Subsurface ablation of atherosclerotic plaque using ultrafast laser pulses

We perform subsurface ablation of atherosclerotic plaque using ultrafast pulses. Excised mouse aortas containing atherosclerotic plaque were ablated with ultrafast near-infrared (NIR) laser pulses. Optical coherence tomography (OCT) was used to observe the ablation result, while the physical damage was inspected in histological sections. We characterize the effects of incident pulse energy on surface damage, ablation hole size, and filament propagation. We find that it is possible to ablate plaque just below the surface without causing surface damage, which motivates further investigation of ultrafast ablation for subsurface atherosclerotic plaque removal

Ultrafast laser ablation for targeted atherosclerotic plaque removal

Coronary artery disease, the main cause of heart disease, develops as immune cells and lipids accumulate into plaques within the coronary arterial wall. As a plaque grows, the tissue layer (fibrous cap) separating it from the blood flow becomes thinner and increasingly susceptible to rupturing and causing a potentially lethal thrombosis. The stabilization and/or treatment of atherosclerotic plaque is required to prevent rupturing and remains an unsolved medical problem. Here we show for the first time targeted, subsurface ablation of atherosclerotic plaque using ultrafast laser pulses. Excised atherosclerotic mouse aortas were ablated with ultrafast near-infrared (NIR) laser pulses. The physical damage was characterized with histological sections of the ablated atherosclerotic arteries from six different mice. The ultrafast ablation system was integrated with optical coherence tomography (OCT) imaging for plaque-specific targeting and monitoring of the resulting ablation volume. We find that ultrafast ablation of plaque just below the surface is possible without causing damage to the fibrous cap, which indicates the potential use of ultrafast ablation for subsurface atherosclerotic plaque removal. We further demonstrate ex vivo subsurface ablation of a plaque volume through a catheter device with the high-energy ultrafast pulse delivered via hollow-core photonic crystal fiber

COVID-19-related consultation-liaison (CL) mental health services in general hospitals: A perspective from Europe and beyond

Objective: The COVID-19 pandemic posed new challenges for integrated health care worldwide. Our study aimed to describe newly implemented structures and procedures of psychosocial consultation and liaison (CL) services in Europe and beyond, and to highlight emerging needs for co-operation. Methods: Cross-sectional online survey from June to October 2021, using a self-developed 25-item questionnaire in four language versions (English, French, Italian, German). Dissemination was via national professional societies, working groups, and heads of CL services. Results: Of the participating 259 CL services from Europe, Iran, and parts of Canada, 222 reported COVID-19 related psychosocial care (COVID-psyCare) in their hospital. Among these, 86.5% indicated that specific COVID-psyCare co-operation structures had been established. 50.8% provided specific COVID-psyCare for patients, 38.2% for relatives, and 77.0% for staff. Over half of the time resources were invested for patients. About a quarter of the time was used for staff, and these interventions, typically associated with the liaison function of CL services, were reported as most useful. Concerning emerging needs, 58.1% of the CL services providing COVID-psyCare expressed wishes for mutual information exchange and support, and 64.0% suggested specific changes or improvements that they considered essential for the future. Conclusion: Over 80% of participating CL services established specific structures to provide COVID-psyCare for patients, their relatives, or staff. Mostly, resources were committed to patient care and specific interventions were largely implemented for staff support. Future development of COVID-psyCare warrants intensified intra- and inter-institutional exchange and co-operation

Effects of Challenging Weather and Illumination on Learning-Based License Plate Detection in Noncontrolled Environments

License Plate Detection (LPD) is one of the most important steps of an Automatic License Plate Recognition (ALPR) system because it is the seed of the entire recognition process. In indoor controlled environments, there are many effective methods for detecting license plates. However, outdoors LPD is still a challenge due to the large number of factors that may affect the process and the results obtained. It is an evidence that a complete training set of images including as many as possible license plates angles and sizes improves the performance of every classifier. On this line of work, numerous training sets contain images taken under different weather conditions. However, no studies tested the differences in the effectiveness of different descriptors for these different conditions. In this paper, various classifiers were trained with features extracted from a set of rainfall images using different kinds of texture-based descriptors. The accuracy of these specific trained classifiers over a test set of rainfall images was compared with the accuracy of the same descriptor-classifier pair trained with features extracted from an ideal conditions images set. In the same way, we repeat the experiment with images affected by challenging illumination. The research concludes, on one hand, that including images affected by rain, snow, or fog in the training sets does not improve the accuracy of the classifier detecting license plates over images affected by these weather conditions. Classifiers trained with ideal conditions images improve the accuracy of license plate detection in images affected by rainfalls up to 19% depending on the kind of extracted features. However, on the other hand, results evidence that including images affected by low illumination regardless of the kind of the selected feature increases the accuracy of the classifier up to 29%

Real-Time Operating Hand Detection for the Optimization of Mobile Web Interfaces

IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS (14th. 2017. Orlando