[Pollution Characteristics and Ozone Formation Potential of Ambient Volatile Organic Compounds(VOCs)in Summer and Autumn in Different Functional Zones of Lianyungang, China].

Atmospheric volatile organic compounds (VOCs) were collected from different functional zones of Lianyungang during the summer and autumn of 2018. One-hundred-seven VOCs species were measured by cryogenic pre-concentration and gas chromatography-mass spectrometry (GC/MS). The ozone generation potential (OFP) of VOCs was estimated by maximum incremental reactivity (MIR).

[Vehicle Exhaust Emission Characteristics and Their Contributions in Jiangsu Province].

An hourly vehicular emission inventory with 1 km×1 km resolution was developed for Jiangsu Province in 2015, using the COPERT model and ArcGIS technology. The improved "standard road length" method, as well as road network information and monthly, weekly, and daily variations of the congestion delay index were used to increase temporal-spatial resolution. The contributions of different vehicle types, emission standards, and road types to total vehicular emissions were analyzed.

A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data.

Background: The ability to sequence the transcriptomes of single cells using single-cell RNA-seq sequencing technologies presents a shift in the scientific paradigm where scientists, now, are able to concurrently investigate the complex biology of a heterogeneous population of cells, one at a time. However, till date, there has not been a suitable computational methodology for the analysis of such intricate deluge of data, in particular techniques which will aid the identification of the unique transcriptomic profiles difference between the different cellular subtypes. In this paper, we describe the novel methodology for the analysis of single-cell RNA-seq data, obtained from neocortical cells and neural progenitor cells, using machine learning algorithms (Support Vector machine (SVM) and Random Forest (RF)).

[Effect of ghrelin on small intestinal transit and interdigestive gastrointestinal migrating myoelectric complex in rats].

Objective: To investigate the effects of ghrelin on small intestinal transit and intergigestive gastrointestinal migrating myoelectric complex (MMC) in rats.

Methods: After a 24-hour fasting, the rats with or without pretreatment with receptor antagonist (D-Lys3)GHRP-6 were given intravenous injections of ghrelin at different doses to observe the changes in small intestinal transit. The MMCs of the fasting rats were recorded using a multilead physiological recording system, and their changes observed in response to intravenous ghrelin injections, or to ghrelin injection following pretreatment with atropine, phentolamine, propranolol, L-arginine or (D-Lys3)GHRP-6, respectively.

[Effect of ghrelin on duodenal myoelectric activity in conscious rats].

Objective: To explore the effect of ghrelin on the duodenal myoelectrical activity during the feeding state and the fasting state in rats.

Methods: One pair of bipolar silver electrodes were chronically implanted in the duodenal serosa of rats for electromyography. The myoelectrical activity was recorded when ghrelin was injected intravenously into rats during the feeding state or the fasting state.