ROSE: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model

Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that has been increasingly used to image the retinal vasculature at capillary level resolution. However, automated segmentation of retinal vessels in OCTA has been under-studied due to various challenges such as low capillary visibility and high vessel complexity, despite its significance in understanding many vision-related diseases. In addition, there is no publicly available OCTA dataset with manually graded vessels for training and validation of segmentation algorithms. To address these issues, for the first time in the field of retinal image analysis we construct a dedicated Retinal OCTA SEgmentation dataset (ROSE), which consists of 229 OCTA images with vessel annotations at either centerline-level or pixel level. This dataset with the source code has been released for public access to assist researchers in the community in undertaking research in related topics. Secondly, we introduce a novel split-based coarse-to-fine vessel segmentation network for OCTA images (OCTA-Net), with the ability to detect thick and thin vessels separately. In the OCTA-Net, a split-based coarse segmentation module is first utilized to produce a preliminary confidence map of vessels, and a split-based refined segmentation module is then used to optimize the shape/contour of the retinal microvasculature. We perform a thorough evaluation of the state-of-the-art vessel segmentation models and our OCTA-Net on the constructed ROSE dataset. The experimental results demonstrate that our OCTA-Net yields better vessel segmentation performance in OCTA than both traditional and other deep learning methods. In addition, we provide a fractal dimension analysis on the segmented microvasculature, and the statistical analysis demonstrates significant differences between the healthy control and Alzheimer's Disease group. This consolidates that the analysis of retinal microvasculature may offer a new scheme to study various neurodegenerative diseases.

The role of stromal cell-derived factor 1 on cartilage development and disease

Stromal cell-derived factor 1 (SDF-1), also known as CXC motif chemokine ligand 12 (CXCL12), is recognized as a homeostatic cytokine with strong chemotactic potency. It plays an important role in physiological and pathological processes, such as the development of multiple tissues and organs, the regulation of cell distribution, and tumour metastasis. SDF-1 has two receptors, CXC chemokine receptor type 4 (CXCR4) and CXC chemokine receptor type 7 (CXCR7). SDF-1 affects the proliferation, survival, differentiation and maturation of chondrocytes by binding to CXCR4 on chondrocytes. Therefore, SDF-1 has been used as an exogenous regulatory target in many studies to explore the mechanism of cartilage development. SDF-1 is also a potential therapeutic target for osteoarthritis (OA) and rheumatoid arthritis (RA), because of its role in pathological initiation and regulation. In addition, SDF-1 shows potent capacity in the repair of cartilage defects by recruiting endogenous stem cells in a cartilage tissue engineering context. To summarize the specific role of SDF-1 on cartilage development and disease, all articles had been screened out in PubMed by May 30, 2020. The search was limited to studies published in English. Search terms included SDF-1; CXCL12; CXCR4; chondrocyte; cartilage; OA; RA, and forty-seven papers were studied. Besides, we reviewed references in the articles we searched to get additional relevant backgrounds. The review aims to conclude the current knowledge regarding the physiological and pathological role of SDF-1 on the cartilage and chondrocyte. More investigations are required to determine methods targeted SDF-1 to cartilage development and interventions to cartilage diseases.

Inhibition of SRSF3 Alleviates Proliferation and Migration of Gastric Cancer Cells by Regulating the PI3K/AKT/mTOR Signalling Pathway

This study was aimed to investigate the impact of serine/arginine-rich splicing factor 3 (SRSF3) on the proliferation and migration of gastric cancer (GC) cells. SRSF3 levels in GC tissues and cell lines were measured by Western blotting. Functional assays were used for evaluation of GC cell proliferation, migration and invasion. The PI3K/AKT/mTOR pathway was then examined by Western blotting. SRSF3 exhibits abnormal expression for the significantly increased levels in GC. SRSF3 knockdown significantly suppressed GC progression. SRSF3 knockdown significantly inhibited activation of PI3K/AKT/mTOR signalling. Inhibition of SRSF3 alleviates proliferation and migration of GC cells, and this process is mediated by inactivation of PI3K/ AKT/mTOR signalling. Targeting SRSF3 may be a promising strategy to combat GC.

Intravenously delivered mesenchymal stem cells prevent MVO formation after myocardial ischemia/reperfusion injury

 

Microvascular obstruction (MVO) after primary PCI is identified as an independent risk factor for prognosis in AMI patients. Inflammatory response induced by ischemia and reperfusion injury (I/R injury) was considered as one of main mechanisms for MVO formation. Mesenchymal stem cells (MSCs) are a unique stromal cell type that confers immunomodulatory effect in cardiac disease. Here we investigate whether intravenously and immediately delivered MSC could be used as potential therapeutic method to attenuate MVO formation. A cardiac-catheterization-induced porcine model of myocardial I/R injury was established, and allograft MSCs were delivered intravenously and immediately. Cardiac magnetic resonance imaging was performed 2 days and 7 days after operation to determine infarct area, MVO and cardiac function. We observed that the animals with allograft MSC delivering revealed decreased MVO and infarct size, as well as improved LVEF. In histology analysis, decreased myocytes area, fibrosis and inflammatory cell infiltration were observed in peri-infarct zone of animals with allograft MSC delivering. Meanwhile, the concentrations of IL-6, CRP and IL-1β in the serum were reduced in the allograft MSC group versus the control group. Flow cytometry indicated that decreased NK cells in the peripheral blood and ischemic heart tissue in the animals with allograft MSC delivering. In summary, we observed that allograft MSC delivering intravenously and immediately after myocardium I/R injury could attenuate MVO formation in porcine by NK cells depression.

Figure 1

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): Natural Science Foundation of China

Histone deacetylase HDA19 interacts with histone methyltransferase SUVH5 to regulate seed dormancy in Arabidopsis

Seed dormancy controls the timing of germination and plays a significant role in adaptation and evolution of seed plants. In this study, a yeast two-hybrid, pull-down assay and co-immunoprecipitation assay were used to ascertain the protein relationship of SUVH5 and HDA19. Both qRT-PCR and ChIP-qPCR were used to examine the molecular mechanism of how HDA19 and SUVH5 regulate seed dormancy. The results demonstrated that histone methyltransferase SUVH5 interacted with histone deacetylase HDA19 in vivo and in vitro. In addition, they showed that mutants of HDA19 could deepen seed dormancy, and that SUVH5 had the same effect. The hda19 suvh5 double mutant displayed a higher level of seed dormancy than the single mutants hda19 or suvh5. Moreover, the expression of seed dormancy-related genes increased in hda19, suvh5 and in hda19 suvh5 double mutant plants, which was associated with increased histone H3 acetylation (H3ac), but decreased histone H3 Lys 9 dimethylation (H3K9me2). ChIP assays proved that HDA19 could directly integrate into the chromatin of genes regulating seed dormancy. Taken together, our results show that HDA19 and SUVH5 work together and have a negative role in seed dormancy.

[Effects of comorbid gestational diabetes mellitus and depression on glucose metabolism during pregnancy and neonatal morphological outcome]

Objective: To estimate the effect of comorbid gestational diabetes mellitus (GDM) and depression on glucose metabolism and neonatal morphology. Methods: From March 2015 to October 2018, recruited 18 to 28 weeks pregnant women who met the criteria in the Hefei First People's Hospital or First Affiliated Hospital of Anhui Medical University or Anhui Maternal and Child Health Hospital, including a total of 4 380 study subjects, of which the birth outcome information of 3 827 newborns were collected. The self-made questionnaire "Maternal Health Questionnaire for Hefei City" and Edinburgh Postpartum Depression Scale were used to obtain basic demographic characteristics and emotional state of depression. Data from the 75-g oral-glucose-tolerance test were obtained at 24-28 weeks of gestation. After delivery, delivery outcome information were collected from the hospital medical records. Covariance analysis was used to analyze the differences in glucose metabolism indicators and neonatal outcome indicators in pregnant women with different GDM and depression status. Multiple logistic regression model was used to analyze the correlation between GDM and depression, with different groups of GDM and depression status (no GDM and depression, simple depression, simple GDM, comorbid GDM and depression)as independent variables and whether they were large for gestational age as dependent variables. The interaction between GDM and depression was also analyzed. Results: The 4 380 pregnant women were (28.8±4.2) years old. The incidence of GDM was 19.5% (852/4 380), and the detection rates of depression in the second and third trimesters were 12.1% (526/4 380) and 12.3% (536/4 367). PG-1h and AUC in the comorbid GDM and depression group were significantly higher than those in the group with no GDM and depression (P<0.05) and the single GDM group (P<0.05). After adjusting for factors such as the childbirth age, education level, family's main economic income, BMI before pregnancy, parity, number of physical activities, and weight gain during pregnancy, compared with the group with no GDM and depression, the RR(95%CI) of LGA occurred in the single depression group, the single GDM group and the comorbid group were 1.31(0.89-1.91), 1.51(1.14-2.00) and 2.43(1.29-4.57), respectively. Further analysis showed that the association between GDM pregnant women with depression and newborn LGA ［RR (95%CI): 2.12 (1.01-4.49)］ was stronger than that between GDM pregnant women without depression and newborn LGA ［RR (95%CI): 1.50 (1.12-1.99)］, the P interaction value was<0.05. Conclusion: The status of comorbid GDM and depression can impair glucose metabolism and increase the risk of LGA.

[Association between sleep and serum hemoglobin A1c in nondiabetic population in Beijing]

Objective: To understand the status quo of sleep and its associations with serum hemoglobin A1c (HbA1c) among nondiabetic people of 18-79 years old in Beijing. Methods: Data was gathered from the 2017 Beijing Non-communicable and Chronic Disease Surveillance Program. Multiple classified clusters sampling method was used while the 18-79 years old were sampled from the 16 districts of Beijing. Questionnaires would include information on demographic characteristics, chronic diseases and related risk factors, sleep duration and related problems (snore/asphyxia, difficult to get to sleep, waking often during the night, waking up early or taking sleeping pills) within the last 30 days. Complex sampling logistic regression models were established to analyze the association between sleep-related problems and serum HbA1c. Results: A total of 11 608 non-diabetic participants were involved in this study, with average age, reported sleep duration and median of serum HbA1c level as (43.36±15.27) years old, (7.49±1.29) h/d and 5.30%, respectively. 47.38% of them reported having sleep problems within the last 30 days. With the increasing time of sleep, serum HbA1c level was fluctuating significantly (F=413.06, P<0.01). Significant differences appeared in serum HbA1c levels among different age groups (t=358.3, P<0.01). Among participants with several kinds of sleep problems, the serum HbA1c levels were significantly higher than those without, through the single factor analysis (U=15.11, P<0.01). After adjusting for potential confounding factors, the combination of one sleep-related problem (OR=1.21, 95%CI: 1.03-1.41) and snore/asphyxia were associated with higher serum HbA1c levels (HbA1c≥5.7%) (OR=1.37, 95%CI: 1.16-1.61). People under 60 years of age were with higher risk of having higher serum HbA1c levels. Conclusion: Duration and sleep-related problems might affect the serum HbA1c levels, especially among those younger than 60 years of age.

TFPI-2 inhibits the invasion and metastasis of bladder cancer cells

INTRODUCTION

Bladder cancer metastasis seriously affects the prognosis of patients, but its molecular mechanism is unclear. This study sought to explore the roles of tissue factor pathway inhibitor-2 (TFPI-2) gene overexpression in the infiltration and metastasis of bladder cancer.

MATERIALS

Firstly, real-time PCR and immunohistochemistry were used to compare the mRNA and protein expression levels, respectively, of TFPI-2 and matrix metalloproteinase-1 (MMP-1) in adjacent non-tumoral tissues, muscle-invasive bladder cancer (MIBC) tissues, and non-muscle-invasive bladder cancer (NMIBC) tissues. BIU-87-TFPI-2 cells that stably expressed TFPI-2 were generated by transfection with pcDNA3.1-TFPI-2. Real-time PCR and western blotting were performed to determine the mRNA and protein expression levels, respectively, of TFPI-2 and MMP-1 in BIU-87-TFPI-2 cells. The invasion and migration abilities of BIU-87-TFPI-2 cells were investigated using the Transwell chamber method.

RESULTS

TFPI-2 was found to be significantly downregulated in bladder cancer tissue. The expression of MMP-1 was increased with the progression of bladder cancer. BIU-87 cells that overexpressed TFPI-2 were successfully generated by transfection with pcDNA3.1-TFPI-2. TFPI-2 overexpression in BIU-87 cells significantly inhibited cancer cell invasion and metastasis. Furthermore, the mRNA and protein expression levels of MMP-1 were significantly reduced in TFPI-2-overexpressing cells.

CONCLUSION

Decreased TFPI-2 expression in bladder tissue was correlated with invasion and metastasis in bladder cancer. TFPI-2 overexpression could inhibit bladder cancer cell invasion and migration in vitro by inhibiting MMP-1 protein expression.

LEVEL OF PROOF

3.

Automated Tortuosity Analysis of Nerve Fibers in Corneal Confocal Microscopy

Precise characterization and analysis of corneal nerve fiber tortuosity are of great importance in facilitating examination and diagnosis of many eye-related diseases. In this paper we propose a fully automated method for image-level tortuosity estimation, comprising image enhancement, exponential curvature estimation, and tortuosity level classification. The image enhancement component is based on an extended Retinex model, which not only corrects imbalanced illumination and improves image contrast in an image, but also models noise explicitly to aid removal of imaging noise. Afterwards, we take advantage of exponential curvature estimation in the 3D space of positions and orientations to directly measure curvature based on the enhanced images, rather than relying on the explicit segmentation and skeletonization steps in a conventional pipeline usually with accumulated pre-processing errors. The proposed method has been applied over two corneal nerve microscopy datasets for the estimation of a tortuosity level for each image. The experimental results show that it performs better than several selected state-of-the-art methods. Furthermore, we have performed manual gradings at tortuosity level of four hundred and three corneal nerve microscopic images, and this dataset has been released for public access to facilitate other researchers in the community in carrying out further research on the same and related topics.

Corneal nerve tortuosity grading via ordered weighted averaging-based feature extraction

PURPOSE

Tortuosity of corneal nerve fibers acquired by in vivo Confocal Microscopy (IVCM) are closely correlated to numerous diseases. While tortuosity assessment has conventionally been conducted through labor-intensive manual evaluation, this warrants an automated and objective tortuosity assessment of curvilinear structures. This paper proposes a method that extracts the image-level features for corneal nerve tortuosity grading.

METHODS

For an IVCM image, all corneal nerve fibers are first segmented and then, their tortuosity are calculated by morphological measures. The ordered weighted averaging (OWA) approach, and the k-Nearest-Neighbor guided dependent ordered weighted averaging (kNNDOWA) approach are proposed to aggregate the tortuosity values and form a set of extracted features. This is followed by running the Wrapper method, a supervised feature selection, with an aim to identify the most informative attributes for tortuosity grading.

RESULTS

Validated on a public and an in-house benchmark data sets, experimental results demonstrate superiority of the proposed method over the conventional averaging and length-weighted averaging methods with performance gain in accuracy (15.44% and 14.34%, respectively).

CONCLUSIONS

The simultaneous use of multiple aggregation operators could extract the image-level features that lead to more stable and robust results compared with that using average and length-weighted average. The OWA method could facilitate the explanation of derived aggregation behavior through stress functions. The kNNDOWA method could mitigate the effects of outliers in the image-level feature extraction.