4-Deoxy-l-erythro-5-hexoseulose Uronate (DEH) and DEH Reductase: Key Molecule and Enzyme for the Metabolism and Utilization of Alginate

4-Deoxy-l-erythro-5-hexoseulose uronate (DEH), DEH reductase, and alginate lyase have key roles in the metabolism of alginate, a promising carbon source in brown macroalgae for biorefinery. In contrast to the widely reviewed alginate lyase, DEH and DEH reductase have not been previously reviewed. Here, we summarize the current understanding of DEH and DEH reductase, with emphasis on (i) the non-enzymatic and enzymatic formation and structure of DEH and its reactivity to specific amino groups, (ii) the molecular identification, classification, function, and structure, as well as the structural determinants for coenzyme specificity of DEH reductase, and (iii) the significance of DEH for biorefinery. Improved understanding of this and related fields should lead to the practical utilization of alginate for biorefinery.

The Role of Matrix Metalloproteinases in Endometriosis: A Potential Target

Endometriosis is a condition that is influenced by hormones and involves stroma and glands being found outside the uterus; there are increases in proliferation, invasion, internal bleeding, and fibrosis. Matrix metalloproteinases (MMPs) have been suggested to be crucial in the progression of invasion. The MMP family includes calcium-dependent zinc-containing endopeptidases, some of which not only affect the process of cell invasion but also participate in other physiological and pathological processes, such as angiogenesis and fibrosis. MMPs act as downstream-targeted molecules and their expression can be regulated by numerous factors such as estrogen, oxidative stress, cytokines, and environmental contaminants. Given their unique roles in endometriosis, MMPs may become effective biomarkers of endometriosis in the future. In the present review, we summarize the current literature on MMPs regarding their classification, function, and potential value for endometriosis, which may contribute to our knowledge of MMPs and MMP-targeted interventions.

Insights into Enhancer RNAs: Biogenesis and Emerging Role in Brain Diseases

Enhancers are cis-acting elements that control the transcription of target genes and are transcribed into a class of noncoding RNAs (ncRNAs) termed enhancer RNAs (eRNAs). eRNAs have shorter half-lives than mRNAs and long noncoding RNAs; however, the frequency of transcription of eRNAs is close to that of mRNAs. eRNA expression is associated with a high level of histone mark H3K27ac and a low level of H3K27me3. Although eRNAs only account for a small proportion of ncRNAs, their functions are important. eRNAs can not only increase enhancer activity by promoting the formation of enhancer-promoter loops but also regulate transcriptional activation. Increasing numbers of studies have found that eRNAs play an important role in the occurrence and development of brain diseases; however, further research into eRNAs is required. This review discusses the concept, characteristics, classification, function, and potential roles of eRNAs in brain diseases.

Applying Multivariate Statistical Methods for Predicting Pinus Forest Fire Danger at Bidoup-Nui Ba National Park

The paper presents results of applying multivariate statistical methods (CCA: canonical correlation analysis and DFA: discriminant function analysis) for determining canonical correlation between a set of variables {T, H, m1, K} and a set of variables {Pc, Tc} (T: temperature, H: relative humidity, m1: mass of dry fuels, K: burning coefficient, K = m1/M, with M: total mass of fire fuels, Pc: % burned fuels and Tc: burningtime) as well as through results of discriminant function analysis DFA to set up models of predicting forest fire danger at Bidoup - Nui Ba National Park. From research data in November, December, January, February and March in the period of 2015-2017 from 340 sampling plots (each 2mx2m), at Bidoup - Nui Ba National Park, we carry on data processing on Excel (calculating) and Statgraphics (multivariate statistical methods: CCA&DFA). Three results were revealed from our analysis: (i) Canonical correlation between a set of variables {T, H, m1, K} and a set of variables {Pc, Tc} is highly significant (R = 0.675581 & P = 3.17*10-58<< 0.05); therefore, we can use a set of variables {T, H, m1, K} in models of predicting forest fire danger, (ii) Coefficients of standardized & unstandardized canonical discriminant functions (SCDF &UCDF) and Fisher classification function (FCF) are determined, (iii) Setting up two models of predicting forest fire danger (Mahalanobis distance model & Fisher classification function model).

Analisis Diskriminan dalam Menentukan Fungsi Pengelompokan Kabupaten/Kota di Indonesia berdasarkan Indikator Indeks Pembangunan Manusia

The Human Development Index (HDI) is a measure used to measure the success of human development in an area. There are several indicators used to compile the HDI value. Previously, regencies/cities were grouped based on the HDI indicator. The grouping is done using K-means cluster analysis with 4 categories, namely regencies/cities that have low, medium, high, and very high HDI indicator values. From the results of determining the category of the HDI indicator in an area, we need a function that can be used to classify an object into one of the HDI indicator value categories. The compilation of the classification function is carried out using discriminant analysis. The results obtained from the discriminant analysis are that there are 10 variables or indicators that fall into the discriminant function. The resulting discriminant function is quite good in classifying each group with a success rate of more than 85% and the discriminant function is supported by a fairly good validation success rate, namely with a classification accuracy of 93.20%.

FORMULAIC LANGUAGE IN AERONAUTICAL ENGLISH – FRIEND OR FOE

The paper discusses formulaic language, its classification, function, and its role in Aeronautical English. On the one hand, using idiomatic expressions in aviation communication may lead to ambiguity, confusion and communication breakdown. On the other hand, teaching formulaic expressions to student pilots and air-traffic controllers can have positive effect on their fluency and help them develop their interactive communicative skills. Despite the fact that research on formulaic language acquisition has been modest, the paper suggests that it should be incorporated in an aeronautical English syllabus.

Generalized Fuzzy c-Means Clustering and its Property of Fuzzy Classification Function

This study shows that a generalized fuzzy c-means (gFCM) clustering algorithm, which covers both standard and exponential fuzzy c-means clustering, can be constructed if a given fuzzified function, its derivative, and its inverse derivative can be calculated. Furthermore, our results show that the fuzzy classification function for gFCM exhibits a behavior similar to that of both standard and exponential fuzzy c-means clustering.

Research of matrix metalloproteinases in therapeutic dentistry

This article the properties of matrix metalloproteinases, their classification, function and role in the development of dental diseases are presented. The analysis of matrix metalloproteinases has been performed, which proves their important role in the physiological and pathological processes of the oral cavity. The possibility of using matrix metalloproteinases as part of one of the methods for diagnosing diseases and using them to evaluate the effectiveness of treatment has been considered. The structure of different types of metalloproteinases, as well as a model of the catalytic domain of the MMP-8 molecule has been presented.