Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma.

Background: This study aims to analyse the effects of reducing Received Dose Intensity (RDI) in chemotherapy treatment for osteosarcoma patients on their survival by using a novel approach. Previous research has highlighted discrepancies between planned and actual RDI, even among patients randomized to the same treatment regimen. To mitigate toxic side effects, treatment adjustments, such as dose reduction or delayed courses, are necessary.

Machine Learning versus Cox Models for Predicting Overall Survival in Patients with Osteosarcoma: A Retrospective Analysis of the EURAMOS-1 Clinical Trial Data.

Since the mid-1980s, there has been little progress in improving survival of patients diagnosed with osteosarcoma. Survival prediction models play a key role in clinical decision-making, guiding healthcare professionals in tailoring treatment strategies based on individual patient risks. The increasing interest of the medical community in using machine learning (ML) for predicting survival has sparked an ongoing debate on the value of ML techniques versus more traditional statistical modelling (SM) approaches.

The EXcellenT Trial: Exercise in Extended Oncogene Addicted Lung Cancer in Active Treatment.

Introduction: The discovery of oncogenic mutations that drive the growth and progression of Non-small-cell lung cancer (NSCLC) led to the development of a range of molecular targeted therapies. Tyrosine kinase inhibitors (TKIs) improve the overall outcome of patients with oncogene addicted NSCLC, ensure a better compliance to treatment and few side effects compared to traditional chemotherapy. However, the treatment is still completely "drug-centric", in a population of patients who usually survive for a long time and desire to regain their quality of life.

Survival after resection of malignant peripheral nerve sheath tumors: Introducing and validating a novel type-specific prognostic model.

Background: This study aimed to assess the performance of currently available risk calculators in a cohort of patients with malignant peripheral nerve sheath tumors (MPNST) and to create an MPNST-specific prognostic model including type-specific predictors for overall survival (OS).

Methods: This is a retrospective multicenter cohort study of patients with MPNST from 11 secondary or tertiary centers in The Netherlands, Italy and the United States of America. All patients diagnosed with primary MPNST who underwent macroscopically complete surgical resection from 2000 to 2019 were included in this study.

Personalized Timing for Allogeneic Stem-Cell Transplantation in Hematologic Neoplasms: A Target Trial Emulation Approach Using Multistate Modeling and Microsimulation.

Purpose: Decision about the optimal timing of a treatment procedure in patients with hematologic neoplasms is critical, especially for cellular therapies (most including allogeneic hematopoietic stem-cell transplantation [HSCT]). In the absence of evidence from randomized trials, real-world observational data become beneficial to study the effect of the treatment timing. In this study, a framework to estimate the expected outcome after an intervention in a time-to-event scenario is developed, with the aim of optimizing the timing in a personalized manner.

SEMA6A drives GnRH neuron-dependent puberty onset by tuning median eminence vascular permeability.

Innervation of the hypothalamic median eminence by Gonadotropin-Releasing Hormone (GnRH) neurons is vital to ensure puberty onset and successful reproduction. However, the molecular and cellular mechanisms underlying median eminence development and pubertal timing are incompletely understood. Here we show that Semaphorin-6A is strongly expressed by median eminence-resident oligodendrocytes positioned adjacent to GnRH neuron projections and fenestrated capillaries, and that Semaphorin-6A is required for GnRH neuron innervation and puberty onset.

Interaction between temperature and nutrients: How does the phytoplankton community cope with climate change?

Climate change and increasing nutrient concentrations are two major threats to lake ecosystems. Furthermore, warming is exacerbating the symptoms of eutrophication in freshwaters. Facing both environmental challenges simultaneously is more urgent than ever to preserve and recover water quality and protect the remaining biodiversity.

First Measurement of Hard Exclusive π^{-}Δ^{++} Electroproduction Beam-Spin Asymmetries off the Proton.

The polarized cross-section ratio σ_{LT^{'}}/σ_{0} from hard exclusive π^{-}Δ^{++} electroproduction off an unpolarized hydrogen target has been extracted based on beam-spin asymmetry measurements using a 10.2  GeV/10.6  GeV incident electron beam and the CLAS12 spectrometer at Jefferson Lab.

First CLAS12 Measurement of Deeply Virtual Compton Scattering Beam-Spin Asymmetries in the Extended Valence Region.

Deeply virtual Compton scattering (DVCS) allows one to probe generalized parton distributions describing the 3D structure of the nucleon. We report the first measurement of the DVCS beam-spin asymmetry using the CLAS12 spectrometer with a 10.2 and 10.

Lombardy diagnostic and therapeutic network of thrombotic microangiopathy.

Background: Thrombotic thrombocytopenic purpura (TTP) is a rare, life-threatening thrombotic microangiopathy (TMA) requiring urgent treatment. Standardization of its diagnosis and optimal management is challenging. This study aimed to evaluate the role of centralized, rapid testing of ADAMTS13 in patients experiencing acute TMAs requiring plasma-exchange (PEX) and to estimate the incidence of TTP in a large Italian Region.

Novel longitudinal Multiple Overall Toxicity (MOTox) score to quantify adverse events experienced by patients during chemotherapy treatment: a retrospective analysis of the MRC BO06 trial in osteosarcoma.

Objectives: This study aims at exploring and quantifying multiple types of adverse events (AEs) experienced by patients during cancer treatment. A novel longitudinal score to evaluate the Multiple Overall Toxicity (MOTox) burden is proposed. The MOTox approach investigates the personalised evolution of high overall toxicity (high-MOTox) during the treatment.

Generation of a Triadin KnockOut Syndrome Zebrafish Model.

Different forms of sudden cardiac death have been described, including a recently identified form of genetic arrhythmogenic disorder, named "Triadin KnockOut Syndrome" (TKOS). TKOS is associated with recessive mutations in the gene, encoding for TRIADIN, but the pathogenic mechanism underlying the malignant phenotype has yet to be completely defined. Moreover, patients with TKOS are often refractory to conventional treatment, substantiating the need to identify new therapeutic strategies in order to prevent or treat cardiac events.

Functional modeling of recurrent events on time-to-event processes.

In clinical practice, it is often the case where the association between the occurrence of events and time-to-event outcomes is of interest; thus, it can be modeled within the framework of recurrent events. The purpose of our study is to enrich the information available for modeling survival with relevant dynamic features, properly taking into account their possibly time-varying nature, as well as to provide a new setting for quantifying the association between time-varying processes and time-to-event outcomes. We propose an innovative methodology to model information carried out by time-varying processes by means of functional data, modeling each time-varying variable as the compensator of marked point process the recurrent events are supposed to derive from.

The Genome-Wide Impact of Loss-of-Function on Zebrafish Gene Expression.

Transcriptional changes normally occur during development but also underlie differences between healthy and pathological conditions. Transcription factors or chromatin modifiers are involved in orchestrating gene activity, such as the cohesin genes and their regulator . In our previous studies, using a zebrafish model for knockdown, we described the effect of loss-of-function in specific contexts, such as central nervous system development and hematopoiesis.

Dynamic monitoring of the effects of adherence to medication on survival in heart failure patients: A joint modeling approach exploiting time-varying covariates.

Adherence to medication is the process by which patients take their drugs as prescribed, and represents an issue in pharmacoepidemiological studies. Poor adherence is often associated with adverse health conditions and outcomes, especially in case of chronic diseases such as heart failure (HF). This turns out in an increased request for health care services, and in a greater burden for the health care system.

Adherence to Disease-Modifying Therapy in Patients Hospitalized for HF: Findings from a Community-Based Study.

Background: Much data about prescription adherence in patients with heart failure (HF) are available, but few exist about the evaluation of true patient adherence. Further, methods for analyzing this issue are poorly known.

Objectives: Our objective was to evaluate the impact of patient adherence to disease-modifying drugs after HF hospitalization in a community-based cohort.

Enigmatic Ladies of the Rings: How Cohesin Dysfunction Affects Myeloid Neoplasms Insurgence.

The genes of the cohesin complex exert different functions, ranging from the adhesion of sister chromatids during the cell cycle, DNA repair, gene expression and chromatin architecture remodeling. In recent years, the improvement of DNA sequencing technologies allows the identification of cohesin mutations in different tumors such as acute myeloid leukemia (AML), acute megakaryoblastic leukemia (AMKL), and myelodysplastic syndromes (MDS). However, the role of cohesin dysfunction in cancer insurgence remains elusive.