bluuebunny/crossref_metadata_2025 huggingface dataset:
Mutational and biophysical robustness in a pre-stabilized monobody
Authors: Chandler Peter G. , Tan Li Lynn , Porebski Benjamin T. , Green James S. , Riley Blake T. , Broendum Sebastian S. , Hoke David E. , Falconer Robert J. , Munro Trent P. , Buckle Malcolm , Jackson Colin J. , Buckle Ashley M.
Published: December 2020

The fibronectin type III (FN3) monobody domain is a promising non-antibody scaffold which features a less complex architecture than an antibody while maintaining analogous binding loops. We previously developed FN3Con, a hyper-stable monobody derivative with diagnostic and therapeutic potential. Pre-stabilization of the scaffold mitigates the stability-function trade-off commonly associated with evolving a protein domain towards biological activity. Here, we aimed to examine if the FN3Con monobody could take on antibody-like binding to therapeutic targets, while retaining its extreme stability. We targeted the first of the Adnectin derivative of monobodies to reach clinical trials, which was engineered by directed evolution for binding to the therapeutic target VEGFR2; however, this function was gained at the expense of large losses in thermostability and increased oligomerisation. In order to mitigate these losses, we grafted the binding loops from Adnectin-anti-VEGFR2 (CT-322) onto the pre-stabilized FN3Con scaffold to produce a domain that successfully bound with high affinity to the therapeutic target VEGFR2. This FN3Con-anti-VEGFR2 construct also maintains high thermostability, including remarkable long-term stability, retaining binding activity after 2 years of storage at 36 °C. Further investigations into buffer excipients doubled the presence of monomeric monobody in accelerated stability trials. These data suggest that loop grafting onto a pre-stabilized scaffold is a viable strategy for the development of monobody domains with desirable biophysical characteristics, and is therefore well-suited to applications such as the evolution of multiple paratopes or shelf-stable diagnostics and therapeutics.
Lactate Accelerates Mouse ES Cell Differentiation Towards the XEN Lineage
Authors: Gatie Mohamed I. , Cooper Tyler T. , Lajoie Gilles A. , Kelly Gregory M.
Published: December 2020

Metabolism plays a crucial role for cell survival and function; however, recent evidence has implicated it in regulating embryonic development. The inner cell mass undergoes orchestrated cellular divisions resulting in the formation of embryonic stem cells and extraembryonic endoderm (XEN) cells. Concomitantly, changes in the metabolic profile occurs during development and are well-documented in the embryonic lineages. However, a comprehensive multi-omics analysis of these features in XEN cells remains lacking. We observed that feeder-free XEN cells exhibited high sensitivity to glycolytic inhibition in addition to maintaining elevated intra- and extracellular lactate levels. XEN cells maintain high lactate levels by increased LDHA activity and re-routing pyruvate away from the mitochondria. Importantly, exogenous lactate supplementation or promoting intracellular lactate accumulation enhances XEN differentiationin vitro. Our results highlight how lactate contributes to XEN differentiation in the mammalian embryo and may serve to enhance reprogramming efficiency of cells used for regenerative medicine.

Highlights

Feeder-free XEN cells exhibit high sensitivity to glycolytic inhibition

Distinct transcriptomic, proteomic and metabolomic profile exists between feeder-free ES and XEN cells

Elevated intracellular and extracellular lactate is observed in feeder-free XEN cells

Lactate enhances feeder-free XEN differentiationin vitro
Characteristics and Risk Factors for Hospitalization and Mortality among Persons with COVID-19 in Atlanta Metropolitan Area
Authors: Chishinga Nathaniel , Gandhi Neel R. , Onwubiko Udodirim N. , Telford Carson , Prieto Juliana , Smith Sasha , Chamberlain Allison T. , Khan Shamimul , Williams Steve , Khan Fazle , Shah Sarita
Published: December 2020

Background: We present data on risk factors for severe outcomes among patients with coronavirus disease 2019 (COVID-19) in the southeast United States (U.S.).
Objective: To determine risk factors associated with hospitalization, intensive care unit (ICU) admission, and mortality among patients with confirmed COVID-19.
Design: A retrospective cohort study.
Setting: Fulton County in Atlanta Metropolitan Area, Georgia, U.S.
Patients: Community-based individuals of all ages that tested positive for SARS-CoV-2.
Measurements: Demographic characteristics, comorbid conditions, hospitalization, ICU admission, death (all-cause mortality), and severe COVID-19 disease, defined as a composite measure of hospitalization and death.
Results: Between March 2 and May 31, 2020, we included 4322 individuals with various COVID-19 outcomes. In a multivariable logistic regression random-effects model, patients in age groups ≥45 years compared to those <25 years were associated with severe COVID-19. Males compared to females (adjusted odds ratio [aOR] 1.4, 95% confidence interval [CI]: 1.1-1.6), non-Hispanic blacks (aOR 1.9, 95%CI: 1.5-2.4) and Hispanics (aOR 1.7, 95%CI: 1.2-2.5) compared to non-Hispanic whites were associated with increased odds of severe COVID-19. Those with chronic renal disease (aOR 3.6, 95%CI: 2.2-5.8), neurologic disease (aOR 2.8, 95%CI: 1.8-4.3), diabetes (aOR 2.0, 95%CI: 1.5-2.7), chronic lung disease (aOR 1.7, 95%CI: 1.2-2.3), and ″other chronic diseases″ (aOR 1.8, 95%CI: 1.3-2.6) compared to those without these conditions were associated with increased odds of having severe COVID-19.
Conclusions: Multiple risk factors for hospitalization, ICU admission, and death were observed in this cohort from an urban setting in the southeast U.S. Improved screening and early, intensive treatment for persons with identified risk factors is urgently needed to reduce COVID-19 related morbidity and mortality.
Mental and social health of children and adolescents with pre-existing mental or somatic problems during the COVID-19 pandemic lockdown
Authors: Zijlmans Josjan , Teela Lorynn , Ewijk Hanneke van , Klip Helen , Mheen Malindi van der , Ruisch Hyun , Luijten Michiel , Muilekom Maud van , Oostrom Kim , Buitelaar Jan , Hoekstra Pieter , Lindauer Ramon , Popma Arne , Staal Wouter , Vermeiren Robert , Oers Hedy van , Haverman Lotte , Polderman Tinca
Published: December 2020

Background: The COVID-19 lockdown increases psychological problems in children and adolescents from the general population. Here we investigate the mental and social health during the COVID-19 lockdown in children and adolescents with pre-existing mental or somatic problems.

Method: We included participants (8-18 years) from a psychiatric (N = 249) and pediatric (N = 90) sample, and compared them to a general population sample (N = 844). Measures were assessed during the first lockdown (April-May 2020) in the Netherlands. Main outcome measures were Patient-Reported Outcomes Measurement Information System (PROMIS) domains: Global Health, Peer Relationships, Anxiety, Depressive Symptoms, Anger, and Sleep-Related Impairment. Additionally, socio-demographic variables, COVID-19-related questions, changes in atmosphere at home from a parent and child perspective, and children's experiences of lockdown regulations were assessed.

Results: On all measures except Global Health, the pediatric sample reported least problems. The psychiatric sample reported significantly more problems than the general population sample on all measures except for Anxiety and Peer Relationships. Having a COVID-19 affected friend/relative and a COVID-19 related change in work situation negatively moderated outcome, but not in the samples with pre-existing problems. All parents reported significant decreases in atmosphere at home, as did children from the general population.

Conclusion: We observed significant differences in mental and social health between three child and adolescent samples during the COVID-19 pandemic lockdown and identified COVID-19-related factors influencing mental and social health. Our findings contribute to current and future policies during pandemic related lockdowns regarding the mental and social health of children and adolescents.
SOCIODEMOGRAPHIC CHARACTERISTICS AND COVID-19 TESTING RATES: SPATIO-TEMPORAL PATTERNS AND IMPACT OF TEST ACCESSIBILITY IN SWEDEN
Authors: Kennedy Beatrice , Varotsis Georgios , Hammar Ulf , Nguyen Diem , Carrasquilla Germán D. , van Zoest Vera , Kristiansson Robert S. , Fitipaldi Hugo , Dekkers Koen F. , Daivadanam Meena , Martinell Mats , Björk Jonas , Fall Tove
Published: December 2020

Background

Diagnostic testing is essential for disease surveillance and test-trace-isolate efforts. Here, we aimed to investigate if residential area sociodemographic characteristics and test accessibility were associated with COVID-19 testing rates.

Methods

We included information on 421 542 patient-initiated COVID-19 PCR tests from Uppsala County in Sweden from 24 June, 2020 to 9 February, 2022. Using Poisson regression analyses, we investigated whether the Care Need Index (CNI; median 1.0, IQR 0.8, 1.4), a composite measure of sociodemographic factors used in Sweden to allocate primary healthcare resources, was associated with aggregated COVID-19 daily testing rates after adjustments for community transmission. We further assessed if distance to the nearest testing station influenced testing. Lastly, we performed a difference-in-difference analysis of the opening of a testing station targeting a disadvantaged neighbourhood.

Results

We observed that CNI, i.e. primary healthcare need, was negatively associated with COVID-19 testing rates in inhabitants aged 5-69 years. More pronounced differences were noted across younger age groups and in Uppsala City, with test rate ratios in children (5-14 years) ranging from 0.56 (95% CI 0.47-0.66) to 0.88 (95% CI 0.81-0.95) across the three pandemic waves. Longer distance to testing station was linked to lower testing rates, foremost in less densely populated areas. Furthermore, the opening of the targeted testing station was associated with increased testing, including twice as high testing rates in individuals aged 70-105, supporting an intervention effect.

Conclusions

Ensuring accessible testing across all residential areas constitutes a promising tool to decrease differences and inequalities in testing.
Sheltering in place and the likelihood of non-natural death
Authors: Catalano Ralph , Glymour Maria , Chen Yea-Hung , Bibbins-Domingo Kirsten
Published: December 2020

Increasing hospitalizations for COVID-19 in the United States (US) and elsewhere have ignited debate over whether to reinstate shelter-in-place policies adopted early in the pandemic to slow the spread of infection. The debate includes claims that sheltering in place influences deaths unrelated to infection or other natural causes. Testing this claim should improve the benefit/cost accounting that presumably informs the decision of whether to reimpose sheltering in place. To distinguish effects of shelter-in-place policies from other events in the pandemic, we compare experiences in two large US states with markedly different policies. We use time-series methods to compare temporal variation in non-natural deaths in California to that in Florida. California was the first state to begin and among the last to end sheltering in place while sheltering began later and ended earlier in Florida. We find that during weeks when California had shelter-in-place orders in effect, but Florida did not, the odds that a non-natural death occurred in California rather than Florida fell 14.8% below values expected from history. These results suggest that sheltering-in-place policies reduce mortality from mechanisms unrelated to infection or other natural causes of death.
Development of a Rapid Point-Of-Care Test that Measures Neutralizing Antibodies to SARS-CoV-2
Authors: Lake Douglas F. , Roeder Alexa J. , Kaleta Erin , Jasbi Paniz , Pfeffer Kirsten , Koelbel Calvin , Periasamy Sivakumar , Kuzmina Natalia , Bukreyev Alexander , Grys Thomas E. , Wu Liang , Mills John R , McAulay Kathrine , Gonzalez-Moa Maria , Seit-Nebi Alim , Svarovsky Sergei
Published: December 2020

Background

After receiving a COVID-19 vaccine, most recipients want to know if they are protected from infection and for how long. Since neutralizing antibodies are a correlate of protection, we developed a lateral flow assay (LFA) that measures levels of neutralizing antibodies from a drop of blood. The LFA is based on the principle that neutralizing antibodies block binding of the receptor-binding domain (RBD) to angiotensin-converting enzyme 2 (ACE2).

Methods

The ability of the LFA was assessed to correctly measure neutralization of sera, plasma or whole blood from patients with COVID-19 using SARS-CoV-2 microneutralization assays. We also determined if the LFA distinguished patients with seasonal respiratory viruses from patients with COVID-19. To demonstrate the usefulness of the LFA, we tested previously infected and non-infected COVID-19 vaccine recipients at baseline and after first and second vaccine doses.

Results

The LFA compared favorably with SARS-CoV-2 microneutralization assays with an area under the ROC curve of 98%. Sera obtained from patients with seasonal coronaviruses did not show neutralizing activity in the LFA. After a single mRNA vaccine dose, 87% of previously infected individuals demonstrated high levels of neutralizing antibodies. However, if individuals were not previously infected only 24% demonstrated high levels of neutralizing antibodies after one vaccine dose. A second dose boosted neutralizing antibody levels just 8% higher in previously infected individuals, but over 63% higher in non-infected individuals.

Conclusions

A rapid, semi-quantitative, highly portable and inexpensive neutralizing antibody test might be useful for monitoring rise and fall in vaccine-induced neutralizing antibodies to COVID-19.
Clinician perspectives on what constitutes good practice in community services for people with Complex Emotional Needs: A qualitative thematic meta-synthesis
Authors: Troup Jordan , Lever-Taylor Billie , Sheridan Rains Luke , Broeckelmann Eva , Russell Jessica , Jeynes Tamar , Cooper Chris , Steare Thomas , Dedat Zainab , McNicholas Shirley , Oram Sian , Dale Oliver , Johnson Sonia
Published: December 2020

Introduction
The need to improve the quality of community mental health services for people with Complex Emotional Needs (CEN) is recognised internationally and has become a renewed policy priority in England. Such improvement requires positive engagement from clinicians across the service system, and their perspectives on achieving good practice need to be understood.

Aim
To synthesise qualitative evidence on clinician perspectives on what constitutes good practice, and what helps or prevents it being achieved, in community mental health services for people with CEN.

Methods
Six bibliographic databases were searched for studies published since 2003 and supplementary citation tracking was conducted. Studies that used any recognised qualitative method and reported clinician experiences and perspectives on community-based mental health services for adults with CEN were eligible for this review, including generic and specialist settings. Meta-synthesis was used to generate and synthesise over-arching themes across included studies.

Results
Twenty-nine papers were eligible for inclusion. Six over-arching themes were identified: 1. The use and misuse of diagnosis; 2. The patient journey into services: nowhere to go; 3. Therapeutic relationships: connection and distance; 4. The nature of treatment: not doing too much or too little; 5. Managing safety issues and crises: being measured and proactive; 6. Clinician and wider service needs: whose needs are they anyway? The overall quality of the evidence was moderate.

Discussion
Through summarising the literature on clinician perspectives on good practice for people with CEN, over-arching priorities were identified on which there appears to be substantial consensus. In their focus on needs such as for a long-term perspective on treatment journeys, high quality and consistent therapeutic relationships, and a balanced approach to safety, clinician priorities are mainly congruent with those found in studies on service user views. They also identify clinician needs that should be met for good care to be provided, including for supervision, joint working and organisational support.
Shared genetic etiology between idiopathic pulmonary fibrosis and COVID-19 severity
Authors: Fadista Joao , Kraven Luke M. , Karjalainen Juha , Andrews Shea J. , Geller Frank ,   The COVID-19 Host Genetics Initiative, Baillie J Kenneth , Wain Louise V. , Gisli Jenkins R. , Feenstra Bjarke
Published: December 2020

Background. Idiopathic pulmonary fibrosis (IPF) is a complex lung disease, characterized by progressive lung scarring. Severe COVID-19 is associated with substantial pneumonitis and has a number of shared major risk factors with IPF. This study aimed to determine the genetic correlation between IPF and severe COVID-19 and assess a potential causal role of genetically increased risk of IPF on COVID-19 severity.
Methods. We performed a Mendelian randomisation (MR) study for IPF causality in COVID-19. Genetic variants associated with IPF susceptibility (P<5x10-8) in previous genome-wide association studies (GWAS) were used as instrumental variables (IVs). Effect estimates of those IVs on COVID-19 severity were gathered from the GWAS meta-analysis by the COVID-19 Host Genetics Initiative. The genetic correlation between IPF and COVID-19 severity was estimated with linkage disequilibrium (LD) score regression.
Findings. We detected a positive genetic correlation of IPF with COVID-19 severity (rg=0.31 [95% CI 0.04-0.57], P = 0.023). The MR estimates for severe COVID-19 did not reveal any genetic association (OR 1.05, [95% CI 0.92-1.20], P = 0.43). However, outlier analysis revealed that the IPF risk allele rs35705950 at MUC5B had a different effect compared with the other variants. When rs35705950 was excluded, MR results provided evidence that genetically increased risk of IPF has a causal effect on COVID-19 severity (OR 1.21, [95% CI 1.06-1.38], P = 4.24x10-3). Furthermore, the IPF risk-allele at MUC5B showed an apparent protective effect against COVID-19 hospitalization only in older adults (OR 0.86, [95% CI 0.73-1.00], P = 2.99x10-2) .
Interpretation. The strongest genetic determinant of IPF, rs35705950 at MUC5B, seems to confer protection against COVID-19, whereas the combined effect of all other IPF risk loci seem to confer risk of COVID-19 severity. The observed effect of rs35705950 could either be due to protective effects of mucin over-production on the airways or a consequence of selection bias due to a patient group that is heavily enriched for the rs35705950 T undertaking strict self-isolation. Due to the diverse impact of IPF causal variants on SARS-CoV-2 infection, further investigation is needed to address this apparent paradox between variance at MUC5B and other IPF genetic risk factors.
The Gradient Clusteron: A model neuron that learns via dendritic nonlinearities, structural plasticity, and gradient descent
Authors: Moldwin Toviah , Kalmenson Menachem , Segev Idan
Published: December 2020

Synaptic clustering on neuronal dendrites has been hypothesized to play an important role in implementing pattern recognition. Neighboring synapses on a dendritic branch can interact in a synergistic, cooperative manner via the nonlinear voltage-dependence of NMDA receptors. Inspired by the NMDA receptor, the single-branch clusteron learning algorithm (Mel 1991) takes advantage of location-dependent multiplicative nonlinearities to solve classification tasks by randomly shuffling the locations of “under-performing” synapses on a model dendrite during learning (“structural plasticity”), eventually resulting in synapses with correlated activity being placed next to each other on the dendrite. We propose an alternative model, the gradient clusteron, or G-clusteron, which uses an analytically-derived gradient descent rule where synapses are “attracted to” or “repelled from” each other in an input- and location- dependent manner. We demonstrate the classification ability of this algorithm by testing it on the MNIST handwritten digit dataset and show that, when using a softmax activation function, the accuracy of the G-clusteron on the All-vs-All MNIST task (∼85%) approaches that of logistic regression (∼93%). In addition to the location update rule, we also derive a learning rule for the synaptic weights of the G-clusteron (“functional plasticity”) and show that a G-clusteron that utilizes the weight update rule can achieve ∼89% accuracy on the MNIST task. We also show that a G-clusteron with both the weight and location update rules can learn to solve the XOR problem from arbitrary initial conditions.
CERMEP-IDB-MRXFDG: A database of 37 normal adult human brain [18F]FDG PET, T1 and FLAIR MRI, and CT images available for research
Authors: Mérida Inés , Jung Julien , Bouvard Sandrine , Le Bars Didier , Lancelot Sophie , Lavenne Franck , Bouillot Caroline , Redouté Jérôme , Hammers Alexander , Costes Nicolas
Published: December 2020

We present a database of cerebral PET FDG and anatomical MRI for 37 normal adult human subjects (CERMEP-IDB-MRXFDG).

Thirty-nine participants underwent [18F]FDG PET/CT and MRI, resulting in [18F]FDG PET, T1 MPRAGE MRI, FLAIR MRI, and CT images. Two participants were excluded after visual quality control. We describe the acquisition parameters, the image processing pipeline and provide participants’ individual demographics (mean age 38 ± 11.5 years, range 23-65, 20 women). Volumetric analysis of the 37 T1 MRIs showed results in line with the literature. A leave-one-out assessment of the 37 FDG images using Statistical Parametric Mapping (SPM) yielded a low number of false positives after exclusion of artefacts.

The database is stored in three different formats, following the BIDS common specification: 1) DICOM (data not processed), 2) NIFTI (multimodal images coregistered to PET subject space), 3) NIFTI normalized (images normalized to MNI space).

Bona fideresearchers can request access to the database via a short form.
Uneven protection of persistent giant kelp forest in the Northeast Pacific Ocean
Authors: Arafeh-Dalmau Nur , Cavanaugh Kyle C. , Possingham Hugh P. , Munguia-Vega Adrian , Montaño-Moctezuma Gabriela , Bell Tom W. , Cavanaugh Kate , Micheli Fiorenza
Published: December 2020

In most regions, the distribution of marine forests and the efficacy of their protection is unknown. We mapped the persistence of giant kelp forests across ten degrees of latitude in the Northeast Pacific Ocean and found that 7.7% of giant kelp is fully protected, with decreasing percentages from north to south. Sustainability goals should prioritize kelp mapping and monitoring, while protection and climate adaption targets should account for habitat dynamics.
COPLA, a taxonomic classifier of plasmids
Authors: Redondo-Salvo Santiago , Bartomeus Roger , Vielva Luis , Tagg Kaitlin A. , Webb Hattie E. , Fernández-López Raúl , de la Cruz Fernando
Published: December 2020

The Plasmid Taxonomic Unit (PTU) concept is an initial step for a natural classification of plasmids. Here we present COPLA, a software for plasmid assignation to existing PTUs. To assess its performance, we used a sample of 1,000 plasmids missing from its current database. Overall, 41% of samples could be assigned an existing PTU (63% within the most abundant order,Enterobacterales), while 4% of samples could help to define new PTUs once COPLA database was updated.
DRAM1 requires PI(3,5)P2generation by PIKfyve to deliver vesicles and their cargo to endolysosomes
Authors: van der Vaart Michiel , Banducci-Karp Adrianna , Forn-Cuní Gabriel , Witt Philip M. M. , Willemse Joost J. , Sánchez Salomé Muñoz , Hosseini Rohola , Meijer Annemarie H.
Published: December 2020

Endolysosomal vesicle trafficking and autophagy are crucial degradative pathways in maintenance of cellular homeostasis. The transmembrane protein DRAM1 is a potential therapeutic target that primarily localises to endolysosomal vesicles and promotes autophagy and vesicle fusion with lysosomes. However, the molecular mechanisms underlying DRAM1-mediated vesicle fusion events remain unclear. Using high-resolution confocal microscopy in the zebrafish model, we show that mCherry-Dram1 labelled vesicles interact and fuse with early endosomes marked by PI(3)P. Following these fusion events, early endosomes mature into late endosomes in a process dependent on the conversion of PI(3)P into PI(3,5)P2by the lipid kinase PIKfyve. Chemical inhibition of PIKfyve reduces the targeting of Dram1 to acidic endolysosomal vesicles, arresting Dram1 in multivesicular bodies, early endosomes, or non-acidified vesicles halted in their fusion with early endosomes. In conclusion, Dram1-mediated vesicle fusion requires the formation of PI(3,5)P2to deliver vesicles and their cargo to the degradative environment of the lysosome.
Extracting neuronal activity signals from microscopy recordings of contractile tissue: a cell tracking approach using B-spline Explicit Active Surfaces (BEAS)
Authors: Kazwiny Youcef , Pedrosa João , Zhang Zhiqing , Boesmans Werend , D’hooge Jan , Berghe Pieter Vanden
Published: December 2020

Ca2+imaging is a widely used microscopy technique to simultaneously study cellular activity in multiple cells. The desired information consists of cell-specific time series of pixel intensity values, in which the fluorescence intensity represents cellular activity. For static scenes, cellular signal extraction is straightforward, however multiple analysis challenges are present in recordings of contractile tissues, like those of the enteric nervous system (ENS). This layer of critical neurons, embedded within the muscle layers of the gut wall, shows optical overlap between neighboring neurons, intensity changes due to cell activity, and constant movement. These challenges reduce the applicability of classical segmentation techniques and traditional stack alignment and regions-of-interest (ROIs) selection workflows. Therefore, a signal extraction method capable of dealing with moving cells and is insensitive to large intensity changes in consecutive frames is needed.

Here we propose a b-spline active contour method to delineate and track neuronal cell bodies based on local and global energy terms. We develop both a single as well as a double-contour approach. The latter takes advantage of the appearance of GCaMP expressing cells, and tracks the nucleus’ boundaries together with the cytoplasmic contour, providing a stable delineation of neighboring, overlapping cells despite movement and intensity changes. The tracked contours can also serve as landmarks to relocate additional and manually-selected ROIs. This improves the total yield of efficacious cell tracking and allows signal extraction from other cell compartments like neuronal processes. Compared to manual delineation and other segmentation methods, the proposed method can track cells during large tissue deformations and high-intensity changes such as during neuronal firing events, while preserving the shape of the extracted Ca2+signal. The analysis package represents a significant improvement to available Ca2+imaging analysis workflows for ENS recordings and other systems where movement challenges traditional Ca2+signal extraction workflows.
The effects of development and chronic oxidative stress on telomere length in an agricultural pest moth,Helicoverpa armigera
Authors: Apirajkamol Nonthakorn (Beatrice) , Walsh Tom K , McGaughran Angela
Published: December 2020

Telomeres are repetitive sequences located at the end of chromosomes in eukaryotes that protect against loss of important sequences during the cell replication process. Telomere length (TL) shortens with every round of cell division. When a telomere becomes too short, cells can no longer proliferate and this triggers the cell apoptosis process. Apart from cell replication, the length of telomeres can be affected by factors such as sex, genetics, and stress levels. Oxidative stress in particular can cause damage to telomeres and telomere maintenance processes, resulting in TL shortening. This phenomenon occurs in humans and many vertebrates, especially endothermic species. However, the ways in which various stress types affect the TL of invertebrate species remains ambiguous.

Here, we examined the effects of development and oxidative stress on TL in the invertebrate pest moth,Helicoverpa armigera. In the former case, we extracted genomic DNA from three developmental stages (1-day old egg, 4th instar, and first-day emerged moths) and measured TL by qPCR. In the latter, we chronically exposed individuals to paraquat – an organic herbicide that induces oxidative stress - and then measured TL as per our development methodology. In addition, we examined TL in a subset of published whole genome short-read sequencing data of caterpillars and moths using the software, Computel.

In our experimental work, we found that TL inH. armigerawas significantly longer at the early stages of development and shortens in later stages. However, oxidative stress does not appear to shorten TL inH. armigerafollowing chronic exposure to paraquat. In our Computel analysis, we found that caterpillars had longer mean TL than moths but this difference was not significant due to the high variation among samples.

Collectively, our research provides new data on TL in an underrepresented group, adding new insights into the progression of TL shortening with development and the effects of oxidative stress on TL, while also more generally highlighting the value of applying complementary approaches to TL measurement.
InSegtCone: Interactive Segmentation of crystalline Cones in compound eyes
Authors: Tichit Pierre , Zhou Tunhe , Kjer Hans Martin , Dahl Vedrana Andersen , Dahl Anders Bjorholm , Baird Emily
Published: December 2020

Understanding the diversity of eyes is crucial to unravel how different animals use vision to interact with their respective environments. To date, comparative studies of eye anatomy are scarce because they often involve time-consuming or inefficient methods. X-ray micro-tomography is a promising high-throughput imaging technique that enables to reconstruct the 3D anatomy of eyes, but powerful tools are needed to perform fast conversions of anatomical reconstructions into functional eye models. We developed a computing method namedInSegtConeto automatically segment the crystalline cones in the apposition compound eyes of arthropods. Here, we describe the full auto-segmentation process, showcase its application to three different insect compound eyes and evaluate its performance. The auto-segmentation could successfully label the full individual shapes of 60%-80% of the crystalline cones, and is about as accurate and 250 times faster than manual labelling of the individual cones. We believe thatInSegtConecan be an important tool for peer scientists to enable extensive comparisons of the diversity of eyes and vision in arthropods.
Leveraging spiking deep neural networks to understand the neural mechanisms underlying selective attention
Authors: Sörensen Lynn K. A. , Zambrano Davide , Slagter Heleen A. , Bohté Sander M. , Scholte H. Steven
Published: December 2020

Spatial attention enhances sensory processing of goal-relevant information and improves perceptual sensitivity. Yet, the specific neural mechanisms underlying the effects of spatial attention on performance are still contested. Here, we examine different attention mechanisms in spiking deep convolutional neural networks. We directly contrast effects of precision (internal noise suppression) and two different gain modulation mechanisms on performance on a visual search task with complex real-world images. Unlike standard artificial neurons, biological neurons have saturating activation functions, permitting implementation of attentional gain as gain on a neuron’s input or on its outgoing connection. We show that modulating the connection is most effective in selectively enhancing information processing by redistributing spiking activity, and by introducing additional task-relevant information, as shown by representational similarity analyses. Precision only produced minor attentional effects in performance. Our results, which mirror empirical findings, show that it is possible to adjudicate between attention mechanisms using more biologically realistic models and natural stimuli.
MiMeNet: Exploring Microbiome-Metabolome Relationships using Neural Networks
Authors: Reiman Derek , Layden Brian T. , Dai Yang
Published: December 2020

The advance in microbiome and metabolome studies has generated rich omics data revealing the involvement of the microbial community in host disease pathogenesis through interactions with their host at a metabolic level. However, the computational tools to uncover these relationships are just emerging. Here, we present MiMeNet, a neural network framework for modeling microbe-metabolite relationships. Using ten iterations of 10-fold cross-validation on three paired microbiome-metabolome datasets, we show that MiMeNet more accurately predicts metabolite abundances (mean Spearman correlation coefficients increase from 0.108 to 0.309, 0.276 to 0.457, and -0.272 to 0.264) and identifies more well-predicted metabolites (increase in the number of well-predicted metabolites from 198 to 366, 104 to 143, and 4 to 29) compared to state-of-art linear models for individual metabolite predictions. Additionally, we demonstrate that MiMeNet can group microbes and metabolites with similar interaction patterns and functions to illuminate the underlying structure of the microbe-metabolite interaction network, which could potentially shed light on uncharacterized metabolites through “Guilt by Association”. Our results demonstrated that MiMeNet is a powerful tool to provide insights into the causes of metabolic dysregulation in disease, facilitating future hypothesis generation at the interface of the microbiome and metabolomics.
A Guide to Pre-Processing High-Throughput Animal Tracking Data
Authors: Gupte Pratik Rajan , Beardsworth Christine E. , Spiegel Orr , Lourie Emmanuel , Toledo Sivan , Nathan Ran , Bijleveld Allert I.
Published: December 2020

Modern, high-throughput animal tracking studies collect increasingly large volumes of data at very fine temporal scales. At these scales, location error can exceed the animal’s step size, leading to mis-estimation of key movement metrics such as speed. ‘Cleaning’ the data to reduce location errors prior to analyses is one of the main ways movement ecologists deal with noisy data, and has the advantage of being more scalable to massive datasets than more complex methods. Though data cleaning is widely recommended, and ecologists routinely consider cleaned data to be the ground-truth, inclusive uniform guidance on this crucial step, and on how to organise the cleaning of massive datasets, is still rather scarce.

A pipeline for cleaning massive high-throughput datasets must balance ease of use and computationally efficient signal vs. noise screening, in which location errors are rejected without discarding valid animal movements. Another useful feature of a pre-processing pipeline is efficiently segmenting and clustering location data for statistical methods, while also being scalable to large datasets and robust to imperfect sampling. Manual methods being prohibitively time consuming, and to boost reproducibility, a robust pre-processing pipeline must be automated.

In this article we provide guidance on building pipelines for pre-processing high-throughput animal tracking data in order to prepare it for subsequent analysis. Our recommended pipeline, consisting of removing outliers, smoothing the filtered result, and thinning it to a uniform sampling interval, is applicable to many massive tracking datasets. We apply this pipeline to simulated movement data with location errors, and also show a case study of how large volumes of cleaned data can be transformed into biologically meaningful ‘residence patches’, for quick biological inference on animal space use. We use calibration data to illustrate how pre-processing improves its quality, and to verify that the residence patch synthesis accurately captures animal space use. Finally, turning to tracking data from Egyptian fruit bats (Rousettus aegyptiacus), we demonstrate the pre-processing pipeline and residence patch method in a fully worked out example.

To help with fast implementation of standardised methods, we developed theRpackageatlastools, which we also introduce here. Our pre-processing pipeline andatlastoolscan be used with any high-throughput animal movement data in which the high data-volume combined with knowledge of the tracked individuals’ movement capacity can be used to reduce location errors. Theatlastoolsfunction is easy to use for beginners, while providing a template for further development. The use of common pre-processing steps that are simple yet robust promotes standardised methods in the field of movement ecology and leads to better inferences from data.
Bait-ER: a Bayesian method to detect targets of selection in Evolve-and-Resequence experiments
Authors: Barata Carolina , Borges Rui , Kosiol Carolin
Published: December 2020

For over a decade, experimental evolution has been combined with high-throughput sequencing techniques in so-called Evolve-and-Resequence (E&R) experiments. This allows testing for selection in populations kept in the laboratory under given experimental conditions. However, identifying signatures of adaptation in E&R datasets is far from trivial, and it is still necessary to develop more efficient and statistically sound methods for detecting selection in genome-wide data. Here, we present Bait-ER – a fully Bayesian approach based on the Moran model of allele evolution to estimate selection coefficients from E&R experiments. The model has overlapping generations, a feature that describes several experimental designs found in the literature. We tested our method under several different demographic and experimental conditions to assess its accuracy and precision, and it performs well in most scenarios. Nevertheless, some care must be taken when analysing trajectories where drift largely dominates and starting frequencies are low. We compare our method with other available software and report that ours has generally high accuracy even for trajectories whose complexity goes beyond a classical sweep model.

Furthermore, our approach avoids the computational burden of simulating an empirical null distribution, outperforming available software in terms of computational time and facilitating its use on genome-wide data.

We implemented and released our method in a new open-source software package that can be accessed athttps://github.com/mrborges23/Bait-ER.
Ruling the Roost: Avian Species Reclaim Urban Habitat During India’s COVID Lockdown
Authors: Madhok Raahil , Gulati Sumeet
Published: December 2020

As we retreated to our dwellings in the “anthropause” of spring 2020, did other species return to our urban centres? We leverage an increase in balcony birdwatching, a million eBird entries, and difference-in-difference techniques to test if avian species richness rose during India’s COVID lockdown. We find that birdwatchers in India’s 20 most populous cities observed 8-17% more species during the lockdown. Most additional observations occurred after a two-week lag, signaling greater abundance instead of improved detection. More frequent appearances of at-risk, rare, and common species were recorded, implying that making our cities more wildlife friendly can protect threatened species in addition to urban specialists. Our contributions are: 1) to isolate and estimate a causal impact of reducing human activity on avian diversity, 2) to improve the external validity of this literature in rapidly urbanizing bio-diverse developing countries, and, 3) to illustrate a method separating abundance from detection in observational avian surveys.
A vision prosthesis based on electrical stimulation of the primary visual cortex using epicortical microelectrodes
Authors: Oswalt Denise , Datta P. , Talbot N. , Mirzadeh Z. , Greger Bradley
Published: December 2020

Prostheses that can restore limited vision in the profoundly blind have been under investigation for several decades. Studies using epicortical macroelectrodes and intracortical microelectrodes have validated that electrical stimulation of primary visual cortical can serve as the basis for a vision prosthesis. However, neither of these approaches has resulted in a clinically viable vision prosthesis. Epicortical macroelectrodes required high levels of electrical current to evoke visual percepts, while intracortical microelectrodes faced challenges with longevity and stability. We hypothesized that epicortical microelectrodes could evoke visual percepts at lower currents than macroelectrodes and provide improved longevity and stability compared with intracortical microelectrodes. To test this hypotheses we implanted epicortical microelectrode arrays over the primary visual cortex of a nonhuman primate. Electrical stimulation via this array was used to evaluate the ability of epicortical microstimulation to evoke differentiable visual percepts. Visual percepts were evoked using the epicortical microelectrode array, and at electrical currents notably lower than those required to evoke visual percepts on macroelectrode arrays. The electrical current thresholds for evoking visual percepts on the epicortical microelectrode array were consistent across multiple array implants and over several months. Normal vision of light perception was not impaired by multiple array implants or chronic electrical stimulation, demonstrating that no gross visual deficit resulted from the experiments. We specifically demonstrate that epicortical microelectrode interfaces can serve as the basis for a vision prosthesis and more generally may provide an approach to evoking perception in multiple sensory modalities.

One Sentence Summary

Electrical stimulation of the brain via microelectrodes resting on the surface of primary visual cortex can evoke multiple differentiable visual percepts.
Subspace-constrained approaches to low-rank fMRI acceleration
Authors: Mason Harry T , Graedel Nadine N. , Miller Karla L. , Chiew Mark
Published: December 2020

Acceleration methods in fMRI aim to reconstruct high fidelity images from undersampled k-space, allowing fMRI datasets to achieve higher temporal resolution, reduced physiological noise aliasing, and increased statistical degrees of freedom. While low levels of acceleration are typically part of standard fMRI protocols through parallel imaging, there exists the potential for approaches that allow much greater acceleration. One such existing approach is k-t FASTER, which exploits the inherent low-rank nature of fMRI. In this paper, we present a reformulated version of k-t FASTER which includes additional L2 constraints within a low-rank framework. We evaluated the effect of three different constraints against existing low-rank approaches to fMRI reconstruction: Tikhonov constraints, low-resolution priors, and temporal subspace smoothness. The different approaches are separately tested for robustness to undersampling and thermal noise levels, in both retrospectively and prospectively-undersampled finger-tapping task fMRI data. Reconstruction quality is evaluated by accurate reconstruction of low-rank subspaces and activation maps. The use of L2 constraints was found to achieve consistently improved results, producing high fidelity reconstructions of statistical parameter maps at higher acceleration factors and lower SNR values than existing methods, but at a cost of longer computation time. In particular, the Tikhonov constraint proved very robust across all tested datasets, and the temporal subspace smoothness constraint provided the best reconstruction scores in the prospectively-undersampled dataset. These results demonstrate that regularized low-rank reconstruction of fMRI data can recover functional information at high acceleration factors without the use of any model-based spatial constraints.
Cooperative nest building in wild jackdaw pairs
Authors: Hahn Luca G. , Hooper Rebecca , McIvor Guillam E. , Thornton Alex
Published: December 2020

Animals create diverse structures, both individually and cooperatively, using materials from their environment. One striking example are the nests birds build for reproduction, which protect the offspring from external stressors such as predators and temperature, promoting reproductive success. To construct a nest successfully, birds need to make various decisions, for example regarding the nest material and their time budgets. To date, research has focused mainly on species where one sex is primarily responsible for building the nest. In contrast, the cooperative strategies of monogamous species in which both sexes contribute to nest building are poorly understood. Here we investigated the role of both sexes in nest building and fitness correlates of behaviour in wild, monogamous jackdaw pairs (Corvus monedula). We show that both partners contributed to nest building and behaved similarly, with females and males present in the nest box for a comparable duration and transporting material to the nest equally often. However, while females spent more time constructing the nest, males tended to invest more time in vigilance, potentially as a means of coping with competition for nest cavities. These findings suggest a moderate degree of division of labour, which may facilitate cooperation. Moreover, some aspects of behaviour were related to proxies of reproductive success (lay date and egg volume). Females that contributed relatively more to bringing material laid earlier clutches and pairs that spent less time together in the nest box had larger eggs. Thus, selection pressures may act on how nest building pairs spend their time and cooperatively divide the labour. We conclude that cooperative nest building in birds could be associated with monogamy and obligate biparental care, and provides a vital but relatively untapped context through which to study the evolution of cooperation.

Highlights

In wild monogamous jackdaws, mates behaved similarly and cooperated to build their nest.

Females built more and called more frequently; males tended to be more vigilant.

Females that contributed relatively more to transporting nest material laid earlier clutches.

Pairs that spent more time together in the nest box had smaller eggs.

Cooperation may be crucial in light of obligate biparental care and nest site competition.