Unique Inner Pore Properties of BK Channels Revealed by Quaternary Ammonium Block

Potassium channels have a very wide distribution of single-channel conductance, with BK type Ca2+-activated K+ channels having by far the largest. Even though crystallographic views of K+ channel pores have become available, the structural basis underlying BK channels' large conductance has not been completely understood. In this study we use intracellularly applied quaternary ammonium compounds to probe the pore of BK channels. We show that molecules as large as decyltriethylammonium (C10) and tetrabutylammonium (TBA) have much faster block and unblock rates in BK channels when compared with any other tested K+ channel types. Additionally, our results suggest that at repolarization large QA molecules may be trapped inside blocked BK channels without slowing the overall process of deactivation. Based on these findings we propose that BK channels may differ from other K+ channels in its geometrical design at the inner mouth, with an enlarged cavity and inner pore providing less spatially restricted access to the cytoplasmic solution. These features could potentially contribute to the large conductance of BK channels

Effect of anti-CIRP antibody on inflammatory response, tumor formation and abdominal aortic aneurysm in rats

Purpose: To investigate the effect of anti-cold induced RNA binding protein (CIRP) antibody on inflammation, tumor formation and abdominal aortic aneurysm in rats.Methods: Thirty healthy male Wistar rats were assigned to pseudo-operation, abdominal aortic aneurysm model, and anti-CIRP groups, with 10 in each group. The levels of CIRP, TNF- α, monocyte giant cytokine chemokine-1 (MCP-1), Toll-like receptor 4 (TLR4)) and nuclear factor kappaB (NF- κB)were determined compared among the groups.Results: At both 2 and 4 weeks, the expression of CIRP protein in the model group was significantly higher than that in the sham operation group (p < 0.05). At these two time-points, tumor formation and maximum diameter were higher in anti-CIRP and model control rats than in pseudo-operation rats. After 4 weeks of treatment, the protein expressions of TNF- α, MCP-1, TLR4 and NF-κB were higher in anti-CIRP and model control rats than in pseudo-operation rats, but were lower than model control values (p < 0.05).Conclusion: CIRP expression is significantly increased in abdominal aortic aneurysm tissue and serum, and is involved in the onset and progress of abdominal aortic aneurysm. Anti-CIRP antibody therapy effectively suppresses tumorigenesis, and inhibits tumor wall inflammatory reaction viaTLR4/NF-κB pathway. This finding provides a clue and new strategy for the clinical management of abdominal aortic aneurysm. Keywords: CIRP, Abdominal aortic tumor wall, Inflammatory reaction, Protein expression, Tumor bod

The role of health system governance in strengthening the rural health insurance system in China.

BACKGROUND: Systems of governance play a key role in the operation and performance of health systems. In the past six decades, China has made great advances in strengthening its health system, most notably in establishing a health insurance system that enables residents of rural areas to achieve access to essential services. Although there have been several studies of rural health insurance schemes, these have focused on coverage and service utilization, while much less attention has been given to the role of governance in designing and implementing these schemes. METHODS: Information from publications and policy documents relevant to the development of two rural health insurance policies in China was obtained, analysed, and synthesise. 92 documents on CMS (Cooperative Medical Scheme) or NCMS (New Rural Cooperative Medical Scheme) from four databases searched were included. Data extraction and synthesis of the information were guided by a framework that drew on that developed by the WHO to describe health system governance and leadership. RESULTS: We identified a series of governance practices that were supportive of progress, including the prioritisation by the central government of health system development and certain health policies within overall national development; strong government commitment combined with a hierarchal administrative system; clear policy goals coupled with the ability for local government to adopt policy measures that take account of local conditions; and the accumulation and use of the evidence generated from local practices. However these good practices were not seen in all governance domains. For example, poor collaboration between different government departments was shown to be a considerable challenge that undermined the operation of the insurance schemes. CONCLUSIONS: China's success in achieving scale up of CMS and NCMS has attracted considerable interest in many low and middle income countries (LMICs), especially with regard to the schemes' designs, coverage, and funding mechanisms. However, this study demonstrates that health systems governance may be critical to enable the development and operation of such schemes. Given that many LMICs are expanding health financing system to cover populations in rural areas or the informal sectors, we argue that strengthening specific practices in each governance domain could inform the adaptation of these schemes to other settings

Selective Differential Privacy for Language Modeling

With the increasing applications of language models, it has become crucial to protect these models from leaking private information. Previous work has attempted to tackle this challenge by training RNN-based language models with differential privacy guarantees. However, applying classical differential privacy to language models leads to poor model performance as the underlying privacy notion is over-pessimistic and provides undifferentiated protection for all tokens in the data. Given that the private information in natural language is sparse (for example, the bulk of an email might not carry personally identifiable information), we propose a new privacy notion, selective differential privacy, to provide rigorous privacy guarantees on the sensitive portion of the data to improve model utility. To realize such a new notion, we develop a corresponding privacy mechanism, Selective-DPSGD, for RNN-based language models. Besides language modeling, we also apply the method to a more concrete application--dialog systems. Experiments on both language modeling and dialog system building show that the proposed privacy-preserving mechanism achieves better utilities while remaining safe under various privacy attacks compared to the baselines. The data and code are released at https://github.com/wyshi/lm_privacy to facilitate future research .Comment: NAACL 202

Research on Noise Reduction of Variable Speed Rotary Compressor with Large Capacity

With the increasing speed and capacity of variable-speed rotary compressors, the problem of noise especially low and medium frequency noise in the air conditioning system which can\u27t be solved by wrapping soundproof cotton has became more serious. In this paper, based on the noise problem of the rotor compressor with a working capacity of more than 80CC, the main frequency and the position of the noise source within 1000Hz are confirmed by simulation and experiment. Then on the base of this，the muffler and accumulator are respectively optimized and improved combining with Computer Aided Engineering (CAE) means. The final application results show that the optimized scheme can reduce noise by 6.1dB in 160Hz and 8.9dB in the frequency range of 500Hz to 800Hz, achieving good results

ViT-CX: Causal Explanation of Vision Transformers

Despite the popularity of Vision Transformers (ViTs) and eXplainable AI (XAI), only a few explanation methods have been proposed for ViTs thus far. They use attention weights of the classification token on patch embeddings and often produce unsatisfactory saliency maps. In this paper, we propose a novel method for explaining ViTs called ViT-CX. It is based on patch embeddings, rather than attentions paid to them, and their causal impacts on the model output. ViT-CX can be used to explain different ViT models. Empirical results show that, in comparison with previous methods, ViT-CX produces more meaningful saliency maps and does a better job at revealing all the important evidence for prediction. It is also significantly more faithful to the model as measured by deletion AUC and insertion AUC