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Background Acute respiratory infections (ARI) exhibit varying lethality rates, influenced by individual and population factors. This retrospective study aimed to analyse infection frequency, clinical characteristics, and factors associated with lethality in hospitalized patients with seasonal ARI pathogens. Methods Virological and demographic data of hospitalized patients ≥ 18 years who tested positive for at least one ARI viral pathogen (Influenza, Adenovirus, Coronavirus, human Metapneumovirus (hMPV), Parainfluenza, Rhinovirus, Respiratory Syncytial Virus (RSV) and SARS-CoV-2) were collected from 07/2022 to 04/2023 at a German tertiary care hospital. Logistic regression analysis was used to analyse factors influencing lethality. Univariate comparisons examined pathogen-specific differences in length of stay and lethality. Results Among 1,657 hospitalized patients with at least one detected ARI pathogen, 89 (5.5%) passed away. Logistic regression analysis indicated a significant association between advanced age and lethality (OR = 1.05 per year, p  < 0.0001). Patients infected with ARI pathogens other than SARS-CoV-2 or hMPV exhibited a heightened risk of lethality compared to those with Influenza. While statistical significance was reached only for Adenovirus (OR = 5.99, p  = 0.049), elevated risk of lethality was also observed among hospitalized patients infected with Coronavirus (OR = 2.22), RSV (OR = 2.18), and more than one pathogen (OR = 2.07). Conclusions Lethality rates varied among the examined ARI pathogens. Compared to Influenza, Adenovirus, Coronavirus, and RSV showed elevated lethality rates and an increased risk of intrahospital death among ARI-infected patients. RSV emerged as a notable concern for hospitalized adults. Additionally, age also arises as a significant risk factor for lethality associated with ARI during hospitalization. Trial registration This study is a retrospective analysis of fully anonymized routinely collected patient data and does not require registration in a clinical trial registry.

Bioconcentration tests using the freshwater amphipod Hyalella azteca as an alternative to conventional fish tests have recently received much attention. An appropriate computational model of H. azteca could help in understanding the mechanisms behind bioconcentration, in comparison to the fish as test organism. We here present the first mechanistic model for H. azteca that considers the single diffusive processes in the gills and gut. The model matches with the experimental data from the literature quite well when appropriate physiological information is used. The implementation of facilitated transport was essential for modeling. Application of the model for superhydrophobic compounds revealed binding to organic matter and the resulting decrease in bioavailable fraction as the main reason for the observed counterintuitive decrease in uptake rate constants with increasing octanol/water partition coefficient. Furthermore, estimations of the time needed to reach steady state indicated that durations of more than a month could be needed for compounds with a log K ow  > 8, limiting the experimental applicability of the test. In those cases, model-based bioconcentration predictions could be a preferable approach, which could be combined with in vitro biotransformation measurements. However, our sensitivity analysis showed that the uncertainty in determining the octanol/water partition coefficients is a strong source of error for superhydrophobic compounds.

BackgroundTherapeutic antibodies (Abs) against the immune checkpoint ‘programmed cell death 1’ (PD1) achieve clinical benefit only in a small subset of patients with microsatellite instable (MSI+), immunologically ‘hot’ colorectal cancer (CRC). One underlying mechanism of this lack of response is frequent activating KRAS mutations which lead to the up-regulation of PD1 within an immune-suppressive microenvironment. Thus, inhibitors of RAS-signaling which down-regulate PD1, are expected to enhance the recognition and killing of cancer cells by the host immune system also in patients with microsatellite stable (‘cold’) (MSS+) tumors.‘Peroxisome proliferator-activated receptor-gamma’ (PPARg), a transcription factor drugable by anti-diabetic insulin sensitizers (pio- and rosiglitazone), attenuates RAS-signaling and is itself negatively regulated by this pathway. We, therefore, hypothesized that PPARg down-regulates PD1 on immune cells and augments PD1 Ab efficacy against MSS+ tumors.MethodsWildtype (wt) and KRASG12V transgenic C57BL6/J mice received a 3 months diet enriched with PPARg-agonist (rosiglitazone, ~25 mg/kg*day, n=5-10 per group and genotype) for measurement of tumor growth and PD1/PD-L1 expression by PCR and immunohistochemistry. Co-cultures of human MSS+ gastrointestinal cell lines (AGS, SW480, HT29) with IL2 lymphokine-activated NK/T killer (LAK) cells from peripheral blood of healthy donors and patients were analysed by PCR microarray, immunoblot, flow cytometry and viability assays.ResultsPPARg-agonist down-regulated PD1 mRNA/protein expression in mice and LAKs. In contact-dependent 3D co-cultures, PPARg-agonist in combination with IFNg promoted cell death of MSS+ tumor cells by LAKs in the presence of IgG4 PD1 Ab (pembrolizumab). Mechanistically, phosphorylation of pp60 Src-like cytoplasmic tyrosine kinases and STAT1 downstream of the T-cell receptor were induced in LAKs, and, vice versa, MHC class I and PD-L1 up-regulated on co-cultured tumor cells, endowing them with a higher immunogenicity.ConclusionsPharmacological PPARg activation down-regulated PD1 on immune cells to enhance the anti-tumor efficacy of PD1 blocking Ab. Thus, metabolic modifiers might be further developed as future immune-sensitizers for current clinical checkpoint therapies in MSS+ tumors.

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years.

Background Implementing evidence-based healthcare practices (EBPs) is a complex endeavour and often lags behind research-informed decision processes. Understanding and systematically improving implementation using implementation theory can help bridge the gap between research findings and practice. This study aims to translate, pilot, and validate a German version of the English NoMAD questionnaire (G-NoMAD), an instrument derived from the Normalisation Process Theory, to explore the implementation of EBPs. Methods Survey data has been collected in four German research projects and subsequently combined into a validation data set. Two versions of the G-NoMAD existed, independently translated from the original English version by two research groups. A measurement invariance analysis was conducted, comparing latent scale structures between groups of respondents to both versions. After determining the baseline model, the questionnaire was tested for different degrees of invariance (configural, metric, scalar, and uniqueness) across samples. A confirmatory factor analysis for three models (a four-factor, a unidimensional, and a hierarchical model) was used to examine the theoretical structure of the G-NoMAD. Finally, psychometric results were discussed in a consensus meeting, and the final instructions, items, and scale format were consented to. Results A total of 539 health care professionals completed the questionnaire. The results of the measurement invariance analysis showed configural, partial metric, and partial scalar invariance indicating that the questionnaire versions are comparable. Internal consistency ranged from acceptable to good (0.79 ≤  α  ≤ 0.85) per subscale. Both the four factor and the hierarchical model achieved a better fit than the unidimensional model, with indices from acceptable (SRMR = 0.08) to good (CFI = 0.97; TLI = 0.96). However, the RMSEA values were only close to acceptable (four-factor model: χ2164 = 1029.84, RMSEA = 0.10; hierarchical model: χ2166 = 1073.43, RMSEA = 0.10). Conclusions The G-NoMAD provides a reliable and promising tool to measure the degree of normalisation among individuals involved in implementation activities. Since the fit was similar in the four-factor and the hierarchical model, priority should be given to the practical relevance of the hierarchical model, including a total score and four subscale scores. The findings of this study support the further usage of the G-NoMAD in German implementation settings. Trial registration Both the AdAM project (No. NCT03430336, 06/02/2018) and the EU-project ImpleMentAll (No. NCT03652883, 29/08/2018) were registered on ClinicalTrials.gov. The ImplementIT study was registered at the German Clinical Trial Registration (No. DRKS00017078, 18/04/2019). The G-NoMAD validation study was registered at the Open Science Framework (No7u9ab, 17/04/2023).

Objective Research on effective implementation options and key factors in blending face-to-face (FTF) psychotherapy with online treatment elements (i.e., blended therapy, BT) remains limited. This study aimed to explore patients’ experiences and to identify relevant factors in implementing BT in routine care. Methods Qualitative semi-structured interviews were conducted with 40 patients (10.7% of N = 375) from the PSYCHOnlineTHERAPY trial. The patients were adults with diagnosed anxiety or depressive disorders and received one of two versions of BT based on cognitive behavioral therapy, differing in the flexibility to decide on the sequence and ratio of BT elements (FTF sessions and online self-help sessions). The interviews were audio-recorded, transcribed, and analyzed using a deductive-inductive qualitative content analysis approach, partly theory-based on the “Efficiency Model of Support.” Results The analysis revealed 163 theme codes, categorized into 30 subcategories. The main categories were “motivation and expectations,” “active components, mechanisms of change, and effects,” “blending scenarios,” “therapeutic alliance,” “negative effects,” “fit,” “facilitators and barriers for engagement and daily life transfer,” “usability,” and “optimization possibilities.” Key findings highlight positive outcomes of BT, the important role of the therapist, the transformative interaction of FTF and online sessions, and the distinctive functions and benefits of each element, suggesting BT's added value over stand-alone treatments. Various patient, therapeutic, and treatment characteristics emerged as relevant facilitators and barriers across different domains. Heterogeneity in patient preferences emphasized the importance of personalization. Conclusion Overall, these results provide valuable insights for the practical implementation and further research on BT. Trial registration German clinical trial register (DRKS00023973, date of registration: December 28, 2020), https://www.drks.de/search/de/trial/DRKS00023973.

Background Internet-based Cognitive Behavioural Therapy (iCBT) is found effective in treating common mental disorders. However, the use of these interventions in routine care is limited. The international ImpleMentAll study is funded by the European Union’s Horizon 2020 programme. It is concerned with studying and improving methods for implementing evidence-based iCBT services for common mental disorders in routine mental health care. A digitally accessible implementation toolkit ( ItFits-toolkit ) will be introduced to mental health care organizations with the aim to facilitate the ongoing implementation of iCBT services within local contexts. This study investigates the effectiveness of the ItFits-toolkit by comparing it to implementation-as-usual activities. Methods A stepped wedge cluster randomized controlled trial (SWT) design will be applied. Over a trial period of 30 months, the ItFits-toolkit will be introduced sequentially in twelve routine mental health care organizations in primary and specialist care across nine countries in Europe and Australia. Repeated measures are applied to assess change over time in the outcome variables. The effectiveness of the ItFits-toolkit will be assessed in terms of the degree of normalization of the use of the iCBT services. Several exploratory outcomes including uptake of the iCBT services will be measured to feed the interpretation of the primary outcome. Data will be collected via a centralized data collection system and analysed using generalized linear mixed modelling. A qualitative process evaluation of routine implementation activities and the use of the ItFits-toolkit will be conducted within this study. Discussion The ImpleMentAll study is a large-scale international research project designed to study the effectiveness of tailored implementation. Using a SWT design that allows to examine change over time, this study will investigate the effect of tailored implementation on the normalization of the use of iCBT services and their uptake. It will provide a better understanding of the process and methods of tailoring implementation strategies. If found effective, the ItFits-toolkit will be made accessible for mental health care service providers, to help them overcome their context-specific implementation challenges. Trial registration ClinicalTrials.gov NCT03652883 . Retrospectively registered on 29 August 2018

The number of hospitalized patients with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) does not differentiate between patients admitted due to coronavirus disease 2019 (COVID-19) (ie, primary cases) and incidental SARS-CoV-2 infection (ie, incidental cases). We developed an adaptable method to distinguish primary cases from incidental cases upon hospital admission. Retrospective cohort study. Data were obtained from 3 German tertiary-care hospitals. The study included patients of all ages who tested positive for SARS-CoV-2 by a standard quantitative reverse-transcription polymerase chain reaction (RT-PCR) assay upon admission between January and June 2022. We present 2 distinct models: (1) a point-of-care model that can be used shortly after admission based on a limited range of parameters and (2) a more extended point-of-care model based on parameters that are available within the first 24-48 hours after admission. We used regression and tree-based classification models with internal and external validation. In total, 1,150 patients were included (mean age, 49.5±28.5 years; 46% female; 40% primary cases). Both point-of-care models showed good discrimination with area under the curve (AUC) values of 0.80 and 0.87, respectively. As main predictors, we used admission diagnosis codes (ICD-10-GM), ward of admission, and for the extended model, we included viral load, need for oxygen, leucocyte count, and C-reactive protein. We propose 2 predictive algorithms based on routine clinical data that differentiate primary COVID-19 from incidental SARS-CoV-2 infection. These algorithms can provide a precise surveillance tool that can contribute to pandemic preparedness. They can easily be modified to be used in future pandemic, epidemic, and endemic situations all over the world.

Purpose We investigated the impact of promoter methylation on APC protein expression in patients with hepatocellular carcinoma (HCC). Materials and methods 50 patients [HCC (n=19), liver metastasis (n=19), cholangiocellular cancer (n=7), and benign liver tumors (n=5)] were studied for methylation using Methylight analysis. APC mutation was investigated by protein truncation test and direct sequencing of genomic DNA. The protein expression was evaluated by immunohistochemistry and Western blot analysis. Results The APC promoter was hypermethylated in 81.8% of non-cancerous liver tissue samples. All HCC samples and ten patients with liver metastasis (52.6%) exhibited APC promoter methylation. The degree of methylation was significantly higher in samples from HCC compared to the non-cancerous liver tissue samples (63.1% vs. 24.98%; p=0.001). The level of APC protein expression was significantly reduced in HCC samples compared to that of the corresponding non-tumor liver tissue (p<0.05). Conclusions Promoter methylation of the APC gene seems to be of significance in hepatocarcinogenesis and results in reduced protein expression in HCC. Interestingly, APC promoter methylation is also present in the vast majority of non-cancerous liver tissue whose (patho)physiological function remains unresolved.