Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been garnered increasing for its rapid worldwide spread. Each country had implemented city-wide lockdowns and immigration regulations to prevent the spread of the infection, resulting in severe economic consequences. Materials and technologies that monitor environmental conditions and wirelessly communicate such information to people are thus gaining considerable attention as a countermeasure. This study investigated the dynamic characteristics of batteryless magnetostrictive alloys for energy harvesting to detect human coronavirus 229E (HCoV-229E). Light and thin magnetostrictive Fe-Co/Ni clad plate with rectification, direct current (DC) voltage storage capacitor, and wireless information transmission circuits were developed for this purpose. The power consumption was reduced by improving the energy storage circuit, and the magnetostrictive clad plate under bending vibration stored a DC voltage of 1.9 V and wirelessly transmitted a signal to a personal computer once every 5 min and 10 s under bias magnetic fields of 0 and 10 mT, respectively. Then, on the clad plate surface, a novel CD13 biorecognition layer was immobilized using a self-assembled monolayer of -COOH groups, thus forming an amide bond with -NH2 groups for the detection of HCoV-229E. A bending vibration test demonstrated the resonance frequency changes because of HCoV-229E binding. The fluorescence signal demonstrated that HCoV-229E could be successfully detected. Thus, because HCoV-229E changed the dynamic characteristics of this plate, the CD13-modified magnetostrictive clad plate could detect HCoV-229E from the interval of wireless communication time. Therefore, a monitoring system that transmits/detects the presence of human coronavirus without batteries will be realized soon.

In recent years, open-source 3D printing technologies have become increasingly applied to biological research. We have created a fully open-source, versatile and low cost XYZ positioning system using 3D printer components. As this system is controlled by a Python3 based operating system running on a Raspberry Pi 3 Model B, its behaviour can be adapted to meet multiple needs in neurophysiology. We have developed two main applications of this system. First, we have created an automated microscopy script that links seamlessly with image stitching plugins in ImageJ (Fiji) allowing the user to create high resolution montages. Second, we have created a series of movement scripts allowing the application of graded rates of stretch to muscle spindles. Here we outline the construction and implementation of this system and discuss how we have utilised this tool in our research.

Recent infectious disease outbreaks, such as COVID-19 and Ebola, have highlighted the need for rapid and accurate diagnosis to initiate treatment and curb transmission. Successful diagnostic strategies critically depend on the efficiency of biological sampling and timely analysis. However, current diagnostic techniques are invasive/intrusive and present a severe bottleneck by requiring specialist equipment and trained personnel. Moreover, centralised test facilities are poorly accessible and the requirement to travel may increase disease transmission. Self-administrable, point-of-care (PoC) microneedle diagnostic devices could provide a viable solution to these problems. These miniature needle arrays can detect biomarkers in/from the skin in a minimally invasive manner to provide (near-) real-time diagnosis. Few microneedle devices have been developed specifically for infectious disease diagnosis, though similar technologies are well established in other fields and generally adaptable for infectious disease diagnosis. These include microneedles for biofluid extraction, microneedle sensors and analyte-capturing microneedles, or combinations thereof. Analyte sampling/detection from both blood and dermal interstitial fluid is possible. These technologies are in their early stages of development for infectious disease diagnostics, and there is a vast scope for further development. In this review, we discuss the utility and future outlook of these microneedle technologies in infectious disease diagnosis.

With the development of the ultra high voltage transmission technology, the voltage level of transmission line rised. Accordingly, the strength of electric field in the vicinity of transmission line increased, thus possible health effects from electric field have caused many public attentions. In this study, in order to compare effects induced by static electric field (SEF) and power frequency electric field (PFEF) on immune function, Institute of Cancer Research (ICR) mice were exposed to 35 kV/m SEF (0 Hz) and PFEF (50 Hz),respectively. Several indicators of white blood cell, red blood cell as well as hemoglobin in peripheral blood were tested after exposure of 7, 14 and 21 days, respectively. There was no significant difference in any indicators under SEF exposure of 35 kV/m for 7d, 14d and 21d between experimental group and control group. Under the PFEF exposure of 35 kV/m, white blood cell count significantly reduced after exposure of 7d, 14d and 21d. Meanwhile, red blood cell count significantly reduced after exposure of 7d, and returned to normal level through the compensatory response of organism after exposure of 14d and 21d. Hemoglobin concentration significantly decreased only after exposure of 21d. Based on tested results of hematological indicators, SEF exposure of 35 kV/m did not affect immune functions in mice but PFEF exposure of 35 kV/m could cause a decline of immune function. This difference of effects from SEF and PFEF on immune function was possibly caused by the difference of the degree of molecular polarization and ion migration in organism under exposure of two kinds of electric fields.

In many cerebral grey matter structures including the neocortex, spreading depolarization (SD) is the principal mechanism of the near-complete breakdown of the transcellular ion gradients with abrupt water influx into neurons. Accordingly, SDs are abundantly recorded in patients with traumatic brain injury, spontaneous intracerebral hemorrhage, aneurysmal subarachnoid hemorrhage (aSAH) and malignant hemispheric stroke using subdural electrode strips. SD is observed as a large slow potential change, spreading in the cortex at velocities between 2 and 9 mm/min. Velocity and SD susceptibility typically correlate positively in various animal models. In patients monitored in neurocritical care, the Co-Operative Studies on Brain Injury Depolarizations (COSBID) recommends several variables to quantify SD occurrence and susceptibility, although accurate measures of SD velocity have not been possible. Therefore, we developed an algorithm to estimate SD velocities based on reconstructing SD trajectories of the wave-front\'s curvature center from magnetic resonance imaging scans and time-of-SD-arrival-differences between subdural electrode pairs. We then correlated variables indicating SD susceptibility with algorithm-estimated SD velocities in twelve aSAH patients. Highly significant correlations supported the algorithm\'s validity. The trajectory search failed significantly more often for SDs recorded directly over emerging focal brain lesions suggesting in humans similar to animals that the complexity of SD propagation paths increase in tissue undergoing injury.