22-groups behaving as automorphism groups of regular 33-polytopes

In this paper, we classify regular polytopes with automorphism groups of order $2^n$ and Schl\"afli types $\{4, 2^{n-3}\}, \{4, 2^{n-4}\}$ and $\{4, 2^{n-5}\}$ for $n \geq 10$, therefore giving a partial answer to a problem proposed by Schulte and Weiss in [Problems on polytopes, their groups, and realizations, Periodica Math. Hungarica 53(2006) 231-255].Comment: 21 page

Improved biocompatibility of novel poly(L-lactic acid)/β-tricalcium phosphate scaffolds prepared by an organic solvent-free method

A porous poly(L-lactic acid)/β-tricalcium phosphate (PLLA/β-TCP) composite scaffold was fabricated using a novel technique comprising powder mixing, compression molding, low-temperature treatment, and particulate leaching without any organic solvent. The effect of this scaffold on osteoblast proliferation and differentiation was evaluated in vitro. The fabricated scaffold had a homogeneously interconnected porous structure with a porosity of 70% and compressive strength of 1.35 MPa. The methylthiazol tetrazolium values and alkaline phosphatase (ALP) activity of osteoblasts seeded on the solvent-free scaffold were significant higher than those of the control. Using real-time PCR, gene expressions of ALP, osteocalcin, and type 1 collagen were shown to be upregulated. As the method does not use any organic solvent, it eliminates problems associated with organic solvent residue and therefore improves the cell compatibility. It has a promising potential for the preparation of porous scaffold for bone tissue engineering

Diagnostic value of two dimensional shear wave elastography combined with texture analysis in early liver fibrosis.

BACKGROUND: Staging diagnosis of liver fibrosis is a prerequisite for timely diagnosis and therapy in patients with chronic hepatitis B. In recent years, ultrasound elastography has become an important method for clinical noninvasive assessment of liver fibrosis stage, but its diagnostic value for early liver fibrosis still needs to be further improved. In this study, the texture analysis was carried out on the basis of two dimensional shear wave elastography (2D-SWE), and the feasibility of 2D-SWE plus texture analysis in the diagnosis of early liver fibrosis was discussed. AIM: To assess the diagnostic value of 2D-SWE combined with textural analysis in liver fibrosis staging. METHODS: This study recruited 46 patients with chronic hepatitis B. Patients underwent 2D-SWE and texture analysis; Young\u27s modulus values and textural patterns were obtained, respectively. Textural pattern was analyzed with regard to contrast, correlation, angular second moment (ASM), and homogeneity. Pathological results of biopsy specimens were the gold standard; comparison and assessment of the diagnosis efficiency were conducted for 2D-SWE, texture analysis and their combination. RESULTS: 2D-SWE displayed diagnosis efficiency in early fibrosis, significant fibrosis, severe fibrosis, and early cirrhosis (AUC \u3e 0.7, P \u3c 0.05) with respective AUC values of 0.823 (0.678-0.921), 0.808 (0.662-0.911), 0.920 (0.798-0.980), and 0.855 (0.716-0.943). Contrast and homogeneity displayed independent diagnosis efficiency in liver fibrosis stage (AUC \u3e 0.7, P \u3c 0.05), whereas correlation and ASM showed limited values. AUC of contrast and homogeneity were respectively 0.906 (0.779-0.973), 0.835 (0.693-0.930), 0.807 (0.660-0.910) and 0.925 (0.805-0.983), 0.789 (0.639-0.897), 0.736 (0.582-0.858), 0.705 (0.549-0.883) and 0.798 (0.650-0.904) in four liver fibrosis stages, which exhibited equivalence to 2D-SWE in diagnostic efficiency (P \u3e 0.05). Combined diagnosis (PRE) displayed diagnostic efficiency (AUC \u3e 0.7, P \u3c 0.01) for all fibrosis stages with respective AUC of 0.952 (0.841-0.994), 0.896 (0.766-0.967), 0.978 (0.881-0.999), 0.947 (0.835-0.992). The combined diagnosis showed higher diagnosis efficiency over 2D-SWE in early liver fibrosis (P \u3c 0.05), whereas no significant differences were observed in other comparisons (P \u3e 0.05). CONCLUSION: Texture analysis was capable of diagnosing liver fibrosis stage, combined diagnosis had obvious advantages in early liver fibrosis, liver fibrosis stage might be related to the hepatic tissue hardness distribution

MicroRNA-101 Exerts Tumor-Suppressive Functions in Non-small Cell Lung Cancer through Directly Targeting Enhancer of Zeste Homolog 2

Introduction:Overexpression of the enhancer of zeste homolog 2 (EZH2) protein has been found in broad range of cancer types, including non-small cell lung cancer (NSCLC). Nevertheless, the mechanisms by which EZH2 becomes overexpressed in NSCLC remain unclear. MicroRNAs (miRNAs) can regulate target gene expression through translational control. In this study, we investigate whether miRNA (miR-101) regulates EZH2 expression in NSCLC.Methods:We evaluated the expression of miR-101 and EZH2 in 20 matched NSCLC and adjacent nontumor lung tissues by reverse-transcriptase polymerase chain reaction and immunohistochemistry, respectively. Luciferase reporter assay was used to determine whether miR-101 directly targets EZH2. To assess the effect of miR-101 on NSCLC biological behavior, cell proliferation, invasion, and response to chemotherapy were analyzed using NSCLC cells transfected with miR-101 mimics or transfected with specific small interfering RNA to deplete EZH2 (small interfering RNA-EZH2).Results:Reduced expression of miR-101 was associated with overexpression of EZH2 in NSCLC tumor tissues. Transfection of miR-101 mimics significantly suppressed the activity of the luciferase reporter containing wild type but not mutant EZH2 3′-UTR and decreased EZH2 expression in NSCLC cell lines. Furthermore, enforced expression of miR-101 or knockdown of EZH2 led to reduced NSCLC cell proliferation and invasion and sensitized cancer cells to paclitaxel-mediated apoptosis through inducing expression of the proapoptotic protein Bim.Conclusions:miR-101 inhibits cell proliferation and invasion and enhances paclitaxel-induced apoptosis in NSCLC cells, at least in part, by directly repressing EZH2 expression. Therapeutic strategies to rescue miR-101 expression or silence EZH2 may be beneficial to patients with NSCLC in the future

Privacy-Enhancing Collaborative Information Sharing through Federated Learning -- A Case of the Insurance Industry

The report demonstrates the benefits (in terms of improved claims loss modeling) of harnessing the value of Federated Learning (FL) to learn a single model across multiple insurance industry datasets without requiring the datasets themselves to be shared from one company to another. The application of FL addresses two of the most pressing concerns: limited data volume and data variety, which are caused by privacy concerns, the rarity of claim events, the lack of informative rating factors, etc.. During each round of FL, collaborators compute improvements on the model using their local private data, and these insights are combined to update a global model. Such aggregation of insights allows for an increase to the effectiveness in forecasting claims losses compared to models individually trained at each collaborator. Critically, this approach enables machine learning collaboration without the need for raw data to leave the compute infrastructure of each respective data owner. Additionally, the open-source framework, OpenFL, that is used in our experiments is designed so that it can be run using confidential computing as well as with additional algorithmic protections against leakage of information via the shared model updates. In such a way, FL is implemented as a privacy-enhancing collaborative learning technique that addresses the challenges posed by the sensitivity and privacy of data in traditional machine learning solutions. This paper's application of FL can also be expanded to other areas including fraud detection, catastrophe modeling, etc., that have a similar need to incorporate data privacy into machine learning collaborations. Our framework and empirical results provide a foundation for future collaborations among insurers, regulators, academic researchers, and InsurTech experts

Seroprevalence and Genetic Characterization of Toxoplasma Gondii in Three Species of Pet Birds in China

Background Toxoplasmosis, caused by the protozoan parasite Toxoplasma gondii, is one of the most common zoonosis worldwide, affecting a wide range of warm-blooded mammals and birds worldwide. However, no information on T. gondii infection in pet birds in China is available. Therefore, this study was performed to determine the prevalence of T. gondii infection in pet birds in Gansu province, China. Methods A total of 687 blood samples were collected from pet birds (Carduelis spinus, Alauda gulgula, Cocothraustes migratorlus) in three representative administrative regions in Gansu province, northwest China between August 2011 and September 2012 T. gondii antibodies were determined using the modified agglutination test (MAT). Genomic DNA was extracted from the brain tissues of seropositive pet birds and T. gondii B1 gene was amplified using a semi-nested PCR.DNA samples giving positive B1 amplification were then genetically characterized using multi-locus PCR-RFLP. Results The overall T. gondii seroprevalence was 11.21% (77/687). C. spinus had the highest T. gondii seroprevalence (11.65%), followed by A. arvensis (11.39%) and C. migratorlus (5.26%), these differences were not statistically significant (P \u3e 0.05). Of 77 DNA samples, 8 were positive for the T. gondii B1 gene, four showed complete genotyping results. Only one genotype (the Type II variant: ToxoDB genotype #3) was identified. Conclusions The results of the present survey indicated the presence of T. gondii infection in pet birds in Gansu province, China. These data provide base-line information for the execution of control strategies against T. gondii infection in pet birds. To our knowledge, this is the first report documenting the occurrence of T. gondii prevalence and genotype in pet birds in China

Measurement of Temperature Distribution Based on Optical Fiber-Sensing Technology and Tunable Diode Laser Absorption Spectroscopy

Temperature is an important physical quantity in most industrial processes. Distributed temperature sensor (DTS), fiber Bragg grating (FBG), and tunable diode laser absorption spectroscopy (TDLAS) are three primary techniques for temperature measurement using fiber optic sensing and spectrum technology. The DTS system can monitor space temperature field along the fiber in real time. In addition, it also can locate a fire source using two sections of optical fibers which are placed orthogonally to each other. The FBG temperature sensor is used to measure the point temperature. The temperature sensitivity of the bare FBG is 10.68 pm/°C and the linearity is 0.99954 in the range of 30–100°C. Based on tunable diode laser absorption spectroscopy (TDLAS), two-dimensional (2D) distribution reconstructions of gas temperature are realized using an algebraic reconstruction technique (ART). The results are in agreement with the simulation results, and the time resolution is less than 1 s