Scientific competence during medical education - insights from a cross-sectional study at a German Medical School.

BACKGROUND: Medical knowledge regarding the pathophysiology, diagnosis and treatment of diseases is constantly evolving. To effectively incorporate these findings into professional practice, it is crucial that scientific competencies are a central component of medical education. This study seeks to analyse the current state of scientific education and students' desires for integration into the curriculum. METHODS: From October to December 2022, a survey was distributed at the Medical Faculty Dresden to all medical students from the 1st to 5th academic year (AY). The survey investigates current expectations of applying scientific competencies later in professional life, and the students were asked to self-assess various scientific skills and in relation to the National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education. The self-assessments were objectified through a competence test with ten multiple-choice questions. The desire for curricular teaching was inquired. RESULTS: 860 students completed the survey. This corresponds to a response rate of 64%. In the 5th AY, approximately 80% of the participants stated that they expected to work with scientific literature on a daily to monthly basis in future professional life and to communicate corresponding scientific findings to patients. Only 30-40% of the 5th AY rate their scientific competencies as sufficient to do this appropriately. This corresponds with the self-assessed competencies that only slightly increased over the 5 AYs from 14.1 ± 11.7 to 21.3 ± 13.8 points (max. 52) and is also reflected in the competence test (1st AY 3.6 ± 1.75 vs. 5th AY 5.5 ± 1.68, max. 10 points). Half of the students in the 4th and 5th AYs were dissatisfied with the current teaching of scientific skills. The majority preferred the implementation of a science curriculum (56%), preferably as seminars dealing with topics such as literature research, analysis, and science communication. CONCLUSIONS: The results show discrepancies between expectations of using scientific knowledge in everyday professional life, self-rated and objectively recorded competencies, and the current state of curricular teaching of scientific competencies. There is a strong need for adequate practical training, particularly in critical analyses of scientific literature, which enables the communication of scientific knowledge to patients.

The Reconstitution Dynamics of Cultivated Hematopoietic Stem Cells and Progenitors Is Independent of Age.

Hematopoietic stem cell transplantation (HSCT) represents the only curative treatment option for numerous hematologic malignancies. While the influence of donor age and the composition of the graft have already been examined in clinical and preclinical studies, little information is available on the extent to which different hematological subpopulations contribute to the dynamics of the reconstitution process and on whether and how these contributions are altered with age. In a murine model of HSCT, we therefore simultaneously tracked different cultivated and transduced hematopoietic stem and progenitor cell (HSPC) populations using a multicolor-coded barcode system (BC32). We studied a series of age-matched and age-mismatched transplantations and compared the influence of age on the reconstitution dynamics. We show that reconstitution from these cultured and assembled grafts was substantially driven by hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) independent of age. The reconstitution patterns were polyclonal and stable in all age groups independently of the variability between individual animals, with higher output rates from MPPs than from HSCs. Our experiments suggest that the dynamics of reconstitution and the contribution of cultured and individually transduced HSPC subpopulations are largely independent of age. Our findings support ongoing efforts to expand the application of HSCT in older individuals as a promising strategy to combat hematological diseases, including gene therapy applications.

Hair follicle stem cell cultures reveal self-organizing plasticity of stem cells and their progeny.

Understanding how complex tissues are formed, maintained, and regenerated through local growth, differentiation, and remodeling requires knowledge on how single-cell behaviors are coordinated on the population level. The self-renewing hair follicle, maintained by a distinct stem cell population, represents an excellent paradigm to address this question. A major obstacle in mechanistic understanding of hair follicle stem cell (HFSC) regulation has been the lack of a culture system that recapitulates HFSC behavior while allowing their precise monitoring and manipulation. Here, we establish an in vitro culture system based on a 3D extracellular matrix environment and defined soluble factors, which for the first time allows expansion and long-term maintenance of murine multipotent HFSCs in the absence of heterologous cell types. Strikingly, this scheme promotes de novo generation of HFSCs from non-HFSCs and vice versa in a dynamic self-organizing process. This bidirectional interconversion of HFSCs and their progeny drives the system into a population equilibrium state. Our study uncovers regulatory dynamics by which phenotypic plasticity of cells drives population-level homeostasis within a niche, and provides a discovery tool for studies on adult stem cell fate.

genBaRcode: a comprehensive R-package for genetic barcode analysis.

MOTIVATION: Genetic barcodes have been established as an efficient method to trace clonal progeny of uniquely labeled cells by introducing artificial genetic sequences into the corresponding genomes. The assessment of those sequences relies on next generation sequencing and the subsequent analysis aiming to identify sequences of interest and correctly quantifying their abundance. RESULTS: We developed the genBaRcode package as a toolbox combining the flexibility of digesting next generation sequencing reads with or without a sophisticated barcode structure, with a variety of error-correction approaches and the availability of several types of visualization routines. Furthermore, a graphical user interface was incorporated to allow also less experienced R users package-based analyses. Finally, the provided tool is intended to bridge the gap between generating and analyzing barcode data and thereby supporting the establishment of standardized and reproducible analysis strategies. AVAILABILITY AND IMPLEMENTATION: The genBaRcode package is available at CRAN (https://cran.r-project.org/package=genBaRcode).

Aging alters the epigenetic asymmetry of HSC division.

Hematopoietic stem cells (HSCs) balance self-renewal and differentiation to maintain homeostasis. With aging, the frequency of polar HSCs decreases. Cell polarity in HSCs is controlled by the activity of the small RhoGTPase cell division control protein 42 (Cdc42). Here we demonstrate-using a comprehensive set of paired daughter cell analyses that include single-cell 3D confocal imaging, single-cell transplants, single-cell RNA-seq, and single-cell transposase-accessible chromatin sequencing (ATAC-seq)-that the outcome of HSC divisions is strongly linked to the polarity status before mitosis, which is in turn determined by the level of the activity Cdc42 in stem cells. Aged apolar HSCs undergo preferentially self-renewing symmetric divisions, resulting in daughter stem cells with reduced regenerative capacity and lymphoid potential, while young polar HSCs undergo preferentially asymmetric divisions. Mathematical modeling in combination with experimental data implies a mechanistic role of the asymmetric sorting of Cdc42 in determining the potential of daughter cells via epigenetic mechanisms. Therefore, molecules that control HSC polarity might serve as modulators of the mode of stem cell division regulating the potential of daughter cells.

Hematopoietic Stem Cell Dynamics Are Regulated by Progenitor Demand: Lessons from a Quantitative Modeling Approach.

The prevailing view on murine hematopoiesis and on hematopoietic stem cells (HSCs) in particular derives from experiments that are related to regeneration after irradiation and HSC transplantation. However, over the past years, different experimental techniques have been developed to investigate hematopoiesis under homeostatic conditions, thereby providing access to proliferation and differentiation rates of hematopoietic stem and progenitor cells in the unperturbed situation. Moreover, it has become clear that hematopoiesis undergoes distinct changes during aging with large effects on HSC abundance, lineage contribution, asymmetry of division, and self-renewal potential. However, it is currently not fully resolved how stem and progenitor cells interact to respond to varying demands and how this balance is altered by an aging-induced shift in HSC polarity. Aiming toward a conceptual understanding, we introduce a novel in silico model to investigate the dynamics of HSC response to varying demand. By introducing an internal feedback within a heterogeneous HSC population, the model is suited to consistently describe both hematopoietic homeostasis and regeneration, including the limited regulation of HSCs in the homeostatic situation. The model further explains the age-dependent increase in phenotypic HSCs as a consequence of the cells' inability to preserve divisional asymmetry. Our model suggests a dynamically regulated population of intrinsically asymmetrically dividing HSCs as suitable control mechanism that adheres with many qualitative and quantitative findings on hematopoietic recovery after stress and aging. The modeling approach thereby illustrates how a mathematical formalism can support both the conceptual and the quantitative understanding of regulatory principles in HSC biology.

[Registries and studies in the Society for Pediatric Oncology and Hematology (GPOH) - What contribution do they make to progress?] / Register und Studien in der Gesellschaft für Pädiatrische Onkologie und Hämatologie (GPOH) ­ Welchen Beitrag leisten sie zum Fortschritt?

Cancer in children and adolescents under the age of 18 is rare; in 2017, approximately 2220 new cases in Germany were reported to the German Childhood Cancer Registry. The aim of the GPOH has always been to treat as many affected patients as possible in a standardized way, preferably in prospective, controlled studies. The Joint Federal Committee has also laid down this requirement in the paediatric oncology guideline. In a survey among the study chairs of the GPOH, it was determined how the number of clinical trials has changed following the amended drug legislation. In 2002, 33 therapy optimization studies (TOS) of the GPOH were open. Overall, TOS decreased from 33 in 2002 to 2 in 2017. The number of drug trials has increased to 16 by 2017 (almost 1100 patients registered). At the time, the number of clinical registries has increased to 28 with a total of more than 1800 registered patents. This observation shows that the clinical registers have taken on a new significance in paediatric oncology. Three examples are used to examine what contributions registries can make in relation to studies on the treatment of patients and to scientific progress. In summary, the experience gained so far from the examples discussed illustrates that studies and registries mutually represent a meaningful and necessary addition to the study group structure in paediatric oncology.

Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology.

BACKGROUND: Individualization and patient-specific optimization of treatment is a major goal of modern health care. One way to achieve this goal is the application of high-resolution diagnostics together with the application of targeted therapies. However, the rising number of different treatment modalities also induces new challenges: Whereas randomized clinical trials focus on proving average treatment effects in specific groups of patients, direct conclusions at the individual patient level are problematic. Thus, the identification of the best patient-specific treatment options remains an open question. Systems medicine, specifically mechanistic mathematical models, can substantially support individual treatment optimization. In addition to providing a better general understanding of disease mechanisms and treatment effects, these models allow for an identification of patient-specific parameterizations and, therefore, provide individualized predictions for the effect of different treatment modalities. RESULTS: In the following we describe a software framework that facilitates the integration of mathematical models and computer simulations into routine clinical processes to support decision-making. This is achieved by combining standard data management and data exploration tools, with the generation and visualization of mathematical model predictions for treatment options at an individual patient level. CONCLUSIONS: By integrating model results in an audit trail compatible manner into established clinical workflows, our framework has the potential to foster the use of systems-medical approaches in clinical practice. We illustrate the framework application by two use cases from the field of haematological oncology.

To Cure or Not to Cure: Consequences of Immunological Interactions in CML Treatment.

Recent clinical findings in chronic myeloid leukemia (CML) patients suggest that the number and function of immune effector cells are modulated by tyrosine kinase inhibitors (TKI) treatment. There is further evidence that the success or failure of treatment cessation at least partly depends on the patients immunological constitution. Here, we propose a general ODE model to functionally describe the interactions between immune effector cells with leukemic cells during the TKI treatment of CML. In total, we consider 20 different sub-models, which assume different functional interactions between immune effector and leukemic cells. We show that quantitative criteria, which are purely based on the quality of model fitting, are not able to identify optimal models. On the other hand, the application of qualitative criteria based on a dynamical system framework allowed us to identify nine of those models as more suitable than the others to describe clinically observed patterns and, thereby, to derive conclusion about the underlying mechanisms. Additionally, including aspects of early CML onset, we can demonstrate that certain critical parameters, such as the strength of immune response or leukemia proliferation rate, need to change during CML growth prior to diagnosis, leading to bifurcations that alter the attractor landscape. Finally, we show that the crucial parameters determining the outcome of treatment cessation are not identifiable with tumor load data only, thereby highlighting the need to measure immune cell number and function to properly derive mathematical models with predictive power.

Reduced tyrosine kinase inhibitor dose is predicted to be as effective as standard dose in chronic myeloid leukemia: a simulation study based on phase III trial data.

Continuing tyrosine kinase inhibitor (TKI)-mediated targeting of the BCR-ABL1 oncoprotein is the standard therapy for chronic myeloid leukemia (CML) and allows for a sustained disease control in the majority of patients. While therapy cessation for patients appeared as a safe option for about half of those patients with optimal response, no systematic assessment of long-term TKI dose de-escalation has been made. We use a mathematical model to analyze and consistently describe biphasic treatment responses from TKI-treated patients from two independent clinical phase III trials. Scale estimates reveal that drug efficiency determines the initial response while the long-term behavior is limited by the rare activation of leukemic stem cells. We use this mathematical framework to investigate the influence of different dosing regimens on the treatment outcome. We provide strong evidence to suggest that TKI dose de-escalation (at least 50%) does not lead to a reduction of long-term treatment efficiency for most patients, who have already achieved sustained remission, and maintains the secondary decline of BCR-ABL1 levels. We demonstrate that continuous BCR-ABL1 monitoring provides patient-specific predictions of an optimal reduced dose without decreasing the anti-leukemic effect on residual leukemic stem cells. Our results are consistent with the interim results of the DESTINY trial and provide clinically testable predictions. Our results suggest that dose-halving should be considered as a long-term treatment option for CML patients with good response under continuing maintenance therapy with TKIs. We emphasize the clinical potential of this approach to reduce treatment-related side-effects and treatment costs.

Incidence of Diabetic Ketoacidosis of New-Onset Type 1 Diabetes in Children and Adolescents in Different Countries Correlates with Human Development Index (HDI): An Updated Systematic Review, Meta-Analysis, and Meta-Regression.

Type 1 diabetes mellitus (T1DM) is usually diagnosed by insulin deficiency at a young age. Diabetic ketoacidosis (DKA) represents a severe complication occurring before the first diagnosis of T1DM. Actually, the data situation is still unsettled in assessing the current state of diagnosis. This study summarizes the latest rates of DKA of new-onset T1DM in children and adolescents in different countries available over the last five years. Different T1DM-related, geographical and socioeconomic moderators are suitable to explain the heterogeneity of observed DKA rates. A systematic literature search using PubMed, EMBASE*, and MedLine* (*via OVID) was conducted to extract worldwide DKA rates covering publications from April 2011 to May 2016. We define DKA consistently by pH<7.3 or bicarbonate<15 mmol/l. We identified 34 suitable studies covering DKA rates in 25 countries. Overall DKA rates were compared to earlier studies to identify a temporal trend. We further applied a random effects meta-analysis and used meta-regression to reveal moderators of DKA rate heterogeneity. This review evaluating 34 studies includes 47 000 children and adolescents in total. DKA rates varied from 14.7% (Denmark) to 79.8% (Saudi Arabia). DKA rates are still high but a decline can also be recognized. The meta-regression shows that latitude (p<0.000) and human development index (HDI) (p<0.000) are moderators of DKA rates. The frequency of DKA rates occurrence varies widely for different countries. Both latitude and HDI partially explain the observed heterogeneity, while other moderators such as density of physicians showed no obvious correlation.

MAGPIE: Simplifying access and execution of computational models in the life sciences.

Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific model classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a Modeling and Analysis Generic Platform with Integrated Evaluation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de.

Clonal competition in BcrAbl-driven leukemia: how transplantations can accelerate clonal conversion.

BACKGROUND: Clonal competition in cancer describes the process in which the progeny of a cell clone supersedes or succumbs to other competing clones due to differences in their functional characteristics, mostly based on subsequently acquired mutations. Even though the patterns of those mutations are well explored in many tumors, the dynamical process of clonal selection is underexposed. METHODS: We studied the dynamics of clonal competition in a BcrAbl-induced leukemia using a γ-retroviral vector library encoding the oncogene in conjunction with genetic barcodes. To this end, we studied the growth dynamics of transduced cells on the clonal level both in vitro and in vivo in transplanted mice. RESULTS: While we detected moderate changes in clonal abundancies in vitro, we observed monoclonal leukemias in 6/30 mice after transplantation, which intriguingly were caused by only two different BcrAbl clones. To analyze the success of these clones, we applied a mathematical model of hematopoietic tissue maintenance, which indicated that a differential engraftment capacity of these two dominant clones provides a possible explanation of our observations. These findings were further supported by additional transplantation experiments and increased BcrAbl transcript levels in both clones. CONCLUSION: Our findings show that clonal competition is not an absolute process based on mutations, but highly dependent on selection mechanisms in a given environmental context.

Factor graph analysis of live cell-imaging data reveals mechanisms of cell fate decisions.

MOTIVATION: Cell fate decisions have a strong stochastic component. The identification of the underlying mechanisms therefore requires a rigorous statistical analysis of large ensembles of single cells that were tracked and phenotyped over time. RESULTS: We introduce a probabilistic framework for testing elementary hypotheses on dynamic cell behavior using time-lapse cell-imaging data. Factor graphs, probabilistic graphical models, are used to properly account for cell lineage and cell phenotype information. Our model is applied to time-lapse movies of murine granulocyte-macrophage progenitor (GMP) cells. It decides between competing hypotheses on the mechanisms of their differentiation. Our results theoretically substantiate previous experimental observations that lineage instruction, not selection is the cause for the differentiation of GMP cells into mature monocytes or neutrophil granulocytes. AVAILABILITY AND IMPLEMENTATION: The Matlab source code is available at http://treschgroup.de/Genealogies.html.

Survival and patient satisfaction of short implants during the first 2 years of function: a retrospective cohort study with 694 implants in 416 patients.

OBJECTIVES: The present study aimed to evaluate the influence of implant length on implant survival and patient satisfaction during the first 24 months in function. MATERIAL AND METHODS: A retrospective cohort of 312 "short" Straumann(®) SLActive(®) implants (length ≤ 8 mm) in 224 patients, which were inserted between 2008 and 2010 in private practice, were evaluated. The mean observation period was 26.7 ± 9.7 months. Three hundred and eighty-two Straumann SLActive(®) implants in 192 patients with a length ≥ 12 mm served as control group. The mean observation period in the control group was 28.3 ± 10.1 months. Implant survival rate, crown-to-implant ratio, resonance frequency analysis, and patient satisfaction were evaluated. RESULTS: Implant survival rate was 99% in the test vs. 98.7% in the control group. The crown-to-implant ratio was significantly higher in the control group (P < 0.0001). Resonance frequency analysis showed slightly higher values for the short implants. There was a tendency to higher satisfaction (Oral Health Impact Profile [OHIP]) in the test group without statistical significant differences but a high overall satisfaction in both groups. CONCLUSION: Within the limits of the present investigation, implant length had no significant influence on implant survival during the first 24 months of function of the specific implant system with hydrophilic surface (SLActive(®) ). Further follow-up studies are required to evaluate long-term results of the reduced implant length.

Multiplexing clonality: combining RGB marking and genetic barcoding.

RGB marking and DNA barcoding are two cutting-edge technologies in the field of clonal cell marking. To combine the virtues of both approaches, we equipped LeGO vectors encoding red, green or blue fluorescent proteins with complex DNA barcodes carrying color-specific signatures. For these vectors, we generated highly complex plasmid libraries that were used for the production of barcoded lentiviral vector particles. In proof-of-principle experiments, we used barcoded vectors for RGB marking of cell lines and primary murine hepatocytes. We applied single-cell polymerase chain reaction to decipher barcode signatures of individual RGB-marked cells expressing defined color hues. This enabled us to prove clonal identity of cells with one and the same RGB color. Also, we made use of barcoded vectors to investigate clonal development of leukemia induced by ectopic oncogene expression in murine hematopoietic cells. In conclusion, by combining RGB marking and DNA barcoding, we have established a novel technique for the unambiguous genetic marking of individual cells in the context of normal regeneration as well as malignant outgrowth. Moreover, the introduction of color-specific signatures in barcodes will facilitate studies on the impact of different variables (e.g. vector type, transgenes, culture conditions) in the context of competitive repopulation studies.

Image-based quantification and mathematical modeling of spatial heterogeneity in ESC colonies.

Pluripotent embryonic stem cells (ESCs) have the potential to differentiate into cells of all three germ layers. This unique property has been extensively studied on the intracellular, transcriptional level. However, ESCs typically form clusters of cells with distinct size and shape, and establish spatial structures that are vital for the maintenance of pluripotency. Even though it is recognized that the cells' arrangement and local interactions play a role in fate decision processes, the relations between transcriptional and spatial patterns have not yet been studied. We present a systems biology approach which combines live-cell imaging, quantitative image analysis, and multiscale, mathematical modeling of ESC growth. In particular, we develop quantitative measures of the morphology and of the spatial clustering of ESCs with different expression levels and apply them to images of both in vitro and in silico cultures. Using the same measures, we are able to compare model scenarios with different assumptions on cell-cell adhesions and intercellular feedback mechanisms directly with experimental data. Applying our methodology to microscopy images of cultured ESCs, we demonstrate that the emerging colonies are highly variable regarding both morphological and spatial fluorescence patterns. Moreover, we can show that most ESC colonies contain only one cluster of cells with high self-renewing capacity. These cells are preferentially located in the interior of a colony structure. The integrated approach combining image analysis with mathematical modeling allows us to reveal potential transcription factor related cellular and intercellular mechanisms behind the emergence of observed patterns that cannot be derived from images directly.

Model-based decision rules reduce the risk of molecular relapse after cessation of tyrosine kinase inhibitor therapy in chronic myeloid leukemia.

Molecular response to imatinib (IM) in chronic myeloid leukemia (CML) is associated with a biphasic but heterogeneous decline of BCR-ABL transcript levels. We analyzed this interindividual heterogeneity and provide a predictive mathematical model to prognosticate the long-term response and the individual risk of molecular relapse on treatment cessation. The parameters of the model were determined using 7-year follow-up data from a randomized clinical trial and validated by an independent dataset. Our model predicts that a subset of patients (14%) achieve complete leukemia eradication within less than 15 years and could therefore benefit from discontinuation of treatment. Furthermore, the model prognosticates that 31% of the patients will remain in deep molecular remission (MR(5.0)) after treatment cessation after a fixed period of 2 years in MR(5.0), whereas 69% are expected to relapse. As a major result, we propose a predictor that allows to assess the patient-specific risk of molecular relapse on treatment discontinuation and to identify patients for whom cessation of therapy would be an appropriate option. Application of the suggested rule for deciding about the time point of treatment cessation is predicted to result in a significant reduction in rate of molecular relapse.

Can prognostic scoring systems for chronic myeloid leukemia as established in adults be applied to pediatric patients?

In contrast to adult medicine, specific scoring systems predicting the treatment response for an individual pediatric patient (pt) with chronic myeloid leukemia (CML) have not yet been defined. We evaluated to what extend prognostic scores as described for adults (e.g., Sokal, Hasford, EUTOS score) resulted in comparable risk group categorizations in a pediatric cohort. Parameters for score calculation were extracted from a data set of 90 patients enrolled into trial CML-PAED-II and treated by a standard dose of imatinib. At month 3 and at month 6, treatment response was analyzed based on the transcript ratio BCR-ABL1/ABL1. By the EUTOS, Hasford, and Sokal scores 81, 59, and 62 % of the patients were categorized as low risk, respectively; 19, 14, and 16 % of the patients as high risk, respectively; and by Hasford and Sokal scores 27 and 22 % of the patients, respectively, as intermediate risk. Twenty-seven out of 72 patients analyzable (38 %) exhibited a transcript ratio >10 % at month 3. We show that only the EUTOS score, but not the Sokal and Hasford score, correlates with this early outcome (p = 0.008). Analyzing the EUTOS score separately, we can demonstrate that lowering the cutoff from 87 to 48 points for categorization in low- and high-risk individuals increases the odds ratio from 2.4 (95 % CI 0.6 to 10.4) to 3.6 (95 % CI 1.3 to 10.9). Data are provided on the distribution of risk categories and resulting discrepancies when adult scores are applied on children and adolescents with CML at diagnosis. A larger number of patients and longer follow-up are still needed to develop a prognostic score specifically adapted to the pediatric and adolescent age cohorts.