Miracle-dz/UniFAR-FTUs huggingface dataset:
Unrevealing Reliable Cortical Parcellation of Individual Brains Using Resting-State Functional Magnetic Resonance Imaging and Masked Graph Convolutions

Brain parcellation helps to understand the structural and functional organization of the cerebral cortex. Resting-state functional magnetic resonance imaging (fMRI) and connectivity analysis provide useful information to delineate individual brain parcels in vivo. We proposed an individualized cortical parcellation based on graph neural networks (GNN) to learn the reliable functional characteristics of each brain parcel on a large fMRI dataset and to infer the areal probability of each vertex on unseen subjects. A subject-specific confidence mask was implemented in the GNN model to account for the tradeoff between the topographic alignment across subjects and functional homogeneity of brain parcels on individual brains. The individualized brain parcellation achieved better functional homogeneity at rest and during cognitive tasks compared with the group-registered atlas (p-values < 0.05). In addition, highly reliable and replicable parcellation maps were generated on multiple sessions of the same subject (intrasubject similarity = 0.89), while notable variations in the topographic organization were captured across subjects (intersubject similarity = 0.81). Moreover, the intersubject variability of brain parcellation indicated large variations in the association cortices while keeping a stable parcellation on the primary cortex. Such topographic variability was strongly associated with the functional connectivity variability, significantly predicted cognitive behaviors, and generally followed the myelination, cytoarchitecture, and functional organization of the human brain. This study provides new avenues to the precise individualized mapping of the cortical areas through deep learning and shows high potentials in the personalized localization diagnosis and treatment of neurological disorders.
Clinical Imaging of the Penumbra in Ischemic Stroke: From the Concept to the Era of Mechanical Thrombectomy

The ischemic penumbra is defined as the severely hypoperfused, functionally impaired, at-risk but not yet infarcted tissue that will be progressively recruited into the infarct core. Early reperfusion aims to save the ischemic penumbra by preventing infarct core expansion and is the mainstay of acute ischemic stroke therapy. Intravenous thrombolysis and mechanical thrombectomy for selected patients with large vessel occlusion has been shown to improve functional outcome. Given the varying speed of infarct core progression among individuals, a therapeutic window tailored to each patient has recently been proposed. Recent studies have demonstrated that reperfusion therapies are beneficial in patients with a persistent ischemic penumbra, beyond conventional time windows. As a result, mapping the penumbra has become crucial in emergency settings for guiding personalized therapy. The penumbra was first characterized as an area with a reduced cerebral blood flow, increased oxygen extraction fraction and preserved cerebral metabolic rate of oxygen using positron emission tomography (PET) with radiolabeled O2. Because this imaging method is not feasible in an acute clinical setting, the magnetic resonance imaging (MRI) mismatch between perfusion-weighted imaging and diffusion-weighted imaging, as well as computed tomography perfusion have been proposed as surrogate markers to identify the penumbra in acute ischemic stroke patients. Transversal studies comparing PET and MRI or using longitudinal assessment of a limited sample of patients have been used to define perfusion thresholds. However, in the era of mechanical thrombectomy, these thresholds are debatable. Using various MRI methods, the original penumbra definition has recently gained a significant interest. The aim of this review is to provide an overview of the evolution of the ischemic penumbra imaging methods, including their respective strengths and limitations, as well as to map the current intellectual structure of the field using bibliometric analysis and explore future directions.
Abg-CoQA: Clarifying Ambiguity in Conversational Question Answering

Eﬀective communication requires the ability to identify ambiguities and request clar-iﬁcation of utterances. For machines to engage in a conversation, they need to learn to generate diﬀerent forms of clariﬁcation questions. This paper aims at studying the extent to which the state of the art neural generation models can generate eﬀective clariﬁca-tion questions in conversational question answering. We introduce Abg-CoQA, a novel crowdsourced dataset for clarifying ambiguities in conversational question answering systems. Our dataset contains 8,615 questions with answers where 994 questions are ambiguous. The conversational questions are about 3,968 text passages from ﬁve diverse domains which are pre-selected from the CoQA dataset. For ambiguous turns, we have collected the clariﬁcation questions and their answers. We evaluate strong language generation models and conversational question answering models on Abg-CoQA. The best-performing system achieves a F1-score of 23.6% on ambiguity detection; an accuracy of 56.0% on generating clariﬁcation question in human evaluation; and a F1 score of 40.1% on question answering after clariﬁcation, which is 35.1 points behind human performance (75.2%), indicating there is ample room for improvement.
Estimating the Impact of Occupants' Behaviour on Energy Consumption by Pls-SEM: A Case Study of Pakdel Residential Complex in Isfahan, IRAN

The importance of saving energy in the current decade has drawn more attention to optimising energy consumption factors. One of the influential and well-known factors affecting energy consumption is the occupants' behaviours (OBs). Reviewing this factor is a requirement to assess buildings, particularly the residential sector, as the majority target of the building industry. In this study, occupants' energy behaviours in Shahid Pakdel residential complex in Isfahan, Iran, are studied based on Annex 53 questionnaire and building performance simulation (BPS). The main objective of this study is to identify the impact of apartment improvement and OBs, including windows opening, curtain controlling behaviour, and turning on heating equipment in the cold season on energy consumption. Due to the invisible effect of some behaviours, especially for gas consumption (GC) and electricity consumption (EC), structural equation modelling (SEM) is applied to evaluate the impacts of OBs. This case study showed that the most influential behaviour factor is related to the improvement sector with a 41.7% share of EC. Moreover, the most negligible influential factor is associated with windows opening with 21.6% of the EC. Regarding GC, the most and the least determining behaviour factor were attributed to apartment improvement and curtain controlling behaviour with an effective rate of 64.5 and 5%, respectively. This result showed the high impact of apartment improvement on reducing GC and EC. The overall effect of behaviour on GC and EC was 46 and 44%, respectively, measured by the partial least squares (PLS) regression and R2 score.
An Overview of Antimicrobial Activity of Lysozyme and Its Functionality in Cheese

Due to the concern of consumers about the presence of synthetic preservatives, researchers and food manufacturers have recently conducted extensive research on the limited use of these preservatives and the introduction and use of natural preservatives, such as herbal extracts and essential oils, bacteriocins, and antimicrobial enzymes. Lysozyme is a natural enzyme with antimicrobial activity that has attracted considerable attention to be potentially utilized in various industries. Since lysozyme is an intrinsic component of the human immune system and has low toxicity; it could be considered as a natural antimicrobial agent for use in food and pharmaceutical industries. Lysozyme exerts antimicrobial activity against microorganisms, especially Gram-positive bacteria, by hydrolyzing 1,4-beta-linkages between N-acetylmuramic acid and N-acetylglucosamine in the cell wall. In addition, increased antimicrobial activity of lysozyme against Gram-negative bacteria could be achieved by the modification of lysozyme through physical or chemical interactions. Lysozyme is presented as a natural preservative in mammalian milk and can be utilized as a bio-preservative in dairy products, such as cheese. Both bacteria and fungi can contaminate and spoil the cheese; especially the one that is made traditionally by raw milk. Furthermore, uncontrolled and improper processes and post-pasteurization contamination can participate in the cheese contamination. Therefore, besides common preservative strategies applied in cheese production, lysozyme could be utilized alone or in combination with other preservative strategies to improve the safety of cheese. Hence, this study aimed to review the antimicrobial properties of lysozyme as natural antimicrobial enzyme and its functionality in cheese.
Behavioral and Neuropathological Changes After Toxoplasma gondii Ocular Conjunctival Infection in BALB/c Mice

Ocular infection with Toxoplasma gondii causes toxoplasmosis in mice. However, following ocular infection with tachyzoites, the cause of the accompanying progressive changes in hippocampal-dependent tasks, and their relationship with the morphology and number of microglia, is less well understood. Here, in 6-month-old, female BALB/c mice, 5 μl of a suspension containing 48.5 × 106 tachyzoites/ml was introduced into the conjunctival sac; control received an equal volume of saline. Before and after instillation, all mice were subject to an olfactory discrimination (OD) test, using predator (cat) feces, and to an open-field (OF) task. After the behavioral tests, the animals were culled at either 22 or 44 days post-instillation (dpi), and the brains and retinas were dissected and processed for immunohistochemistry. The total number of Iba-1-immunolabeled microglia in the molecular layer of the dentate gyrus was estimated, and three-dimensional reconstructions of the cells were evaluated. Immobility was increased in the infected group at 12, 22, and 43 dpi, but the greatest immobility was observed at 22 dpi and was associated with reduced line crossing in the OF and distance traveled. In the OD test, infected animals spent more time in the compartment with feline fecal material at 14 and at 43 dpi. No OD changes were observed in the control group. The number of microglia was increased at 22 dpi but returned to control levels by 44 dpi. These changes were associated with the differentiation of T. gondii tachyzoites into bradyzoite-enclosed cysts within the brain and retina. Thus, infection of mice with T. gondii alters exploratory behavior, gives rise to a loss in predator’s odor avoidance from 2 weeks after infection, increased microglia number, and altered their morphology in the molecular layer of the dentate gyrus.
Compact Neural Architecture Designs by Tensor Representations

We propose a framework of tensorial neural networks (TNNs) extending existing linear layers on low-order tensors to multilinear operations on higher-order tensors. TNNs have three advantages over existing networks: First, TNNs naturally apply to higher-order data without flattening, which preserves their multi-dimensional structures. Second, compressing a pre-trained network into a TNN results in a model with similar expressive power but fewer parameters. Finally, TNNs interpret advanced compact designs of network architectures, such as bottleneck modules and interleaved group convolutions. To learn TNNs, we derive their backpropagation rules using a novel suite of generalized tensor algebra. With backpropagation, we can either learn TNNs from scratch or pre-trained models using knowledge distillation. Experiments on VGG, ResNet, and Wide-ResNet demonstrate that TNNs outperform the state-of-the-art low-rank methods on a wide range of backbone networks and datasets.
Identification of the Genes of the Plant Pathogen Pseudomonas syringae MB03 Required for the Nematicidal Activity Against Caenorhabditis elegans Through an Integrated Approach

Nematicidal potential of the common plant pathogen Pseudomonas syringae has been recently identified against Caenorhabditis elegans. The current study was designed to investigate the detailed genetic mechanism of the bacterial pathogenicity by applying comparative genomics, transcriptomics, mutant library screening, and protein expression. Results showed that P. syringae strain MB03 could kill C. elegans in the liquid assay by gut colonization. The genome of P. syringae MB03 was sequenced and comparative analysis including multi locus sequence typing, and genome-to-genome distance placed MB03 in phylogroup II of P. syringae. Furthermore, comparative genomics of MB03 with nematicidal strains of Pseudomonas aeruginosa (PAO1 and PA14) predicted 115 potential virulence factors in MB03. However, genes for previously reported nematicidal metabolites, such as phenazine, pyochelin, and pyrrolnitrin, were found absent in the MB03 genome. Transcriptomics analysis showed that the growth phase of the pathogen considerably affected the expression of virulence factors, as genes for the flagellum, glutamate ABC transporter, phoP/phoQ, fleS/fleR, type VI secretion system, and serralysin were highly up-regulated when stationary phase MB03 cells interacted with C. elegans. Additionally, screening of a transposon insertion mutant library led to the identification of other nematicidal genes such as acnA, gltP, oprD, and zapE. Finally, the nematicidal activity of selected proteins was confirmed by heterologous expression in Escherichia coli.
Combined Electron Microscopy Approaches for Arterial Glycocalyx Visualization

Mainly constituted of glycosaminoglycans and proteoglycans, the glycocalyx is anchored in the plasma membrane, covering, in particular, the extracellular face of the arterial endothelium. Due to its complex three-dimensional (3D) architecture, the glycocalyx interacts with a wide variety of proteins, contributing to vascular permeability, the flow of mechanotransduction, and the modulation of local inflammatory processes. Alterations of glycocalyx structure mediate the endothelial dysfunction and contribute to the aggravation of peripheral vascular diseases. Therefore, the exploration of its ultrastructure becomes a priority to evaluate the degree of injury under physiopathological conditions and to assess the impact of therapeutic approaches. The objective of this study was to develop innovative approaches in electron microscopy to visualize the glycocalyx at the subcellular scale. Intravenous perfusion on rats with a fixing solution containing aldehyde fixatives enriched with lanthanum ions was performed to prepare arterial samples. The addition of lanthanum nitrate in the fixing solution allowed the enhancement of the staining of the glycocalyx for transmission electron microscopy (TEM) and to detect elastic and inelastic scattered electrons, providing complementary qualitative information. The strength of scanning electron microscopy (SEM) was used on resin-embedded serial sections, allowing rapid and efficient large field imaging and previous correlative TEM observations for ultrastructural fine details. To demonstrate the dynamic feature of the glycocalyx, 3D tomography was provided by dual-beam focus-ion-beam-SEM (FIB-SEM). These approaches allowed us to visualize and characterize the ultrastructure of the pulmonary artery glycocalyx under physiological conditions and in a rat pulmonary ischemia-reperfusion model, known to induce endothelial dysfunction. This study demonstrates the feasibility of combined SEM, TEM, and FIB-SEM tomography approaches on the same sample as the multiscale visualization and the identification of structural indicators of arterial endothelial glycocalyx integrity.
Advances in Multimodality Cardiovascular Imaging in the Diagnosis of Heart Failure With Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is a syndrome defined by the presence of heart failure symptoms and increased levels of circulating natriuretic peptide (NP) in patients with preserved left ventricular ejection fraction and various degrees of diastolic dysfunction (DD). HFpEF is a complex condition that encompasses a wide range of different etiologies. Cardiovascular imaging plays a pivotal role in diagnosing HFpEF, in identifying specific underlying etiologies, in prognostic stratification, and in therapeutic individualization. Echocardiography is the first line imaging modality with its wide availability; it has high spatial and temporal resolution and can reliably assess systolic and diastolic function. Cardiovascular magnetic resonance (CMR) is the gold standard for cardiac morphology and function assessment, and has superior contrast resolution to look in depth into tissue changes and help to identify specific HFpEF etiologies. Differently, the most important role of nuclear imaging [i.e., planar scintigraphy and/or single photon emission CT (SPECT)] consists in the screening and diagnosis of cardiac transthyretin amyloidosis (ATTR) in patients with HFpEF. Cardiac CT can accurately evaluate coronary artery disease both from an anatomical and functional point of view, but tissue characterization methods have also been developed. The aim of this review is to critically summarize the current uses and future perspectives of echocardiography, nuclear imaging, CT, and CMR in patients with HFpEF.
Characterization of Somatic Mutations That Affect Neoantigens in Non-Small Cell Lung Cancer

Purpose Immune checkpoint inhibitors (ICIs) have recently emerged as an important option for treating patients with advanced non-small cell lung cancer (NSCLC). Neoantigens are important biomarkers and potential immunotherapy targets that play important roles in the prognosis and treatment of patients with NSCLC. This study aimed to evaluate and characterize the relationships between somatic mutations and potential neoantigens in specimens from patients who underwent surgical treatment for NSCLC. Patients and Methods This prospective study evaluated specimens from patients with NSCLC who underwent surgical treatment at the Peking Union Medical College, China, from June 2019 to September 2019. Whole-exome sequencing was performed for tumor tissues and corresponding normal tissues. Candidate neoantigens were predicted using generative software, and the relationships between various mutation characteristics and number of neoantigens were evaluated. Results Neoantigen-related gene mutations were less frequent than mutations affecting the whole genome. Genes with high neoantigen burden had more types and higher frequencies of mutations. The number of candidate neoantigens was positively correlated with missense mutations, code shift insertions/deletions, split-site variations, and nonsense mutations. However, in the multiple linear regression analysis, only missense mutations were positively correlated with the number of neoantigens. The number of neoantigens was also positively correlated with base transversions (A>C/C>A, T>G/G>T, and C>G/G>C) and negatively correlated with base transitions (A>G/G>A and C>T/T>C). Conclusion The number of candidate neoantigens in NSCLC specimens was associated with mutation frequency, type of mutation, and type of base substitution.
Human Mitochondrial DNA Polymerase Metal Dependent UV Lesion Bypassing Ability

Human mitochondrial DNA contains more UV-induced lesions than the nuclear DNA due to lack of mechanism to remove bulky photoproducts. Human DNA polymerase gamma (Pol γ) is the sole DNA replicase in mitochondria, which contains a polymerase (pol) and an exonuclease (exo) active site. Previous studies showed that Pol γ only displays UV lesion bypassing when its exonuclease activity is obliterated. To investigate the reaction environment on Pol γ translesion activity, we tested Pol γ DNA activity in the presence of different metal ions. While Pol γ is unable to replicate through UV lesions on DNA templates in the presence of Mg2+, it exhibits robust translesion DNA synthesis (TLS) on cyclobutane pyrimidine dimer (CPD)-containing template when Mg2+ was mixed with or completely replaced by Mn2+. Under these conditions, the efficiency of Pol γ′s TLS opposite CPD is near to that on a non-damaged template and is 800-fold higher than that of exonuclease-deficient Pol γ. Interestingly, Pol γ exhibits higher exonuclease activity in the presence of Mn2+ than with Mg2+, suggesting Mn2+-stimulated Pol γ TLS is not via suppressing its exonuclease activity. We suggest that Mn2+ ion expands Pol γ′s pol active site relative to Mg2+ so that a UV lesion can be accommodated and blocks the communication between pol and exo active sites to execute translesion DNA synthesis.
Directed Evolution of Methanomethylophilus alvus Pyrrolysyl-tRNA Synthetase Generates a Hyperactive and Highly Selective Variant

Pyrrolysyl-tRNA synthetase (PylRS) is frequently used for site-specific incorporation of noncanonical amino acids (ncAAs) into proteins. Recently, the active site of Methanomethylophilus alvus PylRS (MaPylRS) has been rationally engineered to expand its substrate compatibility, enabling the incorporation of difficult ncAAs. However, mutations beyond the active site that enhance the enzymatic properties of MaPylRS have not been reported. We utilized phage-assisted non-continuous evolution (PANCE) to evolve MaPylRS to efficiently incorporate N ε-Boc-l-lysine (BocK). Directed evolution yielded several mutations outside of the active site that greatly improve the activity of the enzyme. We combined the most effective mutations to generate a new PylRS variant (PylRSopt) that is highly active and selective towards several lysine and phenylalanine derivatives. The mutations in PylRSopt can be used to enhance previously engineered PylRS constructs such as MaPylRSN166S, and PylRSopt is compatible in applications requiring dual ncAA incorporation and substantially improves the yield of these target proteins.
Prediction Method of TBM Tunneling Parameters Based on PSO-Bi-LSTM Model

With the wide application of full-face rock tunnel boring machine (TBM) in tunnel construction, the self-adaptive adjustment of TBM tunneling parameters is of great significance for the safety and efficiency of TBM tunnelling. Aiming at the shortcomings of the current TBM data mining capability and optimization methods of tunneling parameters, this paper proposes a prediction method of TBM tunneling parameters based on particle swarm optimization-bi-directional long short-term memory (PSO-Bi-LSTM) model, which selects the complete tunneling cycle data to predict the TBM tunneling parameters, and uses a number of numerical methods such as binary state discriminant function and 3 σ criterion to preprocess the operation data of TBM3 bid section of Songhua River water conveyance project. By comparing with the Bi-LSTM model and evaluating the prediction effect under different surrounding rock levels, the applicability and prediction performance of the model to different strata are verified. The results show that the prediction accuracy of the model is proportional to the surrounding rock grade. Compared with the Bi-LSTM, the overall prediction effect of the proposed PSO-Bi-LSTM model is better, which can assist the intelligent construction of TBM with similar geological conditions.
The Roles of Junctional Adhesion Molecules (JAMs) in Cell Migration

The review briefly summarizes the role of the family of adhesion molecules, JAMs (junctional adhesion molecules), in various cell migration, covering germ cells, epithelial cells, endothelial cells, several leukocytes, and different cancer cells. These functions affect multiple diseases, including reproductive diseases, inflammation-related diseases, cardiovascular diseases, and cancers. JAMs bind to both similar and dissimilar proteins and take both similar and dissimilar effects on different cells. Concluding relevant results provides a reference to further research.