TNFα-mediated subtype switch and tumor progression in pancreatic cancer

Pancreatic cancer (PDAC) represents an extremely poor clinical outcome with a 5-year survival rate of <9%. It is anticipated to become the second leading cause of cancer-related deaths in the industrialized countries by 2030. A vast majority of PDAC patients exhibit locally advanced or distant metastases at the time of diagnosis, which makes surgical resection challenging. The complex molecular heterogeneity within neoplastic-epithelium and stromal cells profoundly attributes to this poor prognosis, and makes therapy challenging. Extensive whole genome sequencing and transcriptional profiling of PDAC biopsies identified the two most clinically relevant and molecularly distinct subtypes: the basal-like (BL) subtype displays highly aggressive phenotype, metastatic disease and chemoresistance profile in PDAC patients, whereas classical (CLA) subtype often responds to therapy and exhibits better prognosis. However, the coexisting stromal components (e.g. inflammatory macrophages and cancer-associated fibroblasts) within CLA or BL subtypes underlie distinct prognosis. Whether and how CLA or BL neoplastic cells shape the stromal microenvironment, and hence, determine PDAC aggressiveness and therapeutic vulnerabilities remain largely unresolved. Herein, we show that BL neoplastic cells recruit inflammatory macrophages, which foster highly inflamed and aggressive tumor phenotype in PDAC. We identified a mutually exclusive AP1-driven transcriptional program, which determines PDAC subtype identity and prognosis. CLA-restricted JUNB/AP1 is associated with less aggressive and chemoresponsive CLA tumors; conversely, BL-restricted cJUN/AP1 largely controls tumor invasiveness, chemoresistance and proinflammatory program. Mechanistically, cJUN controls CCL2 expression via enhancer-promoter regulation, which, in turn, facilitate recruitment of TNFα-producing macrophages in the PDAC microenvironment. Subsequently, TNFα switches PDAC subtype identity through converting CLA tumors into a highly aggressive BL phenotypic state by activating cJUN-CCL2 signaling axis, thus, forming a positive feed forward loop. Finally, we show that BRD4 regulates cJUN-transcription via enhancer-promoter interactions; hence, pharmacological inhibition of the BRD4-cJUN axis induces a favorable subtype switch and improves overall survival in preclinical models. This study provides compelling evidence that subtype-specific transcriptional program shapes the subtype identity, tumor aggressiveness and prognosis in PDAC. Thus, cJUNhigh/TNFαhigh subtype-specific precision therapy has the potential to overcome the highly aggressive and chemoresistant PDAC.2021-10-0

Enhancing plasma-catalytic toluene oxidation: Unraveling the role of Lewis-acid sites on δ-MnO2

The emission of volatile organic compounds (VOCs) into the air, primarily due to human activities, has caused significant environmental pollution and health concerns. In response, the development of advanced environmental catalysts is crucial, and δ-MnO2 has emerged as a promising material for efficient VOC oxidation. However, the identification of the specific active sites and the underlying oxidation mechanisms of this material remain unclear, hindering the development and optimization of high-activity catalysts. Herein, we present a strategy to remove the internal water and hydrated cations from δ-MnO2, thereby unblocking the inter-lamellar gaps and exposing the internal Lewis-acid sites, while maintaining other physical and chemical characteristics of the sample unchanged. Notably, the well-defined δ-MnO2 catalysts with more accessible interlayer Lewis-acid sites exhibited significantly enhanced catalytic activity in toluene oxidation, demonstrated in both two-stage plasma catalysis and single-stage ozonation processes. A quantitative analysis of Lewis-acid sites and initial toluene reaction rates revealed that these Lewis-acid sites serve as the active centers for toluene adsorption and activation, and the heterogeneous reaction between toluene and ozone follows the Langmuir-Hinshelwood mechanism. Moreover, in-depth analysis of byproducts showed that δ-MnO2 rich in Lewis-acid sites promoted the oxidation of intermediates, such as esters, hydrazides, and ketones, leading to a more complete toluene oxidation. This work not only fully explores the potential of δ-MnO2 as a catalyst, but also provides valuable insights into the elucidation of unknown catalytic active sites, potentially paving the way for the rational design of more efficient catalysts for VOC oxidation

Efficient position decoding methods based on fluorescence calcium imaging in the mouse hippocampus

Large-scale and long-term calcium imaging has widely been used for decoding positions from hippocampal place cells in rodents. Developing efficient neural decoding methods for reconstructing the animal's position in real or virtual environments based on calcium imaging can provide a real-time readout of spatial information in closed-loop neuroscience experiments. Spike deconvolution, a procedure to infer the underlying spike trains from calcium imaging data, presents computational challenges in the processing of calcium imaging data for subsequent decoding analysis and hinders the progress of real-time decoding. Here, we developed an efficient strategy to extract features from fluorescence calcium imaging traces that sidestepped the computationally slow spike deconvolution and further decoded animal's positions from these features. We validated our proposed decoding method in multiple in vivo calcium imaging recordings of the mouse hippocampus and simulated data, based on both supervised and unsupervised decoding analysis. We systematically investigated the decoding performance of our proposed method with respect to the number of neurons and signal-to-noise ratio. Our analysis pipeline is ultrafast and robust and therefore promising for online decoding of animal's positions in closed-loop calcium imaging experiments.Bachelor of Science in Physic

Learning enhancement by sleep : closed-loop potentiation of slow oscillations during NREM sleep

Why is sleep important? It is considered that sleep is crucial for memory consolidation by strengthening and integrating labile new memory traces into pre-existing memory networks. 1 Without this process, newly learned information would be susceptible to forgetting. Sleep is classified into two stages, rapid-eye-movement (REM) sleep and non-rapid-eye-movement (NREM) sleep, based on rhythmic activity of the brain. The 0.5 - 4 Hz waves or slow oscillations (SOs), a major characteristic of NREM sleep, are critical for memory consolidation. By enhancing SOshumans, memory was shown to be improved. 2 However, mechanisms underlying SO-dependent memory consolidation have remained unclear. [1st Award

Multi-Access Edge Computing (MEC) Based on MIMO: A Survey

With the rapid development of wireless communication technology and the emergence of intelligent applications, higher requirements have been put forward for data communication and computing capacity. Multi-access edge computing (MEC) can handle highly demanding applications by users by sinking the services and computing capabilities of the cloud to the edge of the cell. Meanwhile, the multiple input multiple output (MIMO) technology based on large-scale antenna arrays can achieve an order-of-magnitude improvement in system capacity. The introduction of MIMO into MEC takes full advantage of the energy and spectral efficiency of MIMO technology, providing a new computing paradigm for time-sensitive applications. In parallel, it can accommodate more users and cope with the inevitable trend of continuous data traffic explosion. In this paper, the state-of-the-art research status in this field is investigated, summarized and analyzed. Specifically, we first summarize a multi-base station cooperative mMIMO-MEC model that can easily be expanded to adapt to different MIMO-MEC application scenarios. Subsequently, we comprehensively analyze the current works, compare them to each other and summarize them, mainly from four aspects: research scenarios, application scenarios, evaluation indicators and research issues, and research algorithms. Finally, some open research challenges are identified and discussed, and these indicate the direction for future research on MIMO-MEC

Efficient position decoding methods based on fluorescence calcium imaging in the mouse hippocampus

Large-scale fluorescence calcium imaging methods have become widely adopted for studies of long-term hippocampal and cortical neuronal dynamics. Pyramidal neurons of the rodent hippocampus show spatial tuning in freely foraging or head-fixed navigation tasks. Development of efficient neural decoding methods for reconstructing the animal's position in real or virtual environments can provide a fast readout of spatial representations in closed-loop neuroscience experiments. Here, we develop an efficient strategy to extract features from fluorescence calcium imaging traces and further decode the animal's position. We validate our spike inference-free decoding methods in multiple in vivo calcium imaging recordings of the mouse hippocampus based on both supervised and unsupervised decoding analyses. We systematically investigate the decoding performance of our proposed methods with respect to the number of neurons, imaging frame rate, and signal-to-noise ratio. Our proposed supervised decoding analysis is ultrafast and robust, and thereby appealing for real-time position decoding applications based on calcium imaging.Published versio

Unlocking the Potential of Cu/TiCT MXene Catalyst in Plasma Catalytic CO2 Hydrogenation

Plasma catalytic CO2 hydrogenation has emerged as a promising approach for converting CO2 into valuable chemicals such as CO, offering a potential solution to mitigate greenhouse gas emissions. In this study, we investigate the synergistic effect between plasma and a Cu/Ti3C2Tx MXene catalyst for CO2 hydrogenation via the reverse water gas shift (RWGS) reaction in a dielectric barrier discharge (DBD) reactor. Our findings reveal a significant enhancement in CO2 conversion (33.1%) and CO yield (31.9%) when using the Cu/Ti3C2Tx catalyst compared to plasma alone or with a Ti3C2Tx foam. Plasma treatment creates unsaturated Ti sites on the Ti3C2Tx surface, dramatically improving CO2 adsorption and activation, while Cu nanoparticles significantly enhances the activation and dissociation of H2 molecules on the catalyst surface. These surface adsorbed hydrogen species readily hydrogenate adsorbed CO2 molecules through the Langmuir-Hinshelwood mechanism. Furthermore, these surface hydrogen species can also participate in the conversion of gas-phase CO2 molecules through the Eley-Rideal pathway. This work sheds light on the synergistic plasma catalytic mechanism and provide insights for optimizing CO2 hydrogenation processes using MXene catalysts