[Expression of miRNA let-7a and HMGA2 and Diagnostic Value of Serum miRNA let-7a Level in Pancreatic Cancer].

Objective: To investigate the diagnostic value of miRNA let-7a, high mobility group A2 (HMGA2) expression and serum miRNA let-7a level in pancreatic cancer.

Methods: From January 2014 to January 2019, 60 patients with pancreatic cancer were collected for fresh pancreatic ductal adenocarcinoma tissue and normal pancreatic tissue adjacent to the cancer after the operation. Serum samples before and after operation were also collected, while 60 healthy people were enrolled as the control group.

[Survival analysis of patients with spontaneous rupture of hepatocellular carcinoma].

Objective: To explore the prognostic factors influencing overall survival (OS) in patients with spontaneous rupture of hepatocellular carcinoma (HCC-SR).

Methods: The medical records of 44 patients with HCC-SR treated in our department from January 1, 2005 to April 1 2011 were retrospectively reviewed. The clinical and prognostic data of 19 HCC-SR patients who received curative hepatectomy were compared with data of 137 HCC patients with no SR who were managed by curative hepatectomy during the same period.

[Fluorescence spectrum monitor for early warning of greenhouse cucumber aphis pests].

The infection and degree of cucumber aphis pests was studied by analyzing chlorophyllfluorescence spectrum in greenhouse. Based on the configuration of the spectrum, characteristic points were established, in which the intensity of waveband F632 was the first characteristic point between healthy and aphis pests leaves. The second characteristic point was K which was the change rate of spectral curve from waveband F512 to F632.

[Chlorophyll fluorescence spectrum analysis of greenhouse cucumber disease and insect damage].

The present paper is based on chlorophyll fluorescence spectrum analysis. The wavelength 685 nm was determined as the primary characteristic point for the analysis of healthy or disease and insect damaged leaf by spectrum configuration. Dimensionality reduction of the spectrum was achieved by combining simple intercorrelation bands selection and principal component analysis (PCA).