bluuebunny/crossref_metadata_2025_split huggingface dataset:
Substantial Impact of Post Vaccination Contacts on Cumulative Infections during Viral Epidemics
Authors: Rochman Nash D. , Wolf Yuri I. , Koonin Eugene V. 
Published: December 2020

AbstractBackgroundThe start of 2021 will be marked by a global vaccination campaign against the novel coronavirus SARS-CoV-2. Formulating an optimal distribution strategy under social and economic constraints is challenging. Optimal distribution is additionally constrained by the potential emergence of vaccine resistance. Analogous to chronic low-dose antibiotic exposure, recently inoculated individuals who are not yet immune play an outsized role in the emergence of resistance. Classical epidemiological modelling is well suited to explore how the behavior of the inoculated population impacts the total number of infections over the entirety of an epidemic.MethodsA deterministic model of epidemic evolution is analyzed, with 7 compartments defined by their relationship to the emergence of vaccine-resistant mutants and representing three susceptible populations, three infected populations, and one recovered population. This minimally computationally intensive design enables simulation of epidemics across a broad parameter space. The results are used to identify conditions minimizing the cumulative number of infections.ResultsWhen an escape variant is only modestly less infectious than the originating strain within a naïve population, there exists an optimal rate of vaccine distribution. Exceeding this rate increases the cumulative number of infections due to vaccine escape. Analysis of the model also demonstrates that inoculated individuals play a major role in the mitigation or exacerbation of vaccine-resistant outbreaks. Modulating the rate of host-host contact for the inoculated population by less than an order of magnitude can alter the cumulative number of infections by more than 20%.ConclusionsMathematical modeling shows that optimization of the vaccination rate and limiting post-vaccination contacts can affect the course of an epidemic. Given the relatively short window between inoculation and the acquisition of immunity, these results might merit consideration for an immediate, practical public health response.
Intracranial EEG biomarkers for seizure lateralization in rapidly-bisynchronous epilepsy after laser corpus callosotomy
Authors: Khuvis Simon , Hwang Sean T. , Mehta Ashesh D. 
Published: December 2020

AbstractObjectiveIt has been asserted that high-frequency analysis of intracranial EEG (iEEG) data may yield information useful in localizing epileptogenic foci.MethodsWe tested whether proposed biomarkers could predict lateralization based on iEEG data collected prior to corpus callostomy (CC) in patients with bisynchronous epilepsy, whose seizures lateralized definitively post-CC. Lateralization data derived from algorithmically-computed ictal phase-locked high gamma (PLHG), high gamma amplitude (HGA) and line length (LL), as well as interictal high-frequency oscillation (HFO) and interictal epileptiform discharge (IED) rate metrics were compared against ground-truth lateralization from post-CC ictal iEEG.ResultsPre-CC unilateral IEDs were more frequent on the more-pathologic side in all subjects. HFO rate predicted lateralization in one subject, but was sensitive to detection threshold. On pre-CC data, no ictal metric showed better predictive power than any other. All post-corpus callosotomy seizures lateralized to the pathological hemisphere using PLHG, HGA and LL metrics.ConclusionsWhile quantitative metrics of IED rate and ictal HGA, PHLG and LL all accurately lateralize based on post-CC iEEG, only IED rate consistently does so based on pre-CC data.SignificanceQuantitative analysis of IEDs may be useful in localizing seizure pathology. More work is needed to develop reliable techniques for high-frequency iEEG analysis.HighlightsWe evaluated intracranial EEG biomarkers in corpus callostomy patients with bisynchronous seizures pre-operatively.Despite testing more contemporary metrics, only interictal epileptiform discharge counting consistently lateralized seizure foci.High-frequency metrics, especially high-frequency oscillation counting, appear to be sensitive to parameter selection.
Hemodynamic changes in response to excitatory and inhibitory modulations by transcranial magnetic stimulation at the human sensorimotor cortex
Authors: Lee Hsin-Ju , Nyrhinen Mikko , Ilmoniemi Risto J. , Lin Fa-Hsuan 
Published: December 2020

AbstractTranscranial magnetic stimulation (TMS) can non-invasively induce both excitatory and inhibitory neuronal activity. However, the neurophysiological basis for both kinds of modulation remains elusive. In this study, with a controlled dosage over the 30-s interval, we elicited excitatory and inhibitory TMS modulations over the human primary motor cortex (M1) with TMS bursts of high (10-Hz and 30-Hz) and low frequency (0.5-Hz), respectively, and took functional magnetic resonance images (fMRI). Excitatory and inhibitory modulations were evidenced by changes in motor evoked potentials (MEP). Significantly increased fMRI signal at M1 was only detected under excitatory high-frequency TMS but not during inhibitory low-frequency TMS. The supplementary motor area (SMA) had significant fMRI signal changes after both excitatory and inhibitory TMS. The topology of the activated M1 and SMA matched the activated sensorimotor network during voluntary movement. The precuneus was selectively activated with bursts of five TMS pulses. These findings demonstrated the asymmetric hemodynamic responses to excitatory and inhibitory TMS modulations with region-dependent relationships between the local fMRI signal changes and TMS dosage over different time scales.
Long-range GABAergic projections contribute to cortical feedback control of sensory processing
Authors: Mazo Camille , Nissant Antoine , Saha Soham , Peroni Enzo , Lledo Pierre-Marie , Lepousez Gabriel 
Published: December 2020

AbstractCortical sensory areas send excitatory projections back to earlier stage of sensory processing. Here, we uncover for the first time the existence of a corticofugal inhibitory feedback between two sensory areas, paralleling the well-documented excitatory feedback. In the olfactory system, we reveal that a subpopulation of GABAergic neurons in the anterior olfactory nucleus and anterior piriform cortex target the olfactory bulb. These long-range inhibitory inputs synapse with both local and output olfactory bulb neurons, mitral and tufted cells. Optogenetic stimulation coupled to in vivo imaging and network modeling showed that activation these inhibitory inputs drives a net subtractive inhibition of both spontaneous and odor-evoked activity in local as well as mitral and tufted cells. Further, cortical GABAergic feedback stimulation enhanced separation of population odor responses in tufted cells, but not mitral cells. Targeted pharmacogenetic silencing of cortical GABAergic axon terminals in the OB impaired discrimination of similar odor mixtures. We propose here that cortical GABAergic feedback represents a new circuit motif in sensory systems, involved in refining sensory processing and perception.
Automation of Leaf Counting in Maize and Sorghum Using Deep Learning
Authors: Miao Chenyong , Guo Alice , Thompson Addie M. , Yang Jinliang , Ge Yufeng , Schnable James C. 
Published: December 2020

ABSTRACTLeaf number and leaf emergence rate are phenotypes of interest to plant breeders, plant geneticists, and crop modelers. Counting the extant leaves of an individual plant is straightforward even for an untrained individual, but manually tracking changes in leaf numbers for hundreds of individuals across multiple time points is logistically challenging. This study generated a dataset including over 150,000 maize and sorghum images for leaf counting projects. A subset of 17,783 images also includes annotations of the positions of individual leaf tips. With these annotated images, we evaluate two deep learning-based approaches for automated leaf counting: the first based on counting-by-regression from whole image analysis and a second based on counting-by-detection. Both approaches can achieve RMSE (root of mean square error) smaller than one leaf, only moderately inferior to the RMSE between human annotators of between 0.57 and 0.73 leaves. The counting-by-regression approach based on CNNs (convolutional neural networks) exhibited lower accuracy and increased bias for plants with extreme leaf numbers which are underrepresented in this dataset. The counting-by-detection approach based on Faster R-CNN object detection models achieve near human performance for plants where all leaf tips are visible. The annotated image data and model performance metrics generated as part of this study provide large scale resources for the comparison and improvement of algorithms for leaf counting from image data in grain crops.
Robust retrieval of data stored in DNA by de Bruijn graph-basedde novostrand assembly
Authors: Song Lifu , Geng Feng , Gong Ziyi , Chen Xin , Tang Jijun , Gong Chunye , Zhou Libang , Xia Rui , Han Mingzhe , Xu Jingyi , Li Bingzhi , Yuan Yingjin 
Published: December 2020

AbstractDNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as the strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. Through ade novoassembly strategy, we developed an algorithm based on the de Bruijn graph and greedy path search (DBGPS) to address these issues. DBGPS shows distinct advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large data scale simulations. Remarkably, 6.8 MB of data can be retrieved accurately from a seriously corrupted sample that has been treated at 70 °C for 70 days. With DBGPS, we were able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.One-Sentence SummaryA de Bruijn graph-basedde novoassembly algorithm for DNA data storage enables fast and robust data readouts even with DNA samples that have been severely corrupted.
Centimeter-scale quorum sensing dictates collective survival of differentiating embryonic stem cells
Authors: Daneshpour Hirad , van den Bersselaar Pim , Youk Hyun 
Published: December 2020

SUMMARYCells can help each other replicate by communicating with diffusible molecules. In cell cultures, molecules may diffuse within a cell colony or between adjacent or distant colonies. Determining which cell helps which cell’s replication is challenging. We developed a systematic approach, integrating modeling and experiments, for determining the length-scales of cell-cell communication (from microns to centimeters). With this approach, we discovered that differentiating murine ES cells, scattered across centimeters on a dish, communicate over millimeters to form one macroscopic entity that survives if and only if its centimeter-scale population-density is above a threshold value. Single-cell-level measurements, transcriptomics, and modeling revealed that this “macroscopic quorum sensing” arises from differentiating ES cells secreting and sensing survival-promoting FGF4 that diffuses over millimeters and activates YAP1-induced survival mechanisms. Through the same mechanism, a lone macroscopic, but not microscopic, colony survives differentiation. Our work rigorously establishes thatin vitroES-cell differentiation relies on macroscopic cooperation.
Unbiased population heterozygosity estimates from genome-wide sequence data
Authors: Schmidt Thomas L , Jasper Moshe , Weeks Andrew R , Hoffmann Ary A 
Published: December 2020

AbstractHeterozygosity is a metric of genetic variability frequently used to inform the management of threatened taxa. Estimating observed and expected heterozygosities from genome-wide sequence data has become increasingly common, and these estimates are often derived directly from genotypes at single nucleotide polymorphism (SNP) markers. While many SNP markers can provide precise estimates of genetic processes, the results of ‘downstream’ analysis with these markers may depend heavily on ‘upstream’ filtering decisions.Here we explore the downstream consequences of sample size, rare allele filtering, missing data thresholds and known population structure on estimates of observed and expected heterozygosity using two reduced-representation sequencing datasets, one from the mosquitoAedes aegypti(ddRADseq) and the other from a threatened grasshopper,Keyacris scurra(DArTseq).We show that estimates based on polymorphic markers only (i.e. SNP heterozygosity) are always biased by global sample size (N), with smaller N producing larger estimates. By contrast, results are unbiased by sample size when calculations consider monomorphic as well as polymorphic sequence information (i.e. genome-wide or autosomal heterozygosity). SNP heterozygosity is also biased when differentiated populations are analysed together, while autosomal heterozygosity remains unbiased. We also show that when nucleotide sites with missing genotypes are included, observed and expected heterozygosity estimates diverge in proportion to the amount of missing data permitted at each site.We make three recommendations for estimating genome-wide heterozygosity: (i) autosomal heterozygosity should be reported instead of (or in addition to) SNP heterozygosity; (ii) sites with any missing data should be omitted; (iii) populations should be analysed in independent runs. This should facilitate comparisons within and across studies and between observed and expected measures of heterozygosity.
Prevalent, protective, and convergent IgG recognition of SARS-CoV-2 non-RBD spike epitopes in COVID-19 convalescent plasma
Authors: Voss William N. , Hou Yixuan J. , Johnson Nicole V. , Kim Jin Eyun , Delidakis George , Horton Andrew P. , Bartzoka Foteini , Paresi Chelsea J. , Tanno Yuri , Abbasi Shawn A. , Pickens Whitney , George Katia , Boutz Daniel R. , Towers Dalton M. , McDaniel Jonathan R. , Billick Daniel , Goike Jule , Rowe Lori , Batra Dhwani , Pohl Jan , Lee Justin , Gangappa Shivaprakash , Sambhara Suryaprakash , Gadush Michelle , Wang Nianshuang , Person Maria D. , Iverson Brent L. , Gollihar Jimmy D. , Dye John , Herbert Andrew , Baric Ralph S. , McLellan Jason S. , Georgiou George , Lavinder Jason J. , Ippolito Gregory C. 
Published: December 2020

SUMMARYAlthough humoral immunity is essential for control of SARS-CoV-2, the molecular composition, binding epitopes and effector functions of the immunoglobulin G (IgG) antibodies that circulate in blood plasma following infection are unknown. Proteomic deconvolution of the circulating IgG repertoire (Ig-Seq1) to the spike ectodomain (S-ECD2) in four convalescent study subjects revealed that the plasma response is oligoclonal and directed predominantly (>80%) to S-ECD epitopes that lie outside the receptor binding domain (RBD). When comparing antibodies directed to either the RBD, the N-terminal domain (NTD) or the S2 subunit (S2) in one subject, just four IgG lineages (1 anti-S2, 2 anti-NTD and 1 anti-RBD) accounted for 93.5% of the repertoire. Although the anti-RBD and one of the anti-NTD antibodies were equally potently neutralizingin vitro, we nonetheless found that the anti-NTD antibody was sufficient for protection to lethal viral challenge, either alone or in combination as a cocktail where it dominated the effect of the other plasma antibodies. We identifiedin vivoprotective plasma anti-NTD antibodies in 3/4 subjects analyzed and discovered a shared class of antibodies targeting the NTD that utilize unmutated or near-germline IGHV1-24, the most electronegative IGHV gene in the human genome. Structural analysis revealed that binding to NTD is dominated by interactions with the heavy chain, accounting for 89% of the entire interfacial area, with germline residues uniquely encoded by IGHV1-24 contributing 20% (149 Å2). Together with recent reports of germline IGHV1-24 antibodies isolated by B-cell cloning3,4our data reveal a class of shared IgG antibodies that are readily observed in convalescent plasma and underscore the role of NTD-directed antibodies in protection against SARS-CoV-2 infection.
Comparative analysis of loop-mediated isothermal amplification (LAMP)-based assays for rapid detection of SARS-CoV-2 genes
Authors: Urrutia-Cabrera Daniel , Liou Roxanne Hsiang-Chi , Chan Jianxiong , Hung Sandy Shen-Chi , Hewitt Alex W , Martin Keith R , Kwan Patrick , Wong Raymond Ching-Bong 
Published: December 2020

AbstractThe COVID-19 pandemic caused by SARS-CoV-2 has infected millions worldwide and there is an urgent need to increase our diagnostic capacity to identify infected cases. Although RT-qPCR remains the gold standard for SARS-CoV-2 detection, this method requires specialised equipment in a diagnostic laboratory and has a long turn-around time to process the samples. To address this, several groups have recently reported development of loop-mediated isothermal amplification (LAMP) as a simple, low cost and rapid method for SARS-CoV-2 detection. Herein we present a comparative analysis of three LAMP-based assays that target different regions of the SARS-CoV-2: ORF1ab RdRP, ORF1ab nsp3 and Gene N. We perform a detailed assessment of their sensitivity, kinetics and false positive rates for SARS-CoV-2 diagnostics in LAMP or RT-LAMP reactions, using colorimetric or fluorescent detection. Our results independently validate that all three assays can detect SARS-CoV-2 in 30 minutes, with robust accuracy at detecting as little as 1000 RNA copies and the results can be visualised simply by color changes. We also note the shortcomings of these LAMP-based assays, including variable results with shorter reaction time or lower load of SARS-CoV-2, and false positive results in some experimental conditions. Overall for RT-LAMP detection, the ORF1ab RdRP and ORF1ab nsp3 assays have higher sensitivity and faster kinetics for detection, whereas the Gene N assay exhibits no false positives in 30 minutes reaction time. This study provides validation of the performance of LAMP-based assays for SARS-CoV-2 detection, which have important implications in development of point-of-care diagnostic for SARS-CoV-2.
Single Cell atlas of uterine myometrium and leiomyomas reveals diverse and novel cell types of non-monoclonal origin
Authors: Goad Jyoti , Rudolph Joshua , Wei Jian-Jun , Bulun Serdar E , Chakravarti Debabrata , Rajkovic Aleksandar 
Published: December 2020

AbstractUterine leiomyomas are the most common tumors of the female reproductive tract with significant morbidity that includes excessive bleeding, infertility and pregnancy complications. The origin and cellular composition of leiomyomas is controversial, yet very important in better understanding the pathogenesis of these tumors. We applied single-cell RNA sequencing to better understand cellular heterogeneity of uterine leiomyomas and normal myometrium at the molecular level. Our data reveal previously unknown heterogeneity in the smooth muscle cells, fibroblast cells, and endothelial cells of normal myometrium and leiomyomas. We discovered a novel lymphatic endothelial cell population in uterine leiomyomas and that the immune as well as transcriptional profile of leiomyomas isMED12genotype-dependent. Moreover, we show that leiomyoma cell moiety is not monoclonal in nature. Our work describes unprecedented single cell resolution of normal uterine myometrium and leiomyoma tumors and provides insight into tumor specific hormone responsiveness and extracellular matrix accumulation.
Variation in pyrethroid resistance phenotypes inAnopheles darlingifrom residual malaria transmission area: warning on suspected resistance built-up in French Guiana
Authors: Vezenegho Samuel , Carinci Romuald , Issaly Jean , Nguyen Christophe , Gaborit Pascal , Ferraro Laetitia , Lacour Guillaume , Mosnier Emilie , de Santi Vincent Pommier , Epelboin Yanouk , Girod Romain , Briolant Sébastien , Dusfour Isabelle 
Published: December 2020

ABSTRACTAnopheles darlingiis the major vector of malaria in South America. In French Guiana, malaria transmission occurs inland and along the rivers with a particular reemergence in the lower Oyapock area. Control against malaria vector is performed using deltamethrin indoor residual spraying and long lasting impregnated bednets. For four years, the level of resistance to pyrethroids was monitored using CDC bottle tests inAn. darlingipopulations. Resistance built-up was suspected in a mosquito population in malaria endemic area but did not sustained, supposably due to the reintroduction of susceptible alleles. No mutation on the insecticide target genes was found, metabolic resistance is then suspected.
Unique intramolecular oxidative rearrangement N-nitrosation mechanism of non-heam iron-containing enzyme SznF
Authors: Wang Junkai , Wang Xixi , Ouyang Qingwen , Liu Wei , Tan Hongwei , Li Xichen , Chen Guangju 
Published: December 2020

ABSTRACTNon-heam iron-dependent enzyme SznF catalyzes a critical step of the L-arginine derived guanidine group rearrangement to produce the N-nitrosourea pharmacophore in the process of SZN biosynthesis. The intramolecular oxidative rearrangement process is accomplished in the Fe(II)-containing active site located at the cupin domain of SznF, with which the catalytic mechanism remains elusive. In this work, density functional theory methods have been employed to investigate possible catalytic mechanisms of SznF. The N-nitrosation reaction in SznF was found to follow an energetically favorable pathway which includes six consecutive steps: (1) formation of FeII-superoxo species with dioxgen binding on the iron center; (2) superoxo group attacking on the Cεof substrate to form the peroxo-bridge complex; (3) Cε-Nωbond homolysis to release NωO; (4) peroxo bridge heterolytic cleavage; (5) deprotonation ofby Fe-O group; (6) thecouples with the NωO group and generates the N-nitroso product. The reaction proceeds in an unexpected way during which the electrons shuttle among two NO groups of the substrate and the peroxo moiety to promote Cε-Nωbond homolysis and O-O bond heterolysis sequentially without generating high-valent Fe-O species, which is distinct from any known reactions catalyzed by the iron-containing enzyme. The unusual mechanism of SznF shed light on the area of enzymatic N-nitrosation reactions.
hRUV: Hierarchical approach to removal of unwanted variation for large-scale metabolomics data
Authors: Kim Taiyun , Tang Owen , Vernon Stephen T , Kott Katharine A , Koay Yen Chin , Park John , James David , Speed Terence P , Yang Pengyi , O’Sullivan John F. , Figtree Gemma A , Yang Jean Yee Hwa 
Published: December 2020

AbstractLiquid chromatography-mass spectrometry based metabolomics studies are increasingly applied to large population cohorts, running for several weeks to months, even extending to years of data acquisition. This inevitably introduces unwanted intra- and inter-batch variations over time that can overshadow true biological signals and thus hinder potential biological discoveries. To date, normalization approaches have struggled to mitigate the variability introduced by technical factors whilst preserving biological variance, especially for protracted acquisitions. Here, we designed an experiment with an arrangement to embed biological sample replicates to measure the variance within and between batches for over 1,000 human plasma samples run over 44 days. We integrate these replicates in a novel workflow to remove unwanted variation in a hierarchical structure (hRUV) by progressively merging the adjustments in neighbouring batches. We demonstrate significant improvement of hRUV over existing methods in maintaining biological signals whilst removing unwanted variation for large scale metabolomics studies.