Gua Lou Er Chen decoction attenuates atherosclerosis by reducing proteoglycans accumulation and inflammation.

BACKGROUND: Proteoglycans (PGs) accumulation and inflammation are two interactional pathological processes of atherosclerosis (AS). Up to now, there is no ideal drug for decreasing these pathological changes. Gua Lou Er Chen decoction (GED) has been used to treat AS for several years. However, if GED could treat AS through reducing PGs accumulation and inflammation remains unknown. PURPOSE: This study was designed to illustrate whether GED could attenuate AS by reducing chondroitin sulphate proteoglycan (CSPG) expressions and alleviating inflammation. METHODS: In vivo study, apolipoprotein E-deficient mice were fed a high-fat diet to induce AS. In vitro study, oxidised low-density lipoprotein (ox-LDL) and tumour necrosis factor (TNF)-α were used to induce proteoglycans accumulation and inflammation changes of vascular smooth muscle cells (VSMCs) and RAW264.7 macrophages. Oil Red O was used to stain mouse aortic lipid plaque. Haematoxylin eosin staining was used to assess the pathological changes of aortic valve and thoracic aorta. Specialised kits were used to identify blood lipids and sGAGs. Immunofluorescence and immunohistochemistry was used to identify aortic valve CSPG and versican. Western blotting, enzyme-linked immunosorbent assay and quantitative reverse transcription-polymerase chain reaction were used to measure versican, interleukin (IL)-6, TNF-α, and chondroitin sulphate (CS) synthetase expressions. CCK-8 was used to measure the cells proliferation. RESULTS: In vivo experiments revealed that GED significantly improved hyperlipidemia, lowered lipid plaque deposition in the aorta, and increased plaque stability of AS mice. In addition, further studies revealed that GED lowered the sGAGs, CSPG, and versican levels and down-regulated CS synthetase and inflammatory factor expressions. In vitro experiments revealed that GED decreased TNF-α expression in the RAW264.7 macrophage supernatant stimulated by ox-LDL; decreased versican, CS-related synthetase, and IL-6 expressions; reduced VSMC proliferation stimulated by ox-LDL; down-regulated sGAG and versican expressions of VSMCs stimulated by TNF-α. CONCLUSION: Our results demonstrated that GED could attenuate AS by reducing hyperlipidemia, hyper-expression of CSPG, and inflammation. This study might provide a novel insight into the development of innovative drug for AS.

Automatic identification of myopia based on ocular appearance images using deep learning.

BACKGROUND: Myopia is the leading cause of visual impairment and affects millions of children worldwide. Timely and annual manual optometric screenings of the entire at-risk population improve outcomes, but screening is challenging due to the lack of availability and training of assessors and the economic burden imposed by the screenings. Recently, deep learning and computer vision have shown powerful potential for disease screening. However, these techniques have not been applied to large-scale myopia screening using ocular appearance images. METHODS: We trained a deep learning system (DLS) for myopia detection using 2,350 ocular appearance images (processed by 7,050 pictures) from children aged 6 to 18. Myopia is defined as a spherical equivalent refraction (SER) [the algebraic sum in diopters (D), sphere + 1/2 cylinder] ≤-0.5 diopters. Saliency maps and gradient class activation maps (grad-CAM) were used to highlight the regions recognized by VGG-Face. In a prospective clinical trial, 100 ocular appearance images were used to assess the performance of the DLS. RESULTS: The area under the curve (AUC), sensitivity, and specificity of the DLS were 0.9270 (95% CI, 0.8580-0.9610), 81.13% (95% CI, 76.86-5.39%), and 86.42% (95% CI, 82.30-90.54%), respectively. Based on the saliency maps and grad-CAMs, the DLS mainly focused on eyes, especially the temporal sclera, rather than the background or other parts of the face. In the prospective clinical trial, the DLS achieved better diagnostic performance than the ophthalmologists in terms of sensitivity [DLS: 84.00% (95% CI, 73.50-94.50%) versus ophthalmologists: 64.00% (95% CI, 48.00-72.00%)] and specificity [DLS: 74.00% (95% CI, 61.40-86.60%) versus ophthalmologists: 53.33% (95% CI, 30.00-66.00%)]. We also computed AUC subgroups stratified by sex and age. DLS achieved comparable AUCs for children of different sexes and ages. CONCLUSIONS: This study for the first time applied deep learning to myopia screening using ocular images and achieved high screening accuracy, enabling the remote monitoring of the refractive status in children with myopia. The application of our DLS will directly benefit public health and relieve the substantial burden imposed by myopia-associated visual impairment or blindness.

Deep learning-based automated diagnosis of fungal keratitis with in vivo confocal microscopy images.

BACKGROUND: The aim of this study was to develop an intelligent system based on a deep learning algorithm for automatically diagnosing fungal keratitis (FK) in in vivo confocal microscopy (IVCM) images. METHODS: A total of 2,088 IVCM images were included in the training dataset. The positive group consisted of 688 images with fungal hyphae, and the negative group included 1,400 images without fungal hyphae. A total of 535 images in the testing dataset were not included in the training dataset. Deep Residual Learning for Image Recognition (ResNet) was used to build the intelligent system for diagnosing FK automatically. The system was verified by external validation in the testing dataset using the area under the receiver operating characteristic curve (AUC), accuracy, specificity and sensitivity. RESULTS: In the testing dataset, 515 images were diagnosed correctly and 20 were misdiagnosed (including 6 with fungal hyphae and 14 without). The system achieved an AUC of 0.9875 with an accuracy of 0.9626 in detecting fungal hyphae. The sensitivity of the system was 0.9186, with a specificity of 0.9834. When 349 diabetic patients were included in the training dataset, 501 images were diagnosed correctly and thirty-four were misdiagnosed (including 4 with fungal hyphae and 30 without). The AUC of the system was 0.9769. The accuracy, specificity and sensitivity were 0.9364, 0.9889 and 0.8256, respectively. CONCLUSIONS: The intelligent system based on a deep learning algorithm exhibited satisfactory diagnostic performance and effectively classified FK in various IVCM images. The context of this deep learning automated diagnostic system can be extended to other types of keratitis.

[Metabolomics study of Danggui Buxue Tang on treatment of type 2 diabetes mice using UHPLC-Q-TOF-MS].

In this paper, ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS)-based metabolomics approach was used to explore the mechanism of Danggui Buxue Tang(DBT) in treating type 2 diabetes mellitus(T2 DM). T2 DM mice model was induced by high-sugar and high-fat fodder and streptozotocin(STZ). The routine indexes such as body weight, blood glucose, plasma insulin, IL-6 and related organ indexes were determined. The UHPLC-Q-TOF-MS technique was used to analyze the metabolism profile of serum samples between the control group and model group, and multiple statistical analysis methods including principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA) were used to screen and identify biomarkers. Metabolic profiling revealed 16 metabolites as the most potential biomarkers distinguishing mice in model group from those in control group. The metabolomics pathway analysis(MetPA) was used to investigate the underlying metabolic pathways. Seven major metabolic pathways such the valine, leucine and isoleucine biosynthesis, glycerophospholipid metabolism, primary bile acid biosynthesis, taurine and hypotaurine metabolism, phenylalanine metabolism, fatty acid metabolism and biosynthesis of unsaturated fatty acid. Eleven metabolites such as taurocholic acid and palmitic acid were down-regulated in T2 DM mice, and five metabolites such as L-leucine and leukotriene E4 were up-regulated. Moreover, the sixteen biomar-kers of each administration group had a trend of returning to mice in control group. The significantly-altered metabolite levels indicated that DBT can improve the progression of type 2 diabetes by increasing insulin sensitivity, regulating sugar and lipid metabolism disorders, and relieving inflammation.

Deep learning for detecting retinal detachment and discerning macular status using ultra-widefield fundus images.

Retinal detachment can lead to severe visual loss if not treated timely. The early diagnosis of retinal detachment can improve the rate of successful reattachment and the visual results, especially before macular involvement. Manual retinal detachment screening is time-consuming and labour-intensive, which is difficult for large-scale clinical applications. In this study, we developed a cascaded deep learning system based on the ultra-widefield fundus images for automated retinal detachment detection and macula-on/off retinal detachment discerning. The performance of this system is reliable and comparable to an experienced ophthalmologist. In addition, this system can automatically provide guidance to patients regarding appropriate preoperative posturing to reduce retinal detachment progression and the urgency of retinal detachment repair. The implementation of this system on a global scale may drastically reduce the extent of vision impairment resulting from retinal detachment by providing timely identification and referral.

The oncological outcome and influence of neoadjuvant chemotherapy on the surgery in the resectable and locally advanced oral squamous cell carcinoma.

AIM: The role of neoadjuvant chemotherapy (NCT) in the treatment of advanced oral squamous cell carcinoma (OSCC) is still controversial. Especially, there are still few studies investigating the influence of NCT on the following surgery. In this retrospective single-center attended cohort study, we investigated the oncological effect of NCT and its influence on the following surgery in patients with resectable locally advanced OSCC. METHOD: The clinical data of 88 patients with locally advanced but resectable OSCC (T3/4) were reviewed retrospectively. NCT plus conservative surgery and radical surgery were compared. Five-year disease-specific survival (DSS) was observed as the main endpoint. RESULTS: Among 88 patients enrolled in this study, 56 patients received upfront radical surgery (non-NCT group) and 32 patients received NCT followed by surgery (NCT group). The patients in the non-NCT group had a statistically better DSS than the patients in the NCT group (P=0.041). Twenty-one out of 32 (65.6%) patients who received NCT were good responders including two patients (6.2%) had a complete response and 19 patients (59.4%) had a partial response. There was no statistical difference between good and poor responders in 5-year DSS (P=0.823). Eleven patients (34.4%) had conservative surgery without flap reconstruction and 21 patients had radical surgery with flap reconstruction after NCT. No statistical difference in surgical margins was found between the two types of surgery (P=0.519). There was also no statistical difference in 5-year DSS between the two types of surgery (P=0.652). CONCLUSION: NCT plus surgery could not improve survival compared with upfront surgery. NCT could modify the surgical extent but would not affect the surgical margins. This conclusion should be explained cautiously, and randomized clinical trials with large sample size were needed to further answer the question.

Realgar transforming solution as a novel arsenic agent with a lower risk of cardiotoxicity.

QTc prolongation has been observed during arsenic trioxide and realgar's clinical use, and become a huge obstacle for the application. Our lab has obtained the soluble arsenic from realgar named realgar transforming solution or RTS. In this study, we first evaluated the cytotoxicity on NB4 cell and found that RTS could remarkably inhibit proliferation of NB4 than arsenic trioxide. Then we figured out the QTc prolongation of RTS treatment contrasted with arsenic trioxide; results revealed that arsenic trioxide prolonged corrected QTc of mice by 20.1% and showed 1.9-fold higher cytotoxicity on H9c2 cell than RTS. On the contrary, there could not find any QTc prolongation of mice in RTS treatment. Also, arsenic trioxide elevated the intercellular calcium accumulation of H9c2 cell by 2.02-fold v.s control and RTS. HE staining and Masson's trichrome staining had shown that there was no injured section after RTS treatments. IK1 currents of rat ventricular cardiomyocytes were diminished by 45.0% after treating with arsenic trioxide while RTS showed no significance than the control group. The results above indicated that RTS could serve as an alternative arsenic agent on leukemia and had a lower risk of cardiotoxicity.

Realgar transforming solution-induced differentiation of NB4 cell by the degradation of PML/RARα partially through the ubiquitin-proteasome pathway.

PML/retinoic acid receptor alpha (RARα), as a hallmark of acute promyeloid leukemia (APL), is directly related to the outcome of clinical APL remedy. It is reported that arsenicals can effectively degrade PML/RARα, such as arsenic trioxide and realgar. However, the high toxicity or insolubility have hampered their clinical applications. Realgar transforming solution (RTS) was produced from realgar by bioleaching process in our lab. Previous studies demonstrated that RTS had a significant anti-cancer ability on chronic myeloid leukemia through oncoprotein degradation. The capacity of RTS on treating APL is what is focused on in this study. The results showed that RTS had a noticeable sensitivity in NB4 cell, and RTS remarkably down-regulated PML/RARα expression and induced cell differentiation. Further, RTS could accumulate PML/RARα into the nuclear bodies and then execute degradation, which could be reversed by proteasome inhibitor MG132. The results also exhibited that the reduction of RTS-induced PML/RARα expression accompanied by the elevation of ubiquitin and SUMO-1 protein expression. Finally, PML and SUMO-1 had been demonstrated to be co-localized after RTS treatment by immunofluorescence co-localization assay and immunoprecipitation assay. In conclusion, these results suggested that RTS-induced cell differentiation may attribute to the PML/RARα degradation partially through the ubiquitin-proteasome pathway.