Traumatic Brain Injury Induces Genome-Wide Transcriptomic, Methylomic, and Network Perturbations in Brain and Blood Predicting Neurological Disorders.

The complexity of the traumatic brain injury (TBI) pathology, particularly concussive injury, is a serious obstacle for diagnosis, treatment, and long-term prognosis. Here we utilize modern systems biology in a rodent model of concussive injury to gain a thorough view of the impact of TBI on fundamental aspects of gene regulation, which have the potential to drive or alter the course of the TBI pathology. TBI perturbed epigenomic programming, transcriptional activities (expression level and alternative splicing), and the organization of genes in networks centered around genes such as Anax2, Ogn, and Fmod. Transcriptomic signatures in the hippocampus are involved in neuronal signaling, metabolism, inflammation, and blood function, and they overlap with those in leukocytes from peripheral blood. The homology between genomic signatures from blood and brain elicited by TBI provides proof of concept information for development of biomarkers of TBI based on composite genomic patterns. By intersecting with human genome-wide association studies, many TBI signature genes and network regulators identified in our rodent model were causally associated with brain disorders with relevant link to TBI. The overall results show that concussive brain injury reprograms genes which could lead to predisposition to neurological and psychiatric disorders, and that genomic information from peripheral leukocytes has the potential to predict TBI pathogenesis in the brain

A Triple-Network Dynamic Connection Study in Alzheimer's Disease

© 2022 Meng, Wu, Liang, Zhang, Xu, Yang and Meng. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY). https://creativecommons.org/licenses/by/4.0/Alzheimer's disease (AD) was associated with abnormal organization and function of large-scale brain networks. We applied group independent component analysis (Group ICA) to construct the triple-network consisting of the saliency network (SN), the central executive network (CEN), and the default mode network (DMN) in 25 AD, 60 mild cognitive impairment (MCI) and 60 cognitively normal (CN) subjects. To explore the dynamic functional network connectivity (dFNC), we investigated dynamic time-varying triple-network interactions in subjects using Group ICA analysis based on k-means clustering (GDA-k-means). The mean of brain state-specific network interaction indices (meanNII) in the three groups (AD, MCI, CN) showed significant differences by ANOVA analysis. To verify the robustness of the findings, a support vector machine (SVM) was taken meanNII, gender and age as features to classify. This method obtained accuracy values of 95, 94, and 77% when classifying AD vs. CN, AD vs. MCI, and MCI vs. CN, respectively. In our work, the findings demonstrated that the dynamic characteristics of functional interactions of the triple-networks contributed to studying the underlying pathophysiology of AD. It provided strong evidence for dysregulation of brain dynamics of AD.Peer reviewedFinal Published versio

Anisotropic Generalized Bayesian Coherent Point Drift for Point Set Registration

Registration is highly demanded in many real-world scenarios such as robotics and automation. Registration is challenging partly due to the fact that the acquired data is usually noisy and has many outliers. In addition, in many practical applications, one point set (PS) usually only covers a partial region of the other PS. Thus, most existing registration algorithms cannot guarantee theoretical convergence. This article presents a novel, robust, and accurate three-dimensional (3D) rigid point set registration (PSR) method, which is achieved by generalizing the state-of-the-art (SOTA) Bayesian coherent point drift (BCPD) theory to the scenario that high-dimensional point sets (PSs) are aligned and the anisotropic positional noise is considered. The high-dimensional point sets typically consist of the positional vectors and normal vectors. On one hand, with the normal vectors, the proposed method is more robust to noise and outliers, and the point correspondences can be found more accurately. On the other hand, incorporating the registration into the BCPD framework will guarantee the algorithm's theoretical convergence. Our contributions in this article are three folds. First, the problem of rigidly aligning two general PSs with normal vectors is incorporated into a variational Bayesian inference framework, which is solved by generalizing the BCPD approach while the anisotropic positional noise is considered. Second, the updated parameters during the algorithm's iterations are given in closed-form or with iterative solutions. Third, extensive experiments have been done to validate the proposed approach and its significant improvements over the BCPD

Two Efficient and Regulatory Confidential Transaction Schemes

With the development of Bitcoin, Ethereum and other projects, blockchain has been widely concerned with its outstanding characteristics such as non-centralization, collective maintenance, openness and transparency. Blockchain has been widely used in finance, logistics, copyright and other fields. However, as transactions are stored in plaintext in the blockchain for public verification, the privacy of users is not well guaranteed such that many financial applications can not be adopted widely. How to securely and economically protect the privacy of transactions is worth further research. In this paper, we have proposed two efficient and regulatory confidential transaction schemes using homomorphic encryption and zero-knowledge proof. ERCO, the first scheme, turns the standard ElGamal algorithm to be additively homomorphic and expands it into four ciphertexts such that $(m,r)$ in the transaction can be decrypted. Its security can be reduced to DDH assumption and the transaction size is less. PailGamal, the second scheme, is based on the combination of Paillier and ElGamal algorithms. Its security can be reduced to DDH assumption and it empowers regulators greater powers to obtain transaction-related specific content. In contrast to other ElGamal-based schemes, PailGamal makes any token amount directly decrypted without calculating a discrete logarithm problem. As any $(m,r)$ in transactions can be decrypted directly, game theory is applied to further reduce transaction size

Microcrystalline Dolomite in a Middle Permian Volcanic Lake: Insights on Primary Dolomite Formation in a Non-Evaporitic Environment

Lacustrine dolomite nucleation commonly occurs in modern and Neogene evaporitic alkaline lakes. As a result, ancient lacustrine microcrystalline dolomite has been conventionally interpreted to be formed in evaporitic environments. This study, however, suggests a non-evaporitic origin of dolomite precipitated in a volcanic–hydrothermal lake, where hydrothermal and volcanic processes interacted. The dolomite occurs in lacustrine fine-grained sedimentary rocks in the middle Permian Lucaogou Formation in the Santanghu intracontinental rift basin, north-west China. Dolostones are composed mainly of nano-sized to micron-sized dolomite with a euhedral to subhedral shape and a low degree of cation ordering, and are interlaminated and intercalated with tuffaceous shale. Non-dolomite minerals, including quartz, alkaline feldspars, smectite and magnesite mix with the dolomite in various proportions. The 87Sr/86Sr ratios (0.704528 to 0.705372, average = 0.705004) and δ26Mg values (−0.89 to −0.24‰, average = −0.55‰) of dolostones are similar to those of mantle rocks, indicating that the precipitates mainly originated from fluids that migrated upward from the mantle and were subject to water–rock reactions at a great depth. The δ18O values (−3.1 to −22.7‰, average = −14.0‰) of the dolostones indicate hydrothermal influence. The trace and rare earth element concentrations suggest a saline, anoxic and volcanic–hydrothermally-influenced subaqueous environment. In this subaqueous environment of Lucaogou lake, locally high temperatures and a supply of abundant Mg2+ from a deep source induced by volcanic–hydrothermal activity formed favourable chemical conditions for direct precipitation of primary dolomite. This study\u27s findings deepen the understanding of the origin and processes of lacustrine primary dolomite formation and provide an alternative possibility for environmental interpretations of ancient dolostones

Evaluation of the reporting quality of clinical practice guidelines on gliomas using the RIGHT checklist

Background: The reporting quality of clinical practice guidelines (CPGs) for gliomas has not yet been thoroughly assessed. The International Reporting Items for Practice Guidelines in Healthcare (RIGHT) statement developed in 2016 provides a reporting framework to improve the quality of CPGs. We aimed to estimate the reporting quality of glioma guidelines using the RIGHT checklist and investigate how the reporting quality differs by selected characteristics. Methods: We systematically searched electronic databases, guideline databases, and medical society websites to retrieve CPGs on glioma published between 2018 and 2020. We calculated the compliance of the CPGs to individual items, domains and the RIGHT checklist overall. We performed stratified analyses by publication year, country of development, reporting of funding, and impact factor (IF) of the journal. Results: Our search revealed 20 eligible guidelines. Mean overall adherence to the RIGHT statement was 54.6%. Eight CPGs reported more than 60% of the items, and five reported less than 50%. All guidelines adhered to the items 1a, 3, 7a, 13a, while no guidelines reported the items 17 or 18b (see http://www.rightstatement.org/right-statement/checklist for a description of the items). Two of the seven domains, "Basic information" and "Background", had mean reporting rates above 60%. The "Review and quality assurance" domain had the lowest mean reporting rate, 12.5%. The reporting quality of guidelines published in 2020, guidelines developed in the United States, and guidelines that reported funding tended to be above average. Conclusions: The reporting quality of CPGs on gliomas is low and needs improvement. Particular attention should be paid on reporting the external review and quality assurance process. The use of the RIGHT criteria should be encouraged to guide the development, reporting and evaluation of CPGs

A Combined Modeling and Experimental Study of Tensile Properties of Additively Manufactured Polymeric Composite Materials

In this study, the mechanical properties, in terms of stress–strain curves, of additively manufactured polymeric composite materials, Tango black plus (TB+), vero white plus (VW ), and their intermediate materials with different mixing ratios, are reported. The ultimate tensile strength and elongation at break are experimentally measured using ASTM standard tensile test. As the content of VM+ increases, the strength of the polymeric materials increases and elongation decreases. Additionally, the Shore A hardness of the materials increases with reduced TB+ concentration. In parallel to the experiment, hyperelastic models are employed to fit the experimental stress–strain curves. The shear modulus of the materials is obtained from the Arruda–Boyce model, and it increases with reduced concentration of TB+. Due to the good quality of the fitted data, it is suggested that the Arruda–Boyce model is the best model for modeling the additively manufactured polymeric materials. With the well characterized and modeled mechanical properties of these hyperelastic materials, designers can conduct computational study for application in flexible electronics field