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Purpose: The efficacy of isolated and relative performance indicators (PIs) has been compared in rugby union; the latter more effective at discerning match outcomes. However, this methodology has not been applied in women's rugby. The aim of this study was to identify PIs that maximize prediction accuracy of match outcome, from isolated and relative data sets, in women's rugby union. Methods: Twenty-six PIs were selected from 110 women's international rugby matches between 2017 and 2022 to form an isolated data set, with relative data sets determined by subtracting corresponding opposition PIs. Random forest classification was completed on both data sets, and feature selection and importance were used to simplify models and interpret key PIs. Models were used in prediction on the 2021 World Cup to evaluate performance on unseen data. Results: The isolated full model correctly classified 75% of outcomes (CI, 65%–82%), whereas the relative full model correctly classified 78% (CI, 69%–86%). Reduced respective models correctly classified 74% (CI, 65%–82%) and 76% (CI, 67%–84%). Reduced models correctly predicted 100% and 96% of outcomes for isolated and relative test data sets, respectively. No significant difference in accuracy was found between data sets. In the relative reduced model, meters made, clean breaks, missed tackles, lineouts lost, carries, and kicks from hand were significant. Conclusions: Increased relative meters made, clean breaks, carries, and kicks from hand and decreased relative missed tackles and lineouts lost were associated with success. This information can be utilized to inform physical and tactical preparation and direct physiological studies in women's rugby. [ABSTRACT FROM AUTHOR]

Despite the growing popularity of women's rugby, there is a lack of research understanding the contribution of place-kicking to match outcomes. This study aims to establish the characteristics and contribution of place-kicking to women's international Rugby Union and evaluate the performance of place-kickers while accounting for factors that contribute to kick difficulty. Data from 674 place-kicks across 80 matches were analysed. A binomial generalised linear mixed model (GLMM) was used to predict the probability of kick success. 60.5% of place-kicks were successful, and they contributed 23.9% of all points scored; conversions accounted for 16.8% and penalties 7.1%. Kick success percentages for conversions (56.9%) and penalties (78.3%) significantly differed (p < 0.01). Kick distance and angle were significant (p < 0.01) predictors of kick success and the GLMM had a prediction accuracy of 73.6%. The performance rankings of kickers changed when comparing observed and expected success, highlighting the need to consider contextual factors contributing to kick difficulty when evaluating performance. The GLMM results provide valuable insights for coaches and players to make informed decisions, for example, whether to attempt a place-kick when a penalty is awarded, by enabling predictions of place-kick success. This could enhance a team's chances of winning matches. [ABSTRACT FROM AUTHOR]

The authors investigated left–right turning preferences of n = 260 juvenile European sea bass (Dicentrarchus labrax) reared in ambient conditions and ocean acidification (OA) conditions or in ambient conditions but tested in OA water. Groups of 10 individuals were observed alone in a circular tank, and individuals' left and right turning during free‐swimming was quantified using trajectory data from the video. The authors showed that near‐future OA levels do not affect the number of turns made, or behavioural lateralization (turning preference), in juvenile D. labrax tested in groups. [ABSTRACT FROM AUTHOR]

The time that animals spend travelling at various speeds and the tortuosity of their movement paths are two of the many things that affect space‐use by animals. In this, high turn rates are predicted to be energetically costly, especially at high travel speeds, which implies that animals should modulate their speed according to path characteristics. When animals move so as to maximize distance and minimize metabolic energy expenditure, they travel most efficiently at the speed that gives them a minimum cost of transport (COTmin), a well‐defined point for animals that move entirely in fluid media. Theoretical considerations show though, that land animals should travel at their maximum speed to minimize COT, which they do not, instead travelling at walking pace. So, to what extent does COTmin depend on speed and turn rate and how might this relate to movement paths? We measured oxygen consumption in humans walking along paths with varied tortuosity at defined speeds to demonstrate that the energetic costs of negotiating these paths increase disproportionately with both speed and angular velocity. This resulted in the COTmin occurring at very low speeds, and these COTmin speeds reduced with increased path tortuosity and angular velocity. Logged movement data from six free‐ranging terrestrial species underpinned this because all individuals turned with greater angular velocity the slower their travel speeds across their full speed range. It seems, therefore, that land animals may strive to achieve minimum movement costs by reducing speed with increasing path variability, providing one of many possible explanations as to why speed is much lower than currently predicted based on lab measurements of mammalian locomotor performance. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine and compare the efficacy of head impact measurements via an electronic sensor framework, embedded within a mouthguard, against an anthropometric testing device. Development of the former is in response to the growing issue of head impacts and concussion in rugby union. Testing was conducted in a vehicle safety laboratory using a standard impact protocol utilising the headforms of anthropometric testing devices. The headforms were subjected to controlled front and side impacts. For each impact, the linear acceleration and rotational velocity was measured over a 104-ms interval at a frequency of 1 kHz. The magnitude of peak linear acceleration and peak rotational velocity was determined from the measured time-series traces and statistically compared. The peak linear acceleration and rotational velocity had intraclass correlation coefficients of 0.95 and 0.99, respectively. The root-mean-square error between the measurement systems was 4.3 g with a standard deviation of 3.5 g for peak linear acceleration and 0.7 rad/s with a standard deviation of 0.4 rad/s for rotational velocity. Bland and Altman analysis indicated a systematic bias of 2.5 g and − 0.5 rad/s and limits of agreement (1.96 × standard deviation) of ± 13.1 g and ± 1.25 rad/s for the instrumented mouthguard. These results provide the basis on which the instrumented mouthguard can be further developed for deployment and application within professional rugby, with a view to accurately and reliably quantify head collision dynamics. [ABSTRACT FROM AUTHOR]

Human exposure to carcinogens occurs via a plethora of environmental sources, with 70–90% of cancers caused by extrinsic factors. Aberrant phenotypes induced by such carcinogenic agents may provide universal biomarkers for cancer causation. Both current in vitro genotoxicity tests and the animal-testing paradigm in human cancer risk assessment fail to accurately represent and predict whether a chemical causes human carcinogenesis. The study aimed to establish whether the integrated analysis of multiple cellular endpoints related to the Hallmarks of Cancer could advance in vitro carcinogenicity assessment. Human lymphoblastoid cells (TK6, MCL-5) were treated for either 4 or 23 h with 8 known in vivo carcinogens, with doses up to 50% Relative Population Doubling (maximum 66.6 mM). The adverse effects of carcinogens on wide-ranging aspects of cellular health were quantified using several approaches; these included chromosome damage, cell signalling, cell morphology, cell-cycle dynamics and bioenergetic perturbations. Cell morphology and gene expression alterations proved particularly sensitive for environmental carcinogen identification. Composite scores for the carcinogens’ adverse effects revealed that this approach could identify both DNA-reactive and non-DNA reactive carcinogens in vitro. The richer datasets generated proved that the holistic evaluation of integrated phenotypic alterations is valuable for effective in vitro risk assessment, while also supporting animal test replacement. Crucially, the study offers valuable insights into the mechanisms of human carcinogenesis resulting from exposure to chemicals that humans are likely to encounter in their environment. Such an understanding of cancer induction via environmental agents is essential for cancer prevention. [ABSTRACT FROM AUTHOR]

Semiconductor quantum dot nanoparticles are in demand as optical biomarkers yet the cellular uptake process is not fully understood; quantification of numbers and the fate of internalized particles are still to be achieved. We have focussed on the characterization of cellular uptake of quantum dots using a combination of analytical electron microscopies because of the spatial resolution available to examine uptake at the nanoparticle level, using both imaging to locate particles and spectroscopy to confirm identity. In this study, commercially available quantum dots, CdSe/ZnS core/shell particles coated in peptides to target cellular uptake by endocytosis, have been investigated in terms of the agglomeration state in typical cell culture media, the traverse of particle agglomerates across U-2 OS cell membranes during endocytosis, the merging of endosomal vesicles during incubation of cells and in the correlation of imaging flow cytometry and transmission electron microscopy to measure the final nanoparticle dose internalized by the U-2 OS cells. We show that a combination of analytical transmission electron microscopy and serial block face scanning electron microscopy can provide a comprehensive description of the internalization of an initial exposure dose of nanoparticles by an endocytically active cell population and how the internalized, membrane bound nanoparticle load is processed by the cells. We present a stochastic model of an endosome merging process and show that this provides a data-driven modelling framework for the prediction of cellular uptake of engineered nanoparticles in general. [ABSTRACT FROM AUTHOR]

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture. © 2015 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

For phenotypic behavior to be understood in the context of cell lineage and local environment, properties of individual cells must be measured relative to population-wide traits. However, the inability to accurately identify, track and measure thousands of single cells via high-throughput microscopy has impeded dynamic studies of cell populations. We demonstrate unique labeling of cells, driven by the heterogeneous random uptake of fluorescent nanoparticles of different emission colors. By sequentially exposing a cell population to different particles, we generated a large number of unique digital codes, which corresponded to the cell-specific number of nanoparticle-loaded vesicles and were visible within a given fluorescence channel. When three colors are used, the assay can self-generate over 17,000 individual codes identifiable using a typical fluorescence microscope. The color-codes provided immediate visualization of cell identity and allowed us to track human cells with a success rate of 78% across image frames separated by 8 h. [ABSTRACT FROM AUTHOR]

Background: Ghrelin is an orexigenic stomach hormone that acts centrally to increase mid-brain dopamine neurone activity, amplify dopamine signaling and protect against neurotoxin-induced dopamine cell death in the mouse substantia nigra pars compacta (SNpc). In addition, ghrelin inhibits the lipopolysaccharide (LPS)-induced release of pro-inflammatory cytokines from peripheral macrophages, T-cells and from LPS stimulated microglia. Here we sought to determine whether ghrelin attenuates pro-inflammatory cytokine release from dopaminergic neurones. Findings: The dopaminergic SN4741 cell-line, which derives from the mouse substantia nigra (SN) and expresses the ghrelin-receptor (growth hormone secretagogue receptor (GHS-R)) and the ghrelin-O-acyl transferase (GOAT) enzyme, was used to determine the neuro-immunomodulatory action of ghrelin. We induced innate immune activation via LPS challenge (1 µg/ml) of SN4741 neurones that had been pre-cultured in the presence or absence of ghrelin (1, 10, 100 nM) for 4 h. After 24 h supernatants were collected for detection of IL-1 beta (IL-1ß ), TNF alpha (TNF-a) and IL-6 cytokines via enzyme linked immunosorbent assay (ELISA) analysis. Nuclear translocation of the transcription factor nuclear factor kappa B (NF-?B) was analyzed by Western blotting, and to determine viability of treatments a cell viability assay and caspase-3 immunohistochemistry were performed. We provide evidence that while IL-1ß and TNF-a were not detectable under any conditions, SN4741 neurones constitutively released IL-6 under basal conditions and treatment with LPS significantly increased IL-6 secretion. Pre-treatment of neurones with ghrelin attenuated LPS-mediated IL-6 release at 24 h, an affect that was inhibited by the GHS-R antagonist [D-Lys3]-GHRP-6. However, while ghrelin pre-treatment attenuated the LPS-mediated increase in NF-?B, there was no alteration in its nuclear translocation. Cell viability assay and caspase-3 immunocytochemistry demonstrated that the results were independent from activation of cytotoxic and/or apoptotic mechanisms in the neuronal population, respectively. Conclusion: Our results provide evidence that the gut-hormone, ghrelin, attenuates IL-6 secretion to LPS challenge in mid-brain dopaminergic neurones. These data suggest that ghrelin may protect against dopaminergic SN nerve cell damage or death via modulation of the innate immune response. [ABSTRACT FROM AUTHOR]

The delivery of nanoparticles into cells is important in therapeutic applications and in nanotoxicology. Nanoparticles are generally targeted to receptors on the surfaces of cells and internalized into endosomes by endocytosis, but the kinetics of the process and the way in which cell division redistributes the particles remain unclear. Here we show that the chance of success or failure of nanoparticle uptake and inheritance is random. Statistical analysis of nanoparticle-loaded endosomes indicates that particle capture is described by an over-dispersed Poisson probability distribution that is consistent with heterogeneous adsorption and internalization. Partitioning of nanoparticles in cell division is random and asymmetric, following a binomial distribution with mean probability of 0.52-0.72. These results show that cellular targeting of nanoparticles is inherently imprecise due to the randomness of nature at the molecular scale, and the statistical framework offers a way to predict nanoparticle dosage for therapy and for the study of nanotoxins. [ABSTRACT FROM AUTHOR]

The cell cycle, with its highly conserved features, is a fundamental driver for the temporal control of cell proliferation-while abnormal control and modulation of the cell cycle are characteristic of tumor cells. The principle aim in cancer biology is to seek anunderstanding of the origin and nature of innate and acquired heterogeneity at the cellular level, driven principally by temporal and functional asynchrony. A major bottleneck when mathematically modeling these biological systems is the lack of interlinked structured experimental data. This often results in the in silico models failing to translate the specific hypothesis into parameterized terms that enable robust validation and hence would produce suitable prediction tools rather than just simulation tools. The focus has been on linking data originating from different cytometric platforms and cell-based event analysis to inform and constrain the input parameters of a compartmental cell cycle model, hence partly measuring and deconvolving cell cycle heterogeneity within a tumor population. Our work has addressed the concept that the interoperability of cytometric data, derived from different cytometry platforms, can complement as well as enhance cellular parameters space, thus providing a more broader and in-depth view of the cellular systems. The initial aim was to enable the cell cycle model to deliver an improved integrated simulation of the well-defined and constrained biological system. From a modeling perspective, such a cross platform approach has provided a paradigm shift from conventional cross-validation approaches, and from a bioinformatics perspective, novel computational methodology has been introduced for integrating and mapping continuous data with cross-sectional data. This establishes the foundation for developing predictive models and in silico tracking and prediction of tumor progression. © 2011 International Society for Advancement of Cytometry. [ABSTRACT FROM AUTHOR]

Background: The inheritance of cellular material between parent and daughter cells during mitosis is highly influential in defining the properties of the cell and therefore the population lineage. This is of particular relevance when studying cell population evolution to assess the impact of a disease or the perturbation due to a drug treatment. The usual technique to investigate inheritance is to use time-lapse microscopy with an appropriate biological marker, however, this is time consuming and the number of inheritance events captured are too low to be statistically meaningful. Results: Here we demonstrate the use of a high throughput fluorescence measurement technique e.g. flow cytometry, to measure the fluorescence from quantum dot markers which can be used to target particular cellular sites. By relating, the fluorescence intensity measured between two time intervals to a transfer function we are able to deconvolve the inheritance of cellular material during mitosis. To demonstrate our methodology we use CdTe/ ZnS quantum dots to measure the ratio of endosomes inherited by the two daughter cells during mitosis in the U2-OS, human osteoscarcoma cell line. The ratio determined is in excellent agreement with results obtained previously using a more complex and computational intensive bespoke stochastic model. Conclusions: The use of a transfer function approach allows us to utilise high throughput measurement of large cell populations to derive statistically relevant measurements of the inheritance of cellular material. This approach can be used to measure the inheritance of organelles, proteins etc. and also particles introduced to cells for drug delivery. [ABSTRACT FROM AUTHOR]

We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. Here we link the ''real'' data to initialise a computer simulation of the cell cycle that mimics the evolution of individual cells within a larger population and simulates the associated changes in fluorescence intensity of functional reporters. The model is based on stochastic formulations of cell cycle progression and cell division and uses evolutionary algorithms, allied to further experimental data sets, to optimise the system variables. At the population level, the in-silico cells provide the same statistical distributions of fluorescence as their real counterparts; in addition the model maintains information at the single cell level. The cell model is demonstrated in the analysis of cell cycle perturbation in human osteosarcoma tumour cells, using the topoisomerase II inhibitor, ICRF-193. The simulation gives a continuous temporal description of the pharmacodynamics between discrete experimental analysis points with a 24 hour interval; providing quantitative assessment of inter-mitotic time variation, drug interaction time constants and sub-population fractions within normal and polyploid cell cycles. Repeated simulations indicate a model accuracy of ±5%. The development of a simulated cell model, initialized and calibrated by reference to experimental data, provides an analysis tool in which biological knowledge can be obtained directly via interrogation of the in-silico cell population. It is envisaged that this approach to the study of cell biology by simulating a virtual cell population pertinent to the data available can be applied to ''generic'' cellbased outputs including experimental data from imaging platforms. [ABSTRACT FROM AUTHOR]

Thrombosis is a severe and frequent complication of heparin-induced thrombocytopenia (HIT). However, there is currently no knowledge of the effects of HIT-like antibodies on the resulting microstructure of the formed clot, despite such information being linked to thrombotic events. We evaluate the effect of the addition of pathogenic HIT-like antibodies to blood on the resulting microstructure of the formed clot. Pathogenic HIT-like antibodies (KKO) and control antibodies (RTO) were added to samples of whole blood containing Unfractionated Heparin and Platelet Factor 4. The formed clot microstructure was investigated by rheological measurements (fractal dimension; d f) and scanning electron microscopy (SEM), and platelet activation was measured by flow cytometry. Our results revealed striking effects of KKO on clot microstructure. A significant difference in d f was found between samples containing KKO (d f = 1.80) versus RTO (d f = 1.74; p < 0.0001). This increase in d f was often associated with an increase in activated platelets. SEM images of the clots formed with KKO showed a network consisting of a highly branched and compact arrangement of thin fibrin fibres, typically found in thrombotic disease. This is the first study to identify significant changes in clot microstructure formed in blood containing HIT-like antibodies. These observed alterations in clot microstructure can be potentially exploited as a much-needed biomarker for the detection, management and monitoring of HIT-associated thrombosis. • The diagnosis of thrombosis in patients receiving heparin remains wholly inadequate. • We identify abnormal microstructure in blood clots containing HIT-like antibodies. • A structural biomarker, the fractal dimension, was significantly elevated in these clots. • This has potential application in the detection of thrombosis associated with HIT. [ABSTRACT FROM AUTHOR]