Results Of Cluster Analysis Research Articles

Identification of a novel mycovirus belonging to the “flexivirus”-related family with icosahedral virion

Abstract The order Tymovirales currently comprises five viral families with positive-sense RNA ((+)RNA) genomes that infect plants, fungi, and insects. Virion morphologies within the order Tymovirales differ between families, with icosahedral virions in the Tymoviridae and filamentous virions in the other “flexi”viridae families. Despite their different morphologies, these viruses are placed in the same order based on phylogenetic analyses of replicase-associated polyproteins. However, one of the families in the Tymovirales, Deltaflexiviridae, is considered to be capsidless because there have been no published reports of virion isolation. Here we report that a new “flexivirus”-related (+)RNA virus, prospectively named Fusarium oxysporum icosahedral virus 1 (FoIV1), is icosahedral, and that most deltaflexiviruses may have icosahedral virions. Phylogenetic analyses based on replicase-associated polyproteins indicated that FoIV1 forms a distinct group in the Tymovirales with some viruses originally assigned to the Deltaflexiviridae. Electron microscopy, protein analysis, and protein structure predictions indicate that FoIV1 ORF4 encodes a single jelly-roll (SJR)-like coat protein (CP) that constitutes the icosahedral virions. Results of clustering analyses based on amino acid sequences and predicted CP structures suggested that most of the deltaflexiviruses have icosahedral virions composed of SJR-like CPs as in FoIV1, rather than having filamentous virions or capsidless. These results challenge the conventional understanding of viruses in the order Tymovirales, with important implications for revising its taxonomic framework and providing insights into the evolutionary relationships within this diverse and broad host range group of (+)RNA viruses.

Morphological Diversity of “Tuni” and “Afo” Cloves, Endemic to the Maluku Islands, Indonesia

“Tuni” and “Afo” cloves are endemic clove varieties from the Maluku islands. Until now, there is still little information on morphological diversity in plant populations and information on the characteristics between the two varieties. The research aims to provide information on the morphological diversity and characteristics of “Tuni” and “Afo” cloves from the Maluku Islands. Morphological characterization of the “Tuni” variety of cloves was carried out at its distribution location on Ambon Island, Maluku Province. In contrast, “Afo” cloves were characterized at their distribution location on Ternate Island, North Maluku Province. The research was carried out in July 2023-May 2024. The used for morphological identification was the modified Tropical Fruit Descriptors. The characterized clove plants consisted of 30 “Tuni” clove plants and 30 “Afo” clove plants, so a total of 60 plants were characterized. The results of the Hierarchical Cluster Analysis (HCA) based on 54 morphological characters that were carried out showed two groups with a dissimilarity coefficient of 44%. The first group is a group of “Tuni” clove accessions, which are clustered with a similarity of 91%, and the second group is a group of “Afo” clove accessions, which are clustered with a similarity of 90%. The results of Principle Component Analysis (PCA) obtained a total diversity of 75.4%, where the specific characteristics of “Tuni” cloves obtained were stem bark color, crown shape, branching angle, leaf thickness, old leaf color, shoot color, leaf petiole tip color, flower stalk weight, flower length, flower tube diameter. The specific characteristics of “Afo” cloves obtained from PCA are plant height, stem circumference, North-South canopy width, East-West canopy width, leaf length, leaf texture, leaf spiciness, ripe picked flower color, picked ripe flower crown color, ripe fruit color, and color seed.

Metabolite and mineral contents in root, seed, testa, stem and leaf of Peganum harmala L

In order to investigate the distribution and accumulation characteristics of metabolites and mineral elements in different parts of Peganum harmala L. (P. harmala), and the synergistic or antagonistic effects between them. In this study, nuclear magnetic resonance (NMR), high performance liquid chromatography (HPLC) and inductively coupled plasma optical emission spectrometer (ICP-OES) were used to determine the contents of metabolites (proline, phosphorylcholine, choline, lysine, 4-hydroxyisoleucine, asparagine, acetic acid, sucrose, harmaline and vasicine) and mineral elements (Ca, Mg, K, P, Na, Cr, Cu, Fe, Zn, Mn, Ni, C, N) in five parts of P. harmala, including root, seed, testa, stem and leaf, and to analyze the relationship among the contents of metabolites and mineral elements. The results showed that the contents of acetic acid, proline, lysine, sucrose and Fe in the root were higher than those in other parts, and the contents of harmaline, phosphorylcholine, P, C, N and Zn in the seeds were the highest. The leaves were rich in vasicine, Na, K, Ca, Mg and Mn. The principal component analysis (PCA) showed that the cumulative variance contribution of the first two principal components was 69.00 %, and the loading values of K, Cu and sucrose were higher, which was consistent with the results of biplot and cluster analysis(HCA). Correlation analysis (CA) results showed that there was a strong overall correlation between the different components of seeds and leaves, and the correlation was greater than that of other parts. The results of this study are helpful to understand the correlation of functional traits among different parts of plants, and determine the internal mechanism of controlling functional traits and the proportional relationship between traits, so as to provide a reference for the resource utilization of plants.

Metagenomic Insights into Coal Slag Remediation Effects on Soil and Microbial Health in Qinghai’s Muli Coal Mine

Long-term coal mining in the Muli coal mine area of Qinghai Province has degraded soil quality and reduced microbial diversity, making it imperative to implement effective ecological restoration measures to restore soil quality and enhance ecosystem functions. This study evaluated soil samples under 11 ecological restoration treatments using metagenomic sequencing combined with soil quality analysis to explore the responses of the microbial community structure and function to identify effective restoration measures. This study demonstrated that ecological restoration significantly increased the soil microbial diversity and richness, with the MLII1 (soil samples treated with a chemical weathering agent, attapulgite, and a microbial agent) and MLIII1 (soil samples treated with sheep manure (2.4 kg/m2), granular organic fertilizer (1.2 kg/m2), and the microbial agent) treatment groups performing exceptionally well. Further analysis of the functional networks revealed that although the MLII2 (soil samples treated with the chemical weathering agent and attapulgite) treatment group did not exhibit the highest species diversity, it exhibited the highest functional network complexity. The results of hierarchical clustering analysis showed that the microbial community of the MLII2 treatment group was most similar to that of the natural meadows compared to the other treatment groups. From the perspective of overall ecological restoration, this study concluded that the MLII2 treatment group exhibited the most favorable ecological restoration outcomes. This finding emphasizes the importance of not only enhancing microbial diversity but also prioritizing the restoration of community functions, especially for the recovery of fragile high-altitude ecosystems.

Research on Statistical Assessment Methods of Stock Investment Value-Taking Education Industry as Example

Abstract: This paper selects the financial statement data of 18 listed companies in the field of education and selects 9 financial indicators from the four aspects of solvency, profitability, development ability and operation ability that can reflect the comprehensive strength of listed companies. Finally, the stocks of 18 listed companies were divided into three categories: high-value stocks, potential stocks and low-value stocks according to the comprehensive strength of the companies. The results show that: (1) From the comparison between the rankings of the selected 18 stocks combined with the traditional methods by combining principal component analysis and entropy weight method, it can be seen that for the comprehensive multi-index evaluation analysis in the past five years, the ranking agreement between the two methods can reach 80% or more. Due to the unstable fluctuations of the stock market, the consistency between the analysis results and investment recommendations obtained in this paper and the actual investment situation of the stock market can also exceed 60%. (2) From the results of cluster analysis, Chuanzhi Education, Entrepreneurship Dark Horse, Guoxin Culture, China Hi-Tech and Action Education are all high-value stocks in the education category, while Meijim, Qinshang Co., Ltd., and Kaiwen Education are potential education stocks.

Species Composition of Fish Larvae and Juveniles in the Nanji Islands, China

To describe the species composition of fish larvae and juveniles in the Nanji Islands, monthly collection was conducted at 12 stations around the Nanji Islands from March 2023 to February 2024 by using horizontal tow at the surface layer. The fish larvae and juveniles were collected by a larva net (1.3 m mouth diameter, 0.5 mm mesh aperture). A total of 6446 fish larvae and juveniles were collected, belonging to 59 species and 54 genera in 11 families. Most of them were preflexion larvae (93.31%). Gobiidae, with eight species, was the most diverse family. Based on the index of relative importance (IRI) result, the dominant species was Sebastiscus marmoratus (Cuvier, 1829), accounting for 84.52% of the total number of samples collected. The common species were Stolephorus commersonii Lacepède, 1803; Omobranchus elegans (Steindachner, 1876); Nibea albiflora (Richardson, 1846); Parablennius yatabei (Jordan & Snyder, 1900); Lateolabrax maculatus (McClelland, 1844); and Odontamblyopus lacepediiand (Temminck & Schlegel, 1845). Other species were all rare species. The highest species number was in September (18 species), and the highest density was in December. Only one fish larva was collected in April. Pielou’s evenness index was highest in November, while Margalef’s richness index and Shannon–Wiener diversity were highest in September. The result of cluster analysis showed that the 11 months (except April) could be divided into four groups. The species number, density, and three diversity indexes showed no significant correlation with temperature and salinity.

Variability of Morphological Characters of the Genus Alburnoides (Pisces, Leuciscidae) from Watercourses in Southern Russia

The variability of the morphological characters of the genus Alburnoides Jeitteles, 1861 from watercourses in the south of Russia (five rivers of the Crimean Peninsula and two rivers of the Krasnodar Territory) is considered. It has been established that in spirlins within the study areas, body sizes average from 60.1 ± 1.45 mm in individuals from the river Gostagayka (Krasnodar region) up to 88.2 ± 1.87 mm in fish from the river Angara (Crimean Peninsula). Using the Mann–Whitney test, statistically significant differences were registered between the samples in most plastic characters; they were absent in meristic characters. In the studied regions, heterogeneity in the structure of the genus Alburnoides was noted: according to the results of cluster analysis for the totality of all studied characters, the greatest similarity was found in samples from Crimean rivers that are geographically close to each other (rivers Chernaya, Belbek, Kacha and Alma), but group from the river Angara adjoins them at a higher level of divergence. A separate group is formed by samples from the rivers of the Krasnodar Territory. The obtained data are consistent with the literary information on the formation of the ichthyofauna in the rivers of Crimea; the established clear differences between the charaters from the rivers of southern Russia require a more detailed study.

Simple Sequence Repeat Marker-Based Genetic Diversity and Chemical Composition Analysis of Ancient Camellia sinensis in Jiulong County, Sichuan Province, China.

The ancient tea plant germplasm resources are rich in genetic diversity and provide an important basis for the genetic diversity in tea germplasm resources. To explore the genetic diversity of ancient tea plant germplasm resources in Jiulong County, Sichuan Province. 59 ancient tea tree germplasm resources were analyzed using simple sequence repeat (SSR) molecular markers and chemical composition analysis. The results showed that a total of 83 alleles were amplified by 23 pairs of SSR primers, with an average observed allele number (Na) of 3.6 and an effective allele number (Ne) of 2.335. The average Shannon information index (I) and the polymorphic information content (PIC) of the primers were 0.896 and 0.446, respectively. The results of the UPGMA cluster analysis showed that 59 ancient tea tree samples could be classified into five different subgroups. Based on the results of chemical composition analysis, two specific tea germplasm resources with high amino acid content, 10 excellent germplasm resources with tea polyphenol content over 20% and some other tea germplasm resources were identified. This study reveals that Jiulong's ancient tea tree germplasm exhibits significant genetic diversity and includes valuable tea tree planting resources. These findings provide a foundational framework for the conservation, detailed exploration and sustainable utilization of these resources.

Evaluating the thermal stability of hazelnut oil in comparison with common edible oils in Turkey using ATR infrared spectroscopy

Hazelnut oil (HO), a high-quality nutrient rich in monounsaturated fatty acids and antioxidants, is not commonly used due to a lack of awareness of its nutritional benefits. The purpose of the current study is to evaluate the stability of HO during the heating process in comparison with Riviera olive, sunflower and corn oils, the most commonly used edible oils in Turkey, by using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR). The oils were heated at 180 °C for 24h, divided into 8-h periods over the course of three days and the measurements were performed on oil samples taken every 2h. Thermogravimetric analysis-differential thermal analysis (TGA-DTA) and the measurement of the specific absorbance of conjugated dienes and trienes by using UV-visible spectroscopy were also performed to confirm the ATR-FTIR data. The spectroscopic results showed that the heating process led to an increase in the amount of primary and secondary oxidation products, a decrease in the amount of cis fatty acids and an increase in the amount of trans fatty acids in all oils. Based on the results of linear regression analysis, HO has the lowest slope value for all parameters, indicating that it is the most resistant to thermal oxidation. Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and TGA-DTA results confirmed that HO has a higher thermal stability than the other oils. These findings revealed that HO has the highest thermal stability among the oils compared and can be utilized as a healthy alternative for cooking. This study also showed that ATR-FTIR spectroscopy holds significant promise in oil analysis, competing with routine quality control techniques.

Exploring and validating the necroptotic gene regulation and related lncRNA mechanisms in colon adenocarcinoma based on multi-dimensional data.

Necroptosis is intimately associated with the initiation and progression of colon adenocarcinoma (COAD). However, studies on necroptosis-related genes (NRGs) and the regulating long non-coding RNAs (NRGlncRNAs) in the context of COAD are limited. We retrieved the cancer genome atlas (TCGA) to collect datasets of NRGs and NRGlncRNAs on COAD patients. The risk model constructed using Cox and least absolute shrinkage and selection operator (LASSO) regression was then employed to identify NRGs and NRGlncRNAs with prognostic significance. Subsequently, we validated the results using gene expression omnibus (GEO) datasets from different populations, conducted Mendelian randomization (MR) analysis to explore the potential causal relationships between prognostic NRGs and COAD, and conducted cell experiments to verify the expression of prognostic NRGlncRNAs in COAD. Furthermore, we explored potential pathways and regulatory mechanisms of these prognostic NRGlncRNAs and NRGs in COAD through enrichment analysis, immune cell correlation analysis, tumor microenvironment analysis, immune checkpoint analysis, tumor sample clustering, and so on. We identified eight NRGlncRNAs (AC245100.5, AP001619.1, LINC01614, AC010463.3, AL162595.1, ITGB1-DT, LINC01857, and LINC00513) used for constructing the prognostic model and nine prognostic NRGs (AXL, BACH2, CFLAR, CYLD, IPMK, MAP3K7, ATRX, BRAF, and OTULIN) with regulatory relationships with them, and their validation was performed using GEO and GWAS datasets, as well as cell experiments, which showed largely consistent results. These prognostic NRGlncRNAs and NRGs modulate various biological functions, including immune inflammatory response, oxidative stress, immune escape, telomere regulation, and cytokine response, influencing the development of COAD. Additionally, stratified analysis of the high-risk and low-risk groups based on the prognostic model revealed elevated expression of immune cells, increased expression of tumor microenvironment cells, and upregulation of immune checkpoint gene expression in the high-risk group. Finally, through cluster analysis, we identified tumor subtypes, and the results of cluster analysis were essentially consistent with the analysis between risk groups. The prognostic NGRlncRNAs and NRGs identified in our study serve as prognostic indicators and potential therapeutic targets for COAD, providing a theoretical basis for the clinical diagnosis and treatment of COAD and offering guidance for further research.

Analysis of codon usage patterns in complete plastomes of four medicinal Polygonatum species (Asparagaceae).

Polygonati Rhizoma and Polygonati odorati Rhizoma, known as "Huangjing" and "Yuzhu" in China, are medicinal Polygonatum species resources with top-grade medical and edible properties. The chloroplast (cp) genome has been used to study species diversity, evolution, and breeding of species for applications in genetic engineering. Codon usage bias (CUB), a common and complex natural phenomenon, is essential for studies of codon optimization of exogenous genes, genetic engineering, and molecular evolution. However, the CUB of medicinal Polygonatum species chloroplast genomes has not been systematically studied. In our study, a detailed analysis of CUB was performed in the medicinal Polygonatum species chloroplast genomes. We investigated the codon bias of 204 plastid protein-coding genes (PCGs) in 4 medicinal Polygonatum species using CodonW and CUSP online software. Through the analysis of the codon bias index, we found that the medicinal Polygonatum species chloroplast genomes had weak codon usage bias. In addition, our results also showed a high preference for AT bases in medicinal Polygonatum species chloroplast genomes, and the preference to use AT-ending codons was observed in these species chloroplast genomes. The neutrality plot, ENC plot, PR2-Bias plot, and correspondence analysis showed that compared with mutation pressure, natural selection was the most important factor of CUB. Based on the comparative analysis of high-frequency codons and high expression codons, we also determined the 10-11 optimal codons of investigative medicinal Polygonatum species. Furthermore, the result of RSCU-based cluster analysis showed that the genetic relationship between different medicinal Polygonatum species could be well reflected. This study provided an essential understanding of CUB and evolution in the medicinal Polygonatum species chloroplast genomes.

Using Multi-Encoder Semi-Implicit Graph Variational Autoencoder to Analyze Single-Cell RNA Sequencing Data.

Rapid advances in single-cell RNA sequencing (scRNA-seq) have made it possible to characterize cell states at a high resolution view for large scale library. scRNA-seq data contains a great deal of biological information, which can be mainly used to discover cell subtypes and track cell development. However, traditional methods face many challenges in addressing scRNA-seq data with high dimensions and high sparsity. For better analysis of scRNA-seq data, we propose a new framework called MSVGAE based on variational graph auto-encoder and graph attention networks. Specifically, we introduce multiple encoders to learn features at different scales and control for uninformative features. Moreover, different noises are added to encoders to promote the propagation of graph structural information and distribution uncertainty. Therefore, some complex posterior distributions can be captured by our model. MSVGAE maps scRNA-seq data with high dimensions and high noise into the low-dimensional latent space, which is beneficial for downstream tasks. In particular, MSVGAE can handle extremely sparse data. Before the experiment, we create 24 simulated datasets to simulate various biological scenarios and collect 8 real-world datasets. The experimental results of clustering, visualization and marker genes analysis indicate that MSVGAE model has excellent accuracy and robustness in analyzing scRNA-seq data.

Characterization and structure-functionality analysis of starch in different layers of Lycoris chinensis bulb scales

According to literature, the size distribution of starch granules varies significantly in different layers of Lycoris chinensis bulb scales, however its effect on structural and physicochemical properties of starch still remains unclear. In this study, outer, middle and inner layers of bulb scales of L. chinensis were compared for starch characteristics. Also, the structure-functionality association was investigated based on correlation analysis and hierarchical cluster analysis, using 37 starch quality traits. Compared to commonly consumed starches with similar amylose content, L. chinensis starch gel had lower hardness and viscosities. Among layers, starches varied significantly in particle size, physicochemical and structural properties. As compared to middle and inner scales, the starch in outer scales had higher amylose content, hardness and viscosities, but lower gelatinization temperature, weight-average molar mass and degree of polymorphism. Correlation analysis revealed significant correlations among traits, and interestingly, gelatinization temperature (Tp) was found positively correlated to traits of molecular weight (p < 0.05). The 37 traits of starch characteristics can be divided into three subgroups, as supported by the results of Pearson correlation analysis and hierarchical cluster analysis. In general, the information presented in the current study are useful for Lycoris bulb starch utilization and insightful for a better understanding of structure-functionality association of starch.

Analysis of the genetic diversity and population structure of Tilia amurensis from China using SSR markers: Implications for conservation

Tilia amurensis is a deciduous broad-leaved tree in the Malvaceae family. It is one of the second-class key protected wild plants in China. The evaluation of genetic polymorphisms of crucial protected species is necessary for conserving germplasm resources. In this study, 15 pairs of highly polymorphic SSR primers were used to analyse the genetic diversity of eight T. amurensis populations and the population structure of nine Tilia populations distributed in China. At the population level (Na = 6.050, Ne = 2.930, I = 1.123, HO = 0.485, HE = 0.523), there was a high level of genetic diversity. The AMOVA results showed that 12 % and 88 % of the total variation occurred among and within populations, respectively. The degree of genetic differentiation was moderate (FST = 0.124), and the level of gene flow was high (Nm = 1.763). The results of UPGMA cluster analysis, PCoA and structure analysis (ΔK = 2) revealed different degrees of gene introgression between the eight T. amurensis populations and Tilia japonica as the outgroup. These findings have important implications for formulating appropriate conservation strategies.

EVALUATION OF VARIOUS COTTON GENOTYPES THROUGH GENETIC DIVERSITY ANALYSIS

Fifty-two varieties/strains of cotton were studied to explore the genetic divergence in the yield trials at Cotton Research Station, Faisalabad. The study aimed to identify strains with earliness, CLCuD tolerance, and superior yield with better fiber quality. Correlation analysis showed significant positive association of seed cotton yield (SCY) with boll number, boll weight(g), ginning out turn (GOT) and fiber length, while significant negative association with leaf curl disease and first flower appearance date was observed. Principal components analysis revealed that four out of 11 principal component showed Eigen value ˃1. The contribution of these PCs towards total variability was 76.8% with PC-1 with maximum (44.4%), followed by PC-2 (12.2%), PC-3 (10.9 %) and PC-4 (9.3%). Traits including yield, bolls number, boll weight and plant height exhibited noteworthy positive factor loading in PC-1, while cotton leaf curl virus, days to first boll opening and first flower had maximum negative loadings. The findings of cluster analysis indicated that the genotypes present in cluster V (FH-1131, FH-1133, FH-1214, FH-525, FH-453, FH-333, FH-1132, FH-1135, FH-416, FH-1134 and FH-938) have excellent combination of all desirable traits viz., earliness, fiber quality, seed cotton yield (SCY) and its contributing traits. As apparent from the results of cluster and principal components analyses, topmost genotypes based on genetic divergence data may also be tested in provincial and national yield trials because they have combination of better yield and quality parameters.

Sensitivity to rewards and punishments in karate athletes: an examination of the temperamental characteristics and profile of karate competitors according to the revised reinforcement sensitivity theory

BackgroundThe revised Reinforcement Sensitivity Theory (rRST) assumes the existence of three systems controlling motivation and behavior: the behavioral activation system (BAS), the behavioral inhibition system (BIS), and the fight-flight-freeze system (FFFS). This study aims to examine for the first time the features of BAS, BIS, and FFFS among karate players in comparison with athletes representing other sports disciplines (physical education students) and physically inactive people. The specific configuration of temperament traits and profiles characterizing karate players will also be found.MethodsThe cross-sectional study was performed among male karate athletes and control groups (physically active and inactive men). The study used the modified Reinforcement Sensitivity Questionnaire (rRSQ) to measure BAS, BIS, and FFFS.ResultsThe ANOVA showed that both karate competitors KS and KK scored significantly higher in BAS than the sample of PI participants. In addition, KK athletes scored significantly lower in Freeze than in PI and KS groups. Research also suggests that KK athletes presented significantly lower overall scores in FFFS than PI individuals. Furthermore, the results of K-means cluster analysis indicated the existence of two distinct patterns of temperamental traits: (1) Cluster 1 suggests avoidance tendencies (high Flight and Freeze, and low BAS, BIS, and Fight levels); while (2) the Cluster 2 describes approach tendencies (high BIS, BAS and Fight scores, and low levels of Flight and Freeze). Significantly more KK athletes were included in Cluster 2 than in Cluster 1, compared to PI, PA, and KS samples.ConclusionsThe research indicates that individuals engaged in karate, particularly those practicing Kyokushin karate, tend to exhibit a heightened sensitivity to rewards (high BAS). This finding holds significance for coaches and sports instructors, suggesting that motivating karate athletes through incentives is more effective, while the use of punishment should be minimized during training. Additionally, the study proposes that the practice of Kyokushin karate has the potential to significantly diminish the freezing response in threatening situations and enhance overall fear management by reducing levels of the Fight-Flight-Freeze System (FFFS). Consequently, the Kyokushin karate style may be considered more advantageous than the Karate Shotokan (KS) style in these aspects, despite both styles contributing to the improvement of BAS. Given that a higher BAS is linked to positive emotions, optimism, and happiness, karate training emerges as a form of health intervention, acting as a preventive measure against mental disorders and promoting overall well-being.

Effects of bacteriocin-producing Lactiplantibacillus plantarum on bacterial community and fermentation profile of whole-plant corn silage and its in vitro ruminal fermentation, microbiota, and CH4 emissions

BackgroundSilage is widely used to formulate dairy cattle rations, and the utilization of antibiotics and methane emissions are 2 major problems for a sustainable and environmentally beneficial ruminant production systems. Bacteriocin has received considerable attention because of its potential as an alternative to antibiotics in animal husbandry. However, the impact of bacteriocin-producing lactic acid bacteria on the microbiological conversion process of whole-plant corn silage and rumen fermentation remains limited. The purpose of this study was to assess the effect of 2 class IIa bacteriocin-producing strains Lactiplantibacillus plantarum ATCC14917 and CICC24194 on bacterial community composition and ensiling profiles of whole-plant corn silage and its in vitro rumen fermentation, microbiota, and CH4 emissions.ResultsBoth bacteriocin-producing strains increased the lactic acid concentration in silage fermented for 7 d, whereas the lowest lactic acid was observed in the ATCC14917 inoculated silage fermented for 90 d (P < 0.05). The highest DM content was observed in the CICC24194 treatment (P < 0.05), and the silages treated with both strains had the lowest DM loss (P < 0.05). Bacteriocin-producing strains promoted the growth of Levilactobacillus brevis on d 60 of ensiling. In addition, treatment with bacteriocin-producing strains increased the in vitro DM digestibility (P < 0.05) and decreased the CH4 production (P < 0.05). The results of random forest and clustering analyses at the genus level showed that ATCC14917 increased the relative abundance of the influential variable Bacillus compared to that in the control group, whereas CICC24194 decreased the relative abundance of the influential variable Ruminococcaceae UCG-005. The CICC24194 treatment had the lowest total bacterial, fungal, protozoan, and methanogen populations (P < 0.05).ConclusionsBoth class IIa bacteriocin-producing L. plantarum strains improved the fermentation quality of whole-plant corn silage by regulating the bacterial community composition during ensiling, with CICC24194 being the most effective. Both bacteriocin-producing strains mitigated CH4 production and improved digestibility by modulating the interactions among rumen bacteria, protozoa, methanogens, and the composition of fibrolytic bacteria.

Measuring health literacy to inform actions to address health inequities: a cluster analysis approach based on the Australian national health literacy survey.

Measuring health literacy can inform interventions to address health inequities. This study used cluster analysis to examine health literacy data to determine if it can provide more insightful information than standard descriptive analysis to better inform intervention development. Using data from the Australian National Health Survey (2018), this study compared descriptive analysis and cluster analysis results of two states-New South Wales (NSW) and Victoria-generated from the Health Literacy Questionnaire (HLQ). Based on the nine scale scores of the HLQ, a hierarchical cluster analysis using Ward's method for linkage was undertaken. The number of NSW and Victoria respondents was 1018 and 923, respectively. The nine HLQ scale full sample mean scores from both states were similar. However, the cluster analyses identified 11 clusters for NSW and 12 clusters for Victoria. While six clusters from each state presented similar health literacy patterns, five and six clusters from NSW and Victoria, respectively, displayed unique health literacy patterns. The results demonstrate that descriptive analysis only provides an overview and may lead to one-size-fits-all interventions. The varying health literacy patterns among subgroups resulting from the cluster analysis pave the way to inform tailored actions to improve health equity.

Application of ion chromatographic fingerprint analysis for quality evaluation of tobacco flavors

Tobacco flavor, an important tobacco additive, is an essential raw material in cigarette production that can effectively improve the quality of tobacco products, add aroma and taste, and increase the suction flavor. The quality consistency of tobacco flavors affects the quality stability of branded cigarettes. Therefore, the quality control of tobacco flavors is a major concern for cigarette and flavor manufacturers. Physical and chemical indices, odor similarity, and sensory efficacy are employed to evaluate the quality of tobacco flavors, and the analysis of chemical components in tobacco flavors is usually conducted using gas chromatography (GC) and high performance liquid chromatography (HPLC). However, because the composition of tobacco flavors is complex, their quality cannot be fully reflected using a single component or combination of components. Therefore, establishing an objective analytical method for the quality control of tobacco flavors is of extreme importance. Chromatographic fingerprint analysis is routinely used for the discriminative analysis of tobacco flavors. Chromatographic fingerprints refer to the general characteristics of the concentration profiles of different chemical compounds. In the daily procurement process, fingerprints established by GC and HPLC are effective for the evaluation and identification of tobacco flavors. However, given continuous improvements in aroma-imitation technology, some flavors with high similarity cannot be directly distinguished using existing methods. In this study, a method for the determination of organic acids and inorganic anions in tobacco flavors based on ion chromatography (IC) was developed to ensure the quality consistency of tobacco flavors. A 1.0 g sample of tobacco flavors and 10 mL of deionized water were mixed and vibrated for 30 min. The aqueous sample solution was passed through a 0.45 μm membrane filter and RP pretreatment column in succession to eliminate interferences and then subjected to IC. Standard solutions containing nine organic acids and seven inorganic anions were used to identify the anions in the tobacco flavors, and satisfactory reproducibility was obtained. The relative standard deviations (RSDs) for retention times and peak areas were <0.71% and <6.02%, respectively. The chromatographic fingerprints of four types of tobacco flavors (samples A-D) from five different batches were obtained. Nine tobacco flavor samples from different manufacturers (samples AY1-AY3, BY1-BY2, CY1-CY2, DY1-DY2) were also analyzed to obtain their chromatographic fingerprints. Hierarchical cluster and similarity analyses were used to evaluate the quality of tobacco flavors from different manufacturers. Hierarchical clustering refers to the process of subdividing a group of samples into clusters that exhibit a high degree of intracluster similarity and intercluster dissimilarity. The dendrograms obtained using SPSS 12.0 indicated good quality consistency among the samples in different batches. Samples AY3, BY2, CY2, and DY1 clustered with the batches of standard tobacco flavors. Therefore, hierarchical cluster analysis can effectively distinguish the quality of products from different manufacturers. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (version 2.0) was used to evaluate the similarity between the standard tobacco flavors and products from different manufacturers. Among the samples analyzed, samples AY3, BY2, CY2, and DY1 showed the highest similarity values (>97.7%), which was consistent with the results of the hierarchical cluster analysis. This finding indicates that IC combined with chromatographic fingerprint analysis could accurately determine the quality of tobacco flavors. GC combined with ultrasonic-assisted liquid-liquid extraction was also used to analyze the tobacco flavors and verify the accuracy of the proposed method. Compared with GC coupled with ultrasonic-assisted liquid-liquid extraction, IC demonstrated more significant quality differences among certain tobacco flavors.

Classification of Human Resources Readiness in Asia: K-Means Clustering Using R Studio

This research aims to classify dichotomously the differences and diversity in human resources of all countries in the Asian region to clarify the position of each country based on the state of its human resources. Several countries were not included in the analysis due to limited data availability. This research uses the K-Mean clustering method. Clustering is an approach to dividing a set of points into similar groups called clusters. K-Mean clustering is one of the most popular unsupervised learning methods in machine learning. Based on the results of the K-Mean clustering analysis, the readiness of human resources in Asian countries shows that there are clusters or groups, with cluster 1 having as many as 29 members and cluster 2 having as many as 9 members. K-Mean clustering for the optimal number of two clusters is dichotomous, so it uses clustering assumptions between country clusters with good and poor human resource readiness.