Objective To minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation(PIRFT)arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.Methods We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance(MR)images of the L5/S1 segments into 7 key structures:L5,S1,Ilium,Disc,N5,Dura mater,and Skin,based on which a needle insertion path planning environment was modeled.Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion,and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability.By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process,and employing various technologies such as ray tracing,CPU multi-threading,and GPU parallel computing,a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.Results A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm,and all the paths met the clinical requirements,with 95.24%of them rated excellent or good.Compared with the physician's planning results,the plans generated by the algorithm showed inferior DIlium,DS1,and Depth(P<0.05)but much better DDura,DL5,DN5,and AKambin(P<0.05).In the 21 cases,the planning time of the algorithm averaged 7.97±3.73 s,much shorter than that by the physicians(typically beyond 10 min).Conclusion The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.

Objective To minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation(PIRFT)arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.Methods We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance(MR)images of the L5/S1 segments into 7 key structures:L5,S1,Ilium,Disc,N5,Dura mater,and Skin,based on which a needle insertion path planning environment was modeled.Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion,and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability.By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process,and employing various technologies such as ray tracing,CPU multi-threading,and GPU parallel computing,a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.Results A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm,and all the paths met the clinical requirements,with 95.24%of them rated excellent or good.Compared with the physician's planning results,the plans generated by the algorithm showed inferior DIlium,DS1,and Depth(P<0.05)but much better DDura,DL5,DN5,and AKambin(P<0.05).In the 21 cases,the planning time of the algorithm averaged 7.97±3.73 s,much shorter than that by the physicians(typically beyond 10 min).Conclusion The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.

OBJECTIVE: To propose an deep learning-based algorithm for automatic prediction of dose distribution in radiotherapy planning for head and neck cancer. METHODS: We propose a novel beam dose decomposition learning (BDDL) method designed on a cascade network. The delivery matter of beam through the planning target volume (PTV) was fitted with the pre-defined beam angles, which served as an input to the convolution neural network (CNN). The output of the network was decomposed into multiple sub-fractions of dose distribution along the beam directions to carry out a complex task by performing multiple simpler sub-tasks, thus allowing the model more focused on extracting the local features. The subfractions of dose distribution map were merged into a distribution map using the proposed multi-voting mechanism. We also introduced dose distribution features of the regions-of-interest (ROIs) and boundary map as the loss function during the training phase to serve as constraining factors of the network when extracting features of the ROIs and areas of dose boundary. Public datasets of radiotherapy planning for head and neck cancer were used for obtaining the accuracy of dose distribution of the BDDL method and for implementing the ablation study of the proposed method. RESULTS: The BDDL method achieved a Dose score of 2.166 and a DVH score of 1.178 (P < 0.05), demonstrating its superior prediction accuracy to that of current state-ofthe-art (SOTA) methods. Compared with the C3D method, which was in the first place in OpenKBP-2020 Challenge, the BDDL method improved the Dose score and DVH score by 26.3% and 30%, respectively. The results of the ablation study also demonstrated the effectiveness of each key component of the BDDL method. CONCLUSION The BDDL method utilizes the prior knowledge of the delivery matter of beam and dose distribution in the ROIs to establish a dose prediction model. Compared with the existing methods, the proposed method is interpretable and reliable and can be potentially applied in clinical radiotherapy.
Humans ; Deep Learning ; Head and Neck Neoplasms/radiotherapy* ; Algorithms ; Neural Networks, Computer

Rosae Radix et Rhizoma is a herbal medicine in a variety of famous Chinese patent medicines, while the quality standard for this medicine remains to be developed due to the insufficient research on the quality of Rosae Radix et Rhizoma from different sources. Therefore, this study comprehensively analyzed the components in Rosae Radix et Rhizoma of different sources from the aspects of extract, component category content, identification based on thin-lay chromatography, active component content determination, and fingerprint, so as to improve the quality control. The results showed that the content of chemical components varied in the samples of different sources, while there was little difference in the chemical composition among the samples. The content of components in the roots of Rosa laevigata was higher than that in the other two species, and the content of components in the roots was higher than that in the stems. The fingerprints of triterpenoids and non-triterpenoids were established, and the content of five main triterpenoids including multiflorin, rosamultin, myrianthic acid, rosolic acid, and tormentic acid in Rosae Radix et Rhizoma was determined. The results were consistent with those of major component categories. In conclusion, the quality of Rosae Radix et Rhizoma is associated with the plant species, producing area, and medicinal parts. The method established in this study lays a foundation for improving the quality standard of Rosae Radix et Rhizoma and provides data support for the rational use of the stem.
Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Plant Roots/chemistry* ; Plants, Medicinal ; Quality Control

Objective:To investigate the antioxidant activity and chemical composition of 75% ethanol extract of Rosa cymosa roots and its different polar parts. Method:The 75% ethanol extract of R. cymosa roots was divided into dichloromethane， ethyl acetate， n-butanol and water parts by organic solvent extraction. In vitro antioxidant activity of each fraction was determined by 1，1-diphenyl-2-picrylhydrazyl （DPPH） and 2，2'-azino-bis（3-ethylbenzothiazoline-6-sulfonic acid） （ABTS） free radical scavenging assays， as well as ferric reducing antioxidant power （FRAP） test. The contents of total triterpenes， total phenols， total tannins and condensed tannins in each fraction were determined by spectrophotometry. SPSS 24.0 software was used to conduct Pearson correlation analysis between the antioxidant activity of each fraction and the content of the main components， and then the main active fraction and the main active components were determined. The chemical constituents of the active fraction was analyzed by ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry （UPLC-Q-TOF-MS/MS）， and the structures of the main chromatographic peaks were predicted. Result:Each fraction of R. cymosa roots had certain antioxidant activity， and there was a significant dose-effect relationship within a certain concentration range， but the antioxidant activity of different polar parts was different. In DPPH and ABTS free radical scavenging tests， the antioxidant activity of each fraction and vitamin C （VC， the positive drug） was ranked as ethyl acetate fraction>VC>n-butanol fraction>ethanol extract>water fraction>dichloromethane fraction. In FRAP test， the activity of ethyl acetate fraction was weaker than that of VC， and the other order was unchanged. The contents of total triterpenes， total phenols， total tannins and condensed tannins in ethyl acetate fraction were 3.81%， 50.33%， 3.32%， and 39.79%， in n-butanol fraction were 0.88%， 41.42%， 2.25% and 23.55%， in ethanol extract were 2.90%， 41.95%， 3.43% and 20.14%， in water fraction were 0， 26.80%， 16.90% and 7.57%， and in dichloromethane fraction were 21.23%， 12.90%， 1.59%， and 6.17%， respectively. Correlation analysis results showed that the contents of total phenols and condensed tannins were positively correlated with the antioxidant activity， the contents of total triterpenes were negatively correlated with the antioxidant activity， and the correlation between total tannins and antioxidant activity was not obvious. A total of 26 compounds were identified from the ethyl acetate fraction by UPLC-Q-TOF-MS/MS， including 11 condensed tannins， 4 hydrolysable tannins， 6 triterpenes， 3 flavonoids， 1 benzoic acid derivative and 1 chlorogenic acid analogue. Conclusion:Ethyl acetate fraction is the main antioxidant active site of R. cymosa roots， and phenols mainly composed of condensed tannins are the main active components. The results can provide experimental basis for the development of natural antioxidants.

Objective:To summarize clinical characteristics of and treatment experience with patients with critical illnesses in a dermatological ward.Methods:All patients with serious or life-threatening conditions, who were hospitalized at the dermatological ward of the Second Xiangya Hospital of Central South University from July 9, 2011 to December 31, 2020, were collected, and their clinical data were retrospectively analyzed. Demographic characteristics, disease types and proportions, main complications, causes of serious or life-threatening conditions, important treatment measures and outcomes were summarized, and causes of death were also analyzed and discussed.Results:A total of 1 057 patients with critical illnesses were collected, with a male-to-female ratio of 1∶1.11, and 64.81% of them aged 18 to 65 years. The types of diseases mainly included drug eruptions (332 cases) , connective tissue diseases (226 cases) , bullous skin diseases (104 cases) , psoriasis (57 cases) , erythroderma (45 cases) , infectious skin diseases (67 cases) , etc. Among them, psoriasis (39 cases) and erythroderma (32 cases) mostly occurred in males, and connective tissue diseases (168 cases) mostly occurred in females. Common complications mainly involved infections, important organ damage or dysfunction, hypoalbuminemia, and fluid, electrolyte and acid-base imbalances. A total of 94 patients were diagnosed with life-threatening conditions, which were found to be mainly caused by primary skin diseases, hematologic abnormalities, respiratory failure, nervous system abnormalities, renal failure, sepsis, fluid, electrolyte and acid-base imbalances, etc. During the management of critical illnesses, 43 patients were treated with high-dose glucocorticoid pulse therapy, 264 were treated with gamma-globulin pulse therapy, 355 were transfused with other blood products, and 34 received special therapies such as hemoperfusion/immunoadsorption therapy, plasma exchange, dialysis, artificial liver support therapy; 42 patients were transferred to the intensive care unit (ICU) , 12 were transferred to the department of surgery for operations, and 12 were transferred to the department of obstetrics and gynecology for delivery or induction of labor. After treatment, 989 patients (93.57%) achieved improvement and were discharged. A total of 14 patients (1.32%) died, of whom 7 died of secondary sepsis, 2 died of severe pulmonary infections, 2 died of asphyxia caused by respiratory mucosa shedding-induced airway obstruction, the other 3 died of gastrointestinal hemorrhage, cerebral hemorrhage and neuropsychiatric systemic lupus erythematosus, respectively.Conclusions:Critical cases in the dermatological ward mainly suffered from serious skin diseases such as severe drug eruptions, connective tissue diseases and bullous skin diseases, as well as complications such as severe underlying diseases, severe organ dysfunction, sepsis or severe fluid, electrolyte and acid-base imbalances. In terms of treatment, it is of critical significance to make a clear diagnosis and assess the severity of disease as early as possible, monitor and prevent possible complications, and to consult with specialists in relevant disciplines in time.

In this paper, the newly isolated tannins were sorted after a review of the literature concerning tannins in recent 10 years, and their research progress was summarized in terms of extraction, isolation, pharmacological activity and metabolism. Hydrolysable tannins and condensed tannins are the main structural types. Modern research shows that tannins have many pharmacological effects, such as bacteriostasis, antioxidation, antitumor, antivirus and blood glucose reduction, and have broad development prospects. They are usually extracted by water, ethanol and acetone and isolated and purified by macroporous resin and gel column chromatography. The packings commonly adopted for the column chromatography mainly included Sephadex LH-20, Diaion HP-20, MCI-gel CHP-20 and Toyopearl HW-40. Modern analytical techniques such as nuclear magnetic resonance spectroscopy(NMR), fast atom bombardment mass spectrometry(FAB-MS) and circular dichroism(CD) are generally used for the structural identification of tannins. Howe-ver, their isolation, purification and structural identification are still challenging. It is necessary to use a variety of high-throughput screening methods to explore their pharmacological activities and to explore the material basis responsible for their functions through experiments in vivo.
China ; Hydrolyzable Tannins ; Medicine, Chinese Traditional ; Proanthocyanidins ; Tannins

Epithelial and stromal tissues are components of the tumor microenvironment and play a major role in tumor initiation and progression. Distinguishing stroma from epithelial tissues is critically important for spatial characterization of the tumor microenvironment. Here, we propose BrcaSeg, an image analysis pipeline based on a convolutional neural network (CNN) model to classify epithelial and stromal regions in whole-slide hematoxylin and eosin (H&E) stained histopathological images. The CNN model is trained using well-annotated breast cancer tissue microarrays and validated with images from The Cancer Genome Atlas (TCGA) Program. BrcaSeg achieves a classification accuracy of 91.02％, which outperforms other state-of-the-art methods. Using this model, we generate pixel-level epithelial/stromal tissue maps for 1000 TCGA breast cancer slide images that are paired with gene expression data. We subsequently estimate the epithelial and stromal ratios and perform correlation analysis to model the relationship between gene expression and tissue ratios. Gene Ontology (GO) enrichment analyses of genes that are highly correlated with tissue ratios suggest that the same tissue is associated with similar biological processes in different breast cancer subtypes, whereas each subtype also has its own idiosyncratic biological processes governing the development of these tissues. Taken all together, our approach can lead to new insights in exploring relationships between image-based phenotypes and their underlying genomic events and biological processes for all types of solid tumors. BrcaSeg can be accessed at https://github.com/Serian1992/ImgBio.

With continuous introduction of relevant national policies on famous classical formulas, the research of famous classical formulas is popular all over the country. Different from other new drugs, in the research and development process of famous classical formulas, substance benchmark is earlier than the product, suggesting that the research and development of substance benchmark is of great significance. Based on previous work of the authors, content of substance benchmark of famous classical formulas was analyzed, which was included in the document The Management Regulation of Simplified Registration and Approval over Chinese Herbal Medicine Compound Preparations of Ancient Famous Classical Formulas released by the National Medical Products Administration in May 2018. In this paper, the significance of substance benchmark development was described, a five-stage of research strategy was proposed, covering the prescription textual research and historical evolution, the collection and quality evaluation of medicinal materials, the processing method and quality evaluation of decoction pieces, the preparation and quality research of substance benchmark, the drafting and formulating of quality standard over substance benchmark. At the same time, some suggestions were put forward to the feasibility of compound preparations development over famous classical formulas, the implementation difficulty of resource evaluation over Chinese medicinal materials, and the irrationality on the quality correlation of Chinese medicinal materials. All of these are expected to provide reference and enlightenment for the development and policy officially landed over ancient famous classical formulas.

OBJECTIVE: To propose a coupled convolutional and graph convolutional network (CCGCN) model for diagnosis of Alzheimer's disease (AD) and its prodromal stage. METHODS: The disease-related brain regions generated by group-wise comparison were used as the input. The convolutional neural networks (CNNs) were used to extract disease-related features from different locations on brain magnetic resonance (MR) images. The generated features via the graph convolutional network (GCN) were processed, and graph pooling was performed to analyze the inherent relationship between the brain topology and the diagnosis task adaptively. Through ADNI dataset, we acquired the accuracy, sensitivity and specificity of the diagnosis tasks for AD and its prodromal stages, followed by an ablation study on the model structure. RESULTS: The CCGCN model outperformed the current state-of-the-art methods and showed a classification accuracy of 92.5% for AD with a sensitivity of 88.1% and a specificity of 96.0%. CONCLUSIONS Based on the structural and topological features of the brain MR images, the proposed CCGCN model shows excellent performance in AD diagnosis and is expected to provide important assistance to physicians in disease diagnosis.
Alzheimer Disease ; diagnostic imaging ; Brain ; Humans ; Magnetic Resonance Imaging ; Neural Networks, Computer