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Abstract This study aimed to construct a novel pelvis-prostate model BPPP which consists of body mass index (BMI), prostate volume (PV), pelvic cavity index (PCI) and prostate-muscle index (PMI) to predict the immediate urinary continence after Retzius-sparing robot assisted laparoscopic radical prostatectomy (RS-RARP). The perioperative data of patients with prostate cancer who underwent RS-RARP in the department of urology of Nanjing Drum Tower Hospital from June 2018 to June 2022 were retrospectively analyzed. 280 patients were eligible for this study in total. Multivariate analysis showed that BMI, PV, PCI, PMI and NVB preservation were significantly associated with immediate urinary continence after RS-RARP. Subgroup analysis showed that patients with low BMI, low PV, high PCI and high PMI had a higher recovery rate of immediate urinary continence. The area under the curve of BPPP (BMI + PV + PCI + PMI) for predicting the immediate recovery of urinary continence after RS-RARP was 0.726. Delong test showed that the area under the curve of the combined test for predicting the immediate urinary continence after RS-RARP was better compared with single parameter (p

Abstract This paper focuses on exploring the application possibilities and optimization problems of Generative Adversarial Networks (GANs) in spatial computing to improve design efficiency and creativity and achieve a more intelligent design process. A method for icon generation is proposed, and a basic architecture for icon generation is constructed. A system with generation and optimization capabilities is constructed to meet various requirements in spatial design by introducing the concept of interactive design and the characteristics of requirement conditions. Next, the generated icons can effectively maintain diversity and innovation while meeting the conditional features by integrating multi-feature recognition modules into the discriminator and optimizing the structure of conditional features. The experiment uses publicly available icon datasets, including LLD-Icon and Icons-50. The icon shape generated by the model proposed here is more prominent, and the color of colored icons can be more finely controlled. The Inception Score (IS) values under different models are compared, and it is found that the IS value of the proposed model is 7.05, which is higher than that of other GAN models. The multi-feature icon generation model based on Auxiliary Classifier GANs performs well in presenting multiple feature representations of icons. After introducing multi-feature recognition modules into the network model, the peak error of the recognition network is only 2.000 in the initial stage, while the initial error of the ordinary GAN without multi-feature recognition modules is as high as 5.000. It indicates that the improved model effectively helps the discriminative network recognize the core information of icon images more quickly. The research results provide a reference basis for achieving more efficient and innovative interactive space design.

Abstract Following significant advances in image acquisition, synapse detection, and neuronal segmentation in connectomics, researchers have extracted an increasingly diverse set of wiring diagrams from brain tissue. Neuroscientists frequently represent these wiring diagrams as graphs with nodes corresponding to a single neuron and edges indicating synaptic connectivity. The edges can contain “colors” or “labels”, indicating excitatory versus inhibitory connections, among other things. By representing the wiring diagram as a graph, we can begin to identify motifs, the frequently occurring subgraphs that correspond to specific biological functions. Most analyses on these wiring diagrams have focused on hypothesized motifs—those we expect to find. However, one of the goals of connectomics is to identify biologically-significant motifs that we did not previously hypothesize. To identify these structures, we need large-scale subgraph enumeration to find the frequencies of all unique motifs. Exact subgraph enumeration is a computationally expensive task, particularly in the edge-dense wiring diagrams. Furthermore, most existing methods do not differentiate between types of edges which can significantly affect the function of a motif. We propose a parallel, general-purpose subgraph enumeration strategy to count motifs in the connectome. Next, we introduce a divide-and-conquer community-based subgraph enumeration strategy that allows for enumeration per brain region. Lastly, we allow for differentiation of edges by types to better reflect the underlying biological properties of the graph. We demonstrate our results on eleven connectomes and publish for future analyses extensive overviews for the 26 trillion subgraphs enumerated that required approximately 9.25 years of computation time.

Abstract SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associated with mild or moderate symptoms were already robust and included severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity was marked by upregulation of classical antiviral pathways, including those regulating IRF1 and IRF7, whereas in moderate disease, these classical antiviral signals diminished, suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.

Abstract In this study, a combination of reverse microemulsion and hydrothermal techniques were used to synthesize HA. A hydrothermal method was used to synthesize HA/TiO2/CNT nanocomposite powders. Cold and hot isostatic pressing techniques were used to fabricate tablet-shaped samples. To investigate the biocompatibility and tribo-mechanical properties of HA/TiO2 and HA/TiO2/CNTs, four samples were prepared with different percentages of CNTs, namely, HA/TiO2 (S0), HA/TiO2/CNT (S1.0), HA/TiO2/CNT (S2.0), and HA/TiO2/CNT (S3.0). The microstructure and morphology of the HA/TiO2/CNTs were characterized by transmission electron microscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Hardness test results show that S3.0 displayed the highest surface hardness (285 HV) compared to other samples. The wear rate of HA/TiO2/CNT with the highest CNT content showed a decrease compared with those of the other samples. The results from nanoindentation tests showed that Young’s modulus of the S3.0 sample was 58.1% greater than that of the S0 sample. Furthermore, the human MDA-MB-231 cell line demonstrated good binding to the surface of the samples in the in-vitro biocompatibility evaluation of the HA/TiO2/CNT composites.

Abstract The plant kingdom provides a large resource of natural products and various related enzymes are analyzed. The high catalytic activity and easy genetically modification of microbial enzymes would be beneficial for synthesis of natural products. But the identification of functional genes of target enzymes is time consuming and hampered by many contingencies. The potential to mine microbe-derived glycosyltransferases (GTs) cross the plant kingdom was assessed based on alignment and evolution of the full sequences and key motifs of target enzymes, such as Rhodiola-derived UDP-glycosyltransferase (UGT73B6) using in salidroside synthesis. The GTs from Bacillus licheniformis ZSP01 with high PSPG motif similarity were speculated to catalyze the synthesis of salidroside. The UGTBL1, which had similarity (61.4%) PSPG motif to UGT73B6, displayed efficient activity and similar regioselectivity. Highly efficient glycosylation of tyrosol (1 g/L) was obtained by using engineered E. coli harboring UGTBL1 gene, which generated 1.04 g/L salidroside and 0.99 g/L icariside D2. All glycosides were secreted into the culture medium and beneficial for downstream purification. It was the first report on the genome mining of UGTs from microorganisms cross the plant kingdom. The mining approach may have broader applications in the selection of efficient candidate for making high-value natural products.

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