Quercetin Mediated TET1 Expression Through MicroRNA-17 Induced Cell Apoptosis in Melanoma Cells.

A previous report suggested that the expression of ten-eleven translocation (TET) proteins is abnormal in certain cancers. Quercetin has been demonstrated as anti-cancer role in cancer development. In order to explore the inhibitory effect and mechanism of quercetin on uveal melanoma cells, the expression of TET proteins was analyzed in the present study. Our results suggest that the expression of TET1 was increased following treatment with quercetin in OCM-1, SK-MEL-1, and B16 cells. In addition, quercetin treatment induced apoptosis and inhibited migration and invasion. To further investigate the association of the expression of TET1 with cell growth, apoptosis, migration, and invasion, cell lines in which TET1 was knocked-down or overexpressed were constructed. The results showed that the increased expression of TET1-induced apoptosis, increased 5-hydroxymethylcytosine (5 hmC). and inhibited invasion. Our bioinformatics studies indicated that TET1 is a target gene of microRNA-17 (miR-17) Our results showed that inhibition of the expression of miR-17 resulted in increased TET1 expression in OCM-1 cells. Furthermore, our results indicated that quercetin treatment increased TET1 expression and inhibited melanoma growth in nude mice. Taken together, our results suggest that quercetin can regulate cell proliferation and apoptosis through TET1 via miR-17 in melanoma cells.

Retinopathy is associated with impaired cognition in patients undergoing peritoneal dialysis.

Objective: Previous studies have shown a relationship between retinopathy and cognition including population with and without chronic kidney disease (CKD) but data regarding peritoneal dialysis (PD) are limited. This study aims to investigate the relationship between retinopathy and cognitive impairment in patients undergoing peritoneal dialysis (PD). Methods: In this observational study, we recruited a total of 107 participants undergoing PD, consisting of 48 men and 59 women, ages ranging from 21 to 78 years. The study followed a cross-sectional design. Retinal microvascular characteristics, such as geometric changes in retinal vascular including tortuosity, fractal dimension (FD), and calibers, were assessed. Retinopathy (such as retinal hemorrhage or microaneurysms) was evaluated using digitized photographs. The Modified Mini-Mental State Examination (3MS) was performed to assess global cognitive function. Results: The prevalence rates of retinal hemorrhage, microaneurysms, and retinopathy were 25%, 30%, and 43%, respectively. The mean arteriolar and venular calibers were 63.2 and 78.5 µm, respectively, and the corresponding mean tortuosity was 37.7 ± 3.6 and 37.2 ± 3.0 mm-1. The mean FD was 1.49. After adjusting for age, sex, education, mean arterial pressure, and Charlson index, a negative association was revealed between retinopathy and 3MS scores (regression coefficient: -3.71, 95% confidence interval: -7.09 to -0.33, p = 0.03). Conclusions: Retinopathy, a condition common in patients undergoing PD, was associated with global cognitive impairment. These findings highlight retinopathy, can serve as a valuable primary screening tool for assessing the risk of cognitive decline.

Automated detection of severe diabetic retinopathy using deep learning method.

PURPOSE: The purpose of this study is to develop and validate the intelligent diagnosis of severe DR with lesion recognition based on color fundus photography. METHODS: The Kaggle public dataset for DR grading is used in the project, including 53,576 fundus photos in the test set, 28,101 in the training set, and 7,025 in the validation set. We randomly select 4,192 images for lesion annotation. Inception V3 structure is adopted as the classification algorithm. Both 299 × 299 pixel images and 896 × 896 pixel images are used as the input size. ROC curve, AUC, sensitivity, specificity, and their harmonic mean are used to evaluate the performance of the models. RESULTS: The harmonic mean and AUC of the model of 896 × 896 input are higher than those of the 299 × 299 input model. The sensitivity, specificity, harmonic mean, and AUC of the method with 896 × 896 resolution images as input for severe DR are 0.925, 0.907, 0.916, and 0.968, respectively. The prediction error mainly occurs in moderate NPDR, and cases with more hard exudates and cotton wool spots are easily predicted as severe cases. Cases with preretinal hemorrhage and vitreous hemorrhage are easily identified as severe cases, and IRMA is the most difficult lesion to recognize. CONCLUSIONS: We have studied the intelligent diagnosis of severe DR based on color fundus photography. This artificial intelligence-based technology offers a possibility to increase the accessibility and efficiency of severe DR screening.

Deep learning-based detection and stage grading for optimising diagnosis of diabetic retinopathy.

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.

TUG1 mediates methotrexate resistance in colorectal cancer via miR-186/CPEB2 axis.

Colorectal cancer (CRC) is a common malignancy, most of which remain unresponsive to chemotherapy. Methotrexate (MTX) is one of the earliest cytotoxic drugs and serves as an anti-metabolite and anti-folate chemotherapy for various types of cancer. However, MTX resistance prevents its clinical application in cancer therapy. Thereby, overcoming the drug resistance is an alternative strategy to maximize the efficacy of MTX therapies in clinics. Long non-coding RNAs (lncRNAs) have gained widespread attention in recent years. More and more evidences have shown that lncRNAs play regulatory roles in various biological activities and disease progression including drug resistance in cancer cells. Here, we observed lncRNA TUG1 was associated to the MTX resistant in colorectal cancer cells. Firstly, quantitative analysis indicated that TUG1 was significantly increased in tumors which were resistant to MTX treatment. TUG1 knockdown re-sensitized the MTX resistance in colorectal cancer cells, which were MTX-resistant colorectal cell line. Furthermore, bioinformatics analysis showed that miR-186 could directly bind to TUG1, suggesting TUG1 might worked as a ceRNA to sponge miR-186. Extensively, our study also showed that CPEB2 was the direct target of miR-186 in colorectal cancer cells. Taken together, our study suggests that lncRNA TUG1 mediates MTX resistance in colorectal cancer via miR-186/CPEB2 axis.

miR-582-5P induces colorectal cancer cell proliferation by targeting adenomatous polyposis coli.

BACKGROUND: microRNA (miRNAs) dysregulation is widely involved in cancer progression and contributed to sustained cell proliferation by directly targeting multiple targets. Therefore, better understand the underlying mechanism of miRNA in carcinogenesis may improve diagnostic and therapeutic strategies for malignancy. METHODS: We assessed microRNA-582 (miR-582-5P) expression in colorectal cancer (CRC) specimens and cell lines by real-time PCR. Luciferase reporter assay was used to confirm the target associations. Colony formation assay and anchorage-independent growth assay were used to analyze the effect of miR-582-5P on cell proliferation. Adenomatous polyposis coli (APC) gene and protein expression were examined using real-time PCR and western blotting, respectively. RESULTS: miR-582-5P was upregulated in the CRC specimens and cell lines and targeted the 3' untranslated region of APC directly. miR-582-5P overexpression increased cyclin D1 and c-MYC expression, which subsequently induced CRC cell proliferation in an APC-dependent manner. CONCLUSIONS: Our findings suggest that miR-582-5P plays an important role in the progression of CRC by inducing proliferation and may identify new targets for anti-cancer treatment.

[Application of FTIR Microspectroscopy in the Study of Lignocellulosic Cell Walls].

The development and utilization of lignocellulosic biomass resource becomes a major subject of widespread concern at home and abroad. To make better use of this resource and reduce cost, a thorough understanding of recalcitrance mechanism as well as chemical compositional and structural characteristics of lignocellulosic cell walls seems desiderated. With the property of fast testing, high sensitivity and simple sample preparation, FTIR microspectroscopy can provide microanalysis and nondestructive test. It has been proved to accurately present compositional and structural information of lignocellulosic cell walls and be suitable for the study of topochemistry of main components at the cellular level. After a brief introduction of the principle of FTIR microspectroscopy and its detailed experimental procedure, this review provides an overview on the feasibility of FTIR microspectroscopy in monitoring as well as evaluating the composition and structure of lignocellulosic cell walls from three aspects, including in situ distribution, changes after pretreatment and molecular orientation of the major components in cell walls. Some prospects, for example development of the magnification of the microscope and the spatial resolution of chemical imaging, combination with various analysis methods and instruments are also proposed. This technology can act as a new approach in characterizing lignocellulosic cell walls.

Comparison between better and poorly differentiated locally advanced gastric cancer in preoperative chemotherapy: a retrospective, comparative study at a single tertiary care institute.

BACKGROUND: Gastric cancer is the third leading cause of cancer-related mortality in China, and the long-term survival for locally advanced gastric cancer is very poor. Simple surgery cannot yield an ideal result because of the high recurrence rate after tumor resection. Preoperative chemotherapy could help to reduce tumor volume, improve the R0 resection rate (no residual tumor after surgery), and decrease the risk of local tumor recurrence. The aim of this study was to evaluate the influence of pathological differentiation in the effect of preoperative chemotherapy for patients with locally advanced gastric cancer. METHODS: Patients with locally advanced gastric cancer (n = 32) received preoperative chemotherapy under the XELOX (capecitabine plus oxaliplatin) regimen. According to pathological examination, patients' tumors were classified into better (well and moderate) and poorly differentiated (lower differentiated and undifferentiated) groups, and the clinical response rate, type of gastrectomy, and negative tumor residual rate were compared between the two groups of patients. Morphological changes and toxic reactions were monitored after chemotherapy. RESULTS: The results showed that the clinical response rate in the better differentiated group was significantly higher than that in the poorly differentiated group (100% versus 25%, P = 0.000). The partial gastrectomy rate in the better differentiated group was significantly higher than that in the poorly differentiated group (87.5% versus 25% P = 0.000). A significant shrinking of tumor and necrosis of tumor tissues caused by chemotherapy could be observed. CONCLUSIONS: In conclusion, the better differentiated group with locally advanced gastric cancer is suitable for preoperative chemotherapy under the XELOX regimen, and as a result of effective preoperative chemotherapy, much more gastric tissue can be preserved for the better differentiated group.

Article expression, purification, and characterization of Cu/ZnSOD from Panax ginseng.

Superoxide dismutase (SOD) has a strong antioxidant effect, but the traditional SOD extraction method is not the most efficient method of SOD amplification. In this study, we report the cloning of the Cu/ZnSOD gene from Panax ginseng into a temperature-regulated expression plasmid, pBV220. Cu/ZnSOD inclusion bodies were expressed in E. coli at a high level. Then, the inclusion bodies were purified by ion-exchange chromatography and molecular sieve chromatography. Finally, we obtained stable SOD in the bacterial broth, with a protein content of 965 mg/L and enzyme specific activity of 9389.96 U/mg. These results provide a foundation for future studies on the antioxidant mechanisms of ginseng and the development and application of ginseng Cu/ZnSOD.

A highly sensitive and anti-freezing conductive strain sensor based on polypyrrole/cellulose nanofiber crosslinked polyvinyl alcohol hydrogel for human motion detection.

Electro-conductive hydrogels emerge as a stretchable conductive materials with diverse applications in the synthesis of flexible strain sensors. However, the high-water content and low cross-links density cause them to be mechanically destroyed and freeze at subzero temperatures, limiting their practical applications. Herein, we report a one-pot strategy by co-incorporating cellulose nanofiber (CNF), Poly pyrrole (PPy) and glycerol with polyvinyl alcohol (PVA) to prepare hydrogel. The addition of PPy endowed the hydrogel with good conductivity (∼0.034 S/m) compared to the no PPy@CNF group (∼0.0095 S/m), the conductivity was increased by 257.9 %. The hydrogel exhibits comparable ionic conductivity at -18 °C as it does at room temperature. It's attributed to the glycerol as a cryoprotectant and the formation of hydrated [Zn(H2O)n]2+ ions via strong interaction between Zn2+ and water molecules. Moreover, the cellulose nanofiber intrinsically assembled into unique hierarchical structures allow for strong hydrogen bonds between adjacent cellulose and PPy polymer chains, greatly improve the mechanical strength (stress∼0.65 MPa, strain∼301 %) and excellent viscoelasticity (G'max âˆ¼ 82.7 KPa). This novel PPy@CNF-PVA hydrogel exhibits extremely high Gauge factor (GF) of 2.84 and shows excellent sensitivity, repeatability and stability. Therefore, the hydrogel can serve as reliable and stable strain sensor which shows excellent responsiveness in human activities monitoration.

The performance of a deep learning system in assisting junior ophthalmologists in diagnosing 13 major fundus diseases: a prospective multi-center clinical trial.

Artificial intelligence (AI)-based diagnostic systems have been reported to improve fundus disease screening in previous studies. This multicenter prospective self-controlled clinical trial aims to evaluate the diagnostic performance of a deep learning system (DLS) in assisting junior ophthalmologists in detecting 13 major fundus diseases. A total of 1493 fundus images from 748 patients were prospectively collected from five tertiary hospitals in China. Nine junior ophthalmologists were trained and annotated the images with or without the suggestions proposed by the DLS. The diagnostic performance was evaluated among three groups: DLS-assisted junior ophthalmologist group (test group), junior ophthalmologist group (control group) and DLS group. The diagnostic consistency was 84.9% (95%CI, 83.0% ~ 86.9%), 72.9% (95%CI, 70.3% ~ 75.6%) and 85.5% (95%CI, 83.5% ~ 87.4%) in the test group, control group and DLS group, respectively. With the help of the proposed DLS, the diagnostic consistency of junior ophthalmologists improved by approximately 12% (95% CI, 9.1% ~ 14.9%) with statistical significance (P < 0.001). For the detection of 13 diseases, the test group achieved significant higher sensitivities (72.2% ~ 100.0%) and comparable specificities (90.8% ~ 98.7%) comparing with the control group (sensitivities, 50% ~ 100%; specificities 96.7 ~ 99.8%). The DLS group presented similar performance to the test group in the detection of any fundus abnormality (sensitivity, 95.7%; specificity, 87.2%) and each of the 13 diseases (sensitivity, 83.3% ~ 100.0%; specificity, 89.0 ~ 98.0%). The proposed DLS provided a novel approach for the automatic detection of 13 major fundus diseases with high diagnostic consistency and assisted to improve the performance of junior ophthalmologists, resulting especially in reducing the risk of missed diagnoses. ClinicalTrials.gov NCT04723160.

Laparoscopic versus open resection of gastric gastrointestinal stromal tumors.

The aims of this study were to explore whether laparoscopic surgical resections of gastric gastrointestinal stromal tumors (GISTs) would produce better perioperative and similar oncologic outcomes compared with open surgical resection in Chinese patients. Thirty-six gastric GISTs cases were divided into a minimally invasive laparoscopic group and open resection group, depending on the surgical approach that was used. The general preoperative information, operative time, incision length, intraoperative blood loss, postoperative time to first flatulence, postoperative complications, postoperative hospital stay, total hospitalization costs, and such follow-up data as recurrence, metastasis, and mortality rates were compared between two groups. Among the 36 gastric GISTs, 15 received laparoscopic surgical treatment (laparoscopy group, n=15), and 21 received routine open resection treatment (open resection group, n=21). The laparoscopy group and the open resection group showed statistically significant differences (P<0.05) in incision length (7.8±2.3 vs. 16.9±3.8 cm), postoperative time to first flatulence (3.8±1.3 vs. 5.1±2.1 d), postoperative hospitalization time (7.6±2.5 vs. 11.3±3.7 d), and total cost of hospitalization (RMB 28,239±5,521 vs. RMB 23,761±5,362). There were no statistically significant differences (P>0.05) between the laparoscopy group and the open resection group in operative time (147.8±59.3 vs. 139.2±62.1 min) and intraoperative blood loss (149.8±98.9 vs. 154.2±99.3 mL). Both groups had no postoperative complications, no recurrence and metastasis, and no postoperative mortality. There were no statistically significant differences between the two groups in postoperative complications, postoperative recurrence and metastasis, and postoperative mortality. In conclusion, compared with open resection, the laparoscopic resection of gastric GISTs offers the advantages of less trauma, faster recovery, and shorter hospital stay.

Multi-physics coupling reinforced polyvinyl alcohol/cellulose nanofibrils based multifunctional hydrogel sensor for human motion monitoring.

Ionic conductive hydrogels have been widely used for sensor, energy storage and human-machine interface. To address the problems of the traditional ionic conductive hydrogels fabricated with the soaking method, such as the lack of frost resistance, poor mechanical properties, time-consuming and chemical-wasting, herein, a multi-physics crosslinking reinforced strong, anti-freezing and ionic conductive hydrogel sensor is fabricated utilizing the tannin acid-Fe2(SO4)3 through the simple one-pot freezing-thawing process at low electrolyte concentration. The results show that the P10C0.4T8-Fe2(SO4)3 (PVA10%CNF0.4%TA8%-Fe2(SO4)3) displayed better mechanical property and ionic conductivity due to hydrogen bonding and coordination interaction. The tensile stress reaches up to 0.980 MPa (570 % strain). Moreover, the hydrogel presents excellent ionic conductivity (0.220 S⋅m-1 at room temperature), anti-freezing performance (0.183 S⋅m-1 at -18 °C), large gauge factor (1.75), excellent sensing stability, repeatability, durability and reliability. This work paves a way for preparing mechanical strong and anti-freezing hydrogel based on multi-physics crosslinking with one-pot freezing-thawing process.

Screening of biomarkers associated with diagnosis and prognosis of colorectal cancer.

We aimed to explore biomarkers associated with diagnosis and prognosis of colorectal cancer. Differentially expressed protein (DEP) genes were obtained and validated. Moreover, co-expressed genes were screened and their prognostic value was evaluated. In addition, miRNAs that were negatively correlated with DEP genes were identified and used to construct a competitive endogenous RNA network. Furthermore, a support vector machine model was built using DEP genes, and a receiver operating characteristic curve was implemented to confirm its prediction performance. The results showed that only one DEP gene, CCL26, was obtained. Moreover, 43 genes co-expressed with CCL26 were identified, among which six (AP3M2, DAPK1, ISYNA1, PPM1K, PRR4 and RNF122) were linked with the prognosis of colorectal cancer. Besides, the axis RP11-47122.2/RP11-527N22.1-hsa-miR-3192-5p-CCL26 was identified as an lncRNA-miRNA-target gene network. Support vector machine model analysis showed that the area under the curve of CCL26 reached 0.878 based on GEO data and 0.743 based on our protein data. In conclusion, AP3M2, DAPK1, ISYNA1, PPM1K, PRR4, RNF122, CCL26 and hsa-miR-3192-5p appear to be related to the progression of colorectal cancer.

Porous Carbon Material Derived from Steam-Exploded Poplar for Supercapacitor: Insights into Synergistic Effect of KOH and Urea on the Structure and Electrochemical Properties.

The electrochemical performance of supercapacitors using porous carbon as electrodes is strongly affected by the fabrication process of carbon material. KOH is commonly used as an activator combined with urea as a nitrogen dopant. However, the roles of KOH and urea in pore structure configuration and the electrochemical behavior of porous carbon electrodes are still ambiguous. Herein, the optimum porous carbon is obtained when KOH and urea are used simultaneously. KOH is used as a pore-forming substance, whereas urea is employed as a nitrogen source for the nitrogen doping of porous carbon, which increases its defect sites while reducing the graphitization degree. More importantly, urea also expands pores as a pore-enlarging agent, inducing interconnected porous structures. As a result, a hierarchical porous structure is formed and ascribed to the synergistic effect of KOH and urea, and the specific surface area reached 3282 m2 g-1 for sample PC800-4. The specific capacitance is 319 F g-1 at 0.5 A g-1 with excellent cycling stability over 2500 cycles. Furthermore, the symmetric supercapacitor reaches an excellent energy density of 11.6 W h kg-1 under 70.0 W kg-1 in a 6 M KOH electrolyte. Our work contributes to the rational designation of the porous carbon structure for supercapacitor applications.

Learning Two-Stream CNN for Multi-Modal Age-Related Macular Degeneration Categorization.

This paper tackles automated categorization of Age-related Macular Degeneration (AMD), a common macular disease among people over 50. Previous research efforts mainly focus on AMD categorization with a single-modal input, let it be a color fundus photograph (CFP) or an OCT B-scan image. By contrast, we consider AMD categorization given a multi-modal input, a direction that is clinically meaningful yet mostly unexplored. Contrary to the prior art that takes a traditional approach of feature extraction plus classifier training that cannot be jointly optimized, we opt for end-to-end multi-modal Convolutional Neural Networks (MM-CNN). Our MM-CNN is instantiated by a two-stream CNN, with spatially-invariant fusion to combine information from the CFP and OCT streams. In order to visually interpret the contribution of the individual modalities to the final prediction, we extend the class activation mapping (CAM) technique to the multi-modal scenario. For effective training of MM-CNN, we develop two data augmentation methods. One is GAN-based CFP/OCT image synthesis, with our novel use of CAMs as conditional input of a high-resolution image-to-image translation GAN. The other method is Loose Pairing, which pairs a CFP image and an OCT image on the basis of their classes instead of eye identities. Experiments on a clinical dataset consisting of 1,094 CFP images and 1,289 OCT images acquired from 1,093 distinct eyes show that the proposed solution obtains better F1 and Accuracy than multiple baselines for multi-modal AMD categorization. Code and data are available at https://github.com/li-xirong/mmc-amd.

Prognostic value of antitumor drug targets prediction using integrated bioinformatic analysis for immunogenic cell death-related lncRNA model based on stomach adenocarcinoma characteristics and tumor immune microenvironment.

Stomach adenocarcinoma (STAD) ranks as the fourth prevalent cause of mortality worldwide due to cancer. The prognosis for those suffering from STAD was bleak. Immunogenic cell death (ICD), a form of induced cellular death that causes an adaptive immune response and has increasing in anticancer treatment. However, it has not been ascertained how ICD-related lncRNAs affect STAD. Using univariate Cox regression and the TCGA database, lncRNAs with prognostic value were identified. Thereafter, we created a prognostic lncRNA-based model using LASSO. Kaplan-Meier assessment, time-dependent receiver operating characteristic (ROC) analyzation, independent prognostic investigation, and nomogram were used to assess model correctness. Additional research included evaluations of the immunological microenvironment, gene set enrichment analyses (GSEA), tumor mutation burdens (TMBs), tumor immune dysfunctions and exclusions (TIDEs), and antitumor compounds IC50 predictions. We found 24 ICD-related lncRNAs with prognostic value via univariate Cox analysis (p < 0.05). Subsequently, a risk model was proposed using five lncRNAs relevant to ICD. The risk signature, correlated with immune cell infiltration, had strong predictive performance. Individuals at low-risk group outlived those at high risk (p < 0.001). An evaluation of the 5-lncRNA risk mode including ROC curves, nomograms, and correction curves confirmed its predictive capability. The findings of functional tests revealed a substantial alteration in immunological conditions and the IC50 sensitivity for the two groups. Using five ICD-related lncRNAs, the authors developed a new risk model for STAD patients that could predict their cumulative overall survival rate and guide their individual treatment.

One-pot freezing-thawing preparation of cellulose nanofibrils reinforced polyvinyl alcohol based ionic hydrogel strain sensor for human motion monitoring.

Ionic conductive hydrogels have been widely applied in sensors, energy storage and soft electronics recently. However, most of the polyvinyl alcohol (PVA) based ionic hydrogels are mainly fabricated by soaking the hydrogels in high concentration electrolyte solution which can induce the waste of electrolyte and solvent. Herein, we have designed cellulose nanofibrils (CNF) and ZnSO4 reinforced PVA based hydrogels through a one-pot simple freezing-thawing method at low ZnSO4 concentration without any soaking process. Furthermore, the hydrogel with 0.4% CNF exhibited stress up to 0.79 MPa (242% strain) and high ionic conductivity of 0.32 S m-1 (0.07 M ZnSO4). Moreover, hydrogel sensor displayed high linear gauge factor 1.70 (0-200% strain), excellent stability, durability and reliability. The integrated hydrogel sensor also showed excellent sensor performance for human motion monitoring. This work provides a new prospect for the design of cellulose reinforced conductive hydrogels via a facile method.

Stereoscopic vs. monoscopic photographs on optic disc evaluation and glaucoma diagnosis among general ophthalmologists: A cloud-based real-world multicenter study.

Purpose: To investigate whether stereoscopic vs. monoscopic viewing condition influences the evaluation of optic disc photographs for morphologic features and glaucoma likelihood in a general ophthalmologist population from multicenters on a cloud-based platform. Methods: A cross-sectional study of 519 pairs of stereoscopic and monoscopic photographs of optic discs with adequate quality were selected and presented using a cloud-based platform. A total of 21 general ophthalmologists from 14 centers assessed 15 morphologic features based on 5R's rules and estimated glaucoma likelihood for each assigned photograph. There were 93 pairs of stereoscopic and monoscopic photographs evaluated by a panel of glaucoma specialists and set as ground truth. The main outcome measures were the agreement between estimates and ground truth and the inter-grader agreements. Results: There were good agreements between ground truth and both monoscopic and stereoscopic estimates (stereo κ 0.532 and mono κ 0.494). There was also a substantial intra-grader agreement between monoscopic and stereoscopic evaluation of glaucoma likelihood (κ 0.636). In eyes with probable glaucoma, the accuracy of the stereo method was greater than that of the mono method (stereo 0.238 vs. mono 0.118) When compared with ground truth, stereoscopic photographs had a better agreement for disc size (stereo κ 0.447 vs. mono κ 0.183), disc color (stereo κ 0.612 vs. mono κ 0.549), neuroretinal rim shape (stereo κ 0.356 vs. mono κ 0.274) on the whole. The stereoscopic method also had a better inter-grade agreement for disc size, disc color, neuroretinal rim shape, and glaucoma likelihood (stereo κ 0.402 vs. mono κ 0.359) on the whole. Conclusions: In the evaluation of optic disc photographs for morphologic features and glaucoma likelihood, the stereoscopic method showed superiority compared to the monoscopic method for general ophthalmologists. The stereoscopic method is more likely to identify glaucomatous eyes which need medical intervention.