ABSTRACT
Oral cancer is a common and deadly malignancy.While multidisciplinary treatment(mainly surgery)has been applied in the treatment of cancer treatment,early diagnosis and complete removal of the primary lesion are essential for a better prognosis.Raman spectroscopy is an optical technique that detects inelastic scattered light generated by the interaction of light and matter.It can detect the vibrational spectra of biochemical and biomolecular structures and tissue conformations,and can provide the "molecular fingerprint" for cells,tissues,and biological fluids.With the development of related technologies and optical instruments,Raman spectroscopy has been widely applied in medical fields.This article reviews the research advances and application of Raman spectroscopy in the diagnosis of oral cancer.
Subject(s)
Humans , Mouth Neoplasms , Spectrum Analysis, RamanABSTRACT
The introduction of computer methods and machine learning has drastically changed the field of drug discovery. Now, drug designing has evolved from Drug Discovery into Computer Aided Drug Discovery (CADD). There are several reasons that led to this change. The low success rate of classification of compounds into drugs and non-drugs, being one of those reasons, has evoked a renewed interest in understanding more clearly what makes a compound drug-like and its new model and methods for classification. Our work reviews a number of works based on different methods and models of machine learning techniques for identifying and classifying drug-like molecules which ranges frombasicdescriptor-basedmethodtothelatestfingerprint-basedmethod.
ABSTRACT
The hierarchical information flow through DNA-RNA-protein-metabolite collectively referred to as 'molecular fingerprint' defines both health and disease. Environment and food (quality and quantity) are the key factors known to affect the health of an individual. The fundamental concepts are that the transition from a healthy condition to a disease phenotype must occur by concurrent alterations in the genome expression or by differences in protein synthesis, function and metabolites. In other words, the dietary components directly or indirectly modulate the molecular fingerprint and understanding of which is dealt with nutrigenomics. Although the fundamental principles of nutrigenomics remain similar to that of traditional research, a collection of comprehensive targeted/untargeted data sets in the context of nutrition offers the unique advantage of understanding complex metabolic networks to provide a mechanistic understanding of data from epidemiological and intervention studies. In this review the challenges and opportunities of nutrigenomic tools in addressing the nutritional problems of public health importance are discussed. The application of nutrigenomic tools provided numerous leads on biomarkers of nutrient intake, undernutrition, metabolic syndrome and its complications. Importantly, nutrigenomic studies also led to the discovery of the association of multiple genetic polymorphisms in relation to the variability of micronutrient absorption and metabolism, providing a potential opportunity for further research toward setting personalized dietary recommendations for individuals and population subgroups.
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Influenza caused by influenza virus,seriously threaten human life and health.Drug treatment is one of the effective measurement. However, there are only two classes of drugs, one class is M2 blockers and another is neuraminidase (NA)inhibitors. The recent antiviral surveillance studies reported a global significant increase in M2 blocker resistance among influenza viruses, and the resistant virus strains against NA inhibitor are also reported in clinical treatment.Therefore thediscovery of new medicines with low resistance has become very urgent.As all known,traditional medicines with multi-target features and network mechanism often possess low resistance. Compound Yizhihao, which consists of radix isatidis,folium isatidis,Artemisia rupestris,is one of the famous traditional medicine for influenza treatment in China, however its mechanism of action against influenza is unclear. In this study, the multiple targets related with influenza disease and the known chemical constituents from Compound Yizhihao were collected, and multi-target QSAR (mt-QSAR) classification models were developed by Na?ve Bayesian algorithm and verified by various datasets. Then the classification models were applied to predict the effective constituents and their drug targets.Finally,the constituent-target-pathway network was constructed,which revealed the effective constituents and their network mechanism in Compound Yizhihao. This study will lay important basis for the clinical uses for influenza treatment and for the further research and development of the effective constituents.
ABSTRACT
Compound Yizhihao, consists of Radix isatidis, Folium isatidis, Artemisia rupestris, has a significant therapeutic effect on the treatment of influenza and fever. However, the mechanism of its action is still unclear. In this investigation, we collected the key target molecule of influenza disease and the chemical constituents of Compound Yizhihao, and developed Naïve Bayesian classification models based on the input molecular fingerprints and molecule descriptors. The built models were further applied to construct classifiers for predicting the effective constituents. We used the professional network-building software to build the constituent-target network and target-pathway network, which revealed the network pharmacology of the effective constituents in Compound Yizhihao. It will contribute to the further research of mechanism of Compound Yizhihao.
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Drugs play the pharmacological effects by combining with target proteins. Identification of drug-target interactions is important for discovering new functions of drugs. In this paper, the target fingerprints based on molecular substructure and the drug-target similarity based on fingerprints are proposed to a random forest-based classification method, in order to identify the drug-target interactions. Experiments on enzymes, ion channels, G protein-coupled receptors and nuclear receptors proved the effectiveness of the proposed method. In addition, the proposed method is applied to predict the interactions between ingredients and targets of traditional Chinese medicines.
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Objective To explore the characteristics of intestinal Microbiota in T2DM patients by two molecular fingerprint technologies,and investigate the correlation of intestinal microbiota and T2DM,and evaluate the application value of two fin-gerprint technologies.Methods Fecal samples of 8 healthy groups and 7 diabetes patients were collected.Then the total DNA of gut microbiota was extracted.Through the analysis of products by two molecular fingerprints of ERIC-PCR and DGGE-PCR,ecological characteristics of diversity and similarity of gut microbiota were obtained in healthy groups and dia-betes patients.Results Compared to healthy groups,the number of bands and Shannon-Wiener index of gut microbiota in di-abetes patients was decreased but no statistical significance.The similarity in patients group was declining(P <0.05),and the construction of gut microbiota was inclined to differ.Two fingerprint technologies of ERIC and DGGE could directly re-flect the diversity of gut microbiota and were the modern molecular biological techniques without depending on cultivation. ERIC was simple and convenient,had a better reflection of microbial diversity,but gel band cutting and regarded asa proper approach with higher diffraction efficiency and excellent repetition to studysequencing couldn’t be performed since there were more influencing factors on the experiment.DGGE could better reflect the ecological characteristics such as microbial diversity and similarity,and selecting bands,gel band cutting and sequencing could be done.Conclusion The composition and construction of gut microbiota in diabetes patients were changed,which suggests the occurrence of the disease had the correlation with gut microbiota.ERIC and DGGE is regarded as a proper approach with higher diffraction efficiency and ex-cellent repetition to study intestinal microbiota,but also gel band cutting,sequencing,bacteria identification can be performed by DGGE,both can be used in combination.