The Influence of Chinese Culture–Poetry to Southeast Asian Ethnic Chinese Writers

The poet James (Teng Choon) Na characterized the unique feel of Filipino Chinese literature as traceable to its Southeast Asian roots. He discussed the hibernation of Philippine-Chinese literature, Philippine-Chinese literature under the guidance of the mass media, and new avenues for the development of Philippine-Chinese literature. He concluded with an optimistic note that Philippine-Chinese literature will flourish despite the challenges of the times

A Convenient Adomian-Pade Technique for the Nonlinear Oscillator Equation

Very recently, the convenient way to calculate the Adomian series was suggested. This paper combines this technique and the Pade approximation to develop some new iteration schemes. Then, the combined method is applied to nonlinear models and the residual functions illustrate the accuracies and conveniences

Synergistic Effects of Serum Uric Acid and Cardiometabolic Risk Factors on Early Stage Atherosclerosis: The Cardiometabolic Risk in Chinese Study

Objective: To comprehensively examine the associations of serum uric acid (SUA) with central and peripheral arterial stiffness in Chinese adults, and particularly assess the interactions between SUA and other cardiometabolic risk factors. Methods: The study included 3,772 Chinese men and women with carotid radial pulse wave velocity (crPWV), carotid femoral PWV (cfPWV), carotid artery dorsalis pedis PWV (cdPWV) and SUA measured. Results: After adjustment for age, sex, and BMI, the levels of SUA were significantly associated with increasing trend of cfPWV, crPWV and cdPWV (P for trend <0.0001). Further adjustment for heart rate (HR), blood pressure (BP) and lipids attenuated the associations with crPWV and cdPWV to be non-significant (P = 0.1, P = 0.099 respectively), but the association between SUV and cfPWV remained significant (P = 0.004). We found significant interactions between SUA and HR or BP in relation to cfPWV (P for interaction = 0.03, 0.003 respectively). The associations between SUA and cfPWV were more evident among individuals with higher HR or normal BP than those with lower HR or hypertension. Conclusions: SUA was associated with elevated aortic arterial stiffness in Chinese adults, independent of conventional cardiovascular risk factors. BP and HR might modify the deleterious effects of SUA

Hemoglobin A1c Levels and Aortic Arterial Stiffness: The Cardiometabolic Risk in Chinese (CRC) Study

Objective: The American Diabetes Association (ADA) recently published new clinical guidelines in which hemoglobin A1c (HbA1c) was recommended as a diagnostic test for diabetes. The present study was to investigate the association between HbA1c and cardiovascular risk, and compare the associations with fasting glucose and 2-hour oral glucose tolerance test (2 h OGTT). Research design and methods: The study samples are from a community-based health examination survey in central China. Carotid-to-femoral pulse wave velocity (cfPWV) and HbA1c were measured in 5,098 men and women. Results: After adjustment for age, sex, and BMI, the levels of HbA1c were significantly associated with an increasing trend of cfPWV in a dose-dependent fashion (P for trend 0.05). Conclusions: HbA1c was related to high cfPWV, independent of conventional cardiovascular risk factors. Senior age and high blood pressure might amplify the adverse effects of HbA1c on cardiovascular risk

Brain disease research based on functional magnetic resonance imaging data and machine learning: a review

Brain diseases, including neurodegenerative diseases and neuropsychiatric diseases, have long plagued the lives of the affected populations and caused a huge burden on public health. Functional magnetic resonance imaging (fMRI) is an excellent neuroimaging technology for measuring brain activity, which provides new insight for clinicians to help diagnose brain diseases. In recent years, machine learning methods have displayed superior performance in diagnosing brain diseases compared to conventional methods, attracting great attention from researchers. This paper reviews the representative research of machine learning methods in brain disease diagnosis based on fMRI data in the recent three years, focusing on the most frequent four active brain disease studies, including Alzheimer's disease/mild cognitive impairment, autism spectrum disorders, schizophrenia, and Parkinson's disease. We summarize these 55 articles from multiple perspectives, including the effect of the size of subjects, extracted features, feature selection methods, classification models, validation methods, and corresponding accuracies. Finally, we analyze these articles and introduce future research directions to provide neuroimaging scientists and researchers in the interdisciplinary fields of computing and medicine with new ideas for AI-aided brain disease diagnosis

Muon and Pion Identification at BESIII Based on Machine Learning Algorithm

BESIII is designed to study physics in the τ-charm energy region utilizing the high luminosity BEPCII. For collision physics experiments like the BESIII experiment, particle identification (PID) is one of the most important and commonly used tools for physics analysis. The effective µ/π identification performance is of great significance for most of BESIII physics analysis. However, due to the close masses of these two particles, as well as the intrinsic correlation between multiple detector information, traditional methods at BESIII is facing challenges in µ/π identification. In recent decades, machine learning (ML) techniques have been rapidly developed and have shown successful applications in HEP experiments. The PID based on ML provides powerful capability of combining more detection information from all sub-detectors with the data-driven approach. In this article, targeting at the µ/π identification problem at the BESIII experiment, we have developed a new PID algorithm based on the gradient boosted decision tree (BDT) model. Preliminary results show that the XGBoost classifier provides obviously higher discrimination power than traditional methods. In addition, based on the substantial amount of high-quality data taken by the BESIII detector, a method of evaluating and suppressing the systematical error of the ML model is also introduced, which is critical for applying the model to physics studies

Marek's disease virus-encoded miR-155 ortholog critical for the induction of lymphomas is not essential for the proliferation of transformed cell lines

MicroRNAs (miRNAs) are small noncoding RNAs with profound regulatory roles in many areas of biology, including cancer. MicroRNA 155 (miR-155), one of the extensively studied multifunctional miRNAs, is important in several human malignancies such as diffuse large B cell lymphoma and chronic lymphocytic leukemia. Moreover, miR-155 orthologs KSHV-miR-K12-11 and MDV-miR-M4, encoded by Kaposi's sarcoma-associated herpesvirus (KSHV) and Marek's disease virus (MDV), respectively, are also involved in oncogenesis. In MDV-induced T-cell lymphomas and in lymphoblastoid cell lines derived from them, MDV-miR-M4 is highly expressed. Using excellent disease models of infection in natural avian hosts, we showed previously that MDV-miR-M4 is critical for the induction of T-cell lymphomas as mutant viruses with precise deletions were significantly compromised in their oncogenicity. However, those studies did not elucidate whether continued expression of MDV-miR-M4 is essential for maintaining the transformed phenotype of tumor cells. Here using an in situ CRISPR/Cas9 editing approach, we deleted MDV-miR-M4 from the MDV-induced lymphoma-derived lymphoblastoid cell line MDCC-HP8. Precise deletion of MDV-miR-M4 was confirmed by PCR, sequencing, quantitative reverse transcription-PCR (qRT-PCR), and functional analysis. Continued proliferation of the MDV-miR-M4-deleted cell lines demonstrated that MDV-miR-M4 expression is not essential for maintaining the transformed phenotype, despite its initial critical role in the induction of lymphomas. Ability to examine the direct role of oncogenic miRNAs in situ in tumor cell lines is valuable in delineating distinct determinants and pathways associated with the induction or maintenance of transformation in cancer cells and will also contribute significantly to gaining further insights into the biology of oncogenic herpesviruses.IMPORTANCE Marek's disease virus (MDV) is an alphaherpesvirus associated with Marek's disease (MD), a highly contagious neoplastic disease of chickens. MD serves as an excellent model for studying virus-induced T-cell lymphomas in the natural chicken hosts. Among the limited set of genes associated with MD oncogenicity, MDV-miR-M4, a highly expressed viral ortholog of the oncogenic miR-155, has received extensive attention due to its direct role in the induction of lymphomas. Using a targeted CRISPR-Cas9-based gene editing approach in MDV-transformed lymphoblastoid cell lines, we show that MDV-miR-M4, despite its critical role in the induction of tumors, is not essential for maintaining the transformed phenotype and continuous proliferation. As far as we know, this was the first study in which precise editing of an oncogenic miRNA was carried out in situ in MD lymphoma-derived cell lines to demonstrate that it is not essential in maintaining the transformed phenotype