The Blood Biomarkers of Asthma

Asthma was a chronic inflammatory airway disease which characterized by complex pathogenesis, various clinical manifestations and severity. Blood biomarkers have been used to evaluate the severity of the disease, predict the efficacy and prognosis. Currently, some incredible progress in most of the research on biomarkers for asthma have achieved, including cell, antibodies, cytokines, chemokines, proteins and non-coding RNAs. We reviewed the application of these biomarkers in diagnosis, treatment, prognosis monitoring and phenotypic identification of asthma, in order to improve clinicians’ understanding of asthma biomarkers

The Accuracy of Single MicroRNAs in Peripheral Blood to Diagnose Ovarian Cancer: An Updated Meta-Analysis

Background. Ovarian cancer is the 5th leading cause of death of women due to cancer in the United States. Although carbohydrate antigen 125 has a moderate diagnostic utility, the phenomenon of false-positive exists. As novel effective biomarkers, some single microRNAs (miRNAs) have diagnostic values for ovarian cancer, but the results lack consistency. In order to precisely and comprehensively assess the diagnostic value of single miRNAs for ovarian cancer, a meta-analysis is performed. Methods. Articles concerning the diagnostic value of single miRNAs for ovarian cancer were searched from databases. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) with the corresponding 95% confidence interval (CI) were calculated. Area under curve (AUC) of the summary receiver-operating characteristic (SROC) curve was also calculated. Results. In total, 22 studies including 8 kinds of single miRNAs were enrolled in this paper (6 studies for miR-200c, 3 studies for miR-200a and miR-200b, and 2 studies for miR-205, miR-145, miR-141, miR-429, and miR-125b). For miR-200c, the pooled SEN and SPE were, respectively, 0.768 (95% CI: 0.722-0.811) and 0.680 (95% CI: 0.624-0.732); the pooled PLR and NLR were, respectively, 2.897 (95% CI: 1.787-4.698) and 0.340 (95% CI: 0.276-0.417); the pooled DOR was 8.917 (95% CI: 4.521-17.587); and AUC of SROC curve was 0.815. For miR-200a, the pooled SEN and SPE were, respectively, 0.759 (95% CI: 0.670-0.833) and 0.717 (95% CI: 0.627-0.795); the pooled PLR and NLR were, respectively, 3.129 (95% CI: 0.997-9.816) and 0.301 (95% CI: 0.207-0.437); the pooled DOR was 11.323 (95% CI: 3.493-36.711); and AUC of SROC curve was 0.857. For miR-200b, the pooled SEN and SPE were, respectively, 0.853 (95% CI: 0.776-0.912) and 0.775 (95% CI: 0.690-0.846); the pooled PLR and NLR were, respectively, 4.327 (95% CI: 0.683-27.415) and 0.225 (95% CI: 0.081-0.625); the pooled DOR was 19.678 (95% CI: 2.812-137.72); and AUC of SROC curve was 0.90. For miR-205, miR-145, miR-141, miR-429, and miR-125b, each diagnostic value should be interpreted cautiously because only two studies were included. Conclusions. miR-200c, miR-200a, and miR-200b can be useful diagnostic biomarkers for ovarian cancer. More related studies are needed for miR-205, miR-145, miR-141, miR-429, and miR-125b

Research on Measures for TBT of Pork Export

With the deepening of economic globalization and increasingly fierce of competition of trade liberalization in WTO member countries, the effect of traditional trade protection measures is gradually weakening or even removed. In recent years, Technical Barriers to Trade (TBT) as a category of nontariff barriers to trade, are the widely divergent measures that countries use to regulate markets, protect their consumers, or preserve their natural resources (among other objectives), but they also can be used (or perceived by foreign countries) to discriminate against imports in order to protect domestic industries. These directly or indirectly lead to gradual rise of trade friction of China’s pork export. This paper analyzed background and significance of measures for TBT of pork export, current situations of researches on TBT both at home and abroad, and came up with new ideas and viewpoints for further strengthening measures for TBT of pork export

Absolute Neutrophil Count and Mean Platelet Volume in the Blood as Biomarkers to Detect Lung Cancer

Objective. Inflammation plays an extremely considerable role in the development and progression of malignancies. Absolute neutrophil count (ANC) and mean platelet volume (MPV) in blood are associated with various inflammatory conditions and resulted in independent prognostic factors for lung cancer. However, whether ANC and MPV can be diagnostic markers for lung cancer remains unknown. This retrospective study investigated the roles of ANC and MPV, either alone or combined, in diagnosing lung cancer. Methods. This study analyzed data from lung cancer patients and healthy individuals in Wuxi People’s Hospital Affiliated with Nanjing Medical University. The Mann–Whitney U-test was performed to compare differences between lung cancer patients and healthy individuals. Spearman’s correlation analysis was used to assess correlations. Receiver operating characteristic (ROC) curves were performed to determine diagnostic accuracy. Results. 209 patients diagnosed with lung cancer and 236 healthy subjects were enrolled in this study. Levels of ANC and MPV increased in lung cancer patients compared with healthy individuals (P<0.001). ANC had statistically significant negative weak correlation with albumin concentrations (r=‐0.154, P=0.026), and MPV had statistically significant negative weak correlation with total protein concentrations (r=‐0.153, P=0.027) in lung cancer patients. ANC and neutrophil-to-lymphocyte ratio had statistically significant positive correlation in both lung cancer patients (r=0.756, P<0.001) and healthy subjects (r=0.639, P<0.001). MPV and platelet-to-lymphocyte ratio had statistically significant negative weak correlation in both lung cancer patients (r=‐0.242, P<0.001) and healthy subjects (r=‐0.325, P<0.001). ANC had sensitivity (SEN) and specificity (SPE) of 0.512 and 0.809, respectively, and the area under the curve (AUC) with 95% confidence interval (95% CI) was 0.656 (0.603-0.710). SEN and SPE of MPV were 0.928 and 0.708, respectively, and the AUC (95% CI) was 0.913 (0.889-0.938). When ANC and MPV were combined, SEN and SPE became 0.842 and 0.835, respectively, and the AUC (95% CI) became 0.919 (0.895-0.943). Conclusions. Compared with ANC or MPV alone, the combination of ANC and MPV can improve diagnostic ability to distinguish lung cancer patients from healthy subjects

Consideration of methods for identifying mite allergens

Abstract House dust mites are small arthropods that produce proteins—found in their feces, body parts, and eggs—that are major triggers of human allergies worldwide. The goal of this review is to describe the current methods used to identify these allergens. A literature search for allergen identification methods employed between 1995 and 2016 revealed multiple techniques that can be broadly grouped into discovery and confirmation phases. The discovery phase employs screening for mite proteins that can bind IgEs in sera from animals or patients allergic to dust mites. The confirmation phase employs biochemical methods to isolate either native or recombinant mite proteins, confirms the IgE binding of the purified allergens, and uses either in vitro or in vivo assays to demonstrate that the purified antigen can stimulate an immune response. The methods used in the two phases are defined and their strengths and weaknesses are discussed. The majority of HDM-allergic patients may respond to just a small subset of proteins, but new protein discovery methods are still warranted in order to develop a complete panel of HDM allergens for component resolved diagnosis and patient-tailored therapies

Research on the International Export Competitiveness of Honey – Taking Anhui Province as an example

This article uses the data of honey export from 2000 to 2013 (Jan. to Aug.) to make an analysis on the fluctuation of honey export number and price in Anhui Province in order to know about the current situation of honey export in Anhui Province. Then it quantitatively makes an analysis on the current situation of international export competitiveness of honey in Anhui Province by market share, trade competitiveness index, export quality index and other methods; It also uses the analysis result to find out the relevant factors that affect the international honey export competitiveness and proposes the relevant countermeasures to improve the international competitiveness of honey in Anhui Province

Research on the International Export Competitiveness of Honey – Taking Anhui Province as an example

This article uses the data of honey export from 2000 to 2013 (Jan. to Aug.) to make an analysis on the fluctuation of honey export number and price in Anhui Province in order to know about the current situation of honey export in Anhui Province. Then it quantitatively makes an analysis on the current situation of international export competitiveness of honey in Anhui Province by market share, trade competitiveness index, export quality index and other methods; It also uses the analysis result to find out the relevant factors that affect the international honey export competitiveness and proposes the relevant countermeasures to improve the international competitiveness of honey in Anhui Province