Physiological Sciences of Biopolymers

Course Title

Course Title in English

Physiological Sciences of Biopolymers

Course Type

-

Functional Analysis of Biological Materials

Eligible Students

Graduate School of Science

Target Grade

1Year

Course Numbering Code

HSSML5MCA1

Credits

2.00Credits

The course numbering code represents the faculty managing the subject, the department of the target students, and the education category (liberal arts / specialized course). For detailed information, please download the separate manual from the upper right 'question mark'.

Type of Class

講義 (Lecture)

Eligible Year/Semester

Fall semester 2026

(Fall semester)

Instructor

吉田　秀郎

Affiliation

Graduate school of Science

Language of Instruction

English

英語を使用する

Related SDGs

9

Office Hours and Location

Anytime at Rm 507

Contact

hide@sci.u-hyogo.ac.jp

Corresponding Diploma Policy

A double circle indicates the most relevant DP number and a circle indicates the associated DP.

Corresponding Undergraduate School DP

ー

Corresponding Graduate School DP

1◎／6〇

Corresponding University-Wide DP

N/a

Academic Goals of Teacher Training Course

ー

Course Objectives and Learning Outcome

Course Objectives：To learn and practice cell biology, it is important to consider cell organelles from the viewpoint of quantitative regulation. In this course, students will deepen their understanding of research on "organelle autoregulation" in English and develop their presentation skills by giving presentations in English on their own current research. The skills acquired in this way are essential for future executive positions in research universities, pharmaceutical companies, food companies, chemical companies, etc.

Aim：(1) To be able to give an outline of research on "organelle autoregulation" (2) To be able to give a presentation in English on his/her own research and to discuss other students' research in English (2) To be able to give a presentation in English on his/her own research and to discuss other students' research in English.

Subtitle and Keywords of the Class

【Key words】
ER stress response, ATF6, IRE1, PERK, XBP1, ATF4, ERSE, UORE, AARE, ER chaperones, ERAD factors, apoptosis, BiP, GRP94, PDI, CNX, CRT, HRD1, EDEM, Golgi stress response, TFE3, proteoglycans, mucins, cholesterol, OSBP, lysosome stress response, mitochondrial stress response, TFEB, ATF5

Course Overview and Schedule

Course Description: In this lecture, the the faculty member will first give an explanation of "organelle autoregulation" in English, and then lecture on English presentation techniques. Students will be asked questions to gauge their understanding, and the the faculty member will also ask questions. Next, students will give a presentation on their own research in English, followed by a question-and-answer session with other students in English.

Lecture Plan:
(1) Lecture in English and Q&A session on "organelle autoregulation" by the faculty member
Lecture 1: ER stress response（Lecture Resume 1）
Lecture 2: Golgi stress response（Lecture Resume２）
Lecture 3: Lysosome stress response and mitochondrial stress response（Lecture Resume３）

(2) English presentation and discussion by students on their "Master's research
Lecture 4: Presentation by Student 1（Lecture Resume４）
Lecture 5: Presentation by Student 2（Lecture Resume５）
Lecture 6: Presentation by Student 3（Lecture Resume６）
Lecture 7: Presentation by Student 4（Lecture Resume７）
Lecture 8: Presentation by Student 5（Lecture Resume８）
Lecture 9: Presentation by Student 6（Lecture Resume９）
Lecture 10: Presentation by Student 7（Lecture Resume１０）
Lecture 11: Presentation by Student 8（Lecture Resume１１）
Lecture 12: Presentation by Student 9（Lecture Resume１２）
Lecture 13: Presentation by Student 10（Lecture Resume１３）
Lecture 14: Presentation by Student 11（Lecture Resume１４）
Lecture 15: Presentation by Student 12（Lecture Resume１５）

In-person/Remote Classification

In-person

Implementation Method and Remote Credit Limit Application

・対面授業のみ
・遠隔授業単位上限の適用を受けない

Uses of Generative AI

Limited permission for use

Precautions for using Generative AI

生成AIの利用にあたっては『本学の教育における生成AIの取扱いについて(学生向け)』の記載内容について留意すること。

この授業においては、以下の範囲において、生成AIの利用を許可し、これ以外の範囲での利用は禁止する。生成AIの利用については担当教員の指示に従うこと。教員が認める範囲を超えて生成AIを利用したことが判明した場合は、単位を認定しない、又は認定を取り消すことがある。生成AIの出力した内容について、事実関係の確認や出典・参考文献を確認・追記することが重要である。また、生成AIによる出力結果をそのまま課題・レポートとして提出してはならない。

<利用可の範囲>
課題・レポート作成の際の参考として使用すること。

Textbook

必要に応じて提示、または、指示する。

References

必要に応じて提示、または、指示する。

Contents and Estimated Time for Pre- and Post- Learning (Preparation and Review)

【preparation】Pre-read lecture materials to be used in lecture (6 h) and preparation of presentation in English (48 h)

【review】Rereading lecture materials to deepen and consolidate understanding of lecture content (6 h)

Contents of Active Learning

English presentation of research by students followed by a question and answer session (12 sessions)Not applicable

Grading Criteria and Methods

【Grading Criteria】

Students who can understand and explain "quantitative regulation mechanisms of cellular organelles (organelle autoregulation)" and those who can give presentations and discussions about their own and others' research in English will be given credits based on the achievement level of the abilities (knowledge, skills, thinking, judgment, expression, etc.) described in the lecture objectives and achievement goals, with grades of S (90 points or higher), A (80 points or higher), B (70 points or higher) and C (60 points or higher).

【Grading Methods】

Comprehensive evaluation will be made based on the question-and-answer session and presentation in each lecture, including the student's attitude (e.g., active questioning).

How to Disclose Assignments and Exam Results

Feedback will be provided on the results within the day's lecture.

Precautions and Requirements for Course Registration

英語の講義が理解できること

Practical Education

Not applicable

Remarks

該当なし

In cases where any differences arise between the English version and the original Japanese version, the Japanese version shall prevail as the official authoritative version.

Syllabus data