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Objectives: Some people do not fully recover from an acute viral infection and experience persistent symptoms or incomplete recovery for months or even years. This is not unique to the SARS-CoV-2 virus and history shows that post-viral conditions like post COVID-19 condition, also referred to as Long Covid, are not new. In particular, during and after pandemics caused by respiratory viruses in which large parts of the population were infected or exposed, professional and public attention was increased, not least because of the large number of people affected.Methods: Given the current relevance of the topic, this article aims to narratively review and summarize the literature on post-viral symptoms during past pandemics and to supplement and illustrate it with Swiss examples from the pandemics of 1890, 1918–1920 and later.Results: Post-viral diseases were an increasingly emphasised health topic during and after past pandemics triggered by respiratory infections over the last 150 years.Conclusion: In the next pandemic, it should not be surprising that post-viral conditions will again play a role, and pandemic plans should reflect this.

Spraying is a common way to distribute occupational products, but it puts worker's health at risk by exposing them to potentially harmful particles and gases. The objective of this study is to use time-resolved measurements to gain an understanding of spray applications at the process level and to compare them to predictions of exposure models. We used proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) at 1-s time resolution to monitor the gas phase concentration of the solvents acetone, ethanol, butyl acetate, xylene and 1-methoxy-2-propy acetate during outdoor spraying and indoor drying of metal plate under various conditions of outdoor air supply. We found that during spraying, gas-phase exposure was dominated by the more volatile solvents acetone and ethanol, which exhibited strong concentration variations due to the outdoor winds. During drying, exposure strongly depended on the strength of ventilation. Under conditions with high supply of outdoor air, our measurements show a near-exponential decay of the solvent concentrations during drying. Conversely, under conditions without outdoor air supply, the drying process required hours, during which the less volatile solvents passed through a concentration maximum in the gas phase, so that the exposure during drying exceeded the exposure during spraying. The concentrations measured during spraying were then compared for each of the substances individually with the predictions of the exposure models ECETOC TRA, Stoffenmanager, and ART using TREXMO. For these conditions, ECETOC TRA and Stoffenmanager predicted exposures in the measured concentration range, albeit not conservative for all solvents and each application. In contrast, ART largely overestimated the exposure for the more volatile solvents acetone and ethanol and slightly underestimated exposure to 1M2PA for one spraying. ECETOC TRA and ART do not have options to predict exposure during drying. Stoffenmanager has the option to predict drying together with spraying, but not to predict the drying phase independently. Our study demonstrates the importance of considering both the spray cloud and solvent evaporation during the drying process. To improve workplace safety, there is a critical need for enhanced exposure models and comprehensive datasets for calibration and validation covering a broader range of exposure situations.

Objectives: The COVID-19 pandemic highlights questions regarding reinfections and immunity resulting from vaccination and/or previous illness. Studies addressing related questions for historical pandemics are limited.Methods: We revisit an unnoticed archival source on the 1918/19 influenza pandemic. We analysed individual responses to a medical survey completed by an entire factory workforce in Western Switzerland in 1919.Results: Among the total of n = 820 factory workers, 50.2% reported influenza-related illness during the pandemic, the majority of whom reported severe illness. Among male workers 47.4% reported an illness vs. 58.5% of female workers, although this might be explained by varied age distribution for each sex (median age was 31 years old for men, vs. 22 years old for females). Among those who reported illness, 15.3% reported reinfections. Reinfection rates increased across the three pandemic waves. The majority of subsequent infections were reported to be as severe as the first infection, if not more. Illness during the first wave, in the summer of 1918, was associated with a 35.9% (95%CI, 15.7–51.1) protective effect against reinfections during later waves.Conclusion: Our study draws attention to a forgotten constant between multi-wave pandemics triggered by respiratory viruses: Reinfection and cross-protection have been and continue to be a key topic for health authorities and physicians in pandemics, becoming increasingly important as the number of waves increases.

Epilepsy surgery can be a very effective therapy in medication refractory patients. During patient evaluation intracranial EEG is analyzed by clinical experts to identify the brain tissue generating epileptiform events. Quantitative EEG analysis increasingly complements this approach in research settings, but not yet in clinical routine. We investigate the correspondence between epileptiform events and a specific quantitative EEG marker. We analyzed 99 preictal epochs of multichannel intracranial EEG of 40 patients with mixed etiologies. Time and channel of occurrence of epileptiform events (spikes, slow waves, sharp waves, fast oscillations) were annotated by a human expert and non-linear excess interrelations were calculated as a quantitative EEG marker. We assessed whether the visually identified preictal events predicted channels that belonged to the seizure onset zone, that were later resected or that showed strong non-linear interrelations. We also investigated whether the seizure onset zone or the resection were predicted by channels with strong non-linear interrelations. In patients with temporal lobe epilepsy (32 of 40), epileptic spikes and the seizure onset zone predicted the resected brain tissue much better in patients with favorable seizure control after surgery than in unfavorable outcomes. Beyond that, our analysis did not reveal any significant associations with epileptiform EEG events. Specifically, none of the epileptiform event types did predict non-linear interrelations. In contrast, channels with strong non-linear excess EEG interrelations predicted the resected channels better in patients with temporal lobe epilepsy and favorable outcome. Also in the small number of patients with seizure onset in the frontal and parietal lobes, no association between epileptiform events and channels with strong non-linear excess EEG interrelations was detectable. In contrast to patients with temporal seizure onset, EEG channels with strong non-linear excess interrelations did neither predict the seizure onset zone nor the resection of these patients or allow separation between patients with favorable and unfavorable seizure control. Our study indicates that non-linear excess EEG interrelations are not strictly associated with epileptiform events, which are one key concept of current clinical EEG assessment. Rather, they may provide information relevant for surgery planning in temporal lobe epilepsy. Our study suggests to incorporate quantitative EEG analysis in the workup of clinical cases. We make the EEG epochs and expert annotations publicly available in anonymized form to foster similar analyses for other quantitative EEG methods.

Patients undergoing allogeneic hematopoietic stem cell transplantation (HSCT) are challenged with severe side effects, which are propagated by mucosal barrier disruption, and the related microbial translocation and systemic inflammation. Glucagon-like peptide-1 (GLP-1), a well-known incretin hormone, possesses anti-inflammatory properties and promotes regeneration of damaged intestinal epithelium in animal studies. We hypothesized that the immense inter-individual variation in the degree of mucosal damage and systemic inflammation, seen after HSCT is influenced by endogenous GLP-1 and could be related to acute post-transplant complications. In this prospective study we measured serial weekly fasting plasma GLP-1, along with C-reactive protein (CRP), and citrulline in 82 pediatric patients during allogeneic HSCT together with a fasting plasma GLP-1 in sex- and age-matched healthy controls. Overall, GLP-1 levels were increased in the patients during the course of HSCT compared with the controls, but tended to decrease post-transplant, most pronounced in patients receiving high-intensity conditioning regimen. The increase in CRP seen in the early post-transplant phase was significantly lower from day +8 to +13 in patients with GLP-1 above the upper quartile (>10 pmol/L) at day 0 (all P ≤ 0.03). Similar findings were seen for peak CRP levels after adjusting for type of conditioning (-47.0%; 95% CI, -8.1 – -69.4%, P = 0.02). Citrulline declined significantly following the transplantation illustrating a decrease in viable enterocytes, most evident in patients receiving high-intensity conditioning regimen. GLP-1 levels at day 0 associated with the recovery rate of citrulline from day 0 to +21 (34 percentage points (pp)/GLP-1 doubling; 95% CI, 10 – 58pp; P = 0. 008) and day 0 to day +90 (48 pp/GLP-1 doubling; 95% CI, 17 – 79pp; P = 0. 004), also after adjustment for type of conditioning. This translated into a reduced risk of acute graft-versus-host disease (aGvHD) in patients with highest day 0 GLP-1 levels (>10 pmol/L) (cause-specific HR: 0.3; 95% CI, 0.2 – 0.9, P = 0.02). In conclusion, this study strongly suggests that GLP-1 influences regeneration of injured epithelial barriers and ameliorates inflammatory responses in the early post-transplant phase.

IntroductionPhysical fitness benefits health. However, there is a research gap on how physical fitness, particularly aerobic endurance capacity and muscle power, is influenced by residential altitude, blood parameters, weight, and other cofactors in a population living at low to moderate altitudes (300–2100 masl).Materials and MethodsWe explored how endurance and muscle power performance changes with residential altitude, Body Mass Index (BMI), hemoglobin and creatinine levels among 108,677 Swiss men aged 18–22 years (covering >90% of Swiss birth cohorts) conscripted to the Swiss Armed Forces between 2007 and 2012. The test battery included a blood test of about 65%, a physical evaluation of about 85%, and the BMI of all conscripts.ResultsResidential altitude was significantly associated with endurance (p < 0.001) but not with muscle power performance (p = 0.858) after adjusting for all available cofactors. Higher BMI showed the greatest negative association with both endurance and muscle power performance. For muscle power performance, the association with creatinine levels was significant. Elevated C-reactive protein (CRP) and hemoglobin levels were stronger contributors in explaining endurance than muscle power performance.ConclusionWe found a significant association between low to moderate residential altitude and aerobic endurance capacity even after adjustment for hemoglobin, creatinine, BMI and sociodemographic factors. Non-assessed factors such as vitamin D levels, air pollution, and lifestyle aspects may explain the presented remaining association partially and could also be associated with residential altitude. Monitoring the health and fitness of young people and their determinants is important and of practical concern for disease prevention and public health implications.

Network models of brain dynamics provide valuable insight into the healthy functioning of the brain and how this breaks down in disease. A pertinent example is the use of network models to understand seizure generation (ictogenesis) in epilepsy. Recently, computational models have emerged to aid our understanding of seizures and to predict the outcome of surgical perturbations to brain networks. Such approaches provide the opportunity to quantify the effect of removing regions of tissue from brain networks and thereby search for the optimal resection strategy. Here, we use computational models to elucidate how sets of nodes contribute to the ictogenicity of networks. In small networks we fully elucidate the ictogenicity of all possible sets of nodes and demonstrate that the distribution of ictogenicity across sets depends on network topology. However, the full elucidation is a combinatorial problem that becomes intractable for large networks. Therefore, we combine computational models with a genetic algorithm to search for minimal sets of nodes that contribute significantly to ictogenesis. We demonstrate the potential applicability of these methods in practice by identifying optimal sets of nodes to resect in networks derived from 20 individuals who underwent resective surgery for epilepsy. We show that they have the potential to aid epilepsy surgery by suggesting alternative resection sites as well as facilitating the avoidance of brain regions that should not be resected.

High frequency oscillations (HFOs) are traditional biomarkers to identify the epileptogenic tissue during presurgical evaluation in pharmacoresistant epileptic patients. Recently, the resection of brain tissue exhibiting coupling between the amplitude of HFOs and the phase of low frequencies demonstrated a more favorable surgical outcome. Here we compare the predictive value of ictal HFOs and four methods for quantifying the ictal phase-amplitude coupling, namely mean vector length, phase-locked high gamma, phase locking value, and modulation index (MI). We analyzed 32 seizures from 16 patients to identify the channels that exhibit HFOs and phase-locked HFOs during seizures. We compared the resection ratio, defined as the percentage of channels exhibiting coupling located in the resected tissue, with the postsurgical outcome. We found that the MI is the only method to show a significant difference between the resection ratios of patients with good and poor outcomes. We further show that the whole seizure, not only the onset, is critical to assess epileptogenicity using the phase-locked HFOs. We postulate that the superiority of MI stems from its capacity to assess coupling of discrete HFO events and its independence from the HFO power. These results confirm that quantitative analysis of HFOs can boost presurgical evaluation and indicate the paramount importance of algorithm selection for clinical applications.

Recent studies have shown that mathematical models can be used to analyze brain networks by quantifying how likely they are to generate seizures. In particular, we have introduced the quantity termed brain network ictogenicity (BNI), which was demonstrated to have the capability of differentiating between functional connectivity (FC) of healthy individuals and those with epilepsy. Furthermore, BNI has also been used to quantify and predict the outcome of epilepsy surgery based on FC extracted from pre-operative ictal intracranial electroencephalography (iEEG). This modeling framework is based on the assumption that the inferred FC provides an appropriate representation of an ictogenic network, i.e., a brain network responsible for the generation of seizures. However, FC networks have been shown to change their topology depending on the state of the brain. For example, topologies during seizure are different to those pre- and post-seizure. We therefore sought to understand how these changes affect BNI. We studied peri-ictal iEEG recordings from a cohort of 16 epilepsy patients who underwent surgery and found that, on average, ictal FC yield higher BNI relative to pre- and post-ictal FC. However, elevated ictal BNI was not observed in every individual, rather it was typically observed in those who had good post-operative seizure control. We therefore hypothesize that elevated ictal BNI is indicative of an ictogenic network being appropriately represented in the FC. We evidence this by demonstrating superior model predictions for post-operative seizure control in patients with elevated ictal BNI.

Interictal spikes (IS) are one of the major hallmarks of epilepsy. Understanding the factors promoting or suppressing IS would increase our comprehension of epilepsy and possibly open new avenues for therapy. Sleep strongly influences epileptic activity, and the modulatory effects of the different sleep stages on IS have been studied for decades. However, several aspects are still disputed, in particular the role of sleep spindles and slow waves in the activation of IS during Non-REM sleep. Here, we correlate the rate of IS with quantitative measures derived from stereo-EEG during one Non-REM cycle in 10 patients suffering from drug-resistant epilepsy due to type 2 focal cortical dysplasia. We show that the IS rate (ISR) is positively correlated with sigma power (a surrogate for sleep-spindle density) but negatively correlated with delta power (surrogate for slow wave activity). In addition, we present two new indices for quantifying the spatial and temporal instability of sleep. We found that both instability indices are correlated with a high ISR. The main contribution of this study is to confirm the suppressive effect of stable deep sleep on IS. This result might influence future guidelines for therapy of patients suffering from epilepsy and sleep disorders.

Background: Periodic leg movements during sleep (PLMS) consist of involuntary periodic movements of the lower extremities. The debated functional relevance of PLMS is based on correlation of clinical parameters with the PLMS index (PLMI). However, periodicity in movements may not be reflected best by the PLMI. Here, an approach novel to the field of sleep research is used to reveal intrinsic periodicity in inter movement intervals (IMI) in patients with PLMS. Methods: Three patient groups of 10 patients showing PLMS with OSA (group 1), PLMS without OSA or RLS (group 2) and PLMS with RLS (group 3) were considered. Applying the ``unfolding'' procedure, a method developed in statistical physics, enhanced or even revealed intrinsic periodicity of PLMS. The degree of periodicity of PLMS was assessed by fitting one-parameter distributions to the unfolded IMI distributions. Finally, it was investigated whether the shape of the IMI distributions allows to separate patients into different groups. Results: Despite applying the unfolding procedure, periodicity was neither homogeneous within nor considerably different between the three clinically defined groups. Data-driven clustering revealed more homogeneous and better separated clusters. However, they consisted of patients with heterogeneous demographic data and comorbidities, including RLS {em and} OSA. Conclusions: The unfolding procedure may be necessary to enhance or reveal periodicity. Thus this method is proposed as a pre-processing step before analyzing PLMS statistically. Data-driven clustering yields much more reasonable results when applied to the unfolded IMI distributions than to the original data. Despite this effort no correlation between the {em degree} of periodicity and demographic data or comorbidities was found. However, there were indications that the {em nature} of the periodicity might be determined by long-range interactions between LM of patients with PLMS and OSA.