bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Learning-Aided Diagnosis of Autoimmune Blistering Diseases
Authors: Cai Daniel , Ardakany Abbas Roayaei , Ay Ferhat 
Published: November 2021

ABSTRACTAutoimmune blistering diseases (AIBDs) are rare, chronic disorders of the skin and mucous membranes, with a broad spectrum of clinical manifestations and morphological lesions. Considering that 1) diagnosis of AIBDs is a challenging task, owing to their rarity and heterogeneous clinical features, and 2) misdiagnoses are common, and the resulting diagnostic delay is a major factor in their high mortality rate, patient prognosis stands to benefit greatly from the development of a computer-aided diagnostic (CAD) tool for AIBDs. Artificial intelligence (AI) research into rare skin diseases like AIBDs is severely underrepresented, due to a variety of factors, foremost a lack of large-scale, uniformly curated imaging data. A study by Julia S. et al. finds that, as of 2020, there exists no machine learning studies on rare skin diseases [1], despite the demonstrated success of AI in the field of dermatology. Whereas previous research has primarily looked to improve performance through extensive data collection and preprocessing, this approach remains tedious and impractical for rarer, under-documented skin diseases. This study proposes a novel approach in the development of a deep learning based diagnostic aid for AIBDs. Leveraging the visual similarities between our imaging data with pre-existing repositories, we demonstrate automated classification of AIBDs using techniques such as transfer learning and data augmentation over a convolutional neural network (CNN). A three-loop process for training is used, combining feature extraction and fine-tuning to improve performance on our classification task. Our final model retains an accuracy nearly on par with dermatologists’ diagnostic accuracy on more common skin cancers. Given the efficacy of our predictive model despite low amounts of training data, this approach holds the potential to benefit clinical diagnoses of AIBDs. Furthermore, our approach can be extrapolated to the diagnosis of other clinically similar rare diseases.
Variations of the quality of care during the COVID-19 pandemic affected the mortality rate of non-COVID patients with hip fracture
Authors: Golinelli Davide , Sanmarchi Francesco , Capodici Angelo , Gribaudo Giorgia , Altini Mattia , Rosa Simona , Esposito Francesco , Fantini Maria Pia , Lenzi Jacopo 
Published: November 2021

AbstractIntroductionAs COVID-19 roared through the world, governments worldwide enforced containment measures that affected various treatment pathways, including those for hip fracture (HF). This study aimed to measure process and outcome indicators related to the quality of care provided to non-COVID-19 elderly patients affected by HF in Emilia-Romagna, a region of Italy severely hit by the pandemic.MethodsWe collected the hospital discharge records of all patients admitted to the hospitals of Emilia-Romagna with a diagnosis of HF from January to May in the years 2019/2020. We analyzed surgery rate, surgery timeliness, length of hospital stay, timely rehabilitation, and 30-day mortality for each HF patient. We evaluated monthly data (2020 vs. 2019) with the chi-square and t-test, where appropriate. Logistic regression was used to investigate the differences in 30-day mortality.ResultsOur study included 5379 patients with HF. In April and May 2020, there was a significant increase in the proportion of HF patients that did not undergo timely surgery. In March 2020, we found a significant increase in mortality (OR = 2.22). Female sex (OR = 0.52), age ≥90 years (OR = 4.33), surgery after 48 hours (OR = 3.08) and not receiving surgery (OR = 6.19) were significantly associated with increased mortality. After adjusting for the aforementioned factors, patients hospitalized in March 2020 still suffered higher mortality (OR = 2.21).ConclusionsOur results show a reduction in the overall quality of care provided to non-COVID-19 elderly patients affected by HF. The mortality rate of patients with HF increased significantly in March 2020. Patients’ characteristics and variations in processes of care partially explained this increase. Our analysis reveals the importance of including process and outcomes indicators, for both acute and post-acute care management issues, in emergency preparedness plans, to monitor healthcare systems’ capacities and capabilities.
Alkaline phosphatase variability predicts new onset heart failure, cardiovascular mortality, and all-cause mortality in patients with type-2 diabetes mellitus: a population-based study
Authors: Zhou Jiandong , Lee Sharen , Adhikari Govinda , Wong Wing Tak , Waleed Khalid Bin , Liu Tong , Wong Ian Chi Kei , Cheung Bernard Man Yung , Tse Gary , Zhang Qingpeng 
Published: November 2021

AbstractObjectiveTo investigate the associations of alkaline phosphatase (ALP) variability measures with new onset heart failure, cardiovascular mortality, and all-cause mortality in type 2 diabetes mellitus patients with a populational-cohort study.MethodThis study included patients with type 2 diabetes mellitus who presented to ambulatory, outpatient and inpatient facilities managed by the public sector in Hong Kong between January 1st, 2000 to December 31st, 2019. Comprehensive clinical and medical data including demographics, past comorbidities, medications, and laboratory examinations of complete blood, lipid/glycemic profile and their variability were collected. ALP and its variability measures were extracted. Univariable and multiple multivariable Cox regression were used to identify the associations of alkaline phosphatase variability with new onset heart failure and mortality risks. Patients were stratified into three subgroups based on the tertiles of baseline ALP level.ResultsThe study cohort consisted of 14289 patients (52.52% males, mean age at initial drug exposure: 74.55 years old [standard deviation (SD): 12.7]). Over a mean follow up of 2513 days [interquartile range (IQR): 1151-4173]), 10182 patients suffered from all-cause mortality (incidence rate [IR]: 71.25%), 1966 patients (IR: 13.75%) died from cardiovascular causes, and 1171 patients (IR: 8.19%) developed with new onset heart failure. Higher cumulative incidences of all three outcomes were observed for the highest tertile of ALP compared to medium/low tertiles. ALP baseline and variability level predicted new onset heart failure, cardiovascular and all-cause mortality before adjusting for subclinical biomarkers (p < 0.01). Amongst the measures of ALP variability, the hazard ratio (HR) of coefficient of variation (CV) was markedly raised in particular (new onset heart failure: HR=2.73, 95% confidence interval [CI]= [1.71-4.37], p <0.0001; all-cause mortality: HR= 5.83, 95% CI= [5.01-6.79], p <0.0001; cardiovascular mortality: HR= 4.81, 95% CI= [3.36-6.88], p <0.0001).ConclusionsRaised ALP level and variability are associated with increased risks of all-cause mortality, cardiovascular mortality and new onset heart failure amongst patients with type 2 diabetes mellitus.
Dosing interval strategies for two-dose COVID-19 vaccination in 13 low- and middle-income countries of Europe: health impact modelling and benefit-risk analysis
Authors: Liu Yang , Pearson Carl AB , Sandmann Frank G , Barnard Rosanna C , Kim Jong-Hoon ,   CMMID COVID-19 Working Group, Flasche Stefan , Jit Mark , Abbas Kaja 
Published: November 2021

SummaryBackgroundIn settings where the COVID-19 vaccine supply is constrained, extending the intervals between the first and second doses of the COVID-19 vaccine could let more people receive their first doses earlier. Our aim is to estimate the health impact of COVID-19 vaccination alongside benefit-risk assessment of different dosing intervals for low- and middle-income countries of Europe.MethodsWe fitted a dynamic transmission model to country-level daily reported COVID-19 mortality in 13 low- and middle-income countries in the World Health Organization European Region (Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Georgia, Republic of Moldova, Russian Federation, Serbia, North Macedonia, Turkey, and Ukraine). A vaccine product with characteristics similar to the Oxford/AstraZeneca COVID-19 (AZD1222) vaccine was used in the base case scenario and was complemented by sensitivity analyses around efficacies related to other COVID-19 vaccines. Both fixed dosing intervals at 4, 8, 12, 16, and 20 weeks and dose-specific intervals that prioritise specific doses for certain age groups were tested. Optimal intervals minimise COVID-19 mortality between March 2021 and December 2022. We incorporated the emergence of variants of concern into the model, and also conducted a benefit-risk assessment to quantify the trade-off between health benefits versus adverse events following immunisation.FindingsIn 12 of the 13 countries, optimal strategies are those that prioritise the first doses among older adults (60+ years) or adults (20-59 years). These strategies lead to dosing intervals longer than six months. In comparison, a four-week fixed dosing interval may incur 10.2% [range: 4.0% - 22.5%; n = 13 (countries)] more deaths. There is generally a negative association between dosing interval and COVID-19 mortality within the range we investigated. Assuming a shorter first dose waning duration of 120 days, as opposed to 360 days in the base case, led to shorter optimal dosing intervals of 8-12 weeks. Benefit-risk ratios were the highest for fixed dosing intervals of 8-12 weeks.InterpretationWe infer that longer dosing intervals of over six months, which are substantially longer than the current label recommendation for most vaccine products, could reduce COVID-19 mortality in low- and middle-income countries of WHO/Europe. Certain vaccine features, such as fast waning of first doses, significantly shorten the optimal dosing intervals.FundingWorld Health Organization
Similarity in evoked responses does not imply similarity in macroscopic network states across tasks
Authors: Rasero Javier , Betzel Richard , Sentis Amy Isabella , Kraynak Thomas E. , Gianaros Peter J. , Verstynen Timothy 
Published: November 2021

AbstractThere is an ongoing debate as to whether cognitive processes arise from a group of functionally specialized brain modules (modularism) or as the result of distributed nonlinear processes (dynamical systems theory). The former predicts that tasks recruiting similar local brain areas should be equally similar in their network profiles. The latter allows for differential connectivity, even when the areas recruited are largely the same. Here we evaluated both views at the macroscopic level by comparing region-wise activation patterns and functional correlation profiles from a large sample of healthy subjects (N=242) that performed two executive control tasks known to recruit nearly identical brain areas, the color-word Stroop task and the Multi-Source Interference Task (MSIT). Using a measure of instantaneous functional correlations, based on edge time series, we estimated the task-related networks that differed between incongruent and congruent conditions. At the group level, the two tasks were much more different in their network profiles than in their evoked activity patterns. This is found even when matching the degrees of freedom of both activation patterns and functional correlation profiles, when considering subject-level differences, after changing brain parcellations, and if employing alternative methods for defining task-related network profiles. Our results are consistent with the perspective of the brain as a dynamical system, suggesting that task representations should be independently evaluated at both node and edge (connectivity) levels.Significant StatementIf the brain is strictly modular at the macroscopic scale, then recruiting the same brain regions should result in the same functional interactions between regions. However, if the brain is a dynamical system, with information represented at both the node and edge levels, then two tasks could have the same pattern of activation, but largely different functional correlation profiles. Here we tested this contrastive prediction using two tasks with overlapping cognitive demands, but different sensory signals. Despite being nearly identical in their activation patterns, we found that the tasks produced largely different functional correlation profiles. These findings reinforce the view of the brain as a dynamical system, with task states represented both within and across regions.
Pharmacogenetic variation in Neanderthals and Denisovans and implications for human health and response to medications
Authors: Wroblewski Tadeusz H. , Witt Kelsey E. , Lee Seung-been , Malhi Ripan S. , Huerta-Sanchez Emilia , Villanea Fernando , Claw Katrina G. 
Published: November 2021

AbstractModern humans carry both Neanderthal and Denisovan (archaic) genome elements that are part of the human gene pool and affect the life and health of living individuals. The impact of archaic DNA may be particularly evident in pharmacogenes – genes responsible for the processing of exogenous substances such as food, pollutants, and medications. However, the health implications and contribution of archaic ancestry in pharmacogenes of modern humans remains understudied. Here, we explore eleven key cytochrome P450 genes (CYP450) involved in drug metabolizing reactions in three Neanderthal and one Denisovan individuals as well as examine archaic introgression in modern human populations. We infer the metabolizing efficiency of these elevenCYP450genes in archaic individuals and find important phenotypic differences relative to modern human variants. We identify several single nucleotide variants shared between archaic and modern humans in each gene, including some potentially function-altering mutations in archaicCYP450genes, which may result in altered metabolism in living people carrying these variants. We highlight three genes which show evidence for archaic introgression into modern humans, as well as one additional gene that shows evidence for a gene duplication found only in Neanderthals and modern Africans.
Effect of host-switching on the eco-evolutionary patterns of parasites
Authors: D’Bastiani Elvira , Princepe Débora , Marquitti Flavia MD , Boeger Walter A , Campião Karla M , Araujo Sabrina LB 
Published: November 2021

AbstractIncreasing empirical evidence has revealed that host-switching are common in the history of parasites. Still, few have explored how the evolutionary histories of hosts might influence such switches and then the evolution of parasites. Here, we investigated how the intensity of host-switching, assumed to depend on the phylogenetic distance between hosts, affects the ecological and evolutionary patterns of parasite species. We developed an individual-based model where parasites can explore and colonise hosts under variable host-switching intensity and have evolution driven by mutation, genetic drift, and mating restriction. We hypothesised that our model can reproduce ecological and evolutionary patterns of empirical communities, characterised by turnover among host species and tree imbalance, respectively. We found an optimum range of host-switching intensity that can predict similar patterns as those observed in the empirical studies, validating our hypothesis. Our results showed that the turnover decreased as the host-switching intensity increased with low variation among the model replications. On the other hand, the tree imbalance had not a monotonic tendency but a wide variation. These results revealed that while the tree imbalance is a sensitive metric to stochastic events, the turnover may be a proxy for host switching. Furthermore, local empirical studies corresponded to higher host-switching intensity when compared to regional studies, highlighting that spatial scale is probably the crucial limitation of host-switching.
Dopamine release in nucleus accumbens is under tonic inhibition by adenosine A1receptors regulated by astrocytic ENT1 and dysregulated by ethanol
Authors: Roberts Bradley M. , Lambert Elizabeth , Livesey Jessica A. , Wu Zhaofa , Li Yulong , Cragg Stephanie J. 
Published: November 2021

ABSTRACTStriatal adenosine A1receptor (A1R) activation can inhibit dopamine release. A1Rs on other striatal neurons are activated by an adenosine tone that is limited by equilibrative nucleoside transporter 1 (ENT1) that is enriched on astrocytes and is ethanol-sensitive. We explored whether dopamine release in nucleus accumbens core is under tonic inhibition by A1Rs, and is regulated by astrocytic ENT1 and ethanol. Inex vivostriatal slices from male and female mice, A1R agonists inhibited dopamine release evoked electrically or optogenetically and detected using fast-scan cyclic voltammetry, most strongly for lower stimulation frequencies and pulse numbers, thereby enhancing the activity-dependent contrast of dopamine release. Conversely, A1R antagonists reduced activity-dependent contrast but enhanced evoked dopamine release levels, even for single optogenetic pulses indicating an underlying tonic inhibition. The ENT1 inhibitor NBTI reduced dopamine release and promoted A1R-mediated inhibition, and conversely, virally-mediated astrocytic overexpression of ENT1 enhanced dopamine release and relieved A1R-mediated inhibition. By imaging the genetically encoded fluorescent adenosine sensor GRAB-Ado, we identified a striatal extracellular adenosine tone that was elevated by the ENT1 inhibitor and sensitive to gliotoxin fluorocitrate. Finally, we identified that ethanol (50 mM) promoted A1R-mediated inhibition of dopamine release, through diminishing adenosine uptake via ENT1. Together, these data reveal that dopamine output dynamics are gated by a striatal adenosine tone, limiting amplitude but promoting contrast, regulated by ENT1, and promoted by ethanol. These data add to the diverse mechanisms through which ethanol modulates striatal dopamine, and to emerging datasets supporting astrocytic transporters as important regulators of striatal function.SIGNIFICANCE STATEMENTDopamine axons in the mammalian striatum are emerging as strategic sites where neuromodulators can powerfully influence dopamine output in health and disease. We found that ambient levels of the neuromodulator adenosine tonically inhibit dopamine release in nucleus accumbens core via adenosine A1receptors (A1Rs), to a variable level that promotes the contrast in dopamine signals released by different frequencies of activity. We reveal that the equilibrative nucleoside transporter 1 (ENT1) on astrocytes limits this tonic inhibition, and that ethanol promotes it by diminishing adenosine uptake via ENT1. These findings support the hypotheses that A1Rs on dopamine axons inhibit DA release and, furthermore, that astrocytes perform important roles in setting the level of striatal dopamine output, in health and disease.
The population dynamic life histories of the birds and mammals of the world
Authors: Witting Lars 
Published: November 2021

AbstractWith life history traits determining the natural selection fitnesses of individuals and growth of populations, estimates of their variation are essential to advance evolutionary theory and ecological management during times of global change. As quantitative predictions improve with the completeness of models, and as data are usually incomplete or missing for most species, I use published data and inter-specific allometric extrapolations to estimate complete population dynamic life history models for birds and mammals with known body masses. This constructs models for 11,188 species of birds and 4,937 species of mammals, covering 27 life history and ecological traits per species. The estimates are used to illustrate natural selection mechanisms and explain a diverse range of population dynamic trajectories by the inclusion of population dynamic regulation. This provides a first step towards the construction of freely accessible and ready-to-use online population dynamic simulations covering all species of birds and mammals.
Supergene degeneration opposes polymorphism: The curious case of balanced lethals
Authors: Berdan Emma L. , Blanckaert Alexandre , Butlin Roger K. , Flatt Thomas , Slotte Tanja , Wielstra Ben 
Published: November 2021

AbstractSupergenes offer some of the most spectacular examples of long-term balancing selection in nature but their origin and maintenance remain a mystery. A critical aspect of supergenes is reduced recombination between arrangements. Reduced recombination protects adaptive multi-trait phenotypes, but can also lead to degeneration through mutation accumulation. Mutation accumulation can stabilize the system through the emergence of associative overdominance (AOD), destabilize the system, or lead to new evolutionary outcomes. One such outcome is the formation of balanced lethal systems, a maladaptive system where both supergene arrangements have accumulated deleterious mutations to the extent that both homozygotes are inviable, leaving only heterozygotes to reproduce. Here, we perform a simulation study to understand the conditions under which these different outcomes occur, assuming a scenario of introgression after allopatric divergence. We found that AOD aids the invasion of a new supergene arrangement and the establishment of a polymorphism. However, this polymorphism is easily destabilized by further mutation accumulation. While degradation may strengthen AOD, thereby stabilizing the supergene polymorphism, it is often asymmetric, which is the key disrupter of the quasi-equilibrium state of the polymorphism. Furthermore, mechanisms that accelerate degeneration also tend to amplify asymmetric mutation accumulation between the supergene arrangements and vice versa. As the evolution of a balanced lethal system requires symmetric degradation of both arrangements, this leaves highly restricted conditions under which such a system could evolve. We show that small population size and low dominance coefficients are critical factors, as these reduce the efficacy of selection. The dichotomy between the persistence of a polymorphism and degradation of supergene arrangements likely underlies the rarity of balanced lethal systems in nature.
The effects of weak selection on neutral diversity at linked sites
Authors: Charlesworth Brian 
Published: November 2021

AbstractThe effects of selection on variability at linked sites have an important influence on levels and patterns of within-population variation across the genome. Most theoretical models of these effects have assumed that selection is sufficiently strong that allele frequency changes at the loci concerned are largely deterministic. These models have led to the conclusion that directional selection for selectively favorable mutations, or against recurrent deleterious mutations, reduces nucleotide site diversity at linked neutral sites. Recent work has shown, however, that fixations of weakly selected mutations, accompanied by significant stochastic changes in allele frequencies, can sometimes cause higher diversity at linked sites when compared with the effects of fixations of neutral mutations. The present paper extends this work by deriving approximate expressions for the mean conditional times to fixation and loss of mutations subject to selection, and analysing the conditions under which selection increases rather than reduces these times. Simulations are used to examine the relations between diversity at a neutral site and the fixation and loss times of mutations at a linked site that is subject to selection. It is shown that the long-term level of neutral diversity can be increased over the purely neutral value by recurrent fixations and losses of linked, weakly selected dominant or partially dominant favorable mutations, or linked recessive or partially recessive deleterious mutations. The results are used to examine the conditions under which associative overdominance, as opposed to background selection, is likely to operate.