Identification and analysis of serum samples by surface-enhanced Raman spectroscopy combined with characteristic ratio method and PCA for gastric cancer detection

This study aimed to explore the application of surface-enhanced Raman scattering(SERS)in the rapid diagnosis of gastric cancer.The SERS spectra of 68 serum samples from gastric cancer patients and healthy volunteers were acquired.The characteristic ratio method(CRM)and principal component analysis(PCA)were used to differentiate gastric cancer serum from normal serum.Compared with healthy volunteers,the serum SERS intensity of gastric cancer patients was relatively high at 722 cm^(-1),while it was relatively low at 588,644,861,1008,1235,1397,1445 and 1586 cm^(-1).These results indicated that the relative content of nucleic acids in the serum of gastric cancer patients rises while the relative content of amino acids and carbohydrates decreases.In PCA,the sensitivity and specificity of discriminating gastric cancer were 94.1%and 94.1%,respectively,with the accuracy of 94.1%.Based on the intensity ratios of four characteristic peaks at 722,861,1008 and 1397 cm^(-1),CRM presented the diagnostic sensitivity and specificity of 100%and 97.4%,respectively,and the accuracy of 98.5%.Therefore,the three peak intensity ratios of I_(722)/I_(861),I_(722)/I_(1008)and I_(722)/I_(1397)can be considered as biologicalfingerprint information for gastric cancer diagnosis and can rapidly and directly reflect the physiological and pathological changes associated with gastric cancer development.This study provides an important basis and standards for the early diagnosis of gastric cancer.

Estimation of Summer Rainfall over an Arid Area using AMSR-E Measurements:A Case Study in Xinjiang,China

Rainfall estimate in arid region using passive microwave remote sensing techniques has been a complex issue for some time.The main reason for this difficulty is that the high and variable emissivity of land surfaces greatly aggravates the complexity of the signatures from the rain cloud.The Xinjiang area,located in the northwest of China,holds all the typical characteristics of arid climate.A rainfall algorithm has been developed for this region by using the Advanced Microwave Scanning Radiometer for Earth Observing System(AMSR-E) measurements.The algorithm attempts to use all 12 chan-nels on the AMSR-E instrument and a two-step method calibrated over 11 days of hourly rain-gauge data.First,Stepwise Discriminant Analysis(SDA) used to optimally estimate rain pixels based on all 12 channels,although only three channels were found to be necessary.Next,a rain predicator scattering index was used to estimate rain rates.A linear relationship between the rain rates and the scattering index above the threshold of 3.0K was constructed with a simple approximately linear function.The estimated rain rates were compared with the rain-gauge data used to calibrate the method,and a good relationship was found with a root-mean-square error of 2.1mm/h.The numerical calculations and comparisons show that the algorithm works well in the Xinjiang area.

Nicotine and its metabolite cotinine target MD2 and inhibit TLR4 signaling

Nicotine is the principal alkaloid of tobacco often manufactured into cigarettes and belongs to a highly addictive class of drugs.Nicotine attenuates the neuroinflammation induced by microglial activation.However,the molecular target(s)underlying anti-inflammatory action of nicotine has not been fully understood.Considering the psychoactive substances morphine,cocaine,and methamphetamine act as xenobiotic-associated molecular patterns and can be specifically sensed by the innate immune receptor Toll-like receptor 4(TLR4),here we sought to delineate whether nicotine and/or its metabolite cotinine may be recognized by the innate immune system via myeloid differentiation protein 2(MD2).