Photodynamic therapy (PDT) is a clinically approved, minimally invasive treatment that can exert selective cytotoxic activity against malignant cells. When the photosensitizer is exposed to light of a specific wavelength, its electrons absorb the energy of light and transition to the excited state. When it returns to the ground state, it releases energy. The released energy is absorbed by oxygen to form singlet oxygen and free radicals, also known as reactive oxygen species (ROS). These ROS produce cytotoxicity. Indocyanine green is a drug that has been reported to be useful as a photodynamic therapy, but it has the problem of easy decomposition in combination with hemoglobin, therefore, this paper uses PFOB as a carrier to transport drugs while coupling the drug to hyaluronic acid, to achieve specific recognition of the CD-44 molecular receptor on the surface of tumor cells. The drug is expected to achieve better killing effect on tumor cells with little toxicity to other cells, and it is expected to be a favorable candidate for photodynamic therapy.
{"title":"Targeted Nanoparticle Carriers Loaded with ICG for Photodynamic Therapy","authors":"Wen-Ching Chao","doi":"10.1145/3570773.3570854","DOIUrl":"https://doi.org/10.1145/3570773.3570854","url":null,"abstract":"Photodynamic therapy (PDT) is a clinically approved, minimally invasive treatment that can exert selective cytotoxic activity against malignant cells. When the photosensitizer is exposed to light of a specific wavelength, its electrons absorb the energy of light and transition to the excited state. When it returns to the ground state, it releases energy. The released energy is absorbed by oxygen to form singlet oxygen and free radicals, also known as reactive oxygen species (ROS). These ROS produce cytotoxicity. Indocyanine green is a drug that has been reported to be useful as a photodynamic therapy, but it has the problem of easy decomposition in combination with hemoglobin, therefore, this paper uses PFOB as a carrier to transport drugs while coupling the drug to hyaluronic acid, to achieve specific recognition of the CD-44 molecular receptor on the surface of tumor cells. The drug is expected to achieve better killing effect on tumor cells with little toxicity to other cells, and it is expected to be a favorable candidate for photodynamic therapy.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127569239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Melanoma is a common cutaneous malignant tumor in clinic. The incidence of melanoma is on the rise, with serious phenotype and easy metastasis. Prior to targeted therapy and ICI, patients with advanced melanoma had a very poor prognosis, with a 5-year survival rate of less than 10%. ICI extended progression-free survival and overall survival and improved quality of life in patients with advanced melanoma compared with conventional treatment. As more and more attention has been paid to the clinical application of ICI, its limitations have been further discovered. Some patients develop resistance or insensitivity to ICI, so further research on the mechanism of drug resistance is needed. In addition, drug combination may be a way to improve the effect of ICI. This article reviews the clinical efficacy of ICI in the treatment of melanoma and the mechanism of drug resistance.
{"title":"Research status and prospect of immune checkpoint inhibitors for melanoma","authors":"Y-H Liang, Tianshi Liu, Yifan Wu","doi":"10.1145/3570773.3570784","DOIUrl":"https://doi.org/10.1145/3570773.3570784","url":null,"abstract":"Melanoma is a common cutaneous malignant tumor in clinic. The incidence of melanoma is on the rise, with serious phenotype and easy metastasis. Prior to targeted therapy and ICI, patients with advanced melanoma had a very poor prognosis, with a 5-year survival rate of less than 10%. ICI extended progression-free survival and overall survival and improved quality of life in patients with advanced melanoma compared with conventional treatment. As more and more attention has been paid to the clinical application of ICI, its limitations have been further discovered. Some patients develop resistance or insensitivity to ICI, so further research on the mechanism of drug resistance is needed. In addition, drug combination may be a way to improve the effect of ICI. This article reviews the clinical efficacy of ICI in the treatment of melanoma and the mechanism of drug resistance.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127480890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: To develop a random forest algorithm-based model for the recognition of angry, neutral, and happy emotions for eye features and to further analyze the importance of eye features. Method: Raw data were obtained using emotional images from the Chinese Emotional Face System (CAFPS), and the code was used to derive relevant eye features data to build the database. The relevant features were left and right pupil size, left and right visible iris size, Distance between inner corners of eyes, upper and lower eyelid distance, left eye opening and closing, AU1 (inner eyebrow raised), AU2 (outer eyebrow raised), AU4 (overall lowered eyebrow), AU5 (raised upper eyelid), AU6 (raised cheek) and AU7 (eye constriction), a total of 13 eye features, were used to construct an emotion recognition model using the random forest algorithm and to analyze the importance of the features. Results: The differences were statistically significant (p<0.01) in all 13 eye features; the accuracy of the model constructed using the random forest algorithm was 70.2%, the recall was 0.702, the accuracy was 0.977 and the F1 was 0.809. AU6 had the highest importance in the process of constructing the model, accounting for 15.4%. Conclusion: Eye features have a role in the process of building an emotion recognition model, validating the theories related to Chinese medicine eye diagnosis, and combining Chinese medicine eye diagnosis with theories related to Chinese medicine emotions to identify patients' emotions by capturing eye information, which has clinical practice implications.
{"title":"A random forest algorithm-based emotion recognition model for eye features","authors":"Hong Feng, Xunbing Shen","doi":"10.1145/3570773.3570851","DOIUrl":"https://doi.org/10.1145/3570773.3570851","url":null,"abstract":"Objective: To develop a random forest algorithm-based model for the recognition of angry, neutral, and happy emotions for eye features and to further analyze the importance of eye features. Method: Raw data were obtained using emotional images from the Chinese Emotional Face System (CAFPS), and the code was used to derive relevant eye features data to build the database. The relevant features were left and right pupil size, left and right visible iris size, Distance between inner corners of eyes, upper and lower eyelid distance, left eye opening and closing, AU1 (inner eyebrow raised), AU2 (outer eyebrow raised), AU4 (overall lowered eyebrow), AU5 (raised upper eyelid), AU6 (raised cheek) and AU7 (eye constriction), a total of 13 eye features, were used to construct an emotion recognition model using the random forest algorithm and to analyze the importance of the features. Results: The differences were statistically significant (p<0.01) in all 13 eye features; the accuracy of the model constructed using the random forest algorithm was 70.2%, the recall was 0.702, the accuracy was 0.977 and the F1 was 0.809. AU6 had the highest importance in the process of constructing the model, accounting for 15.4%. Conclusion: Eye features have a role in the process of building an emotion recognition model, validating the theories related to Chinese medicine eye diagnosis, and combining Chinese medicine eye diagnosis with theories related to Chinese medicine emotions to identify patients' emotions by capturing eye information, which has clinical practice implications.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121710555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Geng Tian, Xiaohang Li, Yi Wu, Ao Liu, Y. Zhang, Yifei Ma, Wenhui Guo, Xiaoli Sun, Bangze Fu, Da Li
Lonicerae japonicae flos, a common clinical Chinese medicine, is widely used in proprietary traditional Chinese medicine for the treatment of various conditions, such as fever, cough, and influenza. The microscopic features of honeysuckle pollen grains significantly correlate with their medicinal effects. In this study, deep learning using artificial intelligence was cross-combined with microscopic images of Chinese herbal medicines, and we proposed microscopic identification through an intelligent recognition method of honeysuckle pollen grains using microscopic images based on YOLO v5. The expandability of the microscopic feature recognition of different magnification models was verified based on different microscopic objectives. The honeysuckle pollen grains model based on YOLO v5 can quickly and accurately identify the microscopic images of pollen grains, which can provide a reference for the quality improvement and quality standardization of traditional Chinese herbs and has good application prospects.
{"title":"Recognition effect of models based on different microscope objectives","authors":"Geng Tian, Xiaohang Li, Yi Wu, Ao Liu, Y. Zhang, Yifei Ma, Wenhui Guo, Xiaoli Sun, Bangze Fu, Da Li","doi":"10.1145/3570773.3570845","DOIUrl":"https://doi.org/10.1145/3570773.3570845","url":null,"abstract":"Lonicerae japonicae flos, a common clinical Chinese medicine, is widely used in proprietary traditional Chinese medicine for the treatment of various conditions, such as fever, cough, and influenza. The microscopic features of honeysuckle pollen grains significantly correlate with their medicinal effects. In this study, deep learning using artificial intelligence was cross-combined with microscopic images of Chinese herbal medicines, and we proposed microscopic identification through an intelligent recognition method of honeysuckle pollen grains using microscopic images based on YOLO v5. The expandability of the microscopic feature recognition of different magnification models was verified based on different microscopic objectives. The honeysuckle pollen grains model based on YOLO v5 can quickly and accurately identify the microscopic images of pollen grains, which can provide a reference for the quality improvement and quality standardization of traditional Chinese herbs and has good application prospects.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121781148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MiR-144 is a tumor suppressor microRNA relevant to the suppressing of mutation cells so should have a positive effect on limiting or slowing the growth of cancerous lung cells. Since smoky coal air pollution is a carcinogen for non-small cell lung cancers (NSCLCs) in humans, this experiment explores how this environmental toxin affects the down-regulation of miR-144 in untreated lung cancer. Cell lines will be cultured in a controlled environment and cells will also be acquired from lung cancer patient's lung tissue. Expression of miR-144 will be measured by RTPCR and cell growth measured by MTT assay and metastasis measured by wound healing assay. The result of this investigation will provide additional information for future clinical and scientific trials regarding smoky coal induced lung cancer and specific microRNAs such as miR-144. The paper will explore the influence an environmental carcinogen might have on a tumor suppressor gene.
{"title":"Smoky Coal Air Pollution's Influence on the Down-Regulation of miR-144 in Lung Cancer Cell","authors":"Xiaole Li","doi":"10.1145/3570773.3570796","DOIUrl":"https://doi.org/10.1145/3570773.3570796","url":null,"abstract":"MiR-144 is a tumor suppressor microRNA relevant to the suppressing of mutation cells so should have a positive effect on limiting or slowing the growth of cancerous lung cells. Since smoky coal air pollution is a carcinogen for non-small cell lung cancers (NSCLCs) in humans, this experiment explores how this environmental toxin affects the down-regulation of miR-144 in untreated lung cancer. Cell lines will be cultured in a controlled environment and cells will also be acquired from lung cancer patient's lung tissue. Expression of miR-144 will be measured by RTPCR and cell growth measured by MTT assay and metastasis measured by wound healing assay. The result of this investigation will provide additional information for future clinical and scientific trials regarding smoky coal induced lung cancer and specific microRNAs such as miR-144. The paper will explore the influence an environmental carcinogen might have on a tumor suppressor gene.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123796367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traditional feature selection algorithms simply compute a feature cost vector to make the random process more tendentious, but do not consider the relative relationship between features, and degenerate into ordinary random forest algorithms when feature differentiation is not significant. In view of this, we propose the dual cost-sensitive random forest algorithm. The algorithm introduces two improvements. 1) Introducing sequential analysis in generating feature vectors, giving dynamic weights to different categories in classification. 2) Introducing cost sensitivity in the decision tree generation stage with the goal of minimum average error. After comparing with logistic regression, random forest, support vector machine and other algorithms, the experimental results show that the method has a lower misclassification rate in heart disease detection, which makes the result classification more reliable and more suitable for practical applications.
{"title":"Application of Double Sensitive Cost Random Forest in Heart Disease Detection","authors":"Zhifeng Wang, Xiaoling Tan","doi":"10.1145/3570773.3570867","DOIUrl":"https://doi.org/10.1145/3570773.3570867","url":null,"abstract":"Traditional feature selection algorithms simply compute a feature cost vector to make the random process more tendentious, but do not consider the relative relationship between features, and degenerate into ordinary random forest algorithms when feature differentiation is not significant. In view of this, we propose the dual cost-sensitive random forest algorithm. The algorithm introduces two improvements. 1) Introducing sequential analysis in generating feature vectors, giving dynamic weights to different categories in classification. 2) Introducing cost sensitivity in the decision tree generation stage with the goal of minimum average error. After comparing with logistic regression, random forest, support vector machine and other algorithms, the experimental results show that the method has a lower misclassification rate in heart disease detection, which makes the result classification more reliable and more suitable for practical applications.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125589737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Attention deficit hyperactivity disorder (ADHD) can have a negative impact on children's development, even into adulthood, so the early diagnosis and screening for ADHD can be an important prerequisite for later intervention. However, the traditional diagnostic methods have limitations in terms of objectivity, convenience and efficiency. With the development of artificial intelligence, deep learning, as an emerging computer technology that can deal with massive data and variables, has gradually been applied to early prediction of ADHD in children and aiding diagnosis. From the traditional diagnostic methods to one based on conventional feature analysis, such as the diagnosis of ADHD in children based on EEG data analysis. With the continuous development of computer technology, the analysis and diagnosis of EEG data based on deep learning, and the combination of deep learning model and computer vision technology have been emerged. Due to the incompleteness of the analysis and diagnosis of unimodal data, the deep learning models of multimodal data can have a strong integrity, which has become a hot spot at present. However, deep learning still has limitations in hardware cost and algorithm selection. In the future, further research is needed in deep learning-assisted diagnosis to continuously optimize the algorithm and accelerate the improvement of ADHD intelligent identification and diagnosis ability.
{"title":"Deep learning-assisted ADHD diagnosis","authors":"Runqing Gao, Kesui Deng, Miaoyun Xie","doi":"10.1145/3570773.3570849","DOIUrl":"https://doi.org/10.1145/3570773.3570849","url":null,"abstract":"Attention deficit hyperactivity disorder (ADHD) can have a negative impact on children's development, even into adulthood, so the early diagnosis and screening for ADHD can be an important prerequisite for later intervention. However, the traditional diagnostic methods have limitations in terms of objectivity, convenience and efficiency. With the development of artificial intelligence, deep learning, as an emerging computer technology that can deal with massive data and variables, has gradually been applied to early prediction of ADHD in children and aiding diagnosis. From the traditional diagnostic methods to one based on conventional feature analysis, such as the diagnosis of ADHD in children based on EEG data analysis. With the continuous development of computer technology, the analysis and diagnosis of EEG data based on deep learning, and the combination of deep learning model and computer vision technology have been emerged. Due to the incompleteness of the analysis and diagnosis of unimodal data, the deep learning models of multimodal data can have a strong integrity, which has become a hot spot at present. However, deep learning still has limitations in hardware cost and algorithm selection. In the future, further research is needed in deep learning-assisted diagnosis to continuously optimize the algorithm and accelerate the improvement of ADHD intelligent identification and diagnosis ability.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128239820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective In this study, we investigated the usage behaviors of clinical nurses for an all-optical network (AON)-based medical information system and the factors influencing these behaviors. The purpose was to provide theoretical support for the wide applications of the system. Methods A whole-group sampling method was adopted. The general information questionnaire and the UTAUT scale were used to survey all nurses from September to October 2022 at the internal medicine building of Puren Hospital (Wuhan University of Science and Technology, WUST), where AONs, a new network prototype for the fifth-generation fixed network (F5G), has been embedded. Results 219 clinical nurses scored (11.97±1.70) on the usage behavior entries, with a mean entry score of (3.99±0.57). Scores for usage behaviors were positively correlated with five factors, namely performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and intention to use, or behavioral intention (BI) (r=0.635,0.760,0.803, 0.826, and 0.802, respectively; P<0.01). The results of the multiple linear regression analysis showed that these five factors greatly affected the usage behaviors of clinical nurses for the system (P< 0.05), explaining 71.9% of the total variance. Conclusion Hospital managers and mid-level leaders are advised to exercise their influence to train clinical nurses and encourage them to use new technologies, thereby promoting the development of information technologies for smart hospitals.
{"title":"Analysis of Factors Influencing Clinical Nurses’ Usage Behavior of F5G All-Optical Network Medical Information System for Smart Hospitals","authors":"Xuan Huang, Chongqing Shi","doi":"10.1145/3570773.3570850","DOIUrl":"https://doi.org/10.1145/3570773.3570850","url":null,"abstract":"Objective In this study, we investigated the usage behaviors of clinical nurses for an all-optical network (AON)-based medical information system and the factors influencing these behaviors. The purpose was to provide theoretical support for the wide applications of the system. Methods A whole-group sampling method was adopted. The general information questionnaire and the UTAUT scale were used to survey all nurses from September to October 2022 at the internal medicine building of Puren Hospital (Wuhan University of Science and Technology, WUST), where AONs, a new network prototype for the fifth-generation fixed network (F5G), has been embedded. Results 219 clinical nurses scored (11.97±1.70) on the usage behavior entries, with a mean entry score of (3.99±0.57). Scores for usage behaviors were positively correlated with five factors, namely performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and intention to use, or behavioral intention (BI) (r=0.635,0.760,0.803, 0.826, and 0.802, respectively; P<0.01). The results of the multiple linear regression analysis showed that these five factors greatly affected the usage behaviors of clinical nurses for the system (P< 0.05), explaining 71.9% of the total variance. Conclusion Hospital managers and mid-level leaders are advised to exercise their influence to train clinical nurses and encourage them to use new technologies, thereby promoting the development of information technologies for smart hospitals.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128261459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lung cancer is the most lethal cancer with the highest mortality rate. However, because of developed resistance from patients, certain drugs for lung cancer treatment have displayed inadequate effects in enhancing prognosis. Recent studies show that the cause of resistance might be due to inhibited T Cell proliferation that results from the binding of LAG 3 with its two ligands, FGL1 and MHC II. Therefore, because the two ligands interact with LAG 3 on the same domains, and the two ligand's both inhibit T Cell proliferation, the binding of one ligand may alter the binding of the other ligand to LAG 3. In this study, we explore the effect of FGL1 knockout on MHC II and LAG 3 binding. The results of this study will provide insight into whether FGL1 increases/decreases MHC II and LAG 3 interaction. Hence, by understanding this mechanism, treatment would be able to alter T Cell proliferation by regulating FGL1 which could lead to improved prognosis in patients.
{"title":"Knockout of FGL1 in Tumor Cell Lines Leads to Decreased Binding Between MHC II and LAG 3","authors":"Run-Run Kang","doi":"10.1145/3570773.3570790","DOIUrl":"https://doi.org/10.1145/3570773.3570790","url":null,"abstract":"Lung cancer is the most lethal cancer with the highest mortality rate. However, because of developed resistance from patients, certain drugs for lung cancer treatment have displayed inadequate effects in enhancing prognosis. Recent studies show that the cause of resistance might be due to inhibited T Cell proliferation that results from the binding of LAG 3 with its two ligands, FGL1 and MHC II. Therefore, because the two ligands interact with LAG 3 on the same domains, and the two ligand's both inhibit T Cell proliferation, the binding of one ligand may alter the binding of the other ligand to LAG 3. In this study, we explore the effect of FGL1 knockout on MHC II and LAG 3 binding. The results of this study will provide insight into whether FGL1 increases/decreases MHC II and LAG 3 interaction. Hence, by understanding this mechanism, treatment would be able to alter T Cell proliferation by regulating FGL1 which could lead to improved prognosis in patients.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130008307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hypothesis: I postulate that the major function of PNS in breast cancer is to induce the apoptosis and inhibit the proliferation through activate the inhibition of P13k/AKT pathway to suppress the effect of Bcl-2 and increase the Bax and caspase-3. Purpose: Breast cancer is malignant disease for human beings. The traditional therapy is mainly resection operation. Though its effect of radical cure is high, it easily metastasizes and invades the tumor. Previous studies have shown that Panax notoginseng Saponins (PNS) has inhibitory proliferation effect and relevant function on apoptosis via PI3k/AKT/mTOR pathway. The study will investigate how PNS effects apoptosis by regulating PI3k/AKT in in vitro condition. Materials and method: The cell line which will be used is 4T1-Leu breast cancer cells. The cell proliferation will be assessed by Cell Counting Kit-8, whereas the apoptotic rate will be investigated by flow cytometry and Annexin V. The relevant proteins about PI3k/AKT/mTOR pathway and apoptosis will be assessed by western blotting. Possible results: There are five possible results in cell proliferation, five results in apoptosis and 6 results in western blot in this study, it can be aggregated to 4 results. 1.PNS can inhibit proliferation and induce apoptosis of 4T1-luc breast cancer cells by suppressing the PI3K/AKT pathway; 2. PNS activates proliferation and inhibit apoptosis of 4T1-luc breast cancer cells by suppressing the PI3K/AKT/mTOR pathway. 3. PNS activates proliferation and inhibit apoptosis of 4T1-luc breast cancer cells by promoting mTOR pathway via PI3K/AKT. 4. PNS inhibit apoptosis of 4T1-luc breast cancer cells by suppressing mTOR pathway via PI3K/AKT. Conclusion: The results of the study will provide a new way to investigate the PNS in breast cancer therapy, in both apoptosis and cell signal pathway ways.
{"title":"Panax Notoginseng Saponins Induces Apoptosis in Breast Cancer by Regulating PI3k/AKT Pathway and Suppressing Bcl-2 by Using Computer Science","authors":"Xiaojing Wei","doi":"10.1145/3570773.3570778","DOIUrl":"https://doi.org/10.1145/3570773.3570778","url":null,"abstract":"Hypothesis: I postulate that the major function of PNS in breast cancer is to induce the apoptosis and inhibit the proliferation through activate the inhibition of P13k/AKT pathway to suppress the effect of Bcl-2 and increase the Bax and caspase-3. Purpose: Breast cancer is malignant disease for human beings. The traditional therapy is mainly resection operation. Though its effect of radical cure is high, it easily metastasizes and invades the tumor. Previous studies have shown that Panax notoginseng Saponins (PNS) has inhibitory proliferation effect and relevant function on apoptosis via PI3k/AKT/mTOR pathway. The study will investigate how PNS effects apoptosis by regulating PI3k/AKT in in vitro condition. Materials and method: The cell line which will be used is 4T1-Leu breast cancer cells. The cell proliferation will be assessed by Cell Counting Kit-8, whereas the apoptotic rate will be investigated by flow cytometry and Annexin V. The relevant proteins about PI3k/AKT/mTOR pathway and apoptosis will be assessed by western blotting. Possible results: There are five possible results in cell proliferation, five results in apoptosis and 6 results in western blot in this study, it can be aggregated to 4 results. 1.PNS can inhibit proliferation and induce apoptosis of 4T1-luc breast cancer cells by suppressing the PI3K/AKT pathway; 2. PNS activates proliferation and inhibit apoptosis of 4T1-luc breast cancer cells by suppressing the PI3K/AKT/mTOR pathway. 3. PNS activates proliferation and inhibit apoptosis of 4T1-luc breast cancer cells by promoting mTOR pathway via PI3K/AKT. 4. PNS inhibit apoptosis of 4T1-luc breast cancer cells by suppressing mTOR pathway via PI3K/AKT. Conclusion: The results of the study will provide a new way to investigate the PNS in breast cancer therapy, in both apoptosis and cell signal pathway ways.","PeriodicalId":153475,"journal":{"name":"Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134006558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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