Learning spiking neuronal networks with artificial neural networks: neural oscillations.

First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be hard to build and expensive to simulate for complex living systems. On the other hand, modern data-driven methods thrive at modeling many types of high-dimensional and noisy data. Still, the training and interpretation of these data-driven models remain challenging. Here, we combine the two types of methods to model stochastic neuronal network oscillations. Specifically, we develop a class of artificial neural networks to provide faithful surrogates to the high-dimensional, nonlinear oscillatory dynamics produced by a spiking neuronal network model. Furthermore, when the training data set is enlarged within a range of parameter choices, the artificial neural networks become generalizable to these parameters, covering cases in distinctly different dynamical regimes. In all, our work opens a new avenue for modeling complex neuronal network dynamics with artificial neural networks.

Ferroelectric compute-in-memory annealer for combinatorial optimization problems.

Computationally hard combinatorial optimization problems (COPs) are ubiquitous in many applications. Various digital annealers, dynamical Ising machines, and quantum/photonic systems have been developed for solving COPs, but they still suffer from the memory access issue, scalability, restricted applicability to certain types of COPs, and VLSI-incompatibility, respectively. Here we report a ferroelectric field effect transistor (FeFET) based compute-in-memory (CiM) annealer for solving larger-scale COPs efficiently. Our CiM annealer converts COPs into quadratic unconstrained binary optimization (QUBO) formulations, and uniquely accelerates in-situ the core vector-matrix-vector (VMV) multiplication operations of QUBO formulations in a single step. Specifically, the three-terminal FeFET structure allows for lossless compression of the stored QUBO matrix, achieving a remarkably 75% chip size saving when solving Max-Cut problems. A multi-epoch simulated annealing (MESA) algorithm is proposed for efficient annealing, achieving up to 27% better solution and ~ 2X speedup than conventional simulated annealing. Experimental validation is performed using the first integrated FeFET chip on 28nm HKMG CMOS technology, indicating great promise of FeFET CiM array in solving general COPs.

A chromosome-level genome assembly for the Silkie chicken resolves complete sequences for key chicken metabolic, reproductive, and immunity genes.

A set of high-quality pan-genomes would help identify important genes that are still hidden/incomplete in bird reference genomes. In an attempt to address these issues, we have assembled a de novo chromosome-level reference genome of the Silkie (Gallus gallus domesticus), which is an important avian model for unique traits, like fibromelanosis, with unclear genetic foundation. This Silkie genome includes the complete genomic sequences of well-known, but unresolved, evolutionarily, endocrinologically, and immunologically important genes, including leptin, ovocleidin-17, and tumor-necrosis factor-α. The gap-less and manually annotated MHC (major histocompatibility complex) region possesses 38 recently identified genes, with differentially regulated genes recovered in response to pathogen challenges. We also provide whole-genome methylation and genetic variation maps, and resolve a complex genetic region that may contribute to fibromelanosis in these animals. Finally, we experimentally show leptin binding to the identified leptin receptor in chicken, confirming an active leptin ligand-receptor system. The Silkie genome assembly not only provides a rich data resource for avian genome studies, but also lays a foundation for further functional validation of resolved genes.

Selection on the promoter regions plays an important role in complex traits during duck domestication.

BACKGROUND: Identifying the key factors that underlie complex traits during domestication is a great challenge for evolutionary and biological studies. In addition to the protein-coding region differences caused by variants, a large number of variants are located in the noncoding regions containing multiple types of regulatory elements. However, the roles of accumulated variants in gene regulatory elements during duck domestication and economic trait improvement are poorly understood. RESULTS: We constructed a genomics, transcriptomics, and epigenomics map of the duck genome and assessed the evolutionary forces that have been in play across the whole genome during domestication. In total, 304 (42.94%) gene promoters have been specifically selected in Pekin duck among all selected genes. Joint multi-omics analysis reveals that 218 genes (72.01%) with selected promoters are located in open and active chromatin, and 267 genes (87.83%) with selected promoters were highly and differentially expressed in domestic trait-related tissues. One important candidate gene ELOVL3, with a strong signature of differentiation on the core promoter region, is known to regulate fatty acid elongation. Functional experiments showed that the nearly fixed variants in the top selected ELOVL3 promoter in Pekin duck decreased binding ability with HLF and increased gene expression, with the overexpression of ELOVL3 able to increase lipid deposition and unsaturated fatty acid enrichment. CONCLUSIONS: This study presents genome resequencing, RNA-Seq, Hi-C, and ATAC-Seq data of mallard and Pekin duck, showing that selection of the gene promoter region plays an important role in gene expression and phenotypic changes during domestication and highlights that the variants of the ELOVL3 promoter may have multiple effects on fat and long-chain fatty acid content in ducks.

Stress relief as a natural resilience mechanism against depression-like behaviors.

Relief, the appetitive state after the termination of aversive stimuli, is evolutionarily conserved. Understanding the behavioral role of this well-conserved phenomenon and its underlying neurobiological mechanisms are open and important questions. Here, we discover that the magnitude of relief from physical stress strongly correlates with individual resilience to depression-like behaviors in chronic stressed mice. Notably, blocking stress relief causes vulnerability to depression-like behaviors, whereas natural rewards supplied shortly after stress promotes resilience. Stress relief is mediated by reward-related mesolimbic dopamine neurons, which show minute-long, persistent activation after stress termination. Circuitry-wise, activation or inhibition of circuits downstream of the ventral tegmental area during the transient relief period bi-directionally regulates depression resilience. These results reveal an evolutionary function of stress relief in depression resilience and identify the neural substrate mediating this effect. Importantly, our data suggest a behavioral strategy of augmenting positive valence of stress relief with natural rewards to prevent depression.

[Effects of blistering cupping combined with thunder-fire moxibustion on the efficacy and airway remodeling of cold-wheezing syndrome in bronchial asthma].

OBJECTIVE: To investigate the clinical efficacy of the combined application of blistering cupping with thunder-fire moxibustion in treating bronchial asthma of cold-wheezing syndrome, and its influences on airway remodeling, inflammatory factors, lung function, and quality of life on the base of conventional western medicine treatment. METHODS: A total of 76 patients with bronchial asthma of cold-wheezing syndrome were randomly divided into an observation group and a control group, 38 cases in each group. In the control group, the basic treatment was used, i.e. budesonide formoterol powder inhalation. In the observation group, on the basis of the treatment as the control group, blistering cupping combined with thunder-fire moxibustion was supplemented, Dazhui (GV 14), Danzhong (CV 17) and bilateral Feishu (BL 13), Gaohuang (BL 43), and Zhongfu (LU 1) were selected; blistering cupping was administered once a day and thunder-fire moxibustion was given twice a day. One course of treatment was composed of 7 days in both groups, and 2 courses of treatment were required. Before and after treatment, the airway remodeling indexes (matrix metalloproteinase-9 [MMP-9], tissue inhibitor of matrix metalloproteinase-1 [TIMP-1], and transforming growth factor-ß1 [TGF-ß1]) and inflammatory indexes (interleukin [IL] -1ß、IL-25) were detected by using radioimmunoassay in the patients of the two groups. The lung function, traditional Chinese medicine symptom score, and asthma quality of life questionnaire (AQLQ) score were observed in the patients of the two groups. RESULTS: After treatment, the serum levels of MMP-9, TIMP-1, TGF-ß1, IL-1ß, IL-25, peak expiratory flow (PEFR), traditional Chinese medicine symptom scores, and AQLQ scores were decreased compared with those before treatment in the patients of the two groups (P<0.05), and the results in the observation group were lower than those in the control group (P<0.05). After treatment, the first second forced expiratory volume (FEV1) and peak expiratory flow rate (PEF) were increased compared with those before treatment in the two groups (P<0.05), and the results in the observation group were higher than those in the control group (P<0.05). CONCLUSION: On the basis of the conventional western medicine treatment, the combination of blistering cupping with thunder-fire moxibustion can effectively ameliorate the clinical symptoms of patients, reduce inflammatory levels, inhibit airway remodeling and improve the lung function and quality of life in the patients with bronchial asthma.

Fe1-xNix(PO3)2/Ni2P Heterostructure for Boosting Alkaline Oxygen Evolution Reaction in Fresh Water and Real Seawater at High Current Density.

Oxygen evolution reaction (OER) is a limiting reaction for highly efficient water electrolysis. Thus, the development of cost-effective and highly efficient OER catalysts is the key to large-scale water electrolysis for hydrogen production. Herein, by using an interfacial engineering strategy, a unique nanoflower-like Fe1-xNix(PO3)2/Ni2P/NF heterostructure with abundant heterogeneous interfaces is successfully fabricated. The catalyst exhibits excellent OER catalytic activity in alkaline fresh water and alkaline natural seawater at high current densities, which only, respectively, requires overpotentials of 318 and 367 mV to drive 1000 mA cm-2 in fresh water and natural seawater both containing 1 M KOH. Furthermore, Fe1-xNix(PO3)2/Ni2P/NF demonstrates excellent durability, which can basically remain stable for 80 h during the electrocatalytic OER processes, respectively, in alkaline fresh water and natural seawater. This work provides a new construction strategy for designing highly efficient electrocatalysts for OER at high current densities both in alkaline fresh water and in natural seawater.

Comprehensive analysis of mitophagy in HPV-related head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a common tumour type in otorhinolaryngology, and its occurrence is related to long-term exposure to tobacco and alcohol. Recently, HPV infection has become an increasingly important contributor to HNSCC, and HPV-associated HNSCC has a different clinical course and better prognosis than non-HPV-associated HNSCC. However, the exact molecular mechanism of HNSCC is unclear. Here, we obtained data from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) to analyse the mitophagy process and related influencing factors of HPV-associated HNSCC via the integration of bioinformatics analysis and experimental validation. We found that in HPV-associated HNSCC, process of mitophagy affects tumour development, immune cell infiltration and prognosis. In the mitophagy process of HPV-related HNSCC: NOS2, IL17REL, TMSB15A, TUBB4A and other hub genes showed significantly higher expression levels than in non-HPV-related HNSCC. Furthermore, this was also confirmed by quantitative real-time PCR (qRT‒PCR), which was used to detect the expression of differentially expressed genes in HNSCC tissues. Furthermore, we found that the unique immunological characteristics by expressing CD8+ T cell in a high level in HPV-related HNSCC, and the scores obtained from the score model affected the prognosis of patients. In conclusion, our study revealed the unique biomolecular signature of mitophagy in HPV-associated HNSCC, which may contribute to the development of precise treatment regimens for HPV-associated HNSCC patients.

Partial Unbalanced Feature Transport for Cross-Modality Cardiac Image Segmentation.

Deep learning based approaches have achieved great success on the automatic cardiac image segmentation task. However, the achieved segmentation performance remains limited due to the significant difference across image domains, which is referred to as domain shift. Unsupervised domain adaptation (UDA), as a promising method to mitigate this effect, trains a model to reduce the domain discrepancy between the source (with labels) and the target (without labels) domains in a common latent feature space. In this work, we propose a novel framework, named Partial Unbalanced Feature Transport (PUFT), for cross-modality cardiac image segmentation. Our model facilities UDA leveraging two Continuous Normalizing Flow-based Variational Auto-Encoders (CNF-VAE) and a Partial Unbalanced Optimal Transport (PUOT) strategy. Instead of directly using VAE for UDA in previous works where the latent features from both domains are approximated by a parameterized variational form, we introduce continuous normalizing flows (CNF) into the extended VAE to estimate the probabilistic posterior and alleviate the inference bias. To remove the remaining domain shift, PUOT exploits the label information in the source domain to constrain the OT plan and extracts structural information of both domains, which are often neglected in classical OT for UDA. We evaluate our proposed model on two cardiac datasets and an abdominal dataset. The experimental results demonstrate that PUFT achieves superior performance compared with state-of-the-art segmentation methods for most structural segmentation.

Local-to-global spatial learning for whole-slide image representation and classification.

Whole-slide image (WSI) provides an important reference for clinical diagnosis. Classification with only WSI-level labels can be recognized for multi-instance learning (MIL) tasks. However, most existing MIL-based WSI classification methods have moderate performance on correlation mining between instances limited by their instance- level classification strategy. Herein, we propose a novel local-to-global spatial learning method to mine global position and local morphological information by redefining the MIL-based WSI classification strategy, better at learning WSI-level representation, called Global-Local Attentional Multi-Instance Learning (GLAMIL). GLAMIL can focus on regional relationships rather than single instances. It first learns relationships between patches in the local pool to aggregate region correlation (tissue types of a WSI). These correlations then can be further mined to fulfill WSI-level representation, where position correlation between different regions can be modeled. Furthermore, Transformer layers are employed to model global and local spatial information rather than being simply used as feature extractors, and the corresponding structure improvements are present. In addition, we evaluate GIAMIL on three benchmarks considering various challenging factors and achieve satisfactory results. GLAMIL outperforms state-of-the-art methods and baselines by about 1 % and 10 %, respectively.

Multi-band oscillations emerge from a simple spiking network.

In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), and gamma (30-120 Hz) oscillations, among others. These rhythms are believed to underlie information processing and cognitive functions and have been subjected to intense experimental and theoretical scrutiny. Computational modeling has provided a framework for the emergence of network-level oscillatory behavior from the interaction of spiking neurons. However, due to the strong nonlinear interactions between highly recurrent spiking populations, the interplay between cortical rhythms in multiple frequency bands has rarely been theoretically investigated. Many studies invoke multiple physiological timescales (e.g., various ion channels or multiple types of inhibitory neurons) or oscillatory inputs to produce rhythms in multi-bands. Here, we demonstrate the emergence of multi-band oscillations in a simple network consisting of one excitatory and one inhibitory neuronal population driven by constant input. First, we construct a data-driven, Poincaré section theory for robust numerical observations of single-frequency oscillations bifurcating into multiple bands. Then, we develop model reductions of the stochastic, nonlinear, high-dimensional neuronal network to capture the appearance of multi-band dynamics and the underlying bifurcations theoretically. Furthermore, when viewed within the reduced state space, our analysis reveals conserved geometrical features of the bifurcations on low-dimensional dynamical manifolds. These results suggest a simple geometric mechanism behind the emergence of multi-band oscillations without appealing to oscillatory inputs or multiple synaptic or neuronal timescales. Thus, our work points to unexplored regimes of stochastic competition between excitation and inhibition behind the generation of dynamic, patterned neuronal activities.

AIGAN: Attention-encoding Integrated Generative Adversarial Network for the reconstruction of low-dose CT and low-dose PET images.

X-ray computed tomography (CT) and positron emission tomography (PET) are two of the most commonly used medical imaging technologies for the evaluation of many diseases. Full-dose imaging for CT and PET ensures the image quality but usually raises concerns about the potential health risks of radiation exposure. The contradiction between reducing the radiation exposure and remaining diagnostic performance can be addressed effectively by reconstructing the low-dose CT (L-CT) and low-dose PET (L-PET) images to the same high-quality ones as full-dose (F-CT and F-PET). In this paper, we propose an Attention-encoding Integrated Generative Adversarial Network (AIGAN) to achieve efficient and universal full-dose reconstruction for L-CT and L-PET images. AIGAN consists of three modules: the cascade generator, the dual-scale discriminator and the multi-scale spatial fusion module (MSFM). A sequence of consecutive L-CT (L-PET) slices is first fed into the cascade generator that integrates with a generation-encoding-generation pipeline. The generator plays the zero-sum game with the dual-scale discriminator for two stages: the coarse and fine stages. In both stages, the generator generates the estimated F-CT (F-PET) images as like the original F-CT (F-PET) images as possible. After the fine stage, the estimated fine full-dose images are then fed into the MSFM, which fully explores the inter- and intra-slice structural information, to output the final generated full-dose images. Experimental results show that the proposed AIGAN achieves the state-of-the-art performances on commonly used metrics and satisfies the reconstruction needs for clinical standards.

Exploring the effect of the microbiota on the production of duck striped eggs.

The microbiota has received plenty of attention in recent years due to its influence on host health and productivity. The striped eggs have reduced hatching performance and resulted in economic loss. The reasons are still unknown. Microbiota is one of the potentially important factors contributing to striped egg formation. This study investigates the relationship between the microbiota and striped eggs. The litter samples, feed samples, and cloacal swab samples of female ducks that produce striped eggs and normal eggs were performed for microbial diversity and composition using 16S rRNA sequencing. The results showed that there was no significant difference between feed microbiota and cloacal swab microbiota by alpha diversity, whereas, the number of microorganisms in the litter samples of female ducks that produced striped eggs was less than those of female ducks with normal eggs. There were compositional differences in litter microbiota of female ducks between the striped egg and the normal eggs. Among them, the abundance of Staphylococcus, Corynebacterium, and Brevibacterium in the litter of female ducks that produced striped eggs was significantly higher than that produced normal eggs. And these differential bacteria maybe affect the health of female ducks and cause abnormalities in the formation process of duck eggs. Therefore, the reduction of harmful bacteria may protect the reproductive health of female ducks and decrease the proportion of striped eggs. It provides an important reference to explore why female ducks produce striped eggs.

Genome-wide association study identified the candidate genes associated with angel wing trait in Pekin duck.

Angel wing is a developmental wing deformity that can influence breeding and reproduction in the commercial duck industry. The nutrition foundation of angel wing trait was initially explored, but the genetic basic remains poorly understood. In this study, we identified candidate genes and single-nucleotide polymorphisms (SNPs) associated with angel wing trait in Pekin ducks using a genome-wide association study (GWAS) and selective sweep analysis. The GWAS results showed that nine SNPs across five chromosomes were significantly correlated with the angel wing trait. In total, 468 selection signals were shown between the angel wing ducks and normal ducks, and these signals harbored 154 genes, which were enriched in the nervous system and metabolism. This study provides the new insights into the genetic factors that may influence duck angel wing.

Study on the extraction of polysaccharides from Dendrobium officinale and its improvement effect on acute lung injury in mice / 中国药房

OBJECTIVE To optimize the extraction process of polysaccharides from Dendrobium officinale， and preliminarily study its effect on acute lung injury （ALI） in mice. METHODS Using D. officinale as raw material， the polysaccharides were extracted from D. officinale by ultrasonic-assisted hot water immersion. Using the extraction rate of D. officinale polysaccharides as response value， the single-factor experiments and Box-Behnken response surface method were used to optimize the ratio of material to liquid， extraction time and extraction temperature. ALI mice were induced by lipopolysaccharide. Using prednisone acetate （5 mg/kg） as the positive control， the effects on the mass ratio of wet and dry lung and pathological changes of lung tissue （HE staining and Masson staining） of low-dose， medium-dose and high-dose D. officinale polysaccharides （50，100，200 mg/kg） were investigated. RESULTS The optimal extraction technology of D. officinale polysaccharides was as follows： the ratio of material to liquid was 1∶25 （g/mL）， the extracting time was 1 h， and the extracting temperature was 58 ℃ . Under these conditions， the average extraction rate of D. officinale polysaccharides was 37.75% （RSD＝1.12%，n＝3）， the relative error of which with predicted value （38.63%） was 2.28%. Compared with the model group， the ratios of wet and dry lung in the positive control group and D. officinale polysaccharides groups were all decreased significantly （P＜0.05 or P＜0.01）， and the pathological changes in lung tissue （severe destruction of alveolar structure， significant widening of alveolar septa， extensive infiltration of inflammatory cells and proliferation of fibroblasts） were alleviated to varying degrees. CONCLUSIONS The optimal extraction process of D. officinale polysaccharides is feasible； the obtained polysaccharide extract has a certain improvement effect on ALI in mice.

Analysis of biliary microbiota in experimental pigs before and after enteral extended biliary stents implantation / 中华消化内镜杂志

Objective:To compare the changes of biliary microbiota after enteral extended biliary stents (EEBS) implantation with that of conventional plastic stents in animal experiment, and to preliminarily investigate its possible mechanism in preventing stents occlusion.Methods:A total of 12 healthy Bama minipigs were randomly assigned to the conventional plastic stent group ( n=6) and the EEBS group ( n=6) using simple random method. The bile samples of all pigs were collected before stents implantation and 4 weeks after stents placement. The biliary microbiota composition and diversity before and after different stents implantation were analyzed by 16S rRNA gene sequencing and compared. Results:No complications including acute cholangitis, perforation, bleeding, or death occurred in 12 pigs. Eight days after stents implantation, stents were out of bile duct in all pigs under endoscopy, while the bile samples were collected again for analysis. The main composition of biliary microbiota at the phylum level were Proteobacteria, Firmicutes and Bacteroidota. Alpha-diversities revealed the Shannon ( P=0.004) and Simpson index ( P=0.008) significantly decreased in the conventional stent group after stents placement, and Bata diversity analysis also showed a significant difference in microbial composition (Anosim: R=0.514 8, P=0.011). There was no significant difference in Observed species index ( P=0.095), Chao1 index ( P=0.136), Shannon index ( P=0.353), Simpson index ( P=0.227) or Bata diversity (Anosim: R=0.059 3, P=0.187) in the EEBS group before and after stents placement. LEfSe algorithm indicated Bacteroides_ fragilis and Proteobacteria- Gammaproteobacteria- Enterobacterales- Enterobacteriaceae- scherichia_ Shigella- Escherichia_ coli significantly increased in the conventional stent group, and Desulfobacterota- Desulfovibrionia- Desulfovibrionales- Desulfovibrionaceae- Bilophila significantly increased in the EEBS group after stents placement. Conclusion:The biliary microbiota change slightly after EEBS implantation in the short-term, and EEBS may prevent duodenobiliary reflux by prolonging the reflux path.

Relationship between smoking abstinence self-efficacy， smoking rationalization belief and willingness to quit smoking—a questionnaire survey of 336 male smokers in Shanghai / 上海预防医学

ObjectiveTo explore the influencing factors of willingness to quit smoking in smokers， and to provide reference for further smoking cessation intervention. MethodsThrough purposive sampling， smokers were recruited from 4 residential communities and 3 companies in Shanghai for an online questionnaire survey. The survey included general demographic characteristics， willingness to quit smoking， smoking condition， tobacco addiction， awareness of influence of smoking， smoking abstinence self-efficacy， and smoking rationalization belief. T-test， χ2 test and multiple logistic regression were used to analyze the data. ResultsA total of 336 valid questionnaires were collected. The average age of the smokers was （37.1±10.2） years， and most of their education level was college or above （58.3%）. The daily number of cigarette use was （11.46±7.22） and most of smokers were classified as low nicotine dependence （58.3%）. Today 248 smokers planned to quit smoking in the next six months. Compared with smokers with low smoking abstinence self-efficacy， smokers with high self-efficacy were more likely to quit smoking （OR=2.406，95%CI： 1.357‒4.267）； Smokers with low smoking rationalization belief were more likely to quit smoking than those with high rationalization belief （OR=2.112， 95%CI： 1.167‒3.821）. ConclusionSmoking abstinence self-efficacy has a positive impact on willingness to quit smoking， while smoking rationalization belief has a negative impact on the willingness to quit smoking. Efforts to improve smoking abstinence self-efficacy and dispel smoking rationalization beliefs of smokers should be made to promote the intention to quit among smokers.

Identification of an LDLR variant in a Chinese familial hypercholesterolemia and its relation to ROS/NLRP3-Mediated pyroptosis in hepatic cells / 老年心脏病学杂志（英文版）

BACKGROUND@#Familial hypercholesterolemia (FH) is a common autosomal dominant hereditary disease. Its early diagnosis and intervention significantly improve the patient's quality of life. However, there are few types of research on the FH pathogenic genes in China.@*METHODS@#In this study, we recruited a family diagnosed with FH and used whole exome sequencing (WES) to analyze the proband variants. Intracellular cholesterol level, reactive oxygen species (ROS) level, and the expression of pyroptosis-related genes were detected after overexpression of wild-type or variant LDLR in L02 cells.@*RESULTS@#A heterozygous missense variant predicted to be deleterious to LDLR (c.1879G > A, p.Ala627Thr) was identified in the proband. Mechanistically, intracellular cholesterol level, ROS level, and the expression of pyroptosis-related genes, nucleotide-binding oligomerization domain-like receptor family protein 3 (NLRP3) inflammasome and components (caspase 1, apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) and NLRP3), gasdermin D (GSDMD), interleukin (IL) -18, IL-1β was elevated in the variant LDLR group, which was attenuated by inhibition of ROS.@*CONCLUSIONS@#FH is associated with a variant (c.1879G>A, p.Ala627Thr) in the LDLR gene. Regarding the mechanism, the ROS/NLRP3-mediated pyroptosis in hepatic cells may contribute to the pathogenesis of the LDLR variant.

Altered nonlinear Granger causality interactions in the large-scale brain networks of patients with schizophrenia.

Objective.It has been demonstrated that schizophrenia (SZ) is characterized by functional dysconnectivity involving extensive brain networks. However, the majority of previous studies utilizing resting-state functional magnetic resonance imaging (fMRI) to infer abnormal functional connectivity (FC) in patients with SZ have focused on the linear correlation that one brain region may influence another, ignoring the inherently nonlinear properties of fMRI signals.Approach. In this paper, we present a neural Granger causality (NGC) technique for examining the changes in SZ's nonlinear causal couplings. We develop static and dynamic NGC-based analyses of large-scale brain networks at several network levels, estimating complicated temporal and causal relationships in SZ patients.Main results. We find that the NGC-based FC matrices can detect large and significant differences between the SZ and healthy control groups at both the regional and subnetwork scales. These differences are persistent and significantly overlapped at various network sparsities regardless of whether the brain networks were built using static or dynamic techniques. In addition, compared to controls, patients with SZ exhibited extensive NGC confusion patterns throughout the entire brain.Significance. These findings imply that the NGC-based FCs may be a useful method for quantifying the abnormalities in the causal influences of patients with SZ, hence shedding fresh light on the pathophysiology of this disorder.

Chromosome-level genome assembly of the Muscovy duck provides insight into fatty liver susceptibility.

The Muscovy duck (Cairina moschata) is an economically important poultry species, which is susceptible to fatty liver. Thus, the Muscovy duck may serve as an excellent candidate animal model of non-alcoholic fatty liver disease. However, the mechanisms underlying fatty liver development in this species are poorly understood. In this study, we report a chromosome-level genome assembly of the Muscovy duck, with a contig N50 of 11.8 Mb and scaffold N50 of 83.16 Mb. The susceptibility of Muscovy duck to fatty liver was mainly attributed to weak lipid catabolism capabilities (fatty acid ß-oxidation and lipolysis). Furthermore, conserved noncoding elements (CNEs) showing accelerated evolution contributed to fatty liver formation by down-regulating the expression of genes involved in hepatic lipid catabolism. We propose that the susceptibility of Muscovy duck to fatty liver is an evolutionary by-product. In conclusion, this study revealed the potential mechanisms underlying the susceptibility of Muscovy duck to fatty liver.