124 research outputs found
On-line PCA with Optimal Regrets
We carefully investigate the on-line version of PCA, where in each trial a
learning algorithm plays a k-dimensional subspace, and suffers the compression
loss on the next instance when projected into the chosen subspace. In this
setting, we analyze two popular on-line algorithms, Gradient Descent (GD) and
Exponentiated Gradient (EG). We show that both algorithms are essentially
optimal in the worst-case. This comes as a surprise, since EG is known to
perform sub-optimally when the instances are sparse. This different behavior of
EG for PCA is mainly related to the non-negativity of the loss in this case,
which makes the PCA setting qualitatively different from other settings studied
in the literature. Furthermore, we show that when considering regret bounds as
function of a loss budget, EG remains optimal and strictly outperforms GD.
Next, we study the extension of the PCA setting, in which the Nature is allowed
to play with dense instances, which are positive matrices with bounded largest
eigenvalue. Again we can show that EG is optimal and strictly better than GD in
this setting
Clinicopathologic characteristics and prognostic factors of ovarian fibrosarcoma: the results of a multi-center retrospective study
<p>Abstract</p> <p>Background</p> <p>Ovarian fibrosarcomas are very rare tumors, and therefore, few case studies have evaluated the prognostic factors of this disease. To our knowledge, this study represents the largest study to evaluate the clinical and pathologic factors associated with ovarian fibrosarcoma patients.</p> <p>Methods</p> <p>Thirty-one cases of ovarian fibrosarcoma were retrospectively reviewed, which included medical records for eight patients, and 23 published case reports from 1995 through 2009. Patient treatment regimens included total hysterectomy with bilateral adnexectomy and an omentectomy (BAO) (n = 9), oophorectomy (OR) (n = 8), chemotherapy (CT) (n = 1), BAO followed by chemotherapy (BAO+CT) (n = 11), BAO followed by radiotherapy (BAO+RT) (n = 1), and oophorectomy followed by radiotherapy (OR + RT) (n = 1).</p> <p>Results</p> <p>The patients of this cohort were staged according to the guidelines of the Federation of Gynecology and Obstetrics (FIGO), with 15, 6, 9, and 1 stage I-IV cases identified, respectively. Mitotic count values were also evaluated from 10 high-power fields (HPFs), and 3 cases had an average mitotic count < 4, 18 cases were between 4 and 10, and 10 cases had an average mitotic count value ≥ 10. The Ki-67 (MIB-1) proliferation index values were grouped according to values that as follows: < 10% (n = 5), between 10% and 50% (n = 9), and ≥ 50% (n = 5). Positive expression of vimentin (100%, 22/22) and negative expression of CD117 (0%, 5/5) were also detected. Moreover, expression of smooth muscle actin (2/18), desmin (1/13), epithelial membrane antigen (0/11), S-100 (1/19), CD99 (0/6), CD34 (1/5), α-inhibin (7/15), estrogen receptor (1/6), and progesterone receptor (1/6) were reported for subsets of the cases examined. After a median follow-up period of 14 months (range, 2-120), the 2-year overall survival rates (OS) and disease-free survival (DFS) rates for all patients were 55.9% and 45.4%, respectively. Cox proportional hazard regression analysis of survival showed that FIGO stage (<it>P </it>= 0.007) and treatment (<it>P </it>= 0.008) were predictive of poor prognosis. Furthermore, patients with stage I tumors that received BAO+CT were associated with a better prognosis.</p> <p>Conclusions</p> <p>Mitotic activity, and cells positive for Ki-67 were identified as important factors in the diagnosis of ovarian fibrosarcoma. Furthermore, FIGO stage and treatment modalities have the potential to be prognostic factors of survival, with BAO followed by adjuvant chemotherapy associated with an improved treatment outcome.</p
Redistribution of Actin during Assembly and Reassembly of the Contractile Ring in Grasshopper Spermatocytes
Cytokinesis in animal cells requires the assembly of an actomyosin contractile ring to cleave the cell. The ring is highly dynamic; it assembles and disassembles during each cell cleavage, resulting in the recurrent redistribution of actin. To investigate this process in grasshopper spermatocytes, we mechanically manipulated the spindle to induce actin redistribution into ectopic contractile rings, around reassembled lateral spindles. To enhance visualization of actin, we folded the spindle at its equator to convert the remnants of the partially assembled ring into a concentrated source of actin. Filaments from the disintegrating ring aligned along reorganizing spindle microtubules, suggesting that their incorporation into the new ring was mediated by microtubules. We tracked incorporation by speckling actin filaments with Qdots and/or labeling them with Alexa 488-phalloidin. The pattern of movement implied that actin was transported along spindle microtubules, before entering the ring. By double-labeling dividing cells, we imaged actin filaments moving along microtubules near the contractile ring. Together, our findings indicate that in one mechanism of actin redistribution, actin filaments are transported along spindle microtubule tracks in a plus-end–directed fashion. After reaching the spindle midzone, the filaments could be transported laterally to the ring. Notably, actin filaments undergo a dramatic trajectory change as they enter the ring, implying the existence of a pulling force. Two other mechanisms of actin redistribution, cortical flow and de novo assembly, are also present in grasshopper, suggesting that actin converges at the nascent contractile ring from diffuse sources within the cytoplasm and cortex, mediated by spindle microtubules
Cortical Mechanics and Meiosis II Completion in Mammalian Oocytes Are Mediated by Myosin-II and Ezrin-Radixin-Moesin (ERM) Proteins
Analysis of mouse oocyte mechanics shows that effective tension drops 6-fold from prophase I to metaphase II; the metaphase II egg has a 2.5-fold tension differential between the cortex over the spindle and the opposite cortex. Manipulation of actin, myosin-II, or ERMs alters tension levels and induces spindle abnormalities during meiosis II
The Mayer-Rokitansky-Küster-Hauser syndrome (congenital absence of uterus and vagina) – phenotypic manifestations and genetic approaches
The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome affects at least 1 out of 4500 women and has for a long time been considered as a sporadic anomaly. Congenital absence of upper vagina and uterus is the prime feature of the disease which, in addition, is often found associated with unilateral renal agenesis or adysplasia as well as skeletal malformations (MURCS association). The phenotypic manifestations of MRKH overlap various other syndromes or associations and thus require accurate delineation. Since MRKH manifests itself in males, the term GRES syndrome (Genital, Renal, Ear, Skeletal) might be more appropriate when applied to both sexes. The MRKH syndrome, when described in familial aggregates, seems to be transmitted as an autosomal dominant trait with an incomplete degree of penetrance and variable expressivity. This suggests the involvement of either mutations in a major developmental gene or a limited chromosomal deletion. Until recently progress in understanding the genetics of MRKH syndrome has been slow, however, now HOX genes have been shown to play key roles in body patterning and organogenesis, and in particular during genital tract development. Expression and/or function defects of one or several HOX genes may account for this syndrome
Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions
Relative Loss Bounds for On-line Density Estimation with the Exponential Family of Distributions
We consider on-line density estimation with a parameterized density from the exponential family. The on-line algorithm receives one example at a time and maintains a parameter that is essentially an average of the past examples. After receiving an example the algorithm incurs a loss, which is the negative loglikelihood of the example with respect to the past parameter of the algorithm. An o-line algorithm can choose the best parameter based on all the examples. We prove bounds on the additional total loss of the on-line algorithm over the total loss of the best o-line parameter. These relative loss bounds hold for an arbitrary sequence of examples. The goal is to design algorithms with the best possible relative loss bounds. We use a Bregman divergence to derive and analyze each algorithm. These divergences are relative entropies between two exponential distributions. We also use our methods to prove relative loss bounds for linear regression
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