Casa Sollievo della Sofferenza

About: Casa Sollievo della Sofferenza is a healthcare organization based out in San Giovanni Rotondo, Italy. It is known for research contribution in the topics: Population & Cancer. The organization has 2234 authors who have published 6183 publications receiving 239811 citations. The organization is also known as: Home for Relief of the Suffering.

Treatment of peripheral arterial disease in diabetes: a consensus of the Italian Societies of Diabetes (SID, AMD), Radiology (SIRM) and Vascular Endovascular Surgery (SICVE).

Abstract: Diabetic foot (DF) is a chronic and highly disabling complication of diabetes. The prevalence of peripheral arterial disease (PAD) is high in diabetic patients and, associated or not with peripheral neuropathy (PN), can be found in 50% of cases of DF. It is worth pointing out that the number of major amputations in diabetic patients is still very high. Many PAD diabetic patients are not revascularised due to lack of technical expertise or, even worse, negative beliefs because of poor experience. This despite the progress obtained in the techniques of distal revascularisation that nowadays allow to reopen distal arteries of the leg and foot. Italy has one of the lowest prevalence rates of major amputations in Europe, and has a long tradition in the field of limb salvage by means of an aggressive approach in debridement, antibiotic therapy and distal revascularisation. Therefore, we believe it is appropriate to produce a consensus document concerning the treatment of PAD and limb salvage in diabetic patients, based on the Italian experience in this field, to share with the scientific community.

On the statistical assessment of classifiers using DNA microarray data

Abstract: In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia – Italy. The data set is made up of normal (22) and tumor (25) specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data. We estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA) classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045) as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS) and Support Vector Machines (SVM) classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035) and e = 18% (p = 0.037) respectively. Moreover, the error rate decreases as the training set size increases, reaching its best performances with 35 training examples. In this case, RLS and SVM have error rates of e = 14% (p = 0.027) and e = 11% (p = 0.019). Concerning the number of genes, we found about 6000 genes (p < 0.05) correlated with the pathology, resulting from the signal-to-noise statistic. Moreover the performances of RLS and SVM classifiers do not change when 74% of genes is used. They progressively reduce up to e = 16% (p < 0.05) when only 2 genes are employed. The biological relevance of a set of genes determined by our statistical analysis and the major roles they play in colorectal tumorigenesis is discussed. The method proposed provides statistically significant answers to precise questions relevant for the diagnosis and prognosis of cancer. We found that, with as few as 15 examples, it is possible to train statistically significant classifiers for colon cancer diagnosis. As for the definition of the number of genes sufficient for a reliable classification of colon cancer, our results suggest that it depends on the accuracy required.

GNAO1 encephalopathy: Broadening the phenotype and evaluating treatment and outcome

Abstract: OBJECTIVE: To describe better the motor phenotype, molecular genetic features, and clinical course of GNAO1-related disease. METHODS: We reviewed clinical information, video recordings, and neuroimaging of a newly identified cohort of 7 patients with de novo missense and splice site GNAO1 mutations, detected by next-generation sequencing techniques. RESULTS: Patients first presented in early childhood (median age of presentation 10 months, range 0-48 months), with a wide range of clinical symptoms ranging from severe motor and cognitive impairment with marked choreoathetosis, self-injurious behavior, and epileptic encephalopathy to a milder phenotype, featuring moderate developmental delay associated with complex stereotypies, mainly facial dyskinesia and mild epilepsy. Hyperkinetic movements were often exacerbated by specific triggers, such as voluntary movement, intercurrent illnesses, emotion, and high ambient temperature, leading to hospital admissions. Most patients were resistant to drug intervention, although tetrabenazine was effective in partially controlling dyskinesia for 2/7 patients. Emergency deep brain stimulation (DBS) was life saving in 1 patient, resulting in immediate clinical benefit with complete cessation of violent hyperkinetic movements. Five patients had well-controlled epilepsy and 1 had drug-resistant seizures. Structural brain abnormalities, including mild cerebral atrophy and corpus callosum dysgenesis, were evident in 5 patients. One patient had a diffuse astrocytoma (WHO grade II), surgically removed at age 16. CONCLUSIONS: Our findings support the causative role of GNAO1 mutations in an expanded spectrum of early-onset epilepsy and movement disorders, frequently exacerbated by specific triggers and at times associated with self-injurious behavior. Tetrabenazine and DBS were the most useful treatments for dyskinesia.

Mutational screening of the cationic trypsinogen gene in a large cohort of subjects with idiopathic chronic pancreatitis.

Abstract: Several missense mutations, including R122H, N29I, K23R, A16V and D22G, in the cationic trypsinogen gene (PRSS1), have been associated with certain forms of hereditary pancreatitis (HP). Their occurrence in the idiopathic chronic pancreatitis (ICP) and whether novel mutations could be identified in PRSS1 remain to be further evaluated. These were addressed by the mutational screening of the entire coding sequence and the intronic/exonic boundaries of the PRSS1 gene in 221 ICP subjects, using a previously established denaturing gradient gel electrophoresis technique. Among the known PRSS1 mutations, only the R122H was detected in a single subject and the A16V in two subjects in the cohort, strengthening that HP-associated PRSS1 mutations are rare in ICP. Additional missense mutations, including P36R, E79K, G83E, K92N and V123M, were identified once separately. By analogy with the known PRSS1 mutations, predisposition to pancreatitis by some of them, particularly the V123M autolysis cleavage site mutation, is suspected. Functional analysis is expected to clarify their possible medical consequences.