Advanced genetics (Hoboken, N.J.)最新文献_第4页

Ciliary Defects in Inherited Retinal Diseases 遗传性视网膜疾病的睫状体缺陷。

Advanced genetics (Hoboken, N.J.) Pub Date : 2026-03-06 DOI: 10.1002/ggn2.202500066

Guizhi Guo, Lin Li, Jun Zhou, Jie Ran

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Advanced genetics (Hoboken, N.J.) Pub Date : 2026-03-06

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RNAi-Based Pesticides: Genetic Innovations for Sustainable Crop Protection and One Health 基于rnai的农药：可持续作物保护和同一个健康的基因创新。

Advanced genetics (Hoboken, N.J.) Pub Date : 2026-03-05 DOI: 10.1002/ggn2.202500063

Jisheng Liu, Guy Smagghe

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Advanced genetics (Hoboken, N.J.) Pub Date : 2026-03-05

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Advanced genetics (Hoboken, N.J.) Pub Date : 2026-02-22

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Recognition, Signal Transduction, and Amplification of Nucleic Acids Under Isothermal Condition 等温条件下核酸的识别、信号转导和扩增。

Advanced genetics (Hoboken, N.J.) Pub Date : 2026-02-22 DOI: 10.1002/ggn2.202500057

Zhaohui Qin, Jiaxin Li, Xin Su, Huiyu Liu

{"title":"Recognition, Signal Transduction, and Amplification of Nucleic Acids Under Isothermal Condition","authors":"Zhaohui Qin, Jiaxin Li, Xin Su, Huiyu Liu","doi":"10.1002/ggn2.202500057","DOIUrl":"10.1002/ggn2.202500057","url":null,"abstract":"Isothermal nucleic acid detection has become a compelling alternative to PCR, enabling rapid analysis with minimal instrumentation and strong potential for point-of-care use. Central to assay performance are three interconnected processes: recognition, signal transduction, and amplification. Recognition strategies now extend beyond base pairing to include engineered proteins, catalytic nucleic acids, and synthetic modules. Signal transduction has advanced through orthogonal chemistries and functional nanomaterials, converting molecular events into optical, electrical, or colorimetric outputs. Amplification encompasses not only nucleic acid replication but also catalytic cycles and cascade reactions that magnify signals across molecular and material scales. These innovations are converging toward integrated, programmable platforms that support multiplexing and digital readouts. In this Perspective, we highlight emerging mechanisms and design principles that define isothermal detection, and outline future opportunities to achieve accurate, scalable, and accessible diagnostics for clinical, environmental, and translational applications.","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12928101/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147286232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Advanced genetics (Hoboken, N.J.) Pub Date : 2026-02-13

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Best Practices for Developing Linear Models With Multiple Explanatory Variables 开发多元解释变量线性模型的最佳实践。

Advanced genetics (Hoboken, N.J.) Pub Date : 2026-02-13 DOI: 10.1002/ggn2.202500024

Baidu Li, Xinhai Li

{"title":"Best Practices for Developing Linear Models With Multiple Explanatory Variables","authors":"Baidu Li, Xinhai Li","doi":"10.1002/ggn2.202500024","DOIUrl":"10.1002/ggn2.202500024","url":null,"abstract":"Linear models, including t-test, ANOVA, regression, ANCOVA, and generalized linear models, are foundational tools in statistical analysis. For large datasets, such as those involving tens of thousands of genes and millions of records, numerous advanced methods have been developed to improve both computational efficiency and reliability. Here, we focus on a more general scenario: a linear model with many explanatory variables (e.g., >10) and a moderate sample size (e.g., thousands of observations). This paper provides the best practices for model selection, emphasizing the importance of including two-way interaction and quadratic terms, which are frequently overlooked in textbooks and classic literature. When dealing with high-dimensional data, we recommend using random forest for initial variable screening, followed by subset selection methods such as stepwise regression. Model selection can be guided by criteria like AIC, BIC, adjusted R2, and Mallows’ Cp, or by cross-validation. Shrinkage methods such as the lasso and ridge regression improve model fitting by penalizing coefficient size. Dimension reduction techniques such as Principal Components Regression (PCR) and Partial Least Squares (PLS) provide alternatives for managing high-dimensional data through uncorrelated component transformation. We provided R code along with detailed descriptions for all analyses, establishing a systematic approach to developing linear models.","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12902702/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146203901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Advanced genetics (Hoboken, N.J.) Pub Date : 2026-01-11

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Evolution of H5N1 Cross-Species Transmission: Adaptive Mutations Driving Avian-to-Human Infection H5N1跨物种传播的进化：适应性突变驱动禽-人感染。

Advanced genetics (Hoboken, N.J.) Pub Date : 2026-01-11 DOI: 10.1002/ggn2.202500051

Wenxin Man, Lin Du, Ying Liu, Zehan Pang, Hongyan Zhu, Bixia Hong, Zhichao Xu, Huahao Fan

{"title":"Evolution of H5N1 Cross-Species Transmission: Adaptive Mutations Driving Avian-to-Human Infection","authors":"Wenxin Man, Lin Du, Ying Liu, Zehan Pang, Hongyan Zhu, Bixia Hong, Zhichao Xu, Huahao Fan","doi":"10.1002/ggn2.202500051","DOIUrl":"10.1002/ggn2.202500051","url":null,"abstract":"First detected in poultry in China in 1996, the H5N1 avian influenza virus has evolved into a significant global public health hazard, primarily owing to its high pathogenicity and potential for interspecies transmission. While primarily affecting avian species, H5N1 has repeatedly breached species barriers, infecting mammals including humans, minks, seals, and cattle. This review synthesizes current knowledge on the molecular mechanisms underpinning H5N1's host adaptation, focusing on key mutations in viral proteins-such as hemagglutinin (HA), neuraminidase (NA), and polymerase subunits (PB2)-which boost binding affinity to human-type receptors, increase replicative efficiency in mammalian cells, and facilitate immune evasion. Critical mutations, including HA-Q226L, HA-T199I, PB2-E627K, and NA-H274Y, are discussed in detail, highlighting their roles in altering receptor specificity, promoting antiviral resistance, and expanding viral tropism. The paper also outlines epidemiological trends, global dissemination patterns driven by migratory birds and trade, and current strategies for prevention and control, including antiviral therapeutics and vaccine development. Ultimately, this comprehensive analysis underscores the urgent need for continued surveillance, broad-spectrum countermeasures, and international collaboration to reduce the pandemic risk posed by H5N1.","PeriodicalId":72071,"journal":{"name":"Advanced genetics (Hoboken, N.J.)","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12791573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145968062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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