This Fructus,study including and aimed to construct a rapid and nondestructive detection flavonoid,model betaine,for and of the content vitamin of(Vit four four quality C).index components Lycium barbarum polysaccharide,of inL ycii rawma total and C Hyperspectral data quantitative of terials modelswere powder developed Lycii using Fructus partial were squares effects collected,regression raw based LSR),on the support content vector the above components,the forest least(P regression compared,(SVR),the and effects random three regression(RFR)were algorithms.also The Four spectral predictive commonly data of the materialsand powder were were applied and of spectral quantitative for models reduction.compared.used were pre-processing screened methods feature to successive pre-process projection the raw algorithm data(SPA),noise competitive Thepre-processed for bands using adaptive reweigh ted sampling howed(CARS),the and maximal effects relevance based and raw minimal materials redundancy and(MRMR)were algorithms Following to optimize multiplicative the models.scatter The correction Based resultss(MS that prediction SPA on feature the powder prediction similar.PLSR C)denoising sproposed and integrated for model,screening the the coefficient bands,determination the effect(R_C~2)of(MSC-SPA-PLSR)coefficient was optimal.of on(R_P~2)thi of of calibration flavonoid,and and of all determination greater prediction0.83,L.barbarum inconte nt prediction of polysaccharide,total mean betaine,of Vit C were than smallest In the compared study,root with mean other prediction content squareserror models of the calibration(RMSEC)residual and deviation root squares was error2.46,prediction2.58,(RMSEP)and were the,and prediction(RPD)2.50,developed3.58,achieve respectively.rapid this the the quality mod el(MSC-SPA-PLSR)fourcomponents based Fructus,on hyperspectral which technology was approach to rapid and effective detection detection of the of Lycii in Lycii provided a new to the and nondestructive of of Fructus.
Spectroscopy, Near-Infrared/methods* ; Betaine ; Powders ; Least-Squares Analysis ; Algorithms ; Flavonoids

In this study, visual-near infrared(VNIR), short-wave infrared(SWIR), and VNIR + SWIR fusion hyperspectral data of Polygonatum cyrtonema from different geographical origins were collected and preprocessed by first derivative(FD), second derivative(SD), Savitzky-Golay smoothing(S-G), standard normalized variate(SNV), multiplicative scatter correction(MSC), FD+S-G, and SD+S-G. Three algorithms, namely random forest(RF), linear support vector classification(LinearSVC), and partial least squares discriminant analysis(PLS-DA), were used to establish the identification models of P. cyrtonema origin from three spatial scales, i.e., province, county, and township, respectively. Successive projection algorithm(SPA) and competitive adaptive reweighted sampling(CARS) were used to screen the characteristic bands, and the P. cyrtonema origin identification models were established according to the selected characteristic bands. The results showed that(1)after FD preprocessing of VNIR+SWIR fusion hyperspectral data, the accuracy of recognition models established using LinearSVC was the highest, reaching 99.97% and 99.82% in the province origin identification model, 100.00% and 99.46% in the county origin identification model, and 99.62% and 98.39% in the township origin identification model. The accuracy of province, county, and township origin identification models reached more than 98.00%.(2)Among the 26 characteristic bands selected by CARS, after FD pretreatment, the accuracy of origin identification models of different spatial scales was the highest using LinearSVC, reaching 98.59% and 97.05% in the province origin identification model, 97.79% and 94.75% in the county origin identification model, and 90.13% and 87.95% in the township origin identification model. The accuracy of identification models of different spatial scales established by 26 characteristic bands reached more than 87.00%. The results show that hyperspectral imaging technology can realize accurate identification of P. cyrtonema origin from different spatial scales.
Spectroscopy, Near-Infrared ; Polygonatum ; Algorithms ; Random Forest ; Least-Squares Analysis

This study established a method for rapid quantification of terpene lactone, bilobalide, ginkgolide C, ginkgolide A and ginkgolide B in the chromatographic process of Ginkgo Folium based on near infrared spectroscopy(NIRS). The effects of competitive adaptive reweighting sampling(CARS), random frog(RF), and synergy interval partial least squares(siPLS) on the performance of partial least squares regression(PLSR) model were compared to the reference values measured by HPLC. Among them, the correlation coefficients of prediction(Rp) of validation sets of terpene lactone, bilobalide, and ginkgolide C were all higher than 0.98, and the relative standard errors of prediction(RSEPs) were 5.87%, 6.90% and 6.63%, respectively. Aiming at ginkgolide A and ginkgolide B with relatively low content, the genetic algorithm joint extreme learning machine(GA-ELM) was used to establish the optimized quantitative analysis model. Compared with CARS-PLSR model, the CARS-GA-ELM models of ginkgolide A and ginkgolide B exhibited a reduction in RSEP from 15.65% to 8.52% and from 21.28% to 10.84%, respectively, which met the needs of quantitative ana-lysis. It has been proved that NIRS can be used for the rapid detection of various lactone components in the chromatographic process of Ginkgo Folium.
Chromatography, High Pressure Liquid ; Ginkgo biloba ; Lactones/analysis* ; Least-Squares Analysis ; Spectroscopy, Near-Infrared/methods*

Working memory is an important foundation for advanced cognitive function. The paper combines the spatiotemporal advantages of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to explore the neurovascular coupling mechanism of working memory. In the data analysis, the convolution matrix of time series of different trials in EEG data and hemodynamic response function (HRF) and the blood oxygen change matrix of fNIRS are extracted as the coupling characteristics. Then, canonical correlation analysis (CCA) is used to calculate the cross correlation between the two modal features. The results show that CCA algorithm can extract the similar change trend of related components between trials, and fNIRS activation of frontal pole region and dorsolateral prefrontal lobe are correlated with the delta, theta, and alpha rhythms of EEG data. This study reveals the mechanism of neurovascular coupling of working memory, and provides a new method for fusion of EEG data and fNIRS data.
Electroencephalography/methods* ; Memory, Short-Term ; Neurovascular Coupling/physiology* ; Prefrontal Cortex ; Spectroscopy, Near-Infrared/methods*

Neurofeedback (NF) technology based on electroencephalogram (EEG) data or functional magnetic resonance imaging (fMRI) has been widely studied and applied. In contrast, functional near infrared spectroscopy (fNIRS) has become a new technique in NF research in recent years. fNIRS is a neuroimaging technology based on hemodynamics, which has the advantages of low cost, good portability and high spatial resolution, and is more suitable for use in natural environments. At present, there is a lack of comprehensive review on fNIRS-NF technology (fNIRS-NF) in China. In order to provide a reference for the research of fNIRS-NF technology, this paper first describes the principle, key technologies and applications of fNIRS-NF, and focuses on the application of fNIRS-NF. Finally, the future development trend of fNIRS-NF is prospected and summarized. In conclusion, this paper summarizes fNIRS-NF technology and its application, and concludes that fNIRS-NF technology has potential practicability in neurological diseases and related fields. fNIRS can be used as a good method for NF training. This paper is expected to provide reference information for the development of fNIRS-NF technology.
Neurofeedback/methods* ; Spectroscopy, Near-Infrared/methods* ; Brain/diagnostic imaging* ; Magnetic Resonance Imaging ; Technology

Objective: Near-infrared spectroscopy (NIRS) is widely used for intraoperative cerebral oxygen saturation monitoring in patients with acute type A aortic dissection. This study aimed to investigate the correlation between NIRS-derived oxygen saturation and risk of postoperative stroke. Methods: This study included 193 patients with acute type A aortic dissection undergoing emergency surgery and elective unilateral cerebral perfusion via the right axillary artery at the Department of Cardiothoracic Surgery, Nanjing Drum Tower Hospital, Nanjing, China, from 2018 to 2020. NIRS was used for intraoperative cerebral oxygen saturation monitoring, and the basal values and the lowest values of cerebral oxygen saturation during deep hypothermic circulatory arrest (DHCA) were recorded. The patients were divided into no-stroke group (n=178, 92.2%) and stroke group (n=15, 7.8%) according to the absence or presence of postoperative stroke. The differences in preoperative, operative and postoperative clinical differences between the two groups were compared, and the relationship between the lowest cerebral oxygen saturation value and the change in cerebral oxygen saturation value ((base-lowest)/basal) and postoperative stroke were analyzed. Results: The proportion of preoperative atrial fibrillation (6.7% vs. 0.6%, P=0.026), and the proportion of preoperative hypotension (26.7% vs. 9.0%, P=0.031) were significantly higher in the stroke group than no-stroke group. There were no differences in the surgical approach between the two groups. Cardiopulmonary bypass (CPB) time ((256.1±84.8) h vs.(217.8±58.4) h, P=0.020), postoperative mechanical ventilation time ((139.3±172.8) h vs. (35.6±45.6) h, P<0.001) were significantly longer in stroke group as compared to no-stroke group. Incidence of postoperative tracheotomy (20.0% vs. 1.1%, P<0.001), acute kidney injury (73.3% vs. 30.3%, P=0.001) and continuous renal replacement therapy (46.7% vs. 11.8%, P<0.001) as well as mortality (20.0% vs. 5.1%, P=0.022) were significantly higher in the stroke group than in non-stroke group. There was no significant difference in the basal NIRS value and the lowest NIRS value during DHCA between the two groups. Patients in the stroke group had a significantly greater intraoperative change rate of right NIRS as compared to no-stroke group (15.2%±15.7% vs. 9.2%±7.0%, P=0.006). Conclusions: NIRS is valuable for monitoring cerebral oxygen saturation during acute type A aortic dissection surgery, and the rate change of NIRS during operation correlates significantly with postoperative stroke.
Aortic Dissection/surgery* ; Humans ; Monitoring, Intraoperative/methods* ; Oxygen ; Oxygen Saturation ; Spectroscopy, Near-Infrared/methods* ; Stroke

Objective: Functional near-infrared spectroscopy (fNIRS) was used to study the effect of aging on the neuroimaging characteristics of cerebral cortex in the process of speech perception. Method: Thirty-four adults with normal hearing were recruited from March 2021 to June 2021, including 17 in the young group, with 6 males, 11 females, age (32.1±5.0) years, age range 20-39 years. and 17 in the elderly group, with 6 males, 11 females, age (63.2±2.8) years, age range 60-70 years. The test material was the sentence table of the Mandarin Hearing Test in Noise (MHINT). The task state block experiment design was adopted, and the temporal lobe, Broca's area, Wernicke's area, motor cortex were used as regions of interest. Objective brain imaging technology (fNIRS) combined with subjective psychophysical testing method was used to analyze the activation area and degree of cerebral cortex related to auditory speech perception in the elderly and young people under different listening conditions (quiet, signal-to-noise ratio of 10 dB, 5 dB, 0 dB, -5 dB). SPSS 23 software was used for statistical analysis. Result: The activation area and degree of activation in the elderly group were lower than those in the young group under each task condition; The number of activation channels in the young group were significantly more than those in the old group, and the number of activation channels in the left hemisphere were more than those in the right hemisphere, but there was no difference in the number of activation channels. There were more channels affected by age in the left hemisphere than in the right hemisphere. The activation degree of the young group when the signal-to-noise ratio was 0 dB was significantly higher than that of other signal-to-noise ratio conditions (P<0.05), but there was no significant difference in the old group under the five conditions (P>0.05). The speech recognition score of the young group was higher than that of the old group under all conditions. When the quiet and signal-to-noise ratio was 10 dB, the correct score of the two groups was equal or close to 100%. With the gradual decrease of signal-to-noise ratio, there was a significant difference between the two groups when the signal-to-noise ratio was 5 dB. The speech recognition accuracy of the young group decreased significantly when the signal-to-noise ratio was 0 dB, while that of the old group decreased significantly when the signal-to-noise ratio was 5 dB. Conclusions: With the increase of age, the speech perception in noisy environment and the activity of cerebral cortex gradually deteriorate, and the speech dominance hemisphere (left hemisphere) will be significantly affected by aging. The overall activation area and activation degree of the elderly under different speech tasks are lower than those of the young.
Acoustic Stimulation/methods* ; Adolescent ; Adult ; Aged ; Auditory Cortex/physiology* ; Female ; Humans ; Male ; Middle Aged ; Spectroscopy, Near-Infrared ; Speech Perception/physiology* ; Technology ; Young Adult

OBJECTIVES: To investigate the incidence and mortality of gastrointestinal dysfunction in children with sepsis, the application of near-infrared spectroscopy (NIRS) in monitoring mesenteric regional tissue oxygen saturation (rSO₂), and the association between rSO₂ and gastrointestinal dysfunction. METHODS: In this prospective study, 79 children with sepsis in the pediatric intensive care unit (sepsis group) and 40 children who underwent physical examination in the Department of Child Healthcare (healthy control group) from January to December, 2021 were enrolled as subjects. The related medical data were collected, including general information on admission and at discharge, treatment during hospitalization, and laboratory examination results. NIRS was used to measure mesenteric rSO₂. Clinical characteristics were compared between the patients with and without gastrointestinal dysfunction. RESULTS: For the 79 children with sepsis, the incidence rate of gastrointestinal dysfunction was 49% (39/79), and the mortality rate of the children with gastrointestinal dysfunction was 26% (10/39). The children with gastrointestinal dysfunction had a longer duration of mechanical ventilation and a higher 28-day mortality rate (P<0.05). The children with gastrointestinal dysfunction had a significantly lower median rSO₂ (64%) than the children without gastrointestinal dysfunction (72%) and the healthy control group (78%) (P<0.05). CONCLUSIONS There are high incidence and mortality rates of gastrointestinal dysfunction in children with sepsis, and the reduction in rSO₂ may be associated with the development of gastrointestinal dysfunction.
Child ; Gastrointestinal Diseases/etiology* ; Humans ; Intensive Care Units, Pediatric ; Oxygen ; Prospective Studies ; Sepsis/complications* ; Spectroscopy, Near-Infrared/methods*

Near-infrared spectroscopy(NIRS) combined with band screening method and modeling algorithm can be used to achieve the rapid and non-destructive detection of the traditional Chinese medicine(TCM) production process. This paper focused on the ginkgo leaf macroporous resin purification process, which is the key technology of Yinshen Tongluo Capsules, in order to achieve the rapid determination of quercetin, kaempferol and isorhamnetin in effluent. The abnormal spectrum was eliminated by Mahalanobis distance algorithm, and the data set was divided by the sample set partitioning method based on joint X-Y distances(SPXY). The key information bands were selected by synergy interval partial least squares(siPLS); based on that, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA) and Monte Carlo uninformative variable(MC-UVE) were used to select wavelengths to obtain less but more critical variable data. With selected key variables as input, the quantitative analysis model was established by genetic algorithm joint extreme learning machine(GA-ELM) algorithm. The performance of the model was compared with that of partial least squares regression(PLSR). The results showed that the combination with siPLS-CARS-GA-ELM could achieve the optimal model performance with the minimum number of variables. The calibration set correlation coefficient R_c and the validation set correlation coefficient R_p of quercetin, kaempferol and isorhamnetin were all above 0.98. The root mean square error of calibration(RMSEC), the root mean square error of prediction(RMSEP) and the relative standard errors of prediction(RSEP) were 0.030 0, 0.029 2 and 8.88%, 0.041 4, 0.034 8 and 8.46%, 0.029 3, 0.027 1 and 10.10%, respectively. Compared with the PLSR me-thod, the performance of the GA-ELM model was greatly improved, which proved that NIRS combined with GA-ELM method has a great potential for rapid determination of effective components of TCM.
Algorithms ; Ginkgo biloba ; Least-Squares Analysis ; Plant Leaves ; Spectroscopy, Near-Infrared

For the field detection problems of critical quality attribute(CQA) of moisture content in traditional Chinese medicine(TCM) manufacturing process, big brand TCM Tongren Niuhuang Qingxin Pills were used as the carrier, to establish a moisture content NIR field detection model with or without cellophane in real world production with use of near infrared(NIR) spectroscopy combined with stoichiometry. With the moisture content determined by drying method as reference value, the partial least square method(PLS) was used to analyze the correlation between the spectrum and the moisture reference value. Then the spectral pretreatment methods were screened and optimized to further improve the accuracy and stability of the model. The results showed that the best quantitative model was developed by the spectral data pretreatment of standard normal variate(SNV) with the latent variable factor number of 2 and 7 of Tongren Niuhuang Qingxin Pills with or without cellophane samples. The prediction coefficient of determination(R_(pre)~2) and standard deviation of prediction(RMSEP) of the model with cellophane samples were 0.765 7 and 0.157 2%; R_(pre)~2 and RMSEP of the model without cellophane samples were 0.772 2 and 0.207 8%. The NIR quantitative models of moisture content of Tongren Niuhuang Qingxin Pills with and without cellophane both showed good predictive performance to realize the rapid, accurate and non-destructive quantitative analysis of moisture content in such pills, and provide a method for the field quality control of the critical chemical attributes of moisture in the manufacturing of big brand TCM.
Drugs, Chinese Herbal ; Least-Squares Analysis ; Medicine, Chinese Traditional ; Spectroscopy, Near-Infrared