“Advocate Goodness of Human Nature to Anyone Coming across”: Analysis on “Good Nature Theory” of Mencius

( Zeng Zhen-yu ) 성균관대학교 유교문화연구소 2013 儒敎文化硏究(中文版) Vol.0 No.19

孟子人性論的基本觀點爲"人性善"或"性善",業已成爲"國民常識"。在這一常識的背後,隱伏著深度的誤讀與曲解。孟子從個體生命體驗和形式邏輯層面反複證明的一個觀點爲――人性有善端。仁義禮智"四端"源自天,存諸人心爲"立命"。人性之善是與善惡相對之善,善不是絶對之善。但是,孟子從未否定"性"有惡端。人性有惡端是眞理,惡具有實質義。硏究孟子人性學說,在方法論上應當遵循"以孟釋孟"原則,在文本釋讀與思想詮釋上,應當區別"君子所性"與"性"兩個槪念。在"君子所性"層面,孟子刻意强調君子與禽獸的"幾希"之別,君子在應然意義上當以"四端"爲性,而不可以"食色"爲性;但在"性"或"人性"層面,孟子幷沒有否定"性"或"人性"有惡端, "大體"與"小體"同在於人心。盡管君子在功夫論層面不將"味"、"色"、"聲"、"臭"稱之爲性,但芸芸衆生之"性"還是蘊含"味"、"色"、"聲"、"臭"。秦漢以降,曆代學人之所以對孟子人性學說理解不一,大多在於未厘淸"君子所性"與"性"兩個槪念的區別。 Mencius’ view on human nature can be summarized as “goodness of human nature” or “goodness of nature”; however, it is seriously misread and distorted when it becomes a “common sense of all the people.” Human nature can be a good starting point - Since Mencius, it has been proven time after time from the aspects of life-experience and of formal logic. The starting points of “humanity, righteousness, propriety and wisdom” come from Heaven (tian 天),1 and are internalized in human heart. The goodness of human nature is, however, not an absolute concept but a relative one, opposite to badness. Mencius, nevertheless, had never denied bad starting points of human nature; for him, bad starting points also truly and substantially lie within human nature. When studying and analyzing Mencius’s theory of human nature, “interpreting Mencius by Mencius” should be adopted as a methodological principle. In interpreting text and thought of Mencius, the distinction between “nature” and “nature for the exemplary person” must also be stressed. On the level of the exemplary person, Mencius deliberately emphasizes “little difference” between nature of the exemplary person and that of animals. As a matter of course, the exemplary person should take “four starting points” as his nature instead of “food and sex.” On the other side, since Mencius does not deny the bad starting points from the aspect of nature or human nature, he also maintains that “the excellent parts 大体” and “the common parts 小体” co-exist within one human heart. From a view of Gongfulun 功夫论 (accomplishment of cognizing things), the exemplary person excludes “taste,” “sex,” “sounds,” and “smell” from one’s nature, but for common people, on the contrary, such bodily functions and desires are still included in their nature. Since Qin and Han dynasties, scholars presented various interpretations on Mencius’ notion of human nature, but most of them had neglected the distinction between “nature” and “nature for the exemplary person.” [Article in Chinese]

Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches

Yu, Ning,Yu, Zeng,Gu, Feng,Li, Tianrui,Tian, Xinmin,Pan, Yi Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.2

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

The Blood Oxygenation T2* Values of Resectable Esophageal Squamous Cell Carcinomas as Measured by 3T Magnetic Resonance Imaging: Association with Tumor Stage

Yu-lian Tang,Xiao-ming Zhang,Zhi-gang Yang,Yu-cheng Huang,Tian-wu Chen,Yan-li Chen,Fan Chen,Nan-lin Zeng,Rui Li,Jiani Hu 대한영상의학회 2017 Korean Journal of Radiology Vol.18 No.4

Objective: To explore the association between the blood oxygenation T2* values of resectable esophageal squamous cell carcinomas (ESCCs) and tumor stages. Materials and Methods: This study included 48 ESCC patients and 20 healthy participants who had undergone esophageal T2*-weighted imaging to obtain T2* values of the tumors and normal esophagi. ESCC patients underwent surgical resections less than one week after imaging. Statistical analyses were performed to identify the association between T2* values of ESCCs and tumor stages. Results: One-way ANOVA and Student-Newman-Keuls tests revealed that the T2* value could differentiate stage T1 ESCCs (17.7 ± 3.3 ms) from stage T2 and T3 tumors (24.6 ± 2.7 ms and 27.8 ± 5.6 ms, respectively; all ps < 0.001). Receiver operating curve (ROC) analysis showed the suitable cutoff T2* value of 21.3 ms for either differentiation. The former statistical tests demonstrated that the T2* value could not differentiate between stages T2 and T3 (24.6 ± 2.7 ms vs. 27.8 ± 5.6 ms, respectively, p > 0.05) or between N stages (N1 vs. N2 vs. N3: 24.7 ± 6.9 ms vs. 25.4 ± 4.5 ms vs. 26.8 ± 3.9 ms, respectively; all ps > 0.05). The former tests illustrated that the T2* value could differentiate anatomic stages I and II (18.8 ± 4.8 ms and 26.9 ± 5.9 ms, respectively) or stages I and III (27.3 ± 3.6 ms). ROC analysis depicted the same cutoff T2* value of 21.3 ms for either differentiation. In addition, the Student’s t test revealed that the T2* value could determine grouped T stages (T0 vs. T1–3: 17.0 ± 2.9 ms vs. 25.2 ± 6.2 ms; T0–1 vs. T2–3: 17.3 ± 3.0 ms vs. 27.1 ± 5.3 ms; and T0–2 vs. T3: 18.8 ± 4.2 ms vs. 27.8 ± 5.6 ms, all ps < 0.001). ROC analysis indicated that the T2* value could detect ESCCs (cutoff, 20 ms), and discriminate between stages T0–1 and T2–3 (cutoff, 21.3 ms) and between T0–2 and T3 (cutoff, 20.4 ms). Conclusion: The T2* value can be an additional quantitative indicator for detecting ESCC except for stage T1 cancer, and can preoperatively discriminate between some T stages and between anatomic stages of this tumor.

Excessive retinoic acid inhibit mouse embryonic palate mesenchymal cell growth through involvement of Smad signaling

Zengli Yu,Xiaozhuan Liu,Zhan Gao,Zhitao Li,Jun Yin,Yuchang Tao,Lingling Cui,Zengli Yu 한국통합생물학회 2017 Animal cells and systems Vol.21 No.1

All-trans retinoic acid (atRA), the oxidative metabolite of retinoic acid (RA), is essential for palatogenesis. Overdose RA is capable of inducing cleft palate in mice and humans. Normal embryonic palatal mesenchymal (EPM) cell growth is crucial for shelf growth. Smad signaling is involved in many biological processes. However, it is not much clear if atRA could affect Smad signaling during EPM cells growth. In this study, the timed pregnant mice with maternal administration of 100 mg/kg body weight of RA by gastric intubation were cervical dislocation executed to evaluate growth changes of palatal shelves by hematoxylin and eosin (H&E) staining. At the same time, a primary mouse EPM (MEPM) cell culture model was also established. MEPM cells were treated with atRA (0.1, 0.5, 1, 5 and 10 μM) for 24, 48 and 72 h. The results indicated that the sizes of the shelves were smaller than those in control. AtRA inhibited MEPM cell growth with both increasing concentration and increasing incubation time, especially at 72 h in vitro. Moreover, atRA significantly increased the mRNA and protein expression levels of Smad7 (P < .05), but the mRNA and protein expression levels of PCNA were reduced (P < .05). We also found atRA inhibited phosphorylation of Smad2 compared with untreated group (P < .05). However, the protein and mRNA levels of Smad2 did not change both in atRA-treated and untreated group (P > .05). We demonstrated that RA induced inhibition of MEPM cell growth that could cause cleft palate partly by down-regulation of Smad pathway.

A Comprehensive Review of Emerging Computational Methods for Gene Identification

Yu, Ning,Yu, Zeng,Li, Bing,Gu, Feng,Pan, Yi Korea Information Processing Society 2016 Journal of information processing systems Vol.12 No.1

Gene identification is at the center of genomic studies. Although the first phase of the Encyclopedia of DNA Elements (ENCODE) project has been claimed to be complete, the annotation of the functional elements is far from being so. Computational methods in gene identification continue to play important roles in this area and other relevant issues. So far, a lot of work has been performed on this area, and a plethora of computational methods and avenues have been developed. Many review papers have summarized these methods and other related work. However, most of them focus on the methodologies from a particular aspect or perspective. Different from these existing bodies of research, this paper aims to comprehensively summarize the mainstream computational methods in gene identification and tries to provide a short but concise technical reference for future studies. Moreover, this review sheds light on the emerging trends and cutting-edge techniques that are believed to be capable of leading the research on this field in the future.

Clinicopathological Features and Prognosis of Gastroenteropancreatic Neuroendocrine Tumors: Analysis from a Single-institution

Zeng, Yu-Jie,Liu, Lu,Wu, Heng,Lai, Wei,Cao, Jie-Zhi,Xu, He-Yang,Wang, Jie,Chu, Zhong-Hua Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.10

Background: The gastroenteropancreatic neuroendocrine neoplasm (GEP-NEN) is the most common type of neuroendocrine neoplasm. We summarized data in our centre to investigate the clinicopathological features, diagnostic methods, therapeutic approaches and prognosis for this neoplasm to increase knowledge of this disease in Asian populations. Method: A total of 122 patients treated at Sun Yet-san Memorial Hospital of Sun Yat-sen University between January 2000 and December 2011 were analyzed retrospectively. Results: Pancreas was the most common site of involvement (65/122, 53.3%); this disease has no special symptoms; positive rates of chromogranin A (CgA) and synaptophysin (Syn) were 81.1% and 87.7%, respectively. The positive rate of Syn had statistical difference among the three grades, but not CgA. Some 68 patients had G1 tumors, 32 G2 tumors and 22 G3 tumors, and Chi-square test showed that higher grading was correlated with worse prognosis (${\chi}^2=32.825$, P=0.0001). A total of 32 patients presented with distant metastasis, and 8 cases emerged during following up. Cox proportional hazards regression modeling showed that the tumor grade (P=0.01), lymphatic metastasis (P=0.025) and distant metastasis (P=0.031) were predictors of unfavorable prognosis. The overall 5-year survival rate was 39.6%, the 5-year survival rate of G1 was 55.7%, and the G2 and G3 were 34.2% and 0%, respectively. Conclusions: The incidence of gastroenteropancreatic neuroendocrine tumors has risen over the last 12 years. All grades of these diseases metastasize readily, and further research regarding the treatment of patients after radical surgery is needed to prolong disease-free survival.

Sensitization of Cervical Carcinoma Cells to Paclitaxel by an IPP5 Active Mutant

Zeng, Qi-Yan,Huang, Yu,Zeng, Lin-Jie,Huang, Min,Huang, Yong-Qi,Zhu, Qi-Fang Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.19

Paclitaxel is one of the best anticancer agents that has been isolated from plants, but its major disadvantage is its dose-limiting toxicity. In this study, we obtained evidence that the active mutant IPP5 ($8-60hIPP5^m$), the latest member of the inhibitory molecules for protein phosphatase 1, sensitizes human cervix carcinoma cells HeLa more efficiently to the therapeutic effects of paclitaxel. The combination of $8-60hIPP5^m$ with paclitaxel augmented anticancer effects as compared to paclitaxel alone as evidenced by reduced DNA synthesis and increased cytotoxicity in HeLa cells. Furthermore, our results revealed that $8-60hIPP5^m$ enhances paclitaxel-induced G2/M arrest and apoptosis, and augments paclitaxel-induced activation of caspases and release of cytochrome C. Evaluation of signaling pathways indicated that this synergism was in part related to downregulation of NF-${\kappa}B$ activation and serine/threonine kinase Akt pathways. We noted that $8-60hIPP5^m$ downregulated the paclitaxel-induced NF-${\kappa}B$ activation, $I{\kappa}B{\alpha}$ degradation, PI3-K activity and phosphorylation of the serine/threonine kinase Akt, a survival signal which in many instances is regulated by NF-${\kappa}B$. Together, our observations indicate that paclitaxel in combination with $8-60hIPP5^m$ may provide a therapeutic advantage for the treatment of human cervical carcinoma.

Biosorption of Methylene Blue from Aqueous Solution Using Xanthoceras sorbifolia Seed Coat Pretreated by Steam Explosion

Zeng-Yu Yao,Jian-Hua Qi 강원대학교 산림과학연구소 2016 Journal of Forest Science Vol.32 No.3

Xanthoceras sorbifolia seed coat (XSSC) is a processing residue of the bioenergy crop. This work aimed to evaluate the applicability of using the steam explosion to modify the residue for dye biosorption from aqueous solutions by using methylene blue as a model cationic dye. Equilibrium, kinetic and thermodynamic parameters for the biosorption of methylene blue on the steam-exploded XSSC (SE-XSSC) were evaluated. The kinetic data followed the pseudo-second- order model, and the rate-limiting step was the chemical adsorption. Intraparticle diffusion was one of the rate-controlling factors. The equilibrium data agreed well with the Langmuir isotherm, and the biosorption was favorable. The steam-explosion pretreatment strongly affected the biosorption in some respects. It reduced the adsorption rate constant and the initial sorption rate of the pseudo-second-order model. It enhanced the adsorption capacity of methylene blue at higher temperatures while reduced the capacity at lower ones. It changed the biosorption from an exothermic process driven by both the enthalpy and the entropy to an endothermic one driven by entropy only. It increased the surface area and decreased the pH point of zero charge of the biomass. Compared with the native XSSC, SE-XSSC is preferable to MB biosorption from warmer dye effluents.

8-60hIPP5^m-Induced G2/M Cell Cycle Arrest Involves Activation of ATM/p53/p21^cip1/waf1 Pathways and Delayed Cyclin B1 Nuclear Translocation

Zeng, Qi-Yan,Zeng, Lin-Jie,Huang, Yu,Huang, Yong-Qi,Zhu, Qi-Fang,Liao, Zhi-Hong Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.9

Protein phosphatase 1 (PP1) is a major serine/threonine phosphatase that controls gene expression and cell cycle progression. The active mutant IPP5 ($8-60hIPP5^m$), the latest member of the inhibitory molecules for PP1, has been shown to inhibit the growth of human cervix carcinoma cells (HeLa). In order to elucidate the underlying mechanisms, the present study assessed overexpression of $8-60hIPP5^m$ in HeLa cells. Flow cytometric and biochemical analyses showed that overexpression of $8-60hIPP5^m$ induced G2/M-phase arrest, which was accompanied by the upregulation of cyclin B1 and phosphorylation of G2/M-phase proteins ATM, p53, $p21^{cip1/waf1}$ and Cdc2, suggesting that $8-60hIPP5^m$ induces G2/M arrest through activation of the ATM/p53/$p21^{cip1/waf1}$/Cdc2/cyclin B1 pathways. We further showed that overexpression of $8-60hIPP5^m$ led to delayed nuclear translocation of cyclin B1. $8-60hIPP5^m$ also could translocate to the nucleus in G2/M phase and interact with $pp1{\alpha}$ and Cdc2 as demonstrated by co-precipitation assay. Taken together, our data demonstrate a novel role for $8-60hIPP5^m$ in regulation of cell cycle in HeLa cells, possibly contributing to the development of new therapeutic strategies for cervix carcinoma.

Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches

( Ning Yu ),( Zeng Yu ),( Feng Gu ),( Tianrui Li ),( Xinmin Tian ),( Yi Pan ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.2

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.