bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing Performance of Different Predictive Models in Estimating Disease Progression in Alzheimer Disease
Authors: Ezzati Ali , Zammit Andrea R. , Lipton Richard B. 
Published: August 2021

Background:
Automatic classification techniques provide tools to analyze complex data and predict disease progression.

Methods:
A total of 305 cognitively normal; 475 patients with amnestic mild cognitive impairment (aMCI); and 162 patients with dementia were included in this study. We compared the performance of 3 different methods in predicting progression from aMCI to dementia: (1) index-based model; (2) logistic regression (LR); and (3) ensemble linear discriminant (ELD) machine learning models. LR and ELD models were trained using data from cognitively normal and dementia subgroups, and subsequently were applied to aMCI subgroup to predict their disease progression.

Results:
Performance of ELD models were better than LR models in prediction of conversion from aMCI to Alzheimer dementia at all time frames. ELD models performed better when a larger number of features were used for prediction.

Conclusion:
Machine learning models have substantial potential to improve the predictive ability for cognitive outcomes.
Industrial applications of digital twins
Authors: Jiang Yuchen , Yin Shen , Li Kuan , Luo Hao , Kaynak Okyay 
Published: August 2021

A digital twin (DT) is classically defined as the virtual replica of a real-world product, system, being, communities, even cities that are continuously updated with data from its physical counterpart, as well as its environment. It bridges the virtual cyberspace with the physical entities and, as such, is considered to be the pillar of Industry 4.0 and the innovation backbone of the future. A DT is created and used throughout the whole life cycle of the entity it replicates, from cradle to grave, so to speak. This article focuses on the present state of the art of DTs, concentrating on the use of DTs in industry in the context of smart manufacturing, especially from the point of view of plantwide optimization. The main capabilities of DTs (mirroring, shadowing and threading) are discussed in this context. The article concludes with a perspective on the future.
This article is part of the theme issue ‘Towards symbiotic autonomous systems’.
The personal digital twin, ethical considerations
Authors: de Kerckhove Derrick 
Published: August 2021

The personal digital twin extends to individual persons, a concept that originated in engineering to twin complex machines with a digital simulation containing a model of its functions to monitor its past and present behaviour, and repair, correct, improve or otherwise ensure its optimal operation. Several independent trends in technological developments are seen to converge towards the elaboration of the digital replication of individual human data and life history, notably in health industries. Among the main ones, we consider the ubiquitous distribution of digital assistants, the rapid progress of machine learning concurrent with the exponential growth of ‘personal’ Big Data and the incipient interest in developing lifelogs. The core hypothesis here is that among the psychological effects of the digital transformation, the externalization of cognitive faculties such as memory, planning and judgement, the decision-making processes located within the human person are also emigrating to digital functions, perhaps as a prelude to a later re-integration within the person via brain–computer interfaces. The paper concludes with ethical considerations about these ongoing developments.
This article is part of the theme issue ‘Towards symbiotic autonomous systems’.
Stochastic model predictive control framework for resilient cyber-physical systems: review and perspectives
Authors: Chen Jicheng , Shi Yang 
Published: August 2021

In the era of Industrial 4.0, the next-generation control system regards the cyber-physical system (CPS) as the core ingredient thanks to the comprehensive integration of physical systems, online computation, networking and control. A reliable, stable and resilient CPS should pledge robustness and safety. A significant concern in CPS development arises from security issues since the CPS is vulnerable to physical constraints, ubiquitous uncertainties and malicious cyber attacks. The integration of the stochastic model predictive control (MPC) framework and the resilient mechanism is a possible approach to guarantee robustness in the presence of stochastic uncertainties and enable resilience against cyber attacks. This review paper aims to offer a detailed overview of existing stochastic MPC algorithms and their CPS applications. More specifically, we first review existing stochastic MPC algorithms for both linear and nonlinear systems subject to probabilistic constraints. We then discuss how to extend the stochastic MPC framework to incorporate resilience mechanisms for constrained CPS under various malicious attacks. Finally, we present an architectural stochastic MPC-based framework for resilient CPS and identify future research challenges.
This article is part of the theme issue ‘Towards symbiotic autonomous systems’.
Sediminihaliea albiluteola gen. nov., sp. nov., a new member of the family Halieaceae, isolated from marine sediment
Authors: Jiang Shan , Lian Feng-Bai , Sun You-Yang , Zhang Xiao-Kui , Du Zong-Jun 
Published: August 2021

A Gram-stain-negative, rod-shaped and facultatively aerobic bacterial strain, designated F7430T, was isolated from coastal sediment collected at Jingzi Wharf in Weihai, PR China. Cells of strain F7430T were 0.3–0.4 µm wide, 2.0–2.6 µm long, non-flagellated, non-motile and formed pale-beige colonies. Growth was observed at 4–40 °C (optimum, 30 °C), pH 6.0–9.0 (optimum, pH 7.5–8.0) and at NaCl concentrations of 1.0–10.0 % (w/v; optimum, 1.0 %). The sole respiratory quinone of strain F7430T was ubiquinone 8 and the predominant cellular fatty acids were summed feature 8 (C18 : 1
ω7c / C18 : 1
ω6c; 60.7 %), summed feature 3 (C16 : 1
ω7c/C16 : 1
ω6c; 30.2 %) and C15 : 0 iso (13.9 %). The polar lipids of strain F7430T consisted of diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylcholine, one unidentified phospholipid and three unidentified lipids. Results of 16S rRNA gene sequences analyses indicated that this strain belonged to the family

Halieaceae

and had high sequence similarities to

Parahaliea aestuarii

JCM 51547T (95.3 %) and

Halioglobus pacificus

DSM 27932T (95.2 %) followed by 92.9–95.0 % sequence similarities to other type species within the aforementioned family. The rpoB gene sequences analyses indicated that the novel strain had the highest sequence similarities to

Parahaliea aestuarii

JCM 51547T (82.2 %) and

Parahaliea mediterranea

DSM 21924T (82.2 %) followed by 75.2–80.5 % sequence similarities to other type species within this family. Phylogenetic analyses showed that strain F7430T constituted a monophyletic branch clearly separated from the other genera of family

Halieaceae

. Whole-genome sequencing of strain F7430T revealed a 3.3 Mbp genome size with a DNA G+C content of 52.6 mol%. The genome encoded diverse metabolic pathways including the Entner–Doudoroff pathway, assimilatory sulphate reduction and biosynthesis of dTDP-l-rhamnose. Based on results from the current polyphasic study, strain F7430T is proposed to represent a novel species of a new genus within the family

Halieaceae

, for which the name Sediminihaliea albiluteola gen. nov., sp. nov. is proposed. The type strain of the type species is F7430T (=KCTC 72873T=MCCC 1H00420T).
Genetic parameters of colostrum and calf serum antibodies in Swedish dairy cattle
Authors: Cordero-Solorzano Juan , de Koning Dirk-Jan , Tråvén Madeleine , de Haan Therese , Jouffroy Mathilde , Larsson Andrea , Myrthe Aline , Arts Joop A.J. , Parmentier Henk K. , Bovenhuis Henk , Wensman Jonas Johansson 
Published: August 2021

AbstractBackgroundColostrum with sufficient IgG content is essential for the newborn calf, as it provides passive immunity which substantially affects the probability of survival during rearing. Failure of passive transfer occurs when a calf does not absorb enough antibodies from the colostrum as indicated by less than 10 g/L of IgG in calf serum. Besides delayed access to colostrum, this can be due to low IgG production of the mother or poor IgG absorption by the calf. The aim of this study was to estimate the genetic background of antibody levels and indicator traits for antibodies in colostrum and calf serum, and their correlation with milk production and health.ResultsColostrum data were available from 1340 cows with at least one calving and calf serum data were available from 886 calves from these cows. Antibody concentrations were estimated using refractometry (digital Brix refractometer for colostrum and optical refractometer for serum) as indicator traits and established using ELISAs to determine total IgG and natural antibodies [NAb] of various antibody isotypes in colostrum and serum. Colostrum traits had heritabilities ranging from 0.16 to 0.31 with repeatabilities from 0.21 to 0.55. Brix had positive genetic correlations with all colostrum antibody traits including total IgG (0.68). Calf serum antibody concentrations had heritabilities ranging from 0.25 to 0.59, with a significant maternal effect accounting for 17 to 27% of the variance. When calves later in life produced their first lactation, lactation-average somatic cell score was found to be negatively correlated with NAb in calf serum.ConclusionsOur results suggest that antibody levels in colostrum and calf serum can be increased by means of selection.
scAgeCom: a murine atlas of age-related changes in intercellular communication inferred with the package scDiffCom
Authors: Lagger Cyril , Ursu Eugen , Equey Anaïs , Avelar Roberto A. , Pisco Angela O. , Tacutu Robi , de Magalhães João Pedro 
Published: August 2021

AbstractDysregulation of intercellular communication is a well-established hallmark of aging. To better understand how this process contributes to the aging phenotype, we built scAgeCom, a comprehensive atlas presenting how cell-type to cell-type interactions vary with age in 23 mouse tissues. We first created an R package, scDiffCom, designed to perform differential intercellular communication analysis between two conditions of interest in any mouse or human single-cell RNA-seq dataset. The package relies on its own list of curated ligand-receptor interactions compiled from seven established studies. We applied this tool to single-cell transcriptomics data from the Tabula Muris Senis consortium and the Calico murine aging cell atlas. All the results can be accessed online, using a user-friendly, interactive web application (https://scagecom.org). The most widespread changes we observed include upregulation of immune system processes, inflammation and lipid metabolism, and downregulation of extracellular matrix organization, growth, development and angiogenesis. More specific interpretations are also provided.
AngioPlate – Biofabrication of perfusable complex tissues in multi-well plates with 4D subtractive manufacturing
Authors: Rajasekar Shravanthi , Lin Dawn S. Y. , Zhang Feng , Sotra Alexander , Boshart Alex , Clotet-Freixas Sergi , Liu Amy , Hirota Jeremy A. , Ogawa Shinichiro , Konvalinka Ana , Zhang Boyang 
Published: August 2021

AbstractOrgan-on-a-chip systems that recapitulate tissue-level functions have been proposed to improve in vitro–in vivo correlation in drug development. Significant progress has been made to control the cellular microenvironment with mechanical stimulation and fluid flow. However, it has been challenging to introduce complex 3D tissue structures due to the physical constraints of microfluidic channels or membranes in organ-on-a-chip systems. Although this problem could be addressed with the integration of 3D bioprinting, it is not an easy task because the two technologies have fundamentally different fabrication processes. Inspired by 4D bioprinting, we develop a 4D subtractive manufacturing technique where a flexible sacrificial material can be patterned on a 2D surface, change shape when exposed to aqueous hydrogel, and subsequently degrade to produce perfusable networks in a natural hydrogel matrix that can be populated with cells. The technique is applied to fabricate organ-specific vascular networks, vascularized kidney proximal tubules, and terminal lung alveoli in a customized 384-well plate and then further scaled to a 24-well plate format to make a large vascular network, vascularized liver tissues, and for integration with ultrasound imaging. This biofabrication method eliminates the physical constraints in organ-on-a-chip systems to incorporate complex ready-to-perfuse tissue structures in an open-well design.
The rs1421085 variant within FTO promotes but not inhibits thermogenesis and is potentially associated with human migration
Authors: Zhang Zhiyin , Chen Na , Liu Ruixin , Yin Nan , He Yang , Li Danjie , Tong Muye , Gao Aibo , Lu Peng , Li Huabing , Zhang Dan , Gu Weiqiong , Hong Jie , Wang Weiqing , Qi Lu , Wang Jiqiu , Ning Guang 
Published: August 2021

SummaryDisease-associated GWAS loci are predominantly scattered among noncoding regions of the human genome, which impedes causality estimation. One lead risk signal of obesity–rs1421085 T>C within the FTO gene–is reported to functional in vitro but lack of organismal evidence. Here, we established global and the brown-adipocyte specific locus-knock-in mice to recapitulate this homologous variant in humans, and discovered the minor allele (C-allele) as one candidate thermogenic locus. Mice carrying the C-alleles showed increased thermogenic capacity and a resistance to high-fat diet-induced adiposity. In terms of mechanism, the knock-in models showed enhanced FTO expression, while FTO knockdown or inhibition effectively eliminated the increased thermogenic ability of brown adipocytes. In humans, the C-allele was associated with lower birthweight, and its allele frequency increases following the environmental temperature decreases. Cumulatively, these findings demonstrated rs1421085 T>C as a functional variant regulating whole-body thermogenesis, and this variation was possibly related to early human migration from hot to cold environments.
ImputeCoVNet: 2D ResNet Autoencoder for Imputation of SARS-CoV-2 Sequences
Authors: Pesaranghader Ahmad , Pelletier Justin , Grenier Jean-Christophe , Poujol Raphaёl , Hussin Julie 
Published: August 2021

AbstractWe describe a new deep learning approach for the imputation of SARS-CoV-2 variants. Our model, ImputeCoVNet, consists of a 2D ResNet Autoencoder that aims at imputing missing genetic variants in SARS-CoV-2 sequences in an efficient manner. We show that ImputeCoVNet leads to accurate results at minor allele frequencies as low as 0.0001. When compared with an approach based on Hamming distance, ImputeCoVNet achieved comparable results with significantly less computation time. We also present the provision of geographical metadata (e.g., exposed country) to decoder increases the imputation accuracy. Additionally, by visualizing the embedding results of SARS-CoV-2 variants, we show that the trained encoder of ImputeCoVNet, or the embedded results from it, recapitulates viral clade’s information, which means it could be used for predictive tasks using virus sequence analysis.
RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks
Authors: Szymborski Joseph , Emad Amin 
Published: August 2021

ABSTRACTMotivationComputational methods for the prediction of protein-protein interactions, while important tools for researchers, are plagued by challenges in generalising to unseen proteins. Datasets used for modelling protein-protein predictions are particularly predisposed to information leakage and sampling biases.ResultsIn this study, we introduce RAPPPID, a method for the Regularised Automatic Prediction of Protein-Protein Interactions using Deep Learning. RAPPPID is a twin AWD-LSTM network which employs multiple regularisation methods during training time to learn generalised weights. Testing on stringent interaction datasets composed of proteins not seen during training, RAPPPID outperforms state-of-the-art methods. Further experiments show that RAPPPID’s performance holds regardless of the particular proteins in the testing set and its performance is higher for biologically supported edges. This study serves to demonstrate that appropriate regularisation is an important component of overcoming the challenges of creating models for protein-protein interaction prediction that generalise to unseen proteins. Additionally, as part of this study, we provide datasets corresponding to several data splits of various strictness, in order to facilitate assessment of PPI reconstruction methods by others in the future. Availability and Implementation: Code and datasets are freely available at https://github.com/jszym/rapppid.Contactamin.emad@mcgill.caSupplementary InformationOnline-only supplementary data is available at the journal’s website.
Point Mutations in SARS-CoV-2 Variants Induce Long-Range Dynamical Perturbations in Neutralizing Antibodies
Authors: Ray Dhiman , Quijano Riley Nicolas , Andricioaei Ioan 
Published: August 2021

AbstractMonoclonal antibodies are emerging as a viable treatment for the coronavirus disease 19 (COVID-19). However, newly evolved variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can reduce the efficacy of currently available antibodies and can diminish vaccine-induced immunity. Here, we demonstrate that the microscopic dynamics of neutralizing monoclonal antibodies can be profoundly modified by the mutations present in the spike proteins of the SARS-COV-2 variants currently circulating in the world population. The dynamical perturbations within the antibody structure, which alter the thermodynamics of antigen recognition, are diverse and can depend both on the nature of the antibody and on the spatial location of the spike mutation. The correlation between the motion of the antibody and that of the spike receptor binding domain (RBD) can also be changed, modulating binding affinity. Using protein-graph-connectivity networks, we delineated the mutant-induced modifications in the information-flow along allosteric pathway throughout the antibody. Changes in the collective dynamics were spatially distributed both locally and across long-range distances within the antibody. On the receptor side, we identified an anchor-like structural element that prevents the detachment of the antibodies; individual mutations there can significantly affect the antibody binding propensity. Our study provides insight into how virus neutralization by monoclonal antibodies can be impacted by local mutations in the epitope via a change in dynamics. This realization adds a new layer of sophistication to the efforts for rational design of monoclonal antibodies against new variants of SARS-CoV2, taking the allostery in the antibody into consideration.
Deep graph learning of inter-protein contacts
Authors: Xie Ziwei , Xu Jinbo 
Published: August 2021

AbstractMotivationInter-protein (interfacial) contact prediction is very useful for in silico structural characterization of protein-protein interactions. Although deep learning has been applied to this problem, its accuracy is not as good as intra-protein contact prediction.ResultsWe propose a new deep learning method GLINTER (Graph Learning of INTER-protein contacts) for interfacial contact prediction of dimers, leveraging a rotational invariant representation of protein tertiary structures and a pretrained language model of multiple sequence alignments (MSAs). Tested on the 13th and 14th CASP-CAPRI datasets, the average top L/10 precision achieved by GLINTER is 54.35% on the homodimers and 51.56% on all the dimers, much higher than 30.43% obtained by the latest deep learning method DeepHomo on the homodimers and 14.69% obtained by BIPSPI on all the dimers. Our experiments show that GLINTER-predicted contacts help improve selection of docking decoys.Contactjinboxu@gmail.com
Arg1+ microglia are critical for shaping cognition in female mice
Authors: Stratoulias Vassilis , Ruiz Rocío , Kanatani Shigeaki , Osman Ahmed M. , Armengol Jose A. , Rodríguez-Moreno Antonio , Murgoci Adriana-Natalia , García-Domínguez Irene , Keane Lily , Vázquez-Cabrera Guillermo , Alonso-Bellido Isabel , Vernoux Nathalie , Tejera Dario , Grabert Kathleen , Cheray Mathilde , González-Rodríguez Patricia , Pérez-Villegas Eva M. , Martinez-Gallego Irene , Brodin David , Avila-Cariño Javier , Airavaara Mikko , Uhlén Per , Heneka Michael T. , Tremblay Marie-Ève , Blomgren Klas , Venero Jose L. , Joseph Bertrand 
Published: August 2021

AbstractDiversity within microglia, the resident brain immune cells, is reported. Whether microglial subsets constitute different subtypes with intrinsic properties and unique functions has not been fully elucidated. Here, we describe a microglial subtype characterized by the expression of the enzyme Arginase-1, i.e. Arg1+microglia, which is found predominantly in the cholinergic neuron-rich forebrain region during early postnatal development. Arg1+ microglia are frequently observed in close apposition to neurons and exhibit a distinctive molecular signature reflecting a reactive profile. Arg1 deficiency in microglia results in impaired dendritic spine maturation in the hippocampus where cholinergic neurons project, and cognitive behavioural deficiencies in female mice. Our results expand on microglia diversity and provide insights into distinctive spatiotemporal functions exerted by microglial subtypes.
Effects Of Video Games On Executive Control, Aggression and Gaming Motivation
Authors: Dixit Akshay , Sinha Divya , Ramachandran Hemalatha 
Published: August 2021

ABSTRACTWith the advancements of computer technology and accessible internet, playing video games has become immensely popular across all age groups. Increasing research talks about the cognitive benefits of Video Games. At the same time, video games are stereotyped as an activity for the lazy and unproductive. Within this backdrop, our study aims to understand the effect of video games on Executive control (Visual Scanning and Visual Perception), Aggression, and Gaming Motivation.Twenty non-gamers were selected and divided into two groups: Action Video Game Players (AVGP) and Non-Action Video Game Players NAVGP). We used two computerized tests: Gabor Orientation Identification Test and Visual Scanning Test (to assess visual perception and visual scanning, respectively) and two questionnaires (to assess aggression and gaming motivation). We found an improvement in visual perception as well as visual scanning following video game training in AVGPs. Interestingly, aggression did not increase with an increase in video game exposure. We also found insignificant changes in gaming motivation after the training, except for self-gratification motives.Cognitive improvements do not relate to action video games alone, but non-action video games also show promising results to enhance cognition. With better timed and controlled training with video games, aggression as a prospective consequence of video game exposure can also be controlled. We propose targeted video game training as an approach to enhance cognition in non-gamers.