Multidimensional Uncertainty-Aware Evidential Neural Networks

Traditional deep neural networks (NNs) have significantly contributed to the state-of-the-art performance in the task of classification under various application domains. However, NNs have not considered inherent uncertainty in data associated with the class probabilities where misclassification under uncertainty may easily introduce high risk in decision making in real-world contexts (e.g., misclassification of objects in roads leads to serious accidents). Unlike Bayesian NN that indirectly infer uncertainty through weight uncertainties, evidential NNs (ENNs) have been recently proposed to explicitly model the uncertainty of class probabilities and use them for classification tasks. An ENN offers the formulation of the predictions of NNs as subjective opinions and learns the function by collecting an amount of evidence that can form the subjective opinions by a deterministic NN from data. However, the ENN is trained as a black box without explicitly considering inherent uncertainty in data with their different root causes, such as vacuity (i.e., uncertainty due to a lack of evidence) or dissonance (i.e., uncertainty due to conflicting evidence). By considering the multidimensional uncertainty, we proposed a novel uncertainty-aware evidential NN called WGAN-ENN (WENN) for solving an out-of-distribution (OOD) detection problem. We took a hybrid approach that combines Wasserstein Generative Adversarial Network (WGAN) with ENNs to jointly train a model with prior knowledge of a certain class, which has high vacuity for OOD samples. Via extensive empirical experiments based on both synthetic and real-world datasets, we demonstrated that the estimation of uncertainty by WENN can significantly help distinguish OOD samples from boundary samples. WENN outperformed in OOD detection when compared with other competitive counterparts.Comment: AAAI 202

Multi-Phase Cross-modal Learning for Noninvasive Gene Mutation Prediction in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the fourth most common cause of cancer-related death worldwide. Understanding the underlying gene mutations in HCC provides great prognostic value for treatment planning and targeted therapy. Radiogenomics has revealed an association between non-invasive imaging features and molecular genomics. However, imaging feature identification is laborious and error-prone. In this paper, we propose an end-to-end deep learning framework for mutation prediction in APOB, COL11A1 and ATRX genes using multiphasic CT scans. Considering intra-tumour heterogeneity (ITH) in HCC, multi-region sampling technology is implemented to generate the dataset for experiments. Experimental results demonstrate the effectiveness of the proposed model.Comment: Accepted version to be published in the 42nd IEEE Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2020, Montreal, Canad

Comprehensive succinylome analyses reveal that hyperthermia upregulates lysine succinylation of annexin A2 by downregulating sirtuin7 in human keratinocytes

Background and Objectives: Local hyperthermia at 44°C can clear multiple human papillomavirus (HPV)-infected skin lesions (warts) by targeting a single lesion, which is considered as a success of inducing antiviral immunity in the human body. However, approximately 30% of the patients had a lower response to this intervention. To identify novel molecular targets for anti-HPV immunity induction to improve local hyperthermia efficacy, we conducted a lysine succinylome assay in HaCaT cells (subjected to 44°C and 37°C water baths for 30 min). Methods: The succinylome analysis was conducted on HaCaT subjected to 44°C and 37°C water bath for 30 min using antibody affinity enrichment together with liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results were validated by western blot (WB), immunoprecipitation (IP), and co-immunoprecipitation (Co-IP). Then, bioinformatic analysis including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, motif characterization, secondary structure, and protein–protein interaction (PPI) was performed. Results: A total of 119 proteins with 197 succinylated sites were upregulated in 44°C-treated HaCaT cells. GO annotation demonstrated that differential proteins were involved in the immune system process and viral transcription. Succinylation was significantly upregulated in annexin A2. We found that hyperthermia upregulated the succinylated level of global proteins in HaCaT cells by downregulating the desuccinylase sirtuin7 (SIRT7), which can interact with annexin A2. Conclusions: Taken together, these data indicated that succinylation of annexin A2 may serve as a new drug target, which could be intervened in combination with local hyperthermia for better treatment of cutaneous warts

The efficacy and neural mechanism of acupuncture therapy in the treatment of visceral hypersensitivity in irritable bowel syndrome

Irritable Bowel Syndrome (IBS) is a complex functional gastrointestinal disorder primarily characterized by chronic abdominal pain, bloating, and altered bowel habits. Chronic abdominal pain caused by visceral Hypersensitivity (VH) is the main reason why patients with IBS seek medication. Significant research effort has been devoted to the efficacy of acupuncture as a non-drug alternative therapy for visceral-hyperalgesia-induced IBS. Herein, we examined the central and peripheral analgesic mechanisms of acupuncture in IBS treatment. Acupuncture can improve inflammation and relieve pain by reducing 5-hydroxytryptamine and 5-HT3A receptor expression and increasing 5-HT4 receptor expression in peripheral intestinal sensory endings. Moreover, acupuncture can also activate the transient receptor potential vanillin 1 channel, block the activity of intestinal glial cells, and reduce the secretion of local pain-related neurotransmitters, thereby weakening peripheral sensitization. Moreover, by inhibiting the activation of N-methyl-D-aspartate receptor ion channels in the dorsal horn of the spinal cord and anterior cingulate cortex or releasing opioids, acupuncture can block excessive stimulation of abnormal pain signals in the brain and spinal cord. It can also stimulate glial cells (through the P2X7 and prokinetic protein pathways) to block VH pain perception and cognition. Furthermore, acupuncture can regulate the emotional components of IBS by targeting hypothalamic-pituitary-adrenal axis-related hormones and neurotransmitters via relevant brain nuclei, hence improving the IBS-induced VH response. These findings provide a scientific basis for acupuncture as an effective clinical adjuvant therapy for IBS pain

ULK1/2 Constitute a Bifurcate Node Controlling Glucose Metabolic Fluxes in Addition to Autophagy

揭示了在外界能量供应缺乏时，细胞通过激活ULK1来介导葡萄糖分解代谢重编程以维持胞内的能量与氧化还原稳态的详细机制，并创新地发现了ULK1独立于自噬的关键功能。基于自噬和糖代谢与人类健康的重要相关性，该研究将很可能为我们预防和治疗各类代谢疾病提供新的思路和药物靶点。Metabolic reprogramming is fundamental to biological homeostasis, enabling cells to adjust metabolic routes after sensing altered availability of fuels and growth factors. ULK1 and ULK2 represent key integrators that relay metabolic stress signals to the autophagy machinery. Here, we demonstrate that, during deprivation of amino acid and growth factors, ULK1/2 directly phosphorylate key glycolytic enzymes including hexokinase (HK), phosphofructokinase 1 (PFK1), enolase 1 (ENO1), and the gluconeogenic enzyme fructose-1,6-bisphosphatase (FBP1). Phosphorylation of these enzymes leads to enhanced HK activity to sustain glucose uptake but reduced activity of FBP1 to block the gluconeogenic route and reduced activity of PFK1 and ENO1 to moderate drop of glucose-6-phosphate and to repartition more carbon flux to pentose phosphate pathway (PPP), maintaining cellular energy and redox homeostasis at cellular and organismal levels. These results identify ULK1/2 as a bifurcate-signaling node that sustains glucose metabolic fluxes besides initiation of autophagy in response to nutritional deprivation.State Key Program of National Natural Science of China， the 973 Program；National Natural Science Foundation of China for Fostering Talents in Basic Research ；the Foundation for Innovative Research Groups of the National Natural Science Foundation of China； and the 111 Project of Education of China

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Application of fast laser deprocessing techniques in the field of semiconductor manufacturing

With technology scaling of semiconductor devices and further growth of the integrated circuit (IC) design and function complexity, it is necessary to increase the number of transistors in IC chip, layer stack, and process steps. The last few metal layers of Back End Of Line (BEOL) are usually very thick metal lines (>4µm thickness) and protected with hard Silicon Dioxide (SiO2) material that is formed from (Tetra Ethyl Ortho Silicate) TEOS as Inter-Metal Dielectric (IMD). In order to perform physical failure analysis (PFA) on the logic or memory, the top thick metal layers must be removed. It is time consuming to deprocess those thick metal layers and thick IMD layers. In this project, Fast Laser Deprocessing Technique (FLDT) is proposed to remove the BEOL thick and stubborn metal layers for memory PFA. The proposed FLDT is a cost-effective and quick way to deprocess a sample for defect identification in PFA. Besides application on top down layer deprocessing, this project also further explores on cross sectional sample preparation. Cross-sectional analysis is one of the important areas for physical failure analysis. Focus Ion Beam (FIB) and mechanical polish sample preparation are commonly used and necessary techniques in the semiconductor industry and FA company. However, each technique has its own limitation. Mechanical polishing technique easily induces artifact by mechanical force, especially on advance technology node. FIB can eliminate mechanically damaged artifact, but have the limitation on cross-sectional view area. Another potential technique will be plasma FIB, it used very high milling current and fast milling speed. However, it comes with a very high cost and having the contamination issue. The contamination issue greatly affects the low kV Scanning Electron Microscopy (SEM) imaging quality. In recent semiconductor industry FA, low kV SEM imaging is preferable, because high kV imaging will be introduced delamination artifact especially on organic material from packaged sample. In third part of this project, Fast Laser Deprocessing Techniques (FLDT) application is further enhanced on large area cross-sectional FA with fast cycle time and low-cost equipment. This is to prevent on mechanical damaged. In short, the proposed FLDT is a cost-effective and quick way to deprocess a sample for defect identification in cross-sectional FA.Bachelor of Engineerin