In vitro antibacterial activity of danofloxacin against Escherichia coli in Gushi chickens and its residue depletion following multiple oral administration.

This study aimed to investigate the in vitro antibacterial activity of danofloxacin against Escherichia coli isolated from Gushi chickens, as well as the tissue distribution and residue depletion of danofloxacin in Gushi chickens following multiple oral administration. A total of 42 clinical E. coli strains were isolated from the cloaca of locally farmed Gushi chickens between August and October 2023. Then the minimum inhibitory concentration (MIC) of danofloxacin against these isolates was determined by broth microdilution method. Additionally, 42 healthy Gushi chickens were randomly divided into 6 groups, and danofloxacin was orally administered at a dose of 5 mg/kg body weight (BW) for 3 consecutive days. Plasma, intestinal content, and tissue samples, including muscle, skin + fat, liver, kidney, lung, and intestine, were collected at 4, 12, 24, 48, 72, and 120 h after the last administration. Danofloxacin concentrations in all samples were determined using a high-performance liquid chromatography (HPLC) method. The average concentration vs. time data were then subjected to noncompartmental analysis using Phoenix software, and withdrawal periods for danofloxacin in Gushi chickens were further determined with WT1.4 software, setting a 95% confidence interval. Results indicated a notable inhibitory effect of danofloxacin on E. coli, with an MIC50 of 0.5 µg/mL. Additionally, danofloxacin exhibited widespread distribution in Gushi chickens, detectable in all collected samples. Among all tissues, the liver exhibited the highest concentration, followed by the intestine. Even on the fifth day postadministration, danofloxacin persisted in skin + fat, liver, and lung. The elimination half-lives (t1/2λzs) of danofloxacin varied across samples: skin + fat (47.87 h), lung (30.61 h), liver (22.07 h), plasma (16.05 h), muscle (12.53 h), intestine (9.83 h), and kidney (6.34 h). Considering residue depletion and the maximum residue limit (MRL) of danofloxacin in poultry set by Chinese regulatory authorities, withdrawal periods for the kidney, muscle, liver, and skin + fat were determined as 1.03, 1.38, 3.34, and 5.85 d, respectively, rounded to a final withdrawal time of 6 d.

Depletion of tilmicosin residue in Gushi chickens following oral administration via drinking water.

This study aimed to examine the depletion of tilmicosin residues in Gushi chickens following the administration at a concentration of 75 mg/L in their drinking water for three consecutive days. Plasma, liver, kidney, lung, muscle, and skin + fat samples were collected from 6 chickens at 6 h, 1, 3, 5, and 7 days after the treatment. Tilmicosin concentrations in the samples were determined using a high-performance liquid chromatography (HPLC) method. The findings revealed that the highest tilmicosin residues were detected in the liver, followed by the kidney, lung, skin + fat, muscle, and plasma. Notably, at 7 days post-treatment, no drug residue was detected in all samples except for the liver and kidney. The non-compartmental model was employed to calculate relevant pharmacokinetic parameters. The elimination half-lives (t1/2λz ) of tilmicosin were as follows, ranked from long to short: skin + fat (45.42 h), liver (44.17 h), kidney (40.06 h), plasma (37.64 h), lung (31.39 h), and muscle (30.05 h). Considering the current residue depletion and the maximum residue limits (MRLs) set by Chinese regulatory authorities, the withdrawal times for tilmicosin were estimated as 18.91, 10.81, and 8.58 days in the kidney, liver, and skin + fat, respectively. A rounded-up value of 19 days was selected as the conclusive withdrawal time. Furthermore, based on the observed tilmicosin concentrations in plasma and lung, combined with previously reported minimum inhibitory concentration (MIC) values against Mycoplasma gallisepticum, the current dosing regimen was deemed adequate for treating Mycoplasma gallisepticum infections in Gushi chickens.

Pharmacokinetics of Danofloxacin in Gushi Chickens after Single Oral and Intravenous Administration.

This study aimed to determine the pharmacokinetics of danofloxacin in Gushi chickens after a single oral (PO) and intravenous (IV) dose at 5 mg/kg body weight (BW). Thirty-two Gushi chickens, aged 20 weeks, were selected and divided into two groups at random, with each group consisting of 16 chickens, evenly distributed between males and females. Following danofloxacin administration, blood samples were taken at predetermined time intervals and the plasma was separated. The concentrations of danofloxacin in plasma were quantified by HPLC with a fluorescence detector. Then the concentrations versus time data were subjected to non-compartmental analysis (NCA) using Phoenix software (version: 8.1.0). After administering danofloxacin orally at a dose of 5 mg/kg BW to Gushi chickens, our results demonstrated that the peak concentration reached 0.53 µg/mL at 4 h. The half-life of absorption (t1/2ka) was determined to be 2.37 ± 1.60 h, and the bioavailability (F) was calculated as 40.12 ± 15.83%. For both oral and intravenous administration, the area under the concentration-time curve (AUC0-∞) was determined to be 4.72 ± 1.86 and 11.76 ± 3.25 h·µg/mL, respectively. The corresponding elimination half-life (t1/2λz) was measured as 11.24 ± 3.90 and 10.17 ± 3.72 h. Moreover, the mean residence time (MRT) was calculated as 10.20 ± 2.47 and 7.05 ± 1.97 h for these respective routes. Based on the calculated AUC/MIC ratio values, it can be inferred that the 5 mg/kg BW dosage of danofloxacin, whether administered orally or intravenously, is expected to effectively treat Escherichia coli and Pasteurella multocida infections in Gushi chickens.

Towards Adversarial Robustness for Multi-Mode Data through Metric Learning.

Adversarial attacks have become one of the most serious security issues in widely used deep neural networks. Even though real-world datasets usually have large intra-variations or multiple modes, most adversarial defense methods, such as adversarial training, which is currently one of the most effective defense methods, mainly focus on the single-mode setting and thus fail to capture the full data representation to defend against adversarial attacks. To confront this challenge, we propose a novel multi-prototype metric learning regularization for adversarial training which can effectively enhance the defense capability of adversarial training by preventing the latent representation of the adversarial example changing a lot from its clean one. With extensive experiments on CIFAR10, CIFAR100, MNIST, and Tiny ImageNet, the evaluation results show the proposed method improves the performance of different state-of-the-art adversarial training methods without additional computational cost. Furthermore, besides Tiny ImageNet, in the multi-prototype CIFAR10 and CIFAR100 where we reorganize the whole datasets of CIFAR10 and CIFAR100 into two and ten classes, respectively, the proposed method outperforms the state-of-the-art approach by 2.22% and 1.65%, respectively. Furthermore, the proposed multi-prototype method also outperforms its single-prototype version and other commonly used deep metric learning approaches as regularization for adversarial training and thus further demonstrates its effectiveness.

Population Pharmacokinetics of Difloxacin in Crucian Carp (Carassius auratus) after a Single Oral Administration.

This study aimed to investigate the population pharmacokinetics of difloxacin in crucian carp (Carassius auratus) orally provided a single dose of 20 mg/kg body weight (BW). To achieve this, fish were sampled at various intervals using a sparse sampling strategy, and plasma samples were analyzed using the high-performance liquid chromatography (HPLC) method. Subsequently, naïve average data were analyzed using a non-compartmental method, and a population model was developed based on the nonlinear mixed effects approach. The covariate of BW and the relationship between covariances were sequentially incorporated into the population model. However, it was found that only covariance and not BW affected the population parameters. Therefore, the covariance model was taken as the final population model, which revealed that the typical values of the absorption rate constant (tvKa), apparent volume of distribution per bioavailability (tvV), and clearance rate per bioavailability (tvCl) were 1.18 1/h, 14.18 L/kg, and 0.20 L/h/kg, respectively. Based on the calculated free AUC/MIC values, the current oral dose of difloxacin (20 mg/kg BW) cannot generate adequate plasma concentrations to inhibit pathogens with MIC values above 0.83 µg/mL. Further study should be carried out to collect the pathogens from crucian carp and determine the MIC data of difloxacin against them. Pharmacodynamic experiments must also be further carried out to determine the optimal therapeutic dose for the treatment of Aeromonas hydrophila infection.

Pharmacokinetics of meloxicam in pigeons after single intravenous, oral, and intramuscular administration.

This study aimed to determine the pharmacokinetics of meloxicam in pigeons. Twenty-four 7-wk-old meat pigeons (Columba livia) were randomly divided into 3 groups (PO, IM, and IV) and given a single dose of 1 mg/kg body weight of meloxicam. Plasma samples were taken at predetermined times, which were then analyzed using a validated high-performance liquid chromatography (HPLC) method and subjected to noncompartmental analysis using Phoenix software. Results indicated that meloxicam was absorbed effectively and quickly after PO and IM dosing. Peak concentrations (0.83 ± 0.21 and 1.59 ± 0.49 µg/mL) were achieved at 2 and 0.26 h, respectively, with mean absorption times of 2.56 ± 1.50 and 1.47 ± 0.89 h. Bioavailability was high at 86.31 ± 43.45% and 81.57 ± 52.58%, respectively, and the area under the concentration-time curve (AUC0-∞) was 5.33 ± 2.68 and 5.03 ± 3.26 h·µg/mL. After IV administration, the elimination was faster with a total body clearance (CL) of 188.75 ± 83.23 mL/h/kg, an elimination half-life (t1/2λz) of 1.76 ± 0.56 h, and a volume of distribution at steady-state (VSS) of 427.50 ± 188.43 mL/kg. Considering the lack of a precise analgesic threshold of meloxicam in pigeons and the notable differences in its analgesic threshold among various animal species, formulating a dosing regimen in pigeons presented a significant challenge. Based on the previous analgesic threshold (3.5 µg/mL) in parrots, a higher dose (e.g., 2 mg/kg) or shorter dosing interval (e.g., every 6 h) is recommended for treating pain in pigeons. Nonetheless, further pharmacodynamic research is required to verify these recommendations.

Egg residue and depletion of meloxicam in Jing Hong laying hens following multiple oral doses.

Meloxicam is a nonsteroidal anti-inflammatory drug (NSAID) commonly used in an extra-label manner in commercial laying hens for the treatment of foot lesions, which are a common issue in this species. The present study aimed to determine the depletion profiles of meloxicam in eggs with multiple oral administration under 2 different dosing regimens and to further recommend reasonable withdrawal intervals (WDIs). Meloxicam (1 mg/kg) was administered orally to laying hens under 2 dosing schedules: 10 doses at 24-h intervals and 15 doses at 12-h intervals. Eggs were collected daily after the first dosing, and meloxicam concentrations in both yolk and white were determined by a high-performance liquid chromatography (HPLC) method. The weight ratio of white to yolk in the whole egg was 1.54 (the mean of 20 eggs with repeated tests), and this value combined with the meloxicam concentrations in white and yolk were used to calculate the drug concentrations in whole eggs. Meloxicam was quickly eliminated from egg white, and its concentrations could only be quantified at 2 time points during the elimination phase. The elimination half-lives in yolk and whole egg were 3.07 ± 1.00 and 2.98 ± 0.88 d, respectively, after 10 repeated doses. And the corresponding elimination half-lives were 2.30 ± 0.83 and 2.18 ± 0.67 d, respectively, after repeated 15 doses. Considering the time when meloxicam was not detectable in eggs with the time of ovum development and maturation, a withdrawal interval (WDI) was suggested as 17 d for both dosing schedules. The current results enriched the study on the residue of meloxicam in domestic Jing Hong laying hens and provided WDIs to help ensure animal-derived food safety.

Development and Application of a Physiologically Based Pharmacokinetic Model for Diclazuril in Broiler Chickens.

Withdrawal periods for diclazuril in broilers have traditionally been determined through regression analysis. However, over the last two decades, the physiologically based pharmacokinetic (PBPK) model has gained prominence as a predictive tool for veterinary drug residues, which offers an alternative method for establishing appropriate withdrawal periods for veterinary drugs. In this current study, a flow-limited PBPK model was developed to predict diclazuril concentrations in broilers following long-duration administration via medicated feed and water. This model consists of nine compartments, including arterial and venous plasma, lung, muscle, skin + fat, kidney, liver, intestine contents, and the rest of the body compartment. Physiological parameters such as tissue weights (Vcxx) and blood flow (Qcxx) were gathered from published studies, and tissue/plasma partition coefficients (Pxx) were calculated through the area method or parameter optimization. Published diclazuril concentrations were compared to the predicted values, indicating the accuracy and validity of the model. The sensitivity analysis showed that parameters associated with cardiac output, drug absorption, and elimination significantly affected diclazuril concentrations in the muscle. Finally, a Monte Carlo analysis, consisting of 1000 iterations, was conducted to calculate the withdrawal period. Based on the Chinese MRL values, we calculated a withdrawal period of 0 days for both recommended dosing regimens (through mediated water and feed at concentrations of 0.5-1 mg/L and 1 mg/kg, respectively). However, based on the European MRLs, longer periods were determined for the mediated feed dosing route. Our model provides a foundation for scaling other coccidiostats and poultry species.

Towards a Controllable and Reversible Privacy Protection System for Facial Images through Enhanced Multi-Factor Modifier Networks.

Privacy protection data processing has been critical in recent years when pervasively equipped mobile devices could easily capture high-resolution personal images and videos that may disclose personal information. We propose a new controllable and reversible privacy protection system to address the concern in this work. The proposed scheme can automatically and stably anonymize and de-anonymize face images with one neural network and provide strong security protection with multi-factor identification solutions. Furthermore, users can include other attributes as identification factors, such as passwords and specific facial attributes. Our solution lies in a modified conditional-GAN-based training framework, the Multi-factor Modifier (MfM), to simultaneously accomplish the function of multi-factor facial anonymization and de-anonymization. It can successfully anonymize face images while generating realistic faces satisfying the conditions specified by the multi-factor features, such as gender, hair colors, and facial appearance. Furthermore, MfM can also de-anonymize de-identified faces to their corresponding original ones. One crucial part of our work is design of physically meaningful information-theory-based loss functions, which include mutual information between authentic and de-identification images and mutual information between original and re-identification images. Moreover, extensive experiments and analyses show that, with the correct multi-factor feature information, the MfM can effectively achieve nearly perfect reconstruction and generate high-fidelity and diverse anonymized faces to defend attacks from hackers better than other methods with compatible functionalities. Finally, we justify the advantages of this work through perceptual quality comparison experiments. Our experiments show that the resulting LPIPS (with a value of 0.35), FID (with a value of 28), and SSIM (with a value of 0.95) of MfM demonstrate significantly better de-identification effects than state-of-the-art works. Additionally, the MfM we designed can achieve re-identification, which improves real-world practicability.

DEFAEK: Domain Effective Fast Adaptive Network for Face Anti-Spoofing.

Existing deep learning based face anti-spoofing (FAS) or deepfake detection approaches usually rely on large-scale datasets and powerful networks with significant amount of parameters to achieve satisfactory performance. However, these make them resource-heavy and unsuitable for handheld devices. Moreover, they are limited by the types of spoof in the dataset they train on and require considerable training time. To produce a robust FAS model, they need large datasets covering the widest variety of predefined presentation attacks possible. Testing on new or unseen attacks or environments generally results in poor performance. Ideally, the FAS model should learn discriminative features that can generalize well even on unseen spoof types. In this paper, we propose a fast learning approach called Domain Effective Fast Adaptive nEt-worK (DEFAEK), a face anti-spoofing approach based on the optimization-based meta-learning paradigm that effectively and quickly adapts to new tasks. DEFAEK treats differences in an environment as domains and simulates multiple domain shifts during training. To further improve the effectiveness and efficiency of meta-learning, we adopt the metric learning in the inner loop update with careful sample selection. With extensive experiments on the challenging CelebA-Spoof and FaceForensics++ datasets, the evaluation results show that DEFAEK can learn cues independent of the environment with good generalization capability. In addition, the resulting model is lightweight following the design principle of modern lightweight network architecture and still generalizes well on unseen classes. In addition, we also demonstrate our model's capabilities by comparing the numbers of parameters, FLOPS, and model performance with other state-of-the-art methods.

Pharmacokinetics of danofloxacin after single oral and intravenous administration in non-laying hens.

The current study aimed to explore the pharmacokinetics of danofloxacin in non-laying hens after a single oral (PO) and intravenous (IV) dose, both at 5 mg/kg body weight (BW). Eighteen 13-week-old healthy hens were equally and randomly divided into two groups. After both doses, blood samples (approximately 1 ml) were collected at different time points. Danofloxacin concentrations were quantified by a validated high-performance liquid chromatography (HPLC) method followed by a non-compartmental analysis using the software of WinNonLin. The elimination half-lives (t1/2λz s) after PO and IV routes were determined as 8.15 ± 3.37 and 7.69 ± 3.40 h, respectively. After IV administration, danofloxacin had an initial concentration (C0 ) of 3.62 µg/ml, a volume of distribution at steady state (VSS ) of 3579.72 ± 454.29 ml/kg, and a total body clearance (Cl) of 0.49 ml/h/g. After PO administration, the absolute bioavailability and absorption half-life (t1/2ka ) were calculated as 100.99% ± 23.10% and 0.82 ± 0.58 h, respectively. Based on the calculated ratio values of AUC/MIC and Cmax /MIC, an oral dose of 5 mg/kg danofloxacin would be expected to successfully treat hens infected with strains with MIC values ≤0.1 µg/ml.

Effects of alfalfa saponins on the production performance, serum biochemical factors, and immune factors in Small-Tailed Han sheep.

This study aimed to determine the potential effects of alfalfa saponins on the production performance, serum biochemical factors, and immune factors in sheep. Twenty Small-Tailed Han sheep were equally and randomly divided into Groups 1-4, fed with diets containing 0, 5, 10, and 20 g alfalfa saponins per kg, respectively, for 40 consecutive days. During the treatments, the body weight change was recorded for each sheep. Before, during, and after the treatments of alfalfa saponins, serum was collected from each group to compare the levels of biochemical and immune factors. All sheep were killed after the treatments, and the longissimus dorsi muscle was collected to compare the meat quality. The results validated the effects of alfalfa saponins on the growth performance and meat quality in Small-Tailed Han sheep, and the supplementation level of 10 g/kg was the best. Alfalfa saponins also had effects on the levels of biochemical factors in serum. However, both dose- and time-dependent effects were observed. After a shorter feeding period (14 days), the concentrations of cholesterol (CHOL) and low-density lipoprotein (LDL) in Groups 2, 3, and 4 were all lower than those in the control group; however, when alfalfa saponins were continuously fed, this effect was not apparent or even gone. Supplying alfalfa saponins increased serum concentrations of IgA, IgG, IgE, IgM, IL-1, IFN-α, and IFN-ß. And this effect was distinctly observed in Groups 3 and 4. Based on the current results, the alfalfa saponins concentration of 10 g/kg (for 14 consecutive days) could be suggested as the optimum ratio for good health conditions of Small-Tailed Han sheep.

Pharmacokinetics of meloxicam in laying hens after single intravenous, oral, and intramuscular administration.

The objective of this study was to determine the pharmacokinetics of meloxicam after a single intravenous (IV), intramuscular (IM), and oral (PO) dose at 1 mg/kg body weight in Jing Hong laying hens. Blood samples were collected at predetermined time points. Plasma meloxicam concentrations were determined using a validated high-performance liquid chromatography (HPLC) assay method and then subjected to a non-compartmental analysis. After IV administration, meloxicam had a mean (±SD) volume of distribution at steady-state (Vdss ) of 206.50 ± 25.23 ml/kg, a terminal half-life (t1/2λ ) of 5.45 ± 0.53 h, and a total body clearance (Cl) of 26.48 ± 4.13 ml/h/kg. After PO and IM administration, meloxicam was absorbed relatively rapidly: the peak concentrations (Cmax s) of 3.04 ± 0.56 and 8.94 ± 2.31 µg/ml were observed at 3.08 and 0.80 h, respectively. After PO and IM administration, the absolute bioavailability (F) was determined as 70.13% and 125.50%, respectively. Assuming that hens shared the same analgesic threshold of meloxicam (0.5 µg/ml) with humans, the plasma concentrations after three different routes (PO, IM, and IV) of administration were above this value for 16.7, 19.2, and 14.9 h, respectively.

Lightweight Face Anti-Spoofing Network for Telehealth Applications.

Online healthcare applications have grown more popular over the years. For instance, telehealth is an online healthcare application that allows patients and doctors to schedule consultations, prescribe medication, share medical documents, and monitor health conditions conveniently. Apart from this, telehealth can also be used to store a patient's personal and medical information. With its rise in usage due to COVID-19, given the amount of sensitive data it stores, security measures are necessary. A simple way of making these applications more secure is through user authentication. One of the most common and often used authentications is face recognition. It is convenient and easy to use. However, face recognition systems are not foolproof. They are prone to malicious attacks like printed photos, paper cutouts, replayed videos, and 3D masks. The goal of face anti-spoofing is to differentiate real users (live) from attackers (spoof). Although effective in terms of performance, existing methods use a significant amount of parameters, making them resource-heavy and unsuitable for handheld devices. Apart from this, they fail to generalize well to new environments like changes in lighting or background. This paper proposes a lightweight face anti-spoofing framework that does not compromise on performance. Our proposed method achieves good performance with the help of an ArcFace Classifier (AC). The AC encourages differentiation between spoof and live samples by making clear boundaries between them. With clear boundaries, classification becomes more accurate. We further demonstrate our model's capabilities by comparing the number of parameters, FLOPS, and performance with other state-of-the-art methods.

Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms.

Achieving the upper limits of face identification accuracy in forensic applications can minimize errors that have profound social and personal consequences. Although forensic examiners identify faces in these applications, systematic tests of their accuracy are rare. How can we achieve the most accurate face identification: using people and/or machines working alone or in collaboration? In a comprehensive comparison of face identification by humans and computers, we found that forensic facial examiners, facial reviewers, and superrecognizers were more accurate than fingerprint examiners and students on a challenging face identification test. Individual performance on the test varied widely. On the same test, four deep convolutional neural networks (DCNNs), developed between 2015 and 2017, identified faces within the range of human accuracy. Accuracy of the algorithms increased steadily over time, with the most recent DCNN scoring above the median of the forensic facial examiners. Using crowd-sourcing methods, we fused the judgments of multiple forensic facial examiners by averaging their rating-based identity judgments. Accuracy was substantially better for fused judgments than for individuals working alone. Fusion also served to stabilize performance, boosting the scores of lower-performing individuals and decreasing variability. Single forensic facial examiners fused with the best algorithm were more accurate than the combination of two examiners. Therefore, collaboration among humans and between humans and machines offers tangible benefits to face identification accuracy in important applications. These results offer an evidence-based roadmap for achieving the most accurate face identification possible.

[Development of a Questionnaire Measuring Sexual Mental Health of Tibetan University Students].

OBJECTIVE: To develop a questionnaire measuring sexual mental health of Tibetan university students. METHODS: A draft questionnaire was developed with reference to the Sexual Civilization Survey for University Students of New Century and other published literature, and in consultation with experts. The questionnaire was tested in 230 students. Exploratory factor analyses with principal component and varimax orthogonal rotation were performed. Common factors with a > 1 eigenvalues and ≥ 3 loaded items (factor loading ≥ 0.4) were retained. Items with a < 0.4 factor loading, < 0.2 commonality, or falling into a common factor with < 3 items were excluded. The revised questionnaire was administered in another sample of 481 university students. Cronbach's α and split-half reliabilities were estimated. Confirmatory factor analyses were performed to test the construct validity of the questionnaire. RESULTS: Four rounds of exploratory factor analyses reduced the draft questionnaire items from 39 to 34 with a 7-factor structure. The questionnaire had a Cronbach's α of 0.920, 0.898, 0.812, 0.844, 0.787, 0.684, 0.703, and 0.608, and a Spearman-Brown coefficient of 0.763, 0.867, 0.742, 0838, 0.746, 0.822, 0.677, and 0.564 for the overall questionnaire and its 7 domains, respectively, suggesting good internal reliability. The structural equation of confirmatory factor analysis fitted well with the raw data: fit index χ²/df 3.736; root mean square residual (RMR) 0.081; root mean square error of approximation (RMSEA = 0.076; goodness of fit index (GFI) 0.805; adjusted goodness of fit index (AGFI) 0.770; normed fit index (NFI) = 0.774; relative fit index (RFI) 0.749; incremental fit index (IFI) 0.824; non-normed fit index (NNFI) = 0.803; comparative fit index (CFI) = 0.823; parsimony goodness of fit index (PGFI) = 0.684; parsimony normed fit index (PNFI) = 0.698; parsimony comparative fit index (PCFI) = 0.742, suggesting good construct validity of the questionnaire. CONCLUSION: The Sexual Mental Health Questionnaire for Tibetan University Student has demonstrated good reliability and validity.

A novel method for the discrimination of Hawthorn and its processed products using an intelligent sensory system and artificial neural networks.

Hawthorn (CFS) has commonly been applied as an important traditional Chinese medicine and food for thousands of years. The raw material of CFS is commonly processed by stir-frying to obtain yellow (CFY), dark brown (CFD), and carbon dark (CFC) colored products, which are used for different clinical uses. In this study, an intelligent sensory system (ISS) was used to obtain the color, gas, and flavor samples data, which were further employed to develop a novel and accurate method for the identification of CFS and its processed products using principal component analysis. Moreover, this research developed a model of an artificial neural network, which could be used to predict the total organic acid, total flavonoids, citric acid, hyperin, and 5-hydroxymethyl furfural via determination of the color, odor, and taste of a sample. In conclusion, the ISS and the artificial neural network are useful tools for rapid, accurate, and effective discrimination of CFS and its processed products.