Appendiceal goblet cell carcinoma has marginal advantages from perioperative chemotherapy: a population-based study with an entropy balancing analysis

PurposeThe aim is to clarify the use of perioperative chemotherapy in resectable goblet cell carcinoma (GCC).MethodsA retrospective study was carried out based on the Surveillance, Epidemiology, and End Results study. The population was divided: into patients who received only radical surgery (group A) and those who received radical surgery plus chemotherapy (group B). An entropy balancing was carried out to correct the imbalance between the two groups. Two models were generated. Model 1 contained only high-risk patients: group B and a "virtual" group A with similar characteristics. Model 2 included only low-risk patients: group A and "virtual" group B with identical attributes. The efficacy of entropy balancing was evaluated with the d value. The overall survival was compared and reported with Hazard Ratio (HR) within a confidence interval of 95% (95 CI).ResultsThe groups A and B were imbalanced for tumor size (d = 0.392), T (d = 1.128), N (d = 1.340), M (d = 1.456), mean number of positive lymph nodes (d = 0.907), and LNR (d = 0.889). Before the balancing, the risk of death was higher in group B than in A (4.3; 2.5 to 7.4). After reweighting, all large differences were eliminated (d < 0.200). In high-risk patients, the risk of death was higher in patients who underwent surgery alone than those who received perioperative chemotherapy (HR 0.5; 0.2 to 1.3) without statistical significance (p = 0.187). In low-risk patients, the risk of death was similar (HR 1.1; 0.3 to 3.3).ConclusionPerioperative chemotherapy could provide some marginal advantages to high-risk patients

Differences in resource assimilation between the unisexual Amazon molly, Poecilia formosa (Poeciliidae) and its sexual host (Poecilia latipinna)

Abstract Unisexual sperm-dependent species depend on a sexual host for reproduction, and must live in sympatry with their sperm donor. If niche overlap between the species is substantial, the intrinsic faster population growth of the unisexual over sexual species can cause competitive exclusion of the host from resources, causing the demise of the unisexual species. However, theoretical models predict that coexistence is possible, even without niche differentiation, if the unisexual species is a poorer competitor than the sexual host and if the effect of the unisexual species on the exploitative abilities of the sexual species is smaller than the effect that the sexually reproducing individuals have among themselves. We tested these predictions in the unisexualbisexual mating complex of Poecilia formosa, and one of its sexual hosts, P. latipinna. Fishes were housed from parturition for 76 days with both conspecific and heterospecific individuals under both limited and ad libitum food regimes. Only one of the predictions of the models was met: the effects of intraspecific competition for P. latipinna were stronger than the effects of interspecific competition. Poecilia latipinna raised with conspecifics with limited food stored fewer fats than both heterospecific P. formosa, and conspecifics raised in any other treatment

Presenilin 1 Protein Directly Interacts with Bcl-2

Presenilin proteins are involved in familial Alzheimer's disease, a neurodegenerative disorder characterized by massive death of neurons. We describe a direct interaction between presenilin 1 (PS1) and Bcl-2, a key factor in the regulation of apoptosis, by yeast two-hybrid interaction system, by co-immunoprecipitation, and by cross-linking experiments. Our data show that PS1 and Bcl-2 assemble into a macromolecular complex, and that they are released from this complex in response to an apoptotic stimulus induced by staurosporine. The results support the idea of cross-talk between these two proteins during apoptosis

Evolving knowledge in surgical oncology of pancreatic cancer: from theory to clinical practice-a fifteen-year journey at a tertiary referral centre

Pancreatic ductal adenocarcinoma (PDAC) is an increasing disease having a poor prognosis. The aim of the present study was to evaluate the effect of different models of care for pancreatic cancer in a tertiary referral centre in the period 2006-2020. Retrospective study of patients with PDAC observed from January 2006 to December 2020. The demographic and clinical data, and data regarding the imaging techniques used, preoperative staging, management, survival and multidisciplinary tumour board (MDTB) evaluation were collected and compared in three different periods characterised by different organisation of pancreatic cancer services: period A (2006-2010); period B (2011-2015) and period C (2016-2020). One thousand four hundred seven patients were analysed: 441(31.3%) in period A; 413 (29.4%) in B and 553 (39.3%) in C. The proportion of patients increased significantly, from 31.3% to 39.3% (P = 0.032). Body mass index (P = 0.033), comorbidity rate (P = 0.002) and Karnofsky performance status (P < 0.001) showed significant differences. Computed tomography scans (P < 0.001), endoscopic ultrasound (P < 0.001), fine needle aspiration, fine needle biopsy (P < 0.001), and fluorodeoxyglucose-positron emission tomography/computed tomography (P < 0.001) increased; contrast-enhanced ultrasound (P = 0.028) decreased. The cTNM was significantly different (P < 0.001). The MDTB evaluation increased significantly (P < 0.001). Up-front surgery and exploratory laparotomy decreased (P < 0.001), neoadjuvant treatment increased (P < 0.001). The present study showed the evolving knowledge in surgical oncology of pancreatic cancer at a tertiary referral centre over the time. The different models of care of pancreatic cancer, in particular the introduction of the MDTB and the institution of a pancreas unit to the decision-making process seemed to be influential

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures

Algoritmos primais-duais de ponto fixo aplicados ao problema Ridge Regression

In this work we propose algorithms for solving a fixed-point general primal-dual formulation applied to the Ridge Regression problem. We study the primal formulation for regularized least squares problems, especially L2-norm, named Ridge Regression and then describe convex duality for that class of problems. Our strategy was to consider together primal and dual formulations and minimize the duality gap between them. We established the primal-dual fixed point algorithm, named SRP and a reformulation for this method, the main contribution of the thesis, which was more efficient and robust, called acc-SRP method or accelerated version of the SRP method. The theoretical study of the algorithms was done through the analysis of the spectral properties of the associated iteration matrices. We proved the linear convergence of algorithms and some numerical examples comparing two variants for each algorithm proposed were presented. We also showed that our best method, acc-SRP, has excellent numerical performance for solving very ill-conditioned problems, when compared to the conjugate gradient method, which makes it computationally more attractive.Neste trabalho propomos algoritmos para resolver uma formulação primal-dual geral de ponto fixo aplicada ao problema de Ridge Regression. Estudamos a formulação primal para problemas de quadrados mínimos regularizado, em especial na norma L2, nomeados Ridge Regression e descrevemos a dualidade convexa para essa classe de problemas. Nossa estratégia foi considerar as formulações primal e dual conjuntamente, e minimizar o gap de dualidade entre elas. Estabelecemos o algoritmo de ponto fixo primal-dual, nomeado SRP e uma reformulação para esse método, contribuição principal da tese, a qual mostrou-se mais eficaz e robusta, designada por método acc-SRP, ou versão acelerada do método SRP. O estudo teórico dos algoritmos foi feito por meio da análise de propriedades espectrais das matrizes de iteração associadas. Provamos a convergência linear dos algoritmos e apresentamos alguns exemplos numéricos comparando duas variantes para cada algoritmo proposto. Mostramos também que o nosso melhor método, acc-SRP, possui excelente desempenho numérico na resolução de problemas muito mal-condicionados quando comparado ao Método de Gradientes Conjugados, o que o torna computacionalmente mais atraente

Il falso dilemma pubblico-privato. L’anomalia della scuola italiana nel contesto europeo

Il modello organizzativo del sistema scolastico italiano in prospettiva storica e comparata nel contesto europeo; prospettive per un adeguamento della scuola italiana al “sistema medio europeo”.- Indice #4- Introduzione, Marcello Pacini #8- Nota metodologica #14- Cap.I Il modello organizzativo del sistema scolastico italiano #18- Cap.II Il sistema medio europeo. Sistemi e problemi di un'analisi comparata #54- Cap.III Verso la deburocratizzazione. Prospettive per un adeguamento della scuola italiana al “sistema medio europeo” #114- Allegato I La struttura del sistema scolastico italiano #146- Relazioni e interventi di discussione sulla ricerca #206- Intervento On. Francesco Casati, Presidente della Commissione Istruzione e Belle Arti della Camera dei Deputati #208- Intervento Sen. Luigi Covatta, Sottosegretario di Stato alla Pubblica Istruzione #212- Intervento Sen. Salvatore Valitutti, Presidente della Commissione Istruzione Pubblica e Belle Arti del Senato della Repubblica #215- Intervento Emanuele Caruso, Dirigente Generale dell'Istruzione Tecnica, Ministero della Pubblica Istruzione #219- Intervento Mario Dupuis, Responsabile Scuola del Movimento Popolare #222- Intervento On. Laura Fincato, Vicepresidente della Commissione Istruzione e Belle Arti della Camera dei Deputati #225- Intervento Aureliana Alberici, Responsabile Scuola/Università della Direzione del P.C.I. #229- Intervento Paolo Serreri, Federazione Scuola Università C.G.I.L. #237- Intervento Daniela Silvestri, Rappresentante nazionale del Sindacato Nazionale Autonomo Lavoratori Scuola SNALS #242- Intervento Paolo Martelli, Direttore di POLITEIA - Centro per la ricerca e la formazione in politica ed etica #245- Intervento Salvatore Sechi, Professore ordinario di Storia Contemporanea, Università di Bologna #252- Intervento Piero Romei, Ricercatore dell'ISGO #257- Intervento Giovanni Bechelloni, Professore ordinario di Sociologia dei processi culturali, Università di Firenze #263- Intervento Giorgio Allulli, Censis #266- Intervento Graziella Morselli, FNISM #270- Intervento Luigi Pedrazzi, Il Mulino #274- Intervento Luciano Benadusi, Responsabile Settore Università e ricerca scientifica della Direzione Socialista #277- Intervento Mario Caronna #Coordinatore scientifico del Centro Studi di Milano #282- Intervento Adriana Rosas, Ricercatore presso il CLAS #287- Intervento Giovanni Tesoro, Ricercatore presso l’ISGO #290- Considerazioni conclusive Luisa Ribolzi, CLAS #29

Neotropical xenarthrans: a data set of occurrence of xenarthran species in the neotropics

Xenarthrans -anteaters, sloths, and armadillos- have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. Have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become.Fil: Marques Santos, Paloma. Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas; BrasilFil: Bocchiglieri, Adriana. Universidade Federal de Sergipe; BrasilFil: Garcia Chiarello, Adriano. Universidade de Sao Paulo; BrasilFil: Pereira Paglia, Adriano. Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas; BrasilFil: Moreira, Adryelle. Amplo Engenharia e Gestão de Projetos ; BrasilFil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; ArgentinaFil: Gatica, Ailin. Universidad Nacional de San Luis; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: Ochoa, Ana Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: de Angelo, Carlos Daniel. Universidad Nacional de Rio Cuarto. Facultad de Cs.exactas Fisicoquimicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente.; ArgentinaFil: Tellaeche, Cintia Gisele. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias. Centro de Estudios Ambientales Territoriales y Sociales; Argentina. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Ecorregiones Andinas; ArgentinaFil: Varela, Diego Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Vanderhoeven, Ezequiel Andres. Ministerio de Salud. Instituto Nacional de Medicina Tropical; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Caruso, María Flavia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Administración de Parques Nacionales. Delegación Regional del Noroeste; ArgentinaFil: Arrabal, Juan Pablo. Secretaria de Gobierno de Salud. Instituto Nacional de Medicina Tropical - Sede Puerto Iguazú Misiones; Argentina. Centro de Investigaciones del Bosque Atlántico; ArgentinaFil: Iezzi, María Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Di Bitetti, Mario Santiago. Centro de Investigaciones del Bosque Atlántico; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Cruz, Paula Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Centro de Investigaciones del Bosque Atlántico; ArgentinaFil: Reppucci, Juan Ignacio. Administración de Parques Nacionales. Delegación Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Benito Santamaria, Silvia. Centro de Investigaciones del Bosque Atlántico; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Quiroga, Verónica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; ArgentinaFil: Di Blanco, Yamil Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Marás, Gustavo Arnaldo. Administración de Parques Nacionales. Delegación Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Camino, Micaela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; ArgentinaFil: Perovic, Pablo Gastón. Administración de Parques Nacionales. Delegación Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martínez Pardo, Julia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Costa, Sebastián Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Pinheiro, Fabiana. Universidade Federal do Rio Grande do Sul; BrasilFil: Volkmer de Castilho, Pedro. Universidade Federal de Santa Catarina; BrasilFil: Bercê, William. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Camara Assis, Julia. Universidade Estadual Paulista Julio de Mesquita Filho. Faculdade de Engenharia.; BrasilFil: Rodrigues Tonetti, Vinicius. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Alves Eigenheer, Milene. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Chinem, Simonne. Universidade de Sao Paulo; BrasilFil: Honda, Laura K.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bergallo, Helena de Godoy. Universidade do Estado de Rio do Janeiro; BrasilFil: Alberici, Vinicius. Universidade de Sao Paulo; BrasilFil: Wallace, Robert. Wildlife Conservation Society; Estados UnidosFil: Ribeiro, Milton Cezar. Universidade de Sao Paulo; BrasilFil: Galetti, Mauro. Universidade Estadual Paulista Julio de Mesquita Filho; Brasi

SARS-CoV-2 vaccination modelling for safe surgery to save lives : data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.Peer reviewe

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