bluuebunny/crossref_metadata_2025_split huggingface dataset:
mokapot: Fast and flexible semi-supervised learning for peptide detection
Authors: Fondrie William E , Noble William S 
Published: December 2020

AbstractProteomics 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

AbstractNeuroanatomical 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

AbstractSummaryWe 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.ResultsWe 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 implementationOur 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

AbstractVision 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

ABSTRACTMosquito 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.IMPORTANCEThe 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

AbstractDevelopment 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.ImportanceTo 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

ABSTRACTRNA 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

AbstractIncreasing 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

AbstractPotato 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 summaryThis 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

AbstractIn 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 summaryAdolescence 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

ABSTRACTBackground and ObjectiveNot 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.MethodTo 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.ResultsThe 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.ConclusionsDeepFlu 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

AbstractThe 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 SummaryEscherichia 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.