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Combining virtual screening with cis-/trans-cleavage enzymatic assays effectively reveals broad-spectrum inhibitors that target the main proteases of SARS-CoV-2 and MERS-CoV

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Antiviral research 2023年 216卷 105653页

作者： Yu-Jen Chang Uyen Nguyen phuong Le Jia-Jun Liu Sin-Rong Li Shao-Ting Chao Hsueh-Chou Lai Yu-Feng Lin Kai-Cheng Hsu Chih-Hao Lu Cheng-Wen Lin The Ph.D. Program of Biotechnology and Biomedical Industry China Medical University Taichung Taiwan. Department of Medical Laboratory Science and Biotechnology China Medical University Taichung Taiwan Graduate Institute of Biological Sciences and Technology China Medical University Taichung Taiwan. Graduate Institute of Biomedical Sciences China Medical University Taichung Taiwan. Department of Laboratory Medicine China Medical University Hospital Taichung Taiwan. Department of Medical Laboratory Science and Biotechnology China Medical University Taichung Taiwan. Division of Hepato-Gastroenterology Department of Internal Medicine China Medical University Hospital Taichung Taiwan. Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan. Graduate Institute of Cancer Biology and Drug Discovery Taipei Medical University Taipei Taiwan. The Ph.D. Program of Biotechnology and Biomedical Industry China Medical University Taichung Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan. Electronic address: chlu@nycu.edu.tw. Graduate Institute of Biological Sciences and Technology China Medical University Taichung Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan. Electronic address: cwlin@mail.cmu.edu.tw.

The main protease (M) of SARS-CoV-2 is essential for viral replication, which suggests that the M is a critical target in the development of small molecules to treat COVId-19. This study used an in-silico prediction approach to investigate the complex structure of SARS-CoV-2 M in compounds from the United States National Cancer Institute (NCI) database, then validate potential inhibitory compounds against the SARS-CoV-2 M in cis- and trans-cleavage proteolytic assays. Virtual screening of ∼280,000 compounds from the NCI database identified 10 compounds with highest site-moiety map scores. Compound NSC89640 (coded C1) showed marked inhibitory activity against the SARS-CoV-2 M in cis-/trans-cleavage assays. C1 strongly inhibited SARS-CoV-2 M enzymatic activity, with a half maximal inhibitory concentration (IC) of 2.69 μM and a selectivity index (SI) of >74.35. The C1 structure served as a template to identify structural analogs based on AtomPair fingerprints to refine and verify structure-function associations. M-mediated cis-/trans-cleavage assays conducted with the structural analogs revealed that compound NSC89641 (coded d2) exhibited the highest inhibitory potency against SARS-CoV-2 M enzymatic activity, with an IC of 3.05 μM and a SI of >65.57. Compounds C1 and d2 also displayed inhibitory activity against MERS-CoV-2 with an IC of <3.5 μM. Thus, C1 shows potential as an effective M inhibitor of SARS-CoV-2 and MERS-CoV. Our rigorous study framework efficiently identified lead compounds targeting the SARS-CoV-2 M and MERS-CoV M.

关键词： In-silico prediction MERS-CoV Main protease National cancer institute database SARS-CoV-2 cis-/trans-cleavage assay

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Correction to: Long noncoding RNA BCRP3 stimulates VPS34 and autophagy activities to promote protein homeostasis and cell survival

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Journal of biomedical science 2022年第1期29卷 59页

作者： Ruei Liang Yan Chiu Lin Luan Chun Chieh Liao Li Heng Liu Fei Yun Chen Hsin Yi Chen Ruey Hwa Chen Institute of Biological Chemistry Academia Sinica Taipei 115 Taiwan. Institute of Molecular Medicine College of Medicine National Taiwan University Taipei 100 Taiwan. Genome and Systems Biology Degree Program College of Life Science National Taiwan University Taipei 106 Taiwan. Graduate Institute of Cancer Biology and Drug Discovery College of Medical Science and Technology Taipei Medical University Taipei 110 Taiwan. Ph.D. Program for Cancer Molecular Biology and Drug Discovery College of Medical Science and Technology Taipei Medical University Taipei 110 Taiwan. Institute of Biological Chemistry Academia Sinica Taipei 115 Taiwan. rhchen@gate.sinica.edu.tw. Institute of Molecular Medicine College of Medicine National Taiwan University Taipei 100 Taiwan. rhchen@gate.sinica.edu.tw. Genome and Systems Biology Degree Program College of Life Science National Taiwan University Taipei 106 Taiwan. rhchen@gate.sinica.edu.tw.

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SWEET: a single-sample network inference method for deciphering individual features in disease

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Briefings in bioinformatics 2023年第2期24卷 bbad032页

作者： Hsin-Hua Chen Chun-Wei Hsueh Chia-Hwa Lee Ting-Yi Hao Tzu-Ying Tu Lan-Yun Chang Jih-Chin Lee Chun-Yu Lin Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu 300 Taiwan. School of Medical Laboratory Science and Biotechnology College of Medical Science and Technology Taipei Medical University Taipei 110 Taiwan. TMU Research Center of Cancer Translational Medicine Taipei Medical University Taipei 110 Taiwan. Ph.D. Program in Medical Biotechnology College of Medical Science and Technology Taipei Medical University Taipei Taiwan. Department of Otolaryngology-Head and Neck Surgery Tri-Service General Hospital National Defense Medical Center Taipei 110 Taiwan. Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu 300 Taiwan. Institute of Data Science and Engineering National Yang Ming Chiao Tung University Hsinchu 300 Taiwan. Center for Intelligent Drug Systems and Smart Bio-devices National Yang Ming Chiao Tung University Hsinchu 300 Taiwan. School of Dentistry Kaohsiung Medical University Kaohsiung 807 Taiwan.

Recently, extracting inherent biological system information (e.g. cellular networks) from genome-wide expression profiles for developing personalized diagnostic and therapeutic strategies has become increasingly important. However, accurately constructing single-sample networks (SINs) to capture individual characteristics and heterogeneity in disease remains challenging. Here, we propose a sample-specific-weighted correlation network (SWEET) method to model SINs by integrating the genome-wide sample-to-sample correlation (i.e. sample weights) with the differential network between perturbed and aggregate networks. For a group of samples, the genome-wide sample weights can be assessed without prior knowledge of intrinsic subpopulations to address the network edge number bias caused by sample size differences. Compared with the state-of-the-art SIN inference methods, the SWEET SINs in 16 cancers more likely fit the scale-free property, display higher overlap with the human interactomes and perform better in identifying three types of cancer-related genes. Moreover, integrating SWEET SINs with a network proximity measure facilitates characterizing individual features and therapy in diseases, such as somatic mutation, mut-driver and essential genes. Biological experiments further validated two candidate repurposable drugs, albendazole for head and neck squamous cell carcinoma (HNSCC) and lung adenocarcinoma (LUAd) and encorafenib for HNSCC. By applying SWEET, we also identified two possible LUAd subtypes that exhibit distinct clinical features and molecular mechanisms. Overall, the SWEET method complements current SIN inference and analysis methods and presents a view of biological systems at the network level to offer numerous clues for further investigation and clinical translation in network medicine and precision medicine.

关键词： drug repurposing gene expression network inference network medicine precision medicine single-sample network

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Author Correction: Multiplexed inhibition of immunosuppressive genes with Cas13d for combinatorial cancer immunotherapy

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Nature biotechnology 2025年 2025 Feb 3页

作者： Feifei Zhang Ryan d Chow Emily He Chuanpeng dong Shan Xin daniyal Mirza Yanzhi Feng Xiaolong Tian Nipun Verma Medha Majety Yueqi Zhang Guangchuan Wang Sidi Chen Department of Genetics Yale University School of Medicine New Haven CT USA. System Biology Institute Yale University West Haven CT USA. Center for Cancer Systems Biology Yale University West Haven CT USA. M.D.-Ph.D. Program Yale University West Haven CT USA. Molecular Cell Biology Genetics and Development Program Yale University New Haven CT USA. Yale College New Haven CT USA. Immunobiology Program Yale University New Haven CT USA. Department of Therapeutic Radiology Yale University School of Medicine New Haven CT USA. Department of Genetics Yale University School of Medicine New Haven CT USA. guangchuan.wang@***. System Biology Institute Yale University West Haven CT USA. guangchuan.wang@***. Center for Cancer Systems Biology Yale University West Haven CT USA. guangchuan.wang@***. Key Laboratory of Multi-Cell Systems Shanghai Institute of Biochemistry and Cell Biology Center for Excellence in Molecular Cell Science Chinese Academy of Sciences Shanghai China. guangchuan.wang@***. Department of Genetics Yale University School of Medicine New Haven CT USA. sidi.chen@yale.edu. System Biology Institute Yale University West Haven CT USA. sidi.chen@yale.edu. Center for Cancer Systems Biology Yale University West Haven CT USA. sidi.chen@yale.edu. M.D.-Ph.D. Program Yale University West Haven CT USA. sidi.chen@yale.edu. Molecular Cell Biology Genetics and Development Program Yale University New Haven CT USA. sidi.chen@yale.edu. Yale College New Haven CT USA. sidi.chen@yale.edu. Immunobiology Program Yale University New Haven CT USA. sidi.chen@yale.edu. Department of Neurosurgery Yale University School of Medicine New Haven CT USA. sidi.chen@yale.edu. Yale Comprehensive Cancer Center Yale University School of Medicine New Haven CT USA. sidi.chen@yale.edu. Yale Stem Cell Center Yale University School of Medicine New Haven CT USA. sidi.chen@yale.edu. Yale Center for Biomedical Data Science Yale University School of Medicine New Have

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Persistence and dynamic structures of diverse cephalosporinase genes in nontyphoidal Salmonella in cross-sectional surveillance in Taiwan

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International Journal of Antimicrobial Agents 2023年第4期62卷 106944-106944页

作者： Lee, Yuarn-Jang Chang, Yu-Chu Lee, I-Hui Ho, Kuo-Hao Fang, Shiuh-Bin Lauderdale, Tsai-Ling Chen, Ting-Wen Chen, Ku-Chung Huang, Chih-Hung Huang, Tzu-Wen Division of Infectious Diseases Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan Division of Infectious Diseases Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Department of Biochemistry and Molecular Cell Biology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan International Ph.D. Program for Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei Taiwan Department of Microbiology and Immunology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Graduate Institute of Medical Sciences College of Medicine Taipei Medical University Taipei Taiwan Division of Pediatric Gastroenterology and Hepatology Department of Pediatrics Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan Department of Medical Research Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan Department of Pediatrics School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Master Program in Clinical Pharmacogenomics and Pharmacoproteomics College of Pharmacy Taipei Medical University Taipei Taiwan National Institute of Infectious Diseases and Vaccinology National Health Research Institutes Zhunan Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B) National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Chemical Engineering and Biotechnology Institute of Chemical Engineering National Taipei University of Technology Taipei Taiwan

Objectives: Nontyphoidal Salmonella (NTS) is a major foodborne pathogen causing from acute gastroenteritis to bacteraemia, particularly in paediatric and elderly patients. Antimicrobial resistance of NTS, especially resistance to extended-spectrum cephalosporins, has emerged over the past decades. Methods: Thirteen NTS isolates resistant to ceftriaxone or cefotaxime were collected from a teaching hospital in Taipei, and another three from a tertiary hospital, in New Taipei City, Taiwan, from September 2018 to december 2019. Ten other archived isolates from 2000 to 2017 were also obtained. Complete genomes of the 26 isolates were obtained. Serovars, sequence types, resistomes, genetic relatedness, and sequence comparison of plasmids were analyzed. Results: Serogroups B, C2 and E were significantly associated with ampicillin resistance. Over 90% of these 26 isolates are susceptible to carbapenems and colistin. Genomic epidemiology of these isolates shows that bla_CMY-2-harbouring isolates in different serovars were prevalent over two decades, presumably resulting from highly mobile IncI1 plasmid harbouring bla_CMY-2. One type of the IncI1 plasmids contained a mobile element, IS26, which might be involved in the acquisition of antimicrobial resistance genes. Two emerging serovars, S. Goldcoast ST358 harbouring bla_CTX-M-55 on IncHI2 plasmids and S. Anatum ST64 harbouring bla_dHA-1 on IncA/C₂ plasmids persisted in Taiwan, possibly through the clonal spread. Integration of complete or partial plasmid sequences into host chromosomes or multiplications of the antimicrobial resistance genes also appears to be mediated by IS26, in the two emerging clones. Conclusion: The dynamic movement of cephalosporinase genes mediated by IS26 in NTS is of great concern. © 2023 The Authors

关键词： Amplification Chromosome integration Epidemiology Foodborne pathogen Insertion sequence Whole-genome sequencing

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Worm Perturb-Seq: massively parallel whole-animal RNAi and RNA-seq

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Nature communications 2025年第1期16卷 4785页

作者： Hefei Zhang Xuhang Li dongyuan Song Onur Yukselen Shivani Nanda Alper Kucukural Jingyi Jessica Li Manuel Garber Albertha J M Walhout Department of Systems Biology University of Massachusetts Chan Medical School Worcester MA USA. Bioinformatics Interdepartmental Ph.D. Program University of California Los Angeles CA USA. Department of Genetics and Genome Sciences University of Connecticut Health Center Farmington CT USA. Via Scientific Inc. Cambridge MA USA. Pathology Beth Israel Deaconess Medical Center Harvard Medical School Boston MA USA. Department of Genomics and Computational Biology University of Massachusetts Chan Medical School Worcester MA USA. Department of Statistics and Data Science Department of Biostatistics Department of Computational Medicine and Department of Human Genetics University of California Los Angeles CA USA. Department of Genomics and Computational Biology University of Massachusetts Chan Medical School Worcester MA USA. manuel.garber@umassmed.edu. Department of Systems Biology University of Massachusetts Chan Medical School Worcester MA USA. marian.walhout@umassmed.edu.

Transcriptomes provide highly informative molecular phenotypes that, combined with gene perturbation, can connect genotype to phenotype. An ultimate goal is to perturb every gene and measure transcriptome changes, however, this is challenging, especially in whole animals. Here, we present 'Worm Perturb-Seq (WPS)', a method that provides high-resolution RNA-sequencing profiles for hundreds of replicate perturbations at a time in living animals. WPS introduces multiple experimental advances combining strengths of Caenhorhabditis elegans genetics and multiplexed RNA-sequencing with a novel analytical framework, EmpirdE. EmpirdE leverages the unique power of large transcriptomic datasets and improves statistical rigor by using gene-specific empirical null distributions to identify dEGs. We apply WPS to 103 nuclear hormone receptors (NHRs) and find a striking 'pairwise modularity' in which pairs of NHRs regulate shared target genes. We envision the advances of WPS to be useful not only for C. elegans, but broadly for other models, including human cells.

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development and validation of a novel combinational index of liquid biopsy biomarker for longitudinal lung cancer patient management

The journal of liquid biopsy

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The journal of liquid biopsy 2024年 6卷 100167页

作者： Min-Yi Liao Yun-Jie Hao Ching-Shan Luo Ching-Mei Chen Po-Hao Feng Hsin-Yu Yang da-Jeng Yao Kang-Yun Lee Fan-Gang Tseng Department of Power Mechanical Engineering National Tsing Hua University Hsinchu 30013 Taiwan. Department of Engineering and System Science National Tsing Hua University Hsinchu 30013 Taiwan. International Ph.D. Program in Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan. Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei City 23561 Taiwan. TMU Research Center of Thoracic Medicine Taipei Medical University Taipei 11031 Taiwan. Division of Pulmonary Medicine Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan. Nano Science and Technology Program National Tsing Hua University Hsinchu 30013 Taiwan. Institute of Nano Engineering and Micro Systems (NEMS) National Tsing Hua University Hsinchu 30013 Taiwan. Graduate Institute of Clinical Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan. Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu 30013 Taiwan.

Objectives:Many cancer biomarkers such as the circulating tumor cells/microemboli (CTCs/CTM) have been reported significant associations with clinical outcomes. However, different biomarkers have different sensitivities and specificities for cancer types and cohort patients, and synergistic effects between certain biomarkers have also been observed, leading to the inaccurate, fluctuating, and even controversial results when multiple biomarkers are analyzed together. In this paper, a novel combinational index, P-score, was developed for monitoring and predicting the disease condition of lung cancer patients during follow-up visits. Materials and methods:There were totally 13 return patients with 54 blood samples involved in this study to examine the number of CTC and CTM. Information from one group of 7 patients including 27 blood samples with published clinical data was employed to develop while those from another group of 4 patients containing 14 blood samples with unpublished clinical data were used to validate the P score in prediction. Enumerations were based on immunofluorescent staining images. distributions of CTC/CTM and their frequencies in stratified patients were carefully examined and analyzed the ROC curve and AUC value to develop the P score and P score-based prediction model. Results and conclusion:We found that the predictive power of P-score was not only comparable to the traditional cancer marker, in comparison with individual CTC/CTM, more false positives could be corrected by using P-score, thereby to improve the accuracy of analysis. From our preliminary validation tests, the prognosis and disease progression monitored longitudinally by P-score were further confirmed by clinical outcome data from physicians and its sensitivity was even better than those from individual biomarkers. We believe that this novel combinational indicator could be a promising tool to interpret clinical outcomes more accurately from multiple factors, particularly useful

关键词： Circulating tumor cells/microemboli Combinational index disease monitoring and prognosis drug screening Lung cancer

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Association between high-density lipoprotein and functional outcome of ischemic stroke patients in a Taiwanese population

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Lipids in health and disease 2024年第1期23卷 275页

作者： Ting-Chun Lin Chun-Yao Huang Yu-Ling Li Hung-Yi Chiou Chaur-Jong Hu Jiann-Shing Jeng Sung-Chun Tang Lung Chan Li-Ming Lien Huey-Juan Lin Chu-Chien Lin Yi-Chen Hsieh Department of Neurosurgery Hokkaido University Sapporo Japan. Division of Cardiology and Cardiovascular Research Center Department of Internal Medicine Taipei Medical University Hospital Taipei Taiwan. Taipei Heart Institute Taipei Medical University Taipei Taiwan. Institute of Population Health Sciences National Health Research Institutes Miaoli County Taiwan. School of Public Health College of Public Health Taipei Medical University Taipei Taiwan. Department of Neurology Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan. School of Medicine College of Medicine Taipei Medical University Taipei Taiwan. Taipei Neuroscience Institute Taipei Medical University Taipei Taiwan. Department of Neurology National Taiwan University Hospital Taipei Taiwan. Department of Neurology Shin Kong Wu Ho-Su Memorial Hospital Taipei Taiwan. Department of Neurology Chi-Mei Medical Center Tainan 71004 Taiwan. Ph.D Program of Neural Regenerative Medicine College of Medical Science and Technology Taipei Medical University Taipei City Taiwan. ychsieh@tmu.edu.tw.

despite recent findings indicating a paradoxical association between high-density lipoprotein cholesterol (HdL-C) levels and cardiovascular disease (CVd) mortality, the impact of HdL-C on subsequent outcomes after ischemic stroke remains unclear. The study aims to investigate the relationships between HdL-C levels and post-stroke functional outcomes while examining the potential modifying influence of HdL-C-related single nucleotide polymorphisms identified through genome-wide association studies. This cohort study included 1,310 patients diagnosed with acute ischemic stroke (AIS), all of whom had their admission serum lipid profile and genotyping information. Participants were categorized into four groups based on gender and HdL-C level. Prognostic outcomes were assessed using a modified Rankin Scale (mRS) at 1, 3, and 12 months post-admission. Multivariate logistic regression and restricted cubic spline regression analysis were used to assess the associations between HdL-C levels and outcomes. The mean age of patients was 61.17 ± 12.08 years, and 69.31% were men. After adjusting confounders, patients with the highest HdL-C level group had a significantly higher risk of poor functional outcomes at 1, 3, and 12 months following stroke compared to the reference group. Restricted cubic splines depicted a nonlinear association between HdL-C levels and poor prognosis in both men and women. The ABCA1 gene rs2575876 AA genotype combined with abnormal HdL-C levels exhibited a significantly heightened risk of post-stroke adverse outcomes at 1 and 3 months compared to patients with normal HdL-C levels and GG + GA genotype. These findings suggest that the combined effects of ABCA1 genetic variants with either low or high HdL-C levels could further heighten this risk.

关键词： ABCA1 Cholesterol Epidemiology Prognosis Restricted cubic spline regression

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Learner Characteristics as Consequences of Active Learning

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Journal of physics: Conference Series 2019年第1期1340卷

作者： Jiratchaya phala Suthida Chamrat Ph.D student Doctor of Philosophy Program in Education (Science education) Faculty of Education Chiang Mai university Department of Curriculum Instruction and Learning Faculty of Education Chiang Mai University

This paper aims to explore the consequences of active learning implementation toward students' characteristics. Literature reviewing, and synthesizing intend to delineate the framework of active learning driven classroom where teachers lessen their own profile from lecturers into facilitators. By deploying active learning, students' multiple skills are activated and practiced. These skills, gradually, become students' characteristics. Reviewing and synthesizing from the existing literature and research reports indicate students' characteristics as possible outcomes of active learning in 12 traits: 1) students have a great opportunity to first-hand experience; 2) students create learning process and construct knowledge by themselves; 3) students learn and reflect from their experiences; 4) students develop higher order thinking; 5) students develop their learning skills; 6) students play important roles in learning which are also varied and diverse; 7) students highly participate in learning process; 8) students reach academic achievements with meaningful learning; 9) students build rapport with teachers and their peers; 10) students integrate information with their prior knowledge; 11) students develop positive attitudes and self-esteem; 12) students are enthusiastic, active, happy and joyful.

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The Nature of science Views among Intern General science Pre-Service Teachers

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Journal of physics: Conference Series 2019年第1期1340卷

作者： Somsak Gathong Suthida Chamrat Ph.D student Doctor of Philosophy Program in Education (Science education) Faculty of Education Chiang Mai University Department of Curriculum Instruction and Learning Faculty of Education Chiang Mai University

This research aimed to study the nature of science views of 23 students who are currently intern general science pre-service teachers in one of Rajabhat Universities in the North. The research instrument used in the study was: the nature view of science questionnaire developed by Haidar (1999) and the researcher has improved it in accordance with the curriculum of science and education in Thailand. The nature of science views had three aspects totally 27 items. There were 8 items for scientific world view, 4 items for the scientific knowledge inquiry, 6 items for scientific enterprise and they were totally 18 items and open-ended question on the nature of science views with three aspects of science in the world: 3 items for scientific world view, 3 items for scientific inquiry and 3 items for scientific enterprise. They were totally 9 items. Then the data were analyzed by grouping the answers and finding the percentage. The results of the research revealed that intern general science pre-service teachers had the same view of the nature of science that was consistent with 3 aspects of the traditional view. That were the 2nd aspect; scientific inquiry. The 1st aspect; scientific found that 91.30 %better understood consistent with the traditional view that working of a scientist must be based on a scientific method that has a definite sequence of steps. As the 2nd aspect; the scientific knowledge creation found that 78.26% had the consistency of understanding with the traditional concept. It stated that scientific knowledge is created by observation, survey or experiment. The 3rd aspect; evidence and imagination, and creative thinking, it affects the scientific knowledge creation. It showed that 73.91% had an understanding that is consistent with the traditional concept that scientists acquire scientific knowledge using only evidence-based. The findings indicated that intern general science pre-service teachers still have many points of view. The most necessary thing i

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