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Artificial intelligence (AI) is increasingly used to make important decisions, from university admissions selections to loan determinations to the distribution of COVID-19 vaccines. These uses of AI raise a host of concerns about discrimination, accuracy, fairness, and accountability. In the United States, recent proposals for regulating AI focus largely on ex ante and systemic governance. This Article argues instead—or really, in addition—for an individual right to contest AI decisions, modeled on due process but adapted for the digital age. The European Union, in fact, recognizes such a right, and a growing number of institutions around the world now call for its establishment. This Article argues that despite considerable differences between the United States and other countries, establishing the right to contest AI decisions here would be in keeping with a long tradition of due process theory. This Article then fills a gap in the literature, establishing a theoretical scaffolding for discussing what a right to contest should look like in practice. This Article establishes four contestation archetypes that should serve as the bases of discussions of contestation both for the right to contest AI and in other policy contexts. The contestation archetypes vary along two axes: from contestation rules to standards and from emphasizing procedure to establishing substantive rights. This Article then discusses four processes that illustrate these archetypes in practice, including the first indepth consideration of the GDPR’s right to contestation for a U.S. audience. Finally, this Article integrates findings from these investigations to develop normative and practical guidance for establishing a right to contest AI.

Patients with advanced Parkinson’s disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recording in unscripted environments. For validation purposes, patients were accompanied by a movement disorder expert, and their motor state was passively evaluated every minute. We acquired a dataset of 8,661 minutes of IMU data from 30 patients, with annotations about the motor state (OFF,ON, DYSKINETIC) based on MDS-UPDRS global bradykinesia item and the AIMS upper limb dyskinesia item. Using a 1-minute window size as an input for a convolutional neural network trained on data from a subset of patients, we achieved a three-class balanced accuracy of 0.654 on data from previously unseen subjects. This corresponds to detecting the OFF, ON, or DYSKINETIC motor state at a sensitivity/specificity of 0.64/0.89, 0.67/0.67 and 0.64/0.89, respectively. On average, the model outputs were highly correlated with the annotation on a per subject scale (r = 0.83/0.84; p < 0.0001), and sustained so for the highly resolved time windows of 1 minute (r = 0.64/0.70; p < 0.0001). Thus, we demonstrate the feasibility of long-term motor-state detection in a free-living setting with deep learning using motion data from a single IMU.

Background The lower Dipteran fungus gnat, Bradysia (aka Sciara ) coprophila , has compelling chromosome biology. Paternal chromosomes are eliminated during male meiosis I and both maternal X sister chromatids are retained in male meiosis II. Embryos start with three copies of the X chromosome, but 1–2 copies are eliminated from somatic cells as part of sex determination, and one is eliminated in the germline to restore diploidy. In addition, there is gene amplification in larval polytene chromosomes, and the X polytene chromosome folds back on itself mediated by extremely long-range interactions between three loci. These developmentally normal events present opportunities to study chromosome behaviors that are unusual in other systems. Moreover, little is known about the centromeric and telomeric sequences of lower Dipterans in general, and there are recent claims of horizontally-transferred genes in fungus gnats. Overall, there is a pressing need to learn more about the fungus gnat chromosome sequences. Results We produced the first chromosome-scale models of the X and autosomal chromosomes where each somatic chromosome is represented by a single scaffold. Extensive analysis supports the chromosome identity and structural accuracy of the scaffolds, demonstrating they are co-linear with historical polytene maps, consistent with evolutionary expectations, and have accurate centromere positions, chromosome lengths, and copy numbers. The positions of alleged horizontally-transferred genes in the nuclear chromosomes were broadly confirmed by genomic analyses of the chromosome scaffolds using Hi-C and single-molecule long-read datasets. The chromosomal context of repeats shows family-specific biases, such as retrotransposons correlated with the centromeres. Moreover, scaffold termini were enriched with arrays of retrotransposon-related sequence as well as nucleosome-length (~ 175 bp) satellite repeats. Finally, the Hi-C data captured Mb-scale physical interactions on the X chromosome that are seen in polytene spreads, and we characterize these interesting “fold-back regions” at the sequence level for the first time. Conclusions The chromosome scaffolds were shown to be of exceptional quality, including loci harboring horizontally-transferred genes. Repeat analyses demonstrate family-specific biases and telomere repeat candidates. Hi-C analyses revealed the sequences of ultra-long-range interactions on the X chromosome. The chromosome-scale scaffolds pave the way for further studies of the unusual chromosome movements in Bradysia coprophila .

Parkinson's Disease is a progressive neurodegenerative disorder marked by motor fluctuations in later disease stages that complicate treatment with levodopa. Traditional approaches to dosing often fail to capture the complex and dynamic nature of these fluctuations. In this study, we present the PD9™ algorithm, a novel approach to continuous motor state monitoring using data from a wrist-worn inertial measurement unit sensor. The algorithm provides minute-by-minute assessments of motor state severity on a unified scale quantifying bradykinesia, dyskinesia, and ON states. Data collected from 67 patients over 55,482 min were analyzed to assess levodopa response cycles. Across 218 identified levodopa cycles, the algorithm revealed reproducible patterns of symptom development based on the motor state at the time of levodopa administration. In particular, levodopa doses administered during non-ideal motor states (e.g., during dyskinesia) highlighted the limitations of fixed, empirically determined dosing regimens and underscore the need for individualized therapy, based on motor state. These findings demonstrate how AI-enabled continuous monitoring could help realize a more personalized treatment of Parkinson's disease and improve patient outcomes.

Background Gait impairment is a key feature in later stages of Parkinson’s disease (PD), which often responds poorly to pharmacological therapies. Neuromodulatory treatment by low-intensity noisy galvanic vestibular stimulation (nGVS) has indicated positive effects on postural instability in PD, which may possibly be conveyed to improvement of dynamic gait dysfunction. Objective To investigate the effects of individually tuned nGVS on normal and cognitively challenged walking in PD patients with mild-to-moderate gait dysfunction. Methods Effects of nGVS of varying intensities (0–0.7 mA) on body sway were examined in 32 patients with PD (ON medication state, Hoehn and Yahr: 2.3 ± 0.5), who were standing with eyes closed on a posturographic force plate. Treatment response and optimal nGVS stimulation intensity were determined on an individual patient level. In a second step, the effects of optimal nGVS vs. sham treatment on walking with preferred speed and with a cognitive dual task were investigated by assessment of spatiotemporal gait parameters on a pressure-sensitive gait carpet. Results Evaluation of individual balance responses yielded that 59% of patients displayed a beneficial balance response to nGVS treatment with an average optimal improvement of 23%. However, optimal nGVS had no effects on gait parameters neither for the normal nor the cognitively challenged walking condition compared to sham stimulation irrespective of the nGVS responder status. Conclusions Low-intensity nGVS seems to have differential treatment effects on static postural imbalance and continuous gait dysfunction in PD, which could be explained by a selective modulation of midbrain-thalamic circuits of balance control.

The potential of psychedelics to persistently treat substance use disorders is known since the 1960s. However, the biological mechanisms responsible for their therapeutic effects have not yet been fully elucidated. While it is known that serotonergic hallucinogens induce changes in gene expression and neuroplasticity, particularly in prefrontal regions, theories on how specifically this counteracts the alterations that occur in neuronal circuitry throughout the course of addiction are largely unknown. This narrative mini-review endeavors to synthesize well-established knowledge from addiction research with findings and theories regarding the neurobiological effects of psychedelics to give an overview of the potential mechanisms that underlie the treatment of substance use disorders with classical hallucinogenic compounds and point out gaps in the current understanding.

Gait festination is one of the most characteristic gait disturbances in patients with Parkinson’s disease or atypical parkinsonism. Although festination is common and disabling, it has received little attention in the literature, and different definitions exist. Here, we argue that there are actually two phenotypes of festination. The first phenotype entails a primary locomotion disturbance, due to the so-called sequence effect: a progressive shortening of step length, accompanied by a compensatory increase in cadence. This phenotype strongly relates to freezing of gait with alternating trembling of the leg. The second phenotype results from a postural control problem (forward leaning of the trunk) combined with a balance control deficit (inappropriately small balance-correcting steps). In this viewpoint, we elaborate on the possible pathophysiological substrate of these two phenotypes of festination and discuss their management in daily clinical practice.

Misfolded α-synuclein (αSyn) is the hallmark of α-synucleinopathies such as Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). While seed amplification assays (SAA) have demonstrated ultrasensitive detection of misfolded αSyn, they have been primarily used reliably to provide binary (positive/negative) results for diagnostic purposes. We developed an SAA with enhanced specificity for Lewy-fold α-synucleinopathies and introduced a quantifiable measure correlating with clinical severity. Cerebrospinal fluid (CSF) of 170 patients with neurodegenerative diseases and controls was analyzed. Blinded measurements demonstrated 97.8% sensitivity and 100% specificity for Lewy-fold α-synucleinopathies, correctly identifying PD and DLB while excluding MSA. In addition, we validated the strain specificity of the assay by testing brain homogenates from 30 neuropathologically confirmed cases. A novel Lewy-fold pathology (LFP) score based on positive signals in a dilution series provided a quantitative measure of αSyn seeds. The LFP score significantly correlated with motor and cognitive impairment presented by Hoehn and Yahr stage, MDS-UPDRS III, and MoCA. Longitudinal tracking in seven PD cases showed progressive LFP score increases corresponding with clinical deterioration, highlighting the assay’s potential for monitoring disease progression at an individual level. Our Lewy-fold-specific SAA enhances ante-mortem diagnosis and differentiates Lewy-fold α-synucleinopathies from MSA. Unlike previous assays, the LFP score offers a quantitative assessment, showing promise as a progression marker and pharmacodynamic biomarker for αSyn-targeting therapies. This represents an important step toward developing an αSyn SAA that could help to track disease progression quantitatively, with potential applications in both clinical diagnostics and therapeutic trials.

To the Editor: The randomized, controlled trial by Marques et al. (Nov. 9 issue) 1 provides evidence that electromyographically guided injections of 150 to 200 IU of onabotulinumtoxinA reduced the severity of essential head tremor. We would like to point out that electromyographic recordings detect activity of tremulous muscles but may not provide precise anatomical localization for injection. Indeed, studies have shown that accuracy for injection into specific muscles is low when it is performed without ultrasonographic guidance. 2,3 Research with the use of ultrasonographically guided electromyographic analyses has shown that the inferior oblique capitis muscle is the most active in dystonic . . .