Objective
To evaluate early retinal microvascular abnormalities in patients with chronic kidney disease (CKD) via optical coherence tomography angiography.
Methods
A cross‐sectional study. Two ...hundred patients with CKD stage ≧3 were enrolled in the CKD group, and 50 age‐matched healthy subjects were enrolled in the control group. Main outcome measures were the differences in parafoveal vessel densities in the superficial vascular plexus (SVP) and deep vascular plexus (DVP) between the CKD and control groups.
Results
The mean ages were 62.7 ± 10.1 in the CKD group and 61.9 ± 9.7 (P = 0.622) in the control group. The CKD group had reduced parafoveal vessel densities in SVP (46.7 ± 4.3 vs 49.7 ± 2.9, P < 0.001) and DVP (50.1 ± 4.1 vs 52. 6 ± 2.9, P < 0.001) when compared to those of the control group. In multiple linear regression models, age, diabetes, estimated glomerular filtration rate, and use of anti‐hypertensive drugs were factors associated with vessel density in SVP, whereas age, diabetes, and smoking were factors associated with vessel density in DVP.
Conclusion
Patients with CKD had reduced vessel densities in parafoveal SVP and DVP, as compared to that of control subjects. Microvasculature in the different retinal layers may be affected by different systemic factors.
We propose using faster regions with convolutional neural network features (faster R-CNN) in the TensorFlow tool package to detect and number teeth in dental periapical films. To improve detection ...precisions, we propose three post-processing techniques to supplement the baseline faster R-CNN according to certain prior domain knowledge. First, a filtering algorithm is constructed to delete overlapping boxes detected by faster R-CNN associated with the same tooth. Next, a neural network model is implemented to detect missing teeth. Finally, a rule-base module based on a teeth numbering system is proposed to match labels of detected teeth boxes to modify detected results that violate certain intuitive rules. The intersection-over-union (IOU) value between detected and ground truth boxes are calculated to obtain precisions and recalls on a test dataset. Results demonstrate that both precisions and recalls exceed 90% and the mean value of the IOU between detected boxes and ground truths also reaches 91%. Moreover, three dentists are also invited to manually annotate the test dataset (independently), which are then compared to labels obtained by our proposed algorithms. The results indicate that machines already perform close to the level of a junior dentist.
Considering the importance of microRNAs (miRNAs) in regulating cellular processes, we performed microarray analysis and revealed miR‐4324 as one of the most differentially expressed miRNAs in bladder ...cancer (BCa). Then, we discovered that miR‐4324 was a negative regulator of Rac GTPase activating protein 1 (RACGAP1) and that RACGAP1 functioned as an oncogenic protein in BCa. Our studies indicated that ectopic overexpression of miR‐4324 in BCa cells significantly suppressed cell proliferation and metastasis and enhanced chemotherapy sensitivity to doxorubicin by repressing RACGAP1 expression. Further studies showed that estrogen receptor 1 (ESR1) increased the expression of miR‐4324 by binding to its promoter, while the downregulation of ESR1 in BCa was caused by hypermethylation of its promoter. p‐STAT3 induced the enrichment of DNMT3B by binding to the ESR1 promoter and then induced methylation of the ESR1 promoter. In turn, RACGAP1 induced STAT3 phosphorylation, increasing p‐STAT3 expression and promoting its translocation to the nucleus. Therefore, the miR‐4324‐RACGAP1‐STAT3‐ESR1 feedback loop could be a critical regulator of BCa progression.
What's new?
MicroRNAs have been reported to play important roles in bladder cancer (BCa) carcinogenesis, but mechanisms of action remain to be fully elucidated. This study reveals that miR‐4324 is one of the most significantly downregulated miRNAs in BCa tissues. miR‐4324 suppresses cell proliferation and metastasis and enhances chemotherapy sensitivity to doxorubicin by repressing RACGAP1 expression. ESR1 can increase the expression of miR‐4324 by binding to its promoter. p‐STAT3 can induce the enrichment of DNMT3B by binding to ESR1 promoter and induce methylation of ESR1 promoter. miR‐4324‐RACGAP1‐STAT3‐ESR1 feedback loop may thus be a critical regulator of BCa progression and potential therapeutic target.
Chromium‐doped zinc gallate, ZnGa2O4:Cr3+ (ZGC), is viewed as a long‐lasting luminescence (LLL) phosphor that can avoid tissue autofluorescence interference for in vivo imaging detection. ZGC is a ...cubic spinel structure, a typical agglomerative or clustered morphology lacking a defined cubic shape, but a sphere‐like feature is commonly obtained for the nanometric ZGC. The substantial challenge remains achieving a well‐defined cubic feature in nanoscale. The process by which dispersed and well‐defined concave cubic ZGC is obtained is described, exhibiting much stronger LLL in UV and X‐ray excitation for the dispersed cubic ZGC compared with the agglomerative form that cannot be excited using X‐rays with a low dose of 0.5 Gy. The cubic ZGC reveals a specific accumulation in liver and 0.5 Gy used at the end of X‐ray excitation is sufficient for imaging of deep‐seated hepatic tumors. The ZGC nanocubes show highly passive targeting of orthotopic hepatic tumors.
Dispersed and well‐defined ZnGa2O4:Cr3+ (ZGC) concave nanocubes are reported as providing highly passive targeting of deep‐seated hepatic tumors. They also exhibit much stronger long‐lasting luminescence in UV and X‐ray excitation for the dispersed cubic ZGC compared with the agglomerative form that cannot be charged using X‐rays with a low dose of 0.5 Gy.
Renal cell carcinoma (RCC) is the most common type of renal tumor, and the clear cell renal cell carcinoma (ccRCC) is the most frequent subtype. In this study, our aim is to identify potential ...biomarkers that could effectively predict the prognosis and progression of ccRCC. First, we used The Cancer Genome Atlas (TCGA) RNA‐sequencing (RNA‐seq) data of ccRCC to identify 2370 differentially expressed genes (DEGs). Second, the DEGs were used to construct a coexpression network by weighted gene coexpression network analysis (WGCNA). Moreover, we identified the yellow module, which was strongly related to the histologic grade and pathological stage of ccRCC. Then, the functional annotation of the yellow module and single‐samples gene‐set enrichment analysis of DEGs were performed and mainly enriched in cell cycle. Subsequently, 18 candidate hub genes were screened through WGCNA and protein–protein interaction (PPI) network analysis. After verification of TCGA’s ccRCC data set, Gene Expression Omnibus (GEO) data set (GSE73731) and tissue validation, we finally identified 15 hub genes that can actually predict the progression of ccRCC. In addition, by using survival analysis, we found that patients of ccRCC with high expression of each hub gene were more likely to have poor prognosis than those with low expression. The receiver operating characteristic curve showed that each hub gene could effectively distinguish between localized and advanced ccRCC. In summary, our study indicates that 15 hub genes have great predictive value for the prognosis and progression of ccRCC, and may contribute to the exploration of the pathogenesis of ccRCC.
We constructed a scale‐free weighted gene coexpression network analysis coexpression network, after a series of rigorous analysis and verification, we finally selected 15 hub genes, which are significantly related to the progress and prognosis of clear cell renal cell carcinoma (ccRCC), as well as could also significantly differentiate between localized and advanced ccRCC. Our study providing new research objects for studying the pathogenesis of ccRCC, they are also new potential therapeutic targets for ccRCC.
We propose an integrated end-to-end automatic speech recognition (ASR) paradigm by joint learning of the front-end speech signal processing and back-end acoustic modeling. We believe that "only good ...signal processing can lead to top ASR performance" in challenging acoustic environments. This notion leads to a unified deep neural network (DNN) framework for distant speech processing that can achieve both high-quality enhanced speech and high-accuracy ASR simultaneously. Our goal is accomplished by two techniques, namely: (i) a reverberation-time-aware DNN based speech dereverberation architecture that can handle a wide range of reverberation times to enhance speech quality of reverberant and noisy speech, followed by (ii) DNN-based multicondition training that takes both clean-condition and multicondition speech into consideration, leveraging upon an exploitation of the data acquired and processed with multichannel microphone arrays, to improve ASR performance. The final end-to-end system is established by a joint optimization of the speech enhancement and recognition DNNs. The recent REverberant Voice Enhancement and Recognition Benchmark (REVERB) Challenge task is used as a test bed for evaluating our proposed framework. We first report on superior objective measures in enhanced speech to those listed in the 2014 REVERB Challenge Workshop on the simulated data test set. Moreover, we obtain the best single-system word error rate (WER) of 13.28% on the 1-channel REVERB simulated data with the proposed DNN-based pre-processing algorithm and clean-condition training. Leveraging upon joint training with more discriminative ASR features and improved neural network based language models, a low single-system WER of 4.46% is attained. Next, a new multi-channel-condition joint learning and testing scheme delivers a state-of-the-art WER of 3.76% on the 8-channel simulated data with a single ASR system. Finally, we also report on a preliminary yet promising experimentation with the REVERB real test data.
The signaling pathways imposing hormonal control over adipocyte differentiation are poorly understood. While insulin and Akt signaling have been found previously to be essential for adipogenesis, the ...relative importance of their many downstream branches have not been defined. One direct substrate that is inhibited by Akt-mediated phosphorylation is the tuberous sclerosis complex 2 (TSC2) protein, which associates with TSC1 and acts as a critical negative regulator of the mammalian target of rapamycin (mTOR) complex 1 (mTORC1). Loss of function of the TSC1-TSC2 complex results in constitutive mTORC1 signaling and, through mTORC1-dependent feedback mechanisms and loss of mTORC2 activity, leads to a concomitant block of Akt signaling to its other downstream targets.
We find that, despite severe insulin resistance and the absence of Akt signaling, TSC2-deficient mouse embryo fibroblasts and 3T3-L1 pre-adipocytes display enhanced adipocyte differentiation that is dependent on the elevated mTORC1 activity in these cells. Activation of mTORC1 causes a robust increase in the mRNA and protein expression of peroxisome proliferator-activated receptor gamma (PPARgamma), which is the master transcriptional regulator of adipocyte differentiation. In examining the requirements for different Akt-mediated phosphorylation sites on TSC2, we find that only TSC2 mutants lacking all five previously identified Akt sites fully block insulin-stimulated mTORC1 signaling in reconstituted Tsc2 null cells, and this mutant also inhibits adipogenesis. Finally, renal angiomyolipomas from patients with tuberous sclerosis complex contain both adipose and smooth muscle-like components with activated mTORC1 signaling and elevated PPARgamma expression.
This study demonstrates that activation of mTORC1 signaling is a critical step in adipocyte differentiation and identifies TSC2 as a primary target of Akt driving this process. Therefore, the TSC1-TSC2 complex regulates the differentiation of mesenchymal cell lineages, at least in part, through its control of mTORC1 activity and PPARgamma expression.
Prostate cancer is initially responsive to androgen deprivation, but the effectiveness of androgen receptor (AR) inhibitors in recurrent disease is variable. Biopsy of bone metastases is challenging; ...hence, sampling circulating tumor cells (CTCs) may reveal drug-resistance mechanisms. We established single-cell RNA-sequencing (RNA-Seq) profiles of 77 intact CTCs isolated from 13 patients (mean six CTCs per patient), by using microfluidic enrichment. Single CTCs from each individual display considerable heterogeneity, including expression of AR gene mutations and splicing variants. Retrospective analysis of CTCs from patients progressing under treatment with an AR inhibitor, compared with untreated cases, indicates activation of noncanonical Wnt signaling (P = 0.0064). Ectopic expression of Wnt5a in prostate cancer cells attenuates the antiproliferative effect of AR inhibition, whereas its suppression in drug-resistant cells restores partial sensitivity, a correlation also evident in an established mouse model. Thus, single-cell analysis of prostate CTCs reveals heterogeneity in signaling pathways that could contribute to treatment failure.
This study examines the antecedents of purchase intention and the relation between purchase intention and image, risk, value, and perceived usefulness in the electric motorcycle market. The paper ...investigates a number of important questions concerning how image, risk, value, and perceived usefulness affect purchase intention. This article offers suggestions for campaigns aiming at increasing consumer demand for green products, including motorcycles. The technology acceptance model provides a theoretical framework in which to analyze consumer attitudes toward green purchase intentions in the motorcycle market. This study proposes and tests an integrative model to examine relations among service image, risk, value, perceived usefulness, and purchase intention. Structural equation modeling and fuzzy set qualitative comparative analysis (fsQCA) provide techniques for analyzing survey data from 305 potential motorcycle users. Results support the argument that image, risk, value, and perceived usefulness are key determinants of purchase intention. The paper also discusses theoretical and managerial implications of the research findings.
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