Linear alkylbenzene sulfonate (LAS) is a synthetic anionic surfactant widely present in the environment due to its intensive production and use in the detergency field. Admitting that current procedure of risk assessment has limits in providing realistic risk assessment data and predicting the cumulative effect of the toxicant mixtures, the incorporation of information regarding the mode of action and cell response mechanism seems to be a potential solution to overcome these limits. In this regard, we investigated in this study the LAS cytotoxicity on human intestinal Caco-2 cells, trying to unveil the protein actors implicated in the cell response using proteomics approach in order to give a better understanding of the toxicological effect and allow the identification of appropriate biomarkers reflecting the mode of action associated with LAS. As results, we demonstrated that LAS induces a time- and dose-dependent cytotoxicity in Caco-2 cells accompanied by an induction of oxidative stress followed by an excessive increase of intracellular calcium level. Proteomics approach helped in discovering three informative biomarkers of effect associated with LAS cytotoxic effect, reported for the first time: calreticulin, thioredoxin, and heat shock cognate 71 (HSP7C), confirmed by real-time PCR and western blot analysis. These biomarkers could serve for more reliable future risk assessment studies that consider the toxicants mode of action in order to help in the prediction of potential cumulative effects of environmentally coexisting contaminants.
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http://dx.doi.org/10.1007/s11356-014-3074-6 | DOI Listing |
Int J Comput Assist Radiol Surg
January 2025
Advanced Medical Devices Laboratory, Kyushu University, Nishi-ku, Fukuoka, 819-0382, Japan.
Purpose: This paper presents a deep learning approach to recognize and predict surgical activity in robot-assisted minimally invasive surgery (RAMIS). Our primary objective is to deploy the developed model for implementing a real-time surgical risk monitoring system within the realm of RAMIS.
Methods: We propose a modified Transformer model with the architecture comprising no positional encoding, 5 fully connected layers, 1 encoder, and 3 decoders.
Pain Med
January 2025
IRCCS IstitutoOrtopedico Galeazzi, Unit of Clinical Epidemiology, Milan, Italy.
Objective: To assess the effectiveness of cognitive functional therapy (CFT) in reducing disability and pain compared to other interventions in chronic spinal pain patients.
Methods: Five databases were queried to October 2023 for retrieving randomized controlled trials (RCTs), including patients with chronic spinal pain and administering CFT. Primary outcomes were disability and pain.
Integr Cancer Ther
January 2025
Guang 'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Background: The incidence and mortality of lung cancer is the highest among malignant tumors worldwide, and it seriously threatens human life and health. Surgery is the primary radical treatment for lung cancer. However, patients often experience discomfort, changes in social roles, economic pressures, and other postsurgical challenges.
View Article and Find Full Text PDFJ Sex Med
January 2025
Clinical Obstetric and Gynecological V Buzzi, ASST-FBF-Sacco, Via Castelvetro 24-20124-University of the Study of Milan, Milan, Italy.
Background: Vulvodynia is a multifactorial disease affecting 7%-16% of reproductive-aged women in general population; however, little is still known about the genetics underlying this complex disease.
Aim: To compare polygenic risk scores for hormones and receptors levels in a case-control study to investigate their role in vulvodynia and their correlation with clinical phenotypes.
Methods: Our case-control study included patients with vestibulodynia (VBD) and healthy women.
BMC Oral Health
January 2025
Sub-Institute of Public Safety Standardization, China National Institute of Standardization, No.4 Zhichun Road, Haidian District, Beijing, 100191, PR China.
Background: This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient's personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications.
Methods: Relevant articles were searched to identify risk factors. Clinical knowledge and experience were used to analyse the risk factors to establish the Bayesian network.
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