The Combined Signatures of Hypoxia and Cellular Landscape Provides a Prognostic and Therapeutic Biomarker in HBV-Related Hepatocellular Carcinoma

Prognosis and treatment options of HBV-related hepatocellular carcinoma (HBV-HCC) are generally based on tumor burden and liver function. Yet, tumor growth and therapeutic resistance of HBV-HCC are strongly influenced by intratumoral hypoxia and cells infiltrating the tumor microenvironment (TME). We, therefore, studied whether linking parameters associated with hypoxia and TME cells could have a better prediction of prognosis and therapeutic responses. Quantification of 109 hypoxia-related genes and 64 TME cells was performed in 452 HBV-HCC tumors. Prognostic hypoxia and TME cells signatures were determined based on Cox regression and meta-analysis for generating the Hypoxia-TME classifier. Thereafter, the prognosis, tumor, and immune characteristics as well as the benefit of therapies in Hypoxia-TME defined subgroups were analyzed. Patients in the Hypoxialow /TMEhigh subgroup showed a better prognosis and therapeutic responses than any other subgroups, which can be well elucidated based on the differences in terms of immune-related molecules, tumor somatic mutations, and cancer cellular signaling pathways. Notably, our analysis furthermore demonstrated the synergistic influence of hypoxia and TME on tumor metabolism and proliferation. Besides, the classifier allowed a further subdivision of patients with early- and late-HCC stages. In addition, the Hypoxia-TME classifier was validated in another independent HBV-HCC cohort (n=144) and several pan-cancer cohorts. Overall, the Hypoxia-TME classifier showed a pretreatment predictive value for prognosis and therapeutic responses, which might provide new directions for strategizing patients with optimal therapies. This article is protected by copyright. All rights reserved

Automatic Implementation of Neural Networks through Reaction Networks -- Part I: Circuit Design and Convergence Analysis

Information processing relying on biochemical interactions in the cellular environment is essential for biological organisms. The implementation of molecular computational systems holds significant interest and potential in the fields of synthetic biology and molecular computation. This two-part article aims to introduce a programmable biochemical reaction network (BCRN) system endowed with mass action kinetics that realizes the fully connected neural network (FCNN) and has the potential to act automatically in vivo. In part I, the feedforward propagation computation, the backpropagation component, and all bridging processes of FCNN are ingeniously designed as specific BCRN modules based on their dynamics. This approach addresses a design gap in the biochemical assignment module and judgment termination module and provides a novel precise and robust realization of bi-molecular reactions for the learning process. Through equilibrium approaching, we demonstrate that the designed BCRN system achieves FCNN functionality with exponential convergence to target computational results, thereby enhancing the theoretical support for such work. Finally, the performance of this construction is further evaluated on two typical logic classification problems

Secure Multiuser Communications in Wireless Sensor Networks with TAS and Cooperative Jamming

In this paper, we investigate the secure transmission in wireless sensor networks (WSNs) consisting of one multiple-antenna base station (BS), multiple single-antenna legitimate users, one single-antenna eavesdropper and one multiple-antenna cooperative jammer. In an effort to reduce the scheduling complexity and extend the battery lifetime of the sensor nodes, the switch-and-stay combining (SSC) scheduling scheme is exploited over the sensor nodes. Meanwhile, transmit antenna selection (TAS) is employed at the BS and cooperative jamming (CJ) is adopted at the jammer node, aiming at achieving a satisfactory secrecy performance. Moreover, depending on whether the jammer node has the global channel state information (CSI) of both the legitimate channel and the eavesdropper's channel, it explores a zero-forcing beamforming (ZFB) scheme or a null-space artificial noise (NAN) scheme to confound the eavesdropper while avoiding the interference to the legitimate user. Building on this, we propose two novel hybrid secure transmission schemes, termed TAS-SSC-ZFB and TAS-SSC-NAN, for WSNs. We then derive the exact closed-form expressions for the secrecy outage probability and the effective secrecy throughput of both schemes to characterize the secrecy performance. Using these closed-form expressions, we further determine the optimal switching threshold and obtain the optimal power allocation factor between the BS and jammer node for both schemes to minimize the secrecy outage probability, while the optimal secrecy rate is decided to maximize the effective secrecy throughput for both schemes. Numerical results are provided to verify the theoretical analysis and illustrate the impact of key system parameters on the secrecy performance.This work was supported by the National Science Foundation of China (No. 61501507), and the Jiangsu Provincial Natural Science Foundation of China (No. BK20150719). The work of Nan Yang is supported by the Australian Research Council Discovery Project (DP150103905)

5-{(2S,3R,4S,5S,6R)-3,4-Dihydr­oxy-6-hydroxy­meth­yl-3-[(2S,3R,4R,5R,6S)-3,4,5-trihydr­oxy-6-methyl­tetra­hydro­pyran-2-yloxy]tetra­hydro­pyran-2-yloxy}­-7-hydr­oxy-2-(4-hydroxy­phen­yl)chromen-4-one monohydrate

In the title compound, C27H30O14·H2O, the hydroxy­phenyl ring makes a dihedral angle of 20.05 (11)° with the chromenone ring system. The crystal structure is stabilized by intra- and inter­molecular O—H⋯O hydrogen bonds. The absolute configuration was assigned on the basis of an analagous structure

Adsorption equilibrium, isotherm, kinetics, and thermodynamic of modified bentonite for removing Rhodamine B

Anionic and cationic surfactant modified sodium bentonite (Na-Bt) has been prepared by the cationic surfactant cetyltrimethyl ammonium bromide (CTAB) and the anionic surfactant sodium dodecyl benzene sulfonate (SDBS) to sodium bentonite, respectively. The properties of the modified samples are characterized by XRD, SEM, BET and FT-IR. The results of characterization shown that the cationic surfactant had changed the structure and properties of natural sodium bentonite, which proved that surfactants had been successfully implanted into sodium bentonite. But anionic surfactant had no change, this manifested SDBS didn’t insert the layers of bentonite. In addition, adsorption experiments of Rhodamine B (RhB) proved that the modified sodium bentonite adsorption performance is greatly improved. The adsorption experiments also indicated that CTAB-bentonite had the largest adsorption capacity compared with SDBS-bentonite due to the formation of a highly effective partition medium by cationic surfactant micelle. The adsorption data of RhB is analyzed with the isothermal model, thermodynamics and kinetics. Overall, this study provided high-efficiency method for the removal RhB by the surfactant modified bentonite

Multiple epigenetic modification profiles reveal the tumor immune microenvironment and clinical outcomes of uveal melanoma

Uveal melanoma (UM) is an aggressive intraocular cancer that, in 50% of cases, spreads to the patient’s other systems. The exact cause of the increased metastatic rate is still unknown. Methylation and immune response, metastasis, and the expansion of cancer cells are closely related. Additionally, proteins linked to RNA methylation have come to light as possible cancer treatment targets. However, the relationship between methylation-related genes (MRGs) and the tumor microenvironment (TME) is still not understood. The goal of this work was to discover important MRGs and create a signature for UM patients’ prognosis prediction. Using two different data sets, we examined the MRG expression patterns in the transcriptional and genomic regions of 106 UM samples. We discovered a connection between the clinicopathological traits of the patients, their prognosis, the capability of TME cells to infiltrate, and various MRG changes. Following that, we developed an MRGs signature to forecast prognosis, and we evaluated the model’s precision in patients with UM. We grouped the patients into multiple categories based on their clinical traits, looked at the survival rates for various groups within various groupings, and tested their accuracy. Additionally, to increase the practical usability of the MRGs model, we created a very accurate nomogram. TIDE scores were higher in the low-risk group. We go over how MGRs could impact UM’s TME, immunotherapy responsiveness, prognosis, and clinically significant features. We looked for different chemotherapeutic drugs and cutting-edge targeted agents for patients in diverse subgroups in order to better understand MRGs in UM. This helped in the creation of customized therapy to open new doors. We could also further research the prognosis and develop more efficient immunotherapy regimens

Adsorption equilibrium, isotherm, kinetics, and thermodynamic of modified bentonite for removing Rhodamine B

116-125Anionic and cationic surfactant modified sodium bentonite (Na-Bt) has been prepared by the cationic surfactant cetyltrimethyl ammonium bromide (CTAB) and the anionic surfactant sodium dodecyl benzene sulfonate (SDBS) to sodium bentonite, respectively. The properties of the modified samples are characterized by XRD, SEM, BET and FT-IR. The results of characterization shown that the cationic surfactant had changed the structure and properties of natural sodium bentonite, which proved that surfactants had been successfully implanted into sodium bentonite. But anionic surfactant had no change, this manifested SDBS didn’t insert the layers of bentonite. In addition, adsorption experiments of Rhodamine B (RhB) proved that the modified sodium bentonite adsorption performance is greatly improved. The adsorption experiments also indicated that CTAB-bentonite had the largest adsorption capacity compared with SDBS-bentonite due to the formation of a highly effective partition medium by cationic surfactant micelle. The adsorption data of RhB is analyzed with the isothermal model, thermodynamics and kinetics. Overall, this study provided high-efficiency method for the removal RhB by the surfactant modified bentonite

Strategies for Constructing College Students' Entrepreneurial Value Judgments Based on Educational Psychology

Against the background of economic globalization, the strategies for constructing college students' entrepreneurial value judgment are explored, providing college graduates with more employment options and thereby keeping up with the trend of the times. The documentary analysis and questionnaire survey methods are adopted to investigate contemporary college students' entrepreneurial value judgments, and the investigation results are organized. According to documentary materials, the discovered problems are analyzed to put forward strategies for constructing college students' entrepreneurial value judgments based on educational psychology. Results show that only 14.1% of college graduates choose to start a business; 48.7% do not understand or recognize the entrepreneurial values; 14.8% believe teaching activities on constructing entrepreneurial value judgments are insufficient, and the entrepreneurial atmosphere is lacking. Regarding the above investigation results, strategies for constructing college students' entrepreneurial value judgments are proposed, involving the construction environment, construction system, construction method, and construction mechanism. Hence, considering contemporary college students' entrepreneurial values, the proposed strategies for constructing college students' entrepreneurial judgments are suitable and valuable, providing a practical reference for enriching and perfecting the college innovation and entrepreneurship education systems

Integrative single-cell transcriptomic investigation unveils long non-coding RNAs associated with localized cellular inflammation in psoriasis

Psoriasis is a complex, chronic autoimmune disorder predominantly affecting the skin. Accumulating evidence underscores the critical role of localized cellular inflammation in the development and persistence of psoriatic skin lesions, involving cell types such as keratinocytes, mesenchymal cells, and Schwann cells. However, the underlying mechanisms remain largely unexplored. Long non-coding RNAs (lncRNAs), known to regulate gene expression across various cellular processes, have been particularly implicated in immune regulation. We utilized our neural-network learning pipeline to integrate 106,675 cells from healthy human skin and 79,887 cells from psoriatic human skin. This formed the most extensive cell transcriptomic atlas of human psoriatic skin to date. The robustness of our reclassified cell-types, representing full-layer zonation in human skin, was affirmed through neural-network learning-based cross-validation. We then developed a publicly available website to present this integrated dataset. We carried out analysis for differentially expressed lncRNAs, co-regulated gene patterns, and GO-bioprocess enrichment, enabling us to pinpoint lncRNAs that modulate localized cellular inflammation in psoriasis at the single-cell level. Subsequent experimental validation with skin cell lines and primary cells from psoriatic skin confirmed these lncRNAs’ functional role in localized cellular inflammation. Our study provides a comprehensive cell transcriptomic atlas of full-layer human skin in both healthy and psoriatic conditions, unveiling a new regulatory mechanism that governs localized cellular inflammation in psoriasis and highlights the therapeutic potential of lncRNAs in this disease’s management

A Method for Rapid Screening of Anilide-Containing AMPK Modulators Based on Computational Docking and Biological Validation

Adenosine 5′-monophsphate-activated protein kinase (AMPK) is a crucial energy sensor for maintaining cellular homeostasis. Targeting AMPK may provide an alternative approach in treatment of various diseases like cancer, diabetes, and neurodegenerations. Accordingly, novel AMPK activators are frequently identified from natural products in recent years. However, most of such AMPK activators are interacting with AMPK in an indirect manner, which may cause off-target effects. Therefore, the search of novel direct AMPK modulators is inevitable and effective screening methods are needed. In this report, a rapid and straightforward method combining the use of in silico and in vitro techniques was established for selecting and categorizing huge amount of compounds from chemical library for targeting AMPK modulators. A new class of direct AMPK modulator have been discovered which are anilides or anilide-like compounds. In total 1,360,000 compounds were virtually screened and 17 compounds were selected after biological assays. Lipinski’s rule of five assessment suggested that, 13 out of the 17 compounds are demonstrating optimal bioavailability. Proton acceptors constituting the structure of these compounds and hydrogen bonds with AMPK in the binding site appeared to be the important factors determining the efficacy of these compounds