Objective: Biomedical data processing generally requires the secure stepwise transfer of sensitive personal information across multiple parties. Mediating such operations using distributed secure digital ledgers, i.e., blockchains, is investigated in this article. Materials and Methods: The bitmark property rights blockchain was used to simulate the process of assessing individuals for enrollment to specific clinical trials. In the scenario presented, a sponsor publishes a recruitment call for a clinical trial and patients signal their willingness to participate in the trial through blockchain transactions. The blockchain creates and maintains digital references of the medical data assets of prospective study participants as well as digital property certificates for assigning access rights to corresponding medical data assets. Trial matching services review the patient blockchain records and recommend study participants that are likely to meet the enrollment criteria of recruiting clinical trials. Digital certificates assign transient access rights to the data assets of the prospective study participants. These certificates are transferred to pertinent matching services and sponsors, allowing these organizations to examine the candidacy of each prospective study participant. Results: The trial matching simulation demonstrates that property rights blockchains can implement complicated multiparty interactions, such as those associated with medical data exchange, without supplemental peer-to-peer communications. Conclusions: Blockchain-based data marketplaces of the type described, when coupled with data-controlled virtual infrastructure environments (i.e., Medical Data Trusts), provide a viable model for managing the transfer, provenance, and processing of individual health information.

Background: A magnetic resonance image (MRI)-guided robotic system dedicated for prostate cancer (PC) was produced that carries a small spherically focused, single-element, ultrasonic transducer which can be potentially utilized endorectally. Materials and Methods: The developed robotic device utilizes four computer-controlled axes. An agar-based phantom was developed, which included a cavity that mimics the rectum geometry. Experiments with the system were performed in a 1.5T MRI system using the gel phantom. The transducer has a diameter of 18 mm, operates with 3 MHz, and focuses energy at 40 mm. Results: The functionality of the robot was assessed by means of magnetic resonance thermometry, demonstrating sufficient heating in both axes of operation (linear and angular). Conclusions: A functional MRI-guided robotic system was produced, which can create significant and controlled thermal exposures. The intention is to use the proposed device endorectally in the future for the focal treatment of PC.

Background: In this article, a medical robotic system that performs magnetic resonance imaging-guided focused ultrasound surgery ablation is presented. The main innovation of this robotic system is that all the actuators are placed outside the water container. The transducer is immersed in water through an arm which is attached to the angular stage. Materials and Methods: The system includes three linear and one angular stage. The device uses piezoelectric motors for each motion stage. The accuracy was achieved with optical encoders. A focused transducer operated at 1 MHz with a radius of curvature of 10 cm and a diameter of 4 cm was used. A polyacrylamide gel was used to assess the ultrasound protocol. Results: The system was tested in the magnetic resonance imaging (MRI) environment and was proved to be a magnetic resonance compatible. The accuracy of the system was tested, and it was found that spatial steps of 0.2 mm can be safely and reliably achieved. With this robotic system, it is possible to access many organs that ultrasound penetrates with the patient placed in a prone position. Conclusion: The proposed robotic system can be modified so that it can be used for other applications. One example of an alternative application is MRI-guided biopsy. Another application is to replace the transducer arm with a radio frequency (RF) device to perform MRI guided RF ablation. Finally, the maneuverability of the robotic system can be enhanced further by attaching another angular stage to the system.

The coronavirus disease 2019 (COVID-19) outbreak has transformed into a global public health emergency and a pandemic, which has demonstrated very high risk of global transmission. The business and commerce sector have been advised to come forward by the government primarily because these businesses have a crucial role in interrupting the chain of transmission and thus reduce the likelihood of community transmission. Any interventions on their part will not only minimize the current risk of acquiring the infection by the employees, but will also play a significant part in reducing the impact on the business itself and the national economy as a whole. Simultaneously, the business sector should be totally dedicated towards the formulation of an emergency response plan in their workplace. In conclusion, the ongoing COVID-19 pandemic is a global health and community-level emergency and it cannot be effectively contained without the persistent support of all the stakeholders, including the business sector. The need of the hour is that the business sector should plan and implement aggressive and evidence-based actions to safeguard the lives of their employees, customers and the community at large.

The role of oxygen therapy in the management of coronavirus disease 2019 (COVID-19) cases is extremely crucial and all steps should be taken to ensure its availability in adequate amount in all the health care establishments treating the patients. The clinical data obtained from China revealed that out of the overall reported cases, 15% severe cases and 5% critically ill patients will require oxygen therapy. Moreover, it is essential to estimate the requirement of oxygen in the hospital and it can be done by using the essential supply forecast tool. In conclusion, in order to improve the treatment outcomes of COVID-19 patients, it is crucial to ensure the supply of high quality medical-grade oxygen to the severe and critically-ill group of patients. In addition, the hospitals should prepare for improving the oxygen surge capacity to meet the needs of sudden rise in the number of cases.

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.

For accurate digital representation of original (e.g. medical) information we have to recall that any information is selection from a common set of possibilities. This one dimensional or multidimensional set is called “domain”. Letters and language vocabulary are only special examples of domains which lead to non-reproducible digital representation. Since introduction of the internet, however, it is technically feasible to define domains online. These “adapted domains” can be optimized in dependence of the application (e.g. medical diagnosis). Then all relevant features of the original information in this application can be represented and transported digitally by comparable and searchable “Domain Vectors” (DVs). This would be important e.g. for medical decision support, therefore the introduction of Domain Vectors is urgently recommended. The setup of a comfortable internet presence for definition of adapted domains (and Domain Vectors) would be a first step for this.

Background and Objectives: Precision medicine and drug repurposing provide an opportunity to ameliorate the challenges of declining pharmaceutical R&D productivity, rising costs of new drugs, and poor patient response rates to existing medications. Multifactorial “disease signatures” provide unique insights into the architecture of complex disease populations that can be used to better stratify patient groups, aiding the delivery of precision medicine. Methods: Analysis of a complex disease (breast cancer) population was undertaken to identify the combinations of single-nucleotide polymorphisms that are associated with different disease subgroups. Target genes associated with the disease risk of these subgroups were examined, followed by identification and evaluation of existing active chemical leads as drug repurposing candidates. Results: One hundred and seventy-five disease-associated gene targets relevant to different subpopulations of breast cancer patients were identified. Twenty-three of these genes were prioritized as both promising novel drug targets and repurposing candidates. Two targets, P4HA2 and TGM2, have high repurposing potential and a strong mechanistic link to breast cancer. Conclusions: This study showed that detailed analysis of combinatorial genomic (and other) features can be used to accurately stratify patient populations and identify highly plausible drug repurposing candidates systematically across all disease-associated targets.

Background: A decline in physical activity (PA) during pregnancy, despite its benefits to the mother and fetus, invites concerns for innovative platforms for its implementation. This cross-sectional study assessed knowledge, attitude, and “willingness to use” and “willingness to pay” for smartphone applications (apps) for PA. Materials and Methods: A total of 196 consenting pregnant women participated in this study. Eligible respondents were pregnant women who were 18 years and older, on at least a second antenatal visit and uses a mobile phone. Three purposively selected antenatal care facilities were surveyed. A self-developed questionnaire pilot tested for face and content validity was used as the research tool. Results: The mean age of the respondents was 27.5 ± 3.42 years, and 52% of them were occasionally engaged in PA. The point prevalence for smartphone use for general purpose and the usability rate of smartphone app were 72.4% and 84.2%, respectively. The rates for willingness to use PA apps for pregnancy and willingness to pay for the apps were 64.3% and 63.8%, respectively. There was a significant association between the attitude of respondents toward smartphone apps use for PA and number of parity (χ² = 7.119; P = 0.028). There was no significant association between knowledge of the use of smartphone apps for PA in pregnancy and each of the educational qualification (χ² = 13.046; P = 0.523), income (χ² = 11.086; P = 0.679), age (χ² = 4.552; P = 0.804), gravidity status (χ² = 5.302; P = 0.506), and number of parity (χ² = 1.878; P = 0.758). Conclusion: Nigerian pregnant women have good knowledge, positive attitude, and willingness to use smartphone apps for PA in pregnancy. There was a significant association between the number of parity and each of the attitude and knowledge of the use of smartphone apps for PA.

Background and Objectives: Nonintrusive heart rate (HR) monitoring can be a useful tool for health monitoring. By creating capacitively coupled textile electrodes, a comfortable monitoring system can be integrated into seating or bedding that can monitor HR through clothing. This work empirically studied two factors for a system of this type: the electrode size and the material worn by the subject. Materials and Methods: HR measurements were taken using six different sizes of the rectangular textile electrode with four subjects and the signal-to-noise ratio (SNR) of the signals were analyzed. A further set of experiments were conducted with a single subject and a fixed electrode size where different materials were worn. Results: Electrode size was seen to have a statistically insignificant effect on the collected signal quality. The SNR was also largely unaffected by the worn material type. Conclusion: This study provided empirical data relating to two important factors for nonintrusive, textile, and HR monitoring systems. This data will be helpful for designing a seat-based HR monitoring system or to understand the operational limitations of a system of this type.

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.

This commentary reflects on the launch of the new, state-of-the-art, mixed-ownership Guiqian International General Hospital in Guiyang and explores its potential as a template for digitally enabled hospitals of the future and economic development hubs.