98 research outputs found
Increased age and male sex are independently associated with higher frequency of blood–cerebrospinal fluid barrier dysfunction using the albumin quotient
Background: The cerebrospinal fluid (CSF)/serum quotient of albumin (QAlb) is the most used biomarker for the evaluation of blood–cerebrospinal fluid barrier (B-CSF-B) permeability. For years QAlb was considered only as an age-related parameter but recently it has also been associated to sex. The aim of the present study was to explore the impact of sex in the determination of B-CSF-B dysfunction.
Methods: The analysis was retrospectively conducted on subjects consecutively admitted to the neurological ward. CSF and serum albumin levels were measured by immunonephelometry and pathological QAlb thresholds were considered: 6.5 under 40 years, 8.0 in the age 40–60 and 9.0 over 60 years.
Results: 1209 subjects were included in the study. 718 females and 491 males (age: 15–88 years): 24.6% of patients had a diagnosis of multiple sclerosis, 23.2% suffered from other inflammatory neurological diseases, 24.6% were affected by non-inflammatory neurological diseases, and for 27.6% of patients the final neurological diagnosis could not be traced. Dysfunctional B-CSF-B was detected more frequently (44 vs. 20.1%, p < 0.0001) and median QAlb value were higher (7.18 vs. 4.87, p < 0.0001) in males than in females in the overall study population and in all disease sub- groups. QAlb and age were positively correlated both in female (p < 0.0001) and male (p < 0.0001) patients, however the slopes of the two regression lines were not significantly different (p = 0.7149), while the difference between the elevations was extremely significant (p < 0.0001) with a gap of 2.2 units between the two sexes. Finally, in a multivari- able linear regression analysis increased age and male sex were independently associated with higher QAlb in the overall study population (both p < 0.001) and after stratification by age and disease group.
Conclusions: Accordingly, identification and validation of sex-targeted QAlb thresholds should be considered as a novel tool in an effort to achieve more precision in the medical approach
Near-infrared spectroscopy estimation of combined skeletal muscle oxidative capacity and O2 diffusion capacity in humans
The final steps of the O2 cascade during exercise depend on the product of the microvascular-tointramyocyte PO2 difference and muscle O2 diffusing capacity (DmO2). Non-invasive methods to determine DmO2 in humans are currently unavailable. Muscle oxygen uptake (mVO2) recovery rate constant (k), measured by near-infrared spectroscopy (NIRS) using intermittent arterial occlusions, is associated with muscle oxidative capacity in vivo. We reasoned that k would be limited by DmO2 when muscle oxygenation is low (kLOW), and hypothesized that: i) k in well-oxygenated muscle (kHIGH) is associated with maximal O2 flux in fiber bundles; and ii) Δk (kHIGH-kLOW) is associated with capillary density (CD). Vastus lateralis k was measured in 12 participants using NIRS after moderate exercise. The timing and duration of arterial occlusions were manipulated to maintain tissue saturation index (TSI) within a 10% range either below (LOW) or above (HIGH) half-maximal desaturation, assessed during sustained arterial occlusion. Maximal O2 flux in phosphorylating state was 37.7±10.6 pmol·s−1·mg−1 (~5.8 ml·min−1·100g−1). CD ranged 348 to 586 mm-2. kHIGH was greater than kLOW (3.15±0.45 vs 1.56±0.79 min-1, p\u3c0.001). Maximal O2 flux was correlated with kHIGH (r=0.80, p=0.002) but not kLOW (r=-0.10, p=0.755). Δk ranged -0.26 to -2.55 min-1, and correlated with CD (r=- 0.68, p=0.015). mVO2 k reflects muscle oxidative capacity only in well-oxygenated muscle. Δk, the difference in k between well- and poorly-oxygenated muscle, was associated with CD, a mediator of DmO2. Assessment of muscle k and Δk using NIRS provides a non-invasive window on muscle oxidative and O2 diffusing capacity
Protein Recognition by Short Peptide Reversible Inhibitors of the Chromatin-Modifying LSD1/CoREST Lysine Demethylase.
The combinatorial assembly of protein complexes is at the heart of chromatin biology. Lysine demethylase LSD1(KDM1A)/CoREST beautifully exemplifies this concept. The active site of the enzyme tightly associates to the N-terminal domain of transcription factors of the SNAIL1 family, which therefore can competitively inhibit the binding of the N-terminal tail of the histone substrate. Our enzymatic, crystallographic, spectroscopic, and computational studies reveal that LSD1/CoREST can bind to a hexapeptide derived from the SNAIL sequence through recognition of a positively charged α-helical turn that forms upon binding to the enzyme. Variations in sequence and length of this six amino acid ligand modulate affinities enabling the same binding site to differentially interact with proteins that exert distinct biological functions. The discovered short peptide inhibitors exhibit antiproliferative activities and lay the foundation for the development of peptidomimetic small molecule inhibitors of LSD1
Digital endpoints in clinical trials of Alzheimer’s disease and other neurodegenerative diseases: challenges and opportunities
Alzheimer’s disease (AD) and other neurodegenerative diseases such as Parkinson’s disease (PD) and Huntington’s disease (HD) are associated with progressive cognitive, motor, affective and consequently functional decline considerably affecting Activities of Daily Living (ADL) and quality of life. Standard assessments, such as questionnaires and interviews, cognitive testing, and mobility assessments, lack sensitivity, especially in early stages of neurodegenerative diseases and in the disease progression, and have therefore a limited utility as outcome measurements in clinical trials. Major advances in the last decade in digital technologies have opened a window of opportunity to introduce digital endpoints into clinical trials that can reform the assessment and tracking of neurodegenerative symptoms. The Innovative Health Initiative (IMI)-funded projects RADAR-AD (Remote assessment of disease and relapse—Alzheimer’s disease), IDEA-FAST (Identifying digital endpoints to assess fatigue, sleep and ADL in neurodegenerative disorders and immune-mediated inflammatory diseases) and Mobilise-D (Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement) aim to identify digital endpoints relevant for neurodegenerative diseases that provide reliable, objective, and sensitive evaluation of disability and health-related quality of life. In this article, we will draw from the findings and experiences of the different IMI projects in discussing (1) the value of remote technologies to assess neurodegenerative diseases; (2) feasibility, acceptability and usability of digital assessments; (3) challenges related to the use of digital tools; (4) public involvement and the implementation of patient advisory boards; (5) regulatory learnings; and (6) the significance of inter-project exchange and data- and algorithm-sharing
Long-term unsupervised mobility assessment in movement disorders
Mobile health technologies (wearable, portable, body-fixed sensors, or domestic-integrated devices) that quantify mobility in unsupervised, daily living environments are emerging as complementary clinical assessments. Data
collected in these ecologically valid, patient-relevant settings can overcome limitations of conventional clinical assessments, as they capture fluctuating and rare events. These data could support clinical decision making and could also serve as outcomes in clinical trials. However, studies that directly compared assessments made in unsupervised and supervised (eg, in the laboratory or hospital) settings point to large disparities, even in the same parameters of mobility. These differences appear to be affected by psychological, physiological, cognitive, environmental, and technical factors, and by the types of mobilities and diagnoses assessed. To facilitate the successful adaptation of the unsupervised assessment of mobility into clinical practice and clinical trials, clinicians and researchers should consider these disparities and the multiple factors that contribute to them
Digital endpoints in clinical trials of Alzheimer's disease and other neurodegenerative diseases: challenges and opportunities.
Alzheimer's disease (AD) and other neurodegenerative diseases such as Parkinson's disease (PD) and Huntington's disease (HD) are associated with progressive cognitive, motor, affective and consequently functional decline considerably affecting Activities of Daily Living (ADL) and quality of life. Standard assessments, such as questionnaires and interviews, cognitive testing, and mobility assessments, lack sensitivity, especially in early stages of neurodegenerative diseases and in the disease progression, and have therefore a limited utility as outcome measurements in clinical trials. Major advances in the last decade in digital technologies have opened a window of opportunity to introduce digital endpoints into clinical trials that can reform the assessment and tracking of neurodegenerative symptoms. The Innovative Health Initiative (IMI)-funded projects RADAR-AD (Remote assessment of disease and relapse-Alzheimer's disease), IDEA-FAST (Identifying digital endpoints to assess fatigue, sleep and ADL in neurodegenerative disorders and immune-mediated inflammatory diseases) and Mobilise-D (Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement) aim to identify digital endpoints relevant for neurodegenerative diseases that provide reliable, objective, and sensitive evaluation of disability and health-related quality of life. In this article, we will draw from the findings and experiences of the different IMI projects in discussing (1) the value of remote technologies to assess neurodegenerative diseases; (2) feasibility, acceptability and usability of digital assessments; (3) challenges related to the use of digital tools; (4) public involvement and the implementation of patient advisory boards; (5) regulatory learnings; and (6) the significance of inter-project exchange and data- and algorithm-sharing
Statin treatment and mortality in community-dwelling frail older patients with diabetes mellitus
Background: Older adults are often excluded from clinical trials. Decision making for administration of statins to older patients with diabetes mellitus (DM) is under debate, particularly in frail older patients with comorbidity and high mortality risk. We tested the hypothesis that statin treatment in older patients with DM was differentially effective across strata of mortality risk assessed by the Multidimensional Prognostic Index (MPI), based on information collected with the Standardized Multidimensional Assessment Schedule for Adults and Aged Persons (SVaMA). Methods: In this retrospective observational study, we estimated the mortality risk in 1712 community-dwelling subjects with DM ≥ 65 years who underwent a SVaMA evaluation to establish accessibility to homecare services/nursing home admission from 2005 to 2013 in the Padova Health District, Italy. Mild (MPI-SVaMA-1), moderate (MPI-SVaMA-2), and high (MPI-SVaMA-3) risk of mortality at baseline and propensity score-adjusted hazard ratios (HR) of three-year mortality were calculated according to statin treatment. Results: Higher MPI-SVaMA scores were associated with lower rates of statin treatment (MPI-SVaMA-1 = 39% vs MPI-SVaMA-2 = 36% vs MPI-SVaMA-3 = 24.9%. p<0.001) and higher three-year mortality (MPI-SVaMA-1 = 12.9% vs MPI-SVaMA-2 = 24% vs MPI-SVaMA-3 = 34.4%, p<0.001). After adjustment for propensity score quintiles, statin treatment was significantly associated with lower three-year mortality irrespective of MPI-SVaMA group (interaction test p = 0.303). HRs [95% confidence interval (CI)] were 0.19 (0.14-0.27), 0.28 (0.21-0.36), and 0.26 (0.20-0.34) in the MPI-SVaMA-1, MPI-SVaMA-2, and MPI-SVaMA-3 groups, respectively. Subgroup analyses showed that statin treatment was also beneficial irrespective of age. HRs (95% CI) were 0.21 (0.15-0.31), 0.26 (0.20-0.33), and 0.26 (0.20-0.35) among patients aged 65-74, 75-84, and ≥ 85 years, respectively (interaction test p=0.812). Conclusions: Statin treatment was significantly associat
Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.
BACKGROUND
In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans.
RESULTS
Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis.
CONCLUSIONS
TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones
Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission
Motor, cognitive and mobility deficits in 1000 geriatric patients : protocol of a quantitative observational study before and after routine clinical geriatric treatment – the ComOn-study
© The Author(s). 2020 Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background: Motor and cognitive deficits and consequently mobility problems are common in geriatric patients. The currently available methods for diagnosis and for the evaluation of treatment in this vulnerable cohort are limited. The aims of the ComOn (COgnitive and Motor interactions in the Older populatioN) study are (i) to define quantitative markers with clinical relevance for motor and cognitive deficits, (ii) to investigate the interaction between both motor and cognitive deficits and (iii) to assess health status as well as treatment outcome of 1000 geriatric inpatients in hospitals of Kiel (Germany), Brescia (Italy), Porto (Portugal), Curitiba (Brazil) and Bochum (Germany).
Methods: This is a prospective, explorative observational multi-center study. In addition to the comprehensive geriatric assessment, quantitative measures of reduced mobility and motor and cognitive deficits are performed before and after a two week's inpatient stay. Components of the assessment are mobile technology-based assessments of gait, balance and transfer performance, neuropsychological tests, frailty, sarcopenia, autonomic dysfunction and sensation, and questionnaires to assess behavioral deficits, activities of daily living, quality of life, fear of falling and dysphagia. Structural MRI and an unsupervised 24/7 home assessment of mobility are performed in a subgroup of participants. The study will also investigate the minimal clinically relevant change of the investigated parameters.
Discussion: This study will help form a better understanding of symptoms and their complex interactions and treatment effects in a large geriatric cohort.info:eu-repo/semantics/publishedVersio
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