Die Temperaturabhängigkeit biologischer Prozesse / Temperature-Dependence of Biological Process

1979 ◽  
Vol 34 (5-6) ◽  
pp. 474-477
Author(s):  
K. Trindier
Keyword(s):  
Temperature Dependence ◽  
Variable Coefficient ◽  
Arrhenius Equation ◽  
Biological Process ◽  
Biological Processes ◽  
Temperature Variable

Abstract Temperature dependence of biological processes is described by the modified Arrhenius equation, in which the constant is replaced by a temperature-variable coefficient. The theoretical foun­dation for this replacement is given and experimentally verified.

scholarly journals Evaluating the Simple Arrhenius Equation for the Temperature Dependence of Complex Developmental Processes

2020 ◽  
Author(s):  
Joseph Crapse ◽  
Nishant Pappireddi ◽  
Meera Gupta ◽  
Stanislav Y. Shvartsman ◽  
Eric Wieschaus ◽  
...  
Keyword(s):  
Embryonic Development ◽  
Temperature Dependence ◽  
Developmental Stages ◽  
Arrhenius Equation ◽  
Arrhenius Plot ◽  
Fruit Fly ◽  
Biological Processes ◽  
Arrhenius Law ◽  
Multistep Reactions ◽  
Single Enzyme

SummaryThe famous Arrhenius equation is well motivated to describe the temperature dependence of chemical reactions but has also been used for complicated biological processes. Here, we evaluate how well the simple Arrhenius equation predicts complex multistep biological processes, using frog and fruit fly embryogenesis as two canonical models. We find the Arrhenius equation provides a good approximation for the temperature dependence of embryogenesis, even though individual developmental stages scale differently with temperature. At low and high temperatures, however, we observed significant departures from idealized Arrhenius Law behavior. When we model multistep reactions of idealized chemical networks we are unable to generate comparable deviations from linearity. In contrast, we find the single enzyme GAPDH shows non-linearity in the Arrhenius plot similar to our observations of embryonic development. Thus, we find that complex embryonic development can be well approximated by the simple Arrhenius Law and propose that the observed departure from this law results primarily from non-idealized individual steps rather than the complexity of the system.

scholarly journals Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Erica Ponzi ◽  
Magne Thoresen ◽  
Therese Haugdahl Nøst ◽  
Kajsa Møllersen
Keyword(s):  
Lung Cancer ◽  
Biological Process ◽  
Case Control ◽  
Integrative Analysis ◽  
Data Sources ◽  
Omics Data ◽  
Biological Processes ◽  
Blood Samples ◽  
Model Predictions

Abstract Background Cancer genomic studies often include data collected from several omics platforms. Each omics data source contributes to the understanding of the underlying biological process via source specific (“individual”) patterns of variability. At the same time, statistical associations and potential interactions among the different data sources can reveal signals from common biological processes that might not be identified by single source analyses. These common patterns of variability are referred to as “shared” or “joint”. In this work, we show how the use of joint and individual components can lead to better predictive models, and to a deeper understanding of the biological process at hand. We identify joint and individual contributions of DNA methylation, miRNA and mRNA expression collected from blood samples in a lung cancer case–control study nested within the Norwegian Women and Cancer (NOWAC) cohort study, and we use such components to build prediction models for case–control and metastatic status. To assess the quality of predictions, we compare models based on simultaneous, integrative analysis of multi-source omics data to a standard non-integrative analysis of each single omics dataset, and to penalized regression models. Additionally, we apply the proposed approach to a breast cancer dataset from The Cancer Genome Atlas. Results Our results show how an integrative analysis that preserves both components of variation is more appropriate than standard multi-omics analyses that are not based on such a distinction. Both joint and individual components are shown to contribute to a better quality of model predictions, and facilitate the interpretation of the underlying biological processes in lung cancer development. Conclusions In the presence of multiple omics data sources, we recommend the use of data integration techniques that preserve the joint and individual components across the omics sources. We show how the inclusion of such components increases the quality of model predictions of clinical outcomes.

scholarly journals Annotating proteins with generalized functional linkages

2008 ◽  
Vol 105 (46) ◽  
pp. 17700-17705 ◽  
Author(s):  
Richard Llewellyn ◽  
David S. Eisenberg
Keyword(s):  
Protein Function ◽  
Biological Process ◽  
Computational Method ◽  
Majority Voting ◽  
Target Protein ◽  
Biological Processes ◽  
Gene Products ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks

As genome sequencing outstrips the rate of high-quality, low-throughput biochemical and genetic experimentation, accurate annotation of protein function becomes a bottleneck in the progress of the biomolecular sciences. Most gene products are now annotated by homology, in which an experimentally determined function is applied to a similar sequence. This procedure becomes error-prone between more divergent sequences and can contaminate biomolecular databases. Here, we propose a computational method of assignment of function, termed Generalized Functional Linkages (GFL), that combines nonhomology-based methods with other types of data. Functional linkages describe pairwise relationships between proteins that work together to perform a biological task. GFL provides a Bayesian framework that improves annotation by arbitrating a competition among biological process annotations to best describe the target protein. GFL addresses the unequal strengths of functional linkages among proteins, the quality of existing annotations, and the similarity among them while incorporating available knowledge about the cellular location or individual molecular function of the target protein. We demonstrate GFL with functional linkages defined by an algorithm known as zorch that quantifies connectivity in protein–protein interaction networks. Even when using proteins linked only by indirect or high-throughput interactions, GFL predicts the biological processes of many proteins in Saccharomyces cerevisiae, improving the accuracy of annotation by 20% over majority voting.

scholarly journals Hidden in plain sight: What remains to be discovered in the eukaryotic proteome?

2018 ◽  
Author(s):  
Valerie Wood ◽  
Antonia Lock ◽  
Midori A. Harris ◽  
Kim Rutherford ◽  
Jürg Bähler ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Fission Yeast ◽  
Genome Sequencing ◽  
Large Scale ◽  
Biological Process ◽  
Blind Spot ◽  
Model Organisms ◽  
Biological Processes ◽  
Health And Disease

AbstractThe first decade of genome sequencing stimulated an explosion in the characterization of unknown proteins. More recently, the pace of functional discovery has slowed, leaving around 20% of the proteins even in well-studied model organisms without informative descriptions of their biological roles. Remarkably, many uncharacterized proteins are conserved from yeasts to human, suggesting that they contribute to fundamental biological processes. To fully understand biological systems in health and disease, we need to account for every part of the system. Unstudied proteins thus represent a collective blind spot that limits the progress of both basic and applied biosciences.We use a simple yet powerful metric based on Gene Ontology (GO) biological process terms to define characterized and uncharacterized proteins for human, budding yeast, and fission yeast. We then identify a set of conserved but unstudied proteins in S. pombe, and classify them based on a combination of orthogonal attributes determined by large-scale experimental and comparative methods. Finally, we explore possible reasons why these proteins remain neglected, and propose courses of action to raise their profile and thereby reap the benefits of completing the catalog of proteins’ biological roles.

scholarly journals The Contribution of the 20S Proteasome to Proteostasis

Biomolecules ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 190 ◽  
Author(s):  
Fanindra Kumar Deshmukh ◽  
Dana Yaffe ◽  
Maya Olshina ◽  
Gili Ben-Nissan ◽  
Michal Sharon
Keyword(s):  
Biological Process ◽  
Intrinsically Disordered Protein ◽  
26S Proteasome ◽  
20S Proteasome ◽  
Biological Processes ◽  
Neuronal Communication ◽  
Intrinsically Disordered ◽  
Disordered Protein ◽  
The Core ◽  
Functional Aspects

The last decade has seen accumulating evidence of various proteins being degraded by the core 20S proteasome, without its regulatory particle(s). Here, we will describe recent advances in our knowledge of the functional aspects of the 20S proteasome, exploring several different systems and processes. These include neuronal communication, post-translational processing, oxidative stress, intrinsically disordered protein regulation, and extracellular proteasomes. Taken together, these findings suggest that the 20S proteasome, like the well-studied 26S proteasome, is involved in multiple biological processes. Clarifying our understanding of its workings calls for a transformation in our perception of 20S proteasome-mediated degradation—no longer as a passive and marginal path, but rather as an independent, coordinated biological process. Nevertheless, in spite of impressive progress made thus far, the field still lags far behind the front lines of 26S proteasome research. Therefore, we also touch on the gaps in our knowledge of the 20S proteasome that remain to be bridged in the future.

scholarly journals An Integrated Approach to the Biological Reactor–Sedimentation Tank System

Resources ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 94 ◽  
Author(s):  
Serena Conserva ◽  
Fabio Tatti ◽  
Vincenzo Torretta ◽  
Navarro Ferronato ◽  
Paolo Viotti
Keyword(s):  
Activated Sludge ◽  
Biological Process ◽  
Wastewater Treatment Plants ◽  
Great Influence ◽  
Integrated Approach ◽  
Biological Processes ◽  
Sludge Characteristics ◽  
Activated Sludge System ◽  
Proposed Model ◽  
Tank System

Secondary clarifiers are demanded to separate solids created in activated sludge biological processes to achieve both a clarified effluent and to manage the biological processes itself. Indeed, the biological process may influence the sludge characteristics, and conversely, the settling efficiency of the sedimentation basin plays an important role on the biological process in the activated sludge system. The proposed model represents a tool for better addressing the design and management of activated sludge system in wastewater treatment plants. The aim is to develop a numerical model which takes into account both the conditions in the biological reactor and the sludge characteristics coupled to the hydrodynamic behavior of a clarifier tank. The obtained results show that the different conditions in the reactor exert a great influence on the sedimentation efficiency.

scholarly journals A study on municipal leachate treatment through a combination of biological processes and ozonation

2019 ◽  
Vol 276 ◽  
pp. 06030 ◽  
Author(s):  
Iva Yenis Septiariva ◽  
Tri Padmi ◽  
Enri Damanhuri ◽  
Qomarudin Helmy
Keyword(s):  
Treatment Process ◽  
Biological Process ◽  
Cod Removal ◽  
Batch Reactors ◽  
Biological Processes ◽  
Solid Waste Disposal ◽  
Leachate Treatment ◽  
Pre Treatment ◽  
Aerobic And Anaerobic ◽  
Post Treatment Process

Landfill is the most commonly method of municipal solid waste disposal in many countries. This practice has great potential to produce highly polluted leachate in massive quantities, which can cause environmental contamination. Biological processes are known as a common method to treat municipal leachate however this process alone in is less effective, especially in reducing the concentration of organic pollutants (BOD5/COD ratio). Leachate properties are site-specific and greatly influenced by landfill age. This study focuses on the investigation of treatment methods that can increase the extent of leachate biodegradability by applying an ozone concentration of 2.5 mg/L with up to 360 minutes of contact time. In this study, batch reactors were used and operated in anaerobic and aerobic conditions. The leachate used here represents both young and old leachate. Several treatment combinations were compared: Variation I (a combination of biologically aerobic and anaerobic process), Variation II (ozonation included as a pre-treatment process), and Variation III (ozonation was included as a post-treatment process). The results suggest that the BOD5/COD ratios of young and old leachates were 0.58 and 0.21, respectively. The COD removal for a young and old leachate treatment by biological process alone was 96.8% and 50.8%, respectively. Meanwhile, a combination of anaerobic-ozonation-aerobic processes gave better COD removal. Ozonation had a significant effect on the old leachate treatment, where the COD removal rose from 50.8% to 75%. Ozonation is a type of technology that can be applied to a subsequence treatment of biological processes in order to elevate the COD removal efficiency.

scholarly journals A pseudotemporal causality approach to identifying miRNA–mRNA interactions during biological processes

2020 ◽  
Author(s):  
Andres M Cifuentes-Bernal ◽  
Vu Vh Pham ◽  
Xiaomei Li ◽  
Lin Liu ◽  
Jiuyong Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Progression ◽  
Cancer Metastasis ◽  
Biological Process ◽  
Supplementary Information ◽  
Biological Processes ◽  
Mesenchymal Transition ◽  
Novel Approach ◽  
Static Information ◽  
Temporal Aspect

Abstract Motivation microRNAs (miRNAs) are important gene regulators and they are involved in many biological processes, including cancer progression. Therefore, correctly identifying miRNA–mRNA interactions is a crucial task. To this end, a huge number of computational methods has been developed, but they mainly use the data at one snapshot and ignore the dynamics of a biological process. The recent development of single cell data and the booming of the exploration of cell trajectories using ‘pseudotime’ concept have inspired us to develop a pseudotime-based method to infer the miRNA–mRNA relationships characterizing a biological process by taking into account the temporal aspect of the process. Results We have developed a novel approach, called pseudotime causality, to find the causal relationships between miRNAs and mRNAs during a biological process. We have applied the proposed method to both single cell and bulk sequencing datasets for Epithelia to Mesenchymal Transition, a key process in cancer metastasis. The evaluation results show that our method significantly outperforms existing methods in finding miRNA–mRNA interactions in both single cell and bulk data. The results suggest that utilizing the pseudotemporal information from the data helps reveal the gene regulation in a biological process much better than using the static information. Availability and implementation R scripts and datasets can be found at https://github.com/AndresMCB/PTC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Review on biological process of soil improvement in the mitigation of liquefaction in sandy soil

2018 ◽  
Vol 250 ◽  
pp. 01017 ◽  
Author(s):  
Abubakar Sadiq Muhammed ◽  
Khairul Anuar Kassim ◽  
Muttaqa Uba Zango
Keyword(s):  
Biological Process ◽  
Soil Improvement ◽  
Emerging Technology ◽  
Biological Processes ◽  
Reagent Concentration ◽  
Calcite Precipitation ◽  
Cyclic Resistance ◽  
Environmental Friendly ◽  
Long Time ◽  
Cyclic Resistance Ratio

Recently, the concept of using biological process in soil improvement otherwise called bio-mediated soil improvement technique has shown greater prospects in the mitigation of liquefiable soils. It is an environmental friendly technique that has generated great interest to geotechnical engineers. This paper presents a review on the microorganism responsible for the biological processes in soil improvement system, factors that affect biological process, identifying the mechanism of liquefaction and commonly adopted method to mitigate liquefaction. Next, the effect of microbial induced calcite precipitation (MICP) on the strength and cyclic response were also analyzed, where it was identified that higher cementation level leads to formation of larger sized calcite crystals which in turn leads to the improved shear strength, stiffness and cyclic resistance ratio of the soil. However, the effects of various bacteria, cementation reagent concentrations amongst other factors were not fully explored in most of the studies. Finally, some of the challenges that lay ahead for the emerging technology are optimizing treatment factors (bacteria and cementation reagent concentration), upscaling process, training of researchers/technologist and long – time durability of the improved soils.

Change of particle structure of sewage sludges during mechanical and biological processes with regard to the dewatering result

1997 ◽  
Vol 36 (4) ◽  
pp. 293-306 ◽  
Author(s):  
Thomas Nellenschulte ◽  
Rolf Kayser
Keyword(s):  
Total Mass ◽  
High Performance ◽  
Suspended Solids ◽  
Biological Process ◽  
Waste Activated Sludge ◽  
Biological Processes ◽  
Small Particles ◽  
Particle Structure ◽  
Integral Property ◽  
Wastewater Sludges

Particle size seems to be the most important parameter, to describe the dewatering behaviour and result of sludges. But there are many other parameters, which can influence the dewatering result. The dewatering result of a sludge depends on the type of sludge, the mechanical and biological process. Out of the numerous parameters to characterize wastewater sludges five were selected, which describe the properties of the particulate matter. These parameters are the suspended solids (SS), the volatile suspended solids (VSS), the density of the particles (ρ), the fraction of small particles (fines) and a new parameter, called φ-value, which is the ratio of the mass of waste activated sludge to the total mass of sludge. The tested sludges were analysed for the Zeta Potential, but there could not be found a correlation between this parameter and the dewatering result. Combining the parameters in a model led to an overall sludge parameter, the so-called “Integral Property Parameter, fE”. A correlation between the fE-values and the dewatering results of municipal sludges (n = 49) can be found. A proposal was made to transfer the experimental results to a full scale dewatering process with high performance centrifuges.

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