Artificial Intelligence-based methods in head and neck cancer diagnosis : an overview

Background This paper reviews recent literature employing Artificial Intelligence/Machine Learning (AI/ML) methods for diagnostic evaluation of head and neck cancers (HNC) using automated image analysis. Methods Electronic database searches using MEDLINE via OVID, EMBASE and Google Scholar were conducted to retrieve articles using AI/ML for diagnostic evaluation of HNC (2009–2020). No restrictions were placed on the AI/ML method or imaging modality used. Results In total, 32 articles were identified. HNC sites included oral cavity (n = 16), nasopharynx (n = 3), oropharynx (n = 3), larynx (n = 2), salivary glands (n = 2), sinonasal (n = 1) and in five studies multiple sites were studied. Imaging modalities included histological (n = 9), radiological (n = 8), hyperspectral (n = 6), endoscopic/clinical (n = 5), infrared thermal (n = 1) and optical (n = 1). Clinicopathologic/genomic data were used in two studies. Traditional ML methods were employed in 22 studies (69%), deep learning (DL) in eight studies (25%) and a combination of these methods in two studies (6%). Conclusions There is an increasing volume of studies exploring the role of AI/ML to aid HNC detection using a range of imaging modalities. These methods can achieve high degrees of accuracy that can exceed the abilities of human judgement in making data predictions. Large-scale multi-centric prospective studies are required to aid deployment into clinical practice

A Scoping Review of Quality of Life Questionnaires in Glaucoma Patients

PRECIS: Multiple questionnaires exist to measure glaucoma's impact on quality of life (QoL). Selecting the right questionnaire for the research question is essential, as is patients' acceptability of the questionnaire to enable collection of relevant patient-reported outcomes. PURPOSE: QoL relating to a disease and its treatment is an important dimension to capture. This scoping review sought to identify the questionnaires most appropriate for capturing the impact of glaucoma on QoL. METHODS: A literature search of QoL questionnaires used in glaucoma, including patient-reported outcomes measures, was conducted and the identified questionnaires were analyzed using a developed quality criteria assessment. RESULTS: Forty-one QoL questionnaires were found which were analyzed with the detailed quality criteria assessment leading to a summary score. This identified the top 10 scoring QoL questionnaires rated by a synthesis of the quality criteria grid, considering aspects such as reliability and reproducibility, and the authors' expert clinical opinion. The results were ratified in consultation with an international panel of ophthalmologists (N=49) from the Educational Club of Ocular Surface and Glaucoma representing 23 countries. CONCLUSIONS: Wide variability among questionnaires used to determine vision related QoL in glaucoma and in the responses elicited was identified. In conclusion, no single existing QoL questionnaire design is suitable for all purposes in glaucoma research, rather we have identified the top 10 from which the questionnaire most appropriate to the study objective may be selected. Development of a new questionnaire that could better distinguish between treatments in terms of vision and treatment-related QoL would be useful that includes the patient perspective of treatment effects as well as meeting requirements of regulatory and health authorities. Future work could involve development of a formal weighting system with which to comprehensively assess the quality of QoL questionnaires used in glaucoma

The Alzheimer's Disease Amyloid-Beta Hypothesis in Cardiovascular Aging and Disease: JACC Focus Seminar

Aging-related cellular and molecular processes including low-grade inflammation are major players in the pathogenesis of cardiovascular disease (CVD) and Alzheimer's disease (AD). Epidemiological studies report an independent interaction between the development of dementia and the incidence of CVD in several populations, suggesting the presence of overlapping molecular mechanisms. Accumulating experimental and clinical evidence suggests that amyloid-beta (Aβ) peptides may function as a link among aging, CVD, and AD. Aging-related vascular and cardiac deposition of Αβ induces tissue inflammation and organ dysfunction, both important components of the Alzheimer's disease amyloid hypothesis. In this review, the authors describe the determinants of Aβ metabolism, summarize the effects of Aβ on atherothrombosis and cardiac dysfunction, discuss the clinical value of Αβ1-40 in CVD prognosis and patient risk stratification, and present the therapeutic interventions that may alter Aβ metabolism in humans. © 2020 The Author

Accelerating Whole-Body Diffusion-weighted MRI with Deep Learning-based Denoising Image Filters.

Purpose To use deep learning to improve the image quality of subsampled images (number of acquisitions = 1 [NOA 1 ]) to reduce whole-body diffusion-weighted MRI (WBDWI) acquisition times. Materials and methods Both retrospective and prospective patient groups were used to develop a deep learning-based denoising image filter (DNIF) model. For initial model training and validation, 17 patients with metastatic prostate cancer with acquired WBDWI NOA 1 and NOA 9 images (acquisition period, 2015-2017) were retrospectively included. An additional 22 prospective patients with advanced prostate cancer, myeloma, and advanced breast cancer were used for model testing (2019), and the radiologic quality of DNIF-processed NOA 1 (NOA 1-DNIF ) images were compared with NOA 1 images and clinical NOA 16 images by using a three-point Likert scale (good, average, or poor; statistical significance was calculated by using a Wilcoxon signed ranked test). The model was also retrained and tested in 28 patients with malignant pleural mesothelioma (MPM) who underwent lung MRI (2015-2017) to demonstrate feasibility in other body regions. Results The model visually improved the quality of NOA 1 images in all test patients, with the majority of NOA 1-DNIF and NOA 16 images being graded as either "average" or "good" across all image-quality criteria. From validation data, the mean apparent diffusion coefficient (ADC) values within NOA 1-DNIF images of bone disease deviated from those within NOA 9 images by an average of 1.9% (range, 1.1%-2.6%). The model was also successfully applied in the context of MPM; the mean ADCs from NOA 1-DNIF images of MPM deviated from those measured by using clinical-standard images (NOA 12 ) by 3.7% (range, 0.2%-10.6%). Conclusion Clinical-standard images were generated from subsampled images by using a DNIF. Keywords: Image Postprocessing, MR-Diffusion-weighted Imaging, Neural Networks, Oncology, Whole-Body Imaging, Supervised Learning, MR-Functional Imaging, Metastases, Prostate, Lung Supplemental material is available for this article. Published under a CC BY 4.0 license

Adenosine-to-inosine RNA editing contributes to type I interferon responses in systemic sclerosis

Objective: Adenosine deaminase acting on RNA-1 (ADAR1) enzyme is a type I interferon (IFN)-stimulated gene (ISG) catalyzing the deamination of adenosine-to-inosine, a process called A-to-I RNA editing. A-to-I RNA editing takes place mainly in Alu elements comprising a primate-specific level of post-transcriptional gene regulation. Whether RNA editing is involved in type I IFN responses in systemic sclerosis (SSc) patients remains unknown. Methods: ISG expression was quantified in skin biopsies and peripheral blood mononuclear cells derived from SSc patients and healthy subjects. A-to-I RNA editing was examined in the ADAR1-target cathepsin S (CTSS) by an RNA editing assay. The effect of ADAR1 on interferon-α/β-induced CTSS expression was assessed in human endothelial cells in vitro. Results: Increased expression levels of the RNA editor ADAR1, and specifically the long ADAR1p150 isoform, and its target CTSS are strongly associated with type I IFN signature in skin biopsies and peripheral blood derived from SSc patients. Notably, IFN-α/β-treated human endothelial cells show 8-10-fold increased ADAR1p150 and 23-35-fold increased CTSS expression, while silencing of ADAR1 reduces CTSS expression by 60-70%. In SSc patients, increased RNA editing rate of individual adenosines located in CTSS 3′ UTR Alu elements is associated with higher CTSS expression (r = 0.36–0.6, P < 0.05 for all). Similar findings were obtained in subjects with activated type I IFN responses including SLE patients or healthy subjects after influenza vaccination. Conclusion: ADAR1p150-mediated A-to-I RNA editing is critically involved in type I IFN responses highlighting the importance of post-transcriptional regulation of proinflammatory gene expression in systemic autoimmunity, including SSc. © 2021 The Author

The association between persistent cognitive difficulties and depression and functional outcomes in people with Major Depressive Disorder

Background: Cognitive symptoms are common during and following episodes of depression. Little is known about the persistence of self-reported and performance-based cognition with depression and functional outcomes. Methods: This is a secondary analysis of a prospective naturalistic observational clinical cohort study of individuals with recurrent Major Depressive Disorder (MDD; N=623). Participants completed app-based self-reported and performance-based cognitive function assessments alongside validated measures of depression, functional disability, and self-esteem every three months. Participants were followed-up for a maximum of 2-years. Multilevel hierarchically nested modelling was employed to explore between- and within-participant variation over time to identify whether persistent cognitive difficulties are related to levels of depression and functional impairment during follow-up. Results: 508 individuals (81.5%) provided data (mean age: 46.6, SD: 15.6; 76.2% female). Increasing persistence of self-reported cognitive difficulty was associated with higher levels of depression and functional impairment throughout the follow-up. In comparison to low persistence of objective cognitive difficulty (75% of timepoints) reported significantly higher levels of depression (B=5.17, SE=2.21, p=0.019) and functional impairment (B=4.82, SE=1.79, p=0.002) over time. Examination of the individual cognitive modules shows that persistently impaired executive function is associated with worse functioning, and poor processing speed is particularly important for worsened depressive symptoms. Conclusions: We replicated previous findings of greater persistence of cognitive difficulty with increasing severity of depression and further demonstrate that these cognitive difficulties are associated with pervasive functional disability. Difficulties with cognition may be an indicator and target for further treatment input

Adenosine-to-inosine RNA editing contributes to type I interferon responses in systemic sclerosis

Parallelism in processor architecture and design imposes a verification challenge as the exponential growth in the number of execution combinations becomes unwieldy. In this paper we report on the verification of a Very Large Instruction Word processor. The verification team used a sophisticated test program generator that modeled the parallel aspects as sequential constraints, and augmented the tool with manually written test templates. The system created large numbers of legal stimuli, however the quality of the tests was proved insufficient by several post silicon bugs. We analyze this experience and suggest an alternative, parallel generation technique. We show through experiments the feasibility of the new technique and its superior quality along several dimensions. We claim that the results apply to other parallel architectures and verification environments

Additive contribution of microRNA-34a/b/c to human arterial ageing and atherosclerosis

Background and aims: Preclinical data suggest that the ageing-induced miR-34a regulates vascular senescence. Herein we sought to assess whether the miR-34 family members miR-34a, miR-34b and miR-34c are involved in human arterial disease. Methods: Expression levels of miR-34a/b/c were quantified by TaqMan assay in peripheral blood mononuclear cells (PBMCs) derived from a consecutive cohort of 221 subjects who underwent cardiovascular risk assessment and thorough vascular examination for aortic stiffness and extent of arterial atherosclerosis. Results: High miR-34a was independently associated with the presence of CAD [OR (95%C.I.): 3.87 (1.56–9.56); p = 0.003] and high miR-34c with the number of diseased arterial beds [OR (95%C.I.): 1.88 (1.034–3.41); p = 0.038], while concurrent high expression of miR-34-a/c or all three miR-34a/b/c was associated with aortic stiffening (miR-34a/c: p = 0.022; miR-34a/b/c: p = 0.041) and with the extent of atherosclerosis [OR (95%C.I.) for number of coronary arteries [miR-34a/c: 3.29 (1.085–9.95); miR-34a/b/c: 6.06 (1.74–21.2)] and number of diseased arterial beds [miR-34a/c: 3.51 (1.45–8.52); miR-34a/b/c: 2.89 (1.05–7.92)] after controlling for possible confounders (p < 0.05 for all). Mechanistically, the increased levels of miR-34a or miR-34c were inversely associated with expression of SIRT1 or JAG1, NOTCH2, CTNNB1 and ATF1, respectively. The association of miR-34a/c or miR-34a/b/c with CAD was mainly mediated through SIRT1 and to a lesser extent through JAG1 as revealed by generalized structural equation modeling. Leukocyte-specific ablation of miR-34a/b/c ameliorates atherosclerotic plaque development and increases Sirt1 and Jag1 expression in an atherosclerosis mouse model confirming the human findings. Conclusions: The present study reveals the clinical significance of the additive role of miR-34a/b/c in vascular ageing and atherosclerotic vascular disease. © 2021 Elsevier B.V