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A modified diffusion synthetic acceleration method is proposed to speed up the convergence process of TD-RTE calculation by employing the finite element method, combined with OpenMP parallel technology to further enhance the computational efficiency. In addition, the sequential quadratic programming algorithm is applied with Gaussian Markov random field (GGMRF) regularization to reconstruct the absorption and scattering parameter fields simultaneously. The accuracy and efficiency of the proposed model are investigated. It was observed that the modified DSA model is more efficient with the increase of the optical thickness, where the acceleration ratio is improved to 6 for the optical thicker media. In addition, similar acceleration effect was witnessed for both scattering dominated and non-scattering dominated media. Furthermore, by employing the modified DSA model into the reconstruction, it is interesting to remark that not only the reconstruction time is significantly reduced with the acceleration ratio of 8–11, but also the reconstructed image is further improved. All the results indicate that the developed scheme is efficient and robust based on TD-RTE, showing great potential in optical imaging. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study is to validate the efficacy and reliability of two predictive models for postoperative fever after retrograde intrarenal surgery (RIRS) in pediatric patients Materials and Methods: A total of 124 children who were treated with RIRS between August 2014 and August 2020 in our center were included. All the predictors were obtained by preoperative routine examinations. Receiver operative curve (ROC) and area under curve (AUC) were showed to compare the predictive power of the two models. Results: One hundred twenty-four children included of 94 boys and 30 girls, with median ages of 2.1 (1.3, 7.0) years and median body mass index of 17.3 (15.6, 20.6) kg/m2. The total points of the two nomograms were 81.0 (67.3, 90.3) and 45.5 (20.4, 94.0). Eventually, 21 children (16.9%) suffered from postoperative fever. With the exception of C-reactive protein values (25.0 mg/L vs 5.0 mg/L, p = 0.015), irrigation volumes (800 mL vs 500 mL, p = 0.01), and total points of the two predictive models (Nomogram 1: 88.0 vs 76.0, p < 0.001; Nomogram 2: 76.0 vs 39.0, p = 0.016), there was no statistical difference detected between the fever and nonfever groups. ROCs showed that Nomogram 1 presented with better predictive accuracy and efficacy with excellent AUC values of 0.805 in comparison with Nomogram 2 (0.805 vs 0.664, p = 0.025). Conclusion: We reported a sample of 124 children undergoing RIRS with a final stone-free rate of 87.1%. Twenty-one pediatric patients (16.9%) suffered from postoperative fever. Nomogram 1 presented with better predictive power for postoperative fever after RIRS in pediatric patients. [ABSTRACT FROM AUTHOR]

Two inverse models, namely as single and double-layer inverse models, are developed on the basis of a light scattering measurement technique to determine the spectral complex refractive indices of microalgae from the total hemispherical reflectance and transmittance measured in-situ. Combined with the Mie theory, a direct problem is solved by the finite volume method with the forward simulation of radiative transfer equation under the incidence of a collimated laser. An inverse problem is solved by an improved Quantum-behaved Particle Swarm Optimization (IQPSO) algorithm. The IQPSO algorithm shows a faster convergence speed and a higher accuracy within a smaller number of generations in retrieving the spectral complex refractive indices than the standard Particle Swarm Optimization (PSO) algorithm and the QPSO algorithm. The spectral complex refractive indices of Chlamydomonas reinhardtii at different wavelengths are estimated on the basis of the IQPSO algorithm with the single-layer inverse model. The influence of measurement errors on the inverse results is also investigated. Results indicate that IQPSO is a potential and effective optimal algorithm to estimate the spectral complex refractive indices of microalgae. The estimated results of the imaginary part of the refractive indices demonstrate a higher accuracy than those of the real part, especially with noisy measurement data. To improve the accuracy of single-layer estimated results, a double-layer inverse model is proposed. The investigation reveals that the double-layer inverse model can obtain more accurate results than the single-layer inverse model, especially with random measurement errors, which is more important for directing the experiment of retrieving optical refractive index of microalgae in the further research. [ABSTRACT FROM AUTHOR]

Objective: Increasing evidence suggests that gut microbiota is involved in the occurrence and progression of urinary system diseases such as clear cell renal cell carcinoma (ccRCC). However, the mechanism of how alteration of gut metagenome promotes ccRCC remains unclear. Here we aim to elucidate the association of specific gut bacteria and their metabolites with ccRCC., Methods: In a pilot case-control study among 30 ccRCC patients (RCC group) and 30 healthy controls (Control group), 16S ribosomal RNA (rRNA) gene sequencing were analyzed from fecal samples collected prior to surgery or hospitalization. Alpha diversity and beta diversity analysis of the gut microbiota were performed, and differential taxa were identified by multivariate statistics. Meanwhile, serum metabolism was measured by UHPLC-MS, and differential genes were identified based on the TCGA database., Results: Alpha diversity found there were no significant microbial diversity differences of gut microbiota between the RCC group and the Control group. However, beta diversity analysis showed that the overall structures of the two groups were significantly separated ( p = 0.008). Random Forests revealed the relative abundances of 20 species differed significantly between the RCC group and the Control group, among which nine species were enriched in the RCC group such as Desulfovibrionaceae , and 11 species were less abundant such as four kinds of Lactobacillus . Concomitantly, serum level of taurine, which was considered to be consumed by Desulfovibrionaceae and released by Lactobacillus , has decreased in the RCC group. In addition, macrophage-related genes such as Gabbr1 was upregulated in ccRCC patients., Conclusion: Reduction of protective bacteria, proliferation of sulfide-degrading bacteria Desulfovibrionaceae , reduction of taurine, and enrichment of macrophage related genes might be the risk predictors of ccRCC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yang, Zhao, Li, Zhao, Lv, Shi, Li, Zhou, Wang and Song.)

Background: Ferroptosis-related genes (FRGs) play vital roles in survival and prognosis of prostate cancer (PCa) patients. We establish a ferroptosis-related prediction model through bioinformatics analysis for overall survival (OS) and disease-free survival (DFS), so as to evaluate the clinical survival status through the characteristics of immune cell infiltration (ICI), which could provide information for treatment monitoring., Methods: At first, 268 FRGs were obtained from previous studies. Differentially expressed FRGs were identified based on The Cancer Genome Atlas (TCGA) database, and FRG enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We then performed univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to establish OS- and DFS-related prognostic prediction models. The association of the model and clinicopathological features was further analyzed. Subsequently, unique genomic signatures of immune cell subsets were obtained through the KEGG database. Based on specific genes associated with ferroptosis and their association with ICI, immune infiltration was assessed in patients in different risk groups., Results: We constructed an OS- and an DFS-prognostic model through bioinformatics analysis. The predicted values of OS and DFS-related models were higher in T3-4 than in T1-2 (P=0.0057, P<0.001), and the predicted value of the DFS model in N0 stage was higher than that in N1 stage (P=0.0136). Results of Single-sample gene set enrichment analysis (ssGSEA) on the basis of the KEGG dataset showed p53 signaling being the most enriched signal in the high-risk group, while endocytosis was the most enriched signal in the low-risk group. M2 macrophages (P=0.007) and neutrophils (P=0.024) were enriched in the high-risk group, and CD4-activated memory T cells were significantly accumulated in the low-risk group (P=0.017)., Conclusions: The OS- and DFS-related model based on FRGs and ICI create new insights into the disease state assessment of PCa patients., which may aid in the development of individualized and precise treatment in the future., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-22-454/coif). The authors have no conflicts of interest to declare., (2022 Translational Andrology and Urology. All rights reserved.)

A two-dimensional optical parameter mapping based on the time-domain radiative transfer equation (TD-RTE) is studied in this work. The finite element method with structured and unstructured grids is employed to solve TD-RTE and OpenMP parallel technology is employed to improve the computing efficiency. The sequential quadratic programming algorithm is used as a powerful optimization method to reconstruct absorption and scattering parameter fields and the maximum a posteriori estimation is employed by introducing the regularization term into the objective function to improve the ill-posed inverse problem. In addition, the effects of measurement errors on reconstruction accuracy are investigated thoroughly. All the simulation results demonstrate that the reconstructed scheme we developed is accurate and efficient in optical parameter mapping based on TD-RTE.

The current study evaluated the effects of Xiao Yao San (XYS) on anxiety-like behaviors and sought to determine whether the c-Jun N-terminal kinase (JNK) signaling pathway is involved. A total of 40 rats were divided into 5 groups (n=8): the control group (deionized water, per os (p.o.)), the model group (deionized water, p.o.), the SP600125 group (surgery), the per se group (surgery), and the XYS group (3.9 g/kg/d, p.o.). A 1% dimethyl sulfoxide (DMSO) citrate buffer solution (2 µL/ventricle/d) and SP600125 (10 µg/ventricle, 2 µL/ventricle/d) were separately and bilaterally injected into the rats of the two surgery groups via the ventricular system of the brain. All but the control group underwent 14 d of chronic immobilization stress (CIS; 3 h/d). On day 15, the body weights of all of the rats were measured; additionally, the rats were subjected to the elevated plus maze (EPM) and novelty suppressed feeding (NSF) tests. Finally, JNK signaling pathway indices, including phosphorylated JNK (P-JNK), JNK, phosphorylated c-Jun (P-c-Jun) and cytochrome C (Cyt-C), were examined. After modeling, the body weight and behavioral analyses of the model rats indicated that this modeling method induced anxiety-like behaviors. P-JNK, JNK, and P-c-Jun were altered in the hippocampus of the model rats. After 14 d of treatment with XYS and SP600125, rat body weight and behaviors as well as P-JNK, JNK, and P-c-Jun had changed. However, no significant difference in Cyt-C was found. XYS improves the anxiety-like behaviors induced by CIS, which might be related to the JNK signaling pathway in the hippocampus.