Microbubble based sonoporation — from the basics into clinical implications

Sonoporation is a rapidly developing novel technique serving for drug delivery and non-viral gene therapy. It is based on the interaction between microbubbles located in the surrounding of a cell and its membrane. The interaction is obtained by excitation of microbubbles with ultrasounds. This leads to reversible cell membrane poration. Depending on the intensity of ultrasounds, structure of microbubbles used in an experiment and different environmental factors, microbubbles can interact in two manners. First, in lower ultrasound intensities, stable cavitation – regular microbubbles oscillations due to changes in the environment pressure. Microbubbles have to be very close to a cell membrane, therefore, they are usually targeted to an antigen located on the cell membrane by antibodies. Consequently, microbubbles push and pull on the cell membrane and create microstreaming around it causing its disruption. Second, inertial cavitation, where in contrary to the previous one, oscillations cause rapid collapse of microbubbles, which creates shock waves and microjets for the same purpose. No matter in which manner prorated, cells tend to reseal their disrupted cell membrane. Ca2+ ions play a crucial role in the process as well as endo exocytosis. Sonoporation has proved to be an effective modality against different diseases, including variety of cancer types in of both laboratory and clinical studies

Signaling pathways in melanoma biology and new targeted therapeutic approaches

Despite the broad prevention programs and early detection and therapy progress, melanoma of skin is still responsible for 0.6% of deaths caused by tumour disease. Every year 300,000 patients are diagnosed and 60,000 die from the most malignant of skin cancer. Generally, melanoma is formed as a result of mutation of growth pathways responsible for proliferation and apoptosis. One of the most investigated pathway, mutated in 90% of melanomas, is RAS > RAF > MEK > ERK also known as mitogen-activated protein kinase (MAPK) pathway. The second one is phosphoinositide-3-OH kinase (PI3K) pathway. The better understanding of melanoma biology resulted in research of inhibitors, which can affect presented pathways and prevent uncontrolled proliferation of melanoma. The BRAF inhibitors vemurafenib and dabrafenib and MEK inhibitor trametinib seem to be the most successful ones. Recent advances in biology of melanoma provided new interesting therapeutic targets. One of the most inquiring is microphthalmia associated transcription factor (MITF), the principal regulator of melanocyte lineage. MITF perform the role of so-called ‘survival’ or ‘addiction’ oncogene. Moreover, the interleukin-1 receptor-associated kinases (IRAKs) might clarify the connection between the inflammatory environment and melanoma carcinogenesis. IRAKs play a key role as mediators of toll-like receptor (TLR) and interleukin-1 receptor (IL1R) in inflammation signalling processes. Moreover, it was observed that metformin cause cell cycle arrest in melanoma cells, secondly leading to activation of autophagy and apoptosis. Although due to targeted and immunotherapy the prognosis of patients with metastatic melanoma is incomparably better, melanoma in its advanced stadium is still predominantly lethal. Therefore, the most present research concentrates on acquired resistance against targeted therapy

Automated correction angle calculation in high tibial osteotomy planning

Abstract High tibial osteotomy correction angle calculation is a process that is usually performed manually or in a semi-automated way. The process, according to the Miniaci method, is divided into several stages to find specific points: the center of the femoral head, the edges of the tibial plateau, the Fujisawa point, the center of the ankle joint, and the Hinge point. In this paper, we proposed an end-to-end approach that consists of different techniques for finding each point. We used YOLOv4 to detect regions of interest. To identify the center of the femoral head, we used the YOLOv4 and the Hough transform. For the other points, we used a combined method of YOLOv4 with the ASM/AAM algorithm and YOLOv4 with image processing algorithms. Our fully-automated method achieved a mean error rate of 0.5 $$^{\circ }$$ ∘ (0 $$^{\circ }$$ ∘ –2.76 $$^{\circ }$$ ∘ ) ICC 0.99 (0.98–0.99) 95% CI on our own dataset of standing long-leg Anterior Posterior view X-rays. This might be the first method that automatically calculates the correction angle of high tibial osteotomy