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- Buchmann Institut für Molekulare Lebenswissenschaften (BMLS) (1)
- Informatik und Mathematik (1)
Background: The adequate allocation of inpatient care resources requires assumptions about the need for health care and how this need will be met. However, in current practice, these assumptions are often based on outdated methods (e.g. Hill-Burton Formula). This study evaluated floating catchment area (FCA) methods, which have been applied as measures of spatial accessibility, focusing on their ability to predict the need for health care in the inpatient sector in Germany.
Methods: We tested three FCA methods (enhanced (E2SFCA), modified (M2SFCA) and integrated (iFCA)) for their accuracy in predicting hospital visits regarding six medical diagnoses (atrial flutter/fibrillation, heart failure, femoral fracture, gonarthrosis, stroke, and epilepsy) on national level in Germany. We further used the closest provider approach for benchmark purposes. The predicted visits were compared with the actual visits for all six diagnoses using a correlation analysis and a maximum error from the actual visits of ± 5%, ± 10% and ± 15%.
Results: The analysis of 229 million distances between hospitals and population locations revealed a high and significant correlation of predicted with actual visits for all three FCA methods across all six diagnoses up to ρ = 0.79 (p < 0.001). Overall, all FCA methods showed a substantially higher correlation with actual hospital visits compared to the closest provider approach (up to ρ = 0.51; p < 0.001). Allowing a 5% error of the absolute values, the analysis revealed up to 13.4% correctly predicted hospital visits using the FCA methods (15% error: up to 32.5% correctly predicted hospital). Finally, the potential of the FCA methods could be revealed by using the actual hospital visits as the measure of hospital attractiveness, which returned very strong correlations with the actual hospital visits up to ρ = 0.99 (p < 0.001).
Conclusion: We were able to demonstrate the impact of FCA measures regarding the prediction of hospital visits in non-emergency settings, and their superiority over commonly used methods (i.e. closest provider). However, hospital beds were inadequate as the measure of hospital attractiveness resulting in low accuracy of predicted hospital visits. More reliable measures must be integrated within the proposed methods. Still, this study strengthens the possibilities of FCA methods in health care planning beyond their original application in measuring spatial accessibility.
Background: The aim of this study was to collect standard reference values of the weight and the maximum pressure distribution in healthy adults aged 18–65 years and to investigate the influence of constitutional parameters on it.
Methods: A total of 416 healthy subjects (208 male / 208 female) aged between 18 and 65 years (Ø 38.3 ± 14.1 years) participated in this study, conducted 2015–2019 in Heidelberg. The age-specific evaluation is based on 4 age groups (G1, 18–30 years; G2, 31–40 years; G3, 41–50 years; G4, 51–65 years). A pressure measuring plate FDM-S (Zebris/Isny/Germany) was used to collect body weight distribution and maximum pressure distribution of the right and left foot and left and right forefoot/rearfoot, respectively.
Results: Body weight distribution of the left (50.07%) and right (50.12%) foot was balanced. There was higher load on the rearfoot (left 54.14%; right 55.09%) than on the forefoot (left 45.49%; right 44.26%). The pressure in the rearfoot was higher than in the forefoot (rearfoot left 9.60 N/cm2, rearfoot right 9.51 N/cm2/forefoot left 8.23 N/cm2, forefoot right 8.59 N/cm2). With increasing age, the load in the left foot shifted from the rearfoot to the forefoot as well as the maximum pressure (p ≤ 0.02 and 0.03; poor effect size). With increasing BMI, the body weight shifted to the left and right rearfoot (p ≤ 0.001, poor effect size). As BMI increased, so did the maximum pressure in all areas (p ≤ 0.001 and 0.03, weak to moderate effect size). There were significant differences in weight and maximum pressure distribution in the forefoot and rearfoot in the different age groups, especially between younger (18–40 years) and older (41–65 years) subjects.
Discussion: Healthy individuals aged from 18 to 65 years were found to have a balanced weight distribution in an aspect ratio, with a 20% greater load of the rearfoot. Age and BMI were found to be influencing factors of the weight and maximum pressure distribution, especially between younger and elder subjects. The collected standard reference values allow comparisons with other studies and can serve as a guideline in clinical practice and scientific studies.
Selective sympathetic and parasympathetic pathways that act on target organs represent the terminal actors in the neurobiology of homeostasis and often become compromised during a range of neurodegenerative and traumatic disorders. Here, we delineate several neurotransmitter and neuromodulator phenotypes found in diverse parasympathetic and sympathetic ganglia in humans and rodent species. The comparative approach reveals evolutionarily conserved and non-conserved phenotypic marker constellations. A developmental analysis examining the acquisition of selected neurotransmitter properties has provided a detailed, but still incomplete, understanding of the origins of a set of noradrenergic and cholinergic sympathetic neuron populations, found in the cervical and trunk region. A corresponding analysis examining cholinergic and nitrergic parasympathetic neurons in the head, and a range of pelvic neuron populations, with noradrenergic, cholinergic, nitrergic, and mixed transmitter phenotypes, remains open. Of particular interest are the molecular mechanisms and nuclear processes that are responsible for the correlated expression of the various genes required to achieve the noradrenergic phenotype, the segregation of cholinergic locus gene expression, and the regulation of genes that are necessary to generate a nitrergic phenotype. Unraveling the neuron population-specific expression of adhesion molecules, which are involved in axonal outgrowth, pathway selection, and synaptic organization, will advance the study of target-selective autonomic pathway generation.
Replacement of a stenotic aortic valve reduces immediately the ventricular to aortic gradient and is expected to improve diastolic and systolic left ventricular function over the long term. However, the hemodynamic changes immediately after valve implantation are so far poorly understood. Within this pilot study, we performed an invasive pressure volume loop analysis to describe the early hemodynamic changes after transcatheter aortic valve implantation (TAVI) with self-expandable prostheses. Invasive left ventricular pressure volume loop analysis was performed in 8 patients with aortic stenosis (mean 81.3 years) prior and immediately after transfemoral TAVI with a self-expandable valve system (St. Jude Medical Portico Valve). Parameters for global hemodynamics, afterload, contractility and the interaction of the cardiovascular system were analyzed. Left ventricular ejection fraction, (53.9% vs. 44.8%, p = 0.018), preload recruitable stroke work (68.5 vs. 44.8 mmHg, p = 0.012) and end-systolic elastance (3.55 vs. 2.17, p = 0.036) both marker for myocardial contractility declined significantly compared to baseline. As sign of impaired diastolic function, TAU, a preload-independent measure of isovolumic relaxation (37.3 vs. 41.8 ms, p = 0.018) and end-diastolic pressure (13.1 vs. 16.4 mmHg, p = 0.015) raised after valve implantation. Contrarily, a smaller ratio of end-systolic to arterial elastance (ventricular-arterial coupling) indicates an improvement of global cardiovascular energy efficiency (1.40 vs. 0.97 p = 0.036). Arterial elastance had a strong correlation with the number of conducted rapid ventricular pacings (Pearson correlation coefficient, r = 0.772, p = 0.025). Invasive left ventricular pressure volume loop analysis revealed impaired systolic and diastolic function in the early phase after TAVI with self-expandable valve for the treatment of severe aortic stenosis. Contrarily, we found indications for early improvement of global cardiovascular energy efficiency.
The nuclear factor kappa beta (NFκB) signaling pathway plays an important role in liver homeostasis and cancer development. Tax1-binding protein 1 (Tax1BP1) is a regulator of the NFκB signaling pathway, but its role in the liver and hepatocellular carcinoma (HCC) is presently unknown. Here we investigated the role of Tax1BP1 in liver cells and murine models of HCC and liver fibrosis. We applied the diethylnitrosamine (DEN) model of experimental hepatocarcinogenesis in Tax1BP1+/+ and Tax1BP1−/− mice. The amount and subsets of non-parenchymal liver cells in in Tax1BP1+/+ and Tax1BP1−/− mice were determined and activation of NFκB and stress induced signaling pathways were assessed. Differential expression of mRNA and miRNA was determined. Tax1BP1−/− mice showed increased numbers of inflammatory cells in the liver. Furthermore, a sustained activation of the NFκB signaling pathway was found in hepatocytes as well as increased transcription of proinflammatory cytokines in isolated Kupffer cells from Tax1BP1−/− mice. Several differentially expressed mRNAs and miRNAs in livers of Tax1BP1−/− mice were found, which are regulators of inflammation or are involved in cancer development or progression. Furthermore, Tax1BP1−/− mice developed more HCCs than their Tax1BP1+/+ littermates. We conclude that Tax1BP1 protects from liver cancer development by limiting proinflammatory signaling.
Background: To detect deviations from a normal postural control, standard values can be helpful for comparison purposes. Since the postural control is influenced by gender and age, the aim of the present study was the collection of standard values for women between 31 and 40 years of age.
Methods: For the study, 106 female, subjectively healthy, German subjects aged between 31 and 40 years (35 ± 2.98 years) were measured using a pressure measuring platform.
Results: Their average BMI was 21.60 ± 4.65 kg/m2. The load distribution between left and right foot was almost evenly balanced with a median 51.46% load on the left [tolerance interval (TR) 37.02%/65.90%; confidence interval (CI) 50.06/52.85%] and 48.54% [TR 43.10/62.97%; CI 47.14/49.93%] on the right foot. The median forefoot load was 33.84% [TR 20.68/54.73%; CI 31.67/37.33%] and the rearfoot load was measured at 66.16% [TR 45.27/79.33%; CI 62.67/68.33%]. The median/mean body sway in the sagittal plane was measured 12 mm [TR 5.45/23.44 mm; CI 11.00/14.00 mm] and 8.17 mm in the frontal plane [TR 3.33/19.08 mm; CI 7.67/9.33 mm]. The median of the ellipse area is 0.72 cm2 [TR 0.15/3.69 cm2; CI 0.54/0.89°]. The ellipse width has a median of 0.66 cm [TR 0.30/1.77 cm; CI 0.61/0.78 cm] and the height of 0.33 cm [TR 0.13/0.71 cm; CI 0.30/0.37 cm]. The ellipse angle (sway, left forefoot to right rearfoot) has a mean of − 19.34° [TR − 59.21/− 0.44°; CI − 22.52/− 16.16°] and the ellipse angle sway from right forefoot to left rearfoot has a mean of 12.75° [TR 0.09/59.09°; CI 9.00/16.33°].
Conclusion: The right-to-left ratio is balanced. The forefoot-to-rearfoot ratio is approximately 1:2. Also, the body sway can be classified with 12 and 8 mm as normal. The direction of fluctuation is either approx. 19° from the left forefoot to the right rearfoot or approx. 13° the opposite. Body weight, height, and BMI were comparable to the German average of women in a similar age group, so that the measured standard values are representative and might serve as baseline for the normal function of the balance system in order to support the diagnosis of possible dysfunctions in postural control.
Background: Patients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS.
Methods: Interviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs.
An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring’s qualitative content analysis approach.
Results: A total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted.
The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs.
Conclusions: This qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.
Of the 16 non-structural proteins (Nsps) encoded by SARS CoV-2, Nsp3 is the largest and plays important roles in the viral life cycle. Being a large, multidomain, transmembrane protein, Nsp3 has been the most challenging Nsp to characterize. Encoded within Nsp3 is the papain-like protease PLpro domain that cleaves not only the viral protein but also polyubiquitin and the ubiquitin-like modifier ISG15 from host cells. We here compare the interactors of PLpro and Nsp3 and find a largely overlapping interactome. Intriguingly, we find that near full length Nsp3 is a more active protease compared to the minimal catalytic domain of PLpro. Using a MALDI-TOF based assay, we screen 1971 approved clinical compounds and identify five compounds that inhibit PLpro with IC50s in the low micromolar range but showed cross reactivity with other human deubiquitinases and had no significant antiviral activity in cellular SARS-CoV-2 infection assays. We therefore looked for alternative methods to block PLpro activity and engineered competitive nanobodies that bind to PLpro at the substrate binding site with nanomolar affinity thus inhibiting the enzyme. Our work highlights the importance of studying Nsp3 and provides tools and valuable insights to investigate Nsp3 biology during the viral infection cycle.
Previous studies reported on the safety and applicability of mesenchymal stem/stromal cells (MSCs) to ameliorate pulmonary inflammation in acute respiratory distress syndrome (ARDS). Thus, multiple clinical trials assessing the potential of MSCs for COVID-19 treatment are underway. Yet, as SARS-inducing coronaviruses infect stem/progenitor cells, it is unclear whether MSCs could be infected by SARS-CoV-2 upon transplantation to COVID-19 patients. We found that MSCs from bone marrow, amniotic fluid, and adipose tissue carry angiotensin-converting enzyme 2 and transmembrane protease serine subtype 2 at low levels on the cell surface under steady-state and inflammatory conditions. We did not observe SARS-CoV-2 infection or replication in MSCs at steady state under inflammatory conditions, or in direct contact with SARS-CoV-2-infected Caco-2 cells. Further, indoleamine 2,3-dioxygenase 1 production in MSCs was not impaired in the presence of SARS-CoV-2. We show that MSCs are resistant to SARS-CoV-2 infection and retain their immunomodulation potential, supporting their potential applicability for COVID-19 treatment.
Background: Rare Diseases (RDs), which are defined as diseases affecting no more than 5 out of 10,000 people, are often severe, chronic and life-threatening. A main problem is the delay in diagnosing RDs. Clinical decision support systems (CDSSs) for RDs are software systems to support clinicians in the diagnosis of patients with RDs. Due to their clinical importance, we conducted a scoping review to determine which CDSSs are available to support the diagnosis of RDs patients, whether the CDSSs are available to be used by clinicians and which functionalities and data are used to provide decision support.
Methods: We searched PubMed for CDSSs in RDs published between December 16, 2008 and December 16, 2018. Only English articles, original peer reviewed journals and conference papers describing a clinical prototype or a routine use of CDSSs were included. For data charting, we used the data items “Objective and background of the publication/project”, “System or project name”, “Functionality”, “Type of clinical data”, “Rare Diseases covered”, “Development status”, “System availability”, “Data entry and integration”, “Last software update” and “Clinical usage”.
Results: The search identified 636 articles. After title and abstracting screening, as well as assessing the eligibility criteria for full-text screening, 22 articles describing 19 different CDSSs were identified. Three types of CDSSs were classified: “Analysis or comparison of genetic and phenotypic data,” “machine learning” and “information retrieval”. Twelve of nineteen CDSSs use phenotypic and genetic data, followed by clinical data, literature databases and patient questionnaires. Fourteen of nineteen CDSSs are fully developed systems and therefore publicly available. Data can be entered or uploaded manually in six CDSSs, whereas for four CDSSs no information for data integration was available. Only seven CDSSs allow further ways of data integration. thirteen CDSS do not provide information about clinical usage.
Conclusions: Different CDSS for various purposes are available, yet clinicians have to determine which is best for their patient. To allow a more precise usage, future research has to focus on CDSSs RDs data integration, clinical usage and updating clinical knowledge. It remains interesting which of the CDSSs will be used and maintained in the future.