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Background: H5N1 influenza vaccines, including live intranasal, appear to be relatively less immunogenic compared to seasonal analogs. The main influenza virus surface glycoprotein hemagglutinin (HA) of highly pathogenic avian influenza viruses (HPAIV) was shown to be more susceptible to acidic pH treatment than that of human or low pathogenic avian influenza viruses. The acidification machinery of the human nasal passageway in response to different irritation factors starts to release protons acidifying the mucosal surface (down to pH of 5.2). We hypothesized that the sensitivity of H5 HA to the acidic environment might be the reason for the low infectivity and immunogenicity of intranasal H5N1 vaccines for mammals. Methodology/Principal Findings: We demonstrate that original human influenza viruses infect primary human nasal epithelial cells at acidic pH (down to 5.4), whereas H5N1 HPAIVs lose infectivity at pH <= 5.6. The HA of A/Vietnam/1203/04 was modified by introducing the single substitution HA2 58K -> I, decreasing the pH of the HA conformational change. The H5N1 reassortants containing the indicated mutation displayed an increased resistance to acidic pH and high temperature treatment compared to those lacking modification. The mutation ensured a higher viral uptake as shown by immunohistochemistry in the respiratory tract of mice and 25 times lower mouse infectious dose50. Moreover, the reassortants keeping 58K -> I mutation designed as a live attenuated vaccine candidate lacking an NS1 gene induced superior systemic and local antibody response after the intranasal immunization of mice. Conclusion/Significance: Our finding suggests that an efficient intranasal vaccination with a live attenuated H5N1 virus may require a certain level of pH and temperature stability of HA in order to achieve an optimal virus uptake by the nasal epithelial cells and induce a sufficient immune response. The pH of the activation of the H5 HA protein may play a substantial role in the infectivity of HPAIVs for mammals.
Background: During the COVID-19 pandemic, decreased volumes of acute stroke admissions were reported. We aimed to examine whether subarachnoid hemorrhage (SAH) volumes demonstrated similar declines in our department. Furthermore, the impact of pandemic on disease progression should be analyzed.
Methods: We conducted a retrospective study in neurosurgical department of university hospital Frankfurt including patients with the diagnosis of aneurysmal SAH during the first year of COVID-pandemic. One year cumulative volume for SAH hospitalization procedures were compared to the one-year period before (03/2020–02/2021 versus 03/2019–02/2020) and the last 5 pre-COVID-pandemic years (2015-2020). All relevant patient characteristics concerning family history, disease history, clinical condition at admission, active/past COVID-infection, treatment management, complications and outcome were analyzed.
Results: There was a decline in SAH hospitalizations, with 84 admissions in the year immediately before and 56 admissions during the pandemic, without reaching a significance. No significant difference in analyzed patient characteristics including clinical condition at onset, treatment, complications and outcome, between 56 SAH patients admitted during COVID pandemic and treated patients in the last 5 years in pre-COVID period were found. Using a multivariable analysis, we detected young age (p<0.05;OR4,2) and no existence of early hydrocephalus (p<0.05;OR0,13) as important factors for a favorable outcome (mRS≤0-2) after aSAH during the COVID-pandemic. A past COVID-infection was detected in young patients suffering from aSAH (Age< 50years, p<0.05;OR10,5) with increased rate of cerebral vasospasm after SAH onset (p<0.05;OR26). Nevertheless, past COVID-infection did not reach a significance as a high risk factor for unfavorable outcome.
Conclusion: There was a relative decrease in the volume of SAH during the COVID-19 pandemic. Despite of extremely different conditions of hospitalization, there was no impairing significant effect on treatment and outcome of admitted SAH patients. A past COVID-infection seemed not to be a relevant limiting factor concerning favorable outcome.
Creatinine and proteinuria are used to monitor kidney transplant patients. However, renal biopsies are needed to diagnose renal graft rejection. Here, we assessed whether the quantification of different urinary cells would allow non-invasive detection of rejection. Urinary cell numbers of CD4+ and CD8+ T cells, monocytes/macrophages, tubular epithelial cells (TEC), and podocalyxin(PDX)-positive cells were determined using flow cytometry and were compared to biopsy results. Urine samples of 63 renal transplant patients were analyzed. Patients with transplant rejection had higher amounts of urinary T cells than controls; however, patients who showed worsening graft function without rejection had similar numbers of T cells. T cells correlated with histological findings (interstitial inflammation p = 0.0005, r = 0.70; tubulitis p = 0.006, r = 0.58). Combining the amount of urinary T cells and TEC, or T cells and PDX+ cells, yielded a significant segregation of patients with rejection from patients without rejection (all p < 0.01, area under the curve 0.89–0.91). Urinary cell populations analyzed by flow cytometry have the potential to introduce new monitoring methods for kidney transplant patients. The combination of urinary T cells, TEC, and PDX-positive cells may allow non-invasive detection of transplant rejection.
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
Dendritic spines are crucial for excitatory synaptic transmission as the size of a spine head correlates with the strength of its synapse. The distribution of spine head sizes follows a lognormal-like distribution with more small spines than large ones. We analysed the impact of synaptic activity and plasticity on the spine size distribution in adult-born hippocampal granule cells from rats with induced homo- and heterosynaptic long-term plasticity in vivo and CA1 pyramidal cells from Munc-13-1-Munc13-2 knockout mice with completely blocked synaptic transmission. Neither induction of extrinsic synaptic plasticity nor the blockage of presynaptic activity degrades the lognormal-like distribution but changes its mean, variance and skewness. The skewed distribution develops early in the life of the neuron. Our findings and their computational modelling support the idea that intrinsic synaptic plasticity is sufficient for the generation, while a combination of intrinsic and extrinsic synaptic plasticity maintains lognormal like distribution of spines.
Nucleation and growth of aerosol particles from atmospheric vapors constitutes a major source of global cloud condensation nuclei (CCN). The fraction of newly formed particles that reaches CCN sizes is highly sensitive to particle growth rates, especially for particle sizes <10 nm, where coagulation losses to larger aerosol particles are greatest. Recent results show that some oxidation products from biogenic volatile organic compounds are major contributors to particle formation and initial growth. However, whether oxidized organics contribute to particle growth over the broad span of tropospheric temperatures remains an open question, and quantitative mass balance for organic growth has yet to be demonstrated at any temperature. Here, in experiments performed under atmospheric conditions in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN), we show that rapid growth of organic particles occurs over the range from −25 ∘C to 25 ∘C. The lower extent of autoxidation at reduced temperatures is compensated by the decreased volatility of all oxidized molecules. This is confirmed by particle-phase composition measurements, showing enhanced uptake of relatively less oxygenated products at cold temperatures. We can reproduce the measured growth rates using an aerosol growth model based entirely on the experimentally measured gas-phase spectra of oxidized organic molecules obtained from two complementary mass spectrometers. We show that the growth rates are sensitive to particle curvature, explaining widespread atmospheric observations that particle growth rates increase in the single-digit-nanometer size range. Our results demonstrate that organic vapors can contribute to particle growth over a wide range of tropospheric temperatures from molecular cluster sizes onward.
The COVID-19 pandemic has triggered health-related anxiety in ways that undermine peoples’ mental and physical health. Contextual factors such as living in a high-risk area might further increase the risk of health deterioration. Based on the Social Identity Approach, we argue that social identities can not only be local that are characterized by social interactions, but also be global that are characterized by a symbolic sense of togetherness and that both of these can be a basis for health. In line with these ideas, we tested how identification with one’s family and with humankind relates to stress and physical symptoms while experiencing health-related anxiety and being exposed to contextual risk factors. We tested our assumptions in a representative sample (N = 974) two-wave survey study with a 4-week time lag. The results show that anxiety at Time 1 was positively related to stress and physical symptoms at Time 2. Feeling exposed to risk factors related to lower physical health, but was unrelated to stress. Family identification and identification with humankind were both negatively associated with subsequent stress and family identification was negatively associated with subsequent physical symptoms. These findings suggest that for social identities to be beneficial for mental health, they can be embodied as well as symbolic.
We extended the job demand–control model by including a social comparison perspective and hypothesised that an employee's work-related well-being is to some degree relative to the perceived work environment of coworkers rather than absolute (in terms of isolated effects of individual work characteristics). Hence, we account for the social context when examining the effects of individual job characteristics. Using a lagged study design with two measurement times eight weeks apart, we examined the effects of the (in)congruence between one´s own job demands and job control with the perceived job demands and job control of coworkers on job satisfaction, emotional exhaustion, cynicism, and professional efficiency. Findings from polynomial regression analyses and response surface methodology revealed that perceiving coworkers as having either higher or lower demands than oneself is associated with lower job satisfaction and higher levels of emotional exhaustion. This provides partial support for our hypotheses. We found first-time evidence that social comparison processes regarding job demands can influence employees´ well-being.
Objectives: Stenosis of the biliary anastomosis predisposes liver graft recipients to bacterial cholangitis. Antibiotic therapy (AT) is performed according to individual clinical judgment, but duration of AT remains unclear.
Methods: All liver graft recipients with acute cholangitis according to the Tokyo criteria grade 1 and 2 after endoscopic retrograde cholangiography (ERC) were included. Outcome of patients treated with short AT (<7 days) was compared to long AT (>6 days). Recurrent cholangitis (RC) within 28 days was the primary end point.
Results: In total, 30 patients were included with a median of 313 (range 34–9849) days after liver transplantation until first proven cholangitis. Among 62 cases in total, 51/62 (82%) were graded as Tokyo-1 and 11/62 (18%) as Tokyo-2. Overall median duration of AT was 6 days (1–14) with 36 cases (58%) receiving short AT and 26 (42%) receiving long AT. RC was observed in 10 (16%) cases, without significant difference in occurrence of RC in short versus long AT cases. CRP and bilirubin were significantly higher in patients with long AT, while low serum albumin and low platelets were associated with risk of RC.
Conclusion: A shorter antibiotic course than 7 days shows good results in selected, ERC-treated patients for post-transplantation biliary strictures.
Understanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. STITCHIT outperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.