Publications by authors named "Visani G"

Group-equivariant neural networks have emerged as an efficient approach to model complex data, using generalized convolutions that respect the relevant symmetries of a system. These techniques have made advances in both the supervised learning tasks for classification and regression, and the unsupervised tasks to generate new data. However, little work has been done in leveraging the symmetry-aware expressive representations that could be extracted from these approaches.

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Class I MHC molecules present peptides derived from intracellular antigens on the cell surface for immune surveillance, and specific targeting of these peptide-MHC (pMHC) complexes could have considerable utility for treating diseases. Such targeting is challenging as it requires readout of the few outward facing peptide antigen residues and the avoidance of extensive contacts with the MHC carrier which is present on almost all cells. Here we describe the use of deep learning-based protein design tools to design small proteins that arc above the peptide binding groove of pMHC complexes and make extensive contacts with the peptide.

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Predicting protein functional characteristics from structure remains a central problem in protein science, with broad implications from understanding the mechanisms of disease to designing novel therapeutics. Unfortunately, current machine learning methods are limited by scarce and biased experimental data, and physics-based methods are either too slow to be useful, or too simplified to be accurate. In this work, we present Loop-Diffusion, an energy based diffusion model which leverages a dataset of general protein loops from the entire protein universe to learn an energy function that generalizes to functional prediction tasks.

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Article Synopsis
  • - The study analyzed data from 229 elderly patients with core binding factor acute myeloid leukemia (CBF-AML) to assess treatment outcomes over two decades, finding a 5-year overall survival (OS) rate of 44.2% and event-free survival (EFS) rate of 32.9%.
  • - In patients over 70 who underwent intensive therapy, those who completed treatment had a median EFS of 11.8 months and a 5-year OS of 40%.
  • - Key factors impacting survival included age, achieving remission after initial treatment, and the number of consolidation therapy cycles, indicating that intensive therapy could be beneficial for selected older patients and should not be overlooked in clinical studies. *
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Rho guanine nucleotide exchange factor (RGNEF) is a guanine nucleotide exchange factor (GEF) mainly involved in regulating the activity of Rho-family GTPases. It is a bi-functional protein, acting both as a guanine exchange factor and as an RNA-binding protein. RGNEF is known to act as a destabilizing factor of neurofilament light chain RNA (NEFL) and it could potentially contribute to their sequestration in nuclear cytoplasmic inclusions.

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The bone marrow microenvironment (BMM) has highly specialized anatomical characteristics that provide a sanctuary place for hematopoietic stem cells (HSCs) that allow appropriate proliferation, maintenance, and self-renewal capacity. Several cell types contribute to the constitution and function of the bone marrow niche. Interestingly, uncovering the secrets of BMM and its interaction with HSCs in health paved the road for research aiming at better understanding the concept of leukemic stem cells (LSCs) and their altered niche.

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Predicting the stability and fitness effects of amino acid mutations in proteins is a cornerstone of biological discovery and engineering. Various experimental techniques have been developed to measure mutational effects, providing us with extensive datasets across a diverse range of proteins. By training on these data, traditional computational modeling and more recent machine learning approaches have advanced significantly in predicting mutational effects.

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Predicting the stability and fitness effects of amino-acid mutations in proteins is a cornerstone of biological discovery and engineering. Various experimental techniques have been developed to measure mutational effects, providing us with extensive datasets across a diverse range of proteins. By training on these data, machine learning approaches have advanced significantly in predicting mutational effects.

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Article Synopsis
  • Therapies for relapsed/refractory acute myeloid leukemia (AML) are limited, particularly for patients who can't tolerate standard treatments, prompting the evaluation of a new combination therapy.
  • In a phase 1b trial, 30 patients were treated with venetoclax, a BCL-2 inhibitor, and cobimetinib, a MEK1/2 inhibitor, but experienced significant adverse effects like diarrhea, nausea, and fatigue, leading to dose modifications in many cases.
  • The combination therapy showed a low overall response rate (15.6% complete remission) and suggested that certain baseline biological markers may help predict patient responses, indicating limited efficacy similar to single-agent venetoclax but with increased toxicity.
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Accurately modeling protein 3D structure is essential for the design of functional proteins. An important sub-task of structure modeling is protein side-chain packing: predicting the conformation of side-chains (rotamers) given the protein's backbone structure and amino-acid sequence. Conventional approaches for this task rely on expensive sampling procedures over hand-crafted energy functions and rotamer libraries.

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Purpose Of Review: Fms -like tyrosine kinase 3 (FLT3) mutations are common in newly diagnosed patients with acute myeloid leukemia (AML). They are associated with a high risk of relapse. The identification of FLT3 mutations has important implications for the management of AML.

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  • A registry analysis was conducted on adult acute myeloid leukemia (AML) patients in remission who underwent haplo-hematopoietic stem cell transplant (HSCT) between 2010 and 2020, comparing thiotepa, busulfan, and fludarabine (TBF) versus treosulfan (Treo) conditioning.
  • The study included 1123 patients, with 968 receiving TBF and 155 receiving Treo, and a matched-pair analysis was performed on 142 patients from each group to assess outcomes.
  • No significant differences were found in terms of graft-versus-host disease incidence, nonrelapse mortality, or leukemia-free survival between the two conditioning
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Primary myelofibrosis (PMF) is a chronic myeloproliferative neoplasm (MPN) characterized by progressive bone marrow sclerosis, extra-medullary hematopoiesis, and possible transformation to acute leukemia. In the last decade, the molecular pathogenesis of the disease has been largely uncovered. Particularly, genetic and genomic studies have provided evidence of deregulated oncogenes in PMF as well as in other MPNs.

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Treatment of acute myeloid leukemia (AML) has changed over the last few years, after the discovery of new drugs selectively targeting AML blasts. Although 3/7 remains the standard of care for most AML patients, several new targeted agents (such as FLT3 inhibitors, CPX-351, gemtuzumab ozogamicin, BCL-2 inhibitor, and oral azacitidine), either as single agents or combined with standard chemotherapy, are approaching clinical practice, starting a new era in AML management. Moreover, emerging evidence has demonstrated that high-risk AML patients might benefit from both allogeneic stem cell transplant and maintenance therapy, providing new opportunities, as well as new challenges, for treating clinicians.

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  • - The study investigates the role of specific heterogeneous nuclear ribonucleoproteins in amyotrophic lateral sclerosis (ALS), focusing on their connection with TAR DNA-binding protein 43 kDa, which is implicated in ALS pathology.
  • - Researchers found that a certain mRNA is a direct target of TAR DNA-binding protein 43 kDa, and manipulating its levels in fly models can alleviate related ALS symptoms.
  • - In human patients, decreased levels of this mRNA are linked to TAR DNA-binding protein 43 kDa-related protein issues, suggesting it could be a promising target for developing new treatments for ALS.
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  • COVID-19 continues to significantly impact patients with chronic lymphocytic leukemia (CLL), with a study analyzing 256 CLL patients showing a high case fatality rate of 30.1%.
  • Most patients were symptomatic and required hospitalization, with a considerable portion having received recent therapy for their CLL.
  • Factors like male sex, age over 70, recent treatment, and severity of COVID-19 were found to be strong predictors of poor survival outcomes among these patients.
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This phase 1b trial (NCT02670044) evaluated venetoclax-idasanutlin in patients with relapsed/refractory (R/R) acute myeloid leukemia (AML) ineligible for cytotoxic chemotherapy. Two-dimensional dose escalation (DE, n = 50) was performed for venetoclax daily with idasanutlin on days 1 to 5 in 28-day cycles, followed by dosing schedule optimization (n = 6) to evaluate reduced venetoclax schedules (21-/14-day dosing). Common adverse events (occurring in ≥40% of patients) included diarrhea (87.

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Purpose: Diffuse idiopathic skeletal hyperostosis (DISH) is a benign condition characterized by ossification of the spine and prominent enthesopathies. Highly heterogeneous epidemiological figures have been reported in the literature, while in Italy the largest study has been conducted in 1992. The aim of our research is to contribute updated information about prevalence of DISH in Italy and to describe the clinical and radiographic characteristics associated with the disorder.

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Idelalisib, a reversible inhibitor of PI3Kδ (phosphoinositide-3 kinase delta), showed remarkable activity in the phase II DELTA trial, leading to its approval by the European Medicines Agency (EMA) in patients with relapsed/refractory (R/R) follicular lymphoma (FL). However, real-life data on idelalisib are scarce. We treated 55 double-refractory FL patients with idelalisib in a real-life setting.

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Acute myeloid leukemia (AML) is an infrequent disease, and it is associated with high morbidity and mortality. It harbors a unique configuration of cytogenetic abnormalities and molecular mutations that can be detected using microscopic and molecular methods respectively. These genetic tests are core elements of diagnosis and prognostication in high-income countries.

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Lymphoma represents a heterogeneous hematological malignancy (HM), which is characterized by severe immunosuppression. Patients diagnosed of coronavirus disease 2019 (COVID-19) during the course of HM have been described to have poor outcome, with only few reports specifically addressing lymphoma patients. Here, we investigated the clinical behavior and clinical parameters of a large multicenter cohort of adult patients with different lymphoma subtypes, with the aim of identifying predictors of death.

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Altered cellular energetic metabolism has recently emerged as important feature of neoplastic cells. Indeed, interfering with cancer cell metabolism might represent a suitable therapeutic strategy. In this study, we aimed to assess glucose metabolism activation in human lymphomas and evaluate how metformin can exert its action on lymphoma cells.

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The efficacy of Covid-19 vaccine in hematopoietic stem cell transplantation (HSCT) recipients is still unknown. We planned a prospective study to evaluate the immune response after the administration of Covid-19 vaccine in HSCT recipients. Fifty patients previously submitted to HSCT (38 autologous and 12 allogeneic) received the mRNA-based SARS-CoV-2 vaccine BNT162b2 (Pfizer-BioNTech).

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COVID-19 is associated with high mortality in patients with haematological malignancies (HM) and rate of seroconversion is unknown. The ITA-HEMA-COV project (NCT04352556) investigated patterns of seroconversion for SARS-CoV-2 IgG in patients with HMs. A total of 237 patients, SARS-CoV-2 PCR-positive with at least one SARS-CoV-2 IgG test performed during their care, entered the analysis.

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Tyrosine kinase inhibitors (TKIs) have radically changed the outcome of chronic myeloid leukemia (CML) patients in the last 20 years. Moreover, the advent of second generation TKIs, namely nilotinib and dasatinib, have largely increased the number of CML patients achieving deep and sustained molecular responses. However, the possible mechanisms capable of influencing the maintenance of the long-term molecular response are not yet fully known and understood.

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