Abstract
Background
The clinical spectrum of acute SARS-CoV-2 infection ranges from an asymptomatic to life-threatening disease. Considering the broad spectrum of severity, reliable biomarkers are ...required for early risk stratification and prediction of clinical outcomes. Despite numerous efforts, no COVID-19-specific biomarker has been established to guide further diagnostic or even therapeutic approaches, most likely due to insufficient validation, methodical complexity, or economic factors. COVID-19-associated coagulopathy is a hallmark of the disease and is mainly attributed to dysregulated immunothrombosis. This process describes an intricate interplay of platelets, innate immune cells, the coagulation cascade, and the vascular endothelium leading to both micro- and macrothrombotic complications. In this context, increased levels of immunothrombotic components, including platelet and platelet-leukocyte aggregates, have been described and linked to COVID-19 severity.
Methods
Here, we describe a label-free quantitative phase imaging approach, allowing the identification of cell-aggregates and their components at single-cell resolution within 30 min, which prospectively qualifies the method as point-of-care (POC) testing.
Results
We find a significant association between the severity of COVID-19 and the amount of platelet and platelet-leukocyte aggregates. Additionally, we observe a linkage between severity, aggregate composition, and size distribution of platelets in aggregates.
Conclusions
This study presents a POC-compatible method for rapid quantitative analysis of blood cell aggregates in patients with COVID-19.
Label-free approaches are attractive in cytological imaging due to their flexibility and cost efficiency. They are supported by machine learning methods, which, despite the lack of labeling and the ...associated lower contrast, can classify cells with high accuracy where the human observer has little chance to discriminate cells. In order to better integrate these workflows into the clinical decision making process, this work investigates the calibration of confidence estimation for the automated classification of leukocytes. In addition, different visual explanation approaches are compared, which should bring machine decision making closer to professional healthcare applications. Furthermore, we were able to identify general detection patterns in neural networks and demonstrate the utility of the presented approaches in different scenarios of blood cell analysis.
The quality of datasets plays a crucial role in the successful training and deployment of deep learning models. Especially in the medical field, where system performance may impact the health of ...patients, clean datasets are a safety requirement for reliable predictions. Therefore, outlier detection is an essential process when building autonomous clinical decision systems. In this work, we assess the suitability of Self-Organizing Maps for outlier detection specifically on a medical dataset containing quantitative phase images of white blood cells. We detect and evaluate outliers based on quantization errors and distance maps. Our findings confirm the suitability of Self-Organizing Maps for unsupervised Out-Of-Distribution detection on the dataset at hand. Self-Organizing Maps perform on par with a manually specified filter based on expert domain knowledge. Additionally, they show promise as a tool in the exploration and cleaning of medical datasets. As a direction for future research, we suggest a combination of Self-Organizing Maps and feature extraction based on deep learning.
Bone cement with reduced amount of monomer and low curing temperature may improve implant fixation due to reduced toxicity. We analyzed the mechanical, chemical and thermal properties of such a ...cement (Cemex Rx) using Palacos R as control. The in vivo performance of the 2 cements was also evaluated in a prospective randomized study of 47 hips, where either of the cement types was used to fixate Lubinus SP2 prostheses with the stem made of titanium alloy. Cemex Rx had a reduced tensile strength, probably because this cement was manually mixed, as recommended by the manufacturer. A standardized laboratory test showed lower curing temperature for Cemex, but measurements at 37° and with prechilled Palacos R and Cemex Rx, as in clinical work, showed no difference. In the clinical study radiostereometric measurements of cup and stem migration showed similar values in the 2 groups up to 5 years after the operation. The cement mantle was stable in both groups, but the stems migrated similarly inside the cement mantle regardless of the type of cement used. Proximal wear was low (0.04-0.05 mm/year) and tended to be lower in the Cemex group (p = 0.02). Aluminum and vanadium levels in serum increased 5 years after the operation, but no difference was noted between the 2 groups. Collagen markers (PICP, ICTP) showed similar increases in bone turnover 6 weeks and 6 months after operation in both groups.
The adoption of machine learning (ML) technology in real-world settings like medical imaging is currently hampered by a lack of trust in ML models and a lack of labeled data. These two issues are ...currently addressed in parallel by two subdisciplines of ML: uncertainty quantification (UQ) is concerned with obtaining reliable estimates of a model's confidence in its outputs, and active learning (AL) deals with efficiently training models in low-data regimes. To date, the usefulness of the new methods emerging from the field of UQ for AL remains under-explored. We here take a step to address this by comparing seven different UQ methods on three image classification data sets. Our experiments confirm previous indications in the AL literature that the ranking of sampling strategies can vary greatly across models and data sets. We find that Concrete Dropout, Least Confidence, Smallest Margin, and Entropy sampling consistently outperform Random sampling across data sets, whereas Ensembles, Monte-Carlo Dropout, and Bayes-by-Backprop do not. We also observe that AL training stability is sensitive to data quality.
This article utilizes a topology optimization approach to design planar multilayer transitions between substrate integrated waveguides (SIWs) and rectangular waveguides (RWGs). The optimization ...problem is formulated based on the modal field analyses and Maxwell's equations in the time domain solved by the finite-difference time-domain (FDTD) method. We present a time-domain boundary condition based on the Klein-Gordon equation to split traveling waves at homogeneous waveguide ports. We employ the boundary condition to compute portal quantities and to devise an adjoint-field system that enabled an efficient computation of the objective function gradient. We solve design problems that include more than 105 000 design variables by using less than 400 solutions of Maxwell's equations. Moreover, a new formulation that effectively combats the development of in-band resonances in the design is presented. The transition configuration allows the direct mount of conventional RWG sections on the circuit board and aims to cover the entire K-band. The guiding structure of the optimized transition requires blind vias, which is realized by a simple and cost-efficient technique. In addition, the transition is optimized for three different setups that can be used to provide different field polarizations. The proposed transitions show less than 1-dB insertion loss and around 15-dB return loss over the frequency interval 18-28 GHz. Several prototypes are fabricated with an excellent match between the simulation and measurement results.
An increase in adipose tissue is caused by the increased size and number of adipocytes. Lipids accumulate in intracellular stores, known as lipid droplets (LDs). Recent studies suggest that ...parameters such as LD size, shape and dynamics are closely related to the development of obesity. Berberine (BBR), a natural plant alkaloid, has been demonstrated to possess anti-obesity effects. However, it remains unknown which cellular processes are affected by this compound or how effective herbal extracts containing BBR and other alkaloids actually are. For this study, we used extracts of Coptis chinensis, Mahonia aquifolium, Berberis vulgaris and Chelidonium majus containing BBR and other alkaloids and studied various processes related to adipocyte functionality. The presence of extracts resulted in reduced adipocyte differentiation, as well as neutral lipid content and rate of lipolysis. We observed that the intracellular fatty acid exchange was reduced in different LD size fractions upon treatment with BBR and Coptis chinensis. In addition, LD motility was decreased upon incubation with BBR, Coptis chinensis and Chelidonium majus extracts. Furthermore, Chelidonium majus was identified as a potent fatty acid uptake inhibitor. This is the first study that demonstrates the selected regulatory effects of herbal extracts on adipocyte function.
Patients with chronic kidney disease (CKD) have a high risk to develop atherosclerosis. The capacity of high-density lipoproteins (HDL) or serum to accept cholesterol from macrophages and the ...capacity of macrophages to export excess cholesterol are critical for the atheroprotective role of reverse cholesterol transport. HDL cholesterol acceptor capacity was reported to be decreased in middle aged hemodialysis patients, but the role of confounding factors remains unclear.
We measured the cholesterol acceptor capacity (CAC) of HDL or serum in 12 pediatric and 17 young adult patients with CKD stages 3–5, 14 young adult hemodialysis patients and 15 adult renal transplant recipients without associated diseases and matched controls using THP-1 macrophages. Moreover we studied the cholesterol export capacity (CEC) of patients' monocyte-derived macrophages (HMDMs) to control serum or HDL.
In adults with CKD stages 3–5 serum CAC was slightly increased, whereas CEC of HMDMs was unaltered in both, adult and pediatric patients. In hemodialysis patients, however, serum CAC was markedly reduced to 85±11% of control (p<0.001), presumably due to low serum apolipoprotein A-I. Interestingly, CEC of HMDMs from dialysis patients was increased. In transplant patients no alterations were found.
CKD without hemodialysis does not reduce cholesterol export from macrophages. Hemodialysis patients might benefit from therapies aiming to restore serum CAC by increasing apolipoprotein A-I. The enhanced export of cholesterol by HMDMs from dialysis patients may represent an adaptive response.
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