Myeloproliferative neoplasms(MPN)are a group of malignant myeloid tumors caused by hematopoietic stem cell proliferation.The discovery of gene mutations has elucidated the pathogenesis of MPN and provided molecular diagnostic criteria for MPN.Recent studies have shown that there are cytokine disorders in MPN patients,and the changes in the microenvironment caused by these cytokine disorders may have great significance for the pathophysiology and pathogenesis of MPN,which may lead to corresponding clinical symptoms and different prognosis in patients.In this review,the latest research progress on the role and status of cytokines in MPN will be summarized.

Five cadinane-type sesquiterpenoids were isolated from the n-hexane extract of Commiphora myrrha by using various chromatographic techniques, including silica gel, ODS and semi-preparative HPLC. Their structures were identified by physicochemical properties and spectroscopic data. These compounds were defined as (3S,4R)-3,9-dimethoxymyrrhone (1), 9-methoxymyrrhone (2), myrrhone (3), commiterpene B (4) and comosone Ⅱ (5). Compound 1 is a new compound, of which the absolute configuration was established by single crystal X-ray crystallographic analysis. Compound 5 is firstly isolated from the Commiphora genus.

The diagnosis of sleep apnea syndrome (SAS) has a significant importance in clinic for preventing diseases of hypertention, coronary heart disease, arrhythmia and cerebrovascular disorder, etc. This study presents a novel method for SAS detection based on single-channel electrocardiogram (ECG) signal. The method preprocessed ECG and detected QRS waves to get RR signal and ECG-derived respiratory (EDR) signal. Then 40 time- and spectral-domain features were extracted to normalize the signals. After that support vector machine (SVM) was used to classify the signals as "apnea" or "normal". Finally, the performance of the method was evaluated by the MIT-BIH Apnea-ECG database, and an accuracy of 95% in train sets and an accuracy of 88% in test sets were achieved.
Algorithms ; Electrocardiography ; methods ; Humans ; Signal Processing, Computer-Assisted ; Sleep Apnea Syndromes ; diagnosis ; Support Vector Machine