84 research outputs found
Lack of acute antipsychotic effect of SCH23390, a selective dopamine D1 receptor antagonist
No full textNo abstract available
Benign multicystic peritoneal mesothelioma in a male patient with previous Wilms' tumor: A Case Report and Review of the Literature
No full textBenign multicystic peritoneal mesothelioma (BMPM) is a rare condition, more common in females of reproductive age, which arises from the peritoneal mesothelium. A 33-year-old male presented to our unit with abdominal pain and constipation. His past medical history included a previous unilateral nephrectomy for Wilms' tumor and the previous incidental finding of some intra-abdominal cystic formations at the level of the mesentery. After performing a CT scan, an exploratory laparotomy was done and a voluminous cystic mesenteric mass, composed of 3 confluent formations, was observed. Some other similar but significantly smaller lesions were found. An en bloc resection of the mesenteric mass together with the corresponding intestinal loops, an appendicectomy, and some peritoneal biopsies were performed. The postoperative period was complicated by a peritonitis due to dehiscence of the intestinal anastomosis, which required another operation, and a delayed return of normal bowel function, which was resolved through prokinetic therapy. Through histological examination, a BMPM was diagnosed. At 8 months of follow-up, the patient is free of symptoms. BMPM exact etiopathogenesis still remains uncertain. Given his high recurrence rate, a long-term follow-up is recommended
Primary thyroid leiomyosarcoma: a case report and review of the literature
No full textPrimary thyroid leiomyosarcoma (LMS) is an extremely rare tumor. We report a case of a 47-year-old male with a rapidly growing neck mass and disfagia. Preoperative investigations were diagnostic of anaplastic carcinoma. Total thyroidectomy with partial esophagectomy and dissection of right infrahyoid muscles was performed. Through histolological and immunohistochemical evaluations a primary thyroid high-grade LMS was diagnosed. At 2 months of follow-up a local recurrence was detected and consequently the patient was submitted to chemotherapy with partial response. He is still alive 9 months after surgery. Diagnosis of primary thyroid LMS is difficult due to its similarity to other more common thyroid tumors. To date, there is no standard therapy and prognosis is poor
Senecio canus (Prairie Groundsel) : Prairie Groundsel
No full textClass: Dicotyledoneae
Family: Asteraceae
Genus: Senecio
Species: canu
TISSUE-SPECIFIC PROCESSING OF THE NEUROENDOCRINE PROTEIN VGF
No full textVGF is a neuroendocrine-specific gene product that is up-regulated by nerve growth factor in the PC12 cell line. In rat neuroendocrine tissues two polypeptides of 90 and 80 kDa were detected by an antiserum to an N-terminal domain of VGF (from residues 4 to 240). In parallel, an antiserum directed against the C-terminal nonapeptide of VGF (from residues 609 to 617) revealed several additional posttranslational products, Peptides of apparent molecular sizes of 20, 18, and 10 kDa were prominent in nerve tissues and the hypophysis but absent in the adrenal medulla, and their relative abundance varied in distinct regions of the CNS. In PC12 cells VGF was proteolytically processed only after nerve growth factor treatment, and primary cultures of rat cerebellar granule cells accumulated the low-molecular-weight forms of VGF during in vitro maturation, In these cells the specific cleavages of VGF occurred in a postendoplasmic reticulum compartment; the processed forms were enriched in the secretory vesicles and were preferentially secreted upon cell membrane depolarization, Distinct differential distribution in the CNS and in vitro release of such posttranslational products indicate that these species may represent biologically relevant forms of VGF that play a role in neuronal communication
LCDB 1.0: An Extensive Learning Curves Database for Classification Tasks
No full textThe use of learning curves for decision making in supervised machine learning is standard practice, yet understanding of their behavior is rather limited. To facilitate a deepening of our knowledge, we introduce the Learning Curve Database (LCDB), which contains empirical learning curves of 20 classification algorithms on 246 datasets. One of the LCDB’s unique strength is that it contains all (probabilistic) predictions, which allows for building learning curves of arbitrary metrics. Moreover, it unifies the properties of similar high quality databases in that it (i) defines clean splits between training, validation, and test data, (ii) provides training times, and (iii) provides an API for convenient access (pip install lcdb). We demonstrate the utility of LCDB by analyzing some learning curve phenomena, such as convexity, monotonicity, peaking, and curve shapes. Improving our understanding of these matters is essential for efficient use of learning curves for model selection, speeding up model training, and to determine the value of more training data.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Pattern Recognition and Bioinformatic
Adversarially Robust Decision Tree Relabeling
No full textDecision trees are popular models for their interpretation properties and their success in ensemble models for structured data. However, common decision tree learning algorithms produce models that suffer from adversarial examples. Recent work on robust decision tree learning mitigates this issue by taking adversarial perturbations into account during training. While these methods generate robust shallow trees, their relative quality reduces when training deeper trees due the methods being greedy. In this work we propose robust relabeling, a post-learning procedure that optimally changes the prediction labels of decision tree leaves to maximize adversarial robustness. We show this can be achieved in polynomial time in terms of the number of samples and leaves. Our results on 10 datasets show a significant improvement in adversarial accuracy both for single decision trees and tree ensembles. Decision trees and random forests trained with a state-of-the-art robust learning algorithm also benefited from robust relabeling.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit
- …
