RNA m6A reader YTHDF1 facilitates inflammation via enhancing NLRP3 translation.

N6-methyladenosine (m6A) modification of mRNAs is involved in multiple essential biological processes, dynamically regulated by m6A "writers", "erasers", and "readers". Yet, the detailed functional roles of RNA m6A reader proteins, such as YTHDFs, are largely unknown. Herein we show that YTHDF1 promotes pro-inflammatory IL-1ß production in macrophages during bacterial infections. YTHDF1 overexpression promotes NLRP3 translation. In vivo knockdown of YTHDF1 facilitates survival in a mouse model of sepsis. Thus, YTHDF1 participates in inflammatory responses and subsequent injuries, serving as a new potential therapeutic target in clinical treatment of inflammatory diseases.

[Analyzing the methods to smooth field reconstructed by algebraic reconstruction technique with spectroscopy].

The effects of filters and filtering methods on the field reconstructed by algebraic reconstruction technique (ART) is discussed with spectroscopy. The field to be constructed was simulated with numerical simulation technique. The effects of many kinds of filters and filtering methods on the field reconstructed by ART were analyzed with spectroscopy. The filters used included quarter, fifth, eighth averaging filter, fifth center filter, and third row, column filter. The filtering methods included filter being inserted in the iterating process or set at its end. The averaging filter mentioned above meant that the value was acquired from the average of the four data, named quarter averaging filter, and so on. The fifth center filter meant that the value was acquired from the center, the third one in ascendant or descendant sequence of the five data. As a result, the authors found that a larger difference existed in the effects of different filters and filtering methods on the reconstructed field. First, the field reconstructed by ART contained much big noise and needed to be smoothed. Secondly, the reconstructive accuracy declined much when an averaging filter, such as quarter, fifth or eighth filter, was only set at the end of iterating process. Thirdly, the accuracy could be improved a little with a quarter or eighth averaging filter inserted in the iterating process and activated according to iterating times. Forthly, a better accuracy could be obtained with a fifth center filter inserted in the iterating process than with a fifth averaging one inserted. Fifthly, the best result in this work was obtained with a fifth averaging filter and a fifth center one inserted in the iterating process and activated alternately according to iterating times.

[Simple self-correlative algebraic reconstruction technique].

A new improvement was brought forward in algebraic reconstruction technique (ART), named simple self-correlative algebraic reconstruction technique (SSCART), and its reconstructive result was discussed in detail. With numerical simulation technique, both ART and SSCART were numerically simulated with computer, and discussed in terms of simulated result and reconstructive accuracy with error indexes such as mean-square error (MSE), absolute value error (AVE) and peak error (PE). As a result, the accuracy of SSCART was markedly improved. Its MSE was decreased sixty-five percent compared to that of ART (the difference between MSE of ART and that of SSCART divided by the MSE of ART) at the level of 10(-4) magnitude, and PE decreased ninety-nine point nine percent at the level of 10 magnitude. The iterating program of SSCART was not a new program to ART, but only a simple factor was added to. SSCART was considered a superior reconstruction technique with many good virtues such as simple iterating program, persistent convergent iterating process, and high reconstructive accuracy. It is the most superior iterating reconstruction technique in current ARTs to our knowledge.