Sleep, Glial Function, and the Endocannabinoid System: Implications for Neuroinflammation and Sleep Disorders.

The relationship between sleep, glial cells, and the endocannabinoid system represents a multifaceted regulatory network with profound implications for neuroinflammation and cognitive function. The molecular underpinnings of sleep modulation by the endocannabinoid system and its influence on glial cell activity are discussed, shedding light on the reciprocal relationships that govern these processes. Emphasis is placed on understanding the role of glial cells in mediating neuroinflammatory responses and their modulation by sleep patterns. Additionally, this review examines how the endocannabinoid system interfaces with glia-immune signaling to regulate inflammatory cascades within the central nervous system. Notably, the cognitive consequences of disrupted sleep, neuroinflammation, and glial dysfunction are addressed, encompassing implications for neurodegenerative disorders, mood disturbances, and cognitive decline. Insights into the bidirectional modulation of cognitive function by the endocannabinoid system in the context of sleep and glial activity are explored, providing a comprehensive perspective on the potential mechanisms underlying cognitive impairments associated with sleep disturbances. Furthermore, this review examines potential therapeutic avenues targeting the endocannabinoid system to mitigate neuroinflammation, restore glial homeostasis, and normalize sleep patterns. The identification of novel therapeutic targets within this intricate regulatory network holds promise for addressing conditions characterized by disrupted sleep, neuroinflammation, and cognitive dysfunction. This work aims to examine the complexities of neural regulation and identify potential avenues for therapeutic intervention.

Interplay between the Glymphatic System and the Endocannabinoid System: Implications for Brain Health and Disease.

The intricate mechanisms governing brain health and function have long been subjects of extensive investigation. Recent research has shed light on two pivotal systems, the glymphatic system and the endocannabinoid system, and their profound role within the central nervous system. The glymphatic system is a recently discovered waste clearance system within the brain that facilitates the efficient removal of toxic waste products and metabolites from the central nervous system. It relies on the unique properties of the brain's extracellular space and is primarily driven by cerebrospinal fluid and glial cells. Conversely, the endocannabinoid system, a multifaceted signaling network, is intricately involved in diverse physiological processes and has been associated with modulating synaptic plasticity, nociception, affective states, appetite regulation, and immune responses. This scientific review delves into the intricate interconnections between these two systems, exploring their combined influence on brain health and disease. By elucidating the synergistic effects of glymphatic function and endocannabinoid signaling, this review aims to deepen our understanding of their implications for neurological disorders, immune responses, and cognitive well-being.

Scientific facts improve cannabis perception and public opinion: results from Sinaloa, México.

Cannabis, the most prevalent drug in Latin America, has long been associated with the state of Sinaloa, Mexico, known for its cultivation and distribution. Despite increasing global acceptance, cannabis use remains stigmatized in Mexican society, driven by perceptions of it as a highly psychoactive and addictive substance lacking medicinal or industrial value. This study investigates the impact of scientific information on societal perceptions of cannabis in Sinaloa. A large convenience sample of 3162 individuals from Sinaloa participated in this research, responding to a questionnaire on cannabis consumption and attitudes. Participants were then subjected to an intervention consisting of an informative briefing based on the documents "Using Evidence to Talk About Cannabis" and "State of the Evidence: cannabis use and regulation" by the International Centre for Science in Drug Policy. After the intervention, participants' attitudes were immediately reevaluated through the same questionnaire, allowing for a comparison of pre- and post-intervention responses. The results indicate that the intervention (providing scientific information) significantly influenced attitudes toward cannabis, with education and age playing prominent roles in its effectiveness. Notably, the intervention fostered more positive or more neutral attitudes, potentially reducing stigma and promoting a better-informed perspective on cannabis. This study highlights the pivotal role of evidence in shaping informed citizens' views, while underscoring the importance of countering misinformation for societal progress. These findings have significant implications for forthcoming cannabis policy modifications in Mexico, emphasizing the necessity of engaging knowledgeable individuals in policy decisions to address the violence and inequalities associated with the illicit drug trade, particularly in Sinaloa.

Clinical Predictors of Monkeypox Diagnosis: A Case-Control Study in a Nonendemic Region during the 2022 Outbreak.

Monkeypox (Mpox) is an emerging zoonotic disease with the potential for severe complications. Early identification and diagnosis are essential to prompt treatment, control its spread, and reduce the risk of human-to-human transmission. This study aimed to develop a clinical diagnostic tool and describe the clinical and sociodemographic features of 19 PCR-confirmed Mpox cases during an outbreak in a nonendemic region of northwestern Mexico. The median age of patients was 35 years, and most were male. Mpox-positive patients commonly reported symptoms such as fever, lumbago, and asthenia, in addition to experiencing painful ulcers and a high frequency of HIV infection among people living with HIV (PLWH). Two diagnostic models using logistic regression were devised, with the best model exhibiting a prediction accuracy of 0.92 (95% CI: 0.8-1), a sensitivity of 0.86, and a specificity of 0.93. The high predictive values and accuracy of the top-performing model highlight its potential to significantly improve early Mpox diagnosis and treatment in clinical settings, aiding in the control of future outbreaks.