Automatic and robust estimation of sex and chronological age from panoramic radiographs using a multi-task deep learning network: a study on a South Korean population.

Sex and chronological age estimation are crucial in forensic investigations and research on individual identification. Although manual methods for sex and age estimation have been proposed, these processes are labor-intensive, time-consuming, and error-prone. The purpose of this study was to estimate sex and chronological age from panoramic radiographs automatically and robustly using a multi-task deep learning network (ForensicNet). ForensicNet consists of a backbone and both sex and age attention branches to learn anatomical context features of sex and chronological age from panoramic radiographs and enables the multi-task estimation of sex and chronological age in an end-to-end manner. To mitigate bias in the data distribution, our dataset was built using 13,200 images with 100 images for each sex and age range of 15-80 years. The ForensicNet with EfficientNet-B3 exhibited superior estimation performance with mean absolute errors of 2.93 ± 2.61 years and a coefficient of determination of 0.957 for chronological age, and achieved accuracy, specificity, and sensitivity values of 0.992, 0.993, and 0.990, respectively, for sex prediction. The network demonstrated that the proposed sex and age attention branches with a convolutional block attention module significantly improved the estimation performance for both sex and chronological age from panoramic radiographs of elderly patients. Consequently, we expect that ForensicNet will contribute to the automatic and accurate estimation of both sex and chronological age from panoramic radiographs.

Genotype-phenotype correlations in children with Gitelman syndrome.

BACKGROUND: This study aimed to analyze genotype-phenotype correlations in children with Gitelman syndrome (GS). METHODS: This multicenter retrospective study included 50 Korean children diagnosed with SLC12A3 variants in one or both alleles and the typical laboratory findings of GS. Genetic testing was performed using the Sanger sequencing except for one patient. RESULTS: The median age at the diagnosis was 10.5 years (interquartile range, 6.8;14.1), and 41 patients were followed up for a median duration of 5.4 years (interquartile range, 4.1;9.6). A total of 30 different SLC12A3 variants were identified. Of the patients, 34 (68%) had biallelic variants, and 16 (32%) had monoallelic variants on examination. Among the patients with biallelic variants, those (n = 12) with the truncating variants in one or both alleles had lower serum chloride levels (92.2 ± 3.2 vs. 96.5 ± 3.8 mMol/L, P = 0.002) at onset, as well as lower serum potassium levels (3.0 ± 0.4 vs. 3.4 ± 0.3 mMol/L, P = 0.016), and lower serum chloride levels (96.1 ± 1.9 vs. 98.3 ± 3.0 mMol/L, P = 0.049) during follow-up than those without truncating variants (n = 22). Patients with monoallelic variants on examination showed similar phenotypes and treatment responsiveness to those with biallelic variants. CONCLUSIONS: Patients with GS who had truncating variants in one or both alleles had more severe electrolyte abnormalities than those without truncating variants. Patients with GS who had monoallelic SLC12A3 variants on examination had almost the same phenotypes, response to treatment, and long-term prognosis as those with biallelic variants.

Particulate matter (PM10) exacerbates on MK-801-induced schizophrenia-like behaviors through the inhibition of ERK-CREB-BDNF signaling pathway.

Particulate matter (PM), released into the air by a variety of natural and human activities, is a key indicator of air pollution. Although PM is known as the extensive health hazard to affect a variety of illness, few studies have specifically investigated the effects of PM10 exposure on schizophrenic development. In the present study, we aimed to investigate the impact of PM10 on MK-801, N-methyl-D-aspartate (NMDA) receptor antagonist, induced schizophrenia-like behaviors in C57BL/6 mouse. Preadolescent mice were exposed PM10 to 3.2 mg/m3 concentration for 4 h/day for 2 weeks through a compartmentalized whole-body inhalation chamber. After PM10 exposure, we conducted behavioral tests during adolescence and adulthood to investigate longitudinal development of schizophrenia. We found that PM10 exacerbated schizophrenia-like behavior, such as psychomotor agitation, social interaction deficits and cognitive deficits at adulthood in MK-801-induced schizophrenia animal model. Furthermore, the reduced expression levels of brain-derived neurotrophic factor (BDNF) and the phosphorylation of BDNF related signaling molecules, extracellular signal-regulated kinase (ERK) and cAMP response element-binding protein (CREB), were exacerbated by PM10 exposure in the adult hippocampus of MK-801-treated mice. Thus, our present study demonstrates that exposure to PM10 in preadolescence exacerbates the cognitive impairment in animal model of schizophrenia, which are considered to be facilitated by the decreased level of BDNF through reduced ERK-CREB expression.

Combination Analysis of PCDHGA12 and CDO1 DNA Methylation in Bronchial Washing Fluid for Lung Cancer Diagnosis.

BACKGROUND: When suspicious lesions are observed on computer-tomography (CT), invasive tests are needed to confirm lung cancer. Compared with other procedures, bronchoscopy has fewer complications. However, the sensitivity of peripheral lesion through bronchoscopy including washing cytology is low. A new test with higher sensitivity through bronchoscopy is needed. In our previous study, DNA methylation of PCDHGA12 in bronchial washing cytology has a diagnostic value for lung cancer. In this study, combination of PCDHGA12 and CDO1 methylation obtained through bronchial washing cytology was evaluated as a diagnostic tool for lung cancer. METHODS: A total of 187 patients who had suspicious lesions in CT were enrolled. PCDHGA12 methylation test, CDO1 methylation test, and cytological examination were performed using 3-plex LTE-qMSP test. RESULTS: Sixty-two patients were diagnosed with benign diseases and 125 patients were diagnosed with lung cancer. The sensitivity of PCDHGA12 was 74.4% and the specificity of PCDHGA12 was 91.9% respectively. CDO1 methylation test had a sensitivity of 57.6% and a specificity of 96.8%. The combination of both PCDHGA12 methylation test and CDO1 methylation test showed a sensitivity of 77.6% and a specificity of 90.3%. The sensitivity of lung cancer diagnosis was increased by combining both PCDHGA12 and CDO1 methylation tests. CONCLUSION: Checking DNA methylation of both PCDHGA12 and CDO1 genes using bronchial washing fluid can reduce the invasive procedure to diagnose lung cancer.

Cyclops lesions associated with both bundles and selective bundle repair of the anterior cruciate ligament.

BACKGROUND: The remnant of a ruptured anterior cruciate ligament (ACL) can increase the risk of impingement or a cyclops lesion, which can increase challenges to proper tunnel placement. PURPOSE: To evaluate the prevalence of cyclops lesions after ACL reconstruction and to assess the difference in the incidence of cyclops lesions between single-bundle repair and selective bundle repair of the ACL. MATERIAL AND METHODS: This retrospective study included 151 patients who were diagnosed with an ACL tear after knee joint magnetic resonance imaging (MRI) who underwent ACL reconstruction surgery. MRI diagnosis of cyclops lesion formation was made if a soft-tissue mass was seen anteriorly in the intercondylar notch near the tibial insertion of the reconstructed ACL, based on sagittal T2-weighted (T2W) imaging. The size of the cyclops lesions was recorded as the largest diameter on the sagittal T2W imaging. RESULTS: A cyclops lesion was detected in 74 (38.5%) cases. Cyclops lesions were detected more frequently in cases with single-bundle repair of the ACL, but the results were not statistically significant (P = 0.609). Compared with selective bundle repair, cyclops lesions had a significantly higher prevalence in the posterolateral (PL) bundle repair than in the anteromedial (AM) bundle repair (P = 0.027) based on MR images at 6-12 months after surgery. CONCLUSION: The incidence of cyclops lesions did not differ significantly in single-bundle repair and selective bundle repair of ACL. However, selective PL bundle repair of the ACL showed a significantly increased incidence of cyclops lesions compared with selective AM bundle repair.

An Explainable EEG-Based Human Activity Recognition Model Using Machine-Learning Approach and LIME.

Electroencephalography (EEG) is a non-invasive method employed to discern human behaviors by monitoring the neurological responses during cognitive and motor tasks. Machine learning (ML) represents a promising tool for the recognition of human activities (HAR), and eXplainable artificial intelligence (XAI) can elucidate the role of EEG features in ML-based HAR models. The primary objective of this investigation is to investigate the feasibility of an EEG-based ML model for categorizing everyday activities, such as resting, motor, and cognitive tasks, and interpreting models clinically through XAI techniques to explicate the EEG features that contribute the most to different HAR states. The study involved an examination of 75 healthy individuals with no prior diagnosis of neurological disorders. EEG recordings were obtained during the resting state, as well as two motor control states (walking and working tasks), and a cognition state (reading task). Electrodes were placed in specific regions of the brain, including the frontal, central, temporal, and occipital lobes (Fz, C1, C2, T7, T8, Oz). Several ML models were trained using EEG data for activity recognition and LIME (Local Interpretable Model-Agnostic Explanations) was employed for interpreting clinically the most influential EEG spectral features in HAR models. The classification results of the HAR models, particularly the Random Forest and Gradient Boosting models, demonstrated outstanding performances in distinguishing the analyzed human activities. The ML models exhibited alignment with EEG spectral bands in the recognition of human activity, a finding supported by the XAI explanations. To sum up, incorporating eXplainable Artificial Intelligence (XAI) into Human Activity Recognition (HAR) studies may improve activity monitoring for patient recovery, motor imagery, the healthcare metaverse, and clinical virtual reality settings.

Effects of Audio Brain Entrainment on Korean People with Mild Insomnia.

Sleep health has become an important healthy lifestyle. Research has shown that almost one-fifth of the Korean adult population does not have sufficient sleep. The lack of sleep is associated with significant medical, psychological, social, and economic issues. People are not only yearning for sufficient sleep but the quality of sleep as well. Usually, the obvious choice will be the use of pharmaceuticals however, these often have various side effects, and the lasting use of these medications could become a concern. Therefore, new non-drug alternatives are sought after. Audio brain entrainment is a procedure that modules neural activities by synchronizing brainwave frequency with pulse tones. By producing frequency tones for the deep sleep stage, it promotes a good night's sleep. In this paper, we developed a pillow integrated with the audio speakers that produce alpha and theta beats that should help improve sleep. Sleep polysomnography was performed on 10 people to compare the effects of the audio stimulus. Initial results showed a positive effect on sleep onset latency, indicating that sleep induction happened. This noninvasive stimulation technique can be a promising candidate for wearable bioelectronics medicine and further neuroscience research.

The Anti-Atopic Dermatitis Effects of Mentha arvensis Essential Oil Are Involved in the Inhibition of the NLRP3 Inflammasome in DNCB-Challenged Atopic Dermatitis BALB/c Mice.

The NLRP3 inflammasome is upregulated by various agents, such as nuclear factor-kappa B (NF-κB), lipopolysaccharide (LPS), and adenosine triphosphate (ATP). The NLRP3 inflammasome facilitations the maturation of interleukin (IL)-1ß, a proinflammatory cytokine that is critically involved in the pathogenesis of atopic dermatitis (AD). Although the NLRP3 inflammasome clearly exacerbates AD symptoms such as erythema and pruritus, drugs for AD patients targeting the NLRP3 inflammasome are still lacking. Based on the previous findings that Mentha arvensis essential oil (MAEO) possesses strong anti-inflammatory and anti-AD properties through its inhibition of the ERK/NF-κB signaling pathway, we postulated that MAEO might be capable of modulating the NLRP3 inflammasome in AD. The aim of this research was to investigate whether MAEO affects the inhibition of NLRP3 inflammasome activation in murine bone marrow-derived macrophages (BMDMs) stimulated with LPS + ATP in vitro and in a murine model displaying AD-like symptoms induced by 2,4-dinitrochlorobenzene (DNCB) in vivo. We found that MAEO inhibited the expression of NLRP3 and caspase-1, leading to the suppression of NLRP3 inflammasome activation and IL-1ß production in BMDMs stimulated with LPS + ATP. In addition, MAEO exhibited efficacy in ameliorating AD symptoms in a murine model induced by DNCB, as indicated by the reduction in dermatitis score, ear thickness, transepidermal water loss (TEWL), epidermal thickness, and immunoglobulin E (IgE) levels. Furthermore, MAEO attenuated the recruitment of NLRP3-expressing macrophages and NLRP3 inflammasome activation in murine dorsal skin lesions induced by DNCB. Overall, we provide evidence for the anti-AD effects of MAEO via inhibition of NLRP3 inflammasome activation.

Safety Assessment of Starch Nanoparticles as an Emulsifier in Human Skin Cells, 3D Cultured Artificial Skin, and Human Skin.

Emulsion systems are widely used in various industries, including the cosmetic, pharmaceutical, and food industries, because they require emulsifiers to stabilize the inherently unstable contact between oil and water. Although emulsifiers are included in many products, excessive use of emulsifiers destroys skin barriers and causes contact dermatitis. Accordingly, the consumer demand for cosmetic products made from natural ingredients with biocompatibility and biodegradability has increased. Starch in the form of solid nanosized particles is considered an attractive emulsifier that forms and stabilizes Pickering emulsion. Chemical modification of nanosized starch via acid hydrolysis can effectively provide higher emulsion stability. However, typical acid hydrolysis limits the industrial application of starch due to its high time consumption and low recovery. In previous studies, the effects of starch nanoparticles (SNPs) prepared by treatment with acidic dry heat, which overcomes these limitations, on the formation and stability of Pickering emulsions were reported. In this study, we evaluated the safety of SNPs in skin cell lines, 3D cultured skin, and human skin. We found that the cytotoxicity of SNPs in both HaCaT cells and HDF cells could be controlled by neutralization. We also observed that SNPs did not induce structural abnormalities on 3D cultured skin and did not permeate across micropig skin tissue or human skin membranes. Furthermore, patches loaded with SNPs were found to belong in the "No irritation" category because they did not cause any irritation when placed on human skin. Overall, the study results suggest that SNPs can be used as a safe emulsifier in various industries, including in cosmetics.

Comparative safety of mRNA COVID-19 vaccines to influenza vaccines: A pharmacovigilance analysis using WHO international database.

Two messenger RNA (mRNA) vaccines developed by Pfizer-BioNTech and Moderna are being rolled out. Despite the high volume of emerging evidence regarding adverse events (AEs) associated with the COVID-19 mRNA vaccines, previous studies have thus far been largely based on the comparison between vaccinated and unvaccinated control, possibly highlighting the AE risks with COVID-19 mRNA vaccination. Comparing the safety profile of mRNA vaccinated individuals with otherwise vaccinated individuals would enable a more relevant assessment for the safety of mRNA vaccination. We designed a comparative safety study between 18 755 and 27 895 individuals who reported to VigiBase for adverse events following immunization (AEFI) with mRNA COVID-19 and influenza vaccines, respectively, from January 1, 2020, to January 17, 2021. We employed disproportionality analysis to rapidly detect relevant safety signals and compared comparative risks of a diverse span of AEFIs for the vaccines. The safety profile of novel mRNA vaccines was divergent from that of influenza vaccines. The overall pattern suggested that systematic reactions like chill, myalgia, fatigue were more noticeable with the mRNA COVID-19 vaccine, while injection site reactogenicity events were more prevalent with the influenza vaccine. Compared to the influenza vaccine, mRNA COVID-19 vaccines demonstrated a significantly higher risk for a few manageable cardiovascular complications, such as hypertensive crisis (adjusted reporting odds ratio [ROR], 12.72; 95% confidence interval [CI], 2.47-65.54), and supraventricular tachycardia (adjusted ROR, 7.94; 95% CI, 2.62-24.00), but lower risk of neurological complications such as syncope, neuralgia, loss of consciousness, Guillain-Barre syndrome, gait disturbance, visual impairment, and dyskinesia. This study has not identified significant safety concerns regarding mRNA vaccination in real-world settings. The overall safety profile patterned a lower risk of serious AEFI following mRNA vaccines compared to influenza vaccines.

Association between joint effusions and concomitant structural injuries (tendinitis and structural injury) on MRI in ankle trauma without fracture.

BACKGROUND: The evaluation of correlations among joint effusion, ligament injuries, tenosynovitis and osteochondral lesion of talus (OLT) in the ankle joint is important for developing a treatment plan and predicting prognosis. PURPOSE: To evaluate correlations among tibiotalar (anterior) and talocalcaneal (posterior) joint effusion, tenosynovitis of major flexor tendons, ligaments, and OLT in a group of patients with ankle trauma. MATERIAL AND METHODS: This retrospective study included 101 patients with ankle trauma who underwent magnetic resonance imaging. Two radiologists assessed the presence and amount of effusion in the tibiotalar and talocalcaneal joints from grade 0 to 2, according to the amount of capsular distension. Concomitant structural injuries were assessed in the tibialis posterior (TP), flexor digitorum longus, flexor hallucis longus, and peroneus tendons, and the anterior talofibular ligament, calcaneofibular ligament, anteroinferior tibiofibular ligament, posteroinferior tibiofibular ligament, and OLT. RESULTS: The proportion of anterior and posterior joint effusion according to grade was 67.3% for anterior joint effusion grade 0, 22.8% for grade 1, and 9.9% for grade 2; for posterior joint effusion, grade 0 was 74.2%, grade 1 was 22.8%, and grade 2 was 3.0%. We found statistically significant correlations between posterior joint effusion and tenosynovitis of TP (P < 0.05) and between posterior joint effusion and OLT (P < 0.05). CONCLUSION: Posterior joint effusion is correlated with TP injury and OLT; however, tendon injuries have no correlation with other structural injuries of the ankle joint in a general population with ankle trauma.

Self-Injurious Behavior Rate in the Short-Term Period of the COVID-19 Pandemic in Korea.

BACKGROUND: The objective of this study was to investigate the trend of self-injurious behavior (SIB) among persons who were directly impacted by coronavirus disease 2019 (COVID-19), especially those with pre-existing mental disorders. METHODS: Using the National Health Insurance Service-COVID-19 database cohort, the monthly SIB rate was calculated by COVID-19 subgroups (i.e., positive for COVID-19 test, negative for COVID-19 test, and non-COVID-19 test [control]). In addition, moderated regression analysis was utilized to examine the statistical difference of SIB (suicide attempt and non-suicidal self-injury using ICD-10 code) trend between COVID-19 subgroups and with and without pre-existing mental disorder. RESULTS: A total of 328,373 persons were included in the cohort study. Of these, 212,678 had been tested for COVID-19, and 7,713 of them were confirmed positive. During the pandemic peak, the "negative for COVID-19" group showed a large increase (P = 0.003) in SIB rates compared to the control group, the "positive for COVID-19" group showed a decreasing trend, but not significant (P = 0.314). Among those who were tested for COVID-19, those with pre-existing mental disorders showed an increasing trend of SIB compared to those without pre-existing mental disorders, however statistically insignificant (P = 0.137). CONCLUSION: Our results suggest that people who are tested for COVID-19 are at a high risk of SIB during the peak COVID-19 pandemic. Therefore, screening for suicide risk and psychological interventions is needed for these high-risk groups.

Effectiveness of Online Video Instruction on Time to Start Ambulation and Duration of Hospital Stay, Satisfaction and Functional Recovery in Patients Undergoing Total Hip Arthroplasty.

BACKGROUND: At the end of 2014, we implemented an online video to inform patients of the entire process from admission to rehabilitation after total hip arthroplasty (THA). In this study, we investigated the effectiveness of online video instruction in THA patients. METHODS: Electronic medical records of 184 patients undergoing THA in 2014 (pre-video group) and 182 patients in 2015 (post-video group) were reviewed. We compared 1) the time to start wheelchair ambulation, 2) walker or crutch ambulation, 3) the length of hospital stay, 4) postoperative satisfaction using visual analogue scale (0-10 points), and 5) modified Harris Hip Score (mHHS) at postoperative 6 weeks. RESULTS: In the post-video group, the time to start wheelchair ambulation (1.8 ± 0.6 vs. 2.4 ± 3.2 days, P = 0.021) and walker/crutch ambulation were faster (2.9 ± 1.2 vs. 3.8 ± 1.0 days, P = 0.016), and the hospital stay was shorter (8.2 ± 4.7 vs. 9.9 ± 7.8 days, P = 0.001) compared to the pre-video group. The visual analogue scale for satisfaction (7.84 ± 1.62 vs. 7.68 ± 1.85 points) and mHHS (89.59 ± 9.47 vs. 89.58 ± 8.59) were similar. CONCLUSION: Online video instruction is an effective tool to expedite ambulation and reduce the hospital stay without compromising the clinical outcome and postoperative complications after THA.

Explainable Artificial Intelligence Model for Stroke Prediction Using EEG Signal.

State-of-the-art healthcare technologies are incorporating advanced Artificial Intelligence (AI) models, allowing for rapid and easy disease diagnosis. However, most AI models are considered "black boxes," because there is no explanation for the decisions made by these models. Users may find it challenging to comprehend and interpret the results. Explainable AI (XAI) can explain the machine learning (ML) outputs and contribution of features in disease prediction models. Electroencephalography (EEG) is a potential predictive tool for understanding cortical impairment caused by an ischemic stroke and can be utilized for acute stroke prediction, neurologic prognosis, and post-stroke treatment. This study aims to utilize ML models to classify the ischemic stroke group and the healthy control group for acute stroke prediction in active states. Moreover, XAI tools (Eli5 and LIME) were utilized to explain the behavior of the model and determine the significant features that contribute to stroke prediction models. In this work, we studied 48 patients admitted to a hospital with acute ischemic stroke and 75 healthy adults who had no history of identified other neurological illnesses. EEG was obtained within three months following the onset of ischemic stroke symptoms using frontal, central, temporal, and occipital cortical electrodes (Fz, C1, T7, Oz). EEG data were collected in an active state (walking, working, and reading tasks). In the results of the ML approach, the Adaptive Gradient Boosting models showed around 80% accuracy for the classification of the control group and the stroke group. Eli5 and LIME were utilized to explain the behavior of the stroke prediction model and interpret the model locally around the prediction. The Eli5 and LIME interpretable models emphasized the spectral delta and theta features as local contributors to stroke prediction. From the findings of this explainable AI research, it is expected that the stroke-prediction XAI model will help with post-stroke treatment and recovery, as well as help healthcare professionals, make their diagnostic decisions more explainable.

Distribution and outliers of anteversion of short-length cementless stem.

INTRODUCTION: Inadequate stem version might lead to impingement and instability after cementless total hip arthroplasty (THA). We evaluated (1) the distribution of short-stem anteversion, (2) the proportion of stems with an anteversion less than 5° or larger than 25°, (3) combined cup and stem anteversion, and (4) dislocation rate. MATERIALS AND METHODS: We evaluated the native femoral anteversion and stem anteversion in 340 patients (340 THAs): 144 men and 196 women. Their mean age was 56.2 (22-87) years and mean body mass index was 25.1 (15.2-40.7) kg/m2. The femoral neck anteversion was measured on pre-operative CT scan and the stem anteversion was obtained during the operation. The safe zone of the stem anteversion was defined as 5 to 25°. RESULTS: The femoral neck anteversion ranged from -15 to 61° (mean, 15.0°; SD, ±10.6°). The stem anteversion ranged -7 to 50° (mean, 15.7°; SD, ±9.5°). It was optimal (5-25°) in 71.2% (242/340), insufficient (<5°) in 13.3% (45/340), and excessive (>25°) in 15.6% (53/340). The stem anteversion had a medium correlation with the femoral neck anteversion (correlation coefficient = 0.449). The combined anteversion was 42.0° (range, 35.2-52.3°; SD, ±2.8°). During two to four year follow-up, no hip dislocated. CONCLUSIONS: Short-length stem had a great variability in the anteversion and considerable portion (28.9%, 98/340) of stems had an anteversion outside the safe zone. Surgeons should be aware of this variability of stem anteversion to compensate for abnormal stem anteversion, which might lead to impingement and instability after THA.

Genetic Polymorphism of PTPN22 in Autoimmune Diseases: A Comprehensive Review.

It is known that the etiology and clinical outcomes of autoimmune diseases are associated with a combination of genetic and environmental factors. In the case of the genetic factor, the SNPs of the PTPN22 gene have shown strong associations with several diseases. The recent exploding numbers of genetic studies have made it possible to find these associations rapidly, and a variety of autoimmune diseases were found to be associated with PTPN22 polymorphisms. Proteins encoded by PTPN22 play a key role in the adaptative and immune systems by regulating both T and B cells. Gene variants, particularly SNPs, have been shown to significantly disrupt several immune functions. In this review, we summarize the mechanism of how PTPN22 and its genetic variants are involved in the pathophysiology of autoimmune diseases. In addition, we sum up the findings of studies reporting the genetic association of PTPN22 with different types of diseases, including type 1 diabetes mellitus, systemic lupus erythematosus, juvenile idiopathic arthritis, and several other diseases. By understanding these findings comprehensively, we can explain the complex etiology of autoimmunity and help to determine the criteria of disease diagnosis and prognosis, as well as medication developments.

Non-viral, direct neuronal reprogramming from human fibroblast using a polymer-functionalized nanodot.

Among various strategies to treat neurodegenerative disorders, cell replacement therapies have drawn much attention recently. Such a trend led to the increase in demand for the rare and specialized cells, followed by the outburst development of various cell reprogramming strategies. However, several limitations on these conventional methods remain to be solved, including the genetic instability of the viral vectors and the high cytotoxicity or poor performance of the non-viral carriers. Therefore, non-viral methods need to be developed to ensure safe and efficient cell reprogramming. Here, we introduce a polymer-modified nano-reagent (Polymer-functionalized Nanodot, PolyN) for the safe and efficient, non-viral direct cell reprogramming. PolyN facilitated the highly efficient contemporary overexpression of the transgene compared to the conventional reagent. With our nano-reagent, we demonstrated the SOX2-mediated cell reprogramming and successfully generated the neuron-like cell from the human fibroblast.

Increased Expression of S100B and RAGE in a Mouse Model of Bile Duct Ligation-induced Liver Fibrosis.

BACKGROUND: Liver fibrosis is defined as the accumulation of the extracellular matrix and scar formation. The receptor for advanced glycation end products (RAGE) has been demonstrated to participate in fibrogenesis. S100B is a ligand of RAGE and exerts extracellular functions by inducing a series of signal transduction cascades. However, the involvement of S100B and RAGE in cholestasis-induced liver fibrosis remains unclear. In this study, we investigated S100B and RAGE expression during liver fibrosis in mice that underwent common bile duct ligation (BDL). METHODS: BDL was performed in 10-week-old male C57BL/6J mice with sham control (n = 26) and BDL (n = 26) groups. Expression levels of S100B, RAGE and fibrotic markers in the livers from both groups at week 1 and 3 after BDL were examined by western blot and quantitative real-time reverse transcription polymerase chain reaction analysis. Liver fibrotic changes were examined by histological and ultrastructural analysis. RESULTS: Histological staining with Sirius Red and the evaluation of the messenger RNA expression of fibrotic markers showed noticeable periportal fibrosis and bile duct proliferation. S100B was mainly present in bile duct epithelial cells, and its expression was upregulated in proportion to the ductular reaction during fibrogenesis by BDL. RAGE expression was also increased, and interestingly, triple immunofluorescence staining and transmission electron microscopy showed that both S100B and RAGE were expressed in proliferating bile duct epithelial cells and activated hepatic stellate cells (HSCs) of the BDL livers. In addition, in rat HSCs (HSC-T6), treatment with recombinant S100B protein significantly increased fibrotic markers in a dose-dependent manner, and RAGE small interfering RNA (siRNA) suppressed S100B-stimulated upregulation of fibrotic markers compared with cells treated with scramble siRNA and S100B. CONCLUSION: These findings suggest that the increased expression of S100B and RAGE and the interaction between S100B and RAGE may play an important role in ductular reaction and liver fibrosis induced by BDL.

Prediction of Myoelectric Biomarkers in Post-Stroke Gait.

Electromyography (EMG) is sensitive to neuromuscular changes resulting from ischemic stroke and is considered a potential predictive tool of post-stroke gait and rehabilitation management. This study aimed to evaluate the potential myoelectric biomarkers for the classification of stroke-impaired muscular activity of the stroke patient group and the muscular activity of the control healthy adult group. We also proposed an EMG-based gait monitoring system consisting of a portable EMG device, cloud-based data processing, data analytics, and a health advisor service. This system was investigated with 48 stroke patients (mean age 70.6 years, 65% male) admitted into the emergency unit of a hospital and 75 healthy elderly volunteers (mean age 76.3 years, 32% male). EMG was recorded during walking using the portable device at two muscle positions: the bicep femoris muscle and the lateral gastrocnemius muscle of both lower limbs. The statistical result showed that the mean power frequency (MNF), median power frequency (MDF), peak power frequency (PKF), and mean power (MNP) of the stroke group differed significantly from those of the healthy control group. In the machine learning analysis, the neural network model showed the highest classification performance (precision: 88%, specificity: 89%, accuracy: 80%) using the training dataset and highest classification performance (precision: 72%, specificity: 74%, accuracy: 65%) using the testing dataset. This study will be helpful to understand stroke-impaired gait changes and decide post-stroke rehabilitation.

Driving-Induced Neurological Biomarkers in an Advanced Driver-Assistance System.

Physiological signals are immediate and sensitive to neurological changes resulting from the mental workload induced by various driving environments and are considered a quantifying tool for understanding the association between neurological outcomes and driving cognitive workloads. Neurological assessment, outside of a highly-equipped clinical setting, requires an ambulatory electroencephalography (EEG) headset. This study aimed to quantify neurological biomarkers during a resting state and two different scenarios of driving states in a virtual driving environment. We investigated the neurological responses of seventeen healthy male drivers. EEG data were measured in an initial resting state, city-roadways driving state, and expressway driving state using a portable EEG headset in a driving simulator. During the experiment, the participants drove while experiencing cognitive workloads due to various driving environments, such as road traffic conditions, lane changes of surrounding vehicles, the speed limit, etc. The power of the beta and gamma bands decreased, and the power of the delta waves, theta, and frontal theta asymmetry increased in the driving state relative to the resting state. Delta-alpha ratio (DAR) and delta-theta ratio (DTR) showed a strong correlation with a resting state, city-roadways driving state, and expressway driving state. Binary machine-learning (ML) classification models showed a near-perfect accuracy between the resting state and driving state. Moderate classification performances were observed between the resting state, city-roadways state, and expressway state in multi-class classification. An EEG-based neurological state prediction approach may be utilized in an advanced driver-assistance system (ADAS).