Gastric Cancer Immune Subtypes and Prognostic Modeling: Insights from Aging-Related Gene Analysis.

Gastric cancer (GC) is highly heterogeneous and influenced by aging-related factors. This study aimed to improve individualized prognostic assessment of GC by identifying aging-related genes and subtypes. Immune scores of GC samples from GEO and TCGA databases were calculated using ESTIMATE and scored as high immune (IS_high) and low immune (IS_low). ssGSEA was used to analyze immune cell infiltration. Univariate Cox regression was employed to identify prognosis-related genes. LASSO regression analysis was used to construct a prognostic model. GSVA enrichment analysis was applied to determine pathways. CCK-8, wound healing, and Transwell assays tested the proliferation, migration, and invasion of the GC cell line (AGS). Cell cycle and aging were examined using flow cytometry, ß-galactosidase staining, and Western blotting. Two aging-related GC subtypes were identified. Subtype 2 was characterized as lower survival probability and higher risk, along with a more immune-responsive tumor microenvironment. Three genes (IGFBP5, BCL11B, and AKR1B1) screened from aging-related genes were used to establish a prognosis model. The AUC values of the model were greater than 0.669, exhibiting strong prognostic value. In vitro, IGFBP5 overexpression in AGS cells was found to decrease viability, migration, and invasion, alter the cell cycle, and increase aging biomarkers (SA-ß-galactosidase, p53, and p21). This analysis uncovered the immune characteristics of two subtypes and aging-related prognosis genes in GC. The prognostic model established for three aging-related genes (IGFBP5, BCL11B, and AKR1B1) demonstrated good prognosis performance, providing a foundation for personalized treatment strategies aimed at GC.

Selective and Scalable CO2 Electrolysis Enabled by Conductive Zinc Ion-Implanted Zeolite-Supported Cadmium Oxide Nanoclusters.

Catalyst supports play an essential role in catalytic reactions, hinting at pronounced metal-support effects. Zeolites are a propitious support in heterogeneous catalysts, while their use in the electrocatalytic CO2 reduction reaction has been limited as yet because of their electrically insulating nature and serious competing hydrogen evolution reaction (HER). Enlightened by theoretical prediction, herein, we implant zinc ions into the structural skeleton of a zeolite Y to strategically tailor a favorable electrocatalytic platform with remarkably enhanced electronic conduction and strong HER inhibition capability, which incorporates ultrafine cadmium oxide nanoclusters as guest species into the supercages of the tailored 12-ring window framework. The metal d-bandwidth tuning of cadmium by skeletal zinc steers the extent of substrate-molecule orbital mixing, enhancing the stabilization of the key intermediate *COOH while weakening the CO poisoning effect. Furthermore, the strong cadmium-zinc interplay causes a considerable thermodynamic barrier for water dissociation in the conversion of H+ to *H, potently suppressing the competing HER. Therefore, we achieve an industrial-level partial current density of 335 mA cm-2 and remarkable Faradaic efficiency of 97.1% for CO production and stably maintain Faradaic efficiency above 90% at the industrially relevant current density for over 120 h. This work provides a proof of concept of tailored conductive zeolite as a favorable electrocatalytic support for industrial-level CO2 electrolysis and will significantly enhance the adaptability of conductive zeolite-based electrocatalysts in a variety of electrocatalysis and energy conversion applications.

Identification and prognostic biomarkers among ZDHHC4/12/18/24, and APT2 in lung adenocarcinoma.

S-palmitoylases and S-depalmitoylases are differentially expressed in various cancers and several malignant tumors and show a strong prognostic ability. Notwithstanding, the potential clinical impact of S-palmitoylases and S-depalmitoylases, particularly in the prognosis and progression of lung adenocarcinoma (LUAD), has not been clarified. Expression levels of S-palmitoylases and S-depalmitoylases in LUAD were investigated using TCGA. GEPIA was used to evaluate the mRNA levels of S-palmitoylases and S-depalmitoylases at different pathological stages. Metascape was used to investigate the biological significance of S-palmitoylases and S-depalmitoylases. The Kaplan-Meier plotter was used to analyze the prognostic value of S-palmitoylases and S-depalmitoylases. CBioportal was used to analyze gene alterations in S-palmitoylases and S-depalmitoylases. UALCAN was used to examine DNA promoter methylation levels of S-palmitoylases and S-depalmitoylases. Finally, we investigated the relationship between S-palmitoylases, S-depalmitoylases, and tumor-infiltrating immune cells using TIMER. Correlations with immune checkpoint-related genes were determined using the R packages reshape2, ggpubr, ggplot2, and corrplot. PCR was also performed to assess the degree of ZDHHC4/12/18/24 and APT2 transcript expression in lung adenocarcinoma and adjacent normal lung tissues. HPA was utilized to investigate protein levels of S-palmitoylases and S-depalmitoylases in LUAD and normal lung tissue. Our study found that ZDHHC2/3/4/5/6/7/9/12/13/16/18/20/21/23/24, APT1/2, PPT1, LYPLAL1, ABHD4/10/11/12/13 and ABHD17C mRNA expression was significantly upregulated in LUAD, whereas ZDHHC1/8/11/11B/14/15/17/19/22, ABHD6/16A and ABHD17A mRNA expression was significantly downregulated. The functions of the differentially expressed S-palmitoylases and S-depalmitoylases were mainly associated with protein-cysteine S-palmitoyltransferase and protein-cysteine S-acyltransferase activities. Patients with high expression of ZDHHC4/12/18/24, APT2, ABHD4, ABHD11 and ABHD12 had a shorter overall survival. Infiltration of six immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) was closely associated with the expression of ZDHHC4/12/18/24 and APT2. ZDHHC4/12/18/24 and APT2 positively correlated with the immune checkpoint-related gene CD276. We assessed the mRNA levels of ZDHHC4/12/18/24 and APT2 using qRT-PCR and found increased expression of ZDHHC4/12/18/24 in LUAD compared with healty control lung tissues. ZDHHC4/12/18/24, and APT2 are potential prognostic biomarkers of LUAD. Their expression levels could be related to the tumor microenvironment in LUAD.

Quantitative Proteomics of Tissue-Infiltrating T Cells From CRC Patients Identified Lipocalin-2 Induces T-Cell Apoptosis and Promotes Tumor Cell Proliferation by Iron Efflux.

T cells play the most pivotal roles in antitumor immunity; the T-cell proteome and the differentially expressed proteins in the tumor immune microenvironment have rarely been identified directly from the clinical samples, especially for tumors that lack effective immunotherapy targets, such as colorectal cancer (CRC). In this study, we analyzed the protein expression pattern of the infiltrating T cells isolated from CRC patients using quantitative proteomics. CD4+ and CD8+ T cells were isolated from clinical samples and labeled by tandem mass tag reagents, and the differentially expressed proteins were quantified by mass spectrometry. The T-cell proteome profiling revealed dysfunctions in these tumor-infiltrating T cells. Specifically, antitumor immunity was suppressed because of differentially expressed metal ion transporters and immunity regulators. For the first time, lipocalin-2 (LCN2) was shown to be significantly upregulated in CD4+ T cells. Quantitative proteomic analysis of LCN2-overexpressed Jurkat cells showed that LCN2 damaged T cells by changes in iron transport. LCN2 induced T-cell apoptosis by reducing cellular iron concentration; moreover, the iron that was transported to the tumor microenvironment aided tumor cell proliferation, promoting tumor development. Meanwhile, LCN2 also influenced tumor progression through immune cytokines and cholesterol metabolism. Our results demonstrated that LCN2 has immunosuppressive functions that can promote tumor development; therefore, it is a potential immunotherapy target for CRC.

Metabolomics analysis of MnO2 nanosheets CDT for breast cancer cells and mechanism of cytotoxic action.

Chemodynamic therapy (CDT) has received more and more attention as an emerging therapeutic strategy, especially transition metals with Fenton or Fenton-like activity have good effects in CDT research, manganese dioxide nanosheets (MnO2 NSs) and their complexes have become one of the most favored nanomaterials in CDT of tumors. CDT is mainly based on the role of reactive oxygen species (ROS) in tumor treatment, which have clear chemical properties and produce clear chemical reactions. However, their mechanism of interaction with cells has not been fully elucidated. Here, we performed CDT on mouse breast cancer cells (4T1) based on MnO2 NSs, extracted the metabolites from the 4T1 cells during the treatment, and analyzed the differences in metabolites by using high-resolution liquid chromatography-mass spectrometry (LC-MS). Untargeted metabolomics studies were conducted using the relevant data. This study mainly explored the changes in MnO2 NSs on the metabolite profile of 4T1 cells and their potential impact on tumor therapy, in order to determine the mechanism of action of MnO2 NSs in the treatment of breast cancer. The results of the study showed the presence of 11 different metabolites in MnO2 NSs CDT for 4T1 tumor cells, including phosphoserine, sphingine, phosphocholine, and stearoylcarnitine. These findings provide a deeper understanding of breast cancer treatment, and are beneficial for the further research and clinical application of CDT.

Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing.

Background: Co-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples. Results: This study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus. Conclusion: During the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool.

Characterization of Tumor Mutation Burden-Based Gene Signature and Molecular Subtypes to Assist Precision Treatment in Gastric Cancer.

Objective: Tumor mutation burden (TMB) represents a useful biomarker for predicting survival outcomes and immunotherapy response. Here, we aimed to conduct TMB-based gene signature and molecular subtypes in gastric cancer. Methods: Based on differentially expressed genes (DEGs) between high- and low-TMB groups in TCGA, a LASSO model was developed for predicting overall survival (OS) and disease-free survival (DFS). The predictive performance was externally verified in the GSE84437 dataset. Molecular subtypes were conducted via consensus clustering approach based on TMB-related DEGs. The immune microenvironment was estimated by ESTIMATE and ssGSEA algorithms. Results: High-TMB patients had prolonged survival duration. TMB-related DEGs were distinctly enriched in cancer- (MAPK, P53, PI3K-Akt, and Wnt pathways) and immune-related pathways (T cell selection and differentiation). The TMB-based gene model was developed (including MATN3, UPK1B, GPX3, and RGS2), and high-risk score was predictive of poor prognosis and recurrence. ROC and multivariate analyses revealed the well predictive performance, which was confirmed in the external cohort. Furthermore, we established the nomogram containing the risk score, age, and stage for personalized prediction of OS and DFS. High-risk score was characterized by high stromal score, increased immune checkpoints, immune cell infiltrations, and enhanced sensitivity to gefitinib, vinorelbine, and gemcitabine. Three TMB-based molecular subtypes were conducted, characterized by distinct prognosis, immune microenvironment, and drug sensitivity. Conclusion: Collectively, we established a prognostic signature and three distinct molecular subtypes based on TMB features for gastric cancer, which might be beneficial for prognostic prediction and clinical decision-making.

Incidence and risk factors for postoperative pancreatic fistula in 2089 patients treated by radical gastrectomy: A prospective multicenter cohort study in China.

OBJECTIVE: To determine the incidence of clinically relevant postoperative pancreatic fistula (CR-POPF) following radical gastrectomy and to identify independent risk factors of CR-POPF. BACKGROUND: CR-POPF and its sequelae are potential complications following radical gastrectomy. The reported incidence of CR-POPF was quite different across various regions, and no consensus was reached. METHODS: Between December 2017 to November 2018, patients who underwent radical gastrectomy from 22 centers across 13 regions in China were prospectively recruited. The primary endpoint was the occurrence of CR-POPF, defined by the International Study Group of Pancreatic Fistula (ISGPF) in 2016. Clinically relevant change and short-term outcomes were recorded to diagnose and grade the POPF. Multivariate regression analyses were performed to identify independent risk factors of clinically relevant postoperative pancreatic fistula (CR-POPF). RESULTS: A total of 2089 cases were analyzed. The incidence of biochemical leakage (BL) and CR-POPF were 19.6% and 1.1% respectively. All CR-POPF patients recovered well after appropriate treatment and no Grade C POPF were recorded. Logistic regression analysis showed pTNM III (OR, 2.940; 95% CI 1.180-7.325; P = 0.021) and LigaSure usage (OR, 6.618; 95% CI 1.847-23.707; P = 0.004) were independent risk factors of CR-POPF. LigaSure usage (OR, 4.817; 95% CI 1.184-19.598; P = 0.028), the drain amylase content (D-AMY) on postoperative day 3 (POD3) ≥5 times the upper limit of normal amylase (OR, 3.476; 95% CI 1.240-9.744; P = 0.018) and open surgery (OR, 2.463; 95% CI 1.003-6.050; P = 0.049) were independent predictors for identifying CR-POPF from BL. CONCLUSION: In rich-experienced gastric cancer centers, there is high prevalence of BL secondary to radical gastrectomy without clinical impact. Fewer patients suffered Grade B POPF, and Grade C POPF was less common. The patients with pTNM III or LigaSure usage were prone to suffer CR-POPF. Surgery procedure, LigaSure usage combined with D-AMY measurement on POD3 are promising for early identification of CR-POPF.

Genetic and functional analysis reveals TENM4 contributes to schizophrenia.

TENM4, encoding a member of the teneurin protein family, is a risk gene shared by many types of mental diseases and is implicated in neuronal plasticity and signaling. However, the role and the mechanisms of TENM4 in schizophrenia (SCZ) remain unclear. We identified possible pathogenic mutations in the TENM4 gene through target sequencing of TENM4 in 68 SCZ families. We further demonstrated that aberrant expression of Ten-m leads to lower learning ability, sleep reduction, and increased aggressiveness in animal models. RNA sequencing showed that aberrant expression of Ten-m was related to stimulus perception and metabolic process, and Gene Ontology enrichment terms were neurogenesis and ATPase activity. This study provides strong evidence that TENM4 contributes to SCZ, and its functional mutations might be responsible for the impaired neural circuits and behaviors observed in SCZ.

Prognostic Significance of Preoperative Serum Carcinoembryonic Antigen Varies with Lymph Node Metastasis Status in Colorectal Cancer.

BACKGROUND: Preoperative serum level of carcinoembryonic antigen (pCEA) is generally recognized as a prognostic factor for colorectal cancer (CRC), but the stage-specific role of pCEA in colorectal cancer remains unclear. OBJECTIVE: We investigated the prognostic significance of pCEA levels in different tumor stages of nonmetastatic CRC patients. METHODS: Six hundred and fifteen CRC patients at stage I-III were retrospectively analyzed. All of them received curative tumor resection. The X-tile program was used to generate stage-specific cutoff values of pCEA for all patients and two subpopulations (lymph node-positive or -negative). The prognostic significance of pCEA was assessed using Kaplan-Meier analysis and Cox proportional hazards regression analysis. A nomogram model that combined pCEA score and clinical feature indexes was established and evaluated. RESULTS: Two cutoff values were identified in the study population. At a cutoff value of 4.9 ng/mL, a significantly higher 5-year overall survival (OS) rate (82.16%) was observed in the pCEA-low group (<4.9 ng/mL) compared with 65.52% in the pCEA-high group (≥4.9 ng/mL). Furthermore, at the second cutoff value of 27.2 ng/mL, 5-year OS was found to be only 40.9%. Stratification analysis revealed that preoperative serum level of pCEA was an independent prognostic factor (OR = 1.991, P < 0.01) in the subpopulation of lymph node metastasis (stage III) patients, and the relative survival rates in the pCEA-low (≤4.9 ng/mL), pCEA-medium (4.9-27.2 ng/mL), and pCEA-high (≥27.2 ng/mL) groups were 73.4%, 60.5%, and 24.8%, respectively (P < 0.05). However, no such effect was observed in the lymph node nonmetastasis (stage I and II) subgroup. The established nomogram showed acceptable predictive power of the 5-year OS rate (C-index: 0.612) in lymph node-positive CRC patients, with an area under the curve value of 0.772, as assessed by ROC curve analysis. CONCLUSIONS: Pretreatment serum CEA levels had different prognostic significance based on the lymph node metastasis status. Among stage III CRC patients, pCEA was an independent prognostic factor. Five-year OS rates could be predicted according to the individual pCEA level at the different cutoff values.

Multi-Target Joint Detection; Tracking and Classification Based on Marginal GLMB Filter and Belief Function Theory.

This paper proposes a new solution to multi-target joint detection, tracking and classification based on labeled random finite set (RFS) and belief function theory. A class dependent multi-model marginal generalized labeled multi-Bernoulli (MGLMB) filter is developed to analytically calculate the multi-target number, state estimates and model probabilities. In addition, a two-level classifier based on continuous transferable belief model (cTBM) is designed for target classification. To make full use of the kinematic characteristics for classification, both the dynamic modes and states are considered in the classifier, the model dependent class beliefs are computed on the continuous state feature subspace corresponding to different dynamic modes and then fused. As a result that the uncertainty about the classes is well described for decision, the classification results are more reasonable and robust. Moreover, as the estimation and classification problems are jointly solved, the tracking and classification performance are both improved. In the simulation, a scenario contains multi-target with miss detection and dense clutter is used. The performance of multi-target detection, tracking and classification is better than traditional methods based on Bayesian classifier or single model. Simulation results are illustrated to demonstrate the effectiveness and superiority of the proposed algorithm.

Performance of a Nomogram Based on the Integration of Inflammation Markers with Tumor Staging in Prognosis Prediction of Stage III Colorectal Cancer.

INTRODUCTION: The aim of the present study was to evaluate a nomogram model for predicting the 5-year overall survival (OS) in lymph node-metastatic colorectal cancer (CRC) patients by combining inflammation markers with some traditional prognostic factors. METHODS: A total of 399 patients with stage III (pTXN1-3M0) CRC operated from January 2007 to December 2012 were enrolled in this retrospective study. All patients underwent D2 lymphadenectomy in the hospital. A prognostic nomogram based on the integration of traditional prognostic factors and NLR (neutrophil-to-lymphocyte ratio) and PLR (platelet-to-lymphocyte ratio) was established and compared with the nomogram based on the traditional prognostic factors alone. ROC curves were further applied to verify the predictive accuracy of the established model. RESULTS: Both NLR (P=0.00) and PLR (P=0.01) predicted the 5-year OS. In multivariate analysis, age, T3 category, T4 category, N2 category, N3 category, Pgp (P-glycoprotein), NLR and PLR are proven to be independent (all P≤0.05). The established nomogram showed better predictive power than that of traditional profile (c-index: 0.66 versus 0.63) in both training and validation cohorts. External assessment by ROC curve analysis demonstrated that the established model had a good prediction accuracy of 5-year OS in stage III CRC patients, with area under curve values of 0.657 and 0.629 in training and validating sets, respectively. CONCLUSION: A nomogram based on the integration of traditional prognostic factors and inflammatory markers (NLR and PLR) could provide more precise long-term prognosis information for lymph node-metastatic CRC patients than the model based on traditional profile alone. This model might be useful for clinical application in personalized evaluation.

High Selectivity to Aromatics by a Mg and Na Co-modified Catalyst in Direct Conversion of Syngas.

The demand for aromatics, especially benzene, toluene, and xylene, has been increased in recent years as the crucial feedstocks of coatings and pharmaceutical industry. In this work, a modified Fischer-Tropsch synthesis (FTS) catalyst FeNaMg was fabricated via a sol-precipitation method and integrated with an HZSM-5 aromatization catalyst for the aromatics synthesis from syngas by a one-step process. Syngas was first converted to lower olefins as intermediates on the active component of the FeNaMg catalyst followed by aromatization on zeolite. Different characterization approaches, such as BET, XRD, XPS, hydrogen temperature-programmed reduction, temperature-programmed desorption of CO, TG, and SEM, revealed that Mg efficiently optimized physicochemical properties of the Fe-based catalyst by generating a MgFe2O4 spinel structure. Further investigation demonstrated that the MgFe2O4 spinel structure could increase the syngas adsorption area, facilitating the reduction and carburization of the Fe phase, while Mg decreased CO2 selectivity (31.26 to21%) by restraining the water-gas shift reaction and improved the utilization efficiency of carbon. At the same time, alkali metal Na changed the surface electronic environment of the FTS catalyst to enhance CO adsorption as an electronic promoter, which suppressed methane formation by restraining over hydrogenation. Therefore, the synergism that existed between Mg and Na during the reaction escalated the CO conversion and aromatics selectivity to 96.19 and 51.38%, respectively.

Contribution of Social Influences through Superposition of Visual and Olfactory Inputs to Circadian Re-entrainment.

Circadian patterns of locomotor activity are influenced by social interactions. Studies on insects highlight the importance of volatile odors and the olfactory system. Wild-type Drosophila exhibit immediate re-entrainment to new light:dark (LD) cycles, whereas cryb and jetc mutants show deficits in re-entrainability. We found that both male mutants re-entrained faster to phase-shifted LD cycles when social interactions with WT female flies were promoted than the isolated males. In addition, we found that accelerated re-entrainment mediated by social interactions depended on both visual and olfactory cues, and the effect of both cues presented jointly was nearly identical to the sum of the effects of the two cues presented separately. Moreover, we found that re-entrainment deficits in period (per) expression-oscillation in jetc mutants were partially restored by promoting social interactions. Our results demonstrated that, in addition to olfaction, social interactions through the visual system also play important roles in clock entrainment.

Suboptimal adaptive Kalman filtering based on the proportional control of prior error covariance.

For linear time-invariant systems, this paper develops a new kind of adaptive Kalman filter to deal with Kalman filtering problems troubled by unknown/inaccurate process noise covariance. The limitation of Kalman filter is that its performance would deteriorate or even degrade if the accurate noise statistics could not be obtained in advance. To reduce or mitigate the negative influence caused by unknown/mismatched process noise covariance, this work elaborates a novel covariance control scheme in which the prior error covariance is recursively regulated with the proportional form of feedback information: the posterior sequence is first evaluated as online feedback to constitute a closed-loop structure for covariance propagation process, and then a proportional gain is employed to amplify the feedback term and fasten the converging of the estimated covariance parameter; note that, the new approach is relatively more independent of the parameter of process noise covariance and, therefore, the Kalman theory's rigorous dependency on accurate process noise covariance could be relaxed significantly. The mathematical properties and sub-optimality of the new covariance control scheme are discussed in detail as well as some practical considerations. The advantage of this newly developed method in filtering accuracy, adaptability and simplicity are illustrated with an object tracking scenario.

Robust Consensus Nonlinear Information Filter for Distributed Sensor Networks With Measurement Outliers.

The traditional consensus-based filters are widely used in distributed sensor networks. However, they suffer from divergence when outliers occur. This paper proposes a robust consensus nonlinear information filter for distributed state estimation with measurement outliers. Unlike the Gaussian assumption in traditional consensus filers, the measurement of each sensor node is modeled here as a multivariate Student- t process with unknown parameters of the sufficient statistic. The variational Bayesian method is employed to jointly estimate the state and the parameters. As the state and parameters are coupled, the updated equation can be solved by fixed point iteration. The centralized outliers robust information filter is first derived for multiple sensors. It is then extended to a distributed version to fuse information from multiple interconnected local estimators. The integral of the consensus-based nonlinear filter is approximated by Gaussian approximation under the framework of the information filter. The consensuses are based on both likelihoods and prior probability distributions. The consensus and convergence of the proposed method are also analyzed. Simulation results show that the proposed approach is effective in dealing with outliers.

SIRT1 facilitates amyloid beta peptide degradation by upregulating lysosome number in primary astrocytes.

Previous studies have shown that sirtuin 1 (SIRT1) reduces the production of neuronal amyloid beta (Aß) and inhibits the inflammatory response of glial cells, thereby generating a neuroprotective effect against Aß neurotoxicity in animal models of Alzheimer's disease. However, the protective effect of SIRT1 on astrocytes is still under investigation. This study established a time point model for the clearance of Aß in primary astrocytes. Results showed that 12 hours of culture was sufficient for endocytosis of oligomeric Aß, and 36 hours sufficient for effective degradation. Immunofluorescence demonstrated that Aß degradation in primary astrocytes relies on lysosome function. Enzymatic agonists or SIRT1 inhibitors were used to stimulate cells over a concentration gradient. Aß was co-cultured for 36 hours in medium. Western blot assay results under different conditions revealed that SIRT1 relies on its deacetylase activity to promote intracellular Aß degradation. The experiment further screened SIRT1 using quantitative proteomics to investigate downstream, differentially expressed proteins in the Aß degradation pathway and selected the ones related to enzyme activity of SIRT1. Most of the differentially expressed proteins detected are close to the primary astrocyte lysosomal pathway. Immunofluorescence staining demonstrated that SIRT1 relies on its deacetylase activity to upregulate lysosome number in primary astrocytes. Taken together, these findings confirm that SIRT1 relies on its deacetylase activity to upregulate lysosome number, thereby facilitating oligomeric Aß degradation in primary astrocytes.

Control of Sleep Onset by Shal/Kv4 Channels in Drosophila Circadian Neurons.

Sleep is highly conserved across animal species. Both wake- and sleep-promoting neurons are implicated in the regulation of wake-sleep transition at dusk in Drosophila However, little is known about how they cooperate and whether they act via different mechanisms. Here, we demonstrated that in female Drosophila, sleep onset was specifically delayed by blocking the Shaker cognate L channels [Shal; also known as voltage-gated K+ channel 4 (Kv4)] in wake-promoting cells, including large ventral lateral neurons (l-LNvs) and pars intercerebralis (PI), but not in sleep-promoting dorsal neurons (DN1s). Delayed sleep onset was also observed in males by blocking Kv4 activity in wake-promoting neurons. Electrophysiological recordings show that Kv4 channels contribute A-type currents in LNvs and PI cells, but are much less conspicuous in DN1s. Interestingly, blocking Kv4 in wake-promoting neurons preferentially increased firing rates at dusk ∼ZT13, when the resting membrane potentials and firing rates were at lower levels. Furthermore, pigment-dispersing factor (PDF) is essential for the regulation of sleep onset by Kv4 in l-LNvs, and downregulation of PDF receptor (PDFR) in PI neurons advanced sleep onset, indicating Kv4 controls sleep onset via regulating PDF/PDFR signaling in wake-promoting neurons. We propose that Kv4 acts as a sleep onset controller by suppressing membrane excitability in a clock-dependent manner to balance the wake-sleep transition at dusk. Our results have important implications for the understanding and treatment of sleep disorders such as insomnia.SIGNIFICANCE STATEMENT The mechanisms by which our brains reversibly switch from waking to sleep state remain an unanswered and intriguing question in biological research. In this study, we identified that Shal/Kv4, a well known voltage-gated K+ channel, acts as a controller of wake-sleep transition at dusk in Drosophila circadian neurons. We find that interference of Kv4 function with a dominant-negative form (DNKv4) in subsets of circadian neurons specifically disrupts sleep onset at dusk, although Kv4 itself does not exhibit circadian oscillation. Kv4 preferentially downregulates neuronal firings at ZT9-ZT17, supporting that it plays an essential role in wake-sleep transition at dusk. Our findings may help understand and eventually treat sleep disorders such as insomnia.

HSPB8 promotes cancer cell growth by activating the ERK­CREB pathway and is indicative of a poor prognosis in gastric cancer patients.

Gastric cancer (GC) is one of the most commonly diagnosed malignancies worldwide, especially in East Asia. Discovery of new biomarker and the elucidation of the molecular mechanisms involved in GC development and progression continue to be important issues for both researchers and clinicians. In the present study, we report that siRNA knockdown of heat shock protein family B (small) member 8 (HSPB8) inhibited the proliferation of GC cells and promoted their apoptosis. Analysis of TCGA dataset indicated that the HSPB8 expression level was strongly positively correlated with the KEGG MAPK signaling pathway (P<0.001, FDR=0.006) and BIOCARTA CREB pathway (P=0.006, FDR=0.043). The association between HSPB8 and the ERK­CREB pathway was confirmed by western blot analysis and we found that pERK and pCREB were significantly decreased following HSPB8 knockdown. Downstream genes of the ERK­CREB pathway were all significantly decreased following HSPB8 knockdown. By evaluating the survival of TCGA GC patients, we found that patients with a high HSPB8 level exhibited significantly worse prognosis than those with low HSPB8 in both overall survival (OS) (log­rank χ2=10.60, P=0.001) and disease­free survival (DFS) (log­rank χ2=11.31, P<0.001). The methylation level of HSPB8 DNA was significantly negatively associated with its expression (R=­0.1368, P=0.041), and positively associated with OS (log­rank χ2=10.60, P=0.001). In conclusion, we provide evidence that HSPB8 promotes cancer cell growth by activating the ERK­CREB pathway and may serve as a potential prognostic factor in GC patients.

MicroRNA-744 Inhibits Cellular Proliferation and Invasion of Colorectal Cancer by Directly Targeting Oncogene Notch1.

Accumulated studies have strongly implicated aberrantly expressed microRNAs (miRNAs) in carcinogenesis and cancer progression of various cancers, including colorectal cancer (CRC). Hence, a comprehensive study of miRNAs and their association with CRC may be a promising therapeutic method for patients with this malignancy. MicroRNA-744 (miR-744) is abnormally expressed in several types of human cancer. Thus far, little is known about the expression, biological roles, and exact mechanisms of miR-744 in CRC. Thus, the present study measured the expression level of miR-744 and investigated its roles and associated molecular mechanisms in CRC. This study demonstrated that miR-744 expression was significantly underexpressed in CRC tissues and cell lines. Low miR-744 expression was positively associated with lymphatic metastasis and TNM stage. Functional experiments revealed that miR-744 overexpression obviously inhibited the proliferation and invasion of CRC cells. Furthermore, Notch1 was identified as a direct target of miR-744 in CRC. Moreover, the inhibition of Notch1 phenocopied the inhibitory effects of miR-744 overexpression on CRC cells. Restored Notch1 expression markedly rescued the tumor-suppressive effects of miR-744 overexpression on CRC cells. Overall, miR-744 exhibits an essential role in CRC progression, and the miR-744/Notch1 axis may provide novel insights into future treatments for patients with CRC.