Ovarian Damage During Chemotherapy in Autoimmune Diseases: Broad Health Implications beyond Fertility

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94402/1/Marder_2012_Ovarian_damage_chemotherapy_autoimmune.pdf165

Fourth mRNA COVID-19 vaccination in immunocompromised patients with haematological malignancies (COBRA KAI): a cohort study

Background Patients with haematological malignancies have impaired antibody responses to SARS-CoV-2 vaccination. We aimed to investigate whether a fourth mRNA COVID-19 vaccination improved antibody quantity and quality. Methods In this cohort study, conducted at 5 sites in the Netherlands, we compared antibody concentrations 28 days after 4 mRNA vaccinations (3-dose primary series plus 1 booster vaccination) in SARS-CoV-2 naive, immunocompromised patients with haematological malignancies to those obtained by age-matched, healthy individuals who had received the standard primary 2-dose mRNA vaccination schedule followed by a first booster mRNA vaccination. Prior to and 4 weeks after each vaccination, peripheral blood samples and data on demographic parameters and medical history were collected. Concentrations of antibodies that bind spike 1 (S1) and nucleocapsid (N) protein of SARS-CoV-2 were quantified in binding antibody units (BAU) per mL according to the WHO International Standard for COVID-19 serological tests. Seroconversion was defined as an S1 IgG concentration > 10 BAU/mL and a previous SARS-CoV-2 infection as N IgG > 14.3 BAU/mL. Antibody neutralising activity was tested using lentiviral-based pseudoviruses expressing spike protein of SARS-CoV-2 wildtype (D614G), Omicron BA.1, and Omicron BA.4/5 variants. This study is registered with EudraCT, number 2021-001072-41. Findings Between March 24, 2021 and May 4, 2021, 723 patients with haematological diseases were enrolled, of which 414 fulfilled the inclusion criteria for the current analysis. Although S1 IgG concentrations in patients significantly improved after the fourth dose, they remained significantly lower compared to those obtained by 58 age-matched healthy individuals after their first booster (third) vaccination. The rise in neutralising antibody concentration was most prominent in patients with a recovering B cell compartment, although potent responses were also observed in patients with persistent immunodeficiencies. 19% of patients never seroconverted, despite 4 vaccinations. Patients who received their first 2 vaccinations when they were B cell depleted and the third and fourth vaccination during B cell recovery demonstrated similar antibody induction dynamics as patients with normal B cell numbers during the first 2 vaccinations. However, the neutralising capacity of these antibodies was significantly better than that of patients with normal B cell numbers after two vaccinations. Interpretation A fourth mRNA COVID-19 vaccination improved S1 IgG concentrations in the majority of patients with a haematological malignancy. Vaccination during B cell depletion may pave the way for better quality of antibody responses after B cell reconstitution

Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers (Jan , 10.1007/s00330-020-07598-8, 2021)

A Correction to this paper has been published:Radiolog

Incorporating radiomics into clinical trials: expert consensus on considerations for data-driven compared to biologically driven quantitative biomarkers

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials.Radiolog

Kansen voor vergroten impact van burgerinitiatieven: Theory of Change & Tiny Forests

Item does not contain fulltext06 april 202

Kansen voor vergroten impact van burgerinitiatieven : Theory of Change & Tiny Forests

Initiatieven van burgers en maatschappelijke organisaties kunnen bijdragen aan structurelemaatschappelijke veranderingen. Dit geldt ook voor een transitie naar een duurzameen natuurinclusieve samenleving. Het gebruik van een Theory of Change biedtaanknopingspunten om hun strategie aan te scherpen. Dit kan de impact van initiatievenvan groene burgerbewegingen vergroten