[Detection of Adulteration in Milk Powder with Starch Near Infrared].

Three China trademarks of milk powder called Mengniu, Yili, Wandashan were taken as testing samples. Each of them mixed varied amount of starch in different gradient, which were consisted of 32 adulterated milk powder samples mixed with starch, was taken as standard samples for constructing predicted model. To those 32 samples, the reflecting spectrum characteristics in middle wave of near infrared spectrum with Near Infrared Spectrum Analyzer (Micro NIR 1700) produced by JDSU Ltd. USA were collected for five repeats in five different days. The time span was nearly two months. Firstly, we build the model used the reflecting spectrum characteristics of those samples with biomimetic pattern recognition (BPR) arithmetic to do the qualitative analysis. The analysis included the reliability of testing result and stability of the model. When we took ninety percent as the evaluation threshold of testing result of CAR (Correct Acceptance Rate) and CRR (Correct Rejection Rate), the lowest starch content of adulterate milk powder in all tested samples which the tested result were bigger than that abovementioned threshold was designated CAR threshold (CAR-T) and CRR threshold (CRR-T). CAR means the correct rate of accepting a sample which is belong to itself, CRR means correct rate of refusing to accept a sample which is not belong to itself. The results were shown that, when we constructed a model based on the near infrared spectrum data from each of three China trademark milk powders, respectively, if we constructed a model with infrared spectrum data tested in a same day, both the CAR-T and CRR-T of adulterate starch content of a sample can reach 0.1% in predicting the remainder infrared spectrum data tested within a same day. The three China trademarks of milk powder had the same result. In addition, when we ignored the trademarks, put the spectrum data of adulterate milk powder samples mixed with the same content of starch of three China trademarks milk powder together to construct a model, the CAR-T of mixed starch content of a sample may reach 0.1%, the CRR-T can reach 1%, if the model construction and predicting were performed with near infrared spectrum data tested in a same day. However, the CAR-T can just stably reach up to 5% and the CRR-T have the same result, if the model construction and predicting were crossly performed with mixed near infrared spectrum data tested in different days. Furthermore, the correct recognizing threshold mixed starch of a sample can stably reach up to 1% and the CAR-T can reach 5%, if the model construction was based on near infrared spectrum data combined the previous four days to predict the output of the another day. On the other hand, we also engaged quantitative analysis to the starch content in milk power with two kinds of arithmetic (PLSR, LS-SVR). In contrast with the testing outputs, the reliability of both the CAR-T and CRR-T in qualitative analysis was further validated.

COVID-19 and early-stage lung cancer both featuring ground-glass opacities: a propensity score-matched study.

BACKGROUND: Radiological manifestations of coronavirus disease 2019 (COVID-19) featured ground-glass opacities (GGOs), especially in the early stage, which might create confusion in differential diagnosis with early lung cancer. We aimed to specify the radiological characteristics of COVID-19 and early lung cancer and to unveil the discrepancy between them. METHODS: One hundred and fifty-seven COVID-19 patients and 374 early lung cancer patients from four hospitals in China were retrospectively enrolled. Epidemiological, clinical, radiological, and pathological characteristics were compared between the two groups using propensity score-matched (PSM) analysis. RESULTS: COVID-19 patients had more distinct symptoms, tended to be younger (P<0.0001), male (P<0.0001), and had a higher body mass index (P=0.014). After 1:1 PSM, 121 matched pairs were identified. Regarding radiological characteristics, patients with a single lesion accounted for 17% in COVID-19 and 89% in lung cancer (P<0.0001). Most lesions were peripherally found in both groups. Lesions in COVID-19 involved more lobes (median 3.5 vs. 1; P<0.0001) and segments (median 6 vs. 1; P<0.0001) and tended to have multiple types (67%) with patchy form (54%). Early lung cancer was more likely to have a single type (92%) with oval form (66%). Also, COVID-19 and early lung cancer either had some distinctive features on computed tomography (CT) images. CONCLUSIONS: Both COVID-19 and early lung cancers showed GGOs, with similar but independent features. The imaging characteristics should be fully understood and combined with epidemiological history, pathogen detection, laboratory tests, short-term CT reexamination, and pathological results to aid differential diagnosis.

[Expression of saliva-binding region of Streptococcus mutans pac in transgenic tomatoes].

OBJECTIVE: To analyze the expression of foreign gene in the filial generation of the transgenic plants on the base of the original transgenic tomatoes seeds carrying the gene encoding saliva-binding region (SBR) in PAc of Streptococcus mutans (S. mutans) gained. METHODS: The tomatoes total DNA was extracted by CTAB methods, and the filial generation transgenic tomatoes carrying the gene encoding SBR in PAc of S. mutans were selected by PCR. The tomatoes total RNA was extracted by trizol and the transcription of the foreign gene was analyzed by RT-PCR. Protein was extracted from fruit tissue and the content of the total protein was determined by Bradford's methods G250. The expression of foreign protein was analyzed by Western blot and the lever of the foreign protein was analyzed by ELISA. RESULTS: The fragment encoding SBR in S. mutans PAc gene integrated in the tomato genomic DNA and was expressed. The foreign protein lever was up to 1.2% of the total soluble protein in tomato fruit tissue. CONCLUSION: The foreign protein gene in the filial generation of the transgenic plants could express the foreign protein.