1,721,023 research outputs found
Vagal nerve stimulation (VNS): best responders (>80% seizures reduction) in a paediatric drug- resistant epileptic population.
No full textVagal nerve stimulation in the treatment of drug resistant epilepsy encephalopathies in inborn errors of metabolism: report of two cases
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Different targets for different patients' profile: how to modulate DBS for Parkinson's disease.
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Globus pallidus internus deep brain stimulation for the treatment of status dystonicus in tardive dystonia
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Fine tuning by protein kinases of CaV1.2 channel current in rat tail artery myocytes
No full textSeventeen compounds, rather selective, direct or indirect inhibitors and activators of PKA, PKG, and PKC, were analysed for effects on vascular CaV1.2 channel current (ICa1.2) by using the patch-clamp technique in single rat tail artery myocytes. The aim was to investigate how PKs regulate ICa1.2 and disclose any unexpected modulation of CaV1.2 channel function by these agents. The cAMP analogues 8-Br-cAMP and 6-Bnz-cAMP partially reduced ICa1.2 in dialysed cells, while weakly increasing it under the perforated configuration. The β-adrenoceptor agonist isoproterenol and the adenylate cyclase activator forskolin concentration-dependently increased ICa1.2; this effect was reversed by PKA inhibitors H-89 and KT5720, but not by PKI 6-22. The cGMP analogue 8-Br-cGMP, similarly to the NO-donor SNP, moderately reduced ICa1.2, this effect being reversed to a slight stimulation under the perforated configuration. Among PKG inhibitors, Rp-8-Br-PET-cGMPS decreased current amplitude in a concentration-dependent manner while Rp-8-Br-cGMPS was ineffective. The non-specific phosphodiesterase inhibitor IBMX increased ICa1.2, while H-89, KT5720, and PKI 6-22 antagonized this effect. The PKC activator PMA, but not the diacylglycerol analogue OAG, stimulated ICa1.2 in a concentration-dependent manner; conversely, the PKCα inhibitor Gö6976 markedly reduced basal ICa1.2 and, similarly to the PKCδ (rottlerin) and PKCε translocation inhibitors antagonised PMA-induced current stimulation. The ensemble of findings indicates that the stimulation of cAMP/PKA, in spite of the paradoxical effect of both 8-Br-cAMP and 6-Bnz-cAMP, or PKC pathways enhanced, while that of cGMP/PKG weakly inhibited ICa1.2 in rat tail artery myocytes. Since Rp-8-Br-PET-cGMPS and Gö6976 appeared to block directly CaV1.2 channel, their docking to the channel protein was investigated. Both compounds appeared to bind the α1C subunit in a region involved in CaV1.2 channel inactivation, forming an interaction network comparable to that of CaV1.2 channel blockers. Therefore, caution should accompany the use of these agents as pharmacological tools to elucidate the mechanism of action of drugs on vascular preparations
Unsupervised Learning in Precision Medicine: Unlocking Personalized Healthcare through AI
Full text linkIntegrating Artificial Intelligence (AI) into Precision Medicine (PM) is redefining healthcare, enabling personalized treatments tailored to individual patients based on their genetic code, environment, and lifestyle. AI’s ability to analyze vast and complex datasets, including genomics and medical records, facilitates the identification of hidden patterns and correlations, which are critical for developing personalized treatment plans. Unsupervised Learning (UL) is particularly valuable in PM as it can analyze unstructured and unlabeled data to uncover novel disease subtypes, biomarkers, and patient stratifications. By revealing patterns that are not explicitly labeled, unsupervised algorithms enable the discovery of new insights into disease mechanisms and patient variability, advancing our understanding of individual responses to treatment. However, the integration of AI into PM presents some challenges, including concerns about data privacy and the rigorous validation of AI models in clinical practice. Despite these challenges, AI holds immense potential to revolutionize PM, offering a more personalized, efficient, and effective approach to healthcare. Collaboration among AI developers and clinicians is essential to fully realize this potential and ensure ethical and reliable implementation in medical practice. This review will explore the latest emerging UL technologies in the biomedical field with a particular focus on PM applications and their impact on human health and well-being
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