Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Support vector machine model for diagnosis of lymph node metastasis in gastric cancer with multidetector computed tomography: a preliminary study

<p>Abstract</p> <p>Background</p> <p>Lymph node metastasis (LNM) of gastric cancer is an important prognostic factor regarding long-term survival. But several imaging techniques which are commonly used in stomach cannot satisfactorily assess the gastric cancer lymph node status. They can not achieve both high sensitivity and specificity. As a kind of machine-learning methods, Support Vector Machine has the potential to solve this complex issue.</p> <p>Methods</p> <p>The institutional review board approved this retrospective study. 175 consecutive patients with gastric cancer who underwent MDCT before surgery were included. We evaluated the tumor and lymph node indicators on CT images including serosal invasion, tumor classification, tumor maximum diameter, number of lymph nodes, maximum lymph node size and lymph nodes station, which reflected the biological behavior of gastric cancer. Univariate analysis was used to analyze the relationship between the six image indicators with LNM. A SVM model was built with these indicators above as input index. The output index was that lymph node metastasis of the patient was positive or negative. It was confirmed by the surgery and histopathology. A standard machine-learning technique called k-fold cross-validation (5-fold in our study) was used to train and test SVM models. We evaluated the diagnostic capability of the SVM models in lymph node metastasis with the receiver operating characteristic (ROC) curves. And the radiologist classified the lymph node metastasis of patients by using maximum lymph node size on CT images as criterion. We compared the areas under ROC curves (AUC) of the radiologist and SVM models.</p> <p>Results</p> <p>In 175 cases, the cases of lymph node metastasis were 134 and 41 cases were not. The six image indicators all had statistically significant differences between the LNM negative and positive groups. The means of the sensitivity, specificity and AUC of SVM models with 5-fold cross-validation were 88.5%, 78.5% and 0.876, respectively. While the diagnostic power of the radiologist classifying lymph node metastasis by maximum lymph node size were only 63.4%, 75.6% and 0.757. Each SVM model of the 5-fold cross-validation performed significantly better than the radiologist.</p> <p>Conclusions</p> <p>Based on biological behavior information of gastric cancer on MDCT images, SVM model can help diagnose the lymph node metastasis preoperatively.</p

The use of zootherapeutics in folk veterinary medicine in the district of Cubati, Paraíba State, Brazil

<p>Abstract</p> <p>Background</p> <p>The present work addresses the use of zootherapy in folk veterinary medicine (ethnoveterinary) by the residents of the municipal district of Cubati, microregion of Seridó, Paraíba State, Brazil. It sought to identify the principal animals used as medicinal sources for zootherapeutics and to contribute to the preservation and sustainability of this traditional knowledge.</p> <p>Methods</p> <p>Field research was undertaken on a weekly or biweekly basis during the period November, 2006, to January, 2007. Free, semi-structured, and open interviews were made with local residents of the municipal district of Cubati (in both urban and rural settings) as well as with venders in public markets. A total of 25 individuals of both sexes were interviewed (with ages varying from 26 to 78 years) although only 16 were finally chosen as informants as these people demonstrated the greatest degree of knowledge concerning zootherapeutics. Graphs and percentages were generated using Microsoft^©Excel 2007 software, and the species were identified by photographic registration and subsequent bibliographical surveys.</p> <p>Results</p> <p>Mammals constitute the main medicinal zootherapeutic source for folk veterinary medicines in the studied area, both in terms of the total number of species used and the frequency of their citation. Sheep (<it>Ovis aries</it>), pigs (<it>Sus scrofa</it>), cattle (<it>Bos taurus</it>), and foxes (<it>Cerdocyon thous</it>) were mentioned by 62.5, 43.75, 37.5, and 31.25% of the informants, respectively, as being used in folk veterinary medicine. Additionally, chameleons (<it>Iguana iguana</it>), chickens (<it>Gallus domesticus</it>), and rattlesnakes (<it>Crotalus durissus</it>) were mentioned by 75, 43.75, and 31.25% of the informants, respectively. Relatively simple animal illnesses, such as furuncles, or injuries resulting from embedded thorns or skin eruptions are responsible for the largest number of zootherapeutic treatment, while, diseases of greater complexity, such as rabies and brucellosis, were not even mentioned. Fat from various animals constituted the most frequently cited resource used for its medicinal-veterinary properties.</p> <p>Conclusion</p> <p>The examination of folk knowledge and health practices allows a better understanding of human interactions with their local environment, and aids in the formulation of appropriate strategies for natural resource conservation.</p

Portuguese recommendations for the use of biological and targeted synthetic diseasemodifying antirheumatic drugs in patients with rheumatoid arthritis – 2020 update

Objective: To update the recommendations for the treatment of rheumatoid arthritis (RA) with biological and targeted synthetic disease-modifying antirheumatic drugs (bDMARDs and tsDMARDs), endorsed by the Portuguese Society of Rheumatology (SPR). Methods: These treatment recommendations were formulated by Portuguese rheumatologists taking into account previous recommendations, new literature evidence and consensus opinion. At a national meeting, in a virtual format, three of the ten previous recommendations were re-addressed and discussed after a more focused literature review. A first draft of the updated recommendations was elaborated by a team of SPR rheumatologists from the SPR rheumatoid arthritis study group, GEAR. The resulting document circulated among all SPR rheumatologists for discussion and input. The level of agreement with each of all the recommendations was anonymously voted online by all SPR rheumatologists. Results: These recommendations cover general aspects such as shared decision, treatment objectives, systematic assessment of disease activity and burden and its registry in Reuma.pt. Consensus was also achieved regarding specific aspects such as initiation of bDMARDs and tsDMARDs, assessment of treatment response, switching and definition of persistent remission. Conclusion: These recommendations may be used for guidance of treatment with bDMARDs and tsDMARDs in patients with RA. As more evidence becomes available and more therapies are licensed, these recommendations will be updated.info:eu-repo/semantics/publishedVersio

Identification and Phylogenetic Analysis of Tityus pachyurus and Tityus obscurus Novel Putative Na+-Channel Scorpion Toxins

Background: Colombia and Brazil are affected by severe cases of scorpionism. In Colombia the most dangerous accidents are caused by Tityus pachyurus that is widely distributed around this country. In the Brazilian Amazonian region scorpion stings are a common event caused by Tityus obscurus. The main objective of this work was to perform the molecular cloning of the putative Na+-channel scorpion toxins (NaScTxs) from T. pachyurus and T. obscurus venom glands and to analyze their phylogenetic relationship with other known NaScTxs from Tityus species. Methodology/Principal Findings: cDNA libraries from venom glands of these two species were constructed and five nucleotide sequences from T. pachyurus were identified as putative modulators of Na+-channels, and were named Tpa4, Tpa5, Tpa6, Tpa7 and Tpa8; the latter being the first anti-insect excitatory b-class NaScTx in Tityus scorpion venom to be described. Fifteen sequences from T. obscurus were identified as putative NaScTxs, among which three had been previously described, and the others were named To4 to To15. The peptides Tpa4, Tpa5, Tpa6, To6, To7, To9, To10 and To14 are closely related to the a-class NaScTxs, whereas Tpa7, Tpa8, To4, To8, To12 and To15 sequences are more related to the b-class NaScTxs. To5 is possibly an arthropod specific toxin. To11 and To13 share sequence similarities with both a and b NaScTxs. By means of phylogenetic analysis using the Maximum Parsimony method and the known NaScTxs from Tityus species, these toxins were clustered into 14 distinct groups. Conclusions/Significance: This communication describes new putative NaScTxs from T. pachyurus and T. obscurus and their phylogenetic analysis. The results indicate clear geographic separation between scorpions of Tityus genus inhabiting the Amazonian and Mountain Andes regions and those distributed over the Southern of the Amazonian rainforest. Based on the consensus sequences for the different clusters, a new nomenclature for the NaScTxs is proposed

The use of citrus pulp silage in Diplodus puntazzo nutrition

[EN] Purpose Studying the efect of citrus pulp silage in the growth performance, amino acid retention of sharpsnout sea bream juveniles. Methods Citrus pulp is an energy and protein source that has been used to replace wheat meal in Diplodus puntazzo fngerlings; 96 fsh of 21.5±0.67 g were nourished with two experimental diets for 105 days. The control diet (CON) contained 421.6 g/kg of protein and 22.6 MJ/kg of energy. The citrus pulp diet (CPD) included 442.7 g/kg of protein and 22.02 MJ/ kg of energy. Results At the end of this trial, the CPD did not afect the growth parameters, but the feed efciency values exhibited statistically signifcant diferences, with those fsh fed the CPD having higher values, possibly due to the presence of limonene in the diet. The CPD also resulted in a reduction in amino acid (AA) content due to the protein being bound to fbre; this consequence did not afect the fnal fsh AA profle. 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