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Background Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. Description BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. Conclusions BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License.

The mitotic checkpoint prevents a eukaryotic cell from commencing to separate its replicated genome into two daughter cells (anaphase) until all of its chromosomes are properly aligned on the metaphase plate, with the two copies of each chromosome attached to opposite poles of the mitotic spindle. The mitotic checkpoint is exquisitely sensitive in that a single unaligned chromosome, 1 of a total of ∼50, is sufficient to delay progression into anaphase; however, when the last chromosome comes into alignment on the metaphase plate, the mitotic checkpoint is quickly satisfied, and the replicated chromosomes are rapidly partitioned to opposite poles of the dividing cell. The mitotic checkpoint is also curious in the sense that, before metaphase alignment, chromosomes that are not being pulled in opposite directions by the mitotic spindle activate the checkpoint, but during anaphase, these same tensionless chromosomes can no longer activate the checkpoint. These and other puzzles associated with the mitotic checkpoint are addressed by a proposed molecular mechanism, which involves two positive feedback loops that create a bistable response of the checkpoint to chromosomal tension.

The mitotic checkpoint prevents a eukaryotic cell from commencing to separate its replicated genome into two daughter cells (anaphase) until all of its chromosomes are properly aligned on the metaphase plate, with the two copies of each chromosome attached to opposite poles of the mitotic spindle. The mitotic checkpoint is exquisitely sensitive in that a single unaligned chromosome, 1 of a total of ∼50, is sufficient to delay progression into anaphase; however, when the last chromosome comes into alignment on the metaphase plate, the mitotic checkpoint is quickly satisfied, and the replicated chromosomes are rapidly partitioned to opposite poles of the dividing cell. The mitotic checkpoint is also curious in the sense that, before metaphase alignment, chromosomes that are not being pulled in opposite directions by the mitotic spindle activate the checkpoint, but during anaphase, these same tensionless chromosomes can no longer activate the checkpoint. These and other puzzles associated with the mitotic checkpoint are addressed by a proposed molecular mechanism, which involves two positive feedback loops that create a bistable response of the checkpoint to chromosomal tension.

Precise regulation of cell cycle events by the Cdk-control network is essential for cell proliferation and the perpetuation of life. The unidirectionality of cell cycle progression is governed by several critical irreversible transitions: the G1-to-S transition, the G2-to-M transition, and the M-to-G1 transition. Recent experimental and theoretical evidence has pulled into question the consensus view that irreversible protein degradation causes the irreversibility of those transitions. A new view has started to emerge, which explains the irreversibility of cell cycle transitions as a consequence of systems-level feedback rather than of proteolysis. This thesis applies mathematical modelling approaches to test this proposal for the Mto- G1 transition, which consists of two consecutive irreversible substeps: the metaphase-to-anaphase transition, and mitotic exit. The main objectives of the present work were: (i) to develop deterministic models to identify the essential molecular feedback loops and to examine their roles in the irreversibility of the M-to-G1 transition; (ii) to present a straightforward and reliable workflow to translate deterministic models of reaction networks into stochastic models; (iii) to explore the effects of noise on the cell cycle transitions using stochastic models, and to compare the deterministic and the stochastic approaches. In the first part of this thesis, I constructed a simplified deterministic model of the metaphase-to-anaphase transition, which is mainly regulated by the spindle assembly checkpoint (the SAC). Based on the essential feedback loops causing the bistability of the transition, this deterministic model provides explanations for three open questions regarding the SAC: Why is the SAC not reactivated when the kinetochore tension decreases to zero at anaphase onset? How can a single unattached kinetochore keep the SAC active? How is the synchronized and abrupt destruction of cohesin triggered? This deterministic model was then translated into a stochastic model of the SAC by treating the kinetochore microtubule attachment at prometaphase as a noisy process. The stochastic model was analyzed and simulation results were compared to the experimental data, with the aim of explaining the mitotic timing regulation by the SAC. Our model works remarkably well in qualitatively explaining experimental key findings and also makes testable predictions for different cell lines with very different number of chromosomes. The noise generated from the chemical interactions was found to only perturb the transit timing of the mitotic events, but not their ultimate outcomes: all cells eventually undergo anaphase, however, the time required to satisfy the SAC differs between cells due to stochastic effects. In the second part of the thesis, stochastic models of mitotic exit were created for two model organisms, budding yeast and mammalian cells. I analyzed the role of noise in mitotic exit at both the single-cell and the population level. Stochastic time series simulations of the models are able to explain the phenomenon of reversible mitotic exit, which is observed under specific experimental conditions in both model organisms. In spite of the fact that the detailed molecular networks of mitotic exit are very different in budding yeast and mammalian cells, their dynamic properties are similar. Importantly, bistability of the transitions is successfully captured also in the stochastic models. This work strongly supports the hypothesis that uni-directional cell cycle progression is a consequence of systems-level feedback in the cell cycle control system. Systems-level feedback creates alternative steady states, which allows cells to accomplish irreversible transitions, such as the M-to-G1 transition studied here. We demonstrate that stochastic models can serve as powerful tools to capture and study the heterogeneity of dynamical features among individual cells. In this way, stochastic simulations not only complement the deterministic approach, but also help to obtain a better understanding of mechanistic aspects. We argue that the effects of noise and the potential needs for stochastic simulations should not be overlooked in studying dynamic features of biological systems.

Enuo Wang verfolgt die neuesten Entwicklungen in der chinesisch-deutschen Geschäftskommunikation und bietet uns in ihrem vorliegenden Buch eine interaktive Perspektive auf diesen wichtigen und noch immer von vielen Missverständnissen geprägten Bereich interkultureller Kommunikation.

Online-learning stress poses a significant challenge to the sustainability of higher education. The present study employs mixed methods to propose a conceptual process model that depicts the mechanism of online-learning stress of college students. The result of the qualitative study indicates 11 influential factors of online-learning stress, 10 manifestations of online-learning stress (OS), and three learning performance outcomes of OS (LP) through in-depth interviews with 15 college students. The result of a quantitative study on 159 online surveys implies that the influential factors of online-learning stress could be further categorized into learner competence and commitment (LC), course design reasonability (CD), and social support (SS). In addition, the results of the structural equation model (SEM) confirm the negative impact of LC and CD on OS, as well as OS on LP. However, the negative effect of SS on OS is unsupported. The study contributes to both OS theory development and online-learning and teaching in higher education.

High-nitrogen austenitic stainless steels (HNASS) require compositional strategies that simultaneously maximize corrosion resistance and microstructural stability while suppressing delta (δ) ferrite and deleterious precipitates. Here, an explainable multi-objective design workflow is developed that couples thermodynamic descriptors from the Calculation of Phase Diagrams (CALPHAD) approach-using both equilibrium and Scheil solidification calculations-with machine learning surrogate models, random forest (RF) and Extreme Gradient Boosting (XGBoost), trained on 60,480 compositions in the Fe-C-N-Cr-Mn-Mo-Ni-Si space. The physics-informed feature set comprises phase fractions; transformation and precipitation temperatures for δ-ferrite, chromium nitride (Cr N), sigma (σ) phase and M C carbides; liquidus and solidus temperatures; and the pitting-resistance equivalent number (PREN). The RF model achieves consistently low prediction errors, with a PREN root-mean-square error (RMSE) of ≈0.004, and exhibits strong generalization. Shapley additive explanations (SHAP) reveal metallurgically consistent trends: increasing nitrogen (N) suppresses δ-ferrite and promotes Cr N; carbon (C) promotes M C ; molybdenum (Mo) promotes the σ-phase; and C and silicon (Si) widen the freezing range. Using the trained surrogate as the objective evaluator, the non-dominated sorting genetic algorithm III (NSGA-III) builds Pareto fronts that minimize the δ-ferrite range, Cr N, σ-phase, M C and the freezing range (ΔT) while maximizing PREN. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is then applied to rank the Pareto-optimal candidates and to select compositions that combine elevated PREN with controlled precipitation windows. This workflow is efficient, reproducible and interpretable and provides actionable composition candidates together with a transferable methodology for data-driven stainless steel design.

Eczema is frequently the first manifestation of an atopic diathesis and alteration in the diversity of gut microbiota has been reported in infants with eczema. To identify specific bacterial communities associated with eczema, we conducted a case-control study of 50 infants with eczema (cases) and 51 healthy infants (controls). We performed high-throughput sequencing for V3-V4 hypervariable regions of the 16S rRNA genes from the gut fecal material. A total of 12,386 OTUs (operational taxonomic units) at a 97% similarity level were obtained from the two groups, and we observed a difference in taxa abundance, but not the taxonomic composition, of gut microbiota between the two groups. We identified four genera enriched in healthy infants: Bifidobacterium, Megasphaera, Haemophilus and Streptococcus; and five genera enriched in infants with eczema: Escherichia/Shigella, Veillonella, Faecalibacterium, Lachnospiraceae incertae sedis and Clostridium XlVa. Several species, such as Faecalibacterium prausnitzii and Ruminococcus gnavus, that are known to be associated with atopy or inflammation, were found to be significantly enriched in infants with eczema. Higher abundance of Akkermansia muciniphila in eczematous infants might reduce the integrity of intestinal barrier function and therefore increase the risk of developing eczema. On the other hand, Bacteroides fragilis and Streptococcus salivarius, which are known for their anti-inflammatory properties, were less abundant in infants with eczema. The observed differences in genera and species between cases and controls in this study may provide insight into the link between the microbiome and eczema risk.

Background Brief lifestyle interventions targeting diet and physical activity play a critical role in the prevention and management of noncommunicable diseases (NCDs). However, healthcare providers often report feeling inadequately prepared to deliver such interventions, as there is limited guidance available to inform their practice. Objective To define and describe the concept of “brief lifestyle intervention” within the context of NCDs. Design A concept analysis. Methods A systematic literature review, including PubMed, Embase, The Cochrane Library, Web of Science, CINAHL, PsycINFO and Scopus, was conducted from inception to 11 August 2023 to yield studies related to brief lifestyle interventions, encompassing brief dietary and physical activity interventions. The Walker and Avant’s method was used to analyse the extracted data to determine the defining attributes, antecedents and consequences of the term “brief lifestyle intervention”. Results The 49 eligible studies were finally included, and the findings were categorized into defining attributes, antecedents and consequences. The defining attributes of brief lifestyle interventions were identified as healthy lifestyle, provider-led, patient-centered, counseling, assessment, feedback and time-limited. The antecedents were the necessity and importance of lifestyle interventions, the important role of healthcare providers in patients’ lifestyle changes, and the urgent need for a brief, cost-effective and easier-to-implement intervention, respectively. The consequences were categorized into consequences related to patients, consequences related to healthcare providers and healthcare system. Conclusion This study developed a universal definition and conceptual model of the term “brief lifestyle intervention” in the context of NCDs, including the theoretical relationships between its antecedents, defining attributes and consequences. The findings highlight the leading role of healthcare providers in delivering brief lifestyle interventions and offer guidance for their effective implementation.