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Upregulation of reactive oxygen species (ROS) levels is a principal feature observed in the brains of neurodegenerative diseases such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). In these diseases, oxidative stress can disrupt the blood–brain barrier (BBB). This disruption allows neurotoxic plasma components, blood cells, and pathogens to enter the brain, leading to increased ROS production, mitochondrial dysfunction, and inflammation. Collectively, these factors result in protein modification, lipid peroxidation, DNA damage, and, ultimately, neural cell damage. In this review article, we present the mechanisms by which oxidative damage leads to BBB breakdown in brain diseases. Additionally, we summarize potential therapeutic approaches aimed at reducing oxidative damage that contributes to BBB disruption in neurodegenerative diseases.

To evaluate the efficacy of low-level light therapy (LLLT) with near-infrared light-emitting diodes (LED-LLLT) for the treatment of dry eye. 40 patients were randomly assigned with a 1:1 allocation ratio to receive LED-LLLT (LLLT group, n = 20) or placebo treatment (placebo group, n = 20). Patients in the LLLT group received LLLT twice a week for 3 weeks, for a total of 6 treatment sessions. The primary endpoint was the changes in the fluorescein corneal staining (FCS) score. The secondary endpoints were the changes in the ocular surface disease index (OSDI) score, lissamine green conjunctival staining (LGCS) scores, tear film break-up time (TBUT), Schirmer test, and the meibomian gland dysfunction (MGD) index. These were evaluated before treatment and 4 weeks after start of treatment. The mean difference of score change in primary endpoint revealed significant improvement in the LLLT group, compared to the placebo. Among secondary endpoints, LGCS, Schirmer's test, upper meibography scores showed significant improvements, while TBUT, lid debris, lid swelling, lid telangiectasia, meibomian gland secretion and expressibility scores had slight improvement without significant differences. No serious adverse events were observed. The use of LED-LLLT for the treatment of dry eye and MGD appears to be safe and beneficial.

Recently, in various fields, research into the path tracking of autonomous vehicles and automated guided vehicles has been conducted to improve worker safety, convenience, and work efficiency. For path tracking of various systems applied to autonomous driving technology, it is necessary to recognize the surrounding environment, determine technology accordingly, and develop control methods. Various sensors and artificial-intelligence-based perception methods have limitations in that they must learn a large amount of data. Therefore, a particle-filter-based path tracking algorithm using a monocular camera was used for the recognition of target RGB. The path tracking errors were calculated and a linear-quadratic-regulator-based desired steering angle were derived. The autonomous trucks were steered and driven using a pulse-width-modulation-based steering and driving motor. Based on an autonomous truck with a single steering and driving module, it was verified that the path tracking could be used in three evaluation scenarios. To compare the LQR-based path tracking control performance proposed in this paper, an elliptical path tracking scenario using a conventional sliding mode control with robust control performance was performed. The results show that the RMS of the lateral preview error of the SMC was approximately 18% larger than that of the LQR-based method.

The COVID-19 pandemic has intensified mental health issues globally, highlighting the urgent need for remote mental health monitoring. Digital phenotyping using smart devices has emerged as a promising approach, but it remains unclear which features are essential for predicting depression and anxiety. This study aimed to identify the types of features collected through smart packages-integrated systems combining smartphones with wearable devices such as Actiwatches, smart bands, and smartwatches-and to determine which features should be considered essential for mental health monitoring based on the type of device used. A systematic review was conducted. Searches were performed across Web of Science, PubMed, and Scopus on February 5, 2025. Inclusion criteria comprised quantitative studies involving adults (≥19 years) using smart devices to predict depression or anxiety based on passive data collection. Studies focusing solely on smartphones or qualitative designs were excluded. Risk of bias was assessed using the Mixed Methods Appraisal Tool and the Quality Criteria Checklist. Data were synthesized descriptively, and the relative contribution of each feature was further assessed by calculating coverage (proportion of studies using a feature) and importance among used (proportion identifying it as important when used). These metrics were visualized in quadrant-based scatter plots to identify consistently important features across devices. From 1382 records, 22 studies across 11 countries were included. The overall synthesis identified a core feature package-accelerometer, steps, heart rate (HR), and sleep. Device-specific analyses revealed further nuances: in Actiwatch studies, accelerometer and activity were consistently important, but sleep features were rarely examined. In smart band studies, HR, steps, sleep, and phone usage were essential, while GPS, electrodermal activity (EDA), and skin temperature showed high importance when used, suggesting opportunities for broader adoption. In smartwatch studies, sleep and HR emerged as core features, whereas steps and accelerometer were widely used but often not identified as important. This systematic review identified a core feature package comprising accelerometer, steps, HR, and sleep that consistently contributes to mood disorder prediction across devices. At the same time, device-specific differences were observed: Actiwatch studies mainly emphasized accelerometer and activity but underused sleep features; smart bands highlighted HR, steps, sleep, and phone usage, with EDA, skin temperature, and GPS showing additional promise; and smartwatches most reliably leveraged sleep and HR, while steps and accelerometer were widely used yet less effective. These findings suggest that while a shared core set of features exists, optimizing digital phenotyping requires tailoring feature selection to the characteristics of each device type. To advance this field, improving data accessibility, particularly in smartwatch ecosystems, and adopting standardized reporting frameworks will be essential to enhance comparability, reproducibility, and future meta-analytic integration.

Interstitial cystitis (IC)/bladder pain syndrome (BPS) is a chronic condition with severe pelvic pain and urinary symptoms significantly impairing quality of life. This study investigated the clinical relevance of the metabotropic glutamate receptor (mGluR) family in IC/BPS. Bladder biopsy samples were taken from 61 patients, including 42 Hunner-type IC, 11 non-Hunner type IC, and 8 controls without IC. Gene expression analysis revealed that mGluR2, mGluR3, and mGluR5 were significantly elevated in patients with IC/BPS compared to controls. Among these, mGluR5 showed the strongest association with pain severity, fibrosis, and lymphoplasmacytic infiltration. Patients with Hunner-type IC also exhibited increased expression of p65 and interleukin-1β, suggesting activation of inflammatory response modulation in IC/BPS. These findings suggest that mGluR5 may contribute to pain through immune response modulation in IC/BPS. Targeting mGluR5 could represent a promising therapeutic strategy to alleviate symptoms and improve patient quality of life.

Meibomian glands exist beneath the palpebral conjunctiva; thus, it is invisible to the naked eye without infrared imaging. This study used meibography to group patients with meibomian gland dysfunction (MGD) and assessed the effects of hyperthermic massage and mechanical squeezing in both groups. Patients with MGD were divided into two groups, according to the degree of meibomian gland loss: group 1, in which the sum of eyelid scores ranged from 0 to 4 (mild to moderate gland loss) and group 2, in which the sum of eyelid scores ranged from 5 to 6 (severe gland loss). Hyperthermic massage and mechanical squeezing were given to both groups once a week for 4 weeks, and only non-preservative artificial tears were allowed. Ocular surface disease index (OSDI), Schirmer's test, meibography score, tear break-up time (TBUT), ocular surface staining, expressible meibomian gland, and quality before and after treatment were compared. Of the 49 patients who completed the 4 weeks of treatment and the evaluation at week 5, 29 were assigned to group 1 and 20 were assigned to group 2. Meibography scores, OSDI, TBUT, and expressibility of meibum had significant differences before and after treatments in both groups. However, there was no significant difference between the changes in clinical signs between group 1 and 2 after treatment. Without grouping, all patients showed significant decreases in meibography score, OSDI, cornea staining score, and increases in TBUT and expressibility of meibum after treatment. Considering the results of the current study, hyperthermic massage and mechanical squeezing may be effective in patients with meibomian gland loss, regardless of the degree of severity.

The increasing complexity of mathematical models developed as part of the recent advancements in autonomous mobility platforms has led to an escalation in uncertainty. Despite the intricate nature of such models, the detection, decision, and control methods for autonomous mobility path tracking remain critical. This study aims to achieve path tracking based on pixel-based control errors without parameters in the mathematical model. The proposed approach entails deriving control errors from a multi-particle filter based on a camera, estimating the error dynamics coefficients through a recursive least squares (RLS) approach, and using the sliding mode approach and weighted injection to formulate a cost function that leverages the estimated coefficients and control errors. The resultant adaptive steering control expedites the convergence of control errors towards zero by determining the magnitude of the injection variable based on the control errors and the finite-time convergence condition. The efficacy of the proposed approach is evaluated through an S-curved and elliptical path using autonomous mobility equipped with a single steering and driving module. The results demonstrate the capability of the approach to reasonably track target paths through driving and steering control facilitated by a multi-particle filter and a lidar-based obstacle detection system.

The blood–brain barrier (BBB) restricts entry of neurotoxic plasma components, blood cells, and pathogens into the brain, leading to proper neuronal functioning. BBB impairment leads to blood-borne protein infiltration such as prothrombin, thrombin, prothrombin kringle-2, fibrinogen, fibrin, and other harmful substances. Thus, microglial activation and release of pro-inflammatory mediators commence, resulting in neuronal damage and leading to impaired cognition via neuroinflammatory responses, which are important features observed in the brain of Alzheimer’s disease (AD) patients. Moreover, these blood-borne proteins cluster with the amyloid beta plaque in the brain, exacerbating microglial activation, neuroinflammation, tau phosphorylation, and oxidative stress. These mechanisms work in concert and reinforce each other, contributing to the typical pathological changes in AD in the brain. Therefore, the identification of blood-borne proteins and the mechanisms involved in microglial activation and neuroinflammatory damage can be a promising therapeutic strategy for AD prevention. In this article, we review the current knowledge regarding the mechanisms of microglial activation-mediated neuroinflammation caused by the influx of blood-borne proteins into the brain via BBB disruption. Subsequently, the mechanisms of drugs that inhibit blood-borne proteins, as a potential therapeutic approach for AD, along with the limitations and potential challenges of these approaches, are also summarized.

Neuroinflammation is one of the key drivers of spinocerebellar ataxia type 2 (SCA2), yet the role of prothrombin-derived proteins in its pathogenesis remains unclear. Here, we show that prothrombin-derived proteins, thrombin and prothrombin kringle-2 (pKr-2), are elevated in the plasma of patients with cerebellar ataxia (CA) and in the cerebellum of SCA2 mice. Intervention strategies, reinforcing the blood–brain barrier (BBB) with caffeine administration and inhibiting thrombin/pKr-2 production through oral administration of rivaroxaban, attenuated cerebellar infiltration of prothrombin-derived proteins, neuroinflammation, and motor deficits in SCA2 mice, whereas pKr-2 upregulation exacerbated neuronal damage and behavioral impairments. These findings reveal a distinct peripheral proteomic signature linked to a cerebellar pathogenic pathway and suggest that limiting the entry of prothrombin-derived proteins into the cerebellum may represent a critical therapeutic approach in CA.