Background Extracellular vesicles (EVs) play an essential role in the communication between cells and transport of diagnostically significant molecules. A wide diversity of approaches utilizing different biochemical properties of EVs and a lack of accepted protocols make data interpretation very challenging. Scope of Review This review consolidates the data on the classical and state-of-the-art methods for isolation of EVs, including exosomes, highlighting the advantages and disadvantages of each method. Various characteristics of individual methods, including isolation efficiency, EV yield, properties of isolated EVs, and labor consumption are compared. Major Conclusions A mixed population of vesicles is obtained in most studies of EVs for all used isolation methods. The properties of an analyzed sample should be taken into account when planning an experiment aimed at studying and using these vesicles. The problem of adequate EVs isolation methods still remains; it might not be possible to develop a universal EV isolation method but the available protocols can be used towards solving particular types of problems. General Significance With the wide use of EVs for diagnosis and therapy of various diseases the evaluation of existing methods for EV isolation is one of the key problems in modern biology and medicine.
Preface to the Second Edition Preface to the First Edition Randomization The Idea of a Randomization Test Examples of Randomization Tests Aspects of Randomization Testing Raised by the Examples Sampling the Randomization Distribution or Systematic Enumeration Equivalent Test Statistics Significance Levels for Classical and Randomization Tests Limitations of Randomization Tests Confidence Limits by Randomization Applications of Randomization in Biology Single Species Ecology Genetics, Evolution and Natural Selection Community Ecology Randomization and Observational Studies Chapter Summary The Jackknife The Jackknife Estimator Applications of Jackknifing in Biology Single Species Analyses Genetics, Evolution and Natural Selection Community Ecology Chapter Summary The Bootstrap Resampling with Replacement Standard Bootstrap Confidence Limits Simple Percentile Confidence Limits Bias Corrected Percentile Confidence Limits Accelerated Bias Corrected Percentile Limits Other Methods for Constructing Confidence Intervals Transformations to Improve Bootstrap Intervals Parametric Confidence Intervals A Better Estimate of Bias Bootstrap Tests of Significance Balanced Bootstrap Sampling Applications of Bootstrapping in Biology Single Species Ecology Genetics, Evolution and Natural Selection Community Ecology Further Reading Chapter Summary Monte Carlo Methods Monte Carlo Tests Generalized Monte Carlo Tests Implicit Statistical Models Applications of Monte Carlo Methods in Biology Single Species Ecology Chapter Summary Some General Considerations Questions about Computer-Intensive Methods Power Number of Random Sets of Data Needed for a Test Determining a Randomization Distribution Exactly The number of replications for confidence intervals More Efficient Bootstrap Sampling Methods The Generation of Pseudo-Random Numbers The Generation of Random Permutations Chapter Summary One and Two Sample Tests The Paired Comparisons Design The One Sample Randomization Test The Two Sample Randomization Test Bootstrap Tests Randomizing Residuals Comparing the Variation in Two Samples A Simulation Study The Comparison of Two Samples on Multiple Measurements Further Reading Chapter Summary Exercises Analysis of Variance One Factor Analysis of Variance Tests for Constant Variance Testing for Mean Differences Using Residuals Examples of More Complicated Types of Analysis of Variance Procedures for Handling Unequal Group Variances Other Aspects of Analysis of Variance Further Reading Chapter Summary Exercises Regression Analysis Simple Linear Regression Randomizing Residuals Testing for a Non-Zero B Value Confidence Limits for B Multiple Linear Regression Alternative Randomization Methods with Multiple Regression Bootstrapping and Jackknifing with Regression Further Reading Chapter Summary Exercises Distance Matrices and Spatial Data Testing for Association between Distance Matrices The Mantel Test Sampling the Randomization Distribution Confidence Limits for Regression Coefficients The Multiple Mantel Test Other Approaches with More than Two Matrices Further Reading Chapter Summary Exercises Other Analyses on Spatial Data Spatial Data Analysis The Study of Spatial Point Patterns Mead's Randomization Test Tests for Randomness Based on Distances Testing for an Association between Two Point Patterns The Besag-Diggle Test Tests Using Distances between Points Testing for Random Marking Further Reading Chapter Summary Exercises Time Series Randomization and Time Series Randomization Tests for Serial Correlation Randomization T ests for Trend Randomization Tests for Periodicity Irregularly Spaced Series Tests on Times of Occurrence Discussion on Procedures for Irregular Series Bootstrap and Monte Carlo Tests Further Reading Chapter Summary Exercises Multivariate Data Univariate and Multivariate Tests Sample Means and Covariance Matrices Comparison of Sample Mean Vectors Chi-Squared Analyses for Count Data Principle Component Analysis and Other One Sample Methods Discriminant Function Analysis Further Reading Chapter Summary Exercises Survival and Growth Data Bootstrapping Survival Data Bootstrapping for Variable Selection Bootstrapping for Model Selection Group Comparisons Growth Data Further Reading Chapter Summary Exercises Non-Standard Situations The Construction of Tests in Non-Standard Situations Species Co-Occurrences on Islands An Alternative Generalized Monte Carlo Test Examining Time Changes in Niche Overlap Probing Multivariate Data with Random Skewers Ant Species Sizes in Europe Chapter Summary Bayesian Methods The Bayesian Approach to Data Analysis The Gibbs Sampler and Related Methods Biological Applications Further Reading Chapter Summary Exercises Conclusion and Final Comments Randomization Bootstrapping Monte Carlo Methods in General Classical versus Bayesian Inference Appendix Software for Computer Intensive Statistics References Index
Abstract Managed retreat, the purposeful relocation of households and assets to reduce flood risk, is gaining recognition as an essential adaptation strategy under intensifying climate change. Although often contested and perceived as socially or politically unacceptable, managed retreat holds potential to enhance the long‐term resilience of at‐risk communities. In Europe, however, it remains comparatively underexplored, with only a handful of European managed retreat cases that have been reported on in the academic literature. Here, we present a data set of European managed retreat cases, based on a multilingual review of academic and gray literature, as well as media articles. We found 44 implemented or planned cases of managed retreat across the continent, spanning 11 countries, ranging from the relocation of individual assets to more than 1,500 households. Through a cross‐case analysis, we identify five key factors that influence the process and outcomes of managed retreat projects: the compensation offered, the timing of the project, the engagement of the affected community, the leadership taken by the government, and the post‐relocation land use. Our analysis demonstrates that, although managed retreat remains less common than engineered protection measures, it is more prevalent in Europe than previously assumed and is already being practiced in varied forms. By uncovering common challenges and enabling conditions, this study offers transferable insights for advancing more anticipatory and strategically designed managed retreat initiatives, both within Europe and beyond.
Giardia duodenalis captured the attention of Leeuwenhoek in 1681 while he was examining his own diarrheal stool, but, ironically, it did not really gain attention as a human pathogen until the 1960s, when outbreaks were reported. Key technological advances, including in vitro cultivation, genomic and proteomic databases, and advances in microscopic and molecular approaches, have led to understand that this is a eukaryotic organism with a reduced genome rather than a truly premitochondriate eukaryote. SUMMARY Giardia duodenalis captured the attention of Leeuwenhoek in 1681 while he was examining his own diarrheal stool, but, ironically, it did not really gain attention as a human pathogen until the 1960s, when outbreaks were reported. Key technological advances, including in vitro cultivation, genomic and proteomic databases, and advances in microscopic and molecular approaches, have led to an understanding that this is a eukaryotic organism with a reduced genome rather than a truly premitochondriate eukaryote. This has included the discovery of mitosomes (vestiges of mitochondria), a transport system with many of the features of the Golgi apparatus, and even evidence for a sexual or parasexual cycle. Cell biology approaches have led to a better understanding of how Giardia survives with two nuclei and how it goes through its life cycle as a noninvasive organism in the hostile environment of the lumen of the host intestine. Studies of its immunology and pathogenesis have moved past the general understanding of the importance of the antibody response in controlling infection to determining the key role of the Th17 response. This work has led to understanding of the requirement for a balanced host immune response that avoids the extremes of an excessive response with collateral damage or one that is unable to clear the organism. This understanding is especially important in view of the remarkable ranges of early manifestations, which range from asymptomatic to persistent diarrhea and weight loss, and longer-term sequelae that include growth stunting in children who had no obvious symptoms and a high frequency of postinfectious irritable bowel syndrome (IBS).
Electric vehicles and renewable energy systems need batteries that charge quickly, last many years and still store a lot of energy, but current chemistries struggle to deliver all three. Inspired by electric fish that deliver bursts of current and birds that sleep with half their brains, we propose a hybrid battery concept called SwiftPulse. It combines sodium-ion cells that provide energy with niobium-oxide cells that accept high-power pulses. A pulse-based charger and a battery-management strategy rotate clusters of cells into rest so they can recover. We derive simple models of energy density, diffusion and capacity fade to show that a pack made mostly of sodium-ion modules with a smaller fraction of niobium-oxide modules could exceed 175 Wh per kg, endure more than ten thousand charge-discharge cycles and recharge to eighty percent in less than ten minutes. Simulations suggest that pulsed charging reduces ion buildup at the surface and slows degradation. We outline a roadmap for cell-level and module-level experiments and suggest integrating machine learning to adapt pulse parameters and rest scheduling. By blending ideas from biology, electrochemistry and data-driven control, this work points toward batteries that are safer, faster to charge and longer lasting.
Probiotics, as defined by the World Health Organization, are live microorganisms that, when consumed in sufficient quantities, provide health benefits to the host. Although some countries have approved specific probiotic species for use in food, safety concerns may still arise with individual strains. <i>Lacticaseibacillus paracasei</i> subsp. <i>paracasei</i> NTU 101 (NTU 101), isolated from the gut of healthy infants, has demonstrated various probiotic effects and shown safety in a prior 28-day animal feeding study. To further verify its safety and mitigate potential risks, we performed a comprehensive genotypic and phenotypic safety evaluation in accordance with the European Food Safety Authority guidelines for safety assessment through whole genome sequencing and related literature. In this research, minimum inhibitory concentration testing identified NTU 101’s resistance to chloramphenicol; however, subsequent gene analysis confirmed no associated risk of resistance. Assessments of safety, including biogenic amine content, hemolytic activity, mucin degradation, and D-lactic acid production, indicated a low level of risk. Additionally, a repeated-dose 90-day oral toxicity study in Sprague-Dawley rats revealed no toxicity at a dose of 2000 mg/kg body weight, further supporting the strain’s safety for consumption. Based on these comprehensive analyses, NTU 101 is considered safe for regular consumption as a health supplement.
Ongoing inflammation in the heart is positively correlated with adverse remodeling, characterized by elevated levels of cytokines that stimulate activation of cardiac fibroblasts. It was found that CaMKIIδ response to Ang II or TAC triggers the accumulation of ROS in cardiomyocytes, which subsequently stimulates NF-κB/NLRP3 and leads to an increase in IL-6, IL-1β, and IL-18. This is an important causative factor in the occurrence of adverse remodeling in heart failure. Sweroside is a biologically active natural iridoids extracted from Lonicerae Japonicae Flos. It shows potent anti-inflammatory and antioxidant activity in various cardiovascular diseases. In this study, we found that sweroside inhibited ROS-mediated NF-κB/NLRP3 in Ang II-treated cardiomyocytes by directly binding to CaMKIIδ. Knockdown of CaMKⅡδ abrogated the effect of sweroside regulation on NF-κB/NLRP3 in cardiomyocytes. AAV-CaMKⅡδ induced high expression of CaMKⅡδ in the myocardium of TAC/Ang II-mice, and the inhibitory effect of sweroside on TAC/Ang Ⅱ-induced elevation of NF-κB/NLRP3 was impeded. Sweroside showed significant inhibitory effects on CaMKIIδ/NF-κB/NLRP3 in cardiomyocytes from TAC/Ang Ⅱ-induced mice. This would be able to mitigate the adverse events of myocardial remodeling and contractile dysfunction at 8 weeks after the onset of the inflammatory response. Taken together, our findings have revealed the direct protein targets and molecular mechanisms by which sweroside improves heart failure, thereby supporting the further development of sweroside as a therapeutic agent for heart failure.
DNA methylation indicates the individual’s aging, so-called Epigenetic clocks, which will improve the research and diagnosis of aging diseases by investigating the correlation between methylation loci and human aging. Although this discovery has inspired many researchers to develop traditional computational methods to quantify the correlation and predict the chronological age, the performance bottleneck delayed access to the practical application. Since artificial intelligence technology brought great opportunities in research, we proposed a perceptron model integrating a channel attention mechanism named PerSEClock. The model was trained on 24,516 CpG loci that can utilize the samples from all types of methylation identification platforms and tested on 15 independent datasets against seven methylation-based age prediction methods. PerSEClock demonstrated the ability to assign varying weights to different CpG loci. This feature allows the model to enhance the weight of age-related loci while reducing the weight of irrelevant loci. The method is free to use for academics at www.dnamclock.com/#/original.
We are interested in the so-called "combined effect" of two different kinds of nonlinear terms for semilinear wave equations in one space dimension. Recently, the first result with the same formulation as in the higher dimensional case has been obtained if and only if the total integral of the initial speed is zero, namely Huygens' principle holds. In this paper, we extend the nonlinear term to the general form including the product type. Such model equations are extremely meaningful only in one space dimension because the most cases in higher dimensions possess the global-in-time existence of a classical solution in the general theory for nonlinear wave equations. It is also remarkable that our results on the lifespan estimates are partially better than those of the general theory. This fact tells us that there is a possibility to improve the general theory which was expected complete more than 30 years ago.
We prove the density property for generalized Calogero--Moser spaces with inner degrees of freedom. This allows us to describe the holomorphic automorphism group of these complex affine manifolds. These generalized Calogero--Moser spaces can also be understood as quiver varieties corresponding to moduli spaces of $\mathrm{SU}(2)$ instantons on a non-commutative $\mathbb{R}^4$.