PD-1/CD80+ small extracellular vesicles from immunocytes induce cold tumours featured with enhanced adaptive immunosuppression.

Only a minority of cancer patients benefit from immune checkpoint blockade therapy. Sophisticated cross-talk among different immune checkpoint pathways as well as interaction pattern of immune checkpoint molecules carried on circulating small extracellular vesicles (sEV) might contribute to the low response rate. Here we demonstrate that PD-1 and CD80 carried on immunocyte-derived sEVs (I-sEV) induce an adaptive redistribution of PD-L1 in tumour cells. The resulting decreased cell membrane PD-L1 expression and increased sEV PD-L1 secretion into the circulation contribute to systemic immunosuppression. PD-1/CD80+ I-sEVs also induce downregulation of adhesion- and antigen presentation-related molecules on tumour cells and impaired immune cell infiltration, thereby converting tumours to an immunologically cold phenotype. Moreover, synchronous analysis of multiple checkpoint molecules, including PD-1, CD80 and PD-L1, on circulating sEVs distinguishes clinical responders from those patients who poorly respond to anti-PD-1 treatment. Altogether, our study shows that sEVs carry multiple inhibitory immune checkpoints proteins, which form a potentially targetable adaptive loop to suppress antitumour immunity.

Dynamic monitoring and analysis of chlorophyll-a concentrations in global lakes using Sentinel-2 images in Google Earth Engine.

Remote estimation of Chlorophyll-a (Chl-a) has long been used to investigate the responses of aquatic ecosystems to global climate change. High-spatiotemporal-resolution Sentinel-2 satellite images make it possible to routinely monitor and trace the spatial distributions of lake Chl-a if reliable retrieval algorithms are available. In this study, Sentinel-2 images and in-situ measured data were used to develop a Chl-a retrieval algorithm based on 13 optical water types (OWTs) with a satisfying performance (R2 = 0.74, RMSE = 0.42 mg/m3, MAE = 0.33 mg/m3, and MAPE = 55.56 %). After removing the disturbance of algal blooms and other factors, the distribution of Chl-a in 3067 of the largest global lakes (≥50 km2) was mapped using the Google Earth Engine (GEE). From 2019 to 2021, the average Chl-a concentration was 16.95 ± 5.95 mg/m3 for the largest global lakes. During the COVID-19 pandemic, global lake-averaged Chl-a concentration reached its lowest value in 2020. From the perspective of spatial distribution, lakes with low Chl-a concentrations were mainly distributed in high-latitude, high-elevation, or economically underdeveloped areas. Among all the potential influencing factors, lake surface temperature had the largest contribution to Chl-a and showed a positive correlation with Chl-a in approximately 92.39 % of the lakes. Conversely, factors such as precipitation and tree cover area around the lake were negatively correlated with Chl-a concentration in nearly 61.44 % of the lakes.

Treatment of adult attention-deficit hyperactivity disorder (ADHD) with transcranial direct current stimulation (tDCS): study protocol for a parallel, randomized, double-blinded, sham-controlled, multicenter trial (Stim-ADHD).

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation treatment used as an alternative or complementary treatment for various neuropsychiatric disorders, and could be an alternative or add-on therapy to psychostimulants in attention-deficit hyperactivity disorder (ADHD). Previous studies provided some evidence for improvements in cognition and clinical symptoms in pediatric and adult ADHD patients. However, data from multi-center randomized controlled trials (RCTs) for this condition are lacking. Thus, our aim is to evaluate short- and mid-term effects of tDCS in this multi-center, randomized, double blind, and sham-controlled, parallel group clinical trial with a 1:1 randomization ratio. Primary endpoint is the total score of DSM-IV scale of the internationally established Conners' Adult ADHD Rating Scales (German self-report screening version, CAARS-S-SR), at day 14 post-intervention (p.i.) to detect short-term lasting effects analyzed via analyses of covariance (ANCOVAs). In case of significant between-groups differences at day 14 p.i., hierarchically ordered hypotheses on mid-term lasting effects will be investigated by linear mixed models with visit (5 time points), treatment, treatment by visit interaction, and covariates as fixed categorical effects plus a patient-specific visit random effect, using an unstructured covariance structure to model the residual within-patient errors. Positive results of this clinical trial will expand the treatment options for adult ADHD patients with tDCS and provide an alternative or add-on therapy to psychostimulants with a low risk for side effects.Trial Registration The trial was registered on July 29, 2022 in the German Clinical Trials Register (DRKS00028148).

Optimizing age-related hearing risk predictions: an advanced machine learning integration with HHIE-S.

OBJECTIVES: The elderly are disproportionately affected by age-related hearing loss (ARHL). Despite being a well-known tool for ARHL evaluation, the Hearing Handicap Inventory for the Elderly Screening version (HHIE-S) has only traditionally been used for direct screening using self-reported outcomes. This work uses a novel integration of machine learning approaches to improve the predicted accuracy of the HHIE-S tool for ARHL in older adults. METHODS: We employed a dataset that was gathered between 2016 and 2018 and included 1,526 senior citizens from several Taipei City Hospital branches. 80% of the data were used for training (n = 1220) and 20% were used for testing (n = 356). XGBoost, Gradient Boosting, and LightGBM were among the machine learning models that were only used and assessed on the training set. In order to prevent data leakage and overfitting, the Light Gradient Boosting Machine (LGBM) model-which had the greatest AUC of 0.83 (95% CI 0.81-0.85)-was then only used on the holdout testing data. RESULTS: On the testing set, the LGBM model showed a strong AUC of 0.82 (95% CI 0.79-0.86), far outperforming conventional techniques. Notably, several HHIE-S items and age were found to be significant characteristics. In contrast to traditional HHIE research, which concentrates on the psychological effects of hearing loss, this study combines cutting-edge machine learning techniques-specifically, the LGBM classifier-with the HHIE-S tool. The incorporation of SHAP values enhances the interpretability of the model's predictions and provides a more comprehensive comprehension of the significance of various aspects. CONCLUSIONS: Our methodology highlights the great potential that arises from combining machine learning with validated hearing evaluation instruments such as the HHIE-S. Healthcare practitioners can anticipate ARHL more accurately thanks to this integration, which makes it easier to intervene quickly and precisely.

Safety and Survival Outcomes of Liver Resection following Triple Combination Conversion Therapy for Initially Unresectable Hepatocellular Carcinoma.

Triple combination conversion therapy, involving transcatheter arterial chemoembolization (TACE) or hepatic arterial infusion chemotherapy (HAIC) combined with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), has shown an encouraging objective response rate (ORR) and successful conversion surgery rate in initially unresectable hepatocellular carcinoma (HCC). However, the safety and long-term survival outcomes of subsequent liver resection after successful conversion still remain to be validated. From February 2019 to February 2023, 726 patients were enrolled in this retrospective study (75 patients received hepatectomy after conversion therapy [CLR group], and 651 patients underwent pure hepatectomy [LR group]). Propensity score matching (PSM) was used to balance the preoperative baseline characteristics. After PSM, 68 patients in the CLR group and 124 patients in the LR group were analyzed, and all the matching variables were well-balanced. Compared with the LR group, the CLR group experienced longer Pringle maneuver time, longer operation time, and longer hospital stays. In addition, the CLR group had significantly higher incidence rates of intra-abdominal bleeding, biliary leakage, post-hepatectomy liver failure (PHLF), and Clavien-Dindo grade IIIa complications than the LR group. There were no significant statistical differences in overall survival (OS) (hazard ratio [HR] 0.724; 95% confidence interval [CI] 0.356-1.474; p = 0.374) and recurrence-free survival (RFS) (HR 1.249; 95% CI 0.807-1.934; p = 0.374) between the two groups. Liver resection following triple combination conversion therapy in initially unresectable HCC may achieve favorable survival outcomes with manageable safety profiles; presenting as a promising treatment option for initially unresectable HCC.

A histopathological image classification method for cholangiocarcinoma based on spatial-channel feature fusion convolution neural network.

Histopathological image analysis plays an important role in the diagnosis and treatment of cholangiocarcinoma. This time-consuming and complex process is currently performed manually by pathologists. To reduce the burden on pathologists, this paper proposes a histopathological image classification method for cholangiocarcinoma based on spatial-channel feature fusion convolutional neural networks. Specifically, the proposed model consists of a spatial branch and a channel branch. In the spatial branch, residual structural blocks are used to extract deep spatial features. In the channel branch, a multi-scale feature extraction module and some multi-level feature extraction modules are designed to extract channel features in order to increase the representational ability of the model. The experimental results of the Multidimensional Choledoch Database show that the proposed method performs better than other classical CNN classification methods.

Overexpression of RAB27A in Oral Squamous Cell Carcinoma Promotes Tumor Migration and Invasion via Modulation of EGFR Membrane Stability.

Oral squamous cell carcinoma (OSCC) is the most prevalent subtype of head and neck tumors, highly prone to lymph node metastasis. This study aims to examine the expression pattern of Ras-related protein Rab-27A (RAB27A) and explore its potential implications in OSCC. The expression of RAB27A was assessed through immunohistochemical analysis utilizing tissue microarrays. In vitro experiments were conducted using RAB27A-knockdown cells to investigate its impact on OSCC tumor cells. Additionally, transcriptome sequencing was performed to elucidate potential underlying mechanisms. RAB27A was significantly overexpressed in OSCC, and particularly in metastatic lymph nodes. It was positively correlated with the clinical progression and poor survival prognosis. Silencing RAB27A notably decreased the proliferation, migration, and invasion abilities of OSCC cells in vitro. A Gene Ontology (GO) enrichment analysis indicated a strong association between RAB27A and the epidermal growth factor receptor (EGFR) signaling pathway. Further investigations revealed that RAB27A regulated the palmitoylation of EGFR via zinc finger DHHC-type containing 13 (ZDHHC13). These findings provide insights into OSCC progression and highlight RAB27A as a potential therapeutic target for combating this aggressive cancer.

Using artificial intelligence algorithms to predict the overall survival of hemodialysis patients during the COVID-19 pandemic: A prospective cohort study.

BACKGROUND: Hemodialysis (HD) patients are a vulnerable population at high risk for severe complications from COVID-19. The impact of partial COVID-19 vaccination on the survival of HD patients remains uncertain. This prospective cohort study was designed to use artificial intelligence algorithms to predict the survival impact of partial COVID-19 vaccination in HD patients. METHODS: A cohort of 433 HD patients was used to develop machine-learning models based on a subset of clinical features assessed between July 1, 2021, and April 29, 2022. The patient cohort was randomly split into training (80%) and testing (20%) sets for model development and evaluation. Machine-learning models, including categorical boosting (CatBoost), light gradient boosting machines (LightGBM), RandomForest, and extreme gradient boosting models (XGBoost), were applied to evaluate their discriminative performance using the patient cohorts. RESULTS: Among these models, LightGBM achieved the highest F1 score of 0.95, followed by CatBoost, RandomForest, and XGBoost, with area under the receiver operating characteristic curve values of 0.94 on the testing dataset. The SHapley Additive explanation summary plot derived from the XGBoost model indicated that key features such as age, albumin, and vaccination details had a significant impact on survival. Furthermore, the fully vaccinated group exhibited higher levels of anti-spike (S) receptor-binding domain antibodies. CONCLUSION: This prospective cohort study involved using artificial intelligence algorithms to predict overall survival in HD patients during the COVID-19 pandemic. These predictive models assisted in identifying high-risk individuals and guiding vaccination strategies for HD patients, ultimately improving overall prognosis. Further research is warranted to validate and refine these predictive models in larger and more diverse populations of HD patients.

ALIX promotes cell migration and invasion of head and neck squamous cell carcinoma by regulating the expression of MMP9, MMP14, VEGF-C.

OBJECTIVE: The poor survival rate of head and neck squamous cell carcinoma (HNSCC), one of the most prevalent human cancer, is attributed to frequent locoregional recurrence and lymph node metastases. Though it is reported that the expression of ALG-2 interacting protein X (ALIX) closely correlates with the progression of various tumors, its role in HNSCC remains unclear. The present study aims to investigate the role of ALIX in the development of HNSCC. DESIGN: With immunohistochemical staining, the expression levels of ALIX and series of related functional proteins were compared in normal mucosal (n = 18), HNSCC tissues (n = 54), and metastatic lymph nodes (n = 11). Further, the correlation analysis was performed among the proteins detected. By knocking down ALIX in HNSCC cell lines, the correlation of ALIX with the proteins was verified in vitro. The role of ALIX in proliferation, migration, and invasion of HNSCC cells was further studied by flow cytometry, wounding healing, and transwell assays, respectively. RESULTS: Higher expression level of ALIX was revealed in HNSCC samples, especially in metastatic lymph nodes, than in normal mucosal tissues. Accordingly, increasing levels of MMP9, MMP14, and VEGF-C were also discovered in metastatic lymph nodes and significantly correlated with the expression of ALIX. In vitro assays demonstrated that the knockdown of ALIX reduced both the transcriptional and protein levels of MMP9, MMP14, and VEGF-C, together with suppressed migration and weakened invasion of HNSCC cell lines. CONCLUSIONS: ALIX up-regulated the expression of MMP9, MMP14 and VEGF-C, and promoted migration and invasion of HNSCC cells.

Real-Time Dissection of the Transportation and miRNA-Release Dynamics of Small Extracellular Vesicles.

Extracellular vesicles (EVs) are cell-derived membrane-enclosed structures that deliver biomolecules for intercellular communication. Developing visualization methods to elucidate the spatiotemporal dynamics of EVs' behaviors will facilitate their understanding and translation. With a quantum dot (QD) labeling strategy, a single particle tracking (SPT) platform is proposed here for dissecting the dynamic behaviors of EVs. The interplays between tumor cell-derived small EVs (T-sEVs) and endothelial cells (ECs) are specifically investigated based on this platform. It is revealed that, following a clathrin-mediated endocytosis by ECs, T-sEVs are transported to the perinuclear region in a typical three-stage pattern. Importantly, T-sEVs frequently interact with and finally enter lysosomes, followed by quick release of their carried miRNAs. This study, for the first time, reports the entire process and detailed dynamics of T-sEV transportation and cargo-release in ECs, leading to better understanding of their proangiogenic functions. Additionally, the QD-based SPT technique will help uncover more secrets of sEV-mediated cell-cell communication.

The impact of emotional dysregulation and comorbid depressive symptoms on clinical features, brain arousal, and treatment response in adults with ADHD.

Introduction: The role of emotional dysregulation (ED) in attention-deficit/hyperactivity disorder (ADHD) has become an important issue. This study, in which we analyzed data from a predictive pharmaco-EEG-trial, aimed to examine whether symptoms of ED in adult ADHD affect ADHD symptom severity, brain arousal regulation as measured by resting EEG, and the response to stimulant medication. Methods: ED is defined as having a sex- and age-corrected T-score of >70 on the emotional lability subscale of the German version of Conners' Adult ADHD Rating Scale. A total of 115 participants were included in the study, 56 of whom had ED. Participants with ED were more impaired in terms of the severity of core ADHD symptoms, especially inattentive symptoms, comorbid depressive symptoms, interpersonal relationships, and quality of life. In addition, participants with ED were more likely to report a total score above 13 on the Beck Depression Inventory-II, which was considered to be the cutoff for mild depression. Results: No differences were found between the ED and non-ED groups in response to stimulant medication or in brain arousal regulation. In addition, there was no significant effect of ED with comorbid depressive symptoms on treatment response. There was a trend for subgroups that showed a change in brain arousal regulation associated with symptom improvement. Discussion: Our findings may support the assumption that ED may be an important feature of ADHD. The use of EEG-based brain arousal regulation as a diagnostic and predictive tool in ADHD in the presence of ED and comorbid depressive symptoms should be further investigated.

Design and Fabrication of Interdigital Supercapacitors as Force/Acceleration Sensors.

The integrated device for energy supply and sensing (IDESS) is a potential candidate for relieving the energy and space burdens caused by the rising integration degrees of microsystems. In this article, we propose a force sensor based on an interdigital supercapacitor (IDTSC). The capacitance and internal resistance of the IDTSC change under external loads, resulting in a transient current fluctuation at a constant bias voltage, which can be used to sense external force/acceleration. The IDTSC showed a specific energy and specific power of 4.16 Wh/kg and 22.26 W/kg (at 0.1 A/g), respectively, which could maintain an essential energy supply. According to the simulation analysis, the designed IDTSC's current response exhibited good linearity with the external force. In addition, benefiting from its light weight and the applied gel electrolytes, the IDTSC showed good high-g impact sensing performance (from 9.9 × 103× g to 3.2 × 104× g). This work demonstrated the feasibility of realizing an integrated energy supply and force-sensing device by empowering energy storage devices with sensing capabilities.

Deriving vertical profiles of chlorophyll-a concentration in the upper layer of seawaters using ICESat-2 photon-counting lidar.

Chlorophyll-a concentration (chl-a) is a great indicator for estimating phytoplankton biomass and productivity levels and is also particularly useful for monitoring the water quality, biodiversity and species distribution, and harmful algal blooms. A great deal of studies investigated to estimate chl-a concentrations using ocean color remotely sensed data. With the development of photon-counting sensors, spaceborne photon-counting lidar can compensate for the shortcomings of passive optical remote sensing by enabling ocean vertical profiling in low-light conditions (e.g., at night). Using geolocated photons captured by the first spaceborne photon-counting lidar borne on ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2), this research reported methods for deriving vertical profiles of chl-a concentration in the upper layer of ocean waters. This study first calculates the average numbers of backscattered subaqueous photons of ICESat-2 at different water depths, and then estimates the optical parameters in water column based on a discrete theoretical model of the expected number of received signal photons. With the estimated optical parameters, vertical profiles of chl-a concentration are calculated by two different empirical algorithms. In two study areas (mostly with Type I open ocean waters and small part of Type II coastal ocean waters), the derived chl-a concentrations are generally consistent when validated by BGC-Argo (Biogeochemical Argo) data in the vertical direction (MAPEs<15%) and compared with MODIS (Moderate Resolution Imaging Spectroradiometer) data in the along-track direction (average R2>0.86). Using globally covered ICESat-2 data, this approach can be used to obtain vertical profiles of chl-a concentration and optical parameters at a larger scale, which will be helpful to analyze impact factors of climate change and human activities on subsurface phytoplankton species and their growth state.

Estimation of chromophoric dissolved organic matter and its controlling factors in Beaufort Sea using mixture density network and Sentinel-3 data.

With the warming of the high-latitude regional climate, melting of permafrost, and acceleration of hydrological cycles, the Arctic Ocean (AO) has undergone a series of rapid changes in the past decades. As a dominant optical component of the AO, the variations in chromophoric dissolved organic matter (CDOM) concentration affect the physiological state marine organisms. In this study, machine learning retrieval model based on in situ data and mixture density network (MDN) was developed. Compared to other models, MDN model performed better on test data (R2 = 0.83, and root mean squared error = 0.22 m-1) and was applied to Sentinel-3 OLCI data. Afterward, the spatiotemporal distribution of CDOM during the ice-free (June-September) from 2016 to 2020 in the Beaufort Sea was obtained. CDOM concentration generally exhibited an upward trend. The maximum monthly average CDOM concentration appeared in June and gradually decreased thereafter, reaching its lowest value in September of each year. The maximum value appeared in June 2020 (0.91 m-1), and the minimum value was observed in September 2017 (0.81 m-1). The CDOM concentration nearshore was higher than that in other areas; and gradually decreased from offshore to the open sea. CDOM was highly correlated with salinity (R2 = 0.49) and discharge (R2 = 0.53), and the tight correlation between salinity and CDOM further suggested that terrestrial inputs were the main source of CDOM in the Beaufort Sea. However, sea level pressure contributed to the spatial variations in CDOM. When southerly wind prevailed and wind direction was aligned with the CDOM diffusion direction, the wind accelerated the diffusion of CDOM into the open sea. Meanwhile, seawater was diluted by the sea ice melting, resulting in decrease in CDOM concentration. Herein, this paper proposed a robust and near real-time method for CDOM monitoring and influence factor analysis, which would promote the understanding of AO CDOM budgets.

Association between Individual Norepinephrine Transporter (NET) Availability and Response to Pharmacological Therapy in Adults with Attention-Deficit/Hyperactivity Disorder (ADHD).

BACKGROUND: The role of the norepinephrine transporter (NET) has received increased focus in recent studies on the pathogenesis of attention-deficit/hyperactivity disorder (ADHD). The predictive value for pharmacological treatment and its link to other health or social limitations has been little-studied. This follow-up research on adult patients with ADHD aimed to explore whether the therapy response and health and social impairments depend on baseline individual NET availability. METHODS: Data were collected from 10 patients on personal, family and professional situations, mental and physical health and treatments received after baseline via online and telephone surveys and were compared to baseline data to evaluate treatment-related changes. RESULTS: The majority of our ADHD patients did not show therapy responses but showed improvements due to pharmacological treatment. There was no evidence of relationships between pre-treatment NET availability and therapy response or health/social limitations. CONCLUSIONS: Pharmacological monotherapy was insufficient to promote symptom remission, especially for participants with extreme insufficiency in NET availability, but improved outcomes in academic and social functioning. Psychotherapy should be considered as an add-on to the standard treatment approach due to its positive outcome in reducing social limitations. The prognostic value of individual NET availability in predicting the response to therapy needs further studies with large sample sizes.

The role of comorbid depressive symptoms on long-range temporal correlations in resting EEG in adults with ADHD.

Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder, characterized by core symptoms of inattention, hyperactivity and impulsivity. Comorbid depression is commonly observed in ADHD-patients. Psychostimulants are recommended as first-line treatment for ADHD. Aberrant long-range temporal correlations (LRTCs) of neuronal activities in resting-state are known to be associated with disorganized thinking and concentrating difficulties (typical in ADHD) and with maladaptive thinking (typical in depression). It has yet to be examined whether (1) LRTC occur in ADHD-patients, and if so, (2) whether LRTC might be a competent biomarker in ADHD comorbid with current depression and (3) how depression affects psychostimulant therapy of ADHD symptoms. The present study registered and compared LRTCs in different EEG frequency bands in 85 adults with ADHD between groups with (n = 28) and without (n = 57) additional depressive symptoms at baseline. Treatment-related changes in ADHD, depressive symptoms and LRTC were investigated in the whole population and within each group. Our results revealed significant LRTCs existed in all investigated frequency bands. There were, however, no significant LRTC-differences between ADHD-patients with and without depressive symptoms at baseline and no LRTC-changes following treatment. However, depressed ADHD patients did seem to benefit more from the therapy with psychostimulant based on self-report.

Acidic Electrolyzed Water Inhibits the Viability of Gardnerella spp. via Oxidative Stress Response.

The vaginal microbiota, dominated by Lactobacilli, plays an important role in maintaining women's health. Disturbance of the vaginal microbiota allows infection by various pathogens such as Gardnerella spp. (GS) and related anaerobic bacteria resulting in bacterial vaginosis (BV). At present, the treatment options for BV are extremely limited. Treatment of antibacterial drugs and vaginal acidification are the two primary therapeutic methods. Acid electrolyzed water (AEW) is known to inactivate microorganisms and is considered a medical application in recent years. Studies have found that Lactobacillus acidophilus (LA) probiotics helps to inhibit GS-induced BV. Our study took GS and LA as the research object, which aims to explore AEW as a potential alternative therapy for BV and its underlying mechanisms. We first obtained the pH of AEW (3.71-4.22) close to normal vaginal pH (3.8-4.5) to maintain normal vaginal acidification conditions. Plate counting experiments showed that AEW (pH: 4.07, ORP: 890.67, ACC: 20 ppm) (20 ppm) could better inhibit the viability of GS but had a more negligible effect on LA. Then, we preliminarily explored the possible mechanism of AEW anti-GS using cell biology experiments and transmission electron microscopy. Results showed that the membrane permeability was significantly increased and the integrity of cell membrane was destroyed by AEW in GS than those in LA. AEW also caused protein leakage and cell lysis in GS without affecting LA. Meanwhile, AEW induced a number of reactive oxygen species (ROS) production in GS, with no obvious LA changes. Finally, we found that 20 ppm AEW exhibited excellent antibacterial effect on the vaginal secretions of women diagnosed with BV by Amsel criteria and sialic acid plum method. Taken together, our findings manifest that 20 ppm AEW has an excellent antibacterial effect in GS with less effect on LA, which might be expected to become a potential therapy for BV.

The Big Five Personality Traits and Brain Arousal in the Resting State.

Based on Eysenck's biopsychological trait theory, brain arousal has long been considered to explain individual differences in human personality. Yet, results from empirical studies remained inconclusive. However, most published results have been derived from small samples and, despite inherent limitations, EEG alpha power has usually served as an exclusive indicator for brain arousal. To overcome these problems, we here selected N = 468 individuals of the LIFE-Adult cohort and investigated the associations between the Big Five personality traits and brain arousal by using the validated EEG- and EOG-based analysis tool VIGALL. Our analyses revealed that participants who reported higher levels of extraversion and openness to experience, respectively, exhibited lower levels of brain arousal in the resting state. Bayesian and frequentist analysis results were especially convincing for openness to experience. Among the lower-order personality traits, we obtained the strongest evidence for neuroticism facet 'impulsivity' and reduced brain arousal. In line with this, both impulsivity and openness have previously been conceptualized as aspects of extraversion. We regard our findings as well in line with the postulations of Eysenck and consistent with the recently proposed 'arousal regulation model'. Our results also agree with meta-analytically derived effect sizes in the field of individual differences research, highlighting the need for large (collaborative) studies.

The "VIP-ADHD trial": Does brain arousal have prognostic value for predicting response to psychostimulants in adult ADHD patients?

EEG studies have shown that adult ADHD patients have less stable brain arousal regulation than age and gender matched controls. Psychostimulants have brain arousal stabilising properties evident in EEG patterns. The aim of this study was to investigate whether the stability of brain arousal regulation has prognostic value in predicting response to methylphenidate therapy in adult ADHD patients. In an open-label, single-arm, multi-centre, confirmatory trial, 121 adult ADHD patients were recruited and 112 qualified for the full analysis set. All participants received an initial dose of 20 mg extended release methylphenidate at baseline. After a titration phase of up to 4 weeks, patients remained on a weight-based target dose of extended release methylphenidate for 4 weeks. Using the Vigilance Algorithm Leipzig (VIGALL 2.1), we assessed brain arousal regulation before the treatment with methylphenidate, based on a 15-min EEG at quiet rest recorded at baseline. Using automatic stage-classification of 1 s segments, we computed the mean EEG-vigilance (indexing arousal level) and an arousal stability score (indexing arousal regulation). The primary endpoint was the association between successful therapy, defined by a 30% reduction in CAARS, and stable/unstable brain arousal. 52 patients (46%) showed an unstable brain arousal regulation of which 23% had therapy success. In the stable group, 35% had therapy success, implying an absolute difference of 12 percentage points (95% CI -5 to 29, p = 0.17) in the direction opposite to the hypothesized one. There were no new findings regarding the tolerability and safety of extended release methylphenidate therapy.

Extracellular Vesicles in Oral and Craniofacial Diseases: from Basic Knowledge to Clinical Perspectives.

Extracellular vesicles (EVs), produced by exocytosis or membrane budding of cells, are membranous vesicles that carry specific proteins, nucleic acids and other bioactive molecules. EVs are indispensable carriers of biological information and play a critical role in cell-to-cell communication. Due to their involvement in physiological and pathological processes, EVs have shown great potential in the diagnosis and treatment of various diseases in recent years. The present review focuses on the regulatory role of EVs in oral and craniofacial diseases to provide valuable insights into possible applications in translational medicine.