Deep Refinement-Based Joint Source Channel Coding over Time-Varying Channels

In recent developments, deep learning (DL)-based joint source-channel coding (JSCC) for wireless image transmission has made significant strides in performance enhancement. Nonetheless, the majority of existing DL-based JSCC methods are tailored for scenarios featuring stable channel conditions, notably a fixed signal-to-noise ratio (SNR). This specialization poses a limitation, as their performance tends to wane in practical scenarios marked by highly dynamic channels, given that a fixed SNR inadequately represents the dynamic nature of such channels. In response to this challenge, we introduce a novel solution, namely deep refinement-based JSCC (DRJSCC). This innovative method is designed to seamlessly adapt to channels exhibiting temporal variations. By leveraging instantaneous channel state information (CSI), we dynamically optimize the encoding strategy through re-encoding the channel symbols. This dynamic adjustment ensures that the encoding strategy consistently aligns with the varying channel conditions during the transmission process. Specifically, our approach begins with the division of encoded symbols into multiple blocks, which are transmitted progressively to the receiver. In the event of changing channel conditions, we propose a mechanism to re-encode the remaining blocks, allowing them to adapt to the current channel conditions. Experimental results show that the DRJSCC scheme achieves comparable performance to the other mainstream DL-based JSCC models in stable channel conditions, and also exhibits great robustness against time-varying channels

Seasonal coronavirus infections trigger NLRP3 inflammasome activation in macrophages but is therapeutically targetable

Seasonal coronaviruses widely circulate in the global population, and severe complications can occur in specific vulnerable populations. Little is known on their pathogenic mechanisms and no approved treatment is available. Here, we present anecdotal evidence that the level of IL-1β, a hallmark of inflammasome activation, appears elevated in a subset of seasonal coronavirus infected patients. We found that cultured human macrophages support the full life cycle of three cultivatable seasonal coronaviruses. Their infections effectively activate NLRP3 inflammasome activation through TLR4 ligation and NF-κB activation. This activation can be attenuated by specific pharmacological inhibitors and clinically used medications including dexamethasone and flufenamic acid. Interestingly, combination of antiviral and anti-inflammatory drugs simultaneously inhibit seasonal coronavirus-triggered inflammatory response and viral replication. Collectively, these findings show that the TLR4/NF-κB/NLRP3 axis drives seasonal coronavirus triggered-inflammatory response, which in turn represents a viable therapeutic target.</p

A Novel Fuzzy c -Means Clustering Algorithm Using Adaptive Norm

Abstract(#br)The fuzzy c -means (FCM) clustering algorithm is an unsupervised learning method that has been widely applied to cluster unlabeled data automatically instead of artificially, but is sensitive to noisy observations due to its inappropriate treatment of noise in the data. In this paper, a novel method considering noise intelligently based on the existing FCM approach, called adaptive-FCM and its extended version (adaptive-REFCM) in combination with relative entropy, are proposed. Adaptive-FCM, relying on an inventive integration of the adaptive norm, benefits from a robust overall structure. Adaptive-REFCM further integrates the properties of the relative entropy and normalized distance to preserve the global details of the dataset. Several experiments are carried out,..

Targeting PELP1 Attenuates Angiogenesis and Enhances Chemotherapy Efficiency in Colorectal Cancer

SIMPLE SUMMARY: Excessive angiogenesis is a distinct feature of colorectal cancer (CRC) and plays a pivotal role in tumor development and metastasis. Therefore, it is essential to clarify the underlying mechanism of angiogenesis. In this study, we found that the level of proline-, glutamic acid, and leucine-rich protein 1 (PELP1) was positively correlated with microvessel density (MVD). In vitro and in vivo assays further showed PELP1 regulated angiogenesis via the Signal transducer and activator of transcription 3 (STAT3)/Vascular endothelial growth factor (VEGFA). Notably, we found that inhibition of PELP1 enhanced the efficacy of chemotherapy due to vascular normalization. Thus, targeting of PELP1 may be a potentially therapeutic strategy for CRC. ABSTRACT: Abnormal angiogenesis is one of the important hallmarks of colorectal cancer as well as other solid tumors. Optimally, anti-angiogenesis therapy could restrain malignant angiogenesis to control tumor expansion. PELP1 is as a scaffolding oncogenic protein in a variety of cancer types, but its involvement in angiogenesis is unknown. In this study, PELP1 was found to be abnormally upregulated and highly coincidental with increased MVD in CRC. Further, treatment with conditioned medium (CM) from PELP1 knockdown CRC cells remarkably arrested the function of human umbilical vein endothelial cells (HUVECs) compared to those treated with CM from wildtype cells. Mechanistically, the STAT3/VEGFA axis was found to mediate PELP1-induced angiogenetic phenotypes of HUVECs. Moreover, suppression of PELP1 reduced tumor growth and angiogenesis in vivo accompanied by inactivation of STAT3/VEGFA pathway. Notably, in vivo, PELP1 suppression could enhance the efficacy of chemotherapy, which is caused by the normalization of vessels. Collectively, our findings provide a preclinical proof of concept that targeting PELP1 to decrease STAT3/VEGFA-mediated angiogenesis and improve responses to chemotherapy due to normalization of vessels. Given the newly defined contribution to angiogenesis of PELP1, targeting PELP1 may be a potentially ideal therapeutic strategy for CRC as well as other solid tumors

Ivermectin effectively inhibits hepatitis E virus replication, requiring the host nuclear transport protein importin α1

We show that ivermectin, an FDA-approved anti-parasitic drug, effectively inhibits infection with hepatitis E virus (HEV) genotypes 1 and 3 in a range of cell culture models, including hepatic and extrahepatic cells. Long-term treatment showed no clear evidence of the development of drug resistance. Gene silencing of importin-α1, a cellular target of ivermectin and a key member of the host nuclear transport complex, inhibited viral replication and largely abolished the anti-HEV effect of ivermectin.</p

Ivermectin effectively inhibits hepatitis E virus replication, requiring the host nuclear transport protein importin α1

We show that ivermectin, an FDA-approved anti-parasitic drug, effectively inhibits infection with hepatitis E virus (HEV) genotypes 1 and 3 in a range of cell culture models, including hepatic and extrahepatic cells. Long-term treatment showed no clear evidence of the development of drug resistance. Gene silencing of importin-α1, a cellular target of ivermectin and a key member of the host nuclear transport complex, inhibited viral replication and largely abolished the anti-HEV effect of ivermectin.</p

Tyrosine Phosphatase PTPRO Deficiency in ERBB2-Positive Breast Cancer Contributes to Poor Prognosis and Lapatinib Resistance

Despite the initial benefit from treating ERBB2-positive breast cancer with tyrosine kinase inhibitor lapatinib, resistance develops inevitably. Since the expression of protein tyrosine phosphatase receptor-type O (PTPRO), a member of the R3 subfamily of receptor protein tyrosine phosphatases (PTPs), is inversely correlated with the aggressiveness of multiple malignancies, we decided to explore the correlation between PTPRO and lapatinib resistance in ERBB2-positive breast cancer. Results of immunohistochemical (IHC) staining and the correlation analysis between the expression levels of PTPRO and the clinicopathological parameters indicate that PTPRO is downregulated in cancer tissues as compared with normal tissues and negatively associated with differentiation, tumor size, tumor depth, as well as the expression of ERBB2 and Ki67. Results from Kaplan–Meier analyses indicate that lower expression of PTPRO is correlated with shorter relapse-free survival for patients with ERBB2-positive breast cancer, and multivariable Cox regression analysis found that PTPRO can potentially serve as an independent prognostic indicator for ERBB2-positive breast cancer. Results from both human breast cancer cells with PTPRO knockdown or overexpression and mouse embryonic fibroblasts (MEFs) which derived from Ptpro ( +/+ ) and Ptpro ( −/− ) mice with then stably transfected plasmid FUGW-Erbb2 consistently demonstrated the essentiality of PTPRO in the lapatinib-mediated anticancer process. Our findings suggest that PTPRO is not only able to serve as an independent prognostic indicator, but upregulating PTPRO can also reverse the lapatinib resistance of ERBB2-positive breast cancer