Exercise to socialize? Bidirectional relationships between physical activity and loneliness in middle-aged and older American adults

Physical inactivity and loneliness are both associated with health risks and can affect each other through various social and behavioral mechanisms. However, current evidence on this relationship is equivocal and mostly based on cross-sectional data. This longitudinal study aims to determine whether current levels of physical activity (moderate- and vigorous-intensity) and loneliness are associated with future respective states of themselves and each other. Data from waves 6-14 (2002-2018) of the Health and Retirement Study were used (n=20,134) in a mixed-effects and random intercept cross-lagged panel model. Analysis showed that current loneliness and physical activity were associated with each future respective state. Additionally, weekly participation in moderate-intensity, but not vigorous-intensity, physical activity was associated with a lower likelihood of becoming lonely in the future (RR: 0.94; 95% CI: 0.90-0.99). However, changes in physical activity were not associated with deviation from a person's typical level of loneliness (vigorous-intensity mean deviation (MD): 0.00; 95% CI: -0.04-0.03, moderate-intensity MD: 0.01; 95% CI: -0.03-0.04). Loneliness was not associated with moderate- or vigorous-intensity physical activity in subsequent waves. This suggests that while lower physical activity levels can be associated with future loneliness, changing levels of physical activity has little impact on loneliness at the individual level.

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 ∼ 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.

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.

Reliability and validity testing of the ASSIST functional performance index

Reliability and validity testing of the ASSIST Functional Performance Index (AFPI) was conducted, focusing on persons with physical disabilities (PwPD). The AFPI was iteratively developed to assess persons' needs for Mainstream Smart Home Technologies (MSHT) as Assistive Technology (AT) and to measure the impact of a service delivery model for MSHT. The AFPI consists of 46 items organized by functional domains. A total of N = 22 PwPD completed the AFPI twice. The median response time between these two time points was four days. Test-retest reliability of overall scores was assessed using the Intraclass Correlation Coefficient model (ICC, 3.1). The weighted kappa coefficient was applied to conduct an item analysis, demonstrating moderate to substantial agreement in all but one of the items. During the second administration, validity was established by correlating the number of hours of assistance and total AFPI scores with the SCI-FI Self-Care and Basic Mobility Short Form Questionnaires. Results indicate that the AFPI demonstrates good to very good validity as an assessment tool and outcome measure in recommending and evaluating the impact of MSHT for PwPD. Future studies, including more participants and persons with cognitive and sensory disabilities, may further establish the clinical utility of the AFPI.

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 P₁₀C_0.4T₈-Fe₂(SO₄)₃ (PVA_10%CNF_0.4%TA_8%-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.

[Soybean isoflavones alleviate cerebral ischemia/reperfusion injury in rats by inhibiting ferroptosis and inflammatory cascade reaction]

OBJECTIVE

To explore the mechanism that mediates the effect of soybean isoflavones (SI) against cerebral ischemia/reperfusion (I/R) injury in light of the regulation of regional cerebral blood flow (rCBF), ferroptosis, inflammatory response and blood-brain barrier (BBB) permeability.

METHODS

A total of 120 male SD rats were equally randomized into sham-operated group (Sham group), cerebral I/R injury group and SI pretreatment group (SI group). Focal cerebral I/R injury was induced in the latter two groups using a modified monofilament occlusion technique, and the intraoperative changes of real-time cerebral cortex blood flow were monitored using a laser Doppler flowmeter (LDF). The postoperative changes of cerebral pathological morphology and the ultrastructure of the neurons and the BBB were observed with optical and transmission electron microscopy. The neurological deficits of the rats was assessed, and the severities of cerebral infarction, brain edema and BBB disruption were quantified. The contents of Fe²⁺, GSH, MDA and MPO in the ischemic penumbra were determined with spectrophotometric tests. Serum levels of TNF-α and IL-1βwere analyzed using ELISA, and the expressions of GPX4, MMP-9 and occludin around the lesion were detected with Western blotting and immunohistochemistry.

RESULTS

The rCBF was sharply reduced in the rats in I/R group and SI group after successful insertion of the monofilament. Compared with those in Sham group, the rats in I/R group showed significantly increased neurological deficit scores, cerebral infarction volume, brain water content and Evans blue permeability (P < 0.01), decreased Fe²⁺ level, increased MDA level, decreased GSH content and GPX4 expression (P < 0.01), increased MPO content and serum levels of TNF-α and IL-1β (P < 0.01), increased MMP-9 expression and lowered occludin expression (P < 0.01). All these changes were significantly ameliorated in rats pretreated with IS prior to I/R injury (P < 0.05 or 0.01).

CONCLUSION

SI preconditioning reduces cerebral I/R injury in rats possibly by improving rCBF, inhibiting ferroptosis and inflammatory response and protecting the BBB.

The Joint Effect of Body Mass Index and Serum Lipid Levels on Incident Dementia among Community-Dwelling Older Adults

OBJECTIVES

This study aimed to explore the joint effect of body mass index (BMI) and serum lipids levels on incident dementia.

METHODS

We prospectively followed up with 1,627 dementia-free community residents aged ≥60 for 5.7 years on average. At baseline, weight, and height were measured, and total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were detected in serum. Demographic characteristics were collected through questionnaires. Dementia was based on consensus diagnosis of neurologists and neuropsychologists using DSM-IV criteria. Additive Cox proportional model was used to assess the exposure-response relationship between BMI and serum lipid levels and dementia risk. Interactions and further classifications of BMI and serum lipid levels were further presented by bivariate surface models and decision-tree models.

RESULTS

The joint effects of TC with BMI, TG with BMI, and LDL-C with BMI on the risk of incident dementia shared a similar pattern, different from their independent exposure-response curves. The joint effect of HDL-C with BMI showed an S-surface but without statistical significance. Participants with TC<5.4 mmol/L and BMI<21 kg/m2 (Hazard Ratio(HR) 1.93, 95% Confidence Interval (CI) 1.05-3.53), TC<5.4 mmol/L and BMI≥21 kg/m2 (HR 1.73, 95% CI 1.09-2.72), and TC≥5.4 mmol/L and BMI<21 kg/m2 (HR 4.02, 95% CI 2.10-7.71) were identified to have the increased risk of incident dementia compared to those with TC≥5.4 mmol/L and BMI≥21 kg/m2. Participants with TG<1.7 mmol/L and BMI<21 kg/m2 had an increased risk of incident dementia compared to those with TG≥1.7 mmol/L and BMI≥21 kg/m2 (HR 1.98, 95%CI 1.17-3.3). Participants with LDL-C≥3.3 mmol/L and BMI<21 kg/m2 were identified to have an increased risk of incident dementia compared to those with LDL-C≥3.3 mmol/L and BMI≥21 kg/m2 (HR 3.33, 95%CI 1.64-6.78).

CONCLUSIONS

Our study showed that low BMI combined with low or high levels of serum lipids may increase the risk of dementia among older adults. This finding suggests the potential impacts of these two metabolic indexes on the risk of dementia.

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.

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.

Diagnostic performance of on-site computation of quantitative flow ratio by a coronary computed tomography angiography based algorithm: comparison of distal and lesion-specific measurements

Introduction

Guidelines recommend secondary ischemia assessment following a coronary computed tomography angiography (CTA) with suspected obstructive coronary artery disease (CAD). Coronary CTA-derived quantitative flow ratio (CT-QFR) is an on-site technique performed on acquired CTA images that estimates the functional severity of a coronary stenosis. However, CT-QFR measurements are available throughout the coronary vessel with no clear recommendations as to which specific values should be used for identifying obstructive CAD, e.g. most distal or lesion-specific values.

Purpose

First, to investigate the feasibility of CT-QFR and the correlation and agreement with invasive fractional flow reserve (FFR). Secondly, to compare the diagnostic performance of distal versus lesion-specific CT-QFR for identifying obstructive CAD defined by invasive coronary angiography (ICA) with FFR.

Methods

A total of 1732 prospectively included patients with symptoms suggestive of CAD referred for CTA were included. All patients with ≥50% diameter stenosis (DS) on CTA were subsequently referred for ICA with conditional FFR in lesions with 30–89%DS. Obstructive CAD was defined by ICA as FFR ≤0.80 or high-grade stenosis by visual assessment (≥90%DS). A blinded analysis of CT-QFR was performed in patients referred to ICA with measurements at the distal end of a vessel (distal CT-QFR) and 1 cm distal to stenotic lesions on CTA (lesion-specific). CT-QFR ≤0.80 was defined as abnormal. For correlation analyses to invasive FFR, CT-QFR was assessed corresponding to the position of the invasive pressure sensor.

Results

In total, 445/1732 (25%) patients had suspected obstructive CAD at CTA and underwent subsequent ICA. CT-QFR analysis was feasible in 423/445 (95%) patients. CT-QFR correlated (Pearson's rho 0.54, p&lt;0.001) and agreed (mean difference –0.02±0.09) to FFR with CT-QFR overestimating FFR (Fig. 1). Obstructive CAD was identified in 190/423 (44%) patients by ICA. Distal and lesion-specific CT-QFR classified 196 (46%) and 171 (40%) patients as abnormal, respectively. Areas under the receiver-operating characteristic curves for distal versus lesion-specific CT-QFR were similar (0.86 (95% CI: 0.82–0.89) vs. 0.86 (0.82–0.90), p=0.80). Sensitivities for distal and lesion-specific CT-QFR were 78% (95% CI: 71–84) vs. 74% (67–80), p=0.01, respectively, and specificities 79% (95% CI: 74–84) vs. 87% (82–91), p&lt;0.01, respectively. Distal and lesion-specific CT-QFR had similar diagnostic accuracy (79 (95% CI: 75–83), vs. 81 (77–85), p=0.07) (Fig. 2).

Conclusion

In patients with suspected obstructive CAD on CTA, non-invasive estimation of FFR using CT-QFR is feasible with moderate correlation and good agreement with invasive FFR. Overall diagnostic performance of distal and lesion-specific values for discriminating obstructive CAD by invasive FFR are similar. The use of CT-QFR could therefore potentially reduce the need for referral to invasive angiography after CTA.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): Aarhus UniversityRegion Mid Jutland

Comparison of second-line on-site computed quantitative flow ratio from coronary computed tomography angiography to PET perfusion imaging for detecting obstructive coronary artery disease

Introduction

In patients with suspected obstructive coronary artery disease (CAD) on coronary computed tomography (CTA), guidelines endorse second-line selective testing for hemodynamic evaluation of suspected CAD. A variety of non-invasive modalities are available, and myocardial perfusion imaging with Rubidium-82 positron emission tomography (PET) is an established method with high diagnostic performance. Recently, an on-site method estimating computed tomography-derived quantitative flow ratio (CT-QFR) showed promising results for discriminating obstructive CAD. However, no study has compared the diagnostic performances of PET and CT-QFR.

Purpose

To assess a possible non-inferiority of CT-QFR compared to PET in patients with suspected obstructive CAD at CTA using invasive coronary angiography (ICA) with fractional flow reserve (FFR) as reference.

Methods

Patients (n=1732, 57% males, age 59±9.5) referred on a clinical indication with symptoms suggestive of obstructive CAD underwent routine CTA. Patients with ≥50% diameter stenosis (DS) on CTA were referred for PET and subsequent ICA with FFR. CT-QFR was analyzed post-hoc blinded to PET and ICA results.

Abnormal CT-QFR was defined as CT-QFR ≤0.80 in any vessel with a diameter ≥1.5mm. An independent core-lab evaluated PET scans as abnormal/normal with optional analyst-dependent application of pre-specified criteria; summed stress score of ≥4 in ≥2 contiguous segments, vessel-specific myocardial blood flow (MBF) &lt;2.00 ml/g/min, global myocardial blood flow reserve ≤1.8, and/or transient ischemic dilatation ratio &gt;1.13. Obstructive CAD was defined as ICA with FFR ≤0.80 or high-grade stenosis (≥90% DS).

Results

In total, 445/1732 patients (25%) had suspected obstructive CAD on CTA of whom 400/445 patients (90%) underwent subsequent PET and ICA. CT-QFR was successfully analysed in 383/400 (96%) patients classifying 174/383 (45%) patients as having disease. In comparison, PET classified 130/383 (34%) patients as having disease. In total, obstructive CAD by ICA with FFR was identified in 162 (42%) patients.

There was no significant difference in area under the receiver-operating characteristic curves for CT-QFR compared to the best performing PET metric (lowest vessel-specific MBF); 0.84 (95% CI 0.80–0.89) vs. 0.81 (0.77–0.85), p=0.19)) (Fig. 1). Overall diagnostic accuracy of CT-QFR versus PET was similar (78% (95% CI 74–82) vs. 77% (72–81), p=0.70. Sensitivities for CT-QFR and PET were 78% (71–84) and 63% (55–70), p&lt;0.01, respectively, and specificities 78% (72–84) and 87% (82–91), p=0.01, respectively (Fig. 2). Three-vessel or left main disease on ICA was correctly identified in 30/31 patients by both CT-QFR and PET.

Conclusion

In patients with suspected obstructive CAD by CTA, second-line CT-QFR was non-inferior to PET for discriminating obstructive CAD by invasive FFR; Although diagnostic accuracy was similar, CT-QFR demonstrated higher sensitivity while PET showed higher specificity

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): Aarhus University PhD fellowshipRegion Mid Health Research Foundation

Murray law-based quantitative flow ratio for assessment of left main bifurcation derived from a single fluoroscopic angiographic view as compared to FFRCT

Background

In patients with complex CAD, the presence of left main (LM) disease is an important prognostic factor in assessing the risk balance between PCI and CABG. Functional assessment has become standard of care to evaluate the significance of coronary stenosis and to justify the performance of PCI in the contemporary practice. FFRCT is a well-established method based on 3D reconstruction of coronary artery derived from CCTA. The Murray law-based quantitative flow reserve (μQFR) is a novel computational method of invasive angiography relying on a single angiographic view that takes into account side branches diameters to compute fractal flow division. The aim of the current analysis is to evaluate in patients with complex CAD the feasibility of μQFR in LM bifurcation and its diagnostic concordance with FFRCT. The impact of the optimal viewing angle defined by CCTA on the physiological assessment of the LM bifurcation using a single angiographic view was also evaluated.

Methods

In 299 consecutive patients with 3-vessel disease with or without LM coronary artery disease, up to 3 analyzable fluoroscopic projections per patient were analysed with μQFR retrospectively. FFRCT and μQFR were measured at 3 fiducial landmark points: i) point of LM bifurcation (POB); ii) proximal LAD 10 mm distal to POB; ii) proximal LCX 10 mm distal to POB. CCTA-based “optimal viewing angle” of LM bifurcation are computed by creating a 3-point closed spline involving the LM, LAD, and LCX at 5mm from the POB and subsequently by reconstructing the “en face” fluoroscopic viewing angle of the spline. The en face viewing angle provides an optimal assessment of the bifurcation geometry [1]. In terms of Rx gantry angulation, the closest angiographic projection to the optimal viewing angle derived from CCTA was defined as the “best fluoroscopic projection” for each patient.

Results

In 299 patients, 793 projections were analysed with μQFR and compared to FFRCT. Single view μQFR was analyzable in 100%. Correlation and agreement between μQFR and FFRCT for 793 projections in 299 patients are shown in Figure 1A, 2A. The Spearman's correlation coefficient showed moderate correlations at POB (r=0.481, p&lt;0.001) and LCX (r=0.584, p&lt;0.001), and strong correlation at LAD (r=0.642, p&lt;0.001). Correlation and agreement between μQFR and FFRCT for best projections from each patient are shown in Figure 1B, 2B. Correlations were improved in the best projections with the following Spearman's correlation coefficient: at POB (r=0.522, p&lt;0.001), LCX (r=0.622, p&lt;0.001), and LAD (r=0.695, p&lt;0.001).

Conclusion

Computation of μQFR from a single angiographic view has a high feasibility. Tailored optimal fluoroscopic view is essential for the physiological assessment of the LM bifurcation using a single angiographic view. Evaluation of diagnostic accuracy of μQFR warrants further analysis of the LMCAD after prospective planning of the optimal fluoroscopic view based on the selection of the best CCTA 3D view.

Funding Acknowledgement

Type of funding sources: None.

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.

An Artificial-Intelligence-Based Automated Grading and Lesions Segmentation System for Myopic Maculopathy Based on Color Fundus Photographs

Purpose

To develop deep learning models based on color fundus photographs that can automatically grade myopic maculopathy, diagnose pathologic myopia, and identify and segment myopia-related lesions.

Methods

Photographs were graded and annotated by four ophthalmologists and were then divided into a high-consistency subgroup or a low-consistency subgroup according to the consistency between the results of the graders. ResNet-50 network was used to develop the classification model, and DeepLabv3+ network was used to develop the segmentation model for lesion identification. The two models were then combined to develop the classification-and-segmentation–based co-decision model.

Results

This study included 1395 color fundus photographs from 895 patients. The grading accuracy of the co-decision model was 0.9370, and the quadratic-weighted κ coefficient was 0.9651; the co-decision model achieved an area under the receiver operating characteristic curve of 0.9980 in diagnosing pathologic myopia. The photograph-level F₁ values of the segmentation model identifying optic disc, peripapillary atrophy, diffuse atrophy, patchy atrophy, and macular atrophy were all >0.95; the pixel-level F₁ values for segmenting optic disc and peripapillary atrophy were both >0.9; the pixel-level F₁ values for segmenting diffuse atrophy, patchy atrophy, and macular atrophy were all >0.8; and the photograph-level recall/sensitivity for detecting lacquer cracks was 0.9230.

Conclusions

The models could accurately and automatically grade myopic maculopathy, diagnose pathologic myopia, and identify and monitor progression of the lesions.

Translational Relevance

The models can potentially help with the diagnosis, screening, and follow-up for pathologic myopic in clinical practice.

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.

The Role and Application of Exosomes in Gastric and Colorectal Cancer

Gastric cancer and colorectal cancer are malignant tumors found in the human gastrointestinal tract. Bidirectional communication between tumor cells and their microenvironment can be realized through the transmission of exosomes—small, cell-derived vesicles containing complex RNA and proteins. Exosomes play an important role in the proliferation, metastasis, immune response, and drug resistance of cancer cells. In this review, we focus on the role and application of exosomes in gastric and colorectal cancer. We also summarize the role of exosomes secreted by different types of cells in tumor development and as drug carriers in cancer treatment.

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.

Valorization of Miscanthus × giganteus by γ-Valerolactone/H2O/FeCl3 system toward efficient conversion of cellulose and hemicelluloses

γ-Valerolactone (GVL), a biomass-derived green chemical, offers an environmentally responsible solvent for conversion of lignocellulose to high value-added chemicals. Herein, we report a two-step process for directly producing cellulosic residual, furfural and lignin from Miscanthus × giganteus (M. × giganteus) bypassing the isolation of xylose, which exhibits promising advantage in energy reduction. The optimized pretreatment (100 mM FeCl₃ at 160 °C for 60 min) induced significant xylan removal (98.4%), resulting in rugged fibre surface, thus leading to the peak cellulose conversion of 99.3%. Furfural yield in the second step reached to 76.6% after 100 mM FeCl₃ catalyzed GVL/H₂O treatment at 180 °C for 10 min without addition of any chemical. The extracted lignin showed representative structure (such as β-O-4', β-β' linkages) and medium molecular weight (4275.5 g/mol). 79.6% of furfural can be recovered by distillation. This study proposes a systematic and energy efficient approach for maximizing biomass utilization.

An Optical Coherence Tomography-Based Deep Learning Algorithm for Visual Acuity Prediction of Highly Myopic Eyes After Cataract Surgery

Background

Due to complicated and variable fundus status of highly myopic eyes, their visual benefit from cataract surgery remains hard to be determined preoperatively. We therefore aimed to develop an optical coherence tomography (OCT)-based deep learning algorithms to predict the postoperative visual acuity of highly myopic eyes after cataract surgery.

Materials and Methods

The internal dataset consisted of 1,415 highly myopic eyes having cataract surgeries in our hospital. Another external dataset consisted of 161 highly myopic eyes from Heping Eye Hospital. Preoperative macular OCT images were set as the only feature. The best corrected visual acuity (BCVA) at 4 weeks after surgery was set as the ground truth. Five different deep learning algorithms, namely ResNet-18, ResNet-34, ResNet-50, ResNet-101, and Inception-v3, were used to develop the model aiming at predicting the postoperative BCVA, and an ensemble learning was further developed. The model was further evaluated in the internal and external test datasets.

Results

The ensemble learning showed the lowest mean absolute error (MAE) of 0.1566 logMAR and the lowest root mean square error (RMSE) of 0.2433 logMAR in the validation dataset. Promising outcomes in the internal and external test datasets were revealed with MAEs of 0.1524 and 0.1602 logMAR and RMSEs of 0.2612 and 0.2020 logMAR, respectively. Considerable sensitivity and precision were achieved in the BCVA < 0.30 logMAR group, with 90.32 and 75.34% in the internal test dataset and 81.75 and 89.60% in the external test dataset, respectively. The percentages of the prediction errors within ± 0.30 logMAR were 89.01% in the internal and 88.82% in the external test dataset.

Conclusion

Promising prediction outcomes of postoperative BCVA were achieved by the novel OCT-trained deep learning model, which will be helpful for the surgical planning of highly myopic cataract patients.

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.

IL-8, MSPa, MIF, FGF-9, ANG-2 and AgRP collection were identified for the diagnosis of colorectal cancer based on the support vector machine model

Colorectal cancer (CRC) is one of the most common cancer, and the early detection of CRC is essential to improve the survival rate of patients. To identify diagnostic markers for colorectal cancer (CRC) by screening differentially expressed proteins (DEPs) in CRC. The DEPs were initially obtained from 12 CRC samples and 12 healthy control samples, and verification analysis was performed in another 34 CRC samples and 34 normal controls. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment with DEPs was analyzed by the R package clusterProfiler (Version 3.2.11), and the DEP-associated protein-protein interaction (PPI) network was created from the STRING database. Additionally, Support Vector Machine (SVM) model prediction and survival analyses were conducted on the key DEPs. Preliminary screening and functional analysis showed that the DEPs mainly overrepresented in pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, Rap1, Ras, and MAPK signaling pathways. The key DEPs, including AgRP, ANG-2, Dtk, EOT3, FGF-4, FGF-9, HCC-4, IL-16, IL-8, MIF, MSPa, TECK, TPO, TRAIL R3, and VEGF-D, were used to construct a custom chip. The drug-gene interaction network suggested that TPO was a key drug target. ROC curve showed the SVM diagnostic model with the DEPs IL-8, MSPa, MIF, FGF-9, ANG-2, and AgRP had better diagnostic performance with an AUC of 0.933. Survival analysis showed the expression of FGF9, TPO, TRAIL R3, Dtk, TECK and FGF4 were associated with prognosis. This study revealed the important serum proteins in the pathogenesis of CRC, which might serve as useful and noninvasive predictors for the diagnosis of CRC.

Development and evaluation of a deep learning model for the detection of multiple fundus diseases based on colour fundus photography

AIM

To explore and evaluate an appropriate deep learning system (DLS) for the detection of 12 major fundus diseases using colour fundus photography.

METHODS

Diagnostic performance of a DLS was tested on the detection of normal fundus and 12 major fundus diseases including referable diabetic retinopathy, pathologic myopic retinal degeneration, retinal vein occlusion, retinitis pigmentosa, retinal detachment, wet and dry age-related macular degeneration, epiretinal membrane, macula hole, possible glaucomatous optic neuropathy, papilledema and optic nerve atrophy. The DLS was developed with 56 738 images and tested with 8176 images from one internal test set and two external test sets. The comparison with human doctors was also conducted.

RESULTS

The area under the receiver operating characteristic curves of the DLS on the internal test set and the two external test sets were 0.950 (95% CI 0.942 to 0.957) to 0.996 (95% CI 0.994 to 0.998), 0.931 (95% CI 0.923 to 0.939) to 1.000 (95% CI 0.999 to 1.000) and 0.934 (95% CI 0.929 to 0.938) to 1.000 (95% CI 0.999 to 1.000), with sensitivities of 80.4% (95% CI 79.1% to 81.6%) to 97.3% (95% CI 96.7% to 97.8%), 64.6% (95% CI 63.0% to 66.1%) to 100% (95% CI 100% to 100%) and 68.0% (95% CI 67.1% to 68.9%) to 100% (95% CI 100% to 100%), respectively, and specificities of 89.7% (95% CI 88.8% to 90.7%) to 98.1% (95%CI 97.7% to 98.6%), 78.7% (95% CI 77.4% to 80.0%) to 99.6% (95% CI 99.4% to 99.8%) and 88.1% (95% CI 87.4% to 88.7%) to 98.7% (95% CI 98.5% to 99.0%), respectively. When compared with human doctors, the DLS obtained a higher diagnostic sensitivity but lower specificity.

CONCLUSION

The proposed DLS is effective in diagnosing normal fundus and 12 major fundus diseases, and thus has much potential for fundus diseases screening in the real world.

A two-in-one Janus NIR-II AIEgen with balanced absorption and emission for image-guided precision surgery

Fluorescence imaging in the near-infrared II (NIR-II, 1000-1700 nm) region opens up new avenues for biological systems due to suppressed scattering and low autofluorescence at longer-wavelength photons. Nonetheless, the development of organic NIR-II fluorophores is still limited mainly due to the shortage of efficient molecular design strategy. Herein, we propose an approach of designing Janus NIR-II fluorophores by introducing electronic donors with distinct properties into one molecule. As a proof-of-concept, fluorescent dye 2 TT-m, oC6B with both twisted and planar electronic donors displayed balanced absorption and emission which were absent in its parent compound. The key design strategy for Janus molecule is that it combines the merits of intense absorption from planar architecture and high fluorescence quantum yield from twisted motif. The resulting 2 TT-m, oC6B nanoparticles exhibit a high molar absorptivity of 1.12 ⨯104 M-1 cm-1 at 808 nm and a NIR-II quantum yield of 3.7%, displaying a typical aggregation-induced emission (AIE) attribute. The highly bright and stable 2 TT-m, oC6B nanoparticles assured NIR-II image-guided cancer surgery to resect submillimeter tumor nodules. The present study may inspire further development of molecular design philosophy for highly bright NIR-II fluorophores for biomedical applications.

Genomic Signature of Mismatch Repair Deficiency in Areca Nut-Related Oral Cancer

Areca nut (AN) chewing contributes to an increase of oral squamous cell carcinoma (OSCC) cases in South and Southeast Asia; however, genomic events underlying the carcinogenesis process of AN-related OSCC remain unclear. Here, we comprehensively describe the genomic and transcriptome alterations of 113 Chinese OSCC patients (89 AN related and 24 AN negative) by whole-exome sequencing and RNA sequencing, and we compared the genomic differences between AN-related and AN-negative samples by integrating sequencing data of 325 OSCC patients from The Cancer Genome Atlas database and 50 from a published Taiwanese study. We identified 11 significantly mutated genes for OSCC, including 4 novel ones (ATG2A, WEE1, DST, and TSC2), of which WEE1 and ATG2A mutated with significantly higher rates in AN-related samples (P = 0.04 and P = 0.003, respectively). Mutational signature analysis revealed that AN-related OSCCs were specially characterized by the genomic signature of mismatch repair deficiency (dMMR), which could also predict the prognosis status of AN-related OSCC. In addition, an elevated PD-L1 expression was also observed in both AN-related patients (P = 3.71 × 10^-11) and those with a high dMMR level (P = 1.99 × 10^-4). Further differential expression analysis and in vitro experiments confirmed the role of dMMR in the development of OSCC induced by AN exposure. Taken together, this study first revealed the molecular profiles and highlighted the role of dMMR in AN-related OSCC among the Chinese population and identified that AN-related OSCC may represent a potential cohort for effective anti-PD-1/L1 immunotherapy.

Automated diagnoses of age-related macular degeneration and polypoidal choroidal vasculopathy using bi-modal deep convolutional neural networks

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.

Prediction of OCT images of short-term response to anti-VEGF treatment for neovascular age-related macular degeneration using generative adversarial network

BACKGROUND/AIMS

The 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).

METHODS

A 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.

RESULTS

We 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).

CONCLUSION

Our results revealed a great potential of GAN to generate post-therapeutic OCT images with both good quality and high accuracy.

MicroRNA‑3651 promotes colorectal cancer cell proliferation through directly repressing T‑box transcription factor 1

Colorectal cancer is a commonly diagnosed gastrointestinal malignancy worldwide with a high mortality rate. Accumulating evidence has indicated that the expression of a number of microRNAs (miRNAs) is associated with the development of colorectal cancer. However, the precise molecular mechanism of these miRNAs in regulating cancer progression is yet to be determined. In the present study, miR‑3651 was demonstrated to be overexpressed in colorectal cancer tissues compared with normal tissues, and to be associated with the tumor‑node‑metastasis stage. The downregulation of miR‑3651 was found to induce growth arrest and apoptosis in colorectal cancer cells. In addition, western blot analysis demonstrated that the downregulation of miR‑3651 inactivated PI3K/AKT and MAPK/ERK signaling in colorectal cancer cells. Bioinformatics analysis predicted T‑box transcription factor 1 (TBX1) as a potential target gene of miR‑3651, and a dual‑luciferase reporter assay confirmed that TBX1 was directly repressed by miR‑3651. The results of the current study also indicated that TBX1 was associated with the miR‑3651 mediated activation of oncogenic signaling and colorectal cancer cell proliferation. In conclusion, the results of the current study revealed the oncogenic potential of miR‑3651 in colorectal cancer.

P202 Are Chinese immigrants with CVD ready to use web-based health information: a comparative study in Australia

Background

Immigrant populations often have poor access to cardiovascular disease (CVD) secondary prevention due to linguistic and cultural barriers. Web-based interventions are effective in risk reduction and lifestyle modification and may reach those hard-to-reach populations such as Chinese immigrants. However, less is known about the current use of web-based health information and confidence in use.

Purposes

We compared the use of web-based health information and confidence in use between Chinese immigrants with CVD to those with and without another chronic condition; and explored the factors associated with the confidence in utilization.

Methods

Chinese immigrants with CVD, musculoskeletal conditions, or no chronic condition were recruited from Chinese communities across New South Wales, Australia. E-health literacy scale was used to explore the perceptions of web-based health information and confidence in use. Demographic, clinical data and use of web-based health information were collected and health literacy was measured using a validated single screening question.

Results

Participants (n = 90 CVD, n = 87 musculoskeletal, n = 154 no chronic conditions) were aged mean 59 ± 16 years, mostly female (69%), 75% reported fair to poor English proficiency, and 51% had completed university. The most accessed web-based health information concerned lifestyle (60%), health resources (45%), diseases (35%), and medications (30%). More than half (54%) were confident in using web-based health information.

Participants with CVD were the oldest (71 vs 65 vs 49 years, p&lt;.001) and participants with any chronic condition had less education (p&lt;.001) and English proficiency (p&lt;.001) than the healthy group. Approximately half of the participants with CVD perceived web-based health information as useful (48%) and important (46%), and the most accessed information concerned lifestyle and medication (56% and 32%). Participants with CVD accessed medication information more often than musculoskeletal group (32% vs 23%), but there was no difference in accessing other information. Both chronic groups showed no difference in accessing web-based medication and lifestyle information compared with the healthy group. Confidence in using web-based health information was similar for CVD and musculoskeletal groups and lower than the healthy group (p&lt;.001).

Participants with the least confidence to use web-based health information were older (p=.016), female (p=.014), had less than university level education (p&lt;.001), and lower health literacy (p=.001) after adjusting for age, gender, education, English proficiency, employment status, social support, health literacy, and number of chronic conditions.

Conclusions

There is a strong potential to provide web-based medication and lifestyle information for Chinese immigrants with CVD if support is provided to improve confidence in this technology for older, women, and those with less education and/or health literacy.

[Role of a liver pathology standardized scoring system in the diagnosis of congenital biliary atresia and its relationship with prognosis]

Objective: To evaluate the diagnostic value of a histologic scoring system in congenital biliary atresia and its prognostic relevance. Methods: From January 2017 to June 2018 at Children's Hospital of Fudan University, 172 wedge liver biopsy specimens were obtained from infants with neonatal cholestasis [119 patients with congenital biliary atresia (CBA) and 53 patients with non-obstructive cholestasis as control]. A pathologist, single-blinded to the final diagnosis, made the histological diagnosis individually based on an 8-feature (portal ductal proliferation, bile duct reaction, bile plugs in portal ductules, liver fibrosis, edema in portal region, cholestasis, inflammatory cells infiltration in portal region, and ductal plate malformation), 21-point scoring system. Results: The main pathologic changes of biliary atresia were hepatocyte cholestasis, hyperplasia of bile ducts, fibrosis and infiltration of inflammatory cells in the portal area. There were significant difference in the degree of portal edema, bile duct hyperplasia and fibrosis between two groups (P<0.01). In addition, there were characteristic bile duct thrombosis in 97.5%(116/119) of the cases and abnormal development of bile duct plate in 9.2%(11/119) of the cases. Compared with non-CBA infant cholestasis group, the difference was statistically significant (P<0.05). The scoring system has high sensitivity, specificity (both 94.1%) and accuracy (94.3%) in the diagnosis of CBA. A score equal to or more than 11 points supported a diagnosis of CBA; whereas a score less than 11 points might suggest cholestasis. The degree of hepatic fibrosis and ductal plate malformation were related to prognosis. Conclusions: The liver pathology scoring system (8-feature, 21-point) is more accurate in diagnosing CBA than previous methods, which may guide the clinicopathological diagnosis. This histological scoring system also helps to assess the prognosis of CBA.

Effect of insulin-like growth factor-1 on promoting healing of skin ulcers in diabetic rats

To investigate the effect of exogenous insulin-like growth factor-1 (IGF-1) on the healing of skin ulcers in diabetic rats, male Sprague Dawleys (SD) rats with back skin ulcers were selected and divided into control group, model group and IGF-1 treatment group which received different doses of IGF-1 (0.5, 1.0, 1.5, and 2.0mg/L). The results showed that the healing speed of the skin ulcers was significantly affected by IGF-1, which reduced the size of wound (P less than 0.05). The expression of MMP-9 was enhanced while the expression of TIMP-1 was decreased in diabetic rats with skin ulcers. The IGF-1 treatment helped to re¬store the normal expression of both MMP-9 and TIMP-1 in diabetic rats with skin ulcers, and diabetic skin ulcers in the 1.5 mg/L IGF-1 group showed the best healing. Histological examination showed that after 20 days, fibroblasts in the IGF-1 experimental group with an appropriate concentration increased and the numbers of fibroblasts and capillaries were significantly higher than those of the other groups. Moreover, there were obvious wound surface contractions and re-epithelialization, and the new epithelium moved to the center of the wound faster. Therefore, it is concluded that an appropriate concentration of IGF-1 can significantly promote the healing of skin ulcers in diabetic rats.

Synergy of hemicelluloses removal and bovine serum albumin blocking of lignin for enhanced enzymatic hydrolysis

A cost efficient synergistic strategy combining mild alkaline pretreatment (0.5-5% NaOH at 70 °C for 60 min) and bovine serum albumin (BSA) blocking of lignin was evaluated for effective conversion of poplar. The highest glucose yield of 69.2% was obtained for 5% alkaline pretreated sample, which was 4.4 times that of untreated sample. The enhanced enzymatic hydrolysis was attributed to significant hemicelluloses removal with limited delignification. Delignification mainly occurred in secondary wall, leading to more open cell wall structure, thus facilitating better transport of enzyme. Hemicelluloses removal helped split adjacent microfibrils, thus increased the specific sites for cellulase binding. After BSA addition in enzymatic hydrolysis, cellulose conversion further improved to 78.4% with 33% reduction of cellulase dosage due to decreased non-specific adsorption of cellulase on residual lignin. The utilization of synergistic alkaline pretreatment - BSA strategy may improve the overall economics of biomass conversion and successful commercial implementation of biorefineries.

Comparing two classification schemes for seizures and epilepsy in rural China

BACKGROUND AND PURPOSE

The International League against Epilepsy (ILAE) updated the classifications of seizures and epilepsies in 2017. The 2017 classifications were compared with the 1980s classifications in rural China.

METHODS

People with epilepsy receiving treatment under the National Epilepsy Control Programme were recruited from rural areas in China. Their seizures and epileptic syndrome were classified using the 1980s ILAE classification system and then re-classified according to the 2017 system. Differences in seizure, epilepsy and aetiology classifications were identified.

RESULTS

A total of 597 individuals (58% males, aged 6-78 years) were included. Amongst them 535 (90%) had a single seizure type, 57 (9.55%) had two types and five (0.84%) had three. There was complete agreement between the 1981 and 2017 classifications for the 525 individuals with focal seizures. Seizures originally classified as generalized in 10 of 65 individuals were re-classified as unknown in the 2017 classification. Compared to the 1980s classifications, the proportion of individuals with unknown seizures and unknown epilepsy increased from 1.2% (7/597) to 2.8% (17/597, P = 0.002), and unknown aetiology increased from 32% (189/597: 182 cryptogenic and seven unclassified) to 39% (230/597; P < 0.001) in the 2017 classifications.

CONCLUSIONS

The 1980s and 2017 classifications had 100% agreement in classifying focal seizures and epilepsy in rural China. A small but significant proportion of generalized seizures and epilepsy and aetiologies classified in the old classifications were re-classified to unknown in the new classifications. These results highlight the need for improvement in clinical evaluation of people with epilepsy in resource-poor settings.

[Application of MDCT and post-processing in children with tracheal foreign body]

Objective:To explore the clinical value of MDCT and post-processing in children with suspected foreign body in trachea.Method:Two hundred patients with suspected tracheal foreign body were treated with 64-slice spiral CT (MDCT) and simulated endoscopic imaging,then compared with seen in bronchoscopy; Compare the results of MDCT and post-processing with the coincidence of intraoperative findings.Result:One hundred and eighty-four cases of positive children were examined by MDCT postprocessing technique and bronchoscopy,179 cases were obstructed by exogenous foreign body,5 cases were phlegm thrombosis (endogenous foreign body) obstruction; 16 cases of children with no foreign body diagnosed by MDCT post-processing technique were also examined by bronchoscopy. The results showed that there was a foreign body in 1 case,and the foreign body was located in the pharyngeal cleft (watermelon spermoderm),and the remaining 15 cases had no foreign body. MDCT and post-treatment techniques for children with tracheal foreign body diagnosis of 99.4% sensitivity,specificity of 75%.There was no significant difference in the detection rate of foreign body between the two techniques of MDCT and post-processing technique and bronchoscopy (P>0.05). Examed by MDCT and postprocessing,we can understand the specific location and size of foreign body,nature,shape preoperatively.Conclusion:Although MDCT and post-processing techniques can not be used to treat tracheal foreign bodies,but the diagnostic rate of bronchial foreign bodies is comparable to that of bronchoscopy. We could apply MDCT examination and post processing before the bronchoscopy,for foreign body inhalation history is not clear,or suspected airway foreign body. We can improve the level of diagnosis and treatment through guiding the operation of bronchoscopy focus.

LncRNA H19/miR-29b-3p/PGRN Axis Promoted Epithelial-Mesenchymal Transition of Colorectal Cancer Cells by Acting on Wnt Signaling

This investigation was aimed at working out the combined role of lncRNA H19, miR-29b and Wnt signaling in the development of colorectal cancer (CRC). In the aggregate, 185 CRC tissues and corresponding para-carcinoma tissues were gathered. The human CRC cell lines (i.e. HT29, HCT116, SW480 and SW620) and normal colorectal mucosa cell line (NCM460) were also purchased. Si-H19, si-NC, miR-29b-3p mimics, miR-29b-3p inhibitor, si-PGRN and negative control (NC) were, respectively, transfected into the CRC cells. Lucif-erase reporter plasmids were prepared to evaluate the transduction activity of Wnt/β-catenin signaling pathway, and dual-luciferase reporter gene assay was arranged to confirm the targeted relationship between H19 and miR-29b-3p, as well as between miR-29b-3p and PGRN. Finally, the proliferative and invasive capacities of CRC cells were appraised through transwell, MTT and scratch assays. As a result, over-expressed H19 and down-expressed miR-29b-3p displayed close associations with the CRC patients' poor prognosis (P < 0.05). Besides, transfection with si-H19, miR-29b-3p mimic or si-PGRN were correlated with elevated E-cadherin expression, decreased snail and vimentin expressions, as well as less-motivated cell proliferation and cell metastasis (P < 0.05). Moreover, H19 was verified to directly target miR-29b-3p based on the luciferase reporter gene assay (P < 0.05), and miR-29b-3p also bound to PGRN in a direct manner (P < 0.05). Finally, addition of LiCl (Wnt/β-catenin pathway activator) or XAV93920 (Wnt/β-catenin pathway inhibitor) would cause remarkably altered E-cadherin, c-Myc, vimentin and snail expressions, as well as significantly changed transcriptional activity of β-catenin/Tcf reporter plasmid (P < 0.05). In conclusion, the lncRNA H19/miR-29b-3p/PGRN/Wnt axis counted a great deal for seeking appropriate diagnostic biomarkers and treatment targets for CRC.

Synergetic Dissolution of Branched Xylan and Lignin Opens the Way for Enzymatic Hydrolysis of Poplar Cell Wall

As the main hemicellulose of poplar, the interaction of xylan with lignin was expected to have profound effect on biomass recalcitrance. In this paper, the dynamic changes of xylan and lignin in poplar cell wall during a mild pretreatment using γ-valerolactone (GVL) was investigated using chemical and microscopic techniques. Synergetic dissolution of branched xylan and lignin from the secondary wall of the fiber cell was found to play a major role in opening the cell wall structure for enzymatic attack. In the case of the removal of xylan and lignin reaching a certain level, β-O-4' cleavage of lignin which destroyed its interaction with hydrophobic cellulose face was found to make great contribution to the enhanced enzymatic hydrolysis. The deep understanding of this process could lead to a new insight into the understanding of the plant cell wall architecture and provide basic information for biomass processing.

[Effects of sural nerve nutrition vess els-supported flap for reconstruction of distal lower leg and ankle soft tissue defects]

Objective: To observe the effects of sural nerve nutrition vessels-supported flap for reconstruction of distal lower leg and ankle soft tissue defects. Methods: From June 2014 to June 2017, 37 patients with calf distal and ankle soft tissue defect were repaired with sural nerve nutrition vessels-supported flap, of them 12 cases with calf distal soft tissue defect wounds and 25 cases with ankle soft tissue defect wounds.The scope of flaps was 9 cm×4 cm to 18 cm×9 cm, anti-infection, anti-freezing and dressing treatments were carried out after operation.The results of two-point discrimination among reexamination were recorded. Results: All the flaps survived without ulcer and effusion, only 1 flap for reconstruction of medial malleolus swelled and deactivated at the beginning while it recovered with proper dressings.During the follow-up periods, all the flaps kept favorable feelings, aspects and functions, and the two-point discrimination was 5 to 15 mm [averaged (11.2±1.7) mm]. Conclusion: Sural nerve nutrition vessels-supported flap brings significant effects with excellent safety and reliability in repairing calf and ankle soft tissue defects.

Analysis of (CAG)n expansion in ATXN1, ATXN2 and ATXN3 in Chinese patients with multiple system atrophy

Multiple system atrophy (MSA) is a complex and multifactorial neurodegenerative disease, and its pathogenesis remains uncertain. Patients with MSA or spinocerebellar ataxia (SCA) show overlapping clinical phenotypes. Previous studies have reported that intermediate or long CAG expansions in SCA genes have been associated with other neurodegenerative disease. In this study, we screened for the number of CAG repeats in ATXN1, 2 and 3 in 200 patients with MSA and 314 healthy controls to evaluate possible associations between (CAG)_n in these three polyQ-related genes and MSA. Our findings indicated that longer repeat lengths in ATXN2 were associated with increased risk for MSA in Chinese individuals. No relationship was observed between CAG repeat length in the three examined genes and age at onset (AO) of MSA.

Two novel Mg(II)-based and Zn(II)-based complexes: inhibiting growth of human liver cancer cells

Two new Mg(II)-based and Zn(II)-based coordination polymers, {[Mg3(BTB)(DMA)4](DMA)2}n (1, H3BTB=1,3,5-benzenetrisbenzoic acid, DMA=N,N-dimethylacetamide) and {(H2NMe2)2[Zn3(BTB)2(OH)(Im)](DMF)9(MeOH)7}n (2, Im=imidazole, DMF=N,N-dimethylformamide), have been successfully synthesized and structurally characterized under solvothermal conditions. 1 contains a linear [Mg3(COO)6] cluster that connected by the fully deprotonated BTB3- ligands to give a kgd-type 2D bilayer structure; 2 represents a microporous 3D pillar-layered system based on the binuclear Zn units and pillared Im ligands, which shows a (3,5)-connected hms topological net. In addition, in vitro anticancer activities of compounds 1 and 2 on 4 human liver cancer cells (HB611, HHCC, BEL-7405 and SMMC-7721) were determined.

Reticulocalbin-2 enhances hepatocellular carcinoma proliferation via modulating the EGFR-ERK pathway

This corrects the article DOI: 10.1038/onc.2017.230.

miR-613 inhibits gastric cancer progression through repressing brain derived neurotrophic factor

MicroRNA (miR)-613 has been reported to function as a tumor suppressor in several types of cancer. However, the biological function and underlying mechanism in gastric cancer (GC) has remained elusive. Therefore, the aim of the present study was to assess the expression and biological role of miR-613 in GC tissues and cell lines. miR-613 expression was found to be downregulated in 38 GC tissue samples compared to that in their adjacent non-cancerous tissues, and low expression of miR-613 was associated with lymph node metastasis and advanced tumor-nodes-metastasis stage. A gain-of-function assay demonstrated that miR-613 overexpression reduced tumor cell proliferation, migration and invasion of SGC-7901 cells, as determined by MTT and Transwell assays. Furthermore, brain-derived neutrophic factor (BDNF) was identified as a direct target of miR-613 in GC cells by a luciferase reporter assay. BDNF expression was upregulated and inversely correlated with miR-613 levels in GC tissues. In addition, knockdown of BDNF expression mimicked the tumor suppressive effect of miR-613 in GC cells. In conclusion, these findings demonstrated that miR-613 functions as a tumor suppressor in GC by targeting BDNF. Thus, miR-613 is a potential therapeutic target for GC.