Identification of a class of non-conventional ER-stress-response-derived immunogenic peptides

Efforts to overcome resistance to immune checkpoint blockade therapy have focused on vaccination strategies using neoepitopes, although they cannot be applied on a large scale due to the “private” nature of cancer mutations. Here, we show that infection of tumor cells with Salmonella induces the opening of membrane hemichannels and the extracellular release of proteasome-generated peptides by the exacerbation of endoplasmic reticulum (ER) stress. Peptides released by cancer cells foster an antitumor response in vivo, both in mice bearing B16F10 melanomas and in dogs suffering from osteosarcoma. Mass spectrometry analysis on the supernatant of human melanoma cells revealed 12 peptides capable of priming healthy-donor CD8+ T cells that recognize and kill human melanoma cells in vitro and when xenotransplanted in vivo. Hence, we identified a class of shared tumor antigens that are generated in ER-stressed cells, such as tumor cells, that do not induce tolerance and are not presented by healthy cells

Formación y difusión científica en la enseñanza de la Farmacología

Dado que la docencia y la investigación son dos funciones primordiales de las universidades, decidimos relacionar ambas aplicando nuestros hallazgos científicos a la enseñanza de la farmacología. Los propósitos generales fueron propiciar la apertura temprana a la investigación científica, sus métodos, criterios y aplicaciones. La propuesta consiste en trabajos prácticos a desarrollar tras los teóricos sobre fármacos antimicrobianos en el grado. El tema central es la búsqueda de medicamentos para tratar micosis superficiales. Como recurso didáctico complementario, elaboramos un video digital que incluye la información necesaria para la comprensión y desarrollo del tema. La primera parte muestra los materiales y procedimientos técnicos que condujeron al descubrimiento de principios activos en Citrus aurantium L. (naranja amarga). La segunda ilustra aspectos clínicos de las micosis superficiales, sus manifestaciones, diagnóstico, tratamiento, etc. Después de analizar el video, los alumnos reproducirán en el laboratorio de la Cátedra las técnicas mostradas y analizarán los resultados en un contexto farmacológico global. La propuesta propicia la formación temprana de criterios científicos en ciencias de la salud, en beneficio del futuro desempeño ya sea en ámbitos científicos, académicos o profesionales. La combinación de métodos multimediales, experimentación en laboratorios y análisis de información diversa mejoraría la enseñanza de la farmacología.Trabajos del área Ciencias NaturalesDepartamento de Ciencias Exactas y Naturale

Medical Informatics Platform (MIP): A Pilot Study Across Clinical Italian Cohorts

Introduction: With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify—CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup. / Methods: We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, n = 432), Mild Cognitive Impairment (MCI, n = 456), and AD (n = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools. / Results: The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from “slight” to “significant” in 80% of the cases. / Discussion: GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology

PMCA-Based Detection of Prions in the Olfactory Mucosa of Patients With Sporadic Creutzfeldt–Jakob Disease

Sporadic Creutzfeldt-Jakob disease (sCJD) is a rare neurodegenerative disorder caused by the conformational conversion of the prion protein (PrPC) into an abnormally folded form, named prion (or PrPSc). The combination of the polymorphism at codon 129 of the PrP gene (coding either methionine or valine) with the biochemical feature of the proteinase-K resistant PrP (generating either PrPSc type 1 or 2) gives rise to different PrPSc strains, which cause variable phenotypes of sCJD. The definitive diagnosis of sCJD and its classification can be achieved only post-mortem after PrPSc identification and characterization in the brain. By exploiting the Real-Time Quaking-Induced Conversion (RT-QuIC) assay, traces of PrPSc were found in the olfactory mucosa (OM) of sCJD patients, thus demonstrating that PrPSc is not confined to the brain. Here, we have optimized another technique, named protein misfolding cyclic amplification (PMCA) for detecting PrPSc in OM samples of sCJD patients. OM samples were collected from 27 sCJD and 2 genetic CJD patients (E200K). Samples from 34 patients with other neurodegenerative disorders were included as controls. Brains were collected from 26 sCJD patients and 16 of them underwent OM collection. Brain and OM samples were subjected to PMCA using the brains of transgenic mice expressing human PrPC with methionine at codon 129 as reaction substrates. The amplified products were analyzed by Western blot after proteinase K digestion. Quantitative PMCA was performed to estimate PrPSc concentration in OM. PMCA enabled the detection of prions in OM samples with 79.3% sensitivity and 100% specificity. Except for a few cases, a predominant type 1 PrPSc was generated, regardless of the tissues analyzed. Notably, all amplified PrPSc were less resistant to PK compared to the original strain. In conclusion, although the optimized PMCA did not consent to recognize sCJD subtypes from the analysis of OM collected from living patients, it enabled us to estimate for the first time the amount of prions accumulating in this biological tissue. Further assay optimizations are needed to faithfully amplify peripheral prions whose recognition could lead to a better diagnosis and selection of patients for future clinical trials

Labor market reform and rent-sharing : a quasi-experiment experience

We analyze the impact on wages of the adoption of a rent-sharing remuneration scheme aiming at making labor institutions more flexible. We are working with a quasi- experimental setting referring to a sample of Italian companies before and after the introduction of the Treu Reform (1997). Our estimations confirm that this reform not only increased insider workers' wages via rent-sharing, but also fueled a s-convergence process of the rent-sharing elasticity across the sectors at a different rate. Finally, we deliver a reasoned discussion of the consequences at large of the implementation of this reform in the Italian job market

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer’s dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB 1.0): development and normative data

Background: Neuropsychological testing plays a cardinal role in the diagnosis and monitoring of Alzheimer’s disease. A major concern is represented by the heterogeneity of the neuropsychological batteries currently adopted in memory clinics and healthcare centers. The current study aimed to solve this issue. Methods: Following the initiative of the University of Washington’s National Alzheimer’s Coordinating Center (NACC), we presented the Italian adaptation of the Neuropsychological Test Battery of the Uniform Data Set (I-UDSNB). We collected data from 433 healthy Italian individuals and employed regression models to evaluate the impact of demographic variables on the performance, deriving the reference norms. Results: Higher education and lower age were associated with a better performance in the majority of tests, while sex affected only fluency tests and Digit Span Forward. Conclusions: The I-UDSNB offers a valuable and harmonized tool for neuropsychological testing in Italy, to be used in clinical and research settings