bluuebunny/crossref_metadata_2025_split huggingface dataset:
The circularization time-scales of late–type binary stars
Authors: Terquem Caroline , Martin Scott 
Published: August 2021

ABSTRACT
We examine the consequences of, and apply, the formalism developed in Terquem (2021) for calculating the rate DR at which energy is exchanged between fast tides and convection. In this previous work, DR (which is proportional to the gradient of the convective velocity) was assumed to be positive in order to dissipate the tidal energy. Here we argue that, even if energy is intermittently transferred from convection to the tides, it must ultimately return to the convective flow and transported efficiently to the stellar surface on the convective time-scale. This is consistent with, but much less restrictive than, enforcing DR &gt; 0. Our principle result is a calculation of the circularization time-scale of late–type binaries, taking into account the full time evolution of the stellar structure. We find that circularization is very efficient during the PMS phase, inefficient during the MS, and once again efficient when the star approaches the RGB. These results are in much better agreement with observations than earlier theories. We also apply our formalism to hot Jupiters, and find that tidal dissipation in a Jupiter mass planet yields a circularization time-scale of 1 Gyr for an orbital period of 3 d, also in good overall agreement with observations. The approach here is novel, and the apparent success of the theory in resolving longstanding time-scale puzzles is compelling.
Improving the reliability of photometric redshift with machine learning
Authors: Razim Oleksandra , Cavuoti Stefano , Brescia Massimo , Riccio Giuseppe , Salvato Mara , Longo Giuseppe 
Published: August 2021

ABSTRACT
In order to answer the open questions of modern cosmology and galaxy evolution theory, robust algorithms for calculating photometric redshifts (photo-z) for very large samples of galaxies are needed. Correct estimation of the various photo-z algorithms’ performance requires attention to both the performance metrics and the data used for the estimation. In this work, we use the supervised machine learning algorithm MLPQNA (Multi-Layer Perceptron with Quasi-Newton Algorithm) to calculate photometric redshifts for the galaxies in the COSMOS2015 catalogue and the unsupervised Self-Organizing Maps (SOM) to determine the reliability of the resulting estimates. We find that for zspec &lt; 1.2, MLPQNA photo-z predictions are on the same level of quality as spectral energy distribution fitting photo-z. We show that the SOM successfully detects unreliable zspec that cause biases in the estimation of the photo-z algorithms’ performance. Additionally, we use SOM to select the objects with reliable photo-z predictions. Our cleaning procedures allow us to extract the subset of objects for which the quality of the final photo-z catalogues is improved by a factor of 2, compared to the overall statistics.
COTAN: scRNA-seq data analysis based on gene co-expression
Authors: Galfrè Silvia Giulia , Morandin Francesco , Pietrosanto Marco , Cremisi Federico , Helmer-Citterich Manuela 
Published: August 2021

Abstract
Estimating the co-expression of cell identity factors in single-cell is crucial. Due to the low efficiency of scRNA-seq methodologies, sensitive computational approaches are critical to accurately infer transcription profiles in a cell population. We introduce COTAN, a statistical and computational method, to analyze the co-expression of gene pairs at single cell level, providing the foundation for single-cell gene interactome analysis. The basic idea is studying the zero UMI counts’ distribution instead of focusing on positive counts; this is done with a generalized contingency tables framework. COTAN can assess the correlated or anti-correlated expression of gene pairs, providing a new correlation index with an approximate p-value for the associated test of independence. COTAN can evaluate whether single genes are differentially expressed, scoring them with a newly defined global differentiation index. Similarly to correlation network analysis, it provides ways to plot and cluster genes according to their co-expression pattern with other genes, effectively helping the study of gene interactions, becoming a new tool to identify cell-identity markers. We assayed COTAN on two neural development datasets with very promising results. COTAN is an R package that complements the traditional single cell RNA-seq analysis and it is available at https://github.com/seriph78/COTAN.
Gotree/Goalign: toolkit and Go API to facilitate the development of phylogenetic workflows
Authors: Lemoine Frédéric , Gascuel Olivier 
Published: August 2021

Abstract
Phylogenetics is nowadays at the center of numerous studies in many fields, ranging from comparative genomics to molecular epidemiology. However, phylogenetic analysis workflows are usually complex and difficult to implement, as they are often composed of many small, reccuring, but important data manipulations steps. Among these, we can find file reformatting, sequence renaming, tree re-rooting, tree comparison, bootstrap support computation, etc. These are often performed by custom scripts or by several heterogeneous tools, which may be error prone, uneasy to maintain and produce results that are challenging to reproduce. For all these reasons, the development and reuse of phylogenetic workflows is often a complex task. We identified many operations that are part of most phylogenetic analyses, and implemented them in a toolkit called Gotree/Goalign. The Gotree/Goalign toolkit implements more than 120 user-friendly commands and an API dedicated to multiple sequence alignment and phylogenetic tree manipulations. It is developed in Go, which makes executables easily installable, integrable in workflow environments, and parallelizable when possible. Moreover, Go is a compiled language, which accelerates computations compared to interpreted languages. This toolkit is freely available on most platforms (Linux, MacOS and Windows) and most architectures (amd64, i386) on GitHub at https://github.com/evolbioinfo/gotree, Bioconda and DockerHub.
Multimodal platform for assessing drug distribution and response in clinical trials
Authors: Lopez Begoña G C , Kohale Ishwar N , Du Ziming , Korsunsky Ilya , Abdelmoula Walid M , Dai Yang , Stopka Sylwia A , Gaglia Giorgio , Randall Elizabeth C , Regan Michael S , Basu Sankha S , Clark Amanda R , Marin Bianca-Maria , Mladek Ann C , Burgenske Danielle M , Agar Jeffrey N , Supko Jeffrey G , Grossman Stuart A , Nabors Louis B , Raychaudhuri Soumya , Ligon Keith L , Wen Patrick Y , Alexander Brian , Lee Eudocia Q , Santagata Sandro , Sarkaria Jann , White Forest M , Agar Nathalie Y R 
Published: August 2021

Abstract

Background
Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy.

Methods
Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial.

Results
PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient’s response to adavosertib.

Conclusions
The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.
Corticosteroids Do Not Increase the Likelihood of Primary Clostridioides difficile Infection in the Setting of Broad-Spectrum Antibiotic Use
Authors: Carlson Travis J , Gonzales-Luna Anne J , Wilcox Melissa F , Theriault Sarah G , Alnezary Faris S , Patel Pankaj , Ahn Bumhee K , Zasowski Evan J , Garey Kevin W 
Published: August 2021

Abstract

Background
The pathogenesis of Clostridioides difficile infection (CDI) involves a significant host immune response. Generally, corticosteroids act by suppressing the host inflammatory response, and their anti-inflammatory effects are used to treat gastrointestinal disorders. Although previous investigations have demonstrated mixed results regarding the effect of corticosteroids on CDI, we hypothesized that the anti-inflammatory effect of corticosteroids would decrease the risk of CDI in hospitalized patients.

Methods
This was a case–control study of hospitalized adults. The case population included patients diagnosed with primary CDI who received at least 1 dose of a high-risk antibiotic (cefepime, meropenem, or piperacillin-tazobactam) in the 90 days before CDI diagnosis. The control population included patients who received at least 1 dose of the same high-risk antibiotic but did not develop CDI in the 90 days following their first dose of antibiotic. The primary study outcome was the development of CDI based on receipt of corticosteroids.

Results
The final study cohort consisted of 104 cases and 153 controls. Those who received corticosteroids had a lower odds of CDI after adjusting for age, proton pump inhibitor use, and antibiotic days of therapy (odds ratio, 0.54; 95% CI, 0.30–0.97; P = .04). We did not observe an association between corticosteroid dose or duration and CDI.

Conclusions
We demonstrated a 46% relative reduction in the odds of developing CDI in patients who received corticosteroids in the past 90 days. We believe that our results provide the best clinical evidence to further support mechanistic studies underlying this phenomenon.
Vertex operator superalgebra/sigma model correspondences: The four-torus case
Authors: Anagiannis Vassilis , Cheng Miranda C N , Duncan John , Volpato Roberto 
Published: August 2021

Abstract
We propose a correspondence between vertex operator superalgebras and families of sigma models in which the two structures are related by symmetry properties and a certain reflection procedure. The existence of such a correspondence is motivated by previous work on ${\cal N}=(4,4)$ supersymmetric non-linear sigma models on K3 surfaces, and on a vertex operator superalgebra with Conway group symmetry. Here we present an example of the correspondence for ${\cal N}=(4,4)$ supersymmetric non-linear sigma models on four-tori, and compare it to the K3 case.
Trusts and beneficiary ownership concept in Russian law and practice
Authors: Kanachevsky Vladimir 
Published: August 2021

Abstract
This article outlines the regulatory landscape of the use of trusts by Russian residents and the implementation of the concept of beneficial ownership by the Russian legal system. The researcher describes an attempt to introduce trusts into the Russian legal system. The article also deals with trusts created by Russian residents abroad. In addition, the approaches of the Russian courts to the beneficial ownership concept, in the context of trusts and offshore companies are also discussed. The author analyses a number of cases which shed light on the issue of recognition of beneficiary owners’ rights in Russia.
The development of an intervention to support uptake and adherence to antiretroviral therapy in people living with HIV: the SUPA intervention. A brief report
Authors: King Kathryn , Horne Rob , Cooper Vanessa , Glendinning Elizabeth , Michie Susan , Chalder Trudie ,   SUPA Group, Jane Anderson , Campbell Lucy J , Chalder Trudie , Collins Simon , Cooper Vanessa , Glendinning Elizabeth , Fisher Martin , Harfield Scott , Horne Rob , King Kathryn , Leake-Date Heather , McCrone Paul , Michie Susan , Nelson Mark , Perry Nicky , Sabin Caroline , Smith Jonathan A , Sseruma Winnie , Walker Sarah 
Published: August 2021

Abstract
The effectiveness of antiretroviral therapy (ART) depends on prompt uptake of treatment and a high level of adherence over the long-term, yet these behaviors are suboptimal. Previous interventions have significantly improved adherence but effect sizes are generally small. The aim of this article is to describe the design and content of an intervention to support uptake and adherence to treatment in HIV positive patients (SUPA intervention), utilizing cognitive behavioral and motivational interviewing (MI) techniques. The intervention was developed in line with Medical Research Council (MRC) guidance for the development of complex interventions and informed by the NICE (National Institute for Health and Care Excellence) Guidelines for adherence, empirical evidence and focus groups. Behavior change techniques were mapped to perceptual and practical barriers to uptake and adherence to ART, identified in previous research. Intervention materials were designed and later discussed within focus groups, where feedback enabled an iterative process of development.
We conclude it is possible to transparently report the design and content of a theory-based intervention to increase uptake and adherence to ART. The intervention has been evaluated within a randomized controlled trial (RCT) at 10 HIV clinics in England, the results of which will be reported elsewhere.
Integrated transcriptome and proteome analysis of developing embryo reveals the mechanisms underlying the high levels of oil accumulation in Carya cathayensis Sarg.
Authors: Huang Chunying , Li Yan , Wang Ketao , Xi Jianwei , Xu Yifan , Hong Junyan , Si Xiaolin , Ye Hongyu , Lyu Shiheng , Xia Guohua , Wang Jianhua , Li Peipei , Xing Yulin , Wang Yige , Huang Jianqin 
Published: August 2021

Abstract
Hickory (Carya cathayensis Sarg.) is an extraordinary nut-bearing deciduous arbor with high content of oil in its embryo. However, the molecular mechanism underlying high oil accumulation is mostly unknown. Here, we reported that the lipid droplets and oil accumulation gradually increased with the embryo development and the oil content was up to ~76% at maturity. Furthermore, transcriptome and proteome analysis of developing hickory embryo identified 32,907 genes and 9857 proteins. Time-series analysis of gene expressions showed that these genes were divided into 12 clusters and lipid metabolism-related genes were enriched in Cluster 3, with the highest expression levels at 95 days after pollination (S2). Differentially expressed genes and proteins indicated high correlation, and both were enriched in the lipid metabolism. Notably, the genes involved in biosynthesis, transport of fatty acid/lipid and lipid droplets formation had high expression levels at S2, while the expression levels of other genes required for suberin/wax/cutin biosynthesis and lipid degradation were very low at all the sampling time points, ultimately promoting the accumulation of oil. Quantitative reverse-transcription PCR analysis also verified the results of RNA-seq. The co-regulatory networks of lipid metabolism were further constructed and WRINKLED1 (WRI1) was a core transcriptional factor located in the nucleus. Of note, CcWRI1A/B could directly activate the expression of some genes (CcBCCP2A, CcBCCP2B, CcFATA and CcFAD3) required for fatty acid synthesis. These results provided in-depth evidence for revealing the molecular mechanism of high oil accumulation in hickory embryo.
Research on pumped two-phase single-sided cold plate of IGBT for rail transit applications
Authors: Wu Hui , Zhang Gang , Feng Zhaozan , He Kai , Yao Lei , Li Wei , Yao Shichune 
Published: August 2021

Abstract
The use of pumped two-phase cooling to improve the thermal management of insulated gate bipolar transistor (IGBT) in rail transportation is a novel cooling technology. An experimental investigation on pumped two-phase cold plate of IGBT used in HXD1C locomotives was conducted at a mass flow rate of 0.1 kg/s–0.29 kg/s and a heat flux of 6.2 W/cm2, with R245fa as the working fluid. The experimental results showed that the base temperature nonuniformity can be controlled within 2.2 °C at flow rates of 0.14 kg/s and 0.19 kg/s, which is of great benefit to the reliability of IGBT. Based on well known correlations for saturated flow boiling in tubes, an analytical model was developed and compared with the experimental data. The model could predict the base temperature data within an error band of ±3 °C, as well as capture the trend of base temperature as a function of vapour quality and mass flow rate. The performance of the pumped two-phase cold plate of IGBT could be further improved with the aid of the developed model.
Uniform asymptotic expansions for the Whittaker functions
M

κ
,
μ

(
z
) and
W

κ
,
μ

(
z
) with
μ
large
Authors: Dunster T. M. 
Published: August 2021

Uniform asymptotic expansions are derived for Whittaker’s confluent hypergeometric functions

M

κ
,
μ

(
z
)

and

W

κ
,
μ

(
z
)

, as well as the numerically satisfactory companion function

W

−
κ
,
μ

(
z

e

−
π

i

)

. The expansions are uniformly valid for

μ
→
∞

,

0
≤
κ

/

μ
≤
1
−
δ
<
1

and

0
≤
arg
⁡
(
z
)
≤
π

. By using appropriate connection and analytic continuation formulae, these expansions can be extended to all unbounded non-zero complex

z

. The approximations come from recent asymptotic expansions involving elementary functions and Airy functions, and explicit error bounds are either provided or available.
SARS-CoV-2 Seroprevalence and Drug Use in Trauma Patients from Six Sites in the United States
Authors: Ngo Tran B. , Karkanitsa Maria , Adusei Kenneth M. , Graham Lindsey A. , Ricotta Emily E. , Darrah Jenna R. , Blomberg Richard D. , Spathies Jacquelyn , Pauly Kyle J. , Klumpp-Thomas Carleen , Travers Jameson , Mehalko Jennifer , Drew Matthew , Hall Matthew D , Memoli Matthew J , Esposito Dominic , Kozar Rosemary A. , Griggs Christopher , Cunningham Kyle W. , Schulman Carl I. , Crandall Marie , Neavyn Mark , Dorfman Jon D. , Lai Jeffrey T. , Whitehill Jennifer M. , Babu Kavita M. , Mohr Nicholas M. , Van Heukelom Jon , Fell James C. , Rooke Whit , Kalish Heather , Thomas F. Dennis , Sadtler Kaitlyn 
Published: August 2021

ABSTRACTIn comparison to the general patient population, trauma patients show higher level detections of bloodborne infectious diseases, such as Hepatitis and Human Immunodeficiency Virus. In comparison to bloodborne pathogens, the prevalence of respiratory infections such as SARS-CoV-2 and how that relates with other variables, such as drug usage and trauma type, is currently unknown in trauma populations. Here, we evaluated SARS-CoV-2 seropositivity and antibody isotype profile in 2,542 trauma patients from six Level-1 trauma centers between April and October of 2020 during the first wave of the COVID-19 pandemic. We found that the seroprevalence in trauma victims 18-44 years old (9.79%, 95% confidence interval/CI: 8.33 11.47) was much higher in comparison to older patients (45-69 years old: 6.03%, 4.59-5.88; 70+ years old: 4.33%, 2.54 – 7.20). Black/African American (9.54%, 7.77 – 11.65) and Hispanic/Latino patients (14.95%, 11.80 – 18.75) also had higher seroprevalence in comparison, respectively, to White (5.72%, 4.62 7.05) and Non-Latino patients (6.55%, 5.57 – 7.69). More than half (55.54%) of those tested for drug toxicology had at least one drug present in their system. Those that tested positive for narcotics or sedatives had a significant negative correlation with seropositivity, while those on anti-depressants trended positive. These findings represent an important consideration for both the patients and first responders that treat trauma patients facing potential risk of respiratory infectious diseases like SARS-CoV-2.
Building Prediction Models for 30-Day Readmissions Among ICU Patients Using Both Structured and Unstructured Data in Electronic Health Records
Authors: Moerschbacher Alex , He Zhe 
Published: August 2021

AbstractICU readmissions are associated with poor outcomes for patients and poor performance of hospitals. Patients who are readmitted have an increased risk of in-hospital deaths; hospitals with a higher readmission rate have a reduced profitability, due to an increase in cost and reduced payments from Medicare and Medicaid programs. Predicting a patient’s likelihood of being readmitted to the ICU can help reduce early discharges, the risk of in-hospital deaths, and help increase profitability. In this study, we built and evaluated multiple machine learning models to predict 30-day readmission rates of ICU patients in the MIMIC-III database. We used both the structured data including demographics, laboratory tests, comorbidities, and unstructured discharge summaries as the predictors and evaluated different combinations of features. The best performing model in this study Logistic Regression achieved an AUROC of 75.7%. This study shows the potential of leveraging machine learning and deep learning for predicting ICU readmissions.
Infectious SARS-CoV-2 is emitted in aerosols
Authors: Hawks Seth A. , Prussin Aaron J. , Kuchinsky Sarah C. , Pan Jin , Marr Linsey C. , Duggal Nisha K. 
Published: August 2021

AbstractRespiratory viruses such as SARS-CoV-2 are transmitted in respiratory droplets and aerosols, which are released during talking, breathing, coughing, and sneezing. Non-contact transmission of SARS-CoV-2 has been demonstrated, suggesting transmission in aerosols. Here we demonstrate that golden Syrian hamsters emit infectious SARS-CoV-2 in aerosols, prior to and concurrent with the onset of mild clinical signs of disease. The average emission rate is 25 infectious virions/hour on days 1 and 2 post-inoculation, with average viral RNA levels 200-fold higher than infectious virus in aerosols. Female hamsters have delayed kinetics of viral shedding in aerosols compared to male hamsters, with peak viral emission for females on dpi 2 and for males on dpi 1. The majority of virus is contained within aerosols <8 µm in size. Thus, we provide direct evidence that, in hamsters, SARS-CoV-2 is an airborne virus.