Search Results (17,043)

(1) Objective: The aim of this study was to assess the biological behavior of bone tissue on a machined surface (MS) and modifications made by a laser beam (LS) and by a laser beam incorporated with hydroxyapatite (HA) using a biomimetic method without thermic treatment (LHS). (2) Methods: Scanning electron microscopy coupled with energy-dispersive X-ray spectrometry (SEM/EDX) was performed before and after installation in the rabbit tibiae. A total of 20 Albinus rabbits randomly received 30 implants of 3.75 × 10 mm in the right and left tibias, with two implants on each surface in each tibia. In the animals belonging to the 4-week euthanasia period group, intramuscular application of the fluorochromes calcein and alizarin was performed. In implants placed mesially in the tibiofemoral joint, biomechanical analysis was performed by means of a removal torque (N/cm). The tibias with the implants located distally to the joint were submitted for analysis by confocal laser microscopy (mineral apposition rate) and for histometric analysis by bone contact implant (%BIC) and newly formed bone area (%NBA). (3) Results: The SEM showed differences between the surfaces. The biomechanical analysis revealed significant differences in removal torque values between the MSs and LHSs over a 2-week period. Over a 4-week period, both the LSs and LHSs demonstrated removal torque values statistically higher than the MSs. BIC of the LHS implants were statistically superior to MS at the 2-week period and LHS and LS surfaces were statistically superior to MS at the 4-week period. Statistical analysis of the NBA of the implants showed difference between the LHS and MS in the period of 2 weeks. (4) Conclusions: The modifications of the LSs and LHSs provided important physicochemical modifications that favored the deposition of bone tissue on the surface of the implants. Full article

Fungi have always posed an unquestionable threat to heritage collections worldwide. Now, in a future of climate change, biological risk factors may have to be considered even more than before. Models and simulations to assess possible impacts a changing outdoor climate will have on indoor environments and, in turn, on biodeterioration are still underdeveloped and require a more substantial data basis. This study aimed at filling some of these knowledge gaps through a broad-based approach combining microclimatic and microbiological monitoring in four historic libraries in Austria with an uncontrolled indoor climate: Altenburg Abbey, Melk Abbey, Klosterneuburg Monastery and the Capuchin Monastery in Vienna. Data were generated from thermohygrometric sensors, cultivation-dependent air- and surface sampling and further surface dust sampling for cultivation-independent analyses. Results gave insights on the status quo of microbiological loads in the libraries and outdoor–indoor relationships. Influences of the geographic location and room-use on corresponding indoor fungal profiles were identified. Lower fungal diversities were found at the most rural site with the strongest climatic fluctuations and extreme values than in the most urban, sheltered library with a very stable climate. Further, the humidity-stabilizing potential of large collections of hygroscopic materials, such as books, was also examined. Implications for a sustainable approach to prevent future biodeterioration are discussed, supporting the long-term preservation of these valuable historic collections. Full article

Background: The clinical spectrum of fibrotic interstitial lung diseases (ILDs) is highly heterogeneous. We aimed to evaluate the prognostic value of widely available baseline biomarkers for the improvement of lung function in patients with fibrotic ILDs. Methods: This registry-based study included 142 patients with fibrotic ILDs as defined by the presence of reticulation, traction bronchiectasis or honeycombing on initial high-resolution computed tomography (HRCT). Functional improvement at 1 year was defined as a relative increase of 5% in forced vital capacity (FVC) or of 10% in diffusion capacity for carbon monoxide (DLCO). The prognostic value of baseline biomarkers was evaluated for all patients and the subgroup with anti-inflammatory treatment. Results: At one year, 44 patients showed improvement while 73 showed disease progression. Multivariate analyses found prognostic significance for age < 60 years (OR 5.4; 95%CI 1.9–15.4; p = 0.002), lactate dehydrogenase (LDH) >250 U/L (OR 2.5; 95%CI 1.1–5.8; p = 0.043) and blood monocyte count < 0.8 G/L (OR 3.5; 95%CI 1.1–11.3; p = 0.034). In 84 patients undergoing anti-inflammatory treatment, multivariate analysis revealed age < 60 years (OR 8.5 (95%CI 2.1–33.4; p = 0.002) as the only significant variable. Conclusion: Younger age, a higher LDH and lower blood monocyte count predicted functional improvement in fibrotic ILD patients, while in those treated with anti-inflammatory drugs, only age had significant implications. Full article

Selecting the optimal settings for the production of rubber goods can be a very time-consuming and resource-intensive process. A promising method for optimizing rubber processing in a short period of time is the use of simulation routines. However, process simulations have only recently enabled meaningful predictions of not only the part’s state of cure but also its mechanical characteristics. As a first approach, second-order polynomials were considered suitable for describing the properties of compression-molded parts. However, more precision is required for injection molding due to the narrower distribution of mechanical characteristics of parts produced at different vulcanization temperatures. This became evident when the approximation of mechanical data with second order models partly revealed significant failures of part behavior prediction. To tackle this issue, a combined approach for approximation is proposed in this contribution by means of logistic growth function in addition to second order polynomials. To feed the model, an experimental plan was designed for producing injection-molded parts from an SBR compound at various temperatures and to different degrees of cure. The parts obtained were then characterized mechanically, and the results were opposed to varying degrees of cure and extents of reaction to calculate the model coefficients. Once available, a simulation-based calculation of the mechanical part quality is possible. The comparison of test results from the simulation and the real process has shown a reliable prediction, as simulation results were found within the natural deviation of the real measurements. Full article

The aim of this work is to optimize the sensor positions of a sensor–actuator measurement system for identifying local variations in the magnetic permeability of cut steel sheets. Before solving the actual identification problem, i.e., finding the material distribution, the sensor placement of the measurement setup should be improved in order to reduce the uncertainty of the identification of the material distribution. The Fisher information matrix (FIM), which allows one to quantify the amount of information that the measurements carry about the unknown parameters, is used as the main metric for the objective function of this design optimization. The forward problem is solved by the finite element method. The results show that the proposed method is able to find optimal sensor positions as well as the minimum number of sensors to achieve a desired maximum parameter uncertainty. Full article

Background: The COVID-19 pandemic has necessitated changes in European healthcare systems, with a significant proportion of COVID-19 cases being managed on an outpatient basis in primary healthcare (PHC). To alleviate the burden on healthcare facilities, many European countries developed contact-tracing apps and symptom checkers to identify potential cases. As the pandemic evolved, the European Union introduced the Digital COVID-19 Certificate for travel, which relies on vaccination, recent recovery, or negative test results. However, the integration between these apps and PHC has not been thoroughly explored in Europe. Objective: To describe if governmental COVID-19 apps allowed COVID-19 patients to connect with PHC through their apps in Europe and to examine how the Digital COVID-19 Certificate was obtained. Methodology: Design and setting: Retrospective descriptive study in PHC in 30 European countries. An ad hoc, semi-structured questionnaire was developed to collect country-specific data on primary healthcare activity during the COVID-19 pandemic and the use of information technology tools to support medical care from 15 March 2020 to 31 August 2021. Key informants belong to the WONCA Europe network (World Organization of Family Doctors). The data were collected from relevant and reliable official sources, such as governmental websites and guidelines. Main outcome measures: Patient’s first contact with health system, governmental COVID-19 app (name and function), Digital COVID-19 Certification, COVID-19 app connection with PHC. Results: Primary care was the first point of care for suspected COVID-19 patients in 28 countries, and 24 countries developed apps to complement classical medical care. The most frequently developed app was for tracing COVID-19 cases (24 countries), followed by the Digital COVID-19 Certificate app (17 countries). Bulgaria, Italy, Serbia, North Macedonia, and Romania had interoperability between PHC and COVID-19 apps, and Poland and Romania’s apps considered social needs. Conclusions: COVID-19 apps were widely created during the first pandemic year. Contact tracing was the most frequent function found in the registered apps. Connection with PHC was scarcely developed. In future pandemics, connections between health system levels should be guaranteed to develop and implement effective strategies for managing diseases. Full article

Introduction: Aneurysmal wall enhancement (AWE) of non-ruptured sacular intracranial aneurysms (IA) after endovascular treatment (ET) is a frequently observed imaging finding using AWE-sequences in brain magnetic resonance imaging (MRI). So far, its value remains unclear. We aimed to investigate the effect of AWE on aneurysm reperfusion rates in a longitudinal cohort. Methods: This is a retrospective MRI study over the timespan of up to 5 years, assessing the correlation of increased AWE of non-ruptured IAs and events of aneurysm reperfusion and retreatment, PHASES Score and grade of AWE. T1 SPACE fat saturation (FS) and T1 SE FS blood suppression sequences after contrast administration were used for visual interpretation of increased AWE. The IAs’ sizes were assessed via the biggest diameter. The grade of enhancement was defined in a grading system from grade 1 to grade 3. Results: 127 consecutive non ruptured IA-patients (58.9 ± 9.0 years, 94 female, 33 male) who underwent elective aneurysm occlusion were included. AWE was observed in 40.2% of patients (51/127) after ET, 6 patients already showed AWE before treatment. In large IAs (which were defined as a single maximum diameter of over 7.5 mm), AWE was significantly associated with aneurysm reperfusion in contrast to large aneurysm without AWE). All grades of AWE were significantly associated with reperfusion. Conclusions: Our data suggests that in patients with initially large IAs, AWE is correlated with aneurysm reperfusion. Full article

An experimental characterization of cupric oxide nanowire (CuO NW) growth from thermally oxidized, microstructured Cu thin films is performed. We have systematically studied the influence of the thickness and dimension of Cu layers on the synthesis of CuO NW. The objective was to determine the optimum Cu geometries for increased CuO NWs growth to bridge the gap between adjacent Cu structures directly on the chip for gas sensing applications. Thresholds for CuO-NW growth regarding film thickness and lateral dimensions are identified based on SEM images. For a film thickness of 560 nm, NWs with lengths > 500 nm start to grow from the edges of Cu structures with an area ≥ 4 µm². NWs growing from the upper surface were observed for an area ≥ 16 µm². NW growth between adjacent thermally oxidized thin films was analyzed. The study provides information on the most relevant parameters of CuO NWs growth, which is mandatory for integrating CuO NWs as gas sensor components directly on microchips. Based on this result, the gap size of the structure was varied to find the optimum value of 3 µm. Full article

(1) Background: Due to similar clinical presentation and a lack of specific biomarkers, initial differentiation between Takotsubo syndrome (TTS) and non-ST-segment elevation myocardial infarction (NSTEMI) remains challenging in daily practice. Heat Shock Protein 70 (HSP70) is a novel biomarker that is recognized for its potential in the diagnosis and differentiation of cardiovascular conditions. (2) Methods: Data from a total of 156 patients were analyzed (32.1% NSTEMI, 32.7% TTS, and 35.3% controls). Serum concentrations of HSP70 were determined using ELISA and compared between patients and controls. ROC curve analysis, logistic regression analysis and propensity-score-weighted logistic regression were conducted. (3) Results: Concentrations of HSP70 were highest in patients with TTS (median 1727 pg/mL vs. ACS: median 1545 pg/mL vs. controls: median 583 pg/mL, p < 0.0001). HSP70 was predictive for TTS in binary logistic regression analysis (B(SE) = 0.634(0.22), p = 0.004), which even remained significant after correction for possible confounders in propensity-score-weighted analysis. ROC curve analysis also revealed a significant association of HSP70 with TTS (AUC: 0.633, p = 0.008). (4) Conclusions: Based on our findings, HSP70 constitutes a promising biomarker for discrimination between TTS and NSTEMI, especially in combination with established cardiovascular biomarkers like pBNP or high-sensitivity cardiac troponin. Full article

Background: Despite the increased use of mechanical thrombectomy (MT) in recent years, there remains a lack of research on in-hospital mortality rates following the procedure, the primary factors influencing these rates, and the potential for predicting them. This study aimed to utilize interpretable machine learning (ML) to help clarify these uncertainties. Methods: This retrospective study involved patients with anterior circulation large vessel occlusion (LVO)-related ischemic stroke who underwent MT. The patient division was made into two groups: (I) the in-hospital death group, referred to as miserable outcome, and (II) the in-hospital survival group, or favorable outcome. Python 3.10.9 was utilized to develop the machine learning models, which consisted of two types based on input features: (I) the Pre-MT model, incorporating baseline features, and (II) the Post-MT model, which included both baseline and MT-related features. After a feature selection process, the models were trained, internally evaluated, and tested, after which interpretation frameworks were employed to clarify the decision-making processes. Results: This study included 602 patients with a median age of 76 years (interquartile range (IQR) 65–83), out of which 54% (n = 328) were female, and 22% (n = 133) had miserable outcomes. Selected baseline features were age, baseline National Institutes of Health Stroke Scale (NIHSS) value, neutrophil-to-lymphocyte ratio (NLR), international normalized ratio (INR), the type of the affected vessel (‘Vessel type’), peripheral arterial disease (PAD), baseline glycemia, and premorbid modified Rankin scale (pre-mRS). The highest odds ratio of 4.504 was observed with the presence of peripheral arterial disease (95% confidence interval (CI), 2.120–9.569). The Pre-MT model achieved an area under the curve (AUC) value of around 79% utilizing these features, and the interpretable framework discovered the baseline NIHSS value as the most influential factor. In the second data set, selected features were the same, excluding pre-mRS and including puncture-to-procedure-end time (PET) and onset-to-puncture time (OPT). The AUC value of the Post-MT model was around 84% with age being the highest-ranked feature. Conclusions: This study demonstrates the moderate to strong effectiveness of interpretable machine learning models in predicting in-hospital mortality following mechanical thrombectomy for ischemic stroke, with AUCs of 0.792 for the Pre-MT model and 0.837 for the Post-MT model. Key predictors included patient age, baseline NIHSS, NLR, INR, occluded vessel type, PAD, baseline glycemia, pre-mRS, PET, and OPT. These findings provide valuable insights into risk factors and could improve post-procedural patient management. Full article

Asphalt pavements are fundamental to modern transportation infrastructure, requiring elasticity, firmness, and longevity. However, traditional asphalt, based on bitumen, faces several limitations. To improve pavement performance, polymer resins are being used to substitute bitumen and improve requirements. Therefore, a deep understanding of the material behavior is required. This study presents the analysis of the relaxation behavior of a poly(methyl methacrylate)-based pavement and the influence of mineral fillers. An approach using a linear elastic–viscoelastic material model was selected based on evidence and validated across the linear and nonlinear deformation range. The results reveal no influence of the mineral fillers on the relaxation behavior. The presented modification of the linear elastic and viscoelastic modeling reveals accurate results to predict long-term pavement performance. This approach offers a practical method for forecasting asphalt behavior. Further research is needed to incorporate deformation behavior into the model. Full article

As chronic illness is common among older people, self-care practices for older people are needed to control health status, to prevent possible complications and to ensure optimal quality of life. The literature has demonstrated that integrated care approaches are one key success factor for delivering person-centered and sustainable care for older people, with rehabilitation being a cornerstone in tertiary care prevention for older citizens. The current paper addresses the state of the literature for person-centered geriatric rehabilitation (GR) and the importance of personalized and participatory goal setting. In accordance with the bio–psycho–social model of the International Classification of Functioning, Disability and Health (ICF), social participation and the related goals are of particular importance for the entire rehabilitation process. The social participation of individuals enrolled into GR is therefore one of the milestones to be achieved during GR. Personalized goal setting during the entire rehabilitation process, Comprehensive Geriatric Assessment (CGA) and shared decision making allow a comprehensive care approach separate from solely function-based rehabilitation. The review also focusses on recent developments in digitalization in healthcare and delivers insights into how healthcare professionals’ collaborative practice supports sustainable rehabilitation results in patients of advanced chronological age. Full article

Background: Drusen and drusenoid deposits are a hallmark of age-related macular degeneration (AMD). Nowadays, a multimodal retinal imaging approach enables the detection of these deposits. However, quantitative data on subretinal drusenoid deposits (SDDs) are still missing. Here, we compare the capability of en-face drusen and SDD area detection in eyes with non-exudative AMD using conventional imaging modalities versus Retro mode imaging. We also quantitatively assess the topographic distribution of drusen and SDDs. Methods: In total, 120 eyes of 90 subjects (mean age ± standard deviation = 74.6 ± 8.6 years) were included. Coherent en-face drusen and SDD areas were measured via near-infrared reflectance, green (G-) and blue (B-) fundus autofluorescence (AF), and Retro mode imaging. Drusen phenotypes were classified by correlating en-face drusen areas using structural high-resolution spectral domain optical coherence tomography. The topographic distribution of drusen was analyzed according to a modified ETDRS (Early Treatment of Diabetic Retinopathy Study) grid. Intraclass correlation coefficient (ICC) analysis was applied to determine the inter-reader agreement in the SDD en-face area assessment. Results: The largest coherent en-face drusen area was found using Retro mode imaging with a mean area of 105.2 ± 45.9 mm² (deviated left mode (DL)) and 105.4 ± 45.5 mm² (deviated right mode (DR)). The smallest en-face drusen areas were determined by GAF (50.9 ± 42.6 mm²) and BAF imaging (49.1 ± 42.9 mm²) (p < 0.001). The inter-reader agreement for SDD en-face areas ranged from 0.93 (DR) to 0.70 (BAF). The topographic analysis revealed the highest number of SDDs in the superior peripheral retina, whereas sub-retinal pigment epithelium drusen were mostly found in the perifoveal retina. Retro mode imaging further enabled the detection of the earliest SDD stages. Conclusions: Retro mode imaging allows for a detailed detection of drusen phenotypes. While hundreds/thousands of SDDs can be present in one eye, the impact of SDD number or volume on AMD progression still needs to be evaluated. However, this new imaging modality can add important knowledge on drusen development and the pathophysiology of AMD. Full article

Breast cancer, a complex disease with a significant prevalence to form metastases, necessitates novel therapeutic strategies to improve treatment outcomes. Here, we present the results of a comparative molecular study of primary breast tumours, their metastases, and the corresponding primary cell lines using Desorption Electrospray Ionisation (DESI) and Laser-Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) imaging. Our results show that ambient ionisation mass spectrometry technology is suitable for rapid characterisation of samples, providing a lipid- and metabolite-rich spectrum within seconds. Our study demonstrates that the lipidomic fingerprint of the primary tumour is not significantly distinguishable from that of its metastasis, in parallel with the similarity observed between their respective primary cell lines. While significant differences were observed between tumours and the corresponding cell lines, distinct lipidomic signatures and several phospholipids such as PA(36:2), PE(36:1), and PE(P-38:4)/PE(O-38:5) for LA-REIMS imaging and PE(P-38:4)/PE(O-38:5), PS(36:1), and PI(38:4) for DESI-MSI were identified in both tumours and cells. We show that the tumours’ characteristics can be found in the corresponding primary cell lines, offering a promising avenue for assessing tumour responsiveness to therapeutic interventions. A comparative analysis by DESI-MSI and LA-REIMS imaging revealed complementary information, demonstrating the utility of LA-REIMS in the molecular imaging of cancer. Full article