The main aim of the present paper is to assess whether the parental generation exposure to such discharges could cause object recognition deficits in their offspring. Male and female C57Bl/6J mice were put to mate after they were exposed to 7.5% and 15% tannery effluents or water (control group), for 60 days. The male mice were withdrawn from the boxes after 15 days and the female mice remained exposed to the treatment during the gestation and lactation periods. The offspring were subjected to the object recognition test after weaning in order to assess possible cognition losses. The results of the analysis of the novel object recognition index found in the testing session (performed 1 h after the training session) applied to offspring from different experimental groups appeared to be statistically different. The novel object recognition index of the offspring from female mice exposed to tannery effluents (7.5% and 15% groups) was lower than that of the control group, and it demonstrated object recognition deficit in the studied offspring. The present study is the first to report evidences that parental exposure to effluent of tannery (father and mother) can cause object recognition deficit in the offspring, which is related to problems in the central nervous system.
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http://dx.doi.org/10.1016/j.chemosphere.2016.08.144 | DOI Listing |
Alzheimers Res Ther
January 2025
MMDN, Univ Montpellier, EPHE, INSERM, Montpellier, France.
Background: Fluoroethylnormemantine (FENM), a new Memantine (MEM) derivative, prevented amyloid-β[25-35] peptide (Aβ)-induced neurotoxicity in mice, a pharmacological model of Alzheimer's disease (AD) with high predictive value for drug discovery. Here, as drug infusion is likely to better reflect drug bioavailability due to the interspecies pharmacokinetics variation, we analyzed the efficacy of FENM after chronic subcutaneous (SC) infusion, in comparison with IP injections in two AD mouse models, Aβ-injected mice and the transgenic APP/PSEN1 (APP/PS1) line.
Methods: In Aβ-treated mice, FENM was infused at 0.
Sci Rep
January 2025
Chongqing Vocational Institute of Tourism, Chongqing, China.
To enhance enterprises' interactive exploration capabilities for unstructured chart data, this paper proposes a multimodal chart question-answering method. Facing the challenge of recognizing curved and irregular text in charts, we introduce Gaussian heatmap encoding technology to achieve character-level precise text annotation. Additionally, we combine a key point detection algorithm to extract numerical information from the charts and convert it into structured table data.
View Article and Find Full Text PDFMetab Brain Dis
January 2025
Xuzhou Engineering Research Center of Medical Genetics and Transformation, Department of Genetics, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
The widely used Radix Astragali (RA) has significant therapeutic effects on cognitive impairment (CI) caused by type 2 diabetes (T2DM). However, the effective active ingredients and the precise mechanism underly RA alleviation of T2DM-induced CI still require further study. In this study, we aim to elucidate whether and how jaranol, a key effective active ingredient in RA, influences CI in db/db mice.
View Article and Find Full Text PDFBrain Struct Funct
January 2025
Laboratoire de Neurosciences Cognitives et Adaptatives, Université de Strasbourg, 67000, Strasbourg, France.
This mini-review explores sexual dimorphism in the ventral midline thalamus, focusing on the reuniens nucleus and its role in behavioral functions. Traditionally linked to tasks such as working memory, cognitive flexibility, fear generalization, and memory consolidation, most studies have been conducted in male rodents. Research comparing the effects of ventral midline thalamus manipulations between female and male rodents is limited.
View Article and Find Full Text PDFFront Plant Sci
December 2024
School of Information Technology (IT) and Engineering, Melbourne Institute of Technology, Melbourne, VIC, Australia.
Introduction: Cotton, being a crucial cash crop globally, faces significant challenges due to multiple diseases that adversely affect its quality and yield. To identify such diseases is very important for the implementation of effective management strategies for sustainable agriculture. Image recognition plays an important role for the timely and accurate identification of diseases in cotton plants as it allows farmers to implement effective interventions and optimize resource allocation.
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