In Situ Heterodyne-Detected Second-Harmonic Generation Study of the Influence of Cholesterol on Dye Molecule Adsorption on Lipid Membrane

Cholesterol plays an essential role in regulating the functionality of biomembranes. This study employed in situ second-harmonic generation (SHG) to investigate the adsorption behavior of the dye molecule 4-(4-(diethylamino)styryl)-N-methyl-pyridinium iodide (D289) on a biomimic membrane composed of 1,2-dipalmitoyl-sn-glycero-3-phospho-(1′-rac-glycerol) (sodium salt) (DPPG) and cholesterol. The time-dependent polarization SHG intensity exhibited an initial rapid increase, followed by a subsequent decline. The initial increased SHG intensity is responsible for the electrostatic interaction-driven adsorption of D289 onto the membrane, while the decrease in the SHG signal results from the broadening of the orientation distribution within the membrane. Heterodyne-detected SHG (HD-SHG) measurements demonstrated that the adsorption of dye molecules influenced the phase of the induced electric field. The interfacial potential Φ(0) as a function of time was measured, and we found that even after reaching a stable Stern layer state, the diffusion layer continued to exhibit a dynamic change. This study offers a comprehensive understanding of the influence of cholesterol on adsorption, reorientation dynamics, and dynamic changes in the reorientation of water in the diffusion layer

Road surface real-time detection based on Raspberry Pi and recurrent neural networks

This paper focuses on road surface real-time detection by using tripod dolly equipped with Raspberry Pi 3 B+, MPU 9250, which is convenient to collect road surface data and realize real-time road surface detection. Firstly, six kinds of road surfaces data are collected by utilizing Raspberry Pi 3 B+ and MPU 9250. Secondly, the classifiers can be obtained by adopting several machine learning algorithms, recurrent neural networks (RNN) and long short-term memory (LSTM) neural networks. Among the machine learning classifiers, gradient boosting decision tree has the highest accuracy rate of 97.92%, which improves by 29.52% compared with KNN with the lowest accuracy rate of 75.60%. The accuracy rate of LSTM neural networks is 95.31%, which improves by 2.79% compared with RNN with the accuracy rate of 92.52%. Finally, the classifiers are embedded into the Raspberry Pi to detect the road surface in real time, and the detection time is about one second. This road surface detection system could be used in wheeled robot-car and guiding the robot-car to move smoothly

Identification of Genes Related to Growth and Lipid Deposition from Transcriptome Profiles of Pig Muscle Tissue

<div><p>Transcriptome profiles established using high-throughput sequencing can be effectively used for screening genome-wide differentially expressed genes (DEGs). RNA sequences (from RNA-seq) and microRNA sequences (from miRNA-seq) from the tissues of <i>longissimus dorsi</i> muscle of two indigenous Chinese pig breeds (Diannan Small-ear pig [DSP] and Tibetan pig [TP]) and two introduced pig breeds (Landrace [LL] and Yorkshire [YY]) were examined using HiSeq 2000 to identify and compare the differential expression of functional genes related to muscle growth and lipid deposition. We obtained 27.18 G clean data through the RNA-seq and detected that 18,208 genes were positively expressed and 14,633 of them were co-expressed in the muscle tissues of the four samples. In all, 315 DEGs were found between the Chinese pig group and the introduced pig group, 240 of which were enriched with functional annotations from the David database and significantly enriched in 27 Gene Ontology (GO) terms that were mainly associated with muscle fiber contraction, cadmium ion binding, response to organic substance and contractile fiber part. Based on functional annotation, we identified 85 DEGs related to growth traits that were mainly involved in muscle tissue development, muscle system process, regulation of cell development, and growth factor binding, and 27 DEGs related to lipid deposition that were mainly involved in lipid metabolic process and fatty acid biosynthetic process. With miRNA-seq, we obtained 23.78 M reads and 320 positively expressed miRNAs from muscle tissues, including 271 known pig miRNAs and 49 novel miRNAs. In those 271 known miRNAs, 20 were higher and 10 lower expressed in DSP-TP than in LL-YY. The target genes of the 30 miRNAs were mainly participated in MAPK, GnRH, insulin and Calcium signaling pathway and others involved cell development, growth and proliferation, etc. Combining the DEGs and the differentially expressed (DE) miRNAs, we drafted a network of 46 genes and 18 miRNAs for regulating muscle growth and a network of 15 genes and 16 miRNAs for regulating lipid deposition. We identified that <i>CAV2</i>, <i>MYOZ2</i>, <i>FRZB</i>, miR-29b, miR-122, miR-145-5p and miR-let-7c, etc, were key genes or miRNAs regulating muscle growth, and <i>FASN</i>, <i>SCD</i>, <i>ADORA1</i>, miR-4332, miR-182, miR-92b-3p, miR-let-7a and miR-let-7e, etc, were key genes or miRNAs regulating lipid deposition. The quantitative expressions of eight DEGs and seven DE miRNAs measured with real-time PCR certified that the results of differential expression genes or miRNAs were reliable. Thus, 18,208 genes and 320 miRNAs were positively expressed in porcine <i>longissimus dorsi</i> muscle. We obtained 85 genes and 18 miRNAs related to muscle growth and 27 genes and 16 miRNAs related to lipid deposition, which provided new insights into molecular mechanism of the economical traits in pig.</p></div

The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enriched for targets of the 20 upregulated miRNAs in the Chinese pigs.

<p>The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enriched for targets of the 20 upregulated miRNAs in the Chinese pigs.</p

Five cardiac tissue differentially expressed (DE) miRNAs validated by reverse-transcription quantitative polymerase chain reaction.

<p>Relative expression levels of DE miRNAs. Upper letters (a, b) on bars denote significantly different expression levels in the same miRNA (<i>P</i> < 0.05).</p

Comparison of the transcript expression levels between the Diannan Small-ear pig-Tibetan pig (DSP-TP) and Landrace-Yorkshire pig (LL-YY) groups.

<p>The vertical axis represents the Log2 fragments per kilobase of exon length million mapped reads (FPKM) in the DSP-TP group, and the horizontal axis represents the Log2 FPKM in the LL-YY group. The differentially expressed genes (DEGs) were filtered using P ≤ 0.05 and |log2ratio| ≥ 1 as a threshold. The red points represent upregulated genes, and the green points indicate downregulated genes. The gray spots represent no significant difference between the DSP-TP and LL-YY groups.</p

The qPCR primers of seven microRNAs (miRNAs).

<p>The qPCR primers of seven microRNAs (miRNAs).</p

Venn diagram of expressed miRNA numbers in each sample.

<p>Venn diagram of expressed miRNA numbers in each sample.</p

Summary of sequencing reads aligned with the <i>Sus scrofa</i> genome and annotated genes.

<p>DSP, Diannan Small-ear pig; TP, Tibetan pig; LL, Landrace; YY, Yorkshire.</p><p>Summary of sequencing reads aligned with the <i>Sus scrofa</i> genome and annotated genes.</p

The significantly enriched Gene Ontology (GO) terms of differentially expressed genes.

<p>The blue clusters represent the cellular component, the yellow clusters represent the biological process, and the green clusters represent the molecular function of the GO terms.</p