bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of α-synuclein fibrillar strains and ß-amyloid assemblies on the endolysosomal logistics of mouse cortical neurons
Authors: Chou Qiao-Ling , Alik Ania , Marquier François , Melki Ronald , Treussart François , Simonneau Michel 
Published: May 2021

AbstractEndosomal transport and positioning are involved in establishing neuronal compartment architecture, dynamics and function, contributing to neuronal intracellular logistics. Furthermore, endo-lysosomal dysfunction has been identified as a common mechanism in neurodegenerative diseases. Here, we analyzed endolysosomal transport following the external application of α-synuclein (α-syn) fibrillar polymorphs, ß-amyloid (Aß) fibrils and oligomers on primary cultures of mouse cortical neurons. We used a simple readout to measure this transport: the spontaneous endocytosis of fluorescent nanodiamonds — a perfectly stable nano-emitter — in cultured neurons. We then performed a high-throughput automatic extraction and quantification of the directed motions of these nanodiamonds. α-syn fibrillar polymorphs, Aß fibrils and oligomers halved the proportion of nanodiamonds transported along microtubules, but only slightly decreased their interactions with cortical neurons. This large decrease in endosomal transport would be expected to have a huge impact on neuronal homeostasis. We then assessed lysosomal dynamics with Lysotracker. The exposure of neurons to Aß oligomers led to an increase in the number of lysosomes, a decrease in the fraction of moving lysosomes and an increase in their size, reminiscent of findings for the APP transgenic model of Alzheimer’s disease. We then analyzed the effect of α-syn fibrillar polymorphs, Aß fibrils and oligomers on endosomal and lysosomal transport and quantified the directed transport of these assemblies within cortical neurons. We report different impacts on endosomal and lysosomal transport parameters and differences in trajectory length for cargoes loaded with pathogenic protein assemblies. Our results suggest that the internalization and transport of intraneuronal pathogenic protein aggregates are potential targets for novel neuroprotective treatment strategies.Significance StatementNeurodegenerative diseases (NDs) are characterized by the deposition of protein aggregates with broad-range neuronal toxicity. Defects of endolysosomal trafficking are increasingly being seen as key pathological features of NDs, probably contributing to synaptic dysfunction and ultimate neuronal death. We used fast fluorescence videomicroscopy to investigate endosomal and lysosomal dynamics in the branches of mouse cortical neurons in primary cultures following the application of α-syn fibrillar polymorphs (fibrils and ribbons) and Aß assemblies (oligomers and fibrils). We provide new insight into the differential effects of these pathogenic protein assemblies on endosomal and lysosomal transport, and reveal differences in the transport characteristics of the compartments loaded with these protein assemblies relative to endosomes.
GP2-enriched pancreatic progenitors give rise to functional beta cells in vivo and eliminate the risk of teratoma formation
Authors: Aghazadeh Yasaman , Sarangi Farida , Poon Frankie , Nkennor Blessing , McGaugh Emily C. , Nunes Sara S. , Nostro M. Cristina 
Published: May 2021

SummaryHuman pluripotent stem cell (hPSC)-derived pancreatic progenitors (PPs) can be differentiated into beta-like cells in vitro and in vivo, and therefore have therapeutic potential for type 1 diabetes (T1D) treatment. However, the purity of PPs varies across different hPSC lines, differentiation protocols and laboratories. The uncommitted cells may give rise to non-pancreatic endodermal, mesodermal, or ectodermal derivatives in vivo, hampering the safety of hPSC-derived PPs for clinical applications. Recently, proteomics and transcriptomics analyses identified glycoprotein 2 (GP2) as a PP-specific cell surface marker. The GP2-enriched PPs generate higher percentages of beta-like cells in vitro compared to unsorted and GP2− fractions, but their potential in vivo remains to be elucidated. Here, we demonstrate that the GP2-enriched-PPs give rise to all pancreatic cells in vivo, including functional beta-like cells. Remarkably, GP2 enrichment eliminated the formation of teratoma in vivo. This study establishes that the GP2-enriched PPs represent a safe option for T1D treatment.
KLFDAPC: A Supervised Machine Learning Approach for Spatial Genetic Structure Analysis
Authors: Qin Xinghu , Chiang Charleston W. K. , Gaggiotti Oscar E. 
Published: May 2021

AbstractGeographic patterns of human genetic variation provide important insights into human evolution and disease. A commonly used tool to detect geographic patterns from genetic data is principal components analysis (PCA) or the supervised linear discriminant analysis of principal components (DAPC). However, genetic features produced from both approaches could fail to correctly characterize population structure for complex scenarios involving admixture. In this study, we introduce Kernel Local Fisher Discriminant Analysis of Principal Components (KLFDAPC), a supervised nonlinear approach for inferring individual geographic genetic structure that could rectify the limitations of these approaches by preserving the multimodal space of samples. We tested the power of KLFDAPC to infer population structure and to predict individual geographic origin using neural networks. Simulation results showed that KLFDAPC significantly improved the population separability compared with PCA and DAPC. The application to POPRES and CONVERGE datasets indicated that the first two reduced features of KLFDAPC correctly recapitulated the geography of individuals, and significantly improved the accuracy of predicting individual geographic origin when compared to PCA and DAPC. Therefore, KLFDAPC can be useful for geographic ancestry inference, design of genome scans and correction for spatial stratification in GWAS that link genes to adaptation or disease susceptibility.
Engineering Gelation Kinetics in Living Silk Hydrogels by Differential Dynamic Microscopy Microrheology and Machine Learning
Authors: Martineau Rhett L. , Bayles Alexandra V. , Hung Chia-Suei , Reyes Kristofer G. , Helgeson Matthew E. , Gupta Maneesh K. 
Published: May 2021

AbstractMicrobes embedded in hydrogels comprise one form of living material. Discovering formulations that balance potentially competing mechanical and biological properties in living hydrogels—for example gel time of the hydrogel formulation and viability of the embedded organisms—can be challenging. In this work, a pipeline is developed to automate characterization of the gel time of hydrogel formulations. Using this pipeline, living materials comprised of enzymatically crosslinked silk and embedded E. coli—formulated from within a 4D parameter space—are engineered to gel within a pre-selected timeframe. Gelation time is estimated using a novel adaptation of microrheology analysis using differential dynamic microscopy (DDM). In order to expedite the discovery of gelation regime boundaries, Bayesian machine learning models are deployed with optimal decision-making under uncertainty. The rate of learning is observed to vary between AI-assisted planning and human planning, with the fastest rate occurring during AI-assisted planning following a round of human planning. For a subset of formulations gelling within a targeted timeframe of 5-15 minutes, fluorophore production within the embedded cells is substantially similar across treatments, evidencing that gel time can be tuned independent of other material properties—at least over a finite range—while maintaining biological activity.
Phase-specific RNA accumulation and duplex thermodynamics in multiphase coacervate models for membraneless organelles
Authors: Choi Saehyun , Bevilacqua Philip C. , Keating Christine D. 
Published: May 2021

AbstractLiquid-liquid phase separation has emerged as an important means of intracellular RNA compartmentalization. Some membraneless organelles host two or more compartments serving different putative biochemical roles; the mechanisms for, and functional consequences of, this subcompartmentalization are not yet well understood. Here, we show that adjacent phases of decapeptide-based multiphase model membraneless organelles differ markedly in their interactions with RNA. Additionally, their coexistence introduces new equilibria that alter RNA duplex stability and RNA sorting by hybridization state. These effects require neither biospecific RNA binding sites nor full-length proteins. As such, they are general and point to more primitive versions of mechanisms operating in extant biology that could aid understanding and enable design of functional artificial membraneless organelles.
Temporal and spatial topography of cell proliferation in cancer
Authors: Gaglia Giorgio , Kabraji Sheheryar , Argyropoulou Danae , Dai Yang , Wang Shu , Bergholz Johann , Coy Shannon , Lin Jia-Ren , Jeselsohn Rinath , Metzger Otto , Winer Eric P. , Dillon Deborah A. , Zhao Jean J. , Sorger Peter K , Santagata Sandro 
Published: May 2021

SUMMARYProliferation is a fundamental trait of cancer cells but is poorly characterized in tumors by classical histologic methods. We use multiplexed tissue imaging to quantify the abundance of multiple cell cycle regulating proteins at single-cell level and develop robust multivariate proliferation metrics. Across cancers, the proliferative architecture is organized at two distinct spatial scales: large domains, and local niches enriched for specific immune lineages. A subset of tumor cells express cell cycle regulators in canonical patterns consistent with unrestrained proliferation, a phenomenon we refer to as “cell cycle coherence”. By contrast, the cell cycles of other tumor cell populations are skewed toward a specific phase or characterized by non-canonical (incoherent) marker combinations. Coherence varies across space, with changes in oncogene activity, and with therapeutic intervention, and is associated with aggressive behavior. Multivariate measures capture clinically significant features of cancer proliferation, a fundamental step in enabling more precise use of anti-cancer therapies.
Climatic suitability predictions for the cultivation of macadamia in Malawi using climate change scenarios
Authors: Zuza Emmanuel Junior , Araya Yoseph Negusse , Maseyk Kadmiel , Bhagwat Shonil A , de Sousa Kauê , Emmott Andrew , Rawes Will 
Published: May 2021

AbstractGlobal climate change is altering the suitable areas of crop species worldwide, with cascading effects on people and animals reliant upon those crop species as food sources. Macadamia is one of these essential lucrative crop species that grows in Malawi. Here, we used an ensemble model approach to determine the current distribution of macadamia production areas across Malawi in relation to climate. For future distribution of suitable areas, we used the climate outputs of 17 general circulation models based on two climate change scenarios (RCP 4.5 and RCP 8.5). The precipitation of the driest month and isothermality were the climatic variables that strongly influenced macadamia’s suitability in Malawi. We found that these climatic requirements were fulfilled across many areas in Malawi under the current conditions. Future projections indicated that vast parts of Malawi’s macadamia growing regions will remain suitable for macadamia, amounting to 36,910 km2 (39.1%) and 33,511 km2 (35.5%) of land based on RCP 4.5 and RCP 8.5, respectively. Alarmingly, suitable areas for macadamia production are predicted to shrink by −18% (17,015 km2) and −21.6% (20,414 km2) based on RCP 4.5 and RCP 8.5, respectively, with much of the suitability shifting northwards. This means that some currently productive areas will become unproductive in the future, while current unproductive areas will become productive. Notably, suitable areas will increase in Malawi’s central and northern highlands, while the southern region will lose most of its suitable areas. Our study, therefore, shows that there is potential for expanding macadamia production in Malawi. Most, importantly our future projections provide critical evidence on the potential negative impacts of climate change on the suitability of macadamia production in the country. We recommend developing area-specific adaptation strategies to build resilience in the macadamia sector in Malawi under climate change.
Genomic context sensitivity of insulator function
Authors: Ribeiro-dos-Santos André M. , Hogan Megan S. , Luther Raven D. , Maurano Matthew T. 
Published: May 2021

AbstractCompartmentalization of interactions between genomic regulatory elements and potential target genes is influenced by the binding of insulator proteins such as CTCF, which act as potent enhancer blockers when interposed between an enhancer and a promoter in a reporter assay. But only a minority of CTCF sites genome-wide function as boundary elements, depending on cellular and genomic context. To dissect the influence of genomic context on enhancer blocker activity, we integrated reporter constructs with promoter-only, promoter and enhancer, and enhancer blocker configurations at hundreds of thousands of genomic sites using the Sleeping Beauty transposase. Deconvolution of reporter activity by genomic position revealed strikingly different patterns of reporter function, including a compartment of enhancer blocker reporter integrations with robust expression. The high density of integration sites permits quantitative delineation of characteristic genomic context sensitivity profiles, and their decomposition into sensitivity to both local and distant DNaseI hypersensitive sites. Furthermore, a single-cell expression approach permits direct linkage of reporters integrated into the same clonal lineage with differential endogenous gene expression, revealing that CTCF insulator activity does not completely abrogate reporter effects on endogenous gene expression. Collectively, our results lend new insight to genomic regulatory compartmentalization and its influence on the determinants of promoter-enhancer specificity.
High-throughput mapping of single-neuron projection and molecular features by retrograde barcoded labelling
Authors: Xu Peibo , Peng Jian , Yuan Tingli , Chen Zhaoqin , He Hui , Wu Ziyan , Li Ting , Li Xiaodong , Wang Luyue , Wei Wu , Li Chengyu T. , Luo Zhen-Ge , Chen Yuejun 
Published: May 2021

AbstractDeciphering patterns of connectivity between neurons in the brain is a critical step toward understanding brain function. Imaging-based neuroanatomical tracing identifies area-to-area or sparse neuron-to-neuron connectivity patterns, but with limited throughput. Barcode-based connectomics maps large numbers of single-neuron projections, but remains a challenge for jointly analyzing single-cell transcriptomics. Here, we established a rAAV2-retro barcode-based multiplexed tracing method that simultaneously characterizes the projectome and transcriptome at the single neuron level. We uncovered dedicated and collateral projection patterns of ventromedial prefrontal cortex (vmPFC) neurons to five downstream targets and found that projection-defined vmPFC neurons are molecularly heterogeneous. We identified transcriptional signatures of projection-specific vmPFC neurons, and verifiedPou3f1as a marker gene of neurons extending collateral branches to dorsomedial striatum and lateral hypothalamus. In summary, we have developed a new multiplexed technique whose paired connectome and gene expression data can help reveal organizational principles that form neural circuits and process information.
A tandem segmentation-classification approach for the localization of morphological predictors of C. elegans lifespan and motility
Authors: Yakimovich Artur , Galimov Evgeniy 
Published: May 2021

ABSTRACTC. elegans is an established model organism for studying genetic and drug effects on ageing, many of which are conserved in humans. It is also an important model for basic research, and C. elegans pathologies is a new emerging field. Here we develop a proof-of-principal convolutional neural network-based platform to segment C. elegans and extract features that might be useful for lifespan prediction. We use a dataset of 734 worms tracked throughout their lifespan and classify worms into long-lived and short-lived. We designed WormNet - a convolutional neural network (CNN) to predict the worm lifespan class based on young adult images (day 1 – day 3 old adults) and showed that WormNet, as well as, InceptionV3 CNN can successfully classify lifespan. Based on U-Net architecture we develop HydraNet CNNs which allow segmenting worms accurately into anterior, mid-body and posterior parts. We combine HydraNet segmentation, WormNet prediction and the class activation map approach to determine the segments most important for lifespan classification. Such a tandem segmentation-classification approach shows posterior part of the worm might be more important for classifying long-lived worms. Our approach can be useful for the acceleration of anti-ageing drug discovery and for studying C. elegans pathologies.
Neuro-musculoskeletal Upper Limb in-silico as virtual patient
Authors: Kapardi Mallampalli , Pithapuram Madhav Vinodh , Rangayyan Yashaswini Mandayam , Iyengar Raghu Sesha , Singh Avinash Kumar , Sripada Sirisha , Raghavan Mohan 
Published: May 2021

AbstractVirtual patients and physiologies allow experimentation, design, and early-stage clinical trials in-silico. Virtual patient technology for human movement systems that encompasses musculoskeleton and its neural control are few and far in between. In this work, we present one such neuro-musculoskeletal upper limb in-silico model. This upper limb is both modular in architecture and generates movement as an emergent phenomenon out of a multiscale co-simulation of spinal cord neural control and musculoskeletal dynamics. It is developed on the NEUROiD movement simulation platform that enables a co-simulation of popular neural simulator NEURON and the musculoskeletal simulator OpenSim. In this work, we describe the design and development of the upper limb in a modular fashion, while reusing existing models and modules. We further characterize and demonstrate the use of this model in generating a range of commonly observed movements by means of a spatio temporal stimulation pattern delivered to the cervical spinal cord. We believe this work enables a first and small step towards an in-silico paradigms for understanding upper limb movement, disease pathology, medication, and rehabilitation.
Verification of SARS-CoV-2-Encoded small RNAs and contribution to Infection-Associated lung inflammation
Authors: Cheng Zhang , Cheng Liu , Lin Jiang , Lunbiao Cui , Chunyu Li , Guoxin Song , Rui Xu , Xiangnan Geng , Changxing Luan , Yan Chen , Baoli Zhu , Wei Zhu 
Published: May 2021

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019 (COVID-19), the respiratory illness responsible for the COVID-19 pandemic. SARS-CoV-2 is a positive-stranded RNA virus belongs toCoronaviridaefamily. The viral genome of SARS-CoV-2 contains around 29.8 kilobase with a 5′-cap structure and 3′-poly-A tail, and shows 79.2% nucleotide identity with human SARS-CoV-1, which caused the 2002-2004 SARS outbreak. As the successor to SARS-CoV-1, SARS-CoV-2 now has circulated across the globe. There is a growing understanding of SARS-CoV-2 in virology, epidemiology, and clinical management strategies. In this study, we verified the existence of two 18-22 nt small viral RNAs (svRNAs) derived from the same precursor in human specimens infected with SARS-CoV-2, including nasopharyngeal swabs and formalin-fixed paraffin-embedded (FFPE) explanted lungs from lung transplantation of COVID-19 patients. We then simulated and confirmed the formation of these two SARS-CoV-2-Encoded small RNAs in human lung epithelial cells. And the potential pro-inflammatory effects of the splicing and maturation process of these two svRNAs in human lung epithelial cells were also explored. By screening cytokine storm genes and the characteristic expression profiling of COVID-19 in the explanted lung tissues and the svRNAs precursor transfected human lung epithelial cells, we found that the maturation of these two small viral RNAs contributed significantly to the infection associated lung inflammation, mainly via the activation of the CXCL8, CXCL11 and type I interferon signaling pathway. Taken together, we discovered two SARS-CoV-2-Encoded small RNAs and investigated the pro-inflammatory effects during their maturation in human lung epithelial cells, which might provide new insight into the pathogenesis and possible treatment options for COVID-19.
Versatile and multiplexed mass spectrometry-based absolute quantification with cell-free-synthesized internal standard peptides
Authors: Masuda Keiko , Kasahara Keiko , Narumi Ryohei , Shimojo Masaru , Shimizu Yoshihiro 
Published: May 2021

AbstractPreparation of stable isotope-labeled internal standard peptides is crucial for mass spectrometry (MS)-based targeted proteomics. Herein, we developed versatile and multiplexed absolute protein quantification method using MS. A previously developed method based on the cell-free peptide synthesis system, termed MS-based quantification by isotope-labeled cell-free products (MS-QBiC), was improved for multiple peptide synthesis in one-pot reaction. We pluralized the quantification tags used for the quantification of synthesized peptides and thus, made it possible to use cell-free synthesized isotope-labeled peptides as mixtures for the absolute quantification. The improved multiplexed MS-QBiC method was proved to be applied to clarify ribosomal proteins stoichiometry in the ribosomal subunit, one of the largest cellular complexes. The study demonstrates that the developed method enables the preparation of several dozens and even several hundreds of internal standard peptides within a few days for quantification of multiple proteins with only a single-run of MS analysis.
Genetic code degeneracy is established by the decoding center of the ribosome
Authors: Ye Shixin , Lehmann Jean 
Published: May 2021

SUMMARYThe degeneracy of the genetic code confers a wide array of properties to coding sequences. Yet, its origin is still unclear. A structural analysis has shown that the stability of the Watson-Crick base pair at the second position of the anticodon-codon interaction is a critical parameter controlling the extent of non-specific pairings accepted at the third position by the ribosome, a flexibility at the root of degeneracy. Based on recent cryo-EM analyses, the present work shows that residue A1493 of the decoding center provides a significant contribution to the stability of this base pair, revealing that the ribosome is directly involved in the establishment of degeneracy. Building on existing evolutionary models, we show the evidence that the early appearance of A1493 and A1492 established the basis of degeneracy when an elementary kinetic scheme of translation was prevailing. Logical considerations on the expansion of this kinetic scheme indicate that the acquisition of the peptidyl transferase center was the next major evolutionary step, while the induced-fit mechanism, that enables a sharp selection of the tRNAs, necessarily arose later when G530 was acquired by the decoding center.