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)). RESULTS: Thirty-eight key transcripts were identified, using the SVM-based recursive feature elimination (SVM-RFE) method of feature selection, to best differentiate developing neocortical cells from neural progenitor cells in the SVM and RF classifiers built. Also, these genes possessed a higher discriminative power (enhanced prediction accuracy) as compared commonly used statistical techniques or geneset-based approaches. Further downstream network reconstruction analysis was carried out to unravel hidden general regulatory networks where novel interactions could be further validated in web-lab experimentation and be useful candidates to be targeted for the treatment of neuronal developmental diseases. CONCLUSION: This novel approach reported for is able to identify transcripts, with reported neuronal involvement, which optimally differentiate neocortical cells and neural progenitor cells. It is believed to be extensible and applicable to other single-cell RNA-seq expression profiles like that of the study of the cancer progression and treatment within a highly heterogeneous tumour.

[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). Results showed that the average volume fraction of VOCs was (22.1±13.1)×10-9. Alkanes and alkenes from C2-C4 as well as acetone and ethyl acetate were the predominant species, accounting for 59.8%-75.8% of TVOCs. The mean volume fraction in the industrial zone was the largest[(28.4±13.5)×10-9], followed by the scenic zone[(21.7±4.4)×10-9] and the traffic and residential mixed zone[(20.8±7.2)×10-9]. The concentration of VOCs in autumn was significantly higher than that in summer. The industrial zone was the site with the highest volume fraction in autumn (35.4×10-9), while the scenic zone had the highest volume fraction in summer (21.5×10-9). Alkane, sulfur, or oxygen containing compounds and halogenated hydrocarbons were the predominant components of VOCs, accounting for 35.3%, 26.9%, and 15.6% of the total amount, respectively. Due to industrial emissions, the content of sulfur or oxygen containing compounds in the industrial zone was significantly higher than that in scenic zone and the traffic and residential mixed zone. The average ratio of T/B (toluene/benzene) indicated that vehicle and solvent use were the main sources of VOCs in the urban area. The highest OFP was found in the industrial zone, followed by the traffic and residential mixed zone and the scenic zone. Alkenes and aromatics were the largest contributors to OFP.

[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. Some rats were pretreated with atropine, phentolamine, propranolol, L-arginine, and (D-Lys3)GHRP-6 respectively to explore the mechanism of ghrelin. RESULTS: Duodenal migrating myoelectrical complex (MMC) could be induced by ghrelin in the feeding state. Ghrelin could shorten the length of duodenal MMC cycle and increase the amplitude and frequency of phase III during the fasting state. The percentage of phase III in the MMC cycle did not change. These effects were inhibited by atropine and L-arginine (D-Lys3)GHRP-6, but not by propranolol and phentolamine. CONCLUSION: Ghrelin seems to be closely related to the duodenal motility. The excitatory effect of ghrelin on duodenal MMC might rely on the cholinergic pathway, and have a close relationship with NO. The receptor of ghrelin can regulate its activity.

[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. Results showed that vehicular emissions of NOx, HC, CO, PM2.5, SO2, OM, and BC were 490.9, 166.3, 1614.8, 16.9, 1.9, 3.6, and 6.7 thousand tons, respectively. On average, Suzhou and Xuzhou contributed 34%-45% of the total. Evaporative emissions of HC were 20.2 thousand tons, accounting for 12% of total HC emissions. Small passenger cars and motorcycles were the major HC and CO contributors, accounting for over 30% of total emissions. Heavy-duty diesel trucks contributed 36%-54% to NOx, PM2.5, SO2, OM, and BC emissions, representing much higher emissions than other vehicles. Heavy-duty and medium-duty diesel trucks in Suzhou and Xuzhou are the main sources of NOx and PM2.5emissions. China Ⅲ diesel vehicles account for the largest share (42%-55%) of NOx, PM2.5, SO2, and BC emissions. China Ⅲ heavy-duty diesel trucks and China 0 medium-duty diesel trucks are the primary and secondary contributors of NOx, PM2.5, OM, and BC emissions, with a total share of 40%-56%. China 0 motorcycles contributed about 16% to total HC and CO.

[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. RESULTS: Ghrelin enhanced the small intestinal transit dose-dependently, and this effect was inhibited by application of ghrelin receptor antagonist. Ghrelin also showed excitatory effect on the MMCs, which was inhibited by atropine, L-arginine or (D-Lys3)GHRP-6, but not by propranolol and phentolamine. CONCLUSION: Ghrelin can promote gastrointestinal motilities, and its excitatory effects rely on the cholinergic pathway in close relation to nitric oxide pathway. Ghrelin receptor is involved in its action in promoting the gastrointestinal motilities.