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The use of microcatheters as a coronary interventional tool for a therapeutic approach to complex coronary interventions like bifurcation lesions, ostial location, tortuous anatomy, angled takeoffs, coronary calcification, and chronic total occlusion (CTO) percutaneous coronary intervention (PCI) is growing among cardiologists across the country. During the treatment of such complex lesions, microcatheters play an essential part of the tool kit with both single-lumen and double-lumen microcatheters (DLMs) having their specific niche areas. The selection of microcatheters involves a detailed understanding of the microcatheter specification, lesion anatomy, lesion location, vessel tortuosity and trajectory, and crossing techniques. The selection of appropriate crossing techniques with different microcatheters increases success rates of PCI, reduces procedural time and contrast use, and lowers the radiation. However, the use of microcatheters and their technicalities have not yet fully realized by many operators and their true scope has not been fully explored. This article discusses and summarizes the thoughts and key opinions of experts in this field.

With the continued development of nanomaterials over the past two decades, specialized photonanomedicines (light-activable nanomedicines, PNMs) have evolved to become excitable by alternative energy sources that typically penetrate tissue deeper than visible light. These sources include electromagnetic radiation lying outside the visible near-infrared spectrum, high energy particles, and acoustic waves, amongst others. Various direct activation mechanisms have leveraged unique facets of specialized nanomaterials, such as upconversion, scintillation, and radiosensitization, as well as several others, in order to activate PNMs. Other indirect activation mechanisms have leveraged the effect of the interaction of deeply penetrating energy sources with tissue in order to activate proximal PNMs. These indirect mechanisms include sonoluminescence and Cerenkov radiation. Such direct and indirect deep-tissue activation has been explored extensively in the preclinical setting to facilitate deep-tissue anticancer photodynamic therapy (PDT); however, clinical translation of these approaches is yet to be explored. This review provides a summary of the state of the art in deep-tissue excitation of PNMs and explores the translatability of such excitation mechanisms towards their clinical adoption. A special emphasis is placed on how current clinical instrumentation can be repurposed to achieve deep-tissue PDT with the mechanisms discussed in this review, thereby further expediting the translation of these highly promising strategies.

The present paper reports a cascaded collision lattice Boltzmann model for the simulation of an incompressible two-dimensional fluid flow in a porous media regime. The cascaded model is first validated for the nonporous regime using limiting conditions against previous finite element model reports. Subsequently, the cascaded collision model is applied to the lid-driven porous-filled cavity to demonstrate the largely augmented numerical stability of the model against the more common Bhatnagar–Gross–Krook and multiple relaxation time collision models. Finally, the cascaded model is applied to an inflow–outflow case of flow and heat transfer over a porous bluff body to showcase its efficiency in capturing the complex fluid and heat transport phenomenon through porous media.

Additional file 1: Table S1. School nurse versus athletic trainer symptom reporting for 300 student-athlete concussions documented in the 2015–2018 school years

The emergence of biomimetic nanotechnology has seen an exponential rise over the past decade with applications in regenerative medicine, immunotherapy and drug delivery. In the context of nanomedicines activated by near infrared (NIR) photodynamic processes (photonanomedicines; PNMs), biomimetic nanotechnology is pushing the boundaries of activatable tumor targeted nanoscale drug delivery systems. This review discusses how, by harnessing a unique collective of biological processes critical to targeting of solid tumors, biomimetic PNMs (bPNMs) can impart tumor cell specific and tumor selective photodynamic therapy-based combination regimens. Through molecular immune evasion and self-recognition, bPNMs can confer both tumor selectivity (preferential bulk tumor accumulation) and tumor specificity (discrete molecular affinity for cancer cells), respectively. They do so in a manner that is akin, yet arguably superior, to synthetic molecular-targeted PNMs. A particular emphasis is made on how bPNMs can be engineered to circumvent tumor cell heterogeneity, which is considered the Achilles’ heel of molecular targeted therapeutics. Forward-looking propositions are also presented on how patient tumor heterogeneity can ultimately be recapitulated to fabricate patient-specific, heterogeneity-targeting bPNMs.

The presented here paper describes a new approach to the video compression problem. Our method uses the neural network image compression algorithm which is based on the predictive vector quantization (PVQ). In this method of image compression two different neural network structures are exploited in the following elements of the proposed system: a competitive neural networks quantizer and a neuronal predictor. For the image compression based on this approach it is important to correctly detect scene changes in order to improve performance of the algorithm. We describe the image correlation method and discuss its effectiveness.

Image transformation is one of the important digital image processing techniques widely used in medical science. Typical applications of image transformation include creation of three dimensional volumetric models from two dimensional images. The two dimension images may be obtained energy source used for hard tissue imaging are x-rays. The three dimension models of hard tissue are created by traditional tomography using CT scans. Since scanners are very expensive they are not easily available at most of health care centers. The algorithm presented in the paper is based on two dimensional image data of hard tissues obtained from basic x-rays equipments. It is unique in context of data gathering collected via arbitrary path to impart maximum flexibility for three dimensional models compared to some other approaches. A series of experiments performed with various data sets validates claim MATLAB® platform is used for implementation.

Summary The authors present an unusual case of chest pain in an 84-year-old Caucasian woman.