The roles of the circadian hormone melatonin in drug addiction

Identification of drug use degree by integrating multi-modal features with dual-input deep learning method

Most of studies on drug use degree are based on subjective judgments without objective quantitative assessment, in this paper, a dual-input bimodal fusion algorithm is proposed to study drug use degree by using electroencephalogram (EEG) and near-infrared spectroscopy (NIRS). Firstly, this paper uses the optimized dual-input multi-modal TiCBnet for extracting the deep encoding features of the bimodal signal, then fuses and screens the features using different methods, and finally fused deep encoding features are classified. The classification accuracy of bimodal is found to be higher than that of single modal, and the classification accuracy is up to 89.9%.

Disrupted Circadian Rhythms and Substance Use Disorders: A Narrative Review

Substance use disorder is a major global health concern, with a high prevalence among adolescents and young adults. The most common substances of abuse include alcohol, marijuana, cocaine, nicotine, and opiates. Evidence suggests that a mismatch between contemporary lifestyle and environmental demands leads to disrupted circadian rhythms that impair optimal physiological and behavioral function, which can increase the vulnerability to develop substance use disorder and related problems. The circadian system plays an important role in regulating the sleep-wake cycle and reward processing, both of which directly affect substance abuse. Distorted substance use can have a reciprocal effect on the circadian system by influencing circadian clock gene expression. Considering the detrimental health consequences and profound societal impact of substance use disorder, it is crucial to comprehend its complex association with circadian rhythms, which can pave the way for the generation of novel chronotherapeutic treatment approaches. In this narrative review, we have explored the potential contributions of disrupted circadian rhythms and sleep on use and relapse of different substances of abuse. The involvement of circadian clock genes with drug reward pathways is discussed, along with the potential research areas that can be explored to minimize disordered substance use by improving circadian hygiene.

Melatonin ameliorates multiorgan injuries induced by severe acute pancreatitis in mice by regulating the Nrf2 signaling pathway

Severe acute pancreatitis (SAP) is a complicated inflammatory reaction that impacts the pancreas, often resulting in damage to numerous organs. This disorder encompasses a range of processes such as inflammation, oxidative stress, and pancreatitis. The hormone melatonin (MT) is primarily secreted by the pineal gland and plays a crucial role in mitigating inflammation, countering the harmful effects of free radicals, and regulating oxidative stress. The aim of this research was to investigate the potential protective impact and the underlying mechanism of melatonin in mice afflicted with SAP. The biochemical and histological assessments unequivocally demonstrated that melatonin effectively inhibited necrosis, infiltration, edema and cell death in pancreatic tissues, thereby suppressing acute pancreatitis. Notably, melatonin also alleviated the consequent harm to distant organs, notably the lungs, liver, and kidneys. Furthermore, both preventive and therapeutic administration of melatonin prompted nuclear factor E2-related factor 2 (Nrf2) activation followed by Nrf2 target gene expression. Nrf2 initiates the activation of antioxidant genes, thereby providing defense against oxidative stress. Conversely, Nrf2 reduction may contribute to impaired antioxidant protection in SAP. The beneficial impact of Nrf2 on antioxidants was absent in Nrf2-knockout mice, leading to the accumulation of LDH and exacerbation of cell death. This deterioration in both pancreatitis and injuries in distant organs intensified significantly. The results indicate that melatonin has an enhanced ability to protect against multiorgan damage caused by SAP, which is accomplished through the increase in Nrf2 expression. Additionally, Nrf2 initiates the activation of antioxidant genes that offer defense against cell death.

Melatonin-Derived Carbon Dots with Free Radical Scavenging Property for Effective Periodontitis Treatment via the Nrf2/HO-1 Pathway

Periodontitis is a chronic inflammatory disease closely associated with reactive oxygen species (ROS) involvement. Eliminating ROS to control the periodontal microenvironment and alleviate the inflammatory response could potentially serve as an efficacious therapy for periodontitis. Melatonin (MT), renowned for its potent antioxidant and anti-inflammatory characteristics, is frequently employed as an ROS scavenger in inflammatory diseases. However, the therapeutic efficacy of MT remains unsatisfactory due to the low water solubility and poor bioavailability. Carbon dots have emerged as a promising and innovative nanomaterial with facile synthesis, environmental friendliness, and low cost. In this study, melatonin-derived carbon dots (MT-CDs) were successfully synthesized via the hydrothermal method. The MT-CDs have good water solubility and biocompatibility and feature excellent ROS-scavenging capacity without additional modification. The in vitro experiments proved that MT-CDs efficiently regulated intracellular ROS, which maintained mitochondrial homeostasis and suppressed the production of inflammatory mediators. Furthermore, findings from the mouse model of periodontitis indicated that MT-CDs significantly inhibited the deterioration of alveolar bone and reduced osteoclast activation and inflammation, thereby contributing to the regeneration of damaged tissue. In terms of the mechanism, MT-CDs may scavenge ROS, thereby preventing cellular damage and the production of inflammatory factors by regulating the nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) pathway. The findings will offer a vital understanding of the advancement of secure and effective ROS-scavenging platforms for more biomedical applications.

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment; however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives: Drugs and Treatments, Causes and Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined six macro-parameters (Diseases and Disorders, Individual Factors, Social and Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for a social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

Acupuncture ameliorates Mobile Phone Addiction with sleep disorders and restores salivary metabolites rhythm

OBJECTIVES

Mobile Phone Addiction (MPA) is a novel behavioral addiction resulting in circadian rhythm disorders that severely affect mental and physical health. The purpose of this study is to detect rhythmic salivary metabolites in MPA with sleep disorder (MPASD) subjects and investigate the effects of acupuncture.

METHODS

Six MPASD patients and six healthy controls among the volunteers were enrolled by MPA Tendency Scale (MPATS) and Pittsburgh Sleep Quality Index (PSQI), then the salivary samples of MPASD and healthy controls were collected every 4-h for three consecutive days. Acupuncture was administered for 7 days to MPASD subjects, then saliva samples were collected again. Salivary metabolomes were analyzed with the method of LC-MS.

RESULT

According to our investigation, 70 (57.85%) MPA patients and 56 (46.28%) MPASD patients were identified among 121 volunteers. The symptoms of the 6 MPASD subjects were significantly alleviated after acupuncture intervention. The number of rhythmic saliva metabolites dropped sharply in MPASD subjects and restored after acupuncture. Representative rhythmic saliva metabolites including melatonin, 2'-deoxyuridine, thymidine, thymidine 3',5'-cyclic monophosphate lost rhythm and restored after acupuncture, which may attribute to promising MPASD treatment and diagnosis biomarkers. The rhythmic saliva metabolites of healthy controls were mainly enriched in neuroactive ligand-receptor interaction, whereas polyketide sugar unit biosynthesis was mainly enriched in MPASD patients.

CONCLUSION

This study revealed circadian rhythm characteristics of salivary metabolites in MPASD and that acupuncture could ameliorate MPASD by restoring part of the dysrhythmia salivary metabolites.