Epidemiology of nasopharyngeal carcinoma: current insights and future outlook.

Nasopharyngeal carcinoma (NPC) is characterised by its remarkable geographical and ethnic distribution. The interplay between genetic susceptibility, environmental exposures, and Epstein-Barr virus (EBV) infections is indicated in the development of NPC. Exposure to tobacco smoking, dietary factors, and inhalants has been associated with the risk of NPC. Genetic association studies have revealed NPC-associated susceptibility loci, including genes involved in immune responses, xenobiotic metabolism, genome maintenance, and cell cycle regulation. EBV exposure timing and strain variation might play a role in its carcinogenicity, although further investigations are required. Other factors including medical history and oral hygiene have been implicated in NPC. Prevention strategies, including primary prevention and secondary prevention through early detection, are vital in reducing mortality and morbidity of NPC. The current review discusses the global and regional distribution of NPC incidences, the risk factors associated with NPC, and the public health implications of these insights. Future investigations should consider international, large-scale prospective studies to elucidate the mechanisms underlying NPC pathogenesis and develop individualized interventions for NPC.

The role of Epstein-Barr virus in nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC) is a metastasis-prone malignancy closely associated with the Epstein-Barr virus (EBV). Despite ubiquitous infection of EBV worldwide, NPC incidences displayed predominance in certain ethnic groups and endemic regions. The majority of NPC patients are diagnosed with advanced-stage disease, as a result of anatomical isolation and non-specific clinical manifestation. Over the decades, researchers have gained insights into the molecular mechanisms underlying NPC pathogenesis as a result of the interplay of EBV infection with several environmental and genetic factors. EBV-associated biomarkers were also used for mass population screening for the early detection of NPC. EBV and its encoded products also serve as potential targets for the development of therapeutic strategies and tumour-specific drug delivery. This review will discuss the pathogenic role of EBV in NPC and efforts in exploiting the potential of EBV-associated molecules as biomarkers and therapeutic targets. The current knowledge on the role of EBV and its associated products in NPC tumorigenesis, development and progression will offer a new outlook and potential intervention strategy against this EBV-associated malignancy.

Nasopharyngeal Carcinoma and Its Microenvironment: Past, Current, and Future Perspectives.

Nasopharyngeal carcinoma (NPC) is an epithelial malignancy that raises public health concerns in endemic countries. Despite breakthroughs in therapeutic strategies, late diagnosis and drug resistance often lead to unsatisfactory clinical outcomes in NPC patients. The tumor microenvironment (TME) is a complex niche consisting of tumor-associated cells, such as fibroblasts, endothelial cells, leukocytes, that influences tumor initiation, progression, invasion, and metastasis. Cells in the TME communicate through various mechanisms, of note, exosomes, ligand-receptor interactions, cytokines and chemokines are active players in the construction of TME, characterized by an abundance of immune infiltrates with suppressed immune activities. The NPC microenvironment serves as a target-rich niche for the discovery of potential promising predictive or diagnostic biomarkers and the development of therapeutic strategies. Thus, huge efforts have been made to exploit the role of the NPC microenvironment. The whole picture of the NPC microenvironment remains to be portrayed to understand the mechanisms underlying tumor biology and implement research into clinical practice. The current review discusses the recent insights into the role of TME in the development and progression of NPC which results in different clinical outcomes of patients. Clinical interventions with the use of TME components as potential biomarkers or therapeutic targets, their challenges, and future perspectives will be introduced. This review anticipates to provide insights to the researchers for future preclinical, translational and clinical research on the NPC microenvironment.

[Study on the Identification of Geographical Indication Wuchang Rice Based on the Content of Inorganic Elements].

Wuchang rice is a geographical indication product in China. Due to its high quality and low production, the phenome- non of fake is more and more serious. An effective identification method of Wuchang rice is urgent needed, for the maintenance of its brand image and interest of consumers. Base on the content of inorganic elements which are analyzed by ICP-AES and ICP-MS in rice, the identification model of Wuchang rice is studied combining with principal component analysis (PCA), Fisher discrimination and artificial neural network (ANN) in this paper. The effect on the identification of samples is poor through PCA, while the samples from Wuchang area and other areas can be identified accurately through Fisher discrimination and ANN. The average accurate identification ratio of training and verification set through Fisher discrimination is 93.5%, while the average accurate identification ratio through ANN is 96.4%. The ability to identify of ANN is better than Fisher discrimination. Wuchang rice can be identified accurately through the result of this research which provides a technology for the protection of geographical indications of this product.

Simultaneous determination of metoprolol and α-hydroxymetoprolol in human plasma using excitation-emission matrix fluorescence coupled with second-order calibration methods.

BACKGROUND: Metoprolol (MET) is a ß1-adrenoceptor antagonist, which is widely used in the treatment of cardiovascular diseases, and α-hydroxymetoprolol (α-OHM) is its hydroxylated metabolite. Owing to their similar structures, optimization of the condition for the chromatography approach, which is in common use for determination, is both time consuming and laborious. RESULTS: A new and effective strategy that combines the excitation-emission matrix fluorescence with second-order calibration methods was developed for simultaneous determination of MET and α-OHM in human plasma. CONCLUSION: Although the fluorescence spectra of MET and α-OHM overlapped and a large number of unknown and uncalibrated fluorescent components coexisted, the developed method enables accurate concentrations together with reasonable resolution of excitation and emission profiles for the analytes of interest. An additional advantage of the proposed method is that there is no need for separation and sample pretreatment, in addition to lower cost than traditional methods.

Four-way self-weighted alternating normalized residue fitting algorithm with application for the analysis of serotonin in human plasma.

A novel algorithm, four-way self-weighted alternating normalized residue fitting (SWANRF), which is an extension of its three-way form, for the decomposition of quadrilinear data with new weight factors, was proposed and applied to the quantitative analysis of serotonin contents in plasma samples. It was observed that the third-order calibration could not only retain a "second-order advantage" and but also obtain other advantages. The introduction of a fourth mode can relieve the serious problem of collinearity, which seems to be one of the "third-order advantages". The proposed algorithm shows great potential as a promising alternative for the third-order calibration of a four-way data array by contrasting with four-way parallel factor analysis (four-way PARAFAC). Furthermore, both algorithms mentioned above were utilized to analyze the 5-hydroxytryptamine (serotonin) contents in plasma samples by obtaining four-way array (excitation-emission-pH-sample) data, and produced satisfactory results. The serotonin contents in plasma samples obtained by using four-way SWANRF and four-way PARAFAC were 0.324 ± 0.005 and 0.348 ± 0.006 nmol mL(-1), respectively.