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Epilepsy in women of reproductive age. Clinical, imagistic, electroencephalographic study: Abstract of the doctoral thesis in medical sciences: 321.05 â Clinical neurology
INTRODUCTION.
Actuality and importance of the issue addressed.
Three important aspects can be highlighted, which outline the research directions of the
work: (a) the issue of prevalence, clinical, electroencephalographic and imagistic semiology of
epilepsy in women of reproductive age, taking into account the age of onset of the disease and its
evolution over time (after a follow-up of patients for 5 years); (b) to identify and describe
(parameterise) correlations between the semiological picture, EEG or MRI descriptions, with the
possibility of using them to guide the exact diagnosis and adaptation of antiepileptic treatment; (c)
attempt to find an answer regarding possible scenarios of disease evolution (e.g. worsening,
remission, resistance to antiepileptic drugs, occurrence of status epilepticus), preferably -
objective, based on simple, reproducible observable indicators that can be included in a
mathematical probability estimation model. It is believed that these three aspects, if known, would
significantly improve the quality of life of patients with epilepsy of reproductive age and increase
the effectiveness of prescribed treatments.
Description of the situation in the field and identification of the research problem
Despite remarkable advances in neuroscience, pharmacology and imaging technologies,
epilepsy continues to have a high prevalence and remains an important public health problem. In
Republic of Moldova, according to data from the National Bureau of Statistics, about 60,000
people suffer from epilepsy, of which 13,500-15,000 are women. The prevalence of epilepsy in
Republic of Moldova is 19 cases per 1000 inhabitants (2015 data) [1]. The prevalence of epilepsy
in women is variably reported in the literature, being considered rarer in women than in men (41
vs. 49 cases per 100,000 population or 6.0 vs. 6.5 cases per 1000 population). However, the
given disease is considered to be underestimated in women due to the stigma of the disease, its
non-reporting or the natural variability of the actual prevalence of the disease throughout life [2-
5]. In addition to the lack of knowledge of the true prevalence of epilepsy in women of
reproductive age, an important problem is the lack of a complete description of the seizure itself
(aura, semiology, circumstances, triggers, duration, postictal signs, EEG tracings or MRI images,
involving specific structural changes). This prevents the correct classification of seizure type
(subtype). It was not until 2017-2021 that the consensus definition of epilepsy syndrome was
given by the International League Against Epilepsy, ILAE [6, 7].
Contemporary electroencephalographic examination allows the differentiation of cortical
areas involved in abnormal electrical activity in the brain (seizure initiation area, epileptogenic
area, as well as symptomogenic, irritative and epileptogenic lesion areas), as well as distinguishing
the phases of the given activity (ictal wave front, followed by excitation and inhibition wave
propagation front) [8, 9].
Equipping hospitals in the Republic of Moldova with high-performance nuclear magnetic
resonance machines opens up new possibilities for identifying and differentiating brain lesions
with epileptogenic potential. Contemporary MRI imaging algorithms can identify and classify
these lesions automatically, thus becoming important tools in diagnosis, choice of treatment
tactics or prognosis of disease evolution [10, 11]. This trend in the use of MRI imaging in
epileptology is nowadays current internationally, and the corroboration with clinical and
neurophysiological results opens new paradigms of approach.
All these descriptions allowed the formulation of the research hypothesis, the purpose of
the work and the research objectives.
Purpose. To describe the interrelationships over time between clinical, neurophysiological
and imagistic features of epilepsy in women of reproductive age, with the development of
predictive mathematical models for the most important clinical events.
Research objectives
1) Characterization of the evolution over time of the clinical, neurophysiological and imaging
features of epilepsy in women of reproductive age, according to the age of onset of the disease;
2) Identification and parameterization of clinically important clinico-neurophysiological and
clinico-imaging correlations in women with epilepsy of reproductive age, according to the age
of onset of the disease.;
3) Argumentation, development and characterization of predictive mathematical models for the
most important clinical events (worsening of the condition over time, risk of progression to
status epilepticus, development of resistance to antiepileptic drugs and stable remission of the
disease) in patients of reproductive age with epilepsy.
Research hypothesis
Epilepsy in women of reproductive age has distinct and possibly different clinical, imaging
and neurophysiological features that may correlate with each other, depending on the age of onset
or progression of the disease, and the likelihood of clinically important events can be estimated by
mathematical models based on the features identified.
General research methodology
The study in the thesis was a prospective-retrospective, cohort, descriptive-analytical study,
with approval of the research protocol by the Research Ethics Committee (minutes no. 55 of
03.06.2016). Data were collected for 5 years (primary visit and the 3 annual conclusive follow-up
visits of patients, neurophysiological and neuroimaging examinations) in the Institute of Neurology
and Neurosurgery "Diomid Gherman", State Hospital of the Republic of Moldova and Private
Medical Institution "Excellence". After the numeration of the primary data, the database was imported
into the statistical analysis software GraphPad Prism, v. 9 trial (Graph Pad Software, Boston, USA).
The data were analyzed both in terms of age categories of onset of illness (3 groups, group 1 - 0-11
years; group 2 - 12-18 years; group 3 - 19-49 years) and in terms of time course of illness (visits 1-4).
From these perspectives, the clinical, electrophysiological and imaging features of epilepsy were
characterized using the Fisher or extended Mantel-Haenszel test. After generalizing the results and
obtaining the general characteristics, a correlational analysis (Pearson's r-test) was performed; the
given analysis allowed the identification of those data, which correspond to a statistically significant
degree of clinical-neurophysiological and clinical-imaging correlation, from which clinically
significant correlations were selected. The results obtained allowed to argue, develop and characterize
probabilistic models for 4 clinically important outcomes (worsening of the condition over time, risk
of progression to status epilepticus, development of resistance to antiepileptic drugs, stable remission
of the disease). The selection of clinical, electroencephalographic and imaging parameters that
entered the probability formula was based on multivariate analysis, testing for multicollinearity
(variance inflation factor calculation) and the contribution of each parameter in the formula using the
Akaike informativeness criterion. The performance of the predictive models developed was expressed
by the area under the ROC curve, positive and negative prognostic power. Based on the results
obtained, practical recommendations were developed.
Scientific innovation of the obtained results
1. For the first time, some patterns of evolution over time and the interrelationships between
clinical, neurophysiological and imaging parameters in women of reproductive age with
epilepsy were characterized according to the age of onset of the disease.
2. Several statistically significant correlations between clinical, neurophysiological and imaging
parameters were found to exist, but only some of them have real clinical significance.
3. Also, as a result of our own research, it has been possible to develop, for the first time,
mathematical models that can accurately predict the worsening of the condition over time, the
risk of developing status epilepticus, the development of resistance to antiepileptic drugs and
stable remission of the disease in patients of reproductive age with epilepsy.
4. The particularities of the evolution over time of clinical, neurophysiological and imaging
features and their interrelationships in patients of reproductive age with epilepsy were
identified, which made it possible to develop predictive mathematical models for the 4
important events listed.
5. The paper provides an elaborated, adapted methodology for the clinical and instrumental
investigation, documentation and monitoring over time of patients of reproductive age with
epilepsy, allowing the identification of clinical, neurophysiological and imaging features over
time, according to the age of onset of the disease. The paper also provides the theoretical and
methodological support for the development and application of predictive mathematical models
for 4 important events (worsening of the condition over time, risk of developing status
epilepticus, development of resistance to antiepileptic drugs and stable remission of the
disease).
The applied value of the work. The research results provide simple practical solutions for
neurologists in assessing, risk stratifying, monitoring patients of reproductive age with epilepsy.
Clinically significant correlations between clinical, neurophysiological and imaging features
(brain lesions with epileptogenic potential, identifiable on MRI) were identified. The mathematical
models developed make it possible to predict with a significantly higher accuracy the 4 important
events identified in the study (worsening of the condition over time, risk of progression to status
epilepticus, development of resistance to antiepileptic drugs, stable remission of the disease)
specific to women of reproductive age with epilepsy.
Implementation of scientific results. The research results were implemented in the
current clinical practice (part of the institutional clinical protocol, standard operating procedure of
the workplace) in the Neurology Department of the State Hospital, Chisinau, Republic of Moldova.
Approval of the results. The results of the study were presented and discussed in the
following national and international scientific fora: 3rd Congress of the European Academy of
Neurology (24-27 June 2017), Netherlands, Amsterdam; Congress dedicated to the 75th Anniversary
of the founding of USMF "Nicolae Testemitanu", Chisinau, Republic of Moldova; World Congress
of Neurology, XXIV edition of 2019 (27-31 October, 2019), Dubai, United Arab Emirates; Congress
of Young Researchers "MedEspera" (3-5 May, 2018), Chisinau, Republic of Moldova; Conference
"Days of the University USMF Nicolae Testemitanu", section no. 8 "Current problems of neurology
and neurosurgery" (October 19, 2017), Chisinau, Republic of Moldova; Conference "Days of the
University USMF Nicolae Testemitanu", section no. 8 "Current Problems of Neurology and
Neurosurgery" (20 October 2016), Chisinau, Republic of Moldova; 4th Congress of the European
Academy of Neurology (16-19 June 2018), Lisbon, Portugal; European Stroke Association
Conference, 4th edition (16-18 May, 2018), Gothenburg, Sweden; European Congress of
Epileptology, 13th edition (26-30 August 2018), Vienna, Austria; European Academy of Neurology
Congress, 5th edition, (June 2019), Oslo, Norway.
Publications on the thesis topic. The basic materials of the thesis have been published in
11 scientific papers, including, 5 articles in nationally indexed journals, 6 abstracts published in
collections of papers at scientific events (including, 4 abroad); 5 intellectual property objects, 10
presentations and oral communications at various international scientific events (4 in the country
and 6 abroad).
Volume and structure of the thesis. The text of the thesis is set out on 164 computerprocessed basic text pages, consisting of: list of abbreviations, introduction, 4 chapters, general
conclusions, practical recommendations, bibliography of 245 sources and 4 appendices. Illustrative
material includes 32 tables, 22 figures
Ruthenium metallotherapeutics: a targeted approach to combatting multidrug resistant pathogens
The discovery of antibiotics revolutionised healthcare practice. However due to overuse, inappropriate use, widespread prophylaxis therapy and the lack of new developments, the threat of antimicrobial resistance is now a major global threat to health. By 2050, it is estimated that mortality due to antimicrobial resistant infections will exceed 10 million people per annum, superseding cancer as the leading cause of global mortality. The use of drug repurposing to identify potential therapies which combat antimicrobial resistance is one potential solution. Metals have been used as antimicrobial agents throughout the history of medicine for a broad range of applications, including the use of Silver as an antimicrobial agent which dates back to antiquity. More recently, Ruthenium metallotherapeutic complexes have been shown to exhibit highly active antimicrobial properties by targeting a range of bacterial species, and in contrast to traditional antibiotics, these compounds are thought to elicit antibacterial activity at multiple sites within the bacterial cell, which may reduce the possibility of resistance evolution. This study aimed to evaluate the antimicrobial activity of a series of Ruthenium metallotherapeutic complexes against multidrug-resistant bacterial pathogens, with a focus on use within wound care applications.
Antimicrobial susceptibility assays identified two lead candidates, Hexaammineruthenium (III) chloride and [Chlorido(η6-p-cymene)(N-(4-chlorophenyl)pyridine-2-carbothioamide) ruthenium (II)] chloride which demonstrated activity against Pseudomonas aeruginosa and Staphylococcus aureus respectively with MIC values ranging between 4 Όg mL-1 and 16 Όg mL-1. Furthermore, Hexaammineruthenium (III) chloride demonstrated antibiofilm activity in both a time and concentration-dependent manner. Synergy studies combining lead complexes with antibiotics demonstrated the potential for use as resistance breakers. Subsequent in vitro infection modelling using scratch assays with skin cell lines, coupled with a 3D full thickness skin wound infection model was used to determine potential applied applications of Hexaammineruthenium (III) chloride for use as topical antimicrobial agent against P. aeruginosa infections.
Antimicrobial mechanistic studies demonstrated that Hexaammineruthenium (III) chloride targeted the bacterial cell ultrastructure of P. aeruginosa strain PAO1 as cell perturbations were observed when treated cells were analysed by scanning electron microscopy. Furthermore, exposure of P. aeruginosa PAO1 to Hexaammineruthenium (III) chloride also resulted in a concentration dependent membrane depolarisation, which further supported the antimicrobial mechanistic role.
Finally, global changes in gene expression following exposure of P. aeruginosa strain PAO1 to Hexaammineruthenium (III) chloride were explored by RNA sequencing. Genes involved in ribosome function, cofactor biosynthesis and membrane fusion were downregulated, which provided a further insight into the wider mechanisms of antibacterial activity.
The research conducted in the present study indicated the potential use of Hexaammineruthenium (III) chloride (and derivatives) as a potential treatment option for chronic wounds infected with P. aeruginosa, which could be applied as either a direct treatment or used within antimicrobial wound care applications
Spatial normalization for voxel-based lesion symptom mapping: impact of registration approaches
BackgroundVoxel-based lesion symptom mapping (VLSM) assesses the relation of lesion location at a voxel level with a specific clinical or functional outcome measure at a population level. Spatial normalization, that is, mapping the patient images into an atlas coordinate system, is an essential pre-processing step of VLSM. However, no consensus exists on the optimal registration approach to compute the transformation nor are downstream effects on VLSM statistics explored. In this work, we evaluate four registration approaches commonly used in VLSM pipelines: affine (AR), nonlinear (NLR), nonlinear with cost function masking (CFM), and enantiomorphic registration (ENR). The evaluation is based on a standard VLSM scenario: the analysis of statistical relations of brain voxels and regions in imaging data acquired early after stroke onset with follow-up modified Rankin Scale (mRS) values.Materials and methodsFluid-attenuated inversion recovery (FLAIR) MRI data from 122 acute ischemic stroke patients acquired between 2 and 3 days after stroke onset and corresponding lesion segmentations, and 30 days mRS values from a European multicenter stroke imaging study (I-KNOW) were available and used in this study. The relation of the voxel location with follow-up mRS was assessed by uni- as well as multi-variate statistical testing based on the lesion segmentations registered using the four different methods (AR, NLR, CFM, ENR; implementation based on the ANTs toolkit).ResultsThe brain areas evaluated as important for follow-up mRS were largely consistent across the registration approaches. However, NLR, CFM, and ENR led to distortions in the patient images after the corresponding nonlinear transformations were applied. In addition, local structures (for instance the lateral ventricles) and adjacent brain areas remained insufficiently aligned with corresponding atlas structures even after nonlinear registration.ConclusionsFor VLSM study designs and imaging data similar to the present work, an additional benefit of nonlinear registration variants for spatial normalization seems questionable. Related distortions in the normalized images lead to uncertainties in the VLSM analyses and may offset the theoretical benefits of nonlinear registration
Resting-state EEG signatures of Alzheimer's disease are driven by periodic but not aperiodic changes
Electroencephalography (EEG) has shown potential for identifying early-stage biomarkers of neurocognitive dysfunction associated with dementia due to Alzheimer's disease (AD). A large body of evidence shows that, compared to healthy controls (HC), AD is associated with power increases in lower EEG frequencies (delta and theta) and decreases in higher frequencies (alpha and beta), together with slowing of the peak alpha frequency. However, the pathophysiological processes underlying these changes remain unclear. For instance, recent studies have shown that apparent shifts in EEG power from high to low frequencies can be driven either by frequency specific periodic power changes or rather by non-oscillatory (aperiodic) changes in the underlying 1/f slope of the power spectrum. Hence, to clarify the mechanism(s) underlying the EEG alterations associated with AD, it is necessary to account for both periodic and aperiodic characteristics of the EEG signal. Across two independent datasets, we examined whether resting-state EEG changes linked to AD reflect true oscillatory (periodic) changes, changes in the aperiodic (non-oscillatory) signal, or a combination of both. We found strong evidence that the alterations are purely periodic in nature, with decreases in oscillatory power at alpha and beta frequencies (AD < HC) leading to lower (alpha + beta) / (delta + theta) power ratios in AD. Aperiodic EEG features did not differ between AD and HC. By replicating the findings in two cohorts, we provide robust evidence for purely oscillatory pathophysiology in AD and against aperiodic EEG changes. We therefore clarify the alterations underlying the neural dynamics in AD and emphasize the robustness of oscillatory AD signatures, which may further be used as potential prognostic or interventional targets in future clinical investigations.</p
Cerebral blood flow velocity progressively decreases with increasing levels of verticalization in healthy adults. A cross-sectional study with an observational design
BackgroundAutoregulation of the cerebral vasculature keeps brain perfusion stable over a range of systemic mean arterial pressures to ensure brain functioning, e.g., in different body positions. Verticalization, i.e., transfer from lying (0°) to upright (70°), which causes systemic blood pressure drop, would otherwise dramatically lower cerebral perfusion pressure inducing fainting. Understanding cerebral autoregulation is therefore a prerequisite to safe mobilization of patients in therapy.AimWe measured the impact of verticalization on cerebral blood flow velocity (CBFV) and systemic blood pressure (BP), heart rate (HR) and oxygen saturation in healthy individuals.MethodsWe measured CBFV in the middle cerebral artery (MCA) of the dominant hemisphere in 20 subjects using continuous transcranial doppler ultrasound (TCD). Subjects were verticalized at 0°, â5°, 15°, 30°, 45° and 70° for 3â5 min each, using a standardized Sara Combilizer chair. In addition, blood pressure, heart rate and oxygen saturation were continuously monitored.ResultsWe show that CBFV progressively decreases in the MCA with increasing degrees of verticalization. Systolic and diastolic BP, as well as HR, show a compensatory increase during verticalization.ConclusionIn healthy adults CBFV changes rapidly with changing levels of verticalization. The changes in the circulatory parameters are similar to results regarding classic orthostasis.RegistrationClinicalTrials.gov, identifier: NCT04573114
Assimilation of Meteosat Third Generation (MTG) Lightning Imager (LI) pseudo-observations in AROME-France â proof of concept
This study develops a lightning data assimilation (LDA) scheme for the regional, convection-permitting numerical weather prediction (NWP) model AROME-France. The LDA scheme intends to assimilate total lightning, i.e., cloud-to-ground (CG) and inter- and intra-cloud (IC), of the future Meteosat Third Generation (MTG) Lightning Imager (LI; MTG-LI). MTG-LI proxy data are created, and flash extent density (FED) fields are derived.
An FED forward observation operator (FFO) is trained based on modeled, column-integrated graupel mass from 24 storm days in 2018. The FFO is successfully verified for 2 independent storm days.
With the FFO, the LDA adapts a 1-dimensional Bayesian (1DBay) retrieval followed by a 3-dimensional variational (3DVar) assimilation approach that is currently run operationally in AROME-France for radar reflectivity data. The 1DBay retrieval derives relative humidity profiles from the background by comparing the FED observations to the FED inferred from the background. Retrieved relative humidity profiles are assimilated as sounding data.
The evaluation of the LDA comprises different LDA experiments and four case studies. It is found that all LDA experiments can increase the background integrated water vapor (IWV) in regions where the observed FED exceeds the FED inferred from AROME-France outputs. In addition, IWV can be reduced where spurious FED is modeled. A qualitative analysis of 6âh accumulated rainfall fields reveals that the LDA is capable of locating and initiating some local precipitation fields better than a radar data assimilation (RDA) experiment. However, the LDA also leads to rainfall accumulations that are too high at some locations. Fractions skill scores (FSSs) of 6âh accumulated rainfall are overall similar for the developed LDA and RDA experiments. An approach aiming at mitigating effects due to differences in the optical extents of lightning flashes and the area of the corresponding cloud was developed and included in the LDA; however, it does not always improve the FSS.</p
Rethink Digital Health Innovation: Understanding Socio-Technical Interoperability as Guiding Concept
Diese Dissertation sucht nach einem theoretischem GrundgerĂŒst, um komplexe, digitale Gesundheitsinnovationen so zu entwickeln, dass sie bessere Erfolgsaussichten haben, auch in der alltĂ€glichen Versorgungspraxis anzukommen. Denn obwohl es weder am Bedarf von noch an Ideen fĂŒr digitale Gesundheitsinnovationen mangelt, bleibt die Flut an erfolgreich in der Praxis etablierten Lösungen leider aus. Dieser unzureichende Diffusionserfolg einer entwickelten Lösung - gern auch als Pilotitis pathologisiert - offenbart sich insbesondere dann, wenn die geplante Innovation mit gröĂeren Ambitionen und KomplexitĂ€t verbunden ist. Dem geĂŒbten Kritiker werden sofort ketzerische Gegenfragen in den Sinn kommen. Beispielsweise was denn unter komplexen, digitalen Gesundheitsinnovationen verstanden werden soll und ob es ĂŒberhaupt möglich ist, eine universale Lösungsformel zu finden, die eine erfolgreiche Diffusion digitaler Gesundheitsinnovationen garantieren kann. Beide Fragen sind nicht nur berechtigt, sondern mĂŒnden letztlich auch in zwei ForschungsstrĂ€nge, welchen ich mich in dieser Dissertation explizit widme.
In einem ersten Block erarbeite ich eine Abgrenzung jener digitalen Gesundheitsinnovationen, welche derzeit in Literatur und Praxis besondere Aufmerksamkeit aufgrund ihres hohen Potentials zur Versorgungsverbesserung und ihrer resultierenden KomplexitĂ€t gewidmet ist. Genauer gesagt untersuche ich dominante Zielstellungen und welche Herausforderung mit ihnen einhergehen. Innerhalb der Arbeiten in diesem Forschungsstrang kristallisieren sich vier Zielstellungen heraus: 1. die UnterstĂŒtzung kontinuierlicher, gemeinschaftlicher Versorgungsprozesse ĂŒber diverse Leistungserbringer (auch als inter-organisationale Versorgungspfade bekannt); 2. die aktive Einbeziehung der Patient:innen in ihre Versorgungsprozesse (auch als Patient Empowerment oder Patient Engagement bekannt); 3. die StĂ€rkung der sektoren-ĂŒbergreifenden Zusammenarbeit zwischen Wissenschaft und Versorgungpraxis bis hin zu lernenden Gesundheitssystemen und 4. die Etablierung daten-zentrierter Wertschöpfung fĂŒr das Gesundheitswesen aufgrund steigender bzgl. VerfĂŒgbarkeit valider Daten, neuen Verarbeitungsmethoden (Stichwort KĂŒnstliche Intelligenz) sowie den zahlreichen Nutzungsmöglichkeiten. Im Fokus dieser Dissertation stehen daher weniger die autarken, klar abgrenzbaren Innovationen (bspw. eine Symptomtagebuch-App zur Beschwerdedokumentation). Vielmehr adressiert diese Doktorarbeit jene Innovationsvorhaben, welche eine oder mehrere der o.g. Zielstellung verfolgen, ein weiteres technologisches Puzzleteil in komplexe Informationssystemlandschaften hinzufĂŒgen und somit im Zusammenspiel mit diversen weiteren IT-Systemen zur Verbesserung der Gesundheitsversorgung und/ oder ihrer Organisation beitragen.
In der Auseinandersetzung mit diesen Zielstellungen und verbundenen Herausforderungen der Systementwicklung rĂŒckte das Problem fragmentierter IT-Systemlandschaften des Gesundheitswesens in den Mittelpunkt. Darunter wird der unerfreuliche Zustand verstanden, dass unterschiedliche Informations- und Anwendungssysteme nicht wie gewĂŒnscht miteinander interagieren können. So kommt es zu Unterbrechungen von InformationsflĂŒssen und Versorgungsprozessen, welche anderweitig durch fehleranfĂ€llige ZusatzaufwĂ€nde (bspw. Doppeldokumentation) aufgefangen werden mĂŒssen. Um diesen EinschrĂ€nkungen der EffektivitĂ€t und Effizienz zu begegnen, mĂŒssen eben jene IT-System-Silos abgebaut werden. Alle o.g. Zielstellungen ordnen sich dieser defragmentierenden Wirkung unter, in dem sie 1. verschiedene Leistungserbringer, 2. Versorgungsteams und Patient:innen, 3. Wissenschaft und Versorgung oder 4. diverse Datenquellen und moderne Auswertungstechnologien zusammenfĂŒhren wollen. Doch nun kommt es zu einem komplexen Ringschluss. Einerseits suchen die in dieser Arbeit thematisierten digitalen Gesundheitsinnovationen Wege zur Defragmentierung der Informationssystemlandschaften.
Andererseits ist ihre eingeschrĂ€nkte Erfolgsquote u.a. in eben jener bestehenden Fragmentierung begrĂŒndet, die sie aufzulösen suchen.
Mit diesem Erkenntnisgewinn eröffnet sich der zweite Forschungsstrang dieser Arbeit, der sich mit der Eigenschaft der 'InteroperabilitĂ€t' intensiv auseinandersetzt. Er untersucht, wie diese Eigenschaft eine zentrale Rolle fĂŒr Innovationsvorhaben in der Digital Health DomĂ€ne einnehmen soll. Denn InteroperabilitĂ€t beschreibt, vereinfacht ausgedrĂŒckt, die FĂ€higkeit von zwei oder mehreren Systemen miteinander gemeinsame Aufgaben zu erfĂŒllen. Sie reprĂ€sentiert somit das Kernanliegen der identifizierten Zielstellungen und ist Dreh- und Angelpunkt, wenn eine entwickelte Lösung in eine konkrete Zielumgebung integriert werden soll. Von einem technisch-dominierten Blickwinkel aus betrachtet, geht es hierbei um die GewĂ€hrleistung von validen, performanten und sicheren Kommunikationsszenarien, sodass die o.g. InformationsflussbrĂŒche zwischen technischen Teilsystemen abgebaut werden. Ein rein technisches InteroperabilitĂ€tsverstĂ€ndnis genĂŒgt jedoch nicht, um die Vielfalt an Diffusionsbarrieren von digitalen Gesundheitsinnovationen zu umfassen. Denn beispielsweise das Fehlen adĂ€quater VergĂŒtungsoptionen innerhalb der gesetzlichen Rahmenbedingungen oder eine mangelhafte PassfĂ€higkeit fĂŒr den bestimmten Versorgungsprozess sind keine rein technischen Probleme. Vielmehr kommt hier eine Grundhaltung der Wirtschaftsinformatik zum Tragen, die Informationssysteme - auch die des Gesundheitswesens - als sozio-technische Systeme begreift und dabei Technologie stets im Zusammenhang mit Menschen, die sie nutzen, von ihr beeinflusst werden oder sie organisieren, betrachtet. Soll eine digitale Gesundheitsinnovation, die einen Mehrwert gemÀà der o.g. Zielstellungen verspricht, in eine existierende Informationssystemlandschaft der Gesundheitsversorgung integriert werden, so muss sie aus technischen sowie nicht-technischen Gesichtspunkten 'interoperabel' sein.
Zwar ist die Notwendigkeit von InteroperabilitĂ€t in der Wissenschaft, Politik und Praxis bekannt und auch positive Bewegungen der DomĂ€ne hin zu mehr InteroperabilitĂ€t sind zu verspĂŒren. Jedoch dominiert dabei einerseits ein technisches VerstĂ€ndnis und andererseits bleibt das Potential dieser Eigenschaft als Leitmotiv fĂŒr das Innovationsmanagement bislang weitestgehend ungenutzt. An genau dieser Stelle knĂŒpft nun der Hauptbeitrag dieser Doktorarbeit an, in dem sie eine sozio-technische Konzeptualisierung und Kontextualisierung von InteroperabilitĂ€t fĂŒr kĂŒnftige digitale Gesundheitsinnovationen vorschlĂ€gt. Literatur- und expertenbasiert wird ein Rahmenwerk erarbeitet - das Digital Health Innovation Interoperability Framework - das insbesondere Innovatoren und Innovationsfördernde dabei unterstĂŒtzen soll, die Diffusionswahrscheinlichkeit in die Praxis zu erhöhen. Nun sind mit diesem Framework viele Erkenntnisse und Botschaften verbunden, die ich fĂŒr diesen Prolog wie folgt zusammenfassen möchte:
1. Um die Entwicklung digitaler Gesundheitsinnovationen bestmöglich auf eine erfolgreiche
Integration in eine bestimmte Zielumgebung auszurichten, sind die Realisierung
eines neuartigen Wertversprechens sowie die GewÀhrleistung sozio-technischer InteroperabilitÀt
die zwei zusammenhÀngenden Hauptaufgaben eines Innovationsprozesses.
2. Die GewÀhrleistung von InteroperabilitÀt ist eine aktiv zu verantwortende Managementaufgabe
und wird durch projektspezifische Bedingungen sowie von externen und internen Dynamiken beeinflusst.
3. Sozio-technische InteroperabilitÀt im Kontext digitaler Gesundheitsinnovationen kann
ĂŒber sieben, interdependente Ebenen definiert werden: Politische und regulatorische Bedingungen;
Vertragsbedingungen; Versorgungs- und GeschÀftsprozesse; Nutzung; Information; Anwendungen; IT-Infrastruktur.
4. Um InteroperabilitÀt auf jeder dieser Ebenen zu gewÀhrleisten, sind Strategien differenziert
zu definieren, welche auf einem Kontinuum zwischen KompatibilitÀtsanforderungen
aufseiten der Innovation und der Motivation von Anpassungen aufseiten der Zielumgebung
verortet werden können.
5. Das Streben nach mehr InteroperabilitÀt fördert sowohl den nachhaltigen Erfolg der einzelnen digitalen
Gesundheitsinnovation als auch die Defragmentierung existierender Informationssystemlandschaften und
trÀgt somit zur Verbesserung des Gesundheitswesens bei.
Zugegeben: die letzte dieser fĂŒnf Botschaften trĂ€gt eher die FĂ€rbung einer Ăberzeugung, als dass sie ein Ergebnis wissenschaftlicher BeweisfĂŒhrung ist. Dennoch empfinde ich diese, wenn auch persönliche Erkenntnis als Maxim der DomĂ€ne, der ich mich zugehörig fĂŒhle - der IT-Systementwicklung des Gesundheitswesens
Model-free optimization of power/efficiency tradeoffs in quantum thermal machines using reinforcement learning
A quantum thermal machine is an open quantum system that enables the conversion between heat and work at the micro or nano-scale. Optimally controlling such out-of-equilibrium systems is a crucial yet challenging task with applications to quantum technologies and devices. We introduce a general model-free framework based on reinforcement learning to identify out-of-equilibrium thermodynamic cycles that are Pareto optimal tradeoffs between power and efficiency for quantum heat engines and refrigerators. The method does not require any knowledge of the quantum thermal machine, nor of the system model, nor of the quantum state. Instead, it only observes the heat fluxes, so it is both applicable to simulations and experimental devices. We test our method on a model of an experimentally realistic refrigerator based on a superconducting qubit, and on a heat engine based on a quantum harmonic oscillator. In both cases, we identify the Pareto-front representing optimal power-efficiency tradeoffs, and the corresponding cycles. Such solutions outperform previous proposals made in the literature, such as optimized Otto cycles, reducing quantum friction
Leveraging elasticity theory to calculate cell forces: From analytical insights to machine learning
Living cells possess capabilities to detect and respond to mechanical features of their surroundings. In traction force microscopy, the traction of cells on an elastic substrate is made visible by observing substrate deformation as measured by the movement of embedded marker beads. Describing the substrates by means of elasticity theory, we can calculate the adhesive forces, improving our understanding of cellular function and behavior. In this dissertation, I combine analytical solutions with numerical methods and machine learning techniques to improve traction prediction in a range of experimental applications. I describe how to include the normal traction component in regularization-based Fourier approaches, which I apply to experimental data. I compare the dominant strategies for traction reconstruction, the direct method and inverse, regularization-based approaches and find, that the latter are more precise while the former is more stress resilient to noise. I find that a point-force based reconstruction can be used to study the force balance evolution in response to microneedle pulling showing a transition from a dipolar into a monopolar force arrangement. Finally, I show how a conditional invertible neural network not only reconstructs adhesive areas more localized, but also reveals spatial correlations and variations in reliability of traction reconstructions
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