Association between P-Selectin Autoantibody Positive and Response to Steroid Treatment in Newly Diagnosed Immune Thrombocytopenia Patients.

OBJECTIVE: This study aimed to detect the association between P-selectin autoantibody positive and response to steroid treatment in newly diagnosed immune thrombocytopenia (ITP) patients. METHODS: The data from 105 newly diagnosed adult ITP patients administered with first-line of steroid treatment from October 2016 to May 2021 were retrospectively analyzed. Treatment responses were evaluated within 3 months after the onset of treatment. RESULTS: Among the 105 patients, 80.00% (84/105) of patients presented with platelet glycoprotein-specific antibody positive; 44.76% (47/105) patients were anti-P-selectin positive, while 35.24% (37/105) were anti-P-selectin negative. No significant difference in overall response was observed between patients who were anti-P-selectin positive and those who were anti-P-selectin negative (74.47% vs. 89.19, χ2 = 2.910, p = 0.088). But patients who were anti-P-selectin negative had significantly higher complete response rate, compared to those who were anti-P-selectin positive (72.97% vs. 48.94%, χ2 = 4,965, p = 0.026). Logistic regression analysis revealed that anti-GP IIb/IIIa positive (OR = 3.114, p = 0.010, 95% CI: 1.313-7.388) and anti-P-selectin positive (OR = 0.309, p = 0.036, 95% CI: 0.127-0.753) were two factors that could affect patients' response. CONCLUSIONS: Our study found that ITP patients with anti-GP IIb/IIIa may have a higher response to steroid treatment, but anti-P-selectin-mediated-ITP might be less responsive to steroid treatment. In adults with ITP, the presence of anti-P-selectin autoantibodies is a predictive factor for poor response to steroid treatment.

Efficient hybrid method for electromagnetic scattering from a coated object above a two-layered rough surface.

A powerful and efficient hybrid method combining the finite-element boundary-integral method with fast multipole method (FE-BI-FMM) is proposed in this paper to study the electromagnetic scattering characteristics from a coated object above a two-layered dielectric rough surface. The finite-element method (FEM) is applied to model the scattering from the coated object, and multiple interactions between the object and layered rough surface are handled by the FMM-enhanced boundary integral method (BIM). A hybrid solver is adopted to efficiently solve the FEM-BIM matrix equation. Several numerical results are presented, and the influence of several parameters of the composite model on the scattering characteristics is analyzed in detail. Both vertical and horizontal polarizations for the incident waves are considered.

Adaptive single-pixel imaging based on guided coefficients.

The existing adaptive single-pixel imaging methods suffer from a waste of sampling resources. The sampling resources are not used adequately for superior localization of significant coefficients and reconstruction. In this paper, an adaptive single-pixel imaging method via the guided coefficients in the Haar wavelet tree is proposed. The goal is to achieve high quality imaging with less sampling resources. The guided coefficients are selected from the unsampled coefficients by a proposed same-scale prediction method based on the sampled coefficients. These guided coefficients are used to localize the significant coefficients with higher resolution belonging to the sampled coefficients and the significant coefficients belonging to the guided coefficients by a proposed guided prediction method. The significant guided coefficients are then used in the composite reconstruction method to reconstruct the image. Performance analysis shows that the proposed method reduces waste of the sampling resources and localizes more significant coefficients. Simulation results demonstrate that the proposed method improves the imaging quality in terms of peak signal-to-noise ratio up to 29.7 dB for the images containing regular and chaotic textures in the noise-free environment. The sampling rate for the same imaging quality can be reduced up to 56%. Under the noisy condition, the proposed method also achieves better imaging quality at a lower sampling rate.

Expression patterns of cluster of differentiation 147 impact the prognosis of hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) has very low overall survival. According to global cancer statistics, approximately 905677 new cases were reported in 2020, with at least 830180 of them being fatal. Cluster of differentiation 147 (CD147) is a novel, transmembrane glycoprotein that is expressed in a wide variety of tumor cells and plays an important role in various stages of tumor development. Based on the reports described previously, we theorize that CD147 may be used as a novel biological indicator to predict the prognosis of HCC. To study this possibility, expression profiles of CD147 and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed, and a hazard ratio (HR) was established. AIM: To explore the pattern of CD147 expression and its applicability in the prognosis of HCC. To establish HRs and probability points for predicting the prognosis of HCC by correlating CD147 expression with clinical characteristics. To determine if CD147 can be a reliable biomarker in HCC prognosis. METHODS: The CD147 expression profile in HCC and corresponding clinical data were obtained from TCGA database. The expression patterns of CD147 were then validated by analyzing data from the GEO database. In addition, CD147 immunohistochemistry in HCC was obtained from the Human Protein Atlas. CD147 expression patterns and clinical characteristics in the prognosis of HCC were analyzed by accessing the UALCAN web resource. Accuracy, sensitivity, and specificity of the CD147 expression profile in predictive prognosis were determined by the time-dependent receiver operating characteristic (ROC) curves. Kaplan-Meier curves were plotted to estimate the HR of survival in HCC. Univariate and multivariate Cox regression proportional hazards analyses of CD147 expression levels and clinical characteristics as prognostic factors of HCC were performed. Nomograms were used to establish probability points and predict prognosis. RESULTS: Data from TCGA and GEO databases revealed that CD147 was significantly overexpressed in HCC (P = 1.624 × 10-12 and P = 1.2 × 10-5, respectively). The expression of CD147 and prognosis of HCC were significantly correlated with the clinical characteristics of HCC as per the data from the UALCAN web resource (P < 0.05). Kaplan-Meier analysis of CD147 expression in HCC revealed that the high expression groups showed poor prognosis and an HR of survival > 1 [log-rank test, P = 0.000542, HR (in high expression group): 1.856, 95% confidence interval (CI): 1.308 to 2.636]. ROC curves were plotted to analyze the 1-year, 3-year, and 5-year survival rates. The area under the ROC curve values were 0.675 (95%CI: 0.611 to 0.740), 0.623 (95%CI: 0.555 to 0.692), and 0.664 (95%CI: 0.582 to 9.745), respectively. Univariate Cox analysis of CD147 expression and clinical characteristics of HCC and multivariate Cox analysis of CD147 patterns and pathological tumor-node-metastasis stage showed significant differences (univariate Cox, P = 0.00013, HR: 1.424, 95%CI: 1.884 to 1.707 and P = 0.00066, HR: 1.376, 95%CI: 1.145 to 1.654, respectively; multivariate Cox, P = 0.00578, HR: 1.507, 95%CI: 1.126 to 2.018 and P = 0.00336, HR: 1.443, 95%CI: 1.129 to 1.844, respectively). Nomograms were plotted to establish the probability points and predict prognosis. The total points ranged from 0 to 180, and the C-index value was 0.673 (95%CI: 0.600 to 1.000, P < 0.01). CONCLUSION: Overexpression of CD147 was correlated with poor prognosis in HCC. The CD147 expression profile combined with clinical characteristics can reliably predict the prognosis of HCC. CD147 can serve as a biomarker to predict the prognosis of HCC.