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A growing body of literature suggests that higher engagement in a range of activities can be beneficial for cognitive health in old age. Such studies typically rely on self-report questionnaires to assess level of engagement. These questionnaires are highly heterogeneous across studies, limiting generalisability. In particular, the most appropriate domains of activity engagement remain unclear. The Victoria Longitudinal Study-Activity Lifestyle Questionnaire comprises one of the broadest and most diverse collections of activity items, but different studies report different domain structures. This study aimed to help establish a generalisable domain structure of the Victoria Longitudinal Study-Activity Lifestyle Questionnaire. The questionnaire was adapted for use in a sample of UK-based older adults (336 community-dwelling adults aged 65-92 with no diagnosed cognitive impairment). An exploratory factor analysis was conducted on 29 items. The final model retained 22 of these items in a six-factor structure. Activity domains were: Manual (e.g., household repairs), Intellectual (e.g., attending a public lecture), Games (e.g., card games), Religious (e.g., attending religious services), Exercise (e.g., aerobics) and Social (e.g., going out with friends). Given that beneficial activities have the potential to be adapted into interventions, it is essential that future studies consider the most appropriate measurement of activity engagement across domains. The factor structure reported here offers a parsimonious and potentially useful way for future studies to assess engagement in different kinds of activities., Competing Interests: The authors have declared that no competing interests exist.

Billions of functionally distinct blood cells emerge from a pool of hematopoietic stem cells in our bodies every day. This progressive differentiation process is hierarchically structured and remarkably robust. We provide an introductory review to mathematical approaches addressing the functional aspects of how lineage choice is potentially implemented on a molecular level. Emerging from studies on the mutual repression of key transcription factors, we illustrate how those simple concepts have been challenged in recent years and subsequently extended. Especially, the analysis of omics data on the single-cell level with computational tools provides descriptive insights on a yet unknown level, while their embedding into a consistent mechanistic and mathematical framework is still incomplete., Competing Interests: Nothing declared., (© 2021 The Authors.)

Biomedical applications of deep learning algorithms rely on large expert annotated data sets. The classification of bone marrow (BM) cell cytomorphology, an important cornerstone of hematological diagnosis, is still done manually thousands of times every day because of a lack of data sets and trained models. We applied convolutional neural networks (CNNs) to a large data set of 171 374 microscopic cytological images taken from BM smears from 945 patients diagnosed with a variety of hematological diseases. The data set is the largest expert-annotated pool of BM cytology images available in the literature. It allows us to train high-quality classifiers of leukocyte cytomorphology that identify a wide range of diagnostically relevant cell species with high precision and recall. Our CNNs outcompete previous feature-based approaches and provide a proof-of-concept for the classification problem of single BM cells. This study is a step toward automated evaluation of BM cell morphology using state-of-the-art image-classification algorithms. The underlying data set represents an educational resource, as well as a reference for future artificial intelligence-based approaches to BM cytomorphology., (© 2021 by The American Society of Hematology.)

Clonal hematopoiesis (CH) is an age-related condition predisposing to blood cancer and cardiovascular disease (CVD). Murine models demonstrate CH-mediated altered immune function and proinflammation. Low-grade inflammation has been implicated in the pathogenesis of osteoarthritis (OA), the main indication for total hip arthroplasty (THA). THA-derived hip bones serve as a major source of healthy hematopoietic cells in experimental hematology. We prospectively investigated frequency and clinical associations of CH in 200 patients without known hematologic disease who were undergoing THA. Prevalence of CH was 50%, including 77 patients with CH of indeterminate potential (CHIP, defined as somatic variant allele frequencies [VAFs] ≥2%), and 23 patients harboring CH with lower mutation burden (VAF, 1% to 2%). Most commonly mutated genes were DNMT3A (29.5%), TET2 (15.0%), and ASXL1 (3.5%). CHIP is significantly associated with lower hemoglobin, higher mean corpuscular volume, previous or present malignant disease, and CVD. Strikingly, we observed a previously unreported association of CHIP with autoimmune diseases (AIDs; multivariable adjusted odds ratio, 6.6; 95% confidence interval, 1.7-30; P = .0081). These findings underscore the association between CH and inflammatory diseases. Our results have considerable relevance for managing patients with OA and AIDs or mild anemia and question the use of hip bone-derived cells as healthy experimental controls., (© 2021 by The American Society of Hematology.)

The efficacy of adoptive cell therapy for solid tumours is hampered by the poor accumulation of the transferred T cells in tumour tissue. Here, we show that forced expression of C-X-C chemokine receptor type 6 (whose ligand is highly expressed by human and murine pancreatic cancer cells and tumour-infiltrating immune cells) in antigen-specific T cells enhanced the recognition and lysis of pancreatic cancer cells and the efficacy of adoptive cell therapy for pancreatic cancer. In mice with subcutaneous pancreatic tumours treated with T cells with either a transgenic T-cell receptor or a murine chimeric antigen receptor targeting the tumour-associated antigen epithelial cell adhesion molecule, and in mice with orthotopic pancreatic tumours or patient-derived xenografts treated with T cells expressing a chimeric antigen receptor targeting mesothelin, the T cells exhibited enhanced intratumoral accumulation, exerted sustained anti-tumoral activity and prolonged animal survival only when co-expressing C-X-C chemokine receptor type 6. Arming tumour-specific T cells with tumour-specific chemokine receptors may represent a promising strategy for the realization of adoptive cell therapy for solid tumours., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

The purpose of this in vitro study was to assess the thermal effect of the 445 nm diode laser on five dental implant systems. In an ailing implant protocol, five commercial dental implant systems were subjected to 445 nm diode laser energy at different wattages [W], exposure times, and modes (continuous wave [CW] vs. pulsed and contact vs. non-contact) of laser beam delivery. Scanning electron microscopy (SEM) allowed the evaluation of irradiated implant surfaces. A total of 2880 temperature response curves were recorded. The 445 nm wavelength caused temperature increases of more than 10 °C at or above the 0.8 W power level working in CW mode for 5 s and in pulsed mode at 3 W for 20 s with 10% duty cycle. Highest rises in temperature were seen in the Straumann Pure ceramic implant, lowest in the Ankylos system. SEM analysis revealed no surface alteration in all systems in non-contact mode. The applied laser is not inherently safe for the decontamination of ailing implants. From the results of this study it was concluded that different dental implant materials and geometries show different temperature response curves when subjected to 445 nm diode laser energy. Clinicians ought to be aware of this. Therefore, manufacturers of laser devices should provide implant-specific laser parameters for the decontamination process. However, both laser irradiation systems can prevent harmful rises in temperature and surface alteration when used at moderate laser parameters., (© 2021. The Author(s).)

Eyewitnesses may experience stress during a crime and when attempting to identify the perpetrator subsequently. Laboratory studies can provide insight into how acute stress at encoding and retrieval affects memory performance. However, previous findings exploring this issue have been mixed. Across two preregistered experiments, we examined the effects of stress during encoding and retrieval on face and word recognition performance. We used the Maastricht Acute Stress Test (MAST) to induce stress and verified the success of the stress manipulation with blood pressure measures, salivary cortisol levels, and negative affect scores. To examine differences in stressor timing, participants encoded target faces or words both when confronted with the stressor and during the subsequent cortisol peak and retrieved these stimuli 24 h later. We found neither effects of acute stress on face recognition memory during encoding or retrieval (Experiments 1 and 2), nor effects of encoding stress on word recognition memory (Experiment 2). Bayesian analyses largely provided substantial or strong evidence for the null hypotheses. We emphasize the need for well-powered experiments using contemporary methodology for a more complete understanding of the effect of acute stress on face recognition memory., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

The eyewitness and fundamental memory research fields have investigated the effects of acute stress at encoding on memory performance for decades yet results often demonstrate contrasting conclusions. In this review, we first summarise findings on the effects of acute encoding stress on memory performance and discuss how these research fields often come to these diverging findings regarding the effects of encoding stress on memory performance. Next, we critically evaluate methodological choices that underpin these discrepancies, emphasising the strengths and limitations of different stress-memory experiments. Specifically, we elaborate on choice of stressors and stimuli, stress manipulation checks, stressor timing, and the interval between encoding and retrieval and discuss how methodological shortcomings in both the eyewitness and fundamental memory fields have limited our understanding of how encoding stress may affect eyewitness memory performance. Finally, we propose several recommendations for researchers interested in this topic, such as confirming stress inductions with physiological measures, implementing sufficient retrieval intervals to isolate the memory phase of interest and using ecologically valid memory paradigms. We conclude that the best progress can be made if researchers are responsive to the methodologies and findings reported in other research fields and encourage collaborations between the different disciplines.

Objective The aim of this study was to determine how individual, group and leadership factors influence clinician engagement in safety and quality improvement work. Methods The study was conducted through an online questionnaire. Participants were alumni of Australian healthcare safety and quality improvement capability development programs. Relationships between five factors influencing clinicians' perception of value for time and effort in safety and quality improvement work were explored. The five factors were psychological empowerment; task cohesion; social cohesion; transformational leadership behaviour of project leads and sponsors; and value for time and effort for self and patients. Correlation and regression analyses were used to explore the aspects of the hypothesised model. Moderation and mediation analysis was then used to explore the relationships further. Structural equation modelling was used to determine the path model. Results All factors showed strong positive correlations, with psychological empowerment and transformational leadership having the strongest relationships with perceived value for effort for self and patient. The factorial structure of measures was examined, and all indicators loaded significantly on their corresponding latent constructs and the model showed a good fit to the data. Conclusions The findings of this study suggest that the most crucial factor to clinician engagement in safety and quality improvement at the point of care is the leader's behaviour and how that influences team dynamics and individual motivation and empowerment. What is known about the topic? Healthcare organisations remain challenged regarding clinician engagement in safety and quality improvement. Although much is known about clinicians' perceptions of safety and quality, there is more to understand about what practically motivates clinicians to engage. Tapping into individual, group and leadership factors' influences on clinician engagement offers a deeper perspective. What does this paper add? This study explored the individual, group and leadership factors that drive clinician engagement. The factors include the clinician's individual motivation and empowerment to participate, the group dynamics that surround the clinician and the leadership behaviours of the team's leader. The research design allowed for greater understanding about how and to what extent these factors drive clinician engagement. The study's findings can be applied in practice in capability development activities or leadership for safety and quality improvement. What are the implications for practitioners? Rather than taking a perspective that the clinician needs to engage, this study suggests a strong onus on leadership behaviours to engage those clinicians. Focusing on the self as leader and a leader's own behaviours, as well as how those behaviours are fostering positive team dynamics and motivating and empowering individual team members, will have a great benefit on clinician engagement in safety and quality improvement. Higher clinical engagement in safety and quality improvement should translate into better value care.

CAR T cell therapy remains ineffective in solid tumors, due largely to poor infiltration and T cell suppression at the tumor site. T regulatory (T reg ) cells suppress the immune response via inhibitory factors such as transforming growth factor-β (TGF-β). T reg cells expressing the C-C chemokine receptor 8 (CCR8) have been associated with poor prognosis in solid tumors. We postulated that CCR8 could be exploited to redirect effector T cells to the tumor site while a dominant-negative TGF-β receptor 2 (DNR) can simultaneously shield them from TGF-β. We identified that CCL1 from activated T cells potentiates a feedback loop for CCR8 + T cell recruitment to the tumor site. This sustained and improved infiltration of engineered T cells synergized with TGF-β shielding for improved therapeutic efficacy. Our results demonstrate that addition of CCR8 and DNR into CAR T cells can render them effective in solid tumors., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

With the availability of cellular-resolution connectivity maps, connectomes, from the mammalian nervous system, it is in question how informative such massive connectomic data can be for the distinction of local circuit models in the mammalian cerebral cortex. Here, we investigated whether cellular-resolution connectomic data can in principle allow model discrimination for local circuit modules in layer 4 of mouse primary somatosensory cortex. We used approximate Bayesian model selection based on a set of simple connectome statistics to compute the posterior probability over proposed models given a to-be-measured connectome. We find that the distinction of the investigated local cortical models is faithfully possible based on purely structural connectomic data with an accuracy of more than 90%, and that such distinction is stable against substantial errors in the connectome measurement. Furthermore, mapping a fraction of only 10% of the local connectome is sufficient for connectome-based model distinction under realistic experimental constraints. Together, these results show for a concrete local circuit example that connectomic data allows model selection in the cerebral cortex and define the experimental strategy for obtaining such connectomic data.

In the adult brain, NG2-glia represent a cell population that responds to injury. To further investigate if, how and why NG2-glia are recruited to the injury site, we analyzed in detail the long-term reaction of NG2-glia after a lesion by time-lapse two-photon in vivo microscopy. Live imaging over several weeks of GFP-labeled NG2-glia in the stab wounded cerebral cortex revealed their fast and heterogeneous reaction, including proliferation, migration, polarization, hypertrophy, or a mixed response, while a small subset of cells remained unresponsive. At the peak of the reaction, 2-4 days after the injury, NG2-glia accumulated around and within the lesion core, overcoming the homeostatic control of their density, which normalized back to physiological conditions only 4 weeks after the insult. Genetic ablation of proliferating NG2-glia demonstrated that this accumulation contributed beneficially to wound closure. Thus, NG2-glia show a fast response to traumatic brain injury (TBI) and participate in tissue repair., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 von Streitberg, Jäkel, Eugenin von Bernhardi, Straube, Buggenthin, Marr and Dimou.)

Convolutional neural networks (CNNs) excel as powerful tools for biomedical image classification. It is commonly assumed that training CNNs requires large amounts of annotated data. This is a bottleneck in many medical applications where annotation relies on expert knowledge. Here, we analyze the binary classification performance of a CNN on two independent cytomorphology datasets as a function of training set size. Specifically, we train a sequential model to discriminate non-malignant leukocytes from blast cells, whose appearance in the peripheral blood is a hallmark of leukemia. We systematically vary training set size, finding that tens of training images suffice for a binary classification with an ROC-AUC over 90%. Saliency maps and layer-wise relevance propagation visualizations suggest that the network learns to increasingly focus on nuclear structures of leukocytes as the number of training images is increased. A low dimensional tSNE representation reveals that while the two classes are separated already for a few training images, the distinction between the classes becomes clearer when more training images are used. To evaluate the performance in a multi-class problem, we annotated single-cell images from a acute lymphoblastic leukemia dataset into six different hematopoietic classes. Multi-class prediction suggests that also here few single-cell images suffice if differences between morphological classes are large enough. The incorporation of deep learning algorithms into clinical practice has the potential to reduce variability and cost, democratize usage of expertise, and allow for early detection of disease onset and relapse. Our approach evaluates the performance of a deep learning based cytology classifier with respect to size and complexity of the training data and the classification task.

Grandparents are frequently relied upon to care for their preschool-aged grandchildren. These early years are a crucial age in the development of dietary habits and preferences. This review aims to determine grandparental dietary provision, feeding practices and feeding styles when caring for their preschool-aged grandchildren. Medline, PsycInfo and Web of Science were searched in January 2020. A systematic mixed methods approach was used to synthesize the qualitative (n = 13) and quantitative (n = 7) articles describing grandparents' feeding styles (n = 9), feeding practices (n = 14) and dietary provision (n = 18). Grandparents are serving large portion sizes and encouraging their grandchildren to eat frequently. Results are mixed for the types of foods provided; grandparents provide discretionary foods high in sugar and fat, and some also choose more expensive core foods as treats (e.g., berries). Grandparents engage in feeding practices that promote healthy eating (e.g., creating a healthy feeding environment) and promote autonomy and independence (e.g., considering their grandchild's preferences). However, they also use some coercive feeding practices (e.g., using food as a reward) and may be using indulgent feeding styles, which can be conducive to obesogenic dietary intakes. Interventions targeting grandparents could be an effective way to improve dietary-related health outcomes in young children., (© 2020 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of World Obesity Federation.)

This survey examined lay and expert beliefs about statements concerning stress effects on (eyewitness) memory. Thirty-seven eyewitness memory experts, 36 fundamental memory experts, and 109 laypeople endorsed, opposed, or selected don't know responses for a range of statements relating to the effects of stress at encoding and retrieval. We examined proportions in each group and differences between groups (eyewitness memory experts vs. fundamental memory experts; experts vs. laypeople) for endorsements (agree vs. disagree) and selections (don't know vs. agree/disagree). High proportions of experts from both research fields agreed that very high levels of stress impair the accuracy of eyewitness testimony. A majority of fundamental experts, but not eyewitness experts, endorsed the idea that stress experienced during encoding can enhance memory. Responses to statements regarding moderating factors such as stressor severity and detail type provided further insight into this discrepancy. Eyewitness memory experts more frequently selected the don't know option for neuroscientific statements regarding stress effects on memory than fundamental memory experts, although don't know selections were substantial among both expert groups. Laypeople's responses to eight of the statements differed statistically from expert answers on topics such as memory in children, in professionals such as police officers, for faces and short crimes, and the existence of repression, providing insight into possible 'commonsense' beliefs on stress effects on memory. Our findings capture the current state of knowledge about stress effects on memory as reflected by sample of experts and laypeople, and highlight areas where further research and consensus would be valuable.

Background: Deep learning contributes to uncovering molecular and cellular processes with highly performant algorithms. Convolutional neural networks have become the state-of-the-art tool to provide accurate and fast image data processing. However, published algorithms mostly solve only one specific problem and they typically require a considerable coding effort and machine learning background for their application., Results: We have thus developed InstantDL, a deep learning pipeline for four common image processing tasks: semantic segmentation, instance segmentation, pixel-wise regression and classification. InstantDL enables researchers with a basic computational background to apply debugged and benchmarked state-of-the-art deep learning algorithms to their own data with minimal effort. To make the pipeline robust, we have automated and standardized workflows and extensively tested it in different scenarios. Moreover, it allows assessing the uncertainty of predictions. We have benchmarked InstantDL on seven publicly available datasets achieving competitive performance without any parameter tuning. For customization of the pipeline to specific tasks, all code is easily accessible and well documented., Conclusions: With InstantDL, we hope to empower biomedical researchers to conduct reproducible image processing with a convenient and easy-to-use pipeline.

In a preregistered experiment, we examined the efficacy of arousal reappraisal as an intervention for reducing the negative effects of stress at retrieval on memory. Participants ( N  = 177) were semi-randomly assigned to one of three conditions: a Stress-intervention condition, a Stress-placebo condition, and a No-stress-placebo control condition. Participants viewed four images of complex, mildly negatively valenced scenes. One day later, they received an arousal reappraisal intervention or placebo before exposure to a laboratory stressor (or a control version for the No-stress condition). Participants were then tested on their memory of the images using a free recall instruction and multiple-choice recognition questions. As expected, negative affect and blood pressure increased for the stress conditions but not the control condition. Contrary to our hypotheses, memory performance did not statistically significant differ between the Stress-placebo condition and the No-stress-placebo control condition, indicating a lack of negative effects of acute retrieval stress on memory. Furthermore, we also found no statistically significant differences between the Stress-intervention condition and Stress-placebo condition in terms of memory performance, suggesting that the intervention did not assist with enhancing memory. We integrate interpretations of the findings from this study with a discussion of avenues for future research in this area.

Classically, hematopoietic stem cell (HSC) differentiation is assumed to occur via progenitor compartments of decreasing plasticity and increasing maturity in a specific, hierarchical manner. The classical hierarchy has been challenged in the past by alternative differentiation pathways. We abstracted experimental evidence into 10 differentiation hierarchies, each comprising 7 cell type compartments. By fitting ordinary differential equation models with realistic waiting time distributions to time-resolved data of differentiating HSCs from 10 healthy human donors, we identified plausible lineage hierarchies and rejected others. We found that, for most donors, the classical model of hematopoiesis is preferred. Surprisingly, multipotent lymphoid progenitor differentiation into granulocyte-monocyte progenitors is plausible in 90% of samples. An in silico analysis confirmed that, even for strong noise, the classical model can be identified robustly. Our computational approach infers differentiation hierarchies in a personalized fashion and can be used to gain insights into kinetic alterations of diseased hematopoiesis., Competing Interests: The authors declare no competing interests., (© 2021 The Authors.)

DNA replication during cell division leads to dilution of histone modifications and can thus affect chromatin-mediated gene regulation, raising the question of how the cell-cycle shapes the histone modification landscape, particularly during embryogenesis. We tackled this problem by manipulating the cell cycle during early Xenopus laevis embryogenesis and analyzing in vivo histone H4K20 methylation kinetics. The global distribution of un-, mono-, di-, and tri-methylated histone H4K20 was measured by mass spectrometry in normal and cell-cycle-arrested embryos over time. Using multi-start maximum likelihood optimization and quantitative model selection, we found that three specific biological methylation rate constants were required to explain the measured H4K20 methylation state kinetics. While demethylation is essential for regulating H4K20 methylation kinetics in non-cycling cells, demethylation is very likely dispensable in rapidly dividing cells of early embryos, suggesting that cell-cycle-mediated dilution of H4K20 methylation is an essential regulatory component for shaping its epigenetic landscape during early development. A record of this paper's transparent peer review process is included in the Supplemental Information., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Regulation of quiescence and cell cycle entry is pivotal for the maintenance of stem cell populations. Regulatory mechanisms, however, are poorly understood. In particular, it is unclear how the activity of single stem cells is coordinated within the population or if cells divide in a purely random fashion. We addressed this issue by analyzing division events in an adult neural stem cell (NSC) population of the zebrafish telencephalon. Spatial statistics and mathematical modeling of over 80,000 NSCs in 36 brain hemispheres revealed weakly aggregated, nonrandom division patterns in space and time. Analyzing divisions at 2 time points allowed us to infer cell cycle and S-phase lengths computationally. Interestingly, we observed rapid cell cycle reentries in roughly 15% of newly born NSCs. In agent-based simulations of NSC populations, this redividing activity sufficed to induce aggregated spatiotemporal division patterns that matched the ones observed experimentally. In contrast, omitting redivisions leads to a random spatiotemporal distribution of dividing cells. Spatiotemporal aggregation of dividing stem cells can thus emerge solely from the cells' history., Competing Interests: The authors have declared that no competing interests exist.

Scars are more severe when the subcutaneous fascia beneath the dermis is injured upon surgical or traumatic wounding. Here, we present a detailed analysis of fascia cell mobilisation by using deep tissue intravital live imaging of acute surgical wounds, fibroblast lineage-specific transgenic mice, and skin-fascia explants (scar-like tissue in a dish - SCAD). We observe that injury triggers a swarming-like collective cell migration of fascia fibroblasts that progressively contracts the skin and form scars. Swarming is exclusive to fascia fibroblasts, and requires the upregulation of N-cadherin. Both swarming and N-cadherin expression are absent from fibroblasts in the upper skin layers and the oral mucosa, tissues that repair wounds with minimal scar. Impeding N-cadherin binding inhibits swarming and skin contraction, and leads to reduced scarring in SCADs and in animals. Fibroblast swarming and N-cadherin thus provide therapeutic avenues to curtail fascia mobilisation and pathological fibrotic responses across a range of medical settings.

While the analysis of mitochondrial morphology has emerged as a key tool in the study of mitochondrial function, efficient quantification of mitochondrial microscopy images presents a challenging task and bottleneck for statistically robust conclusions. Here, we present Mitochondrial Segmentation Network (MitoSegNet), a pretrained deep learning segmentation model that enables researchers to easily exploit the power of deep learning for the quantification of mitochondrial morphology. We tested the performance of MitoSegNet against three feature-based segmentation algorithms and the machine-learning segmentation tool Ilastik. MitoSegNet outperformed all other methods in both pixelwise and morphological segmentation accuracy. We successfully applied MitoSegNet to unseen fluorescence microscopy images of mitoGFP expressing mitochondria in wild-type and catp-6 ATP13A2 mutant C. elegans adults. Additionally, MitoSegNet was capable of accurately segmenting mitochondria in HeLa cells treated with fragmentation inducing reagents. We provide MitoSegNet in a toolbox for Windows and Linux operating systems that combines segmentation with morphological analysis., Competing Interests: None., (© 2020 The Authors.)

Multispectral Optoacoustic Tomography (MSOT) resolves oxy- (HbO 2 ) and deoxy-hemoglobin (Hb) to perform vascular imaging. MSOT suffers from gradual signal attenuation with depth due to light-tissue interactions: an effect that hinders the precise manual segmentation of vessels. Furthermore, vascular assessment requires functional tests, which last several minutes and result in recording thousands of images. Here, we introduce a deep learning approach with a sparse-UNET (S-UNET) for automatic vascular segmentation in MSOT images to avoid the rigorous and time-consuming manual segmentation. We evaluated the S-UNET on a test-set of 33 images, achieving a median DICE score of 0.88. Apart from high segmentation performance, our method based its decision on two wavelengths with physical meaning for the task-at-hand: 850 nm (peak absorption of oxy-hemoglobin) and 810 nm (isosbestic point of oxy-and deoxy-hemoglobin). Thus, our approach achieves precise data-driven vascular segmentation for automated vascular assessment and may boost MSOT further towards its clinical translation., Competing Interests: The authors declare that there are no conflicts of interest., (© 2020 The Authors.)

Motivation: Dimensionality reduction is a key step in the analysis of single-cell RNA-sequencing data. It produces a low-dimensional embedding for visualization and as a calculation base for downstream analysis. Nonlinear techniques are most suitable to handle the intrinsic complexity of large, heterogeneous single-cell data. However, with no linear relation between gene and embedding coordinate, there is no way to extract the identity of genes driving any cell's position in the low-dimensional embedding, making it difficult to characterize the underlying biological processes., Results: In this article, we introduce the concepts of local and global gene relevance to compute an equivalent of principal component analysis loadings for non-linear low-dimensional embeddings. Global gene relevance identifies drivers of the overall embedding, while local gene relevance identifies those of a defined sub-region. We apply our method to single-cell RNA-seq datasets from different experimental protocols and to different low-dimensional embedding techniques. This shows our method's versatility to identify key genes for a variety of biological processes., Availability and Implementation: To ensure reproducibility and ease of use, our method is released as part of destiny 3.0, a popular R package for building diffusion maps from single-cell transcriptomic data. It is readily available through Bioconductor., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press.)

Transcriptional memory of gene expression enables adaptation to repeated stimuli across many organisms. However, the regulation and heritability of transcriptional memory in single cells and through divisions remains poorly understood. Here, we combined microfluidics with single-cell live imaging to monitor Saccharomyces cerevisiae galactokinase 1 (GAL1) expression over multiple generations. By applying pedigree analysis, we dissected and quantified the maintenance and inheritance of transcriptional reinduction memory in individual cells through multiple divisions. We systematically screened for loss- and gain-of-memory knockouts to identify memory regulators in thousands of single cells. We identified new loss-of-memory mutants, which affect memory inheritance into progeny. We also unveiled a gain-of-memory mutant, elp6Δ, and suggest that this new phenotype can be mediated through decreased histone occupancy at the GAL1 promoter. Our work uncovers principles of maintenance and inheritance of gene expression states and their regulators at the single-cell level., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Non-genetic transcriptional variability is a potential mechanism for therapy resistance in melanoma. Specifically, rare subpopulations of cells occupy a transient pre-resistant state characterized by coordinated high expression of several genes and survive therapy. How might these rare states arise and disappear within the population? It is unclear whether the canonical models of probabilistic transcriptional pulsing can explain this behavior, or if it requires special, hitherto unidentified mechanisms. We show that a minimal model of transcriptional bursting and gene interactions can give rise to rare coordinated high expression states. These states occur more frequently in networks with low connectivity and depend on three parameters. While entry into these states is initiated by a long transcriptional burst that also triggers entry of other genes, the exit occurs through independent inactivation of individual genes. Together, we demonstrate that established principles of gene regulation are sufficient to describe this behavior and argue for its more general existence. A record of this paper's transparent peer review process is included in the Supplemental Information., Competing Interests: Declaration of Interests A.R. receives royalties related to Stellaris RNA FISH probes. All other authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The personal and societal impact of age-related cognitive decline supports the development of effective interventions. While some strategies, such as cognitive training, exercise or socio-intellectual engagement, appear beneficial, few studies have examined the association between personality and intervention efficacy. A systematic review was therefore conducted to summarise and synthesise the literature regarding the influence of personality traits on the effectiveness of non-pharmacological interventions for cognitive ageing. A systematic search of PubMed, PsycINFO and Web of Science was carried out. Of the 2100 papers identified by the search strategy, 10 studies were retained that met the relevant criteria (e.g., intervention studies with one or more cognitive outcomes and a measure of personality). Of these, two studies reported that higher levels of Openness to Experience were associated with greater improvement in memory performance after cognitive training interventions. Another found a positive association between Openness and improvement in divergent thinking following a novel group-based problem solving programme. One social intervention study reported positive moderating effects of Conscientiousness and Agreeableness, and mixed effects of Extraversion. Mixed evidence was also found regarding Need for Cognition, with one study reporting a positive association with memory improvement and another reporting less improvement in divergent thinking. Others found no evidence of personality influencing intervention outcomes. Due to the relatively small and heterogeneous sample of studies identified, any conclusions should currently be considered preliminary. These findings highlight the need for further research exploring the role of personality in intervention efficacy, so that interventions might be better tailored to individuals., Competing Interests: Declaration of Competing Interest All authors declare that we have no conflicts of interest., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Chromatin states must be maintained during cell proliferation to uphold cellular identity and genome integrity. Inheritance of histone modifications is central in this process. However, the histone modification landscape is challenged by incorporation of new unmodified histones during each cell cycle, and the principles governing heritability remain unclear. We take a quantitative computational modeling approach to describe propagation of histone H3K27 and H3K36 methylation states. We measure combinatorial H3K27 and H3K36 methylation patterns by quantitative mass spectrometry on subsequent generations of histones. Using model comparison, we reject active global demethylation and invoke the existence of domains defined by distinct methylation endpoints. We find that H3K27me3 on pre-existing histones stimulates the rate of de novo H3K27me3 establishment, supporting a read-write mechanism in timely chromatin restoration. Finally, we provide a detailed quantitative picture of the mutual antagonism between H3K27 and H3K36 methylation and propose that it stabilizes epigenetic states across cell division., Competing Interests: Declaration of Interests A.G. is cofounder and CSO of Ankrin Therapeutics. A.I. and M.V.-A. are cofounders of EpiQMAx., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Caregivers are mostly responsible for the foods young children consume; however, it is unknown how caregivers determine what portion sizes to serve. This study examined factors which predict smaller or larger than recommended snack portion sizes in an online survey. Caregivers of children aged 2 to 4 years were presented with 10 snack images, each photographed in six portion sizes. Caregivers (n = 659) selected the portion they would usually serve themselves and their child for an afternoon snack. Information on child eating traits, parental feeding practices and demographics were provided by caregivers. Most caregivers selected portions in line with recommended amounts for preschool children, demonstrating their ability to match portion sizes to their child's energy requirements. However, 16% of caregivers selected smaller than recommended low energy-dense (LED, e.g., fruits and vegetables) snacks for their child which was associated with smaller caregiver's own portion size, reduced child food liking and increased satiety responsiveness. In contrast, 28% of caregivers selected larger than recommended amounts of high energy-dense (HED, e.g., cookies, crisps) snacks for their child which were associated with larger caregiver's own portion size, greater frequency of consumption, higher child body mass index (BMI), greater pressure to eat and lower child food liking. These findings suggest that most caregivers in this study select portions adjusted to suit their child's age and stage of development. Future interventions could provide support to caregivers regarding the energy and nutrient density of foods given the relatively small portion sizes of LED and large portions of HED snacks offered to some children.

Caregivers are responsible for the type and amount of food young children are served. However, it remains unclear what considerations caregivers make when serving snacks to children. The aim of the study was to explore mothers' decisions and portion control strategies during snack preparation in the home environment. Forty mothers of children aged 24-48 months participated in the study. Mothers prepared five snack foods for themselves and their child whilst verbalizing their actions and thoughts. Mothers were then asked about their portion size decisions in a semi-structured interview. Transcripts were imported into NVivo and analyzed thematically. Three key themes were identified: (1) portion size considerations, (2) portion control methods, and (3) awareness and use of portion size recommendations. Transient, food-related situational influences influenced mothers and disrupted planning and portion control. Food packaging and dishware size were used as visual cues for portion control; however, these vary widely in their size, thus emphasizing mothers' uncertainty regarding appropriate portion sizes. Mothers called for portion size information to be accessible, child-centered, and simple. These findings reveal multiple considerations when deciding on the correct snack portion sizes for children. These decisions are complex and vary across situations and time, and according to the types of snacks offered.

Background: Ghana has reached an advanced stage of nutrition transition, contributing to an increase in nutrition-related non-communicable diseases, particularly amongst urban women. Community involvement is an important factor in the success of efforts to promote healthy eating. The readiness of populations to accept a range of interventions needs to be understood before appropriate interventions can be implemented. Therefore, this study assessed how ready urban communities are to improve diets of women of reproductive age in Ghana., Methods: Using the Community Readiness Model (CRM), in-depth interviews were conducted with 24 key informants from various sectors in low income communities across two cities in Ghana: Accra and Ho. The CRM consists of 36 open questions addressing five readiness dimensions (community knowledge of efforts, leadership, community climate, knowledge of the issue and resources). Interviews were scored using the CRM protocol with a maximum of 9 points per dimension (from 1 = no awareness to 9 = high level of community ownership). Thematic analysis was undertaken to gain insights of community factors that could affect the implementation of interventions to improve diets., Results: The mean community readiness scores indicated that both communities were in the "vague awareness stage" (3.35 ± 0.54 (Accra) and 3.94 ± 0.41 (Ho)). CRM scores across the five dimensions ranged from 2.65-4.38/9, ranging from denial/resistance to pre-planning. In both communities, the mean readiness score for 'knowledge of the issue' was the highest of all dimensions (4.10 ± 1.61 (Accra); 4.38 ± 1.81 (Ho)), but was still only at the pre-planning phase. The lowest scores were found for community knowledge of efforts (denial/resistance; 2.65 ± 2.49 (Accra)) and resources (vague awareness; 3.35 ± 1.03 (Ho)). The lack of knowledge of the consequences of unhealthy diets, misconceptions of the issue partly from low education, as well as challenges faced from a lack of resources to initiate/sustain programmes explained the low readiness., Conclusions: Despite recognising that unhealthy diets are a public health issue in these urban Ghanaian communities, it is not seen as a priority. The low community readiness ratings highlight the need to increase awareness of the issue prior to intervening to improve diets.

Objective:: Development of a Mental Health Quality and Safety Framework with co-designed priority areas for improvement., Method:: A qualitative and inductive approach was utilised, including a literature search, consultations with staff and focus groups with consumers and carers., Results:: Thematic analysis resulted in 32 categories, grouped into seven key themes. Combined with the evidence base, these were distilled into component parts of the Framework., Conclusions:: A change in strategy and culture is required, balancing a traditionally centralised top-down approach to health care governance and improvement, with a complementary localised bottom-up model that embeds improvement science principles involving frontline staff, consumers and carers. This Framework, that centres on patient safety and quality improvement, in combination with a corresponding cultural change, can enhance clinical outcomes, service efficiency, staff morale and staff retention rates.

An intricate link is becoming apparent between metabolism and cellular identities. Here, we explore the basis for such a link in an in vitro model for early mouse embryonic development: from naïve pluripotency to the specification of primordial germ cells (PGCs). Using single-cell RNA-seq with statistical modelling and modulation of energy metabolism, we demonstrate a functional role for oxidative mitochondrial metabolism in naïve pluripotency. We link mitochondrial tricarboxylic acid cycle activity to IDH2-mediated production of alpha-ketoglutarate and through it, the activity of key epigenetic regulators. Accordingly, this metabolite has a role in the maintenance of naïve pluripotency as well as in PGC differentiation, likely through preserving a particular histone methylation status underlying the transient state of developmental competence for the PGC fate. We reveal a link between energy metabolism and epigenetic control of cell state transitions during a developmental trajectory towards germ cell specification, and establish a paradigm for stabilizing fleeting cellular states through metabolic modulation., (© 2018 The Authors. Published under the terms of the CC BY 4.0 license.)

Cells vary in their dynamic response to external stimuli, due to stochastic fluctuations and non-uniform progression through the cell cycle. Hence, single-cell studies are required to reveal the range of heterogeneity in their responses to defined perturbations, which provides detailed insight into signaling processes. Here, we present a time-lapse study using arrays of micro-trenches to monitor the timing of cell division and apoptosis in non-adherent cells at the single-cell level. By employing automated cell tracking and division detection, we precisely determine cell cycle duration and sister-cell correlations for hundreds of individual cells in parallel. As a model application we study the response of leukemia cells to the chemostatic drug vincristine as a function of cell cycle phase. The time-to-death after drug addition is found to depend both on drug concentration and cell cycle phase. The resulting timing and dose-response distributions were reproduced in control experiments using synchronized cell populations. Interestingly, in non-synchronized cells, the time-to-death intervals for sister cells appear to be correlated. Our study demonstrates the practical benefits of micro-trench arrays as a platform for high-throughput, single-cell time-lapse studies on cell cycle dependence, correlations and cell fate decisions in general.

Adult murine neural stem cells (NSCs) generate neurons in drastically declining numbers with age. How cellular dynamics sustain neurogenesis and how alterations with age may result in this decline are unresolved issues. We therefore clonally traced NSC lineages using confetti reporters in young and middle-aged adult mice. To understand the underlying mechanisms, we derived mathematical models that explain observed clonal cell type abundances. The best models consistently show self-renewal of transit-amplifying progenitors and rapid neuroblast cell cycle exit. In middle-aged mice, we identified an increased probability of asymmetric stem cell divisions at the expense of symmetric differentiation, accompanied by an extended persistence of quiescence between activation phases. Our model explains existing longitudinal population data and identifies particular cellular properties underlying adult NSC homeostasis and the aging of this stem cell compartment., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: This case report describes a 13-year-old cob-cross gelding presented for evaluation of recent onset hindlimb ataxia. The gelding had undergone general anaesthesia and tenoscopy of the right hindlimb digital flexor tendon sheath at a nearby clinic three months earlier and had appeared normal at routine post-operative assessments until the sudden onset of neurological deficits. Spinal trauma was suspected initially but radiography and scintigraphy were unremarkable. Due to the severity and progressive nature of the clinical signs the -gelding was subjected to euthanasia. Post mortem examinations (computed tomography, dissection and histopathology) revealed spinal cord compression caused by a single extradural hydatid cyst (Echinococcus equinus), confirmed with PCR, at the level of the 15th thoracic vertebra. This is the first report of a spinal hydatid cyst causing hindlimb ataxia and should therefore be considered a potential differential diagnosis for ataxia in the equine patient.

On the occasion of the 13th International Conference on Osteogenesis imperfecta in August 2017 an expert panel was convened to develop an international consensus paper regarding physical rehabilitation in children and adolescents with Osteogenesis imperfecta. The experts were chosen based on their clinical experience with children with osteogenesis imperfecta and were identified by sending out questionnaires to specialized centers and patient organizations in 26 different countries. The final expert-group included 16 representatives (12 physiotherapists, two occupational therapists and two medical doctors) from 14 countries. Within the framework of a collation of personal experiences and the results of a literature search, the participating physiotherapists, occupational therapists and medical doctors formulated 17 expert-statements on physical rehabilitation in patients aged 0-18 years with osteogenesis imperfecta.

The inherent stochasticity of gene expression in the context of regulatory networks profoundly influences the dynamics of the involved species. Mathematically speaking, the propagators which describe the evolution of such networks in time are typically defined as solutions of the corresponding chemical master equation (CME). However, it is not possible in general to obtain exact solutions to the CME in closed form, which is due largely to its high dimensionality. In the present article, we propose an analytical method for the efficient approximation of these propagators. We illustrate our method on the basis of two categories of stochastic models for gene expression that have been discussed in the literature. The requisite procedure consists of three steps: a probability-generating function is introduced which transforms the CME into (a system of) partial differential equations (PDEs); application of the method of characteristics then yields (a system of) ordinary differential equations (ODEs) which can be solved using dynamical systems techniques, giving closed-form expressions for the generating function; finally, propagator probabilities can be reconstructed numerically from these expressions via the Cauchy integral formula. The resulting 'library' of propagators lends itself naturally to implementation in a Bayesian parameter inference scheme, and can be generalised systematically to related categories of stochastic models beyond the ones considered here.

Molecular regulation of cell fate decisions underlies health and disease. To identify molecules that are active or regulated during a decision, and not before or after, the decision time point is crucial. However, cell fate markers are usually delayed and the time of decision therefore unknown. Fortunately, dividing cells induce temporal correlations in their progeny, which allow for retrospective inference of the decision time point. We present a computational method to infer decision time points from correlated marker signals in genealogies and apply it to differentiating hematopoietic stem cells. We find that myeloid lineage decisions happen generations before lineage marker onsets. Inferred decision time points are in agreement with data from colony assay experiments. The levels of the myeloid transcription factor PU.1 do not change during, but long after the predicted lineage decision event, indicating  that the PU.1/GATA1 toggle switch paradigm cannot explain the initiation of early myeloid lineage choice.

Despite the intrinsically stochastic nature of damage, sensory organs recapitulate normal architecture during repair to maintain function. Here we present a quantitative approach that combines live cell-lineage tracing and multifactorial classification by machine learning to reveal how cell identity and localization are coordinated during organ regeneration. We use the superficial neuromasts in larval zebrafish, which contain three cell classes organized in radial symmetry and a single planar-polarity axis. Visualization of cell-fate transitions at high temporal resolution shows that neuromasts regenerate isotropically to recover geometric order, proportions and polarity with exceptional accuracy. We identify mediolateral position within the growing tissue as the best predictor of cell-fate acquisition. We propose a self-regulatory mechanism that guides the regenerative process to identical outcome with minimal extrinsic information. The integrated approach that we have developed is simple and broadly applicable, and should help define predictive signatures of cellular behavior during the construction of complex tissues., Competing Interests: OV, VL, LP, CM, HL No competing interests declared, (© 2018, Viader-Llargués et al.)

Proliferating stem cells in the adult body are the source of constant regeneration. In the brain, neural stem cells (NSCs) divide to maintain the stem cell population and generate neural progenitor cells that eventually replenish mature neurons and glial cells. How much spatial coordination of NSC division and differentiation is present in a functional brain is an open question. To quantify the patterns of stem cell divisions, one has to (i) identify the pool of NSCs that have the ability to divide, (ii) determine NSCs that divide within a given time window, and (iii) analyze the degree of spatial coordination. Here, we present a bioimage informatics pipeline that automatically identifies GFP expressing NSCs in three-dimensional image stacks of zebrafish brain from whole-mount preparations. We exploit the fact that NSCs in the zebrafish hemispheres are located on a two-dimensional surface and identify between 1,500 and 2,500 NSCs in six brain hemispheres. We then determine the position of dividing NSCs in the hemisphere by EdU incorporation into cells undergoing S-phase and calculate all pairwise NSC distances with three alternative metrics. Finally, we fit a probabilistic model to the observed spatial patterns that accounts for the non-homogeneous distribution of NSCs. We find a weak positive coordination between dividing NSCs irrespective of the metric and conclude that neither strong inhibitory nor strong attractive signals drive NSC divisions in the adult zebrafish brain. © 2017 International Society for Advancement of Cytometry., (© 2017 International Society for Advancement of Cytometry.)

Background: Birthweight of Thoroughbred foals has increased in recent years. It is unknown whether this is associated with increased broodmare obesity or endocrine dysfunction., Objectives: To determine insulin, leptin and triglyceride concentrations in Thoroughbred mares throughout gestation and investigate their association with obesity and foal birthweight., Study Design: Cohort study., Methods: A total of 66 mares were included from 40 days post-breeding. Body condition score (BCS), weight and blood samples were obtained every 60 days throughout gestation. Serum/plasma insulin, leptin and triglyceride concentrations and foal birthweight were recorded. Associations between hormone/triglyceride concentration with BCS, stage of gestation and birthweight were analysed using a linear mixed effects model., Results: Serum insulin concentrations were greater at 1-60 days (4.31 μiu/mL) compared with 241-300 days (3.13 μiu/mL) and 61-120 days (5.33 μiu/mL) compared with 181-240, 241-300 and 301-360 days (3.78, 3.13, 3.37 μiu/mL) gestation (P<0.05). There was no significant hyperinsulinaemia and no association of insulin concentration with BCS. Leptin concentration was greater at 181-240 days (2.28 μg/L, P<0.0001) compared with all other time points and correlated with BCS (P<0.0003). Triglyceride concentration was greater at 241-300 days (0.245 mmol, P<0.02) compared with earlier time points, but was not associated with BCS. Foal birthweight was weakly positively correlated with BCS (r = 0.13, P<0.001) and inversely correlated with leptin concentrations at 61-120 and 241-300 days gestation (r = -0.64, P<0.05)., Main Limitations: Reduction in sample size over the study and tight clustering of BCS., Conclusions: Mare BCS correlated with foal birthweight; obese mares had heavier foals. Significant hyperinsulinaemia was not identified in this population. Increased leptin concentration in early and late gestation was associated with decreased foal birthweight. Further work is required to establish whether leptin concentration in late gestation could predict foal birthweight., (© 2016 EVJ Ltd.)

Motivation: Quantitative large-scale cell microscopy is widely used in biological and medical research. Such experiments produce huge amounts of image data and thus require automated analysis. However, automated detection of cell outlines (cell segmentation) is typically challenging due to, e.g. high cell densities, cell-to-cell variability and low signal-to-noise ratios., Results: Here, we evaluate accuracy and speed of various state-of-the-art approaches for cell segmentation in light microscopy images using challenging real and synthetic image data. The results vary between datasets and show that the tested tools are either not robust enough or computationally expensive, thus limiting their application to large-scale experiments. We therefore developed fastER, a trainable tool that is orders of magnitude faster while producing state-of-the-art segmentation quality. It supports various cell types and image acquisition modalities, but is easy-to-use even for non-experts: it has no parameters and can be adapted to specific image sets by interactively labelling cells for training. As a proof of concept, we segment and count cells in over 200 000 brightfield images (1388 × 1040 pixels each) from a six day time-lapse microscopy experiment; identification of over 46 000 000 single cells requires only about two and a half hours on a desktop computer., Availability and Implementation: C ++ code, binaries and data at https://www.bsse.ethz.ch/csd/software/faster.html ., Contact: oliver.hilsenbeck@bsse.ethz.ch or timm.schroeder@bsse.ethz.ch., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com)

Quantitative analysis of bioimaging data is often skewed by both shading in space and background variation in time. We introduce BaSiC, an image correction method based on low-rank and sparse decomposition which solves both issues. In comparison to existing shading correction tools, BaSiC achieves high-accuracy with significantly fewer input images, works for diverse imaging conditions and is robust against artefacts. Moreover, it can correct temporal drift in time-lapse microscopy data and thus improve continuous single-cell quantification. BaSiC requires no manual parameter setting and is available as a Fiji/ImageJ plugin.

Accessing gene expression at a single-cell level has unraveled often large heterogeneity among seemingly homogeneous cells, which remains obscured when using traditional population-based approaches. The computational analysis of single-cell transcriptomics data, however, still imposes unresolved challenges with respect to normalization, visualization and modeling the data. One such issue is differences in cell size, which introduce additional variability into the data and for which appropriate normalization techniques are needed. Otherwise, these differences in cell size may obscure genuine heterogeneities among cell populations and lead to overdispersed steady-state distributions of mRNA transcript numbers. We present cgCorrect, a statistical framework to correct for differences in cell size that are due to cell growth in single-cell transcriptomics data. We derive the probability for the cell-growth-corrected mRNA transcript number given the measured, cell size-dependent mRNA transcript number, based on the assumption that the average number of transcripts in a cell increases proportionally to the cell's volume during the cell cycle. cgCorrect can be used for both data normalization and to analyze the steady-state distributions used to infer the gene expression mechanism. We demonstrate its applicability on both simulated data and single-cell quantitative real-time polymerase chain reaction (PCR) data from mouse blood stem and progenitor cells (and to quantitative single-cell RNA-sequencing data obtained from mouse embryonic stem cells). We show that correcting for differences in cell size affects the interpretation of the data obtained by typically performed computational analysis.