Spectrometer-based wavelength interrogation SPR imaging via Hadamard transform.

We present spectrometer-based wavelength interrogation surface plasmon resonance imaging (SPRi) without mechanical scanning. A polarized broadband light source illuminates an object via a gold-coated prism; the reflected light is spatially modulated by a digital mirror device (DMD) and then measured with a spectrometer. Reflectance spectral images are reconstructed via the Hadamard transform (HT), and a refractive index (RI) map is visualized from the reflectance spectral images by analyzing the resonance peak shift of the spectrum at each image pixel. We demonstrate the feasibility of our method by evaluating the resolution, sensitivity, and dynamic detection range, experimentally obtained as ∼2.203 × 10-6 RI unit (RIU), ∼3,407 nm/RIU, and ∼0.1403 RIU, respectively. Furthermore, simulations are performed to validate the experimental results.

Explainable Artificial Intelligence and Wearable Sensor-Based Gait Analysis to Identify Patients with Osteopenia and Sarcopenia in Daily Life.

Osteopenia and sarcopenia can cause various senile diseases and are key factors related to the quality of life in old age. There is need for portable tools and methods that can analyze osteopenia and sarcopenia risks during daily life, rather than requiring a specialized hospital setting. Gait is a suitable indicator of musculoskeletal diseases; therefore, we analyzed the gait signal obtained from an inertial-sensor-based wearable gait device as a tool to manage bone loss and muscle loss in daily life. To analyze the inertial-sensor-based gait, the inertial signal was classified into seven gait phases, and descriptive statistical parameters were obtained for each gait phase. Subsequently, explainable artificial intelligence was utilized to analyze the contribution and importance of descriptive statistical parameters on osteopenia and sarcopenia. It was found that XGBoost yielded a high accuracy of 88.69% for osteopenia, whereas the random forest approach showed a high accuracy of 93.75% for sarcopenia. Transfer learning with a ResNet backbone exhibited appropriate performance but showed lower accuracy than the descriptive statistical parameter-based identification result. The proposed gait analysis method confirmed high classification accuracy and the statistical significance of gait factors that can be used for osteopenia and sarcopenia management.

COVID-19, flattening the curve, and Benford's law.

For many countries attempting to control the fast-rising number of coronavirus cases and deaths, the race is on to "flatten the curve," since the spread of coronavirus disease 2019 (COVID-19) has taken on pandemic proportions. In the absence of significant control interventions, the curve could be steep, with the number of COVID-19 cases growing exponentially. In fact, this level of proliferation may already be happening, since the number of patients infected in Italy closely follows an exponential trend. Thus, we propose a test. When the numbers are taken from an exponential distribution, it has been demonstrated that they automatically follow Benford's Law (BL). As a result, if the current control interventions are successful and we flatten the curve (i.e., we slow the rate below an exponential growth rate), then the number of infections or deaths will not obey BL. For this reason, BL may be useful for assessing the effects of the current control interventions and may be able to answer the question, "How flat is flat enough?" In this study, we used an epidemic growth model in the presence of interventions to describe the potential for a flattened curve, and then investigated whether the epidemic growth model followed BL for ten selected countries with a relatively high mortality rate. Among these countries, South Korea showed a particularly high degree of control intervention. Although all of the countries have aggressively fought the epidemic, our analysis shows that all countries except for Japan satisfied BL, indicating the growth rates of COVID-19 were close to an exponential trend. Based on the simulation table in this study, BL test shows that the data from Japan is incorrect.

Safety and immunogenicity of recombinant rabies virus (ERAGS) in mice and raccoon dogs.

PURPOSE: The development of a genetically modified live rabies vaccine applicable to wild raccoon dogs is necessary for the eradication of rabies in Korea. Thus, we constructed a recombinant rabies virus (RABV) called the ERAGS strain, using a reverse genetic system and evaluated its safety and efficacy in mice and its safety and immunogenicity in raccoon dogs. MATERIALS AND METHODS: ERAGS, which has Asn194Ser and Arg333Glu substitutions in the glycoprotein, was constructed using site-directed mutagenesis. Mice were inoculated with the ERAGS strain (either 10(5.0) or 10(7.0) FAID50/mL) via intramuscular (IM) or intracranial injections and then challenged with a virulent RABV. Raccoon dogs were administered the ERAGS strain (10(8.0) FAID50/mL) either orally or via the IM route and the immunogenicity of the strain was evaluated using fluorescent antibody virus neutralization tests. RESULTS: The ERAGS strain inoculated into murine neuroblastoma cells reached 10(7.8) FAID50/mL at 96-hour post-inoculation. The virus was not pathogenic and induced complete protection from virulent RABV in immunized 4- and 6-week-old mice. Korean raccoon dogs immunized with the ERAGS strain via IM or oral route were also safe from the virus and developed high titer levels (26.4-32.8 IU/mL) of virus-neutralizing antibody (VNA) at 4 weeks post-inoculation. CONCLUSION: The ERAGS RABV strain was effectively protective against rabies in mice and produced a high VNA titer in raccoon dogs.