745 research outputs found
Automated DNA Fragments Recognition and Sizing through AFM Image Processing
No full textThis paper presents an automated algorithm to determine DNA fragment size from atomic force microscope images and to extract the molecular profiles. The sizing of DNA fragments is a widely used procedure for investigating the physical properties of individual or protein-bound DNA molecules. Several atomic force microscope (AFM) real and computer-generated images were tested for different pixel and fragment sizes and for different background noises. The automated approach minimizes processing time with respect to manual and semi-automated DNA sizing. Moreover, the DNA molecule profile recognition can be used to perform further structural analysis. For computer-generated images, the root mean square error incurred by the automated algorithm in the length estimation is 0.6% for a 7.8 nm image pixel size and 0.34% for a 3.9 nm image pixel size. For AFM real images we obtain a distribution of lengths with a standard deviation of 2.3% of mean and a measured average length very close to the real one, with an error around 0.33%
Automated segmentation of tissue images for computerized IHC analysis
No full textThis paper presents two automated methods for the segmentation ofimmunohistochemical tissue images that overcome the limitations of themanual approach aswell as of the existing computerized techniques. The first independent method, based on unsupervised color clustering, recognizes automatically the target cancerous areas in the specimen and disregards the stroma; the second method, based on colors separation and morphological processing, exploits automated segmentation of the nuclear membranes of the cancerous cells. Extensive experimental results on real tissue images demonstrate the accuracy of our techniques compared to manual segmentations; additional experiments show that our techniques are more effective in immunohistochemical images than popular approaches based on supervised learning or active contours. The proposed procedure can be exploited for any applications that require tissues and cells exploration and to perform reliable and standardized measures of the activity of specific proteins involved in multi-factorial genetic pathologie
Joint co-clustering: co-clustering of genomic and clinical bioimaging data
No full textAbstractFor better understanding the genetic mechanisms underlying clinical observations, and better defining a group of potential candidates for protein-family-inhibiting therapy, it is interesting to determine the correlations between genomic, clinical data and data coming from high resolution and fluorescent microscopy. We introduce a computational method, called joint co-clustering, that can find co-clusters or groups of genes, bioimaging parameters and clinical traits that are believed to be closely related to each other based on the given empirical information. As bioimaging parameters, we quantify the expression of growth factor receptor EGFR/erb-B family in non-small cell lung carcinoma (NSCLC) through a fully-automated computer-aided analysis approach. This immunohistochemical analysis is usually performed by pathologists via visual inspection of tissue samples images. Our fully-automated techniques streamlines this error-prone and time-consuming process, thereby facilitating analysis and diagnosis. Experimental results for several real-life datasets demonstrate the high quantitative precision of our approach. The joint co-clustering method was tested with the receptor EGFR/erb-B family data on non-small cell lung carcinoma (NSCLC) tissue and identified statistically significant co-clusters of genes, receptor protein expression and clinical traits. The validation of our results with the literature suggest that the proposed method can provide biologically meaningful co-clusters of genes and traits and that it is a very promising approach to analyse large-scale biological data and to study multi-factorial genetic pathologies through their genetic alterations
Editorial comment on: Holmium laser enucleation versus transurethral resection of the prostate: 3-year follow-up results of a randomized clinical trial.
No full textNo abstract availabl
Does Stretching Training Influence Muscular Strength? A Systematic Review With Meta-Analysis and Meta-Regression
No full textThomas, E, Ficarra, S, Nunes, JP, Paoli, A, Bellafiore, M, Palma, A, and Bianco, A. Does stretching training influence muscular strength? A systematic review with meta-analysis and meta-regression. J Strength Cond Res 37(5): 1145-1156, 2023 - The aim of this study was to review articles that performed stretching training and evaluated the effects on muscular strength. Literature search was performed using 3 databases. Studies were included if they compared the effects on strength following stretching training vs. a nontraining control group or stretching training combined with resistance training (RT) vs. an RT-only group, after at least 4 weeks of intervention. The meta-analyses were performed using a random-effect model with Hedges' g effect size (ES). A total of 35 studies (n = 1,179 subjects) were included in this review. The interventions lasted for a mean period of 8 weeks (range, 4-24 weeks), 3-4 days per week, applying approximately 4 sets of stretching of approximately 1-minute duration. The meta-analysis for the stretching vs. nontraining control group showed a significant small effect on improving dynamic (k = 14; ES = 0.33; p = 0.007) but not isometric strength (k = 8; ES = 0.10; p = 0.377), following static stretching programs (k = 17; ES = 0.28; p = 0.006). When stretching was added to RT interventions, the main analysis indicated no significant effect (k = 17; ES = -0.15; p = 0.136); however, moderator analysis indicated that performing stretching before RT sessions has a small but negative effect (k = 7; ES = -0.43; p = 0.014); the meta-regression revealed a significant negative association with study length (β = -0.100; p = 0.004). Chronic static stretching programs increase dynamic muscular strength to a small magnitude. Performing stretching before RT and for a prolonged time (>8 weeks) can blunt the strength gains to a small-to-moderate magnitude. Performing stretching in sessions distant from RT sessions might be a strategy to not hinder strength development
Automated Segmentation of Cells with IHC Membrane Staining
No full textThis study presents a fully automated membrane segmentation technique for immunohistochemical tissue images with membrane staining, which is a critical task in computerized immunohistochemistry (IHC). Membrane segmentation is particularly tricky in immunohistochemical tissue images because the cellular membranes are visible only in the stained tracts of the cell, while the unstained tracts are not visible. Our automated method provides accurate segmentation of the cellular membranes in the stained tracts and reconstructs the approximate location of the unstained tracts using nuclear membranes as a spatial reference. Accurate cell-by-cell membrane segmentation allows per cell morphological analysis and quantification of the target membrane proteins that is fundamental in several medical applications such as cancer characterization and classification, personalized therapy design, and for any other applications requiring cell morphology characterization. Experimental results on real datasets from different anatomical locations demonstrate the wide applicability and high accuracy of our approach in the context of IHC analysi
Automated Discrimination of Pathological Regions in Tissue Images: Unsupervised Clustering vs Supervised SVM Classification
No full textRecognizing and isolating cancerous cells from non pathological tissue areas (e.g. connective stroma) is crucial for fast and objective immunohistochemical analysis of tissue images. This operation allows the further application of fully-automated techniques for quantitative evaluation of protein activity, since it avoids the necessity of a preventive manual selection of the representative pathological areas in the image, as well as of taking pictures only in the pure-cancerous portions of the tissue. In this paper we present a fully-automated method based on unsupervised clustering that performs tissue segmentations highly comparable with those provided by a skilled operator, achieving on average an accuracy of 90%. Experimental results on a heterogeneous dataset of immunohistochemical lung cancer tissue images demonstrate that our proposed unsupervised approach overcomes the accuracy of a theoretically superior supervised method such as Support Vector Machine (SVM) by 8%
Acceleration of Coarse Grain Molecular Dynamics on GPU Architectures
No full textCoarse grain (CG) molecular models have been proposed to simulate complex sys- tems with lower computational overheads and longer timescales with respect to atom- istic level models. However, their acceleration on parallel architectures such as Graphic Processing Units (GPU) presents original challenges that must be carefully evaluated. The objective of this work is to characterize the impact of CG model features on parallel simulation performance. To achieve this, we implemented a GPU-accelerated version of a CG molecular dynamics simulator, to which we applied specic optimizations for CG models, such as dedicated data structures to handle dierent bead type interac- tions, obtaining a maximum speed-up of 14 on the NVIDIA GTX480 GPU with Fermi architecture. We provide a complete characterization and evaluation of algorithmic and simulated system features of CG models impacting the achievable speed-up and accuracy of results, using three dierent GPU architectures as case studie
Editorial Comment on: Cytological Punctures in the Diagnosis of Renal Tumours: AStudy on Accuracy and Reproducibility.
No full textOBJECTIVE: To evaluate the impact of antegrade scrotal sclerotherapy on seminal
parameters and pregnancy rates in varicocele patients who have impairment of
seminal parameters and/or couple infertility.
DESIGN: Longitudinal, noncomparative study.
SETTING: Tertiary university hospital.
PATIENT(S): Three hundred sixty-four consecutive varicocele patients with seminal
impairment, including 173 (47.5%) patients who were not interested in fertility
and 191 (52.5%) who were infertile.
INTERVENTION(S): Modified antegrade scrotal sclerotherapy.
MAIN OUTCOME MEASURE(S): Increase in sperm count, motility, and/or normal forms
in all patients. Pregnancy rates 12 months after treatment in infertile men.
RESULT(S): The median patient age was 32 years. Twelve months after treatment,
persistent reflux was present in 45 (12.4%) cases. In 188 (51.6%) patients with
low sperm number, sperm count statistically significantly improved, from 12 to
19.5 x 10(6) per milliliter. In the 336 (92.3%) patients with asthenospermia,
progressive motile forms statistically significantly improved, from 25% to 45%.
In the 147 (40.4%) patients with teratospermia, normal forms increased from 17%
to 35%. In infertile patients without persistent varicocele, 65 (37.4%) patients
fathered offspring. Patients obtaining a pregnancy presented a significantly
higher sperm motility than did infertile patients (46% vs. 35%).
CONCLUSION(S): Antegrade scrotal sclerotherapy significantly improves sperm
count, motility, and morphology. Patients with couple infertility achieved a
pregnancy in 37% of cases. Patients achieving pregnancy present a better
progressive motility after treatment than patients who did not father any child
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