Objective To detect and analyse the levels of nitrite in marketed milk powder.Methods 6 brands of maketed milk powder were selected in this study.Interferents,such as protein,were removed from milk powder preliminarily by using potassium ferrocynide and zinc acetate.The levels of nitrite were detected by using fluorospectrophotometry method,and compared with na-tional standard(2 mg/kg).Results The levels of nitrite in the 6 brands of maketed milk powder were lower than the national stand-ard limit,had statistically significant differences(P <0.05).Conclusion The levels of nitrite of 6 brands of milk powders do not ex-ceed the national standard.

The monitoring of pregnant women is very important. It plays an important role in reducing fetal mortality, ensuring the safety of perinatal mother and fetus, preventing premature delivery and pregnancy accidents. At present, regular examination is the mainstream method for pregnant women's monitoring, but the means of examination out of hospital is scarce, and the equipment of hospital monitoring is expensive and the operation is complex. Using intelligent information technology (such as machine learning algorithm) can analyze the physiological signals of pregnant women, so as to realize the early detection and accident warning for mother and fetus, and achieve the purpose of high-quality monitoring out of hospital. However, at present, there are not enough public research reports related to the intelligent processing methods of out-of-hospital monitoring for pregnant women, so this paper takes the out-of-hospital monitoring for pregnant women as the research background, summarizes the public research reports of intelligent processing methods, analyzes the advantages and disadvantages of the existing research methods, points out the possible problems, and expounds the future development trend, which could provide reference for future related researches.
Female ; Fetus ; Humans ; Pregnancy ; Pregnant Women

Stroma surrounding the tumor cells plays crucial roles for tumor progression. However, little is known about the factors that maintain the symbiosis between stroma and tumor cells. In this study, we found that the transcriptional regulator-signal transducer and activator of transcription 3 (Stat3) was frequently activated in cancer-associated fibroblasts (CAFs), which was a potent facilitator of tumor malignancy, and formed forward feedback loop with platelet-activating factor receptor (PAFR) both in CAFs and tumor cells. Importantly, PAFR/Stat3 axis connected intercellular signaling crosstalk between CAFs and cancer cells and drove mutual transcriptional programming of these two types of cells. Two central Stat3-related cytokine signaling molecules-interleukin 6 (IL-6) and IL-11 played the critical role in the process of PAFR/Stat3 axis-mediated communication between tumor and CAFs. Pharmacological inhibition of PAFR and Stat3 activities effectively reduced tumor progression using CAFs/tumor co-culture xenograft model. Our study reveals that PAFR/Stat3 axis enhances the interaction between tumor and its associated stroma and suggests that targeting this axis can be an effective therapeutic strategy against tumor malignancy.