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Objective To explore the application value of near infrared spectrum (NIRS) in the detection of epidural and subdural hematoma in clinic.Methods Thirty-four patients with subdural and epidural hematomas (study group) confirmed by CT or MRI and 14 healthy volunteers (contrast group) were selected.The NIRS equipment which was produced by Institute of Automation of Chinese Academy of Sciences were used to assess the intracranial hematomas.Taking CT or MRI results as the golden standard,the diagnostic efficiency of NIRS for subdural and epidural hematomas were evaluated.Results For the diagnosis of subdural and epidural hematomas,the sensitivity,specificity,accuracy,positive predictive value and negative predictive value were 91.18％(31/34),71.43％ (10/14),85.42％(41/48),88.57％(31/35) and 76.92％ (10/13),respectively.Conclusion NIRS is a good device to predict intracranial subdural and epidural hematomas with high sensitivity and positive predictive value,which is helpful for early diagnosis and therapy in clinic.
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This study was aimed to develop in-line monitoring of extraction process of Lonicerajaponica in the extraction process trajectory of Re-Du-Ning (RDN) injection.Several batches of near-infrared (NIR) spectrum dates were collected and multivariate statistical process control (MSPC) method was in conjunction with.The results showed that using score,Hotelling T2 and DModX control chart,various normal and abnormal behaviors of the test batches were detected in time by comparison with the extraction process trajectory.It was concluded that the process trajectory for in-line quality control based on NIR spectrum dates and MSPC could indicate the changes of process.It was a feasible technology tool of the total process quality control during traditional Chinese medicine (TCM) manufacturing process.
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In order to improve the precision and robustness in determination of soluble solids content ( SSC) of ‘Fuji ’ apple by NIR spectroscopy and eliminate the effect of origin variability on the accuracy of NIR calibration models for the SSC, sample set partitioning based on joint x-y distances ( SPXY) was used to select representative subset from the apple samples of 4 different origins. As a comparison, partial least square ( PLS) was used to establish local origin and hybrid origin models for the prediction of SSC in apple. Competitive adaptive reweighted sampling ( CARS ) and successive projections algorithm ( SPA ) were implemented to select effective variables of the NIR spectroscopy of SSC of apple. The results indicated that the PLS model established based on the 4 origin apple samples performed better than local origin and other hybrid origin models. The model could be effectively simplified using 16 characteristic variables selected by CARS-SPA method from full-spectrum which had 3112 wavelengths. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) were 0. 978 and 0. 441 oBrix, respectively for SSC. It was found that the model developed by more samples of different origins combined with effective wavelengths showed good prediction ability for apple sample of unknown origin, which indicated that it could significantly reduce the origin effect on the robustness of NIR models for SSC of apple.
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MS96A type spectrum analyzer was applied to determine the spectral characteristic of near infrared radiated by moxa stick moxi-bustion, ginger-partitioned moxibustion, garlic-partitioned moxibustion and Aconium Carmichaeli-par titioned moxibustion. The spectrum of moxa stick moxibustion was relatively discrete and several wave crests are appeared. But in the spectrum of ginger-partitioned moxibustion, garlic-partitioned moxibustion or Aconium Carmichaeli-partitioned moxibustion, a specific and relatively steady wave crest formed respectively. It was concluded different indirect moxibustion could bring respective spectrum of near infrared and have the relevant physiologic and biochemical effects.
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The conventional invasive tissue blood oxygen content measurement is poor in continuity.The weakness of the signal,strong interference and random transmission of the photon in tissues make the measurement difficult.Recently,near infrared spectrum technology has been applied to tissue blood oxygen content measurement.This paper presents a hardware design method for tissue blood oxygen content measurement by near infrared spectrum technology.
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AIM: To determine baicalin of scutellaria-extract rapidly by FT-NIRS and data analysis software. METHODS: The correction model was set up based on partial least square and was used to predict baicalin of scutellaria-extract in the samples. RESULTS: Cross validation and test samples determination showed that the co-rrelation coefficient(R2) of this correction model was 95.05,the RMSECV was 0.861,respectively. CONCLUSION: It is fast and convenient.The correction model could be used to predict baicalin of scutellaria-extract rapidly.It can offer reference to content determination of other extracts of Chinese herbs.
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AIM:To study the feasibility of online monitoring and controlling of the key process of column chromatographic separation in the production of Salvianolate by combining near-infrared(NIR) spectrum and HPLC fingerprinting. METHODS: Partial Least Square(PLS) regression was used to model the correlation of NIR spectra with the concentrations of salvianolic acid B,and the influences of light path,wavelength selection,and preprocessing method on the PLS model were investigated systematically. RESULTS: A 2 mm light path was better than 1 mm one,and with 2 mm light path,the optimal wave-number was in the range of 6 102.1-5 446.3 cm~(-1) and the optimal preprocessing method was the vector normalization.The root mean-square error of PLS model on test samples was 0.234 mg/mL,and R~2 was 0.995 2. CONCLUSION: This method is proved to be fast,convenient,and precise.It can be used to online monitoring and quality control of the manufacturing of Salvianolate.