AIP and MEN1 mutations and AIP immunohistochemistry in pituitary adenomas in a tertiary referral center.

Background: Pituitary adenomas have a high disease burden due to tumor growth/ invasion and disordered hormonal secretion. Germline mutations in genes such as MEN1 and AIP are associated with early onset of aggressive pituitary adenomas that can be resistant to medical therapy. Aims: We performed a retrospective screening study using published risk criteria to assess the frequency of AIP and MEN1 mutations in pituitary adenoma patients in a tertiary referral center. Methods: Pituitary adenoma patients with pediatric/adolescent onset, macroadenomas occurring ≤30 years of age, familial isolated pituitary adenoma (FIPA) kindreds and acromegaly or prolactinoma cases that were uncontrolled by medical therapy were studied genetically. We also assessed whether immunohistochemical staining for AIP (AIP-IHC) in somatotropinomas was associated with somatostatin analogs (SSA) response. Results: Fifty-five patients met the study criteria and underwent genetic screening for AIP/MEN1 mutations. No mutations were identified and large deletions/duplications were ruled out using MLPA. In a cohort of sporadic somatotropinomas, low AIP-IHC tumors were significantly larger (P = 0.002) and were more frequently sparsely granulated (P = 0.046) than high AIP-IHC tumors. No significant relationship between AIP-IHC and SSA responses was seen. Conclusions: Germline mutations in AIP/MEN1 in pituitary adenoma patients are rare and the use of general risk criteria did not identify cases in a large tertiary-referral setting. In acromegaly, low AIP-IHC was related to larger tumor size and more frequent sparsely granulated subtype but no relationship with SSA responsiveness was seen. The genetics of pituitary adenomas remains largely unexplained and AIP screening criteria could be significantly refined to focus on large, aggressive tumors in young patients

Comparison of Clustering Algorithms for Learning Analytics with Educational Datasets

Learning Analytics is becoming a key tool for the analysis and improvement of digital education processes, and its potential benefit grows with the size of the student cohorts generating data. In the context of Open Education, the potentially massive student cohorts and the global audience represent a great opportunity for significant analyses and breakthroughs in the field of learning analytics. However, these potentially huge datasets require proper analysis techniques, and different algorithms, tools and approaches may perform better in this specific context. In this work, we compare different clustering algorithms using an educational dataset. We start by identifying the most relevant algorithms in Learning Analytics and benchmark them to determine, according to internal validation and stability measurements, which algorithms perform better. We analyzed seven algorithms, and determined that K-means and PAM were the best performers among partition algorithms, and DIANA was the best performer among hierarchical algorithms

PDbm: People detection benchmark repository

This paper is a postprint of a paper submitted to and accepted for publication in Electronics Letters and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library and IEEE XploreFollowing the approach of the change detection challenge, in order to facilitate the evaluation of new algorithms for people detection, a people detection benchmarking repository is presented. It includes realistic sequences, people detection ground truth and an evaluation framework. It will be updated based on received feedback, and will maintain a comprehensive ranking of submitted methods for years to come

Humoral response (IgG) of goats experimentally infected with Fasciola hepatica against cysteine proteinases of adult fluke

The use of cysteine proteinases from Fasciola hepatica adult flukes for the serodiagnosis of caprine fasciolosis by means of an indirect ELISA test was studied. Two proteolytic fractions from adult fluke homogenates, with apparent molecular weights of 28 and 34 kDa (P28 and P34 respectively), were characterised as cysteine proteinases using azocasein assays and gelatin gel analysis. Both P28 and P34 fractions were electroluted and used as antigens in two different indirect ELISA tests. Serum IgG levels against P28 and P34 in goats given an experimental primary infection with 200 metacercariae or in goats given two experimental infections with 200 metacercariae were determined and compared with those observed in an uninfected control group. ELISA tests using both cysteine proteases showed a rapid and consistent detection of specific IgG in all experimentally infected goats. The IgG response to P28 was the first to be detected as early as 2–3 weeks post-infection and remained elevated throughout the experiment. The response to P34 was detected later (4–6 wpi) and disappeared in some animals at 18 wpi, while flukes were still present in the bile ducts. No significant differences were observed between the anti-P28 and anti-P34 IgG responses between animals receiving a primary or a challenge infection. The results of our study, although preliminary, are promising since the P28 ELISA described here may be a reliable method for the immunodiagnosis of F. hepatica infection in goats

La valoración de la prueba neurocientífica en el proceso penal español: la P300

Debido al gran desarrollo que han sufrido las nuevas tecnologías nos encontramos ante la necesidad de incluirlas en el proceso penal. Esta situación ha supuesto que se tengan que analizar los derechos y garantías que se pueden ver vulnerados a la hora de aplicarse. El trabajo se ha centrado principalmente en la P300 y la opinión que tiene la doctrina y los tribunales sobre su uso tanto en la fase de instrucción como en el juicio oral.<br /

On-line remaining useful life estimation of power connectors focused on predictive maintenance

Connections are critical elements in power systems, exhibiting higher failure probability. Power connectors are considered secondary simple devices in power systems despite their key role, since a failure in one such element can lead to major issues. Thus, it is of vital interest to develop predictive maintenance approaches to minimize these issues. This paper proposes an on-line method to determine the remaining useful life (RUL) of power connectors. It is based on a simple and accurate model of the degradation with time of the electrical resistance of the connector, which only has two parameters, whose values are identified from on-line acquired data (voltage drop across the connector, electric current and temperature). The accuracy of the model presented in this paper is compared with the widely applied autoregressive integrated moving average model (ARIMA), showing enhanced performance. Next, a criterion to determine the RUL is proposed, which is based on the inflection point of the expression describing the electrical resistance degradation. This strategy allows determination of when the connector must be replaced, thus easing predictive maintenance tasks. Experimental results from seven connectors show the potential and viability of the suggested method, which can be applied to many other devices.This research was partially funded by Ministerio de Ciencia, Innovación y Universidades de España, grant number RTC-2017-6297-3 and by the Generalitat de Catalunya, grant number 2017 SGR 967.Peer ReviewedPostprint (author's final draft

E-cadherin expression is associated with somatostatin analogue response in acromegaly

Acromegaly is a rare disease resulting from hypersecretion of growth hormone (GH) and insulin‐like growth factor 1 (IGF1) typically caused by pituitary adenomas, which is associated with increased mortality and morbidity. Somatostatin analogues (SSAs) represent the primary medical therapy for acromegaly and are currently used as first‐line treatment or as second‐line therapy after unsuccessful pituitary surgery. However, a considerable proportion of patients do not adequately respond to SSAs treatment, and therefore, there is an urgent need to identify biomarkers predictors of response to SSAs. The aim of this study was to examine E‐cadherin expression by immunohistochemistry in fifty‐five GH‐producing pituitary tumours and determine the potential association with response to SSAs as well as other clinical and histopathological features. Acromegaly patients with tumours expressing low E‐cadherin levels exhibit a worse response to SSAs. E‐cadherin levels are associated with GH‐producing tumour histological subtypes. Our results indicate that the immunohistochemical detection of E‐cadherin might be useful in categorizing acromegaly patients based on the response to SSAs.ISCIII‐Subdirección General de Evaluación y Fomento de la Investigación PI13/02043 PI16/00175FEDER PI13/02043 PI16/00175Junta de Andalucía A‐0023‐2015 A‐0003‐2016 CTS‐1406 BIO‐0139Andalusian Ministry of Health C‐0015‐2014CIBERobn PI13/ 02043 PI16/0017