bluuebunny/crossref_metadata_2025 huggingface dataset:
Total correlation explanation of toxic metal concentrations and physiological biomarkers amongst NHANES participants
Authors: Rooney James , Böse-O’Reilly Stephan , Rakete Stefan
Published: October 2021

Introduction

Unravelling the health effects of multiple pollutants presents scientific and computational challenges. CorEx is an unsupervised learning algorithm that can efficiently discover multiple latent factors in highly multivariate datasets. Here, we used the CorEx algorithm to perform a hypothesis free analysis of demographic, biochemical, and toxic metal biomarker data.

Methods

Our data included 77 variables from 2,750 adult participants of the National Health and Nutrition Examination Survey (NHANES 2015-2016). We used an implementation of the CorEx algorithm designed to deal with the features of bioinformatic datasets including mixed data-types. Models were fit for a range of possible latent variables and the best fit model was selected as that which resulted in the largest Total Correlation (TC) after adjustment for the number of parameters. Successive layers of CorEx were run to discovered hierarchical data structure.

Results

The CorEx algorithm identified 20 variable clusters at the first layer. For the majority clusters, the associations between variables were consistent with known associations – e.g. gender and the hormones, estradiol and testosterone were included in the first cluster; blood organic mercury and blood total mercury were grouped in cluster 4, and cluster 6 included the liver function enzymes ALT, AST and GGT. At the second layer, 3 branches of were identified reflecting hierarchical structure. The first branch included numerous physiological biomarkers and several exogenous biomarkers. The second branch included a number endogenous and exogenous variables previously associated with hypertension, while the third branch included mercury biomarkers and some related endogenous biomarkers.

Discussion

We have demonstrated the CorEx algorithm as a useful tool for hypothesis free exploration of a biomedical dataset. This work extends previous implementations of CorEx by allowing mixed data-types to be modelled and the results showed that CorEx detected meaningful hierarchical structure. CorEx may facilitate exploration of novel datasets in future.
Risk-benefit analysis of the AstraZeneca COVID-19 vaccine in Australia using a Bayesian network modelling framework
Authors: Lau Colleen L , Mayfield Helen J , Sinclair Jane E , Brown Samuel J , Waller Michael , Enjeti Anoop K , Baird Andrew , Short Kirsty , Mengersen Kerrie , Litt John
Published: October 2021

Thrombosis and Thromobocytopenia Syndrome (TTS) has been associated with the AstraZencea (AZ) COVID-19 vaccine. Australia has reported low TTS incidence of <3/100,000 after the first dose, with case fatality rate (CFR) of 5-6%. Risk-benefit analysis of vaccination has been challenging because of rapidly evolving data, changing levels of transmission, and age-specific variation in rates of TTS, COVID-19, and CFR. We aim to optimise risk-benefit analysis by developing a model that enables inputs to be updated rapidly as evidence evolves. A Bayesian network was used to integrate local and international data, government reports, published literature and expert opinion. The model estimates probabilities of outcomes under different scenarios of age, sex, low/medium/high transmission (0.05%/0.45%/5.76% of population infected over 6 months), SARS-CoV-2 variant, vaccine doses, and vaccine effectiveness. We used the model to compare estimated deaths from vaccine-associated TTS with i) COVID-19 deaths prevented under different scenarios, and ii) deaths from COVID-19 related atypical severe blood clots (cerebral venous sinus thrombosis & portal vein thrombosis). For a million people aged ≥70 years where 70% received first dose and 35% received two doses, our model estimated <1 death from TTS, 25 deaths prevented under low transmission, and >3000 deaths prevented under high transmission. Risks versus benefits varied significantly between age groups and transmission levels. Under high transmission, deaths prevented by AZ vaccine far exceed deaths from TTS (by 8 to >4500 times depending on age). Probability of dying from COVID-related atypical severe blood clots was 58-126 times higher (depending on age and sex) than dying from TTS. To our knowledge, this is the first example of the use of Bayesian networks for risk-benefit analysis for a COVID-19 vaccine. The model can be rapidly updated to incorporate new data, adapted for other countries, extended to other outcomes (e.g., severe disease), or used for other vaccines.

HIGHLIGHTS

AZ vaccination risk-benefit analysis must consider age/community transmission level

AZ vaccine benefits far outweigh risks in older age groups and during high transmission

AZ vaccine-associated TTS lower fatality than COVID-related atypical blood clots

Bayesian networks utility for risk-benefit analysis of rapidly evolving situations

BNs allow integrating multiple data sources when large datasets are not available
Non-Markovian modelling highlights the importance of age structure on Covid-19 epidemiological dynamics
Authors: Reyné Bastien , Richard Quentin , Noûs Camille , Selinger Christian , Sofonea Mircea T. , Djidjou-Demasse Ramsès , Alizon Samuel
Published: October 2021

The Covid-19 pandemic outbreak was followed by a huge amount of modelling studies in order to rapidly gain insights to implement the best public health policies. Most of these compartmental models involved ordinary differential equations (ODEs) systems. Such a formalism implicitly assumes that the time spent in each compartment does not depend on the time already spent in it, which is at odds with the clinical data. To overcome this “memoryless” issue, a widely used solution is to increase and chain the number of compartments of a unique reality (e.g. have infected individual move between several compartments). This allows for greater heterogeneity and thus be closer to the observed situation, but also tends to make the whole model more difficult to apprehend and parameterize. We develop a non-Markovian alternative formalism based on partial differential equations (PDEs) instead of ODEs, which, by construction, provides a memory structure for each compartment thereby allowing us to limit the number of compartments. We apply our model to the French 2021 SARS-CoV-2 epidemic and, while accounting for vaccine-induced and natural immunity, we analyse and determine the major components that contributed to the Covid-19 hospital admissions. The results indicate that the observed vaccination rate alone is not enough to control the epidemic, and a global sensitivity analysis highlights a huge uncertainty attributable to the age-structured contact matrix. Our study shows the flexibility and robustness of PDE formalism to capture national COVID-19 dynamics and opens perspectives to study medium or long-term scenarios involving immune waning or virus evolution.
Genomic diversity of SARS-CoV-2 in Pakistan during fourth wave of pandemic
Authors: Umair Massab , Ikram Aamer , Rehman Zaira , Haider Adnan , Badar Nazish , Ammar Muhammad , Ahad Abdul , Suleman Rana , Salman Muhammad
Published: October 2021

The emergence of different variants of concern of SARS-CoV-2 has resulted in upsurges of COVID positive cases around the globe. Pakistan is also experiencing fourth wave of COVID-19 with increasing number of positive cases. In order to understand the genomic diversity of circulating SARS-CoV-2 strains during fourth wave of pandemic in Pakistan, the current study was designed. The samples from 89 COVID-19 positive patients were subjected to whole genome sequencing using GeneStudio S5. The results showed that 99% (n=88) of isolates belonged to delta variant and only one isolate belonged to alpha variant. Among delta variant cases 26.1% (n=23) isolates were showing B.1.617.2 while 74% of isolates showing AY.4 lineage. Islamabad was found to be the most affected city with 54% (n=48) of cases, followed by Karachi (28%, n=25), and Rawalpindi (10%, n=9). AY.4 has slight difference in mutation profile compared to B.1.617.2. E156del, G142D and V26I mutations in spike and T181I in NSP6 were present in B.1.617.2 but not in AY.4. Interestingly, A446V mutation in NSP4 has been only observed in AY.4. The current study highlights the circulation of primarily delta variant (B.1.617.2 and AY.4) during fourth wave of pandemic in Pakistan.
Longitudinal changes and key determinants of meeting WHO recommended levels of physical activity during the COVID-19 pandemic in a UK-based sample: Findings from the HEBECO Study
Authors: Mitchell JJ , Dicken SJ , Kale D , Herbec A , Beard E , Shahab L
Published: October 2021

Background

The COVID-19 pandemic has seen government enforced restrictions on movement, with ‘stay-at-home’ orders in place for a second and third time in many nations. Such restrictions have altered physical activity (PA) habits. This study aimed to evaluate longitudinal trends in PA in a self-selected UK-based sample and the key predictors of these trends.

Methods

From 23 April 2020 to 30 January 2021, an online survey collected detailed measures of PA engagement in a sample of 1,947 UK-based adults. Generalised estimating equations (GEE) were fitted to explore trends in PA engagement over time, and how sociodemographic, health, lifestyle and contextual factors impacted participant’s attainment of Word Health Organisation (WHO) recommended levels of PA (constituting muscle strengthening activity (MSA), and moderate or vigorous PA (MVPA)).

Results

Attainment of WHO recommended levels of total PA showed a decline. While one in five achieved the recommended levels of total PA in the first UK lockdown in April-June 2020 (19.5%, 95%, CI 17.8-21.3%) and a similar proportion in June-July 2020 (17.7%, 95%CI 16.1-19.5%), this reduced significantly during the period of eased restrictions in August-September 2020 (15.2%, 95%CI 13.7-16.9%) and the second UK lockdown in November 2020-January 2021 (14.1%, 95%CI 12.6-15.9%). The same trends were observed for MSA and MVPA individually. Better quality of life, higher socioeconomic position and higher pre-COVID-19 PA levels were associated with meeting WHO recommended PA levels, while having overweight or obesity, a limiting chronic health condition, or being in strict isolation showed the inverse associations. Time-specific associations with MSA or MVPA were observed for gender, age, ethnicity, and other health behaviours.

Conclusion

Among a self-selected sample of UK-based adults, there were reductions in PA levels throughout the first UK lockdown without reversal during the ensuing period. Based on observed associations of reduced PA with socioeconomic and health-related indices, such changes may point towards deepening health inequities during the pandemic.
The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus
Authors: Nardin Michele , Kaefer Karola , Csicsvari Jozsef
Published: October 2021

Hippocampal and neocortical neural activity is modulated by the position of the individual in space. While hippocampal neurons provide the basis for a spatial map, prefrontal cortical neurons generalize over environmental features. Whether these generalized representations result from a bidirectional interaction with, or are mainly derived from hippocampal spatial representations is not known. By examining simultaneously recorded hippocampal and medial prefrontal neurons, we observed that prefrontal spatial representations show a delayed coherence with hippocampal ones. We also identified subpopulations of cells in the hippocampus and medial prefrontal cortex that formed functional cross-area couplings; these resembled the optimal connections predicted by a probabilistic model of spatial information transfer and generalization. Moreover, cross-area couplings were strongest and had the shortest delay preceding spatial decision-making. Our results suggest that generalized spatial coding in the medial prefrontal cortex is inherited from spatial representations in the hippocampus, and that the routing of information can change dynamically with behavioral demands.
Gamma Entrainment Improves Synchronization Deficits in Dementia Patients
Authors: Lahijanian Mojtaba , Aghajan Hamid , Vahabi Zahra , Afzal Arshia
Published: October 2021

Non-invasive gamma entrainment has shown promising results in alleviating cognitive symptoms of Alzheimer’s disease in mice and humans. In this study, we examine improvements in the synchronization characteristics of the brain’s oscillations induced by 40Hz auditory stimulation based on electroencephalography data recorded from a group of dementia patients. We observed that when the quality of entrainment surpasses a certain level, several indicators of brain synchronization significantly improve. Specifically, the entrained oscillatory activity maintains temporal phase stability in the frontal, parietal, and occipital regions, and persistent spatial phase coupling between them. In addition, notable theta-gamma phase-amplitude coupling is observed in these areas. Interestingly, a high theta power at rest predicts the quality of entrainment. We identify differentiating attributes of temporal/spatial synchronization and cross-frequency coupling in the data of two groups with entrained and non-entrained responses which point to enhanced network synchronization caused by entrainment and can explain its potential therapeutic effects.
SomaticSiMu: A mutational signature simulator
Authors: Chen David , Randhawa Gurjit S. , Soltysiak Maximillian P.M. , de Souza Camila P.E. , Kari Lila , Singh Shiva M. , Hill Kathleen A.
Published: October 2021

SomaticSiMu is an in silico simulator of single and double base substitutions, and single base insertions and deletions in an input genomic sequence to mimic mutational signatures. SomaticSiMu outputs simulated DNA sequences and mutational catalogues with imposed mutational signatures. The tool is the first mutational signature simulator featuring a graphical user interface, control of mutation rates, and built-in visualization tools of the simulated mutations. Simulated datasets are useful as a ground truth to test the accuracy and sensitivity of DNA sequence classification tools and mutational signature extraction tools under different experimental scenarios. The reliability of SomaticSiMu was affirmed by 1) supervised machine learning classification of simulated sequences with different mutation types and burdens, and 2) mutational signature extraction from simulated mutational catalogs.

Availability and Implementation

SomaticSiMu is written in Python 3.8.3. The open-source code, documentation, and tutorials are available at https://github.com/HillLab/SomaticSiMu under the terms of the Creative Commons Attribution 4.0 International License.

Contact

khill22@uwo.ca

Supplementary information

Supplementary data are available at Bioinformatics online.
Transcriptomic analysis of DNA damage response in zebrafish embryos under simulated microgravity
Authors: Barua Subhrajit , Komissarov Aleksey , Kaur Harpreet , Brodsky Elia
Published: October 2021

Space is an extremely hostile environment. Traveling to space has numerous effects on the body of the astronauts at a molecular level. As space agencies prepare for long-term missions, it becomes important to investigate these problems and address them. Thus, in the current study, we assessed the impact of simulated microgravity on the basic pathways especially DNA damage response. We identified a total of 7542 significantly differentially expressed genes. Out of these genes, 4504 were found to be up-regulated while 3038 were down-regulated in the simulated microgravity group in comparison to controls. Pathway enrichment analysis revealed that simulated microgravity has an effect on vital basic biological processes like DNA damage repair, peptide transport, and metabolism. To explore if the same pathways were also altered in humans, we explored the NASA twin study data and found that DDR was also significantly affected in the astronaut but due to ionizing radiation. Upon further investigation, we found that 62 genes belonging to the DDR pathway were mutually differentially expressed in Scott Kelly and the zebrafish embryos. However, there were 29 significantly differentially expressed genes belonging to the DDR pathway in zebrafish embryos that were not found to be differentially expressed in Scott Kelly. Out of these 29 genes, 14 were specific to zebrafish. Upon further investigation, we found that the DDR pathway is affected differently in simulated microgravity as compared to ionizing radiation. These observations provide a preliminary look into the difference in DDR induced by the different factors of spaceflight.
Normalizing automatic spinal cord cross-sectional area measures
Authors: Bédard S. , Cohen-Adad J.
Published: October 2021

Spinal cord cross-sectional area (CSA) is a relevant biomarker to assess spinal cord atrophy in various neurodegenerative diseases. However, the considerable inter-subject variability among healthy participants currently limits its usage. Previous studies explored factors contributing to the variability, yet the normalization models were based on a relatively limited number of participants (typically < 300 participants), required manual intervention, and were not implemented in an open-access comprehensive analysis pipeline. Another limitation is related to the imprecise prediction of the spinal levels when using vertebral levels as a reference; a question never addressed before in the search for a normalization method. In this study we implemented a method to measure CSA automatically from a spatial reference based on the central nervous system (the pontomedullary junction, PMJ), we investigated various factors to explain variability, and we developed normalization strategies on a large cohort (N=804).

Cervical spinal cord CSA was computed on T1w MRI scans for 804 participants from the UK Biobank database. In addition to computing cross-sectional at the C2-C3 vertebral disc, it was also measured at 64 mm caudal from the PMJ. The effect of various biological, demographic and anatomical factors was explored by computing Pearson’s correlation coefficients. A stepwise linear regression found significant predictors; the coefficients of the best fit model were used to normalize CSA.

The correlation between CSA measured at C2-C3 and using the PMJ was y = 0.98x + 1.78 (R2 = 0.97). The best normalization model included thalamus volume, brain volume, sex and interaction between brain volume and sex. With this model, the coefficient of variation went down from 10.09% (without normalization) to 8.59%, a reduction of 14.85%.

In this study we identified factors explaining inter-subject variability of spinal cord CSA over a large cohort of participants, and developed a normalization model to reduce the variability. We implemented an approach, based on the PMJ, to measure CSA to overcome limitations associated with the vertebral reference. This approach warrants further validation, especially in longitudinal cohorts. The PMJ-based method and normalization models are readily available in the Spinal Cord Toolbox.
Predicting the Effects of Per- and Polyfluoroalkyl Substance Mixtures on Peroxisome Proliferator-Activated Receptor Alpha Activity in Vitro
Authors: Nielsen Greylin , Heiger-Bernays Wendy J. , Schlezinger Jennifer J. , Webster Thomas F.
Published: October 2021

Human exposure to per- and polyfluoroalkyl substances (PFAS) is ubiquitous, with mixtures of PFAS detected in drinking water, food, household dust, and other exposure sources. Animal toxicity studies and human epidemiology indicate that PFAS may act through shared mechanisms including activation of peroxisome proliferator activated receptor α (PPARα). However, the effect of PFAS mixtures on human relevant molecular initiating events remains an important data gap in the PFAS literature. Here, we tested the ability of modeling approaches to predict the effect of diverse PPARα ligands on receptor activity using Cos7 cells transiently transfected with a full length human PPARα (hPPARα) expression construct and a peroxisome proliferator response element-driven luciferase reporter. Cells were treated for 24 hours with two full hPPARα agonists (pemafibrate and GW7647), a full and a partial hPPARα agonist (pemafibrate and mono(2-ethylhexyl) phthalate), or a full hPPARα agonist and a competitive antagonist (pemafibrate and GW6471). Receptor activity was modeled with three additive approaches: effect summation, relative potency factors (RPF), and generalized concentration addition (GCA). While RPF and GCA accurately predicted activity for mixtures of full hPPARα agonists, only GCA predicted activity for full and partial hPPARα agonists and a full agonist and antagonist. We then generated concentration response curves for seven PFAS, which were well-fit with three-parameter Hill functions. The four perfluorinated carboxylic acids (PFCA) tended to act as full hPPARα agonists while the three perfluorinated sulfonic acids (PFSA) tended to act as partial agonists that varied in efficacy between 28-67% of the full agonist, positive control level. GCA and RPF performed equally well at predicting the effects of mixtures with three PFCAs, but only GCA predicted experimental activity with mixtures of PFSAs and a mixture of PFCAs and PFSAs at ratios found in the general population. We conclude that of the three approaches, GCA most accurately models the effect of PFAS mixtures on hPPARα activity in vitro.

Highlights

Perfluorinated carboxylic acids are full human PPARα agonists

Perfluorinated sulfonic acids are partial human PPARα agonists

GCA predicts human PPARα activity for mixtures of full and partial agonists

GCA predicts human PPARα activity for mixtures of agonists and competitive antagonists

GCA accurately predicts human PPARα activity in response to PFAS mixtures
Oral and injected tamoxifen alter adult hippocampal neurogenesis in female and male mice
Authors: Smith Bryon M. , Saulsbery Angela I. , Sarchet Patricia , Devasthali Nidhi , Einstein Dalia , Kirby Elizabeth D.
Published: October 2021

Inducible Cre recombinase facilitates temporal control of genetic recombination in numerous transgenic model systems, a feature which has made it a popular tool for studies of adult neurogenesis. One of the most common forms of inducible Cre, CreERT2, requires activation by the synthetic estrogen tamoxifen (TAM) to initiate recombination of LoxP-flanked sequences. To date, most studies deliver TAM via intraperitoneal injection. But the introduction of TAM-infused commercial chows has recently expanded the possible modes of TAM delivery. Despite the widespread use of TAM-inducible genetic models in adult neurogenesis research, the comparative efficiency and off-target effects of TAM administration protocols is surprisingly infrequently studied. Here we compare a standard, 5 day TAM injection regimen with voluntary consumption of TAM-infused chow. First, we used adult NestinCreERT2;Rosa-LoxP-STOP-LoxP-EYFP reporter mice to show that 2 weeks of TAM chow and 5 days of injections led to LoxP recombination in a similar phenotypic population of neural stem and progenitor cells in the adult dentate gyrus. However, TAM chow resulted in substantially less overall recombination than injections. TAM administration also altered adult neurogenesis, but in different ways depending on administration route: TAM injection disrupted neural progenitor cell proliferation 3 weeks after TAM, whereas TAM chow increased neuronal differentiation of cells generated during the diet period. These findings provide guidance for selection of TAM administration route and appropriate controls in adult neurogenesis studies using TAM-inducible Cre mice. They also highlight the need for better understanding of off-target effects of TAM in other neurological processes and organ systems.
An internal expectation guidesDrosophilaegg-laying decisions
Authors: Vijayan Vikram , Wang Zikun , Chandra Vikram , Chakravorty Arun , Li Rufei , Sarbanes Stephanie L. , Akhlaghpour Hessameddin , Maimon Gaby
Published: October 2021

When presented with two egg-laying substrates,Drosophilalay most of their eggs on the option with higher relative value. How do flies make this relative-value decision? Might the strategy they use allow them to choose the best option even when they experience substrates with a more complex spatiotemporal profile than in canonical two-choice paradigms? We measuredDrosophilaegg-laying behavior in diverse substrate environments. In all cases, we found that flies dynamically increase or decrease their egg-laying rates as they explore substrates for a deposition site so as to target eggs to the best, recently visited option. Visiting the best option typically led to a strong reduction in egg laying on other substrates for several minutes, with this timescale varying across fly strains. Our data support a model in which flies compare the value of the current substrate with an internally constructedexpectationon the value of available options to regulate the likelihood of laying an egg. We show that dopamine-neuron activity is critical for learning and/or expressing this expectation, similar to its role in certain tasks in vertebrates. Integrating sensory experiences over minutes to generate an internal sense of the quality of available options, i.e., forming an expectation, allows flies to use a dynamic reference point for judging the current substrate and might be a general way in which decisions are made, even beyond flies and egg laying.
Blood variation implicates respiratory limits on elevational ranges of Andean birds
Authors: Linck Ethan B. , Williamson Jessie L. , Bautista Emil , Beckman Elizabeth J. , Benham Phred M. , DuBay Shane G. , Flores L. Monica , Gadek Chauncey R. , Johnson Andrew B. , Jones Matthew R. , Núñez-Zapata Jano , Quiñonez Alessandra , Schmitt C. Jonathan , Susanibar Dora , Jorge Tiravanti C. , Verde-Guerra Karen , Wright Natalie A. , Valqui Thomas , Storz Jay F. , Witt Christopher C.
Published: October 2021

The extent to which species ranges reflect intrinsic physiological tolerances is a major, unsolved question in evolutionary ecology. To date, consensus has been hindered by the limited tractability of experimental approaches across most of the tree of life. Here, we apply a macrophysiological approach to understand how hematological traits related to oxygen transport shape elevational ranges in a tropical biodiversity hotspot. Along Andean elevational gradients, we measured traits that affect blood oxygen-carrying capacity—total and cellular hemoglobin concentration and hematocrit—for 2,355 individuals of 136 bird species. We used these data to evaluate the influence of hematological traits on elevational ranges. First, we asked whether hematological plasticity is predictive of elevational range breadth. Second, we asked whether variance in hematological traits changed as a function of distance from the midpoint of the elevational range. We found that the correlation between hematological plasticity and elevational range breadth was slightly positive, consistent with a facilitative role for plasticity in elevational range expansion. We further found reduced local variation in hematological traits near elevational range limits and at high elevations, patterns consistent with intensified natural selection, reduced effective population size, or compensatory changes in other cardiohematological traits with increasing distance from species-specific optima for oxygen availability. Our findings suggest that constraints on hematological plasticity and local genetic adaptation to oxygen availability promote the evolution of the narrow elevational ranges that underpin tropical montane biodiversity.
Time-series Multi-spectral Imaging in Soybean for Improving Biomass and Genomic Prediction Accuracy
Authors: Sakurai Kengo , Toda Yusuke , Kajiya-Kanegae Hiromi , Ohmori Yoshihiro , Yamasaki Yuji , Takahashi Hirokazu , Takanashi Hideki , Tsuda Mai , Tsujimoto Hisashi , Kaga Akito , Nakazono Mikio , Fujiwara Toru , Iwata Hiroyoshi
Published: October 2021

Multi-spectral (MS) imaging enables the measurement of characteristics important for increasing the prediction accuracy of genotypic and phenotypic values for yield-related traits. In this study, we evaluated the potential application of temporal MS imaging for the prediction of above-ground biomass (AGB) and determined which developmental stages should be used for accurate prediction in soybean. Field experiments with 198 accessions of soybean were conducted with four different irrigation levels. Five vegetation indices (VIs) were calculated using MS images from soybean canopies from early to late growth stages. To predict the genotypic values of AGB, VIs at the different growth stages were used as secondary traits in a multi-trait genomic prediction. The accuracy of the prediction model increased starting at an early stage of growth (31 days after sowing). To predict phenotypic values of AGB, we employed multi-kernel genomic prediction. Consequently, the prediction accuracy of phenotypic values reached a maximum at a relatively early growth stage (38 days after sowing). Hence, the optimal timing for MS imaging may depend on the irrigation levels.
Evaluating metagenomic assembly approaches for biome-specific gene catalogues
Authors: Delgado Luis Fernando , Andersson Anders F.
Published: October 2021

For many environments, biome-specific microbial gene catalogues are being recovered using shotgun metagenomics followed by assembly and gene-calling on the assembled contigs. The assembly can be conducted either by individually assembling each sample or by co-assembling reads from all the samples. The co-assembly approach can potentially recover genes that display too low abundance to be assembled from individual samples. On the other hand, combining samples increases the risk of mixing data from closely related strains, which can hamper the assembly process. In this respect, assembly on individual samples followed by clustering of (near) identical genes is likely preferable. Thus, both approaches have pros and cons and it remains to be evaluated which assembly strategy is most effective. Here, we have evaluated three assembly strategies for generating gene catalogues from metagenomes using a dataset of 124 samples from the Baltic Sea: 1) assembly on individual samples followed by clustering of the resulting genes, 2) co-assembly on all samples, and 3) mix-assembly, combining individual and co-assembly. The mix-assembly approach resulted in a more extensive non-redundant gene set than the other approaches, and with more genes predicted to be complete and that could be functionally annotated. The mix-assembly consists of 67 million genes (Baltic Sea gene set; BAGS) that have been functionally and taxonomically annotated. The majority of the BAGS genes are dissimilar (<95% amino acid identity) to the Tara Oceans gene dataset, and hence BAGS represents a valuable resource for brackish water research.

IMPORTANCE

Several ecosystem types, such as soils and oceans, are studied through metagenomics. It allows the analysis of genetic material of the microbes within a sample without the need for cultivation. When performing the DNA sequencing with an instrument that generates short sequence reads, these reads need to be assembled in order to obtain more complete gene sequences. In this paper, we have evaluated three strategies for assembling metagenome sequences using a large metagenomic dataset from the Baltic Sea. The method that we call mix-assembly generated the greatest number of non-redundant genes and the largest fraction of genes that were predicted to be complete. The resulting gene catalogue will serve as an important resource for brackish water research. We believe this method to be efficient also for generating gene catalogs for other biomes.
Exhaled particles from nanometre to millimetre and their origin in the human respiratory tract
Authors: Bagheri Gholamhossein , Schlenczek Oliver , Turco Laura , Thiede Birte , Stieger Katja , Kosub Jana-Michelle , Pöhlker Mira L. , Pöhlker Christopher , Moláček Jan , Scheithauer Simone , Bodenschatz Eberhard
Published: October 2021

Detailed knowledge of the properties of exhaled particles from the human respiratory tract for all genders and ages is essential to determine the modes of transmission of airborne diseases. This applies not only to the current COVID-19 pandemic, but also to many others, be it measles, seasonal influenza or tuberculosis. To date, there are no data on the individual-specific concentrations and sizes of exhaled particles over the entire size range from nanometre to millimetre. Here we present a comprehensive data set, measured by particle size spectrometry and in-line holography covering the entire size range from 132 healthy volunteers aged 5 to 80 years for a defined set of breathing and vocalisation activities. We find age to have a large effect on small particle concentrations (<5 µm), doubling in children during adolescence and in adults over a 30-year period. In contrast, gender, body mass index, smoking or exercise habits have no discernible influence. Particles >20 µm show on average no measurable dependence on the type of vocalisation with the exception of shouting. We show evidence that particles <5 µm mainly originate in the lower respiratory tract, 5-15 µm in the larynx/pharynx, and >15 µm in the oral cavity.
COVID-19 mortality in Italy varies by patient age, sex and pandemic wave
Authors: Minnai Francesca , De Bellis Gianluca , Dragani Tommaso A. , Colombo Francesca
Published: October 2021

Background

SARS-CoV-2 has caused a worldwide epidemic of enormous proportions, which resulted in different mortality rates in different countries for unknown reasons.

Aim

We aimed to evaluate which independent parameters are associated with risk of mortality from COVID-19 in a series that includes all Italian cases, ie, more than 4 million individuals infected with the SARS-CoV-2 coronavirus.

Methods

We analyzed factors associated with mortality using data from the Italian national database of SARS-CoV-2-positive cases, including more than 4 million cases, >415 thousand hospitalized for coronavirus disease-19 (COVID-19) and >127 thousand deceased. For patients for whom age, sex and date of infection detection were available, we determined the impact of these variables on mortality 30 days after the date of diagnosis or hospitalization.

Results

Multivariable Cox analysis showed that each of the analyzed variables independently affected COVID-19 mortality. Specifically, in the overall series, age was the main risk factor for mortality, with HR >100 in the age groups older than 65 years compared with a reference group of 15-44 years. Male sex presented an excess risk of death (HR = 2.1; 95% CI, 2.0–2.1). Patients infected in the first pandemic wave (before 30 June 2020) had a greater risk of death than those infected later (HR = 2.7; 95% CI, 2.7–2.8).

Conclusions

In a series of all confirmed SARS-CoV-2-infected cases in an entire European nation, elderly age was by far the most significant risk factor for COVID-19 mortality, confirming that protecting the elderly should be a priority in pandemic management. Male sex and being infected during the first wave were additional risk factors associated with COVID-19 mortality.
COVID-19 Neutralizing Antibody Surveillance Testing for Fully Vaccinated Individuals During Delta Variant Spread
Authors: Pan Jing , Li Zhigang , Wang Lin , Szymanski Joshua , Romano Maria , Yin Dylan , Wang Allen , Small Thomas , Zou Zhiying , Li Jing , Witham Greg , Wang Li , Zhang Yubei , Qi Kai , Yin Ray
Published: October 2021

We recently performed 568 rapid neutralizing antibody (NAb) tests on 164 fully vaccinated individuals who received either Moderna or Pfizer COVID-19 vaccine regimens over 7 weeks. The NAb levels against the wild type (WA1/2020), Delta, and Kappa variants were measured and compared. Depending on each individual’s medical condition and vaccination status, the NAb levels for most of the fully vaccinated people decreased within 2-6 months, while a small number of individuals either generated non-detectable amount of NAbs after full vaccination (e.g., immunocompromised), or had high NAb levels lasting beyond 6 months. Since the NAb levels vary significantly among different individuals and decrease over time, the deployment of a low-cost rapid test to monitor NAb levels against both the wild type and emerging variants among fully vaccinated individuals can play a very crucial role to control the current pandemic. Our study provides an example of using such a rapid NAb test to fill this currently unmet medical need.
Forgoing healthcare during the COVID-19 pandemic in Geneva, Switzerland – a cross-sectional population-based study
Authors: Menon Lakshmi Krishna , Richard Viviane , de Mestral Carlos , Baysson Helene , Wisniak Ania , Guessous Idris , Stringhini Silvia ,   for the Specchio-COVID19 Study Group
Published: October 2021

Background

Health systems around the world continue to navigate through operational challenges surfaced by the COVID-19 pandemic; these have implications for access to healthcare. In this study, we estimate the prevalence and reasons for forgoing healthcare during the pandemic in Geneva, Switzerland; a country with a universal and mandatory private health insurance coverage.

Methods

Participants from a randomly selected population-based sample of the adult population living in the Canton of Geneva completed an online socio-demographic and lifestyle questionnaire between November 2020 and January 2021. The prevalence and reasons for forgoing healthcare since the beginning of the COVID-19 pandemic were examined descriptively, and logistic regression models were used to assess determinants for forgoing healthcare.

Results

The study included 5,397 participants, among which 8.0% reported having forgone healthcare since the beginning of the COVID-19 pandemic; participants with a disadvantaged financial situation (OR=2.04; 95% CI: 1.56-2.65), and those reporting an average (OR=2.55; 95% CI: 1.94-3.32) or poor health (OR=4.40; 95% CI: 2.40-7.68) were more likely to forgo healthcare. The most common reasons to forgo healthcare were appointment cancellations by healthcare providers (53.9%), fear of infection (35.3%), and personal organizational issues (11.1%).

Conclusion

Our paper highlights the effects of the COVID-19 pandemic on access to healthcare and identifies population sub-groups at-risk for forgoing healthcare. These results necessitate public health efforts to ensure equitable and accessible healthcare as the COVID-19 pandemic continues.

Highlights

8% of the Geneva, Switzerland, adults renounced healthcare in the COVID-19 pandemic

Main forgoing healthcare reasons are appointment cancellation and fear of infection

Underprivileged participants with poor health are more likely to forgo healthcare
Initial SARS-CoV-2 viral load is associated with disease severity: a retrospective cohort study
Authors: Souverein Dennis , van Stralen Karlijn , van Lelyveld Steven , van Gemeren Claudia , Haverkort Milly , Snijders Dominic , Soetekouw Robin , Kapteijns Erik , de Jong Evelien , Hermanides Gonneke , Aronson Sem , Wagemakers Alex , Euser Sjoerd
Published: October 2021

Background

We aimed to assess the association between initial SARS-CoV-2 viral load and the subsequent hospital and intensive care unit (ICU) admission and overall survival.

Methods

All persons with a positive SARS-CoV-2 RT-PCR result from a combined nasopharyngeal (NP) and oropharyngeal (OP) swab (first samples from unique persons only) that was collected between March 17, 2020, and March 31, 2021, in Public Health testing facilities in the region Kennemerland, province of North Holland, the Netherlands were included. Data on hospital (and ICU) admission were collected from the two large teaching hospitals in the region Kennemerland.

Results

In total, 20,207 SARS-CoV-2 positive persons were included in this study, of whom 310 (1.5%) were hospitalized in a regional hospital within 30 days of their positive SARS-CoV-2 RT-PCR test. When persons were categorized in three SARS-CoV-2 viral load groups, the high viral load group (Cp < 25) was associated with an increased risk of hospitalization as compared to the low viral load group (Cp > 30) (ORadjusted [95%CI]: 1.57 [1.11-2.26], p-value=0.012), adjusted for age and sex. The same association was seen for ICU admission (ORadjusted [95%CI]: 7.06 [2.15-43.57], p-value=0.007). For a subset of 243 of the 310 hospitalized patients, the association of initial SARS-CoV-2 Cp-value with in-hospital mortality was analyzed. The initial SARS-CoV-2 Cp-value of the 17 patients who deceased in the hospital was significantly lower (indicating a higher viral load) compared to the 226 survivors: median Cp-value [IQR]: 22.7 [3.4] vs. 25.0 [5.2], OR[95%CI]: 0.81 [0.68-0.94], p-value = 0.010.

Conclusions

Our data show that higher initial SARS-CoV-2 viral load is associated with an increased risk of hospital admission, ICU admission, and in-hospital mortality. We believe that our findings emphasize the added value of reporting SARS-CoV-2 viral load based on Cp-values to identify persons who are at the highest risk of adverse outcomes such as hospital or ICU admission and who therefore may benefit from more intensive monitoring.
ContaTester: Fast cross-contamination estimation and identification for large human sequencing cohorts
Authors: Delafoy Damien , Mercier Jonathan , Larsonneur Elise , Wiart Nicolas , Sandron Florian , Mejean Thomas , Meslage Stéphane , Daian Delphine , Olaso Robert , Boland Anne , Deleuze Jean-François , Meyer Vincent
Published: October 2021

Background

Interest in genomic medicine for human health studies and clinical applications is rapidly increasing. Clinical applications require contamination-free samples to avoid misleading results and provide a sound basis for diagnosis.

Results

Here we present ContaTester, a tool which requires only allele balance information gathered from a VCF file to detect cross-contamination in germline human DNA samples. Based on a regression model of allele balance distribution, ContaTester allows fast checking of contamination levels for single samples or large cohorts (less than two minutes per sample). We demonstrate the efficiency of ContaTester using experimental validations: ContaTester shows similar results to methods requiring alignment data but with a significantly reduced storage footprint and less computation time. Additionally, for contamination levels above 5%, ContaTester can identify contaminants across a cohort, providing important clues for troubleshooting and quality assessment.

Conclusions

ContaTester estimates contamination levels from VCF files generated from whole genome sequencing normal sample and provides reliable contaminant identification for cohorts or experimental batches.
Capillary stall quantification from optical coherence tomography angiogram maximum intensity projections
Authors: Fruekilde Signe K. , Jiménez Eugenio G. , Drasbek Kim R. , Bailey Christopher J.
Published: October 2021

Optical coherence tomography (OCT) is applicable to the study of cerebral microvasculaturein vivo. Optimised acquisition schemes enable the generation of three-dimensional OCT angiograms,i.e., volumetric images of red blood cell flux in capillary networks, currently at a repetition rate of up to 1/10 seconds. This makes testable a new class of hypotheses that strive to bridge the gap between microscopic phenomena occurring at the spatial scale of neurons, and less invasive but crude techniques to measure macroscopic blood flow dynamics. Here we present a method for quantifying the occurrence of transient capillary stalls in OCT angiograms,i.e., events during which blood flow through a capillary branch is temporarily occluded. By making the assumption that information on such events is present predominantly in the imaging plane, we implemented a pipeline that automatically segments a network of interconnected capillaries from the maximum intensity projections (MIP) of a series of 3D angiograms. We then developed tools enabling rapid manual assessment of the binary flow status (open/stalled) of hundreds of capillary segments based on the intensity profile of each segment across time. The entire pipeline is optimized to run on a standard laptop computer, requiring no high-performance, low-availability resources, despite very large data volumes. To further reduce the threshold of adoption, and ultimately to support the development of reproducible research methods in the young field, we provide the documented code for scrutiny and re-use under a permissive open-source license.
Context-dependent selectivity to natural scenes in the retina
Authors: Goldin Matías A. , Lefebvre Baptiste , Virgili Samuele , Ecker Alexander , Mora Thierry , Ferrari Ulisse , Marre Olivier
Published: October 2021

Retina ganglion cells extract specific features from natural scenes and send this information to the brain. In particular, they respond to local light increase (ON responses), and/or decrease (OFF). However, it is unclear if this ON-OFF selectivity, characterized with synthetic stimuli, is maintained when they are stimulated with natural scenes. Here we recorded the responses of ganglion cells of mice and axolotls to stimuli composed of natural images slightly perturbed by patterns of random noise to determine their selectivity during natural stimulation. The ON-OFF selectivity strongly depended on the natural image. A single ganglion cell can signal luminance increase for one natural image, and luminance decrease for another. Modeling and experiments showed that this was due to the non-linear combination of different pathways of the retinal circuit. Despite the versatility of the ON-OFF selectivity, a systematic analysis demonstrated that contrast was reliably encoded in these responses. Our perturbative approach thus uncovers the selectivity of retinal ganglion cells to more complex features than initially thought during natural scene stimulation.
A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures
Authors: Mo Chen , Ye Zhenyao , Ke Hongjie , Lu Tong , Canida Travis , Liu Song , Wu Qiong , Zhao Zhiwei , Ma Yizhou , Hong L. Elliot , Kochunov Peter , Ma Tianzhou , Chen Shuo
Published: October 2021

The advent of simultaneously collected imaging-genetics data in large study cohorts provides an unprecedented opportunity to assess the causal effect of brain imaging traits on externally measured experimental results (e.g., cognitive tests) by treating genetic variants as instrumental variables. However, classic Mendelian Randomization methods are limited when handling high-throughput imaging traits as exposures to identify causal effects. We propose a new Mendelian Randomization framework to jointly select instrumental variables and imaging exposures, and then estimate the causal effect of multivariable imaging data on the outcome. We validate the proposed method with extensive data analyses and compare it with existing methods. We further apply our method to evaluate the causal effect of white matter microstructure integrity on cognitive function. The findings suggest that our method achieved better performance regarding sensitivity, bias, and false discovery rate compared to individually assessing the causal effect of a single exposure and jointly assessing the causal effect of multiple exposures without dimension reduction. Our application results indicated that WM measures across different tracts have a joint causal effect that significantly impacts the cognitive function among the participants from the UK Biobank.