[Serological Diagnosis and Clinical Data Analysis of Neonatal Alloimmune Thrombocytopenia].

OBJECTIVE: To investigate the pathogenesis and clinical diagnosis of fetal/neonatal alloimmune thrombocytopenia (FNAIT) and analyze the laboratory test results and clinical data related to the disease, so as to provide reference for clinical treatment and improvement of prognosis. METHODS: The clinical data of six neonatal patients with FNAIT in the Neonatology Department of our hospital from March 2017 to September 2020 were retrospectively analyzed, which included laboratory diagnosis, clinical symptoms, treatment, and prognosis. RESULTS: Among six patients, two cases occurred in the first pregnancy and four cases in the second pregnancy. The platelet count of six cases were decreased at admission or during hospitalization and maternal and neonatal serum autoimmune platelet antibody tests were positive. Five cases were accompanied by different degrees of skin and facial bleeding spots or petechiae and ecchymosis, intracranial hemorrhage. Four cases were treated with immunoglobulin and/or steroid hormone therapy (one of them received cross-matched platelets transfusion), while the symptoms of the other two cases improved spontaneously. Five cases recovered and were discharged from the hospital, while one case had not recovered but the family members requested to be discharged forwardly. Four cases were hospitalized within two weeks, but two cases were hospitalized for more than two weeks due to other diseases or factors (e.g., neonatal sepsis, neonatal enteritis, congenital heart disease, neonatal asphyxia, etc.). CONCLUSION: FNAIT is characterized by decreased platelet count, with or without bleeding symptoms, and may occur in the first and following pregnancy. FNAIT can recover spontaneously or have a good prognosis after treatment. However, the complication with other diseases or factors may affect the prognosis.

Stochastic Conjugate Gradient Algorithm With Variance Reduction.

Conjugate gradient (CG) methods are a class of important methods for solving linear equations and nonlinear optimization problems. In this paper, we propose a new stochastic CG algorithm with variance reduction1 and we prove its linear convergence with the Fletcher and Reeves method for strongly convex and smooth functions. We experimentally demonstrate that the CG with variance reduction algorithm converges faster than its counterparts for four learning models, which may be convex, nonconvex or nonsmooth. In addition, its area under the curve performance on six large-scale data sets is comparable to that of the LIBLINEAR solver for the L2 -regularized L2 -loss but with a significant improvement in computational efficiency.1CGVR algorithm is available on github: https://github.com/xbjin/cgvr.

Correction to: Graphical Representation and Similarity Analysis of DNA Sequences Based on Trigonometric Functions.

In the original publication of the article, the y axis labels present in Figs. 1a and 2a are incorrect. The correct Figs. 1a and 2a are provided here.

Graphical Representation and Similarity Analysis of DNA Sequences Based on Trigonometric Functions.

In this paper, we propose two four-base related 2D curves of DNA primary sequences (termed as F-B curves) and their corresponding single-base related 2D curves (termed as A-related, G-related, T-related and C-related curves). The constructions of these graphical curves are based on the assignments of individual base to four different sinusoidal (or tangent) functions; then by connecting all these points on these four sinusoidal (tangent) functions, we can get the F-B curves; similarly, by connecting the points on each of the four sinusoidal (tangent) functions, we get the single-base related 2D curves. The proposed 2D curves are all strictly non degenerate. Then, a 8-component characteristic vector is constructed to compare similarity among DNA sequences from different species based on a normalized geometrical centers of the proposed curves. As examples, we examine similarity among the coding sequences of the first exon of beta-globin gene from eleven species, similarity of cDNA sequences of beta-globin gene from eight species, and similarity of the whole mitochondrial genomes of 18 eutherian mammals. The experimental results well demonstrate the effectiveness of the proposed method.

Hierarchical Morphology-Dependent Gas-Sensing Performances of Three-Dimensional SnO2 Nanostructures.

Hierarchical morphology-dependent gas-sensing performances have been demonstrated for three-dimensional SnO2 nanostructures. First, hierarchical SnO2 nanostructures assembled with ultrathin shuttle-shaped nanosheets have been synthesized via a facile and one-step hydrothermal approach. Due to thermal instability of hierarchical nanosheets, they are gradually shrunk into cone-shaped nanostructures and finally deduced into rod-shaped ones under a thermal treatment. Given the intrinsic advantages of three-dimensional hierarchical nanostructures, their gas-sensing properties have been further explored. The results indicate that their sensing behaviors are greatly related with their hierarchical morphologies. Among the achieved hierarchical morphologies, three-dimensional cone-shaped hierarchical SnO2 nanostructures display the highest relative response up to about 175 toward 100 ppm of acetone as an example. Furthermore, they also exhibit good sensing responses toward other typical volatile organic compounds (VOCs). Microstructured analyses suggest that these results are mainly ascribed to the formation of more active surface defects and mismatches for the cone-shaped hierarchical nanostructures during the process of thermal recrystallization. Promisingly, this surface-engineering strategy can be extended to prepare other three-dimensional metal oxide hierarchical nanostructures with good gas-sensing performances.

Porous and single-crystalline ZnO nanobelts: fabrication with annealing precursor nanobelts, and gas-sensing and optoelectronic performance.

Porous and single-crystalline ZnO nanobelts have been prepared through annealing precursors of ZnSe · 0.5N2H4 well-defined and smooth nanobelts, which have been synthesized via a simple hydrothermal method. The composition and morphology evolutions with the calcination temperatures have been investigated in detail for as-prepared precursor nanobelts, suggesting that they can be easily transformed into ZnO nanobelts by preserving their initial morphology via calcination in air. In contrast, the obtained ZnO nanobelts are densely porous, owing to the thermal decomposition and oxidization of the precursor nanobelts. More importantly, the achieved porous ZnO nanobelts are single-crystalline, different from previously reported ones. Motivated by the intrinsic properties of the porous structure and good electronic transporting ability of single crystals, their gas-sensing performance has been further explored. It is demonstrated that porous ZnO single-crystalline nanobelts exhibit high response and repeatability toward volatile organic compounds, such as ethanol and acetone, with a short response/recovery time. Furthermore, their optoelectronic behaviors indicate that they can be promisingly employed to fabricate photoelectrochemical sensors.