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Background: Thymic carcinoma (TC) is a rare malignant tumor that can have a poor prognosis, and accurate prognostication prediction remains difficult. We aimed to develop a nomogram to predict overall survival (OS) and cancer-specific survival (CSS) based on a large cohort of patients.Methods: The Surveillance Epidemiology and End Results (SEER) database was searched to identify TC patients (1975–2016). Univariate and multivariable Cox regression analyses were used to identify predictors of OS and CSS, which were used to construct nomograms. The nomograms were evaluated using the concordance index (C-index), calibration curve, receiver operating characteristic curve, and decision curve analysis (DCA). Subgroup analysis was performed to identify high-risk patients.Results: The analysis identified six predictors of OS (Masaoka stage, surgical method, lymph node metastasis, liver metastasis, bone metastasis, and radiotherapy) and five predictors of CSS (Masaoka stage, surgical method, lymph node metastasis, tumor size, and brain metastasis), which were used to create nomograms for predicting three-year and five-year OS and CSS. The nomograms had reasonable C-index values (OS: 0.687 [training] and 0.674 [validation], CSS: 0.712 [training] and 0.739 [validation]). The DCA curve revealed that the nomograms were better for predicting OS and CSS, relative to the Masaoka staging system.Conclusion: We developed nomograms using eight clinicopathological factors that predicted OS and CSS among TC patients. The nomograms performed better than the traditional Masaoka staging system and could identify high-risk patients. Based on the nomograms’ performance, we believe they will be useful prognostication tools for TC patients.

Lung cancer has become the second most commonly diagnosed type of cancer after female breast cancer but remains the leading cause of cancer deaths [1].

To decrease the computational complexity and improve the performance of channel estimation for underwater acoustic (UWA) sparse multipath channels, a sparse least square (SLS) channel estimation algorithm is proposed. The proposed algorithm combines advantages of both generalized akaike information criterion (GAIC) estimation and estimation using effective order of channel impulse response (CIR). Known pilot data is used to estimate effective order of CIR and then the position of taps of CIR is estimated. In order to adapt to the environment with low SNR and reduce the dimension of signal space, adaptive threshold is also used. Simulation results indicate that the proposed method has good performance of channel estimation and low complexity.

Common joint synchronization of timing and frequency algorithms based on training symbols are analyzed. Training symbols are discussed and then a new algorithm based on training symbol with special structure is proposed and applied in SC-FDE (Single Carrier Frequency Domain Equalization) systems. The proposed algorithm absorbs the advantages of the common algorithms and comparison between different algorithms shows that the proposed algorithm achieves better performance.

The commercially available diphosphane ligand MeO-BIPHEP was first investigated in the palladium-catalyzed Sonogashira reaction in the absence of copper and amine. The coupling of various aryl bromides and aryl chlorides with phenylacetylene gave moderate to excellent yields.

Objectives: To construct a simplified prognostic risk model to predict overall survival after adjuvant radiotherapy for parotid gland carcinoma patients with stage T1-4aN1-3M0.Materials and Methods: We evaluated 879 patients who were pathological diagnosed as stage T1-4aN1-3M0 parotid gland cancer. Those eligible patients treated with parotidectomy and neck lymph node dissection between 2004 and 2015 in the Surveillance Epidemiology and End Results database. All cases received adjuvant radiotherapy. Independent prognostic factors included in the original model were identified by Cox regression analysis. The primary endpoint was overall survival. The model’s prediction power was evaluated by the concordance index. The entire cohort was categorized into new low- and high-risk groups using X-tile software according to the results of prognostic model. Kaplan-Meier method was used to depict the survival curves. And the statistical significance was determined by log-rank test. Besides, a heat map was visually described the association between the survival time and 2 most significant prognostic factors.Results: In the univariable and multivariate analyses, 4 independent factors for overall survival were age, tumor size, pTNM stage, and the number of positive lymph nodes, which were all selected in the parsimonious prognostic model. The concordance indices of the prognostic model and pTNM stage were 0.652 and 0.565, respectively. Patients in the low-risk group had better overall survival over patients in the high-risk group [unadjusted hazard ratio =  2.578, 95% confidence interval 2.095-3.172, P< 0.001]. The results of the heat map revealed that patients with smaller tumor size and fewer positive lymph nodes had much longer survival time.Conclusions: This parsimonious prognostic model could estimate the long-term survival after adjuvant radiotherapy for parotid gland carcinoma with stage T1-4aN1-3N0M0. The tools may be valuable to guide multidisciplinary team in making treatment decisions.

Aryl bromides are more suitable than the chlorides.

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