Medium to long term follow-up of survival and quality of life in patients with primary tumors of the cervical spine: Experience From a large single center

ObjectivesTo evaluate the survival and medium to long term health-related quality of life (HRQoL) of patients with primary cervical spinal tumors in a cross-sectional study and to identify any significant associations with demographic or clinical characteristics.MethodsPatients diagnosed with primary cervical spinal tumors were retrospectively enrolled and their clinical, radiologic, and follow-up data (specifically the EQ-5D questionnaire) were collected. Univariate and multivariate Cox time-dependent regression analyses were performed to examine the significance of certain variables on overall survival. Univariate and multivariate logistic regression analyses were conducted to identify variables significant for overall HRQoL and each dimension of the EQ-5D.ResultsA total of 341 patients were enrolled in the study with a mean follow-up of 70 months. The diagnosis was benign in 246 cases, malignant in 84, and unconfirmed in 11. The 5-year overall survival rate was 86% and the 10-year overall survival rate was 65%. Multivariate analysis suggested that surgical treatment (P = 0.002, hazard ratio [HR] = 0.431, 95% CI. [0.254, 0.729]), benign and malignant tumors [P < 0.001, HR = 2.788, 95% CI. (1.721, 4.516)], tumor and surrounding normal tissue boundary [P = 0.010, HR = 1.950, 95% CI. (1.171, 3.249)], and spinal instability [P = 0.031, HR = 1.731, 95% CI. (1.051, 2.851)] still had significant effects on survival.ConclusionsIn this cross-sectional study, we evaluated the survival period and medium and long-term health-related quality of life of patients with primary tumors of the cervical spine, and analyzed the significant related factors of tumor clinical characteristics. Surgery, myelopathy, malignancy, spinal pain relieved by lying down or supine position, and tumor infiltration on MRI were significant predictors for overall survival. Enneking stage and age were significant predictors for HRQoL

A Bi-Functional Anti-Thrombosis Protein Containing Both Direct-Acting Fibrin(ogen)olytic and Plasminogen-Activating Activities

Direct-acting fibrin(ogen)olytic agents such as plasmin have been proved to contain effective and safety thrombolytic potential. Unfortunately, plasmin is ineffective when administered by the intravenous route because it was neutralized by plasma antiplasmin. Direct-acting fibrin(ogen)olytic agents with resistance against antiplasmin will brighten the prospect of anti-thrombosis. As reported in ‘Compendium of Materia Medica’, the insect of Eupolyphaga sinensis Walker has been used as traditional anti-thrombosis medicine without bleeding risk for several hundreds years. Currently, we have identified a fibrin(ogen)olytic protein (Eupolytin1) containing both fibrin(ogen)olytic and plasminogen-activating (PA) activities from the beetle, E. sinensis. Objectives: To investigate the role of native and recombinant eupolytin1 in fibrin(ogen)olytic and plasminogen-activating processes. Methods and Results: Using thrombus animal model, eupolytin1 was proved to contain strong and rapid thrombolytic ability and safety in vivo, which are better than that of urokinase. Most importantly, no bleeding complications were appeared even the intravenous dose up to 0.12 µmol/kg body weight (3 times of tested dose which could completely lyse experimental thrombi) in rabbits. It is the first report of thrombolytic agents containing both direct-acting fibrin(ogen)olytic and plasminogen-activating activities. Conclusions: The study identified novel thrombolytic agent with prospecting clinical potential because of its bi-functional merits containing both plasmin- and PA-like activities and unique pharmacological kinetics in vivo

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

Optimisation Analysis of Structural Parameters of an Annular Slot Ejector Based on the Coanda Effect

To investigate the effect of structural parameters on the performance of an annular slot ejector, a series of numerical simulations were conducted with single-factor analysis. Moreover, a multifactor grey relational analysis was applied to examine the correlations between the structural parameters and entrainment ratio. Subsequently, the optimised model was verified by comparing the simulated results with experimental data. Results show that the performance of the optimised ejector model was improved. The RNG k-ε turbulent transport mode can simulate the internal field characteristics of an annular slot ejector, and the corresponding simulated results, as verified by experiment, satisfy engineering requirements. In addition, a quantitative correlation between structural parameters and entrainment ratio was obtained as follows: e (nozzle clearance) > θ (diffusing chamber angle) > HL (mixing chamber length) > d (throat diameter) > KL (diffusing chamber length). This work may provide a certain guiding significance for the design and application of annular slot ejectors

Research on simulation technology of surface air leakage of shallow-buried goaf based on network calculatio

In order to analyze influence of surface air leakage of shallow-buried coal seam on mine ventilation system and goaf flow field, a coupling model of shallow-buried goaf flow field and roadway ventilation network under surface air leakage was established. According to feature of many branches in goaf network, a LDLT decomposition method was put forward to improve ventilation network calculation performance of Newton method. Taking surface air leakage of 15207 goaf of Hongliulin Coal Mine as an example, affection of large-scale surface air leakage on ventilation system and goaf flow field under different surface air leakage were simulated, and conclusions were gotten such as unnormal distribution of spontaneous combustion 'three zones' in goaf caused by surface air leakage and surface air leakage should not exceed 5 m3/s, which provided technical support for safety mining of working face

Dataset analysis on Cu9S5 material structure and its electrochemical behavior as anode for sodium-ion batteries

The data presented in this data article are related to the research article entitled “Facile Synthetic Strategy to Uniform Cu9S5 Embedded into Carbon: A Novel Anode for Sodium-Ion Batteries” (Jing et al., 2018) [1]. The related experiment details of pure Cu9S5 has been stated. The structure data of pure Cu9S5 and the electrochemical performance for sodium-ion batteries are described