Theoretical and Natural Science最新文献_第10页

Transmissibility of phosphorylated -synuclein in the brain of Parkinsons Disease model mice 磷酸化-突触核蛋白在帕金森病模型小鼠大脑中的传递性

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240803

Zhihan Chen, Siyuan Zhou, ShuangFeng Zhang, Peng Cao

引用次数: 0

Systematic Mendelian randomization reveals the causal roles of the microbiome on the risk of Parkinson's disease 系统孟德尔随机化揭示微生物组对帕金森病风险的因果作用

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240883

Zixuan Zhao

{"title":"Systematic Mendelian randomization reveals the causal roles of the microbiome on the risk of Parkinson's disease","authors":"Zixuan Zhao","doi":"10.54254/2753-8818/32/20240883","DOIUrl":"https://doi.org/10.54254/2753-8818/32/20240883","url":null,"abstract":"Parkinsons Disease (PD) is a neurodegenerative disorder whose etiology is not fully understood. The human gut microbiome, a complex community of microorganisms residing in the digestive tract, has recently emerged as a potential factor influencing various health conditions, including neurodegenerative diseases. The causal involvement of the human gut microbiome in Parkinsons disease (PD) remains elusive, primarily due to the challenge of distinguishing causation from mere correlation, and the presence of contradictory findings in existing research. The relationship between the gut microbiome and PD was assessed using a two-sample Mendelian randomization (MR) approach. Assessing the impact of microbial traits using data from independent genome-wide association studies (GWAS) (comprising 2,259 samples) on PD within a cohort of 15,056 cases and 449,056 controls. We performed multiple sensitivity analyses to validate our findings. Preliminary MR analysis indicated that modifications in the bacterial composition of the Firmicutes and Proteobacteria phyla are associated with changes in PD risk. Additionally, bacteria in other genera also play a role in this causal association. We provide a comprehensive discussion of the results obtained from our MR analysis and highlight the distinctions between our study and prior research efforts.","PeriodicalId":506830,"journal":{"name":"Theoretical and Natural Science","volume":"23 S6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140262485","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}

引用次数: 0

Current therapeutic targets and promising strategies for triple-negative breast cancer 三阴性乳腺癌的当前治疗目标和可行策略

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240849

Sha Tao

引用次数: 0

Comparison and analysis of the effect of various machine learning algorithms on cancer prediction 比较和分析各种机器学习算法对癌症预测的影响

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240846

Zonghao Wang, Dan Wang, Guomin Si

{"title":"Comparison and analysis of the effect of various machine learning algorithms on cancer prediction","authors":"Zonghao Wang, Dan Wang, Guomin Si","doi":"10.54254/2753-8818/32/20240846","DOIUrl":"https://doi.org/10.54254/2753-8818/32/20240846","url":null,"abstract":"Cancer is a serious disease that can have a big impact on the physical and mental health of patients. The incidence and mortality rate of cancer are increasing globally. Therefore, predicting the occurrence and treatment effect of cancer has become a hot research topic in the medical field. Machine learning algorithms can use vast amounts of data and algorithmic models to predict aspects of cancer occurrence, progression, and treatment effectiveness. This algorithm can learn and find patterns from large amounts of medical data, thereby improving the diagnosis and treatment of cancer. In this paper, naive Bayes model, logistic regression model, random forest model, KNN model and Ridge regression model were used to predict the data of cancer patients. The accuracy of naive Bayes model and logistic regression model is the highest, reaching 95%. The accuracy of random forest model and KNN model is 94%. The worst performing model was Ridge regression, with an accuracy of 93%. Naive Bayes algorithm and logistic regression algorithm perform well in solving binary classification problems because they are both probability-based classification algorithms. In this problem, the number of features is large, so the ridge regression algorithm can effectively process the data, but due to the small amount of data, it is easy to appear underfitting, so the performance is poor. In this paper, a variety of machine learning algorithms are used to predict cancer patients, and the accuracy, accuracy, recall rate and f1 parameters of each model are calculated and compared, which provides a basis for subsequent research.","PeriodicalId":506830,"journal":{"name":"Theoretical and Natural Science","volume":"134 34","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140078412","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}

引用次数: 0

Changes in intrinsic excitability of hippocampal pyramidal cells in Parkinsons disease model 帕金森病模型中海马锥体细胞内在兴奋性的变化

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240739

A. Wu

{"title":"Changes in intrinsic excitability of hippocampal pyramidal cells in Parkinsons disease model","authors":"A. Wu","doi":"10.54254/2753-8818/32/20240739","DOIUrl":"https://doi.org/10.54254/2753-8818/32/20240739","url":null,"abstract":"Parkinsons disease (PD) is the second most common fatal neurodegenerative disease in the world, and it reduces patients quality of life by causing movement disorders (e.g., tremors, muscle stiffness, and impaired balance) and non-motor disorders (e.g., depression, anxiety, and dementia). Previous research has mostly concentrated on dopamine-producing neurons in the substantia nigra compacta (SNc) that are dying off, which restricts therapeutic options and renders the search for disease-modifying therapies fruitless. In order to make a breakthrough, pathological changes in other brain areas deserve more attention. Previous PD studies reported atrophy in the hippocampus, an indispensable part of spatial and temporal memory formation. To answer the question of the cellular mechanism of hippocampus atrophy, this paper intends to research previously uncharted hippocampal intrinsic plasticity alterations. After analysing intercellular recordings of pyramidal neurons gathered from normal mice and genetically engineered PD mice, this paper demonstrates disparities in the intrinsic factors not noted in the previous research, such as peaks and afterhyperpolarization. These findings represent a progressive advancement in our comprehension of hippocampal pyramidal neurons, indicating potential therapeutic targets for Parkinsons disease treatment via SK channels, BK channels, and sodium channels.","PeriodicalId":506830,"journal":{"name":"Theoretical and Natural Science","volume":"13 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140262572","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}

引用次数: 0

Organ-on-chip technology's development and usages: A comprehensive review 片上器官技术的发展与应用：全面回顾

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240886

Yinzhou Lyu

{"title":"Organ-on-chip technology's development and usages: A comprehensive review","authors":"Yinzhou Lyu","doi":"10.54254/2753-8818/32/20240886","DOIUrl":"https://doi.org/10.54254/2753-8818/32/20240886","url":null,"abstract":"Organ-on-a-chip technology is a new development technology that has made great contributions to the field of biomedicine-medicine, which began to be studied in 1950 but has not achieved effective results. With the development of technology and the passage of time, the first successful organ-on-a-chip products were introduced in 1990. Organ-on-chip technology has broken through the limitations of human drug testing and pathological research, solved the problem of unsatisfactory efficacy after using animal simulation, and greatly promoted the development of pathology and pharmacology. Organ-on-a-chip refers to the cell culture of human organs on a chip to simulate the function and characteristics of human organs, providing a new way for disease treatment and drug research and development. The researchers began by trying to grow cells on artificial substrates to mimic the structure and function of human organs. Organ-on-a-chip technology can process cell cultures while improving the environment for human drug testing and pathology research, truly simulating and performing experiments on humans. Organ-on-a-chip is a cell culture analog that utilizes a microfluidic device in which microchannels are used to guide and manipulate the solution. In recent years, with the development of bio print technology, the research of organ chips has entered a new stage. Bioprinting allows cells and biomaterials to be arranged in predetermined patterns and structures to build tissues and organs with specific functions. At present, the research of organ chips can already help us complete the test drug and case analysis, the development time of this technology is very short, and there is still a lot of development and exploration space in the future.","PeriodicalId":506830,"journal":{"name":"Theoretical and Natural Science","volume":"8 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140262729","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}

引用次数: 0

The impact of Aspergillus Niger and Neurospora sitophila co-fermentation on the soluble dietary fiber of soybean residue 尼日尔曲霉和嗜坐果神经孢子菌共同发酵对大豆残渣中可溶性膳食纤维的影响

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240877

Zituo He, Zhiying Xu, Yiming Sun

引用次数: 0

Vaccine innovations and potential targets of breast cancer 疫苗创新和乳腺癌的潜在靶点

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240796

Georgia Jiang

引用次数: 0

Research on the duplication and death probability of the DNA of Escherichia coli within different generational time periods 研究大肠杆菌 DNA 在不同世代中的复制和死亡概率

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240835

Ho Tsz Hin

引用次数: 0

The role of Wnt5a in aging-related diseases Wnt5a 在衰老相关疾病中的作用

Theoretical and Natural Science Pub Date : 2024-03-06 DOI: 10.54254/2753-8818/32/20240810

Zewei Zhang

引用次数: 0