The elimination of ocular artifacts is critical in analyzing electroencephalography (EEG) data for various brain-computer interface (BCI) applications. Despite numerous promising solutions, electrooculography (EOG) recording or an eye-blink detection algorithm is required for the majority of artifact removal algorithms. This reliance can hinder the model’s implementation in real-world applications. This paper proposes EEGANet, a framework based on generative adversarial networks (GANs), to address this issue as a data-driven assistive tool for ocular artifacts removal (source code is available at https://github.com/IoBT-VISTEC/EEGANet ). After the model was trained, the removal of ocular artifacts could be applied calibration-free without relying on the EOG channels or the eye blink detection algorithms. First, we tested EEGANet’s ability to generate multi-channel EEG signals, artifacts removal performance, and robustness using the EEG eye artifact dataset, which contains a significant degree of data fluctuation. According to the results, EEGANet is comparable to state-of-the-art approaches that utilize EOG channels for artifact removal. Moreover, we demonstrated the effectiveness of EEGANet in BCI applications utilizing two distinct datasets under inter-day and subject-independent schemes. Despite the absence of EOG signals, the classification performance of the signals processed by EEGANet is equivalent to that of traditional baseline methods. This study demonstrates the potential for further use of GANs as a data-driven artifact removal technique for any multivariate time-series bio-signal, which might be a valuable step towards building next-generation healthcare technology.

Background: Cardiac ischemic/reperfusion (I/R) injury leads to brain damage. A new antihyperlipidemic drug is aimed at inhibiting PCSK 9 (proprotein convertase subtilisin/kexin type 9), a molecule first identified in a neuronal apoptosis paradigm. Thus, the PCSK 9 inhibitor ( PCSK 9i) may play a role in neuronal recovery following cardiac I/R insults. We hypothesize that PCSK 9i attenuates brain damage caused by cardiac I/R via diminishing microglial/astrocytic hyperactivation, β‐amyloid aggregation, and loss of dendritic spine. Methods and Results: Adult male rats were divided into 7 groups: (1) control (n=4); (2) PCSK 9i without cardiac I/R (n=4); (3) sham (n=4); and cardiac I/R (n=40). Cardiac I/R rats were divided into 4 subgroups (n=10/subgroup): (1) vehicle; (2) PCSK 9i (10 μg/kg, IV) before ischemia; (3) PCSK 9i during ischemia; and (4) PCSK 9i at the onset of reperfusion. At the end of cardiac I/R protocol, brains were removed to determine microglial and astrocytic activities, β‐amyloid aggravation, and dendritic spine density. The cardiac I/R led to the activation of the brain's innate immunity resulting in increasing Iba1 ⁺ microglia, GFAP ⁺ astrocytes, and CD 11b ⁺ / CD 45 ^+high cell numbers. However, CD 11b ⁺ / CD 45 ^+low cell numbers were decreased following cardiac I/R. In addition, cardiac I/R led to reduced dendritic spine density, and increased β‐amyloid aggregation. Only the administration of PCSK 9i before ischemia effectively attenuated these deleterious effects on the brain following cardiac I/R. PCSK 9i administration under the physiologic condition did not affect the aforementioned parameters. Conclusions: Cardiac I/R injury activated microglial activity in the brain, leading to brain damage. Only the pretreatment with PCSK 9i prevented dendritic spine loss via reduction of microglial activation and Aβ aggregation.

The coronavirus disease 19 (COVID-19) pandemic that has been raging in 2020 does affect not only the physical state but also the mental health of the general population, particularly, that of the healthcare workers. Given the unprecedented large-scale impacts of the COVID-19 pandemic, digital technology has gained momentum as invaluable social interaction and health tracking tools in this time of great turmoil, in part due to the imposed state-wide mobilization limitations to mitigate the risk of infection that might arise from in-person socialization or hospitalization. Over the last five years, there has been a notable increase in the demand and usage of mobile and wearable devices as well as their adoption in studies of mental fitness. The purposes of this scoping review are to summarize evidence on the sweeping impact of COVID-19 on mental health as well as to evaluate the merits of the devices for remote psychological support. We conclude that the COVID-19 pandemic has inflicted a significant toll on the mental health of the population, leading to an upsurge in reports of pathological stress, depression, anxiety, and insomnia. It is also clear that mobile and wearable devices (e.g., smartwatches and fitness trackers) are well placed for identifying and targeting individuals with these psychological burdens in need of intervention. However, we found that most of the previous studies used research-grade wearable devices that are difficult to afford for the normal consumer due to their high cost. Thus, the possibility of replacing the research-grade wearable devices with the current smartwatch is also discussed.

Background: Attention deficit hyperactivity disorder (ADHD) is associated with depression among college students, while perceived social support is also associated with depression, especially among young adults. This study aimed to examine to what extent perceived social support mediated the relationship between ADHD symptoms and depressive symptoms. Methods: In total, 124 first year medical students completed the Adult ADHD Self-Report Scale Screener (ASRS), the Patient Health questionnaire-9 and the revised Thai Multidimensional scale of perceived social support reflecting ADHD symptoms, depressive symptoms, and perceive social support, i.e., family members, friends and other significant people, respectively. Structural equation modeling was used to investigate the hypothesized mediation model. Results: ADHD symptoms exhibited a significant indirect effect on depressive symptoms via perceived social support. ADHD symptoms initially had a direct effect on depression; thereafter, it reduced to a non-significance effect after perceived social support was added. The total variance explained by this model was 35.2%. The mediation model with family support as a mediator showed the highest effect size. Conclusions: The study highlighted the importance of perceived social support, particularly family support, on depressive symptoms among young medical students experiencing ADHD symptoms. The model suggests promising relationships for further research on ADHD-related depression and potential treatment in the future.

Monthatip K, et al. J Gynecol Oncol. 2023 Oct;35:e17. https://doi.org/10.3802/jgo.2024.35.e17

Background: CHIVID is a telemedicine solution developed under tight time constraints that assists Thai healthcare practitioners in monitoring non-severe COVID-19 patients in isolation programs during crises. It assesses patient health and notifies healthcare practitioners of high-risk scenarios through a chatbot. The system was designed to integrate with the famous Thai messaging app LINE, reducing development time and enhancing user-friendliness, and the system allowed patients to upload a pulse oximeter image automatically processed by the PACMAN function to extract oxygen saturation and heart rate values to reduce patient input errors. Methods: This article describes the proposed system and presents a mixed-methods study that evaluated the system’s performance by collecting survey responses from 70 healthcare practitioners and analyzing 14,817 patient records. Results: Approximately 71.4% of healthcare practitioners use the system more than twice daily, with the majority managing 1–10 patients, while 11.4% handle over 101 patients. The progress note is a function that healthcare practitioners most frequently use and are satisfied with. Regarding patient data, 58.9%(8,724/14,817) are male, and 49.7%(7,367/14,817) within the 18 to 34 age range. The average length of isolation was 7.6 days, and patients submitted progress notes twice daily on average. Notably, individuals aged 18 to 34 demonstrated the highest utilization rates for the PACMAN function. Furthermore, most patients, totaling over 95.52%(14,153/14,817), were discharged normally. Conclusion: The findings indicate that CHIVID could be one of the telemedicine solutions for hospitals with patient overflow and healthcare practitioners unfamiliar with telemedicine technology to improve patient care during a critical crisis. Clinical and Translational Impact Statement— CHIVID’s success arises from seamlessly integrating telemedicine into third-party application within a limited timeframe and effectively using clinical decision support systems to address challenges during the COVID-19 crisis.