Electroencephalography (EEG) signals are prone to contamination by noise, such as ocular and muscle artifacts. Minimizing these artifacts is crucial for EEG-based downstream applications like disease diagnosis and brain-computer interface (BCI). This paper presents a new EEG denoising model, DTP-Net. It is a fully convolutional neural network comprising Densely-connected Temporal Pyramids (DTPs) placed between two learnable time-frequency transformations. In the time-frequency domain, DTPs facilitate efficient propagation of multi-scale features extracted from EEG signals of any length, leading to effective noise reduction. Comprehensive experiments on two public semi-simulated datasets demonstrate that the proposed DTP-Net consistently outperforms existing state-of-the-art methods on metrics including relative root mean square error (RRMSE) and signal-to-noise ratio improvement ( $\Delta$ SNR). Moreover, the proposed DTP-Net is applied to a BCI classification task, yielding an improvement of up to 5.55% in accuracy. This confirms the potential of DTP-Net for applications in the fields of EEG-based neuroscience and neuro-engineering. An in-depth analysis further illustrates the representation learning behavior of each module in DTP-Net, demonstrating its robustness and reliability.

Background: The inappropriate use of pharmacological treatments for insomnia may increase patients' risk of serious adverse events. However, few epidemiological studies on the use of medications for insomnia in China have been conducted to date.Objective: We aimed to investigate the current pharmacological treatments for insomnia and guide the rational use of drugs.Methods: The prescription data of outpatients with insomnia between 2015 and 2019 in Zhejiang province were extracted from the Hospital Prescription Analysis Cooperative Project of China and evaluated. The demographic characteristics of insomnia and the proportion and prescription trends of different drugs were analyzed along with multidrug combinations for insomnia.Results: The number of patients with insomnia who were prescribed medications for insomnia increased from 2,385 in 2015 to 3,919 in 2019, with an increase of 64.32%, whereas the mean age of these patients decreased from 64.07 years to 60.94 years. There were nearly 1.42 times as many female patients prescribed medications for insomnia as male patients, and female patients tended to be younger than male patients. Benzodiazepines (53.99%) were the most common type of medicine for insomnia. The incidence of benzodiazepine usage decreased significantly yearly (P < 0.01), whereas the incidences of non-benzodiazepine receptor agonist (nBZRA) and antidepressant usage increased (P < 0.05). The most common benzodiazepine, nBZRA, antidepressant, and antipsychotic were estazolam, zolpidem, trazodone, and olanzapine, respectively. A total of 13.97% of outpatients with insomnia were prescribed multiple drugs for insomnia, even though nearly half of the drug combinations had similar pharmacological mechanisms.Conclusions: Benzodiazepines remained the most common medication for insomnia, but the prescription rates of nBZRAs and antidepressants increased. Attention should be paid to multidrug combinations for insomnia, which may lead to an increased risk of serious adverse effects.

Long-term drug treatment for Restless Legs Syndrome (RLS) patients can frequently result in augmentation, which is the deterioration of symptoms with an increased drug dose. The cause of augmentation, especially derived from dopamine therapy, remains elusive. Here, we review recent research and clinical progress on the possible mechanism underlying RLS augmentation. Dysfunction of the dopamine system highly possibly plays a role in the development of RLS augmentation, as dopamine agonists improve desensitization of dopamine receptors, disturb receptor interactions within or outside the dopamine receptor family, and interfere with the natural regulation of dopamine synthesis and release in the neural system. Iron deficiency is also indicated to contribute to RLS augmentation, as low iron levels can affect the function of the dopamine system. Furthermore, genetic risk factors, such as variations in the BTBD9 and MEIS1 genes, have been linked to an increased risk of RLS initiation and augmentation. Additionally, circadian rhythm, which controls the sleep–wake cycle, may also contribute to the worsening of RLS symptoms and the development of augmentation. Recently, Vitamin D deficiency has been suggested to be involved in RLS augmentation. Based on these findings, we propose that the progressive reduction of selective receptors, influenced by various pathological factors, reverses the overcompensation of the dopamine intensity promoted by short-term, low-dose dopaminergic therapy in the development of augmentation. More research is needed to uncover a deeper understanding of the mechanisms underlying the RLS symptom and to develop effective RLS augmentation treatments.

Background: Sleep disorders such as insomnia can lead to a range of health problems. The high risk of side effects and drug abuse of traditional pharmacotherapy calls for a safer non-pharmacotherapy.Aims: To examine the use and efficacy of weighted blankets in improving sleep and related disorders in different populations and explore the possible mechanisms.Methods: A literature search was conducted using PubMed, Embase, Web of Science, MEDLINE, Cochrane Library and CNKI databases. Eligible studies included an intervention with weighted blankets and outcomes covering sleep and/or related disorders (behavioral disturbance, negative emotions and daytime symptoms). Studies using other deep pressure, compression, or exercise-related interventions were excluded.Conclusions: Most of the included studies showed that weighted blankets could effectively improve sleep quality and alleviate negative emotions and daytime symptoms in patients with sleep disorders, attention deficit hyperactivity disorder, autism spectrum disorder, and other related disorders, with a possible mechanism of deep pressure touch.Recommendations: Weighted blankets might be a promising tool for sleep interventions among individuals with sleep disorders in clinical settings. More high-quality and large-scale randomized controlled trials are needed to further validate the safety and efficacy of weighted blankets and explore precise mechanisms.