bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Vitamin D deficiency on COVID-19 status: A systematic review
Authors: Das Pranta , Samad Nandeeta , Ahinkorah Bright Opoku , Peprah Prince , Mohammed Aliu , Seidu Abdul-Aziz
Published: December 2020

Background

One major micronutrient known to have a possible protective effect against COVID-19 disease is vitamin D. This systematic review sought to identify and synthesise available evidence to aid the understanding of the possible effect of vitamin D deficiency on COVID-19 status and health outcomes in COVID-19 patients.

Methods

Three databases PubMed, ScienceDirect, and Google Scholar were searched systematically to obtain English language journal article published within 1/12/2019 and 3/11/2020. The search consisted of the terms (“Vitamin D,” OR “25□Hydroxyvitamin D,” OR “Low Vitamin D.”) AND (“COVID-19” OR “2019-nCoV” OR “Coronavirus” OR “SARS-CoV-2”) AND (“disease severity” OR “IMV” OR “ICU admission” OR “mortality” OR “hospitalization” OR “infection”). We followed the recommended PRISMA guidelines in executing this study. After going through the screening of the articles, eleven articles were included in the review.

Findings

Almost all the included studies reported a positive association between Vitamin D sufficiency and COVID-19 status and health outcomes. Vitamin D deficient patients (< 25 ng/mL) are 5.84 times [aOR=6.84, p=0.01] more likely to die from COVID-19 compared to the vitamin D sufficient people. Another study also found that Vitamin D deficiency is associated with higher risk of death with Hazard ratio (HR) 14.73, p<0.001. Vitamin D deficient (<12 ng/mL) people were 2.2 times [aOR=3.2, p=0.07] more likely to develop severe COVID-19 after adjusting for age, gender, obesity, cardiac disease, and kidney disease compared to the vitamin D sufficient people. One study found that after controlling for confounders, patients with low 25(OH)D (<30 ng/mL) level are more likely [aOR=1.45, p=<0.001] to be COVID-19 infected compared to the patients with 25(OH)D level >=30 ng/mL.

Conclusion

Findings from the study included suggest Vitamin D may serve as a mitigating effect for covid-19 infection, severity and mortality. We recommend the need to encourage people to eat foods rich in vitamin D such as fish, red meat, liver and egg yolks whiles at the same time providing vitamin D supplements for individuals with COVID-19 in order to boost their immune systems.
Vaginal Microbiome Topic Modelling of Laboring Ugandan Women With and Without Fever
Authors: Movassagh Mercedeh , Bebell Lisa M. , Burgoine Kathy , Hehnly Christine , Zhang Lijun , Moran Kim , Sheldon Kathryn , Sinnar Shamim A. , Mbabazi Edith , Kumbakumba Elias , Bazira Joel , Ochoa Moses , Mulondo Ronnie , Nsubuga Brian K. , Weeks Andrew , Gladstone Melissa , Olupot-Olupot Peter , Ngonzi Joseph , Roberts Drucilla J. , Meier Frederick A. , Irizarry Rafael , Broach James , Schiff Steven J. , Paulson Joseph N.
Published: December 2020

The composition of the maternal vaginal microbiome may influence the duration of pregnancy, onset of labor and even neonatal outcomes. Maternal microbiome research in sub Saharan-Africa has focused on non-pregnant and postpartum composition of the vaginal microbiome. We examined the vaginal microbiome composition of 99 laboring Ugandan women using routine microbiology and 16S ribosomal DNA sequencing from two hypervariable regions (V1-V2 and V3-V4), using standard hierarchical methods. We then introduce Grades of Membership (GoM) modeling for the vaginal microbiome, a method often used in the text mining machine learning literature. Leveraging GoM models, we create a basis composed of a small number of microbial ‘topic’s whose linear combination optimally represents each patient yielding more accurate associations. We identified relationships between defined communities and the presentation or absence of intrapartum fever. Using a random forest model we showed that by including novel microbial topic models we improved upon clinical variables to predict maternal fever. We also show by integrating clinical variables with a microbial topic model into this model found young maternal age, fever report earlier in the current pregnancy, and longer labors, as well as a more diverse, lessLactobacillusdominated microbiome were features of labor associated with intrapartum fever. These results better define relationships between presentation or absence of intrapartum fever, demographics, peripartum course, and vaginal microbial communities, and improve our understanding of the impact of the microbiome on maternal and neonatal infection risk.
Parental feeding preferences rather than sibling competition determine the death of smaller nestlings in asynchronous broods
Authors: Soler Manuel , Ruiz-Raya Francisco , Sánchez-Pérez Lucía , Ibáñez-Álamo Juan Diego
Published: December 2020

Hatching asynchrony is a reproductive tactic that, through the creation of competitive hierarchies among offspring, allows parents for a quick adjustment of brood size via the death of smaller nestlings. This strategy is considered to be adaptive in case of unpredictable and/or poor environments in which it would guarantee that at least larger nestlings will fledge. Brood reduction is the usual outcome in asynchronously hatched broods since first-hatched nestlings are larger and get a disproportionately larger share of the food delivered by parents, often leading the youngest nestling to starve to death soon after hatching. However, we still do not know the proximate mechanisms of such brood reduction. One possibility is that the smallest nestling is not fed because larger nestlings outcompete it, which implies that nestlings control resource allocation. Alternatively, parents might actively ignore the persistent begging from their smallest nestling, which would involve that parents control food allocation. To determine whether parents or nestlings ultimately induce brood reduction in this situation, we experimentally created asynchronous broods of Eurasian blackbird (Turdus merula) nestlings and quantified food allocation by parents in two different situations: when sibling competition was allowed and, alternatively, when competition was prevented by physically separating nestlings within the nests by using wooden barriers. Our results showed that experimentally introduced smaller nestlings received less food than their larger nestmates both when competition among nestlings was allowed and when it was prevented. When adult males and females are considered separately, males fed the smallest nestling less often regardless of whether sibling competition was allowed or not, but adult females showed no differences. We can conclude that the smallest nestling starves mainly because parents actively ignore its begging. The higher competitive ability of the larger nestlings seem to have little effect given that although the smallest nestling is fed at a higher rate when physical interactions are prevented by the wooden barrier than when not, this difference is not significant. These findings suggest that parents rather than nestlings have the main control over food allocation.
Epigenetic scores for the circulating proteome as tools for disease prediction
Authors: Gadd Danni A , Hillary Robert F , McCartney Daniel L , Zaghlool Shaza B , Stevenson Anna J , Nangle Cliff , Campbell Archie , Flaig Robin , Harris Sarah E , Walker Rosie M , Shi Liu , Tucker-Drob Elliot M , Gieger Christian , Peters Annette , Waldenberger Melanie , Graumann Johannes , McRae Allan F , Deary Ian J , Porteous David J , Hayward Caroline , Visscher Peter M , Cox Simon R , Evans Kathryn L , McIntosh Andrew M , Suhre Karsten , Marioni Riccardo E
Published: December 2020

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNAm signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample, (Generation Scotland; n=9,537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore – disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.
No evidence for whole-chromosome dosage compensation or global transcriptomic expression differences in spontaneously-aneuploid mutation accumulation lines ofSaccharomyces cerevisiae
Authors: McQueary Holly C. , Behringer Megan G. , Demario Sam , Canas Alexander Joao Jamarillo , Johnson Brittania , Tsfoni Ariella , Chamberlin John , Hall David W.
Published: December 2020

Aneuploidy, the state in which an organism’s genome contains one or more missing or additional chromosomes, often causes widespread genotypic and phenotypic effects. Most often, aneuploidies are deleterious; the most common examples in humans being Down’s syndrome (Trisomy 21) and Turner’s syndrome (monosomy X). However, aneuploidy is surprisingly common in wild yeast populations. In recent years, there has been debate as to whether yeast contain an innate dosage compensation response that operates at the gene, chromosome, or the whole-genome level, or if natural isolates are robust to aneuploidy without such a mechanism. In this study, we tested for differential gene expression in 20 aneuploid and 16 euploid lines of yeast from two previous mutation accumulation experiments, where selection was minimized and therefore aneuploidies arose spontaneously. We found no evidence for whole-chromosome dosage compensation in aneuploid yeast but did find some evidence for attenuation of expression on a gene-by-gene basis. We additionally found that aneuploidy has no effect on the expression of the rest of the genome (i.e. “trans” genes), and that very few mutually exclusive aneuploid lines shared differentially expressed genes. However, we found there was a small set of genes that exhibited a shared expression response in the euploid lines, suggesting an effect of mutation accumulation on gene expression. Our findings contribute to our understanding of aneuploidy in yeast and support the hypothesis that there is no innate dosage compensation mechanism at the whole-chromosome level.
A Kernel-Based Change Detection Method to Map Shifts in Phytoplankton Communities Measured by Flow Cytometry
Authors: Jones Corinne , Clayton Sophie , Ribalet François , Armbrust E. Virginia , Harchaoui Zaid
Published: December 2020

Automated, ship-board flow cytometers provide high-resolution maps of phytoplankton composition over large swaths of the world’s oceans. They therefore pave the way for understanding how environmental conditions shape community structure. Identification of community changes along a cruise transect commonly segments the data into distinct regions. However, existing segmentation methods are generally not applicable to flow cytometry data, as this data is recorded as “point cloud” data, with hundreds or thousands of particles measured during each time interval. Moreover, nonparametric segmentation methods that do not rely on prior knowledge of the number of species, are desirable to map community shifts.

We present CytoSegmenter, a kernel-based change-point estimation method for segmenting point cloud data that does not rely on parametric assumptions on the data distributions. Our method relies on a Hilbertian embedding of point clouds that allows us to work with point cloud data similarly to vectorial data. The change-point locations can be found using an efficient dynamic programming algorithm. The method can be used to automatically segment long series of underway flow cytometry data.

Through an analysis of 12 cruises, we demonstrate that CytoSegmenter allows us to locate abrupt changes in phytoplankton community structure. We show that the changes in community structure generally coincide with changes in the temperature and salinity of the ocean. We also illustrate how the main parameter of CytoSegmenter can be easily calibrated using limited auxiliary annotated data.

CytoSegmenter is publicly available and implemented in the programming language Python. The method is generally applicable for segmenting series of point cloud data from any domain. Moreover, it readily scales to thousands of point clouds, each containing thousands of points. In the context of underway flow cytometry data, it does not require prior clustering of particles to define taxa labels, eliminating a potential source of error. This represents an important advance in automating the analysis of large datasets now emerging in biological oceanography and other fields. It also allows for the approach to potentially be applied during research cruises.
An Interactive Health Game Using Machine Learning: A Prototype
Authors: Ay Esra , Eken Burak , Önal-Süzek Tuğba
Published: December 2020

According to World Health Organization (WHO) 2016 report, there are over 650 million obese adults and more than 2 billion overweight individuals in the world and it is estimated that this number will reach 2.7 billion in 2025 [1]. A sedentary lifestyle with low physical activity is considered to be one of the most effective environmental effects leading to various chronic disease phenotypes such as obesity and metabolic syndrome. On average, every 1 out of 3 people over the age of 20 in Turkey are known to have struggled with the metabolic syndrome [2]. Our project aims to apply the concept of “serious gaming”, to entertain people, play games, socialize and exercise in parallel to increase the ratio of the healthy individuals in our society. In this project, we applied machine learning techniques to integrate real-life accelerometer and gyroscope sensor data obtained from mobile phones to develop an interactive mobile based exercise game which does not require any external device such as smart watches. To our knowledge and research, our game is the first mobile-only interactive serious game that integrates machine learning techniques and an encouraging virtual environment to the individuals in need of exercise.
BAP1/ASXL complex modulation regulates Epithelial-Mesenchymal Transition during trophoblast differentiation and invasion
Authors: Perez-Garcia Vicente , Lopez-Jimenez Pablo , Burton Graham J , Moffett Ashley , Turco Margherita Y. , Hemberger Myriam
Published: December 2020

Normal function of the placenta depends on the earliest developmental stages when trophoblast cells differentiate and invade into the endometrium to establish the definitive maternal-fetal interface. Previously, we identified the ubiquitously expressed tumour suppressor BRCA1-associated protein 1 (BAP1) as a central factor of a novel molecular node controlling early mouse placentation. However, functional insights into how BAP1 regulates trophoblast biology are still missing. Using CRISPR/Cas9 knockout and overexpression technology, here we demonstrate that the downregulation of BAP1 protein is essential to trigger epithelial-mesenchymal transition (EMT) during trophoblast differentiation associated with a gain of invasiveness. This function, which is conserved in mouse and humans, is dependent on the binding of BAP1 binding to Additional sex comb-like (ASXL1/2/3) proteins to form the Polycomb repressive deubiquitinase (PR-DUB) complex. Our results reveal that the physiological modulation of BAP1 determines the invasive properties of trophoblast, delineating a new role of the BAP1 PR-DUB complex in regulating early placentation.
Human retrosplenial theta and alpha modulation in active spatial navigation
Authors: Do Tien-Thong Nguyen , Lin Chin-Teng , Gramann Klaus
Published: December 2020

Spatial navigation is a complex cognitive process based on multiple senses that are integrated and processed by a wide network of brain areas. Previous studies have revealed the retrosplenial complex (RSC) to be modulated in a task-related manner during navigation. However, these studies restricted participants’ movement to stationary setups, which might have impacted heading computations due to the absence of vestibular and proprioceptive inputs. Here, we investigated neural dynamics of RSC in an active spatial navigation task where participants actively ambulated from one location to several other points while the position of a landmark and the starting location were updated. The results revealed theta power in the RSC to be pronounced during heading changes but not during translational movements, indicating that physical rotations induce human RSC theta activity. This finding provides a potential evidence of head-direction computation in RSC in healthy humans during active spatial navigation.
Active and machine learning-based approaches to rapidly enhance microbial chemical production
Authors: Kumar Prashant , Adamczyk Paul A. , Zhang Xiaolin , Andrade Ramon Bonela , Romero Philip A. , Ramanathan Parameswaran , Reed Jennifer L.
Published: December 2020

In order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic models (e.g., kinetic/stoichiometric models of metabolism) — requiring many experimental datasets for their parameterization—while experimental methods may require screening large mutant libraries to explore the design space for the few mutants with desired behaviors. To address these limitations, we developed an active and machine learning approach (ActiveOpt) to intelligently guide experiments to arrive at an optimal phenotype with minimal measured datasets. ActiveOpt was applied to two separate case studies to evaluate its potential to increase valine yields and neurosporene productivity inEscherichia coli. In both the cases, ActiveOpt identified the best performing strain in fewer experiments than the case studies used. This work demonstrates that machine and active learning approaches have the potential to greatly facilitate metabolic engineering efforts to rapidly achieve its objectives.
A non-coding indel polymorphism in thefruitlessgene ofDrosophila melanogasterexhibits antagonistically pleiotropic fitness effects
Authors: Jardine Michael D. , Ruzicka Filip , Diffley Charlotte , Fowler Kevin , Reuter Max
Published: December 2020

The amount of genetic variation for fitness within populations tends to exceed that expected under mutation-selection-drift balance. Several mechanisms have been proposed to actively maintain polymorphism and account for this discrepancy, including antagonistic pleiotropy (AP), where allelic variants have opposing effects on different components of fitness. Here we identify a non-coding indel polymorphism in thefruitlessgene ofDrosophila melanogasterand measure survival and reproductive components of fitness in males and females of replicate lines carrying one or the other allele. Expressing the fruitless region in a hemizygous state we observe a pattern of AP, with one allele resulting in greater reproductive fitness while the other confers greater survival to adulthood. Different fitness effects were observed in an alternative genetic background, suggesting widespread epistatic effects. Our findings link sequence-level variation at a single locus with complex effects on a range of fitness components, thus helping to explain the maintenance of genetic variation for fitness. Transcription factors, such asfruitless, may be prime candidates for targets of balancing selection since they interact with multiple target loci and their associated phenotypic effects.
Parasitoid wasp venom targets host immune cell production in aDrosophila-parasitoid interaction
Authors: Trainor Jordann E. , Pooja KR , Mortimer Nathan T.
Published: December 2020

The interactions betweenDrosophila melanogasterand the parasitoid wasps that infectDrosophilaspecies provide an important model for understanding host-parasite relationships. Following parasitoid infection,D. melanogasterlarvae mount a response in which immune cells (hemocytes) form a capsule around the wasp egg, which then melanizes leading to death of the parasitoid. Previous studies have found that host hemocyte load, the number of hemocytes available for the encapsulation response, and the production of lamellocytes, an infection induced hemocyte type, are major determinants of host resistance. Parasitoids have evolved various virulence mechanisms to overcome the immune response of theD. melanogasterhost, including both active immune suppression by venom proteins and passive immune evasive mechanisms. We find that a previously undescribed parasitoid species,Asobara sp. AsDen, utilizes an active virulence mechanism to infectD. melanogasterhosts.Asobara sp. AsDeninfection inhibits host hemocyte expression ofmsn, a member of the JNK signaling pathway, which plays a role in lamellocyte production.Asobara sp. AsDeninfection restricts the production of lamellocytes as assayed by hemocyte cell morphology and alteredmsnexpression. Our findings suggest thatAsobara sp. AsDenvenom targets host signaling to suppress immunity.

Declarations

Funding

This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R35GM133760.

Availability of data and material

Sequence data has been deposited in GenBank under accession #MT498809. Custom BLAST databases are available on request to corresponding author.

Authors’ contributions

Conceived of or designed study: J.E.T., N.T.M.; Performed research: J.E.T., P.K.; Analyzed data: J.E.T., P.K., N.T.M.; Wrote the paper: J.E.T., P.K., N.T.M.
Coherent natural scene structure facilitates the extraction of task-relevant object information in visual cortex
Authors: Kaiser Daniel , Häberle Greta , Cichy Radoslaw M.
Published: December 2020

Looking for objects within complex natural environments is a task everybody performs multiple times each day. In this study, we explore how the brain uses the typical composition of real-world environments to efficiently solve this task. We recorded fMRI activity while participants performed two different categorization tasks on natural scenes. In the object task, they indicated whether the scene contained a person or a car, while in the scene task, they indicated whether the scene depicted an urban or a rural environment. Critically, each scene was presented in an “intact” way, preserving its coherent structure, or in a “jumbled” way, with information swapped across quadrants. In both tasks, participants’ categorization was more accurate and faster for intact scenes. These behavioral benefits were accompanied by stronger responses to intact than to jumbled scenes across high-level visual cortex. To track the amount of object information in visual cortex, we correlated multi-voxel response patterns during the two categorization tasks with response patterns evoked by people and cars in isolation. We found that object information in object- and body-selective cortex was enhanced when the object was embedded in an intact, rather than a jumbled scene. However, this enhancement was only found in the object task: When participants instead categorized the scenes, object information did not differ between intact and jumbled scenes. Together, these results indicate that coherent scene structure facilitates the extraction of object information in a task-dependent way, suggesting that interactions between the object and scene processing pathways adaptively support behavioral goals.
Role of bradykinin type 2 receptors in human sweat secretion: translational evidence does not support a functional relationship
Authors: Wilson Thad E. , Narra Seetharam , Metzler-Wilson Kristen , Schneider Artur , Bullens Kelsey A. , Holt Ian S.
Published: December 2020

Bradykinin increases skin blood flow via a cGMP mechanism but its role in sweatingin vivois unclear. There is a current need to translate cell culture and non-human paw pad studies intoin vivohuman preparations to test for therapeutic viability for disorders affecting sweat glands. Protocol 1: physiological sweating was induced in 10 healthy subjects via perfusing warm (46-48°C) water through a tube-lined suit while bradykinin type 2 receptor (B2R) antagonist (HOE-140; 40 μM) and only the vehicle (lactated Ringer’s) were perfused intradermally via microdialysis. Heat stress increased sweat rate (HOE-140 = +0.79±0.12 and vehicle = +0.64±0.10 mg/cm2/min), but no differences were noted with B2R antagonism. Protocol 2: pharmacological sweating was induced in 6 healthy subjects via intradermally perfusing pilocarpine (1.67 mg/ml) followed by the same B2R antagonist approach. Pilocarpine increased sweating (HOE-140 = +0.38±0.16 and vehicle = +0.32±0.12 mg/cm2/min); again no differences were observed with B2R antagonism. Lastly, 5 additional subjects were recruited for various control experiments which identified that a functional dose of HOE-140 was utilized and it was not sudorific during normothermic conditions. These data indicate B2R antagonists do not modulate physiologically-or pharmacologically-induced eccrine secretion volumes. Thus, B2R agonist/antagonist development as a potential therapeutic target for hypo- and hyperhidrosis appears unwarranted.
mokapot: Fast and flexible semi-supervised learning for peptide detection
Authors: Fondrie William E , Noble William S
Published: December 2020

Proteomics studies rely on the accurate assignment of peptides to the acquired tandem mass spectra—a task where machine learning algorithms have proven invaluable. We describe mokapot, which provides a flexible semi-supervised learning algorithm that allows for highly customized analyses. We demonstrate some of the unique features of mokapot by improving the detection of RNA-cross-linked peptides from an analysis of RNA-binding proteins and increasing the consistency of peptide detection in a single-cell proteomics study.
Rigorous anterograde trans-monosynaptic tracing of genetic defined neurons with retargeted HSV1 H129
Authors: Su Peng , Ying Min , Xia Jinjin , Li Yingli , Wu Yang , Wang Huadong , Xu Fuqiang
Published: December 2020

Neuroanatomical tracing technology is fundamental for unraveling the complex network of brain connectome. Tracing tools that could spread between neurons are urgently needed, especially the rigorous trans-monosynaptic anterograde tracer is still lacking. HSV1 strain H129 was proved to be an anterograde tracer and has been used to trace neuronal networks in several reports. However, H129 has a serious defect that it was demonstrated to infect neurons via axon terminals. Thus, when using H129 to dissect output neural circuit, its terminal take up capacity should be carefully considered. Here, we report a recombinant H129 that carrying the anti-Her2 scFv in glycoprotein D to target genetically defined neurons. With the usage of helper virus complementarily expressing Her2 and gD, we can realize the elucidation of direct projection regions of either a given brain nucleus or a specific neuron type. The retargeted H129 system complements the current neural circuit tracer arsenal, which provides a rigorous and practical anterograde trans-monosynaptic tool.
multiTFA: a Python package for multi-variate Thermodynamics-based Flux Analysis
Authors: Mahamkali Vishnuvardhan , McCubbin Tim , Beber Moritz Emanuel , Marcellin Esteban , Nielsen Lars Keld
Published: December 2020

We achieve a significant improvement in thermodynamic-based flux analysis (TFA) by introducing multivariate treatment of thermodynamic variables and leveraging component contribution, the state-of-the-art implementation of the group contribution methodology. Overall, the method greatly reduces the uncertainty of thermodynamic variables.

Results

We present multiTFA, a Python implementation of our framework. We evaluated our application using the coreE. colimodel and achieved a median reduction of 6.8 kJ/mol in reaction Gibbs free energy ranges, while three out of 12 reactions in glycolysis changed from reversible to irreversible.

Availability and implementation

Our framework along with documentation is available onhttps://github.com/biosustain/multitfa.
Retinotopic organization of visual cortex in human infants
Authors: Ellis C. T. , Yates T. S. , Skalaban L. J. , Bejjanki V. R. , Arcaro M. J. , Turk-Browne N. B.
Published: December 2020

Vision develops rapidly during infancy, yet how visual cortex is organized during this period is unclear. One possibility is that the retinotopic organization of visual cortex emerges gradually as perceptual abilities improve. This may result in a hierarchical maturation of visual areas from striate to extrastriate cortex. Another possibility is that retinotopic organization is present from early infancy. This early maturation of area boundaries and tuning could scaffold further developmental changes. Here we test the functional maturity of infant visual cortex by performing retinotopic mapping with fMRI. Infants aged 5–23 months had retinotopic maps, with alternating preferences for vertical and horizontal meridians indicative of area boundaries from V1 to V4, and an orthogonal gradient of preferences from high to low spatial frequencies indicative of growing receptive field sizes. Although present in the youngest infants, these retinotopic maps showed subtle agerelated changes, suggesting that early maturation undergoes continued refinement.
Host-environment interplay shapes fungal diversity in mosquitoes
Authors: Tawidian Patil , Coon Kerri L. , Jumpponen Ari , Cohnstaedt Lee W. , Michel Kristin
Published: December 2020

Mosquito larvae encounter diverse assemblages of bacteria (i.e. ‘microbiota’) and fungi (i.e. ‘mycobiota’) in the aquatic environments they develop in. However, while a number of studies have addressed the diversity and function of microbiota in mosquito life history, relatively little is known about mosquito-mycobiota interactions outside of several key fungal entomopathogens. In this study, we used high-throughput sequencing of ITS2 gene amplicons to provide the first simultaneous characterization of the mycobiota in field-collectedAedes albopictuslarvae and their associated aquatic environments. Our results reveal unprecedented variation in mycobiota among adjacent but discrete larval breeding habitats. Our results also reveal distinct mycobiota assembly in the mosquito gut versus other tissues, with gut-associated fungal communities being most similar to those present in the environment where larvae feed. Altogether, our results identify the environment as the dominant factor shaping mosquito mycobiota with no evidence of environmental filtering of the gut mycobiota. These results also identify mosquito feeding behavior and fungal mode of nutrition as potential drivers of tissue-specific mycobiota assembly after environmental acquisition.

IMPORTANCE

The Asian tiger mosquito,Aedes albopictus, is the dominant mosquito species in the USA and an important vector of arboviruses of major public health concern. One aspect of mosquito control to curb mosquito-borne diseases has been the use of biological control agents such as fungal entomopathogens. Recent studies also demonstrate the impact of mosquito-associated microbial communities on various mosquito traits, including vector competence. However, while much research attention has been dedicated to understanding the diversity and function of mosquito-associated bacterial communities, relatively little is known about mosquito-associated fungal communities. A better understanding of the factors that drive mycobiota diversity and assembly in mosquitoes will be essential for future efforts to target mosquito micro- and mycobiomes for mosquito and mosquito-borne disease control.
Subunit Vaccine-Elicited Effector-Like Memory CD8 T Cells Protect Against Listeriosis
Authors: Lee Woojong , Larsen Autumn , Kingstad-Bakke Brock , Suresh M.
Published: December 2020

Development of T-cell-based subunit protein vaccines against diseases, such as AIDS, tuberculosis and malaria remains a challenge for immunologists. Here, we have evaluated whether cross-presentation induced by nanoemulsion adjuvant Adjuplex (ADJ), can be combined with the immunomodulatory effects of TLR agonists (CpG or glucopyranosyl lipid adjuvant [GLA]) to evoke protective systemic CD8 T cell-based immunity toListeria monocytogenes(LM). Vaccination with ADJ, alone or in combination with CpG or GLA augmented activation and antigen uptake by migratory and resident dendritic cells and up-regulated CD69 expression on B and T lymphocytes in draining lymph nodes. By virtue of its ability to engage BATF3-dependent cross-presenting DCs, ADJ potently elicited effector CD8 T cells that differentiated into a distinct subset of granzyme B-expressing CD27LOeffector-like memory CD8 T cells, which provided highly effective immunity to LM in spleen and liver. CpG or GLA alone did not elicit effector-like memory CD8 T cells and induced moderate protection in spleen, but not in the liver. Surprisingly, combining CpG or GLA with ADJ limited the magnitude of ADJ-induced CD8 T cell memory and compromised protective immunity to LM, especially in the liver. Taken together, data presented in this manuscript provides a glimpse of protective CD8 T cell memory differentiation induced by a nano-emulsion adjuvant and demonstrates the unexpected negative effects of TLR signaling on the magnitude of CD8 T cell memory and protective immunity to listeriosis.

Importance

To date, the most effective vaccines primarily provide protection by eliciting neutralizing antibodies, while development of T-cell-based subunit vaccines against infectious diseases, such as tuberculosis and malaria, remains a challenge for immunologists. Axiomatically, engagement of multiple innate immune receptors early in the response might be key to programming effective immunity. Hence, there is an impetus to develop combination adjuvants that engage multiple innate signaling pathways and additionally promote cross-presentation to stimulate CD8 T-cell immunity. Here, we show that a nano-emulsion adjuvant ADJ alone elicits effector-like memory CD8 T cells and provides highly effective immunity to listeriosis; combining ADJ with TLR agonists, including CpG and GLA, compromised T cell immunity to LM. In summary, this study provided fundamental insights into the effects of combining innate immune signaling with nano-emulsion adjuvants on memory T cell differentiation and protective immunity. These findings are expected to have implications in the use of combination adjuvants to develop subunit vaccines that engender systemic CD8 T-cell immunity to intracellular pathogens.
Intron-assisted, viroid-based production of insecticidal circular double-stranded RNA inEscherichia coli
Authors: Ortolá Beltrán , Cordero Teresa , Hu Xu , Daròs José-Antonio
Published: December 2020

RNA interference (RNAi) is a natural mechanism for protecting against harmful genetic elements and regulating gene expression, which can be artificially triggered by the delivery of homologous double-stranded RNA (dsRNA). This mechanism can be exploited as a highly specific and environmentally friendly pest control strategy. To this aim, systems for producing large amounts of recombinant dsRNA are necessary. We describe a system to efficiently produce large amounts of circular dsRNA inEscherichia coliand demonstrate the efficient insecticidal activity of these molecules against Western corn rootworm (WCR,Diabrotica virgifera virgiferaLeConte), a highly damaging pest of corn crops. In our system, the two strands of the dsRNA are expressed inE. coliembedded within the very stable scaffold ofEggplant latent viroid(ELVd), a small circular non-coding RNA. Stability inE. coliof the corresponding plasmids with long inverted repeats was achieved by using a cDNA coding for a group-I autocatalytic intron fromTetrahymena thermophilaas a spacer. RNA circularization and large-scale accumulation inE. colicells was facilitated by co-expression of eggplant tRNA ligase, the enzyme that ligates ELVd during replication in the host plant. The inserted intron efficiently self-spliced from the RNA product during transcription. Circular RNAs containing a dsRNA moiety homologous tosmooth septate junction 1(DvSSJ1) gene exhibited excellent insecticide activity against WCR larvae. Finally, we show that the viroid scaffold can be separated from the final circular dsRNA product using a secondT. thermophilaself-splicing intron in a permuted form.
Effects of rumen-protected methionine supplementation on the performance of high production dairy cows in the tropics
Authors: Junior Valdir Chiogna , Lopes Fernanda , Schwab Charles George , Toledo Mateus Zucato , Collao-Saenz Edgar Alain
Published: December 2020

Increasing methionine availability in dairy cow diets during the first third of lactation may enhance their performance and health. The aim of this study was to determine the effect of supplementing rumen-protected methionine (RPMet) in a lactation diet containing adequate protein and energy levels. Seventy-six multiparous Holstein cows (39.1 ± 6.8 kg of milk/d and 65 ± 28 DIM) were assigned to 1 of 2 dietary treatments (38/treatment) according to a randomized complete block design with a 2-wk (covariate) and 10-wk experimental period. Treatments were a basal diet (CON; 3.77 Lys:1Met); and CON + 14 g RPMet (2.97 Lys:1 Met). Individual milk samples were taken every 2 weeks to determine milk composition. Blood was collected from 24 cows on d+30 d to measure plasma AA levels. Body weight and body condition score (BCS) were measured at the beginning and the end of the experiment. The SM diet promoted higher milk yield (41.7 vs. 40.1 kg/d;P= 0.026), energy-corrected milk yield (41.0 vs. 38.0 kg/d;P≤ 0.01), milk protein yield (1.30 vs. 1.18 kg/d;P≤ 0.01), and milk fat yield (1.42 vs. 1.29 kg/d;P= 0.02). Higher milk protein (3.14% vs. 2.97%;P≤ 0.01) and casein (2.39% vs. 2.28%;P≤ 0.01) and a trend (P= 0.06) for higher milk fat % (3.41% vs. 3.21%) were also observed. Both diets resulted in similar body weight, but CON-fed cows tended (P= 0.08) to have higher BCS. Higher plasma methionine levels were determined with SM compared with CON (29.6 vs. 18.4 μM;P< 0.01), but lysine and histidine were not different. Dietary supplementation of RPM improved productive performance by increasing milk yield and milk components yields, suggesting better dietary AA utilization when Met levels are adjusted in Lys-adequate lactation diets.
CONCENTRATION OF THIOUREA IS EFFECTIVE IN BREAKING THE DORMANCY OF POTATO VARIETIES
Authors: Ranabhat Sambat , Dhital Madhav , Subedi Ramkrishna , Adhikari Ansu , Adhikari Binod , Shrestha Saroj
Published: December 2020

Potato germination is highly sensitive to ecological conditions. High altitude and low annual average temperature results in tuber dormancy and poor sprouting. Dormancy has become a significant constraint for lowering potato production that hinders the possibility of growing two crops per year. An experiment was conducted from February to April 2020, where two major potato varieties (Desiree and Cardinal) were treated with four concentrations of Thiourea (0, 1, 2, and 3%) in a two factorial completely randomized block design with three replications. Results showed that Thiourea has a significant effect on all observed attributes as per varieties of potato. For Desiree variety, Thiourea (1%) decreased breaking of dormancy by 22 days compared to control (Desiree*Thiourea 0%) and produced the longest average sprout of 7.36cm at 49 days after treatment (DAT). On the other hand, for the Cardinal variety, Thiourea (3%) decreased tuber dormancy by 27 days compared to control (Cardinal*Thiourea 0%) and produced a sprout of 7.75 cm at 49 DAT. In conclusion, for breaking dormancy and enhancing sprouting of potato varieties Desiree and Cardinal, Thiourea concentration of 1% and 3% is recommended, respectively.

Author summary

This work is the combined effort of all the authors; conceptualization and designing the plot experiments, S.R. and M.D.; performing the experiment and data collection, S.R. and A.A.; statistical analysis and preparation of presentation table and figure, S.R. and B.A.; writing the original draft and editing the whole manuscript, S.R., M.D., R.S., S.S., and A.A. All the author have read and agreed to the published version of the manuscript.
Modeling Changes in Probabilistic Reinforcement Learning during Adolescence
Authors: Xia Liyu , Master Sarah L , Eckstein Maria K , Baribault Beth , Dahl Ronald E , Wilbrecht Linda , Collins Anne GE
Published: December 2020

In the real world, many relationships between events are uncertain and probabilistic. Uncertainty is also likely to be a more common feature of daily experience for youth because they have less experience to draw from than adults. Some studies suggests probabilistic learning may be inefficient in youth compared to adults [1], while others suggest it may be more efficient in youth that are in mid adolescence [2, 3]. Here we used a probabilistic reinforcement learning task to test how youth age 8-17 (N = 187) and adults age 18-30 (N = 110) learn about stable probabilistic contingencies. Performance increased with age through early-twenties, then stabilized. Using hierarchical Bayesian methods to fit computational reinforcement learning models, we show that all participants’ performance was better explained by models in which negative outcomes had minimal to no impact on learning. The performance increase over age was driven by 1) an increase in learning rate (i.e. decrease in integration time horizon); 2) a decrease in noisy/exploratory choices. In mid-adolescence age 13-15, salivary testosterone and learning rate were positively related. We discuss our findings in the context of other studies and hypotheses about adolescent brain development.

Author summary

Adolescence is a time of great uncertainty. It is also a critical time for brain development, learning, and decision making in social and educational domains. There are currently contradictory findings about learning in adolescence. We sought to better isolate how learning from stable probabilistic contingencies changes during adolescence with a task that previously showed interesting results in adolescents. We collected a relatively large sample size (297 participants) across a wide age range (8-30), to trace the adolescent developmental trajectory of learning under stable but uncertain conditions. We found that age in our sample was positively associated with higher learning rates and lower choice exploration. Within narrow age bins, we found that higher saliva testosterone levels were associated with higher learning rates in participants age 13-15 years. These findings can help us better isolate the trajectory of maturation of core learning and decision making processes during adolescence.
DeepFlu: a deep learning approach for forecasting symptomatic influenza A infection based on pre-exposure gene expression
Authors: Zan Anna , Xie Zhong-Ru , Hsu Yi-Chen , Chen Yu-Hao , Lin Tsung-Hsien , Chang Yong-Shan , Chang Kuan Y.
Published: December 2020

Background and Objective

Not everyone gets sick after an exposure to influenza A viruses (IAV). Although KLRD1 has been identified as a potential biomarker for influenza susceptibility, it remains unclear whether forecasting symptomatic flu infection based on pre-exposure host gene expression might be possible.

Method

To examine this hypothesis, we developed DeepFlu using the state-of-the-art deep learning approach on the human gene expression data infected with IAV subtype H1N1 or H3N2 viruses to forecast who would catch the flu prior to an exposure to IAV.

Results

The results indicated that such forecast is possible and, in other words, gene expression could reflect the strength of host immunity. In the leave-one-person-out cross-validation, DeepFlu based on deep neural network outperformed the models using convolutional neural network, random forest, or support vector machine, achieving 70.0% accuracy, 0.787 AUROC, and 0.758 AUPR for H1N1 and 73.8% accuracy, 0.847 AUROC, and 0.901 AUPR for H3N2. In the external validation, DeepFlu also reached 71.4% accuracy, 0.700 AUROC, and 0.723 AUPR for H1N1 and 73.5% accuracy, 0.732 AUROC, and 0.749 AUPR for H3N2, surpassing the KLRD1 biomarker. In addition, DeepFlu which was trained only by pre-exposure data worked the best than by other time spans and mixed training data of H1N1 and H3N2 did not necessarily enhance prediction. DeepFlu is available athttps://github.com/ntou-compbio/DeepFlu.

Conclusions

DeepFlu is a prognostic tool that can moderately recognize individuals susceptible to the flu and may help prevent the spread of IAV.
Prophage-dependent recombination drives genome structural variation and phenotypic heterogeneity inEscherichia coliO157:H7
Authors: Fitzgerald Stephen F. , Lupolova Nadejda , Shaaban Sharif , Dallman Timothy J. , Greig David , Allison Lesley , Tongue Sue C. , Evans Judith , Henry Madeleine K. , McNeilly Tom N. , Bono James L. , Gally David L.
Published: December 2020

The human zoonotic pathogenEscherichia coliO157 is defined by its extensive prophage repertoire including those that encode Shiga toxin, the factor responsible for inducing life-threatening pathology in humans. As well as introducing genes that can contribute to the virulence of a strain, prophage can enable the generation of large-chromosomal rearrangements (LCRs) by homologous recombination. This work examines the types and frequencies of LCRs across the major lineages of the O157 serogroup and defines the phenotypic consequences of specific structural variants. We demonstrate that LCRs are a major source of genomic variation across all lineages ofE. coliO157 and by using both optical mapping and ONT long-read sequencing demonstrate that LCRs are generated in laboratory cultures started from a single colony and particular variants are selected during animal colonisation. LCRs are biased towards the terminus region of the genome and are bounded by specific prophages that share large regions of sequence homology associated with the recombinational activity. RNA transcriptional profiling and phenotyping of specific structural variants indicated that important virulence phenotypes such as Shiga toxin production, type 3 secretion and motility are affected by LCRs. In summary,E. coliO157 has acquired multiple prophage regions over time that act as genome engineers to continually produce structural variants of the genome. This structural variation is a form of epigenetic regulation that generates sub-population phenotypic heterogeneity with important implications for bacterial adaptation and survival.

Author Summary

Escherichia colihas an ‘open genome’ and has acquired genetic information over evolutionary time, often in the form of bacteriophages that integrate into the bacterial genome (prophages).E. coliO157 is a clonal serogroup that is found primarily in ruminants such as cattle but can cause life-threatening infections in humans.E. coliO157 isolates contain multiple prophages including those that encode Shiga-like toxins which are responsible for the more serious disease associated with human infections. We show in this study that many of these prophages exhibit large regions of sequence similarity that allow rearrangements to occur in the genome generating structural variants. These occur routinely during bacterial culture in the laboratory and the variants are detected during animal colonization. The variants generated can give the bacteria altered phenotypes, such as increased motility or toxin production which can be selected in specific environments and therefore represent a highly dynamic mechanism to generate variation in bacterial populations without a change in overall gene content.