Artificial intelligence-enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes.

AIM: To develop and employ machine learning (ML) algorithms to analyse electrocardiograms (ECGs) for the diagnosis of cardiac autonomic neuropathy (CAN). MATERIALS AND METHODS: We used motif and discord extraction techniques, alongside long short-term memory networks, to analyse 12-lead, 10-s ECG tracings to detect CAN in patients with diabetes. The performance of these methods with the support vector machine classification model was evaluated using 10-fold cross validation with the following metrics: accuracy, precision, recall, F1 score, and area under the receiver-operating characteristic curve (AUC). RESULTS: Among 205 patients (mean age 54 ± 17 years, 54% female), 100 were diagnosed with CAN, including 38 with definite or severe CAN (dsCAN) and 62 with early CAN (eCAN). The best model performance for dsCAN classification was achieved using both motifs and discords, with an accuracy of 0.92, an F1 score of 0.92, a recall at 0.94, a precision of 0.91, and an excellent AUC of 0.93 (95% confidence interval [CI] 0.91-0.94). For the detection of any stage of CAN, the approach combining motifs and discords yielded the best results, with an accuracy of 0.65, F1 score of 0.68, a recall of 0.75, a precision of 0.68, and an AUC of 0.68 (95% CI 0.54-0.81). CONCLUSION: Our study highlights the potential of using ML techniques, particularly motifs and discords, to effectively detect dsCAN in patients with diabetes. This approach could be applied in large-scale screening of CAN, particularly to identify definite/severe CAN where cardiovascular risk factor modification may be initiated.

Evaluation of Huawei smart wearables for detection of atrial fibrillation in patients following ischemic stroke: The Liverpool-Huawei stroke study.

BACKGROUND: Atrial fibrillation (AF) often remains undetected following stroke. Documenting AF is critical to initiate oral anticoagulation, which has proven benefit in reducing recurrent stroke and mortality in patients with AF. The accuracy and acceptability of using smart wearables to detect AF in patients following stroke is unknown. METHODS: The aims of the Liverpool-Huawei Stroke Study are to determine the effectiveness, cost-effectiveness and patient and staff acceptability of using Huawei smart wearables to detect AF following ischemic stroke. The study plans to recruit 1,000 adults aged ≥18 years following ischemic stroke from participating hospitals over 12 months. All participants will be asked to wear a Huawei smart band for 4 weeks postdischarge. If participants do not have access to a compatible smartphone required for the study, they will be provided with a smartphone for the 4-week AF monitoring period. RESULTS: Participants with suspected AF detected by the smart wearables, without previous known AF, will be referred for further evaluation. To determine the effectiveness of the Huawei smart wearables to detect AF, the positive predictive value will be determined. Patient acceptability of using this technology will also be examined. Additional follow-up assessments will be conducted at 6 and 12 months, and clinical outcomes recorded in relation to prevalent and incident AF post-stroke. The study opened for recruitment on May 30, 2022, and is currently open at 4 participating hospitals; the first 106 participants have been recruited. One further hospital is preparing to open for recruitment. CONCLUSIONS: This prospective study will examine the effectiveness and acceptability of the use of smart wearables in patients following ischemic stroke. This could have important implications for detection of AF and therefore, earlier prophylaxis for recurrent stroke. The study is registered on https://www.isrctn.com/ (Identifier ISRCTN30693819).

Retinal imaging technologies in cerebral malaria: a systematic review.

BACKGROUND: Cerebral malaria (CM) continues to present a major health challenge, particularly in sub-Saharan Africa. CM is associated with a characteristic malarial retinopathy (MR) with diagnostic and prognostic significance. Advances in retinal imaging have allowed researchers to better characterize the changes seen in MR and to make inferences about the pathophysiology of the disease. The study aimed to explore the role of retinal imaging in diagnosis and prognostication in CM; establish insights into pathophysiology of CM from retinal imaging; establish future research directions. METHODS: The literature was systematically reviewed using the African Index Medicus, MEDLINE, Scopus and Web of Science databases. A total of 35 full texts were included in the final analysis. The descriptive nature of the included studies and heterogeneity precluded meta-analysis. RESULTS: Available research clearly shows retinal imaging is useful both as a clinical tool for the assessment of CM and as a scientific instrument to aid the understanding of the condition. Modalities which can be performed at the bedside, such as fundus photography and optical coherence tomography, are best positioned to take advantage of artificial intelligence-assisted image analysis, unlocking the clinical potential of retinal imaging for real-time diagnosis in low-resource environments where extensively trained clinicians may be few in number, and for guiding adjunctive therapies as they develop. CONCLUSIONS: Further research into retinal imaging technologies in CM is justified. In particular, co-ordinated interdisciplinary work shows promise in unpicking the pathophysiology of a complex disease.

RETINAL VASCULITIS SEVERITY ASSESSMENT: Intraobserver and Interobserver Reliability of a New Scheme for Grading Wide-Field Fluorescein Angiograms in Retinal Vasculitis.

PURPOSE: Wide-field fluorescein angiography is commonly used to assess retinal vasculitis (RV), which manifests as vascular leakage and occlusion. Currently, there is no standard grading scheme for RV severity. The authors propose a novel RV grading scheme and assess its reliability and reproducibility. METHODS: A grading scheme was developed to assess both leakage and occlusion in RV. Wide-field fluorescein angiography images from 50 patients with RV were graded by four graders, and one grader graded them twice. An intraclass correlation coefficient (ICC) was used to determine intraobserver-interobserver reliability. Generalized linear models were calculated to associate the scoring with visual acuity. RESULTS: Repeated grading by the same grader showed good intraobserver reliability for both leakage (ICC = 0.85, 95% CI 0.78-0.89) and occlusion (ICC = 0.82, 95% CI 0.75-0.88) scores. Interobserver reliability among four independent graders showed good agreement for both leakage (ICC = 0.66, 95% CI 0.49-0.77) and occlusion (ICC = 0.75, 95% CI 0.68-0.81) scores. An increasing leakage score was significantly associated with worse concurrent visual acuity (generalized linear models, ß = 0.090, P < 0.01) and at 1-year follow-up (generalized linear models, ß = 0.063, P < 0.01). CONCLUSION: The proposed grading scheme for RV has good to excellent intraobserver and interobserver reliability across a range of graders. The leakage score related to present and future visual acuity.

Machine learning-based predictions of dietary restriction associations across ageing-related genes.

BACKGROUND: Dietary restriction (DR) is the most studied pro-longevity intervention; however, a complete understanding of its underlying mechanisms remains elusive, and new research directions may emerge from the identification of novel DR-related genes and DR-related genetic features. RESULTS: This work used a Machine Learning (ML) approach to classify ageing-related genes as DR-related or NotDR-related using 9 different types of predictive features: PathDIP pathways, two types of features based on KEGG pathways, two types of Protein-Protein Interactions (PPI) features, Gene Ontology (GO) terms, Genotype Tissue Expression (GTEx) expression features, GeneFriends co-expression features and protein sequence descriptors. Our findings suggested that features biased towards curated knowledge (i.e. GO terms and biological pathways), had the greatest predictive power, while unbiased features (mainly gene expression and co-expression data) have the least predictive power. Moreover, a combination of all the feature types diminished the predictive power compared to predictions based on curated knowledge. Feature importance analysis on the two most predictive classifiers mostly corroborated existing knowledge and supported recent findings linking DR to the Nuclear Factor Erythroid 2-Related Factor 2 (NRF2) signalling pathway and G protein-coupled receptors (GPCR). We then used the two strongest combinations of feature type and ML algorithm to predict DR-relatedness among ageing-related genes currently lacking DR-related annotations in the data, resulting in a set of promising candidate DR-related genes (GOT2, GOT1, TSC1, CTH, GCLM, IRS2 and SESN2) whose predicted DR-relatedness remain to be validated in future wet-lab experiments. CONCLUSIONS: This work demonstrated the strong potential of ML-based techniques to identify DR-associated features as our findings are consistent with literature and recent discoveries. Although the inference of new DR-related mechanistic findings based solely on GO terms and biological pathways was limited due to their knowledge-driven nature, the predictive power of these two features types remained useful as it allowed inferring new promising candidate DR-related genes.

Artificial intelligence utilising corneal confocal microscopy for the diagnosis of peripheral neuropathy in diabetes mellitus and prediabetes.

AIMS/HYPOTHESIS: We aimed to develop an artificial intelligence (AI)-based deep learning algorithm (DLA) applying attribution methods without image segmentation to corneal confocal microscopy images and to accurately classify peripheral neuropathy (or lack of). METHODS: The AI-based DLA utilised convolutional neural networks with data augmentation to increase the algorithm's generalisability. The algorithm was trained using a high-end graphics processor for 300 epochs on 329 corneal nerve images and tested on 40 images (1 image/participant). Participants consisted of healthy volunteer (HV) participants (n = 90) and participants with type 1 diabetes (n = 88), type 2 diabetes (n = 141) and prediabetes (n = 50) (defined as impaired fasting glucose, impaired glucose tolerance or a combination of both), and were classified into HV, those without neuropathy (PN-) (n = 149) and those with neuropathy (PN+) (n = 130). For the AI-based DLA, a modified residual neural network called ResNet-50 was developed and used to extract features from images and perform classification. The algorithm was tested on 40 participants (15 HV, 13 PN-, 12 PN+). Attribution methods gradient-weighted class activation mapping (Grad-CAM), Guided Grad-CAM and occlusion sensitivity displayed the areas within the image that had the greatest impact on the decision of the algorithm. RESULTS: The results were as follows: HV: recall of 1.0 (95% CI 1.0, 1.0), precision of 0.83 (95% CI 0.65, 1.0), F1-score of 0.91 (95% CI 0.79, 1.0); PN-: recall of 0.85 (95% CI 0.62, 1.0), precision of 0.92 (95% CI 0.73, 1.0), F1-score of 0.88 (95% CI 0.71, 1.0); PN+: recall of 0.83 (95% CI 0.58, 1.0), precision of 1.0 (95% CI 1.0, 1.0), F1-score of 0.91 (95% CI 0.74, 1.0). The features displayed by the attribution methods demonstrated more corneal nerves in HV, a reduction in corneal nerves for PN- and an absence of corneal nerves for PN+ images. CONCLUSIONS/INTERPRETATION: We demonstrate promising results in the rapid classification of peripheral neuropathy using a single corneal image. A large-scale multicentre validation study is required to assess the utility of AI-based DLA in screening and diagnostic programmes for diabetic neuropathy.

Anatomical and functional outcomes of pneumatic vitreolysis for treatment of vitreomacular traction with and without macular holes.

PURPOSE: To evaluate the outcome of pneumatic vitreolysis (PVL) for vitreomacular traction (VMT) with or without full thickness macular hole (MH) < 400 µm. METHODS: Forty-seven eyes of 47 patients were included who had undergone PVL for VMT with or without MH. Main outcome measures were release of VMT, MH closure, best-corrected visual acuity (BCVA) and adverse events. RESULTS: Thirty-three patients had isolated VMT and 14 patients VMT with a MH. Four weeks after PVL, the overall VMT release rate was 35/47 (74.5%): 25/37 (67.6%) in phakic and 10/10 (100%) in pseudophakic eyes (p = 0.03). Four of 14 MH (28.6%) were closed. Twenty-two of 47 (46.8%) eyes required a subsequent PPV: 12/33 (36.4%) in the VMT only group and 10/14 (71.4%) in the VMT with MH group. Mean BCVA improved from 0.48 (± 0.24) to 0.34 (± 0.23) logMAR at 6 months in patients with VMT alone (p < 0.001), and from 0.57 (± 0.27) to 0.41 (± 0.28) logMAR in patients with VMT and MH (p = 0.008). Adverse events included new formation of a large MH in 4/33 (12.1%) eyes, failure of MH closure in 10/14 (71.4%) eyes, progression of mean minimum linear diameter (MLD) MH size from baseline 139 (± 67) to 396 (± 130) µm (p < 0.001) and development of a retinal detachment in 4/47 (8.5%) eyes. CONCLUSION: While PVL leads to a high VMT release rate particularly in pseudophakic eyes, it is associated with a relatively high incidence of MH formation, MH size progression and retinal detachment.

A pipeline to evaluate inhibitors of the Pseudomonas aeruginosa exotoxin U.

Pseudomonas aeruginosa has recently been highlighted by the World Health Organisation (WHO) as a major threat with high priority for the development of new therapies. In severe P. aeruginosa infections, the phospholipase activity of the type 3 secretion system toxin, ExoU, induces lysis of target host cells and results in the poorest clinical outcomes. We have developed an integrated pipeline to evaluate small molecule inhibitors of ExoU in vitro and in cultured cell models, including a disease-relevant corneal epithelial (HCE-T) scratch and infection model using florescence microscopy and cell viability assays. Compounds Pseudolipasin A, compound A and compound B were effective in vitro inhibitors of ExoU and mitigated P. aeruginosa ExoU-dependent cytotoxicity after infection of HCE-T cells at concentrations as low as 0.5 µM. Addition of the antimicrobial moxifloxacin controlled bacterial load, allowing these assays to be extended from 6 h to 24 h. P. aeruginosa remained cytotoxic to HCE-T cells with moxifloxacin, present at the minimal inhibitory concentration for 24 h, but, when used in combination with either Pseudolipasin A, compound A or compound B, a greater amount of viable cells and scratch healing were observed. Thus, our pipeline provides evidence that ExoU inhibitors could be used in combination with certain antimicrobials as a novel means to treat infections due to ExoU producing P. aeruginosa, as well as the means to identify more potent ExoU inhibitors for future therapeutics.

An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy: a development and validation study.

AIMS/HYPOTHESIS: Corneal confocal microscopy is a rapid non-invasive ophthalmic imaging technique that identifies peripheral and central neurodegenerative disease. Quantification of corneal sub-basal nerve plexus morphology, however, requires either time-consuming manual annotation or a less-sensitive automated image analysis approach. We aimed to develop and validate an artificial intelligence-based, deep learning algorithm for the quantification of nerve fibre properties relevant to the diagnosis of diabetic neuropathy and to compare it with a validated automated analysis program, ACCMetrics. METHODS: Our deep learning algorithm, which employs a convolutional neural network with data augmentation, was developed for the automated quantification of the corneal sub-basal nerve plexus for the diagnosis of diabetic neuropathy. The algorithm was trained using a high-end graphics processor unit on 1698 corneal confocal microscopy images; for external validation, it was further tested on 2137 images. The algorithm was developed to identify total nerve fibre length, branch points, tail points, number and length of nerve segments, and fractal numbers. Sensitivity analyses were undertaken to determine the AUC for ACCMetrics and our algorithm for the diagnosis of diabetic neuropathy. RESULTS: The intraclass correlation coefficients for our algorithm were superior to those for ACCMetrics for total corneal nerve fibre length (0.933 vs 0.825), mean length per segment (0.656 vs 0.325), number of branch points (0.891 vs 0.570), number of tail points (0.623 vs 0.257), number of nerve segments (0.878 vs 0.504) and fractals (0.927 vs 0.758). In addition, our proposed algorithm achieved an AUC of 0.83, specificity of 0.87 and sensitivity of 0.68 for the classification of participants without (n = 90) and with (n = 132) neuropathy (defined by the Toronto criteria). CONCLUSIONS/INTERPRETATION: These results demonstrated that our deep learning algorithm provides rapid and excellent localisation performance for the quantification of corneal nerve biomarkers. This model has potential for adoption into clinical screening programmes for diabetic neuropathy. DATA AVAILABILITY: The publicly shared cornea nerve dataset (dataset 1) is available at http://bioimlab.dei.unipd.it/Corneal%20Nerve%20Tortuosity%20Data%20Set.htm and http://bioimlab.dei.unipd.it/Corneal%20Nerve%20Data%20Set.htm.

Simultaneous optical coherence tomography and Scheimpflug imaging using the same incident light.

For any single anterior chamber cross-sectional (tomographic) imaging method, there is a practical compromise between image size and image resolution. In order to obtain large field-of-view cross-sectional images of the whole anterior chamber and high-resolution cross-sectional images of the fine corneal layers, measurements by multiple devices are currently required. This paper presents a novel raster scanning tomographic imaging device that acquires simultaneous large field-of-view Scheimpflug (12.5 mm image depth, 50 µm axial resolution in air) and high-resolution spectral domain optical coherence tomography (SD-OCT) (2 mm image depth, 3.7µm axial resolution in air) using the same illuminating photons. For the novel raster scanning 3D Scheimpflug imaging, a tunable lens system together with numerical methods for correcting refraction distortion were used. To demonstrate the capability of simultaneous measurement of both fine corneal layers and whole anterior chambers topology, ex vivo measurements on 12 porcine and 12 bovine eyes were carried out. There is a reasonable agreement in the overall central corneal thicknesses (CCT) obtained from the simultaneous SD-OCT and Scheimpflug measurements. In addition, because the same infrared light beam was used to illuminate the sample, both OCT and Scheimpflug images were taken at the exact same location of a sample simultaneously in a single measurement. This provides a unique method for measuring both the thickness and the refractive index of a sample.

Sub-surface imaging of soiled cotton fabric using full-field optical coherence tomography.

In the laundry industry, colorimetry is a common way to evaluate the stain removal efficiency of detergents and cleaning products. For ease of visualization, the soiling agent is treated with a dye before measurement. However, it effectively measures the dye removal rather than stain removal, and it cannot provide depth-resolved information of the sample. In this study, we show that full-field (FF) optical coherence tomography (OCT) technique is capable of measuring the cleaning effect on cotton fabric by imaging the sub-surface features of fabric samples. We used a broadband light-emitting diode (LED) source to power the FF-OCT system that achieves the resolution of 1 µm axially and 1.6 µm laterally. This allows the micron-sized cotton fibres/fibrils at different depth positions to be resolved. The clean, the soiled, and the washed samples can be differentiated from their cross-sectional images using OCT, where the cleaning effect can be correlated with the sub-surface fibre volume. The experimental results of the proposed method were found to be in good agreement with those of the standard colorimetry method. The proposed technique therefore offers an alternative way for measuring the stain removal from fabric substrate to assess the effectiveness of laundry detergent products.

Non-destructive analysis of flake properties in automotive paints with full-field optical coherence tomography and 3D segmentation.

Automotive coating systems are designed to protect vehicle bodies from corrosion and enhance their aesthetic value. The number, size and orientation of small metallic flakes in the base coat of the paint has a significant effect on the appearance of automotive bodies. It is important for quality assurance (QA) to be able to measure the properties of these small flakes, which are approximately 10µm in radius, yet current QA techniques are limited to measuring layer thickness. We design and develop a time-domain (TD) full-field (FF) optical coherence tomography (OCT) system to scan automotive panels volumetrically, non-destructively and without contact. We develop and integrate a segmentation method to automatically distinguish flakes and allow measurement of their properties. We test our integrated system on nine sections of five panels and demonstrate that this integrated approach can characterise small flakes in automotive coating systems in 3D, calculating the number, size and orientation accurately and consistently. This has the potential to significantly impact QA testing in the automotive industry.

Hypermethylation of PRDM1/Blimp-1 promoter in extranodal NK/T-cell lymphoma, nasal type: an evidence of predominant role in its downregulation.

The loss of PRDM1 expression is common in extranodal NK/T-cell lymphoma, nasal type (EN-NK/T-NT), but the role of promoter methylation in silencing PRDM1 expression remains unclear. Hence, we performed pyrosequencing analysis to evaluate the promoter methylation of PRDM1 gene in vivo and in vitro, to analyze the association between methylation and its expression, and to assess cellular effects of PRDM1 reexpression. The promoter hypermethylation of PRDM1 gene was detected in 11 of 25 EN-NK/T-NT cases (44.0%) and NK92 and NKL cells. The promoter hypermethylation of PRDM1 was significantly correlated with PRDM1 expression in vivo and in vitro, predominantly contributing to the loss of PRDM1 expression compared with genetic deletion and aberrant expression of miR-223 in EN-NK/T-NT. PRDM1 expression was significantly restored by demethylation treatment, which induced cell proliferation suppression, cell cycle arrest, and apoptosis increase. We also found that PRDM1 reexpression could downregulate the expression of Ets-1, T-bet, granzyme B, and c-myc. Our findings demonstrated that the promoter hypermethylation of PRDM1 harbored a predominant role in the downregulation of PRDM1 expression, significantly affecting the biological behavior of tumor cells in EN-NK/T-NT.

High resolution corneal and single pulse imaging with line field spectral domain optical coherence tomography.

We report the development of a Spectral Domain Line Field Optical Coherence Tomography (LF-OCT) system, using a broad bandwidth and spatial coherent Super-Continuum (SC) source. With conventional quasi-Continuous Wave (CW) setup we achieve axial resolutions up to 2.1 µm in air and 3D volume imaging speeds up to 213 kA-Scan/s. Furthermore, we report the use of a single SC pulse, of 2 ns duration, to temporally gate an OCT B-Scan image of 70 A-Scans. This is the equivalent of 35 GA-Scans/s. We apply the CW setup for high resolution imaging of the fine structures of a human cornea sample ex-vivo. The single pulse setup is applied to imaging of a coated pharmaceutical tablet. The fixed pattern noise due to spectral noise is removed by subtracting the median magnitude A-Scan. We also demonstrate that the Fourier phase can be used to remove aberration caused artefacts.

Nondestructive analysis of automotive paints with spectral domain optical coherence tomography.

We have demonstrated for the first time, to our knowledge, the use of optical coherence tomography (OCT) as an analytical tool for nondestructively characterizing the individual paint layer thickness of multiple layered automotive paints. A graph-based segmentation method was used for automatic analysis of the thickness distribution for the top layers of solid color paints. The thicknesses measured with OCT were in good agreement with the optical microscope and ultrasonic techniques that are the current standard in the automobile industry. Because of its high axial resolution (5.5 µm), the OCT technique was shown to be able to resolve the thickness of individual paint layers down to 11 µm. With its high lateral resolution (12.4 µm), the OCT system was also able to measure the cross-sectional area of the aluminum flakes in a metallic automotive paint. The range of values measured was 300-1850 µm2. In summary, the proposed OCT is a noncontact, high-resolution technique that has the potential for inclusion as part of the quality assurance process in automobile coating.

Corneal angiography for guiding and evaluating fine-needle diathermy treatment of corneal neovascularization.

PURPOSE: To investigate the outcome of selective occlusion of the afferent vessel of corneal neovascular complexes (CoNVs), using angiographically guided fine-needle diathermy (FND). DESIGN: Retrospective interventional case series. SUBJECTS: Patients with CoNV unresponsive to topical steroid therapy. METHODS: Visual acuity, color images, and fluorescein angiography and indocyanine green angiography were measured before and after FND with a minimum of 3 months of follow-up. The number of afferent vessels crossing the limbus, time to fluorescein leakage, area, and geometric properties of the CoNV were determined using an in-house automated program written in numerical computing language (MatLab R14; The MathWorks Inc., Natick, MA). The location of the afferent vessel was identified from the angiographic images and marked at the slit lamp using a needle to make a cut to the depth of the vessel. We then applied FND using an electrolysis needle. MAIN OUTCOME MEASURES: Area of CoNV. RESULTS: Thirty patients underwent FND for CoNV that had not responded to treatment with topical steroids. The CoNV was associated with previous microbial keratitis (n = 26), intrastromal corneal ring segments (n = 2), ectodermal dysplasia (n = 1), and corneal choristoma (n = 1). Duration of CoNV was >6 months in 23 patients (77%), between 3 and 6 months in 3 patients (10%), and <3 months in 5 patients (13%). The number of afferent vessels per CoNV ranged from 1 to 3, with a mean diameter of 40 µm (standard deviation [SD], 10 µm) and mean time to leakage from apical vessels was 44.22 seconds (minimum, 27.43 seconds; maximum, 63.59 seconds). The number of FND treatments that were required was 1 for 20 patients (66.6%), 2 for 8 patients (26.6%), and 3 for 2 patients (6.6%). After FND, the area of CoNV reduced by 1.80 mm(2) (SD, 1.40 mm(2)), from 2.42 (SD, 1.59) to 0.62 mm(2) (SD, 0.73 mm(2)) up to 12 weeks postoperatively (P < 0.01). CONCLUSIONS: The differentiation of afferent and efferent vessels using corneal angiography enables treatment to be selectively applied to the afferent vessels; there are usually 1 to 2 for each CoNV complex.

Investigation of inter-rater and test-retest reliability of Y balance test in college students with flexible flatfoot.

BACKGROUND: The Lower Quarter Y Balance Test (YBT-LQ) has been widely used to assess dynamic balance in various populations. Dynamic balance in flexible flatfoot populations is one of the risk factors for lower extremity injuries, especially in college populations in which more exercise is advocated. However, no study has demonstrated the reliability of the YBT-LQ in a college student flexible flatfoot population. METHODS: A cross-sectional observational study. 30 college students with flexible flatfoot were recruited from Beijing Sports University. They have been thrice assessed for the maximal reach distance of YBT under the support of the lower limb on the flatfoot side. Test and retest were performed with an interval of 14 days. The outcome measures using the composite score and normalized maximal reach distances in three directions (anterior, posteromedial, and posterolateral). The relative reliability was reported as the Intraclass Correlation Coefficient (ICC). Minimal Detectable Change (MDC), Smallest worthwhile change (SWC), and Standard Error of Measurement (SEM) were used to report the absolute reliability. RESULTS: For inter-rater reliability, the ICC values for all directions ranged from 0.84 to 0.92, SEM values ranged from 2.01 to 3.10%, SWC values ranged from 3.67 to 5.12%, and MDC95% values ranged from 5.58 to 8.60%. For test-retest reliability, the ICC values for all directions ranged from 0.81 to 0.92, SEM values ranged from 1.80 to 2.97%, SWC values ranged from 3.75 to 5.61%, and MDC95% values ranged from 4.98 to 8.24%. CONCLUSIONS: The YBT-LQ has "good" to "excellent" inter-rater and test-retest reliability. It appears to be a reliable assessment to use with college students with flexible flatfoot. TRIAL REGISTRATION: This trial was prospectively registered at the Chinese Clinical Trial Registry with the ID number ChiCTR2300075906 on 19/09/2023.

Research progress on the application of anti-gravity treadmill in the rehabilitation of Parkinson's disease patients: a mini review.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. It is the second most common chronic progressive neurodegenerative disease. PD still lacks a known cure or prophylactic medication. Current treatments primarily address symptoms without halting the progression of PD, and the side effects of dopaminergic therapy become more apparent over time. In contrast, physical therapy, with its lower risk of side effects and potential cardiovascular benefits, may provide greater benefits to patients. The Anti-Gravity Treadmill is an emerging rehabilitation therapy device with high safety, which minimizes patients' fear and allows them to focus more on a normal, correct gait, and has a promising clinical application. Based on this premise, this study aims to summarize and analyze the relevant studies on the application of the anti-gravity treadmill in PD patients, providing a reference for PD rehabilitation practice and establishing a theoretical basis for future research in this area.

Exosomal Proteomics: Unveiling Novel Insights into Lung Cancer.

Although significant progress has been made in early lung cancer screening over the past decade, it remains one of the most prevalent and deadliest forms of cancer worldwide. Exosomal proteomics has emerged as a transformative field in lung cancer research, with the potential to redefine diagnostics, prognostic assessments, and therapeutic strategies through the lens of precision medicine. This review discusses recent advances in exosome-related proteomic and glycoproteomic technologies, highlighting their potential to revolutionise lung cancer treatment by addressing issues of heterogeneity, integrating multiomics data, and utilising advanced analytical methods. While these technologies show promise, there are obstacles to overcome before they can be widely implemented, such as the need for standardization, gaps in clinical application, and the importance of dynamic monitoring. Future directions should aim to overcome the challenges to fully utilize the potential of exosomal proteomics in lung cancer. This promises a new era of personalized medicine that leverages the molecular complexity of exosomes for groundbreaking advancements in detection, prognosis, and treatment.

Linking Vascular Structure and Function: Image-Based Virtual Populations of the Retina.

Purpose: This study explored the relationship among microvascular parameters as delineated by optical coherence tomography angiography (OCTA) and retinal perfusion. Here, we introduce a versatile framework to examine the interplay between the retinal vascular structure and function by generating virtual vasculatures from central retinal vessels to macular capillaries. Also, we have developed a hemodynamics model that evaluates the associations between vascular morphology and retinal perfusion. Methods: The generation of the vasculature is based on the distribution of four clinical parameters pertaining to the dimension and blood pressure of the central retinal vessels, constructive constrained optimization, and Voronoi diagrams. Arterial and venous trees are generated in the temporal retina and connected through three layers of capillaries at different depths in the macula. The correlations between total retinal blood flow and macular flow fraction and vascular morphology are derived as Spearman rank coefficients, and uncertainty from input parameters is quantified. Results: A virtual cohort of 200 healthy vasculatures was generated. Means and standard deviations for retinal blood flow and macular flow fraction were 20.80 ± 7.86 µL/min and 15.04% ± 5.42%, respectively. Retinal blood flow was correlated with vessel area density, vessel diameter index, fractal dimension, and vessel caliber index. The macular flow fraction was not correlated with any morphological metrics. Conclusions: The proposed framework is able to reproduce vascular networks in the macula that are morphologically and functionally similar to real vasculature. The framework provides quantitative insights into how macular perfusion can be affected by changes in vascular morphology delineated on OCTA.