Convection in nanofluids with a particle-concentration-dependent thermal conductivity

Thermal convection in nanofluids is investigated by means of a continuum model for binary-fluid mixtures, with a thermal conductivity depending on the local concentration of colloidal particles. The applied temperature difference between the upper and the lower boundary leads via the Soret effect to a variation of the colloid concentration and therefore to a spatially varying heat conductivity. An increasing difference between the heat conductivity of the mixture near the colder and the warmer boundary results in a shift of the onset of convection to higher values of the Rayleigh number for positive values of the separation ratio psi>0 and to smaller values in the range psi<0. Beyond some critical difference of the thermal conductivity between the two boundaries, we find an oscillatory onset of convection not only for psi<0, but also within a finite range of psi>0. This range can be extended by increasing the difference in the thermal conductivity and it is bounded by two codimension-2 bifurcations.Comment: 13 pages, 11 figures; submitted to Physical Review

Thrombocytopenia limits the feasibility of salvage lomustine chemotherapy in recurrent glioblastoma: a secondary analysis of EORTC 26101

BACKGROUND Thrombocytopenia represents the main cause of stopping alkylating chemotherapy for toxicity. Here, we explored the incidence, and the consequences for treatment exposure and survival, of thrombocytopenia induced by lomustine in recurrent glioblastoma. METHODS We performed a retrospective analysis of the associations of thrombocytopenia with treatment delivery and outcome in EORTC 26101, a randomised trial designed to define the role of lomustine versus bevacizumab versus their combination in recurrent glioblastoma. RESULTS A total of 225 patients were treated with lomustine alone (median 1 cycle) (group 1) and 283 patients were treated with lomustine plus bevacizumab (median 3 lomustine cycles) (group 2). Among cycle delays and dose reductions of lomustine for toxicity, thrombocytopenia was the leading cause. Among 129 patients (57%) of group 1 and 187 patients (66%) of group 2 experiencing at least one episode of thrombocytopenia, 36 patients (16%) in group 1 and 93 (33%) in group 2 had their treatment modified because of thrombocytopenia. Lomustine was discontinued for thrombocytopenia in 16 patients (7.1%) in group 1 and in 38 patients (13.4%) in group 2. On adjusted analysis accounting for major prognostic factors, dose modification induced by thrombocytopenia was associated with inferior progression-free survival in patients with MGMT promoter-methylated tumours in groups 1 and 2. This effect was noted for overall survival, too, but only for group 2 patients. CONCLUSION Drug-induced thrombocytopenia is a major limitation to adequate exposure to lomustine chemotherapy in recurrent glioblastoma. Mitigating thrombocytopenia to enhance lomustine exposure might improve outcome in patients with MGMT promoter-methylated tumours

Prognostic Markers of DNA Methylation and Next-Generation Sequencing in Progressive Glioblastoma from the EORTC-26101 Trial

PURPOSE: The EORTC-26101 study was a randomized phase II and III clinical trial of bevacizumab in combination with lomustine versus lomustine alone in progressive glioblastoma. Other than for progression-free survival (PFS), there was no benefit from addition of bevacizumab for overall survival (OS). However, molecular data allow for the rare opportunity to assess prognostic biomarkers from primary surgery for their impact in progressive glioblastoma. EXPERIMENTAL DESIGN: We analyzed DNA methylation array data and panel sequencing from 170 genes of 380 tumor samples of the EORTC-26101 study. These patients were comparable with the overall study cohort in regard to baseline characteristics, study treatment, and survival.RESULTS: Of patients' samples, 295/380 (78%) were classified into one of the main glioblastoma groups, receptor tyrosine kinase (RTK)1, RTK2 and mesenchymal. There were 10 patients (2.6%) with isocitrate dehydrogenase mutant tumors in the biomarker cohort. Patients with RTK1 and RTK2 classified tumors had lower median OS compared with mesenchymal (7.6 vs. 9.2 vs. 10.5 months). O6-methylguanine DNA-methyltransferase (MGMT) promoter methylation was prognostic for PFS and OS. Neurofibromin (NF)1 mutations were predictive of response to bevacizumab treatment.CONCLUSIONS: Thorough molecular classification is important for brain tumor clinical trial inclusion and evaluation. MGMT promoter methylation and RTK1 classifier assignment were prognostic in progressive glioblastoma. NF1 mutation may be a predictive biomarker for bevacizumab treatment.</p

Myeloid cell iron uptake pathways and paramagnetic rim formation in multiple sclerosis

In multiple sclerosis (MS), sustained inflammatory activity can be visualized by iron-sensitive magnetic resonance imaging (MRI) at the edges of chronic lesions. These paramagnetic rim lesions (PRLs) are associated with clinical worsening, although the cell type-specific and molecular pathways of iron uptake and metabolism are not well known. We studied two postmortem cohorts: an exploratory formalin-fixed paraffin-embedded (FFPE) tissue cohort of 18 controls and 24 MS cases and a confirmatory snap-frozen cohort of 6 controls and 14 MS cases. Besides myelin and non-heme iron imaging, the haptoglobin-hemoglobin scavenger receptor CD163, the iron-metabolizing markers HMOX1 and HAMP as well as immune-related markers P2RY12, CD68, C1QA and IL10 were visualized in myeloid cell (MC) subtypes at RNA and protein levels across different MS lesion areas. In addition, we studied PRLs in vivo in a cohort of 98 people with MS (pwMS) via iron-sensitive 3&nbsp;T MRI and haptoglobin genotyping by PCR. CSF samples were available from 38 pwMS for soluble CD163 (sCD163) protein level measurements by ELISA. In postmortem tissues, we observed that iron uptake was linked to rim-associated C1QA-expressing MC subtypes, characterized by upregulation of CD163, HMOX1, HAMP and, conversely, downregulation of P2RY12. We found that pwMS with [Formula: see text] 4 PRLs had higher sCD163 levels in the CSF than pwMS with [Formula: see text] 3 PRLs with sCD163 correlating with the number of PRLs. The number of PRLs was associated with clinical worsening but not with age, sex or haptoglobin genotype of pwMS. However, pwMS with Hp2-1/Hp2-2 haplotypes had higher clinical disability scores than pwMS with Hp1-1. In summary, we observed upregulation of the CD163-HMOX1-HAMP axis in MC subtypes at chronic active lesion rims, suggesting haptoglobin-bound hemoglobin but not transferrin-bound iron as a critical source for MC-associated iron uptake in MS. The correlation of CSF-associated sCD163 with PRL counts in MS highlights the relevance of CD163-mediated iron uptake via haptoglobin-bound hemoglobin. Also, while Hp haplotypes had no noticeable influence on PRL counts, pwMS carriers of a Hp2 allele might have a higher risk to experience clinical worsening

Mutational Analysis Identifies Therapeutic Biomarkers in Inflammatory Bowel Disease-Associated Colorectal Cancers.

Purpose: Inflammatory bowel disease-associated colorectal cancers (IBD-CRC) are associated with a higher mortality than sporadic colorectal cancers. The poorly defined molecular pathogenesis of IBD-CRCs limits development of effective prevention, detection, and treatment strategies. We aimed to identify biomarkers using whole-exome sequencing of IBD-CRCs to guide individualized management.Experimental Design: Whole-exome sequencing was performed on 34 formalin-fixed paraffin-embedded primary IBD-CRCs and 31 matched normal lymph nodes. Computational methods were used to identify somatic point mutations, small insertions and deletions, mutational signatures, and somatic copy number alterations. Mismatch repair status was examined.Results: Hypermutation was observed in 27% of IBD-CRCs. All hypermutated cancers were from the proximal colon; all but one of the cancers with hypermutation had defective mismatch repair or somatic mutations in the proofreading domain of DNA POLE Hypermutated IBD-CRCs had increased numbers of predicted neo-epitopes, which could be exploited using immunotherapy. We identified six distinct mutation signatures in IBD-CRCs, three of which corresponded to known mechanisms of mutagenesis. Driver genes were also identified.Conclusions: IBD-CRCs should be evaluated for hypermutation and defective mismatch repair to identify patients with a higher neo-epitope load who may benefit from immunotherapies. Prospective trials are required to determine whether IHC to detect loss of MLH1 expression in dysplastic colonic tissue could identify patients at increased risk of developing IBD-CRC. We identified mutations in genes in IBD-CRCs with hypermutation that might be targeted therapeutically. These approaches would complement and individualize surveillance and treatment programs. Clin Cancer Res; 24(20); 5133-42. ©2018 AACR

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology:a multicentre, retrospective cohort study

International audienceBackground Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology. Methods In this multicentre, retrospective cohort study, we used MRI examinations to train and validate a dCNN for synthesising post-contrast T1-weighted sequences from pre-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery sequences. We used MRI scans with availability of these sequences from 775 patients with glioblastoma treated at Heidelberg University Hospital, Heidelberg, Germany (775 MRI examinations); 260 patients who participated in the phase 2 CORE trial (1083 MRI examinations, 59 institutions); and 505 patients who participated in the phase 3 CENTRIC trial (3147 MRI examinations, 149 institutions). Separate training runs to rank the importance of individual sequences and (for a subset) diffusion-weighted imaging were conducted. Independent testing was performed on MRI data from the phase 2 and phase 3 EORTC-26101 trial (521 patients, 1924 MRI examinations, 32 institutions). The similarity between synthetic and true contrast enhancement on post-contrast T1-weighted MRI was quantified using the structural similarity index measure (SSIM). Automated tumour segmentation and volumetric tumour response assessment based on synthetic versus true post-contrast T1-weighted sequences was performed in the EORTC-26101 trial and agreement was assessed with Kaplan-Meier plots. Interpretation Generating synthetic post-contrast T1-weighted MRI from pre-contrast MRI using dCNN is feasible and quantification of the contrast-enhancing tumour burden from synthetic post-contrast T1-weighted MRI allows assessment of the patient's response to treatment with no significant difference by comparison with true post-contrast T1-weighted sequences with administration of GBCAs. This finding could guide the application of dCNN in radiology to potentially reduce the necessity of GBCA administration

Effect of 3BNC117 and romidepsin on the HIV-1 reservoir in people taking suppressive antiretroviral therapy (ROADMAP): a randomised, open-label, phase 2A trial

Background The administration of broadly neutralising anti-HIV-1 antibodies before latency reversal could facilitate elimination of HIV-1-infected CD4 T cells. We tested this concept by combining the broadly neutralising antibody 3BNC117 in combination with the latency-reversing agent romidepsin in people with HIV-1 who were taking suppressive antiretroviral therapy (ART). Methods We did a randomised, open-label, phase 2A trial at three university hospital centres in Denmark, Germany, and the USA. Eligible participants were virologically suppressed adults aged 18-65 years who were infected with HIV-1 and on ART for at least 18 months, with plasma HIV-1 RNA concentrations of less than 50 copies per mL for at least 12 months, and a CD4 T-cell count of greater than 500 cells per mu L. Participants were randomly assigned (1:1) to receive 3BNC117 plus romidepsin or romidepsin alone in two cycles. All participants received intravenous infusions of romidepsin (5 mg/m(2) given over 120 min) at weeks 0, 1, and 2 (treatment cycle 1) and weeks 8, 9, and 10 (treatment cycle 2). Those in the 3BNC117 plus romidepsin group received an intravenous infusion of 3BNC117 (30 mg/kg given over 60 min) 2 days before each treatment cycle. An analytic treatment interruption (ATI) of ART was done at week 24 in both groups. Our primary endpoint was time to viral rebound during analytic treatment interruption, which was assessed in all participants who completed both treatment cycles and ATI. We used a log-rank test to compare time to viral rebound during analytic treatment interruption between the two groups. This trial is registered with ClinicalTrials. gov, NCT02850016. It is closed to new participants, and all follow-up is complete. Findings Between March 20, 2017, and Aug 14, 2018, 22 people were enrolled and randomly assigned, 11 to the 3BNC117 plus romidepsin group and 11 to the romidepsin group. 19 participants completed both treatment cycles and the ATI: 11 in the 3BNC117 plus romidepsin group and 8 in the romidepsin group. The median time to viral rebound during ATI was 18 days (IQR 14-28) in the 3BNC117 plus romidepsin group and 28 days (21-35) in the romidepsin group B (p=0.0016). Although this difference was significant, prolongation of time to viral rebound was not clinically meaningful in either group. All participants in both groups reported adverse events, but overall the combination of 3BNC117 and romidepsin was safe. Two severe adverse events were observed in the romidepsin group during 48 weeks of follow-up, one of which-increased direct bilirubin-was judged to be related to treatment. Interpretation The combination of 3BNC117 and romidepsin was safe but did not delay viral rebound during analytic treatment interruptions in individuals on long-term ART. The results of our trial could serve as a benchmark for further optimisation of HIV-1 curative strategies among people with HIV-1 who are taking suppressive ART. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd

Autologous haematopoietic stem cell transplantation for multiple sclerosis: a position paper and registry outline

Background: While substantial progress has been made in the development of disease-modifying medications for multiple sclerosis (MS), a high percentage of treated patients still show progression and persistent inflammatory activity. Autologous haematopoietic stem cell transplantation (AHSCT) aims at eliminating a pathogenic immune repertoire through intense short-term immunosuppression that enables subsequent regeneration of a new and healthy immune system to re-establish immune tolerance for a long period of time. A number of mostly open-label, uncontrolled studies conducted over the past 20 years collected about 4000 cases. They uniformly reported high efficacy of AHSCT in controlling MS inflammatory disease activity, more markedly beneficial in relapsing-remitting MS. Immunological studies provided evidence for qualitative immune resetting following AHSCT. These data and improved safety profiles of transplantation procedures spurred interest in using AHSCT as a treatment option for MS. Objective: To develop expert consensus recommendations on AHSCT in Germany and outline a registry study project. Methods: An open call among MS neurologists as well as among experts in stem cell transplantation in Germany started in December 2021 to join a series of virtual meetings. Results: We provide a consensus-based opinion paper authored by 25 experts on the up-to-date optimal use of AHSCT in managing MS based on the Swiss criteria. Current data indicate that patients who are most likely to benefit from AHSCT have relapsing-remitting MS and are young, ambulatory and have high disease activity. Treatment data with AHSCT will be collected within the German REgistry Cohort of autologous haematopoietic stem CeLl trAnsplantation In MS (RECLAIM). Conclusion: Further clinical trials, including registry-based analyses, are urgently needed to better define the patient characteristics, efficacy and safety profile of AHSCT compared with other high-efficacy therapies and to optimally position it as a treatment option in different MS disease stages. Keywords: Autologous haematopoietic stem cell transplantation (AHSCT), multiple sclerosis, registry study, treatment recommendation

Deep-learning-based reconstruction of undersampled MRI to reduce scan times: a multicentre, retrospective, cohort study

Background: The extended acquisition times required for MRI limit its availability in resource-constrained settings. Consequently, accelerating MRI by undersampling k-space data, which is necessary to reconstruct an image, has been a long-standing but important challenge. We aimed to develop a deep convolutional neural network (dCNN) optimisation method for MRI reconstruction and to reduce scan times and evaluate its effect on image quality and accuracy of oncological imaging biomarkers. Methods: In this multicentre, retrospective, cohort study, MRI data from patients with glioblastoma treated at Heidelberg University Hospital (775 patients and 775 examinations) and from the phase 2 CORE trial (260 patients, 1083 examinations, and 58 institutions) and the phase 3 CENTRIC trial (505 patients, 3147 examinations, and 139 institutions) were used to develop, train, and test dCNN for reconstructing MRI from highly undersampled single-coil k-space data with various acceleration rates (R=2, 4, 6, 8, 10, and 15). Independent testing was performed with MRIs from the phase 2/3 EORTC-26101 trial (528 patients with glioblastoma, 1974 examinations, and 32 institutions). The similarity between undersampled dCNN-reconstructed and original MRIs was quantified with various image quality metrics, including structural similarity index measure (SSIM) and the accuracy of undersampled dCNN-reconstructed MRI on downstream radiological assessment of imaging biomarkers in oncology (automated artificial intelligence-based quantification of tumour burden and treatment response) was performed in the EORTC-26101 test dataset. The public NYU Langone Health fastMRI brain test dataset (558 patients and 558 examinations) was used to validate the generalisability and robustness of the dCNN for reconstructing MRIs from available multi-coil (parallel imaging) k-space data. Findings: In the EORTC-26101 test dataset, the median SSIM of undersampled dCNN-reconstructed MRI ranged from 0·88 to 0·99 across different acceleration rates, with 0·92 (95% CI 0·92-0·93) for 10-times acceleration (R=10). The 10-times undersampled dCNN-reconstructed MRI yielded excellent agreement with original MRI when assessing volumes of contrast-enhancing tumour (median DICE for spatial agreement of 0·89 [95% CI 0·88 to 0·89]; median volume difference of 0·01 cm3 [95% CI 0·00 to 0·03] equalling 0·21%; p=0·0036 for equivalence) or non-enhancing tumour or oedema (median DICE of 0·94 [95% CI 0·94 to 0·95]; median volume difference of -0·79 cm3 [95% CI -0·87 to -0·72] equalling -1·77%; p=0·023 for equivalence) in the EORTC-26101 test dataset. Automated volumetric tumour response assessment in the EORTC-26101 test dataset yielded an identical median time to progression of 4·27 months (95% CI 4·14 to 4·57) when using 10-times-undersampled dCNN-reconstructed or original MRI (log-rank p=0·80) and agreement in the time to progression in 374 (95·2%) of 393 patients with data. The dCNN generalised well to the fastMRI brain dataset, with significant improvements in the median SSIM when using multi-coil compared with single-coil k-space data (p<0·0001). Interpretation: Deep-learning-based reconstruction of undersampled MRI allows for a substantial reduction of scan times, with a 10-times acceleration demonstrating excellent image quality while preserving the accuracy of derived imaging biomarkers for the assessment of oncological treatment response. Our developments are available as open source software and hold considerable promise for increasing the accessibility to MRI, pending further prospective validation

Deep-learning-based reconstruction of undersampled MRI to reduce scan times:a multicentre, retrospective, cohort study

BACKGROUND: The extended acquisition times required for MRI limit its availability in resource-constrained settings. Consequently, accelerating MRI by undersampling k-space data, which is necessary to reconstruct an image, has been a long-standing but important challenge. We aimed to develop a deep convolutional neural network (dCNN) optimisation method for MRI reconstruction and to reduce scan times and evaluate its effect on image quality and accuracy of oncological imaging biomarkers. METHODS: In this multicentre, retrospective, cohort study, MRI data from patients with glioblastoma treated at Heidelberg University Hospital (775 patients and 775 examinations) and from the phase 2 CORE trial (260 patients, 1083 examinations, and 58 institutions) and the phase 3 CENTRIC trial (505 patients, 3147 examinations, and 139 institutions) were used to develop, train, and test dCNN for reconstructing MRI from highly undersampled single-coil k-space data with various acceleration rates (R=2, 4, 6, 8, 10, and 15). Independent testing was performed with MRIs from the phase 2/3 EORTC-26101 trial (528 patients with glioblastoma, 1974 examinations, and 32 institutions). The similarity between undersampled dCNN-reconstructed and original MRIs was quantified with various image quality metrics, including structural similarity index measure (SSIM) and the accuracy of undersampled dCNN-reconstructed MRI on downstream radiological assessment of imaging biomarkers in oncology (automated artificial intelligence-based quantification of tumour burden and treatment response) was performed in the EORTC-26101 test dataset. The public NYU Langone Health fastMRI brain test dataset (558 patients and 558 examinations) was used to validate the generalisability and robustness of the dCNN for reconstructing MRIs from available multi-coil (parallel imaging) k-space data. FINDINGS: In the EORTC-26101 test dataset, the median SSIM of undersampled dCNN-reconstructed MRI ranged from 0·88 to 0·99 across different acceleration rates, with 0·92 (95% CI 0·92-0·93) for 10-times acceleration (R=10). The 10-times undersampled dCNN-reconstructed MRI yielded excellent agreement with original MRI when assessing volumes of contrast-enhancing tumour (median DICE for spatial agreement of 0·89 [95% CI 0·88 to 0·89]; median volume difference of 0·01 cm3 [95% CI 0·00 to 0·03] equalling 0·21%; p=0·0036 for equivalence) or non-enhancing tumour or oedema (median DICE of 0·94 [95% CI 0·94 to 0·95]; median volume difference of -0·79 cm3 [95% CI -0·87 to -0·72] equalling -1·77%; p=0·023 for equivalence) in the EORTC-26101 test dataset. Automated volumetric tumour response assessment in the EORTC-26101 test dataset yielded an identical median time to progression of 4·27 months (95% CI 4·14 to 4·57) when using 10-times-undersampled dCNN-reconstructed or original MRI (log-rank p=0·80) and agreement in the time to progression in 374 (95·2%) of 393 patients with data. The dCNN generalised well to the fastMRI brain dataset, with significant improvements in the median SSIM when using multi-coil compared with single-coil k-space data (p&lt;0·0001). INTERPRETATION: Deep-learning-based reconstruction of undersampled MRI allows for a substantial reduction of scan times, with a 10-times acceleration demonstrating excellent image quality while preserving the accuracy of derived imaging biomarkers for the assessment of oncological treatment response. Our developments are available as open source software and hold considerable promise for increasing the accessibility to MRI, pending further prospective validation. FUNDING: Deutsche Forschungsgemeinschaft (German Research Foundation) and an Else Kröner Clinician Scientist Endowed Professorship by the Else Kröner Fresenius Foundation.</p