Staged Screening Identifies People with Biomarkers Related to Neuronal Alpha-Synuclein Disease.

Objective: Remote identification of individuals with severe hyposmia may enable scalable recruitment of participants with underlying alpha-synuclein aggregation. We evaluated the performance of a staged screening paradigm using remote smell testing to enrich for abnormal dopamine transporter single-photon emission computed tomography imaging (DAT-SPECT) and alpha-synuclein aggregation.

Methods: The Parkinson's Progression Markers Initiative (PPMI) recruited participants for the prodromal cohort who were 60-years and older without a Parkinson's disease diagnosis.

Impact of dopamine deficiency and REM sleep behavior disorder on cognition in early neuronal synuclein disease with hyposmia.

Objectives: To determine the impact of dopamine deficiency and isolated REM sleep behavior disorder (iRBD) on cognitive performance in early neuronal alpha-synuclein disease (NSD) with hyposmia.

Methods: Using Parkinson's Progression Markers Initiative baseline data, cognitive performance was assessed with a cognitive summary score (CSS) developed by applying regression-based internal norms derived from a robust healthy control (HC) group. Performance was examined for participants with hyposmia classified as NSD-Integrated Staging System (NSD-ISS) Stage 2, either Stage 2A (CSF alpha-synuclein seed amplification assay [SAA]+, SPECT dopamine transporter scan [DaTscan]-) or 2B (SAA+, DaTscan+).

From "invisible" to "audible": Features extracted during simple speech tasks classify patient-reported fatigue in multiple sclerosis.

Background: Fatigue is a major "invisible" symptom in people with multiple sclerosis (PwMS), which may affect speech. Automated speech analysis is an objective, rapid tool to capture digital speech biomarkers linked to functional outcomes.

Objective: To use automated speech analysis to assess multiple sclerosis (MS) fatigue metrics.

Validation of Parkinson's Disease Ascertainment in the Veterans Administration Electronic Medical Record.

Background: Electronic medical record (EMR)-based studies hold great potential for epidemiologic investigations of Parkinson's disease (PD) causal factors and phenomenology, but diagnostic misclassification may obscure or bias inferences.

Objectives: The aims were to determine the validity of PD diagnostic codes in the Veterans Administration (VA) national electronic medical databases and develop recommendations for maximizing ascertainment accuracy.

Methods: We investigated a cohort of 146,776 veterans who utilized VA healthcare between 1999 and 2021.

Analysis of ChatGPT in the Triage of Common Spinal Complaints.

Background: ChatGPT is a natural language processing chatbot with a significant prevalence in modern media with a clear application in the medical triage workflow. ChatGPT has shown significant capacity for understanding clinical vignettes, radiology reports, and even passing the American Board of Neurological Surgery board examination. There has never been an evaluation of the chatbot in triage and diagnosing spinal vignettes common to primary and urgent care practice.

Range maps and waterbody occupancy data for 1158 freshwater macroinvertebrate genera in the contiguous USA.

Range maps are used to estimate the geographic extent of taxa, providing valuable information for biodiversity and conservation research and management. Freshwater macroinvertebrates are not well-represented in the range map literature relative to freshwater vertebrates. To address this knowledge gap, we provide range maps for 1158 freshwater macroinvertebrate genera based on two decades of publicly available occurrence data from the USEPA National Aquatic Resource Surveys, which included 11,628 sites and 6,906,990 organisms across the contiguous USA.

ChatGPT as a Decision Support Tool in the Management of Chiari I Malformation: A Comparison to 2023 CNS Guidelines.

Objective: ChatGPT has been increasingly investigated for its ability to provide clinical decision support in the management of neurosurgical pathologies. However, concerns exist regarding the validity of its responses. To assess the reliability of ChatGPT, we compared its responses against the 2023 Congress of Neurological Surgeons (CNS) guidelines for patients with Chiari I Malformation (CIM).

Parkinson's Disease Progression and Exposure to Contaminated Water at Camp Lejeune.

Background: We recently reported an increased risk of Parkinson's disease (PD) in service members who resided at Marine Base Camp Lejeune, North Carolina, when water supplies were contaminated with trichloroethylene and other volatile organic compounds (VOCs). Prior studies suggest that environmental exposures may affect PD phenotype or progression, but this has not been reported for VOCs.

Objective: The objective of this study was to test whether PD progression is faster in individuals exposed to VOCs in water at Camp Lejeune.

A Bibliometric Analysis of the 20 Most Cited Articles on Sacrococcygeal Chordomas.

This study aims to summarize sacrococcygeal chordoma literature through bibliometric analysis and to offer insights into key studies to guide clinical practices and future research. The Web of Science database was searched using the terms "sacral chordoma", "chordomas of the sacrum", "chordomas of the sacral spine", "chordomas of the sacrococcygeal region", "coccygeal chordoma", and "coccyx chordoma". Articles were analyzed for citation count, authorship, publication date, journal, research area tags, impact factor, and evidence level.

Enhancing Diagnostic Support for Chiari Malformation and Syringomyelia: A Comparative Study of Contextualized ChatGPT Models.

Objectives: The rapidly increasing adoption of large language models in medicine has drawn attention to potential applications within the field of neurosurgery. This study evaluates the effects of various contextualization methods on ChatGPT's ability to provide expert-consensus aligned recommendations on the diagnosis and management of Chiari Malformation and Syringomyelia.

Methods: Native GPT4 and GPT4 models contextualized using various strategies were asked questions revised from the 2022 Chiari and Syringomyelia Consortium International Consensus Document.

Occupational Pesticide Exposure in Parkinson's Disease Related to GBA and LRRK2 Variants.

Background: The penetrance of common genetic risk variants for Parkinson's disease (PD) is low. Pesticide exposure increases PD risk, but how exposure affects penetrance is not well understood.

Objective: To determine the relationship between occupational pesticide exposure and PD in people with LRRK2 and GBA risk variants.

A meta-analysis on global change drivers and the risk of infectious disease.

Anthropogenic change is contributing to the rise in emerging infectious diseases, which are significantly correlated with socioeconomic, environmental and ecological factors. Studies have shown that infectious disease risk is modified by changes to biodiversity, climate change, chemical pollution, landscape transformations and species introductions. However, it remains unclear which global change drivers most increase disease and under what contexts.

Enthesis maturation in engineered ligaments is differentially driven by loads that mimic slow growth elongation and rapid cyclic muscle movement.

Entheses are complex attachments that translate load between elastic-ligaments and stiff-bone via organizational and compositional gradients. Neither natural healing, repair, nor engineered replacements restore these gradients, contributing to high re-tear rates. Previously, we developed a culture system which guides ligament fibroblasts in high-density collagen gels to develop early postnatal-like entheses, however further maturation is needed.

Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review.

Introduction: Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS.

The Thyroid Hormone Axis and Female Reproduction.

Thyroid function affects multiple sites of the female hypothalamic-pituitary gonadal (HPG) axis. Disruption of thyroid function has been linked to reproductive dysfunction in women and is associated with menstrual irregularity, infertility, poor pregnancy outcomes, and gynecological conditions such as premature ovarian insufficiency and polycystic ovarian syndrome. Thus, the complex molecular interplay between hormones involved in thyroid and reproductive functions is further compounded by the association of certain common autoimmune states with disorders of the thyroid and the HPG axes.

Impact of the Dopamine System on Long-Term Cognitive Impairment in Parkinson Disease: An Exploratory Study.

Background: Little is known about the impact of the dopamine system on development of cognitive impairment (CI) in Parkinson disease (PD).

Objectives: We used data from a multi-site, international, prospective cohort study to explore the impact of dopamine system-related biomarkers on CI in PD.

Methods: PD participants were assessed annually from disease onset out to 7 years, and CI determined by applying cut-offs to four measures: (1) Montreal Cognitive Assessment; (2) detailed neuropsychological test battery; (3) Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) cognition score; and (4) site investigator diagnosis of CI (mild cognitive impairment or dementia).

Early detection of Parkinson's disease through enriching the electronic health record using a biomedical knowledge graph.

Introduction: Early diagnosis of Parkinson's disease (PD) is important to identify treatments to slow neurodegeneration. People who develop PD often have symptoms before the disease manifests and may be coded as diagnoses in the electronic health record (EHR).

Methods: To predict PD diagnosis, we embedded EHR data of patients onto a biomedical knowledge graph called Scalable Precision medicine Open Knowledge Engine (SPOKE) and created patient embedding vectors.

Risk of Parkinson Disease Among Service Members at Marine Corps Base Camp Lejeune.

Importance: An increased risk of Parkinson disease (PD) has been associated with exposure to the solvent trichloroethylene (TCE), but data are limited. Millions of people in the US and worldwide are exposed to TCE in air, food, and water.

Objective: To test whether the risk of PD is higher in veterans who served at Marine Corps Base Camp Lejeune, whose water supply was contaminated with TCE and other volatile organic compounds (VOCs), compared with veterans who did not serve on that base.

Temporal novelty detection and multiple timescale integration drive Drosophila orientation dynamics in temporally diverse olfactory environments.

To survive, insects must effectively navigate odor plumes to their source. In natural plumes, turbulent winds break up smooth odor regions into disconnected patches, so navigators encounter brief bursts of odor interrupted by bouts of clean air. The timing of these encounters plays a critical role in navigation, determining the direction, rate, and magnitude of insects' orientation and speed dynamics.

Density declines, richness increases, and composition shifts in stream macroinvertebrates.

Documenting trends of stream macroinvertebrate biodiversity is challenging because biomonitoring often has limited spatial, temporal, and taxonomic scopes. We analyzed biodiversity and composition of assemblages of >500 genera, spanning 27 years, and 6131 stream sites across forested, grassland, urban, and agricultural land uses throughout the United States. In this dataset, macroinvertebrate density declined by 11% and richness increased by 12.