-indigenous, and regional populations. In addition, the most relevant features used by the models were in line with risk factors commonly identified by previous studies. Finally, the online platform was deployed and made accessible to the public on a massive scale.

CONCLUSIONS

The use of large databases representative of the Mexican population, coupled with modern statistical learning methods, allowed the development of risk models with state-of-the-art accuracy and equity for two of the most relevant chronic diseases, their eye complications, and COVID-19 severity. These tools can have a meaningful impact on democratizing early detection, enabling large-scale preventive strategies in low-resource health systems, increasing public awareness, and ultimately raising social well-being.