FAT1 inhibits AML autophagy and proliferation via downregulating ATG4B expression.

Background: Emerging studies have shown that FAT atypical cadherin 1 (FAT1) and autophagy separately inhibits and promotes acute myeloid leukemia (AML) proliferation. However, it is unknown whether FAT1 were associated with autophagy in regulating AML proliferation.

Methods: AML cell lines, 6-week-old male nude mice and AML patient samples were used in this study.

[Spatio-Temporal Characteristics and Potential Source Areas of Seasonal Atmospheric Pollution in Shijiazhuang].

In order to systematically study the transmission characteristics of seasonal and typical pollutants in Shijiazhuang, hourly data of ground-level pollutants(PM, PM, O, NO, SO, and CO) from 46 state-and provincial-controlled stations, and meteorological(temperature, humidity, and wind speed) data from 17 counties in Shijiazhuang City from December 2018 to November 2019 was analyzed. The interpolation(IDW) and correlation analysis were applied to seasonal and temporal spatial patterns of pollutant concentration. The backward trajectories analysis was performed to explore the seasonal transmission pattern and potential source areas of pollution in Shijiazhuang by combining with the global data assimilation system(GDAS).

An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm.

The identification of chemical structures in natural product mixtures is an important task in drug discovery but is still a challenging problem, as structural elucidation is a time-consuming process and is limited by the available mass spectra of known natural products. Computer-aided structure elucidation (CASE) strategies seek to automatically propose a list of possible chemical structures in mixtures by utilizing chromatographic and spectroscopic methods. However, current CASE tools still cannot automatically solve structures for experienced natural product chemists.

Rule-based classification models of molecular autofluorescence.

Fluorescence-based detection has been commonly used in high-throughput screening (HTS) assays. Autofluorescent compounds, which can emit light in the absence of artificial fluorescent markers, often interfere with the detection of fluorophores and result in false positive signals in these assays. This interference presents a major issue in fluorescence-based screening techniques.

A comprehensive support vector machine binary hERG classification model based on extensive but biased end point hERG data sets.

The human ether-a-go-go related gene (hERG) potassium ion channel plays a key role in cardiotoxicity and is therefore a key target as part of preclinical drug discovery toxicity screening. The PubChem hERG Bioassay data set, composed of 1668 compounds, was used to construct an in silico screening model. The corresponding trial models were constructed from a descriptor pool composed of 4D fingerprints (4D-FP) and traditional 2D and 3D VolSurf-like molecular descriptors.

In silico binary classification QSAR models based on 4D-fingerprints and MOE descriptors for prediction of hERG blockage.

Blockage of the human ether-a-go-go related gene (hERG) potassium ion channel is a major factor related to cardiotoxicity. Hence, drugs binding to this channel have become an important biological end point in side effects screening. A set of 250 structurally diverse compounds screened for hERG activity from the literature was assembled using a set of reliability filters.