Synthesis and Antiproliferative Activity of Some Steroidal Lactams

Using cholesterol as starting material, a series of 6-substituted-3-aza-A-homo-3-oxycholestanes and 6-substituted-4-aza-A-homo-3-oxycholestanes were synthesized by the oxidation, reduction, oximation, Beckman rearrangement and condensation reaction. These synthesized compounds displayed a distinct cytotoxicity against MGC 7901, HeLa and SMMC 7404 cancer cells. Our results revealed that the structures of functional groups at position-6 on the steroidal ring are crucial for the IC50 value of antiproliferative activities of these compounds and the cytotoxic activity against MGC 7901 and SMMC 7404 cells was not significantly different between 4-N-lactams and 3-N-lactams when its 6-substituted group was a carbonyl or a hydroximino, but all 3-N-lactams showed a higher cytotoxicity against HeLa cells than 4-N-lactams. In particular, compounds 6, 8, 9 (IC506: 6.5 μmol/L; 8: 7.7 μmol/L; 9: 5.6 μmol/L) were even more cytotoxic than cisplatin to HeLa cells (positive contrast, 10.1 μmol/L). The information obtained from the studies may be useful for the design of novel chemotherapeutic drugs

Synthesis and Evaluation of Some New Aza-B-Homocholestane Derivatives as Anticancer Agents

Using analogues of some marine steroidal oximes as precursors, a series of aza-B-homocholestane derivatives possessing different substituted groups at the 3-position of the steroidal nucleus were synthesized. Their biological activity against cancer cell proliferation was determined with multiple cancer cell lines. Aza-B-homocholestane derivatives possessing 3-hydroxyl, 3-hydroximino and 3-thiosemicarbazone groups displayed remarkable cytotoxicity to cancer cells via apoptosis inducing mechanism. Compounds 5, 10, 12, 15 and 18 exhibited better potency to inhibit cancer cell proliferation. In addition, compound 15 was further evaluated with three dimensional (3D) multicellular spheroids assay to determine its potency against spheroid growth. The structure-activity relationship (SAR) generated in the studies is valuable for the design of novel chemotherapeutic agents

Instructive Feature Enhancement for Dichotomous Medical Image Segmentation

Deep neural networks have been widely applied in dichotomous medical image segmentation (DMIS) of many anatomical structures in several modalities, achieving promising performance. However, existing networks tend to struggle with task-specific, heavy and complex designs to improve accuracy. They made little instructions to which feature channels would be more beneficial for segmentation, and that may be why the performance and universality of these segmentation models are hindered. In this study, we propose an instructive feature enhancement approach, namely IFE, to adaptively select feature channels with rich texture cues and strong discriminability to enhance raw features based on local curvature or global information entropy criteria. Being plug-and-play and applicable for diverse DMIS tasks, IFE encourages the model to focus on texture-rich features which are especially important for the ambiguous and challenging boundary identification, simultaneously achieving simplicity, universality, and certain interpretability. To evaluate the proposed IFE, we constructed the first large-scale DMIS dataset Cosmos55k, which contains 55,023 images from 7 modalities and 26 anatomical structures. Extensive experiments show that IFE can improve the performance of classic segmentation networks across different anatomies and modalities with only slight modifications. Code is available at https://github.com/yezi-66/IFEComment: Accepted by MICCAI 202

Molecular characterization, expression pattern and immunologic function of CD82a in large yellow croaker (Larimichthys crocea)

Visceral white spot disease (VWND) caused by Pseudomonas plecoglossicida poses a major threat to the sustainable development of large yellow croaker (Larimichthys crocea) aquaculture. Genome-wide association analysis (GWAS) and RNA-seq research indicated that LcCD82a play an important role in resistance to visceral white spot disease in L. crocea, but the molecular mechanism of LcCD82a response to P. plecoglossicida infection is still unclear. In this study, we cloned and validated the Open Reading Frame (ORF) sequence of LcCD82a and explored the expression profile of LcCD82a in various tissues of L.crocea. In addition, two different transcript variants (LcCD82a-L and LcCD82a-S) of LcCD82a were identified that exhibit alternative splicing patterns after P. plecoglossicida infection, which may be closely related to the immune regulation during pathogenetic process of VWND. In order to explore the function of LcCD82a, we purified the recombinant protein of LcCD82a-L and LcCD82a-S. The bacterial agglutination and apoptosis function analysis showed that LcCD82a may involve in extracellular bacterial recognition, agglutination, and at the same time participate in the process of antigen presentation and induction of cell apoptosis. Collectively, our studies demonstrate that LcCD82a plays a crucial role in regulating apoptosis and antimicrobial immunity

Impact of Teenage EFL Learners’ Psychological Needs on Learning Engagement and Behavioral Intention in Synchronous Online English Courses

There is a relatively small body of literature that is concerned with the extent to which students are actively engaged in online English learning. To address this issue, the present study investigates 233 Chinese secondary school students attending online English courses during the pandemic and explores the degree to which learners are behaviorally, cognitively, emotionally, and socially engaged in synchronous online English courses. Three basic psychological needs (autonomy, competence, and relatedness) are examined as antecedents of learning engagement, and the behavioral intention is hypothesized as a learning outcome. This study takes a mixed-methods approach, integrating quantitative data from questionnaires and qualitative data from semi-structured interviews. A partial least squares (PLS)-structural equation modeling (SEM) technique was used to test hypotheses and the proposed research model. The quantitative findings indicate that, firstly, whereas the basic psychological needs predict students’ four dimensions of online learning engagement, competence is confirmed to be the strongest predicting factor. Secondly, behavioral intention is significantly influenced by students’ cognitive engagement and emotional engagement. Thirdly, thematic analysis of the qualitative data shows that students tend to have a lower level of engagement compared with a face-to-face classroom learning enviroment, and a more interesting and interactive online course design is crucial to the fulfillment of learners’ psychological needs of autonomy and relatedness in synchronous online English learning

Supply and Demand Forecasting of Water Resource Coupling System in Upstream Yangtze River under Changing Environmental Conditions

The upstream Yangtze River is located in the southwest of central China, where it flows through several ecosystems and densely populated regions that constitute a unique complex coupled system. To determine how the characteristics of supply and demand in a water-coupled system will vary under the influence of climate change and human activity in this area in the next 85 years, the upper Yangtze basin was considered as the study area and was divided into seven sub-basins according to seven main control sections: Shigu, Panzhihua, Xiluodu, Xiangjiaba, Zhutuo, Cuntan, and Yichang; a method for water supply and demand research considering climate change was proposed. Based on simulated runoff in the study area under changing environmental conditions, this study analyzed the available water supply and constructed a long-term water demand forecasting model using the classified water use index method under macro regulation in the study area from 2016 to 2100. The results show that the total water demand in the upstream Yangtze River appears to first increase and then decrease in 2016–2100 and will reach its peak around 2028. The ecological pressure in the upstream Yangtze River increases gradually from upstream to downstream but will not reach the surface water utilization stress threshold (hereinafter referred to as stress threshold) for the next 85 years. The contradiction between monthly supply and demand is more prominent under ecological restrictions. Under the RCP4.5 scenario, water demand exceeds the stress threshold in each sub-basin across several months (mainly March, April, and May), and the water demand nearly reaches the damage threshold in May as the basin extends below the Zhutuo section

How can virtual water trade reshape water stress pattern? A global evaluation based on the metacoupling perspective

With water scarcity increasingly becoming a growing global risk, it is prevalent to explore water supply-demand interaction within and beyond national borders driven by global virtual water trade and its effects on water sustainability. However, there is little study on system integration of differential environmental impacts of various types of trade. Based on metacoupling framework highlighting human-nature interactions across space- within a place (intracoupling), between adjacent places (pericoupling), and between distant places (telecoupling), this study quantified the linkages and intensities of three kinds of coupling processes during global virtual water trade for the first time. Correspondingly, water stress changes under a set of trade scenarios were evaluated based on the indicator of UN SDG 6.4.2 to distinguish the influence of trade taking place on different spatial scales. Results show that during 2005–2015, local water resources supported 80% of global water consumption. Distant virtual water import was about 5 times in volume as large as adjacent virtual water import, alleviating 99.8% of global average water stress. Virtual water trade reduced water stress in 86% of developed countries and increased that in 71% of developing countries in 2005. Owing to trade, water stress in many countries with poor water resources endowment declined while that of many with relatively good endowment went up from 2005 to 2015. Our findings can help to systematically understand the influence of virtual water trade on water stress change and provide scientific guidance for sustainable water management and regional regulations

Iteration Bayesian Reweighed Algorithm for Optical Carrier-Based Microwave Interferometry Sensing

This paper proposes a novel iteration Bayesian reweighed (IBR) algorithm to obtain accurate estimates of a measurement parameter that uses only a few noisy measurement data. The method is applied to optimize the frequency fluctuation in an optical carrier-based microwave interferometry (OCMI) system. The algorithm iteratively estimates the frequency of the S-parameter valley point by collecting training samples to rebalance the weights between prior samples, which reduces the impact of noise in the system. Simulation shows that the estimated result of this algorithm is closer to the true value than that of the maximum likelihood estimation (MLE) using the same amount of measured data. Under the influence of system noise, this algorithm optimizes the frequency fluctuation of the S-parameter and reduces the impact of individual measured data. In this study, we applied the algorithm in the strain sensing experiment and compared it with the MLE. When axial strain changes 240 με, the IBR algorithm yields a deviation of 36 με, which is a significant reduction from 138 με (using the MLE method). Moreover, the average error rate decreases from 25% to 3% (with the MLE method), suggesting that the linear fitting degree of the estimated results and accuracy of the system are improved. Moreover, the algorithm has a wide range of applicability, for it can handle different application models in the OCMI system and the systems with frequency fluctuation problems