MicroRNA-519a promotes proliferation and inhibits apoptosis of hepatocellular carcinoma cells by targeting FOXF2

AbstractRecent studies report that microRNA-519a (miR-519a) is a novel oncomir, which facilitates the onset and progression of human cancers. However, the clinical significance of miR-519a and its functional role and underlying mechanisms in hepatocellular carcinoma (HCC) are poorly investigated. In the present study, elevated expression of miR-519a was observed in HCC tissues compared with adjacent non-tumor tissues. The increased level of miR-519a expression was significantly correlated with adverse clinical features of HCC including hepatitis B virus (HBV) infection, large tumor size, cirrhosis and advanced tumor-node-metastasis tumor stage. Furthermore, high expression of miR-519a was prominently associated with a poorer 5-year overall survival and recurrence-free survival of HCC patients. Gain- and loss-of function experiments showed that miR-519a overexpression enhanced proliferation and reduced apoptosis of Huh7 cells. By contrast, miR-519a knockdown inhibited SMMC-7721 cell proliferation and induced apoptosis. Importantly, up-regulation of miR-519a reduced the expression of FOXF2 mRNA and protein in Huh7 cells, while down-regulation of miR-519a resulted in increased expression of FOXF2 in SMMC-7721 cells. An inverse correlation between mRNA levels of miR-519a and FOXF2 was observed in HCC tissues. Thus, Forkhead box F2 (FOXF2) was identified as a downstream target of miR-519a in HCC. Mechanistically, the effects of miR-519a knockdown on SMMC-7721 cells were abrogated by FOXF2 repression. In conclusion, miR-519a is a novel prognostic predictor for HCC patients and it may potentiate proliferation and inhibits apoptosis of HCC cells by targeting FOXF2

Understanding Client Reactions in Online Mental Health Counseling

Communication success relies heavily on reading participants' reactions. Such feedback is especially important for mental health counselors, who must carefully consider the client's progress and adjust their approach accordingly. However, previous NLP research on counseling has mainly focused on studying counselors' intervention strategies rather than their clients' reactions to the intervention. This work aims to fill this gap by developing a theoretically grounded annotation framework that encompasses counselors' strategies and client reaction behaviors. The framework has been tested against a large-scale, high-quality text-based counseling dataset we collected over the past two years from an online welfare counseling platform. Our study shows how clients react to counselors' strategies, how such reactions affect the final counseling outcomes, and how counselors can adjust their strategies in response to these reactions. We also demonstrate that this study can help counselors automatically predict their clients' states.Comment: Accept to ACL 2023, oral. For code and data, see https://github.com/dll-wu/Client-Reac

Slightly Shift New Classes to Remember Old Classes for Video Class-Incremental Learning

Recent video class-incremental learning usually excessively pursues the accuracy of the newly seen classes and relies on memory sets to mitigate catastrophic forgetting of the old classes. However, limited storage only allows storing a few representative videos. So we propose SNRO, which slightly shifts the features of new classes to remember old classes. Specifically, SNRO contains Examples Sparse(ES) and Early Break(EB). ES decimates at a lower sample rate to build memory sets and uses interpolation to align those sparse frames in the future. By this, SNRO stores more examples under the same memory consumption and forces the model to focus on low-semantic features which are harder to be forgotten. EB terminates the training at a small epoch, preventing the model from overstretching into the high-semantic space of the current task. Experiments on UCF101, HMDB51, and UESTC-MMEA-CL datasets show that SNRO performs better than other approaches while consuming the same memory consumption

The cosmic ray test of MRPCs for the BESIII ETOF upgrade

In order to improve the particle identification capability of the Beijing Spectrometer III (BESIII),t is proposed to upgrade the current endcap time-of-flight (ETOF) detector with multi-gap resistive plate chamber (MRPC) technology. Aiming at extending ETOF overall time resolution better than 100ps, the whole system including MRPC detectors, new-designed Front End Electronics (FEE), CLOCK module, fast control boards and time to digital modules (TDIG), was built up and operated online 3 months under the cosmic ray. The main purposes of cosmic ray test are checking the detectors' construction quality, testing the joint operation of all instruments and guaranteeing the performance of the system. The results imply MRPC time resolution better than 100$ps$, efficiency is about 98$\%$ and the noise rate of strip is lower than 1$Hz/$($scm^{2}$) at normal threshold range, the details are discussed and analyzed specifically in this paper. The test indicates that the whole ETOF system would work well and satisfy the requirements of upgrade

A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications

We present a framework for the automated measurement of responsible AI (RAI) metrics for large language models (LLMs) and associated products and services. Our framework for automatically measuring harms from LLMs builds on existing technical and sociotechnical expertise and leverages the capabilities of state-of-the-art LLMs, such as GPT-4. We use this framework to run through several case studies investigating how different LLMs may violate a range of RAI-related principles. The framework may be employed alongside domain-specific sociotechnical expertise to create measurements for new harm areas in the future. By implementing this framework, we aim to enable more advanced harm measurement efforts and further the responsible use of LLMs.Comment: This is a living documen

The corporate social responsibility of TQLS group in the Liangshan prefecture (C)

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Influence of the Force Arm on the Flexural Performance of Prestressed Glulam Beams

In recent years, extensive attention has been drawn to prefabricated buildings, particularly wood construction. Glulam beams are the major supporting components of modern wood buildings. Since the force arm is the most critical indicator to evaluate the resistance moment of the glulam beam string structure, it is necessary to further study the influence of the force arm on the mechanical properties of the glulam beam string structure. We tested the flexural performance of 15 prestressed glulam beams, which were divided into two groups (A and B) to, respectively, research the influences of the string arm and the end arm on the bearing capacity, failure mode, stress distribution, and deformation performance of glulam beams. The results showed that when the height of the end arm remained constant and the string arm increased from 90 mm to 130 mm and 170 mm, the bearing capacity of the beam increased by 6.77% and 17.22%, respectively. Moreover, as the depth of the compression zone of the glued timber beam gradually increased, the failure mode of the beam changed from the brittle tension failure of the beam bottom to the ductile compression failure of the beam top. When the height of the string arm remained constant and the end arm increased from 10 mm to 30 mm and 50 mm, the bearing capacity of the beam increased by 4.27% and 8.13%, respectively. The beam had no significant change in the failure mode, while it could bear the stress more uniformly. Based on the experimental results and principles of equilibrium, moment equilibrium, and similar triangle, we calculated the ultimate bearing capacity of the glulam beam and proposed a design method for durable wood structures