bluuebunny/crossref_metadata_2025 huggingface dataset:
Before trilobite legs:Pygmaclypeatus daziensisreconsidered and the ancestral appendicular organization of Cambrian artiopods
Authors: Schmidt Michel , Hou Xianguang , Zhai Dayou , Mai Huijuan , Belojević Jelena , Chen Xiaohan , Melzer Roland R. , Ortega-Hernández Javier , Liu Yu
Published: February 2022

The Cambrian Stage 3 Chengjiang biota in South China is one of the most influential Konservat-Lagerstätten worldwide thanks to the fossilization of diverse non-biomineralizing organisms through pyritization. Despite their contributions to understanding the evolution of early animals, several Chengjiang species remain poorly known owing to their scarcity and/or incomplete preservation. Here, we use micro-computed tomography to reveal in detail the ventral appendage organization of the enigmatic non-trilobite artiopodPygmaclypeatus daziensis—one of the rarest euarthropods in Chengjiang—and explore its functional ecology and broader evolutionary significance.Pygmaclypeatus daziensispossesses a set of uniramous antennae and 14 pairs of post-antennal biramous appendages, the latter of which show an unexpectedly high degree of heteronomy based on the localized differentiation of the protopodite, endopodite and exopodite along with the antero-posterior body axis. The small body size (less than 2 cm), the presence of delicate spinose endites and well-developed exopodites with multiple paddle-shaped lamellae on the appendages ofP. daziensisindicate a nekto-benthic mode of life and a scavenging/detritus feeding strategy.Pygmaclypeatus daziensisshows that appendage heteronomy is phylogenetically widespread within Artiopoda—the megadiverse clade that includes trilobites and their relatives with non-biomineralizing exoskeletons—and suggests that a single exopodite lobe with paddle-like lamellae is ancestral for this clade.

This article is part of the theme issue ‘The impact of Chinese palaeontology on evolutionary research’.
ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves
Authors: Brum Arthur A. , Vasconcelos Giovani L. , Duarte-Filho Gerson C. , Ospina Raydonal , Almeida Francisco A. G. , Macêdo Antônio M. S.
Published: February 2022

We present the software ModInterv as an informatics tool to monitor, in an automated and user-friendly manner, the evolution and trend of COVID-19 epidemic curves, both for cases and deaths. The ModInterv software uses parametric generalized growth models, together with LOWESS regression analysis, to fit epidemic curves with multiple waves of infections for countries around the world as well as for states and cities in Brazil and the USA. The software automatically accesses publicly available COVID-19 databases maintained by the Johns Hopkins University (for countries as well as states and cities in the USA) and the Federal University of Viçosa (for states and cities in Brazil). The richness of the implemented models lies in the possibility of quantitatively and reliably detecting the distinct acceleration regimes of the disease. We describe the backend structure of software as well as its practical use. The software helps the user not only to understand the current stage of the epidemic in a chosen location but also to make short term predictions as to how the curves may evolve. The app is freely available on the internet (http://fisica.ufpr.br/modinterv), thus making a sophisticated mathematical analysis of epidemic data readily accessible to any interested user.
Can the Kuznetsov Model Replicate and Predict Cancer Growth in Humans?
Authors: Wajeh Mohammad El , Jung Falco , Bongartz Dominik , Kappatou Chrysoula Dimitra , Laleh Narmin Ghaffari , Mitsos Alexander , Kather Jakob Nikolas
Published: February 2022

Several mathematical models to predict tumor growth over time have been developed in the last decades. A central aspect of such models is the interaction of tumor cells with immune effector cells. The Kuznetsov model (Kuznetsov et al. (1994), Bulletin of Mathematical Biology, vol. 56, no. 2, pp. 295–321) is the most prominent of these models and has been used as a basis for many other related models and theoretical studies. However, none of these models have been validated with large-scale real-world data of human patients treated with cancer immunotherapy. In addition, parameter estimation of these models remains a major bottleneck on the way to model-based and data-driven medical treatment. In this study, we quantitatively fit Kuznetsov’s model to a large dataset of 1472 patients, of which 210 patients have more than six data points, by estimating the model parameters of each patient individually. We also conduct a global practical identifiability analysis for the estimated parameters. We thus demonstrate that several combinations of parameter values could lead to accurate data fitting. This opens the potential for global parameter estimation of the model, in which the values of all parameters are fixed for all patients. Furthermore, by omitting the last two or three data points, we show that the model can be extrapolated and predict future tumor dynamics. This paves the way for a more clinically relevant application of mathematical tumor modeling, in which the treatment strategy could be adjusted in advance according to the model’s future predictions.
Optical Genome Mapping And Single Nucleotide Polymorphism Microarray: An Integrated Approach For Investigating Challenging Cases Of Products Of Conception
Authors: Sahajpal Nikhil S , Mondal Ashis K , Ananth Sudha , Pundkar Chetan , Jones Kimya , Williams Colin , Fee Timothy , Weissman Amanda , Tripodi Giuseppe , Oza Eesha , Gavrilova-Jordan Larisa , Omar Nivin , Hastie Alex , DuPont Barbara R , Layman Lawrence , Chaubey Alka , Kolhe Ravindra
Published: February 2022

Conventional cytogenetic analysis of products of conception (POC) is of limited utility because of failed cultures, microbial and maternal cell contamination (MCC). Optical genome mapping (OGM) is an emerging technology that has the potential to replace conventional cytogenetic methods. The use of OGM precludes the requirement for culturing (and related microbial contamination). However, a high percentage of MCC impedes a definitive diagnosis, which can be addressed by an additional pre-analytical quality control step that includes histological assessment of H&E stained slides from FFPE tissue with macro-dissection for Chorionic villi to enrich fetal tissue component for Single nucleotide polymorphism (SNP) microarray analysis. An internal audit of POC cases subjected to karyotype-only analysis showed a low yield on clinically actionable information that contributed to patient care. To improve the diagnostic yield, an integrated workflow was devised that included MCC characterization of POC tissue, followed by OGM for MCC negative cases or SNPM with histological assessment for MCC positive cases. A result was obtained in 93% (29/31) cases with a diagnostic yield of 45.1% (14/31) with proposed workflow compared to 9.6% (3/31) and 6.4% (2/31) with routine workflow, respectively. The integrated workflow with these technologies demonstrates the clinical utility and higher diagnostic yield in evaluating POC specimens.
Recurrent circuits amplify corticofugal signals and drive feedforward inhibition in the inferior colliculus
Authors: Oberle Hannah M. , Ford Alexander N. , Czarny Jordyn E. , Rogalla Meike M. , Apostolides Pierre F.
Published: February 2022

The inferior colliculus (IC) is a midbrain hub critical for perceiving complex sounds such as speech. In addition to processing ascending inputs from most auditory brainstem nuclei, the IC receives descending inputs from auditory cortex that control IC neuron feature selectivity, plasticity, and certain forms of perceptual learning. Although corticofugal synapses primarily release the excitatory transmitter glutamate, many physiology studies show that auditory cortical activity has a net inhibitory effect on IC neuron spiking. Perplexingly, anatomy studies imply that corticofugal axons primarily target glutamatergic IC neurons while only sparsely innervating IC GABA neurons.

Corticofugal inhibition of the IC may thus occur largely independently of feedforward activation of local GABA neurons. We shed light on this paradox usingin vitroelectrophysiology in acute IC slices from fluorescent reporter mice of either sex. Using optogenetic stimulation of corticofugal axons, we find that excitation evoked with single light flashes is indeed stronger in presumptive glutamatergic neurons compared to GABAergic neurons. However, many IC GABA neurons fire tonically at rest, such that sparse and weak excitation suffices to significantly increase their spike rates.

Furthermore, a subset of glutamatergic IC neurons fire spikes during repetitive corticofugal activity, leading to polysynaptic excitation in IC GABA neurons owing to a dense intra-collicular connectivity. Consequently, recurrent excitation amplifies corticofugal activity, drives spikes in IC GABA neurons, and generates substantial local inhibition in the IC. Thus, descending signals engage intra-collicular inhibitory circuits despite apparent constraints of monosynaptic connectivity between auditory cortex and IC GABA neurons.

Significance Statement

Descending “corticofugal” projections are ubiquitous across mammalian sensory systems, and enable the neocortex to control subcortical activity in a predictive or feedback manner. Although corticofugal neurons are glutamatergic, neocortical activity often inhibits subcortical neuron spiking. How does an excitatory pathway generate inhibition? Here we study the corticofugal pathway from auditory cortex to inferior colliculus (IC), a midbrain hub important for complex sound perception. Surprisingly, cortico-collicular transmission was stronger onto IC glutamatergic compared to GABAergic neurons. However, corticofugal activity triggered spikes in IC glutamate neurons with local axons, thereby generating strong polysynaptic excitation and feed-forward spiking of GABAergic neurons. Our results thus reveal a novel mechanism that recruits local inhibition despite limited monosynaptic convergence onto inhibitory networks.
Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
Authors: Borges Fernando S. , Moreira Joao V.S. , Takarabe Lavinia M. , Lytton William W. , Dura-Bernal Salvador
Published: February 2022

The primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimotor behaviors. In 2015, the Blue Brain Project developed a groundbreaking rat S1 microcircuit simulation with over 31,000 neurons with 207 morpho-electrical neuron types, and 37 million synapses, incorporating anatomical and physiological information from a wide range of experimental studies. We have implemented this highly-detailed and complex S1 model in NetPyNE, using the data available in the Neocortical Microcircuit Collaboration Portal. NetPyNE provides a Python high-level interface to NEURON and allows defining complicated multiscale models using an intuitive declarative standardized language. It also facilitates running parallel simulations, automates the optimization and exploration of parameters using supercomputers, and provides a wide range of built-in analysis functions. This will make the S1 model more accessible and simpler to scale, modify and extend in order to explore research questions or interconnect to other existing models. Despite some implementation differences, the NetPyNE model preserved the original cell morphologies, electrophysiological responses and spatial distribution for all 207 cell types; and the connectivity properties of all 1941 pathways, including synaptic dynamics and short-term plasticity (STP). The NetPyNE S1 simulations produced reasonable physiological firing rates and activity patterns across all populations. The network generated a 1 Hz oscillation comparable to the original model in vitro-like state. By then reducing the extracellular calcium concentration, the model reproduced the original S1 in vivo-like states with asynchronous activity. These results validate the original study using a new modeling tool. Simulated local field potentials (LFPs) exhibited realistic oscillatory patterns and features, including distance- and frequency-dependent attenuation. The model was extended by adding thalamic circuits, including 6 distinct thalamic populations with intrathalamic, thalamocortical and corticothalamic connectivity derived from experimental data. The thalamic model reproduced single known cell and circuit-level dynamics, including burst and tonic firing modes and oscillatory patterns, providing a more realistic input to cortex and enabling study of thalamocortical interactions. Overall, our work provides a widely accessible, data-driven and biophysically-detailed model of the somatosensory thalamocortical circuits that can be employed as a community tool for researchers to study neural dynamics, function and disease.
Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics
Authors: Dura-Bernal Salvador , Griffith Erica Y , Barczak Annamaria , O’Connell Monica N , McGinnis Tammy , Schroeder Charles E , Lytton William W , Lakatos Peter , Neymotin Samuel A
Published: February 2022

We developed a biophysically-detailed model of the macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB) and thalamic reticular nuclei (TRN), using the NEURON simulator and NetPyNE multiscale modeling tool. We simulated A1 as a cortical column with a depth of 2000 μm and 200 μm diameter, containing over 12k neurons and 30M synapses. Neuron densities, laminar locations, classes, morphology and biophysics, and connectivity at the long-range, local and dendritic scale were derived from published experimental data. The A1 model included 6 cortical layers and multiple populations of neurons consisting of 4 excitatory and 4 inhibitory types, and was reciprocally connected to the thalamus (MGB and TRN), mimicking anatomical connectivity. MGB included core and matrix thalamocortical neurons with layer-specific projection patterns to A1, and thalamic interneurons projecting locally. Auditory stimulus-related inputs to the MGB were simulated using phenomenological models of the cochlear/auditory nerve and the inferior colliculus. The model generated cell type and layer-specific firing rates consistent with experimentally observed ranges, and accurately simulated the corresponding local field potentials (LFPs), current source density (CSD), and electroencephalogram (EEG) signals. Laminar CSD patterns during spontaneous activity, and in response to speech input, were similar to those recorded experimentally. Physiological oscillations emerged spontaneously across frequency bands without external rhythmic inputs and were comparable to those recorded in vivo. We used the model to unravel the contributions from distinct cell type and layer-specific neuronal populations to oscillation events detected in CSD, and explored how these relate to the population firing patterns. Overall, the computational model provides a quantitative theoretical framework to integrate and interpret a wide range of experimental data in auditory circuits. It also constitutes a powerful tool to evaluate hypotheses and make predictions about the cellular and network mechanisms underlying common experimental measurements, including MUA, LFP and EEG signals.
Multiscale model of primary motor cortex circuits predicts in vivo cell type-specific, behavioral state-dependent dynamics
Authors: Dura-Bernal Salvador , Neymotin Samuel A , Suter Benjamin A , Dacre Joshua , Schiemann Julia , Duguid Ian , Shepherd Gordon MG , Lytton William W
Published: February 2022

Understanding cortical function requires studying multiple scales: molecular, cellular, circuit and behavior. We developed a biophysically detailed multiscale model of mouse primary motor cortex (M1) with over 10,000 neurons and 30 million synapses. Neuron types, densities, spatial distributions, morphologies, biophysics, connectivity and dendritic synapse locations were tightly constrained by experimental data. The model includes long-range inputs from 7 thalamic and cortical regions, as well as noradrenergic inputs from locus coeruleus. Connectivity depended on cell class and cortical depth at sublaminar resolution. The model accurately predicted in vivo layer- and cell type-specific responses (firing rates and LFP) associated with behavioral states (quiet wakefulness and movement) and experimental manipulations (noradrenaline receptor blocking and thalamus inactivation). It also enabled evaluation of multiple mechanistic hypotheses underlying the observed activity. This quantitative theoretical framework can be used to integrate and interpret M1 experimental data and sheds light on the cell type-specific multiscale dynamics associated with a range of experimental conditions and behaviors.
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

In 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

Multiple 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

Background

The 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.

Aims

The primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality.

Methods

This 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.

Results

Out 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.

Conclusion

The 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

As 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

We 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

Motivation

Advancing 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.

Results

Optocoder 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.

Availability

Optocoder 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

Background and aims

This 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.

Methods

Three-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.

Results

Six 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).

Conclusions

To 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

The 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.
Delimiting Continuity: Comparison of Target Enrichment and ddRAD for Delineating Admixing Parapatric Melitaea Butterflies
Authors: Joshi Mukta , Espeland Marianne , Dinca Vlad Eugen , Vila Roger , Tahami Mohadeseh Sadat , Dietz Lars , Mayer Christoph , Martin Sebastian , Dapporto Leonardo , Mutanen Marko
Published: February 2022

Parapatrically distributed taxa pose a challenge for species delimitation due to the presence of gene flow and inherent arbitrariness of exactly defining the species boundaries in such systems. We tackled the problem of species delimitation in a parapatric species pair of Melitaea butterflies using two popular genomic methods, double digest restriction-site associated DNA sequencing (ddRAD) and target enrichment. The former is mainly applied at shallow phylogenetic scales and the latter at both deep and shallow scales. Although both of these methods have been adequately utilised for species delimitation purposes, there are only a handful of studies that have compared these two genomic approaches in the same study system. We applied phylogenetic, population genetic and species delimitation methods and compared the results obtained from the two approaches. Using a recently developed target enrichment probe kit, we were able to capture 1,743 loci with a low amount of missing data and compared these with already available ddRAD data from a previous study on the same set of specimens. We recovered consistent phylogenetic relationships across the datasets, both demonstrating the presence of a genetically distinct Balkan lineage and paraphyly of Melitaea athalia with respect to Melitaea celadussa. The same relationships were also found in a species tree analysis of the target enrichment dataset using ASTRAL. Population genetic STRUCTURE analyses supported the presence of two species when using ddRAD data, but three species when using target enrichment, while the Bayes factor delimitation analysis found both two and three species scenarios equally decisive in both datasets. From the geographic distribution of genomic admixture, we confirm the patterns observed by a previous study that used ddRAD data. As the results obtained from both methods were largely congruent, we discuss some practical considerations and benefits of target enrichment over RAD sequencing. We conclude that the choice of method of genomic data collection does not influence the results of phylogenetic analyses at alpha taxonomic level, given a sufficient number of loci. Finally, we recommend a solution for delineating species in parapatric scenarios by proposing that parapatric taxa be consistently classified as subspecies or complete species, but not both, to promote taxonomic stability.
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

Extensive 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

The 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

Many 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.
The effects of job crafting on tour leaders’ work engagement: the mediating role of person-job fit and meaningfulness of work
Authors: Guo Yongrui , Hou Xinyi
Published: February 2022

Purpose

This study aims to examine the effects of job crafting on the work engagement of tour leaders mediated by person-job fit and the meaningfulness of work.

Design/methodology/approach

Derived from a sample of 331 tour leaders in China, the data for this research were analyzed using partial least squares structural equation modeling.

Findings

The findings revealed that job crafting increased tour leaders’ person-job fit and meaningfulness of work, which stimulated their work engagement. Tour leaders’ person-job fit also increased their work engagement and perceptions of the meaningfulness of work. Enhancing the work meaningfulness of tour leaders can significantly increase their work engagement. Person-job fit and meaningfulness of work had a significant mediating effect between job crafting and tour leaders’ work engagement.

Practical implications

Managers need to provide external conditions for tour leaders’ job crafting by expanding structural and social job resources and by creating more stimulating job environments. Managers can enhance tour leaders’ work engagement by shaping their work meaning and person-job fit.

Originality/value

First, this study empirically tested the effects of job crafting on tour leaders’ work engagement, thus directly addressed the lack of academic attention paid to this topic. Second, this study examines the mediating role of person-job fit and meaningfulness of work, with regard to tour leaders’ job crafting and work engagement, based on an integrative concept model.
Education for sustainable development amidst COVID-19 pandemic: role of sustainability pedagogies in developing students’ sustainability consciousness
Authors: Nousheen Ayesha , Kalsoom Qudsia
Published: February 2022

Purpose

This study aims to assess the impact of sustainability pedagogies on students’ sustainability consciousness (SC) in the online instructional settings during the COVID-19 pandemic.

Design/methodology/approach

A mixed-method, embedded research design was applied to conduct the research. The participants of the study were the pre-service teachers studying a course, namely, “Education for Sustainable Development” (ESD) in a public sector university of Pakistan. A total of 49 participants were divided into control and experimental groups. The experimental group experienced ESD-pedagogies in online teaching-learning (educational) settings, whereas the control group was taught through a lecture-based approach in an online educational setting. The outcome of the research was measured in terms of a change in the pre-service teachers’ SC. The qualitative data were collected from the experimental group only. The quantitative data were analyzed using paired sample t-test and independent sample t-test, whereas the qualitative data were analyzed through thematic analysis.

Findings

The quantitative and qualitative data indicate that sustainability pedagogies (i.e. case studies, critical incidents, discussions, debates and problem-based teaching) enhanced pre-service teachers’ SC in online educational settings during the COVID-19 pandemic.

Originality/value

The current research expands the discussion on the effectiveness of sustainability pedagogies in online educational settings in teacher education programs.
Exploring differences in the subjective well-being of teleworkers prior to and during the pandemic
Authors: Pataki-Bittó Fruzsina , Kun Ágota
Published: February 2022

Purpose

This study aims to find out the differences in the employee well-being of teleworkers in Hungary prior to and during the pandemic restrictions and explores whether the differences stem from (1) the presence of children or (2) the changes in the telework situation (freely chosen or forced by pandemic restrictions).

Design/methodology/approach

As the first step of this study of office workers, the authors created a “one working day” measure within the conceptual framework of positive psychology that is suitable for comparing the well-being factors experienced in various work environments. The survey was completed by two independent samples: 52 office workers regarding home office before the appearance of the virus in Europe (Phase 1) and 152 office workers during the first wave of the COVID-19 pandemic in Hungary (Phase 2).

Findings

This research reveals that teleworking during the pandemic has increased irritability and tension for all teleworkers, but the stress levels, the overall subjective well-being and the level of engagement were significantly affected only in the case of those teleworkers who raise small children. Despite the overlapping responsibilities of parents, their work-related sense of accomplishment did not change during the COVID-19 lockdown. The forced home office setup may, however, entail the strengthening of co-worker relationships in the online space.

Originality/value

By understanding the relationship between well-being predictors and the changes in the situation of remote working, the results may help develop intervention programs to promote employee well-being in challenging times.