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Cellulose hydrogels derived from agave bagasse were formulated to promote the regeneration of gingival connective tissue in lagomorphs. Three treatment modalities were randomly implanted in the gingival diastema area in 16 rabbits. The general characteristics were analyzed and histopathological studies were carried out at 4, 8, 12, and 16 weeks. A chi-squared test was performed using IBM-SPSS version 25, indicating that cellulose hydrogels implanted in lagomorph’s gingival tissue showed the presence of greater angiogenesis and fibrogenesis at the four evaluation intervals during 16 consecutive weeks. The presence of inflammatory infiltrates had no significant impact. No significant changes were observed in body weight and water and food intake. This suggests that hydrogels contribute to the regeneration and/or repair of oral connective tissue, showing angiogenesis and fibrogenesis in 50 to 100% of rabbits tested with hydrogel cellulose membrane. Regarding angiogenesis, in the specimens where membranes were implanted, its presence predominated in all variants (50%), followed by diffuse angiogenesis (37.5%), and finally the absence of angiogenesis (12.5%).

Cellulose hydrogels derived from agave bagasse were formulated to promote the regeneration of gingival connective tissue in lagomorphs. Three treatment modalities were randomly implanted in the gingival diastema area in 16 rabbits. The general characteristics were analyzed and histopathological studies were carried out at 4, 8, 12, and 16 weeks. A chi-squared test was performed using IBM-SPSS version 25, indicating that cellulose hydrogels implanted in lagomorph's gingival tissue showed the presence of greater angiogenesis and fibrogenesis at the four evaluation intervals during 16 consecutive weeks. The presence of inflammatory infiltrates had no significant impact. No significant changes were observed in body weight and water and food intake. This suggests that hydrogels contribute to the regeneration and/or repair of oral connective tissue, showing angiogenesis and fibrogenesis in 50 to 100% of rabbits tested with hydrogel cellulose membrane. Regarding angiogenesis, in the specimens where membranes were implanted, its presence predominated in all variants (50%), followed by diffuse angiogenesis (37.5%), and finally the absence of angiogenesis (12.5%). [ABSTRACT FROM AUTHOR]

Cannabidiol (CBD) is a natural product associated with a wide range of biological and therapeutic activities. Despite the widespread cultural acceptance of CBD as a medicinal agent, much remains to be determined regarding its precise mechanism(s) of action in treating multiple conditions. CBD has been shown to promiscuously interact with several neurological targets with varying affinities. To expand the chemical space of phytocannabinoids and develop novel chemical compounds, we have designed and synthesized a series of CBD and Δ 8 -THC homodimers, and CBD/Δ 8 -THC heterodimers. The capacity of the dimers to interact with a panel of CNS targets was explored along with the capacity to activate CB1 receptors, as measured by a GIRK channel activation assay. In the panel screen, the dimers were shown to be generally more active toward 5-HT2B and sigma 2 receptors with a range of K i values from 0.6 to 8.7 μM. These findings provide early evidence that this new class of dimers can serve as novel chemical entities to explore receptor function and the potential for these dimers to have bivalent, bitopic, or dual mechanisms of action.

Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuable strategy for studying the prevalence of infectious diseases within populations in a time- and resource-efficient manner, as wastewater samples are representative of all cases within the catchment area, whether they are clinically reported or not. However, analysis and interpretation of WBS datasets for decision-making during public health emergencies, such as the COVID-19 pandemic, remains an area of opportunity. In this article, a database obtained from wastewater sampling at wastewater treatment plants (WWTPs) and university campuses in Monterrey and Mexico City between 2021 and 2022 was used to train simple clustering- and regression-based risk assessment models to allow for informed prevention and control measures in high-affluence facilities, even if working with low-dimensionality datasets and a limited number of observations. When dividing weekly data points based on whether the seven-day average daily new COVID-19 cases were above a certain threshold, the resulting clustering model could differentiate between weeks with surges in clinical reports and periods between them with an 87.9% accuracy rate. Moreover, the clustering model provided satisfactory forecasts one week (80.4% accuracy) and two weeks (81.8%) into the future. However, the prediction of the weekly average of new daily cases was limited (R 2 = 0.80, MAPE = 72.6%), likely because of insufficient dimensionality in the database. Overall, while simple, WBS-supported models can provide relevant insights for decision-makers during epidemiological outbreaks, regression algorithms for prediction using low-dimensionality datasets can still be improved.