BACKGROUND Leiomyosarcoma (LMS) can originate from the retroperitoneum, uterus, extremity, and trunk. It is unclear whether tumors of different origin represent discrete entities. We compared clinicopathologic features and outcomes following surgical resection of LMS stratified by site of origin. METHODS Patients with LMS undergoing resection at a single institution were retrospectively revie...

Aim was to investigate expression of Ki-67, P53 and progesterone receptors (PR) in leiomyomas (LM), smooth muscle tumors of uncertain malignant potential (STUMP) and leiomyosarcomas (LMS) and to establish possible usefulness of these three parameters in distinguishing between LM and STUMP and STUMP and LMS. Retrospective study of 51 uterine smooth muscle neoplasm (16 LM, 18 STUMP, 17 LMS) techn...

This article presents the results from an analysis of online education and Learning Management Systems (LMS) in the five Nordic countries. The analysis is based on literature review and in-depth interviews with 20 selected Nordic training managers. The analysis comprises a broad range of institutions from primary education, secondary education, higher education, distance education, and corporat...

A cell's ability to recognize and adapt to the physical environment is central to its survival and function, but how mechanical cues are perceived and transduced into intracellular signals remains unclear. In mesenchymal stem cells (MSCs), high-magnitude substrate strain (HMS, ≥2%) effectively suppresses adipogenesis via induction of focal adhesion (FA) kinase (FAK)/mTORC2/Akt signaling generat...

Human uterine leiomyosarcoma (LMS) develops more often in the muscle tissue layer of the uterine body than in the uterine cervix. The development of gynecologic tumors is often correlated with female hormone secretion; however, the development of uterine LMS is not substantially correlated with hormonal conditions, and the risk factors are not yet known. Importantly, a diagnostic-biomarker, whi...

{ The fast exact least-mean-square (LMS) algorithm is a computationally-eecient method for computing the outputs and updates for an adaptive LMS nite-impulse-response (FIR) lter. In this paper, we extend this method to several useful algorithms for feedforward active noise control: the ltered-X LMS, modiied ltered-X LMS, eecient modiied ltered-X LMS, periodic ltered-X LMS, and sequential ltered...