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Aims To investigate the efficacy of a bi-modality deep convolutional neural network (DCNN) framework to categorise age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) from colour fundus images and optical coherence tomography (OCT) images. Methods A retrospective cross-sectional study was proposed of patients with AMD or PCV who came to Peking Union Medical College Hospital. Diagnoses of all patients were confirmed by two retinal experts based on diagnostic gold standard for AMD and PCV. Patients with concurrent retinal vascular diseases were excluded. Colour fundus images and spectral domain OCT images were taken from dilated eyes of patients and healthy controls, and anonymised. All images were pre-labelled into normal, dry or wet AMD or PCV. ResNet-50 models were used as the backbone and alternate machine learning models including random forest classifiers were constructed for further comparison. For human-machine comparison, the same testing data set was diagnosed by three retinal experts independently. All images from the same participant were presented only within a single partition subset. Results On a test set of 143 fundus and OCT image pairs from 80 eyes (20 eyes per-group), the bi-modal DCNN demonstrated the best performance, with accuracy 87.4%, sensitivity 88.8% and specificity 95.6%, and a perfect agreement with diagnostic gold standard (Cohen’s κ 0.828), exceeds slightly over the best expert (Human1, Cohen’s κ 0.810). For recognising PCV, the model outperformed the best expert as well. Conclusion A bi-modal DCNN for automated classification of AMD and PCV is accurate and promising in the realm of public health.

Background/aimsThe aim of this study was to generate and evaluate individualised post-therapeutic optical coherence tomography (OCT) images that could predict the short-term response of antivascular endothelial growth factor therapy for typical neovascular age-related macular degeneration (nAMD) based on pretherapeutic images using generative adversarial network (GAN).MethodsA total of 476 pairs of pretherapeutic and post-therapeutic OCT images of patients with nAMD were included in training set, while 50 pretherapeutic OCT images were included in the tests set retrospectively, and their corresponding post-therapeutic OCT images were used to evaluate the synthetic images. The pix2pixHD method was adopted for image synthesis. Three experiments were performed to evaluate the quality, authenticity and predictive power of the synthetic images by retinal specialists.ResultsWe found that 92% of the synthetic OCT images had sufficient quality for further clinical interpretation. Only about 26%–30% synthetic post-therapeutic images could be accurately identified as synthetic images. The accuracy to predict macular status of wet or dry was 0.85 (95% CI 0.74 to 0.95).ConclusionOur results revealed a great potential of GAN to generate post-therapeutic OCT images with both good quality and high accuracy.

Amlexanox, an anti-inflammatory and anti-allergic agent, has been widely used clinically for the treatment of canker sores, asthma, and allergic rhinitis. Recently, amlexanox has received considerable attention in curing nonalcoholic fatty liver diseases and hepatitis virus infection. Herein, we first established a sensitive high-performance liquid chromatography-tandem mass spectrum (LC-MS/MS) method for the determination of amlexanox in rat plasma. Propranolol was used as the internal standard (IS). Using a simple protein precipitation method, the amlexanox and IS were separated with Capcell Pak C18 column (2.0 × 50 mm, 5 μm) and eluted with water and acetonitrile each containing 0.1% formic acid using gradient elution condition at a flow rate of 0.4 mL·min-1 . Amlexanox and IS were detected by a triple quadrupole mass in multiple reactive monitoring (MRM) under the transitions of m/z 299.2 → 281.2 and m/z 259.9→116.1 with positive electrospray ionization, respectively. The calibration curves of amlexanox were established with the range of 50 to 2000 ng·mL-1 (r2 > 0.99). The validation method consisted of selectivity, accuracy, precision, carryover effect, matrix effect, recovery, dilution effect, and stability. The fully validated method was successfully applied to the pharmacokinetic study of amlexanox in Wistar rats.

Myricetin is a natural dietary flavonoid compound with multiple activities, such as anti-oxidant, anti-inflammatory, anti-carcinogenic and anti-proliferative effects. However, myricetin exhibited substantial limitations, such as poor water-solubility, and low stability in body when it was administrated by oral. To solve these problems, we designed and synthesized a series of derivatives based on the structure of myricetin. M10 was produced by adding a hydrophilic glycosylation group and then forming a sodium salt derivative, which exhibited excellent water-solubility (>100 mg/mL), and better stability in Wistar rat plasma and liver microsomes. In vivo study, M10 exhibited higher efficacy than myricetin and mesalazine in a dextran sulfate sodium (DSS) induced mice model with ulcerative colitis. In addition, M10 also exhibited high safety (LD50 > 5 g/kg) in mice. Based on these results, M10 could be developed as a potential therapeutic agent for treatment of ulcerative colitis.

Aims To establish an automated method for identifying referable diabetic retinopathy (DR), defined as moderate nonproliferative DR and above, using deep learning-based lesion detection and stage grading. Materials and methods A set of 12,252 eligible fundus images of diabetic patients were manually annotated by 45 licenced ophthalmologists and were randomly split into training, validation, and internal test sets (ratio of 7:1:2). Another set of 565 eligible consecutive clinical fundus images was established as an external test set. For automated referable DR identification, four deep learning models were programmed based on whether two factors were included: DR-related lesions and DR stages. Sensitivity, specificity and the area under the receiver operating characteristic curve (AUC) were reported for referable DR identification, while precision and recall were reported for lesion detection. Results Adding lesion information to the five-stage grading model improved the AUC (0.943 vs. 0.938), sensitivity (90.6% vs. 90.5%) and specificity (80.7% vs. 78.5%) of the model for identifying referable DR in the internal test set. Adding stage information to the lesion-based model increased the AUC (0.943 vs. 0.936) and sensitivity (90.6% vs. 76.7%) of the model for identifying referable DR in the internal test set. Similar trends were also seen in the external test set. DR lesion types with high precision results were preretinal haemorrhage, hard exudate, vitreous haemorrhage, neovascularisation, cotton wool spots and fibrous proliferation. Conclusions The herein described automated model employed DR lesions and stage information to identify referable DR and displayed better diagnostic value than models built without this information.

This paper tackles automated screening of Retinopathy of Prematurity (ROP), one of the most common causes of visual loss in childhood. Clinically, ROP screening per case requires multiple color fundus image instances that capture different zones of the (premature) retina. A desirable model shall not only make a decision at the case level, but also pinpoint which instances and what part of the instances are responsible for the decision. This paper makes the first attempt to accomplish three tasks, i.e. ROP case classification, instance selection and abnormality localization in a unified framework. To that end, we propose a new model that effectively combines instance-attention based deep multiple instance learning (MIL) and spatial attention (SA). The propose model, which we term MIL-SA, identifies positive instances in light of their contributions to case-level decision. Meanwhile, abnormal regions in the identified instances are automatically localized by the SA mechanism. Moreover, MIL-SA is learned from case-level binary labels exclusively, and in an end-to-end manner. Experiments on a large clinical dataset of 2,186 cases with 11,053 fundus images show the viability of the proposed model for all the three tasks.

Deuterium substitution has been widely known that can improve the pharmacokinetic profiles due to isotope effect. Herein, a series of deuterated sorafenib derivatives have been synthesized and characterized by 1H NMR, 13C NMR and MS. Their antitumor activities were evaluated in vitro against human hepatoma cell line HepG2 and human cervical carcinoma cell line HeLa. The LogP values were detected by high-performance liquid chromatography. Subsequently, the metabolic stability and pharmacokinetics study were assessed in vitro and in vivo.

A series of novel indazole-based diarylurea derivatives targeting c-kit were designed by structure-based drug design. The derivatives were prepared, and their antiproliferative activities were evaluated against human colon cancer HCT-116 cell line and hepatocellular carcinoma PLC/PRF/5 cell line. The antiproliferative activities demonstrated that six of nine compounds exhibited comparable activities with sorafenib against HCT-116. The structure-activity relationship (SAR) analysis indicated that the indazole ring part tolerated different kinds of substituents, and the N position of the central pyridine ring played key roles in antiproliferative activity. The SAR and interaction mechanisms were further explored using molecular docking method. Compound 1i with N-(2-(pyrrolidin-1-yl)ethyl)-carboxamide possessed improved solubility, 596.1 ng/ml and best activities, IC50 at 1.0 μm against HCT-116, and 3.48 μm against PLC/PRF/5. It is a promising anticancer agent for further development.

Pancreatic cancer (PC) is a highly malignant cancer with poor prognosis. Although gemcitabine (GEM; 2',2'-difluoro-deoxycytidine) has been used as the first-line chemotherapeutic agent in PC treatment for decades, its limited efficacy remains a significant clinical issue, which may be resolved by GEM combination therapy. In this study, we aimed to investigate the anti-tumor effects of MBRI-001 in combination with GEM in BxPC-3 and MIA PaCa-2 human PC cell lines. In vitro and in vivo results indicate that MBRI-001 showed synergistic activity with GEM. GEM induced apoptosis by increasing DNA damage (phosphorylated core histone protein H2AX (γ-H2AX)), MBRI-001 activated mitochondrial-apoptotic pathway (cleaved poly-ADP ribose polymerase (PARP)). Thus, the combination of the two intensified both apoptosis and DNA damage and showed significantly superior anti-tumor activity compared to each agent alone. The adoption of combination of MBRI-001 with GEM may be beneficial as they act synergistically and thus, can be a potential therapeutic choice for improving the prognosis of PC patients in the future.

This paper studies automated categorization of age-related macular degeneration (AMD) given a multi-modal input, which consists of a color fundus image and an optical coherence tomography (OCT) image from a specific eye. Previous work uses a traditional method, comprised of feature extraction and classifier training that cannot be optimized jointly. By contrast, we propose a two-stream convolutional neural network (CNN) that is end-to-end. The CNN’s fusion layer is tailored to the need of fusing information from the fundus and OCT streams. For generating more multi-modal training instances, we introduce Loose Pair training, where a fundus image and an OCT image are paired based on class labels rather than eyes. Moreover, for a visual interpretation of how the individual modalities make contributions, we extend the class activation mapping technique to the multi-modal scenario. Experiments on a real-world dataset collected from an outpatient clinic justify the viability of our proposal for multi-modal AMD categorization.

MBRI-001 was demonstrated preliminary better pharmacokinetics and antitumor effects than that of plinabulin in vivo. In this approach, we further carried out systematic pharmacokinetic and pharmacodynamic study of MBRI-001 in vitro and in vivo. MBRI-001 was tested stable in rat plasma and more stable in liver microsomes than plinabulin in vitro. In vivo, MBRI-001 could be distributed rapidly and widely in various tissues, especially the concentration of MBRI-001 in lung was remarkably higher than other tissues. Excretion study indicated that MBRI-001 might been decomposed and excreted as metabolites. Additionally, the combination treatment of MBRI-001 and gefitinib revealed better antitumor inhibition rate than monotherapy in vivo. Therefore, we suggest that MBRI-001 could be developed as a promising anti-cancer agent in near future.

MBRI-001 is a novel synthetic derivative of plinabulin. In this study, our purpose is to investigate the inhibition effects of MBRI-001 on human hepatocellular carcinoma as monotherapy or in combination with sorafenib. HCCLM3 and Bel-7402 cell lines were used for activity evaluation in vitro. The anti-proliferative activity of MBRI-001 was assessed by MTT assay. The morphological change of microtubules was determined by immunofluorescence assay. The cell cycle was measured by flow cytometer. The expression of cyclin B1 (CCNB1) was analyzed by RT-qPCR and western blotting assays. The antitumor activities in vivo were evaluated with human HCC xenograft mice model. Our data demonstrated that MBRI-001 had better anti-proliferative activities than that of plinabulin against HCCLM3 and Bel-7402 cell lines. MBRI-001 inhibited the formation of microtubules and induced G2/M arrest with the downregulation of CCNB1. In vivo orthotopic mice model demonstrated that MBRI-001 significantly inhibited the growth of HCCLM3 with the apoptosis and necrosis observed in tumor. The combination treatment of MBRI-001 with sorafenib in subcutaneous mice model exhibited a higher antitumor inhibition rate at 72.0%, in comparison with MBRI-001 or sorafenib as monotherapy at 40.7% or 47.7%, respectively. MBRI-001 had better inhibition effects on microtubules and human hepatocellular carcinoma than that of plinabulin. The combination treatment of MBRI-001 and sorafenib exhibited a higher antitumor effect, which could provide a new strategy to treat HCC in the future.

Plinabulin, a drug targeting microtubule of cancer cells, has been currently tried in its phase III clinical study. However, low efficacy caused by poor pharmacokinetic (PK) properties has been considered to be the main obstacle to approved by the Food and Drug Administration. Herein, we introduced a deuterium atom as an isostere in its structure to become a new compound named (MBRI-001, No. 9 in a series of deuterium-substituted compounds). The structure of MBRI-001 was characterized by HRMS, NMR, IR and a single crystal analysis. MBRI-001 exhibited better pharmacokinetic characteristics than that of plinabulin. Additionally, its antitumor activity is in a low nanomolar level for a variety of cancer cell lines and high activity against human NCI-H460 xenograted in mice intravenous administration. Importantly, continuous administration of MBRI-001 exhibited lower toxicity compared to docetaxel. We thus suggest that MBRI-001 could be developed as a promising anti-cancer agent in near future.

Background and Purpose— To determine incidence and risks of subarachnoid hemorrhage in China. Methods— A prospective, population-based, 1:2 matched case–control study in Baotou, Inner Mongolia (≈2 million population) in 2009–2011. Multiple variable models used to determine relative risk and population-attributable risks for exposures. Results— For a total of 226 patients (mean age, 59 years; 65% women; 434 controls), crude annual incidence (per 100 000) of subarachnoid hemorrhage was 6.2 (95% confidence intervals, 5.4–7.0); 4.3 (3.3–5.2) for men and 8.2 (6.9–9.6) for women. Compared with nonsmokers, adjusted relative risk of subarachnoid hemorrhage in current smokers was 2.31 (95% confidence interval, 1.31–4.09) but was 4.00 (1.62–9.89) in women. Population-attributable risk for smoking, hypertension, and low income were 18%, 36% and 59%, respectively. Conclusions— The incidence of subarachnoid hemorrhage in China is slightly lower than in Western countries and is related to smoking, hypertension, and poor socioeconomic status.