In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

Process analytical technology(PAT) is a key means for digital transformation and upgrading of the traditional Chinese medicine(TCM) manufacturing process, serving as an important guarantee for consistent and controllable TCM product quality. Near-infrared(NIR) spectroscopy has become the core technology for measuring the TCM manufacturing process. By incorporating NIR spectroscopy into PAT and starting from the construction of a smart platform for the TCM manufacturing process, this paper systematically described the development history and innovative application of the combination of NIR spectroscopy with chemometrics in measuring the TCM manufacturing process by the research team over the past two decades. Additionally, it explored the application of a validation method based on accuracy profile(AP) in the practice of NIR spectroscopy. Furthermore, the software development progress driven by NIR spectroscopy supported by modeling technology was analyzed, and the prospect of integrating NIR spectroscopy in smart factory control platforms was exemplified with the construction practices of related platforms. By integrating with the smart platform, NIR spectroscopy could improve production efficiency and guarantee product quality. Finally, the prospect of the smart platform application in measuring the TCM manufacturing process was projected. It is believed that the software development for NIR spectroscopy and the smart manufacturing platform will provide strong technical support for TCM digitalization and industrialization.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/analysis* ; Software ; Medicine, Chinese Traditional ; Quality Control

Clinical grading diagnosis of disorder of consciousness (DOC) patients relies on behavioral assessment, which has certain limitations. Combining multi-modal technologies and brain-computer interface (BCI) paradigms can assist in identifying patients with minimally conscious state (MCS) and vegetative state (VS). This study collected electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals under motor BCI paradigms from 14 DOC patients, who were divided into two groups based on clinical scores: 7 in the MCS group and 7 in the VS group. We calculated event-related desynchronization (ERD) and motor decoding accuracy to analyze the effectiveness of motor BCI paradigms in detecting consciousness states. The results showed that the classification accuracies for left-hand and right-hand movement tasks using EEG were 93.28% and 76.19% for the MCS and VS groups, respectively; the classification precisions using fNIRS were 53.72% and 49.11% for these groups. When combining EEG and fNIRS features, the classification accuracies for left-hand and right-hand movement tasks in the MCS and VS groups were 95.56% and 87.38%, respectively. Although there was no statistically significant difference in motor decoding accuracy between the two groups, significant differences in ERD were observed between different consciousness states during left-hand movement tasks ( P < 0.001). This study demonstrates that motor BCI paradigms can assist in assessing the level of consciousness, with EEG being more sensitive for evaluating residual motor intention intensity. Moreover, the ERD feature of motor intention intensity is more sensitive than BCI classification accuracy.
Humans ; Brain-Computer Interfaces ; Spectroscopy, Near-Infrared/methods* ; Electroencephalography/methods* ; Consciousness Disorders/diagnosis* ; Male ; Movement ; Adult ; Female ; Intention ; Persistent Vegetative State/diagnosis*

Early identification of adolescent depression requires objective biomarkers. This study investigated the functional near-infrared spectroscopy (fNIRS) activation patterns and mismatch negativity (MMN) characteristics in adolescents with first-episode mild-to-moderate depression. We enrolled 33 patients and 33 matched healthy controls, measuring oxyhemoglobin (Oxy-Hb) concentration in the frontal cortex during verbal fluency tasks via fNIRS, and recording MMN latency/amplitude at Fz/Cz electrodes using event-related potentials (ERP). Compared with healthy controls, the depression group showed significantly prolonged MMN latency [Fz: (227.88 ± 31.08) ms vs. (208.70 ± 25.35) ms, P < 0.01; Cz: (223.73 ± 29.03) ms vs. (204.18 ± 22.43) ms, P < 0.01], and obviously reduced Fz amplitude [(2.42 ± 2.18) μV vs. (5.65 ± 5.59) μV, P = 0.03]. A significant positive correlation was observed between MMN latencies at Fz and Cz electrodes ( P < 0.01). Oxy-Hb in left frontopolar prefrontal channels (CH15/17) was significantly decreased in patient group ( P < 0.05). Our findings suggest that adolescents with depression exhibit hypofunction in the left prefrontal cortex and impaired automatic sensory processing. The combined application of fNIRS and ERP techniques may provide an objective basis for early clinical identification.
Humans ; Spectroscopy, Near-Infrared/methods* ; Adolescent ; Prefrontal Cortex/physiopathology* ; Evoked Potentials/physiology* ; Depression/physiopathology* ; Female ; Male ; Oxyhemoglobins ; Electroencephalography

Gongju(Chrysanthemum morifolium) is one of the five major medicinal Chrysanthemum varieties included in the Chinese Pharmacopoeia. In recent years, its cultivation areas have changed significantly, resulting in mixed quality of the medicinal herbs. In this study, Gongju cultivated in Anhui, Yunnan, Chongqing, and other places were selected as research objects. Hyperspectral data were collected in the visible-near-infrared(VNIR) and short-wave infrared(SWIR) bands using different modes, such as corolla facing up(A) and flower base facing up(B). After pre-processing the hyperspectral data using five methods, including multiplicative scatter correction(MSC), Savitzky-Golay smoothing(SG), first derivative(D1), second derivative(D2), and standard normal variate(SNV), partial least squares discriminant analysis(PLSDA), random forest(RF), and support vector machine(SVM) were used to establish origin identification models of Gongju at the two geographical scales of the province and the city-county in Anhui province. The accuracy of the prediction results was used as an evaluation index to select the optimal models, and the classification performance of the models was evaluated by confusion matrix. The results showed that the flower base facing up(B) collection model combined with second derivative pretreatment and RF method was the best model for both geographical scale identification models. The modeling effect of the full-band(VNIR + SWIR) was slightly better than that of the single band, with the accuracy of the prediction set in the province and city-county regions reaching 99.69% and 99.40%, respectively. The competitive adaptive reweighted sampling algorithm(CARS), successive projections algorithm(SPA), and variable iterative space shrinkage approach(VISSA) were further used to screen the feature wavelength modeling. The number of feature wavelengths screened by CARS was fewer, and the prediction set accuracy of the two geographical scales models after optimization could reach 99.56% and 98.65%, which was basically comparable to the full-band model. However, the removal of redundant variables could greatly reduce the complexity of the model. The hyperspectral technology combined with the chemometrics model established in this study can achieve the origin identification of Gongju at different geographical scales, providing a theoretical basis and technical reference for the construction of a rapid detection system for Gongju origin and the development of exclusive miniaturized instrumentation and equipment systems.
Chrysanthemum/growth & development* ; China ; Support Vector Machine ; Geography ; Discriminant Analysis ; Spectroscopy, Near-Infrared/methods* ; Spectrum Analysis/methods* ; Drugs, Chinese Herbal/analysis* ; Least-Squares Analysis

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

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

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: 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*