Primal Dual Alternating Proximal Gradient Algorithms for Nonsmooth Nonconvex Minimax Problems with Coupled Linear Constraints

Nonconvex minimax problems have attracted wide attention in machine learning, signal processing and many other fields in recent years. In this paper, we propose a primal dual alternating proximal gradient (PDAPG) algorithm and a primal dual proximal gradient (PDPG-L) algorithm for solving nonsmooth nonconvex-strongly concave and nonconvex-linear minimax problems with coupled linear constraints, respectively. The corresponding iteration complexity of the two algorithms are proved to be $\mathcal{O}\left( \varepsilon ^{-2} \right)$ and $\mathcal{O}\left( \varepsilon ^{-3} \right)$ to reach an $\varepsilon$-stationary point, respectively. To our knowledge, they are the first two algorithms with iteration complexity guarantee for solving the two classes of minimax problems

Neurophysiological features of STN LFP underlying sleep fragmentation in Parkinson’s disease

Background: Sleep fragmentation is a persistent problem throughout the course of Parkinson’s disease (PD). However, the related neurophysiological patterns and the underlying mechanisms remained unclear. Method: We recorded subthalamic nucleus (STN) local field potentials (LFPs) using deep brain stimulation (DBS) with real-time wireless recording capacity from 13 patients with PD undergoing a one-night polysomnography recording, 1 month after DBS surgery before initial programming and when the patients were off-medication. The STN LFP features that characterised different sleep stages, correlated with arousal and sleep fragmentation index, and preceded stage transitions during N2 and REM sleep were analysed. Results: Both beta and low gamma oscillations in non-rapid eye movement (NREM) sleep increased with the severity of sleep disturbance (arousal index (ArI)-betaNREM: r=0.9, p=0.0001, sleep fragmentation index (SFI)-betaNREM: r=0.6, p=0.0301; SFI-gammaNREM: r=0.6, p=0.0324). We next examined the low-to-high power ratio (LHPR), which was the power ratio of theta oscillations to beta and low gamma oscillations, and found it to be an indicator of sleep fragmentation (ArI-LHPRNREM: r=−0.8, p=0.0053; ArI-LHPRREM: r=−0.6, p=0.0373; SFI-LHPRNREM: r=−0.7, p=0.0204; SFI-LHPRREM: r=−0.6, p=0.0428). In addition, long beta bursts (>0.25 s) during NREM stage 2 were found preceding the completion of transition to stages with more cortical activities (towards Wake/N1/REM compared with towards N3 (p<0.01)) and negatively correlated with STN spindles, which were detected in STN LFPs with peak frequency distinguishable from long beta bursts (STN spindle: 11.5 Hz, STN long beta bursts: 23.8 Hz), in occupation during NREM sleep (β=−0.24, p<0.001). Conclusion: Features of STN LFPs help explain neurophysiological mechanisms underlying sleep fragmentations in PD, which can inform new intervention for sleep dysfunction. Trial registration number: NCT02937727

Classification for Single-Trial N170 During Responding to Facial Picture With Emotion

Whether an event-related potential (ERP), N170, related to facial recognition was modulated by emotion has always been a controversial issue. Some researchers considered the N170 to be independent of emotion, whereas a recent study has shown the opposite view. In the current study, electroencephalogram (EEG) recordings while responding to facial pictures with emotion were utilized to investigate whether the N170 was modulated by emotion. We found that there was a significant difference between ERP trials with positive and negative emotions of around 170 ms at the occipitotemporal electrodes (i.e., N170). Then, we further proposed the application of the single-trial N170 as a feature for the classification of facial emotion, which could avoid the fact that ERPs were obtained by averaging most of the time while ignoring the trial-to-trial variation. In order to find an optimal classifier for emotional classification with single-trial N170 as a feature, three types of classifiers, namely, linear discriminant analysis (LDA), L1-regularized logistic regression (L1LR), and support vector machine with radial basis function (RBF-SVM), were comparatively investigated. The results showed that the single-trial N170 could be used as a classification feature to successfully distinguish positive emotion from negative emotion. L1-regularized logistic regression classifiers showed a good generalization, whereas LDA showed a relatively poor generalization. Moreover, when compared with L1LR, the RBF-SVM required more time to optimize the parameters during the classification, which became an obstacle while applying it to the online operating system of brain-computer interfaces (BCIs). The findings suggested that face-related N170 could be affected by facial expression and that the single-trial N170 could be a biomarker used to monitor the emotional states of subjects for the BCI domain

Pro-inflammatory miR-223 mediates the cross-talk between the IL23 pathway and the intestinal barrier in inflammatory bowel disease

Genes that showed greater than four-fold upregulation in IBD. (XLSX 28 kb

Effects of electroacupuncture on the correlation between serum and central immunity in AD model animals

Objective. The goal was to investigate the connection between neuroinflammation in the brain and serum inflammatory markers as Alzheimer's disease progressed. We also sought to determine whether electroacupuncture had an effect on inflammatory markers found in blood and other brain regions. Methods. As an animal model for AD, we used senescence-accelerated mouse prone 8 (SAMP8) mice. To examine the effects and probable mechanism of electroacupuncture, we used HE staining, immunofluorescence staining, western blotting, and enzyme-linked immunosorbent assay. Results. Electroacupuncture therapy protected neurons, significantly downregulated the Iba-1 level in the hippocampus (p value was 0.003), frontal lobe cortex (p value was 0.042), and temporal lobe cortex (p value was 0.013) of the AD animal model, all of which had significantly lower levels of IL-6 (p value was 0.001), IL-1β (p value was 0.001), and TNF-α (p value was 0.001) in their serum. Conclusion. The amounts of IL-6, IL-1β, and TNF-α detected in the serum were strongly linked to the levels discovered in the hippocampus and the frontal lobes of the brain, respectively. A better understanding of the electroacupuncture process as well as the course of Alzheimer's disease and the therapeutic benefits of electroacupuncture may be gained by using biomarkers such as serum inflammatory marker biomarkers

Elevated expression of CDK4 in lung cancer

<p/> <p>Background</p> <p>The aim of the present study was to analyze the expression of Cyclin-dependent kinase 4 (<it>CDK4</it>) in lung cancer and its correlation with clinicopathologic features. Furthermore, the involvement of <it>CDK4</it>-mediated cell cycle progression and its molecular basis were investigated in the pathogenesis of lung cancer.</p> <p>Methods</p> <p>Using immunohistochemistry analysis, we analyzed <it>CDK4 </it>protein expression in 89 clinicopathologically characterized lung cancer patients (59 males and 30 females) with ages ranging from 36 to 78 years and compared them to 23 normal lung tissues. Cases with cytoplasmic and nuclear <it>CDK4 </it>immunostaining score values greater than or equal to 7 were regarded as high expression while scores less than 7 were considered low expression. The correlation between the expression level of <it>CDK4 </it>and clinical features was analyzed. Furthermore, we used lentiviral-mediated shRNA to suppress the expression of CDK4 and investigate its function and molecular mechanism for mediating cell cycle progression.</p> <p>Results</p> <p>The expression level of <it>CDK4 </it>protein was significantly increased in lung cancer tissues compared to normal tissues (<it>P </it>< 0.001). In addition, high levels of <it>CDK4 </it>protein were positively correlated with the status of pathology classification (<it>P </it>= 0.047), lymph node metastasis (<it>P </it>= 0.007), and clinical stage (<it>P </it>= 0.004) of lung cancer patients. Patients with higher <it>CDK4 </it>expression had a markedly shorter overall survival time than patients with low <it>CDK4 </it>expression. Multivariate analysis suggested the level of <it>CDK4 </it>expression was an independent prognostic indicator (<it>P </it>< 0.001) for the survival of patients with lung cancer. Use of lentiviral-mediated shRNA to inhibit the expression of <it>CDK4 </it>in lung cancer cell line A549 not only inhibited cell cycle progression, but also dramatically suppressed cell proliferation, colony formation, and migration. Furthermore, suppressing <it>CDK4 </it>expression also significantly elevated the expression of cell cycle regulator <it>p21</it></p> <p>Conclusion</p> <p>Overexpressed <it>CDK4 </it>is a potential unfavorable prognostic factor and mediates cell cycle progression by regulating the expression of <it>p21 </it>in lung cancer</p

CHIP promotes Runx2 degradation and negatively regulates osteoblast differentiation

Runx2, an essential transactivator for osteoblast differentiation, is tightly regulated at both the transcriptional and posttranslational levels. In this paper, we report that CHIP (C terminus of Hsc70-interacting protein)/STUB1 regulates Runx2 protein stability via a ubiquitination-degradation mechanism. CHIP interacts with Runx2 in vitro and in vivo. In the presence of increased Runx2 protein levels, CHIP expression decreases, whereas the expression of other E3 ligases involved in Runx2 degradation, such as Smurf1 or WWP1, remains constant or increases during osteoblast differentiation. Depletion of CHIP results in the stabilization of Runx2, enhances Runx2-mediated transcriptional activation, and promotes osteoblast differentiation in primary calvarial cells. In contrast, CHIP overexpression in preosteoblasts causes Runx2 degradation, inhibits osteoblast differentiation, and instead enhances adipogenesis. Our data suggest that negative regulation of the Runx2 protein by CHIP is critical in the commitment of precursor cells to differentiate into the osteoblast lineage

Amygdala connectivity related to subsequent stress responses during the COVID-19 outbreak

Introduction: The amygdala plays an important role in stress responses and stress-related psychiatric disorders. It is possible that amygdala connectivity may be a neurobiological vulnerability marker for stress responses or stress-related psychiatric disorders and will be useful to precisely identify the vulnerable individuals before stress happens. However, little is known about the relationship between amygdala connectivity and subsequent stress responses. The current study investigated whether amygdala connectivity measured before experiencing stress is a predisposing neural feature of subsequent stress responses while individuals face an emergent and unexpected event like the COVID-19 outbreak. Methods: Data collected before the COVID-19 pandemic from an established fMRI cohort who lived in the pandemic center in China (Hubei) during the COVID-19 outbreak were used to investigate the relationship between amygdala connectivity and stress responses during and after the pandemic in 2020. The amygdala connectivity was measured with resting-state functional connectivity (rsFC) and effective connectivity. Results: We found the rsFC of the right amygdala with the dorsomedial prefrontal cortex (dmPFC) was negatively correlated with the stress responses at the first survey during the COVID-19 outbreak, and the rsFC between the right amygdala and bilateral superior frontal gyri (partially overlapped with the dmPFC) was correlated with SBSC at the second survey. Dynamic causal modeling suggested that the self-connection of the right amygdala was negatively correlated with stress responses during the pandemic. Discussion: Our findings expand our understanding about the role of amygdala in stress responses and stress-related psychiatric disorders and suggest that amygdala connectivity is a predisposing neural feature of subsequent stress responses

Critical Role of Activating Transcription Factor 4 in the Anabolic Actions of Parathyroid Hormone in Bone

Parathyroid hormone (PTH) is a potent anabolic agent for the treatment of osteoporosis. However, its mechanism of action in osteoblast and bone is not well understood. In this study, we show that the anabolic actions of PTH in bone are severely impaired in both growing and adult ovariectomized mice lacking bone-related activating transcription factor 4 (ATF4). Our study demonstrates that ATF4 deficiency suppresses PTH-stimulated osteoblast proliferation and survival and abolishes PTH-induced osteoblast differentiation, which, together, compromise the anabolic response. We further demonstrate that the PTH-dependent increase in osteoblast differentiation is correlated with ATF4-dependent up-regulation of Osterix. This regulation involves interactions of ATF4 with a specific enhancer sequence in the Osterix promoter. Furthermore, actions of PTH on Osterix require this same element and are associated with increased binding of ATF4 to chromatin. Taken together these experiments establish a fundamental role for ATF4 in the anabolic actions of PTH on the skeleton