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ICM Partners

About: ICM Partners is a based out in . It is known for research contribution in the topics: Population & Breast cancer. The organization has 1311 authors who have published 1521 publications receiving 33745 citations. The organization is also known as: International Creative Management Partners.


Papers
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Journal ArticleDOI
02 Nov 2017-PLOS ONE
TL;DR: Lesions in deep gray matter nuclei may predict long-term outcome after severe TBI with high sensitivity and specificity.
Abstract: Purpose This study evaluates the correlation between injuries to deep gray matter nuclei, as quantitated by lesions in these nuclei on MR T2 Fast Spin Echo (T2 FSE) images, with 6-month neurological outcome after severe traumatic brain injury (TBI). Materials and methods Ninety-five patients (80 males, mean age = 36.7y) with severe TBI were prospectively enrolled. All patients underwent a MR scan within the 45 days after the trauma that included a T2 FSE acquisition. A 3D deformable atlas of the deep gray matter was registered to this sequence; deep gray matter lesions (DGML) were evaluated using a semi-quantitative classification scheme. The 6-month outcome was dichotomized into unfavorable (death, vegetative or minimally conscious state) or favorable (minimal or no neurologic deficit) outcome. Results Sixty-six percent of the patients (63/95) had both satisfactory registration of the 3D atlas on T2 FSE and available clinical follow-up. Patients without DGML had an 89% chance (P = 0.0016) of favorable outcome while those with bilateral DGML had an 80% risk of unfavorable outcome (P = 0.00008). Multivariate analysis based on DGML accurately classified patients with unfavorable neurological outcome in 90.5% of the cases. Conclusion Lesions in deep gray matter nuclei may predict long-term outcome after severe TBI with high sensitivity and specificity.

8 citations

Journal ArticleDOI
TL;DR: This paper performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS) and acute myeloid leukemia (AML) post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters.
Abstract: In spite of the recent discovery of genetic mutations in most myelodysplasic (MDS) patients, the pathophysiology of these disorders still remains poorly understood, and only few in vivo models are available to help unravel the disease. We performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS) and acute myeloid leukemia (AML) post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters MRP8NRASD12/tethBCL-2 or MRP8[NRASD12/hBCL-2], respectively. Analysis of dysregulated genes that were unique to the diseased HR-MDS and AML post MDS mice and not their founder mice pointed first to pathways that had previously been reported in MDS patients, including DNA replication/damage/repair, cell cycle, apoptosis, immune responses, and canonical Wnt pathways, further validating these models at the gene expression level. Interestingly, pathways not previously reported in MDS were discovered. These included dysregulated genes of noncanonical Wnt pathways and energy and lipid metabolisms. These dysregulated genes were not only confirmed in a different independent set of BM and spleen Sca1+ cells from the MDS mice but also in MDS CD34+ BM patient samples. These two MDS models may thus provide useful preclinical models to target pathways previously identified in MDS patients and to unravel novel pathways highlighted by this study.

8 citations

Journal ArticleDOI
01 Feb 2019-Cortex
TL;DR: Functional near-infrared spectroscopy was used to measure changes in RSFC and found a significant learning effect indicated by a monotonic decrease in reaction time and an increase in accuracy, suggesting the sensitivity and importance of fronto-parietal connectivity to arithmetic learning.

8 citations

Journal ArticleDOI
TL;DR: This work uses calibration‐free parallel transmission, a dedicated pulse‐sequence parameter optimization and signal fitting to recover 3D proton density, flip angle, T1, and T2 maps over the whole brain, in a clinically suitable time.
Abstract: Purpose: Performing simultaneous quantitative MRI at ultra-high field is challenging, as B0 and B1 + heterogeneities as well as Specific Absorption Rate increase. Too large deviations of flip angle from the target can induce biases and impair signal-to-noise ratio in the quantification process. In this work, we use calibration-free parallel transmission, a dedicated pulse sequence parameter optimization and signal fitting to recover 3D proton density, flip angle, T1 and T2 maps over the whole brain, in a clinically suitable time. Methods: Eleven optimized contrasts were acquired with an unbalanced Steady-State Free Precession sequence by varying flip angle amplitude and radiofrequency phase cycling increment, at a 1.0x1.0x3.0mm 3 resolution. Acquisition time was of 16min36sec for the whole brain. Parallel transmission and Universal Pulses were used to mitigate B1 + heterogeneity to improve the results' reliability over six healthy volunteers (3 females/males, age 22.6±2.7 years-old). Quantification of the physical parameters was performed by fitting acquired contrasts to the simulated ones using the Bloch-Torrey equations with a realistic diffusion coefficient. Results: Whole-brain 3D maps of effective flip angle, PD and relaxation times were estimated. Parallel transmission improved the robustness of the results at 7T. Results were in accordance with literature and with measurements from standard methods. Conclusion: These preliminary results show robust PD, FA, T1 and T2 map retrieval. Other parameters, such as Apparent Diffusion Coefficient, could be assessed. With further optimization in the acquisition, scan time could be reduced and spatial resolution increased to bring this multi-parametric quantification method to clinical research routine at 7-tesla.

8 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated cfDNA and mutant ctDNA as potential biomarkers to predict the best outcomes of regorafenib-treated metastatic colorectal cancer (mCRC) patients.

8 citations


Authors

Showing all 1311 results

NameH-indexPapersCitations
Alexis Brice13587083466
Bruno Dubois12464678784
Harald Hampel10960165160
Alexandra Durr10459447018
Laurent D. Cohen9441742709
Jürgen Eckert92136842119
Stéphane Lehéricy8933227214
Antoine Danchin8048330219
Marie Vidailhet7939121836
Josep M. Gasol7731322638
Mélanie Boly7623221552
Etienne C. Hirsch7521822591
Måns Ehrenberg7423417637
Elizabeth M. C. Fisher7429821150
Isabelle Arnulf7333118456
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20223
2021141
2020171
2019167
2018160
2017172