The 10 most recently published documents
Whether at the intramolecular or cellular scale in organisms, cell-cell adhesion adapt to external mechanical cues arising from the static environment of cells and from dynamic interactions between neighboring cells. Cell-cell adhesions need to resist detachment forces to secure the integrity and internal organization of organisms. In the past, various techniques have been developed to characterize adhesion properties of molecules and cells in vitro, and to understand how cells sense and probe their environment. Atomic force microscopy and dual-pipette aspiration, where cells are mainly present in suspension, are common methods for studying detachment forces of cell-cell adhesions. How cell-cell adhesion forces are developed for adherent and environment-adapted cells, however, is less clear. Here, we designed the Cell-Cell Separation Device (CC-SD), a microstructured substrate that measures both intercellular forces and external stresses of cells towards the matrix. The design is based on micropillar arrays originally designed for cell traction-force measurements. We designed PDMS micropillar-blocks, to which cells could adhere and be able to connect to each other across the gap. Controlled stretching of the whole substrate changed the distance between blocks and increased gap size. That allowed us to apply strains to cell-cell contacts, eventually leading to cell-cell adhesion detachment, which was measured by pillar deflections. The CC-SD provided an increase of the gap between the blocks of up to 2.4-fold, which was sufficient to separate substrate-attached cells with fully developed F-actin network. Simultaneously measured pillar deflections allowed us to address cellular response to the intercellular strain applied. The CC-SD thus opens up possibilities for the analysis of intercellular force detachments and sheds light on the robustness of cell-cell adhesions in dynamic processes in tissue development.
Power plant operators increasingly rely on predictive models to diagnose and monitor their systems. Data-driven prediction models are generally simple and can have high precision, making them superior to physics-based or knowledge-based models, especially for complex systems like thermal power plants. However, the accuracy of data-driven predictions depends on (1) the quality of the dataset, (2) a suitable selection of sensor signals, and (3) an appropriate selection of the training period. In some instances, redundancies and irrelevant sensors may even reduce the prediction quality.
We investigate ideal configurations for predicting the live steam production of a solid fuel-burning thermal power plant in the pulp and paper industry for different modes of operation. To this end, we benchmark four machine learning algorithms on two feature sets and two training sets to predict steam production. Our results indicate that with the best possible configuration, a coefficient of determination of R^2 = 0.95 and a mean absolute error of MAE=1.2 t/h with an average steam production of 35.1 t/h is reached. On average, using a dynamic dataset for training lowers MAE by 32% compared to a static dataset for training. A feature set based on expert knowledge lowers MAE by an additional 32 %, compared to a simple feature set representing the fuel inputs. We can conclude that based on the static training set and the basic feature set, machine learning algorithms can identify long-term changes. When using a dynamic dataset the performance parameters of thermal power plants are predicted with high accuracy and allow for detecting short-term problems.
Highly-sensitive single-step sensing of levodopa by swellable microneedle-mounted nanogap sensors
(2023)
Microneedle (MN) sensing of biomarkers in interstitial fluid (ISF) can overcome the challenges of self-diagnosis of diseases by a patient, such as blood sampling, handling, and measurement analysis. However, the MN sensing technologies still suffer from poor measurement accuracy due to the small amount of target molecules present in ISF, and require multiple steps of ISF extraction, ISF isolation from MN, and measurement with additional equipment. Here, we present a swellable MN-mounted nanogap sensor that can be inserted into the skin tissue, absorb ISF rapidly, and measure biomarkers in situ by amplifying the measurement signals by redox cycling in nanogap electrodes. We demonstrate that the MN-nanogap sensor measures levodopa (LDA), medication for Parkinson disease, down to 100 nM in an aqueous solution, and 1 μM in both the skin-mimicked gelatin phantom and porcine skin.
Organic acidurias (OAs), urea-cycle disorders (UCDs), and maple syrup urine disease (MSUD) belong to the category of intoxication-type inborn errors of metabolism (IT-IEM). Liver transplantation (LTx) is increasingly utilized in IT-IEM. However, its impact has been mainly focused on clinical outcome measures and rarely on health-related quality of life (HRQoL). Aim of the study was to investigate the impact of LTx on HrQoL in IT-IEMs. This single center prospective study involved 32 patients (15 OA, 11 UCD, 6 MSUD; median age at LTx 3.0 years, range 0.8–26.0). HRQoL was assessed pre/post transplantation by PedsQL-General Module 4.0 and by MetabQoL 1.0, a specifically designed tool for IT-IEM. PedsQL highlighted significant post-LTx improvements in total and physical functioning in both patients' and parents' scores. According to age at transplantation (≤3 vs. >3 years), younger patients showed higher post-LTx scores on Physical (p = 0.03), Social (p < 0.001), and Total (p =0.007) functioning. MetabQoL confirmed significant post-LTx changes in Total and Physical functioning in both patients and parents scores (p ≤ 0.009). Differently from PedsQL, MetabQoL Mental (patients p = 0.013, parents p = 0.03) and Social scores (patients p = 0.02, parents p = 0.012) were significantly higher post-LTx. Significant improvements (p = 0.001–0.04) were also detected both in self- and proxy-reports for almost all MetabQoL subscales. This study shows the importance of assessing the impact of transplantation on HrQoL, a meaningful outcome reflecting patients' wellbeing. LTx is associated with significant improvements of HrQol in both self- and parentreports. The comparison between PedsQL-GM and MetabQoL highlighted that MetabQoL demonstrated higher sensitivity in the assessment of diseasespecific domains than the generic PedsQL tool.
Long-Term outcome of infantile onset pompe disease patients treated with enzyme replacement therapy
(2024)
Background: Enzyme replacement therapy (ERT) with recombinant human alglucosidase alfa (rhGAA) was approved in Europe in 2006. Nevertheless, data on the long-term outcome of infantile onset Pompe disease (IOPD) patients at school age is still limited.
Objective: We analyzed in detail cardiac, respiratory, motor, and cognitive function of 15 German-speaking patients aged 7 and older who started ERT at a median age of 5 months.
Results: Starting dose was 20 mg/kg biweekly in 12 patients, 20 mg/kg weekly in 2, and 40 mg/kg weekly in one patient. CRIM-status was positive in 13 patients (86.7%) and negative or unknown in one patient each (6.7%). Three patients (20%) received immunomodulation. Median age at last assessment was 9.1 (7.0–19.5) years. At last follow-up 1 patient (6.7%) had mild cardiac hypertrophy, 6 (42.9%) had cardiac arrhythmias, and 7 (46.7%) required assisted ventilation. Seven patients (46.7%) achieved the ability to walk independently and 5 (33.3%) were still ambulatory at last follow-up. Six patients (40%) were able to sit without support, while the remaining 4 (26.7%) were tetraplegic. Eleven patients underwent cognitive testing (Culture Fair Intelligence Test), while 4 were unable to meet the requirements for cognitive testing. Intelligence quotients (IQs) ranged from normal (IQ 117, 102, 96, 94) in 4 patients (36.4%) to mild developmental delay (IQ 81) in one patient (9.1%) to intellectual disability (IQ 69, 63, 61, 3x < 55) in 6 patients (54.5%). White matter abnormalities were present in 10 out of 12 cerebral MRIs from 7 patients.
Measuring what matters
(2023)
Patient reported outcomes (PROs) are generally defined as ‘any report of the status of a patient's health condition that comes directly from the patient, without interpretation of the patient's response by a clinician or anyone else’. A broader definition of PRO also includes ‘any information on the outcomes of health care obtained directly from patients without modification by clinicians or other health care professionals’. Following this approach, PROs encompass subjective perceptions of patients on how they function or feel not only in relation to a health condition but also to its treatment as well as concepts such as health-related quality of life (HrQoL), information on the functional status of a patient, signs and symptoms and symptom burden. PRO measurement instruments (PROMs) are mostly questionnaires and inform about what patients can do and how they feel. PROs and PROMs have not yet found unconditional acceptance and wide use in the field of inborn errors of metabolism. This review summarises the importance and usefulness of PROs in research, drug legislation and clinical care and informs about quality standards, development, and potential methodological shortfalls of PROMs. Inclusion of PROs measured with high-quality, well-selected PROMs into clinical care, drug legislation, and research helps to identify unmet needs, improve quality of care, and define outcomes that are meaningful to patients. The field of IEM should open to new methodological approaches such as the definition of core sets of variables including PROs to be systematically assessed in specific metabolic conditions and new collaborations with PRO experts, such as psychologists to facilitate the systematic collection of meaningful data.
Zu Beginn des Forschungsprojektes „Neue Museumswelten“ wollten wir von Studierenden der Studiengänge Bachelor und Master InterMedia an der Fachhochschule Vorarlberg wissen, was sie mit dem Begriff „Museum“ verbinden. „Museum? Da gehe ich nur im Urlaub hin. Aber hier in Vorarlberg nicht“, war eine geläufige Aussage, die auf ein bestimmtes mentales Modell von Museum verweist. Viele Studierenden gehören also der Gruppe der Gelegenheits- oder Nichtbesucher:innen an. Wie sich in weiterer Folge herausstellte, handelt es sich dabei um eine durchaus heterogene Gruppe, die jedoch auch Gemeinsamkeiten aufweist: Alle Menschen, mit denen wir bisher im Zuge des Forschungsprojekts im Stadtraum, auf Events und im Museum sprachen, spielten und Zukunftsvisionen entwickelten, brachten ihre eigenen Bilder, Vorstellungen und Ideen zu Museen und möglichen Museumszukünften mit. Der Untersuchung genau dieser Bilder und Vorstellungen – der mentalen Modelle von Museum also –, widmet sich das von Interreg geförderte Forschungsprojekt unter Einbindung vielfältiger Perspektiven und Methoden aus Sozialforschung und Design. Es verfolgt den innovativen Weg, „Designerly Ways of Knowing“0 von Beginn an konsequent in den Forschungsprozess zu integrieren, um anstrebenswerte Museumszukünfte gemeinsam mit den Menschen auszuloten...