The Amyloid β peptide (Aβ) is a main component of senile plaques in Alzheimer's disease. Currently, NADPH oxidase (NOX) and mitochondria are considered as primary sources of ROS induced by Aβ. However, the contribution of NOX and mitochondria to Aβ-induced ROS generation has not been well defined. To delineate the relative involvement of NOX and mitochondria in Aβ-induced ROS generation and neuronal death in mouse cortical cultures, we examined the effect of NOX inhibitors, apocynin and AEBSF, and the mitochondria-targeted antioxidants (MTAs), mitotempol and mitoquinone, on Aβ-induced ROS generation and neuronal deaths. Cell death was assessed by measuring lactate dehydrogenase efflux in bathing media at 24 and 48 hrs after exposure to Aβ₁₋₄₂. Aβ₁₋₄₂ induced dose- and time-dependent neuronal deaths in cortical cultures. Treatment with 20 µM Aβ₁₋₄₂ markedly and continuously increased not only the DHE fluorescence (intracellular ROS signal), but also the DHR123 fluorescence (mitochondrial ROS signal) up to 8 hrs. Treatment with apocynin or AEBSF selectively suppressed the increase in DHE fluorescence, while treatment with mitotempol selectively suppressed the increase in DHR123 fluorescence. Each treatment with apocynin, AEBSF, mitotempol or mitoquinone significantly attenuated the Aβ₁₋₄₂-induced neuronal deaths. However, any combined treatment with apocynin/AEBSF and mitotempol/mitoquinone failed to show additive effects. These findings indicate that 20 µM Aβ₁₋₄₂ induces oxidative neuronal death via inducing mitochondrial ROS as well as NOX activation in mixed cortical cultures, but combined suppression of intracellular and mitochondrial ROS generation fail to show any additive neuroprotective effects against Aβ neurotoxicity.
Alzheimer Disease ; Amyloid beta-Peptides ; Amyloid* ; Animals ; Antioxidants* ; Baths ; Cell Death ; Fluorescence ; L-Lactate Dehydrogenase ; Mice* ; Mitochondria ; NADP* ; NADPH Oxidase* ; Neurons* ; Neuroprotective Agents ; Oxidative Stress ; Plaque, Amyloid

We examined the effect of fluoxetine, a selective serotonin reuptake inhibitor antidepressant, on neuronal viability in mouse cortical near-pure neuronal cultures. Addition of fluoxetine to the media for 24 hours induced neuronal death in a concentration-dependent manner. To delineate the mechanisms of fluoxetine-induced neuronal death, we investigated the effects of trolox, cycloheximide (CHX), BDNF, z-VAD-FMK, and various metal-chelators on fluoxetine-induced neuronal death. Neuronal death was assessed by MTT assay. The addition of 20 µM fluoxetine to the media for 24 hours induced 60–70% neuronal death, which was associated with the hallmarks of apoptosis, chromatin condensation and DNA laddering. Fluoxetine-induced death was significantly attenuated by CHX, BDNF, or z-VAD-FMK. Treatment with antioxidants, trolox and ascorbate, also markedly attenuated fluoxetine-induced death. Interestingly, some divalent cation chelators (EGTA, Ca-EDTA, and Zn-EDTA) also markedly attenuated the neurotoxicity. Fluoxetine-induced reactive oxygen species (ROS) generation was measured using the fluorescent dye 2′,7′-dichlorofluorescin diacetate. Trolox and bathocuproine disulfonic acid (BCPS), a cell membrane impermeable copper ion chelator, markedly attenuated the ROS production and neuronal death. However, deferoxamine, an iron chelator, did not affect ROS generation or neurotoxicity. We examined the changes in intracellular copper concentration using a copper-selective fluorescent dye, Phen Green FL, which is quenched by free copper ions. Fluoxetine quenched the fluorescence in neuronal cells, and the quenching effect of fluoxetine was reversed by co-treatment with BCPS, however, not by deferoxamine. These findings demonstrate that fluoxetine could induce apoptotic and oxidative neuronal death associated with an influx of copper ions.

N-acetylcysteine (NAC) has been used as an antioxidant to prevent oxidative cell death.However, we found NAC itself to induce neuronal death in mouse cortical cultures.Therefore, the current study was performed to investigate the mechanism of neuronal death caused by NAC. Cell death was assessed by measuring lactate dehydrogenase efflux to bathing media after 24-48 h exposure to NAC. NAC (0.1-10 mM) induced neuronal death in a concentration- and exposure time-dependent manner. However, NAC did not injure astrocytes even at a concentration of 10 mM. Also, 10 mM NAC markedly attenuated oxidative astrocyte death induced by 0.5 mM diethyl maleate or 0.25 mM H2O2 . The NMDA receptor antagonist MK-801 (10 μM) markedly attenuated the neuronal death caused by 10 mM NAC, while NBQX did not affect the neuronal death. Cycloheximide (a protein synthesis inhibitor, 0.1 μg/mL) and z-VAD-FMK (a caspase inhibitor, 100 μM) also significantly attenuated neuronal death. Apoptotic features such as chromatin condensation, nuclear fragmentation, and caspase 3 activation were observed 1 h after the NAC treatment. The neuronal death induced by 1 or 10 mM NAC was significantly attenuated by the treatment with 100 μM Trolox or 1 mM ascorbic acid. NAC induced the generation of intracellular reactive oxygen species (ROS), as measured by the fluorescent dye 2’,7’-dichlorofluorescein diacetate. The ROS generation was almost completely abolished by treatment with Trolox or ascorbic acid. These findings demonstrate that NAC can cause oxidative, apoptotic, and excitotoxic neuronal death in mouse neuronal cultures.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

Present study was performed to delineate the inter-relationship among neuronal death, mossy fiber sprouting (MFS) and neurogenesis in hippocampal formation of pilocarpine-treated mice. Status epilepticus was induced by intraperitoneal administration of 300 mg/kg pilocarpine in male ICR and C57BL/6 mouse. The severity of seizure was evaluated using 5 grades of Racine scales for first 4 hr after pilocarpine injection. Fluro-Jade C (FJC) staing, NeoTimm's staining and immunohistochemistry for BrdU were employed to evaluate neuronal cell death, MFS and neurogenesis, respectively. All animals in the present study induced seizures over grade 3 of Racine scale by pilocarpine injection. ICR mice show higher seizure severity (mean Racine scale; 4.37) than C57BL/6 mice do (mean Racine scale; 3.22), while the latency times for the first seizure over Racine scale grade 3 are from 15 min to 20 min and showed no difference between the 2 strains. In ICR mouse, numerous FJC-positive cells in hilus of hippocampus were detected at 4 h after pilocarpine injection, while they were not detected at that time in C57BL/6 mouse. The number of FJC-positive neuronal cells, which were densely found in the pyramidal layer of CA1, CA3 and hilus polymorphic regions of hippocampus, reached peak at 3 days after injection and then few cells were found at 7 days after injection in both strains. In control animals, BrdU positive cells in dentate subgranular layer which represent the hippocampal neurogenesis were more numerous in C57BL/6 than in ICR. The number of BrdU positive cells significantly increased at 2 days after pilocarpine injection and reached the peak at 8 days after injection and returned to control level at 15 day after injection in both strains. The percent increase of the BrdU positive cell was more prominent in ICR mouse. MFS was found at 2 weeks after the injection and the intensity of MFS was getting strong at 4 weeks after injection. There was no differences in MFS grading between 2 strains. These results suggest that there are some inter-relationships among the seizure severity, hippocampal neuronal cell death and hippocampal neurogenesis, but they don't have any significant relationships with the mossy fiber sprouting from dentate granule cells.
Animals ; Bromodeoxyuridine ; Cell Death ; Hippocampus ; Humans ; Immunohistochemistry ; Male ; Mice ; Mice, Inbred ICR ; Neurogenesis ; Neurons ; Pilocarpine ; Seizures ; Status Epilepticus ; Weights and Measures

Valproic acid (VPA) is a well-known anti-epileptic and mood stabilizing drug. A growing number of reports demonstrate that VPA is neuroprotective against various insults. Despite intensive efforts to develop new therapeutics for stroke over the past two decades, all treatments have thus far failed to show clinical effect because of treatment-limiting side effects of the drugs. Therefore, a safety-validated drug like VPA would be an attractive candidate if it has neuroprotective effects against ischemic insults. The present study was undertaken to examine whether pre- and post-insult treatments with VPA protect against brain infarct and neurological deficits in mouse transient (tMCAO) and permanent middle cerebral artery occlusion (pMCAO) models. In the tMCAO (2 hr MCAO and 22 hr reperfusion) model, intraperitoneal injection of VPA (300 mg/kg, i.p.) 30 min prior to MCAO significantly reduced the infarct size and the neurological deficit. VPA treatment immediately after reperfusion significantly reduced the infarct size. The administration of VPA at 4 hr after reperfusion failed to reduce the infarct size and the neurological deficit. In the pMCAO model, treatment with VPA (300 mg/kg, i.p.) 30 min prior to MCAO significantly attenuated the infarct size, but did not affect the neurological deficit. Western blot analysis of acetylated H3 and H4 protein levels in extracts from the ischemic cortical area showed that treatment with VPA increased the expression of acetylated H3 and H4 at 2 hrs after MCAO. These results demonstrated that treatment with VPA prior to ischemia attenuated ischemic brain damage in both mice tMCAO and pMCAO models and treatment with VPA immediately after reperfusion reduced the infarct area in the tMCAO model. VPA could therefore be evaluated for clinical use in stroke patients.
Animals ; Blotting, Western ; Brain ; Brain Ischemia ; Histone Deacetylase Inhibitors ; Humans ; Infarction, Middle Cerebral Artery ; Injections, Intraperitoneal ; Ischemia ; Mice ; Neuroprotective Agents ; Reperfusion ; Stroke ; Valproic Acid