Background: Large language models (LLMs) are increasingly used in medical and dental education to enhance clinical reasoning, patient communication, and academic learning. This study evaluates the effectiveness of four advanced LLMs— ChatGPT-4 (OpenAI), Claude 3.5 Sonnet (Anthropic), Microsoft Copilot, and Grok 3 (xAI)—in conveying fluoride-related dental knowledge. Methods: A cross-sectional comparative study was conducted using a mixed-methods approach. Each LLM answered 50 multiple- choice questions (MCQs) and 10 open-ended questions on fluoride chemistry, clinical applications, and safety concerns. Two blinded experts rated the open-ended responses on accuracy, depth, clarity, and evidence. Interrater reliability was assessed using Cohen’s kappa and Spearman’s correlation, and statistical analyses were performed using analysis of variance, Kruskal-Wallis, and post-hoc tests. Results: All models showed high MCQ accuracy (88%–94%). Claude 3.5 Sonnet achieved the highest scores in open-ended responses, especially for clarity (p=0.009). Minor differences in accuracy, depth, and evidence were not statistically significant. Overall, all LLMs performed strongly, with high interrater agreement supporting result reliability. Conclusion Advanced LLMs show strong potential as supportive tools in dental education and patient communication on fluoride use. Claude 3.5 Sonnet demonstrated superior linguistic clarity, enhancing its educational value. Continued evaluation and clinical oversight are crucial for their safe and effective integration into dentistry.

Objective: Holmes tremor (HT) comprises rest, postural and intention tremor subtypes, usually involving both proximal and distal musculature. Perturbations of nigro-striatal pathways might be fundamental in the pathogenesis of HT along with cerebello-thalamic connections. Methods: Nine patients with an HT phenotype secondary to thalamic stroke were included. Epidemiological and clinical records were obtained. Structural and functional brain imaging were performed with magnetic resonance imaging (MRI) or computed tomography (CT) and positron emission tomography (PET), respectively. Levodopa was administered in sequentially increasing dosage, with various other drugs in case of inadequate response. Longitudinal follow-up was performed for at least three months. The essential tremor rating assessment scale (TETRAS) was used for assessment. Results: The mean latency from stroke to tremor onset was 50.4 ± 30.60 days (range 21–90 days). Dystonia was the most frequently associated hyperkinetic movement (88.8%). Tremor was bilateral in 22.2% of participants. Clinical response was judged based on a reduction in the TETRAS score by a prefixed value (≥ 30%), pertaining to which 55.5% (n = 5) of subjects were classified as responders and the rest as non-responders. The responders showed improvement with significantly lower doses of levodopa than the remaining nonresponders (240 ± 54.7 mg vs. 400 ± 40.8 mg; p = 0.012). Conclusion Although levodopa is useful in HT, augmenting the dosage of levodopa beyond a certain point might not benefit patients clinically. Topography of vascular lesions within the thalamus might additionally influence the phenomenology of HT.

Young-onset dementia, defined as dementia occurring under the age of 65, is an increasingly recognized cause of morbidity and disability. There are few reports of the clinical profile of young-onset dementia from India. The objective of this study was to determine the clinical profile of patients attending a specialist cognitive disorders clinic in West Bengal, an eastern state of India. Almost one-fourth (94/379, 24.5%) of all the patients with dementia were of young onset. Women constituted about one-third of these cases. There was a gradual increase in the number of cases with rising age. The most common etiologies were Alzheimer disease (33%), frontotemporal dementia (27%), and vascular dementia (20%). In contrast to other published studies of young-onset dementia, frontotemporal dementia was commoner than vascular dementia. This could be due to referral bias. A positive family history was found in close to one-fifth of the patients. Close to 10% of the patients had reversible causes of dementia. Community based study is required to confirm the findings of this study.