Endogenous mutant Huntingtin alters the corticogenesis via lowering Golgi recruiting ARF1 in cortical organoid.

Pathogenic mutant huntingtin (mHTT) infiltrates the adult Huntington's disease (HD) brain and impairs fetal corticogenesis. However, most HD animal models rarely recapitulate neuroanatomical alterations in adult HD and developing brains. Thus, the human cortical organoid (hCO) is an alternative approach to decode mHTT pathogenesis precisely during human corticogenesis. Here, we replicated the altered corticogenesis in the HD fetal brain using HD patient-derived hCOs. Our HD-hCOs had pathological phenotypes, including deficient junctional complexes in the neural tubes, delayed postmitotic neuronal maturation, dysregulated fate specification of cortical neuron subtypes, and abnormalities in early HD subcortical projections during corticogenesis, revealing a causal link between impaired progenitor cells and chaotic cortical neuronal layering in the HD brain. We identified novel long, oriented, and enriched polyQ assemblies of HTTs that hold large flat Golgi stacks and scaffold clathrin+ vesicles in the neural tubes of hCOs. Flat Golgi stacks conjugated polyQ assemblies by ADP-ribosylation factor 1 (ARF1). Inhibiting ARF1 activation with Brefeldin A (BFA) disassociated polyQ assemblies from Golgi. PolyQ assembles with mHTT scaffolded fewer ARF1 and formed shorter polyQ assembles with fewer and shorter Golgi and clathrin vesicles in neural tubes of HD-hCOs compared with those in hCOs. Inhibiting the activation of ARF1 by BFA in healthy hCOs replicated impaired junctional complexes in the neural tubes. Together, endogenous polyQ assemblies with mHTT reduced the Golgi recruiting ARF1 in the neuroepithelium, impaired the Golgi structure and activities, and altered the corticogenesis in HD-hCO.

IDO-1 inhibitor INCB24360 elicits distant metastasis of basal extruded cancer cells in pancreatic ductal adenocarcinoma.

Neoplastic cells of non-immunogenic pancreatic ductal adenocarcinoma (PDAC) express indoleamine 2,3-dioxygenase 1 (IDO-1), an immunosuppressive enzyme. The metabolites of IDO-1 in cancers provide one-carbon units that annihilate effector T cells, and recruit immunosuppressive cells. In this study we investigated how IDO-1 affected the neoplastic cell behaviors in PDACs. Using multiple markers co-labeling method in 45-µm-thick tissue sections, we showed that IDO-1 expression was uniquely increased in the neoplastic cells extruded from ducts' apical or basal domain, but decreased in lymph metastatic cells. IDO-1+ extruding neoplastic cells displayed increased vimentin expression and decreased cytokeratin expression in PDACs, characteristics of epithelial-mesenchymal transition (EMT). However, IDO-1 expression was uncorrelated with immunosuppressive infiltrates and clinicopathological characteristics of grim outcome. We replicated basal extrusion with EMT in murine KPIC PDAC organoids by long-term IFN-γ induction; application of IDO-1 inhibitor INCB24360 or 1-MT partially reversed basal extrusion coupled EMT. Ido-1 deletion in KPIC cells deprived its tumorigenicity in immunocompetent mice, decreased cellular proliferation and macropinocytic ability, and increased immunogenicity. KPIC organoids with IFN-γ-induced basal extrusion did not accelerate distant metastasis, whereas inhibition IFN-γ-induced IDO-1 with INB24360 but not 1-MT in KPIC organoids elicited liver metastasis of subcutaneous KPIC organoid tumors, suggesting that lower IDO-1 activity accelerated distant metastasis, whereas IDO-1 was indispensable for tumorigenicity of PDAC cells and supports the survival of extruding cells.

A Secure and Efficient Data Sharing and Searching Scheme in Wireless Sensor Networks.

Wireless sensor networks (WSN) generally utilize cloud computing to store and process sensing data in real time, namely, cloud-assisted WSN. However, the cloud-assisted WSN faces new security challenges, particularly outsourced data confidentiality. Data Encryption is a fundamental approach but it limits target data retrieval in massive encrypted data. Public key encryption with keyword search (PEKS) enables a data receiver to retrieve encrypted data containing some specific keyword in cloud-assisted WSN. However, the traditional PEKS schemes suffer from an inherent problem, namely, the keyword guessing attack (KGA). KGA includes off-line KGA and on-line KGA. To date, the existing literature on PEKS cannot simultaneously resist both off-line KGA and on-line KGA performed by an external adversary and an internal adversary. In this work, we propose a secure and efficient data sharing and searching scheme to address the aforementioned problem such that our scheme is secure against both off-line KGA and on-line KGA performed by external and internal adversaries. We would like to stress that our scheme simultaneously achieves document encryption/decryption and keyword search functions. We also prove our scheme achieves keyword security and document security. Furthermore, our scheme is more efficient than previous schemes by eliminating the pairing computation.

Construction of a pancreatic cancer nerve invasion system using brain and pancreatic cancer organoids.

Pancreatic cancer (PC) is a fatal malignancy in the human abdominal cavity that prefers to invade the surrounding nerve/nerve plexus and even the spine, causing devastating and unbearable pain. The limitation of available in vitro models restricts revealing the molecular mechanism of pain and screening pain-relieving strategies to improve the quality of life of end-stage PC patients. Here, we report a PC nerve invasion model that merged human brain organoids (hBrO) with mouse PC organoids (mPCO). After merging hBrOs with mPCOs, we monitored the structural crosstalk, growth patterns, and mutual interaction dynamics of hBrO with mPCOs for 7 days. After 7 days, we also analyzed the pathophysiological statuses, including proliferation, apoptosis and inflammation. The results showed that mPCOs tend to approximate and intrude into the hBrOs, merge entirely into the hBrOs, and induce the retraction/shrinking of neuronal projections that protrude from the margin of the hBrOs. The approximating of mPCOs to hBrOs accelerated the proliferation of neuronal progenitor cells, intensified the apoptosis of neurons in the hBrOs, and increased the expression of inflammatory molecules in hBrOs, including NLRP3, IL-8, and IL-1ß. Our system pathophysiologically replicated the nerve invasions in mouse GEMM (genetically engineered mouse model) primary and human PCs and might have the potential to be applied to reveal the molecular mechanism of nerve invasion and screen therapeutic strategies in PCs.

An Improved Double Channel Long Short-Term Memory Model for Medical Text Classification.

There are a large number of symptom consultation texts in medical and healthcare Internet communities, and Chinese health segmentation is more complex, which leads to the low accuracy of the existing algorithms for medical text classification. The deep learning model has advantages in extracting abstract features of text effectively. However, for a large number of samples of complex text data, especially for words with ambiguous meanings in the field of Chinese medical diagnosis, the word-level neural network model is insufficient. Therefore, in order to solve the triage and precise treatment of patients, we present an improved Double Channel (DC) mechanism as a significant enhancement to Long Short-Term Memory (LSTM). In this DC mechanism, two channels are used to receive word-level and char-level embedding, respectively, at the same time. Hybrid attention is proposed to combine the current time output with the current time unit state and then using attention to calculate the weight. By calculating the probability distribution of each timestep input data weight, the weight score is obtained, and then weighted summation is performed. At last, the data input by each timestep is subjected to trade-off learning to improve the generalization ability of the model learning. Moreover, we conduct an extensive performance evaluation on two different datasets: cMedQA and Sentiment140. The experimental results show that the DC-LSTM model proposed in this paper has significantly superior accuracy and ROC compared with the basic CNN-LSTM model.

Comparison between a Passive and Active response task and their effect on the Amplitude and Latency of the P300 component for Visual Stimuli while using Low Fidelity Equipment.

In this paper, we investigate the effect, in terms of amplitude and latency, of the P300 component in a separate active and passive task response condition. This work is based on the P300 speller BCI (oddball) paradigm and the xDAWN algorithm, with five healthy subjects; while using a noninvasive Brain-Computer Interface (BCI) based on low fidelity electroencephalographic (EEG) equipment. Our results suggest that an active task yielded a larger P300 peak amplitude while there was no discriminable difference in the peak latency. The signal was also morphological consistent in both scenarios, even though they did not yield identical P300 components. This groundwork yields imperative data for future work where we plan to introduce several distractions, including communication with the user while performing the P300 speller paradigm.