bluuebunny/crossref_metadata_2025 huggingface dataset:
Aberrant Prestimulus Oscillations in Developmental Dyslexia Support an Underlying Attention Shifting Deficit
Authors: Meyer Lars , Schaadt Gesa
Published: March 2020

Developmental dyslexia (DD) impairs reading and writing acquisition in 5–10% of children, compromising schooling, academic success, and everyday adult life. DD associates with reduced phonological skills, evident from a reduced auditory mismatch negativity (MMN) in the electroencephalogram (EEG). It was argued that such phonological deficits are secondary to an underlying deficit in the shifting of attention to upcoming speech sounds. Here, we tested whether the aberrant MMN in individuals with DD is a function of EEG correlates of prestimulus attention shifting; based on prior findings, we focused prestimulus analyses on alpha-band oscillations. We administered an audio–visual oddball paradigm to school children with and without DD. Children with DD showed EEG markers of deficient attention switching (i.e., increased prestimulus alpha-band intertrial phase coherence [ITPC]) to precede and predict their reduced MMN—aberrantly increased ITPC predicted an aberrantly reduced MMN. In interaction, ITPC and MMN predicted reading abilities, such that poor readers showed both high ITPC and a reduced MMN, the reverse being true in good readers. Prestimulus ITPC may be an overlooked biomarker of deficient attention shifting in DD. The findings support the proposal that an attention shifting deficit underlies phonological deficits in DD, entailing new opportunities for targeted intervention.
Pyrazinamide enhances lipid peroxidation and antioxidant levels to induce liver injury in rat models through PI3k/Akt inhibition
Authors: Xu Yun , Jiang Yongfang , Li Yi
Published: March 2020

Pyrazinamide (PZA) is an anti-tuberculosis drug known to causes liver injury. phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) signaling protects against liver injury by promoting cellular antioxidant defenses and reducing intracellular reactive oxygen species (ROS) and lipid peroxidation. The regulatory mechanisms and functions of PI3K/Akt signaling during the hepatotoxicity of PZA are however not fully understood. Rats were administered PZA or/and the PI3K activator (740Y-P) for 7 days. The levels of serum parameters were examined via standard enzymatic techniques and the pathological status of the liver was confirmed by H & E staining. The levels of lipid peroxidation and antioxidant production were determined using commercial kits. Liver apoptosis was assessed by TUNEL staining. The expression of apoptosis-related proteins and PI3K/Akt signaling were assessed by western blot analysis. PZA treatment significantly increased serum alanine transaminase, aspartate transaminase, gamma-glutamyl transpeptidase and tall bilirubin leading to liver damage in rats. PZA also facilitated lipid peroxidation and suppressed antioxidant defenses. PZA led to apoptotic induction in rat liver cells through the downregulation of Bcl-2 and the upregulation of Bax and caspase-3. PZA also dramatically inhibited PI3K/Akt signaling in rat liver cells. We further verified that PI3K/Akt signaling in response to 740Y-P could attenuate hepatic injury, lipid peroxidation and apoptosis in rat liver cells in response to PZA. We reveal that PZA-induced liver injury in rats occurs through PI3k/Akt signaling, the recovery of which prevents liver injury in rat models.
Per- and Polyfluoroalkyl Substances Differentially Inhibit Placental Trophoblast Migration and Invasion In Vitro
Authors: Szilagyi John T , Freedman Anastasia N , Kepper Stewart L , Keshava Arjun M , Bangma Jackie T , Fry Rebecca C
Published: March 2020

Per- and polyfluoroalkyl substances (PFAS) are used as industrial surfactants and chemical coatings for household goods such as Teflon. Despite regulatory efforts to phase out legacy PFAS, they remain detectable in drinking water throughout the United States. This is due to the stability of legacy PFAS and the continued use of replacement compounds. In humans, PFAS have been detected in placenta and cord blood and are associated with low birth weight and preeclampsia risk. Preeclampsia is a leading cause of maternal mortality and is driven by insufficient endometrial trophoblast invasion, resulting in poor placental blood flow. PFAS alter invasion of other cell types, but their impact on trophoblasts is not understood. We therefore assessed the effects of PFAS on trophoblast migration, invasion, and gene expression in vitro. Trophoblast migration and invasion were assessed using a modified scratch assay in the absence or presence of Matrigel, respectively. Treatment with perfluorooctanoic sulfate (PFOS), perfluorooctanoic acid (PFOA), and GenX (1000 ng/ml) each decreased trophoblast migration over 24 h. However, only GenX (1000 ng/ml) significantly inhibited trophoblast invasion. Treatment with PFOS, PFOA, and GenX also decreased trophoblast expression of chemokines (eg, CCL2), chemokine receptors (eg, CCR4), and inflammatory enzymes (eg, ALOX15) involved in migration. Inhibition of chemokine receptors with pertussis toxin (10 ng/ml), a G-protein inhibitor, inhibited trophoblast migration similar to the PFAS. Taken together, PFAS decrease trophoblast migration, invasion, and inflammatory signaling. By understanding the mechanisms involved, it may be possible to identify the biological and exposure factors that contribute to preeclampsia.
Disease Resistance Evaluation of Elite CIMMYT Wheat Lines Containing the Coupled Fhb1 and Sr2 Genes
Authors: He Xinyao , Brar Gurcharn S. , Bonnett David , Dreisigacker Susanne , Hyles Jessica , Spielmeyer Wolfgang , Bhavani Sridhar , Singh Ravi P. , Singh Pawan K.
Published: March 2020

Fusarium head blight (FHB) and stem rust are among the most devastating diseases of wheat worldwide. Fhb1 is the most widely utilized and the only isolated gene for FHB resistance, while Sr2 is a durable stem rust resistance gene used in rust-prone areas. The two loci are closely linked on the short arm of chromosome 3B and the two genes are in repulsion phase among cultivars. With climate change and the shift in Fusarium populations, it is imperative to develop wheat cultivars resistant to both diseases. The present study was dedicated to developing wheat germplasm combining Fhb1 and Sr2 resistance alleles in the International Maize and Wheat Improvement Center (CIMMYT)’s elite cultivars’ backgrounds. Four recombinant inbred lines (RILs) in Hartog background that have the resistant Fhb1 and Sr2 alleles in coupled phase linkage were crossed with seven CIMMYT bread wheat lines, resulting in 208 lines. Molecular markers for both genes were employed in addition to the use of pseudo-black chaff (PBC) as a phenotypic marker for the selection of Sr2. At various stages of the selection process, progeny lines were assessed for FHB index, Fusarium damaged kernels (FDK), stem rust, and PBC expression as well as other diseases of interest (stripe rust and leaf spotting diseases). The 25 best lines were selected for CIMMYT’s wheat breeding program. In addition to expressing resistance to FHB, most of these 25 lines have an acceptable level of resistance to other tested diseases. These lines will be useful for wheat breeding programs worldwide and potentially speed up the resistance breeding efforts against FHB and stem rust.
Gene Genealogies Reveal High Nucleotide Diversity and Admixture Haplotypes Within ThreeAlternariaSpecies Associated with Tomato and Potato
Authors: Adhikari Tika B. , Ingram Thomas , Halterman Dennis , Louws Frank J.
Published: March 2020

Early blight (EB) and leaf blight are two destructive diseases of tomato in North Carolina (NC), caused by Alternaria linariae and A. alternata, respectively. During the last decade, EB caused by A. solani has increased in potato-producing areas in Wisconsin (WI). We collected 152 isolates of three Alternaria spp. associated with tomato and potato in NC and WI and used the gene genealogical approach to compare the genetic relationships among them. Two nuclear genes: the glyceraldehyde-3-phosphate dehydrogenase (GPDH), RNA polymerase second largest subunit (RPB2), and the rDNA internal transcribed spacer (ITS) region of these isolates were sequenced. Besides, sequences of the GPDH locus from international isolates described in previous studies were included for comparison purposes. A set of single nucleotide polymorphisms was assembled to identify locus-specific and species-specific haplotypes. Nucleotide diversity varied among gene sequences and species analyzed. For example, the estimates of nucleotide diversity and Watterson’s theta were higher in A. alternata than in A. linariae and A. solani. There was little or no polymorphisms in the ITS sequences and thus restricted haplotype placement. The RPB2 sequences were less informative to detect haplotype diversity in A. linariae and A. solani, yet six haplotypes were detected in A. alternata. The GPDH sequences enabled strongly supported phylogenetic inferences with the highest haplotype diversity and belonged to five haplotypes (AaH1 to AaH5), which consisted of only A. alternata from NC. However, 13 haplotypes were identified within and among A. linariae and A. solani sequences. Among them, six (AsAlH1 to AsAlH6) were identical to previously reported haplotypes in global samples and the remaining were new haplotypes. The most divergent haplotypes were AaH1, AsAlH2/AsAlH3, and AsAlH4 and consisted exclusively of A. alternata, A. linariae, and A. solani, respectively. Neutrality tests suggested an excess of mutations and population expansion, and selection may play an important role in nucleotide diversity of Alternaria spp.
Community coalescence: an eco-evolutionary perspective
Authors: Castledine Meaghan , Sierocinski Pawel , Padfield Daniel , Buckling Angus
Published: March 2020

Community coalescence, the mixing of different communities, is widespread throughout microbial ecology. Coalescence can result in approximately equal contributions from the founding communities or dominance of one community over another. These different outcomes have ramifications for community structure and function in natural communities, and the use of microbial communities in biotechnology and medicine. However, we have little understanding of when a particular outcome might be expected. Here, we integrate existing theory and data to speculate on how a crucial characteristic of microbial communities—the type of species interaction that dominates the community—might affect the outcome of microbial community coalescence. Given the often comparable timescales of microbial ecology and microevolution, we explicitly consider ecological and evolutionary dynamics, and their interplay, in determining coalescence outcomes.

This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.
Linking regional shifts in microbial genome adaptation with surface ocean biogeochemistry
Authors: Garcia Catherine A. , Hagstrom George I. , Larkin Alyse A. , Ustick Lucas J. , Levin Simon A. , Lomas Michael W. , Martiny Adam C.
Published: March 2020

Linking ‘omics measurements with biogeochemical cycles is a widespread challenge in microbial community ecology. Here, we propose applying genomic adaptation as ‘biosensors’ for microbial investments to overcome nutrient stress. We then integrate this genomic information with a trait-based model to predict regional shifts in the elemental composition of marine plankton communities. We evaluated this approach using metagenomic and particulate organic matter samples from the Atlantic, Indian and Pacific Oceans. We find that our genome-based trait model significantly improves our prediction of particulate C : P (carbon : phosphorus) across ocean regions. Furthermore, we detect previously unrecognized ocean areas of iron, nitrogen and phosphorus stress. In many ecosystems, it can be very challenging to quantify microbial stress. Thus, a carefully calibrated genomic approach could become a widespread tool for understanding microbial responses to environmental changes and the biogeochemical outcomes.

This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.
Experimental manipulation of selfish genetic elements links genes to microbial community function
Authors: Quistad Steven D. , Doulcier Guilhem , Rainey Paul B.
Published: March 2020

Microbial communities underpin the Earth's biological and geochemical processes, but their complexity hampers understanding. Motivated by the challenge of diversity and the need to forge ways of capturing dynamical behaviour connecting genes to function, biologically independent experimental communities comprising hundreds of microbial genera were established from garden compost and propagated on nitrogen-limited minimal medium with cellulose (paper) as sole carbon source. After 1 year of bi-weekly transfer, communities retained hundreds of genera. To connect genes to function, we used a simple experimental manipulation that involved the periodic collection of selfish genetic elements (SGEs) from separate communities, followed by pooling and redistribution across communities. The treatment was predicted to promote amplification and dissemination of SGEs and thus horizontal gene transfer. Confirmation came from comparative metagenomics, which showed the substantive movement of ecologically significant genes whose dynamic across space and time could be followed. Enrichment of genes implicated in nitrogen metabolism, and particularly ammonification, prompted biochemical assays that revealed a measurable impact on community function. Our simple experimental strategy offers a conceptually new approach for unravelling dynamical processes affecting microbial community function.

This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.
Cohort Profile: Prematurity Immunology in HIV-infected Mothers and their infants Study (PIMS)
Authors: Malaba Thokozile R , Gray Clive M , Myer Landon , Newell Marie-Louise ,   for the PIMS Study Group
Published: March 2020

Purpose

PIMS, is a prospective cohort study in South Africa investigating the association between antiretroviral therapy (ART) use, preterm delivery (PTD)and small-for gestational age (SGA) live births. PIMS main hypotheses are that ART initiation in pregnancy and ART-induced hypertension are associated with PTD and SGA respectively and that reconstitution of cellular immune responses in women on ART from before pregnancy results in increases in PTD of appropriate-for-gestational age (AGA) infants.

Participants

Pregnant women (n=3972) aged ≥18 years regardless of HIV status recruited from 2015 to 2016 into the overall PIMS cohort (2517 HIV-uninfected, 1455 HIV-infected). A nested cohort contained 551 HIV-infected women who were ≤24 weeks’ GA on ultrasound: 261 initiated ART before pregnancy, 290 initiated during pregnancy.

Findings to date

Women in the overall cohort were followed antenatally through to delivery using routine clinical records; further women in the nested cohort were actively followed up until 12 months postpartum, with data were collected on maternal health (HIV care and ART use, clinical care and inter-current clinical history). Other procedures conducted on the nested cohort included physical examinations (anthropometry, blood pressure measurement), assessment of fetal growth (ultrasound), maternal and infant phlebotomy for storage of plasma, RNA and peripheral blood mononuclear cells, collection of delivery specimens (placenta and cord blood), and infant 12 month developmental assessment. Preliminary findings have contributed to our understanding of risk factors for adverse birth outcomes, and the relationship between pregnancy immunology, HIV/ART and adverse birth outcomes.

Future plans

Using specimens collected from HIV-infected study participants throughout pregnancy and first year of life, the PIMS provides a valuable platform for answering a variety of research questions focused on temporal changes of immunology markers in women whose immune status is altered by HIV infection, and how ART initiated during pregnancy affects immune responses. The relationship between these immunological changes with adverse birth outcomes as well as possible longer-term impact of exposure to ART in fetal and early life will be explored. Additionally, further active and passive follow-up of mothers and their infants is planned at school-going age and beyond to chart growth, morbidity and development, as well as changes in family circumstances.
CAR T cell therapy in B-cell acute lymphoblastic leukaemia: Insights from mathematical models
Authors: León-Triana Odelaisy , Sabir Soukaina , Calvo Gabriel F. , Belmonte-Beitia Juan , Chulián Salvador , Martínez-Rubio Álvaro , Rosa María , Pérez-Martínez Antonio , Ramirez-Orellana Manuel , Pérez-García Víctor M.
Published: March 2020

Immunotherapies use components of the patient immune system to selectively target cancer cells. The use of CAR T cells to treat B-cell malignancies – leukaemias and lymphomas– is one of the most successful examples, with many patients experiencing long-lasting complete responses to this therapy. This treatment works by extracting the patient’s T cells and adding them the CAR group, which enables them to recognize and target cells carrying the antigen CD19+, that is expressed in these haematological tumors.

Here we put forward a mathematical model describing the time response of leukaemias to the injection of CAR T-cells. The model accounts for mature and progenitor B-cells, tumor cells, CAR T cells and side effects by incorporating the main biological processes involved. The model explains the early post-injection dynamics of the different compartments and the fact that the number of CAR T cells injected does not critically affect the treatment outcome. An explicit formula is found that provides the maximum CAR T cell expansion in-vivo and the severity of side effects. Our mathematical model captures other known features of the response to this immunotherapy. It also predicts that CD19+ tumor relapses could be the result of the competition between tumor and CAR T cells analogous to predator-prey dynamics. We discuss this fact on the light of available evidences and the possibility of controlling relapses by early re-challenging of the tumor with stored CAR T cells.
Geo-temporal distribution of 1,688 Chinese healthcare workers infected with COVID-19 in severe conditions – a secondary data analysis
Authors: Gao Wayne , Sanna Mattia , Wen Chi Pang
Published: March 2020

Introduction

The COVID-19 outbreak is posing an unprecedented challenge to healthcare workers. This study analyzes the geo-temporal effects on disease severity for the 1,688 Chinese healthcare workers infected with COVID-19.

Method

Using the descriptive results recently reported by the Chinese CDC, we compare the percentage of infected healthcare workers in severe conditions over time and across three areas in China, and the fatality rate of infected healthcare workers with all the infected individuals in China aged 22-59 years.

Results

Among the infected Chinese healthcare workers whose symptoms onset appeared during the same ten-day period, the percentage of those in severe conditions decreased statistical significantly from 19.7% (Jan 11 – 20) to 14.4% (Jan 21 – 31) to 8.7% (Feb 1 – 11). Across the country, there was also a significant difference in the disease severity among patients symptoms onset during the same period, with Wuhan being the most severe (17%), followed by Hubei Province (10.4%), and the rest of China (7.0%). The case fatality rate for the 1,688 infected Chinese healthcare workers was significantly lower than that for the 29,798 infected patients aged 20-59 years—0.3% (5/1,688) vs. 0.65% (193/29,798), respectively.

Conclusion

The disease severity improved considerably over a short period of time in China. The more severe conditions in Wuhan compared to the rest of the country may be attributable to the draconian lockdown. The clinical outcomes of infected Chinese healthcare workers may represent a more accurate estimation of the severity of COVID-19 for those who have access to quality healthcare.
Climatic influences on the worldwide spread of SARS-CoV-2
Authors: Bariotakis Michail , Sourvinos George , Castanas Elias , Pirintsos Stergios A.
Published: March 2020

The rapid global spread of the novel, pathogenic, SARS-CoV-2 causing the severe acute respiratory disease COVID-19, becomes a major health problem worldwide and pose the need for international predictive programs. Given the lack of both specific drugs and an efficient preventive vaccine, the expectation that SARS-CoV-2’s transmission rate might decrease in temperate regions during summer, dominated the social scene. Here, we attempted a prediction of the worldwide spread of the infections based on climatic data, expressed by 19 bioclimatic variables. The calculated probability maps shown that potential areas of infection follow a shift from the Tropical to Temperate and Mediterranean Bioclimatic regions, and back to the Tropics again. Maps show an increased probability of infections in Europe, followed by an expansion covering areas of the Middle East and Northern Africa, as well as Eastern coastal areas of North America, South-Eastern coastal areas of Latin America and two areas of Southern Australia, and later return to areas of Southeastern Asia, in a manner similar to that of influenza strains (H3N2). Our approach may therefore be of value for the worldwide spread of SARS-CoV-2, suggesting an optimistic scenario of asynchronous seasonal global outbreaks, like other viral respiratory diseases. Consequently, we suggest the incorporation of a climatic impact in the design and implementation of public health policies. Maps of our model are available (constantly updated up to the saturation of the model) at: https://navaak.shinyapps.io/CVRisk/.
Bibliometric Analysis of Global Scientific Research on SARS-CoV-2 (COVID-19)
Authors: Nasab Fatemeh Rafiei , Rahim Fakher
Published: March 2020

Background and Aim

Since late 2019, an unknown-origin pneumonia outbreak detected in Wuhan city, Hubei Province, China. We aimed to build a model to qualitatively and quantitatively assess publications of research of COVID-19 from 2019 to 2020.

Materials and Methods

Data were obtained from the Web of Science (WOS), PubMed, and Scopus Core Collection on March 02, 2020, and updated on March 10. We conducted a qualitative and quantitative analysis of publication outputs, journals, authors, institutions, countries, cited references, keywords, and terms according to bibliometric methods using VOS viewer c software packages.

Results

Initially, we identified 227 papers, of which after an exclusion process, 92 studies were selected for statistical analyses. China accounted for the highest proportion of published research (44 papers, 40.48%), followed by the United States (21 papers, 19.32%), and Canada (7 papers, 6.44%). Adjusted by gross domestic product (GDP), ranked first, with 0.003 articles per billion GDP. In total, the top 10 journals published 47 articles, which accounted for 51.08% of all publications in this Feld. A total of 6 studies (05.52%) were supported by National Natural Science Foundation of China. Chinese Academy of Sciences ranked second 2, 2.76%).

Conclusion

Bibliometric and visualized mapping may quantitatively monitor research performance in science and present predictions. The subject of this study was the fast growing publication on COVID-19. Most studies are published in journals with very high impact factors (IFs) and other journals are more interested in this type of research.

Highlights

Bibliometric description and mapping provided a birds-eye view of information on Covid-19 related research

Readers to comprehend the history of published Covid-19 articles in just a few minutes.

We evaluated the research strength of countries and institutions,

Scholars might refer to in order to find cooperative institutions.

During our research using the selected database, we tried to guarantee comprehension and objectivity.
Modelling the epidemiological trend and behavior of COVID-19 in Italy
Authors: Rovetta Alessandro , Bhagavathula Akshaya Srikanth , Castaldo Lucia
Published: March 2020

As of May 14, 2020, Italy has been one of the red hotspots for the COVID-19 pandemic. With over 220,000 confirmed cases and almost 33,000 confirmed deaths reported from February, it is necessary to fully understand the spread of COVID-19 in this country. By S.E.I.R. simulation, we estimated the most representative basic reproduction number R0 for the three most affected regions from February 22 to March 14, 2020. In doing so, we have been able to evaluate the consistency of the first containment measures until the end of April, as well as identify possible SARS-CoV-2 local behavior mutations and specificities. Next to that, through new estimates of the infection mortality rate, we recalculated a more plausible number of real infected. Finally, given the absolutely anomalous trend of the Lombardy region, we looked for correlations between COVID-19 total cases and air pollutants such as PM 10 and PM 2.5.
Forecasting Ultra-early Intensive Care Strain from COVID-19 in England, v1.1.4
Authors: Deasy Jacob , Rocheteau Emma , Kohler Katharina , Stubbs Daniel J. , Barbiero Pietro , Liò Pietro , Ercole Ari
Published: March 2020

The COVID-19 pandemic has led to unprecedented strain on intensive care unit (ICU) admission in parts of the world. Strategies to create surge ICU capacity require complex local and national service reconfiguration and reduction or cancellation of elective activity. These measures have an inevitable lag-time before additional capacity comes on-line. An accurate short-range forecast would be helpful in guiding such difficult, costly, and ethically challenging decisions.

At the time this work began, cases in England were starting to increase. If this represents a true spread in disease then ICU demand could increase rapidly. Here we present a short-range forecast based on published real-time COVID-19 case data from the seven National Health Service (NHS) commissioning regions in England (East of England, London, Midlands, North East and Yorkshire, North West, South East and South West). We use a Monte Carlo approach to model the likely impact of current diagnoses on regional ICU capacity over a 14-day horizon under the assumption that the increase in cases represents the start of an exponential growth in infections. Our model is designed to be parsimonious and based on available epidemiological data from the literature at the moment.

On the basis of the modelling assumptions made, ICU occupancy is likely to increase dramatically in the days following the time of modelling. If the current exponential growth continues, case numbers will be comparable to current ICU bed numbers within weeks. Despite variable growth in absolute patients, all commissioning regions are forecast to be heavily burdened under the assumptions used.

Whilst, like any forecast model, there remain uncertainties both in terms of model specification and robust epidemiological data in this early prospective phase, it would seem that surge capacity will be required in the very near future. Our findings should be interpreted with caution, but we hope that our model will help policy decision makers with their preparations. The uncertainties in the data highlight the urgent need for ongoing real-time surveillance to allow forecasts to be constantly updated using high quality local patient-facing data as it emerges.
Assessing the potential impact of COVID-19 in Brazil: Mobility, Morbidity and the burden on the Health Care System
Authors: Coelho Flávio C , Lana Raquel M , Cruz Oswaldo G , Villela Daniel , Bastos Leonardo S , Piontti Ana Pastore y , Davis Jessica T , Vespignani Alessandro , Codeço Claudia T , Gomes Marcelo F C
Published: March 2020

Background

Brazil detected community transmission of COVID-19 on March 13, 2020. In this study we identify which areas in the country are most vulnerable for COVID-19, both in terms of the risk of arrival of COVID-19 cases and the risk of sustained transmission. The micro-regions with higher social vulnerability are also identified.

Methods

Probabilistic models were used to calculate the probability of COVID-19 spread from São Paulo and Rio de Janeiro, according to previous data available on human mobility in Brazil. We also perform a multivariate cluster analysis of socio-economic indices to identify areas with similar social vulnerability.

Results

The results consist of a series of maps of effective distance, outbreak probability, hospital capacity and social vulnerability. They show areas in the North and Northeast with high risk of COVID-19 outbreak that are also highly vulnerable.

Interpretation

The maps produced are useful for authorities in their efforts to prioritize actions such as resource allocation to mitigate the effects of the pandemic and may help other countries to use a similar approach to predict the virus route in their countries as well.

Funding

No funding
The local stability of a modified multi-strain SIR model for emerging viral strains
Authors: Fudolig Miguel , Howard Reka
Published: March 2020

We study a novel multi-strain SIR epidemic model with selective immunity by vaccination. A newer strain is made to emerge in the population when a preexisting strain has reached equilbrium. We assume that this newer strain does not exhibit cross-immunity with the original strain, hence those who are vaccinated and recovered from the original strain become susceptible to the newer strain. Recent events involving the COVID-19 virus demonstrates that it is possible for a viral strain to emerge from a population at a time when the influenza virus, a well-known virus with a vaccine readily available for some of its strains, is active in a population. We solved for four different equilibrium points and investigated the conditions for existence and local stability. The reproduction number was also determined for the epidemiological model and found to be consistent with the local stability condition for the disease-free equilibrium.
Basic and effective reproduction numbers of COVID-19 cases in South Korea excluding Sincheonji cases
Authors: Hwang Jeongeun , Park Hyunjung , Jung Jiwon , Kim Sung-Han , Kim Namkug
Published: March 2020

In February and March 2020, COVID-19 epidemic in South Korea met a large black swan effect by a Sincheonji cult mass infection in Daegu-Gyeongbuk area. The black swan made it difficult to evaluate that the current policies for infection prevention including social distancing, closing schools, hand washing, and wearing masks good enough or not. Therefore, in this study, we evaluated basic reproduction number (R0) and time-dependent reproduction number (Rt) of confirmed cases based on various kinds of populations, including total, Daegu-Geyoengbuk, except-Daegu-Gyeongbuk, Sincheonji, and except-Sincheonji. In total, it seems the infection is going to be under control, but this is never true because in the except-Sincheonji and except-Daegu-Geyongbuk cases, R0 is still above 1.0, and Rt is drifting around 1.0. This study could be used to determine government policies in the near future.
Investigating the potential effect of antihypertensive medication on psychiatric disorders: a mendelian randomisation study
Authors: Chauquet Solal , O’Donovan Michael , Walters James , Wray Naomi , Shah Sonia
Published: March 2020

Background

There is growing evidence from observational studies that drugs used for the prevention and treatment of CVD may cause, exacerbate, or relieve neuropsychiatric symptoms.

Aim

Use Mendelian randomisation (MR) analysis to investigate the potential effect of different antihypertensive drugs on schizophrenia, bipolar disorder and major depressive disorder.

Methods

We conduct two sample MR using expression quantitative trait loci (eQTLs) for antihypertensive drug target genes as genetic instruments, together with summary data from published genome-wide association studies, to investigate the causal effect of changes in drug target gene expression (as proxies of drug exposure) on psychiatric disorders.

Results

A 1 standard deviation lower expression of the ACE gene in blood was associated with 4.0 mmHg (95% CI = 2.7 – 5.3) lower systolic blood pressure, but increased risk of schizophrenia (OR (95% CI) = 1.75 (1.28 – 2.38)). A concordant direction of effect was observed with ACE expression in brain tissue.

Conclusions

Findings suggest an adverse effect of lower ACE expression on schizophrenia risk. This warrants further investigation to determine if lowering ACE activity for treatment of hypertension using ACE inhibitors (particularly centrally-acting drugs) may worsen symptoms in patients with schizophrenia, and whether there is any association between ACE inhibitor use and risk of (mainly late-onset) schizophrenia.
The generalized Price equation: forces that change population statistics
Authors: Frank Steven A. , Godsoe William
Published: March 2020

The Price equation partitions the change in the expected value of a population measure. The first component describes the partial change caused by altered frequencies. The second component describes the partial change caused by altered measurements. In biology, frequency changes often associate with the direct effect of natural selection. Measure changes reflect processes during transmission that alter trait values. More broadly, the two components describe the direct forces that change population composition and the altered frame of reference that changes measured values. The classic Price equation is limited to population statistics that can expressed as the expected value of a measure. Many statistics cannot be expressed as expected values, such as the harmonic mean and the family of rescaled diversity measures. We generalize the Price equation to any population statistic that can be expressed as a function of frequencies and measurements. We obtain the generalized partition between the direct forces that cause frequency change and the altered frame of reference that changes measurements.
maxnodf: an R package for fair and fast comparisons of nestedness between networks
Authors: Hoeppke Christoph , Simmons Benno I.
Published: March 2020

Nestedness is a widespread pattern in mutualistic networks that has high ecological and evolutionary importance due to its role in enhancing species persistence and community stability. Nestedness measures tend to be correlated with fundamental properties of networks, such as size and connectance, and so nestedness values must be normalised to enable fair comparisons between different ecological communities. Current approaches, such as using null-corrected nestedness values andz-scores, suffer from extensive statistical issues. Thus a new approach called NODFcwas recently proposed, where nestedness is expressed relative to network size, connectance and the maximum nestedness that could be achieved in a particular network. While this approach is demonstrably effective in overcoming the issues of collinearity with basic network properties, it is computationally intensive to calculate, and current approaches are too slow to be practical for many types of analysis, or for analysing large networks.

We developed three highly-optimised algorithms, based on greedy, hillclimbing and simulated annealing approaches, for calculation of NODFc, spread along a speed-quality continuum. Users thus have the choice between a fast algorithm with a less accurate estimate, a slower algorithm with a more accurate estimate, and an intermediate option.

We outline the package, and its implementation, as well as provide comparative performance benchmarking and two example analyses. We show thatmaxnodfenables speed increases of hundreds of times faster than existing approaches, with large networks seeing the biggest improvements. For example, for a large network with 3000 links, computation time was reduced from 50 minutes using the fastest existing algorithm to 11 seconds usingmaxnodf.

maxnodfmakes correctly-normalised nestedness measures feasible for complex analyses of even large networks. Analyses that would previously take weeks to complete can now be finished in hours or even seconds. Given evidence that correctly normalising nestedness values can significantly change the conclusions of ecological studies, we believe this package will usher in necessary widespread use of appropriate comparative nestedness statistics.
Limits to flow detection in phase contrast MRI
Authors: Williamson Nathan H. , Komlosh Michal E. , Benjamini Dan , Basser Peter J.
Published: March 2020

Pulsed gradient spin echo (PGSE) complex signal behavior becomes dominated by attenuation rather than oscillation when displacements due to flow are similar or less than diffusive displacements. In this “slow-flow” regime, the optimal displacement encoding parameterqfor phase contrast velocimetry depends on the diffusive length scalerather than the velocity encoding parametervenc= π/(qΔ). The minimum detectable mean velocity using the difference between the phase at +qslowand −qslowis. These theories are then validated and applied to MRI by performing PGSE echo planar imaging experiments on water flowing through a column with a bulk region and a beadpack region at controlled flow rates. Velocities as slow as 6 µm/s are detected with velocimetry. Theories, MRI experimental protocols, and validation on a controlled phantom help to bridge the gap between porous media NMR and pre-clinical phase contrast and diffusion MRI.
OVERWHELMING GENETIC HETEROGENEITY AND EXHAUSTING MOLECULAR DIAGNOSTIC PROCESS IN CHRONIC AND PROGRESSIVE ATAXIAS: FACING IT UP WITH AN ALGORITHM, A GENE, A PANEL AT A TIME
Authors: Maturo J Perez , Zavala L , Vega P , González-Morón D , Medina N , Salinas V , Rosales J , Córdoba M , Arakaki T , Garretto N , Rodríguez-Quiroga S. , Kauffman MA
Published: March 2020

Ataxias is one of the most frequent complaints in Neurogenetics units worldwide. Currently, more than 50 subtypes of spinocerebellar ataxias and more than 60 recessive ataxias are recognized. We conducted an 11-year prospective, observational, analytical study in order to estimate the frequency of pediatric and adult genetic ataxias in Argentina, to describe the phenotypes of this cohort and evaluate the diagnostic yield of the algorithm used in our unit. We included 334 ataxic patients. Our diagnostic approach was successful in one third of the cohort. A final molecular diagnosis was reached in 113 subjects. This rate is significantly higher in the subgroup of patients with a positive family history, where the diagnostic yield increased to 55%. The most prevalent dominant and recessive ataxias in Argentina were SCA-2 (36% of dominant ataxias) and FA (62% of recessive ataxias), respectively. Next generation sequencing based assays were diagnostic in the 65% of the patients requiring these tests. These results provide relevant epidemiological information, bringing a comprehensive knowledge of the most prevalent subtypes of genetic ataxias and their phenotypes in our territory and laying the groundwork for rationally implementing genetic diagnostic programs for these disorders in our country.
Deep learning for predicting COVID-19 malignant progression
Authors: Fang Cong , Bai Song , Chen Qianlan , Zhou Yu , Xia Liming , Qin Lixin , Gong Shi , Xie Xudong , Zhou Chunhua , Tu Dandan , Zhang Changzheng , Liu Xiaowu , Chen Weiwei , Bai Xiang , Torr Philip H.S.
Published: March 2020

As COVID-19 is highly infectious, many patients can simultaneously flood into hospitals for diagnosis and treatment, which has greatly challenged public medical systems. Treatment priority is often determined by the symptom severity based on first assessment. However, clinical observation suggests that some patients with mild symptoms may quickly deteriorate. Hence, it is crucial to identify patient early deterioration to optimize treatment strategy. To this end, we develop an early-warning system with deep learning techniques to predict COVID-19 malignant progression. Our method leverages clinical data and CT scans of outpatients and achieves an AUC of 0.920 in the single-center study and an average AUC of 0.874 in the multicenter study. Moreover, our model automatically identifies crucial indicators that contribute to the malignant progression, including Troponin, Brain natriuretic peptide, White cell count, Aspartate aminotransferase, Creatinine, and Hypersensitive C-reactive protein.
Early Outcomes of Preoperative 5-fraction Radiation Therapy for Soft Tissue Sarcoma Followed by Immediate Surgical Resection
Authors: Parsai Shireen , Lawrenz Joshua , Kilpatrick Scott , Rubin Brian , Hymes Cory , Gray Michele , Mesko Nathan , Shah Chirag , Nystrom Lukas , Scott Jacob G
Published: March 2020

Purpose/Objectives

There are limited data regarding the use of hypofractionated radiation therapy (RT) for soft tissue sarcoma. We report early oncologic outcomes and wound complications of patients undergoing preoperative hypofractionated (5 fraction) RT followed by immediate surgical resection.

Materials/Methods

An IRB-approved database of patients treated with preoperative RT for soft tissue sarcoma was queried. Patients treated with a hypofractionated dosing regimen followed by immediate (within 7 days) planned wide surgical resection were identified.

Results

Between 2016 to 2019, sixteen patients met eligibility criteria. The median clinical follow-up was 10.7 months (range 1.7-33.2). The median patient age was 64 years old (range 33-88). Ten of the sarcomas were located in the lower extremity, 4 in the upper extremity, and two were located in the trunk. Five patients had metastatic disease at diagnosis. The majority of the patients received a total radiation dose of 30 Gy in 5 fractions (range 27.5-40 Gy) on consecutive days. All patients were planned with IMRT/VMAT. The median time to surgical resection following the completion of RT was 1 day (range 0-7 days). The median time from initial biopsy results to completion of primary oncologic therapy was 20 days (range 16-35). Ten patients achieved R0 resection, whereas the remaining 6 patients achieved R1 resection. Of the 13 patients assessed for local control, no patients developed local failure. Five patients developed wound healing complications (31%), of which only three patients (19%) required return to the operating room.

Conclusions

Treatment of soft tissue sarcoma with preoperative hypofractionated RT followed by immediate resection resulted in a median of 20 days from biopsy results to completion of oncologic therapy. Early outcomes demonstrate favorable wound healing. Further prospective data with long-term follow-up is required to determine the oncologic outcomes and toxicity of hypofractionated preoperative RT.
Using a Simulation Centre to Evaluate the Effect of anArtificial Intelligence-Powered Clinical Decision Support System for Depression Treatment on the Physician-Patient Interaction
Authors: Benrimoh David , Tanguay-Sela Myriam , Perlman Kelly , Israel Sonia , Mehltretter Joseph , Armstrong Caitrin , Fratila Robert , Parikh Sagar V. , Karp Jordan F. , Heller Katherine , Vahia Ipsit V. , Blumberger Daniel M. , Karama Sherif , Vigod Simone , Myhr Gail , Martins Ruben , Rollins Colleen , Popescu Christina , Lundrigan Eryn , Snook Emily , Wakid Marina , Williams Jérôme , Soufi Ghassen , Perez Tamara , Tunteng Jingla-Fri , Rosenfeld Katherine , Miresco Marc , Turecki Gustavo , Cardona Liliana Gomez , Linnaranta Outi , Margolese Howard C.
Published: March 2020

Objective

Aifred is an artificial intelligence (AI)-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician-patient interaction.

Methods

Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-hour study at a clinical interaction simulation centre with standardized patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-minute clinical scenarios with standardized patients portraying mild, moderate, and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews, and standardized patient feedback.

Results

All twenty participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the AI’s predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool’s impact on the physician-patient interaction.

Conclusions

The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician-patient interaction prior to clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.
Under detection of depression in primary care settings in low and middle-income countries: A systematic review and meta-analysis
Authors: Fekadu Abebaw , Demissie Mekdes , Berhane Rahel , Medhin Girmay , Bitew Teserra , Hailemariam Maji , Minaye Abebaw , Habtamu Kassahun , Milkias Barkot , Petersen Inge , Patel Vikram , Cleare Anthony J , Mayston Rosie , Thornicroft Graham , Alem Atalay , Hanlon Charlotte , Prince Martin
Published: March 2020

Objective

Depression is the commonest mental disorder in primary care but is poor identified. The objective of this review was to determine the level of detection of depression by primary care clinicians and its determinants in studies from low-and middle-income countries (LMICs).

Methods

Design

Systematic review and meta-analysis. Review protocol was registered in the PROSPERO database (CRD42016039704).

Databases

PubMed, PsycINFO, Medline, EMBASE, LILAC and AJOL.

Quality assessment

Risk of bias within studies evaluated with the Effective Public Health Practice Project (EPHPP).

Synthesis

“Gold standard” diagnosis for the purposes of this review were based on the 9-item Patient Health Questionnaire (PHQ-9; cutoff scores of 5 and 10), structured interview or expert diagnosis. Meta-analysis was conducted excluding studies on special populations. Analysis of pooled data were stratified by diagnostic approaches.

Results

A total of 2223 non-duplicate publications were screened. Ten publications, from two multi-country studies and eight single country studies, making 18 country level reports, were included. One of the multi-country studies used an enriched sample of screen positive participants. Overall methodological quality of the studies was good. Depression detection was 0.0% in five reports and <12% in another five. The pooled detection for two reports that used PHQ-9 at a cutoff point of 5 (combined sample size = 1426) was 3.9% (95% CI = 2.3%, 5.5%); in the four reports that used PHQ-9 cutoff score of 10 (combined sample size =5481), the pooled detection was 7.0% (95% CI = 3.9%, 10.2%). For the enriched sample, the pooled detection was 43.5 % (95% CI: 25.7%, 61.0%). Severity of depression and suicidality were significantly associated with detection.

Conclusions

The extremely low detection of depression by primary care clinicians poses a serious threat to scaling up mental healthcare in LMICs. Interventions to improve detection should be prioritized.

Strength and limitation of study

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This is the first review of detection of depression in LMIC settings

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The review was comprehensive in terms of databases searched

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Screening tools were used as gold standards, which may lead to overestimation of prevalence and underestimation of detection

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The small number of studies and the use of different instruments and cutoff

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points precluded exploration of sources of heterogeneity

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The review does not include studies on distress or sub-threshold depression