Hyperspectral imaging (HSI) is a novel optical imaging modality, which has recently found diverse applications in the medical field. HSI is a hybrid imaging modality, combining a digital photographic camera with a spectrographic unit, and it allows for a contactless and non-destructive biochemical analysis of living tissue. HSI provides quantitative and qualitative information of the tissue composition at molecular level in a contrast-free manner, hence making it possible to objectively discriminate between different tissue types and between healthy and pathological tissue. Over the last two decades, HSI has been increasingly used in the medical field, and only recently it has found an application in the operating room. In the last few years, several research groups have used this imaging modality as an intraoperative guidance tool within different surgical disciplines. Despite its great potential, HSI still remains far from being routinely used in the daily surgical practice, since it is still largely unknown to most of the surgical community. The aim of this study is to provide clinical surgeons with an overview of the capabilities, current limitations, and future directions of HSI for intraoperative guidance.

Redox regulation has recently been proposed as a critical intracellular mechanism affecting cell survival, proliferation, and differentiation. Redox homeostasis has also been implicated in a variety of degenerative neurological disorders such as Parkinson's and Alzheimer's disease. In fact, it is hypothesized that markers of oxidative stress precede pathologic lesions in Alzheimer's disease and other neurodegenerative diseases. Several therapeutic approaches have been suggested so far to improve the endogenous defense against oxidative stress and its harmful effects. Among such approaches, the use of artificial antioxidant systems has gained increased popularity as an effective strategy. Nanoscale drug delivery systems loaded with enzymes, bioinspired catalytic nanoparticles and other nanomaterials have emerged as promising candidates. The development of degradable hydrogels scaffolds with antioxidant effects could also enable scientists to positively influence cell fate. This current review summarizes nanobiomaterial‐based approaches for redox regulation and their potential applications as central nervous system neurodegenerative disease treatments.

The interplay between mechanical stimuli and cellular mechanobiology orchestrates the physiology of tissues and organs in a dynamic balance characterized by constant remodelling and adaptative processes. Environmental mechanical properties can be interpreted as a complex set of information and instructions that cells read continuously, and to which they respond. In cirrhosis, chronic inflammation and injury drive liver cells dysfunction, leading to excessive extracellular matrix deposition, sinusoidal pseudocapillarization, vascular occlusion and parenchymal extinction. These pathological events result in marked remodelling of the liver microarchitecture, which is cause and result of abnormal environmental mechanical forces, triggering and sustaining the long-standing and progressive process of liver fibrosis. Multiple mechanical forces such as strain, shear stress, and hydrostatic pressure can converge at different stages of the disease until reaching a point of no return where the fibrosis is considered non-reversible. Thereafter, reciprocal communication between cells and their niches becomes the driving force for disease progression. Accumulating evidence supports the idea that, rather than being a passive consequence of fibrosis and portal hypertension (PH), mechanical force-mediated pathways could themselves represent strategic targets for novel therapeutic approaches. In this manuscript, we aim to provide a comprehensive review of the mechanobiology of PH, by furnishing an introduction on the most important mechanisms, integrating these concepts into a discussion on the pathogenesis of PH, and exploring potential therapeutic strategies.

Nerves are critical structures that may be difficult to recognize during surgery. Inadvertent nerve injuries can have catastrophic consequences for the patient and lead to life-long pain and a reduced quality of life. Hyperspectral imaging (HSI) is a non-invasive technique combining photography with spectroscopy, allowing non-invasive intraoperative biological tissue property quantification. We show, for the first time, that HSI combined with deep learning allows nerves and other tissue types to be automatically recognized in in vivo hyperspectral images. An animal model was used, and eight anesthetized pigs underwent neck midline incisions, exposing several structures (nerve, artery, vein, muscle, fat, skin). State-of-the-art machine learning models were trained to recognize these tissue types in HSI data. The best model was a convolutional neural network (CNN), achieving an overall average sensitivity of 0.91 and a specificity of 1.0, validated with leave-one-patient-out cross-validation. For the nerve, the CNN achieved an average sensitivity of 0.76 and a specificity of 0.99. In conclusion, HSI combined with a CNN model is suitable for in vivo nerve recognition.