bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of novel PCR primer sets for DNA metabarcoding of aquatic insects, and the discovery of some cryptic species
Authors: Takenaka Masaki , Yano Koki , Suzuki Tomoya , Tojo Koji 
Published: November 2021

AbstractDNA barcoding is a powerful tool that provides rapid, accurate, and automatable species identification by using standardized genetic region(s). It can be a powerful tool in various fields of biology such as for revealing the existence of cryptic species and/or rare species and in environmental science such as when monitoring river biota. Biodiversity reduction in recent times has become one of the most serious environmental issues on a worldwide scale. DNA barcoding techniques require the development of sets of universal PCR primers for DNA metabarcoding. We tried to develop universal primer sets for the DNA barcoding of all insect groups. In this study, we succeeded in designing not only universal primer sets for DNA barcoding regions of almost all insects, which were designed to include a hypervariable site between highly conserved sites, but also primer sets for longer fragment sequences for registration in a database. We confirmed successful amplification for 14 orders, 43 families, and 68 species with DNA barcoding in the mtDNA 16S rRNA region, and for 13 orders, 42 families, and 66 species with DNA barcoding in the mtDNA 12S rRNA region. A key feature is that the DNA fragments of the DNA barcoding regions amplified by these primer sets are both short at about 200-bp, and longer fragment sequences will increase the level of data registration in the DNA database. Such resulting database enhancements will serve as a powerful tool for increasingly accurate assessment of biodiversity and genetic diversity.
Fast and optimal sequence-to-graph alignment guided by seeds
Authors: Ivanov Pesho , Bichsel Benjamin , Vechev Martin 
Published: November 2021

AbstractWe present a novel A⋆seed heuristic that enables fast and optimal sequence-to-graph alignment, guaranteed to minimize the edit distance of the alignment assuming non-negative edit costs.We phrase optimal alignment as a shortest path problem and solve it by instantiating the A⋆ algorithm with our seed heuristic. The seed heuristic first extracts non-overlapping substrings (seeds) from the read, finds exact seed matches in the reference, marks preceding reference positions by crumbs, and uses the crumbs to direct the A⋆ search. The key idea is to punish paths for the absence of foreseeable seed matches. We prove admissibility of the seed heuristic, thus guaranteeing alignment optimality.Our implementation extends the free and open source aligner and demonstrates that the seed heuristic outperforms all state-of-the-art optimal aligners including GraphAligner, Vargas, PaSGAL, and the prefix heuristic previously employed by AStarix. Specifically, we achieve a consistent speedup of >60× on both short Illumina reads and long HiFi reads (up to 25kbp), on both the E. coli linear reference genome (1Mbp) and the MHC variant graph (5Mbp). Our speedup is enabled by the seed heuristic consistently skipping >99.99% of the table cells that optimal aligners based on dynamic programming compute.AStarix aligner and evaluations: https://github.com/eth-sri/astarix Full paper: https://www.biorxiv.org/content/10.1101/2021.11.05.467453
Obesity and adiposity have opposing genetic impacts on human blood traits
Authors: Thom Christopher S , Wilken Madison B , Chou Stella T , Voight Benjamin F 
Published: November 2021

AbstractObesity, hyperlipidemia, and truncal adiposity concordantly elevate cardiovascular disease risks, but have unknown genetic effects on blood trait variation. Using Mendelian randomization, we define unexpectedly opposing roles for generalized obesity and truncal adiposity on blood traits. Elevated genetically determined body mass index (BMI) and lipid levels decreased hemoglobin and hematocrit levels, explaining consistent with clinical observations associating obesity and anemia. However, lipid-related effects were confined to erythroid traits, whereas BMI affected multiple blood lineages, indicating broad effects on hematopoiesis. BMI-related effects were unexpectedly opposed by truncal adipose distribution, which increased hemoglobin and blood cell counts across lineages. Conditional analyses indicated genes, pathways, and cell types responsible for these effects, including Leptin Receptor and other blood cell-extrinsic factors in adipocytes and endothelium, which regulate hematopoietic stem and progenitor cell biology. Our findings identify novel roles for obesity and adipose distribution on hematopoiesis and show that genetically determined adiposity plays a previously underappreciated role in determining blood cell formation and function.
Making Common Fund data more findable: Catalyzing a Data Ecosystem
Authors: Charbonneau Amanda L , Brady Arthur , Czajkowski Karl , Aluvathingal Jain , Canchi Saranya , Carter Robert , Chard Kyle , Clarke Daniel J.B. , Creasy Heather H , D’Arcy Mike , Giglio Michelle , Gingrich Alicia , Harris Rayna M , Hodges Theresa K , Ifeonu Olukemi , Jeon Minji , Kropiwnicki Eryk , Lim Marisa C.W. , Liming R. Lee , Mandal Meisha , Munro James B , Nadendla Suvarna , Richter Rudyard , Romano Cia , Rocca-Serra Philippe , Schuler Robert E. , Tangmunarunkit Hongsuda , Waldrop Alex , Williams Cris , Word Karen , Sansone Susanna-Assunta , Ma’ayan Avi , Wagner Rick , Foster Ian , Kesselman Carl , Brown C. Titus , White Owen 
Published: November 2021

AbstractThe Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables users to discover datasets from across the U.S. National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. The CFDE’s federation system is centered on a catalog that ingests metadata from individual Common Fund Program’s Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This uniform Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by the individual DCCs and is designed to enable easy expansion to accommodate new data types. We describe its use to ingest and index data from ten DCCs.
SARS-CoV-2 specific T cell and humoral immune responses upon vaccination with BNT162b2: A 9 months longitudinal study
Authors: Takeuchi Junko S. , Fukunaga Ami , Yamamoto Shohei , Tanaka Akihito , Matsuda Kouki , Kimura Moto , Kamikawa Azusa , Kito Yumiko , Maeda Kenji , Ueda Gohzoh , Mizoue Tetsuya , Ujiie Mugen , Mitsuya Hiroaki , Ohmagari Norio , Sugiura Wataru 
Published: November 2021

AbstractIntroductionThe humoral and cellular immune responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) upon coronavirus disease 2019 (COVID-19) vaccination remain to be clarified. Hence, we aimed to investigate the long-term chronological changes in SARS-CoV-2 specific IgG antibody, neutralizing antibody, and T cell responses during and after receiving the BNT162b2 vaccine.MethodsWe performed serological, neutralization, and T cell assays among 100 hospital workers aged 22-73 years who received the vaccine. We conducted seven surveys up to eight months after the second vaccination dose.ResultsSARS-CoV-2 spike protein-specific IgG (IgG-S) titers and T cell responses increased significantly following the first vaccination dose. The highest titers were observed on day 29 and decreased gradually until the end of the follow-up period. There was no correlation between IgG-S and T cell responses. Notably, T cell responses were detected on day 15, earlier than the onset of neutralizing activity.ConclusionsThis study demonstrated that both IgG-S and T cell responses were detected before acquiring sufficient levels of SARS-CoV-2 neutralizing antibodies. These immune responses are sustained for approximately six–ten weeks but not for seven months or later following the second vaccination, indicating the need for the booster dose (i.e., third vaccination).
Crosstalk between β-catenin and WT1 signalling activity in acute myeloid leukemia
Authors: Wagstaff M , Tsaponina O , Caalim G , Greenfield H , Milton-Harris L , Mancini EJ , Blair A , Heesom KJ , Tonks A , Darley RL , Roberts SG , Morgan RG 
Published: November 2021

Wnt signalling is an evolutionary conserved signal transduction pathway heavily implicated in normal development and disease. The central mediator of this pathway, β-catenin, is frequently overexpressed, mislocalised and overactive in acute myeloid leukaemia (AML) where it mediates the establishment, maintenance and drug resistance of leukaemia stem cells. Critical to the stability, localisation and activity of β-catenin are the protein-protein interactions it forms, yet these are poorly defined in AML. We recently performed the first β-catenin interactome study in blood cells of any kind and identified a plethora of novel interacting partners. This study shows for the first time that β-catenin interacts with Wilms tumour protein (WT1), a protein frequently overexpressed and mutated in AML, in both myeloid cell lines and also primary AML samples. We demonstrate crosstalk between the signalling activity of these two proteins in myeloid cells, and show that modulation of either protein can affect expression of the other. Finally, we demonstrate that WT1 mutations frequently observed in AML can increase stabilise β-catenin and augment Wnt signalling output. This study has uncovered new context-dependent molecular interactions for β-catenin which could inform future therapeutic strategies to target this dysregulated molecule in AML.Article summaryβ-Catenin is frequently dysregulated in acute myeloid leukemia (AML) and protein interactions govern its stability, localization and activity, but these are poorly defined in AML.This study shows for the first time that β-catenin and Wilms tumour protein (WT1) interact and influence each other’s expression level and signalling activity in AML cells, which could inform future therapeutic strategies.
Normalization by orientation-tuned surround in human V1-V3
Authors: Fang Zeming , Bloem Ilona , Olsson Catherine , Ma Wei Ji , Winawer Jonathan 
Published: November 2021

AbstractAn influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a two-stage computation. The first stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of linear filters in quadrature phase. The second stage is normalization, in which a local population of complex cells mutually inhibit one another. Because the population includes cells tuned to a range of orientations and spatial frequencies, the result is that the responses are effectively normalized by the local stimulus contrast. Here, using evidence from human functional MRI, we show that the classical model fails to account for the relative responses to two classes of stimuli: straight, parallel, band-passed contours (gratings), and curved, band-passed contours (snakes). The snakes elicit fMRI responses that are about twice as large as the gratings, yet a traditional divisive normalization model predicts responses that are about the same. Here, motivated by these observations and others from the literature, we implement a divisive normalization model, in which there is a preferential inhibition between cells matched in orientation tuning (“tuned normalization”). We first show that this model accounts for differential responses to these two classes of stimuli. We then show that the model successfully generalizes to other band-pass textures, both in V1 and in extrastriate cortex (V2 and V3). We conclude that even in primary visual cortex, complex features of images such as the degree of heterogeneity, can have large effects on neural responses.
Lipopolysaccharide induces placental mitochondrial dysfunction by reducing MNRR1 levels via a TLR4-independent pathway
Authors: Purandare Neeraja , Kunji Yusef , Xi Yue , Romero Roberto , Gomez-Lopez Nardhy , Fribley Andrew , Grossman Lawrence I. , Aras Siddhesh 
Published: November 2021

AbstractMitochondria play a key role in the growth and development of the placenta, an organ essential for pregnancy in eutherian mammals. Mitochondrial dysfunction has been associated with pregnancy pathologies. However, the mechanisms whereby placental mitochondria sense inflammatory signals at a cellular and mechanistic level are unknown. Mitochondrial Nuclear Retrograde Regulator 1 (MNRR1) is a bi-organellar protein responsible for optimal mitochondrial function to achieve energy and redox homeostasis. In addition, MNRR1 also is required for optimal induction of cellular stress-responsive signaling pathways such as the mitochondrial unfolded protein response (UPRmt). Here, in a lipopolysaccharide-induced model of placental inflammation, we show that MNRR1 levels are reduced in placental tissues and cell lines. Reduction in MNRR1 is associated with mitochondrial dysfunction and enhanced oxidative stress along with activation of pro-inflammatory signaling. Mechanistically, we uncover a non-conventional pathway independent of Toll-like receptor 4 (TLR4) that results in a specific ATM kinase-dependent threonine phosphorylation and activation of a mitochondrial protease, YME1L1, degrading MNRR1. Furthermore, enhancing MNRR1 levels in placental cells either genetically or with specific activators abrogates the bioenergetic defect and induces an anti-inflammatory phenotype, suggesting that MNRR1 is upstream of the mitochondrial dysfunction observed in our model. Reduction in MNRR1 levels is a generalized phenomenon observed in cells under an inflammatory stimulus. We therefore propose MNRR1 as a novel anti-inflammatory therapeutic target in pathologies associated with placental inflammation.
Gestational Cd Exposure in the CD-1 Mouse Sex-Specifically Disrupts Essential Metal Ion Homeostasis
Authors: Jackson Thomas W. , Baars Oliver , Belcher Scott M. 
Published: November 2021

AbstractIn CD-1 mice, gestational-only exposure to cadmium (Cd) causes female-specific hepatic insulin resistance, metabolic disruption, and obesity. To evaluate whether sex differences in cadmium uptake and changes in essential metal concentrations contribute to metabolic outcomes, placental and liver cadmium and essential metal concentrations were quantified in male and female offspring perinatally exposed to 500 ppb CdCl2. Exposure resulted in increased maternal liver Cd+2 concentrations (364 μg/kg) similar to concentrations found in non-occupationally exposed human liver. At gestational day (GD) 18, placental cadmium and manganese concentrations were significantly increased in exposed males and females, and zinc was significantly decreased in females. Placental efficiency was significantly decreased in GD18 exposed males. Increases in hepatic Cd concentrations and a transient prenatal increase in zinc were observed in exposed female liver. Fetal and adult liver iron concentrations were decreased in both sexes, and decreases in hepatic zinc, iron, and manganese were observed in exposed females. Analysis of GD18 placental and liver metallothionein mRNA expression revealed significant Cd-induced upregulation of placental metallothionein in both sexes, and a significant decrease in fetal hepatic metallothionein in exposed females. In placenta, expression of metal ion transporters responsible for metal ion uptake was increased in exposed females. In liver of exposed adult female offspring, expression of the divalent cation importer (Slc39a14/Zip14) decreased, whereas expression of the primary exporter (Slc30a10) increased. These findings demonstrate that Cd can preferentially cross the female placenta, accumulate in the liver, and cause lifelong dysregulation of metal ion concentrations associated with metabolic disruption.
Identification of Low Population States in Cryo-EM Using Deep Learning
Authors: Fraser Alec , Prokhorov Nikolai S. , Miller John-Mark , Knyazhanskaya Ekaterina S. , Leiman Petr G. 
Published: November 2021

AbstractCryo-EM has made extraordinary headway towards becoming a semi-automated, high-throughput structure determination technique. In the general workflow, high-to-medium population states are grouped into two- and three-dimensional classes, from which structures can be obtained with near-atomic resolution and subsequently analyzed to interpret function. However, low population states, which are also functionally important, are often discarded. Here, we describe a technique whereby low population states can be efficiently identified with minimal human effort via a deep convolutional neural network classifier. We use this deep learning classifier to describe a transient, low population state of bacteriophage A511 in the midst of infecting its bacterial host. This method can be used to further automate data collection and identify other functionally important low population states.
Three-dimensional in vitro model of the device-tissue interface reveals innate neuroinflammation can be mitigated by antioxidant ceria nanoparticles
Authors: Atherton Elaina , Hu Yue , Brown Sophie , Papiez Emily , Ling Vivian , Colvin Vicki L. , Borton David A. 
Published: November 2021

AbstractThe recording instability of neural implants due to neuroinflammation at the device-tissue interface (DTI) is a primary roadblock to broad adoption of brain-machine interfaces. While a multiphasic immune response, marked by glial scaring, oxidative stress (OS), and neurodegeneration, is well-characterized, the independent contributions of systemic and local “innate” immune responses are not well-understood. Three-dimensional primary neural cultures provide a unique environment for studying the drivers of neuroinflammation by decoupling the innate and systemic immune systems, while conserving an endogenous extracellular matrix and structural and functional network complexity. We created a three-dimensional in vitro model of the DTI by seeding primary cortical cells around microwires. Live imaging of microtissues over time revealed independent innate neuroinflammation, marked by increased OS, decreased neuronal density, and increased functional connectivity. We demonstrated the use of this model for therapeutic screening by directly applying drugs to neural tissue, bypassing low bioavailability through the in vivo blood brain barrier. As there is growing interest in long-acting antioxidant therapies, we tested efficacy of “perpetual” antioxidant ceria nanoparticles, which reduced OS, increased neuronal density, and protected functional connectivity. Overall, our avascular in vitro model of the DTI exhibited symptoms of OS-mediated innate neuroinflammation which were mitigated by antioxidant intervention.
RUV-III-NB: Normalization of single cell RNA-seq Data
Authors: Salim Agus , Molania Ramyar , Wang Jianan , De Livera Alysha , Thijssen Rachel , Speed Terence P. 
Published: November 2021

AbstractDespite numerous methodological advances, the normalization of single cell RNA-seq (scRNA-seq) data remains a challenging task and the performance of different methods can vary greatly across datasets. Part of the reason for this is the different kinds of unwanted variation, including library size, batch and cell cycle effects, and the association of these with the biology embodied in the cells. A normalization method that does not explicitly take into account cell biology risks removing some of the signal of interest. Furthermore, most normalization methods remove the effects of unwanted variation for the cellembeddingused for clustering-based analysis but not from gene-level data typically used for differential expression (DE) analysis to identify marker genes. Here we propose RUV-III-NB, a statistical method that can be used to remove unwanted variation from both the cellembeddingand gene-level counts. RUV-III-NB explicitly takes into account its potential association with biology when removing unwanted variation via the use of pseudo-replicates. The method can be used for both UMI or sequence read counts and returns adjusted counts that can be used for downstream analyses such as clustering, DE and pseudotime analyses. Using five publicly available datasets that encompass different technological platforms, kinds of biology and levels of association between biology and unwanted variation, we show that RUV-III-NB manages to remove library size and batch effects, strengthen biological signals, improve differential expression analyses, and lead to results exhibiting greater concordance with independent datasets of the same kind. The performance of RUV-III-NB is consistent across the five datasets and is not sensitive to the number of factors assumed to contribute to the unwanted variation. It also shows promise for removing other kinds of unwanted variation such as platform effects. The method is implemented as a publicly available R package available fromhttps://github.com/limfuxing/ruvIIInb.
Circuit-specific sonogenetic stimulation of the deep brain elicits distinct signaling and behaviors in freely moving mice
Authors: Xian Quanxiang , Qiu Zhihai , Kala Shashwati , Wong Kin Fung , Murugappan Suresh , Wu Yong , Hou Xuandi , Zhu Jiejun , Guo Jinghui , Sun Lei 
Published: November 2021

AbstractSonogenetics uses heterologously-expressed proteins to sensitize neurons to ultrasound, enabling selective, non-invasive, and deep brain stimulation. However, its ability to modulate specific circuits or induce behavioral changes remains to be studied and characterized. Here, we demonstrate that sonogenetics enables efficient activation of well-defined neural circuits by transcranial low-intensity, low-frequency ultrasonic stimulation with high spatiotemporal resolution. Targeted neurons in subcortical regions were made to express a mechanosensitive ion channel (MscL-G22S). Ultrasound could trigger activity in MscL-expressing neurons in the dorsal striatum without increased activation in neighboring regions, and increase locomotion in freely-moving mice. Ultrasound stimulation of MscL-expressing neurons in the ventral tegmental area could activate the mesolimbic pathway to trigger dopamine release in the nucleus accumbens and modulate appetitive conditioning. In MscL-expressing cells, neuronal responses to ultrasound pulses were rapid, reversible and repeatable. Altogether, we show that sonogenetics can selectively manipulate targeted cells to activate defined neural pathways and affect behaviors.