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Background: Musculoskeletal disorders represent one of the most common complains among video display terminal (VDT) users and are responsible for an important burden of disease in white collars. Methods: From May 2017 to March 2018, 69 VDT users working at Trieste hospitals were recruited for a training session aimed to reduce musculoskeletal disorders in white collars workers. Thirty-three were assigned to the intervention group, whereas 36 were included in the control group. The intervention group received three personalized 1-hour-one-to-one sessions with a physiotherapist and a thorough evaluation of their workstation. Data were collected at baseline (T0), at 2 months (T1) and at 6 months (T2) using a standardized questionnaire and analyzed with the software STATA. Results: Overall pain significantly decreased in cases at T1 and T2 (p < 0.05). Headache significantly decreased in cases at T1 (p < 0.05). Body awareness significantly increased in cases both at T1 and T2 (p < 0.05). Headache was positively correlated with an increased perception of pain (Coef 6.85, CI95% 3.2-10.5; p < 0.001), while the intervention determined a significant reduction of overall pain during the follow up (OR 0.97, IC 0.95-0.99, p = 0.013). Cases showed a significant increase of the cranial-vertebral angle at the 6 months follow up (p < 0.05). Conclusion: A tailored physiotherapeutic intervention has showed a statistically significant decrease in osteoarticular pain and an increased body awareness in VDT users undergoing a personalized training session.

BACKGROUND: Methylchloroisothiazolinone (MCI)/methylisothiazolinone (MI) (Kathon® CG) is a common preservative used in industrial products, owing to its strong biocide effect. Contact allergy to MCI/MI has been reported in different occupations, including mechanics, hairdressers and healthcare workers. OBJECTIVE: To retrospectively analyse the temporal trend of MCI/MI sensitization in north-eastern Italy and to evaluate the associations with occupations in our geographical area. METHODS: From 1996 to 2016, 27 381 patients with suspected allergic contact dermatitis were patch tested in eight departments of Dermatology or Occupational Medicine in north-eastern Italy. Individual characteristics were collected through a standardized questionnaire. RESULTS: The overall prevalence of MCI/MI sensitization was 4.2%, with the highest prevalence found in women and in patients younger than 25 years. MCI/MI sensitization was significantly associated with atopic eczema (OR: 1.34, 95% CI: 1.10-1.70), hand/forearm dermatitis (OR: 1.20, 95% CI: 1.05-1.36) and face dermatitis (OR 1.30, 95% CI: 1.10-1.40). There was a significant association between MCI/MI sensitization and chemical processing workers (OR 1.74, 95% CI: 1.03-2.94), while mechanics and healthcare workers resulted more sensitized to this hapten only in the last 3 years. CONCLUSIONS Sensitization to MCI/MI is rising in the last years in Triveneto region, the 'epidemic' of sensitization to MCI/MI is mainly driven by extra-occupational dermatitis, and sensitization in some occupational groups is emerging only in the last years. A full labelling is compulsory for all products that contain isothiazolinones, to permit to identify the culprit agent.

The fast progress of information technology in the present years led to a substantial growth interms of the volume of data to be analyzed and the size of the problems needed to be solved.Since the Eighties, the formulation of out-of-memory models of computation was motivated by theintractability of the problems by the prevailing architectures. This trend is expected to grow evenfurther. Therefore, algorithm designers have to provide solutions specifically tailored for big dataprocessing.The design of algorithms often relies on kernels, basic yet essential primitives that may beinvoked several times by an algorithm during its execution. It is therefore fundamental to rely ontheoretically efficient, highly optimized and high performance kernels.In the field of linear algebra, the most common primitives concern the manipulation of datavectors, such as matrix-matrix multiplication or matrix-vector multiplication. Matrix multiplicationhas countless applications, from graph algorithms, machine learning, to computer graphics andimage processing. Its prominence is validated by the almost half century old research field thataims at providing optimal algorithms for matrix multiplication and trying to answer a long-standingconjecture.This dissertation aims at providing efficient kernels for sparse matrix multiplication. The maincontributions are the following:1. we present new Monte Carlo data structures for sparse output-sensitive matrix multiplicationbased on repeated predecessor queries that are used to find specific random linear combinationof vectors in sparse matrices,2. we introduce new Atlantic City algorithms for sparse Boolean matrix multiplication derivedfrom a novel framework that exploits size estimators for sparse matrix products,3. we design new Monte Carlo algorithms for fast sparse matrix multiplication that combineseveral existing frameworks to provide improved bounds for sparse matrix multiplication,4. we present new deterministic data structures for permutation matrices in the Parallel ExternalMemory model that translate into efficient and experimentally evaluated algorithms for permutingin concurrent out-of-memory models.The result is a collection of randomized and deterministic algorithms for sparse matrixcomputations that are meant to provide improvements over the state of the art in time or memoryefficiency. The fast progress of information technology in the present years led to a substantial growth in terms of the volume of data to be analyzed and the size of the problems needed to be solved. Since the Eighties, the formulation of out-of-memory models of computation was motivated by the intractability of the problems by the prevailing architectures. This trend is expected to grow evenfurther. Therefore, algorithm designers have to provide solutions specifically tailored for big data processing.The design of algorithms often relies on kernels, basic yet essential primitives that may be invoked several times by an algorithm during its execution. It is therefore fundamental to rely on theoretically efficient, highly optimized and high performance kernels.In the field of linear algebra, the most common primitives concern the manipulation of data vectors, such as matrix-matrix multiplication or matrix-vector multiplication. Matrix multiplication has countless applications, from graph algorithms, machine learning, to computer graphics and image processing. Its prominence is validated by the almost half century old research field that aims at providing optimal algorithms for matrix multiplication and trying to answer a long-standing conjecture.This dissertation aims at providing efficient kernels for sparse matrix multiplication. The main contributions are the following:(i) we present new Monte Carlo data structures for sparse outputsensitive matrix multiplication based on repeated predecessor queries that are used to find specific random linear combination of vectors in sparse matrices,(ii) we introduce new Atlantic City algorithms for sparse Boolean matrix multiplication derived from a novel framework that exploits size estimators for sparse matrix products,(iii) we design new Monte Carlo algorithms for fast sparse matrix multiplication that combine several existing frameworks to provide improved bounds for sparse matrix multiplication, (iv) we present new deterministic data structures for permutation matrices in the Parallel External Memory model that translate into efficient and experimentally evaluated algorithms for permuting in concurrent out-of-memory models.The result is a collection of randomized and deterministic algorithms for sparse matrix computations that are meant to provide improvements over the state of the art in time or memory efficiency.

Background Diagnostic trajectories for neurogenetic disorders frequently require the use of considerable time and resources, exposing patients and families to so-called “diagnostic odysseys”. Previous studies have provided strong evidence for increased diagnostic and clinical utility of whole-exome sequencing in medical genetics. However, specific reports assessing its utility in a setting such as ours- a neurogeneticist led academic group serving in a low-income country—are rare. Objectives To assess the diagnostic yield of WES in patients suspected of having a neurogenetic condition and explore the cost-effectiveness of its implementation in a research group located in an Argentinean public hospital. Methods This is a prospective study of the clinical utility of WES in a series of 40 consecutive patients selected from a Neurogenetic Clinic of a tertiary Hospital in Argentina. We evaluated patients retrospectively for previous diagnostic trajectories. Diagnostic yield, clinical impact on management and economic diagnostic burden were evaluated. Results We demonstrated the clinical utility of Whole Exome Sequencing in our patient cohort, obtaining a diagnostic yield of 40% (95% CI, 24.8%-55.2%) among a diverse group of neurological disorders. The average age at the time of WES was 23 (range 3–70). The mean time elapsed from symptom onset to WES was 11 years (range 3–42). The mean cost of the diagnostic workup prior to WES was USD 1646 (USD 1439 to 1853), which is 60% higher than WES cost in our center. Conclusions WES for neurogenetics proved to be an effective, cost- and time-saving approach for the molecular diagnosis of this heterogeneous and complex group of patients. Fil: Córdoba, Marta. Universidad Austral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Rodríguez Quiroga, Sergio Alejandro. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: Vega, Patricia Analía. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: Salinas, Valeria. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina Fil: Perez Maturo, Josefina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina Fil: Amartino, Hernán. Universidad Austral; Argentina Fil: Vásquez Dusefante, Cecilia. Universidad Austral; Argentina Fil: Medina, Nancy. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: González Morón, Dolores. Hospital Universitario Austral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Kauffman, Marcelo Andres. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina

Clinical variability is a hallmark of neurogenetic disorders. They involve widespread neurological entities such as neuropathies, ataxias, myopathies, mitochondrial encephalopathies, leukodystrophies, epilepsy and intellectual disabilities. Despite the use of considerable time and resources, the diagnostic yield in this field has been disappointingly low. This etiologic search has been called a “diagnostic odyssey” for many families. Whole exome sequencing (WES) has proved to be useful across a variety of genetic disorders, simplifying the odyssey of many patients and their families and leading to subsequent changes in clinical management in a proportion of them. Although a diagnostic yield of about 30% in neurogenetic disorders can be extrapolated from the results of large series that have included other medical conditions as well, there are not specific reports assessing its utility in a setting such as ours: a neurogeneticist led academic group serving in a low-income country. Herein, we report on a series of our first 40 consecutive cases that were selected for WES in a research-based neurogenetics laboratory. We demonstrated the clinical utility of WES in our patient cohort, obtaining a diagnostic yield of 40% (95% CI, 24.8%-55.2%), describing cases in which clinical management was altered, and suggesting the potential cost-effectiveness of WES as a single test by examining the number and types of tests that were performed prior to WES which added up to a median cost of $3537.6 ($2892 to $5084) for the diagnostic odysseys experienced by our cohort.

As a whole neurogenetic diseases are a common group of neurological disorders. However, the recognition and molecular diagnosis of these disorders is not always straightforward. Besides, there is a paucity of information regarding the diagnostic yield that specialized neurogenetic clinics could obtain. We performed a prospective, observational, analytical study of the patients seen in a neurogenetic clinic at a tertiary medical centre to assess the diagnostic yield of a comprehensive diagnostic evaluation that included a personalized clinical assessment along with traditional and next-generation sequencing diagnostic tests. We included a cohort of 387 patients from May 2008 to June 2014. For sub-group analysis we selected a sample of patients whose main complaint was the presence of progressive ataxia, to whom we applied a systematic molecular diagnostic algorithm. Overall, a diagnostic mutation was identified in 27·4% of our cohort. However, if we only considered those patients where a molecular test could be performed, the success rate rises to 45%. We obtained diagnostic yields of 23·5 and 57·5% in the global group of ataxic patients and in the subset of ataxic patients with a positive family history, respectively. Thus, about a third of patients evaluated in a neurogenetic clinic could be successfully diagnosed. Fil: Rodríguez Quiroga, Sergio Alejandro. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: Córdoba, Marta. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina Fil: González Morón, Dolores. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina Fil: Medina, Nancy. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: Vega, Patricia. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: Vazquez Dusefante, Cecilia. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: Arakaki, Tomoko. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: Garreto, Nélida Susana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina Fil: Kauffman, Marcelo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; Argentina