Traditional Chinese Medicine Formulae QY305 Reducing Cutaneous Adverse Reaction and Diarrhea by its Nanostructure.

Traditional Chinese medicine (TCM) is widely used in clinical practice, including skin and gastrointestinal diseases. Here, a potential TCM QY305 (T-QY305) is reported that can modulate the recruitment of neutrophil in skin and colon tissue thus reducing cutaneous adverse reaction and diarrhea induced by epidermal growth factor receptor inhibitors (EGFRIs). On another hand, the T-QY305 formula, through regulating neutrophil recruitment features would highlight the presence of N-QY305, a subunit nanostructure contained in T-QY305, and confirm its role as potentially being the biomaterial conferring to T-QY305 its pharmacodynamic features. Here, the clinical records of two patients are analyzed expressing cutaneous adverse reaction and demonstrate positive effect of T-QY305 on the simultaneous inhibition of both cutaneous adverse reaction and diarrhea in animal models. The satisfying results obtained from T-QY305, lead to further process to the isolation of N-QY305 from T-QY305, in order to demonstrate that the potency of T-QY305 originates from the nanostructure N-QY305. Compared to T-QY305, N-QY305 exhibits higher potency upon reducing adverse reactions. The data represent a promising candidate for reducing cutaneous adverse reaction and diarrhea, meanwhile proposing a new strategy to highlight the presence of nanostructures being the "King" of Chinese medicine formula as the pharmacodynamic basis.

Nanostructures in Chinese herbal medicines (CHMs) for potential therapy.

With its long clinical history, traditional Chinese medicine (TCM) has gained acceptance for its specific efficacy and safety in the treatment of multiple diseases. Nano-sized materials study of Chinese herbal medicines (CHMs) leads to an increased understanding of assessing TCM therapies, which may be a promising way to illustrate the material basis of CHMs through their processing and extraction. In this review, we provide an overview of the nanostructures of natural and engineered CHMs, including extracted CHMs, polymer nanoparticles, liposomes, micelles, and nanofibers. Subsequently, the applications of these CHM-derived nanostructures to particular diseases are summarized and discussed. Additionally, we discuss the advantages of these nanostructures for studying the therapeutic efficacy of CHMs. Finally, the key challenges and opportunities for the development of these nanostructures are outlined.

Rheumatic valvular heart disease treated with traditional Chinese medicine: A case report.

BACKGROUND: Rheumatic heart disease (RHD) is an autoimmune disease that leads to irreversible valve damage and heart failure. Surgery is an effective treatment; however, it is invasive and carries risks, restricting its broad application. Therefore, it is essential to find alternative nonsurgical treatments for RHD. CASE SUMMARY: A 57-year-old woman was assessed with cardiac color Doppler ultrasound, left heart function tests, and tissue Doppler imaging evaluation at Zhongshan Hospital of Fudan University. The results showed mild mitral valve stenosis with mild to moderate mitral and aortic regurgitation, confirming a diagnosis of rheumatic valve disease. After her symptoms became severe, with frequent ventricular tachycardia and supraventricular tachycardia > 200 beats per minute, her physicians recommended surgery. During a 10-day preoperative waiting period, the patient asked to be treated with traditional Chinese medicine. After 1 week of this treatment, her symptoms improved significantly, including resolution of the ventricular tachycardia, and the surgery was postponed pending further follow-up. At 3 -month follow-up, color Doppler ultrasound showed mild mitral valve stenosis with mild mitral and aortic regurgitation. Therefore, it was determined that no surgical treatment was required. CONCLUSION: Traditional Chinese medicine treatment effectively relieves symptoms of RHD, particularly mitral valve stenosis and mitral and aortic regurgitation.

Pathologic responses to neoadjuvant chemoimmunotherapy in primary limited-stage small-cell lung cancer.

BACKGROUND: Immunotherapy has been proved to have a large effect on extensive-stage small cell lung cancer, but the role of immunotherapy in limited-stage small-cell lung cancer (LS-SCLC) is still unknown. METHODS: A retrospective study of six patients with LS-SCLC who were treated with neoadjuvant chemoimmunotherapy (durvalumab plus etoposide combined with cisplatin) was performed. Patients were evaluated by the safety, feasibility and pathologic responses of neoadjuvant chemoimmunotherapy. RESULTS: Neoadjuvant durvalumab combined chemotherapy was associated with few immediate adverse events and did not delay planned surgery. All patients achieved partial pathologic response (pPR) instead of major pathologic response, or pathologic complete response. No association was observed between programmed death-ligand 1 expression in tumor specimens and the pathologic response. However, tumors with high expression of immune cells such as CD4+ T cells, CD8+ T cells and FoxP3+ Tregs tended to have better pathologic responses than tumors with low expression of immune cells. CONCLUSIONS: Neoadjuvant durvalumab combined chemotherapy could induce pPR with few side effects in resectable LS-SCLC. The immune cells in the tumor microenvironment might play an important role in neoadjuvant chemoimmunotherapy in resectable LS-SCLC.

Rapid and visual detection of Staphylococcus aureus in milk using a recombinase polymerase amplification-lateral flow assay combined with immunomagnetic separation.

AIMS: The aim of this study was to develop a novel approach using lateral flow recombinase polymerase amplification (RPA-LF) combined with immunomagnetic separation (IMS) for the rapid detection of Staphylococcus aureus in milk. METHODS AND RESULTS: Under optimum conditions, the average capture efficiency values for S. aureus strains (104 colony-forming units [CFU] per ml) was above 95.0% in PBST and ~80% in milk within 45 min with 0.7 mg immunomagnetic beads. The RPA-LF assay, which comprised DNA amplification via RPA at 39°C for 10 min and visualization of the amplicons through LF strips for 5 min, detected S. aureus within 15 min. The method only detected S. aureus and did not show cross-reaction with other bacteria, exhibiting a high level of specificity. Sensitivity experiments confirmed a detection limit of RPA-LF assay as low as 600 fg per reaction for the S. aureus genome (corresponding to approximately 36 CFU of S. aureus), which was about 16.7-fold more sensitive than that of the conventional polymerase chain reaction method. When RPA-LF was used in combination with IMS to detect S. aureus inoculated into artificially contaminated milk, it exhibited a detection limit of approximately 40 CFU per reaction. CONCLUSIONS: The newly developed IMS-RPA-LF method enabled detection of S. aureus at levels as low as 40 CFU per reaction in milk samples without culture enrichment for an overall testing time of only 70 min. SIGNIFICANCE AND IMPACT OF THE STUDY: The newly developed IMS-lateral flow RPA-LF assay effectively combines sample preparation, amplification and detection into a single platform. Because of its high sensitivity, specificity and speed, the IMS-RPA-LF assay will have important implications for the rapid detection of S. aureus in contaminated food.

Synthesis, biological evaluation and cellular localization study of fluorescent derivatives of Jiyuan Oridonin A.

Jiyuan Oridonin A (JOA) is a naturally occurring ent-kaurane diterpenoid that exhibits significant potential in the field of anti-tumor drug development. However, its detailed anti-cancer mechanism of action has not been fully understood. In order to investigate its anticancer mode of action, two series of novel fluorescent derivatives of JOA conjugated with naphthalimide dyes were synthesized, and their antitumor activity against five selected cancer cell lines (MGC-803, SW1990, PC-3, TE-1 and HGC-27) was evaluated. Compared with JOA, the anti-tumor activity of the vast majority of compounds were improved. Among them, B12 exhibited promising anti-proliferative activity against HGC-27 cells with IC50 value of 0.39 ± 0.09 µM. Fluorescence imaging studies demonstrated that probe B12 could enter HGC-27 cells in a dose-dependent and time-dependent manner and was mainly accumulated in mitochondria. Preliminary biological mechanism studies indicated that B12 was able to inhibit cell cloning and migration. Further studies suggested that B12-induced apoptosis was related to the mitochondrial pathway. Overall, our results provide new approaches to explore the molecular mechanism of the natural product JOA, which would contribute to its further development as an antitumor agent.

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Treeline ecotone is an alpine ecological transition zone characterized by strong biotic interactions, which are closely related to treeline ecological processes. Herein, we reviewed the research progress regarding the impacts of plant-plant, plant-animal, and plant-microbe interactions on the ecological processes of treeline ecotone under climate change. Both facilitation and competition among individual plants are important factors mediating dynamics of treeline processes under climate change. However, there is a dearth of dendroecological evidence. Impacts of higher-order interactions on the ecological processes of treeline ecotone remain to be tested. Herbivory and microbe-plant interactions could enhance or reduce the couplings of treeline and climate through affecting soil conditions or altering dynamics of ecological processes such as tree growth and recruitment. How the linkages between aboveground and belowground processes affect treeline responses to climate change remain unclear. In addition, biotic interactions across trophic levels might regulate the responses of ecological processes of treeline ecotone to climate change. Tibetan Plateau provides an excellent opportunity to explore the effects of biotic interactions on the changes of ecological process of treeline ecotone.

Designed, synthesized and biological evaluation of proteolysis targeting chimeras (PROTACs) as AR degraders for prostate cancer treatment.

As a continuation of our research on developing potent and potentially safe androgen receptor (AR) degrader, a series of novel proteolysis targeting chimeras (PROTACs) containing the phthalimide degrons with different linker were designed, synthesized and evaluated for their AR degradation activity against LNCaP (AR+) cell line. Most of the synthesized compounds displayed moderate to satisfactory AR binding affinity and might lead to antagonist activity against AR. Among them, compound A16 exhibited the best AR binding affinity (85%) and degradation activity against AR. Due to the strong fluorescence properties of pomalidomide derivatives, B10 was found to be effectively internalized and visualized in LNCaP (AR + ) cells than PC-3 (AR-) cells. Moreover, the molecular docking of A16 with AR and the active site of DDB1-CRBN E3 ubiquitin ligase complex provides guidance to design new PROTAC degrons targeting AR for prostate cancer therapy. These results represent a step toward the development of novel and improved AR PROTACs.

The design, synthesis and anti-tumor mechanism study of new androgen receptor degrader.

Targeted protein degradation using small molecules is a novel strategy for drug development. In order to solve the problem of drug resistance in the treatment of prostate cancer, proteolysis-targeting chimeras (PROTAC) was introduced into the design of anti-prostate cancer derivatives. In this work, we synthesized two series of selective androgen receptor degraders (SARDs) containing the hydrophobic degrons with different linker, and then investigated the structure-activity relationships of these hybrid compounds. Most of the synthesized compounds exhibited moderate to good activity against all the cancer cell lines selected. Among them, compound A9 displayed potent inhibitory activity against LNCaP prostate cancer cell line with IC50 values of 1.75 µM, as well as excellent AR degradation activity. Primary mechanism studies elucidated compound A9 arrested cell cycle at G0/G1 phase and induced a mild apoptotic response in LNCaP cells. Further study indicated that the degradation of AR was mediated through proteasome-mediated process. For all these reasons, compound A9 held promising potential as anti-proliferative agent for the development of highly efficient SARDs for drug-resistance prostate cancer therapies.

Computer-assisted diagnosis of early esophageal squamous cell carcinoma using narrow-band imaging magnifying endoscopy.

BACKGROUND: We developed a computer-assisted diagnosis model to evaluate the feasibility of automated classification of intrapapillary capillary loops (IPCLs) to improve the detection of esophageal squamous cell carcinoma (ESCC). METHODS: We recruited patients who underwent magnifying endoscopy with narrow-band imaging for evaluation of a suspicious esophageal condition. Case images were evaluated to establish a gold standard IPCL classification according to the endoscopic diagnosis and histological findings. A double-labeling fully convolutional network (FCN) was developed for image segmentation. Diagnostic performance of the model was compared with that of endoscopists grouped according to years of experience (senior > 15 years; mid level 10 - 15 years; junior 5 - 10 years). RESULTS: Of the 1383 lesions in the study, the mean accuracies of IPCL classification were 92.0 %, 82.0 %, and 73.3 %, for the senior, mid level, and junior groups, respectively. The mean diagnostic accuracy of the model was 89.2 % and 93.0 % at the lesion and pixel levels, respectively. The interobserver agreement between the model and the gold standard was substantial (kappa value, 0.719). The accuracy of the model for inflammatory lesions (92.5 %) was superior to that of the mid level (88.1 %) and junior (86.3 %) groups (P < 0.001). For malignant lesions, the accuracy of the model (B1, 87.6 %; B2, 93.9 %) was significantly higher than that of the mid level (B1, 79.1 %; B2, 90.0 %) and junior (B1, 69.2 %; B2, 79.3 %) groups (P < 0.001). CONCLUSIONS: Double-labeling FCN automated IPCL recognition was feasible and could facilitate early detection of ESCC.

CNN-SVM for Microvascular Morphological Type Recognition with Data Augmentation.

This paper focuses on the problem of feature extraction and the classification of microvascular morphological types to aid esophageal cancer detection. We present a patch-based system with a hybrid SVM model with data augmentation for intraepithelial papillary capillary loop recognition. A greedy patch-generating algorithm and a specialized CNN named NBI-Net are designed to extract hierarchical features from patches. We investigate a series of data augmentation techniques to progressively improve the prediction invariance of image scaling and rotation. For classifier boosting, SVM is used as an alternative to softmax to enhance generalization ability. The effectiveness of CNN feature representation ability is discussed for a set of widely used CNN models, including AlexNet, VGG-16, and GoogLeNet. Experiments are conducted on the NBI-ME dataset. The recognition rate is up to 92.74% on the patch level with data augmentation and classifier boosting. The results show that the combined CNN-SVM model beats models of traditional features with SVM as well as the original CNN with softmax. The synthesis results indicate that our system is able to assist clinical diagnosis to a certain extent.

Operating Room Within the Neonatal Intensive Care Unit--Experience of a Medical Center in Taiwan.

BACKGROUND: Most neonates who reside in the neonatal intensive care unit (NICU) and require surgery are transferred to the operating room (OR) or undergo bedside surgery. However, critically ill neonates who are transferred often encounter the risk of complications. An OR in our NICU was therefore launched in 2009. This study was to appraise the surgeries performed in the NICU OR and compare results with the traditional main OR outside the NICU. METHODS: This was a retrospective study in the NICU of a tertiary center. Retrospective chart review was conducted for all neonates who underwent surgical procedures in the NICU OR and the main OR. The information regarding baseline characteristics, surgical procedures and duration, ventilator use, hypothermia, hyperglycemia, instrument dislocations, surgically related infection or complications, and outcomes was obtained. RESULTS: There were a total of 65 patients in this study, 37 in the NCIU OR group and 28 in the main OR group. The presurgical mean airway pressure and the fraction of inspired oxygen (FiO2) were comparable between the two groups, but the postsurgical FiO2 was significantly lower in the NICU OR group (31.0%) than in the main OR group (40.9%; p = 0.027). Furthermore, the NICU OR group required a significantly shorter preoperation waiting time (34.4 minutes vs. 63.6 minutes, p = 0.001) and had a lower incidence of hypothermia than the main OR group (8.1% vs. 39.3%, p = 0.008). However, surgically related complications were similar between groups. CONCLUSION: The OR within the NICU may reduce the risk of complications during transportation and provide continuity of care to critically ill neonates. It also decreases the disturbance to other NICU patients during operation.

Inquiry diagnosis of coronary heart disease in Chinese medicine based on symptom-syndrome interactions.

BACKGROUND: There is a long history of coronary heart disease (CHD) diagnosis and treatment in Chinese medicine (CM), but a formalized description of CM knowledge is still unavailable. This study aims to analyze a set of CM clinical data, which is important and urgent. METHODS: Relative associated density (RAD) was used to analyze the one-way links between the symptoms or syndromes or both. RAD results were further used in symptom selection. RESULTS: Analysis of a dataset of clinical CHD diagnosis revealed some significant relationships, not only between syndromes but also between symptoms and syndromes. Using RAD to select symptoms based on different classifiers improved the accuracy of syndrome prediction. Compared with other traditional symptom selection methods, RAD provided a higher interpretability of the CM data. CONCLUSION: The RAD method is effective for CM clinical data analysis, particular for analysis of relationships between symptoms in diagnosis and generation of compact and comprehensible symptom feature subsets.

Modelling of inquiry diagnosis for coronary heart disease in Traditional Chinese Medicine by using multi-label learning.

BACKGROUND: Coronary heart disease (CHD) is a common cardiovascular disease that is extremely harmful to humans. In Traditional Chinese Medicine (TCM), the diagnosis and treatment of CHD have a long history and ample experience. However, the non-standard inquiry information influences the diagnosis and treatment in TCM to a certain extent. In this paper, we study the standardization of inquiry information in the diagnosis of CHD and design a diagnostic model to provide methodological reference for the construction of quantization diagnosis for syndromes of CHD. In the diagnosis of CHD in TCM, there could be several patterns of syndromes for one patient, while the conventional single label data mining techniques could only build one model at a time. Here a novel multi-label learning (MLL) technique is explored to solve this problem. METHODS: Standardization scale on inquiry diagnosis for CHD in TCM is designed, and the inquiry diagnostic model is constructed based on collected data by the MLL techniques. In this study, one popular MLL algorithm, ML-kNN, is compared with other two MLL algorithms RankSVM and BPMLL as well as one commonly used single learning algorithm, k-nearest neighbour (kNN) algorithm. Furthermore the influence of symptom selection to the diagnostic model is investigated. After the symptoms are removed by their frequency from low to high; the diagnostic models are constructed on the remained symptom subsets. RESULTS: A total of 555 cases are collected for the modelling of inquiry diagnosis of CHD. The patients are diagnosed clinically by fusing inspection, pulse feeling, palpation and the standardized inquiry information. Models of six syndromes are constructed by ML-kNN, RankSVM, BPMLL and kNN, whose mean results of accuracy of diagnosis reach 77%, 71%, 75% and 74% respectively. After removing symptoms of low frequencies, the mean accuracy results of modelling by ML-kNN, RankSVM, BPMLL and kNN reach 78%, 73%, 75% and 76% when 52 symptoms are remained. CONCLUSIONS: The novel MLL techniques facilitate building standardized inquiry models in CHD diagnosis and show a practical approach to solve the problem of labelling multi-syndromes simultaneously.