Comparative analysis of salivary cortisol measurements using different assay methods in relation to serum-free cortisol measurement.

Objectives: Salivary cortisol reflects the biologically active form of serum cortisol, offering a noninvasive evaluation method for the diurnal rhythm of the hypothalamic-pituitary-adrenal (HPA) axis. While liquid chromatography-tandem mass spectrometry (LC-MS/MS) is known for its specificity, immunoassays (IA) are commonly used because of their simplicity. This study aimed to assess the performance of salivary cortisol measurement using both IA and LC-MS/MS in comparison to serum-free cortisol measurement. Methods: Assay results for 188 saliva and 94 serum samples from 47 participants were analyzed. Salivary samples collected at different time points were analyzed using IA and LC-MS/MS. Serum samples were analyzed for cortisol, cortisol-binding globulin, and free cortisol. The statistical analyses included correlations and method comparisons. Results: The diurnal salivary cortisol profiles exhibited a comparable circadian rhythm pattern; however, the concentrations measured using IA were consistently higher than those measured using LC-MS/MS. The correlation analysis revealed robust associations among salivary cortisol (IA), salivary cortisol (LC-MS/MS), and serum-free cortisol levels (LC-MS/MS). However, the method comparison revealed a systematic bias between IA and LC-MS/MS in salivary cortisol measurement. Conclusions: This study contributes to the ongoing debate on assay techniques by affirming the suitability of IA and LC-MS/MS for salivary cortisol measurement to assess dynamic changes in HPA axis activity. The identified systematic bias emphasizes the importance of selecting methods based on specific research or clinical requirements.

Novel ultrasonic technology for advanced oxidation processes of water treatment.

Textile wastewater accounts for a significant proportion of industrial wastewater worldwide. In particular, dye wastewater accounts for a large proportion and consists of non-degradable dyes, which are substances resistant to biodegradation. Methylene blue is a representative example of such non-degradable dyes. It is not biologically degraded and exhibits toxicity. Various methods for their decomposition are currently being studied. Advanced oxidation processes (AOPs), which generate highly reactive hydroxyl radicals that oxidize and degrade pollutants, have been actively studied. Particularly, the photocatalytic degradation method using TiO2 nanoparticles is one of the most actively studied fields; however, there are still concerns regarding the toxicity of nanoparticles. Research is currently being conducted on AOPs using the cavitation phenomenon of ultrasonic waves. However, achieving high efficiency using existing ultrasonic equipment is difficult. Therefore, in this study, we evaluated a new water treatment technology through AOPs using a focused ultrasonic system with a cylindrical piezoelectric ceramic structure. After determining the optimal conditions for degradation, the degradation process was evaluated as a useful tool for mitigating the toxicity of methylene blue. We found that, under the optimal conditions of 100 W intensity at a frequency of 400 kHz, this system is a helpful instrument for degradation and a new water treatment technology suitable for removing ecotoxicity and genotoxicity.

Exploratory Clinical Trial of a Depression Diagnostic Software That Integrates Stress Biomarkers and Composite Psychometrics.

OBJECTIVE: This study evaluated the clinical effectiveness of Minds.NAVI, a depression screening kit combining psychometric measures and stress hormone biomarkers, in a prospective clinical trial. The objective was to assess its potential as a depression screening tool and investigate the associations between psychological assessments, salivary hormone staging, and depression severity. METHODS: Thirty-five participants with major depressive disorder and 12 healthy controls (HCs) were included. The Minds.NAVI software, utilizing the PROtective and Vulnerable factors battEry Test (PROVE) and salivary cortisol/dehydroepiandrosterone (DHEA) analysis, was employed. The PROVE test is a comprehensive self-report questionnaire that assesses depressive symptoms, suicide risk, attachment style, adverse childhood experiences, mentalization capacity, and resilience. In addition, salivary cortisol and DHEA levels were measured to evaluate the functional stage of the hypothalamic-pituitary-adrenal (HPA) axis. RESULTS: Minds.NAVI exhibited 100% sensitivity, 91.7% specificity, and 97.9% accuracy in distinguishing depression from HCs within an exploratory small group. Salivary stress hormone phases showed changes with depression stage (p=0.030), and the proportion of patients with "adrenal exhaustion stage" was higher in the moderate/severe depression group (p=0.038). Protective/vulnerable factors differed significantly between controls and depressed groups (p<0.001). Cortisol awakening response inversely correlated with depressive symptom severity (r=-0.31, p=0.034). CONCLUSION: This study suggested possible clinical effectiveness of Minds.NAVI, a depression screening tool that integrates psychometric measures and stress hormone biomarkers. The findings support the potential association between depression, chronic stress, and HPA axis hyporesponsiveness.

Hepatoprotective Effect of Allium ochotense Extracts on Chronic Alcohol-Induced Fatty Liver and Hepatic Inflammation in C57BL/6 Mice.

This study was performed to investigate the protective effects of Allium ochotense on fatty liver and hepatitis in chronic alcohol-induced hepatotoxicity. The physiological compounds of a mixture of aqueous and 60% ethanol (2:8, w/w) extracts of A. ochotense (EA) were identified as kestose, raffinose, kaempferol and quercetin glucoside, and kaempferol di-glucoside by UPLC Q-TOF MSE. The EA regulated the levels of lipid metabolism-related biomarkers such as total cholesterol, triglyceride, low-density lipoprotein (LDL), and high-density lipoprotein (HDL)-cholesterol in serum. Also, EA ameliorated the levels of liver toxicity-related biomarkers such as glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT), and total bilirubin in serum. EA improved the antioxidant system by reducing malondialdehyde contents and increasing superoxide dismutase (SOD) levels and reduced glutathione content. EA improved the alcohol metabolizing enzymes such as alcohol dehydrogenase, acetaldehyde dehydrogenase, and cytochrome P450 2E1 (CYP2E1). Treatment with EA alleviated lipid accumulation-related protein expression by improving phosphorylation of AMP-activated protein kinase (p-AMPK) expression levels. Especially, EA reduced inflammatory response by regulating the toll-like receptor-4/nuclear factor kappa-light-chain-enhancer of activated B cells (TLR-4/NF-κB) signaling pathway. EA showed an anti-apoptotic effect by regulating the expression levels of B-cell lymphoma 2 (BCl-2), BCl-2-associated X protein (BAX), and caspase 3. Treatment with EA also ameliorated liver fibrosis via inhibition of transforming growth factor-beta 1/suppressor of mothers against decapentaplegic (TGF-ß1/Smad) pathway and alpha-smooth muscle actin (α-SMA). Therefore, these results suggest that EA might be a potential prophylactic agent for the treatment of alcoholic liver disease.

Preliminary Study of Novel Bio-Crypto Key Generation Using Clustering-Based Binarization of ECG Features.

In modern society, the popularity of wearable devices has highlighted the need for data security. Bio-crypto keys (bio-keys), especially in the context of wearable devices, are gaining attention as a next-generation security method. Despite the theoretical advantages of bio-keys, implementing such systems poses practical challenges due to their need for flexibility and convenience. Electrocardiograms (ECGs) have emerged as a potential solution to these issues but face hurdles due to intra-individual variability. This study aims to evaluate the possibility of a stable, flexible, and convenient-to-use bio-key using ECGs. We propose an approach that minimizes biosignal variability using normalization, clustering-based binarization, and the fuzzy extractor, enabling the generation of personalized seeds and offering ease of use. The proposed method achieved a maximum entropy of 0.99 and an authentication accuracy of 95%. This study evaluated various parameter combinations for generating effective bio-keys for personal authentication and proposed the optimal combination. Our research holds potential for security technologies applicable to wearable devices and healthcare systems.

InsightSleepNet: the interpretable and uncertainty-aware deep learning network for sleep staging using continuous Photoplethysmography.

BACKGROUND: This study was conducted to address the existing drawbacks of inconvenience and high costs associated with sleep monitoring. In this research, we performed sleep staging using continuous photoplethysmography (PPG) signals for sleep monitoring with wearable devices. Furthermore, our aim was to develop a more efficient sleep monitoring method by considering both the interpretability and uncertainty of the model's prediction results, with the goal of providing support to medical professionals in their decision-making process. METHOD: The developed 4-class sleep staging model based on continuous PPG data incorporates several key components: a local attention module, an InceptionTime module, a time-distributed dense layer, a temporal convolutional network (TCN), and a 1D convolutional network (CNN). This model prioritizes both interpretability and uncertainty estimation in its prediction results. The local attention module is introduced to provide insights into the impact of each epoch within the continuous PPG data. It achieves this by leveraging the TCN structure. To quantify the uncertainty of prediction results and facilitate selective predictions, an energy score estimation is employed. By enhancing both the performance and interpretability of the model and taking into consideration the reliability of its predictions, we developed the InsightSleepNet for accurate sleep staging. RESULT: InsightSleepNet was evaluated using three distinct datasets: MESA, CFS, and CAP. Initially, we assessed the model's classification performance both before and after applying an energy score threshold. We observed a significant improvement in the model's performance with the implementation of the energy score threshold. On the MESA dataset, prior to applying the energy score threshold, the accuracy was 84.2% with a Cohen's kappa of 0.742 and weighted F1 score of 0.842. After implementing the energy score threshold, the accuracy increased to a range of 84.8-86.1%, Cohen's kappa values ranged from 0.75 to 0.78 and weighted F1 scores ranged from 0.848 to 0.861. In the case of the CFS dataset, we also noted enhanced performance. Before the application of the energy score threshold, the accuracy stood at 80.6% with a Cohen's kappa of 0.72 and weighted F1 score of 0.808. After thresholding, the accuracy improved to a range of 81.9-85.6%, Cohen's kappa values ranged from 0.74 to 0.79 and weighted F1 scores ranged from 0.821 to 0.857. Similarly, on the CAP dataset, the initial accuracy was 80.6%, accompanied by a Cohen's kappa of 0.73 and weighted F1 score was 0.805. Following the application of the threshold, the accuracy increased to a range of 81.4-84.3%, Cohen's kappa values ranged from 0.74 to 0.79 and weighted F1 scores ranged from 0.813 to 0.842. Additionally, by interpreting the model's predictions, we obtained results indicating a correlation between the peak of the PPG signal and sleep stage classification. CONCLUSION: InsightSleepNet is a 4-class sleep staging model that utilizes continuous PPG data, serves the purpose of continuous sleep monitoring with wearable devices. Beyond its primary function, it might facilitate in-depth sleep analysis by medical professionals and empower them with interpretability for intervention-based predictions. This capability can also support well-informed clinical decision-making, providing valuable insights and serving as a reliable second opinion in medical settings.

Central Nervous System Dissemination of Solitary Sporadic Supratentorial Hemangioblastoma: A Case Report and Literature Review.

We report a patient with whole neuroaxis dissemination of a sporadic supratentorial hemangioblastoma (HB) for more than 15 years. A 68-year-old female patient presented with severe radiating pain in the right leg. Gadolinium-enhanced lumbar spine MRI showed an intradural mass (2.5 cm in diameter) at the L4 level. The patient had been severely disabled for 22 years after a previous intraventricular brain tumor resection. At that time, the diagnosis was angioblastic meningioma, which was thought to be incorrect. At 14 years after the brain surgery, gamma knife radiosurgery was performed three times for newly developed or recurred supratentorial and infratentorial tumors in the cerebrospinal fluid pathway. The patient underwent lumbar spinal surgery, and a gross total removal of the mass was performed, which confirmed the histopathological diagnosis of HB. We reexamined the old histopathological specimen of the intraventricular tumor from 20 years ago and changed the diagnosis from angioblastic meningioma to supratentorial HB. Six months after spinal surgery, the patient underwent a second spinal surgery and brain surgery, and the histopathological diagnosis was HB following both surgeries, which was the same following the first spinal surgery. Here, we report a sporadic supratentorial HB patient who showed cranial and spinal disseminations for more than two decades along with a literature review.

Gamma knife radiosurgery as primary management for intracranial meningioma identified as growing on serial imaging.

Gamma knife radiosurgery (GKRS) has emerged as a highly effective therapeutic modality for the management of intracranial meningiomas. However, the role of GKRS in treating growing meningiomas detected during active surveillance remains unclear. This study seeks to investigate the long-term outcomes of GKRS treatment for growing meningiomas. A retrospective analysis was conducted on patients who underwent GKRS as the primary treatment for growing meningiomas between 2004 and 2021. Growing meningiomas were defined as those exhibiting a > 10% increase in tumor volume (TV) compared to the previous imaging. Fifty-nine patients who received GKRS as their initial treatment were included, with a minimum follow-up period of 12 months. Comprehensive clinical, radiological, and procedural data were analyzed. Serial TV assessments were performed for all tumors before and after GKRS. Tumor progression and regression were defined as a > 10% increase or decrease in TV, respectively, compared to the pretreatment image. At a median follow-up of 41 months (range 15-197 months), TV was unchanged in 16 patients (27.1%), decreased in 41 patients (69.5%), and increased in 2 patients (3.4%). Multivariate analysis revealed that both TV (cm3) (hazard ratio [HR], 1.107; 95% confidence interval [CI], 1.002-1.222; P = .045) and volume growing rate (%/yr) (HR, 1.013; 95% CI, 1.000-1.025; P = .04) significantly correlated with tumor progression. Eleven patients (18.6%) experienced new or worsening symptoms. In multivariate analysis, factor predicting new or worsening neurological function was preexisting calcification (HR, 5.297; 95% CI, 1.328-21.124; P = .018). GKRS demonstrates a promising level of tumor control with minimal risk of neurological deterioration when applied to growing meningiomas. These findings provide compelling support for considering GKRS as a valuable therapeutic option following an initial period of active surveillance for these tumors.

Effects of Game-Related Tasks for the Diagnosis and Classification of Gaming Disorder.

Gaming disorder (GD) is an addictive behavior characterized by an insatiable need to play video games and shares similar symptoms with the failure of self-control due to a decline in cognitive function. Current GD diagnostic and screening tools rely on questionnaires and behavioral observations related to cognitive functions to assess an individual's capacity to maintain self-control in everyday life. However, current GD screening approaches rely on subjective symptoms, and a reliable diagnosis requires long-term clinical follow-up. Recent studies have measured biosignals along with cognitive functional tasks to provide objectivity to GD diagnosis and to acquire immediate results. However, people with GD are hypersensitive to game-related cues, so their responses may vary depending on the type of stimuli, and the difference in response to stimuli might manifest as a difference in the degree of change in the biosignal. Therefore, it is critical to choose the correct stimulus type when performing GD diagnostic tasks. In this study, we investigated the task dependence of cognitive decline in GD by comparing two cognitive functional tasks: a continuous performance task (CPT) and video game play. For this study, 69 young male adults were classified into either the gaming disorder group (GD, n = 39) or a healthy control group (HC, n = 30). CPT score, EEG signal (theta, alpha, and beta), and HRV-HF power were assessed. We observed differences in the left frontal region (LF) of the brain between the GD and HC groups during online video game play. The GD group also showed a significant difference in HF power of HRV between CPT and online video gaming. Furthermore, LF and HRV-HF significantly correlated with Young's Internet Addiction Test (Y-IAT) score, which is positively associated with impulsivity score. The amount of change in theta band activity in LF and HRV-HF-both biomarkers for changes in cognitive function-during online video game play suggests that people with GD express task-dependent cognitive decline compared with HC. Our results demonstrate the feasibility of quantifying individual self-regulation ability for gaming and underscore its importance for GD classification.

Leksell Frame-Based Stereotactic Biopsy for Infratentorial Tumor : Practical Tips and Considerations.

The Leksell frame-based transcerebellar approach was proposed with the arc support frame attached upside down to the Z coordinate. This study presented practical tips and considerations for obtaining adequate tissue samples for deep-seated cerebellar lesions or lower brainstem lesions specifically those accessible via the cerebellar peduncle. For practical insights, the Leksell coordinate frame G was fixed to prevent the anterior screw implantation within the temporalis muscle, to avoid interference with the magnetic resonance (MR)-adapter, and taking into account the magnetic field of MR in close proximity to the tentorium. After mounting of indicator box, the MR imaging evaluation should cover both the indicator box and the infratentorial region that deviated from it. The coordinates [X, Y, Za, Arc0, Ringa0] obtained from Leksell SurgiPlan® software (Elekta, Stockholm, Sweden) with arc 00 located on the patient's right side were converted to [X, Y, Zb=360-Za, Arc0, Ringb0=Ringa0-1800]. The operation was performed in the prone position under general anesthesia in four patients with deep cerebellar (n=3) and brainstem (n=1) tumors. The biopsy results showed two cases of diffuse large B-cell lymphoma, one metastatic braintumor and one glioblastoma. One patient required frame repositioning as a complication. Drawing upon the methodology outlined in existing literature, we anticipate that imparting supplementary expertise could render the stereotactic biopsy of infratentorial tumors more consistent and manageable for the practitioner, thereby facilitating adequate tissue samples and minimizing patient complications.

Akt enhances the vulnerability of cancer cells to VCP/p97 inhibition-mediated paraptosis.

Valosin-containing protein (VCP)/p97, an AAA+ ATPase critical for maintaining proteostasis, emerges as a promising target for cancer therapy. This study reveals that targeting VCP selectively eliminates breast cancer cells while sparing non-transformed cells by inducing paraptosis, a non-apoptotic cell death mechanism characterized by endoplasmic reticulum and mitochondria dilation. Intriguingly, oncogenic HRas sensitizes non-transformed cells to VCP inhibition-mediated paraptosis. The susceptibility of cancer cells to VCP inhibition is attributed to the non-attenuation and recovery of protein synthesis under proteotoxic stress. Mechanistically, mTORC2/Akt activation and eIF3d-dependent translation contribute to translational rebound and amplification of proteotoxic stress. Furthermore, the ATF4/DDIT4 axis augments VCP inhibition-mediated paraptosis by activating Akt. Given that hyperactive Akt counteracts chemotherapeutic-induced apoptosis, VCP inhibition presents a promising therapeutic avenue to exploit Akt-associated vulnerabilities in cancer cells by triggering paraptosis while safeguarding normal cells.

Two-Day Fraction Gamma Knife Radiosurgery for Large Brain Metastasis.

Objective: We investigated how treating large brain metastasis (LBM) using two-day fraction gamma knife radiosurgery (GKRS) affects tumor control and patient survival. A prescription dose of 10.3 Gy was applied for two consecutive days, with a biologically effective dose (BED) equivalent to a tumor single-fraction dose of 16.05 Gy and a brain single-fraction dose of 15.12 Gy. Methods: Between November 2017 and December 2021, 42 patients (mean age: 68.3 years, range: 50-84 years, male: 29 [69.1%], female: 13 [30.9%]) with 44 tumors underwent two-day fraction GKRS to treat large volume brain metastasis. The main cancer types were non-small cell lung cancer (NSCLC, N=16), small cell lung cancer (SCLC, N=7), colorectal cancer (N=7), breast cancer (N=3), gastric cancer (N=2), and other cancers (N=7). Twenty-one (50.0%) patients had a single LBM, nineteen (46.3%) had a single LBM and other metastasi(e)s, and two had two (4.7%) large brain metastases. At the time of the two-day fraction GKRS, the tumors had a mean volume of 23.1 cc (range: 12.5-67.4). on each day, radiation was administered at a dose of 10.3 Gy, mainly using a 50% isodose-line. Results: We obtained clinical and magnetic resonance imaging (MRI) follow-up data for 34 patients (81%) with 35 tumors, who had undergone two-day fraction GKRS. These patients did not experience acute or late radiation-induced complications during follow-up. The median and mean progression-free survival (PFS) periods were 188 and 194 days, respectively. The local control rates at 6, 9, and 12 months were 77%, 40%, and 34%, respectively. The prognostic factors related to PFS were prior radiotherapy (P = 0.019) and lung cancer origin (P = 0.041). Other factors such as tumor volumes, each isodose volumes, and peri-GKRS systemic treatment were not significantly related to PFS. The overall survival period of the 44 patients following repeat SRS ranged from 15-878 days (median: 263±38 days, mean: 174±43) after the two-day fraction GKRS. Eight patients (18.2%) were still alive. Conclusion: Considering the unsatisfactory tumor control, a higher prescription dose should be needed in this procedure as a salvage management. Moreover, in the treatment for LBM with fractionated SRS, using different isodoses and prescription doses at the treatment planning for LBMs should be important. However, this report might be a basic reference with the same fraction number and prescription dose in the treatment for LBMs with frame-based SRS.

Severity identification for internet gaming disorder using heart rate variability reactivity for gaming cues: a deep learning approach.

Background: The diminished executive control along with cue-reactivity has been suggested to play an important role in addiction. Hear rate variability (HRV), which is related to the autonomic nervous system, is a useful biomarker that can reflect cognitive-emotional responses to stimuli. In this study, Internet gaming disorder (IGD) subjects' autonomic response to gaming-related cues was evaluated by measuring HRV changes in exposure to gaming situation. We investigated whether this HRV reactivity can significantly classify the categorical classification according to the severity of IGD. Methods: The present study included 70 subjects and classified them into 4 classes (normal, mild, moderate and severe) according to their IGD severity. We measured HRV for 5 min after the start of their preferred Internet game to reflect the autonomic response upon exposure to gaming. The neural parameters of deep learning model were trained using time-frequency parameters of HRV. Using the Class Activation Mapping (CAM) algorithm, we analyzed whether the deep learning model could predict the severity classification of IGD and which areas of the time-frequency series were mainly involved. Results: The trained deep learning model showed an accuracy of 95.10% and F-1 scores of 0.995 (normal), 0.994 (mild), 0.995 (moderate), and 0.999 (severe) for the four classes of IGD severity classification. As a result of checking the input of the deep learning model using the CAM algorithm, the high frequency (HF)-HRV was related to the severity classification of IGD. In the case of severe IGD, low frequency (LF)-HRV as well as HF-HRV were identified as regions of interest in the deep learning model. Conclusion: In a deep learning model using the time-frequency HRV data, a significant predictor of IGD severity classification was parasympathetic tone reactivity when exposed to gaming situations. The reactivity of the sympathetic tone for the gaming situation could predict only the severe group of IGD. This study suggests that the autonomic response to the game-related cues can reflect the addiction status to the game.

Strategy for dealing with unfamiliar and thick vessels during microvascular decompression: A first case report of hemifacial spasm caused by a persistent primitive trigeminal artery.

RATIONALE: A persistent primitive trigeminal artery (PPTA) is a rare embryonic cerebrovascular anomaly. Hemifacial spasm (HFS) refers to involuntary contractions of facial muscles caused by the compression of blood vessels against the root exit zone of the facial nerve. There have been no reported cases of PPTA causing neurovascular contact and HFS. Microvascular decompression surgery effectively treats HFS, but operating on strong PPTA vessels poses challenges. We aim to introduce a more efficient approach for overcomes these difficulties and facilitates surgery. PATIENT CONCERNS: A 44-year-old male patient without any underlying medical conditions presented to our hospital with involuntary movements of the left side of his face accompanied by numbness in the left maxilla (V2 area). DIAGNOSIS: Brain magnetic resonance imaging and magnetic resonance angiography showed that PPTA was in contact with the left facial nerve. INTERVENTIONS AND OUTCOMES: Following a retro-sigmoid craniotomy, we attempted to interpose the facial nerve and the PPTA as an offender vessel, but the decompression was not sufficient. However, after transposing the vessel using the proximal Teflon transposition with interposition technique, the strength of the involuntary movements was reduced. Following surgery, there was no more lateral spreading response, and the patient symptoms improved. LESSIONS: In cases where the vessel causing HFS is particularly strong and thick, the proximal Teflon transposition with interposition technique for transposition may be advantageous. This method could simplify and enhance the efficacy of microvascular decompression, without compromising the quality of surgical outcomes.

Women with Metabolic Syndrome and Unhealthy Lifestyle Factors Are at a Higher Risk for Hyperuricemia.

Hyperuricemia (HUA) has become a significant medical concern due to its complications and links to metabolic syndrome (MetS) and cardiovascular disease (CVD), which result in increased mortality. The pathogenic processes associated with unhealthy behaviors, MetS, and HUA can be cooperative and potentially synergistic in the activation of risk factors. Recent research has shown sex-based differences in the relationship between HUA and its associated risk factors. This study aimed to investigate these differences, particularly in the context of MetS and CVD risk factors and unhealthy lifestyles. We also aimed to evaluate the joint effects of these factors based on sex. We conducted a cross-sectional study using nationally representative survey data from the Korean National Health and Nutritional Examination Survey 2016-2018. We performed multivariable logistic regression analysis, calculating adjusted odds ratios (ORs) with their 95% confidence intervals (CIs). We also conducted subgroup analyses based on sex and the presence of MetS with or without unhealthy lifestyle factors (tobacco use, alcohol intake). We found sex-based differences in the relationships between HUA and MetS, CVD risk factors, and lifestyle behaviors. Our major finding was a significant association between MetS and HUA in both men and women, regardless of alcohol consumption and smoking status, and this association was stronger in women. We also observed a synergistic effect of MetS and lifestyle factors on the risk of HUA, particularly in women, in whom the risk of HUA increased up to four times compared to the reference group. A sex-based clinical strategy for HUA is necessary to reduce related complications and their socio-economic burden.

Quantitative analysis of pulse arrival time and PPG morphological features based cuffless blood pressure estimation: a comparative study between diabetic and non-diabetic groups.

Pulse arrival time (PAT) and PPG morphological features have attracted much interest in cuffless blood pressure (BP) estimation, but their effects are not clearly understood when vascular characteristics are affected by diseases such as diabetes. This work quantitatively analyzes the effect of diabetic disease on the PAT and PPG morphological features-based BP estimation. We selected 112 diabetic patients and 308 non-diabetic subjects from VitalDB, and extracted 16 features including PAT, PPG morphological features, and heart rate. BP estimation performance was statistically compared between groups using linear regression models with several feature sets, and the relative importance of each feature in the optimal feature set was extracted. As a result, the standard deviation of the error and mean absolute error of PAT-based BP estimation were significantly higher in the diabetic group than in the non-diabetic group (p < 0.01). A feature set containing PAT and PPG morphological features achieved the best performance in both groups. However, the relative importance of each feature for BP estimation differed notably between groups. The results indicate that different features are important depending on the vascular characteristics, which could help to construct different models to accommodate specific diseases.

SelANet: decision-assisting selective sleep apnea detection based on confidence score.

BACKGROUND: One of the most common sleep disorders is sleep apnea syndrome. To diagnose sleep apnea syndrome, polysomnography is typically used, but it has limitations in terms of labor, cost, and time. Therefore, studies have been conducted to develop automated detection algorithms using limited biological signals that can be more easily diagnosed. However, the lack of information from limited signals can result in uncertainty from artificial intelligence judgments. Therefore, we performed selective prediction by using estimated respiratory signals from electrocardiogram and oxygen saturation signals based on confidence scores to classify only those sleep apnea occurrence samples with high confidence. In addition, for samples with high uncertainty, this algorithm rejected them, providing a second opinion to the clinician. METHOD: Our developed model utilized polysomnography data from 994 subjects obtained from Massachusetts General Hospital. We performed feature extraction from the latent vector using the autoencoder. Then, one dimensional convolutional neural network-long short-term memory (1D CNN-LSTM) was designed and trained to measure confidence scores for input, with an additional selection function. We set a confidence score threshold called the target coverage and performed optimization only on samples with confidence scores higher than the target coverage. As a result, we demonstrated that the empirical coverage trained in the model converged to the target coverage. RESULT: To confirm whether the model has been optimized according to the objectives, the coverage violation was used to measure the difference between the target coverage and the empirical coverage. As a result, the value of coverage violation was found to be an average of 0.067. Based on the model, we evaluated the classification performance of sleep apnea and confirmed that it achieved 90.26% accuracy, 91.29% sensitivity, and 89.21% specificity. This represents an improvement of approximately 7.03% in all metrics compared to the performance achieved without using a selective prediction. CONCLUSION: This algorithm based on selective prediction utilizes confidence measurement method to minimize the problem caused by limited biological information. Based on this approach, this algorithm is applicable to wearable devices despite low signal quality and can be used as a simple detection method that determine the need for polysomnography or complement it.

In situ magnesiothermic reduction synthesis of a Ge@C composite for high-performance lithium-ion batterie anodes.

Metallothermic, especially magnesiothermic, solid-state reactions have been widely applied to synthesize various materials. However, further investigations regarding the use of this method for composite syntheses are needed because of the high reactivity of magnesium. Herein, we report an in situ magnesiothermic reduction to synthesize a composite of Ge@C as an anode material for lithium-ion batteries. The obtained electrode delivered a specific capacity of 454.2 mAh·g-1 after 200 cycles at a specific current of 1000 mA·g-1. The stable electrochemical performance and good rate performance of the electrode (432.3 mAh·g-1 at a specific current of 5000 mA·g-1) are attributed to the enhancement in distribution and chemical contact between Ge nanoparticles and the biomass-based carbon matrix. A comparison with other synthesis routes has been conducted to demonstrate the effectiveness of contact formation during in situ synthesis.

Exploring Autonomic Alterations during Seizures in Temporal Lobe Epilepsy: Insights from a Heart-Rate Variability Analysis.

Epilepsy's impact on cardiovascular function and autonomic regulation, including heart-rate variability, is complex and may contribute to sudden unexpected death in epilepsy (SUDEP). Lateralization of autonomic control in the brain remains the subject of debate; nevertheless, ultra-short-term heart-rate variability (HRV) analysis is a useful tool for understanding the pathophysiology of autonomic dysfunction in epilepsy patients. A retrospective study reviewed medical records of patients with temporal lobe epilepsy who underwent presurgical evaluations. Data from 75 patients were analyzed and HRV indices were extracted from electrocardiogram recordings of preictal, ictal, and postictal intervals. Various HRV indices were calculated, including time domain, frequency domain, and nonlinear indices, to assess autonomic function during different seizure intervals. The study found significant differences in HRV indices based on hemispheric laterality, language dominancy, hippocampal atrophy, amygdala enlargement, sustained theta activity, and seizure frequency. HRV indices such as the root mean square of successive differences between heartbeats, pNN50, normalized low-frequency, normalized high-frequency, and the low-frequency/high-frequency ratio exhibited significant differences during the ictal period. Language dominancy, hippocampal atrophy, amygdala enlargement, and sustained theta activity were also found to affect HRV. Seizure frequency was correlated with HRV indices, suggesting a potential relationship with the risk of SUDEP.

Intracranial Efficacy of Systemic Therapy in Patients with Asymptomatic Brain Metastases from Lung Cancer.

There has been controversy over whether to radiologically follow up or use local treatment for asymptomatic small-sized brain metastases from primary lung cancer. For brain tumors without local treatment, we evaluated potential factors related to the brain progression and whether systemic therapy controlled the tumor. We analyzed 96 patients with asymptomatic small-sized metastatic brain tumors from lung cancer. These underwent a radiologic follow-up every 2 or 3 months without local treatment of brain metastases. The pathologies of the tumors were adenocarcinoma (n = 74), squamous cell carcinoma (n = 11), and small cell carcinoma (n = 11). The primary lung cancer was treated with cytotoxic chemotherapy (n = 57) and targeted therapy (n = 39). Patients who received targeted therapy were divided into first generation (n = 23) and second or third generation (n = 16). The progression-free survival (PFS) of brain metastases and the overall survival (OS) of patients were analyzed depending on the age, tumor pathology, number, and location of brain metastases, the extent of other organ metastases, and chemotherapy regimens. The median PFS of brain metastases was 7.4 months (range, 1.1-48.3). Targeted therapy showed statistically significant PFS improvement compared to cytotoxic chemotherapy (p = 0.020). Especially, on univariate and multivariate analyses, the PFS in the second or third generation targeted therapy was more significantly improved compared to cytotoxic chemotherapy (hazard ratio 0.229; 95% confidence interval, 0.082-0.640; p = 0.005). The median OS of patients was 13.7 months (range, 2.0-65.0). Univariate and multivariate analyses revealed that the OS of patients was related to other organ metastases except for the brain (p = 0.010 and 0.020, respectively). Three out of 52 patients with brain recurrence showed leptomeningeal dissemination, while the recurrence patterns of brain metastases were mostly local and/or distant metastases (94.2%). Of the 52 patients who relapsed, 25 patients received local brain treatment. There was brain-related mortality in two patients (2.0%). The intracranial anti-tumor effect was superior to cytotoxic chemotherapy in the treatment of asymptomatic small-sized brain metastases with targeted therapy. Consequently, it becomes possible to determine the optimal timing for local brain treatment while conducting radiological follow-up for these tumors, which do not appear to increase brain-related mortality. Furthermore, this approach has the potential to reduce the number of cases requiring brain local treatment.