Sleep and physical activity - the dynamics of bi-directional influences over a fortnight

Study objectives The day-to-next day predictions between physical activity (PA) and sleep are not well known, although they are crucial for advancing public health by delivering valid sleep and physical activity recommendations. We used Big Data to examine cross-lagged time-series of sleep and PA over 14 days and nights. Methods Bi-directional cross-lagged autoregressive pathways over 153,154 days and nights from 12,638 Polar watch users aged 18-60 years (M = 40.1 SD = 10.1; 44.5% female) were analyzed with cross-lagged panel data modeling (RI-CPL). We tested the effects of moderate-to-vigorous physical activity (MVPA) vs. high intensity PA (vigorous, VPA) on sleep duration and quality, and vice versa. Results Within-subject results showed that more minutes spent in VPA the previous day was associated with shorter sleep duration the next night, whereas no effect was observed for MVPA. Longer sleep duration the previous night was associated with less MVPA but more VPA the next day. Neither MVPA nor VPA were associated with subsequent night's sleep quality, but better quality of sleep predicted more MVPA and VPA the next day. Conclusions Sleep duration and PA are bi-directionally linked, but only for vigorous physical activity. More time spent in VPA shortens sleep the next night, yet longer sleep duration increases VPA the next day. The results imply that a 24-h framing for the interrelations of sleep and physical activity is not sufficient - the dynamics can even extend beyond, and are activated specifically for the links between sleep duration and vigorous activity. The results challenge the view that sleep quality can be improved by increasing the amount of PA. Yet, better sleep quality can result in more PA the next day.Peer reviewe

Existence of the magnetization plateau in a class of exactly solvable Ising-Heisenberg chains

The mapping transformation technique is applied to obtain exact results for the spin-1/2 and spin-S (S=1/2,1) Ising-Heisenberg antiferromagnetic chain in the presence of an external magnetic field. Within this scheme, a field-induced first-order metamagnetic transition resulting in multiplateau magnetization curves, is investigated in detail. It is found that the scenario of the plateau formation depends fundamentally on the ratio between Ising and Heisenbrg interaction constants, as well as on the anisotropy strength of the XXZ Heisenberg interaction.Comment: 16 pages, 10 figures, submitted to J. Phys: Condens. Matte

DSP107 combines inhibition of CD47/SIRPα axis with activation of 4-1BB to trigger anticancer immunity

BACKGROUND: Treatment of Diffuse Large B Cell Lymphoma (DLBCL) patients with rituximab and the CHOP treatment regimen is associated with frequent intrinsic and acquired resistance. However, treatment with a CD47 monoclonal antibody in combination with rituximab yielded high objective response rates in patients with relapsed/refractory DLBCL in a phase I trial. Here, we report on a new bispecific and fully human fusion protein comprising the extracellular domains of SIRPα and 4-1BBL, termed DSP107, for the treatment of DLBCL. DSP107 blocks the CD47:SIRPα ‘don’t eat me’ signaling axis on phagocytes and promotes innate anticancer immunity. At the same time, CD47-specific binding of DSP107 enables activation of the costimulatory receptor 4-1BB on activated T cells, thereby, augmenting anticancer T cell immunity. METHODS: Using macrophages, polymorphonuclear neutrophils (PMNs), and T cells of healthy donors and DLBCL patients, DSP107-mediated reactivation of immune cells against B cell lymphoma cell lines and primary patient-derived blasts was studied with phagocytosis assays, T cell activation and cytotoxicity assays. DSP107 anticancer activity was further evaluated in a DLBCL xenograft mouse model and safety was evaluated in cynomolgus monkey. RESULTS: Treatment with DSP107 alone or in combination with rituximab significantly increased macrophage- and PMN-mediated phagocytosis and trogocytosis, respectively, of DLBCL cell lines and primary patient-derived blasts. Further, prolonged treatment of in vitro macrophage/cancer cell co-cultures with DSP107 and rituximab decreased cancer cell number by up to 85%. DSP107 treatment activated 4-1BB-mediated costimulatory signaling by HT1080.4-1BB reporter cells, which was strictly dependent on the SIRPα-mediated binding of DSP107 to CD47. In mixed cultures with CD47-expressing cancer cells, DSP107 augmented T cell cytotoxicity in vitro in an effector-to-target ratio-dependent manner. In mice with established SUDHL6 xenografts, the treatment with human PBMCs and DSP107 strongly reduced tumor size compared to treatment with PBMCs alone and increased the number of tumor-infiltrated T cells. Finally, DSP107 had an excellent safety profile in cynomolgus monkeys. CONCLUSIONS: DSP107 effectively (re)activated innate and adaptive anticancer immune responses and may be of therapeutic use alone and in combination with rituximab for the treatment of DLBCL patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-022-02256-x

Metabolic syndrome and risk factors for cardiovascular disease: are nonagenarians protected?

This study assessed cardiovascular disease risk factors in three groups of human subjects aged 20–34 [young, 20 male (M)/33 female (F)], 60–74 (aged, 29M/29F), and > 90 years (nonagenarian, 47M/50F). Components of the metabolic syndrome, cardiovascular disease, and markers of inflammation and oxidative stress were assessed. Nonagenarians weighed less than the two other groups (P < 0.001); however, there was no difference in percent fat among the three groups. Aged individuals had the highest prevalence of the metabolic syndrome (P < 0.001) according to the Adult Treatment Panel III classification. Both fibrinogen and homocysteine concentrations were significantly higher in the nonagenarians compared to younger groups. However, there were no significant differences between groups in fasting insulin, high sensitive C-reactive protein, and plasminogen activator inhibitor 1 concentrations. There were also no relationships between inflammation/ oxidative stress and the metabolic syndrome or cardiovascular disease although nonagenarians appear to be protected from oxidative damage to DNA

Disruption of Growth Hormone Receptor Prevents Calorie Restriction from Improving Insulin Action and Longevity

Most mutations that delay aging and prolong lifespan in the mouse are related to somatotropic and/or insulin signaling. Calorie restriction (CR) is the only intervention that reliably increases mouse longevity. There is considerable phenotypic overlap between long-lived mutant mice and normal mice on chronic CR. Therefore, we investigated the interactive effects of CR and targeted disruption or knock out of the growth hormone receptor (GHRKO) in mice on longevity and the insulin signaling cascade. Every other day feeding corresponds to a mild (i.e. 15%) CR which increased median lifespan in normal mice but not in GHRKO mice corroborating our previous findings on the effects of moderate (30%) CR on the longevity of these animals. To determine why insulin sensitivity improves in normal but not GHRKO mice in response to 30% CR, we conducted insulin stimulation experiments after one year of CR. In normal mice, CR increased the insulin stimulated activation of the insulin signaling cascade (IR/IRS/PI3K/AKT) in liver and muscle. Livers of GHRKO mice responded to insulin by increased activation of the early steps of insulin signaling, which was dissipated by altered PI3K subunit abundance which putatively inhibited AKT activation. In the muscle of GHRKO mice, there was elevated downstream activation of the insulin signaling cascade (IRS/PI3K/AKT) in the absence of elevated IR activation. Further, we found a major reduction of inhibitory Ser phosphorylation of IRS-1 seen exclusively in GHRKO muscle which may underpin their elevated insulin sensitivity. Chronic CR failed to further modify the alterations in insulin signaling in GHRKO mice as compared to normal mice, likely explaining or contributing to the absence of CR effects on insulin sensitivity and longevity in these long-lived mice

Ectopic PDX-1 Expression Directly Reprograms Human Keratinocytes along Pancreatic Insulin-Producing Cells Fate

BACKGROUND: Cellular differentiation and lineage commitment have previously been considered irreversible processes. However, recent studies have indicated that differentiated adult cells can be reprogrammed to pluripotency and, in some cases, directly into alternate committed lineages. However, although pluripotent cells can be induced in numerous somatic cell sources, it was thought that inducing alternate committed lineages is primarily only possible in cells of developmentally related tissues. Here, we challenge this view and analyze whether direct adult cell reprogramming to alternate committed lineages can cross the boundaries of distinct developmental germ layers. METHODOLOGY/PRINCIPAL FINDINGS: We ectopically expressed non-integrating pancreatic differentiation factors in ectoderm-derived human keratinocytes to determine whether these factors could directly induce endoderm-derived pancreatic lineage and β-cell-like function. We found that PDX-1 and to a lesser extent other pancreatic transcription factors, could rapidly and specifically activate pancreatic lineage and β-cell-like functional characteristics in ectoderm-derived human keratinocytes. Human keratinocytes transdifferentiated along the β cell lineage produced processed and secreted insulin in response to elevated glucose concentrations. Using irreversible lineage tracing for KRT-5 promoter activity, we present supporting evidence that insulin-positive cells induced by ectopic PDX-1 expression are generated in ectoderm derived keratinocytes. CONCLUSIONS/SIGNIFICANCE: These findings constitute the first demonstration of human ectoderm cells to endoderm derived pancreatic cells transdifferentiation. The study represents a proof of concept which suggests that transcription factors induced reprogramming is wider and more general developmental process than initially considered. These results expanded the arsenal of adult cells that can be used as a cell source for generating functional endocrine pancreatic cells. Directly reprogramming somatic cells into alternate desired tissues has important implications in developing patient-specific, regenerative medicine approaches

Metrics reloaded: Pitfalls and recommendations for image analysis validation

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, our large international expert consortium created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. The framework was developed in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint - a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool, which also provides a point of access to explore weaknesses, strengths and specific recommendations for the most common validation metrics. The broad applicability of our framework across domains is demonstrated by an instantiation for various biological and medical image analysis use cases

Common Limitations of Image Processing Metrics:A Picture Story

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide.Comment: This is a dynamic paper on limitations of commonly used metrics. The current version discusses metrics for image-level classification, semantic segmentation, object detection and instance segmentation. For missing use cases, comments or questions, please contact [email protected] or [email protected]. Substantial contributions to this document will be acknowledged with a co-authorshi

Reward-Related Dorsal Striatal Activity Differences between Former and Current Cocaine Dependent Individuals during an Interactive Competitive Game

Cocaine addiction is characterized by impulsivity, impaired social relationships, and abnormal mesocorticolimbic reward processing, but their interrelationships relative to stages of cocaine addiction are unclear. We assessed blood-oxygenation-level dependent (BOLD) signal in ventral and dorsal striatum during functional magnetic resonance imaging (fMRI) in current (CCD; n = 30) and former (FCD; n = 28) cocaine dependent subjects as well as healthy control (HC; n = 31) subjects while playing an interactive competitive Domino game involving risk-taking and reward/punishment processing. Out-of-scanner impulsivity-related measures were also collected. Although both FCD and CCD subjects scored significantly higher on impulsivity-related measures than did HC subjects, only FCD subjects had differences in striatal activation, specifically showing hypoactivation during their response to gains versus losses in right dorsal caudate, a brain region linked to habituation, cocaine craving and addiction maintenance. Right caudate activity in FCD subjects also correlated negatively with impulsivity-related measures of self-reported compulsivity and sensitivity to reward. These findings suggest that remitted cocaine dependence is associated with striatal dysfunction during social reward processing in a manner linked to compulsivity and reward sensitivity measures. Future research should investigate the extent to which such differences might reflect underlying vulnerabilities linked to cocaine-using propensities (e.g., relapses)

Understanding metric-related pitfalls in image analysis validation

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.Comment: Shared first authors: Annika Reinke, Minu D. Tizabi; shared senior authors: Paul F. J\"ager, Lena Maier-Hei