Amministratori, possidenti, tessitori e contadini: ritratto relazionale di una comunità dell’ottocento veneto

This article describes the hierarchical system, the management and the social integration of families in a textile community of the Venetian countryside, Follina (TV) in the nineteenth century. The article considers how families relate each other within the community, fitting in the social context. For these reasons it is important to measure the distance and the relationships ‘between’ families and ‘towards’ families who constitute the communitarian leadership, i.e. the notables who wield the economic (often wool entrepreneurs), the political and the parish power. The social network analysis is often cited in social history as a possible explanatory model of historical processes, as it would be able to overcome the rigid classification schemes of class membership. However, it remains a rarely practiced approach. If it is used in a formal way, it allows to understand the relational dynamics actually experienced by individuals, social groups, families and kinships. A relational dynamic reconstruction between 1834 and 1888 is carried out by means of a detailed study of kinship and godparenthood relations. This reconstruction allows to observe the role played by different elites over time and their different attitudes, in terms of integration or social isolation

Between Constraints and Coercion. Marriage and Social Reproduction in Northern and Central Italy, 18th-19th Centuries

In this paper we review the main theories of household and marriage systems, highlighting their inability to account for the astonishing variety of family and marriage patterns that characterized modern Italy. We propose a new interpretative framework, where social reproduction is given pride of place as the main factor shaping marital behavior and household formation in the past. We test our theory analyzing five populations in northern and central Italy, characterized by different ecological, economic, and social conditions. We use an event history analysis approach to model the timing of marriage in the populations under study. The results confirm that coercion mattered much more than Malthusian economic constraints. We conclude suggesting a more general application of our approach to the study of marital behavior, family formation, and residential patterns in the past

Adverse events during longterm low-dose glucocorticoid treatment of polymyalgia rheumatica: a retrospective study

To assess the occurrence of adverse events in a cohort of patients with polymyalgia rheumatica (PMR), treated with low-dose glucocorticoids (GC). METHODS: This was a retrospective study by review of medical records. RESULTS: We identified 222 patients who had a mean duration of followup of 60 ± 22 months and a mean duration of GC therapy of 46 ± 22 months. We found that 95 patients (43%) had at least 1 adverse event after a mean duration of GC therapy of 31 ± 22 months and a mean cumulative dose of 3.4 ± 2.4 g. In particular, 55 developed osteoporosis, 31 had fragility fractures; 27 developed arterial hypertension; 11 diabetes mellitus; 9 acute myocardial infarction; 3 stroke; and 2 peripheral arterial disease. Univariate analysis showed that the duration of GC treatment was significantly associated with osteoporosis (p < 0.0001), fragility fractures (p < 0.0001), arterial hypertension (p < 0.005), and acute myocardial infarction (p < 0.05). Cumulative GC dose was significantly associated with osteoporosis (p < 0.0001), fragility fractures (p < 0.0001), and arterial hypertension (p < 0.01). The adverse events occurred more frequently after 2 years of treatment. Multivariate analysis showed that GC duration was significantly associated with osteoporosis (adjusted OR 1.02, 95% CI 1.02-1.05) and arterial hypertension (adjusted OR 1.03, 95% CI 1.01-1.06); GC cumulative dose was significantly associated with fragility fractures (adjusted OR 1.4, 95% CI 1.03-1.8). CONCLUSION: Longterm, low-dose GC treatment of PMR is associated with serious adverse events such as osteoporosis, fractures, and arterial hypertension; these adverse events occur mostly after 2 years of treatment

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Discriminant analysis on small cell lung cancer and non-small cell lung cancer by means of NSE and CYFRA-21.1

A correct diagnosis of small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) is essential both for prognostic and therapeutic reasons. We used discriminant analysis as a method to optimize the discriminant power of serum tumour marker levels for differentiation between SCLC and NSCLC. A panel of serum markers, including neurone specific enolase (NSE), cytokeratin fragment antigen 21.1 (CYFRA-21.1), tissue polypeptide antigen (TPA) and carcinoembryonic antigen (CEA) was obtained in 50 consecutive NSCLC and 17 SCLC. Data were analysed by the BMDP statistical program after logarithmic transformation of marker levels. The variables selected were NSE and CYFRA-21.1. Considered together, they were able to give a 97% rate of correct classification. The formula generated (canonic variable, CV) was validated on a group of seven SCLC and 22 NSCLC patients. Only two errors occurred. We therefore conclude that the canonic variable tested, based on NSE and CYFRA-21.1, provides a good discrimination between the two types of lung cancer. The method is rapid, relatively inexpensive, and based on simple serum tests

Prevalence and incidence of osteoporotic fractures in patients on long-term glucocorticoid treatment for rheumatic diseases: The glucocorticoid induced OsTeoporosis TOol (GIOTTO) study

Osteoporosis and fractures are common and invalidating consequences of chronic glucorticoid (GC) treatment. Reliable information regarding the epidemiology of GC induced osteoporosis (GIOP) comes exclusively from the placebo group of randomized clinical trials while observational studies are generally lacking data on the real prevalence of vertebral fractures, GC dosage and primary diagnosis. The objective of this study was to evaluate the prevalence and incidence of osteoporotic fractures and to identify their major determinants (primary disease, GC dosage, bone mineral density, risk factors, specific treatment for GIOP) in a large cohort of consecutive patients aged &gt;21 years, on chronic treatment with GC ( 655 mg prednisone - PN - equivalent) and attending rheumatology centers located all over Italy. Glucocorticoid Induced OsTeoporosis TOol (GIOTTO) is a national multicenter cross-sectional and longitudinal observational study. 553 patients suffering from Rheumatoid Arthritis (RA), Polymyalgia Rheumatica (PMR) and Connective Tissue Diseases (CTDs) and in chronic treatment with GCs were enrolled. Osteoporotic BMD values (T score &lt;-2.5) were observed in 28%, 38% and 35% of patients with CTDs, PMR or RA at the lumbar spine, and in 18%, 29% and 26% at the femoral neck, respectively. Before GC treatment, prevalent clinical fractures were reported by 12%, 37% and 17% of patients with CTDs, PMR, or RA, respectively. New clinical fragility fractures during GC treatment were reported by 12%, 10% and 23% of CTDs, PMR and RA patients, respectively. Vertebral fractures were the prevailing type of fragility fracture. More than 30% of patients had recurrence of fracture. An average of 80% of patients were in supplementation with calcium and/or vitamin D during treatment with GCs. Respectively, 64%, 80%, and 72% of the CTDs, PMR and RA patients were on pharmacological treatment for GIOP, almost exclusively with bisphosphonates. The GIOTTO study might provide relevant contributions to clinical practice, in particular by highlighting and quantifying in real life the prevalence of GIOP and relative fractures, the frequency of the main risk factors, and the currently sub-optimal prevention. Moreover, these results emphasize the importance of the underlying rheumatic disease on the risk of GIOP associated fractures

A developmental approach to predicting neuronal connectivity from small biological datasets: a gradient-based neuron growth model.

PMCID: PMC3931784 Open Access article: BB/G006652/1 and BB/G006369/1.Relating structure and function of neuronal circuits is a challenging problem. It requires demonstrating how dynamical patterns of spiking activity lead to functions like cognitive behaviour and identifying the neurons and connections that lead to appropriate activity of a circuit. We apply a "developmental approach" to define the connectome of a simple nervous system, where connections between neurons are not prescribed but appear as a result of neuron growth. A gradient based mathematical model of two-dimensional axon growth from rows of undifferentiated neurons is derived for the different types of neurons in the brainstem and spinal cord of young tadpoles of the frog Xenopus. Model parameters define a two-dimensional CNS growth environment with three gradient cues and the specific responsiveness of the axons of each neuron type to these cues. The model is described by a nonlinear system of three difference equations; it includes a random variable, and takes specific neuron characteristics into account. Anatomical measurements are first used to position cell bodies in rows and define axon origins. Then a generalization procedure allows information on the axons of individual neurons from small anatomical datasets to be used to generate larger artificial datasets. To specify parameters in the axon growth model we use a stochastic optimization procedure, derive a cost function and find the optimal parameters for each type of neuron. Our biologically realistic model of axon growth starts from axon outgrowth from the cell body and generates multiple axons for each different neuron type with statistical properties matching those of real axons. We illustrate how the axon growth model works for neurons with axons which grow to the same and the opposite side of the CNS. We then show how, by adding a simple specification for dendrite morphology, our model "developmental approach" allows us to generate biologically-realistic connectomes

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets