Effect of a combination of infrared irradiation and magnesium sulfate wet compress on infection and healing of episiotomy incision in puerperae

Purpose: To investigate the effect of a combination of infrared irradiation and magnesium sulfate wet compress on infection and healing of episiotomy incision in puerperae during spontaneous delivery. Methods: A total of 120 puerperae who underwent lateral episiotomy in Jinan Maternity and Child Hospital Affiliated to Shandong First Medical University from January 2019 to January 2020 were used as study subjects. They were randomly assigned to group A (n = 60) and group B (n = 60). Group B received external application of anerdian, while group A was treated with infrared irradiation and magnesium sulfate wet compress, in addition to receiving the treatment given to group B. The two groups were compared with respect to perineal edema, levels of inflammatory factors, wound pain grading, degree of incision healing, incision healing time, and incidence of infection. Results: Group A patients had significantly lighter perineal edema and more pronounced pain relief than group B patients (p < 0.05). The number of puerperae with grade A healing and grade C healing in group A was significantly higher than that in group B (p < 0.05). Incision healing time and incidence of infection were lower in group A than in group B (p < 0.05). Conclusion: The combination of infrared irradiation and magnesium sulfate wet compress effectively mitigates perineal edema in puerperae, reduces pain, enhances the healing of incision, and lowers maternal infection. Thus, this combination strategy may have some merit in clinical practice

Rime length, stress, and association domains

Every regular Chinese syllable has a syllable tone (the tone we get when the syllable is read in isolation). In some Chinese languages, the tonal pattern of a multisyllabic expression is basically a concatenation of the syllable tones. In other Chinese languages, the tonal pattern of a multisyllabic expression is determined solely by the initial syllable. I call the former M -languages (represented by Mandarin) and the latter S -languages (represented by Shanghai). I argue that there is an additional difference in rime structures between the two language groups. In S-languages, all rimes are simple, i.e., there are no underlying diphthongs or codas. In M-languages, all regular rimes are heavy. I further argue that a syllable keeps its underlying tones only if it has stress. Independent metrical evidence tells us that heavy rimes may carry inherent stress. Thus, in M-languages, all regular syllables are stressed and retain their underlying tones (which may or may not undergo further changes). In contrast, in S-languages, regular rimes do not carry inherent stress; instead, only those syllables that are assigned stress by rule can keep their underlying tones and hence head a multisyllabic tonal domain.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42998/1/10831_2005_Article_BF01440582.pd

A Gaussian Process Latent Variable Model for Subspace Clustering

Effective feature representation is the key to success of machine learning applications. Recently, many feature learning models have been proposed. Among these models, the Gaussian process latent variable model (GPLVM) for nonlinear feature learning has received much attention because of its superior performance. However, most of the existing GPLVMs are mainly designed for classification and regression tasks, thus cannot be used in data clustering task. To address this issue and extend the application scope, this paper proposes a novel GPLVM for clustering (C-GPLVM). Specifically, by combining GPLVM with the subspace clustering method, our C-GPLVM can obtain more representative latent variable for clustering. Moreover, it can directly predict the new samples by introducing a back constraint in the model, thus being more suitable for big data learning tasks such as analysis of chaotic time series and so on. In the experiment, we compare it with the related GPLVMs and clustering algorithms. The experimental results show that the proposed model not only inherits the feature learning ability of GPLVM but also has superior clustering accuracy

Substrate Specificity of GSDA Revealed by Cocrystal Structures and Binding Studies

In plants, guanosine deaminase (GSDA) catalyzes the deamination of guanosine for nitrogen recycling and re-utilization. We previously solved crystal structures of GSDA from Arabidopsis thaliana (AtGSDA) and identified several novel substrates for this enzyme, but the structural basis of the enzyme activation/inhibition is poorly understood. Here, we continued to solve 8 medium-to-high resolution (1.85–2.60 Å) cocrystal structures, which involved AtGSDA and its variants bound by a few ligands, and investigated their binding modes through structural studies and thermal shift analysis. Besides the lack of a 2-amino group of these guanosine derivatives, we discovered that AtGSDA’s inactivity was due to the its inability to seclude its active site. Furthermore, the C-termini of the enzyme displayed conformational diversities under certain circumstances. The lack of functional amino groups or poor interactions/geometries of the ligands at the active sites to meet the precise binding and activation requirements for deamination both contributed to AtGSDA’s inactivity toward the ligands. Altogether, our combined structural and biochemical studies provide insight into GSDA

Binding asymmetry and conformational studies of the AtGSDA dimer

Guanosine deaminase (GSDA) is an important deaminase that converts guanosine to xanthosine, a key intermediate in nitrogen recycling in plants. We previously solved complex structures of Arabidopsis thaliana GSDA bound by various ligands and examined its catalytic mechanism. Here, we report cocrystal structures of AtGSDA bound by inactive guanosine derivatives, which bind relatively weakly to the enzyme and mostly have poor binding geometries. The two protomers display unequal binding performances, and molecular dynamics simulation identified diverse conformations during the enzyme-ligand interactions. Moreover, intersubunit, tripartite salt bridges show conformational differences between the two protomers, possibly acting as “gating” systems for substrate binding and product release. Our structural and biochemical studies provide a comprehensive understanding of the enzymatic behavior of this intriguing enzyme