Dances of death: Macabre mirrors of an unequal society

Objectives Between 1400 and 1800, Dances of Death were a popular art form depicting a metaphorical encounter between Death and representatives of a stratified human society. We review the thematic development of Dances of Death and study the development of social critique. Methods We first assembled a full catalogue of all Dances of Death created between 1400 and 1800. We then analyzed patterns of spatiotemporal diffusion and made an in-depth hermeneutic study of the combined texts and images of a carefully selected set of 20 Dances of Death, comparing four distinct periods (1425-1525, 1525-1600, 1600-1650, and 1650-1800). Results We identified more than 500 Dances of Death. It was only in its first stage of development, coinciding with the Pre-Reformation (1425-1525), that social critique was very prominent. This was represented in four forms: explicit references to social (in) equality, to failures of t

Visualization of perfusion changes with laser speckle contrast imaging using the method of motion history image

Laser speckle contrast imaging (LSCI) is a real-time imaging modality reflecting microvascular perfusion. We report on the application of the motion history image (MHI) method on LSCI data obtained from the two hemispheres of a mouse. Through the generation of a single image, MHI stresses the microvascular perfusion changes. Our experimental results performed during a pinprick-triggered spreading depolarization demonstrate the effectiveness of MHI: MHI allows the visualization of perfusion changes without loss of resolution and definition. Moreover, MHI provides close results to the ones given by the generalized differences (GD) algorithm. However, MHI has the advantage of giving information on the temporal evolution of the perfusion variations, which GD does not

Monitoring microvascular perfusion variations with laser speckle contrast imaging using a view-based temporal template method

Purpose Laser speckle contrast imaging (LSCI) continues to gain an increased interest in clinical and research studies to monitor microvascular perfusion. Due to its high spatial and temporal resolutions, LSCI may lead to a large amount of data. The analysis of such data, as well as the determination of the regions where the perfusion varies, can become a lengthy and tedious task. We propose here to analyze if a view-based temporal template method, the motion history image (MHI) algorithm, may be of use in detecting the perfusion variations locations. Methods LSCI data recorded during three different kinds of perfusion variations are considered: (i) cerebral blood flow during spreading depolarization (SD) in a mouse; (ii) cerebral blood flow during SD in a rat; (iii) cerebral blood flow during cardiac arrest in a rat. Each of these recordings was processed with MHI. Results We show that, for the three pathophysiological situations, MHI identifies the area in which perfusion evolves with time. The results are more easily obtained compared with a visual inspection of all of the frames constituting the recordings. MHI also has the advantage of relying on a rather simple algorithm. Conclusions MHI can be tested in clinical and research studies to aid the user in perfusion analyses

Stroke-prone salt-sensitive spontaneously hypertensive rats show higher susceptibility to spreading depolarization (SD) and altered hemodynamic responses to SD

Spreading depolarization (SD) occurs in a plethora of clinical conditions including migraine aura, delayed ischemia after subarachnoid hemorrhage and malignant hemispheric stroke. It describes waves of near-breakdown of ion homeostasis, particularly Na(+) homeostasis in brain gray matter. SD induces tone alterations in resistance vessels, causing either hyperperfusion in healthy tissue; or hypoperfusion (inverse hemodynamic response = spreading ischemia) in tissue at risk. Observations from mice with genetic dysfunction of the ATP1A2-encoded α(2)-isoform of Na(+)/K(+)-ATPase (α(2)NaKA) suggest a mechanistic link between (1) SD, (2) vascular dysfunction, and (3) salt-sensitive hypertension via α(2)NaKA. Thus, α(2)NaKA-dysfunctional mice are more susceptible to SD and show a shift toward more inverse hemodynamic responses. α(2)NaKA-dysfunctional patients suffer from familial hemiplegic migraine type 2, a Mendelian model disease of SD. α(2)NaKA-dysfunctional mice are also a genetic model of salt-sensitive hypertension. To determine whether SD thresholds and hemodynamic responses are also altered in other genetic models of salt-sensitive hypertension, we examined these variables in stroke-prone spontaneously hypertensive rats (SHRsp). Compared with Wistar Kyoto control rats, we found in SHRsp that electrical SD threshold was significantly reduced, propagation speed was increased, and inverse hemodynamic responses were prolonged. These results may have relevance to both migraine with aura and stroke

School-based prevention for adolescent Internet addiction: prevention is the key. A systematic literature review

Adolescents’ media use represents a normative need for information, communication, recreation and functionality, yet problematic Internet use has increased. Given the arguably alarming prevalence rates worldwide and the increasingly problematic use of gaming and social media, the need for an integration of prevention efforts appears to be timely. The aim of this systematic literature review is (i) to identify school-based prevention programmes or protocols for Internet Addiction targeting adolescents within the school context and to examine the programmes’ effectiveness, and (ii) to highlight strengths, limitations, and best practices to inform the design of new initiatives, by capitalizing on these studies’ recommendations. The findings of the reviewed studies to date presented mixed outcomes and are in need of further empirical evidence. The current review identified the following needs to be addressed in future designs to: (i) define the clinical status of Internet Addiction more precisely, (ii) use more current psychometrically robust assessment tools for the measurement of effectiveness (based on the most recent empirical developments), (iii) reconsider the main outcome of Internet time reduction as it appears to be problematic, (iv) build methodologically sound evidence-based prevention programmes, (v) focus on skill enhancement and the use of protective and harm-reducing factors, and (vi) include IA as one of the risk behaviours in multi-risk behaviour interventions. These appear to be crucial factors in addressing future research designs and the formulation of new prevention initiatives. Validated findings could then inform promising strategies for IA and gaming prevention in public policy and education

Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Estimates of protection levels against SARS-CoV-2 infection and severe COVID-19 in Germany before the 2022/2023 winter season: the IMMUNEBRIDGE project

PURPOSE: Despite the need to generate valid and reliable estimates of protection levels against SARS-CoV-2 infection and severe course of COVID-19 for the German population in summer 2022, there was a lack of systematically collected population-based data allowing for the assessment of the protection level in real time. METHODS: In the IMMUNEBRIDGE project, we harmonised data and biosamples for nine population-/hospital-based studies (total number of participants n = 33,637) to provide estimates for protection levels against SARS-CoV-2 infection and severe COVID-19 between June and November 2022. Based on evidence synthesis, we formed a combined endpoint of protection levels based on the number of self-reported infections/vaccinations in combination with nucleocapsid/spike antibody responses ("confirmed exposures"). Four confirmed exposures represented the highest protection level, and no exposure represented the lowest. RESULTS: Most participants were seropositive against the spike antigen; 37% of the participants ≥ 79 years had less than four confirmed exposures (highest level of protection) and 5% less than three. In the subgroup of participants with comorbidities, 46-56% had less than four confirmed exposures. We found major heterogeneity across federal states, with 4-28% of participants having less than three confirmed exposures. CONCLUSION: Using serological analyses, literature synthesis and infection dynamics during the survey period, we observed moderate to high levels of protection against severe COVID-19, whereas the protection against SARS-CoV-2 infection was low across all age groups. We found relevant protection gaps in the oldest age group and amongst individuals with comorbidities, indicating a need for additional protective measures in these groups

Serum metabolome associated with severity of acute traumatic brain injury

Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relationship to severity of injury and patient outcome. We performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We identified panels of metabolites specifically associated with TBI severity and patient outcomes. Choline phospholipids (lysophosphatidylcholines, ether phosphatidylcholines and sphingomyelins) were inversely associated with TBI severity and were among the strongest predictors of TBI patient outcomes, which was further confirmed in a separate validation dataset of 558 patients. The observed metabolic patterns may reflect different pathophysiological mechanisms, including protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain