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Binding Interaction Activities Powered by Desmos

JOURNAL OF CHEMICAL EDUCATION 2023年第5期100卷 2027-2032页

作者： Russell, Paige M. Potratz, Jeffrey P. Concordia Univ Wisconsin Dept Phys Sci Mequon WI 53097 USA

Three computer-based activities focusing on fundamentals of binding interactions are described that are powered by Desmos, freely available web-based software. The software allows the instructor to monitor the progress of each student completing the activity by privately viewing their answers in real time, to enforce class pacing by modulating which parts of the activity are available at certain times, to acquire the full attention of the class for vital teaching moments by pausing the activity at will, and to promote learning by seamlessly graphing and fitting nonlinear data. Students learn that binding interactions are governed by kinetics and energetics which dictate affinities and binding curves. A generic binding interaction is used to derive an equation describing a hyperbolic-binding curve, and given binding curves are used to identify Kd values and relate them to relative affinities. This leads into a case study using myoglobin and oxygen where given binding curves are used to identify P50 values and relative values are justified via the energetics of the particular binding site. Last, students use nonlinear regression to fit imported binding data to the derived equation to construct a binding curve and determine the P50 affinity value. Students report acclimating to the Desmos environment quickly and an increased understanding of the relationship between Kd and binding affinity. After the activities, students are prepared for a lab analyzing hyperbolic binding and discussions on allosteric binding and sigmoidal curves. Ultimately, steps are laid out for instructors to try using Desmos, and thoroughly developed and assessed activities involving graphical biochemistry content are provided for use.

关键词： Upper-Division Undergraduate Biochemistry computer-based learning Web-based learning Discovery learning Molecular Recognition Noncovalent Interactions

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Interactive Python Notebook Modules for Chemoinformatics in Medicinal Chemistry

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JOURNAL OF CHEMICAL EDUCATION 2023年第12期100卷 4895-4902页

作者： Mahjour, Babak Mcgrath, Andrew Outlaw, Andrew Zhao, Ruheng Zhang, Charles Cernak, Tim Univ Michigan Coll Pharm Dept Med Chem Ann Arbor MI 48109 USA Univ Michigan Dept Chem Ann Arbor MI 48109 USA

Data science is becoming a mainstay in research. Despite this, very few STEM graduates matriculate with basic formal training in programming. The current lesson plan was developed to introduce undergraduates studying chemistry or biology to chemoinformatics and data science in medicinal chemistry. The objective of this lesson plan is to introduce students to common techniques used in analyzing medicinal chemistry data sets, such as visualizing chemical space, filtering to molecules that observe the Lipinski rules of drug-likeness, and principal component analysis. The content provided in this lesson plan is intended to serve as a tutorial-based reference for aspiring researchers. The lesson plan is split into two three-hour class sessions, each with an introductory slide deck, Python notebook consisting of several modules, and lab report template. During this activity, students learned to parse medicinal chemistry data sets with Python, perform simple machine learning analyses, and develop interactive graphs. During each session, students complete the Python notebook protocol and fill out a lab report template after a short lecture. By the end of the lesson plan, students were able to generate and manipulate various plots of chemical space and they reported having increased confidence in their understanding of chemistry, Python, and data science.

关键词： Upper-Division Undergraduate Python Chemoinformatics computer-based learning Medicinal Chemistry

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Practical Computational Chemistry Course for a Comprehensive Understanding of Organic, Inorganic, and Physical Chemistry: From Molecular Interactions to Chemical Reactions br

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JOURNAL OF CHEMICAL EDUCATION 2023年第2期100卷 647-654页

作者： Kuroki, Nahoko Mochizuki, Yuji Mori, Hirotoshi Chuo Univ Fac Sci & Engn Dept Appl Chem Tokyo 1128551 Japan Rikkyo Univ Fac Sci Res Ctr Smart Mol Tokyo 1718501 Japan Rikkyo Univ Dept Chem Tokyo 1718501 Japan Univ Tokyo Inst Ind Sci Tokyo 1538505 Japan

In all fields of chemistry, it has become essential to use quantum chemical calculations and machine learning for explaining and predicting chemical phenomena. However, it is challenging to apply textbook knowledge to practical research. In this study, we developed teaching material based on computational chemistry to promote the integration of knowledge from all fields of chemistry, including organic, inorganic, and physical chemistry, to bridge the gap between classroom learning and chemistry research. This experimental material, which comprehensively covers weak intermolecular interactions and chemical reactions, is expected to help students conduct purposeful research activities after being assigned to a laboratory.

关键词： Upper-Division Undergraduate Physical Chemistry Computational Chemistry computer-based learning Internet Web-based learning

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App-Free Method for Visualization of Polymers in 3D and Augmented Reality

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JOURNAL OF CHEMICAL EDUCATION 2023年第5期100卷 2039-2044页

作者： Roshandel, Hootan Shammami, Matthew Lin, Shiyun Wong, Yin-Pok Diaconescu, Paula L. Univ Calif Los Angeles Dept Chem & Biochem Los Angeles CA 90095 USA

The rise of virtual and online education in recent years has led to the development and popularization of many online tools, notably three-dimensional (3D) models and augmented reality (AR), for visualizing various structures in chemical sciences. The majority of the developed tools focus on either small molecules or biological systems, as information regarding their structure can be easily accessed from online databases or obtained through relatively quick calculations. As such, due to a lack of crystallographic and theoretical data available for nonbiological macromolecules, there is a noticeable lack of accessible online tools for the visualization of polymers in 3D. Herein, using a few sample polymers, we showcase a workflow for the generation of 3D models using molecular dynamics and Blender. The 3D structures can then be hosted on ***, where AR models can be generated automatically. Furthermore, the hosted 3D models can then be shared via quick response (QR) codes and used in various settings without the need to download any applications.

关键词： computer-based learning General Public Upper-division Undergraduate Web-based learning Solids Polymer Chemistry

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Ardith D. Brave n e c-;s;symbolscript symbolscript 0000-0001-9835-5173;Email: ardithbravenec@ ***

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JOURNAL OF CHEMICAL EDUCATION 2023年第2期100卷 933-940页

作者： Bravenec, Ardith D. Ward, Karen D. Millsaps Coll Dept Chem & Biochem Jackson MS 39210 USA William Howard Taft Univ Dept Educ Lakewood CO 80227 USA Univ Washington Earth & Space Sci Seattle WA 98195 USA

Chemistry simulations using interactive graphic user interfaces (GUIs) represent uniquely effective and safe tools to support multidimensional learning. computer literacy and coding skills have become increasingly important in the chemical sciences. In response to both of these facts, a series of Jupyter notebooks hosted on Google Colaboratory were developed for undergraduate students enrolled in physical chemistry. These modules were developed for use during the COVID-19 pandemic when Millsaps College courses were virtual and only virtual or online laboratories could be used. These interactive exercises employ the Python programming language to explore a variety of chemical problems related to kinetics, the Maxwell-Boltzmann distribution, numerical versus analytical solutions, and real-world application of concepts. All of the modules are available for download from GitHub (https://***/Abravene/Python-Notebooks-for-Physical-Chemistry). Accessibility was prioritized, and students were assumed to have no prior programming experience;the notebooks are cost-free and browser-based. Students were guided to use widgets to build interactive GUIs that provide dynamic representations, immediate access to multiple investigations, and interaction with key variables. To evaluate the perceived effectiveness of this introduction to Python programming, participants were surveyed at the beginning and end of the course to gauge their interest in pursuing programming and data analysis skills and how they viewed the importance of programming and data analysis for their future careers. Student reactions were generally positive and showed increased interest in programming and its importance in their futures, so these notebooks will be incorporated into the in-person laboratory in the future.

关键词： Upper-Division Undergraduate Physical Chemistry computer-based learning Chemometrics Gases Kinetic-Molecular Theory Maxwell-Boltzmann Python Programming

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Impact of artificial intelligence in transforming and replacing traditional learning and development of employees

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FORESIGHT 2025年第3期27卷 524-542页

作者： Chitranshi, Jaya Chopra, Komal Banerjee, Pallabi Symbiosis Int Deemed Univ Symbiosis Inst Management Studies Pune India

PurposeThe purpose of this study was to examine the impact of artificial intelligence interventions in transforming learning and development of organizations and to investigate whether artificial intelligence can replace traditional learning ***/methodology/approachMixed method approach was adopted to conduct the study. The sample size for quantitative study was 300 employees belonging to domains of technology, finance, health care and manufacturing. Structural equation modeling was done to arrive at the results. The qualitative study was done on 25 employees by conducting in-depth interviews followed by thematic *** findings of quantitative study revealed that perceived usefulness, perceived experience and learning effectiveness significantly contributed to transformation of traditional learning. The same was validated by qualitative study, and it also indicated that respondents preferred blended learning and artificial intelligence cannot replace traditional ***/valueThe study contributes to research by highlighting the impact of artificial intelligence in transformation of traditional learning and development based on departmental and job-specific roles as well as sectors that require physical training in addition to knowledge-based training.

关键词： Artificial intelligence Training and development Technology computer-based learning

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Adaptation of Chemistry Experiments for Middle School Blind or Visually Impaired Students

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JOURNAL OF CHEMICAL EDUCATION 2023年第6期100卷 2262-2268页

作者： Rashid, Ibtisam Chehadeh, Dduha Kuwait Inst Sci Res Syst & Software Dev Dept Sci & Technol Sect Safat 13109 Kuwait

Hands-on chemistry experiments often stimulate students'curiosity about this subject, but blind or visually impaired (BVI)students usually do not get to participate in such hands-on *** to adaptive methods and assisting technology, BVI studentscan actively participate in chemistry experiments. In this study,chemical laboratory experiments were modified and tested on BVI *** adaptations use Sci-Voice Talking LabQuest, associated sensors,and other tactile tools. This article explains the procedures to conductthe experiments and presents practical ways to introduce assistivetechnology to enhance learning. We encourage accommodating Arabiclanguage into the Sci-Voice Talking LabQuest.

关键词： computer-based learning Hands-On learning Manipulatives Laboratory Equipment Apparatus Elementary Middle SchoolScience

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Thermochromism: Theory Directed Design of a Thermochromic Thermometer

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JOURNAL OF CHEMICAL EDUCATION 2023年第2期100卷 796-802页

作者： Zacher, Brian Ferrante, Sam Romero, Rances Univ Arizona Dept Chem & Biochem Tucson AZ 85721 USA

The dissolution of cobalt(II) chloride in an appropriate binary alcohol solvent yields an equilibrium mixture, consisting of the differently colored octahedral (pink in color) and tetrahedral (blue in color) cobalt(II) coordination complexes, which can exhibit a brilliant and reversible pink-to-blue color transition over a similar to 10 degrees C window-i.e., function as a thermochromic thermometer-where the dynamic equilibrium is described by CoCl2(R1OH)(4) + 2R(2)OH reversible arrow CoCl2(R2OH)(2) + 4R(1)OH. In this experiment, students are challenged to exploit the principles of equilibrium in order to exhibit control over the chemical system and design, model, and implement a thermochromic thermometer which, when correctly prepared, exhibits a specifically targeted composition and color at a unique temperature assigned to each student. By employing fundamental principles of physical chemistry in conjunction with spectrophotometric analysis, students quantify pertinent thermodynamic parameters for the chemical system, and then use them to predictively model/calculate (via Excel) the exact initial composition required to enable the specifically desired equilibrium composition and color to emerge at precisely the target temperature. Completely directed by their modeled prescriptions, students then validate their theoretical predictions by implementing the functional thermochromic thermometer in the laboratory.

关键词： Upper-Division Undergraduate Physical Chemistry computer-based learning Hands-on learning Equilibrium Spectroscopy

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Accessible 3D Printing: Multicolor Molecular Models from Consumer-Grade, Single Filament 3D Printers

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JOURNAL OF CHEMICAL EDUCATION 2023年第12期100卷 4860-4865页

作者： Martin, H. Eisner, E. Klosterman, J. K. Univ Calif San Diego Dept Chem & Biochem La Jolla CA 92093 USA

3D printers have facilitated a wealth of 3D printed molecular models illustrating key structural concepts for student learning. However, general adoption of 3D printed models in the organic chemistry classroom proceeds slowly as the majority of consumer-grade 3D (fused deposition modeling (FDM) and resin) printers are inherently monochromatic, limited to printing a single color at a time. Here, we report a general procedure for 3D printed multicolor space-filling molecular models and molecular orbital models using freely available software that can be printed and assembled using accessible and affordable consumer-grade 3D printers.

关键词： Second-Year Undergraduate Upper-DivisionUndergraduate Organic Chemistry Demonstrations Hands-Onlearning/Manipulatives computer-based learning Alkanes/Cycloalkanes Alkenes Alkynes Aromatic Compounds MO Theory Molecular Properties/Structure

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Artificial Intelligence Applications in Hepatology

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CLINICAL GASTROENTEROLOGY AND HEPATOLOGY 2023年第8期21卷 2015-2025页

作者： Schattenberg, Joern M. Chalasani, Naga Alkhouri, Naim Univ Med Ctr Mainz Dept Med 1 Metab Liver Res Program Mainz Germany Indiana Univ Sch Med Indianapolis IN USA Indiana Univ Hlth Indianapolis IN USA Arizona Liver Hlth 3051 East Rock Wren Rd Phoenix AZ 85048 USA Univ Arizona Tucson AZ USA

Over the past 2 decades, the field of hepatology has witnessed major developments in diagnostic tools, prognostic models, and treatment options making it one of the most complex medical subspecialties. Through artificial intelligence (AI) and machine learning, computers are now able to learn from complex and diverse clinical datasets to solve real-world medical problems with performance that surpasses that of physicians in certain areas. AI algorithms are currently being implemented in liver imaging, interpretation of liver histopathology, noninvasive tests, prediction models, and more. In this review, we provide a summary of the state of AI in hepatology and discuss current challenges for large-scale implementation including some ethical aspects. We emphasize to the readers that most AI-based algorithms that are discussed in this review are still considered in early development and their utility and impact on patient outcomes still need to be assessed in future large-scale and inclusive studies. Our vision is that the use of AI in hepatology will enhance physician performance, decrease the burden and time spent on documentation, and reestablish the personalized patient-physician relationship that is of utmost importance for obtaining good outcomes.

关键词： computer-based learning Ethics Machine learning Deep learning

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