Dissipation-Induced Extended-Localized Transition.

A mobility edge (ME), representing the critical energy that distinguishes between extended and localized states, is a key concept in understanding the transition between extended (metallic) and localized (insulating) states in disordered and quasiperiodic systems. Here we explore the impact of dissipation on a quasiperiodic system featuring MEs by calculating steady-state density matrix and analyzing quench dynamics with sudden introduction of dissipation. We demonstrate that dissipation can lead the system into specific states predominantly characterized by either extended or localized states, irrespective of the initial state. Our results establish the use of dissipation as a new avenue for inducing transitions between extended and localized states and for manipulating dynamic behaviors of particles.

Evaluation of plasma-derived extracellular vesicles miRNAs and their connection with hippocampal mRNAs in alcohol use disorder.

Alcohol use disorder (AUD) is a common mental illness with high morbidity and disability. The discovery of laboratory biomarkers has progressed slowly, resulting in suboptimal diagnosis and treatment of AUD. This study aimed to identify promising biomarkers, as well as the potential miRNA-mRNA networks associated with AUD pathogenesis. RNA sequencing was performed on plasma-derived small extracellular vesicles (sEVs) from AUD patients and healthy controls (HCs) to harvest miRNAs expression profiles. Machine learning (ML) models were built to screen characteristic miRNAs, whose target mRNAs were analyzed using TargetScan, miRanda and miRDB databases. Gene Expression Omnibus (GEO) datasets (GSE181804 and GSE180722) providing postmortem hippocampal gene expression profiles of AUD subjects were mined. A total of 247 differentially expressed (DE) plasma-derived sEVs miRNAs and 122 DE hippocampal mRNAs were obtained. Then, 22 overlapping sEVs miRNAs with high importance scores were gained by intersecting 5 ML models. As a result, we established a putative sEVs miRNA-hippocampal mRNA network that can effectively distinguish AUD patients from HCs. In conclusion, we proposed 5 AUD-representative sEVs miRNAs (hsa-miR-144-5p, hsa-miR-182-5p, hsa-miR-142-5p, hsa-miR-7-5p, and hsa-miR-15b-5p) that may participate in the pathogenesis of AUD by modulating downstream target hippocampal genes. These findings may provide novel insights into the diagnosis and treatment of AUD.

CRISPR/Cas13a-based supersensitive circulating tumor DNA assay for detecting EGFR mutations in plasma.

Despite recent technological advancements in cell tumor DNA (ctDNA) mutation detection, challenges persist in identifying low-frequency mutations due to inadequate sensitivity and coverage of current procedures. Herein, we introduce a super-sensitivity and specificity technique for detecting ctDNA mutations, named HiCASE. The method utilizes PCR-based CRISPR, coupled with the restriction enzyme. In this work, HiCASE focuses on testing a series of EGFR mutations to provide enhanced detection technology for non-small cell lung cancer (NSCLC), enabling a detection sensitivity of 0.01% with 40 ng cell free DNA standard. When applied to a panel of 140 plasma samples from 120 NSCLC patients, HiCASE exhibits 88.1% clinical sensitivity and 100% specificity with 40 µL of plasma, higher than ddPCR and Super-ARMS assay. In addition, HiCASE can also clearly distinguish T790M/C797S mutations in different positions at a 1% variant allele frequency, offering valuable guidance for drug utilization. Indeed, the established HiCASE assay shows potential for clinical applications.

Identification of toll-like receptor 2 as a key regulator of neuronal apoptosis in vascular dementia by bioinformatics analysis and experimental validation.

BACKGROUND: Vascular dementia (VaD), the second most prevalent type of dementia, lacks a well-defined cause and effective treatment. Our objective was to utilize bioinformatics analysis to discover the fundamental disease-causing genes and pathological mechanisms in individuals diagnosed with VaD. METHODS: To identify potential pathogenic genes associated with VaD, we conducted weighted gene co-expression network analysis (WGCNA), differential expression analysis, and protein-protein interaction (PPI) analysis. The exploration of potential biological mechanisms involved the utilization of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. Moreover, a bilateral common carotid artery stenosis (BCAS) mouse model of VaD was established, and the expression of the hub gene, its relationship with cognitive function and its potential pathogenic mechanism were verified by cognitive behavior tests, cerebral blood flow measurement, Western blotting, and immunofluorescence experiments. RESULTS: This study identified 293 DEGs from the brain cortex of VaD patients and healthy controls, among these genes, the Toll-like receptor 2 (TLR2) gene was identified as hub gene, and it was associated with the apoptosis-related pathway PI3K/AKT.The BCAS model demonstrated that the use of TLR2 inhibitors greatly enhanced the cognitive function of the mice (p < 0.05). Additionally, there was a notable decrease in the number of apoptotic cells in the brain cortex of the mice (p < 0.01). Moreover, significant alterations in the levels of proteins related to the PI3K/AKT pathway and cleaved-caspase3 proteins were detected (p < 0.05). CONCLUSIONS: TLR2 plays a role in the pathophysiology of VaD by enhancing the neuronal apoptotic pathway, suggesting it could be a promising therapeutic target.

A LAMP-based hydrogen ion selective electrochemical sensor for highly sensitive detection of Mycoplasma pneumoniae.

A concise and rapid detection method for Mycoplasma pneumoniae is urgently required due to its severe impact on human health. To meet such a need, this study proposed and constructed an innovative point-of-care testing (POCT) platform that consists of a hydrogen ion-selective loop-mediated isothermal amplification (H+-LAMP) sensor and an electrochemical detection device. The H+-LAMP sensor successfully integrated the working and reference electrodes and converted the H+ generated during the LAMP process into an electrochemical signal. High sensitivity and stability for pathogen detection were also achieved by treating the working electrode with an electrodeposited polyaniline solid contact layer and by using an ion-selective membrane. As a result, the sensor shows a sensitivity of 68.26 mV per pH, a response time of less than 2 s, and a potential drift of less than 5 mV within one hour, which well meets the urgent need. The results also demonstrated that the detection limit for Mycoplasma pneumoniae was lowered to 1 copy per µL, the nucleic acid extraction and detection process could be completed in 30 minutes, and the impact of interfering ions on the sensor was negligible. Validation with 20 clinical samples yielded satisfactory results. More importantly, the storage lifespan of such an electrochemical sensor is over seven days, which is a great advantage for on-site pathogen detection. Therefore, the hydrogen ion-selective sensor constructed in this investigation is particularly suitable as a core component for instant pathogen detection platforms.

Global insights into endophytic bacterial communities of terrestrial plants: Exploring the potential applications of endophytic microbiota in sustainable agriculture.

Endophytic microorganisms are indispensable symbionts during plant growth and development and often serve functions such as growth promotion and stress resistance in plants. Therefore, an increasing number of researchers have applied endophytes for multifaceted phytoremediation (e.g., organic pollutants and heavy metals) in recent years. With the availability of next-generation sequencing technologies, an increasing number of studies have shifted the focus from culturable bacteria to total communities. However, information on the composition, structure, and function of bacterial endophytic communities is still not widely synthesized. To explore the general patterns of variation in bacterial communities between plant niches, we reanalyzed data from 1499 samples in 30 individual studies from different continents and provided comprehensive insights. A group of bacterial genera were commonly found in most plant roots and shoots. Our analysis revealed distinct variations in the diversity, composition, structure, and function of endophytic bacterial communities between plant roots and shoots. These variations underscore the sophisticated mechanisms by which plants engage with their endophytic microbiota, optimizing these interactions to bolster growth, health, and resilience against stress. Highlighting the strategic role of endophytic bacteria in promoting sustainable agricultural practices and environmental stewardship, our study not only offers global insights into the endophytic bacterial communities of terrestrial plants but also underscores the untapped potential of these communities as invaluable resources for future research.

Construction of GPC3-modified Lipopolymer SiRNA Delivery System.

BACKGROUND: Gene therapy has been widely concerned because of its unique therapeutic mechanism. However, due to the lack of safe and effective carries, it has not been widely used in clinical practice. Glypican 3 (GPC3) is a highly specific proteoglycan for hepatocellular carcinoma and is a potential diagnostic and therapeutic target for hepatocellular carcinoma. Herein, to monitor the effect of gene therapy and enhance the transfection efficiency of gene carriers, GPC3-modified lipid polyethyleneimine-modified superparamagnetic nanoparticle (GLPS), a type of visualized carrier for siRNA (small-interfering RNA) targeting the liver, was prepared. METHODS: We performed in vitro gene silencing, cytotoxicity, and agarose gel electrophoresis to identify the optimal GLPS formulation. In vitro MRI and Prussian blue staining verified the liver-targeting function of GLPS. We also analyzed the biocompatibility of GLPS by co-culturing with rabbit red blood cells. Morphological changes were evaluated using HE staining. RESULTS: The GLPS optimal formulation consisted of LPS and siRNA at a mass ratio of 25:1 and LPS and DSPE-PEG-GPC3 at a molar ratio of 2:3. GLPS exhibited evident liver-targeting function. In vitro, we did not observe morphological changes in red blood cells or hemolysis after co-culture. In vivo, routine blood analysis revealed no abnormalities after GLPS injection. Moreover, the tissue morphology of the kidney, spleen, and liver was normal without injury or inflammation. CONCLUSION: GLPS could potentially serve as an effective carrier for liver-targeted MRI monitoring and siRNA delivery.

An SSVEP-based BCI with 112 targets using frequency spatial multiplexing.

Objective.Brain-computer interface (BCI) systems with large directly accessible instruction sets are one of the difficulties in BCI research. Research to achieve high target resolution (⩾100) has not yet entered a rapid development stage, which contradicts the application requirements. Steady-state visual evoked potential (SSVEP) based BCIs have an advantage in terms of the number of targets, but the competitive mechanism between the target stimulus and its neighboring stimuli is a key challenge that prevents the target resolution from being improved significantly.Approach.In this paper, we reverse the competitive mechanism and propose a frequency spatial multiplexing method to produce more targets with limited frequencies. In the proposed paradigm, we replicated each flicker stimulus as a 2 × 2 matrix and arrange the matrices of all frequencies in a tiled fashion to form the interaction interface. With different arrangements, we designed and tested three example paradigms with different layouts. Further we designed a graph neural network that distinguishes between targets of the same frequency by recognizing the different electroencephalography (EEG) response distribution patterns evoked by each target and its neighboring targets.Main results.Extensive experiment studies employing eleven subjects have been performed to verify the validity of the proposed method. The average classification accuracies in the offline validation experiments for the three paradigms are 89.16%, 91.38%, and 87.90%, with information transfer rates (ITR) of 51.66, 53.96, and 50.55 bits/min, respectively.Significance.This study utilized the positional relationship between stimuli and did not circumvent the competing response problem. Therefore, other state-of-the-art methods focusing on enhancing the efficiency of SSVEP detection can be used as a basis for the present method to achieve very promising improvements.

CSF1R blockade slows progression of cerebral hemorrhage by reducing microglial proliferation and increasing infiltration of CD8 + CD122+ T cells into the brain.

Microglia play a pivotal role in the neuroinflammatory response after brain injury, and their proliferation is dependent on colony-stimulating factors. In the present study, we investigated the effect of inhibiting microglia proliferation on neurological damage post intracerebral hemorrhage (ICH) in a mouse model, an aspect that has never been studied before. Using a colony-stimulating factor-1 receptor antagonist (GW2580), we observed that inhibition of microglia proliferation significantly ameliorated neurobehavioral deficits, attenuated cerebral edema, and reduced hematoma volume after ICH. This intervention was associated with a decrease in pro-inflammatory factors in microglia and an increased infiltration of peripheral regulatory CD8 + CD122+ T cells into the injured brain tissue. The CXCR3/CXCL10 axis is the mechanism of brain homing of regulatory CD8 + CD122+ T cells, and the high expression of IL-10 is the hallmark of their synergistic anti-inflammatory effect with microglia. And activated astrocytes around the insult site are a prominent source of CXCL10. Thus, inhibition of microglial proliferation offers a new perspective for clinical translation. The cross-talk between multiple cells involved in the regulation of the inflammatory response highlights the comprehensive nature of neuroimmunomodulation.

Effect of destability time on microstructure and properties of hypoeutectic high chromium cast iron.

The present work investigated the effect of destabilization time on the mechanical properties and microstructure evolution of high chromium cast iron, and scanning electron microscopy and electron probe microanalysis techniques were employed. The results show that the hardness of hypoeutectic high chromium cast iron is related to the size and volume fraction of secondary carbides precipitated from the matrix. The hardness of the alloy continues to rise due to the continuous increase of the volume fraction of the secondary carbide at the initial stage of destabilization. The alloy reaches its peak hardness value at 950 °C and 1000 °C for 1 hour holding time. The solid solubility of carbon and alloying elements in the matrix increases as the holding time extends, resulting in a large number of carbides redissolved into the matrix, making the hardness of the alloy decrease; the hardness of the alloy at 14 h is less than that at 10 min. Under 1050 °C, the size and density of the secondary carbide increase significantly; extending the holding time will lead to the continuous reduction of the carbide rod that provides strength, thus, the hardness curve shows a downward trend.

[Liujunzi Decoction treats 4NQO-induced esophageal cancer in mice: a study based on serum metabolomics].

This study aims to explore the mechanism of Liujunzi Decoction in the treatment of 4-nitroquinoline-N-oxide(4NQO)-induced esophageal cancer in mice. One hundred mice of 35-45 days were randomized into blank, model, and low-, medium-, and high-concentration(18.2, 36.4, and 54.6 g·kg~(-1), respectively) Liujunzi Decoction groups. The mice in other groups except the blank group had free access to the water containing 100 µg·mL~(-1) 4NQO for 16 weeks for the modeling of esophageal cancer. The mice in the Liujunzi Decoction groups were fed with the diets supplemented with corresponding concentrations of Liujunzi Decoction. The body weight and organ weights were weighed for the calculation of organ indexes. The pathological changes of the esophageal tissue were observed by hematoxylin-eosin(HE) staining. Ultra performance liquid chromatography-mass spectrometry(UPLC-MS/MS) was employed to collect metabolites from mouse serum samples, screen out potential biomarkers, and predict related metabolic pathways. Compared with the blank group, the model group showed decreased spleen and stomach indexes and increased lung, esophagus, and kidney indexes. Compared with the model group, Liujunzi Decoction groups had no significant changes in the organ indexes. The HE staining results showed that Liujunzi Decoction inhibited the invasive growth and cancerization of the esophageal cancer cells. A total of 9 potential biomarkers of Liujunzi Decoction in treating esophageal cancer were screened out in this study, which were urocanic acid, 1-oleoylglycerophosphoserine, 11-deoxy prostaglandin E1, Leu-Glu-Lys-Glu,(±) 4-hydroxy-5E,7Z,10Z,13Z,16Z,19Z-docosahexaenoic acid, ureidosuccinic acid,(2R)-2,4-dihydroxy-3,3-dimethylbutanoic acid, kynurenic acid, and bicyclo prostaglandin E2, which were mainly involved in histidine, pyrimidine, alanine, aspartate, glutamate, pantothenate and tryptophan metabolism and coenzyme A biosynthesis. In summary, Liujunzi Decoction may exert the therapeutic effect on the 4NQO-induced esophageal cancer in mice by regu-lating the amino acid metabolism, inflammation, and immune function.

Non-Noble-Metal-Doped Carbon Nitride Photocatalysts for Water Splitting Screened Out by Empty Defect States and the d-Band Center.

A rational design of water-splitting photocatalysts from the perspective of the electronic structure is highly desirable for optimizing catalytic activities. However, the structure-activity relationship is still unclear, which impedes the development of efficient catalysts. Herein, by comparing systematically the overall water-splitting capability of 20 kinds of metallic elements anchored at three sites (including cavity, carbon vacancy, and nitrogen vacancy) of graphitic carbon nitride (g-C3N4) through density functional theory calculations, we uncover that availability of in-gap empty defect states and the d-band center position are paramount parameters to determine activities of g-C3N4 on photocatalytic water splitting. In-gap empty states play a role in accommodating electrons from H2O to facilitate its splitting. A lower d-band center weakens the interaction between reaction intermediates and g-C3N4, thereby promoting O2 desorption. Metals embedded at carbon vacancies are found to be superior to those at cavities and nitrogen vacancies because the former not only provides ample in-gap empty states but also has a lower d-band center. We also discover a rule that, for a reaction in which the bond order between the metal and intermediate enlarges (reduces), its reaction difficulty increases (decreases) with the increasing atomic number for elements in the same period. After screening, we find that non-noble metals Co, Ni, and Ga anchored at carbon vacancies possess catalytic performances comparable to Pd- and Pt-doped systems, with the rate-determining barriers less than 0.55 eV. Our findings may provide useful information for designing effective photocatalysts.

Multi-Task Collaborative Network: Bridge the Supervised and Self-Supervised Learning for EEG Classification in RSVP Tasks.

Electroencephalography (EEG) datasets are characterized by low signal-to-noise signals and unquantifiable noisy labels, which hinder the classification performance in rapid serial visual presentation (RSVP) tasks. Previous approaches primarily relied on supervised learning (SL), which may result in overfitting and reduced generalization performance. In this paper, we propose a novel multi-task collaborative network (MTCN) that integrates both SL and self-supervised learning (SSL) to extract more generalized EEG representations. The original SL task, i.e., the RSVP EEG classification task, is used to capture initial representations and establish classification thresholds for targets and non-targets. Two SSL tasks, including the masked temporal/spatial recognition task, are designed to enhance temporal dynamics extraction and capture the inherent spatial relationships among brain regions, respectively. The MTCN simultaneously learns from multiple tasks to derive a comprehensive representation that captures the essence of all tasks, thus mitigating the risk of overfitting and enhancing generalization performance. Moreover, to facilitate collaboration between SL and SSL, MTCN explicitly decomposes features into task-specific features and task-shared features, leveraging both label information with SL and feature information with SSL. Experiments conducted on THU, CAS, and GIST datasets illustrate the significant advantages of learning more generalized features in RSVP tasks. Our code is publicly accessible at https://github.com/Tammie-Li/MTCN.

CT features based preoperative predictors of aggressive pathology for clinical T1 solid renal cell carcinoma and the development of nomogram model.

BACKGROUND: We aimed to identify preoperative predictors of aggressive pathology for cT1 solid renal cell carcinoma (RCC) by combining clinical features with qualitative and quantitative CT parameters, and developed a nomogram model. METHODS: We conducted a retrospective study of 776 cT1 solid RCC patients treated with partial nephrectomy (PN) or radical nephrectomy (RN) between 2018 and 2022. All patients underwent four-phase contrast-enhanced CT scans and the CT parameters were obtained by two experienced radiologists using region of interest (ROI). Aggressive pathology was defined as patients with nuclear grade III-IV; upstage to pT3a; type II papillary renal cell carcinoma (pRCC), collecting duct or renal medullary carcinoma, unclassified RCC or sarcomatoid/rhabdoid features. Univariate and multivariate logistic analyses were used to determine significant predictors and develop the nomogram model. To evaluate the accuracy and clinical utility of the nomogram model, we used the receiver operating characteristic (ROC) curve, calibration plot, decision curve analysis (DCA), risk stratification, and subgroup analysis. RESULTS: Of the 776 cT1 solid RCC patients, 250 (32.2%) had aggressive pathological features. The interclass correlation coefficient (ICC) of CT parameters accessed by two reviewers ranged from 0.758 to 0.982. Logistic regression analyses showed that neutrophil-to-lymphocyte ratio (NLR), distance to the collecting system, CT necrosis, tumor margin irregularity, peritumoral neovascularity, and RER-NP were independent predictive factors associated with aggressive pathology. We built the nomogram model using these significant variables, which had an area under the curve (AUC) of 0.854 in the ROC curve. CONCLUSIONS: Our research demonstrated that preoperative four-phase contrast-enhanced CT was critical for predicting aggressive pathology in cT1 solid RCC, and the constructed nomogram was useful in guiding patient treatment and postoperative follow-up.

Tumor margin irregularity degree is an important preoperative predictor of adverse pathology for clinical T1/2 renal cell carcinoma and the construction of predictive model.

PURPOSE: To explore the critical role of the tumor margin irregularity degree (TMID) of renal tumors in predicting adverse pathology of patients with clinical T1/2 (cT1/2) renal cell carcinoma (RCC). METHODS: A total of 821 patients with cT1/2 RCC undergoing nephrectomy in the Second Hospital of Tianjin Medical University between January 2017 and December 2020 were reviewed. The tumor margin irregularity (TMI) was classified into renal mass with locally raised protrusion and smooth margin called 'lobular', sharply and unsmooth nodular margin called 'spiculation', blurred margins between tumor and renal parenchyma or a completely irregular and non-elliptical shape. The ratio between the number of irregular cross-sections (X) and the number of total cross-sections from top to bottom occupied (Y) was defined as TMID (X/Y). The logistic regression was performed to determine the independent predictors of adverse pathology, and the Kaplan-Meier curve and log-rank test were used to analyze the survival outcomes. RESULTS: Among 821 cT1/2 RCC patients, 245 (29.8%) had adverse pathology. The results of the univariate and multivariate logistic regressions showed that the age, tumor size, hemoglobin, and TMID were the independent predictors of adverse pathology. Incorporation of TMID could increase the discrimination of the predictive model with the area under curve (AUC) of ROC curves increasing from 0.725 to 0.808. Patients with adverse pathology or higher TMID both had significantly shorter recurrence-free survival (RFS). CONCLUSION: The nomogram model incorporated with TMID for predicting adverse pathology could increase its discrimination, calibration, and clinical application values, compared with the models without TMID.

Effects of tomato-Sedum alfredii Hance intercropping on crop production and Cd remediation as affected by soil types.

Intercropping crops with hyperaccumulators is a proven model for coupling crop safety production and soil heavy metal remediation. And both crop genotypes and soil properties might have great impacts on the effect of intercropping. Therefore, a greenhouse pot experiment was designed to investigate the effects of intercropping different tomato varieties with the cadmium (Cd) hyperaccumulator Sedum alfredii Hance (S. alfredii Hance) on different soils. The results showed that intercropping promoted Cd uptake by S. alfredii Hance and reduced soil total Cd concentration. There was no significant effect of intercropping on tomato yield and Cd concentration. Different tomato varieties had different effects on tomato yield and Cd concentration. The yield of cherry tomato was 1.04 times higher than that of common large fruit tomato, while the Cd concentration in all parts was lower than that of common large fruit tomato. Different typical zonal soils had different effects on tomato production and soil remediation. And among the four studied soils, tomatoes grown on ZJ soil had the highest yields and lowest fruit Cd concentration, making them more suitable for remediation coupled with safety production. This study provided a comprehensive analysis of tomato production benefits and soil remediation effects, which could be useful as a guide in vegetable safety production coupled with soil remediation practices in the Cd-contaminated greenhouse.

ZnO-rGO-based electrochemical biosensor for the detection of organophosphorus pesticides.

The accurate determination of organophosphorus pesticide residues is of great importance for human disease monitoring and environmental safety. Numerous detection methods exist, among which sensitive monitoring of organophosphorus compounds using electrochemical sensors has gradually become a research hotspot. This paper used acetylcholinesterase (AChE) as an indicator anchored on a zinc oxide-reduced graphene oxide (ZnO-rGO) composite rich in active sites, in which green non-toxic zinc oxide (ZnO) nanomaterials were uniformly distributed on the reduced graphene for rapid detection of organophosphorus. The effects of different ratios of ZnO to reduced graphene on the performance of ZnO-rGO nanocomposites were investigated. The AChE/ZnO-rGO biosensor detects organophosphorus by electrochemical inhibition of acetylcholinesterase in the presence of organophosphorus. The developed electrochemical biosensor has high selectivity and good linearity, and the ZnO-rGO nanocomposite as a matrix for immobilization of acetylcholinesterase and detection of organophosphorus has the potential for highly sensitive pesticide detection.

Discovery of natural multi-targets neuraminidase inhibitor glycosides compounds against influenza A virus through network pharmacology, virtual screening, molecular dynamics simulation, and in vitro experiment.

Influenza virus continually challenges both human and animal health. Moreover, influenza viruses are easy to mutate. In a certain degree, vaccines may not catch up with rapid mutant paces of viruses. Anti-influenza drugs NIs (neuraminidase inhibitors) are one of the best choices. Therefore, based on ADMET properties, eight optimal natural multi-targets NIs glycosides compounds (IC50 = 0.094-97.275 µM) are found from radix glycyrrhizae, flos sophorae, caulis spatholobi, radix astragali, radix glycyrrhizae, semen astragali complanati, and common fenugreek seed through network pharmacology, molecular docking, dynamics simulation, quantum chemistry, and in vitro experiment. Moreover, mechanism research illustrates these natural compounds treat influenza A virus through key targets TLR4, TNF, and IL6 (high fever, acute respiratory distress syndrome), MAPK1, and MAPK3 (MAPK signaling pathway, viral RNP export, and viral protein expression), IL1B (NOD-like receptor signaling pathway, suppressed maturation of pro-IL-1ß and pro-IL-18), CASP3 (apoptosis), AKT1 (inhibited premature apoptosis), and EP300 (viral myocarditis, chemoattraction of monocytes and macrophages, T-cell activation antibody response).

Extreme multistability in symmetrically coupled clocks.

Extreme multistability (EM) is characterized by the emergence of infinitely many coexisting attractors or continuous families of stable states in dynamical systems. EM implies complex and hardly predictable asymptotic dynamical behavior. We analyze a model for pendulum clocks coupled by springs and suspended on an oscillating base and show how EM can be induced in this system by specifically designed coupling. First, we uncover that symmetric coupling can increase the dynamical complexity. In particular, the coexistence of multiple isolated attractors and continuous families of stable periodic states is generated in a symmetric cross-coupling scheme of four pendulums. These coexisting infinitely many states are characterized by different levels of phase synchronization between the pendulums, including anti-phase and in-phase states. Some of the states are characterized by splitting of the pendulums into groups with silent sub-threshold and oscillating behavior, respectively. The analysis of the basins of attraction further reveals the complex dependence of EM on initial conditions.

Clinical Significance and Immune Infiltration Analyses of a Novel Nerve-Related lncRNA Signature in Gastric Cancer.

Gastric cancer (GC) is a progressive disease with high morbidity and mortality. Accumulating evidence indicated that nervous system-cancer crosstalk can affect the occurrence and progression of GC. However, the role of nerve-related lncRNAs (NRLs) in GC remains largely unexplored. In this study, a total of 441 nerve-related genes were collected from the KEGG database, and two approaches, unsupervised clustering and WGCNA, were employed to identify NRLs. Lasso regression analysis was then used to construct the nerve-related lncRNA signature (NRLS). Based on the expression profiles of 5 lncRNAs, we developed a stable NRLS to predict survival in GC patients, and survival analyses showed significantly shorter overall survival (OS) in patients with high NRLS. In addition, the NRLS was found to be positively correlated with immune characteristics, including tumor-infiltrating immune cells, immune modulators, cytokines and chemokines. We then analyzed the role of NRLS in predicting chemotherapy and immunotherapy responses, and constructed the OS nomogram combining NRLS and other clinical features. In conclusion, we constructed a robust NRLS model to stratify GC patients and predict the outcomes of chemotherapy and immunotherapy. This study can provide a new perspective for future individualized treatment of GC.