215 research outputs found
A Comparison of Pattern of Pregnancy Loss in Women with Infertility Undergoing IVF and Women with Unexplained Recurrent Miscarriages Who Conceive Spontaneously
Objective. Women with infertility and recurrent miscarriages may have an overlapping etiology. The aim of this study was to compare the pregnancy loss in pregnancies after IVF treatment with spontaneous pregnancies in women with recurrent miscarriages and to assess differences related to cause of infertility. Methods. The outcome from 1220 IVF pregnancies (Group I) was compared with 611 spontaneous pregnancies (Group II) in women with recurrent miscarriages. Subgroup analysis was performed in Group I based on cause of infertility: tubal factor (392 pregnancies); male factor (610 pregnancies); and unexplained infertility (218 pregnancies). Results. The clinical pregnancy loss rate in Group I (14.3%) was significantly lower than that of Group II (25.8%, p<0.001) and this was independent of the cause of infertility. However the timing of pregnancy loss was similar between Groups I and II. The clinical pregnancy loss rate in Group I was similar in different causes of infertility. Conclusions. The clinical pregnancy loss rate following IVF treatment is lower than that of women with unexplained recurrent miscarriages who conceived spontaneously. This difference persists whether the infertility is secondary to tubal factors, male factors, or unexplained cause
Robust Exponential Stabilization of Stochastic Delay Interval Recurrent Neural Networks with Distributed Parameters and Markovian Jumping by Using Periodically Intermittent Control
We consider a class of stochastic delay recurrent neural networks with
distributed parameters and Markovian jumping. It is assumed that the coefficients in
these neural networks belong to the interval matrices. Several sufficient conditions
ensuring robust exponential stabilization are derived by using periodically intermittent control and Lyapunov functional. The obtained results are very easy to verify
and implement, and improve the existing results. Finally, an example with numerical
simulations is given to illustrate the presented criteria
Dataset Condensation via Generative Model
Dataset condensation aims to condense a large dataset with a lot of training
samples into a small set. Previous methods usually condense the dataset into
the pixels format. However, it suffers from slow optimization speed and large
number of parameters to be optimized. When increasing image resolutions and
classes, the number of learnable parameters grows accordingly, prohibiting
condensation methods from scaling up to large datasets with diverse classes.
Moreover, the relations among condensed samples have been neglected and hence
the feature distribution of condensed samples is often not diverse. To solve
these problems, we propose to condense the dataset into another format, a
generative model. Such a novel format allows for the condensation of large
datasets because the size of the generative model remains relatively stable as
the number of classes or image resolution increases. Furthermore, an
intra-class and an inter-class loss are proposed to model the relation of
condensed samples. Intra-class loss aims to create more diverse samples for
each class by pushing each sample away from the others of the same class.
Meanwhile, inter-class loss increases the discriminability of samples by
widening the gap between the centers of different classes. Extensive
comparisons with state-of-the-art methods and our ablation studies confirm the
effectiveness of our method and its individual component. To our best
knowledge, we are the first to successfully conduct condensation on
ImageNet-1k.Comment: old work,done in 202
Proto-Tethys magmatic evolution along northern Gondwana: Insights from Late Silurian–Middle Devonian A-type magmatism, East Kunlun Orogen, Northern Tibetan Plateau, China
The East Kunlun Orogen records the geological evolutions of the Neoproterozoic – Early Paleozoic Proto-Tethyan Ocean and Late Paleozoic–Mesozoic Paleo-Tethys Ocean along northern Gondwana. However, the late-stage evolution of the Proto-Tethyan Ocean and the configuration of peri-Gondwana microcontinents during the Silurian – Devonian is under debate. Here we report new geochronological and geochemical data of A-type granites from the western Wulonggou and the eastern Gouli areas in the East Kunlun Orogen to deepen our understanding of these problems. Zircon LA-ICP-MS UPb data reveal that the Danshuigou monzogranite and Shenshuitan syenogranite from the western Wulonggou area were emplaced simultaneously at 418 ± 3 Ma, while the Niantang syenogranite from the eastern Gouli area was emplaced at 403 ± 2 Ma. All these rocks display high-K calcic-alkalic to shoshonitic and metaluminous to slight peraluminous signatures, with relatively low CaO, Al2O3, MgO and Sr, and high FeOt/MgO, Ga/Al, Zr, and Nb, indicating their A-type affinity. Their moderate whole-rock εNd(t) (−5.3 to −0.6) and zircon εHf(t) (−6.3–6.4) are different from those of depleted mantle and old basement rocks, but similar to those of the Ordovician–Silurian granitoids in the East Kunlun Orogen. These chemical signatures, together with the anhydrous, low-pressure and high-temperature characteristics of the magmas, indicate that partial melting of the Ordovician–Silurian granitoids generated these A-type granites. Regionally, these A-type granites and previously reported A-type granites in the East Kunlun Orogen compose a Late Silurian – Middle Devonian A-type granite belt. This belt, together with the regionally coeval molasse formation and mafic-ultramafic rocks, indicate a post-collisional extensional regime for the East Kunlun Orogen during the Late Silurian – Middle Devonian. Given that extensive contemporaneous post-collision-related magmatic rocks have also been revealed in the neighboring West Kunlun, Altyn, Qilian and Qinling blocks/terranes, we contend that the Neoproterozoic – Early Paleozoic Proto-Tethyan Ocean that separated these blocks/terranes from Gondwana had closed by the Late Silurian – Middle Devonian, which]resulted in the re-welding of the above blocks/terranes to northern Gondwana or Gondwana-derived microcontinents
Soluble CD40 ligand-activated human peripheral B cells as surrogated antigen presenting cells: A preliminary approach for anti-HBV immunotherapy
<p>Abstract</p> <p>Background</p> <p>We aimed to clarify whether soluble CD40 ligand (sCD40L) activated B cells may be loaded with HBcAg18-27 peptide and served as antigen-producing cells (APCs) to induce HBV-specific cytolytic T lymphocytes (CTLs).</p> <p>Results</p> <p>Human B cells could be cultured in the presence of sCD40L up to 54 days, and the proportion of B cells in the S phase increased from 0% to 8.34% in the culture. The expression of CD80, CD86, major histocompatibility complex (MHC) classes I and II molecules on the sCD40L-activated B cell was significantly increased after long-time culture. Cytometry and fluorescence microscopy showed that more than 98% sCD40L-activated B cells were loaded by the HBcAg peptide. Furthermore, the peptide-pulsed activated B cells could induce HBcAg18-27 specific CTLs.</p> <p>Conclusions</p> <p>Our results demonstrate that sCD40L-activated B cells may function as APCs and induce HBV-specific CTLs.</p
Hemodialysis or Peritoneal Dialysis, Which Is Better for Patients with Delayed Graft Function?
Background/Aims: Hemodialysis (HD) or peritoneal dialysis (PD) is an important renal replacement method in patients with delayed graft function (DGF) after kidney transplantation; however, it is not clear which dialysis modality is superior. This study determined the impact of different dialysis modalities on patients with DGF. Methods: It was a single-center, retrospective and descriptive study. We performed 673 kidney transplants from donors after cardiac death (DCD) between January 2010 and December 2016 at our center and 138 (20.5%) recipients developed DGF after transplantation. We classified the recipients into two groups according to post-transplant dialysis: DGF-HD (n=96) and DGF-PD (n=42). We analyzed the outcomes of the different dialysis modalities 30 days and 1 year post-transplantation. Results: There were no differences in baseline factors between patients with post-transplant HD (n = 96) or PD (n = 42). There were 10 patients with conversion from PD to HD during DGF. The DGF-PD patients had a higher rate of treatment failure than the DGF-HD patients (23.8% vs. 0%, p < 0.001), peritonitis (7.1% vs. 0%, p = 0.027), and longer duration of dialysis dependence (10.5 vs. 9 days, p = 0.003). There was no statistically significant difference between both groups with respect to acute rejection, hemorrhage, and patient and graft survival at 1 year. Conclusion: In renal transplant recipients with DGF, post-transplant PD led to increased treatment failure. PD did not result in rapid recovery of transplanted renal function, and had a high probability of peritonitis
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