192 research outputs found
Real-time diagnostics of gas/water assisted injection moulding using integrated ultrasonic sensors
YesAn ultrasound sensor system has been applied to the mould of both the water and gas assisted
injection moulding processes. The mould has a cavity wall mounted pressure sensor and instrumentation to
monitor the injection moulding machine. Two ultrasound sensors are used to monitor the arrival of the fluid
(gas or water) bubble tip through the detection of reflected ultrasound energy from the fluid polymer
boundary and the fluid bubble tip velocity through the polymer melt is estimated. The polymer contact with
the cavity wall is observed through the reflected ultrasound energy from that boundary. A theoretically
based estimation of the residual wall thickness is made using the ultrasound reflection from the fluid (gas or
water) polymer boundary whilst the samples are still inside the mould and a good correlation with a physical
measurement is observed
Habitudes de vie et qualité de vie des couples qui désirent se prévaloir des services du programme québécois de procréation médicalement assistée
Scaling, Propagation, and Kinetic Roughening of Flame Fronts in Random Media
We introduce a model of two coupled reaction-diffusion equations to describe
the dynamics and propagation of flame fronts in random media. The model
incorporates heat diffusion, its dissipation, and its production through
coupling to the background reactant density. We first show analytically and
numerically that there is a finite critical value of the background density,
below which the front associated with the temperature field stops propagating.
The critical exponents associated with this transition are shown to be
consistent with mean field theory of percolation. Second, we study the kinetic
roughening associated with a moving planar flame front above the critical
density. By numerically calculating the time dependent width and equal time
height correlation function of the front, we demonstrate that the roughening
process belongs to the universality class of the Kardar-Parisi-Zhang interface
equation. Finally, we show how this interface equation can be analytically
derived from our model in the limit of almost uniform background density.Comment: Standard LaTeX, no figures, 29 pages; (to appear in J. Stat. Phys.
vol.81, 1995). Complete file available at
http://www.physics.helsinki.fi/tft/tft.html or anonymous ftp at
ftp://rock.helsinki.fi/pub/preprints/tft
Presence of tumor necrosis factor-alpha in urine samples of patients with chronic low back pain undergoing chiropractic care: Preliminary findings from a prospective cohort study
Background and aims:
Low back pain is the leading cause of years lived with disability worldwide. Chiropractors employ different interventions to treat low back pain, including spinal manipulative therapy, although the mechanisms through which chiropractic care improves low back pain are still unclear. Clinical research and animal models suggest that spinal manipulation might modulate plasma levels of inflammatory cytokines, which have been involved in different stages of low back pain. More specifically, serum levels of Tumor Necrosis Factor-alpha (TNF-α) have been found to be elevated in patients with chronic low back pain. We aimed to investigate whether urine from chronic low back pain patients could be an appropriate medium to measure concentrations of TNF-α and to examine possible changes in its levels associated to chiropractic care.
Methods:
Urine samples were collected from 24 patients with chronic low back pain and TNF-α levels were analyzed by ELISA before and after 4–6 weeks of care compared to a reference value obtained from 5 healthy control subjects, by means of a Welch’s t-test. Simultaneously, pain intensity and disability were also evaluated before and after care. Paired t-tests were used to compare mean pre and post urinary concentrations of TNF-α and clinical outcomes.
Results:
Significantly higher baseline levels of urinary TNF-α were observed in chronic low back pain patients when compared to our reference value (p < 0.001), which were significantly lower after the period of chiropractic treatment (p = 0.03). Moreover, these changes were accompanied by a significant reduction in pain and disability (both p < 0.001). However, levels of urinary TNF-α were not correlated with pain intensity nor disability.
Conclusion:
These results suggest that urine could be a good milieu to assess TNF-α changes, with potential clinical implications for the management of chronic low back pain. Copyright © 2022 Gevers-Montoro, Romero-Santiago, Losapio, Conesa-Buendía, Newell, Álvarez-Galovich, Piché and Ortega-De Mues
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Targeted T1 Magnetic Resonance Imaging Contrast Enhancement with Extraordinarily Small CoFe2O4 Nanoparticles
Extraordinarily small (2.4 nm) cobalt ferrite nanoparticles (ESCIoNs) were synthesized by a one-pot thermal decomposition approach to study their potential as magnetic resonance imaging (MRI) contrast agents. Fine size control was achieved using oleylamine alone, and annular dark-field scanning transmission electron microscopy revealed highly crystalline cubic spinel particles with atomic resolution. Ligand exchange with dimercaptosuccinic acid rendered the particles stable in physiological conditions with a hydrodynamic diameter of 12 nm. The particles displayed superparamagnetic properties and a low r2/r1 ratio suitable for a T1 contrast agent. The particles were functionalized with bile acid, which improved biocompatibility by significant reduction of reactive oxygen species generation and is a first step toward liver-targeted T1 MRI. Our study demonstrates the potential of ESCIoNs as T1 MRI contrast agents
Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context
Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas
This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing
molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin
Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas
Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images
of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL
maps are derived through computational staining using a convolutional neural network trained to
classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and
correlation with overall survival. TIL map structural patterns were grouped using standard
histopathological parameters. These patterns are enriched in particular T cell subpopulations
derived from molecular measures. TIL densities and spatial structure were differentially enriched
among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial
infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic
patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for
the TCGA image archives with insights into the tumor-immune microenvironment
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