bluuebunny/crossref_metadata_2025_split huggingface dataset:
ARTIFICIAL INTELLIGENCE TOOLS FOR EFFECTIVE MONITORING OF POPULATION AT DISTANCE DURING COVID-19 PANDEMIC. RESULTS FROM AN ITALIAN PILOT FEASIBILITY STUDY (RICOVAI-19 STUDY)
Authors: Mazzanti Marco , Salvi Aldo , Giacomini Stefania , Perazzini Elisabetta , Nitti Cinzia , Contucci Susanna , D’Angelo Massimo , Ballanti Danilo , Ursino Domenico , Marcosignori Matteo , Romagnoli Raniero , Tavio Marcello , Giacometti Andrea , Tomassetti Serena , Bonazzi Riccardo , Maccioni Matteo , Zuccatosta Lina ,   RICOVAI-19 Study
Published: February 2022

AbstractIn order to reduce the burden on healthcare systems and in particular to support an appropriate way to the Emergency Department (ED) access, home tele-monitoring patients was strongly recommended during the COVID-19 pandemic. Furthermore, paper from numerous groups has shown the potential of using data from wearable devices to characterize each individual’s unique baseline, identify deviations from that baseline suggestive of a viral infection, and to aggregate that data to better inform population surveillance trends. However, no evidence about usage of Artificial Intelligence (AI) applicatives on digitally data collected from patients and doctors exists. With a growing global population of connected wearable users, this could potentially help to improve the earlier diagnosis and management of infectious individuals and improving timeliness and precision of tracking infectious disease outbreaks.During the study RICOVAI-19 (RICOVero ospedaliero con strumenti diArtificial Intelligence nei pazienti conCOVid-19) performed in the Marche Region, Italy, we evaluated 129 subjects monitored at home in a six-months period between March 22, 2021 and October 22, 2021. During the monitoring, personal on demand health technologies were used to collect clinical and vital data in order to feed the database and the machine learning engine. The AI output resulted in a clinical stability index (CSI) which enables the system to deliver suggestions to the population and doctors about how intervene.Results showed the beneficial influence of CSI for predicting clinical classes of subjects and identifying who of them need to be admitted at ED. The same pattern of results was confirming the alert included in the decision support system in order to request further testing or clinical information in some cases.In conclusion, our study does support a high impact of AI tools on COVID-19 outcomes to fight this pandemic by driving new approaches to public awareness.
Not all roads lead to the immune system: The Genetic Basis of Multiple Sclerosis Severity Implicates Central Nervous System and Mitochondrial Involvement
Authors: Jokubaitis Vilija G. , Ibrahim Omar , Stankovich Jim , Kleinova Pavlina , Matesanz Fuencisla , Hui Daniel , Eichau Sara , Slee Mark , Lechner-Scott Jeannette , Lea Rodney , Kilpatrick Trevor J , Kalincik Tomas , De Jager Philip L. , Beecham Ashley , McCauley Jacob L. , Taylor Bruce V. , Vucic Steve , Laverick Louise , Vodehnalova Karolina , García-Sanchéz Maria-Isabel , Alcina Antonio , van der Walt Anneke , Havrdova Eva Kubala , Izquierdo Guillermo , Patsopoulos Nikolaos , Horakova Dana , Butzkueven Helmut 
Published: February 2022

AbstractMultiple sclerosis (MS) is a leading cause of neurological disability in adults. Heterogeneity in MS clinical presentation has posed a major challenge for identifying genetic variants associated with disease outcomes. To overcome this challenge, we used prospectively ascertained clinical outcomes data from the largest international MS Registry, MSBase. We assembled a cohort of deeply phenotyped individuals with relapse-onset MS. We used unbiased genome-wide association study and machine learning approaches to assess the genetic contribution to longitudinally defined MS severity phenotypes in 1,813 individuals. Our results did not identify any variants of moderate to large effect sizes that met genome-wide significance thresholds. However, we demonstrate that clinical outcomes in relapse-onset MS are associated with multiple genetic loci of small effect sizes. Using a machine learning approach incorporating over 62,000 variants and demographic variables available at MS disease onset, we could predict severity with an area under the receiver operator curve (AUROC) of 0.87 (95% CI 0.83 – 0.91). This approach, if externally validated, could quickly prove useful for clinical stratification at MS onset. Further, we find evidence to support central nervous system and mitochondrial involvement in determining MS severity.
The usefulness of D-dimer as a predictive marker for mortality in patients with COVID-19 hospitalized during the first wave in Italy
Authors: Hassan Shermarke , Ferrari Barbara , Rossio Raffaella , la Mura Vincenzo , Artoni Andrea , Gualtierotti Roberta , Martinelli Ida , Nobili Alessandro , Bandera Alessandra , Gori Andrea , Blasi Francesco , Monzani Valter , Costantino Giorgio , Harari Sergio , Rosendaal Frits R. , Peyvandi Flora 
Published: February 2022

AbstractBackgroundThe coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources.AimsThe primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality.MethodsThis was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrell’s C-index and model calibration was assessed using a calibration plot.ResultsOut of 1049 patients, 501 patients had evaluable data. Of these 501 patients, 96 died. The cumulative incidence of in-hospital mortality within 30 days was 20% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot.ConclusionThe predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance.
Daily heart rate variability biofeedback training decreases locus coeruleus MRI contrast in younger adults
Authors: Bachman Shelby L. , Cole Steve , Yoo Hyun Joo , Nashiro Kaoru , Min Jungwon , Mercer Noah , Nasseri Padideh , Thayer Julian F. , Lehrer Paul , Mather Mara 
Published: February 2022

AbstractAs an arousal hub region in the brain, the locus coeruleus (LC) has bidirectional connections with the autonomic nervous system. Magnetic resonance imaging (MRI)-based measures of LC structural integrity have been linked to cognition and arousal, but less is known about factors that influence LC structure and function across time. Here, we tested the effects of heart rate variability (HRV) biofeedback, an intervention targeting the autonomic nervous system, on LC MRI contrast and sympathetic activity. Younger and older participants completed daily HRV biofeedback training for five weeks. Those assigned to an experimental condition performed biofeedback involving slow, paced breathing designed to increase heart rate oscillations, whereas those assigned to a control condition performed biofeedback to decrease heart rate oscillations. At the pre- and post-training timepoints, LC contrast was assessed using turbo spin echo MRI scans, and RNA sequencing was used to assess cAMP-responsive element binding protein (CREB)-regulated gene expression in circulating blood cells, an index of sympathetic nervous system signaling. We found that left LC contrast decreased in younger participants in the experimental group, and across younger participants, decreases in left LC contrast were related to the extent to which participants increased their heart rate oscillations during training. Furthermore, decreases in left LC contrast were associated with decreased expression of CREB-associated gene transcripts. On the contrary, there were no effects of biofeedback on LC contrast among older participants in the experimental group. These findings provide novel evidence that in younger adults, HRV biofeedback involving slow, paced breathing can decrease both LC contrast and sympathetic nervous system signaling.
USA Winter 2021 CoVID-19 Resurgence Post-Christmas Update
Authors: Eng Genghmun 
Published: February 2022

AbstractWe have successfully modeled every USA CoVID-19 wave using:

where N (t) is the total number of new CoVID-19 cases above a prior baseline, and tR sets the doubling time tdbl = tR (ln 2). The new parameters {αS ; δo} measure mitigation efforts among the uninfected population, with {αS > 0} being associated with Social Distancing and vaccinations ; while {δo > 0 }is associated with mask-wearing, which gives a faster post-peak drop-off. The predicted pandemic wave end is when N (t) no longer increases.Using data from 11/15/21-12/30/21, our prior medrxiv.org preprint* showed this initial Omicron CoVID-19 wave had values that matched the initial stage of the prior USA Winter 2020 resurgence {tR ≈8 05 days ; αS ≈ 0 011 / day}, when practically no one was vaccinated. In addition, this initial Winter 2021 wave showed virtually no mask-wearing {δo≈ × 0 001 10−3 / day}, making it capable of infecting virtually everyone. These parameter values indicated that the Omicron variant was likely evading the vaccines in people who thought they were protected.As a result, stopping the Omicron CoVID-19 spread must once again rely on enhanced Social Distancing and mask-wearing, just like the initial pandemic wave in March 2020. Analyzing the USA follow-on data from 12/25/21-1/31/22 shows that people did exactly that after the Christmas Holiday season, resulting in the following model parameters and values:

for this wave by itself, with all prior waves subtracted out as a baseline. Combining all the USA CoVID-19 waves gives these updated totals:

assuming no future CoVID-19 Resurgence (with 4 Figures).*(10.1101_2021.10.15.21265078)
Optocoder: computational decoding of spatially indexed bead arrays
Authors: Senel Enes , Rajewsky Nikolaus , Karaiskos Nikos 
Published: February 2022

AbstractMotivationAdvancing technologies that quantify gene expression in space are transforming contemporary biology research. A class of spatial transcriptomics methods uses barcoded bead arrays that are optically decoded via microscopy and are later matched to sequenced data from the respective libraries. To obtain a detailed representation of the tissue in space, robust and efficient computational pipelines are required to process microscopy images and accurately basecall the bead barcodes.ResultsOptocoder is a computational framework that processes microscopy images to decode bead barcodes in space. It efficiently aligns images, detects beads, and corrects for confounding factors of the fluorescence signal, such as crosstalk and phasing. Furthermore, Optocoder employs supervised machine learning to strongly increase the number of matches between optically decoded and sequenced barcodes. We benchmark Optocoder using data from an in-house spatial transcriptomics platform, as well as from Slide-Seq(V2), and we show that it efficiently processes all datasets without modification.AvailabilityOptocoder is publicly available, open-source and provided as a stand-alone Python package on GitHub: https://github.com/rajewsky-lab/optocoder
An Oscillatory Shear Index-based Model to Describe Progressive Carotid Artery Stenosis
Authors: Patalano P 
Published: February 2022

ABSTRACTBackground and aimsThis study describes and demonstrates the applicability of a novel in silico method for modeling progressive carotid artery stenosis using the oscillatory shear index (OSI) as the basis of stenosis function.MethodsThree-dimensional reconstructions of 11 carotid arteries were generated using patient-derived magnetic resonance angiography and duplex ultrasound data. Computational fluid dynamic simulations were sequentially performed following computational stenosis assessment, and corresponding changes in OSI were observed and used as measure of morphological stabilization.ResultsSix carotid models showed progressive stenosis with statistically significant increases in regions of high OSI (OSI > 0.2, p < 0.05) with eventual carotid occlusion in one of the cases. Three models remained free or nearly free of increased OSI, whereas one model showed an overall decrease in high OSI regions (p < 0.05) and another trended in that direction but did not achieve statistical significance (p = 0.145).ConclusionsTo our knowledge, this is the first computational model describing progressive stenosis in any peripheral artery including the carotid. Taken together, this study provides a novel framework for computational hemodynamic investigations on progressive atherosclerosis in the carotid artery.
Heteractis magnifica Sea Anemone Population Dynamics at Village Reef, Perhentian Kecil, Malaysia: Monitoring of Growth, Formations, and Hosting Status
Authors: Versteeg Melissa , Campbell Alanah , Halid Hidayah 
Published: February 2022

ABSTRACTThe coastal waters of Malaysia have been known to allow proliferation of sea anemone assemblages, which are resident species of tropical coral reefs. Along the Perhentian Islands of Terengganu, no efforts have been made thus far to investigate the presence and population dynamics of sea anemone assemblages locally. In this study, Heteractis magnifica assemblages at Village Reef at Perhentian Kecil were monitored during May, July, and August of 2020, thus providing a first assessment of their abundance. Sea anemone formation size, individual size, habitat location, and hosting status of anemonefish were assessed. Results demonstrate significantly larger counts of individuals within aggregated formations in the patch reef as compared to the fringe reef, without the presence of larger individual sizes. In addition, Heteractis magnifica specimens that were actively hosting anemonefish had significantly larger cover, larger individual sizes, and demonstrated higher individual counts within their aggregated formations compared to non-hosting specimens. There was no significant overall effect of time on sea anemone growth throughout the monitoring period, nor were there any significant changes in abundance levels regarding formation make-up throughout the monitoring phase. However, time related effects where present upon data inspection per assessment period. The restricted time frame of the monitoring period could play a role in explaining the absence of overall time related effects. A prolonged monitoring will help to further understand Heteractis magnifica population dynamics at this location, which can increase knowledge capacity for reef management and conservation strategies.
Complex genotype-phenotype relationships shape the response to treatment of Down Syndrome Childhood Acute Lymphoblastic Leukaemia
Authors: Lutz Christoph , Turati Virginia A. , Clifford Ruth , Woll Petter S. , Stiehl Thomas , Castor Anders , Clark Sally A. , Ferry Helen , Buckle Veronica , Trumpp Andreas , Ho Anthony , Marciniak-Czochra Anna , Herrero Javier , Schuh Anna , Jacobsen Sten-Eirik W. , Enver Tariq 
Published: February 2022

AbstractExtensive genetic and epigenetic variegation has been demonstrated in many malignancies. Importantly, their interplay has the potential to contribute to disease progression and treatment resistance. To shed light on the complex relationships between these different sources of intra-tumour heterogeneity, we explored their relative contributions to the evolutionary dynamics of Acute Lymphoblastic Leukemia (ALL) in children with Down syndrome, which has particularly poor prognosis. We quantified the tumour propagating potential of genetically distinct sub-clones using serial transplantation assays and SNP-arrays. While most leukaemias were characterized by a single dominant subclone, others were highly heterogeneous. Importantly, we provide clear and direct evidence that genotypes and phenotypes with functional relevance to leukemic progression and treatment resistance can co-segregate within the disease. Hence, individual genetic lesions can be restricted to well-defined cell immunophenotypes, corresponding to different stages of the leukemic differentiation hierarchy and varied proliferation potentials. As a result of this difference in fitness, which can be accurately quantified via competitive transplantation assays, matching diagnostic, post-treatment, and relapse leukemias can be dominated by different genotypes, including pre-leukemic clones persisting throughout the disease progression and treatment. Intriguingly, plasticity also appears to be a temporally defined property that can segregate with genotype. These results suggest that Down Syndrome ALL should be viewed as a complex matrix of cells exhibiting genetic and epigenetic heterogeneity that foster extensive clonal evolution and competition. Therapeutic intervention reshapes this ‘eco-system’ and may provide the right conditions for the preferential expansion of selected compartments and subsequently relapse.
Novel cerebello-amygdala connections provide missing link between cerebellum and limbic system
Authors: Jung Se Jung , Vlasov Ksenia , D’Ambra Alexa , Parigi Abhijna , Baya Mihir , Frez Edbertt Paul , Villalobos Jacqueline , Fernandez-Frentzel Marina , Anguiano Maribel , Ideguchi Yoichiro , Antzoulatos Evan G. , Fioravante Diasynou 
Published: February 2022

AbstractThe cerebellum is emerging as a powerful regulator of cognitive and affective processing and memory in both humans and animals and has been implicated in affective disorders. How the cerebellum supports affective function remains poorly understood. The short-latency (just a few ms) functional connections that were identified between the cerebellum and amygdala -a structure crucial for the processing of emotion and valence-more than 4 decades ago raise the exciting, yet untested, possibility that a cerebellum-amygdala pathway communicates information important for emotion. The major hurdle in rigorously testing this possibility is the lack of knowledge about the anatomy and functional connectivity of this pathway. Our initial anatomical tracing studies in mice excluded the existence of a direct monosynaptic pathway between cerebellum and amygdala. Using transneuronal tracing techniques, we have identified a novel disynaptic pathway that connects the cerebellar output nuclei to the basolateral amygdala. This pathway recruits the understudied intralaminar thalamus as a node. Using ex vivo optophysiology and super-resolution microscopy, we provide the first evidence for the functionality of the pathway, thus offering a missing mechanistic link between the cerebellum and amygdala. This discovery provides a connectivity blueprint between the cerebellum and a key structure of the limbic system. As such, it is the requisite first step toward obtaining new knowledge about cerebellar function in emotion, thus fundamentally advancing understanding of the neurobiology of emotion, which is perturbed in mental and autism spectrum disorders.
The optimal docking strength for reversibly tethered kinases
Authors: Dyla Mateusz , González Foutel Nicolás S. , Otzen Daniel E. , Kjaergaard Magnus 
Published: February 2022

AbstractMany kinases use reversible docking interactions to augment the specificity of their catalytic domains. Such docking interactions are often structurally independent of the catalytic domain, which allow for flexible combination of modules in evolution and in bioengineering. The affinity of docking interactions spans several orders of magnitude. This led us to ask how the affinity of the docking interaction affects enzymatic activity, and how to pick the optimal interaction module to complement a given substrate. Here, we develop equations that predict the optimal binding strength of a kinase docking interaction and validate it using numerical simulations and steady-state phosphorylation kinetics for tethered protein kinase A. We show that a kinase-substrate pair has an optimum docking strength that depends on their enzymatic constants, the tether architecture, the substrate concentration and the kinetics of the docking interactions. We show that a reversible tether enhances phosphorylation rates most when: I) The docking strength is intermediate, II) the substrate is non-optimal, III) the substrate concentration is low, IV) the docking interaction has rapid exchange kinetics, and V) the tether optimizes the effective concentration of the intra-molecular reaction. This work serves as a framework for interpreting mutations in kinase docking interactions and as a design guide for engineering enzyme scaffolds.
Aero-propulsive interaction model for conceptual distributed propulsion aircraft design
Authors: Awad Mohamed , Stumpf Eike 
Published: February 2022

Purpose
This research aims to present an aero-propulsive interaction model applied to conceptual aircraft design with distributed electric propulsion (DeP). The developed model includes a series of electric ducted fans integrated into the wing upper trailing edge, taking into account the effect of boundary layer ingestion (BLI). The developed model aims to estimate the aerodynamic performance of the wing with DeP using an accurate low-order computational model, which can be easily used in the overall aircraft design's optimization process.

Design/methodology/approach
First, the ducted fan aerodynamic performance is investigated using a low-order computational model over a range of angle of attack required for conventional flight based on ducted fan design code program and analytical models. Subsequently, the aero-propulsive coupling with the wing is introduced. The DeP location chordwise is placed at the wing's trailing edge to have the full benefits of the BLI. After that, the propulsion integration process is introduced. The nacelle design's primary function is to minimize the losses due to distortion. Finally, the aerodynamic forces of the overall configuration are estimated based on Athena Vortex Lattice program and the developed ducted fan model.

Findings
The ducted fan model is validated with experimental measurements from the literature. Subsequently, the overall model, the wing with DeP, is validated with experimental measurements and computational fluid dynamics, both from the literature. The results reveal that the currently developed model successfully estimates the aerodynamic performance of DeP located at the wing trailing edge.

Originality/value
The developed model's value is to capture the aero-propulsive coupling accurately and fast enough to execute multiple times in the overall aircraft design's optimization loop without increasing runtime substantially.