The scientists here examined six-month prevalence and risk/protective factors associated with self-reported HI among veterans and non-veteran U.S. Logistic regression models were constructed to examine rates of HI, and the association of HI with veteran status as well as demographic, socioeconomic, substance use, and health characteristics. Male sex, middle age, unmarried status, lifetime cigarette smoking, and worse health were associated with greater HI odds, while higher income and health insurance availability were associated with lower HI odds, irrespective of veteran status. In addition, among non-veterans, adults who were unemployed or reported any lifetime alcohol consumption were more likely to experience HI, whereas any lifetime use of drugs was associated with lower likelihood of HI. In conclusion, although distinct sociodemographic and clinical correlates of HI were identified, HI did not differ by veteran status in a fully adjusted model.

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The scientists here assessed the topography of focused ultrasound subthalamotomy by voxel-based lesion-symptom mapping to identify statistically validated brain voxels with the optimal effect against each cardinal feature and their respective cortical connectivity patterns by diffusion-weighted tractography. Bradykinesia and rigidity amelioration were associated with ablation of the rostral motor STN subregion connected to the supplementary motor and premotor cortices, whereas antitremor effect was explained by lesioning the posterolateral STN projection to the primary motor cortex. These findings were corroborated prospectively in another Parkinson disease cohort. This work concurs with recent deep brain stimulation findings that suggest different corticosubthalamic circuits underlying each Parkinson disease cardinal feature.

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Mild cognitive impairment poses significant challenges in early diagnosis and timely intervention. Underdiagnosis, coupled with the economic and social burden of dementia, necessitates more precise detection methods. Machine learning algorithms show promise in managing complex data for MCI and dementia prediction.

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