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Drought and salinity stresses present significant challenges that exert a severe impact on crop productivity worldwide. Understanding the dynamics of salicylic acid (SA), a vital phytohormone involved in stress response, can provide valuable insights into the mechanisms of plant adaptation to cope with these challenging conditions. This paper describes and tests a sensor system that enables real-time and non-invasive monitoring of SA content in avocado plants exposed to drought and salinity. By using a reverse iontophoretic system in conjunction with a laser-induced graphene electrode, we demonstrated a sensor with high sensitivity (82.3 nA/[µmol L-1⋅cm-2]), low limit of detection (LOD, 8.2 µmol L-1), and fast sampling response (20 s). Significant differences were observed between the dynamics of SA accumulation in response to drought versus those of salt stress. SA response under drought stress conditions proved to be faster and more intense than under salt stress conditions. These different patterns shed light on the specific adaptive strategies that avocado plants employ to cope with different types of environmental stressors. A notable advantage of the proposed technology is the minimal interference with other plant metabolites, which allows for precise SA detection independent of any interfering factors. In addition, the system features a short extraction time that enables an efficient and rapid analysis of SA content.

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Gastric cancer (GC) is one of the most fatal cancers, characterized by non-specific early symptoms and difficulty in detection. However, there are no valid non-invasive screening tools available for GC. Here we establish a non-invasive method that employs exhaled volatolomics and ensemble learning to detect GC. We developed a comprehensive mass spectrometry-based procedure and determined of a wide range of volatolomics from 314 breath samples. The discovery, identification and verification research screened a biomarker panel to distinguish GC from controls. This panel has achieved 0.90 (0.87-0.94, 95%CI) accuracy, with an area under curve (AUC) of 0.92 (0.89-0.94, 95%CI) in discovery cohort and 0.88 (0.83-0.91, 95%CI) accuracy with an AUC of 0.91 (0.87-0.93, 95%CI) in replication cohort, which outperformed traditional serum markers. Single-cell sequencing and gene set enrichment analysis revealed that these exhaled markers originated from aldehyde oxidation and pyruvate metabolism. Our approach advances the design of exhaled analysis for GC detection and holds promise as a non-invasive method to the clinic.

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Non-invasive detection of hemoglobin (Hb) concentration is of great clinical value for health screening and intraoperative blood transfusion. However, the accuracy and stability of non-invasive detection still need to be improved to meet clinical requirement. This paper proposes a non-invasive Hb detection method using ensemble extreme learning machine (EELM) regression based on eight-wavelength PhotoPlethysmoGraphic (PPG) signals. Firstly, a mathematical model for non-invasive Hb detection based on the Beer-Lambert law is established. Secondly, the captured eight-channel PPG signals are denoised and fifty-six feature values are extracted according to the derived mathematical model. Thirdly, a recursive feature elimination (RFE) algorithm is used to select the features that contribute most to the Hb prediction. Finally, a regression model is built by integrating several independent ELM models to improve prediction stability and accuracy. Experiments conducted on 249 clinical data points (199 cases as the training dataset and 50 cases as the test dataset) evaluate the proposed method, achieving a root mean square error (RMSE) of 1.72 g/dL and a Pearson correlation coefficient (PCC) of 0.76 (p < 0.01) between predicted and reference values. The results demonstrate that the proposed non-invasive Hb detection method exhibits a strong correlation with traditional invasive methods, suggesting its potential for non-invasive detection of Hb concentration.

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INTRODUCTION: Early detection of patients with advanced chronic liver disease is critical for the prevention of complications and inclusion in surveillance programs for hepatocellular carcinoma. In daily clinical care, it remains challenging to differentiate early cirrhosis from lower fibrosis grades without performing a liver biopsy. The aim of the present study was to assess the performance of different non-invasive detection tools to differentiate cirrhosis from lower fibrosis grades. METHODS: Data of 116 patients (51 male, 65 female) with chronic liver disease of various origins undergoing liver biopsy was analyzed. Routine laboratory values, liver stiffness measurement (LSM) by transient elastography, and histological liver assessment were collected. RESULTS: Robust and significant correlations with the histological fibrosis stage were identified for LSM (r = 0.65), the FAST score (0.64), the FIB-4 (0.48), serum aspartate aminotransferase (AST) concentration (0.41), NFS (0.33), international normalized ratio (INR; 0.30), methacetin breath test results (-0.40), and serum albumin concentration (-0.29) by spearman rank correlation. Receiver operating characteristic curves were built for these parameters to separate patients with cirrhosis from those with any other fibrosis stage. The highest AUC was achieved by LSM (0.9130), followed by the FAST score (0.8842), the FIB-4 (0.8644), the NFS (0.8227), INR (0.8142), serum albumin (0.7710), and serum AST (0.7620). The most promising clinical applicability would be an LSM value of 12.2 kPa, achieving 95.7% sensitivity and 75.3% specificity. CONCLUSION: LSM and FAST score seem to be robust non-invasive measurements for liver fibrosis. LSM and FAST scores may have the potential to reliably detect patients with liver cirrhosis in clinical routine settings.

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BACKGROUND: The cell-free RNA (cf-RNA) of spent embryo medium (SEM) has aroused a concern of academic and clinical researchers for its potential use in non-invasive embryo screening. However, comprehensive characterization of cf-RNA from SEM still presents significant technical challenges, primarily due to the limited volume of SEM. Hence, there is urgently need to a small input liquid volume and ultralow amount of cf-RNA library preparation method to unbiased cf-RNA sequencing from SEM. (75) RESULT: Here, we report a high sensitivity agarose amplification-based cf-RNA sequencing method (SEM-Acf) for human preimplantation SEM cf-RNA analysis. It is a cf-RNA sequencing library preparation method by adding agarose amplification. The agarose amplification sensitivity (0.005 pg) and efficiency (105.35 %) were increased than that of without agarose addition (0.45 pg and 96.06 %) by âˆ¼ 90 fold and 9.29 %, respectively. Compared with SMART sequencing (SMART-seq), the correlation of gene expression was stronger in different SEM samples by using SEM-Acf. The cf-RNA number of detected and coverage uniformity of 3' end were significantly increased. The proportion of 5' end adenine, alternative splicing events and short fragments (<400 bp) were increased. It is also found that 4-mer end motifs of cf-RNA fragments was significantly differences between different embryonic stage by day3 spent cleavage medium and day5/6 spent blastocyst medium. (141) SIGNIFICANCE: This study established an efficient SEM amplification and library preparation method. Additionally, we successfully described the characterizations of SEM cf-RNA in preimplantation embryo using SEM-Acf, including expression features and fragment lengths. SEM-Acf facilitates the exploration of cf-RNA as a noninvasive embryo screening biomarker, and opens up potential clinical utilities of small input liquid volume and ultralow amount cf-RNA sequencing. (59).

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Detection of intestinal parasites in fish typically requires autopsy, resulting in the sacrifice of the fish. Here, we describe a non-lethal method for detecting the tapeworm Eubothrium crassum in fish using anal swabs and real-time PCR detection. Two assays were developed to detect cytochrome oxidase I (COI) mitochondrial DNA and 18S ribosomal DNA sequences of E. crassum, respectively. The assays were tested on swab samples from confirmed pathogen free Atlantic salmon (Salmo salar L.) and on samples from farmed Atlantic salmon, where the presence and intensity of parasites had been established through autopsy. The COI assay was shown to be specific to E. crassum, while the 18S assay also amplified the closely related E. salvelini, a species infecting Arctic charr (Salvelinus alpinus L.) in freshwater. The COI assay detected E. crassum in all field samples regardless of parasite load while the 18S assay failed to detect the parasite in two samples. The results thus demonstrates that this non-lethal approach can effectively detect E. crassum and can be a valuable tool in assessing the prevalence of infection in farmed salmon, aiding in treatment decisions and evaluating treatment effectiveness.

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Edema, characterized by brain swelling, is a common response observed in various brain injuries. Timely detection of edema is crucial to mitigate the associated risks and improve patient care. This study evaluates the efficacy of CEREBO®, a non-invasive machine learning-powered near-infrared spectroscopy (mNIRS) based device, in detecting edema. The study was conducted on 234 participants with suspected head injuries who underwent simultaneous CEREBO® scans and CT head scans. The results of the study showed that CEREBO® effectively identified edematous lobes, achieving a sensitivity of 95.7%, specificity of 97%, and accuracy of 96.9% for cases with intracranial hemorrhage (ICH). Additionally, for cases without ICH, the device exhibited a sensitivity of 100%, specificity of 97.2%, and accuracy of 97.2%. Two cases were reported where CEREBO® failed to detect edematous ICH. The study highlights the potential of CEREBO® as a valuable tool for early detection of pre-symptomatic edema and ICH, enabling timely interventions and improved patient care. The findings support the reliability of near-infrared spectroscopy as a diagnostic modality for edema.

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Eosinophilic pustular folliculitis (EPF) is a rare skin disease for which the gold standard of diagnosis relies on the invasive examination of pathological tissue sections. However, due to its invasive nature, many patients tend to refuse this diagnostic test. In such situations, reflectance confocal microscopy (RCM) can be a valuable diagnosis tool. Reflectance confocal microscopy (RCM) can accurately identify the specific structures for biopsy and provide objective imaging data to evaluate clinical symptoms following treatment. Therefore, we present a case report demonstrating the utility of RCM in diagnosing and assessing the treatment of the rare disease EPF for reference.

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In recent years, the incidence of diabetes mellitus has grown exponentially worldwide. It is well-established that blood glucose monitoring is crucial to evaluate pancreatic islet function and determine the optimal medication regimen. However, most current blood glucose meters use invasive techniques, which can cause pain and infection. Non-invasive blood glucose monitoring techniques have gained significant attention as a potential solution to overcome the limitations of current monitoring methods. This review compares the progress and challenges of electrochemical, optical, and electromagnetic/microwave non-invasive blood glucose monitoring techniques to discuss future research trends. Due to the rapid development of wearable devices and transdermal biosensors, which provide efficient, stable, and cost-effective monitoring without the need for invasive blood samples, the market for non-invasive blood glucose monitoring is predicted to become more competitive.

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BACKGROUND AND OBJECTIVE: Abnormal bilirubin metabolism can result in various liver function disorders. Current clinical practice for bilirubin level detection involves invasive blood collection from patients, which is time-consuming, painful, and poses infection risks. Thus, there is a pressing need for non-invasive bilirubin detection methods. This study aims to develop a non-invasive total serum bilirubin(TSB) detection method in humans based on multi-wavelength photoplethysmography (PPG) signals. METHODS: The experimental instrument includes a light source and a spectrometer. PPG signals are collected from the subjects' fingers, and the samples are selected based on the PPG deviation degree screening method. The absorption spectrum of blood is extracted from the PPG signal using dynamic spectroscopy. Finally, locally developed software calculates the total bilirubin value. The instrument is modeled and validated according to the clinical-biochemical test values. RESULTS: The results of the prediction set (correlation coefficient is 0.91, RSMEP is 2.32 umol/L, average absolute error percentage is 9.3%) show that our method has a strong correlation with the detection results of clinical-biochemical analysis instruments. The Bland-Altman test showed that the device deviated from the data detected by biochemical methods in the clinic with a mean deviation of about 0.12 umol/L and a 95% confidence interval between -2.95 umol/L and 2.7 umol/L. CONCLUSIONS: This study's non-invasive bilirubin detection method has high accuracy, which can meet the needs of continuous non-invasive total bilirubin detection in clinical practice.

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Plant stress responses involve a suite of genetically encoded mechanisms triggered by real-time interactions with their surrounding environment. Although sophisticated regulatory networks maintain proper homeostasis to prevent damage, the tolerance thresholds to these stresses vary significantly among organisms. Current plant phenotyping techniques and observables must be better suited to characterize the real-time metabolic response to stresses. This impedes practical agronomic intervention to avoid irreversible damage and limits our ability to breed improved plant organisms. Here, we introduce a sensitive, wearable electrochemical glucose-selective sensing platform that addresses these problems. Glucose is a primary plant metabolite, a source of energy produced during photosynthesis, and a critical molecular modulator of various cellular processes ranging from germination to senescence. The wearable-like technology integrates a reverse iontophoresis glucose extraction capability with an enzymatic glucose biosensor that offers a sensitivity of 22.7 nA/(µM·cm2), a limit of detection (LOD) of 9.4 µM, and a limit of quantification (LOQ) of 28.5 µM. The system's performance was validated by subjecting three different plant models (sweet pepper, gerbera, and romaine lettuce) to low-light and low-high temperature stresses and demonstrating critical differential physiological responses associated with their glucose metabolism. This technology enables non-invasive, non-destructive, real-time, in-situ, and in-vivo identification of early stress response in plants and provides a unique tool for timely agronomic management of crops and improving breeding strategies based on the dynamics of genome-metabolome-phenome relationships.

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In the present study, bimetallic nanoparticles (NPs) consisting of gold (AuNPs) as the core and silver (AgNPs) as the shell have been synthesized and applied as the nanoprobe for detection of fluvoxamine (FXM) as the anti-depression drug. The physicochemical properties of the prepared citrate-capped Au@Ag core-shell NPs have been characterized by UV-Vis, Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM) and scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) techniques. The design of the smartphone-based colorimetric FXM sensor relies on the fast hydrolysis of FXM under alkaline conditions by producing of 2-(Aminooxy)ethanamine without any significant peak at 400-700 nm. The interaction of the resulted molecule with the nanoprobe induced a red shift in the longitudinal localized surface plasmon resonance (LSPR) peak of the nanoprobe, which was accompanied by sharp and vivid color variations in the solution. A linear relationship between the absorption signal increasing by FXM concentration increasing from 1 µM to 10 µM presented a simple, low cost and minimally instrumented format for FXM quantification with a limit of detection (LOD) of 100 nM. The collected visual data with the elegant colorimetric response of the nanoprobe in the presence of FXM from Indian red to light red violet and bluish-purple color offered simple detection of FXM with the naked eye. The satisfactory results of the proposed cost-effective sensor in the rapid assay of FXM in human serum, urine, saliva and pharmaceutical samples guarantee the potential of the nanoprobe for on-site and visual determination of FXM in actual samples. The proposed sensor as the first non-invasive FXM sensor for saliva sample analysis may hold great promise to provide the technical support for the rapid and valid detection of FXM for forensic medicine and clinical organizations.

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The rate of pregnancy can be affected by many factors in assisted reproductive technology (ART), and one of which is the quality of embryos. Therefore, selecting the embryos with high potential is crucial for the outcome. Fifteen spent blastocyst medium (SBM) samples were collected from 14 patients who received in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI), seven from high-grade embryos and eight from low-grade embryos. Cell-free RNA (cf-RNA) profile of SBM samples were analyzed by RNA sequencing in the present study. It was found that a large amount of cf-RNA were released into SBM, including protein-coding genes (68.9%) and long noncoding RNAs (lncRNAs) (17.26%). Furthermore, a high correlation was observed between blastocyst genes and SBM genes. And the cf-mRNAs of SBM were highly fragmented, and coding sequence (CDS) and untranslated (UTR) regions were released equally. Two hundred and thirty-two differentially expressed genes were identified in high-grade SBM (hSBM) and low-grade SBM (lSBM), which could be potential biomarker in distinguishing the embryos with different quality as an alternative or supplementary approach for subjective morphology criteria. Hence, cf-RNAs sequencing revealed the characterization of circulating transcriptomes of embryos with different quality. Based on the results, the genes related to blastocyst quality were screened, including the genes closely related to translation, immune-signaling pathway, and amino acid metabolism. Overall, the present study showed the types of SBM cf-RNAs, and the integrated analysis of cf-RNAs profiling with morphology grading displayed its potential in predicting blastocyst quality. The present study provided valuable scientific basis for noninvasive embryo selection in ART by RNA-profiling analysis.

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Bladder cancer (BC) is the 10th most common cancer in the world. While there are FDA-approved urinary assays to detect BC, none have demonstrated sufficient sensitivity and specificity to be integrated into clinical practice. Telomerase Reverse Transcriptase (TERT) gene mutations have been identified as the most common BC mutations that could potentially be used as non-invasive urinary biomarkers to detect BC. This study aims to evaluate the validity of these tests to detect BC in the Kerman province of Iran, where BC is the most common cancer in men. Urine samples of 31 patients with primary (n = 11) or recurrent (n = 20) bladder tumor and 50 controls were prospectively collected. Total urinary DNA was screened for the TERT promoter mutations (uTERTpm) by Droplet Digital PCR (ddPCR) assays. The performance characteristics of uTERTpm and the influence by disease stage and grade were compared to urine cytology results. The uTERTpm was 100% sensitive and 88% specific to detect primary BC, while it was 50% sensitive and 88% specific in detecting recurrent BC. The overall sensitivity and specificity of uTERTpm to detect bladder cancer were 67.7% and 88.0%, respectively, which were consistent across different tumor stages and grades. The most frequent uTERTpm mutations among BC cases were C228T (18/31), C250T (4/31), and C158A (1/31) with mutant allelic frequency (MAF) ranging from 0.2% to 63.3%. Urine cytology demonstrated a similar sensitivity (67.7%), but lower specificity (62.0%) than uTERTpm in detecting BC. Combined uTERTpm and urine cytology increased the sensitivity to 83.8%, but decreased the specificity to 52.0%. Our study demonstrated promising diagnostic accuracy for the uTERTpm as a non-invasive urinary biomarker to detect, in particular, primary BC in this population.

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Lactate concentration is of increasing interest as a diagnostic for sepsis, septic shock, and trauma. Compared with the traditional blood sample media, the exhaled breath condensate (EBC) has the advantages of non-invasiveness and higher user acceptance. An amperometric biosensor was developed and its application in EBC lactate detection was investigated in this paper. The sensor was modified with PEDOT:PSS-PB, and two different lactate oxidases (LODs). A rotating disk electrode and Koutecky-Levich analysis were applied for the kinetics analysis and gel optimization. The optimized gel formulation was then tested on disposable screen-printed sensors. The disposable sensors exhibited good performance and presented a high stability for both LOD modifications. Finally, human EBC analysis was conducted from a healthy subject at rest and after 30 min of intense aerobic cycling exercise. The sensor coulometric measurements showed good agreement with fluorometric and triple quadrupole liquid chromatography mass spectrometry reference methods. The EBC lactate concentration increased from 22.5 µM (at rest) to 28.0 µM (after 30 min of cycling) and dropped back to 5.3 µM after 60 min of rest.

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Sentinel lymph node (SLN) biopsy is the key diagnostic procedure to determine tumor metastasis and treatment plan. Current SLN biopsy has considerable drawbacks in that SLNs (both malignant and normal) must be removed by navigation surgery, followed by a time-consuming pathological examination. The selective, non-invasive, and real-time diagnosis of metastatic status in SLNs is becoming essential. Methods: Here, we design two lanthanide-doped nanoparticles as a pair of NIR-II ratiometric fluorescence probes, one of which is conjugated with tumor-targeting moiety, while the other is conjugated with PEG as an internal reference. The NIR-II ratiometric fluorescence signal (I1060 nm/I1525 nm) from two well-separated channels were used to identify the tumor-draining SLNs. The precise navigation surgery of metastatic SLNs was performed and we further evaluated their surgery outcomes. Results: The NIR-II ratiometric fluorescence facilitates an ideal fluorescence-guided surgery with only resection of tumor-positive SLNs, thereby avoiding unnecessary removal of the normal SLNs. In addition, our system has a time-saving operation procedure and can be performed under the operation light without altering the appearance of surgical settings. Conclusion: The present study enables non-invasive and real-time detection metastatic status in SLNs with high sensitivity and selectivity. Our investigations will provide a new direction for SLN biopsy and substantially improve cancer surgery outcomes.

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BACKGROUND: Cystoscopy is the gold standard for bladder cancer detection, but is costly, invasive and has imperfect diagnostic accuracy. We aimed to identify novel and accurate DNA methylation biomarkers for non-invasive detection of bladder cancer in urine, with the potential to reduce the number of cystoscopies among hematuria patients. RESULTS: Biomarker candidates (n = 32) were identified from methylome sequencing of urological cancer cell lines (n = 16) and subjected to targeted methylation analysis in tissue samples (n = 60). The most promising biomarkers (n = 8) were combined into a panel named BladMetrix. The performance of BladMetrix in urine was assessed in a discovery series (n = 112), consisting of bladder cancer patients, patients with other urological cancers and healthy individuals, resulting in 95.7% sensitivity and 94.7% specificity. BladMetrix was furthermore evaluated in an independent prospective and blinded series of urine from patients with gross hematuria (n = 273), achieving 92.1% sensitivity, 93.3% specificity and a negative predictive value of 98.1%, with the potential to reduce the number of cystoscopies by 56.4%. CONCLUSIONS: We here present BladMetrix, a novel DNA methylation urine test for non-invasive detection of bladder cancer, with high accuracy across tumor grades and stages, and the ability to spare a significant number of cystoscopies among patients with gross hematuria.

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PURPOSE: Atherosclerosis plays a significant role in the initiation of coronary artery aneurysms (CAA). Although the treatment options for this kind of vascular disease are developing, there are challenges and limitations in both selecting and applying sufficient medical solutions. For surgical interventions, that are novel therapies, non-invasive specific patient-based studies could lead to obtaining more promising results. Despite medical and pathological tests, these pre-surgical investigations require special biomedical and computer-aided engineering techniques. In this study, a machine learning (ML) model is proposed for the non-invasive detection of atherosclerotic CAA for the first time. METHODS: The database for study was collected from hemodynamic analysis and computed tomography angiography (CTA) of 80 CAAs from 61 patients, approved by the Institutional Review Board (IRB). The proposed ML model is formulated for learning by a one-class support vector machine (1SVM) that is a field of ML to provide techniques for outlier and anomaly detection. RESULTS: The applied ML algorithms yield reasonable results with high and significant accuracy in designing a procedure for the non-invasive diagnosis of atherosclerotic aneurysms. This proposed method could be employed as a unique artificial intelligence (AI) tool for assurance in clinical decision-making procedures for surgical intervention treatment methods in the future. CONCLUSIONS: The non-invasive diagnosis of the atherosclerotic CAAs, which is one of the vital factors in the accomplishment of endovascular surgeries, is important due to some clinical decisions. Although there is no accurate tool for managing this kind of diagnosis, an ML model that can decrease the probability of endovascular surgical failures, death risk, and post-operational complications is proposed in this study. The model is able to increase the clinical decision accuracy for low-risk selection of treatment options.

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Quality control methods of current traditional Chinese medicine (TCM) preparation is time-consuming and difficult to assess in terms of overall efficiency of the drug. A non-destructive rapid near-infrared spectroscopy detection system for key chemical components and biological activity of Lanqin oral solution (LOS), one of the best-selling TCM formulations, was established for comprehensive quality evaluation. Near infrared spectral scanning was carried out on 101 batches of commercial LOS under the penetrated vial state and traditional state. RAW 264.7 cells were cultured to detect the anti-inflammatory ability of LOS, and the reference concentrations of epigoitrin, geniposide, and baicalin were obtained by HPLC. The quantitative models were optimized by three kinds of variable selection methods. The correlation coefficients of prediction value of the models were greater than 0.94. The system also passed the external validation. The performance of the non-invasive models was similar to the traditional models. The established non-destructive system can be applied to the rapid quality inspection of LOS to avoid unqualified drugs from entering the market and ensure drug effectiveness. The biological activity index of LOS was introduced and predicted by NIRs for the first time, which provides a new idea about the quality control of TCM formulations.

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