bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental evidence of the multiple microclimatic impacts of bushfires in affected urban areas: the case of Sydney during the 2019/2020 Australian season
Authors: Ulpiani Giulia , Ranzi Gianluca , Santamouris Mat 
Published: July 2020

Abstract
This paper presents the results of a monitoring campaign conducted in the inner west of the city of Sydney during the 2019/2020 bushfire season. The combined effects of extreme pollution, heat waves and droughts are analyzed in terms of microclimatic perturbation. A compact meteorological station measured air temperature, relative humidity, barometric pressure, precipitation, wind (speed and direction), solar radiation, UV radiation, UV index, PM1, PM2.5 and PM10, at the one site. The monitoring campaign lasted from the 20th of December 2019 to the 13th of January 2020, when hundreds of bushfires were ravaging the bordering areas. A suite of dependencies emerged between PM concentration and air temperature, relative humidity, wind speed and rain. PM concentration was higher during the night and in the morning, especially after daytime overheating events (temperature above 35 °C). Raindrops triggered the highest and most persistent dust levels. Dense layers of PMs, in turn, strongly attenuated the UV radiation. Collected data also indicated anomalies in the intensity of the urban heat island compared to historical trends. This study is a first attempt to link together several different parameters on a local scale under weather anomalies. Future efforts will be directed to strengthening the validity of the above results and approach to broader boundary conditions.
Impact of a Modified HistoGel Method for Processing Endocervical Curettage Specimens on Diagnostic Yield
Authors: Ramia de Cap Maximiliano , Jou David , Chen Yigu , Hecht Jonathan L , VanderLaan Paul A , Chen Athena L 
Published: July 2020

Abstract

Objectives
Endocervical curettage (ECC) specimens may be limited by scant tissue. We evaluated whether a cellular concentration processing method could improve their diagnostic quality.

Methods
Between October 2018 and June 2019, ECC specimens were assigned chronologically to one of two groups: nonconcentrated ECC (NECC) or concentrated ECC (CECC). NECC specimens underwent routine histologic processing. CECC specimens were processed using a published HistoGel-based cell block method. We reviewed diagnoses for ECCs, concurrent cervical biopsies and/or loop electrosurgical excision procedures (LEEPs), and preceding Papanicolaou (Pap) smears. We performed multivariate logistic regression analyses to evaluate the impact of processing method on ECC adequacy and discordance between Pap smear and worst tissue diagnoses.

Results
NECC and CECC adequacy was 88.2% and 84.7% (P = .06). ECC adequacy was greater if concurrent biopsy/LEEP was performed (odds ratio [OR] = 1.76, P &lt; .01). Discordance between Pap smear and worst tissue diagnoses was 9.5% and 13.3% (P = .04) for cases with NECC and CECC processing, although processing method was not significant in multivariate analysis (OR = 0.74, P = .11). Adequate ECC sampling and concurrent biopsy/LEEP were independently associated with concordance between Pap smear and worst tissue diagnosis (OR = 0.46, P &lt; .01 and OR = 0.65, P = .02).

Conclusions
ECC processing method did not significantly affect either specimen adequacy (P = .06) or diagnostic discordance (P = .11) when controlled for other factors.
Positive Effect of Helicobacter pylori Treatment on Outcome of Patients With Chronic Spontaneous Urticaria
Authors: Elhendawy Mohammed , Hagras Maha M , Soliman Shaimaa S , Shaker Engi Seif E 
Published: July 2020

Abstract

Objectives
The association between Helicobacter pylori and chronic spontaneous urticaria (CSU) is controversial. Therefore, we aimed to directly diagnose H pylori by polymerase chain reaction (PCR) in gastric tissue from patients with CSU and to investigate the association between H pylori eradication therapy and CSU remission.

Methods
Twenty-seven of 72 patients with CSU who were positive for H pylori stool antigen and PCR in gastric biopsy specimens were randomized to receive either anti–H pylori treatment or placebo.

Results
Patients with H pylori were found to have significantly lower hemoglobin concentrations with microcytic hypochromic anemia and a significantly higher occurrence of dyspepsia symptoms. All H pylori–treated patients (except two) showed significant improvement of the urticaria itching and red wheals after 2 weeks of therapy compared with the placebo group (P &lt; .001). The response rate to treatment was 85.7% (12 patients; 95% confidence interval, 64.3%-100.0%). The two patients who failed to eradicate H pylori had an H pylori strain resistant to amoxicillin.

Conclusions
An association was observed between CSU and presence of H pylori infection in the gastric tissue. Whether this is a causal relationship or not remains to be discovered, but treatment of H pylori can significantly improve the symptoms of CSU.
Spatial molecular profiling: platforms, applications and analysis tools
Authors: Zhang Minzhe , Sheffield Thomas , Zhan Xiaowei , Li Qiwei , Yang Donghan M , Wang Yunguan , Wang Shidan , Xie Yang , Wang Tao , Xiao Guanghua 
Published: July 2020

Abstract
Molecular profiling technologies, such as genome sequencing and proteomics, have transformed biomedical research, but most such technologies require tissue dissociation, which leads to loss of tissue morphology and spatial information. Recent developments in spatial molecular profiling technologies have enabled the comprehensive molecular characterization of cells while keeping their spatial and morphological contexts intact. Molecular profiling data generate deep characterizations of the genetic, transcriptional and proteomic events of cells, while tissue images capture the spatial locations, organizations and interactions of the cells together with their morphology features. These data, together with cell and tissue imaging data, provide unprecedented opportunities to study tissue heterogeneity and cell spatial organization. This review aims to provide an overview of these recent developments in spatial molecular profiling technologies and the corresponding computational methods developed for analyzing such data.
Style transfer with variational autoencoders is a promising approach to RNA-Seq data harmonization and analysis
Authors: Russkikh Nikolai , Antonets Denis , Shtokalo Dmitry , Makarov Alexander , Vyatkin Yuri , Zakharov Alexey , Terentyev Evgeny 
Published: July 2020

Abstract

Motivation
The transcriptomic data are being frequently used in the research of biomarker genes of different diseases and biological states. The most common tasks there are the data harmonization and treatment outcome prediction. Both of them can be addressed via the style transfer approach. Either technical factors or any biological details about the samples which we would like to control (gender, biological state, treatment, etc.) can be used as style components.

Results
The proposed style transfer solution is based on Conditional Variational Autoencoders, Y-Autoencoders and adversarial feature decomposition. To quantitatively measure the quality of the style transfer, neural network classifiers which predict the style and semantics after training on real expression were used. Comparison with several existing style-transfer based approaches shows that proposed model has the highest style prediction accuracy on all considered datasets while having comparable or the best semantics prediction accuracy.

Availability and implementation
https://github.com/NRshka/stvae-source.

Supplementary information
Supplementary data are available at Bioinformatics online.
General tests of the Markov property in multi-state models
Authors: Titman Andrew C , Putter Hein 
Published: July 2020

Abstract
Multi-state models for event history analysis most commonly assume the process is Markov. This article considers tests of the Markov assumption that are applicable to general multi-state models. Two approaches using existing methodology are considered; a simple method based on including time of entry into each state as a covariate in Cox models for the transition intensities and a method involving detecting a shared frailty through a stratified Commenges–Andersen test. In addition, using the principle that under a Markov process the future rate of transitions of the process at times $t &gt; s$ should not be influenced by the state occupied at time $s$, a new class of general tests is developed by considering summaries from families of log-rank statistics where patients are grouped by the state occupied at varying initial time $s$. An extended form of the test applicable to models that are Markov conditional on observed covariates is also derived. The null distribution of the proposed test statistics are approximated by using wild bootstrap sampling. The approaches are compared in simulation and applied to a dataset on sleeping behavior. The most powerful test depends on the particular departure from a Markov process, although the Cox-based method maintained good power in a wide range of scenarios. The proposed class of log-rank statistic based tests are most useful in situations where the non-Markov behavior does not persist, or is not uniform in nature across patient time.
Intranasal oxytocin enhances approach-related EEG frontal alpha asymmetry during engagement of direct eye contact
Authors: Soriano Javier R , Daniels Nicky , Prinsen Jellina , Alaerts Kaat 
Published: July 2020

AbstractThe neuropeptide oxytocin is suggested to play a major role in a variety of complex human behaviours, including interpersonal bonding, trust and attachment. Recent theories have suggested that the role oxytocin plays in these complex social behaviours involves a modulation of motivational tendencies of approach-/avoidance-related behaviours. However, to date, direct neurophysiological evidence supporting this notion is limited. In this double-blind, randomized, placebo-controlled study with parallel design, we assessed the effects of administered intranasal oxytocin in 40 adult men on gaze behaviour and a neural marker of approach/avoidance motivational tendencies. Specifically, electroencephalography recordings were performed during the engagement of eye contact with a live model in a naturalistic two-person social context and electroencephalographic frontal alpha asymmetry, an established neurophysiological index of motivational tendencies for approach-/avoidance-related behaviours, was assessed. Compared to placebo, a single dose of oxytocin (24 international units) was shown to increase relative left-sided frontal asymmetry upon direct eye contact with a live model, which is indicative of an increase in approach-related motivational tendencies towards the presented eye contact stimulus. Notably, the treatment effect was most prominently observed in participants with lower self-reported social motivation (higher Motivation subscale scores on the Social Responsiveness Scale), indicating that participants with lower social motivation benefitted the most from the administered oxytocin. No treatment-specific changes were identified in terms of gaze behaviour towards the eye region of the live model. Together, these observations add neurophysiological evidence to the hypothesized role of oxytocin in modulating approach-/avoidance-related tendencies and suggest that inter-subject variability in person-dependent factors need to be considered to evaluate the potential benefit of intranasal oxytocin as a treatment. This notion is of particular relevance to the variety of neuropsychiatric populations such as autism spectrum disorder, social anxiety disorder and depression, for which intranasal oxytocin is increasingly considered a potential treatment.
Frequency-specific neural synchrony in autism during memory encoding, maintenance and recognition
Authors: Audrain Samantha P , Urbain Charline M , Yuk Veronica , Leung Rachel C , Wong Simeon M , Taylor Margot J 
Published: July 2020

AbstractWorking memory impairment is associated with symptom severity and poor functional outcome in autistic individuals, and yet the neurobiology underlying such deficits is poorly understood. Neural oscillations are an area of investigation that can shed light on this issue. Theta and alpha oscillations have been found consistently to support working memory in typically developing individuals and have also been shown to be functionally altered in people with autism. While there is evidence, largely from functional magnetic resonance imaging studies, that neural processing underlying working memory is altered in autism, there remains a dearth of information concerning how sub-processes supporting working memory (namely encoding, maintenance and recognition) are impacted. In this study, we used magnetoencephalography to investigate inter-regional theta and alpha brain synchronization elicited during the widely used one-back task across encoding, maintenance and recognition in 24 adults with autism and 30 controls. While both groups performed comparably on the working-memory task, we found process- and frequency-specific differences in networks recruited between groups. In the theta frequency band, both groups used similar networks during encoding and recognition, but different networks specifically during maintenance. In comparison, the two groups recruited distinct networks across encoding, maintenance and recognition in alpha that showed little overlap. These differences may reflect a breakdown of coherent theta and alpha synchronization that supports mnemonic functioning, or in the case of alpha, impaired inhibition of task-irrelevant neural processing. Thus, these data provide evidence for specific theta and widespread alpha synchrony alterations in autism, and underscore that a detailed examination of the sub-processes that comprise working memory is warranted for a complete understanding of cognitive impairment in this population.
Dynamic neurocognitive changes in interoception after heart transplant
Authors: Salamone Paula Celeste , Sedeño Lucas , Legaz Agustina , Bekinschtein Tristán , Martorell Miguel , Adolfi Federico , Fraile-Vazquez Matías , Rodríguez Arriagada Nicolás , Favaloro Liliana , Peradejordi Margarita , Absi Daniel O , García Adolfo M , Favaloro Roberto , Ibáñez Agustín 
Published: July 2020

Abstract
Heart–brain integration dynamics are critical for interoception (i.e. the sensing of body signals). In this unprecedented longitudinal study, we assessed neurocognitive markers of interoception in patients who underwent orthotopic heart transplants and matched healthy controls. Patients were assessed longitudinally before surgery (T1), a few months later (T2) and a year after (T3). We assessed behavioural (heartbeat detection) and electrophysiological (heartbeat evoked potential) markers of interoception. Heartbeat detection task revealed that pre-surgery (T1) interoception was similar between patients and controls. However, patients were outperformed by controls after heart transplant (T2), but no such differences were observed in the follow-up analysis (T3). Neurophysiologically, although heartbeat evoked potential analyses revealed no differences between groups before the surgery (T1), reduced amplitudes of this event-related potential were found for the patients in the two post-transplant stages (T2, T3). All these significant effects persisted after covariation with different cardiological measures. In sum, this study brings new insights into the adaptive properties of brain–heart pathways.
Artificial intelligence for clinical decision support in neurology
Authors: Pedersen Mangor , Verspoor Karin , Jenkinson Mark , Law Meng , Abbott David F , Jackson Graeme D 
Published: July 2020

AbstractArtificial intelligence is one of the most exciting methodological shifts in our era. It holds the potential to transform healthcare as we know it, to a system where humans and machines work together to provide better treatment for our patients. It is now clear that cutting edge artificial intelligence models in conjunction with high-quality clinical data will lead to improved prognostic and diagnostic models in neurological disease, facilitating expert-level clinical decision tools across healthcare settings. Despite the clinical promise of artificial intelligence, machine and deep-learning algorithms are not a one-size-fits-all solution for all types of clinical data and questions. In this article, we provide an overview of the core concepts of artificial intelligence, particularly contemporary deep-learning methods, to give clinician and neuroscience researchers an appreciation of how artificial intelligence can be harnessed to support clinical decisions. We clarify and emphasize the data quality and the human expertise needed to build robust clinical artificial intelligence models in neurology. As artificial intelligence is a rapidly evolving field, we take the opportunity to iterate important ethical principles to guide the field of medicine is it moves into an artificial intelligence enhanced future.
Heritability Estimates of Antler and Body Traits in White-Tailed Deer (Odocoileus virginianus) From Genomic-Relatedness Matrices
Authors: Jamieson Aidan , Anderson Spencer J , Fuller Jérémie , Côté Steeve D , Northrup Joseph M , Shafer Aaron B A 
Published: July 2020

AbstractEstimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and genome-wide single-nucleotide polymorphism (SNP) data are available. We estimated the heritability of 5 body and 3 antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated classic and robust GRMs from &gt;10,000 SNPs: hind foot length, dressed body mass, and peroneus muscle mass had high h2 values of 0.62, 0.44, and 0.55, respectively. Heritability in male-only antler features ranged from 0.07 to 0.33. We explored the influence of filtering by minor allele frequency and data completion on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs, specifically many unrelated individuals, can increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management as these traits could respond to selection.
Probabilistic cosmic web classification using fast-generated training data
Authors: Buncher Brandon , Carrasco Kind Matias 
Published: July 2020

ABSTRACT
We present a novel method of robust probabilistic cosmic web particle classification in three dimensions using a supervised machine learning algorithm. Training data were generated using a simplified ΛCDM toy model with pre-determined algorithms for generating haloes, filaments, and voids. While this framework is not constrained by physical modelling, it can be generated substantially more quickly than an N-body simulation without loss in classification accuracy. For each particle in this data set, measurements were taken of the local density field magnitude and directionality. These measurements were used to train a random forest algorithm, which was used to assign class probabilities to each particle in a ΛCDM, dark matter-only N-body simulation with 2563 particles, as well as on another toy model data set. By comparing the trends in the ROC curves and other statistical metrics of the classes assigned to particles in each data set using different feature sets, we demonstrate that the combination of measurements of the local density field magnitude and directionality enables accurate and consistent classification of halo, filament, and void particles in varied environments. We also show that this combination of training features ensures that the construction of our toy model does not affect classification. The use of a fully supervised algorithm allows greater control over the information deemed important for classification, preventing issues arising from arbitrary hyperparameters and mode collapse in deep learning models. Due to the speed of training data generation, our method is highly scalable, making it particularly suited for classifying large data sets, including observed data.
Constraining the growth rate of structure with phase correlations
Authors: Byun Joyce , Franco Felipe Oliveira , Howlett Cullan , Bonvin Camille , Obreschkow Danail 
Published: July 2020

ABSTRACT
We show that correlations between the phases of the galaxy density field in redshift space provide additional information about the growth rate of large-scale structure that is complementary to the power-spectrum multipoles. In particular, we consider the multipoles of the line correlation function (LCF), which correlates phases between three collinear points, and use the Fisher forecasting method to show that the LCF multipoles can break the degeneracy between the measurement of the growth rate of structure f and the amplitude of perturbations σ8 that is present in the power-spectrum multipoles at large scales. This leads to an improvement in the measurement of f and σ8 by up to 220 per cent for $k_{\rm max} = 0.15 \, h\, \mathrm{Mpc}^{-1}$ and up to 50 per cent for $k_{\rm max} = 0.30 \, h\, \mathrm{Mpc}^{-1}$ at redshift z = 0.25, with respect to power-spectrum measurements alone for the upcoming generation of galaxy surveys like DESI and Euclid. The average improvements in the constraints on f and σ8 for $k_{\rm max} = 0.15 \, h\, \mathrm{Mpc}^{-1}$ are ∼90 per cent for the DESI BGS sample with mean redshift $\overline{z}=0.25$, ∼40 per cent for the DESI ELG sample with $\overline{z}=1.25$, and ∼40 per cent for the Euclid Hα galaxies with $\overline{z}=1.3$. For $k_{\rm max} = 0.30 \, h\, \mathrm{Mpc}^{-1}$, the average improvements are ∼40 per cent for the DESI BGS sample and ∼20 per cent for both the DESI ELG and Euclid Hα galaxies.
HRT Atlas v1.0 database: redefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets
Authors: Hounkpe Bidossessi Wilfried , Chenou Francine , de Lima Franciele , De Paula Erich Vinicius 
Published: July 2020

Abstract
Housekeeping (HK) genes are constitutively expressed genes that are required for the maintenance of basic cellular functions. Despite their importance in the calibration of gene expression, as well as the understanding of many genomic and evolutionary features, important discrepancies have been observed in studies that previously identified these genes. Here, we present Housekeeping and Reference Transcript Atlas (HRT Atlas v1.0, www.housekeeping.unicamp.br) a web-based database which addresses some of the previously observed limitations in the identification of these genes, and offers a more accurate database of human and mouse HK genes and transcripts. The database was generated by mining massive human and mouse RNA-seq data sets, including 11 281 and 507 high-quality RNA-seq samples from 52 human non-disease tissues/cells and 14 healthy tissues/cells of C57BL/6 wild type mouse, respectively. User can visualize the expression and download lists of 2158 human HK transcripts from 2176 HK genes and 3024 mouse HK transcripts from 3277 mouse HK genes. HRT Atlas also offers the most stable and suitable tissue selective candidate reference transcripts for normalization of qPCR experiments. Specific primers and predicted modifiers of gene expression for some of these HK transcripts are also proposed. HRT Atlas has also been integrated with a regulatory elements resource from Epiregio server.