Temporal Muscle Thickness and Sarcopenia Components in Healthy Adults, Validated through Allgeun Diagnostic Tool.

Sarcopenia, characterized by progressive muscle loss and functional decline, poses significant risks, including falls, impaired daily activities, and increased mortality. We developed Allgeun, a novel device that measures handgrip strength, muscle mass, and physical performance. This study aimed to investigate whether temporal muscle thickness (TMT) could be used as a sarcopenia marker and to evaluate the usability of Allgeun. This prospective study enrolled 28 participants without medical or neurological disorders. They underwent three-dimensional T1-weighted imaging using a 3 Tesla magnetic resonance imaging scanner. TMT was measured based on T1-weighted images by a board-certified neuroradiologist. Allgeun was used to measure the following three key components of sarcopenia: muscle strength (handgrip strength), muscle mass (calf and thigh circumference), and physical performance (five times the chair stand test). Correlation analysis was conducted between TMT and the results of the handgrip strength, calf and thigh circumferences, and chair stand tests. There were moderate positive correlations between TMT and calf circumference (r = 0.413, p = 0.029), thigh circumference (r = 0.486, p = 0.008), and handgrip strength (r = 0.444, p = 0.018). However, no significant correlation was observed between TMT and physical performance (r = -0.000, p = 0.998). Our findings underscore TMT's potential as an indicator of sarcopenia, particularly regarding muscle mass and strength. Additionally, we demonstrated that the new device, Allgeun, is useful for screening and diagnosing the severity of sarcopenia.

Correlation of diffusion tensor tractography with obstructive sleep apnea severity.

INTRODUCTION: Using correlation tractography, this study aimed to find statistically significant correlations between white matter (WM) tracts in participants with obstructive sleep apnea (OSA) and OSA severity. We hypothesized that changes in certain WM tracts could be related to OSA severity. METHODS: We enrolled 40 participants with OSA who underwent diffusion tensor imaging (DTI) using a 3.0 Tesla MRI scanner. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and quantitative anisotropy (QA)-values were used in the connectometry analysis. The apnea-hypopnea index (AHI) is a representative measure of the severity of OSA. Diffusion MRI connectometry that was used to derive correlational tractography revealed changes in the values of FA, MD, AD, RD, and QA when correlated with the AHI. A false-discovery rate threshold of 0.05 was used to select tracts to conduct multiple corrections. RESULTS: Connectometry analysis revealed that the AHI in participants with OSA was negatively correlated with FA values in WM tracts that included the cingulum, corpus callosum, cerebellum, inferior longitudinal fasciculus, fornices, thalamic radiations, inferior fronto-occipital fasciculus, superior and posterior corticostriatal tracts, medial lemnisci, and arcuate fasciculus. However, there were no statistically significant results in the WM tracts, in which FA values were positively correlated with the AHI. In addition, connectometry analysis did not reveal statistically significant results in WM tracts, in which MD, AD, RD, and QA values were positively or negatively correlated with the AHI. CONCLUSION: Several WM tract changes were correlated with OSA severity. However, WM changes in OSA likely involve tissue edema and not neuronal changes, such as axonal loss. Connectometry analyses are valuable tools for detecting WM changes in sleep disorders.

Assessing Radiation Exposure and Contrast Agent Utilization: A Comparative Analysis of the Woven EndoBridge Device and Stent-Assisted Coil Embolization for Managing Unruptured Wide-Neck Bifurcation Aneurysms.

PURPOSE: In this study, we determined whether there were significant differences in procedure time, radiation dose, fluoroscopy time, and total contrast media dose when unruptured wideneck bifurcation aneurysms (WNBAs) were treated with the Woven EndoBridge (WEB) device and stent-assisted coil (SAC) embolization. MATERIALS AND METHODS: The WEB device and SAC embolization (14:17) were used to treat 31 cases of internal carotid artery bifurcation, anterior communicating artery, middle cerebral artery bifurcation, and basilar bifurcation aneurysms between August 2021 and December 2022. The procedure time, radiation dose, fluoroscopy time, and total contrast medium dose between the 2 treatment groups were compared and analyzed. In the WEB device group, the results between operators were compared, and the follow-up radiologic outcomes were investigated. RESULTS: The procedure and fluoroscopy times were significantly shorter in the WEB device group. Radiation and total contrast media dose were also significantly smaller in the WEB device, but there was no significant difference in results between operators. The follow-up radiological outcome showed adequate occlusion in 83.3% (10/12) of cases. CONCLUSION: The WEB device can be used as an alternative treatment method among the available endovascular treatment methods for WNBAs to reduce radiation exposure and the dose of contrast media when used adequately with appropriate indications.

Deep Learning Super-Resolution Technique Based on Magnetic Resonance Imaging for Application of Image-Guided Diagnosis and Surgery of Trigeminal Neuralgia.

This study aimed to implement a deep learning-based super-resolution (SR) technique that can assist in the diagnosis and surgery of trigeminal neuralgia (TN) using magnetic resonance imaging (MRI). Experimental methods applied SR to MRI data examined using five techniques, including T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), contrast-enhancement T1WI (CE-T1WI), T2WI turbo spin-echo series volume isotropic turbo spin-echo acquisition (VISTA), and proton density (PD), in patients diagnosed with TN. The image quality was evaluated using the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). High-quality reconstructed MRI images were assessed using the Leksell coordinate system in gamma knife radiosurgery (GKRS). The results showed that the PSNR and SSIM values achieved by SR were higher than those obtained by image postprocessing techniques, and the coordinates of the images reconstructed in the gamma plan showed no differences from those of the original images. Consequently, SR demonstrated remarkable effects in improving the image quality without discrepancies in the coordinate system, confirming its potential as a useful tool for the diagnosis and surgery of TN.

Alterations in the multilayer network in patients with rapid eye movement sleep behaviour disorder.

This study aimed to reveal the pathophysiology of isolated rapid eye movement sleep behaviour disorder (RBD) in patients using multilayer network analysis. Participants eligible for isolated RBD were included and verified via polysomnography. Both iRBD patients and healthy controls underwent brain MRI, including T1-weighted imaging and diffusion tensor imaging. Grey matter matrix was derived from T1-weighted images using a morphometric similarity network. White matter matrix was formed from diffusion tensor imaging-based structural connectivity. Multilayer network analysis of grey and white matter was performed using graph theory. We studied 29 isolated RBD patients and 30 healthy controls. Patients exhibited a higher average overlap degree (27.921 vs. 23.734, p = 0.002) and average multilayer clustering coefficient (0.474 vs. 0.413, p = 0.002) compared with controls. Additionally, several regions showed significant differences in the degree of overlap and multilayer clustering coefficient between patients with isolated RBD and healthy controls at the nodal level. The degree of overlap in the left medial orbitofrontal, left posterior cingulate, and right paracentral nodes and the multilayer clustering coefficients in the left lateral occipital, left rostral middle frontal, right fusiform, right inferior posterior parietal, and right parahippocampal nodes were higher in patients with isolated RBD than in healthy controls. We found alterations in the multilayer network at the global and nodal levels in patients with isolated RBD, and these changes may be associated with the pathophysiology of isolated RBD. Multilayer network analysis can be used widely to explore the mechanisms underlying various neurological disorders.

Integrated Stress Response Potentiates Ponatinib-Induced Cardiotoxicity.

BACKGROUND: Mitochondrial dysfunction is a primary driver of cardiac contractile failure; yet, the cross talk between mitochondrial energetics and signaling regulation remains obscure. Ponatinib, a tyrosine kinase inhibitor used to treat chronic myeloid leukemia, is among the most cardiotoxic tyrosine kinase inhibitors and causes mitochondrial dysfunction. Whether ponatinib-induced mitochondrial dysfunction triggers the integrated stress response (ISR) to induce ponatinib-induced cardiotoxicity remains to be determined. METHODS: Using human induced pluripotent stem cells-derived cardiomyocytes and a recently developed mouse model of ponatinib-induced cardiotoxicity, we performed proteomic analysis, molecular and biochemical assays to investigate the relationship between ponatinib-induced mitochondrial stress and ISR and their role in promoting ponatinib-induced cardiotoxicity. RESULTS: Proteomic analysis revealed that ponatinib activated the ISR in cardiac cells. We identified GCN2 (general control nonderepressible 2) as the eIF2α (eukaryotic translation initiation factor 2α) kinase responsible for relaying mitochondrial stress signals to trigger the primary ISR effector-ATF4 (activating transcription factor 4), upon ponatinib exposure. Mechanistically, ponatinib treatment exerted inhibitory effects on ATP synthase activity and reduced its expression levels resulting in ATP deficits. Perturbed mitochondrial function resulting in ATP deficits then acts as a trigger of GCN2-mediated ISR activation, effects that were negated by nicotinamide mononucleotide, an NAD+ precursor, supplementation. Genetic inhibition of ATP synthase also activated GCN2. Interestingly, we showed that the decreased abundance of ATP also facilitated direct binding of ponatinib to GCN2, unexpectedly causing its activation most likely because of a conformational change in its structure. Importantly, administering an ISR inhibitor protected human induced pluripotent stem cell-derived cardiomyocytes against ponatinib. Ponatinib-treated mice also exhibited reduced cardiac function, effects that were attenuated upon systemic ISRIB administration. Importantly, ISRIB does not affect the antitumor effects of ponatinib in vitro. CONCLUSIONS: Neutralizing ISR hyperactivation could prevent or reverse ponatinib-induced cardiotoxicity. The findings that compromised ATP production potentiates GCN2-mediated ISR activation have broad implications across various cardiac diseases. Our results also highlight an unanticipated role of ponatinib in causing direct activation of a kinase target despite its role as an ATP-competitive kinase inhibitor.

Structural variability of the cerebral cortex in schizophrenia and its association with clinical symptoms.

BACKGROUND: Substantial evidence indicates structural abnormalities in the cerebral cortex of patients with schizophrenia (SCZ), although their clinical implications remain unclear. Previous case-control studies have investigated group-level differences in structural abnormalities, although the study design cannot account for interindividual differences. Recent research has focused on the association between the heterogeneity of the cerebral cortex morphometric features and clinical heterogeneity. METHODS: We used neuroimaging data from 420 healthy controls and 695 patients with SCZ from seven studies. Four cerebral cortex measures were obtained: surface area, gray matter volume, thickness, and local gyrification index. We calculated the coefficient of variation (CV) and person-based similarity index (PBSI) scores and performed group comparisons. Associations between the PBSI scores and cognitive functions were evaluated using Spearman's rho test and normative modeling. RESULTS: Patients with SCZ had a greater CV of surface area and cortical thickness than those of healthy controls. All PBSI scores across cortical measures were lower in patients with SCZ than in HCs. In the patient group, the PBSI scores for gray matter volume and all cortical measures taken together positively correlated with the full-scale IQ scores. Patients with deviant PBSI scores for gray matter volume and all cortical measures taken together had lower full-scale IQ scores than those of other patients. CONCLUSIONS: The cerebral cortex in patients with SCZ showed greater regional and global structural variability than that in healthy controls. Patients with deviant similarity of cortical structural profiles exhibited a lower general intelligence than those exhibited by the other patients.

Microsurgical treatment of distal middle cerebral artery aneurysm: A single-center review.

OBJECTIVE: To review the characteristics of distal middle cerebral artery (MCA) aneurysm treated by microsurgery, the detailed surgical options, and the clinical result. METHODS: We retrospectively reviewed cerebral aneurysm in the M2 and M3 segments of the MCA surgically treated between January 2015 and December 2022. The demographic data, aneurysm-related findings, type of surgical approach, surgical technique, and clinical outcomes of the enrolled patients were analyzed. RESULTS: Sixteen distal MCA aneurysms were treated with microneurosurgery (incidence, 1.0%; female, 12; mean age, 58.1 years; ruptured, three). Twelve aneurysms were in the M2 segment (insular segment), two aneurysms at the M2-M3 junction, and two aneurysms in the M3 segment (opercular segment). Twelve aneurysms were saccular (average size, 4.9 mm; multiplicity, 50%; average aneurysms, 3.0; partially thrombosed, 1; sidewall aneurysm, 2). Three aneurysms were fusiform, of which two were ruptured. Of the ruptured aneurysms, one was a ruptured dissecting aneurysm. The trans-sylvian and trans-sulcal approaches were used in fourteen and two patients, respectively. Neck clipping, wrap clipping, and surgical trapping were performed in twelve, one, and one patient, respectively. Proximal occlusion was performed in one patient. Bypass technique was required in two patients (neck clipping and proximal occlusion). The modified Rankin Score was 6 in the two patients with ruptured aneurysms. The remaining patients did not show further neurological deterioration after microneurosurgery. CONCLUSIONS: Distal MCA aneurysms had a high incidence of being diagnosed with multiple other aneurysms and were relatively non-saccular.

The association of tonsillar microbiota with biochemical indices based on obesity and tonsillar hypertrophy in children.

The correlation between tonsil microbiome and tonsillar hypertrophy has not been well established. Given that oral dysbiosis is related to several metabolic diseases and that tonsillar hypertrophy leads to disordered breathing during sleep and obesity in children, it is necessary to investigate the relationship between the oral microbiome and tonsillar hypertrophy. After 16S rRNA amplicon sequencing of tonsillectomy samples, we evaluated the correlation between the tonsil microbiome and biochemical blood indices in pediatric patients who underwent tonsillectomy. Groups are classified into two categories: based on BMI, and grades 2, 3, and 4 based on tonsil size. Children with obesity and tonsillar hypertrophy have similar microbiome compositions and induce comparable changes in microbiome abundance and composition, confirming the association from a metagenomic perspective. In addition, obesity and tonsillar hypertrophy demonstrated a strong correlation with the Proteobacteria to Firmicutes (P/F) ratio, and among various biochemical indicators, alanine aminotransferase (ALT) levels increase with obesity and tonsillar hypertrophy, indicating a possible association of tonsil microbiome and liver metabolism. These novel findings demonstrate the significance of the tonsil microbiome and suggest the need for tonsil regulation, particularly during childhood.

MRI radiomics may predict early tumor recurrence in patients with sinonasal squamous cell carcinoma.

OBJECTIVES: Sinonasal squamous cell carcinoma (SCC) follows a poor prognosis with high tendency for local recurrence. We aimed to evaluate whether MRI radiomics can predict early local failure in sinonasal SCC. METHODS: Sixty-eight consecutive patients with node-negative sinonasal SCC (January 2005-December 2020) were enrolled, allocated to the training (n = 47) and test sets (n = 21). Early local failure, which occurred within 12 months of completion of initial treatment, was the primary endpoint. For clinical features (age, location, treatment modality, and clinical T stage), binary logistic regression analysis was performed. For 186 extracted radiomic features, different feature selections and classifiers were combined to create two prediction models: (1) a pure radiomics model; and (2) a combined model with clinical features and radiomics. The areas under the receiver operating characteristic curves (AUCs) were calculated and compared using DeLong's method. RESULTS: Early local failure occurred in 38.3% (18/47) and 23.8% (5/21) in the training and test sets, respectively. We identified several radiomic features which were strongly associated with early local failure. In the test set, both the best-performing radiomics model and the combined model (clinical + radiomic features) yielded higher AUCs compared to the clinical model (AUC, 0.838 vs. 0.438, p = 0.020; 0.850 vs. 0.438, p = 0.016, respectively). The performances of the best-performing radiomics model and the combined model did not differ significantly (AUC, 0.838 vs. 0.850, p = 0.904). CONCLUSION: MRI radiomics integrated with a machine learning classifier may predict early local failure in patients with sinonasal SCC. CLINICAL RELEVANCE STATEMENT: MRI radiomics intergrated with machine learning classifiers may predict early local failure in sinonasal squamous cell carcinomas more accurately than the clinical model. KEY POINTS: • A subset of radiomic features which showed significant association with early local failure in patients with sinonasal squamous cell carcinomas was identified. • MRI radiomics integrated with machine learning classifiers can predict early local failure with high accuracy, which was validated in the test set (area under the curve = 0.838). • The combined clinical and radiomics model yielded superior performance for early local failure prediction compared to that of the radiomics (area under the curve 0.850 vs. 0.838 in the test set), without a statistically significant difference.

E2F1 Mediates SOX17 Deficiency-Induced Pulmonary Hypertension.

BACKGROUND: Rare genetic variants and genetic variation at loci in an enhancer in SOX17 (SRY-box transcription factor 17) are identified in patients with idiopathic pulmonary arterial hypertension (PAH) and PAH with congenital heart disease. However, the exact role of genetic variants or mutations in SOX17 in PAH pathogenesis has not been reported. METHODS: SOX17 expression was evaluated in the lungs and pulmonary endothelial cells (ECs) of patients with idiopathic PAH. Mice with Tie2Cre-mediated Sox17 knockdown and EC-specific Sox17 deletion were generated to determine the role of SOX17 deficiency in the pathogenesis of PAH. Human pulmonary ECs were cultured to understand the role of SOX17 deficiency. Single-cell RNA sequencing, RNA-sequencing analysis, and luciferase assay were performed to understand the underlying molecular mechanisms of SOX17 deficiency-induced PAH. E2F1 (E2F transcription factor 1) inhibitor HLM006474 was used in EC-specific Sox17 mice. RESULTS: SOX17 expression was downregulated in the lung and pulmonary ECs from patients with idiopathic PAH. Mice with Tie2Cre-mediated Sox17 knockdown and EC-specific Sox17 deletion induced spontaneously mild pulmonary hypertension. Loss of endothelial Sox17 in EC exacerbated hypoxia-induced pulmonary hypertension in mice. Loss of SOX17 in lung ECs induced endothelial dysfunctions including upregulation of cell cycle programming, proliferative and antiapoptotic phenotypes, augmentation of paracrine effect on pulmonary arterial smooth muscle cells, impaired cellular junction, and BMP (bone morphogenetic protein) signaling. E2F1 signaling was shown to mediate the SOX17 deficiency-induced EC dysfunction. Pharmacological inhibition of E2F1 in Sox17 EC-deficient mice attenuated pulmonary hypertension development. CONCLUSIONS: Our study demonstrated that endothelial SOX17 deficiency induces pulmonary hypertension through E2F1. Thus, targeting E2F1 signaling represents a promising approach in patients with PAH.

Human Activity Prediction Based on Forecasted IMU Activity Signals by Sequence-to-Sequence Deep Neural Networks.

Human Activity Recognition (HAR) has gained significant attention due to its broad range of applications, such as healthcare, industrial work safety, activity assistance, and driver monitoring. Most prior HAR systems are based on recorded sensor data (i.e., past information) recognizing human activities. In fact, HAR works based on future sensor data to predict human activities are rare. Human Activity Prediction (HAP) can benefit in multiple applications, such as fall detection or exercise routines, to prevent injuries. This work presents a novel HAP system based on forecasted activity data of Inertial Measurement Units (IMU). Our HAP system consists of a deep learning forecaster of IMU activity signals and a deep learning classifier to recognize future activities. Our deep learning forecaster model is based on a Sequence-to-Sequence structure with attention and positional encoding layers. Then, a pre-trained deep learning Bi-LSTM classifier is used to classify future activities based on the forecasted IMU data. We have tested our HAP system for five daily activities with two tri-axial IMU sensors. The forecasted signals show an average correlation of 91.6% to the actual measured signals of the five activities. The proposed HAP system achieves an average accuracy of 97.96% in predicting future activities.

Modulation of lncRNA links endothelial glycocalyx to vascular dysfunction of tyrosine kinase inhibitor.

AIMS: Novel cancer therapies leading to increased survivorship of cancer patients have been negated by a concomitant rise in cancer therapies-related cardiovascular toxicities. Sunitinib, a first line multi-receptor tyrosine kinase inhibitor, has been reported to cause vascular dysfunction although the initiating mechanisms contributing to this side effect remain unknown. Long non-coding RNAs (lncRNAs) are emerging regulators of biological processes in endothelial cells (ECs); however, their roles in cancer therapies-related vascular toxicities remain underexplored. METHODS AND RESULTS: We performed lncRNA expression profiling to identify potential lncRNAs that are dysregulated in human-induced pluripotent stem cell-derived ECs (iPSC-ECs) treated with sunitinib. We show that the lncRNA hyaluronan synthase 2 antisense 1 (HAS2-AS1) is significantly diminished in sunitinib-treated iPSC-ECs. Sunitinib was found to down-regulate HAS2-AS1 by an epigenetic mechanism involving hypermethylation. Depletion of HAS2-AS1 recapitulated sunitinib-induced detrimental effects on iPSC-ECs, whereas CRISPR-mediated activation of HAS2-AS1 reversed sunitinib-induced dysfunction. We confirmed that HAS2-AS1 stabilizes the expression of its sense gene HAS2 via an RNA/mRNA heteroduplex formation. Knockdown of HAS2-AS1 led to reduced synthesis of hyaluronic acid (HA) and up-regulation of ADAMTS5, an enzyme involved in extracellular matrix degradation, resulting in disruption of the endothelial glycocalyx which is critical for ECs. In vivo, sunitinib-treated mice showed reduced coronary flow reserve, accompanied by a reduction in Has2os and degradation of the endothelial glycocalyx. Finally, we identified that treatment with high molecular-weight HA can prevent the deleterious effects of sunitinib both in vitro and in vivo by preserving the endothelial glycocalyx. CONCLUSIONS: Our findings highlight the importance of lncRNA-mediated regulation of the endothelial glycocalyx as an important determinant of sunitinib-induced vascular toxicity and reveal potential novel therapeutic avenues to attenuate sunitinib-induced vascular dysfunction.

Monitoring the Depth of Anesthesia Based on Phase-Amplitude Coupling of Near-Infrared Spectroscopy Signals.

Accurate monitoring of the depth of anesthesia (DOA) is essential to ensure the safety of the operation. In this study, a new index using near-infrared spectroscopy (NIRS) signal was proposed to assess the relationship between the DOA and cerebral hemodynamic variables. METHODS: Four cerebral hemodynamic variables of 15 patients were collected, including left, right, proximal, distal, oxygenated (HbO 2) and deoxygenated (Hb) hemoglobin concentration changes. The Phase-Amplitude coupling (PAC), an adaptation of cross-frequency coupling to reflect the modulation of the amplitude of high-frequency signals by the phase of low-frequency signals, was measured and the modulation index (MI) was obtained to monitor the DOA afterwards. Meanwhile, the BIS value based on electroencephalogram is also measured and compared. RESULTS: Compared with awake period, in anesthesia maintenance period, the PAC was strengthened. The analysis of receiver operating characteristic (ROC) curve showed that the MI, especially the MI of rp-HbO2, could effectively discriminate these two periods. Additionally, during the whole anesthesia process, the BIS value was statistically consistent with the MI of cerebral hemodynamic variables, and cerebral hemodynamic variables were immune from interference by clinical electric devices. CONCLUSION: The MI of cerebral hemodynamic variables was appropriate to be used as a new index to monitor the DOA. SIGNIFICANCE: This study is of great significance to the development of new modes of anesthesia monitoring and new decoding methods, and is expected to develop a high-performance anesthesia monitoring system.

E2F1 Mediates SOX17 Deficiency-Induced Pulmonary Hypertension.

Rationale: Rare genetic variants and genetic variation at loci in an enhancer in SRY-Box Transcription Factor 17 (SOX17) are identified in patients with idiopathic pulmonary arterial hypertension (PAH) and PAH with congenital heart disease. However, the exact role of genetic variants or mutation in SOX17 in PAH pathogenesis has not been reported. Objectives: To investigate the role of SOX17 deficiency in pulmonary hypertension (PH) development. Methods: Human lung tissue and endothelial cells (ECs) from IPAH patients were used to determine the expression of SOX17. Tie2Cre-mediated and EC-specific deletion of Sox17 mice were assessed for PH development. Single-cell RNA sequencing analysis, human lung ECs, and smooth muscle cell culture were performed to determine the role and mechanisms of SOX17 deficiency. A pharmacological approach was used in Sox17 deficiency mice for therapeutic implication. Measurement and Main Results: SOX17 expression was downregulated in the lungs and pulmonary ECs of IPAH patients. Mice with Tie2Cre mediated Sox17 knockdown and EC-specific Sox17 deletion developed spontaneously mild PH. Loss of endothelial Sox17 in EC exacerbated hypoxia-induced PH in mice. Loss of SOX17 in lung ECs induced endothelial dysfunctions including upregulation of cell cycle programming, proliferative and anti-apoptotic phenotypes, augmentation of paracrine effect on pulmonary arterial smooth muscle cells, impaired cellular junction, and BMP signaling. E2F Transcription Factor 1 (E2F1) signaling was shown to mediate the SOX17 deficiency-induced EC dysfunction and PH development. Conclusions: Our study demonstrated that endothelial SOX17 deficiency induces PH through E2F1 and targeting E2F1 signaling represents a promising approach in PAH patients.

E-cigarettes Induce Dysregulation of Autophagy Leading to Endothelial Dysfunction in Pulmonary Arterial Hypertension.

Given the increasing popularity of electronic cigarettes (e-cigs), it is imperative to evaluate the potential health risks of e-cigs, especially in users with preexisting health concerns such as pulmonary arterial hypertension (PAH). The aim of the present study was to investigate whether differential susceptibility exists between healthy and patients with PAH to e-cig exposure and the molecular mechanisms contributing to it. Patient-specific induced pluripotent stem cell-derived endothelial cells (iPSC-ECs) from healthy individuals and patients with PAH were used to investigate whether e-cig contributes to the pathophysiology of PAH and affects EC homeostasis in PAH. Our results showed that PAH iPSC-ECs showed a greater amount of damage than healthy iPSC-ECs upon e-cig exposure. Transcriptomic analyses revealed that differential expression of Akt3 may be responsible for increased autophagic flux impairment in PAH iPSC-ECs, which underlies increased susceptibility upon e-cig exposure. Moreover, knockdown of Akt3 in healthy iPSC-ECs significantly induced autophagic flux impairment and endothelial dysfunction, which further increased with e-cig treatment, thus mimicking the PAH cell phenotype after e-cig exposure. In addition, functional disruption of mTORC2 by knocking down Rictor in PAH iPSC-ECs caused autophagic flux impairment, which was mediated by downregulation of Akt3. Finally, pharmacological induction of autophagy via direct inhibition of mTORC1 and indirect activation of mTORC2 with rapamycin reverses e-cig-induced decreased Akt3 expression, endothelial dysfunction, autophagic flux impairment, and decreased cell viability, and migration in PAH iPSC-ECs. Taken together, these data suggest a potential link between autophagy and Akt3-mediated increased susceptibility to e-cig in PAH.

Development and validation of a deep learning model to diagnose COVID-19 using time-series heart rate values before the onset of symptoms.

One of the effective ways to minimize the spread of COVID-19 infection is to diagnose it as early as possible before the onset of symptoms. In addition, if the infection can be simply diagnosed using a smartwatch, the effectiveness of preventing the spread will be greatly increased. In this study, we aimed to develop a deep learning model to diagnose COVID-19 before the onset of symptoms using heart rate (HR) data obtained from a smartwatch. In the deep learning model for the diagnosis, we proposed a transformer model that learns HR variability patterns in presymptom by tracking relationships in sequential HR data. In the cross-validation (CV) results from the COVID-19 unvaccinated patients, our proposed deep learning model exhibited high accuracy metrics: sensitivity of 84.38%, specificity of 85.25%, accuracy of 84.85%, balanced accuracy of 84.81%, and area under the receiver operating characteristics (AUROC) of 0.8778. Furthermore, we validated our model using external multiple datasets including healthy subjects, COVID-19 patients, as well as vaccinated patients. In the external healthy subject group, our model also achieved high specificity of 77.80%. In the external COVID-19 unvaccinated patient group, our model also provided similar accuracy metrics to those from the CV: balanced accuracy of 87.23% and AUROC of 0.8897. In the COVID-19 vaccinated patients, the balanced accuracy and AUROC dropped by 66.67% and 0.8072, respectively. The first finding in this study is that our proposed deep learning model can simply and accurately diagnose COVID-19 patients using HRs obtained from a smartwatch before the onset of symptoms. The second finding is that the model trained from unvaccinated patients may provide less accurate diagnosis performance compared with the vaccinated patients. The last finding is that the model trained in a certain period of time may provide degraded diagnosis performances as the virus continues to mutate.

Effect of male age on reproductive function: A comparison of young and middle-aged men.

PURPOSE: There have been concerns regarding potential effects of older paternal age on male reproductive function. However, currently available data on this topic are insufficient and controversy exists. We analyzed semen characteristics and reproductive hormones in young men and middle-aged men to investigate the effect of age on male reproductive function. MATERIALS AND METHODS: This study examined healthy males of reproductive age who visited a single infertility center from January 2016 to July 2021. The young group consisted of men who were less than 35 years-old, and the middle-age group consisted of men who were more than 45 years-old. RESULTS: The two groups had no significant differences in sperm concentration ([89.9±59.4]×106/mL vs. [104.4±82.1]×106/mL, p=0.108) or sperm morphology (normal forms: 3.6%±1.5% vs. 3.4%±1.6%, p=0.131). However, the middle-age group had a smaller semen volume (3.2±1.5 mL vs. 2.5±1.4 mL, p<0.001), lower sperm motility (42.3%±9.8% vs. 31.2%±12.4%, p<0.001), lower progressive sperm motility (39.2%±10.3% vs. 28.4%±12.6%, p<0.001), and a higher serum follicle-stimulating hormone level. CONCLUSIONS: Our results suggest that advanced male age might have a negative effect on fertility potential, as in women. This finding has important clinical implications because more couples are choosing to have children when they are older. Further studies on this issue, especially those that examine reproductive outcome, are warranted.

Contrasting clinical characteristics and treatment patterns in women with newly diagnosed advanced-stage epithelial ovarian cancer in Australia, South Korea and Taiwan.

OBJECTIVE: The real-world INFORM study analyzed sociodemographics, treatment patterns and clinical outcomes for patients with newly diagnosed advanced epithelial ovarian cancer (EOC) in Australia, South Korea (S.Korea) and Taiwan preceding incorporation of poly(ADP-ribose) polymerase inhibitors into clinical practice. METHODS: Retrospective data from patients diagnosed with EOC (high-grade serous EOC for Taiwan) between January 2014 and December 2018 with ≥12 months follow-up from diagnosis were analyzed descriptively. Survival was evaluated by Kaplan-Meier with two-sided 95% confidence interval (CI). RESULTS: Of the 987 patients (Australia, 223; S.Korea, 513; Taiwan, 251), 98% received platinum-based chemotherapy (CT). In S.Korea and Taiwan 76.0% and 78.9% respectively underwent primary cytoreductive surgery; in Australia, 56.5% had interval debulking surgery. Bevacizumab was included in primary/maintenance therapy for 22.4%, 14.6% and 6.8% of patients in Australia, S.Korea and Taiwan, respectively. Patients receiving bevacizumab were high-risk (reimbursement policy) and achieved similar real-world progression-free survival (PFS) compared with CT only. Overall, the median real-world PFS (months; 95% CI) was similar across Australia (16.0 [14.63-18.08]), S.Korea (17.7 [16.18-19.27]) and Taiwan (19.1 [17.56-22.29]). CONCLUSION: This study reveals poor prognosis despite differences in demographics and treatment patterns for patients with EOC across Asia-Pacific suggesting the need for biomarker-driven novel therapies to improve outcomes.

Real-Time Human Activity Recognition with IMU and Encoder Sensors in Wearable Exoskeleton Robot via Deep Learning Networks.

Wearable exoskeleton robots have become a promising technology for supporting human motions in multiple tasks. Activity recognition in real-time provides useful information to enhance the robot's control assistance for daily tasks. This work implements a real-time activity recognition system based on the activity signals of an inertial measurement unit (IMU) and a pair of rotary encoders integrated into the exoskeleton robot. Five deep learning models have been trained and evaluated for activity recognition. As a result, a subset of optimized deep learning models was transferred to an edge device for real-time evaluation in a continuous action environment using eight common human tasks: stand, bend, crouch, walk, sit-down, sit-up, and ascend and descend stairs. These eight robot wearer's activities are recognized with an average accuracy of 97.35% in real-time tests, with an inference time under 10 ms and an overall latency of 0.506 s per recognition using the selected edge device.