Single cell molecular alterations reveal target cells and pathways of concussive brain injury.

The complex neuropathology of traumatic brain injury (TBI) is difficult to dissect, given the convoluted cytoarchitecture of affected brain regions such as the hippocampus. Hippocampal dysfunction during TBI results in cognitive decline that may escalate to other neurological disorders, the molecular basis of which is hidden in the genomic programs of individual cells. Using the unbiased single cell sequencing method Drop-seq, we report that concussive TBI affects previously undefined cell populations, in addition to classical hippocampal cell types. TBI also impacts cell type-specific genes and pathways and alters gene co-expression across cell types, suggesting hidden pathogenic mechanisms and therapeutic target pathways. Modulating the thyroid hormone pathway as informed by the T4 transporter transthyretin Ttr mitigates TBI-associated genomic and behavioral abnormalities. Thus, single cell genomics provides unique information about how TBI impacts diverse hippocampal cell types, adding new insights into the pathogenic pathways amenable to therapeutics in TBI and related disorders

Rule-Guided Compositional Representation Learning on Knowledge Graphs

Representation learning on a knowledge graph (KG) is to embed entities and relations of a KG into low-dimensional continuous vector spaces. Early KG embedding methods only pay attention to structured information encoded in triples, which would cause limited performance due to the structure sparseness of KGs. Some recent attempts consider paths information to expand the structure of KGs but lack explainability in the process of obtaining the path representations. In this paper, we propose a novel Rule and Path-based Joint Embedding (RPJE) scheme, which takes full advantage of the explainability and accuracy of logic rules, the generalization of KG embedding as well as the supplementary semantic structure of paths. Specifically, logic rules of different lengths (the number of relations in rule body) in the form of Horn clauses are first mined from the KG and elaborately encoded for representation learning. Then, the rules of length 2 are applied to compose paths accurately while the rules of length 1 are explicitly employed to create semantic associations among relations and constrain relation embeddings. Besides, the confidence level of each rule is also considered in optimization to guarantee the availability of applying the rule to representation learning. Extensive experimental results illustrate that RPJE outperforms other state-of-the-art baselines on KG completion task, which also demonstrate the superiority of utilizing logic rules as well as paths for improving the accuracy and explainability of representation learning.Comment: The full version of a paper accepted to AAAI 202

Infection-free rates and Sequelae predict factors in bone transportation for infected tibia: a systematic review and meta-analysis

Abstract Background Tibia infected nonunion and chronic osteomyelitis are challenging clinical presentations. Bone transportation with external or hybrid fixators (combined external and internal fixators) is versatile to solve these problems. However, the infection-free rates of these fixator systems are unknown. Additionally, the prognosis factors for results of bone transportation are obscure. Therefore, this systematic review and meta-analysis was conducted to answer these questions. Methods A systematic review was conducted following the PRISMA-IPD guidelines. Relevant publications from January 1995 to September 2018 were compiled from Medline, Embase, and Cochrane. The infection-free rates of external and hybrid fixators were achieved by synthesizing aggregate data and individual participant data (IPD). IPD was analyzed by two-stage method with logistical regression to identify prognosis factors of sequelae. Results Twenty-two studies with 518 patients were identified, including 11 studies with 167 patients’ IPD, and 11 studies with 351 patients’ aggregate data. The infection-free rate of hybrid fixator group was 86% (95%CI: 79–94%), lower than that of external fixator which was 97% (95%CI: 95–98%,). The number of previous surgeries was found predict factor of bone union sequelae (p = 0.04) and function sequelae(p < 0.01); The external fixation time was found predict factor of function sequelae (p = 0.015). Conclusions Hybrid fixators may be associated with a greater risk of infection-recurrence in the treatment of tibia infected nonunion and chronic osteomyelitis. The number of previous surgeries and external fixation time can be used as predictors of outcomes. Proper fixators and meticulously designed surgery are important to avoid unexpected operations and shorten external fixation time.https://deepblue.lib.umich.edu/bitstream/2027.42/146740/1/12891_2018_Article_2363.pd

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

General synthesis of transition metal oxide ultrafine nanoparticles embedded in hierarchically porous carbon nanofibers as advanced electrodes for lithium storage

A unique general, large-scale, simple, and cost-effective strategy, i.e., foaming-assisted electrospinning, for fabricating various transition metal oxides into ultrafine nanoparticles (TMOs UNPs) that are uniformly embedded in hierarchically porous carbon nanofibers (HPCNFs) has been developed. Taking advantage of the strong repulsive forces of metal azides as the pore generator during carbonization, the formation of uniform TMOs UNPs with homogeneous distribution and HPCNFs is simultaneously implemented. The combination of uniform ultrasmall TMOs UNPs with homogeneous distribution and hierarchically porous carbon nanofibers with interconnected nanostructure can effectively avoid the aggregation, dissolution, and pulverization of TMOs, promote the rapid 3D transport of both Li ions and electrons throughout the whole electrode, and enhance the electrical conductivity and structural integrity of the electrode. As a result, when evaluated as binder-free anode materials in Li-ion batteries, they displayed extraordinary electrochemical properties with outstanding reversible capacity, excellent capacity retention, high Coulombic efficiency, good rate capability, and superior cycling performance at high rates. More importantly, the present work opens up a wide horizon for the fabrication of a wide range of ultrasmall metal/metal oxides distributed in 1D porous carbon structures, leading to advanced performance and enabling their great potential for promising large-scale applications