@article{HermanussenSchefflerPulunganetal.2023, author = {Hermanussen, Michael and Scheffler, Christiane and Pulungan, Aman B. and Bandyopadhyay, Arup Ratan and Ghosh, Jyoti Ratan and {\"O}zdemir, Ay{\c{s}}eg{\"u}l and Koca {\"O}zer, Ba{\c{s}}ak and Musalek, Martin and Lebedeva, Lidia and Godina, Elena and Bogin, Barry and Tutkuviene, Janina and Budrytė, Milda and Gervickaite, Simona and Limony, Yehuda and Kirchengast, Sylvia and Buston, Peter and Groth, Detlef and R{\"o}sler, Antonia and Gasparatos, Nikolaos and Erofeev, Sergei and Novine, Masiar and Navazo, B{\´a}rbara and Dahinten, Silvia and Gomuła, Aleksandra and Nowak-Szczepańska, Natalia and Kozieł, Sławomir}, title = {Environment, social behavior, and growth}, series = {Human biology and public health}, volume = {1}, journal = {Human biology and public health}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {2748-9957}, doi = {10.52905/hbph2023.1.59}, pages = {14}, year = {2023}, abstract = {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.}, language = {en} } @article{GrothSchefflerHermanussen2023, author = {Groth, Detlef and Scheffler, Christiane and Hermanussen, Michael}, title = {Human growth data analysis and statistics - the 5th G{\"u}lpe International Student Summer School}, series = {Human biology and public health}, volume = {1}, journal = {Human biology and public health}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {2748-9957}, doi = {10.52905/hbph2023.1.70}, pages = {5}, year = {2023}, abstract = {The Summer School in G{\"u}lpe (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 G{\"u}lpe 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.}, language = {en} } @article{HakeBodenbergerGroth2023, author = {Hake, Tim and Bodenberger, Bernhard and Groth, Detlef}, title = {In Python available: St. Nicolas House Algorithm (SNHA) with bootstrap support for improved performance in dense networks}, series = {Human biology and public health}, volume = {1}, journal = {Human biology and public health}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {2748-9957}, doi = {10.52905/hbph2023.1.63}, pages = {16}, year = {2023}, abstract = {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.}, language = {en} } @article{NovineMattssonGroth2022, author = {Novine, Masiar and Mattsson, Cecilie Cordua and Groth, Detlef}, title = {Network reconstruction based on synthetic data generated by a Monte Carlo approach}, series = {Human biology and public health}, volume = {2021}, journal = {Human biology and public health}, number = {3, Summer School Supplement}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {2748-9957}, doi = {10.52905/hbph2021.3.26}, pages = {23}, year = {2022}, abstract = {Background: Network models are useful tools for researchers to simplify and understand investigated systems. Yet, the assessment of methods for network construction is often uncertain. Random resampling simulations can aid to assess methods, provided synthetic data exists for reliable network construction. Objectives: We implemented a new Monte Carlo algorithm to create simulated data for network reconstruction, tested the influence of adjusted parameters and used simulations to select a method for network model estimation based on real-world data. We hypothesized, that reconstructs based on Monte Carlo data are scored at least as good compared to a benchmark. Methods: Simulated data was generated in R using the Monte Carlo algorithm of the mcgraph package. Benchmark data was created by the huge package. Networks were reconstructed using six estimator functions and scored by four classification metrics. For compatibility tests of mean score differences, Welch's t-test was used. Network model estimation based on real-world data was done by stepwise selection. Samples: Simulated data was generated based on 640 input graphs of various types and sizes. The real-world dataset consisted of 67 medieval skeletons of females and males from the region of Refshale (Lolland) and Nordby (Jutland) in Denmark. Results: Results after t-tests and determining confidence intervals (CI95\%) show, that evaluation scores for network reconstructs based on the mcgraph package were at least as good compared to the benchmark huge. The results even indicate slightly better scores on average for the mcgraph package. Conclusion: The results confirmed our objective and suggested that Monte Carlo data can keep up with the benchmark in the applied test framework. The algorithm offers the feature to use (weighted) un- and directed graphs and might be useful for assessing methods for network construction.}, language = {en} } @article{WilkeBoekerMummetal.2022, author = {Wilke, Liza and Boeker, Sonja and Mumm, Rebecca and Groth, Detlef}, title = {The Social status influences human growth}, series = {Human biology and public health}, volume = {2021}, journal = {Human biology and public health}, number = {3, Summer School Supplement}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {2748-9957}, doi = {10.52905/hbph2021.3.22}, pages = {9}, year = {2022}, abstract = {Background: In the animal kingdom body size is often linked to dominance and subsequently the standing in social hierarchy. Similarly, human growth has been associated and linked to socioeconomic factors, including one's social status. This has already been proposed in the early 1900s where data on young German school girls from different social strata have been compared. Objectives: This paper aims to summarize and analyze these results and make them accessible for non-German speakers. The full English translation of the historic work of Dikanski (Dikanski, 1914) is available as a supplement. Further, this work aims to compare the historical data with modern references, to test three hypotheses: (1) higher social class is positively associated with body height and weight, (2) affluent people from the used historical data match modern references in weight and height and (3) weight distributions are skewed in both modern and historical populations. Methods: Comparison of historical data from 1914 with WHO and 1980s German data. The data sets, for both body weight and height for 6.0- and 7.0-year-old girls, were fitted onto centile curves and quantile correlation coefficients were calculated. Results: In historical data social status is positively associated with body height and weight while both are also normally distributed, which marks a significant difference to modern references. Conclusion: Social status is positively associated with height, signaling social dominance, making children of affluent classes taller. Children from the historical data do not reach the average height of modern children, even under the best environmental conditions. The children of the upper social class were not skewed in weight distribution, although they had the means to become as obese as modern children.}, language = {en} } @article{HermanussenGrothScheffler2022, author = {Hermanussen, Michael and Groth, Detlef and Scheffler, Christiane}, title = {Human growth data analyses and statistics}, series = {Human biology and public health}, volume = {2021}, journal = {Human biology and public health}, number = {3, Summer School Supplement}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {2748-9957}, doi = {10.52905/hbph2021.3.29}, pages = {4}, year = {2022}, abstract = {Students learn by repetition. Repetition is essential, but repetition needs questioning, and questioning the repertoire belongs to the essential tasks of student education. Guiding students to questioning was and is our prime motive to offer our International Student Summer Schools. The data were critically discussed among the students, in the twilight of Just So Stories, common knowledge, and prompted questioning of contemporary solutions. For these schools, the students bring their own data, carry their preliminary concepts, and in group discussions, they may have to challenge these concepts. Catch-up growth is known to affect long bone growth, but different opinions exist to what extent it also affects body proportions. Skeletal age and dental development are considered appropriate measures of maturation, but it appears that both system develop independently and are regulated by different mechanisms. Body weight distributions are assumed to be skewed, yet, historic data disproved this assumption. Many discussions focused on current ideas of global growth standards as a common yardstick for all populations world-wide, with new statistical tools being developed including network reconstruction and evaluation of the reconstructs to determine the confidence of graph prediction methods.}, language = {en} } @article{HoangGryzikHoppeetal.2022, author = {Hoang, Yen and Gryzik, Stefanie and Hoppe, Ines and Rybak, Alexander and Sch{\"a}dlich, Martin and Kadner, Isabelle and Walther, Dirk and Vera, Julio and Radbruch, Andreas and Groth, Detlef and Baumgart, Sabine and Baumgrass, Ria}, title = {PRI: Re-analysis of a public mass cytometry dataset reveals patterns of effective tumor treatments}, series = {Frontiers in immunology}, volume = {13}, journal = {Frontiers in immunology}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1664-3224}, doi = {10.3389/fimmu.2022.849329}, pages = {9}, year = {2022}, abstract = {Recently, mass cytometry has enabled quantification of up to 50 parameters for millions of cells per sample. It remains a challenge to analyze such high-dimensional data to exploit the richness of the inherent information, even though many valuable new analysis tools have already been developed. We propose a novel algorithm "pattern recognition of immune cells (PRI)" to tackle these high-dimensional protein combinations in the data. PRI is a tool for the analysis and visualization of cytometry data based on a three or more-parametric binning approach, feature engineering of bin properties of multivariate cell data, and a pseudo-multiparametric visualization. Using a publicly available mass cytometry dataset, we proved that reproducible feature engineering and intuitive understanding of the generated bin plots are helpful hallmarks for re-analysis with PRI. In the CD4(+)T cell population analyzed, PRI revealed two bin-plot patterns (CD90/CD44/CD86 and CD90/CD44/CD27) and 20 bin plot features for threshold-independent classification of mice concerning ineffective and effective tumor treatment. In addition, PRI mapped cell subsets regarding co-expression of the proliferation marker Ki67 with two major transcription factors and further delineated a specific Th1 cell subset. All these results demonstrate the added insights that can be obtained using the non-cluster-based tool PRI for re-analyses of high-dimensional cytometric data.}, language = {en} } @misc{HermanussenSchefflerMartinetal.2021, author = {Hermanussen, Michael and Scheffler, Christiane and Martin, Lidia and Groth, Detlef and Waxmonsky, James G. and Swanson, James and Nowak-Szczepanska, Natalia and Gomula, Aleksandra and Apanasewicz, Anna and Konarski, Jan M. and Malina, Robert M. and Bartkowiak, Sylwia and Lebedeva, Lidia and Suchomlinov, Andrej and Konstantinov, Vsevolod and Blum, Werner and Limony, Yehuda and Chakraborty, Raja and Kirchengast, Sylvia and Tutkuviene, Janina and Jakimaviciene, Egle Marija and Cepuliene, Ramune and Franken, Daniel and Navazo, B{\´a}rbara and Moelyo, Annang G. and Satake, Takashi and Koziel, Slawomir}, title = {Growth, Nutrition and Economy}, series = {Human Biology and Public Health}, volume = {2021}, journal = {Human Biology and Public Health}, number = {1}, editor = {Scheffler, Christiane and Koziel, Slawomir and Hermanussen, Michael and Bogin, Barry}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {2748-9957}, doi = {10.52905/hbph.v1.1}, pages = {1 -- 13}, year = {2021}, abstract = {Twenty-three scientists met at Krobielowice, Poland to discuss the role of growth, nutrition and economy on body size. Contrasting prevailing concepts, re-analyses of studies in Indonesian and Guatemalan school children with high prevalence of stunting failed to provide evidence for an association between nutritional status and body height. Direct effects of parental education on growth that were not transmitted via nutrition were shown in Indian datasets using network analysis and novel statistical methods (St. Nicolas House Analysis) that translate correlation matrices into network graphs. Data on Polish children suggest significant impact of socioeconomic sensitivity on child growth, with no effect of maternal money satisfaction. Height and maturation tempo affect the position of a child among its peers. Correlations also exist between mood disorders and height. Secular changes in height and weight varied across decades independent of population size. Historic and recent Russian data showed that height of persons whose fathers performed manual work were on average four cm shorter than persons whose fathers were high-degree specialists. Body height, menarcheal age, and body proportions are sensitive to socioeconomic variables. Additional topics included delayed motherhood and its associations with newborn size; geographic and socioeconomic indicators related to low birth weight, prematurity and stillbirth rate; data on anthropometric history of Brazil, 1850-1950; the impact of central nervous system stimulants on the growth of children with attention-deficit/hyperactivity disorder; and pituitary development and growth hormone secretion. Final discussions debated on reverse causality interfering between social position, and adolescent growth and developmental tempo.}, language = {en} } @article{SchefflerRogolIancuetal.2021, author = {Scheffler, Christiane and Rogol, Alan D. and Iancu, Mirela and Hanc, Tomasz and Moelyo, Annang Giri and Suchomlinov, Andrej and Lebedeva, Lidia and Limony, Yehuda and Musalek, Martin and Veldre, Gudrun and Godina, Elena Z. and Kirchengast, Sylvia and Mumm, Rebekka and Groth, Detlef and Tutkuviene, Janina and B{\"o}ker, Sonja and Ozer, Basak Koca and Navazo, Barbara and Spake, Laure and Koziel, Slawomir and Hermanussen, Michael}, title = {Growth during times of fear and emotional stress}, series = {Human biology and public health}, journal = {Human biology and public health}, number = {2}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {2748-9957}, doi = {10.52905/hbph.v2.15}, year = {2021}, abstract = {Twenty-one scientists met for this year's virtual conference on Auxology held at the University Potsdam, Germany, to discuss child and adolescent growth during times of fear and emotional stress. Growth within the broad range of normal for age and sex is considered a sign of good general health whereas fear and emotional stress can lead to growth faltering. Stunting is a sign of social disadvantage and poor parental education. Adverse childhood experiences affect child development, particularly in families with low parental education and low socioeconomic status. Negative effects were also shown in Indian children exposed prenatally and in early postnatal life to the cyclone Aila in 2009. Distrust, fears and fake news regarding the current Corona pandemic received particular attention though the effects generally appeared weak. Mean birth weight was higher; rates of low, very and extremely low birth weight were lower. Other topics discussed by the participants, were the influences of economic crises on birth weight, the measurement of self-confidence and its impact on growth, the associations between obesity, peer relationship, and behavior among Turkish adolescents, height trends in Indonesia, physiological neonatal weight loss, methods for assessing biological maturation in sportsmen, and a new method for skeletal age determination. The participants also discussed the association between acute myocardial infarction and somatotype in Estonia, rural-urban growth differences in Mongolian children, socio-environmental conditions and sexual dimorphism, biological mortality bias, and new statistical techniques for describing inhomogeneity in the association of bivariate variables, and for detecting and visualizing extensive interactions among variables.}, language = {en} } @article{MartinDorjeeGrothetal.2020, author = {Martin, Lidia and Dorjee, Binu and Groth, Detlef and Scheffler, Christiane}, title = {Positive influence of parental education on growth of children}, series = {Journal of biological and clinical anthropology : Anthropologischer Anzeiger}, volume = {77}, journal = {Journal of biological and clinical anthropology : Anthropologischer Anzeiger}, number = {5}, publisher = {Schweizerbart science publishers}, address = {Stuttgart}, issn = {0003-5548}, doi = {10.1127/anthranz/2020/1177}, pages = {375 -- 387}, year = {2020}, abstract = {In nature, dominance is often shown by body size; even in humans many studies report that social status is associated with body height. In today's society, educational status is an important factor for social classification. Since growing children do not have their own educational or social status, they are often affected by the status of their parents. Therefore, the question appears, whether parental educational status measurably affects the growth of a child. If so, is this explainable by the nutritional factors? To test this hypothesis, seven different Indian data sets where reexamined using the St. Nicolas House Analysis. The results show a direct association between parental education and body height (hSDS) of the child, but there was no influence of parental education on the nutritional status. We conclude that education has a direct effect on height that is not mediated via nutrition.}, language = {en} }