Study of slope length (L) extraction based on slope streamline and the comparison of method results.

Slope length is an important factor in soil erosion modeling, and the reasonable automatic extraction of slope length is of great significance in soil erosion research. However, previous studies have mainly focused on the regional scale, and how to effectively extract slope length at the slope scale deserves further research. In this study, a slope length extraction algorithm based on slope streamlines method (SSM) is proposed for the slope length extraction problem in geomorphology, and it is compared with three existing slope length calculation methods. The experimental results show that the new method can quickly calculate the length of slope streamlines, and the extracted slope lengths have better accuracy; the coefficients of determination demonstrates a better overall fitting effect of the four extraction methods, with coefficients of determination exceeding 0.7; this indicates that the use of SSM has similar accuracy and stability to other methods in calculating slope lengths. Among all the calculation methods, SSM has a better overall fitting effect for slope length calculation, and the obtained slope length value domain range is relatively small and concentrated in a small range, which expresses the slope length better.

A Study on the Formation of Flavor Substances by Bacterial Diversity in the Fermentation Process of Canned Bamboo Shoots in Clear Water.

Canned bamboo shoots in clear water could produce a unique flavor through bacterial diversity via the fermentation process. Weissella, Streptococcus, Leuconostoc, Acinetobacter, Lactococcus and Lactobacillus were the main microorganisms. Tyrosine was the most abundant free amino acid (FAA), which had a negative correlation with Lactococcus. Ten kinds of flavor substances, such as 3-methyl-1-butanol, acetic acid, 2-phenylethyl ester, benzene acetaldehyde, benzoic acid and ethyl ester, were important influential factors in the flavor of fermented bamboo shoots. Through the verification test of tyrosine and phenylalanine decarboxylase, it was found that Lactococcus lactis TJJ2 could decompose tyrosine and phenylalanine to produce benzaldehyde and benzene acetaldehyde, which provided the fermented bamboo shoots with a grassy aroma.

Screening, Identification and Physiological Characteristics of Lactobacillus rhamnosus M3 (1) against Intestinal Inflammation.

The probiotic role of lactic acid bacteria (LAB) in regulating intestinal microbiota to promote human health has been widely reported. However, the types and quantities of probiotics used in practice are still limited. Therefore, isolating and screening LAB with potential probiotic functions from various habitats has become a hot topic. In this study, 104 strains of LAB were isolated from and identified in traditionally fermented vegetables, fresh milk, healthy infant feces, and other environments. The antibacterial properties-resistance to acid, bile salts, and digestive enzymes-and adhesion ability of the strains were determined, and the biological safety of LAB with better performance was studied. Three LAB with good comprehensive performance were obtained. These bacteria had broad-spectrum antibacterial properties and good acid resistance and adhesion ability. They exhibited some tolerance to pig bile salt, pepsin, and trypsin and showed no hemolysis. They were sensitive to the selected antibiotics, which met the required characteristics and safety evaluation criteria for probiotics. An in vitro fermentation experiment and milk fermentation performance test of Lactobacillus rhamnosus (L. rhamnosus) M3 (1) were carried out to study its effect on the intestinal flora and fermentation performance in patients with inflammatory bowel disease (IBD). Studies have shown that this strain can effectively inhibit the growth of harmful microorganisms and produce a classic, pleasant flavor. It has probiotic potential and is expected to be used as a microecological agent to regulate intestinal flora and promote intestinal health. It can also be used as an auxiliary starter to enhance the probiotic value of fermented milk.

Metabolomics Strategy Assisted by Transcriptomics Analysis to Identify Potential Biomarkers Associated with Tuberculosis.

PURPOSE: To investigate the dysregulated pathways and identify reliable diagnostic biomarkers for tuberculosis using integrated analysis of metabolomics and transcriptomics. METHODS: Three groups of samples, untargeted metabolomics analysis of healthy controls (HC), latent tuberculosis infection patients (LTBI), and active tuberculosis patients (TB), were analyzed using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) and ultra-high performance liquid chromatography-quantitative mass spectrometry (UHPLC-QE-MS). Both univariate and multivariate and statistical analyses were used to select differential metabolites (DMs) among group comparison, and LASSO regression analysis was employed to discover potential diagnostic biomarkers. Metabolite set enrichment analysis was performed to identify the altered metabolic pathways specifically in patients with TB. Meanwhile, a transcriptomic dataset GSEG4992 was downloaded from the GEO database to explore the differentially expressed genes (DEGs) between TB and HC identified in significantly enriched pathways. Finally, an integrative analysis of DMs and DEGs was performed to investigate the possible molecular mechanisms of TB. RESULTS: Thirty-three specific metabolites were significantly different between TB and HC, of which 7 (5-hydroxyindoleacetic acid, isoleucyl-isoleucine, heptadecanoic acid, indole acetaldehyde, 5-ethyl-2,4-dimethyloxazole, and 2-hydroxycaproic acid, unknown 71) were chosen as combinational potential biomarkers for TB. The area under the curve (AUC) value of these biomarkers was 0.97 (95% CI: 0.92-1.00). Metabolites set enrichment analysis (MSEA) displayed that there were 3 significantly enriched pathways among all. The genes in 3 significantly enriched pathways were further analyzed, of which 9(ALDH3B1, BCAT1, BCAT2, GLYAT, GOT1, IL4I1, MIF, SDS, SDSL) were expressed differentially. The area under the curve (AUC) values of these DEGs enriched in pathways mostly were greater than 0.8. As a result, a connected network of metabolites and genes in the pathways were established, which provides insights into the credibility of selected metabolites. CONCLUSION: The newly identified metabolic biomarkers display a high potential to be developed into a promising tool for TB screening, diagnosis, and therapeutic effect monitoring.

Classification of Alzheimer's disease using a self-smoothing operator.

In this study, we present a system for Alzheimer's disease classification on the ADNI dataset. Our system is able to learn/fuse registration-based (matching) and overlap-based similarity measures, which are enhanced using a self-smoothing operator (SSO). From a matrix of pair-wise affinities between data points, our system uses a diffusion process to output an enhanced matrix. The diffusion propagates the affinity mass along the intrinsic data space without the need to explicitly learn the manifold. Using the enhanced metric in nearest neighborhood classification, we show significantly improved accuracy for Alzheimer's Disease over Diffusion Maps and a popular metric learning approach. State-of-the-art results are obtained in the classification of 120 brain MRIs from ADNI as normal, mild cognitive impairment, and Alzheimer's.