AI in evaluating ambulation of stroke patients: severity classification with video and functional ambulation category scale.

BACKGROUND: The evaluation of gait function and severity classification of stroke patients are important to determine the rehabilitation goal and the level of exercise. Physicians often qualitatively evaluate patients' walking ability through visual gait analysis using naked eye, video images, or standardized assessment tools. Gait evaluation through observation relies on the doctor's empirical judgment, potentially introducing subjective opinions. Therefore, conducting research to establish a basis for more objective judgment is crucial. OBJECTIVE: To verify a deep learning model that classifies gait image data of stroke patients according to Functional Ambulation Category (FAC) scale. METHODS: Gait vision data from 203 stroke patients and 182 healthy individuals recruited from six medical institutions were collected to train a deep learning model for classifying gait severity in stroke patients. The recorded videos were processed using OpenPose. The dataset was randomly split into 80% for training and 20% for testing. RESULTS: The deep learning model attained a training accuracy of 0.981 and test accuracy of 0.903. Area Under the Curve(AUC) values of 0.93, 0.95, and 0.96 for discriminating among the mild, moderate, and severe stroke groups, respectively. CONCLUSION: This confirms the potential of utilizing human posture estimation based on vision data not only to develop gait parameter models but also to develop models to classify severity according to the FAC criteria used by physicians. To develop an AI-based severity classification model, a large amount and variety of data is necessary and data collected in non-standardized real environments, not in laboratories, can also be used meaningfully.

Deep learning model for classifying shoulder pain rehabilitation exercises using IMU sensor.

BACKGROUND: Artificial intelligence is being used for rehabilitation, including monitoring exercise compliance through sensor technology. AI classification of shoulder exercise wearing an IMU sensor has only been reported in normal (i.e. painless) subjects. To prove the feasibility of monitoring exercise compliance, we aimed to classify 11 types of shoulder rehabilitation exercises using an AI (artificial intelligence) algorithm in patients with shoulder pain. We had the patients wear an IMU-based sensor, collected data during exercise, and determined the accuracy of exercise classification. METHODS: Data were collected from 58 patients (27 males, 31 females, age range 37-82 years) diagnosed with shoulder diseases such as adhesive capsulitis and rotator cuff disease. 11 types of shoulder pain rehabilitation exercise programs were developed and repeated each exercise ten times per session while wearing an IMU sensor. The study applied the Rectified Linear Unit (ReLU) and the SoftMax as the activation function for hidden layers, the output layer. RESULTS: The acquired data was used to train a DNN model using the multilayer perceptron algorithm. The trained model was used to classify 11 types of shoulder pain rehabilitation exercises. The training accuracy was 0.975 and the test accuracy was 0.925. CONCLUSION: The study demonstrates that IMU sensor data can effectively classify shoulder pain rehabilitation exercises, providing more appropriate feedback for patients. The model can be utilized to establish a system for remotely monitoring patients' exercise performance. The use of deep learning in patient monitoring and rehabilitation has significant potential to bring innovative changes to healthcare service delivery.

Evolution of a Strategy for Concise Enantioselective Total Synthesis of the Salinosporamide Family of Natural Products.

Our first strategy for rapidly accessing pyrrolidinone cores of salinosporamides involved combined use of memory of chirality and dynamic kinetic resolution principles in aldol reactions of the serine-derived 5-oxazolidinone substrate, which was ultimately unsuccessful with respect to enantioselectivity. This failure led us to the revised strategy. The influence of the stereocenter in 5-oxazolidinone enabled selective installation of the C-2 stereocenter. The intramolecular aldol reaction of the C-2 stereodefined aldol substrate was successful. An unexpected hydrolytic dynamic kinetic resolution was observed in hydrolyses of the bicyclic aldol products. This unprecedented substrate-driven hydrolytic dynamic kinetic resolution was utilized in preparing the pyrrolidinone core with excellent efficiency. Through this strategy, the concise total syntheses of salinosporamides A and B as well as cinnabaramides A, E, and F were achieved with high selectivity.

Ovalicin attenuates atopic dermatitis symptoms by inhibiting IL-31 signaling and intracellular calcium influx.

Atopic dermatitis (AD) is a common skin disorder difficult to be treated with medication. This study investigated the potential of ovalicin extracted from Cordyceps militaris for the treatment of AD using in vitro and in vivo models. We found that, in canine macrophage cell line DH82, lipopolysaccharide (LPS) upregulated the expression of genes associated with inflammation and pruritic responses through activating calcium and interleukin-31 (IL-31) signaling, and the upregulation could be suppressed by ovalicin, with an effect significantly stronger than dexamethasone. Ovalicin also reduced the expression of IL-31 downstream genes, including JAK2 (Janus kinase 2), TRPV1 (transient receptor potential vanilloid receptor-1), and HRH2 (histamine receptor H2). Ovalicin significantly alleviated the allergic symptoms in the AD mouse model. Histologically, the number of macrophages and mast cells infiltrated in the dermis was significantly reduced by ovalicin treatment. In the skin tissue of AD mice, reduction of IL-31 receptor was observed in the ovalicin treated group compared to the group without ovalicin treatment. To our knowledge, this is the first study to elucidate the anti-atopic mechanism of ovalicin, which could be an alternative to steroidal drugs commonly used for AD treatment.

Comparison of three types of analyzers for urine protein-to-creatinine ratios in dogs.

BACKGROUND: Quantitation of urine protein is important in dogs with chronic kidney disease. Various analyzers are used to measure urine protein-to-creatinine ratios (UPCR). OBJECTIVES: This study aimed to compare the UPCR obtained by three types of analyzers (automated wet chemistry analyzer, in-house dry chemistry analyzer, and dipstick reading device) and investigate whether the differences could affect clinical decision process. METHODS: Urine samples were collected from 115 dogs. UPCR values were obtained using three analyzers. Bland-Altman and Passing Bablok tests were used to analyze agreement between the UPCR values. Urine samples were classified as normal or proteinuria based on the UPCR values obtained by each analyzer and concordance in the classification evaluated with Cohen's kappa coefficient. RESULTS: Passing and Bablok regression showed that there were proportional as well as constant difference between UPCR values obtained by a dipstick reading device and those obtained by the other analyzers. The concordance in the classification of proteinuria was very high (κ = 0.82) between the automated wet chemistry analyzer and in-house dry chemistry analyzer, while the dipstick reading device showed moderate concordance with the automated wet chemistry analyzer (κ = 0.52) and in-house dry chemistry analyzer (κ = 0.53). CONCLUSIONS: Although the urine dipstick test is simple and a widely used point-of-care test, our results indicate that UPCR values obtained by the dipstick test are not appropriate for clinical use. Inter-instrumental variability may affect clinical decision process based on UPCR values and should be emphasized in veterinary practice.

Glucose starvation induces resistance to metformin through the elevation of mitochondrial multidrug resistance protein 1.

Metformin, a drug for type 2 diabetes mellitus, has shown therapeutic effects for various cancers. However, it had no beneficial effects on the survival rate of human malignant mesothelioma (HMM) patients. The present study was performed to elucidate the underlying mechanism of metformin resistance in HMM cells. Glucose-starved HMM cells had enhanced resistance to metformin, demonstrated by decreased apoptosis and autophagy and increased cell survival. These cells showed abnormalities in mitochondria, such as decreased ATP synthesis, morphological elongation, altered mitochondrial permeability transition pore and hyperpolarization of mitochondrial membrane potential (MMP). Intriguingly, Mdr1 was significantly upregulated in mitochondria but not in cell membrane. The upregulated mitochondrial Mdr1 was reversed by treatment with carbonyl cyanide m-chlorophenyl hydrazone, an MMP depolarization inducer. Furthermore, apoptosis and autophagy were increased in multidrug resistance protein 1 knockout HMM cells cultured under glucose starvation with metformin treatment. The data suggest that mitochondrial Mdr1 plays a critical role in the chemoresistance to metformin in HMM cells, which could be a potential target for improving its therapeutic efficacy.

Coniferyl aldehyde attenuates radiation enteropathy by inhibiting cell death and promoting endothelial cell function.

Radiation enteropathy is a common complication in cancer patients. The aim of this study was to investigate whether radiation-induced intestinal injury could be alleviated by coniferyl aldehyde (CA), an HSF1-inducing agent that increases cellular HSP70 expression. We systemically administered CA to mice with radiation enteropathy following abdominal irradiation (IR) to demonstrate the protective effects of CA against radiation-induced gastrointestinal injury. CA clearly alleviated acute radiation-induced intestinal damage, as reflected by the histopathological data and it also attenuated sub-acute enteritis. CA prevented intestinal crypt cell death and protected the microvasculature in the lamina propria during the acute and sub-acute phases of damage. CA induced HSF1 and HSP70 expression in both intestinal epithelial cells and endothelial cells in vitro. Additionally, CA protected against not only the apoptotic cell death of both endothelial and epithelial cells but also the loss of endothelial cell function following IR, indicating that CA has beneficial effects on the intestine. Our results provide novel insight into the effects of CA and suggest its role as a therapeutic candidate for radiation-induced enteropathy due to its ability to promote rapid re-proliferation of the intestinal epithelium by the synergic effects of the inhibition of cell death and the promotion of endothelial cell function.