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Objectives: Cytogenetic abnormalities are predictors of poor prognosis in multiple myeloma (MM). This paper aims to build and validate a multiparametric conventional and functional whole-body MRI-based prediction model for cytogenetic risk classification in newly diagnosed MM., Methods: Patients with newly diagnosed MM who underwent multiparametric conventional whole-body MRI, spinal dynamic contrast-enhanced (DCE-)MRI, spinal diffusion-weighted MRI (DWI) and had genetic analysis were retrospectively included (2011-2020/Ghent University Hospital/Belgium). Patients were stratified into standard versus intermediate/high cytogenetic risk groups. After segmentation, 303 MRI features were extracted. Univariate and model-based methods were evaluated for feature and model selection. Testing was performed using receiver operating characteristic (ROC) and precision-recall curves. Models comparing the performance for genetic risk classification of the entire MRI protocol and of all MRI sequences separately were evaluated, including all features. Four final models, including only the top three most predictive features, were evaluated., Results: Thirty-one patients were enrolled (mean age 66 ± 7 years, 15 men, 13 intermediate-/high-risk genetics). None of the univariate models and none of the models with all features included achieved good performance. The best performing model with only the three most predictive features and including all MRI sequences reached a ROC-area-under-the-curve of 0.80 and precision-recall-area-under-the-curve of 0.79. The highest statistical performance was reached when all three MRI sequences were combined (conventional whole-body MRI + DCE-MRI + DWI). Conventional MRI always outperformed the other sequences. DCE-MRI always outperformed DWI, except for specificity., Conclusions: A multiparametric MRI-based model has a better performance in the noninvasive prediction of high-risk cytogenetics in newly diagnosed MM than conventional MRI alone., Critical Relevance Statement: An elaborate multiparametric MRI-based model performs better than conventional MRI alone for the noninvasive prediction of high-risk cytogenetics in newly diagnosed multiple myeloma; this opens opportunities to assess genetic heterogeneity thus overcoming sampling bias., Key Points: • Standard genetic techniques in multiple myeloma patients suffer from sampling bias due to tumoral heterogeneity. • Multiparametric MRI noninvasively predicts genetic risk in multiple myeloma. • Combined conventional anatomical MRI, DCE-MRI, and DWI had the highest statistical performance to predict genetic risk. • Conventional MRI alone always outperformed DCE-MRI and DWI separately to predict genetic risk. DCE-MRI alone always outperformed DWI separately, except for the parameter specificity to predict genetic risk. • This multiparametric MRI-based genetic risk prediction model opens opportunities to noninvasively assess genetic heterogeneity thereby overcoming sampling bias in predicting genetic risk in multiple myeloma., (© 2024. The Author(s).)

Background: Malaria is a leading cause of childhood mortality worldwide. However, accurate estimates of malaria prevalence and causality among patients who die at the country level are lacking due to the limited specificity of diagnostic tools used to attribute etiologies. Accurate estimates are crucial for prioritizing interventions and resources aimed at reducing malaria-related mortality., Methods: Seven Child Health and Mortality Prevention Surveillance (CHAMPS) Network sites collected comprehensive data on stillbirths and children <5 years, using minimally invasive tissue sampling (MITS). A DeCoDe (Determination of Cause of Death) panel employed standardized protocols for assigning underlying, intermediate, and immediate causes of death, integrating sociodemographic, clinical, laboratory (including extensive microbiology, histopathology, and malaria testing), and verbal autopsy data. Analyses were conducted to ascertain the strength of evidence for cause of death (CoD), describe factors associated with malaria-related deaths, estimate malaria-specific mortality, and assess the proportion of preventable deaths., Findings: Between December 3, 2016, and December 31, 2022, 2673 deaths underwent MITS and had a CoD attributed from four CHAMPS sites with at least 1 malaria-attributed death. No malaria-attributable deaths were documented among 891 stillbirths or 924 neonatal deaths, therefore this analysis concentrates on the remaining 858 deaths among children aged 1-59 months. Malaria was in the causal chain for 42.9% (126/294) of deaths from Sierra Leone, 31.4% (96/306) in Kenya, 18.2% (36/198) in Mozambique, 6.7% (4/60) in Mali, and 0.3% (1/292) in South Africa. Compared to non-malaria related deaths, malaria-related deaths skewed towards older infants and children (p < 0.001), with 71.0% among ages 12-59 months. Malaria was the sole infecting pathogen in 184 (70.2%) of malaria-attributed deaths, whereas bacterial and viral co-infections were identified in the causal pathway in 24·0% and 12.2% of cases, respectively. Malnutrition was found at a similar level in the causal pathway of both malaria (26.7%) and non-malaria (30.7%, p = 0.256) deaths. Less than two-thirds (164/262; 62.6%) of malaria deaths had received antimalarials prior to death. Nearly all (98·9%) malaria-related deaths were deemed preventable., Interpretation: Malaria remains a significant cause of childhood mortality in the CHAMPS malaria-endemic sites. The high bacterial co-infection prevalence among malaria deaths underscores the potential benefits of antibiotics for severe malaria patients. Compared to non-malaria deaths, many of malaria-attributed deaths are preventable through accessible malaria control measures., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: The objective of our study is to evaluate the involvement of the transient receptor potential vanilloid 4 (TRPV4) in the alteration of lymphatic pumping in response to flow and determine the signaling pathways involved., Methods: We used immunofluorescence imaging and western blotting to assess TRPV4 expression in rat mesenteric lymphatic vessels. We examined inhibition of TRPV4 with HC067047, nitric oxide synthase (NOS) with L-NNA and cyclooxygenases (COXs) with indomethacin on the contractile response of pressurized lymphatic vessels to flow changes induced by a stepwise increase in pressure gradients, and the functionality of endothelial TRPV4 channels by measuring the intracellular Ca 2+ response of primary lymphatic endothelial cell cultures to the selective agonist GSK1016790A., Results: TRPV4 protein was expressed in both the endothelial and the smooth muscle layer of rat mesenteric lymphatics with high endothelial expression around the valve sites. When maintained under constant transmural pressure, most lymphatic vessels displayed a decrease in contraction frequency under conditions of flow and this effect was ablated through inhibition of NOS, COX or TRPV4., Conclusions: Our findings demonstrate a critical role for TRPV4 in the decrease in contraction frequency induced in lymphatic vessels by increases in flow rate via the production and action of nitric oxide and dilatory prostanoids., (© 2023 John Wiley & Sons Ltd.)

The last decades, increasing research has been conducted on dynamic contrast-enhanced and diffusion-weighted MRI techniques in multiple myeloma and its precursors. Apart from anatomical sequences which are prone to interpretation errors due to anatomical variants, other pathologies and subjective evaluation of signal intensities, dynamic contrast-enhanced and diffusion-weighted MRI provide additional information on microenvironmental changes in bone marrow and are helpful in the diagnosis, staging and follow-up of plasma cell dyscrasias. Diffusion-weighted imaging provides information on diffusion (restriction) of water molecules in bone marrow and in malignant infiltration. Qualitative evaluation by visually assessing images with different diffusion sensitising gradients and quantitative evaluation of the apparent diffusion coefficient are studied extensively. Dynamic contrast-enhanced imaging provides information on bone marrow vascularisation, perfusion, capillary resistance, vascular permeability and interstitial space, which are systematically altered in different disease stages and can be evaluated in a qualitative and a (semi-)quantitative manner. Both diffusion restriction and abnormal dynamic contrast-enhanced MRI parameters are early biomarkers of malignancy or disease progression in focal lesions or in regions with diffuse abnormal signal intensities. The added value for both techniques lies in better detection and/or characterisation of abnormal bone marrow otherwise missed or misdiagnosed on anatomical MRI sequences. Increased detection rates of focal lesions or diffuse bone marrow infiltration upstage patients to higher disease stages, provide earlier access to therapy and slower disease progression and allow closer monitoring of high-risk patients. Despite promising results, variations in imaging protocols, scanner types and post-processing methods are large, thus hampering universal applicability and reproducibility of quantitative imaging parameters. The myeloma response assessment and diagnosis system and the international myeloma working group provide a systematic multicentre approach on imaging and propose which parameters to use in multiple myeloma and its precursors in an attempt to overcome the pitfalls of dynamic contrast-enhanced and diffusion-weighted imaging.Single sentence summary statementDiffusion-weighted imaging and dynamic contrast-enhanced MRI provide important additional information to standard anatomical MRI techniques for diagnosis, staging and follow-up of patients with plasma cell dyscrasias, although some precautions should be taken on standardisation of imaging protocols to improve reproducibility and application in multiple centres., (© 2021. ISS.)