bluuebunny/crossref_metadata_2025 huggingface dataset:
X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs
Authors: Duncan Keith E , Czymmek Kirk J , Jiang Ni , Thies August C. , Topp Christopher N.
Published: December 2020

Capturing complete internal anatomies of plant organs and tissues within their relevant morphological context remains a key challenge in plant science. While plant growth and development are inherently multiscale, conventional light, fluorescence, and electron microscopy platforms are typically limited to imaging of plant microstructure from small flat samples that lack direct spatial context to, and represent only a small portion of, the relevant plant macrostructures. We demonstrate technical advances with a lab-based X-ray microscope (XRM) that bridge the imaging gap by providing multiscale high-resolution 3D volumes of intact plant samples from the cell to whole plant level. Serial imaging of a single sample is shown to provide sub-micron 3D volumes co-registered with lower magnification scans for explicit contextual reference. High quality 3D volume data from our enhanced methods facilitate more sophisticated and effective computational segmentation and analyses than have previously been employed for X-ray based imaging. Advances in sample preparation make multimodal correlative imaging workflows possible, where a single resin-embedded plant sample is scanned via XRM to generate a 3D cell-level map, and then used to identify and zoom in on sub-cellular regions of interest for high resolution scanning electron microscopy. In total, we present the methodologies for use of XRM in the multiscale and multimodal analysis of 3D plant features using numerous economically and scientifically important plant systems.
Novel fungal metal-dependent GH54 α-L-arabinofuranosidase: expanded substrate specificity and potential use for plant biomass degradation
Authors: Motta Maria Lorenza Leal , Filho Jaire Alves Ferreira , de Melo Ricardo Rodrigues , Murakami Leticia Maria Zanphorlin , dos Santos Clelton Aparecido , de Souza Anete Pereira
Published: December 2020

Trichodermagenus fungi present great potential for the production of carbohydrate-active enzymes (CAZYmes), including glycoside hydrolase (GH) family members. From a renewability perspective, CAZYmes can be biotechnologically exploited to convert plant biomass into free sugars for the production of advanced biofuels and other high-value chemicals. GH54 is an attractive enzyme family for biotechnological applications because many GH54 enzymes are bifunctional. Thus, GH54 enzymes are interesting targets in the search for new enzymes for use in industrial processes such as plant biomass conversion. Herein, a novel metal-dependent GH54 arabinofuranosidase (ThABF) from the cellulolytic fungusTrichoderma harzianumwas identified and biochemically characterized. Initialin silicosearches were performed to identify the GH54 sequence. Next, the gene was cloned and heterologously overexpressed inEscherichia coli. The recombinant protein was purified, and the enzymes biochemical and biophysical properties were assessed. The GH54 members show wide functional diversity and specifically remove plant cell decorations including arabinose and galactose, in the presence of a metallic cofactor. Plant cell wall decoration have a major impact on lignocellulosic substrate conversion into high-value chemicals. These results expand the known functional diversity within the GH54 family, showing the potential of a novel arabinofuranosidase for plant biomass degradation.
Effect of land use, habitat suitability, and hurricanes on the population connectivity of an endemic insular bat
Authors: Calderón-Acevedo Camilo A. , Rodríguez-Durán Armando , Soto-Centeno J. Angel
Published: December 2020

Habitat loss and fragmentation are a leading cause of vertebrate population declines and extinction. Urbanization and natural disasters disrupt landscape connectivity, effectively isolating populations and increasing the risk of local extirpation particularly in island systems. Puerto Rico, one of the most isolated islands in the Caribbean, is home to 13 bat species that have been differentially affected by disturbance during the Anthropocene. We used circuit theory to model the landscape connectivity within Puerto Rico with the goal of understanding how fragmentation affects corridors among forested areas. Models combined species occurrences, land use, habitat suitability, and vegetation cover data to examine connectivity in the endemic bat Stenoderma rufum, and also at the bat community level across the island. Urbanization in Puerto Rico affected bat connectivity overall from east to west and underscored protected and rustic areas for the maintenance of forest corridors. Suitable habitat provided a reliable measure of connectivity among potential movement corridors that connected more isolated areas. We found that intense hurricanes can disrupt forest integrity and affect connectivity of suitable habitat. Some of the largest protected areas in the east of Puerto Rico are at an increasing risk of becoming disconnected from more continuous forest patches. The disruption of corridors that maintain connectivity on the island could explain previous findings of the slow post-hurricane population recovery of S. rufum. Given the increasing rate of urbanization, this pattern could also apply to other vertebrates not analyzed in this study. Our findings show the importance of maintaining forest integrity, emphasizing the considerable conservation value of rustic areas for the preservation of local biodiversity.
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

Background

The 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.

Methods

A 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.

Results

When 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%.

Conclusions

Mathematical 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

Objective

It has been asserted that high-frequency analysis of intracranial EEG (iEEG) data may yield information useful in localizing epileptogenic foci.

Methods

We 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.

Results

Pre-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.

Conclusions

While 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.

Significance

Quantitative analysis of IEDs may be useful in localizing seizure pathology. More work is needed to develop reliable techniques for high-frequency iEEG analysis.

Highlights

We 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

Transcranial 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

Cortical 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.
A scale-dependent measure of system dimensionality
Authors: Recanatesi Stefano , Bradde Serena , Balasubramanian Vijay , Steinmetz Nicholas A , Shea-Brown Eric
Published: December 2020

A fundamental problem in science is uncovering the effective number of dynamical degrees of freedom in a complex system, a quantity that depends on the spatio-temporal scale at which the system is observed. Here, we propose a scale-dependent generalization of a classic enumeration of latent variables, the Participation Ratio. We show how this measure relates to conventional quantities such as the Correlation dimension and Principal Component Analysis, and demonstrate its properties in dynamical systems such as the Lorentz attractor. We apply the method to neural population recordings in multiple brain areas and brain states, and demonstrate fundamental differences in the effective dimensionality of neural activity in behaviorally engaged states versus spontaneous activity. Our method applies broadly to multivariate data across fields of science.
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

Leaf 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

DNA 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 Summary

A 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

Cells 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

Heterozygosity 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

Although 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

The 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

Uterine 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

Anopheles 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

Non-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

Liquid 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.
Inclusion of maintenance energy improves the intracellular flux predictions of CHO
Authors: Széliová Diana , Štor Jerneja , Thiel Isabella , Weinguny Markus , Hanscho Michael , Lhota Gabriele , Borth Nicole , Zanghellini Jürgen , Ruckerbauer David E , Rocha Isabel
Published: December 2020

Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.
Institutionalizing an Evidence-Based Practice in a Selected Government Agency in Nigeria
Authors: Nwaichi E. O. , Chidebe I. , Osuoha J. O. , Chimezie E. , Mbaoji C. , Ifeanyi-Obi C. C. , Ugwoha E.O. , Odogwu B. , Okengwu U. , Olua V. , Oghenekaro L U. , Agbagwa O. E. , Frank-Peterside N. , Ozah M. A. , Raphael C. , Ugiomoh I. , Nwoha P. A. , Akpoji B. A.
Published: December 2020

The need to tackle the discrepancy between research outputs and the execution of the findings into real practice is a crucial factor in establishing evidence-based practice in a selected government agency. There is a need to increase the number of experts in our education sector who can synthesise, translate, and package the evidence for ready use by decision-makers and to foster entrepreneurship in Africa. To achieve this, the activities of a 28-man Evidence Leaders in Africa (ELA) team were recruited to drive the project through capacity building training and workshop sessions. Thereafter, a non-random purposive sampling technique targeted at policy makers at various government and non-governmental organizations was adopted as the study design. In all, purposive administration of 424 copies of questionnaire to individuals in different governmental and non-governmental organizations was done by the recruited personnel. The retrieved data from the questionnaire were analyzed using standard statistical method. Socio-demographic characteristics of respondents reveal 34% representation of (31-40 years) age bracket, with (57%) of them working in the University spanning over 2 to 5years (47%) work experience. Approximately 64% of the respondents are not aware of EIDM while 71% had no understanding of EIDM. As regards knowledge of EIDM, 36% had no knowledge of EIDM, 29% had moderate knowledge, 34% were beginners while approximately 1% had advanced knowledge of EIDM. Also, approximately 99% of the respondents have neither been trained nor involved in training others in EIDM. It was also observed that 8.5% of the respondents were policy-makers in the organization, yet 90.7% of the respondents agree that EIDM is useful in policy-making while 81.3% of the respondents engage their colleagues in EIDM. From this study, it is safe to infer that institutionalizing EIDM in NNMDA has numerous benefits as shown by the findings of this study. This will only be possible when all parties involved in producing and using research evidence are well informed and knowledgeable in EIDM.
Classification of protein binding ligands using structural dispersion of binding site atoms from principal axes
Authors: Premarathna Galkande Iresha , Ellingson Leif
Published: December 2020

Many researchers have studied the relationship between the biological functions of proteins and the structures of both their overall backbones of amino acids and their binding sites. A large amount of the work has focused on summarizing structural features of binding sites as scalar quantities, which can result in a great deal of information loss since the structures are three-dimensional. Additionally, a common way of comparing binding sites is via aligning their atoms, which is a computationally intensive procedure that substantially limits the types of analysis and modeling that can be done. In this work, we develop a novel encoding of binding sites as covariance matrices of the distances of atoms to the principal axes of the structures. This representation is invariant to the chosen coordinate system for the atoms in the binding sites, which removes the need to align the sites to a common coordinate system, is computationally efficient, and permits the development of probability models. These can then be used to both better understand groups of binding sites that bind to the same ligand and perform classification for these ligand groups. We demonstrate the effectiveness of our method through classification studies with two benchmark datasets using nearest mean and polytomous logistic regression classifiers.
What we can and what we cannot see with extracellular multielectrodes
Authors: Chintaluri Chaitanya , Bejtka Marta , Średniawa Władysław , Czerwiński Michał , Dzik Jakub M. , Jędrzejewska-Szmek Joanna , Kondrakiewicz Kacper , Kublik Ewa , Wójcik Daniel K.
Published: December 2020

Extracellular recording is an accessible technique used in animals and humans to study the brain physiology and pathology. As the number of recording channels and their density grows it is natural to ask how much improvement the additional channels bring in and how we can optimally use the new capabilities for monitoring the brain. Here we show that for any given distribution of electrodes we can establish exactly what information about current sources in the brain can be recovered and what information is strictly unobservable.

We demonstrate this in the general setting of previously proposed kernel Current Source Density method and illustrate it with simplified examples as well as using evoked potentials from the barrel cortex obtained with a Neuropixels probe and with compatible model data.

Author Summary

Every set of measurements is a window into reality rendering its incomplete or distorted picture. It is often difficult to relate the obtained representation of the world to underlying ground truth. Here we show, for brain electrophysiology, for arbitrary experimental setup (distribution of electrodes), and arbitrary analytical setup (function space of current source densities), that one can identify distributions of current sources which can be recovered precisely, and those which are invisible in the system. This shows what is and what is not observable in the studied system for a given setup, allows to improve the analysis results by modifying analytical setup, and facilitates interpretation of the measured sets of LFP, ECoG and EEG recordings.
CLEC-2 promotes inflammatory peritoneal macrophage emigration to draining lymph nodes during endotoxemia
Authors: Bourne Joshua H. , Beristain-Covarrubias Nonantzin , Zuidscheroude Malou , Campos Joana , Di Ying , Garlick Evelyn , Colicchia Martina , Terry Lauren V. , Thomas Steven G. , Brill Alexander , Bayry Jagadeesh , Watson Steve P. , Rayes Julie
Published: December 2020

Macrophage recruitment during sterile inflammation and infection is essential to clear pathogens, apoptotic cells and debris. However, persistent macrophage accumulation leads to chronic inflammation. Platelets are emerging as key modulators of the inflammatory response. Here, we identify that platelet C-type-lectin-like receptor-2 (CLEC-2) is a crucial immunomodulatory receptor through the interaction with podoplanin, upregulated on inflammatory macrophages.

Mechanistically, platelet CLEC-2 upregulates the expression of podoplanin and its co-ligands CD44 and ERM proteins, leading to actin rearrangement and promotion of cell migration; this is mimicked by recombinant CLEC-2-Fc (rCLEC-2-Fc). Treatment of LPS-challenged mice with rCLEC-2-Fc induces a rapid emigration of peritoneal macrophages to mesenteric lymph nodes, through a gradient generated by the podoplanin ligand, CCL21, to prime T cells. We propose that crosslinking podoplanin using rCLEC-2-Fc is a novel, cell-specific strategy to accelerate macrophage removal from the site of inflammation, and hence promote the resolution of the inflammatory response.

Visual Abstract

Persistent macrophage accumulation in inflamed tissue leads to chronic inflammation and organ damage. Bourne et al. identify recombinant CLEC-2-Fc crosslinking podoplanin on inflammatory macrophages, as a cell-specific strategy to accelerate their emigration to draining lymph nodes, and reduce local inflammation.
To See, Not to See, or to See Poorly: Perceptual Quality and Guess Rate as a Function of Electroencephalography (EEG) Brain Activity in an Orientation Perception Task
Authors: Sheldon Sarah S. , Mathewson Kyle E.
Published: December 2020

Detection of visual stimuli fluctuates over time, and these fluctuations have been shown to correlate with time-domain evoked activity and frequency-domain periodic activity. However, it is unclear if these fluctuations are related to a change in guess rate, perceptual quality, or both. Here we determined whether the quality of perception randomly varies across trials or is fixed so that the variability is the same. Then we estimated how perceptual quality and guess rate on an orientation perception task relates to EEG activity. Response errors were fitted to variable precision models and the standard mixture model to determine whether perceptual quality is from a varying or fixed distribution. Overall, the best fit was the standard mixture model that assumes response variability can be defined by a fixed distribution.

The power and phase of 2-7 Hz post-target activities were found to vary along with task performance in that more accurate trials had greater power, and the preferred phase differed significantly between accurate and guess trials. Guess rate and σ were significantly lower on trials with high 2-3 Hz power than low and the difference started around 250 ms post-target.

These effects coincide with changes in the P3 ERP: there was a more positive deflection in the accurate trials vs guesses. These results suggest that the spread of errors (perceptual quality) can be characterized by a fixed range of values. Where the errors fall within that range is modulated by the post-target power in the lower frequency bands and their analogous ERPs.
Age-related reductions in the number of serial sarcomeres contribute to shorter fascicle lengths but not elevated passive tension
Authors: Power Geoffrey A. , Crooks Sean , Fletcher Jared R. , Macintosh Brian R. , Herzog Walter
Published: December 2020

We investigated age-related changes to fascicle length (FL), sarcomere length (SL), and serial sarcomere number (SSN), and how this affects passive force. Following mechanical testing to determine passive force, the medial gastrocnemius muscle of young (n=9) and old (n=8) Fisher 344BN hybrid rats was chemically fixed at the optimal muscle length for force production; individual fascicles were dissected for length measurement, and laser diffraction was used to assess SL. Old rats had ∼14% shorter FLthan young, which was driven by a ∼10% reduction in SSN, with no difference in SL (∼4%). Passive force was greater in the old compared to young rats at long muscle lengths. Shorter FLand reduced SSN in the old rats could not entirely explain increased passive forces for absolute length changes, owing to a slight reduction in SL in old, resulting in similar SL at long muscle lengths.

Summary Statement

This study sought to explain the increased passive tension observed for muscles of older individuals owing to age-related changes to muscle architecture.
The ENIGMA Toolbox: Cross-disorder integration and multiscale neural contextualization of multisite neuroimaging datasets
Authors: Larivière Sara , Paquola Casey , Park Bo-yong , Royer Jessica , Wang Yezhou , Benkarim Oualid , Vos de Wael Reinder , Valk Sofie L. , Thomopoulos Sophia I. , Kirschner Matthias ,   ENIGMA Consortium, Lewis Lindsay B. , Evans Alan C. , Sisodiya Sanjay M. , McDonald Carrie R. , Thompson Paul M. , Bernhardt Boris C.
Published: December 2020

Among ‘big data’ initiatives, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium—a worldwide alliance of over 2,000 scientists diversified into over 50 Working Groups—has yielded some of the largest studies of the healthy and diseased brain. Integration of multisite datasets to assess transdiagnostic similarities and differences and to contextualize findings with respect to neural organization, however, have been limited. Here, we introduce the ENIGMA Toolbox, a Python/Matlab ecosystem for (i) accessing 100+ ENIGMA datasets, facilitating cross-disorder analysis, (ii) visualizing data on brain surfaces, and (iii) contextualizing findings at the microscale (postmortem cytoarchitecture and gene expression) and macroscale (structural and functional connectomes). Our Toolbox equips scientists with tutorials to explore molecular, histological, and network correlates of noninvasive neuroimaging markers of brain disorders. Moreover, our Toolbox bridges the gap between standardized data processing protocols and analytic workflows and facilitates cross-consortia initiatives. The Toolbox is documented and openly available at http://enigma-toolbox.readthedocs.io.

Abstract Figure
Effect of Lauric Acid on the Stability of Aβ42-Oligomers
Authors: Khatua Prabir , Jana Asis , Hansmann Ulrich H. E.
Published: December 2020

While Alzheimer’s disease is correlated with the presence of Aβfibrils in patient brains, the more likely agents are their precursors, soluble oligomers that may form pores or otherwise distort cell membranes. Using all-atom molecular dynamics simulation we study how presence of fatty acids such as lauric acid changes the stability of pore-forming oligomers built from three-stranded Aβ42chains. Such a change would alter the distribution of amyloids in the fatty-acid rich brain environment, and therefore could explain the lower polymorphism observed in Aβ-fibrils derived from brains of patients with Alzheimer’s disease. We find that lauric acid stabilizes both ring-like and barrel-shaped models, with the effect being stronger for barrel-like models than for ring-like oligomers.
Dispersal rate and riverine network connectivity shape the genetic diversity of freshwater amphipod metapopulations
Authors: Alther Roman , Fronhofer Emanuel A. , Altermatt Florian
Published: December 2020

Theory predicts that the distribution of genetic diversity in a landscape is strongly dependent on the connectivity of the metapopulation and the dispersal of individuals between patches. However, the influence of explicit spatial configurations such as dendritic landscapes on the genetic diversity and structure of metapopulations is still understudied, and theoretical corroborations of empirical patterns are largely lacking. Here, we used real-world microsatellite data and stochastic simulations of two metapopulations of freshwater amphipods in a 28,000 km2riverine network to study the influence of spatial connectivity and dispersal strategies on their spatial genetic diversity and structure. We found a significant imprint of the riverine network connectivity on the genetic diversity of both amphipod species. Data from 95 sites showed that allelic richness and observed heterozygosity significantly increased towards more central nodes of the network. In simulation models, dispersal rate was suggested to be the key factor explaining the empirically observed distribution of genetic diversity. Contrary to often-claimed expectations, however, the relevance of directionality of dispersal was only minor. Surprisingly, also the consideration of site-specific carrying capacities, for example by assuming a direct dependency of population size with local river size, substantially decreased the model fit to empirical data. This highlights that directional dispersal and the spatial arrangement of population sizes may have a smaller relevance in shaping population genetic diversity of riverine organisms than previously thought, and that dispersal along the river network is the single-most important determinant of population genetic diversity.