352 research outputs found
One More Step Towards Well-Composedness of Cell Complexes over nD Pictures
An nD pure regular cell complex K is weakly well-composed
(wWC) if, for each vertex v of K, the set of n-cells incident to v is
face-connected. In previous work we proved that if an nD picture I is
digitally well composed (DWC) then the cubical complex Q(I) associated
to I is wWC. If I is not DWC, we proposed a combinatorial algorithm
to “locally repair” Q(I) obtaining an nD pure simplicial complex PS(I)
homotopy equivalent to Q(I) which is always wWC. In this paper we give
a combinatorial procedure to compute a simplicial complex PS(¯I) which
decomposes the complement space of |PS(I)| and prove that PS(¯I) is also
wWC. This paper means one more step on the way to our ultimate goal:
to prove that the nD repaired complex is continuously well-composed
(CWC), that is, the boundary of its continuous analog is an (n − 1)-
manifold.Ministerio de Economía y Competitividad MTM2015-67072-
Comparison of MRI properties between multimeric DOTAGA and DO3A gadolinium-dendron conjugates
The inherent lack of sensitivity of MRI needs the development of new Gd contrast agents in order to extend 20Hz,37%, the application of this technique to cellular imaging. For this purpose, two multimeric MR contrast agents obtained by peptidic coupling between an amido amine dendron and GdDOTAGA chelates (premetalation strategy, G1-4GdDOTAGA) or DO3A derivatives which then were postmetalated (G1-4GdDO-3A) have been prepared. By comparison to the monomers, an increase of longitudinal relaxivity has been observed for both structures. Especially for G1-4GdDO-3A, a marked increase is observed between 20 and 60 MHz. This structure differs from G1-4GdDOTAGA by an increased rigidity due to the aromatic linker between each chelate and the organic framework. This has the effect of limiting local rotational movements, which has a positive impact on relaxivity
Antioxidant, antibacterial and cell toxicity effects of polyphenols Fromahmeur bouamer grape seed extracts
In this work and for the first time, significant concentrations of total polyphenols and flavonoids from Vitis vinifera L. grape seed extracts were obtained (256.15 ± 17.40 mg GAE/gdm and 14.08 ± 0.64 mg CE/gdm, respectively).The LC/MS analysis revealed richness in procyanidins. For antioxidant, antimicrobial and antifungal effects, the grape seed extract (GSE) responded positively. At 100 μg/mL, GSE induced a moderate toxicity of the order of 3.88% on 3T6 cells at the first 24 hours of treatment, whereas, its prolonged effect to 48 hours reduced this toxicity to less than 0.5%. As for the anti-proliferative effect on tumoral cell lines, a cell death of 18.39% to 23.79% and 10.30% to 20.37% was registered respectively for HeLa and BCPAP cells during 24 and 48 hours of treatment. Consequently, it is possible to consider using GSE at lower concentrations as an anti-proliferative agent without losing sight of its benefic effect on healthy cells.Keywords: grape seed extract, 3T6 cell, antioxidant, antibacterial, anti-proliferation
Synthesis and Relaxometric Characterization of New Poly[N,N-bis(3-aminopropyl)glycine] (PAPGly) Dendrons Gd-Based Contrast Agents and Their in Vivo Study by Using the Dynamic Contrast-Enhanced MRI Technique at Low Field (1 T)
How does a cadaver model work for testing ultrasound diagnostic capability for rheumatic-like tendon damage?
To establish whether a cadaver model can serve as an effective surrogate for the detection of tendon damage characteristic of rheumatoid arthritis (RA). In addition, we evaluated intraobserver and interobserver agreement in the grading of RA-like tendon tears shown by US, as well as the concordance between the US findings and the surgically induced lesions in the cadaver model. RA-like tendon damage was surgically induced in the tibialis anterior tendon (TAT) and tibialis posterior tendon (TPT) of ten ankle/foot fresh-frozen cadaveric specimens. Of the 20 tendons examined, six were randomly assigned a surgically induced partial tear; six a complete tear; and eight left undamaged. Three rheumatologists, experts in musculoskeletal US, assessed from 1 to 5 the quality of US imaging of the cadaveric models on a Likert scale. Tendons were then categorized as having either no damage, (0); partial tear, (1); or complete tear (2). All 20 tendons were blindly and independently evaluated twice, over two rounds, by each of the three observers. Overall, technical performance was satisfactory for all items in the two rounds (all values over 2.9 in a Likert scale 1-5). Intraobserver and interobserver agreement for US grading of tendon damage was good (mean κ values 0.62 and 0.71, respectively), with greater reliability found in the TAT than the TPT. Concordance between US findings and experimental tendon lesions was acceptable (70-100 %), again greater for the TAT than for the TPT. A cadaver model with surgically created tendon damage can be useful in evaluating US metric properties of RA tendon lesions
Mn2+ Complexes with Pyclen-Based Derivatives as Contrast Agents for Magnetic Resonance Imaging: Synthesis and Relaxometry Characterization
Magnetic resonance imaging (MRI) has a leading place in medicine as an imaging tool of high resolution for anatomical studies and diagnosis of diseases, in particular for soft tissues that cannot be accessible by other modalities. Many research works are thus focused on improving the images obtained with MRI. This technique has indeed poor sensitivity, which can be compensated by using a contrast agent (CA). Today, the clinically approved CAs on market are solely based on gadolinium complexes that may induce nephrogenic systemic fibrosis for patients with kidney failure, whereas more recent studies on healthy rats also showed Gd retention in the brain. Consequently, researchers try to elaborate other types of safer MRI CAs like manganese-based complexes. In this context, the synthesis of Mn2+ complexes of four 12-membered pyridine-containing macrocyclic ligands based on the pyclen core was accomplished and described herein. Then, the properties of these Mn(II) complexes were studied by two relaxometric methods, 17O NMR spectroscopy and 1H NMR dispersion profiles. The time of residence (τM) and the number of water molecules (q) present in the inner sphere of coordination were determined by these two experiments. The efficacy of the pyclen-based Mn(II) complexes as MRI CAs was evaluated by proton relaxometry at a magnetic field intensity of 1.41 T near those of most medical MRI scanners (1.5 T). Both the 17O NMR and the nuclear magnetic relaxation dispersion profiles indicated that the four hexadentate ligands prepared herein left one vacant coordination site to accommodate one water molecule, rapidly exchanging, in around 6 ns. Furthermore, it has been shown that the presence of an additional amide bond formed when the paramagnetic complex is conjugated to a molecule of interest does not alter the inner sphere of coordination of Mn, which remains monohydrated. These complexes exhibit r1 relaxivities, large enough to be used as clinical MRI CAs (1.7–3.4 mM–1·s–1, at 1.41 T and 37 °C)
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing
reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation
of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core
challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and
2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of
deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020
challenges are designed to address research questions in these remits. In this paper, we present a summary of methods
developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by
the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and
segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled
for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also
evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The
best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences
by exploring data augmentation, data fusion, and optimal class thresholding techniques
Tailoring force sensitivity and selectivity by microstructure engineering of multidirectional electronic skins
Electronic skins (e-skins) with high sensitivity to multidirectional mechanical stimuli are crucial for healthcare monitoring devices, robotics, and wearable sensors. In this study, we present piezoresistive e-skins with tunable force sensitivity and selectivity to multidirectional forces through the engineered microstructure geometries (i.e., dome, pyramid, and pillar). Depending on the microstructure geometry, distinct variations in contact area and localized stress distribution are observed under different mechanical forces (i.e., normal, shear, stretching, and bending), which critically affect the force sensitivity, selectivity, response/relaxation time, and mechanical stability of e-skins. Microdome structures present the best force sensitivities for normal, tensile, and bending stresses. In particular, microdome structures exhibit extremely high pressure sensitivities over broad pressure ranges (47,062 kPa(-1) in the range of < 1 kPa, 90,657 kPa(-1) in the range of 1-10 kPa, and 30,214 kPa(-1) in the range of 10-26 kPa). On the other hand, for shear stress, micropillar structures exhibit the highest sensitivity. As proof-of-concept applications in healthcare monitoring devices, we show that our e-skins can precisely monitor acoustic waves, breathing, and human artery/carotid pulse pressures. Unveiling the relationship between the microstructure geometry of e-skins and their sensing capability would provide a platform for future development of high-performance microstructured e-skins
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and 2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020 challenges are designed to address research questions in these remits. In this paper, we present a summary of methods developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences by exploring data augmentation, data fusion, and optimal class thresholding technique
MRI identifies plantar plate pathology in the forefoot of patients with rheumatoid arthritis
Previous cadaveric studies have suggested that forefoot deformities at the metatarsophalangeal (MTP) joints in patients with rheumatoid arthritis (RA) might result from the failure of the ligamentous system and displacement of the plantar plates. This study aimed to examine the relationship between plantar plate pathology and the rheumatoid arthritis magnetic resonance imaging score (RAMRIS) of the lesser (second to fifth) MTP joints in patients with RA using high-resolution 3 T magnetic resonance imaging (MRI). In 24 patients with RA, the forefoot was imaged using 3 T MRI. Proton density fat-suppressed, T2-weighted fat-suppressed and T1-weighted post gadolinium sequences were acquired through 96 lesser MTP joints. Images were scored for synovitis, bone marrow oedema and bone erosion using the RAMRIS system and the plantar plates were assessed for pathology. Seventeen females and 7 males with a mean age of 55.5 years (range 37–71) and disease duration of 10.6 years (range 0.6–36) took part in the study. Plantar plate pathology was most frequently demonstrated on MRI at the fifth MTP joint. An association was demonstrated between plantar plate pathology and RAMRIS-reported synovitis, bone marrow oedema and bone erosion at the fourth and fifth MTP joints. In patients with RA, 3 T MRI demonstrates that plantar plate pathology at the lesser MTP joints is associated with features of disease severity. Plantar plate pathology is more common at the fourth and fifth MTP joints in subjects with RA in contrast to the predilection for the second MTP reported previously in subjects without RA
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