Identification of Parkinsons disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data.

Parkinsons disease (PD) is a serious neurodegenerative disorder marked by significant clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD through integrative analysis of various data modalities. We analyzed clinical progression data (≥5 years) of individuals with de novo PD using machine learning and deep learning, to characterize individuals phenotypic progression trajectories for PD subtyping. We discovered three pace subtypes of PD exhibiting distinct progression patterns: the Inching Pace subtype (PD-I) with mild baseline severity and mild progression speed; the Moderate Pace subtype (PD-M) with mild baseline severity but advancing at a moderate progression rate; and the Rapid Pace subtype (PD-R) with the most rapid symptom progression rate. We found cerebrospinal fluid P-tau/α-synuclein ratio and atrophy in certain brain regions as potential markers of these subtypes. Analyses of genetic and transcriptomic profiles with network-based approaches identified molecular modules associated with each subtype. For instance, the PD-R-specific module suggested STAT3, FYN, BECN1, APOA1, NEDD4, and GATA2 as potential driver genes of PD-R. It also suggested neuroinflammation, oxidative stress, metabolism, PI3K/AKT, and angiogenesis pathways as potential drivers for rapid PD progression (i.e., PD-R). Moreover, we identified repurposable drug candidates by targeting these subtype-specific molecular modules using network-based approach and cell line drug-gene signature data. We further estimated their treatment effects using two large-scale real-world patient databases; the real-world evidence we gained highlighted the potential of metformin in ameliorating PD progression. In conclusion, this work helps better understand clinical and pathophysiological complexity of PD progression and accelerate precision medicine

Progressive Supranuclear Palsy (PSP)

Objectives:; To provide an overview of PSP and its pathophysiology;; To present typical clinical features of the disease with a focus on ocular findings;; To provide a template for work up, diagnosis and treatment; ; To demonstrate typical eye movement abnormalities seen in PS

Dementia: Overview and Classification

PowerPoint providing a broad overview of dementia, including definition, clinical findings, work up, diagnosis, classification, and management

Case Report of Granulicatella adiacens as a Cause of Bacterascites

Granulicatella adiacens is a Gram-positive coccus, formerly grouped with nutritionally variant Streptococcus, often found as commensal bacteria of the human oral cavity, urogenital tract, and gastrointestinal tract. Prior case reports have demonstrated Granulicatella spp. as a pathogen that can cause bacteremia and infective endocarditis particularly of prosthetic valves and pacemaker leads. Here, we report on a unique case of Granulicatella adiacens bacterascites in a 50-year-old male