Increased mean platelet volume (MPV) is an independent predictor of inferior survival in patients with primary and secondary myelofibrosis

Neoplastic megakaryopoiesis is a dominant feature of Philadelphia-chromosome-negative myeloproliferative neoplasms (Ph- MPNs), and elevated mean-platelet-volume (MPV) is a common finding in these diseases. The clinical and prognostic significances of MPV in patients with primary (PMF) and secondary myelofibrosis (SMF) have not been reported. We retrospectively analyzed 87 patients with myelofibrosis (66 with PMF, 21 with SMF) treated at our institution. MPV was recorded in addition to other hematological and clinical parameters. MPV was elevated in both PMF and SMF patients in comparison to controls, whereas there was no statistically significant difference between PMF and SMF. Elevated MPV was associated with lower platelets (P = 0.016), higher white blood cells (P = 0.015), higher percentage of circulatory blasts (P = 0.009), higher lactate dehydrogenase (P = 0.011), larger spleen size (P = 0.014) and higher Dynamic International Prognostic score category (P = 0.027), while there was no statistically significant association with driver mutations or degree of bone marrow fibrosis. Higher MPV was univariately associated with inferior overall survival in the whole cohort (HR = 3.82, P = 0.006), PMF (HR = 4.35, P = 0.007) and SMF patients (HR = 7.22, P = 0.034). These associations remained significant in multivariate analyses adjusted for DIPSS. Higher MPV is associated with more aggressive disease features and exhibits powerful independent prognostic properties in both PMF and SMF settings

Assessing serum albumin concentration, lymphocyte count and prognostic nutritional index might improve prognostication in patients with myelofibrosis

BACKGROUND: Primary and secondary myelofibrosis (PMF and SMF) are malignant diseases of hematopoietic stem cell characterized by the neoplastic myeloproliferation and a strong inflammatory milieu. The prognostic nutritional index (PNI) integrates information on albumin and absolute lymphocyte count (ALC) and reflects the inflammatory, nutritional and immune status of a patient. The clinical and prognostic significance of albumin, ALC and PNI in patients with myelofibrosis has not been previously investigated. ----- METHODS: We retrospectively analyzed a cohort of 83 myelofibrosis patients treated in our institution from 2006 to 2017. Albumin, ALC and PNI were assessed in addition to other disease specific markers. ----- RESULTS: The PMF and SMF patients had significantly lower ALC and PNI but similar albumin compared to controls. Lower albumin was significantly associated with older age and parameters reflecting more aggressive disease biology (e.g. anemia, lower platelet levels, higher lactate dehydrogenase (LDH), circulatory blasts, transfusion dependency, blast phase disease), inflammation (higher C reactive protein (CRP), constitutional symptoms) and higher degree of bone marrow fibrosis. Lower ALC was significantly associated with lower white blood cells (WBC) and lower circulatory blasts. Low PNI was associated with lower albumin, lower ALC, anemia, lower WBCs, lower serum iron and lower transferrin saturation. There was no difference in albumin, ALC and PNI regarding the driver mutations. In multivariate analysis adjusted for age and gender, low albumin (hazard ratio [HR] = 4.61, P = 0.001), low ALC (HR = 3.54, P = 0.004) and Dynamic International Prognostic Scoring System (DIPSS) (HR = 2.45, P = 0.001) were able to predict inferior survival independently of each other. Accordingly, low PNI (HR = 4.32, P < 0.001) predicted poor survival independently of DIPSS (HR = 3.31, P < 0.001). ----- CONCLUSION: Assessing albumin, ALC and PNI might improve prognostication in patients with myelofibrosis and could assist in recognition of patients under increased risk of death

Multiscale in modelling and validation for solar photovoltaics

Photovoltaics is amongst the most important technologies for renewable energy sources, and plays a key role in the development of a society with a smaller environmental footprint. Key parameters for solar cells are their energy conversion efficiency, their operating lifetime, and the cost of the energy obtained from a photovoltaic system compared to other sources. The optimization of these aspects involves the exploitation of new materials and development of novel solar cell concepts and designs. Both theoretical modeling and characterization of such devices require a comprehensive view including all scales from the atomic to the macroscopic and industrial scale. The different length scales of the electronic and optical degrees of freedoms specifically lead to an intrinsic need for multiscale simulation, which is accentuated in many advanced photovoltaics concepts including nanostructured regions. Therefore, multiscale modeling has found particular interest in the photovoltaics community, as a tool to advance the field beyond its current limits. In this article, we review the field of multiscale techniques applied to photovoltaics, and we discuss opportunities and remaining challenges