Emodin is a natural occurring anthraquinone derivative isolated from roots and barks of numerous plants, molds, and lichens. It is found to be an active ingredient in different Chinese herbs ...including
Rheum palmatum
and
Polygonam multiflorum
, and it is a pleiotropic molecule with diuretic, vasorelaxant, anti-bacterial, anti-viral, anti-ulcerogenic, anti-inflammatory, and anti-cancer effects. Moreover, emodin has also been shown to have a wide activity of anti-cardiovascular diseases. It is mainly involved in multiple molecular targets such as inflammatory, anti-apoptosis, anti-hypertrophy, anti-fibrosis, anti-oxidative damage, abnormal, and excessive proliferation of smooth muscle cells in cardiovascular diseases. As a new type of cardiovascular disease treatment drug, emodin has broad application prospects. However, a large amount of evidences detailing the effect of emodin on many signaling pathways and cellular functions in cardiovascular disease, the overall understanding of its mechanisms of action remains elusive. In addition, by describing the evidence of the effects of emodin in detail, the toxicity and poor oral bioavailability of mice have been continuously discovered. This review aims to describe a timely overview of emodin related to the treatment of cardiovascular disease. The emphasis is to summarize the pharmacological effects of emodin as an anti-cardiovascular drug, as well as the targets and its potential mechanisms. Furthermore, the treatment of emodin compared with conventional cardiovascular drugs or target inhibitors, the toxicity, pharmacokinetics and derivatives of emodin were discussed.
Tongue coating has been used as an effective signature of health in traditional Chinese medicine (TCM). The level of greasy coating closely relates to the strength of dampness or pathogenic qi in TCM ...theory. Previous empirical studies and our systematic review have shown the relation between greasy coating and various diseases, including gastroenteropathy, coronary heart disease, and coronavirus disease 2019 (COVID-19). However, the objective and intelligent greasy coating and related diseases recognition methods are still lacking. The construction of the artificial intelligent tongue recognition models may provide important syndrome diagnosis and efficacy evaluation methods, and contribute to the understanding of ethnopharmacological mechanisms based on TCM theory.
The present study aimed to develop an artificial intelligent model for greasy tongue coating recognition and explore its application in COVID-19.
Herein, we developed greasy tongue coating recognition networks (GreasyCoatNet) using convolutional neural network technique and a relatively large (N = 1486) set of tongue images from standard devices. Tests were performed using both cross-validation procedures and a new dataset (N = 50) captured by common cameras. Besides, the accuracy and time efficiency comparisons between the GreasyCoatNet and doctors were also conducted. Finally, the model was transferred to recognize the greasy coating level of COVID-19.
The overall accuracy in 3-level greasy coating classification with cross-validation was 88.8% and accuracy on new dataset was 82.0%, indicating that GreasyCoatNet can obtain robust greasy coating estimates from diverse datasets. In addition, we conducted user study to confirm that our GreasyCoatNet outperforms TCM practitioners, yet only consuming roughly 1% of doctors’ examination time. Critically, we demonstrated that GreasyCoatNet, along with transfer learning, can construct more proper classifier of COVID-19, compared to directly training classifier on patient versus control datasets. We, therefore, derived a disease-specific deep learning network by finetuning the generic GreasyCoatNet.
Our framework may provide an important research paradigm for differentiating tongue characteristics, diagnosing TCM syndrome, tracking disease progression, and evaluating intervention efficacy, exhibiting its unique potential in clinical applications.
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•Meta-analysis is used to review the relation between tongue and COVID-19.•Developing and testing datasets for greasy coating recognition are constructed.•The GreasyCoatNet obtains robust greasy coating classifications from diverse datasets.•Expectation of greasy coating is proposed to evaluate the continuous greasy level.•A COVID-specific deep network is derived by finetuning the GreasyCoatNet.
The fundamental theory of traditional Chinese medicine (TCM) implies that when different diseases have the same pathogen, the syndromes of these individual diseases will be the same. "Treating ...different diseases with the same method" is a TCM principle suggesting that when different diseases have similar pathological changes during different stages of their development, the same method of treatment can be applied. Our study aims to analyze the concept "treating different diseases with the same method" from a molecular perspective, in order to clarify its biological basis and to objectively standardize future TCM syndrome research.
The TCM syndromes Qi deficiency and blood stasis have similar pathogenesis in relation to coronary heart disease (CHD) and stroke. We aim to use big data technology and complex network theory to mine the genes specifically relevant to these TCM syndromes. This study aims to explore the correlation between the biological indicators of CHD and stroke from a scientific perspective.
Mining the relevant neuroendocrine-immune (NEI) genes by means of gene entity recognition, complex network construction, network integration, and decomposition to categorize relevant syndrome terms and establish a digital dictionary of gene specifically related to individual diseases. We analyzed the biological basis of "treating different diseases with the same method" from a molecular level using the TCMIP v2.0 platform in order to categorize the TCM syndromes most relevant to CHD and stroke.
We found 46 genes were involved in the TCM syndromes of Qi deficiency and blood stasis of CHD and stroke. The same genes and their molecular mechanism also appeared to be in close relation to inflammatory response, apoptosis, and proliferation.
By using information extraction and complex network technology, we discovered the biological indicators of the TCM syndromes Qi deficiency and blood stasis of CHD and stroke. In the era of big data, our results can provide a new method for the researchers of TCM syndrome differentiation, as well as an effective and specific methodology for standardization of TCM.
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•Large datasets for tooth-marked tongue recognition are constructed.•The deep CNN in artificial intelligence gain classification accuracy over 90%.•The models can be successfully ...generalized to images with different illuminations.•Isolation of the tongue region can enhance tongue diagnosis performance.
Tongue diagnosis plays a pivotal role in traditional Chinese medicine (TCM) for thousands of years. As one of the most important tongue characteristics, tooth-marked tongue is related to spleen deficiency and can greatly contribute to the symptoms differentiation and treatment selection. Yet, the tooth-marked tongue recognition for TCM practitioners is subjective and challenging. Most of the previous studies have concentrated on subjectively selected features of the tooth-marked region and gained accuracy under 80%. In the present study, we proposed an artificial intelligence framework using deep convolutional neural network (CNN) for the recognition of tooth-marked tongue. First, we constructed relatively large datasets with 1548 tongue images captured by different equipments. Then, we used ResNet34 CNN architecture to extract features and perform classifications. The overall accuracy of the models was over 90%. Interestingly, the models can be successfully generalized to images captured by other devices with different illuminations. The good effectiveness and generalization of our framework may provide objective and convenient computer-aided tongue diagnostic method on tracking disease progression and evaluating pharmacological effect from a informatics perspective.
The outbreak of new infectious pneumonia caused by SARS-CoV-2 has posed a significant threat to public health, but specific medicines and vaccines are still being developed. Traditional Chinese ...medicine (TCM) has thousands of years of experience in facing the epidemic disease, such as influenza and viral pneumonia. In this study, we revealed the efficacy and pharmacological mechanism of Ma Xing Shi Gan (MXSG) Decoction against COVID-19. First, we used liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) to analyze the chemical components in MXSG and identified a total of 97 components from MXSG. Then, the intervention pathway of MXSG based on these components was analyzed with network pharmacology, and it was found that the pathways related to the virus infection process were enriched in some of MXSG component targets. Simultaneously, through literature research, it was preliminarily determined that MXSG, which is an essential prescription for treating COVID-19, shared the feature of antiviral, improving clinical symptoms, regulating immune inflammation, and inhibiting lung injury. The regulatory mechanisms associated with its treatment of COVID-19 were proposed. That MXSG might directly inhibit the adsorption and replication of SARS-CoV-2 at the viral entry step. Besides, MXSG might play a critical role in inflammation and immune regulatory, that is, to prevent cytokine storm and relieve lung injury through toll-like receptors signaling pathway. Next, in this study, the regulatory effect of MXSG on inflammatory lung injury was validated through transcriptome results. In summary, MXSG is a relatively active and safe treatment for influenza and viral pneumonia, and its therapeutic effect may be attributed to its antiviral and anti-inflammatory effects.
Objectives:
The objective of this study was to provide a new classification method by analyzing the relationship between urine color (Ucol) distribution and urine dry chemical parameters based on ...image digital processing. Furthermore, this study aimed to assess the reliability of Ucol to evaluate the states of body hydration and health.
Methods:
A cross-sectional study among 525 college students, aged 17–23 years old, of which 59 were men and 466 were women, was conducted. Urine samples were obtained during physical examinations and 524 of them were considered valid, including 87 normal samples and 437 abnormal dry chemistry parameters samples. The urinalysis included both micro- and macro-levels, in which the CIE L
*
a
*
b
*
values and routine urine chemical examination were performed through digital imaging colorimetry and a urine chemical analyzer, respectively.
Results:
The results showed that L
*
(53.49 vs. 56.69) in the abnormal urine dry chemistry group was lower than the normal group, while b
*
(37.39 vs. 33.80) was greater. Urine color can be initially classified based on shade by grouping b
*
. Abnormal urine dry chemical parameter samples were distributed more in the dark-colored group. Urine dry chemical parameters were closely related to Ucol. Urine specific gravity (USG), protein, urobilinogen, bilirubin, occult blood, ketone body, pH, and the number of abnormal dry chemical parameters were all correlated with Ucol CIE L
*
a
*
b
*
; according to a stepwise regression analysis, it was determined that more than 50% of the variation in the three-color space values came from the urine dry chemical parameters, and the b
*
value was most affected by USG (standardized coefficient β = 0.734,
p
< 0.05). Based on a receiver operating characteristic curve (ROC) analysis, Ucol ≥ 4 provided moderate sensitivity and good specificity (AUC = 0.892) for the detection of USG ≥ 1.020.
Conclusions:
Our findings on the Ucol analysis showed that grouping Ucol based on b
*
value is an objective, simple, and practical method. At the same time, the results suggested that digital imaging colorimetry for Ucol quantification is a potential method for evaluating body hydration and, potentially, health.
Left bundle branch area pacing (LBBAP), a new pacing approach, lacks adequate evaluation.
To assess the feasibility, safety, and acute effect of permanent LBBAP in patients with atrioventricular ...block (AVB).
A total of 33 AVB patients with indications for ventricular pacing were recruited. Electrocardiograms, pacing parameters, echocardiographic measurements, and complications associated with LBBAP were evaluated perioperatively and at 3-month follow-up. Successful LBBAP was defined as a paced QRS morphology of right bundle branch block pattern in lead V
and QRS duration (QRSd) less than 130 ms.
LBBAP was successfully performed in 90.9% (30/33) of patients (mean age: 55.1 ± 18.5 years; 66.7% male). The mean capture threshold was similar during the procedure (0.76 ± 0.26 V at 0.4 ms) and at the 3-month follow-up (0.64 ± 0.20 V at 0.4 ms). The paced QRSd was 112.8 ± 10.9 ms during the procedure and 116.8 ± 10.4 ms at the 3-month follow-up. Baseline left or right bundle branch block was corrected (intrinsic QRSd 153.3 ± 27.8 ms vs paced QRSd 122.2 ± 9.9 ms) with a success rate of 68.7% (11/16). One ventricular septal lead perforation occurred soon after the procedure with characteristics of pacing failure, and lead revision was successful. Cardiac function and left ventricular synchronization by 2-dimensional echocardiographic strain imaging at the 3-month follow-up slightly improved compared with that at baseline.
Permanent LBBAP yielded a stable threshold, a narrow QRSd, and preserved left ventricular synchrony with few complications. Our preliminary results indicate that LBBAP holds promise as an attractive physiological pacing strategy for AVB.
Purpose
To introduce a dual‐domain reconstruction network with V‐Net and K‐Net for accurate MR image reconstruction from undersampled k‐space data.
Methods
Most state‐of‐the‐art reconstruction ...methods apply U‐Net or cascaded U‐Nets in the image domain and/or k‐space domain. Nevertheless, these methods have the following problems: (1) directly applying U‐Net in the k‐space domain is not optimal for extracting features; (2) classical image‐domain–oriented U‐Net is heavyweighted and hence inefficient when cascaded many times to yield good reconstruction accuracy; (3) classical image‐domain–oriented U‐Net does not make full use of information of the encoder network for extracting features in the decoder network; and (4) existing methods are ineffective in simultaneously extracting and fusing features in the image domain and its dual k‐space domain. To tackle these problems, we present 3 different methods: (1) V‐Net, an image‐domain encoder–decoder subnetwork that is more lightweight for cascading and effective in fully utilizing features in the encoder for decoding; (2) K‐Net, a k‐space domain subnetwork that is more suitable for extracting hierarchical features in the k‐space domain, and (3) KV‐Net, a dual‐domain reconstruction network in which V‐Nets and K‐Nets are effectively combined and cascaded.
Results
Extensive experimental results on the fastMRI dataset demonstrate that the proposed KV‐Net can reconstruct high‐quality images and outperform state‐of‐the‐art approaches with fewer parameters.
Conclusions
To reconstruct images effectively and efficiently from incomplete k‐space data, we have presented a dual‐domain KV‐Net to combine K‐Nets and V‐Nets. The KV‐Net achieves better results with 9% and 5% parameters than comparable methods (XPD‐Net and i‐RIM).
Background: Epithelial ovarian cancer (EOC) is the most common gynecological cancer in women. Resistin, an inflammatory adipocytokine, is associated with obesity, insulin resistance, and various ...cancer types. Materials and Methods: We investigated resistin expression in tissues and its association with the clinicopathological characteristics and prognosis of patients with EOC. The SKOV3 and CAOV3 cell lines were treated with exogenous resistin and rapamycin (resistin inhibitor), and the expression of mTOR in SKOV3 and CAOV3 cells was measured. Cell proliferation was measured using the CCK-8 assay. Western blotting analysis was performed to examine the phosphorylation of P70S6K and mTOR. Wound healing and Transwell analyses were conducted to examine the effect of resistin on the migration of SKOV3 and CAOV3 cells. Results: High resistin expression was positively correlated with the pathological grade (P = 0.017) and lymph node metastasis (P = 0.045). However, resistin expression was not correlated with age, FIGO stage, or residual tumor after initial laparotomy (P > 0.05). Cox multivariate analysis showed that resistin expression was an independent factor for determining disease-free survival, whereas lymph node metastasis, resistin expression, and age (≥ 55 years) were independent factors affecting overall survival. Exogenous resistin induced ovarian cancer cell proliferation, whereas rapamycin had the opposite effect. Resistin promoted the proliferation of ovarian cancer cells via the mTOR signaling pathway and was associated with phosphorylating P70S6K. Furthermore, resistin promoted the migration of ovarian cancer cells. Conclusions: Resistin may promote the occurrence of ovarian cancer and is related to the prognosis of patients. This protein may also affect the proliferation of EOC cells through the mTOR signaling pathway. Therefore, resistin shows potential as a molecular therapeutic target in ovarian cancer.
This study focuses on diagrams that use mathematical models to describe the spatial experience, from 1920 to 2020 s. By reviewing and discussing the diagrams classified by the two main mathematical ...models, topology and encoding, this study tries to rediscover the empirical studies of spatial experience.
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