Distinct subnetworks of the thalamic reticular nucleus.

The thalamic reticular nucleus (TRN), the major source of thalamic inhibition, regulates thalamocortical interactions that are critical for sensory processing, attention and cognition1-5. TRN dysfunction has been linked to sensory abnormality, attention deficit and sleep disturbance across multiple neurodevelopmental disorders6-9. However, little is known about the organizational principles that underlie its divergent functions. Here we performed an integrative study linking single-cell molecular and electrophysiological features of the mouse TRN to connectivity and systems-level function. We found that cellular heterogeneity in the TRN is characterized by a transcriptomic gradient of two negatively correlated gene-expression profiles, each containing hundreds of genes. Neurons in the extremes of this transcriptomic gradient express mutually exclusive markers, exhibit core or shell-like anatomical structure and have distinct electrophysiological properties. The two TRN subpopulations make differential connections with the functionally distinct first-order and higher-order thalamic nuclei to form molecularly defined TRN-thalamus subnetworks. Selective perturbation of the two subnetworks in vivo revealed their differential role in regulating sleep. In sum, our study provides a comprehensive atlas of TRN neurons at single-cell resolution and links molecularly defined subnetworks to the functional organization of thalamocortical circuits.

Whole-brain mapping of histaminergic projections in mouse brain.

Histamine is a conserved neuromodulator in mammalian brains and critically involved in many physiological functions. Understanding the precise structure of the histaminergic network is the cornerstone in elucidating its function. Herein, using histidine decarboxylase (HDC)-CreERT2 mice and genetic labeling strategies, we reconstructed a whole-brain three dimensional (3D) structure of histaminergic neurons and their outputs at 0.32 × 0.32 × 2 µm3 pixel resolution with a cutting-edge fluorescence microoptical sectioning tomography system. We quantified the fluorescence density of all brain areas and found that histaminergic fiber density varied significantly among brain regions. The density of histaminergic fiber was positively correlated with the amount of histamine release induced by optogenetic stimulation or physiological aversive stimulation. Lastly, we reconstructed a fine morphological structure of 60 histaminergic neurons via sparse labeling and uncovered the largely heterogeneous projection pattern of individual histaminergic neurons. Collectively, this study reveals an unprecedented whole-brain quantitative analysis of histaminergic projections at the mesoscopic level, providing a foundation for future functional histaminergic study.

Rice myo-inositol-3-phosphate synthase 2 (RINO2) alleviates heat injury-induced impairment in pollen germination and tube growth by modulating Ca2+ signaling and actin filament cytoskeleton.

Low phytic acid (lpa) crop is considered as an effective strategy to improve crop nutritional quality, but a substantial decrease in phytic acid (PA) usually has negative effect on agronomic performance and its response to environment adversities. Myo-inositol-3-phosphate synthase (MIPS) is the rate-limiting enzyme in PA biosynthesis pathway, and regarded as the prime target for engineering lpa crop. In this paper, the rice MIPS gene (RINO2) knockout mutants and its wild type were performed to investigate the genotype-dependent alteration in the heat injury-induced spikelet fertility and its underlying mechanism for rice plants being imposed to heat stress at anthesis. Results indicated that RINO2 knockout significantly enhanced the susceptibility of rice spikelet fertility to heat injury, due to the severely exacerbated obstacles in pollen germination and pollen tube growth in pistil for RINO2 knockout under high temperature (HT) at anthesis. The loss of RINO2 function caused a marked reduction in inositol and phosphatidylinositol derivative concentrations in the HT-stressed pollen grains, which resulted in the strikingly lower content of phosphatidylinositol 4,5-diphosphate (PI (4,5) P2) in germinating pollen grain and pollen tube. The insufficient supply of PI (4,5) P2 in the HT-stressed pollen grains disrupted normal Ca2+ gradient in the apical region of pollen tubes and actin filament cytoskeleton in growing pollen tubes. The severely repressed biosynthesis of PI (4,5) P2 was among the regulatory switch steps leading to the impaired pollen germination and deformed pollen tube growth for the HT-stressed pollens of RINO2 knockout mutants.

How well do neural signatures of resting-state EEG detect consciousness? A large-scale clinical study.

The assessment of consciousness states, especially distinguishing minimally conscious states (MCS) from unresponsive wakefulness states (UWS), constitutes a pivotal role in clinical therapies. Despite that numerous neural signatures of consciousness have been proposed, the effectiveness and reliability of such signatures for clinical consciousness assessment still remains an intense debate. Through a comprehensive review of the literature, inconsistent findings are observed about the effectiveness of diverse neural signatures. Notably, the majority of existing studies have evaluated neural signatures on a limited number of subjects (usually below 30), which may result in uncertain conclusions due to small data bias. This study presents a systematic evaluation of neural signatures with large-scale clinical resting-state electroencephalography (EEG) signals containing 99 UWS, 129 MCS, 36 emergence from the minimally conscious state, and 32 healthy subjects (296 total) collected over 3 years. A total of 380 EEG-based metrics for consciousness detection, including spectrum features, nonlinear measures, functional connectivity, and graph-based measures, are summarized and evaluated. To further mitigate the effect of data bias, the evaluation is performed with bootstrap sampling so that reliable measures can be obtained. The results of this study suggest that relative power in alpha and delta serve as dependable indicators of consciousness. With the MCS group, there is a notable increase in the phase lag index-related connectivity measures and enhanced functional connectivity between brain regions in comparison to the UWS group. A combination of features enables the development of an automatic detector of conscious states.

Rice ins(3)P synthase1 (RINO1) participates in embryonic development by regulating inositol-associated changes in auxin synthesis and its distribution.

The breeding of low phytic acid (LPA) crops is widely considered an effective strategy to improve crop nutrition, but the LPA crops usually have inferior seed germination performance. To clarify the reason for the suboptimal seed performance of LPA rice, this study investigated the impact of reduced seed phytic acid (InsP6) content in rice ins(3)P synthase1 (EC 5.5.1.4, RINO1), one of the key targets for engineering LPA rice, knockouton cellular differentiation in seed embryos and its relation to myo-inositol metabolism and auxin signalling during embryogenesis. The results indicated that the homozygotes of RINO1 knockout could initiate differentiation at the early stage of embryogenesis but failed to form normal differentiation of plumule and radicle primordia. The loss of RINO1 function disrupted vesicle trafficking and auxin signalling due to the significantly lowered phosphatidylinositides (PIs) concentration in seed embryos, thereby leading to the defects of seed embryos without the recognizable differentiation of shoot apex meristem (SAM) and radicle apex meristem (RAM) for the homozygotes of RINO1 knockout. The abnormal embryo phenotype of RINO1 homozygotes was partially rescued by exogenous spraying of inositol and indole-3-acetic acid (IAA) in rice panicle. Thus, RINO1 is crucial for both seed InsP6 biosynthesis and embryonic development. The lower phosphatidylinositol (4,5)-bisphosphate (PI (4,5) P2) concentration and the disorder auxin distribution induced by insufficient inositol supply in seed embryos were among the regulatory switch steps leading to aberrant embryogenesis and failure of seed germination in RINO1 knockout.

Design and application of a multimodality-compatible 1Tx/6Rx RF coil for monkey brain MRI at 7T.

OBJECTIVE: Blood-oxygen-level-dependent functional MRI allows to investigte neural activities and connectivity. While the non-human primate plays an essential role in neuroscience research, multimodal methods combining functional MRI with other neuroimaging and neuromodulation enable us to understand the brain network at multiple scales. APPROACH: In this study, a tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed in the coil housing to accommodate multimodal devices, and the coil performance was quantitatively evaluated and compared to a commercial knee coil. In addition, experiments over three macaques with infrared neural stimulation (INS), focused ultrasound stimulation (FUS), and transcranial direct current stimulation (tDCS) were conducted. MAIN RESULTS: The RF coil showed higher transmit efficiency, comparable homogeneity, improved SNR and enlarged signal coverage over the macaque brain. Infrared neural stimulation was applied to the amygdala in deep brain region, and activations in stimulation sites and connected sites were detected, with the connectivity consistent with anatomical information. Focused ultrasound stimulation was applied to the left visual cortex, and activations were acquired along the ultrasound traveling path, with all time course curves consistent with pre-designed paradigms. The existence of transcranial direct current stimulation electrodes brought no interference to the RF system, as evidenced through high-resolution MPRAGE structure images. SIGNIFICANCE: This pilot study reveals the feasibility for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks.

ABA-triggered ROS burst in rice developing anthers is critical for tapetal programmed cell death induction and heat stress-induced pollen abortion.

High temperatures (HT) cause pollen abortion and poor floret fertility in rice, which is closely associated with excessive accumulation of reactive oxygen species (ROS) in the developing anthers. However, the relationships between accumulation of abscisic acid (ABA) and ROS, and their effects on tapetum-specific programmed cell death (PCD) in HT-stressed anthers are poorly characterised. Here, we determined the spatiotemporal changes in ABA and ROS levels, and their relationships with tapetal PCD under HT exposure. Mutants lacking ABA-activated protein kinase 2 (SAPK2) functions and exogenous ABA treatments were used to explore the effects of ABA signalling on the induction of PCD and ROS accumulation during pollen development. HT-induced pollen abortion was tightly associated with ABA accumulation and oxidative stress. The higher ABA level in HT-stressed anthers resulted in the earlier initiation of PCD induction and subsequently abnormal tapetum degeneration by activating ROS accumulation in developing anthers. Interactions between SAPK2 and DEAD-box ATP-dependent RNA helicase elF4A-1 (RH4) were required for ABA-induced ROS generation in developing anthers. The OsSAPK2 knockout mutants showed the impaired PCD responses in the absence of HT. However, the deficiency of SAPK2 functions did not suppress the ABA-mediated ROS generation in HT-stressed anthers.

A novel ribociclib derivative WXJ-103 exerts anti-breast cancer effect through CDK4/6.

The triple-negative breast cancer (TNBC) subtype is the most aggressive type of breast cancer with a low survival prognosis and high recurrence rate. There is currently no effective treatment to improve it. In this work, we explored the effect of a synthetic compound named WXJ-103 on several aspects of TNBC biology. The human breast cancer cell lines MDA-MB-231 and MCF-7 were used in the experiments, and the cell viability was detected by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide method, and the cell migration and invasion abilities were detected by wound healing assay and Transwell invasion assay. Cell cycle and apoptosis experiments were analyzed by flow cytometry, and protein levels related to cyclin-dependent kinase (CDK) 4/6-cyclin D-Rb-E2F pathway were analyzed by western blotting. Then, in-vivo experiments were performed to determine the clinical significance and functional role of WXJ-103. The results show that WXJ-103 can inhibit the adhesion, proliferation, migration, and invasion of TNBC cells, and can arrest the cell cycle in G1 phase. The levels of CDK4/6-cyclin D-Rb-E2F pathway-related proteins such as CDK6 and pRb decreased in a dose-dependent manner. Therefore, the antitumor activity of WXJ-103 may depend on the inhibition of CDK4/6-cyclin D1-Rb-E2F pathway. This research shows that WXJ-103 may be a new promising antitumor drug, which can play an antitumor effect on TNBC and provide new ideas for the treatment of TNBC.

Synthesis and biological evaluation of novel aromatic amide derivatives as potential BCR-ABL inhibitors.

BCR-ABL1 kinase is a key driver of the pathophysiology of chronic myeloid leukemia (CML). Current treatments need to broaden the chemical diversity of BCR-ABL1 kinase inhibitors to overcome drug resistance. We designed and synthesized a series of aromatic amide derivatives based on several generations of BCR-ABL1 kinase inhibitors. Biological studies showed that compared with Imatinib, these compounds showed significant proliferation inhibitory activities of HL-60 and K562 in cell activity assay. Compounds 4g and 4j exhibited significant anti-tumor activity against the K562 cells with IC50 values of 6.03 ± 0.49 µM and 5.66 ± 2.06 µM respectively. Compounds 4g and 4j, as potential BCR-ABL1 inhibitors, inhibit the phosphorylation of ABL1 and CRKL in a dose-dependent manner. Therefore, compounds 4g and 4j can be used as a starting point for further optimization.

Oxygen micro-nanobubbles for mitigating eutrophication induced sediment pollution in freshwater bodies.

Sediment hypoxia is a growing problem and has negative ecological impacts on the aquatic ecosystem. Hypoxia can disturb the biodiversity and biogeochemical cycles of both phosphorus (P) and nitrogen (N) in water columns and sediments. Anthropogenic eutrophication and internal nutrient release from lakebed sediment accelerate hypoxia to form a dead zone. Thus, sediment hypoxia mitigation is necessary for ecological restoration and sustainable development. Conventional aeration practices to control sediment hypoxia, are not effective due to high cost, sediment disturbance and less sustainability. Owing to high solubility and stability, micro-nanobubbles (MNBs) offer several advantages over conventional water and wastewater treatment practices. Clay loaded oxygen micro-nanobubbles (OMNBs) can be delivered into deep water sediment by gravity and settling. Nanobubble technology provides a promising route for cost-effective oxygen delivery in large natural water systems. OMNBs also have the immense potential to manipulate biochemical pathways and microbial processes for remediating sediment pollution in natural waters. This review article aims to analyze recent trends employing OMNBs loaded materials to mitigate sediment hypoxia and subsequent pollution. The first part of the review highlights various minerals/materials used for the delivery of OMNBs into benthic sediments of freshwater bodies. Release of OMNBs at hypoxic sediment water interphase (SWI) can provide significant dissolved oxygen (DO) to remediate hypoxia induced sediment pollution Second part of the manuscript unveils the impacts of OMNBs on sediment pollutants (e.g., methylmercury, arsenic, and greenhouse gases) remediation and microbial processes for improved biogeochemical cycles. The review article will facilitate environmental engineers and ecologists to control sediment pollution along with ecological restoration.

Answering medical questions in Chinese using automatically mined knowledge and deep neural networks: an end-to-end solution.

BACKGROUND: Medical information has rapidly increased on the internet and has become one of the main targets of search engine use. However, medical information on the internet is subject to the problems of quality and accessibility, so ordinary users are unable to obtain answers to their medical questions conveniently. As a solution, researchers build medical question answering (QA) systems. However, research on medical QA in the Chinese language lags behind work on English-based systems. This lag is mainly due to the difficulty of constructing a high-quality knowledge base and the underutilization of medical corpora in the Chinese language. RESULTS: This study developed an end-to-end solution to implement a medical QA system for the Chinese language with low cost and time. First, we created a high-quality medical knowledge graph from hospital data (electronic health/medical records) in a nearly automatic manner that trained a supervised model based on data labeled using bootstrapping techniques. Then, we designed a QA system based on a memory-based neural network and attention mechanism. Finally, we trained the system to generate answers from the knowledge base and a QA corpus on the internet. CONCLUSIONS: Bootstrapping and deep neural network techniques can construct a knowledge graph from electronic health/medical records with satisfactory precision and coverage. Our proposed context bridge mechanisms perform training with a variety of language features. Our QA system can achieve state-of-the-art quality in answering medical questions with constrained topics. As we evaluated, complex Chinese language processing techniques, such as segmentation and parsing, were not necessary for practice and complex architectures were not necessary to build the QA system. Lastly, we created an application using our method for internet QA usage.

Hierarchical Core-Shell Co2 N/CoP Embedded in N, P-doped Carbon Nanotubes as Efficient Oxygen Reduction Reaction Catalysts for Zn-air Batteries.

Projecting a cost-effective and highly efficient electrocatalyst for the oxygen reaction reduction (ORR) counts a great deal for Zn-air batteries. Herein, a hierarchical core-shell ORR catalyst (Co2 N/CoP@PNCNTs) is developed by embedding cobalt phosphides and/or cobalt nitrides as the core into N, P-doped carbon nanotubes (PNCNTs) as the shell via one-step carbonization, nitridation, and phosphorization of pyrolyzing Co-MOF precursor. The globally N, P-doped structure of Co2 N/CoP@PNCNTs demonstrates an outstanding electrocatalytic activity in the alkaline solution with the onset and half-wave potentials of 1.07 and 0.85 V respectively. Moreover, a Zn-air battery assembled from Co2 N/CoP@PNCNTs as the air cathode delivers an open circuit potential of 1.49 V, a maximum power density of 151.1 mW cm-2 and a specific capacity of 823.8 mAh kg-1 . It is reflected that Co2 N/CoP@PNCNTs provides a long-term durability with a slight decline of 15 h in the chronoamperometry measurement and an excellent charge-discharge stability with negligible voltage decay for 150 h at 10 mA cm-2 in Zn-air batteries. The results reveal that Co2 N/CoP@PNCNTs has superiority over most Co-Nx -C or Cox P@C catalysts reported so far. The excellent catalytic properties and stability of Co2 N/CoP@PNCNTs derive from synergistic effects between Co2 N/CoP and mesoporous N, P-doped carbon nanotubes.

An alanine to valine mutation of glutamyl-tRNA reductase enhances 5-aminolevulinic acid synthesis in rice.

KEY MESSAGE: An alanine to valine mutation of glutamyl-tRNA reductase's 510th amino acid improves 5-aminolevulinic acid synthesis in rice. 5-aminolevulinic acid (ALA) is the common precursor of all tetrapyrroles and plays an important role in plant growth regulation. ALA is synthesized from glutamate, catalyzed by glutamyl-tRNA synthetase (GluRS), glutamyl-tRNA reductase (GluTR), and glutamate-1-semialdehyde aminotransferase (GSAT). In Arabidopsis, ALA synthesis is the rate-limiting step in tetrapyrrole production via GluTR post-translational regulations. In rice, mutations of GluTR and GSAT homologs are known to confer chlorophyll deficiency phenotypes; however, the enzymatic activity of rice GluRS, GluTR, and GSAT and the post-translational regulation of rice GluTR have not been investigated experimentally. We have demonstrated that a suppressor mutation in rice partially reverts the xantha trait. In the present study, we first determine that the suppressor mutation results from a G → A nucleotide substitution of OsGluTR (and an A → V change of its 510th amino acid). Protein homology modeling and molecular docking show that the OsGluTRA510V mutation increases its substrate binding. We then demonstrate that the OsGluTRA510V mutation increases ALA synthesis in Escherichia coli without affecting its interaction with OsFLU. We further explore homologous genes encoding GluTR across 193 plant species and find that the amino acid (A) is 100% conserved at the position, suggesting its critical role in GluTR. Thus, we demonstrate that the gain-of-function OsGluTRA510V mutation underlies suppression of the xantha trait, experimentally proves the enzymatic activity of rice GluRS, GluTR, and GSAT in ALA synthesis, and uncovers conservation of the alanine corresponding to the 510th amino acid of OsGluTR across plant species.

Training Deep Convolutional Spiking Neural Networks With Spike Probabilistic Global Pooling.

Recent work on spiking neural networks (SNNs) has focused on achieving deep architectures. They commonly use backpropagation (BP) to train SNNs directly, which allows SNNs to go deeper and achieve higher performance. However, the BP training procedure is computing intensive and complicated by many trainable parameters. Inspired by global pooling in convolutional neural networks (CNNs), we present the spike probabilistic global pooling (SPGP) method based on a probability function for training deep convolutional SNNs. It aims to remove the difficulty of too many trainable parameters brought by multiple layers in the training process, which can reduce the risk of overfitting and get better performance for deep SNNs (DSNNs). We use the discrete leaky-integrate-fire model and the spatiotemporal BP algorithm for training DSNNs directly. As a result, our model trained with the SPGP method achieves competitive performance compared to the existing DSNNs on image and neuromorphic data sets while minimizing the number of trainable parameters. In addition, the proposed SPGP method shows its effectiveness in performance improvement, convergence, and generalization ability.

Gab1 Overexpression Attenuates Susceptibility to Ventricular Arrhythmias in Pressure Overloaded Heart Failure Mouse Hearts.

PURPOSE: Grb2 associated binding protein 1 (Gab1) is an adaptor protein that is important for intracellular signal transduction which involved in several pathological process. However, the role of Gab1 in pressure overload-induced ventricular arrhythmias (VAs) remain poorly understood. In the current study, we aimed to test the role of Gab1 in VA susceptibility induced by pressure overload. METHODS: We overexpressed Gab1 in the hearts using an adeno-associated virus 9 (AAV9) system through tail vein injection. Aortic banding (AB) surgery was performed in C57BL6/J mice to induce heart failure (HF). Four weeks following AB, histology, echocardiography, and biochemical analysis were conducted to investigate cardiac structural remodeling and electrophysiological studies were performed to check the electrical remodeling. Western blot analysis was used to explore the underlying mechanisms. RESULTS: The mRNA and protein expression were downregulated in AB hearts compared to sham hearts. Gab1 overexpression significantly reversed AB-induced cardiac structural remodeling including ameliorated AB-induced cardiac dysfunction, cardiac fibrosis, and inflammatory response. Moreover, Gab1 overexpression also markedly alleviated AB-induced electrical remodeling including ion channel alterations and VA susceptibility. Mechanistically, we found that TLR4/MyD88/NF-κB contributes to the cardio protective effect of Gab1 overexpression on AB-induced VAs. CONCLUSIONS: Our study manifested that Gab1 may serve as a promising anti-arrhythmic target via inhibiting TLR4/MyD88/NF-κB signaling pathway induced by AB.

Microstructural profiles of thalamus and thalamocortical connectivity in patients with disorder of consciousness.

Thalamus and thalamocortical connectivity are crucial for consciousness; however, their microstructural changes in patients with a disorder of consciousness (DOC) have not yet been thoroughly characterized. In the present study, we applied the novel fixel-based analysis to comprehensively investigate the thalamus-related microstructural abnormalities in 10 patients with DOC using 7-T diffusion-weighted imaging data. We found that compared to healthy controls, patients with DOC showed reduced fiber density (FD) and fiber density and cross-section (FDC) in the mediodorsal, anterior, and ventral anterior thalamic nuclei, while fiber-bundle cross-section (FC) was not significantly altered in the thalamus. Impaired thalamocortical connectivity in the DOC cohort was mainly connected to the middle frontal gyrus, anterior cingulate gyrus, fusiform gyrus, and sensorimotor cortices, including the precentral gyrus and postcentral gyrus, with predominant microstructural abnormalities in FD and FDC. Correlation analysis showed that FC of the right mediodorsal thalamus was negatively correlated with the level of consciousness. Our results suggest that microstructural abnormalities of thalamus and thalamocortical connectivity in DOC were mainly attributed to axonal injury. In particular, the microstructural integrity of the thalamus is a vital factor in consciousness generation.

Single nucleus transcriptomics data integration recapitulates the major cell types in human liver.

AIM: The aim of this study was to explore the benefits of data integration from different platforms for single nucleus transcriptomics profiling to characterize cell populations in human liver. METHODS: We generated single-nucleus RNA sequencing data from Chromium 10X Genomics and Drop-seq for a human liver sample. We utilized state of the art bioinformatics tools to undertake a rigorous quality control and to integrate the data into a common space summarizing the gene expression variation from the respective platforms, while accounting for known and unknown confounding factors. RESULTS: Analysis of single nuclei transcriptomes from both 10X and Drop-seq allowed identification of the major liver cell types, while the integrated set obtained enough statistical power to separate a small population of inactive hepatic stellate cells that was not characterized in either of the platforms. CONCLUSIONS: Integration of droplet-based single nucleus transcriptomics data enabled identification of a small cluster of inactive hepatic stellate cells that highlights the potential of our approach. We suggest single-nucleus RNA sequencing integrative approaches could be utilized to design larger and cost-effective studies.

A toolbox for brain network construction and classification (BrainNetClass).

Brain functional network has been increasingly used in understanding brain functions and diseases. While many network construction methods have been proposed, the progress in the field still largely relies on static pairwise Pearson's correlation-based functional network and group-level comparisons. We introduce a "Brain Network Construction and Classification (BrainNetClass)" toolbox to promote more advanced brain network construction methods to the filed, including some state-of-the-art methods that were recently developed to capture complex and high-order interactions among brain regions. The toolbox also integrates a well-accepted and rigorous classification framework based on brain connectome features toward individualized disease diagnosis in a hope that the advanced network modeling could boost the subsequent classification. BrainNetClass is a MATLAB-based, open-source, cross-platform toolbox with both graphical user-friendly interfaces and a command line mode targeting cognitive neuroscientists and clinicians for promoting reliability, reproducibility, and interpretability of connectome-based, computer-aided diagnosis. It generates abundant classification-related results from network presentations to contributing features that have been largely ignored by most studies to grant users the ability of evaluating the disease diagnostic model and its robustness and generalizability. We demonstrate the effectiveness of the toolbox on real resting-state functional MRI datasets. BrainNetClass (v1.0) is available at https://github.com/zzstefan/BrainNetClass.

Studies of liver tissue identify functional gene regulatory elements associated to gene expression, type 2 diabetes, and other metabolic diseases.

BACKGROUND: Genome-wide association studies (GWAS) of diseases and traits have found associations to gene regions but not the functional SNP or the gene mediating the effect. Difference in gene regulatory signals can be detected using chromatin immunoprecipitation and next-gen sequencing (ChIP-seq) of transcription factors or histone modifications by aligning reads to known polymorphisms in individual genomes. The aim was to identify such regulatory elements in the human liver to understand the genetics behind type 2 diabetes and metabolic diseases. METHODS: The genome of liver tissue was sequenced using 10X Genomics technology to call polymorphic positions. Using ChIP-seq for two histone modifications, H3K4me3 and H3K27ac, and the transcription factor CTCF, and our established bioinformatics pipeline, we detected sites with significant difference in signal between the alleles. RESULTS: We detected 2329 allele-specific SNPs (AS-SNPs) including 25 associated to GWAS SNPs linked to liver biology, e.g., 4 AS-SNPs at two type 2 diabetes loci. Two hundred ninety-two AS-SNPs were associated to liver gene expression in GTEx, and 134 AS-SNPs were located on 166 candidate functional motifs and most of them in EGR1-binding sites. CONCLUSIONS: This study provides a valuable collection of candidate liver regulatory elements for further experimental validation.

Binless Kernel Machine: Modeling Spike Train Transformation for Cognitive Neural Prostheses.

Modeling spike train transformation among brain regions helps in designing a cognitive neural prosthesis that restores lost cognitive functions. Various methods analyze the nonlinear dynamic spike train transformation between two cortical areas with low computational eficiency. The application of a real-time neural prosthesis requires computational eficiency, performance stability, and better interpretation of the neural firing patterns that modulate target spike generation. We propose the binless kernel machine in the point-process framework to describe nonlinear dynamic spike train transformations. Our approach embeds the binless kernel to eficiently capture the feedforward dynamics of spike trains and maps the input spike timings into reproducing kernel Hilbert space (RKHS). An inhomogeneous Bernoulli process is designed to combine with a kernel logistic regression that operates on the binless kernel to generate an output spike train as a point process. Weights of the proposed model are estimated by maximizing the log likelihood of output spike trains in RKHS, which allows a global-optimal solution. To reduce computational complexity, we design a streaming-based clustering algorithm to extract typical and important spike train features. The cluster centers and their weights enable the visualization of the important input spike train patterns that motivate or inhibit output neuron firing. We test the proposed model on both synthetic data and real spike train data recorded from the dorsal premotor cortex and the primary motor cortex of a monkey performing a center-out task. Performances are evaluated by discrete-time rescaling Kolmogorov-Smirnov tests. Our model outperforms the existing methods with higher stability regardless of weight initialization and demonstrates higher eficiency in analyzing neural patterns from spike timing with less historical input (50%). Meanwhile, the typical spike train patterns selected according to weights are validated to encode output spike from the spike train of single-input neuron and the interaction of two input neurons.