596 research outputs found
Learned and handcrafted features for early-stage laryngeal SCC diagnosis
Squamous cell carcinoma (SCC) is the most common and malignant laryngeal cancer. An early-stage diagnosis is of crucial importance to lower patient mortality and preserve both the laryngeal anatomy and vocal-fold function. However, this may be challenging as the initial larynx modifications, mainly concerning the mucosa vascular tree and the epithelium texture and color, are small and can pass unnoticed to the human eye. The primary goal of this paper was to investigate a learning-based approach to early-stage SCC diagnosis, and compare the use of (i) texture-based global descriptors, such as local binary patterns, and (ii) deep-learning-based descriptors. These features, extracted from endoscopic narrow-band images of the larynx, were classified with support vector machines as to discriminate healthy, precancerous, and early-stage SCC tissues. When tested on a benchmark dataset, a median classification recall of 98% was obtained with the best feature combination, outperforming the state of the art (recall = 95%). Despite further investigation is needed (e.g., testing on a larger dataset), the achieved results support the use of the developed methodology in the actual clinical practice to provide accurate early-stage SCC diagnosis. [Figure not available: see fulltext.]
Synthetic and Real Inputs for Tool Segmentation in Robotic Surgery
Semantic tool segmentation in surgical videos is important for surgical scene
understanding and computer-assisted interventions as well as for the
development of robotic automation. The problem is challenging because different
illumination conditions, bleeding, smoke and occlusions can reduce algorithm
robustness. At present labelled data for training deep learning models is still
lacking for semantic surgical instrument segmentation and in this paper we show
that it may be possible to use robot kinematic data coupled with laparoscopic
images to alleviate the labelling problem. We propose a new deep learning based
model for parallel processing of both laparoscopic and simulation images for
robust segmentation of surgical tools. Due to the lack of laparoscopic frames
annotated with both segmentation ground truth and kinematic information a new
custom dataset was generated using the da Vinci Research Kit (dVRK) and is made
available
Novel atrazine-binding biomimetics inspired to the D1 protein from the photosystem II of Chlamydomonas reinhardtii
Biomimetic design represents an emerging field for improving knowledge of natural molecules, as well as to project novel artificial tools with specific functions for biosensing. Effective strategies have been exploited to design artificial bioreceptors, taking inspiration from complex supramolecular assemblies. Among them, size-minimization strategy sounds promising to provide bioreceptors with tuned sensitivity, stability, and selectivity, through the ad hoc manipulation of chemical species at the molecular scale. Herein, a novel biomimetic peptide enabling herbicide binding was designed bioinspired to the D1 protein of the Photosystem II of the green alga Chlamydomonas reinhardtii. The D1 protein portion corresponding to the QB plastoquinone binding niche is capable of interacting with photosynthetic herbicides. A 50-mer peptide in the region of D1 protein from the residue 211 to 280 was designed in silico, and molecular dynamic simulations were performed alone and in complex with atrazine. An equilibrated structure was obtained with a stable pocked for atrazine binding by three H-bonds with SER222, ASN247, and HIS272 residues. Computational data were confirmed by fluorescence spectroscopy and circular dichroism on the peptide obtained by automated synthesis. Atrazine binding at nanomolar concentrations was followed by fluorescence spectroscopy, highlighting peptide suitability for optical sensing of herbicides at safety limits
Ongoing microstructural changes in the cervical cord underpin disability progression in early primary progressive multiple sclerosis
Background: Pathology in the spinal cord of patients with primary progressive multiple sclerosis (PPMS) contributes to disability progression. We previously reported abnormal Q-space imaging (QSI)-derived indices in the spinal cord at baseline in patients with early PPMS, suggesting early neurodegeneration. /
Objective: The aim was to investigate whether changes in spinal cord QSI over 3 years in the same cohort are associated with disability progression and if baseline QSI metrics predict clinical outcome. /
Methods: Twenty-three PPMS patients and 23 healthy controls recruited at baseline were invited for follow-up cervical cord 3T magnetic resonance imaging (MRI) and clinical assessment after 1 year and 3 years. Cord cross-sectional area (CSA) and QSI measures were obtained, together with standard brain MRI measures. Mixed-effect models assessed MRI changes over time and their association with clinical changes. Linear regression identified baseline MRI indices associated with disability at 3 years. /
Results: Over time, patients deteriorated clinically and showed an increase in cord QSI indices of perpendicular diffusivity that was associated with disability worsening, independently of the decrease in CSA. Higher perpendicular diffusivity and lower CSA at baseline predicted worse disability at 3 years.
Conclusion:
Increasing spinal cord perpendicular diffusivity may indicate ongoing neurodegeneration, which underpins disability progression in PPMS, independently of the development of spinal cord atrophy
A retrospective exploratory analysis on cardiovascular risk and cognitive dysfunction in multiple sclerosis
Background. Cardiovascular comorbidities have been associated with cognitive decline in the general population. Objectives. To evaluate the associations between cardiovascular risk and neuropsychological performances in MS. Methods. This is a retrospective study, including 69 MS patients. For all patients, we calculated the Framingham risk score, which provides the 10-year probability of developing macrovascular disease, using age, sex, diabetes, smoking, systolic blood pressure, and cholesterol levels as input variables. Cognitive function was examined with the Brief International Cognitive Assessment for MS (BICAMS), including the Symbol Digit Modalities Test (SDMT), the California Verbal Learning Test-II (CVLT-II), and the Brief Visuospatial Memory Test-Revised (BVMT-R). Results. Each point increase of the Framingham risk score corresponded to 0.21 lower CVLT-II score. Looking at Framingham risk score components, male sex and higher total cholesterol levels corresponded to lower CVLT scores (Coeff = −8.54; 95%CI = −15.51, −1.57; and Coeff = −0.11; 95%CI = −0.20, −0.02, respectively). No associations were found between cardiovascular risk and SDMT or BVMT-R. Conclusions. In our exploratory analyses, cardiovascular risk was associated with verbal learning dysfunction in MS. Lifestyle and pharmacological interventions on cardiovascular risk factors should be considered carefully in the management of MS, given the possible effects on cognitive function
Electron affinity of Li: A state-selective measurement
We have investigated the threshold of photodetachment of Li^- leading to the
formation of the residual Li atom in the state. The excited residual
atom was selectively photoionized via an intermediate Rydberg state and the
resulting Li^+ ion was detected. A collinear laser-ion beam geometry enabled
both high resolution and sensitivity to be attained. We have demonstrated the
potential of this state selective photodetachment spectroscopic method by
improving the accuracy of Li electron affinity measurements an order of
magnitude. From a fit to the Wigner law in the threshold region, we obtained a
Li electron affinity of 0.618 049(20) eV.Comment: 5 pages,6 figures,22 reference
The Framingham cardiovascular risk score in multiple sclerosis
Background and purpose: Cardiovascular risk factors can increase the risk of multiple sclerosis (MS) and modify its course. However, such factors possibly interact, determining a global cardiovascular risk. Our aim was to compare the global cardiovascular risk of subjects with and without MS with the simplified 10-year Framingham General Cardiovascular Disease Risk Score (FR) and to evaluate its importance on MS-related outcomes. Methods: Age, gender, smoking status, body mass index, systolic blood pressure, type II diabetes and use of antihypertensive medications were recorded in subjects with and without MS to estimate the FR, an individualized percentage risk score estimating the 10-year likelihood of cardiovascular events. Results: In total, 265 MS subjects were identified with 530 matched controls. A t test showed similar FR in cases and controls (P = 0.212). Secondary progressive MS presented significantly higher FR compared to relapsing-remitting MS (P < 0.001). Linear regression analysis showed a direct relationship between FR and Expanded Disability Status Scale (P < 0.001) and MS Severity Scale (P < 0.001). Conclusion: The FR, evaluating the global cardiovascular health by the interaction amongst different risk factors, relates to MS disability, severity and course
Understanding the heart-brain axis response in COVID-19 patients: A suggestive perspective for therapeutic development
In-depth characterization of heart-brain communication in critically ill patients with severe acute respiratory failure is attracting significant interest in the COronaVIrus Disease 19 (COVID-19) pandemic era during intensive care unit (ICU) stay and after ICU or hospital discharge. Emerging research has provided new insights into pathogenic role of the deregulation of the heart-brain axis (HBA), a bidirectional flow of information, in leading to severe multiorgan disease syndrome (MODS) in patients with confirmed infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Noteworthy, HBA dysfunction may worsen the outcome of the COVID-19 patients. In this review, we discuss the critical role HBA plays in both promoting and limiting MODS in COVID-19. We also highlight the role of HBA as new target for novel therapeutic strategies in COVID-19 in order to open new translational frontiers of care. This is a translational perspective from the Italian Society of Cardiovascular Researches
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