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Of those who underwent surgery, all patients had previously received non-surgical treatment, but 42% had undergone only one non-surgical intervention.

Non-traumatic wrist pain represents a significant burden to secondary care both in terms of new patient referrals and in terms of investigation, follow-up and treatment. Those presenting with OA are more likely to be older and male, whereas those presenting with other diagnoses are more likely to be younger and female.

Non-traumatic wrist pain represents a significant burden to secondary care both in terms of new patient referrals and in terms of investigation, follow-up and treatment. Those presenting with OA are more likely to be older and male, whereas those presenting with other diagnoses are more likely to be younger and female.Most of what we know about the coronavirus disease 2019 (COVID-19) is limited to what we know about severe acute respiratory syndrome (SARS) and COVID-19's epidemiology, fatality, and acute care. However, infection with COVID-19 may also involve the central nervous system (CNS), which may or may not be due to a multi-organ injury. Our aim in this paper is to briefly summarize the main aspects of the growing literature on neurological manifestations of the COVID-19 infection. As such, after mentioning some general background on the economic and medical implications of the pandemic on individuals, the healthcare system, and the society, we summarize some common aspects of the published literature on neurological manifestations of the COVID-19 infection. We also highlight the existing gaps in the literature, which requires additional work. learn more The most common neurological manifestation of COVID-19 infection is an olfactory deficit. However, it is still unknown if it is inflammatory or degenerative in nature. Still, the incidence of neurological complications, and also their mechanisms and treatments are unknown. This literature is predominantly composed of opinions and reviews rather than original articles, so the patients' data are not used for a majority of the studies. Multi-center studies that not only conduct chest CT or MRI but also brain CT or MRI are needed. Randomized trials are still required on the management of acute and chronic neurological conditions due to COVID-19 infection. Cohort studies may also determine the natural history of the conditions and factors that are prognostic. Furthermore, while disparities in COVID-19 infections are known, inequalities in neurological manifestations are unknown. Besides this, the efficacy of specific treatments on CNS involvement is still unknown. We will discuss the health care needs of patients with chronic neurological conditions. We Included a few recommendations for practice and further research at the end of this paper.Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for analyzing complex medical data and extracting meaningful relationships in datasets, for several clinical aims. Specifically, in the brain care domain, several innovative approaches have achieved remarkable results and open new perspectives in terms of diagnosis, planning, and outcome prediction. In this work, we present an overview of different artificial intelligent techniques used in the brain care domain, along with a review of important clinical applications. A systematic and careful literature search in major databases such as Pubmed, Scopus, and Web of Science was carried out using "artificial intelligence" and "brain" as main keywords. Further references were integrated by cross-referencing from key articles. 155 studies out of 2696 were identified, which actually made use of AI algorithms for different purposes (diagnosis, surgical treatment, intra-operative assistance, and postoperative assessment). Artificial neural networks have risen to prominent positions among the most widely used analytical tools. Classic machine learning approaches such as support vector machine and random forest are still widely used. Task-specific algorithms are designed for solving specific problems. Brain images are one of the most used data types. AI has the possibility to improve clinicians' decision-making ability in neuroscience applications. However, major issues still need to be addressed for a better practical use of AI in the brain. To this aim, it is important to both gather comprehensive data and build explainable AI algorithms.Biofabrication technologies that use light for polymerization of biomaterials have made significant progress in the quality, resolution, and generation of precise complex tissue structures. In recent years, the evolution of these technologies has been growing along with the development of new photocurable resins and photoinitiators that are biocompatible and biodegradable with bioactive properties. Such evolution has allowed the progress of a large number of tissue engineering applications. Flexibility in the design, scale, and resolution and wide applicability of technologies are strongly dependent on the understanding of the biophysics involved in the biofabrication process. In particular, understanding cell-light interactions is crucial when bioprinting using cell-laden biomaterials. Here, we summarize some theoretical mechanisms, which condition cell response during bioprinting using light based technologies. We take a brief look at the light-biomaterial interaction for a better understanding of how linear effects (refraction, reflection, absorption, emission, and scattering) and nonlinear effects (two-photon absorption) influence the biofabricated tissue structures and identify the different parameters essential for maintaining cell viability during and after bioprinting.Patient-derived xenografts (PDXs) are tools of the trade for many researchers from all disciplines and medical specialties. Most endocrinologists, and especially those working in oncology, commonly use PDXs for preclinical drug testing and development, and over the last decade large collections of PDXs have emerged across all tumor streams. In this review, we examine how the field has evolved to include PDXs as versatile resources for research discoveries, providing evidence for guidelines and changes in clinical practice.