The inferior mesenteric artery (IMA) is the blood supply vessel in the left colorectal cancer (CRC) and is the focus for clinicians during the operation of the left-sided CRC. Different IMA treatment methods will affect the blood supply of the anastomotic bowel after the operation, thus affecting the prognosis. Nevertheless, the individual anatomical variation rate of IMA is great. It is the crucial to perform precise high/low ligation and standardized lymph node dissection according to the anatomical characteristics of IMA in laparoscopic radical resection of left-sided CRC. In the present study, we reviewed the effects of IMA length, classification, the relationship with adjacent vessels and ureter, and different IMA treatments on the prognosis of patients.

Three-dimensional (3D) printed porous titanium alloy has good mechanical and physical properties and chemical stability. It is widely used in the field of additive manufacturing to realize the personalized customization of complex structures, such as industry, military, aerospace, and medicine, especially in the customization of personalized orthopedic implants and the repair and reconstruction of bone defects. However, due to the biological inertia of titanium alloy, the cell adhesion of the untreated metal surface is poor. Therefore, surface modification to enhance the biocompatibility and promote bone activity and antibacterial activity of 3D printed porous titanium alloy has become a research hotspot. In this article, the surface modification technology of 3D printing porous titanium alloys is reviewed from four aspects: physical modification, chemical modification, biochemical modification, and metal ion coating.

Considering the extensive use of mobile devices by medical teachers, undergraduate students, postgraduate residents, and patients, it becomes an indispensable need to deploy mobile technologies in various areas of the health professions education, medical training, and patient care. The purpose of the current review is to explore the scope and utility of mobile technology in ensuring the effective delivery of medical education and clinical teaching. An extensive search of all materials related to the topic was carried out in the PubMed search engine and a total of 15 articles were selected based on their suitability with the current review objectives and analyzed. The use of mobile technologies creates a gamut of educational experiences and learning opportunities for medical students and thereby enhances the efficiency and effectiveness of the learning process. The adoption of mobile technology in medical training is more of a student-centered approach and ensures active engagement of the students with an ultimate goal to become a competent health-care professional. In conclusion, in the best interest of the medical students, it is high time to employ mobile-based applications and technologies in the period of medical training as it is expected to play an important role in the accomplishment of learning outcomes and patient care.

On March 12, 2020, with more than 20,000 confirmed cases and almost 1000 deaths in the European Region, the World Health Organization classified the COVID-19 outbreak as a pandemic. As of August 15, 2020, there are 21.5 million confirmed cases of COVID-19 and over 766,000 deaths from the virus, worldwide. Most governments have imposed quarantine measures of varied degrees of strictness on their populations in attempts to stall the spread of the infection in their communities. However, the isolation may have inflicted long-term psychological injury to the general population and, in particular, to at-risk groups such as the elderly, the mentally ill, children, and frontline healthcare staff. In this article, we offer the most up-to-date review of the effects of COVID-19 confinement on all the disorders listed in the Diagnostic and Statistical Manual of Mental Disorders. We make data-driven predictions of the impact of COVID-19 confinement on mental health outcomes and discuss the potential role of telemedicine and virtual reality in mental health screening, diagnosis, treatment, and monitoring, thus improving the above outcomes in such a difficult time.

Rheumatoid arthritis (RA) is an autoimmune systemic disease of unknown etiology, characterized by chronic inflammation and synovial infiltration of immune cells. Pain is one of the most dominant symptoms for patients with RA, which affects the health and quality of life. Animal models are helpful to study the pathogenesis of RA and related factors and mechanisms of RA-induced pain, which may aid in the development of new and better treatment strategies. Several animal models of RA have been validated to predict for efficacy in humans that include collagen type II-induced arthritis in rats and mice, adjuvant-induced arthritis in rats, and antigen induced arthritis in several species. However, the quantitative evaluation of pain in animal models is technically challenging. Until recent years, behavior methods are used to characterize acute and chronic pain stages by observing behavioral changes in preclinical arthritis models. Significant progress has been made in pain assessment with the development of nonreflexive tools, dynamic weight-bearing (DWB) apparatus was developed for the measurement of pain in rodents by capturing weight-bearing and surface distribution of the paws. In this article, we summarize several classical animal models of rheumatoid pain as well as discussion of the advantages and disadvantages of DWB test for spontaneous pain used in these models.

Epidemic outbreaks and biological disasters pose serious challenges to the country due to enormous population and weak public health system; to combat the same, we need epidemic preparedness. The steps of epidemic preparedness embrace and incorporate to anticipate, prevent, prepare, detect, and respond. The four stages of the present epidemic COVID-19 have been described. The requirement of proper coordination among the epidemiologist, clinician, laboratory personnel, and health educator is sum and substance of it. Levels for epidemic preparedness inculcate preparation at four levels including central, state, local, and health facility. The impact of epidemic has adverse health, social, as well as economic implications.

Precision medicine is based on the premise that genomic analysis radically changes the nature and scope of therapeutic medicine. While genome sequencing has revolutionized the study of human disease, to date progress in translating genomic knowledge into treatments for inherited disorders has been less apparent. However, increasing attention on the relationship(s) between rare diseases (RDs) and precision medicine should significantly accelerate this process, as evidenced by the increasing numbers of molecular therapies receiving approval from the U.S. Food and Drug Administration. There are an estimated 7000 RDs, a majority of which affect <1/million people; but, collectively, it has been calculated that in high-income countries ≥1/17 persons have a RD. RDs represent both a significant health challenge and a major economic burden for many affected individuals and their families, and although many are life-threatening, they often remain undiagnosed or misdiagnosed. Unfortunately, global progress in resolving these issues has been hindered by basic problems such as differing national and regional definitions, from a RD prevalence of 1 to 5/10,000 affected persons in Europe and Australia to 1/500,000 in China. There also has been failure to recognize that many RDs originated as founder mutations and are community-specific, an especially important consideration in populations where community endogamy is the rule and close-kin marriage is traditional. The near-global transition from a communicable to a predominantly noncommunicable disease profile has, however, served to highlight the importance of genetics in medicine, and resulted in a rapidly growing focus on RDs. Against this background, collaborative international programs to facilitate the prevention and curative treatment of RDs merit urgent adoption and support.

Biomechanical models of blood flows in the last century were devoted to the handling of flow pattern in simple models more or less representative of rigid and deformable segments of the vasculature with bends and branchings, in normal and pathological conditions. With the development of medical three-dimensional (3D) imaging techniques, availability of 3D reconstruction software, improved fluid–structure interaction methods, and high-performance computing, computational models of blood flows are now aimed at guiding medical decision in the framework of precision medicine. However, most often, input data remain unavailable for a given patient, especially those related to blood and vascular wall rheology. This review summarizes the main blood flow features and yields the state-of-the-art.

Many elderly people prefer to live at home independently. They and their relatives face challenges with respect to physical and mental health care in this environment. In addition, the traditional model of hospital-based centralized healthcare is now under stress due to the ageing population worldwide, especially in countries, such as Japan, China and Europe. Robots are now being used extensively for many different applications in business (e.g., materials handling) and homes (e.g., floor cleaning). On the other hand, researchers all over the world have been investigating the use of robots (e.g., PARO the therapeutic baby seal robot) to provide emotional support and well-being for the elderly. The EU project VictoryaHome was designed to trial telepresence robots for the care, safety and emotional well-being of the elderly across four countries in Europe and Australia. This paper examines the potential of integrated care of the elderly in their own homes and is based on the findings of the VictoryaHome project.

This work presents our vision and work-in-progress on a new platform for immersive virtual and augmented reality (AR) training. ImmersiMed is aimed at medical educational and professional institutions for educating nurses, doctors, and other medical personnel. ImmersiMed is created with multi-platform support and extensibility in mind. By creating consistent experiences across different platforms and applications, ImmersiMed intends to increase simulation availability. Furthermore, it is expected to improve the quality of training and prepare students better for more advanced tasks and boost confidence in their abilities. Tools for educators are being provided so new scenarios can be added without the intervention of costly content creators or programmers. This article addresses how Immersive's mixed platform approach can ease the transition from basic school training to real-world applications by starting from a virtual reality simulation and gradually let the student move on to guided AR in the real world. By explaining the idea of a single development platform for multiple applications using different technologies and by providing tools for educators to create their own scenarios, ImmersiMed will improve training quality and availability at a low training and simulation costs.

Automatic processing large amount of microscopic images is important for medical and biological studies. Deep learning has demonstrated better performance than traditional machine learning methods for processing massive quantities of images; therefore, it has attracted increasing attention from the research and industry fields. This paper summarizes the latest progress of deep learning methods in biological microscopic image processing, including image classification, object detection, and image segmentation. Compared to the traditional machine learning methods, deep neural networks achieved better accuracy without tedious feature selection procedure. Obstacles of the biological image analysis with deep learning methods include limited training set and imperfect image quality. Viable solutions to these obstacles are discussed at the end of the paper. With this survey, we hope to provide a reference for the researchers conducting biological microscopic image processing.

For decision support, a globally connected digital information system is desirable, which uses diagnostic findings and makes language independently statistical (anonymized) information from similar cases of all countries available. It can be realized efficiently in the following way: The definitions of all used diagnostics and measurement procedures are placed online. The defined data are called “Domain Vectors.” Doctors who use the online definitions get measurement results as Domain Vectors in comparable and searchable form. Anonymized selective statistics over patient groups with similar data can help to find the best treatment. Precondition for such distributed and simultaneously connected Domain Vectors are their global online definitions. Every Domain Vector only consists of a link to its definition (e.g., via URL or an abbreviated equivalent) plus numbers. This article explains details and concludes that introduction of the Domain Vectors with their online definitions would be an important step toward internationally connected medicine.

Rapid developments in sensing and imaging technologies are transforming our ability to detect, diagnose, and manage disease. Given financial pressures on managed health care, there is increasing emphasis on disease prevention and wellness programs have become a feature of many plans. Recent market developments include the merger of pharmacy and health-care organizations, which promises to open new avenues in health maintenance and diagnosis. Herein, we review recent developments in the field and present a vision for how point-of-care providers can play a pivotal role in prodromal diagnostics and wellness programs. Emphasis is placed on recent advances in digital detection technologies which have the potential to accelerate evolution of such models. An additional potential benefit of large-scale community-based screening centers lies in the identification of patients for recruitment into clinical trials, and mechanisms are proposed.