The effects of acupuncture on sleep disorders and its underlying mechanism: a literature review of rodent studies.

Sleep is a set of physiological processes mainly under neurobiological regulation that affect several physiological systems, and sleep disorders are a condition where normal sleep patterns are disturbed. Clinical studies have confirmed the effects of acupuncture on sleep duration and quality. Although many studies have explored the therapeutic effects of acupuncture on sleep disorders, the mechanisms are unclear. We investigated the mechanism of acupuncture efficacy in a rodent model of sleep disorders and evaluated the therapeutic effects of acupuncture treatment. According to our results, sleep disorders are associated with several brain regions and neurotransmitters. Furthermore, this review showed that neurological processes, such as catecholamine and BDNF signaling pathways, can be regulated by acupuncture, which is a crucial aspect of the acupuncture mechanism in sleep disorders.

Effects of acupuncture on gastrointestinal diseases and its underlying mechanism: a literature review of animal studies.

Acupuncture is a non-pharmacological traditional Chinese medical technique that has been used for various types of gastrointestinal (GI) diseases in Eastern medicine. However, the specific mechanisms underlying acupuncture treatment in the GI tract have not yet been elucidated. In this study, we searched the electronic databases PUBMED, EMBASE, and MEDLINE and identified 30 eligible studies that were summarized in this review. This review demonstrates that treatments, including both manual and electroacupuncture, have therapeutic mechanisms in diverse GI diseases. The underlying mechanisms are broadly divided into the following: changes in gene expression in the gastric mucosa or nuclei of the solitary tract, metabolic change induction, regulation of anti-inflammatory substances, vagal activity increase, change in functional connectivity between brain regions, and control of the number of neurons related to GI diseases. Although this study is limited in that it does not represent all types of GI diseases with different acupuncture methods, this study identified acupuncture as effective for GI diseases through various biological mechanisms. We hope that our study will reveal various mechanisms of acupuncture in GI diseases and play an important role in the therapy and treatment of GI diseases, thus advancing the field of study.

Egg Microneedle for Transdermal Delivery of Active Liraglutide.

Liraglutide, a human glucagon-like peptide-1 (GLP-1) analog, is promising for safely treating type 2 diabetes mellitus (T2DM), compared to insulin, by significantly reducing the risk of glucose-dependent hypoglycemia. Concerns related to injection prevent T2DM patients from taking liraglutide regularly, even though once-a-day subcutaneous (SC) injections. Dissolving microneedles (DMNs) are promising substitutes for SC injection and for improving patient convenience. However, there are two fundamental limitations: the low drug delivery due to incomplete insertion and loss of drug activity during DMN fabrication. Here, it is shown that an egg microneedle (EMN) designed with three functional layered structures can maintain the maximum activity of the loaded compound during DMN fabrication and deliver it completely into the skin, with the base layer allowing the complete delivery of liraglutide, and the shell layer maintaining the drug activity by mimicking the role of albumin in eggs. In a diabetic mouse model, liraglutide administration via EMN exhibited similar effect when compared to that of injection. Therefore, EMN-mediated liraglutide administration is a good potential option for replacing liraglutide injections in T2DM treatment.

The Extracellular MicroRNAs on Inflammation: A Literature Review of Rodent Studies.

Inflammation is an indispensable biological process stimulated by infection and injuries. Inflammatory mechanisms related to extracellular vesicles (EVs), which are small membrane structures carrying various molecules, were summarized in this review. Emerging evidence from animal studies has highlighted the role of EVs in modulating inflammatory responses, by transporting various molecules involved in host defense. In this review, we have discussed the role of EV miRNAs in inflammation. Rodent studies associated with extracellular miRNAs in inflammatory diseases, published from 2012 to 2022, were explored from PUBMED, EMBASE, and MEDLINE. A total of 95 studies were reviewed. In summary, EV-associated miRNAs play a key role in various diseases, including organ injury, immune dysfunction, neurological disease, metabolic syndrome, vesicular disease, arthritis, cancer, and other inflammatory diseases. Diverse EV-associated miRNAs regulate inflammasome activation and pro- and anti-inflammatory cytokine levels by targeting genes.

Two-Stage Latent Dynamics Modeling and Filtering for Characterizing Individual Walking and Running Patterns with Smartphone Sensors.

Recently, data from built-in sensors in smartphones have been readily available, and analyzing data for various types of health information from smartphone users has become a popular health care application area. Among relevant issues in the area, one of the most prominent topics is analyzing the characteristics of human movements. In this paper, we focus on characterizing the human movements of walking and running based on a novel machine learning approach. Since walking and running are human fundamental activities, analyzing their characteristics promptly and automatically during daily smartphone use is particularly valuable. In this paper, we propose a machine learning approach, referred to as 'two-stage latent dynamics modeling and filtering' (TS-LDMF) method, where we combine a latent space modeling stage with a nonlinear filtering stage, for characterizing individual dynamic walking and running patterns by analyzing smartphone sensor data. For the task of characterizing movements, the proposed method makes use of encoding the high-dimensional sequential data from movements into random variables in a low-dimensional latent space. The use of random variables in the latent space, often called latent variables, is particularly useful, because it is capable of conveying compressed information concerning movements and efficiently handling the uncertainty originating from high-dimensional sequential observation. Our experimental results show that the proposed use of two-stage latent dynamics modeling and filtering yields promising results for characterizing individual dynamic walking and running patterns.