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Background: Assessing short-term growth in humans is still fraught with difficulties. Especially when looking for small variations and increments, such as mini growth spurts, high precision instruments or frequent measurements are necessary. Daily measurements however require a lot of effort, both for anthropologists and for the subjects. Therefore, new sophisticated approaches are needed that reduce fluctuations and reveal underlying patterns.
Objectives: Changepoints are abrupt variations in the properties of time series data. In the context of growth, such variations could be variation in mean height. By adjusting the variance and using different growth models, we assessed the ability of changepoint analysis to analyse short-term growth and detect mini growth spurts.
Sample and Methods: We performed Bayesian changepoint analysis on simulated growth data using the bcp package in R. Simulated growth patterns included stasis, linear growth, catch-up growth, and mini growth spurts. Specificity and a normalised variant of the Matthews correlation coefficient (MCC) were used to assess the algorithm’s performance. Welch’s t-test was used to compare differences of the mean.
Results: First results show that changepoint analysis can detect mini growth spurts. However, the ability to detect mini growth spurts is highly dependent on measurement error. Data preparation, such as ranking and rotating time series data, showed negligible improvements. Missing data was an issue and may affect the prediction quality of the classification metrics.
Conclusion: Changepoint analysis is a promising tool to analyse short-term growth. However, further optimisation and analysis of real growth data is needed to make broader generalisations.
Protein-protein-interactions play an important role in many cellular functions. Quantitative non-invasive techniques are applied in living cells to evaluate such interactions, thereby providing a broader understanding of complex biological processes. Fluorescence fluctuation spectroscopy describes a group of quantitative microscopy approaches for the characterization of molecular interactions at single cell resolution. Through the obtained molecular brightness, it is possible to determine the oligomeric state of proteins. This is usually achieved by fusing fluorescent proteins (FPs) to the protein of interest. Recently, the number of novel green FPs has increased, with consequent improvements to the quality of fluctuation-based measurements. The photophysical behavior of FPs is influenced by multiple factors (including photobleaching, protonation-induced "blinking" and long-lived dark states). Assessing these factors is critical for selecting the appropriate fluorescent tag for live cell imaging applications. In this work, we focus on novel green FPs that are extensively used in live cell imaging. A systematic performance comparison of several green FPs in living cells under different pH conditions using Number & Brightness (N & B) analysis and scanning fluorescence correlation spectroscopy was performed. Our results show that the new FP Gamillus exhibits higher brightness at the cost of lower photostability and fluorescence probability (pf), especially at lower pH. mGreenLantern, on the other hand, thanks to a very high pf, is best suited for multimerization quantification at neutral pH. At lower pH, mEGFP remains apparently the best choice for multimerization investigation. These guidelines provide the information needed to plan quantitative fluorescence microscopy involving these FPs, both for general imaging or for protein-protein-interactions quantification via fluorescence fluctuation-based methods.
Starch has been a convenient, economically important polymer with substantial applications in the food and processing industry. However, native starches present restricted applications, which hinder their industrial usage. Therefore, modification of starch is carried out to augment the positive characteristics and eliminate the limitations of the native starches. Modifications of starch can result in generating novel polymers with numerous functional and value-added properties that suit the needs of the industry. Here, we summarize the possible starch modifications in planta and outside the plant system (physical, chemical, and enzymatic) and their corresponding applications. In addition, this review will highlight the implications of each starch property adjustment.
Im Rahmen des PSI-Projekts wurde eine Lehrveranstaltung konzipiert, die Lehramtsstudierenden einen vertieften Einblick sowohl in den Ablauf von Forschung als auch eine Bearbeitung einer eigenen experimentellen Forschungsaufgabe ermöglichen soll. Anlass waren die Berücksichtigung eines „Wissens über Erkenntnisgewinnung in der Disziplin“ im Modell des „Erweiterten Fachwissens für den schulischen Kontext“ (PSI) sowie Erkenntnisse empirischer Studien, die die Relevanz eigener Forschungserfahrung für das Unterrichten naturwissenschaftlicher Erkenntnisgewinnungsprozesse zeigen. Hier stellen wir eine neue Lehrveranstaltung (4 SWS) vor, die den angehenden Lehrkräften Forschungserfahrung ermöglicht (Seminar und Praktikum). Die Lehrveranstaltung vermittelt Einblicke in Forschung und die „Natur der Naturwissenschaften“, ermöglicht das Durchführen eigener wissenschaftlicher und schulrelevanter Experimente und bietet eine angemessene Reflexion über die verschiedenen Kurselemente. Die Evaluationsergebnisse sind überwiegend positiv, zeigen aber auch, dass für die Studierenden die wahrgenommene Schulrelevanz und die fachdidaktischen Aspekte ein wichtiges Kriterium für die positive Bewertung sind.
Here, we demonstrate the utility of native membrane derived vesicles (nMVs) as tools for expeditious electrophysiological analysis of membrane proteins. We used a cell-free (CF) and a cell-based (CB) approach for preparing protein-enriched nMVs. We utilized the Chinese Hamster Ovary (CHO) lysate-based cell-free protein synthesis (CFPS) system to enrich ER-derived microsomes in the lysate with the primary human cardiac voltage-gated sodium channel 1.5 (hNaV1.5; SCN5A) in 3 h. Subsequently, CB-nMVs were isolated from fractions of nitrogen-cavitated CHO cells overexpressing the hNaV1.5. In an integrative approach, nMVs were micro-transplanted into Xenopus laevis oocytes. CB-nMVs expressed native lidocaine-sensitive hNaV1.5 currents within 24 h; CF-nMVs did not elicit any response. Both the CB- and CF-nMV preparations evoked single-channel activity on the planar lipid bilayer while retaining sensitivity to lidocaine application. Our findings suggest a high usability of the quick-synthesis CF-nMVs and maintenance-free CB-nMVs as ready-to-use tools for in-vitro analysis of electrogenic membrane proteins and large, voltage-gated ion channels.
Twenty-four scientists met for the annual Auxological conference held at Krobielowice castle, Poland, to discuss the diverse influences of the environment and of social behavior on growth following last year’s focus on growth and public health concerns (Hermanussen et al., 2022b). Growth and final body size exhibit marked plastic responses to ecological conditions. Among the shortest are the pygmoid people of Rampasasa, Flores, Indonesia, who still live under most secluded insular conditions. Genetics and nutrition are usually considered responsible for the poor growth in many parts of this world, but evidence is accumulating on the prominent impact of social embedding on child growth. Secular trends not only in the growth of height, but also in body proportions, accompany the secular changes in the social, economic and political conditions, with major influences on the emotional and educational circumstances under which the children grow up (Bogin, 2021). Aspects of developmental tempo and aspects of sports were discussed, and the impact of migration by the example of women from Bangladesh who grew up in the UK. Child growth was considered in particular from the point of view of strategic adjustments of individual size within the network of its social group. Theoretical considerations on network characteristics were presented and related to the evolutionary conservation of growth regulating hypothalamic neuropeptides that have been shown to link behavior and physical growth in the vertebrate species. New statistical approaches were presented for the evaluation of short term growth measurements that permit monitoring child growth at intervals of a few days and weeks.
Genomic and epigenomic determinants of heat stress-induced transcriptional memory in Arabidopsis
(2023)
Background
Transcriptional regulation is a key aspect of environmental stress responses. Heat stress induces transcriptional memory, i.e., sustained induction or enhanced re-induction of transcription, that allows plants to respond more efficiently to a recurrent HS. In light of more frequent temperature extremes due to climate change, improving heat tolerance in crop plants is an important breeding goal. However, not all heat stress-inducible genes show transcriptional memory, and it is unclear what distinguishes memory from non-memory genes. To address this issue and understand the genome and epigenome architecture of transcriptional memory after heat stress, we identify the global target genes of two key memory heat shock transcription factors, HSFA2 and HSFA3, using time course ChIP-seq.
Results
HSFA2 and HSFA3 show near identical binding patterns. In vitro and in vivo binding strength is highly correlated, indicating the importance of DNA sequence elements. In particular, genes with transcriptional memory are strongly enriched for a tripartite heat shock element, and are hallmarked by several features: low expression levels in the absence of heat stress, accessible chromatin environment, and heat stress-induced enrichment of H3K4 trimethylation. These results are confirmed by an orthogonal transcriptomic data set using both de novo clustering and an established definition of memory genes.
Conclusions
Our findings provide an integrated view of HSF-dependent transcriptional memory and shed light on its sequence and chromatin determinants, enabling the prediction and engineering of genes with transcriptional memory behavior.
Human growth data analysis and statistics – the 5th Gülpe International Student Summer School
(2023)
The Summer School in Gülpe (Ecological Station of the University of Potsdam) offers an exceptional learning opportunity for students to apply their knowledge and skills to real-world problems. With the guidance of experienced human biologists, statisticians, and programmers, students have the unique chance to analyze their own data and gain valuable insights. This interdisciplinary setting not only bridges different research areas but also leads to highly valuable outputs. The progress of students within just a few days is truly remarkable, especially when they are motivated and receive immediate feedback on their questions, problems, and results. The Summer School covers a wide range of topics, with this year’s focus mainly on two areas: understanding the impact of socioeconomic and physiological factors on human development and mastering statistical techniques for analyzing data such as changepoint analysis and the St. Nicolas House Analysis (SNHA) to visualize interacting variables. The latter technique, born out of the Summer School’s emphasis on gaining comprehensive data insights and understanding major relationships, has proven to be a valuable tool for researchers in the field. The articles in this special issue demonstrate that the Summer School in Gülpe stands as a testament to the power of practical learning and collaboration. Students who attend not only gain hands-on experience but also benefit from the expertise of professionals and the opportunity to engage with peers from diverse disciplines.
The St. Nicolas House Algorithm (SNHA) finds association chains of direct dependent variables in a data set. The dependency is based on the correlation coefficient, which is visualized as an undirected graph. The network prediction is improved by a bootstrap routine. It enables the computation of the empirical p-value, which is used to evaluate the significance of the predicted edges. Synthetic data generated with the Monte Carlo method were used to firstly compare the Python package with the original R package, and secondly to evaluate the predicted network using the sensitivity, specificity, balanced classification rate and the Matthew's correlation coefficient (MCC). The Python implementation yields the same results as the R package. Hence, the algorithm was correctly ported into Python. The SNHA scores high specificity values for all tested graphs. For graphs with high edge densities, the other evaluation metrics decrease due to lower sensitivity, which could be partially improved by using bootstrap,while for graphs with low edge densities the algorithm achieves high evaluation scores. The empirical p-values indicated that the predicted edges indeed are significant.
Keeping cool on hot days
(2023)
Long-lived organisms are likely to respond to a rapidly changing climate with behavioral flexibility. Animals inhabiting the arid parts of southern Africa face a particularly rapid rise in temperature which in combination with food and water scarcity places substantial constraints on the ability of animals to tolerate heat. We investigated how three species of African antelope-springbok Antidorcas marsupialis, kudu Tragelaphus strepsiceros and eland T. oryx-differing in body size, habitat preference and movement ecology, change their activity in response to extreme heat in an arid savanna. Serving as a proxy for activity, dynamic body acceleration data recorded every five minutes were analyzed for seven to eight individuals per species for the three hottest months of the year. Activity responses to heat during the hottest time of day (the afternoons) were investigated and diel activity patterns were compared between hot and cool days. Springbok, which prefer open habitat, are highly mobile and the smallest of the species studied, showed the greatest decrease in activity with rising temperature. Furthermore, springbok showed reduced mean activity over the 24 h cycle on hot days compared to cool days. Large-bodied eland seemed less affected by afternoon heat than springbok. While eland also reduced diurnal activity on hot days compared to cool days, they compensated for this by increasing nocturnal activity, possibly because their predation risk is lower. Kudu, which are comparatively sedentary and typically occupy shady habitat, seemed least affected during the hottest time of day and showed no appreciable difference in diel activity patterns between hot and cool days. The interplay between habitat preference, body size, movement patterns, and other factors seems complex and even sub-lethal levels of heat stress have been shown to impact an animal's long-term survival and reproduction. Thus, differing heat tolerances among species could result in a shift in the composition of African herbivore communities as temperatures continue to rise, with significant implications for economically important wildlife-based land use and conservation.