Early vascular aging determined by brachial-ankle pulse wave velocity and its impact on ischemic stroke outcome: a retrospective observational study.

Vascular aging phenotype may be useful in predicting stroke prognosis. In the present study, the relationship between vascular aging phenotypes and outcomes after acute ischemic stroke was investigated. The study included consecutive patients with acute ischemic stroke who had brachial-ankle pulse wave velocity (baPWV) measured to assess vascular aging phenotype. The 2.5th and 97.5th percentile age-specific baPWVs were used as cutoffs to define supernormal vascular aging (SUPERNOVA) and early vascular aging (EVA), respectively, and the remainder was considered normal vascular aging (NVA). A total of 2738 patients were enrolled and followed for a median of 38.1 months. The mean age was 67.02 years and 1633 were male. EVA was 67, NVA was 2605, and SUPERNOVA was 66. Compared with NVA, multivariable logistic regression showed EVA was associated with poor functional outcome (modified Rankin Scale ≥ 3) at 3 months (odds ratio 2.083, 95% confidence interval 1.147‒3.783). Multivariable Cox regression showed EVA was associated with all-cause mortality (hazard ratio 2.320, 95% confidence interval 1.283‒4.197). EVA was associated with poor functional outcome and all-cause mortality after acute ischemic stroke, especially when diabetes or atrial fibrillation coexisted. These findings indicate the vascular aging phenotype, notably EVA, can aid in identifying high-risk stroke patients.

Functional Characterization of Circadian Nuclear Receptors REV-ERBα and REV-ERBß in Human Osteosarcoma Cell Cultures.

REV-ERBα and its paralog, REV-ERBß, encoded by NR1D1 and NR1D2 genes, are key nuclear receptors that link the circadian timing system and metabolic homeostasis. Since heme is an endogenous ligand, REV-ERBs have been considered key components of the circadian molecular clock and can be pharmacologically targeted to treat various circadian rhythm-related diseases, such as cardiometabolic, inflammatory, and neuropsychiatric diseases, as well as cancer. REV-ERBs are believed to be functionally redundant and compensatory, although they often affect the expression of gene subsets in an isoform-specific manner. Therefore, this study aimed to identify the redundant and distinct roles of each isoform in controlling its target genes by comparing the transcriptome profiles of a panel of mutant U2OS human osteosarcoma cells in which either NR1D1 or NR1D2 was ablated. Indeed, our transcriptomic analyses revealed that most REV-ERB-regulated genes are controlled by redundant or even additive actions. However, the RNA expression profiles of each single mutant cell line also provide strong evidence for isoform-dependent actions. For example, REV-ERBα is more responsible for regulating the NF-κΒ signaling pathway, whereas a group of extracellular matrix components requires REV-ERBß to maintain their expression. We found that REV-ERBs have isoform-selective functions in the regulation of certain circadian output pathways despite their overlapping roles in the circadian molecular clock. Thus, the development of isoform-selective REV-ERB modulators can help treat metabolic disturbances and certain types of cancer.

A subfamily of the small heat shock proteins of the marine red alga Neopyropia yezoensis localizes in the chloroplast.

Small heat shock proteins (sHSPs) play a crucial role under abiotic stress and are present in all organisms, from eukaryotes to prokaryotes. However, studies on the sHSP gene family in red alga are limited. In this study, we aimed to identify and characterize NysHSP genes from the genome of N. yezoensis, a marine red alga adapted to the stressful intertidal zone. We identified seven NysHSP genes distributed on all three chromosomes. Expression analysis revealed that all NysHSP genes responded to H2O2 and heat stress in the gametophytic thalli, but these genes responded only to heat stress in the sporophytic conchocelis. NysHSP20.3, which has an acidic isoelectric point (pI) and short N-terminal region, was localized as granules in the cytosol. Fluorescence imaging of the NysHSP25.8-GFP and NysHSP28.4-GFP fusion proteins revealed that these proteins were located in the chloroplast. Based on their characteristics and cellular localization, the NysHSPs are divided into two subfamilies. Subfamily I includes four sHSP genes that strongly respond to heat stress and encode a protein localized in the cytosol. The NysHSP gene of subfamily II encodes a polypeptide with a long N-terminal region located in the chloroplast. This study provides insights into the evolution and function of the sHSP gene family of the marine red alga N. yezoensis and how it adapts to the stressful intertidal zone.

Cancer Prediction With Machine Learning of Thrombi From Thrombectomy in Stroke: Multicenter Development and Validation.

BACKGROUND: We aimed to develop and validate machine learning models to diagnose patients with ischemic stroke with cancer through the analysis of histopathologic images of thrombi obtained during endovascular thrombectomy. METHODS: This was a retrospective study using a prospective multicenter registry which enrolled consecutive patients with acute ischemic stroke from South Korea who underwent endovascular thrombectomy. This study included patients admitted between July 1, 2017 and December 31, 2021 from 6 academic university hospitals. Whole-slide scanning was performed for immunohistochemically stained thrombi. Machine learning models were developed using transfer learning with image slices as input to classify patients into 2 groups: cancer group or other determined cause group. The models were developed and internally validated using thrombi from patients of the primary center, and external validation was conducted in 5 centers. The model was also applied to patients with hidden cancer who were diagnosed with cancer within 1 month of their index stroke. RESULTS: The study included 70 561 images from 182 patients in both internal and external datasets (119 patients in internal and 63 in external). Machine learning models were developed for each immunohistochemical staining using antibodies against platelets, fibrin, and erythrocytes. The platelet model demonstrated consistently high accuracy in classifying patients with cancer, with area under the receiver operating characteristic curve of 0.986 (95% CI, 0.983-0.989) during training, 0.954 (95% CI, 0.937-0.972) during internal validation, and 0.949 (95% CI, 0.891-1.000) during external validation. When applied to patients with occult cancer, the model accurately predicted the presence of cancer with high probabilities ranging from 88.5% to 99.2%. CONCLUSIONS: Machine learning models may be used for prediction of cancer as the underlying cause or detection of occult cancer, using platelet-stained immunohistochemical slide images of thrombi obtained during endovascular thrombectomy.

Overexpression of putative glutathione peroxidase from Neopyropia-associated microorganisms in Chlamydomonas to respond to abiotic stress.

Lipid accumulation in microalgae can be substantially enhanced by exposing the microalgae to abiotic stress, thus increasing biofuel production. However, this also generates reactive oxygen species (ROS), which disrupts cell metabolism and reduces their productivity. Previous mRNA sequencing analyses in Neopyropia yezoensis and its associated microorganisms elucidated a putative glutathione peroxidase (PuGPx) gene. Here, this putative glutathione peroxidase was overexpressed in the microalga Chlamydomonas reinhardtii, which increased cell growth and survival rates compared to the control group under abiotic stress. Additionally, increased lipid accumulation was observed under salinity stress, high-temperature stress, and hydrogen peroxide (H2O2)-induced oxidative stress. These results suggest that PuGPx plays a protective role against abiotic stress in C. reinhardtii and stimulates lipid accumulation, which could be considered advantageous in terms of biofuel production.

Overexpression of S-Adenosylmethionine Synthetase in Recombinant Chlamydomonas for Enhanced Lipid Production.

Microalgae are attracting much attention as promising, eco-friendly producers of bioenergy due to their fast growth, absorption of carbon dioxide from the atmosphere, and production capacity in wastewater and salt water. However, microalgae can only accumulate large quantities of lipid in abiotic stress, which reduces productivity by decreasing cell growth. In this study, the strategy was investigated to increase cell viability and lipid production by overexpressing S-adenosylmethionine (SAM) synthetase (SAMS) in the microalga Chlamydomonas reinhardtii. SAM is a substance that plays an important role in various intracellular biochemical reactions, such as cell proliferation and stress response, and the overexpression of SAMS could allow cells to withstand the abiotic stress and increase productivity. Compared to wild-type C. reinhardtii, recombinant cells overexpressing SAMS grew 1.56-fold faster and produced 1.51-fold more lipids in a nitrogen-depleted medium. Furthermore, under saline-stress conditions, the survival rate and lipid accumulation were 1.56 and 2.04 times higher in the SAMS-overexpressing strain, respectively. These results suggest that the overexpression of SAMS in recombinant C. reinhardtii has high potential in the industrial-scale production of biofuels and various other high-value-added materials.

A popularization of curation service for dermatological condition in Republic of Korea.

BACKGROUND: Consumer and advanced consumption culture in modern society is an era that focuses on individual personality and value, and "my own customized products", or customized marketing strategies, are actively being developed throughout the industry. Recently, IT technologies that can support personalized services such as artificial intelligence, ubiquitous systems, and marketing automation have been recognized for their potential, directly or indirectly affecting distribution industries affected by personal consumption culture. Accordingly, customized products or services, i.e., customization, are attracting attention as an effective methodology to cope with such market changes. OBJECTIVES: Among the necessities used by modern women, cosmetics account for an endless interest in beauty and maintaining physical and mental health, and as the cosmetics market expands, it is considered that the cosmetics industry needs a clearer and in-depth study on the cosmetics submarket to satisfy consumers' diverse needs. METHODS: This review paper is a literature review, and a narrative review approach has been used for this study. A total of 300 to 400 references were selected using representative journal search websites such as PubMed, Google Scholar, Scopus, ResearchGate, LitCovid, DBPia, and RISS, of which a total of 42 papers were selected in the final stage based on 2013 to 2022 using PRISMA flow diagram. RESULTS: This study suggested to indicate the changes in the cosmetics market due to the emergence of cosmetics curation services after the coronavirus disease-19 pandemic, advanced changes in consumer purchase patterns following the 4th Industrial Revolution, and significant future prospects of cosmetics curation services. CONCLUSION: As the beauty and cosmetology industry is expected to develop in the future, it will grow as a centerpiece of the beauty industry and symbolizes nationalized cultural pride. Therefore, this review article will be continuing to promote customization as a premium beauty service for dermatological condition in Republic of Korea through corporate analysis.

Prediction of Hidden Coronary Artery Disease Using Machine Learning in Patients With Acute Ischemic Stroke.

BACKGROUND AND OBJECTIVES: A machine learning technique for identifying hidden coronary artery disease (CAD) might be useful. We developed and validated machine learning models to predict patients with hidden CAD and to assess long-term outcomes in patients with acute ischemic stroke. METHODS: Multidetector coronary CT was performed for patients without a known history of CAD. Primary outcomes were defined as having any degree of CAD and having obstructive CAD (≥50% stenosis). Demographic variables, risk factors, laboratory results, Trial of ORG 10172 in Acute Stroke Treatment classification, NIH Stroke Scale score, blood pressure, and carotid artery stenosis were used to develop and validate machine learning models to predict CAD. Area under the receiver operating characteristic curves (AUC) was calculated for performance analysis, and Kaplan-Meier and Cox survival analyses of long-term outcomes were performed. Major adverse cardiovascular events (MACEs) were defined as ischemic stroke, myocardial infarction, unstable angina, urgent coronary revascularization, and cardiovascular mortality. RESULTS: Overall, 1,710 patients were included for the training dataset and 348 patients for the validation dataset. An extreme gradient boosting model was developed to predict any degree of CAD, which showed an AUC of 0.763 (95% CI 0.711-0.814) on validation. A logistic regression model was used to predict obstructive CAD and had an AUC of 0.714 (95% CI 0.692-0.799). During the first 5 years of follow-up, MACEs occurred more frequently with predictions of any CAD (p = 0.022) or obstructive CAD (p < 0.001). Cox proportional analysis showed that the hazard ratio of MACE was 1.5 (95% CI 1.1-2.2; p = 0.016) with prediction of any CAD, whereas it was 1.9 (95% CI 1.3-2.6; p < 0.001) for obstructive CAD. DISCUSSION: We demonstrated that machine learning may help identify hidden CAD in patients with acute ischemic stroke. Long-term outcomes were also associated with prediction results. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with acute ischemic stroke with CAD risk factors but no known history of CAD, a machine learning model predicts CAD on multidetector coronary CT with an AUC of 0.763 (95% CI 0.711-0.814).

Impact of interankle blood pressure difference on major adverse cardiovascular events in cryptogenic stroke patients without peripheral artery disease: a retrospective cohort study.

OBJECTIVE: We investigated whether interankle blood pressure difference (IAND) can predict major adverse cardiovascular events (MACEs) in patients with cryptogenic stroke (CS) without peripheral artery disease (PAD). DESIGN: A retrospective cohort study. SETTING: Retrospective medical record data of patients with first-ever acute cerebral infarction who were admitted between 1 January 2007 and 31 July 2013. PARTICIPANTS: CS patients admitted within 7 days of symptom onset were included. OUTCOME MEASURES: MACEs were defined as stroke recurrence, myocardial infarction occurrence, or death. Survival analyses were conducted using the Kaplan-Meier method and Cox regression analysis. METHODS: Consecutive CS patients without PAD who underwent ankle-brachial index (ABI) measurements were enrolled. PAD was defined if a patient had an ABI of <0.90 or a history of angiographically confirmed PAD. Systolic and diastolic IANDs were calculated as follows: right ankle blood pressure-left ankle blood pressure. RESULTS: A total of 612 patients were enrolled and followed up for a median 2.6 (interquartile range, 1.0-4.3) years. In the Cox regression analysis, systolic and diastolic IANDs ≥15 mm Hg were independently associated with MACEs in CS patients without PAD (hazard ratio (HR) 2.115, 95% confidence interval (CI) 1.230 to 3.635 and HR 2.523, 95% CI 1.086 to 5.863, respectively). In the subgroup analysis, systolic IAND ≥15 mm Hg was independently associated with MACEs in older patients (age ≥65 years) (HR 2.242, 95% CI 1.170 to 4.298) but not in younger patients (age <65 years). CONCLUSIONS: Large IAND is independently associated with the long-term occurrence of MACEs in patients with CS without PAD. In particular, the association between IAND and MACEs is only valid in elderly patients.

Agreement and Reliability Analysis of Machine Learning Scaling and Wireless Monitoring in the Assessment of Acute Proximal Weakness by Experts and Non-Experts: A Feasibility Study.

Assessing the symptoms of proximal weakness caused by neurological deficits requires the knowledge and experience of neurologists. Recent advances in machine learning and the Internet of Things have resulted in the development of automated systems that emulate physicians' assessments. The application of those systems requires not only accuracy in the classification but also reliability regardless of users' proficiency in the real environment for the clinical point-of-care and the personalized health management. This study provides an agreement and reliability analysis of using a machine learning-based scaling of Medical Research Council (MRC) proximal scores to evaluate proximal weakness by experts and non-experts. The system trains an ensemble learning model using the signals from sensors attached to the limbs of patients in a neurological intensive care unit. For the agreement analysis, we investigated the percent agreement of MRC proximal scores and Bland-Altman plots of kinematic features between the expert- and non-expert scaling. We also analyzed the intra-class correlation coefficients (ICCs) of kinematic features and Krippendorff's alpha of the observers' scaling for the reliability analysis. The mean percent agreement between the expert- and the non-expert scaling was 0.542 for manual scaling and 0.708 for autonomous scaling. The ICCs of kinematic features measured using sensors ranged from 0.742 to 0.850, whereas the Krippendorff's alpha of manual scaling for the three observers was 0.275. The autonomous assessment system can be utilized by the caregivers, paramedics, or other observers during an emergency to evaluate acute stroke patients.

Vitamin D deficiency and mortality among critically ill surgical patients in an urban Korean hospital.

Critically ill patients in intensive care units (ICUs) are exposed to various risk factors for vitamin D deficiency. Vitamin D deficiency in extended-stay patients may result in decreased muscle mass and increased fat tissue, which may impair rehabilitation and recovery. Our study aimed to evaluate the degree of serum vitamin D deficiency in critically ill surgical patients and its association with clinical outcomes. Clinical data from 186 adult male (n = 121; 65.1%) and female (n = 65; 34.9%) patients hospitalized in surgical ICUs at Ajou University Hospital from April 2015 to September 2016 were retrospectively analyzed. All adult surgical patients between the age of 18 and 88 years were enrolled. The mean serum 25-hydroxyvitamin D (25[OH]D) level of all patients was 17.8 ng/mL. A total of 120 patients (64.5%) with serum 25(OH)D levels < 20 ng/mL were classified as the deficiency group. A prolonged hospital stay was observed among the deficiency group but was not statistically significant (p = 0.824). Serum 25(OH)D levels were significantly correlated with age but inversely correlated with Sequential Organ Failure Assessment (SOFA) score, selenium, triglycerides, and C-reactive protein levels. There was no significant difference in mortality rates between the group with a vitamin D injection and the group without a vitamin D injection (14.6% vs. 16.9%, p = 0.074). Vitamin D deficiency was common in surgical ICU patients; however, vitamin D levels were higher in older patients. In conclusion, vitamin D deficiency was inversely associated with the SOFA severity score (correlation coefficient -0.165, p = 0.024) but was not associated with the length of hospital or ICU stay and mortality.

Low Ankle-Brachial Index Is Associated With Stroke Recurrence in Ischemic Stroke Patients With Atrial Fibrillation.

Introduction: Cardioembolic stroke (CE) has poor outcomes and high recurrence rates. A low ankle-brachial index (ABI <0.9) is associated with atrial fibrillation (AF) and poor stroke outcomes. We investigated whether a low ABI is associated with stroke recurrence, major adverse cardiovascular events (MACE), and mortality in patients with CE and whether this association is affected by AF. Methods: We enrolled patients with CE who underwent ABI measurements during hospitalization. Recurrent stroke was defined based on newly developed neurologic symptoms with relevant lesions 7 days after the index stroke. MACE comprised stroke recurrence, myocardial infarction, or death. Results: Of 775 patients, 427 (55.1%) were AF patients and 348 (44.9%) were non-AF patients. Patients were followed up for a median of 33.6 (IQR, 18.0-51.6) months. In total, 194 (25.0%) patients experienced MACE, including 77 (9.9%) patients with stroke recurrence and 101 (13.0%) patients with mortality, during the study period. Multivariable Cox regression analysis showed that an ABI <0.9 was independently associated with MACE (AF patients: hazard ratio [HR] = 2.327, 95% confidence interval [CI] = 1.371-3.949, non-AF patients: HR = 3.116, 95% CI = 1.465-6.629) and mortality (AF patients: HR = 2.659, 95% CI = 1.483-4.767, non-AF patients: HR = 3.645, 95% CI = 1.623-8.187). Stroke recurrence was independently associated with an ABI <0.9 in AF patients (HR = 3.559, 95% CI = 1.570-8.066), but not in non-AF patients (HR = 1.186, 95% CI = 0.156-8.989). Conclusions: We found that a low ABI is associated with stroke recurrence, MACE, and mortality in patients with CE. In particular, the association between ABI and recurrent stroke is only present in AF patients. A low ABI may be a useful prognostic marker in patients with CE, especially in AF patients.

Short-Term Event Prediction in the Operating Room (STEP-OP) of Five-Minute Intraoperative Hypotension Using Hybrid Deep Learning: Retrospective Observational Study and Model Development.

BACKGROUND: Intraoperative hypotension has an adverse impact on postoperative outcomes. However, it is difficult to predict and treat intraoperative hypotension in advance according to individual clinical parameters. OBJECTIVE: The aim of this study was to develop a prediction model to forecast 5-minute intraoperative hypotension based on the weighted average ensemble of individual neural networks, utilizing the biosignals recorded during noncardiac surgery. METHODS: In this retrospective observational study, arterial waveforms were recorded during noncardiac operations performed between August 2016 and December 2019, at Seoul National University Hospital, Seoul, South Korea. We analyzed the arterial waveforms from the big data in the VitalDB repository of electronic health records. We defined 2s hypotension as the moving average of arterial pressure under 65 mmHg for 2 seconds, and intraoperative hypotensive events were defined when the 2s hypotension lasted for at least 60 seconds. We developed an artificial intelligence-enabled process, named short-term event prediction in the operating room (STEP-OP), for predicting short-term intraoperative hypotension. RESULTS: The study was performed on 18,813 subjects undergoing noncardiac surgeries. Deep-learning algorithms (convolutional neural network [CNN] and recurrent neural network [RNN]) using raw waveforms as input showed greater area under the precision-recall curve (AUPRC) scores (0.698, 95% CI 0.690-0.705 and 0.706, 95% CI 0.698-0.715, respectively) than that of the logistic regression algorithm (0.673, 95% CI 0.665-0.682). STEP-OP performed better and had greater AUPRC values than those of the RNN and CNN algorithms (0.716, 95% CI 0.708-0.723). CONCLUSIONS: We developed STEP-OP as a weighted average of deep-learning models. STEP-OP predicts intraoperative hypotension more accurately than the CNN, RNN, and logistic regression models. TRIAL REGISTRATION: ClinicalTrials.gov NCT02914444; https://clinicaltrials.gov/ct2/show/NCT02914444.

Antitussive effect of a magnesium infusion during anesthetic emergence in patients with double-lumen endotracheal tube: a randomized controlled trial.

BACKGROUND: A double-lumen endotracheal tube (DLT) inserted into the bronchus can stimulate the respiratory tracts, causing coughing. Opioids have been introduced to prevent emergence cough. However, the administration of a significant opioid dose at the end of surgery may result in undesirable events. Magnesium, common intracellular ion, suppress bronchial smooth muscle contraction and have antitussive effect. We investigated the antitussive effects of a magnesium infusion during anesthetic emergence in patients who underwent thoracic surgery requiring one-lung ventilation (OLV) anesthesia with a DLT. METHODS: One-hundred forty patients undergoing OLV anesthesia with a DLT were enrolled in this prospective, randomized double-blinded trial. In combination with a low dose of remifentanil, patients were randomly allocated to receive either magnesium sulphate (infusion of 15 mg/kg/hour after a single bolus of 30 mg/kg) or normal saline during the operation and emergence. Primary outcomes were the severity and incidence of cough during emergence. RESULTS: The severity of cough was assessed by the cough severity grading score: 0, no cough; 1, single cough; 2, cough persistence <5 seconds; 3, cough persistence ≥5 seconds. There was a significant difference in the severity score of cough between the groups [median (IQR): 2 (0 to 3) in control group vs. 0 (0 to 1) in magnesium group, P=0.003]. However, there was no significant difference in the overall incidence of cough between both groups [42 (64.6%) in control group vs. 31 (47.7%) in magnesium group, P=0.077]. CONCLUSIONS: Magnesium attenuated the severity of cough during emergence after OLV anesthesia using a DLT without adverse events.

Persistent STAT5 activation reprograms the epigenetic landscape in CD4+ T cells to drive polyfunctionality and antitumor immunity.

The presence of polyfunctional CD4+ T cells is often associated with favorable antitumor immunity. We report here that persistent activation of signal transducer and activator of transcription 5 (STAT5) in tumor-specific CD4+ T cells drives the development of polyfunctional T cells. We showed that ectopic expression of a constitutively active form of murine STAT5A (CASTAT5) enabled tumor-specific CD4+ T cells to undergo robust expansion, infiltrate tumors vigorously, and elicit antitumor CD8+ T cell responses in a CD4+ T cell adoptive transfer model system. Integrated epigenomic and transcriptomic analysis revealed that CASTAT5 induced genome-wide chromatin remodeling in CD4+ T cells and established a distinct epigenetic and transcriptional landscape. Single-cell RNA sequencing analysis further identified a subset of CASTAT5-transduced CD4+ T cells with a molecular signature indicative of progenitor polyfunctional T cells. The therapeutic significance of CASTAT5 came from our finding that adoptive transfer of T cells engineered to coexpress CD19-targeting chimeric antigen receptor (CAR) and CASTAT5 gave rise to polyfunctional CD4+ CAR T cells in a mouse B cell lymphoma model. The optimal therapeutic outcome was obtained when both CD4+ and CD8+ CAR T cells were transduced with CASTAT5, indicating that CASTAT5 facilitates productive CD4 help to CD8+ T cells. Furthermore, we provide evidence that CASTAT5 is functional in primary human CD4+ T cells, underscoring its potential clinical relevance. Our results implicate STAT5 as a valid candidate for T cell engineering to generate polyfunctional, exhaustion-resistant, and tumor-tropic antitumor CD4+ T cells to potentiate adoptive T cell therapy for cancer.

Automatic Grading of Stroke Symptoms for Rapid Assessment Using Optimized Machine Learning and 4-Limb Kinematics: Clinical Validation Study.

BACKGROUND: Subtle abnormal motor signs are indications of serious neurological diseases. Although neurological deficits require fast initiation of treatment in a restricted time, it is difficult for nonspecialists to detect and objectively assess the symptoms. In the clinical environment, diagnoses and decisions are based on clinical grading methods, including the National Institutes of Health Stroke Scale (NIHSS) score or the Medical Research Council (MRC) score, which have been used to measure motor weakness. Objective grading in various environments is necessitated for consistent agreement among patients, caregivers, paramedics, and medical staff to facilitate rapid diagnoses and dispatches to appropriate medical centers. OBJECTIVE: In this study, we aimed to develop an autonomous grading system for stroke patients. We investigated the feasibility of our new system to assess motor weakness and grade NIHSS and MRC scores of 4 limbs, similar to the clinical examinations performed by medical staff. METHODS: We implemented an automatic grading system composed of a measuring unit with wearable sensors and a grading unit with optimized machine learning. Inertial sensors were attached to measure subtle weaknesses caused by paralysis of upper and lower limbs. We collected 60 instances of data with kinematic features of motor disorders from neurological examination and demographic information of stroke patients with NIHSS 0 or 1 and MRC 7, 8, or 9 grades in a stroke unit. Training data with 240 instances were generated using a synthetic minority oversampling technique to complement the imbalanced number of data between classes and low number of training data. We trained 2 representative machine learning algorithms, an ensemble and a support vector machine (SVM), to implement auto-NIHSS and auto-MRC grading. The optimized algorithms performed a 5-fold cross-validation and were searched by Bayes optimization in 30 trials. The trained model was tested with the 60 original hold-out instances for performance evaluation in accuracy, sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). RESULTS: The proposed system can grade NIHSS scores with an accuracy of 83.3% and an AUC of 0.912 using an optimized ensemble algorithm, and it can grade with an accuracy of 80.0% and an AUC of 0.860 using an optimized SVM algorithm. The auto-MRC grading achieved an accuracy of 76.7% and a mean AUC of 0.870 in SVM classification and an accuracy of 78.3% and a mean AUC of 0.877 in ensemble classification. CONCLUSIONS: The automatic grading system quantifies proximal weakness in real time and assesses symptoms through automatic grading. The pilot outcomes demonstrated the feasibility of remote monitoring of motor weakness caused by stroke. The system can facilitate consistent grading with instant assessment and expedite dispatches to appropriate hospitals and treatment initiation by sharing auto-MRC and auto-NIHSS scores between prehospital and hospital responses as an objective observation.

Gamma-irradiation degraded sulfated polysaccharide from a new red algal strain Pyropia yezoensis Sookwawon 104 with in vitro antiproliferative activity.

Pyropia yezoensis Sookwawon 104 is a newly cultivated strain of red marine algae. The present study aimed to investigate the in vitro antiproliferative activity of sulfated polysaccharide extracted from P. yezoensis Sookwawon 104 (PYSP), as well as that of its low molecular weight (Mw) derivatives. PYSP is a heterogeneous sulfated polysaccharide mainly composed of galactose, glucose and fucose. PYSP was degraded by gamma-irradiation at doses of 20 and 100 kGy to produce two derivatives, named as PYSP-20 and PYSP-100, respectively. Comparison of PYSP, PYSP-20 and PYSP-100 revealed clear differences in their molecular weight (Mw) distributions, and distinct in vitro antiproliferative activities against Hep3B, MDA-MB-231 and HeLa cancer cell lines. PYSP-20 and PYSP-100 exhibited stronger antiproliferative effects than PYSP, suggesting that the reduction in Mw may have increased the in vitro antiproliferative activity. Furthermore, the mRNA expression levels of the antitumor gene P53 and cell cycle-associated genes P21, Cyclin B1 and cyclin dependent kinase 1 (Cdk1) were further analyzed by reverse transcription-quantitative PCR in PYSP-20 and PYSP-100-treated cancer cells. PYSP and its derivatives were shown to inhibit the proliferation of tumor cells by regulating the expression of P53, P21, Cyclin B1 and Cdk1. In conclusion, low-Mw polysaccharide derivatives prepared from P. yezoensis Sookwawon 104 by gamma-irradiation exhibit significant inhibition effects on cancer cell proliferation in vitro and may be a novel source of potential anticancer therapeutic agents.

Predicting Stroke Outcomes Using Ankle-Brachial Index and Inter-Ankle Blood Pressure Difference.

BACKGROUND: This study investigated the association of high ankle-brachial index difference (ABID) and systolic inter-ankle blood pressure difference (IAND) with short- and long-term outcomes in acute ischemic stroke patients without peripheral artery disease (PAD). METHODS: Consecutive patients with acute ischemic stroke who underwent ankle-brachial index (ABI) measurement were enrolled. ABID was calculated as |right ABI-left ABI|. IAND and systolic inter-arm blood pressure difference (IAD) were calculated as |right systolic blood pressure - left systolic blood pressure|. Poor functional outcome was defined as modified Rankin Scale score ≥3 at 3 months. Major adverse cardiovascular events (MACEs) were defined as stroke recurrence, myocardial infarction, or death. RESULTS: A total of 2901 patients were enrolled and followed up for a median of 3.1 (interquartile range, 1.6-4.7) years. Among them, 2643 (84.9%) patients did not have PAD. In the logistic regression analysis, ABID ≥ 0.15 and IAND ≥ 15 mmHg were independently associated with poor functional outcome (odds ratio (OR), 1.970, 95% confidence interval (CI), 1.175‒3.302; OR, 1.665, 95% CI, 1.188‒2.334, respectively). In Cox regression analysis, ABID ≥0.15 and IAND ≥ 15 mmHg were independently associated with MACEs (hazard ratio (HR), 1.514, 95% CI, 1.058‒2.166; HR, 1.343, 95% CI, 1.051‒1.716, respectively) and all-cause mortality (HR, 1.524, 95% CI, 1.039‒2.235; HR, 1.516, 95% CI, 1.164‒1.973, respectively) in patients without PAD. CONCLUSION: High ABID and IAND are associated with poor short-term outcomes, long-term MACE occurrence, and all-cause mortality in acute ischemic stroke without PAD.