Attribute Reduction Algorithm of Neighborhood Rough Set Based on Supervised Granulation and Its Application

In neighborhood rough set theory, attribute reduction based on measure of information has important application significance. The influence of different decision classes was not considered for calculation of traditional conditional neighborhood entropy, and the improvement of algorithm based on conditional neighborhood entropy mainly includes of introducing multi granularity and different levels, while the mutual influence between samples with different labels is less considered. To solve this problem, this paper uses the supervised strategy to improve the conditional neighborhood entropy of three-layer granulation. By using two different neighborhood radii to adjust the mutual influence degree of different label samples, and by considering the mutual influence between conditional attributes through the feature complementary relationship, a neighborhood rough set attribute reduction algorithm based on supervised granulation is proposed. Experiment results on UCI data sets show that the proposed algorithm is superior to the traditional conditional neighborhood entropy algorithm in both aspects of reduction rate and reduction accuracy. Finally, the proposed algorithm is applied to the evaluation of fatigue life influencing factors of titanium alloy welded joints. The results of coupling relationship analysis show that the effect of joint type should be most seriously considered in the calculation of stress concentration factor. The results of influencing factors analysis show that the stress range has the highest weight among all the fatigue life influencing factors of titanium alloy welded joint.

Nano-enhanced biolubricant in sustainable manufacturing: From processability to mechanisms

To eliminate the negative effect of traditional metal-working fluids and achieve sustainable manufacturing, the usage of nano-enhanced biolubricant (NEBL) is widely researched in minimum quantify lubrication (MQL) machining. It’s improved tool wear and surface integrity have been preliminarily verified by experimental studies. The previous review papers also concluded the major influencing factors of processability including nano-enhancer and lubricant types, NEBL concentration, micro droplet size, and so on. Nevertheless, the complex action of NEBL, from preparation, atomization, infiltration to heat transfer and anti-friction, is indistinct which limits preparation of process specifications and popularity in factories. Especially in the complex machining process, in-depth understanding is difficult and meaningful. To fill this gap, this paper concentrates on the comprehensive quantitative assessment of processability based on tribological, thermal, and machined surface quality aspects for NEBL application in turning, milling, and grinding. Then it attempts to answer mechanisms systematically considering multi-factor influence of molecular structure, physicochemical properties, concentration, and dispersion. Firstly, this paper reveals advanced lubrication and heat transfer mechanisms of NEBL by quantitative comparison with biolubricant-based MQL machining. Secondly, the distinctive filmformation, atomization, and infiltration mechanisms of NEBL, as distinguished from metal-working fluid, are clarified combining with its unique molecular structure and physical properties. Furtherly, the process optimization strategy is concluded based on the synergistic relationship analysis among process variables, physicochemical properties, machining mechanisms, and performance of NEBL. Finally, the future development directions are put forward aiming at current performance limitations of NEBL, which requires improvement on preparation and jet methods respects. This paper will help scientists deeply understand effective mechanism, formulate process specifications, and find future development trend of this technology.

tRNAleu A3243G Gene Mutation of Mitochondrial DNA as a Risk Factor for Diabetic Retinopathy in Type 2 Diabetes Mellitus in Bali

Introduction: Diabetic retinopathy is one of the chronic complications in patients with diabetes mellitus caused by progressive microangiopathy. Various types of risk factors can affect the occurrence of diabetic retinopathy, one of which is mitochondrial DNA mutations in the tRNAleu A3243G gene that is common in T2DM. This study was conducted with the aim to identify whether the mutation of the tRNAleu A3243G gene acts as a risk factor for diabetic retinopathy in T2DM patients in Bali. Material and Methods: This study used a case control design with 35 T2DM patients with diabetic retinopathy and 35 T2DM patients without diabetic retinopathy. The techniques used to identify these mutations are PCR and DNA sequencing. Results: Based on the results obtained, no mutations were found in the tRNAleu A3243G gene in the entire sample. Therefore, the relationship analysis of the two variables cannot be identified. Conclusions: Mutations of the tRNAleu A3243G gene that were not successfully identified in this study can be concluded not play a role as a risk factor for diabetic retinopathy. Keywords: Diabetic Retinopathy, Diabetes Mellitus, tRNAleu Gene Mutation, Mitochondrial DNA.

Synthesis, Molecular Modeling, DNA Damage Interaction, and Antioxidant Potential of Hesperidin Loaded on Gold Nanoparticles

The flavonoglycone hesperidin is recognized as a potent anti-inflammatory, anticancer, and antioxidant agent. However, its poor bioavailability is a crucial bottleneck regarding its therapeutic activity. Gold nanoparticles are widely used in drug delivery because of its unique properties that differ from bulk metal. Hesperidin loaded gold nanoparticles were successfully prepared to enhance its stability and bioactive potential, as well as to minimize the problems associated with its absorption. The free radical scavenging activities of hesperidin, gold nanoparticles, and hesperidin loaded gold nanoparticles were compared with that of Vitamin C and subsequently evaluated in vitro using 2,2-diphenyl-1-picrylhydrazyl assay. The antioxidant pharmacophore-based structure-activity relationship analysis was assessed by the density functional theory as well as quantum chemical calculations. Moreover, the structural properties were utilized using Becke’s three-parameter hybrid exchange and Lee-Yang-Parr’s correction of functional approaches. Hesperidin-loaded gold nanoparticles were found to decrease hydrogen peroxide (H2O2) and thus induce Deoxyribonucleic acid (DNA) instability. In addition, hesperidin-gold nanoparticles were observed to display important antioxidant potential as well as ameliorate the functional activity of macrophages against Escherichia coli, possibly protecting DNA. These particles might be appropriate for clinical trials and could prove useful for the treatment of various life-threatening disorders.

The Study of Steaming Durations and Temperatures on the Chemical Characterization, Neuroprotective, and Antioxidant Activities of Panax notoginseng

Panax notoginseng (PN) is one of the most valuable traditional Chinese medicines and has extensive pharmacological effects. Recent studies demonstrated that PN exhibited pharmacological effect related to Alzheimer’s disease (AD). However, whether steaming process can boost its anti-AD activity is still unexplored. To fill this gap, effects of steaming durations and temperatures on the chemical characterization, neuroprotective and antioxidant activities of PN were systematically investigated in this study. HPLC fingerprint coupled with quantitative analysis demonstrated striking conversion of original saponins to less polar ones with the increase in the steaming time and temperature. In the viewpoint of anti-AD activity on neuroprotective and antioxidant effects, several steamed PN samples (110°C-6/8/10 h, 120°C ‐4/6 h samples) displayed a significant increase both in cell viability and oxygen radical absorption capacity (ORAC) values compared with the no steamed one ( P < 0.01 or P < 0.005 ). Steaming temperature had the greater impact on the change of chemical composition and anti-AD activity of PN. Moreover, the spectrum-effect relationship analysis revealed that the transformed saponins were partially responsible for the increased neuroprotective and antioxidant effects of steamed PN. Therefore, steamed PN could be used as a potential crude drug for prevention and treatment of AD.

Catalase (CAT) Gene Family in Wheat (Triticum aestivum L.): Evolution, Expression Pattern and Function Analysis

Catalases (CATs) are present in almost all living organisms and play important roles in plant development and response to various stresses. However, there is relatively little information on CAT genes in wheat and related Triticeae species. A few studies on CAT family genes in wheat have been reported. In this study, ten CAT proteins (TaCATs) were identified in wheat and classified into three groups based on their phylogenetic features and sequence analysis. The analysis of the structure and motif composition of the TaCAT proteins suggested that a segmental duplication event occurred in the TaCAT gene family. Collinearity relationship analysis among different species showed that there were three orthologous CAT genes in rice and in maize. By analyzing the cis-elements in the promoter regions, we speculated that TaCAT genes expression might be regulated by light, oxygen deficit, methyl jasmonate and abscisic acid, and by transcription factors such as MYB. A Gene Ontology (GO)-based analysis showed that TaCAT proteins may be related to the response to various stresses, are cytoplasm localized, and may function as antioxidant enzymes. RT-qPCR and transcriptome data analyses exhibited distinct expression patterns of TaCAT genes in different tissues and in response to various treatments. In this study, a comprehensive analysis of wheat CAT genes was performed, enriching our knowledge of CAT genes and providing a foundation for further functional analyses of this gene family in wheat.

Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity

Lonicerae japonicae flos (L. japonicae flos, Lonicera japonica Thunb.) is one of the most commonly prescribed botanical drugs in the treatment or prevention of corona virus disease 2019. However, L. japonicae flos is often confused or adulterated with Lonicerae flos (L. flos, Lonicera macrantha (D.Don) Spreng., Shanyinhua in Chinese). The anti-SARS-CoV2 activity and related differentiation method of L. japonicae flos and L. flos have not been documented. In this study, we established a chemical pattern recognition model for quality analysis of L. japonicae flos and L. flos based on ultra-high performance liquid chromatography (UHPLC) and anti-SARS-CoV2 activity. Firstly, chemical data of 59 batches of L. japonicae flos and L. flos were obtained by UHPLC, and partial least squares-discriminant analysis was applied to extract the components that lead to classification. Next, anti-SARS-CoV2 activity was measured and bioactive components were acquired by spectrum-effect relationship analysis. Finally, characteristic components were explored by overlapping feature extracted components and bioactive components. Accordingly, eleven characteristic components were successfully selected, identified, quantified and could be recommended as quality control marker. In addition, chemical pattern recognition model based on these eleven components was established to effectively discriminate L. japonicae flos and L. flos. In sum, the demonstrated strategy provided effective and highly feasible tool for quality assessment of natural products, and offer reference for the quality standard setting.