Decision trees to evaluate the risk of developing multiple sclerosis

Introduction: Multiple sclerosis (MS) is a persistent neurological condition impacting the central nervous system (CNS). The precise cause of multiple sclerosis is still uncertain; however, it is thought to arise from a blend of genetic and environmental factors. MS diagnosis includes assessing medical history, conducting neurological exams, performing magnetic resonance imaging (MRI) scans, and analyzing cerebrospinal fluid. While there is currently no cure for MS, numerous treatments exist to address symptoms, decelerate disease progression, and enhance the quality of life for individuals with MS. Methods: This paper introduces a novel machine learning (ML) algorithm utilizing decision trees to address a key objective: creating a predictive tool for assessing the likelihood of MS development. It achieves this by combining prevalent demographic risk factors, specifically gender, with crucial immunogenetic risk markers, such as the alleles responsible for human leukocyte antigen (HLA) class I molecules and the killer immunoglobulin-like receptors (KIR) genes responsible for natural killer lymphocyte receptors. Results: The study included 619 healthy controls and 299 patients affected by MS, all of whom originated from Sardinia. The gender feature has been disregarded due to its substantial bias in influencing the classification outcomes. By solely considering immunogenetic risk markers, the algorithm demonstrates an ability to accurately identify 73.24% of MS patients and 66.07% of individuals without the disease. Discussion: Given its notable performance, this system has the potential to support clinicians in monitoring the relatives of MS patients and identifying individuals who are at an increased risk of developing the disease

The bromodomain and extra-terminal domain degrader MZ1 exhibits preclinical anti-tumoral activity in diffuse large B-cell lymphoma of the activated B cell-like type

AIM: Bromodomain and extra-terminal domain (BET) proteins are epigenetic readers that play a fundamental role in transcription regulation. Preclinical and early clinical evidence sustain BET targeting as an anti-cancer approach. BET degraders are chimeric compounds comprising of a BET inhibitor, which allows the binding to BET bromodomains, linked to a small molecule, binder for an E3 ubiquitin ligase complex, triggering BET proteins degradation via the proteasome. These degraders, called proteolysis-targeting chimeras (PROTACs), can exhibit greater target specificity compared to BET inhibitors and overcome some of their limitations, such as the upregulation of the BET proteins themselves. Here are presented data on the anti-tumor activity and the mechanism of action of the BET degrader MZ1 in diffuse large B cell lymphoma (DLBCL) of the activated B-cell like (ABC, ABC DLBCL), using a BET inhibitor as a comparison. METHODS: Established lymphoma cell lines were exposed for 72 h to increasing doses of the compounds. Cell proliferation was evaluated by using an 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazoliumbromide (MTT) assay. Fluorescent-Activated Cell Sorter (FACS) analysis was performed to measure apoptotic activation and RNA sequencing (RNA-Seq) to study the transcriptional changes induced by the compounds. RESULTS: MZ1, and not its negative control epimer cisMZ1, was very active with a median half maximal inhibitory concentration (IC(50)) of 49 nmol/L. MZ1 was more in vitro active than the BET inhibitor birabresib (OTX015). Importantly, MZ1 induced cell death in all the ABC DLBCL cell lines, while the BET inhibitor was cytotoxic only in a fraction of them. BET degrader and inhibitor shared partially similar changes at transcriptome level but the MZ1 effect was stronger and overlapped with that caused cyclin-dependent kinase 9 (CDK9) inhibition. CONCLUSIONS: The BET degrader MZ1 had strong cytotoxic activity in all the ABC DLBCL cell lines that were tested, and, at least in vitro, it elicited more profound effects than BET inhibitors, and encourages further investigations

Decision trees to evaluate the risk of developing multiple sclerosis

IntroductionMultiple sclerosis (MS) is a persistent neurological condition impacting the central nervous system (CNS). The precise cause of multiple sclerosis is still uncertain; however, it is thought to arise from a blend of genetic and environmental factors. MS diagnosis includes assessing medical history, conducting neurological exams, performing magnetic resonance imaging (MRI) scans, and analyzing cerebrospinal fluid. While there is currently no cure for MS, numerous treatments exist to address symptoms, decelerate disease progression, and enhance the quality of life for individuals with MS.MethodsThis paper introduces a novel machine learning (ML) algorithm utilizing decision trees to address a key objective: creating a predictive tool for assessing the likelihood of MS development. It achieves this by combining prevalent demographic risk factors, specifically gender, with crucial immunogenetic risk markers, such as the alleles responsible for human leukocyte antigen (HLA) class I molecules and the killer immunoglobulin-like receptors (KIR) genes responsible for natural killer lymphocyte receptors.ResultsThe study included 619 healthy controls and 299 patients affected by MS, all of whom originated from Sardinia. The gender feature has been disregarded due to its substantial bias in influencing the classification outcomes. By solely considering immunogenetic risk markers, the algorithm demonstrates an ability to accurately identify 73.24% of MS patients and 66.07% of individuals without the disease.DiscussionGiven its notable performance, this system has the potential to support clinicians in monitoring the relatives of MS patients and identifying individuals who are at an increased risk of developing the disease

Evidence of delocalized excitons in amorphous solids

We studied the temperature dependence of the absorption coefficient of amorphous SiO$_2$ in the range from 8 to 17.5~eV obtained by Kramers-Kronig dispersion analysis of reflectivity spectra. We demonstrate the main excitonic resonance at 10.4~eV to feature a close Lorentzian shape red-shifting with increasing temperature. This provides a strong evidence of excitons being delocalized notwithstanding the structural disorder intrinsic to the amorphous system. Excitons turn out to be coupled to an average phonon mode of 83~meV energy

Innovative Clinical\u2010Organizational Model to Ensure Appropriateness and Quality in the Management of Medical Cannabis: An Italian Regional Case

This work focuses on the clinical\u2010organizational model implemented in an Italian region (Liguria) to streamline the access procedures to galenic cannabis preparations. The competent local health care authority that takes care of tracing a virtuous path to obtain common, uniform and shared protocols and ensure high standards of care is A.Li.Sa. (Azienda Ligure Sanitaria), a public organization with the function of coordination, direction and governance of the health care in the regional hospitals and health facilities. To this purpose, different working groups and a board meeting have been set up with the main role to define and develop technical standards to be applied to the prescription, preparation and dispensing of pharmaceutical forms based on therapeutic cannabis. In particular, the galenic preparations provided by the Italian Ministry of Health, described in detail in the regional standard operating protocols, are described and discussed. Moreover, the most significant data monitored from 2018 to 2020 and collected by hospitals and the evaluation of those derived from local pharmacies and health facilities are presented, discussed and compared in regards to their adherence and coherence with the Italian Institute of Health (ISS) data

Titolazioni dei preparati galenici oleosi a base di cannabis in Regione Liguria: progetto sperimentale dei laboratori di riferimento regionale

Analysis of cannabinoids concentration in cannabis oil galenic preparations in the Liguria Region: experimental project of the regional reference laboratories. Introduction: the medical use of cannabis is increasingly being applied in the treatment and support of several diseases and syndromes. In the Liguria Region, olive oil galenic preparations are mainly prepared by hospital pharmacies, according to common standard procedures. The preparations must be analyzed in order to establish the concentration of the two main active compounds (delta-9 tetrahydrocannabinol, THC and cannabidiol, CBD) thus allowing the correct setting of the therapeutic prescription. Liguria Region is at the forefront in the use of medical cannabis with a high number of patients treated (>1000). The aim of this work is to describe the organization of the titration activity centralized at the two regional reference laboratories (Central Laboratory of Analyses of Giannina Gaslini Institute, Genova and Toxicology Laboratory of Sarzana, La Spezia), coordinated by the inter-hospital department (DIAR) of the Laboratories Area. Methods: the phases of the analytical process (pre-analytical, analytical and post-analytical) have been identified and described. The analysis of the workflow has been carried out including the methods to prepare cannabis oil in the pharmacies, the intervals and production volumes, the medical-legal handling requirements and operational responsibilities. The definition of the pre-analytical phase foresees the methods of packaging, transport and recording of the samples and related responsibilities. Results: the analytical phase included the development and validation of the analytical method Ultra High Performance Liquid Chromatography coupled to tandem mass spectrometry, (UHPLC-MS/MS) in the two laboratories, with common procedures and the comparison of results conducted both on reference material and real samples of olive oil galenic preparations. The definition of the post-analytical phase included the reporting procedures. Discussion: the experimental phase has been concluded at the end of 2019 and the implementation phase of the project has started in march 2020

MEDLEM database, a data collection on large Elasmobranchs in the Mediterranean and Black seas

The Mediterranean Large Elasmobranchs Monitoring (MEDLEM) database contains over 3000 records (more than 4000 individuals) of large elasmobranch species from 20 different countries around the Mediterranean and Black seas, observed from 1666 to 2017. The main species included in the archive are the devil fish (1 813 individuals), the basking shark (939 individuals), the blue shark (585 individuals) and the great white shark (337 individuals).In the last decades other species such as the shortfin mako (166 individuals), the spiny butterfly ray (138) and the thresher shark (174 individuals) were reported with an increasing frequency. This was possibly due to an increased public awareness on the conservation status of sharks, and a consequent development of new monitoring programmes. MEDLEM does not have a homogeneous reporting coverage throughout the Mediterranean and Black seas and it should be considered as a database of observed species presence. Scientific monitoring efforts in the south-eastern Mediterranean and Black seas are generally lower than in the northern sectors and the absence in our database of some species does not imply their actual absence in these regions. Some considerations are made on the frequency and spatial distribution of records, size structure of the observed individuals for selected species, general area coverage and species involved as by-catch by fishing gear

Figure S14 from ERBB4-Mediated Signaling Is a Mediator of Resistance to PI3K and BTK Inhibitors in B-cell Lymphoid Neoplasms

Karpas1718 parental (A-B), SP53 (C-D), OCILY10 (C, E) and JEKO1-Cas9-ERBB4 (F-G) cells were exposed with DMSO (grey), idelalisib (red) or idelalisib + lapatinib (yellow) for 2-weeks. Expression levels of let-7c and miR-29c miRNAs (real-time PCR); and surface ERBB4 and intracellular HBEGF (both by FACS), were evaluated. RQ values calculated by the DDCt method. MFI for median fluorescence intensity. Expression levels of let-7c and miR-29c miRNAs (A), and surface ERBB4 and intracellular HBEGF (B) in Karpas1718 parental cells exposed with DMSO (grey), idelalisib (red) or idelalisib + lapatinib (yellow). Expression levels of let-7c and miR-29c miRNAs (C), and surface ERBB4 and intracellular HBEGF in SP53 (D) and OCILY10 (E) cells exposed with DMSO (grey), idelalisib (red) or idelalisib + lapatinib (yellow). Expression levels of surface ERBB4 and intracellular HBEGF in JEKO1-CNT (scramble sgRNA, F) and JEKO1-ERBB4 (sgRNA-ERBB4, G) cells exposed with DMSO (grey), idelalisib (red) or idelalisib + lapatinib (yellow). Data derived from two independent experiments; error bars represent standard deviation of the mean. * for p<0.05 from a t-test.</p