Brain and Nerve最新文献

In a hyper-aging society, taking measures against dementia, especially against dementia due to Alzheimer's disease, which accounts for about two thirds of dementia cases, is an important task socially and economically. Forty years have passed since amyloid β was isolated from a patient, 30 years have passed since the amyloid cascade hypothesis was proposed and antibody drugs based on this hypothesis have emerged, which has led to the new era of Alzheimer's disease treatment. This article reviews the significance of amyloid plaque removal with amyloid β-targeting antibody treatment for Alzheimer's disease. (Recieved October 17, 2024; Accepted June 6, 2025; Published October 1, 2025).

Multiple system atrophy (MSA) is a sporadic, progressive neurodegenerative disease that affects multiple systems, including the Parkinsonian and cerebellar systems. It is commonly associated with obstructive and central sleep apnea, sleep-related hypoventilation, and stridor, which may evolve with changes in the disease phenotype and severity. These respiratory complications are considered potential causes of sudden death, making the critical importance of their evaluation and management in patients with MSA. However, no established treatment has been developed, and therapeutic approaches, such as continuous positive airway pressure (CPAP) or tracheostomy, have been attempted on a case-by-case basis.

Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is a parasomnia characterized by dream-enacting behaviors caused by the loss of muscle atonia during REM sleep. It is widely recognized as a prodromal phase of α-synucleinopathies such as Parkinson's disease and dementia with Lewy bodies. Longitudinal cohort and pathological studies have demonstrated that approximately 70% of patients with iRBD develop defined neurodegenerative disorders within 10 years. Recent advances have identified several promising biomarkers to predict phenoconversion, including dopamine transporter imaging (DaT SPECT), cerebrospinal fluid α-synuclein detected via RT-QuIC, decreased CSF Aβ42, and elevated CSF/serum albumin ratio indicating blood-brain barrier dysfunction. Moreover, functional magnetic resonance imaging studies have revealed altered connectivity in the frontostriatal and posterior cortical networks in patients with iRBD, which correlates with cognitive and motor symptoms. These multimodal markers have significant potential for stratifying phenoconversion risks and guiding early therapeutic interventions. Future efforts should focus on standardizing biomarker assays and validating them through multicenter longitudinal studies to enhance diagnostic precision and support disease-modifying clinical trials in the prodromal phase of Lewy body diseases.

Parasomnia is an undesirable physical phenomena that occurs during sleep and is classified into three groups: non-rapid eye movement (REM), REM, and other parasomnias. Non-REM parasomnias that occur during non-REM sleep include wakefulness disorders, including confusional arousal, sleepwalking, sleep terrors, and newly added sleep-related eating disorders. REM sleep parasomnias related to dream content during REM sleep include isolated sleep paralysis and nightmare disorder, in addition to REM sleep behavior disorder. Other types of parasomnia that are not specific to non-REM sleep and REM sleep include explosive head syndrome, sleep-related hallucinations, sleep enuresis, parasomnia due to physical diseases, and parasomnia due to medicines and substances. It is necessary to conduct a detailed interview about the time of symptom onset and contest of symptoms to confirm whether the mechanism is due to non-REM sleep, REM sleep, or wakefulness with polysomnography and to make a diagnosis. It is important to explain each disease to patients and caregivers and provide treatment for each parasomnia.

Obstructive sleep apnea (OSA) and cerebrovascular disease (CVD) have a bidirectional relationship. OSA serves as an independent risk factor for stroke, and a prior meta-analysis has demonstrated a 2.24-fold increased risk for stroke development. Conversely, the prevalence of OSA after stroke is remarkably high (50-70%, significantly impairing both functional and survival outcomes). Continuous positive airway pressure (CPAP) therapy is effective in improving neurological symptoms during the acute phase of stroke, although evidence for stroke prevention remains limited. However, OSA is often overlooked in patients with acute stroke because of specific challenges that include impaired consciousness, cognitive dysfunction, positioning limitations, and medical device constraints that complicate evaluation procedures. Current clinical practice faces several barriers to OSA assessment that include limited access to sleep-testing facilities and specialists, unclear timing for post-stroke evaluation, insufficient awareness among healthcare providers regarding sleep disorders, and inadequate evidence levels for treatment interventions. Future directions require a strengthened collaboration between neurologists and sleep medicine specialists to establish systematic OSA evaluation systems in the acute stroke phase. This comprehensive multidisciplinary approach, which involves not only physicians, but also nurses, therapists, pharmacists, and nutritionists, is essential for improving the quality of life and prognosis of patients with stroke with concurrent sleep-disordered breathing.

Epilepsy is a chronic neurological disorder that significantly impairs quality of life. Importantly, interest in seizure forecasting technologies has been growing in recent years. With the widespread adoption of noninvasive wearable devices, research has advanced in analyzing biological, behavioral, and environmental data using artificial intelligence to estimate individualized seizure risk. At Tohoku University, industry-academia collaborations have promoted the development and social implementation of machine-learning-based prediction models. This article provides an overview of the status and challenges of these efforts.

Digital therapeutics are gaining attention with the advancement of digital transformations in the medical field. This paper outlines the effectiveness and limitations of the widespread adoption of face-to-face cognitive behavioral therapy for insomnia (CBT-I), examines the classification and effectiveness of digital cognitive behavioral therapy for insomnia (d-CBTI), and provides an overview of its implementation in medical settings. Based on these findings, we discuss the application of d-CBTI in Japan and its future potential.

Dementia is becoming a serious social and healthcare issue worldwide. While recent studies suggest that timely intervention can prevent its progression, most patients with dementia remain undiagnosed. The low diagnosis rate is mainly caused by the lack of an efficient screening tool for dementia. The first step toward diagnosing dementia involves cognitive assessments with interview-based neuropsychological tests, which have a well-established clinical utility. Traditional neuropsychological tests have high validity and reliability for dementia testing; however, they have limitations such as high test-related burdens and inter-rater variability of the results. Digital technologies with artificial intelligence have transformed traditional cognitive tests into efficient tools for dementia screening. This review article introduces recent developments in the research on digital biomarkers for dementia and discusses their limitations in clinical settings.

Anxiety disorders are among the most prevalent psychiatric conditions worldwide; however, a significant proportion of affected individuals do not receive adequate treatment because of barriers such as stigma, limited access to specialists, and geographical constraints. Recent advances in digital medicine have introduced new possibilities to address these challenges. This review summarizes the current clinical applications of digital interventions for anxiety disorders across diagnosis, treatment, and relapse prevention stages. Particular attention has been paid to internet-based cognitive behavioral therapy (ICBT), which has presented efficacy comparable to face-to-face CBT for conditions such as panic disorder, social anxiety disorder, and generalized anxiety disorder. However, its use has several limitations, including reduced effectiveness in obsessive-compulsive disorders and issues related to digital literacy. Furthermore, ethical and legal implications, such as those related to privacy protection, liability, and health equity, must be addressed to ensure safe and equitable implementation. Emerging technologies, including virtual reality and AI-based personalization, provide promising directions for future development. Furthermore, digital medicine holds substantial potential as a complementary tool for the treatment of anxiety disorders, but its widespread adoption requires ongoing empirical validation and the development of appropriate regulatory and clinical frameworks.

Cognitive behavioral therapy (CBT) is an effective treatment for depression; however, challenges remain, including a shortage of trained therapists and difficulties in treatment adherence. In recent years, digital CBT (iCBT) using smartphone applications has gained attention because of its potential to reduce disparities in treatment access and improve adherence. While the research and development of iCBT is progressing in Japan, further dissemination will require institutional support and attention to ethical issues. This article reviews the status and challenges of iCBT in the treatment of depression.