Learn to integrate parts for whole through correlated neural variability

Sensory perception originates from the responses of sensory neurons, which react to a collection of sensory signals linked to various physical attributes of a singular perceptual object. Unraveling how the brain extracts perceptual information from these neuronal responses is a pivotal challenge in both computational neuroscience and machine learning. Here we introduce a statistical mechanical theory, where perceptual information is first encoded in the correlated variability of sensory neurons and then reformatted into the firing rates of downstream neurons. Applying this theory, we illustrate the encoding of motion direction using neural covariance and demonstrate high-fidelity direction recovery by spiking neural networks. Networks trained under this theory also show enhanced performance in classifying natural images, achieving higher accuracy and faster inference speed. Our results challenge the traditional view of neural covariance as a secondary factor in neural coding, highlighting its potential influence on brain function.Comment: 18 pages, 5 figure

CXCL13/CXCR5 Axis Predicts Poor Prognosis and Promotes Progression Through PI3K/AKT/mTOR Pathway in Clear Cell Renal Cell Carcinoma

The chemokine ligands and their receptors play critical roles in cancer progression and patients outcomes. We found that CXCL13 was significantly upregulated in ccRCC tissues compared with normal tissues in both The Cancer Genome Atlas (TCGA) cohort and a validated cohort of 90 pairs ccRCC tissues. Statistical analysis showed that high CXCL13 expression related to advanced disease stage and poor prognosis in ccRCC. We also revealed that serum CXCL13 levels in ccRCC patients (n = 50) were significantly higher than in healthy controls (n = 40). Receiver operating characteristic (ROC) curve revealed that tissue and serum CXCL13 expression might be a diagnostic biomarker for ccRCC with an area under curve (AUC) of 0.809 and 0.704, respectively. CXCL13 was significantly associated with its receptor, CXCR5, in ccRCC tissues, and ccRCC patients in high CXCL13 high CXCR5 expression group have a worst prognosis. Functional and mechanistic study revealed that CXCL13 promoted the proliferation and migration of ccRCC cells by binding to CXCR5 and activated PI3K/AKT/mTOR signaling pathway. These results suggested that CXCL13/CXCR5 axis played a significant role in ccRCC and might be a therapeutic target and prognostic biomarker

Knockdown of a novel lincRNA AATBC suppresses proliferation and induces apoptosis in bladder cancer

Long intergenic noncoding RNAs (lincRNAs) play important roles in regulating various biological processes in cancer, including proliferation and apoptosis. However, the roles of lincRNAs in bladder cancer remain elusive. In this study, we identified a novel lincRNA, which we termed AATBC. We found that AATBC was overexpressed in bladder cancer patient tissues and positively correlated with tumor grade and pT stage. We also found that inhibition of AATBC resulted in cell proliferation arrest through G1 cell cycle mediated by cyclin D1, CDK4, p18 and phosphorylated Rb. In addition, inhibition of AATBC induced cell apoptosis through the intrinsic apoptosis signaling pathway, as evidenced by the activation of caspase-9 and caspase-3. The investigation for the signaling pathway revealed that the apoptosis following AATBC knockdown was mediated by activation of phosphorylated JNK and suppression of NRF2. Furthermore, JNK inhibitor SP600125 could attenuate the apoptotic effect achieved by AATBC knockdown, confirming the involvement of JNK signaling in the induced apoptosis. Moreover, mouse xenograft model revealed that knockdown of AATBC led to suppress tumorigenesis in vivo. Taken together, our study indicated that AATBC might play a critical role in pro-proliferation and anti-apoptosis in bladder cancer by regulating cell cycle, intrinsic apoptosis signaling, JNK signaling and NRF2. AATBC could be a potential therapeutic target and molecular biomarker for bladder cancer

Long Non-Coding RNA LUCAT1 Promotes Proliferation and Invasion in Clear Cell Renal Cell Carcinoma Through AKT/GSK-3β Signaling Pathway

Background/Aims: Long non-coding RNAs (lncRNAs) have emerged as new regulators and biomarkers in several cancers. However, few lncRNAs have been well characterized in clear cell renal cell carcinoma (ccRCC). Methods: We investigated the lncRNA expression profile by microarray analysis in 5 corresponding ccRCC tissues and adjacent normal tissues. Lung cancer–associated transcript 1 (LUCAT1) expression was examined in 90 paired ccRCC tissues by real-time PCR and validated by The Cancer Genome Atlas (TCGA) database. Kaplan-Meier analysis was used to examine the prognostic value of LUCAT1 and CXCL2 in ccRCC patients. Loss and gain of function were performed to explore the effect of LUCAT1 on proliferation and invasion in ccRCC cells. Western blotting was performed to evaluate the underlying mechanisms of LUCAT1 in ccRCC progression. Chemokine stimulation assay was performed to investigate possible mechanisms controlling LUCAT1 expression in ccRCC cells. Enzyme-linked immunosorbent assays were performed to determine serum CXCL2 in ccRCC patients and healthy volunteers. Receiver operating characteristic curve analysis was performed to examine the clinical diagnostic value of serum CXCL2 in ccRCC. Results: We found that LUCAT1 was significantly upregulated in both clinical ccRCC tissues (n = 90) and TCGA ccRCC tissues (n = 448) compared with normal tissues. Statistical analysis revealed that the LUCAT1 expression level positively correlated with tumor T stage (P < 0.01), M stage (P < 0.01), and TNM stage (P < 0.01). Overall survival and disease-free survival time were significantly shorter in the high-LUCAT1-expression group than in the low-LUCAT1-expression group (log-rank P < 0.01). LUCAT1 knockdown inhibited ccRCC cell proliferation and colony formation, induced cell cycle arrest at G1 phase, and inhibited cell migration and invasion. Overexpression of LUCAT1 promoted proliferation, migration, and invasion of ccRCC cells. Mechanistic investigations showed that LUCAT1 induced cell cycle G1 arrest by regulating the expression of cyclin D1, cyclin-dependent kinase 4, and phosphorylated retinoblastoma transcriptional corepressor 1. Moreover, LUCAT1 promoted proliferation and invasion in ccRCC cells partly through inducing the phosphorylation of AKT and suppressing the phosphorylation of GSK-3β. We also revealed that chemokine CXCL2, upregulated in ccRCC, induced LUCAT1 expression and might be a diagnostic and prognostic biomarker in ccRCC. Conclusions: LUCAT1 was upregulated in ccRCC tissues and renal cancer cell lines, and significantly correlated with malignant stage and poor prognosis in ccRCC. LUCAT1 promoted proliferation and invasion in ccRCC cells through the AKT/GSK-3β signaling pathway. We also revealed that LUCAT1 overexpression was induced by chemokine CXCL2. These findings indicate that the CXCL2/LUCAT1/AKT/GSK-3β axis is a potential therapeutic target and molecular biomarker for ccRCC

Pattern Classification of Large-Scale Functional Brain Networks: Identification of Informative Neuroimaging Markers for Epilepsy

The accurate prediction of general neuropsychiatric disorders, on an individual basis, using resting-state functional magnetic resonance imaging (fMRI) is a challenging task of great clinical significance. Despite the progress to chart the differences between the healthy controls and patients at the group level, the pattern classification of functional brain networks across individuals is still less developed. In this paper we identify two novel neuroimaging measures that prove to be strongly predictive neuroimaging markers in pattern classification between healthy controls and general epileptic patients. These measures characterize two important aspects of the functional brain network in a quantitative manner: (i) coordinated operation among spatially distributed brain regions, and (ii) the asymmetry of bilaterally homologous brain regions, in terms of their global patterns of functional connectivity. This second measure offers a unique understanding of brain asymmetry at the network level, and, to the best of our knowledge, has not been previously used in pattern classification of functional brain networks. Using modern pattern-recognition approaches like sparse regression and support vector machine, we have achieved a cross-validated classification accuracy of 83.9% (specificity: 82.5%; sensitivity: 85%) across individuals from a large dataset consisting of 180 healthy controls and epileptic patients. We identified significantly changed functional pathways and subnetworks in epileptic patients that underlie the pathophysiological mechanism of the impaired cognitive functions. Specifically, we find that the asymmetry of brain operation for epileptic patients is markedly enhanced in temporal lobe and limbic system, in comparison with healthy individuals. The present study indicates that with specifically designed informative neuroimaging markers, resting-state fMRI can serve as a most promising tool for clinical diagnosis, and also shed light onto the physiology behind complex neuropsychiatric disorders. The systematic approaches we present here are expected to have wider applications in general neuropsychiatric disorders

Role of Scrib and Dlg in anterior-posterior patterning of the follicular epithelium during Drosophila oogenesis

<p>Abstract</p> <p>Background</p> <p>Proper patterning of the follicle cell epithelium over the egg chamber is essential for the <it>Drosophila </it>egg development. Differentiation of the epithelium into several distinct cell types along the anterior-posterior axis requires coordinated activities of multiple signaling pathways. Previously, we reported that <it>lethal(2)giant larvae </it>(<it>lgl</it>), a <it>Drosophila </it>tumor suppressor gene, is required in the follicle cells for the posterior follicle cell (PFC) fate induction at mid-oogenesis. Here we explore the role of another two tumor suppressor genes, <it>scribble </it>(<it>scrib</it>) and <it>discs large </it>(<it>dlg</it>), in the epithelial patterning.</p> <p>Results</p> <p>We found that removal of <it>scrib </it>or <it>dlg </it>function from the follicle cells at posterior terminal of the egg chamber causes a complete loss of the PFC fate. Aberrant specification and differentiation of the PFCs in the mosaic clones can be ascribed to defects in coordinated activation of the EGFR, JAK and Notch signaling pathways in the multilayered cells. Meanwhile, the clonal analysis revealed that loss-of-function mutations in <it>scrib/dlg </it>at the anterior domains result in a partially penetrant phenotype of defective induction of the stretched and centripetal cell fate, whereas specification of the border cell fate can still occur in the most anterior region of the mutant clones. Further, we showed that <it>scrib </it>genetically interacts with <it>dlg </it>in regulating posterior patterning of the epithelium.</p> <p>Conclusion</p> <p>In this study we provide evidence that <it>scrib </it>and <it>dlg </it>function differentially in anterior and posterior patterning of the follicular epithelium at oogenesis. Further genetic analysis indicates that <it>scrib </it>and <it>dlg </it>act in a common pathway to regulate PFC fate induction. This study may open another window for elucidating role of <it>scrib/dlg </it>in controlling epithelial polarity and cell proliferation during development.</p

Heterogeneity of tumor vasculature and antiangiogenic intervention: insights from MR angiography and DCE-MRI.

Solid tumor vasculature is highly heterogeneous, which presents challenges to antiangiogenic intervention as well as the evaluation of its therapeutic efficacy. The aim of this study is to evaluate the spatial tumor vascular changes due to bevacizumab/paclitaxel therapy using a combination approach of MR angiography and DCE-MRI method.Tumor vasculature of MCF-7 breast tumor mouse xenografts was studied by a combination of MR angiography and DCE-MRI with albumin-Gd-DTPA. Tumor macroscopic vasculature was extracted from the early enhanced images. Tumor microvascular parameters were obtained from the pharmacokinetic modeling of the DCE-MRI data. A spatial analysis of the microvascular parameters based on the macroscopic vasculature was used to evaluate the changes of the heterogeneous vasculature induced by a 12 day bevacizumab/paclitaxel treatment in mice bearing MCF-7 breast tumor.Macroscopic vessels that feed the tumors were not affected by the bevacizumab/paclitaxel combination therapy. A higher portion of the tumors was within close proximity of these macroscopic vessels after the treatment, concomitant with tumor growth retardation. There was a significant decrease in microvascular permeability and vascular volume in the tumor regions near these vessels.Bevacizumab/paclitaxel combination therapy did not block the blood supply to the MCF-7 breast tumor. Such finding is consistent with the modest survival benefits of adding bevacizumab to current treatment regimens for some types of cancers

Optimizing design of a free piston Stirling engine using response surface methodology and grey relation analysis

The performance analysis and optimization of a γ-type free-piston Stirling engine (FPSE) are conducted using Response Surface Methodology (RSM) and Grey Relation Analysis (GRA). The input-output parameters table is determined by the RSM. A regression model is presented to investigate the influence of structural parameters of FPSE on its performance. The relation coefficients for the four output parameters obtained from the RSM are determined to be 0.9980, 0.9983, 0.9999, and 0.9995, respectively, thus unequivocally demonstrating the exceptional precision of the RSM model. Also, the relationship between displacer and piston amplitudes, operating frequency, and output power and these parameters of Stirling engine is presented via 3D surface plots. The performance of the FPSE is optimized using the desirability approach and GRA, respectively, followed by a comparison of four groups of optimization results to determine the most suitable model. The maximum output power achieved is 78.02 W, with corresponding operating frequency, displacer amplitude, and piston amplitude values of 60.24 Hz, 2.55 mm, and 7.27 mm. Finally, by comparing pre- and post-optimization, the output power is increased by 36.85%. The GRA exhibits superior optimization compared to the RSM, thus providing valuable guidance for enhancing the optimization of FPSE in this study

Tumor macrovasculature extracted from the 3D T1-weighted images acquired immediately after the administration of albumin-Gd-DTPA.

<p>A: pre-treatment, B: day 12 of saline control, C: day 12 of bevacizumab/paclitaxel combination treatment. The arrows indicate where the tumor was attached to the mouse body.</p