Gauge-optimal approximate learning for small data classification problems

Small data learning problems are characterized by a significant discrepancy between the limited amount of response variable observations and the large feature space dimension. In this setting, the common learning tools struggle to identify the features important for the classification task from those that bear no relevant information, and cannot derive an appropriate learning rule which allows to discriminate between different classes. As a potential solution to this problem, here we exploit the idea of reducing and rotating the feature space in a lower-dimensional gauge and propose the Gauge-Optimal Approximate Learning (GOAL) algorithm, which provides an analytically tractable joint solution to the dimension reduction, feature segmentation and classification problems for small data learning problems. We prove that the optimal solution of the GOAL algorithm consists in piecewise-linear functions in the Euclidean space, and that it can be approximated through a monotonically convergent algorithm which presents -- under the assumption of a discrete segmentation of the feature space -- a closed-form solution for each optimization substep and an overall linear iteration cost scaling. The GOAL algorithm has been compared to other state-of-the-art machine learning (ML) tools on both synthetic data and challenging real-world applications from climate science and bioinformatics (i.e., prediction of the El Nino Southern Oscillation and inference of epigenetically-induced gene-activity networks from limited experimental data). The experimental results show that the proposed algorithm outperforms the reported best competitors for these problems both in learning performance and computational cost.Comment: 47 pages, 4 figure

The S-HOCK dataset: Analyzing crowds at the stadium

The topic of crowd modeling in computer vision usually assumes a single generic typology of crowd, which is very simplistic. In this paper we adopt a taxonomy that is widely accepted in sociology, focusing on a particular category, the spectator crowd, which is formed by people \u201cinterested in watching something specific that they came to see\u201d [6]. This can be found at the stadiums, amphitheaters, cinema, etc. In particular, we propose a novel dataset, the Spectators Hockey (S-HOCK), which deals with 4 hockey matches during an international tournament. In the dataset, a massive annotation has been carried out, focusing on the spectators at different levels of details: at a higher level, people have been labeled depending on the team they are supporting and the fact that they know the people close to them; going to the lower levels, standard pose information has been considered (regarding the head, the body) but also fine grained actions such as hands on hips, clapping hands etc. The labeling focused on the game field also, permitting to relate what is going on in the match with the crowd behavior. This brought to more than 100 millions of annotations, useful for standard applications as people counting and head pose estimation but also for novel tasks as spectator categorization. For all of these we provide protocols and baseline results, encouraging further research

Risk Factors and Outcomes of Infections by Multidrug-Resistant Gram-Negative Bacteria in Patients Undergoing Hematopoietic Stem Cell Transplantation

Abstract The objective of this study was to determine risk factors and outcomes of infections by multidrug-resistant gram-negative (MDR GN) bacteria in 241 recipients of hematopoietic stem cell transplantation (HSCT). The cumulative incidence of infections was 10.5% (95% CI, 12.0% to 25.8%), with 57% of infections occurring during the period of severe neutropenia (neutrophil count  6 /L). In multivariate analysis, allogeneic transplant and colonization with MDR GN bacteria at admission to the transplant unit were significantly associated with an increased risk of infection. Although we observed neither transplant-related mortality (TRM) nor deaths due to infections by MDR GN bacteria after autologous transplant, in the allogeneic setting a significant difference was reported in terms of overall survival (OS) and TRM between patients who developed infections and those who did not (1-year OS, 39% versus 68%; 1-year TRM, 42% versus 19%). In multivariate analysis, refractory disease and development of grades III to IV graft-versus-host disease (GVHD) were factors that affected both TRM and OS, whereas occurrence of infections by MDR GN pathogens significantly reduced OS. We conclude that eligibility to allogeneic HSCT in MDR GN bacteria carriers should be carefully evaluated together with all other factors that independently influence outcome (disease status, donor, and GVHD risk)

NEW EARLY HOLOCENE SETTLEMENT IN CENTRAL ITALY: THE MESOLITHIC SITE OF CONTRADA PACE (MARCHE REGION)

Early Holocene hunter-gatherer settlements are spread throughout Italy and testify to the exploitation of very different landscapes. Nonetheless, their preservation state is not always exceptional. This is not the case for Contrada Pace, an archaeological site recently discovered on a terrace of the Chienti river in central-eastern Italy. This paper reports on the geomorphological, pedo-stratigraphic, and archaeological record of one of the most complete and well-preserved Early Mesolithic open-air sites in Italy and southern Europe. Micro-stratigraphic excavations extended over more than 500 square meters have exposed a buried paleosol with anthropogenic features, which contained thousand lithic artefacts and organic remains framed in the context of a primary forest. These findings appear clustered in different functional areas that yielded multiple structured features. The field evidence integrated by radiocarbon dating and archaeobotanical, archaeomalacological and zooarchaeological data allowed to propose a first interpretation of the general structure of the site and the most significant featuresThe archaeological excavation of the site was carried out by ArcheoLAB (Macerata, Italy) in the framework of construction activities promoted by the Province of Macerata and the Municipality of Tolentino. DV has received funding from the European Union's Horizon 2020 research and innovation programme (Grant Agreement number: 886476 - LiMPH - H2020-MSCA-IF-2019). The archaeobotanical study and 14C dates were funded by the European Research Council (ERC) as part of the Research and Innovation program of the European Community Horizon 2020 (HIDDEN FOODS no.639286 to EC)

A modular framework for the development of targeted Covid-19 blood transcript profiling panels

Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of targeted blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection.; We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates.; As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: immunological relevance, therapeutic development relevance and SARS biology relevance.; Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients

Outcomes and Predictors of Mortality in Patients With KPC-Kp Infections Treated With Meropenem Vaborbactam: An Observational Multicenter Study

Background Meropenem-vaborbactam is a recent and promising option for the treatment of KPC-producing Klebsiella pneumoniae (KPC-Kp) infections, including those resistant to ceftazidime-avibactam.Methods We conducted a retrospective analysis of observational data from 19 Italian hospitals on use and outcomes of patients treated with meropenem-vaborbactam for at least >= 24 hours for KPC-Kp infections. Crude and propensity-weighted multiple Cox regression models were performed to ascertain risk factors independently associated with 30-day mortality.Results The cohort included 342 adults with bloodstream infections (n = 172) and nonbacteremic infections (n = 170), of which 107 were lower respiratory tract infections, 30 were complicated urinary tract infections, and 33 were infections involving other sites. Most infections (62.3%) were managed with meropenem-vaborbactam monotherapy, or in combination with at least 1 other active drug (usually fosfomycin, tigecycline, or gentamicin) (37.7%). The 30-day mortality rate was 31.6% (108/342). In multiple Cox regression model, 30-day mortality was independently associated with septic shock at infection onset, Charlson comorbidity index >= 3, dialysis, concomitant COVID-19, and INCREMENT score >= 8. Administration of meropenem-vaborbactam within 48 hours from infection onset was a negative predictor of mortality. All predictors, except administration of meropenem-vaborbactam within 48 hours, remained significant when the multiple Cox regression model was repeated after adjustment for the propensity score for receipt of combination therapy.Conclusions Despite the limits of a retrospective study, the data derived from this multicenter cohort provide additional evidence on the efficacy of meropenem-vaborbactam in treating severe KPC-Kp infections, even when used as monotherapy

Ceftolozane/Tazobactam for Treatment of Severe ESBL-Producing Enterobacterales Infections: A Multicenter Nationwide Clinical Experience (CEFTABUSE II Study)

Background. Few data are reported in the literature about the outcome of patients with severe extended-spectrum beta-lactamase-producing Enterobacterales (ESBL-E) infections treated with ceftolozane/tazobactam (C/T), in empiric or definitive therapy.Methods. A multicenter retrospective study was performed in Italy (June 2016-June 2019). Successful clinical outcome was defined as complete resolution of clinical signs/symptoms related to ESBL-E infection and lack of microbiological evidence of infection. The primary end point was to identify predictors of clinical failure of C/T therapy.Results. C/T treatment was documented in 153 patients: pneumonia was the most common diagnosis (n = 46, 30%), followed by 34 cases of complicated urinary tract infections (22.2%). Septic shock was observed in 42 (27.5%) patients. C/T was used as empiric therapy in 46 (30%) patients and as monotherapy in 127 (83%) patients. Favorable clinical outcome was observed in 128 (83.7%) patients; 25 patients were considered to have failed C/T therapy. Overall, 30-day mortality was reported for 15 (9.8%) patients. At multivariate analysis, Charlson comorbidity index >4 (odds ratio [OR], 2.3; 95% confidence interval [CI], 1.9-3.5; P = .02), septic shock (OR, 6.2; 95% CI, 3.8-7.9; P < .001), and continuous renal replacement therapy (OR, 3.1; 95% CI, 1.9-5.3; P = .001) were independently associated with clinical failure, whereas empiric therapy displaying in vitro activity (OR, 0.12; 95% CI, 0.01-0.34; P < .001) and adequate source control of infection (OR, 0.42; 95% CI, 0.14-0.55; P < .001) were associated with clinical success.Conclusions. Data show that C/T could be a valid option in empiric and/or targeted therapy in patients with severe infections caused by ESBL-producing Enterobacterales. Clinicians should be aware of the risk of clinical failure with standard-dose C/T therapy in septic patients receiving CRRT

Nationwide consensus on the clinical management of treatment-resistant depression in Italy: a Delphi panel

Background: Treatment-resistant depression (TRD) is defined by the European Medicines Agency as a lack of clinically meaningful improvement after treatment, with at least two different antidepressants. Individual, familiar, and socio-economic burden of TRD is huge. Given the lack of clear guidelines, the large variability of TRD approaches across different countries and the availability of new medications to meet the need of effective and rapid acting therapeutic strategies, it is important to understand the consensus regarding the clinical characteristics and treatment pathways of patients with TRD in Italian routine clinical practice, particularly in view of the recent availability of esketamine nasal spray. Methods: A Delphi questionnaire with 17 statements (with a 7 points Likert scale for agreement) was administered via a customized web-based platform to Italian psychiatrists with at least 5 years of experience and specific expertise in the field of depression. In the second-round physicians were asked to answer the same statements considering the interquartile range of each question as an index of their colleagues' responses. Stata 16.1 software was used for the analyses. Results: Sixty panellists, representative of the Italian territory, answered the questionnaire at the first round. For 8/17 statements more than 75% of panellists reached agreement and a high consensus as they assigned similar scores; for 4 statements the panellists assigned similar scores but in the middle of the Likert scale showing a moderate agreement with the statement, while for 5 statements there was indecision in the agreement and low consensus with the statement. Conclusions: This Delphi Panel showed that there is a wide heterogeneity in Italy in the management of TRD patients, and a compelling need of standardised strategies and treatments specifically approved for TRD. A high level of consensus and agreement was obtained about the importance of adding lithium and/or antipsychotics as augmentation therapies and in the meantime about the need for long-term maintenance therapy. A high level of consensus and agreement was equally reached for the identification of esketamine nasal spray as the best option for TRD patients and for the possibility to administrate without difficulties esketamine in a community outpatient setting, highlighting the benefit of an appropriate educational support for patients

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients