npj Parkinson's Disease

Abstract/SummaryO_ST_ABSBackgroundC_ST_ABSCerebrospinal fluid (CSF) -synuclein seed amplification assay (SAA) has emerged as a diagnostic biomarker for Parkinsons disease (PD) and has been linked to differences in disease severity and progression. However, whether SAA status predicts responsiveness to levodopa remains unknown. We investigated the longitudinal association between SAA status, levodopa responsiveness, dopaminergic denervation, and motor complications in sporadic PD. MethodsIn this longitudinal analysis, PD participants from the Parkinsons Progression Markers Initiative (PPMI) cohort with CSF SAA testing who initiated levodopa treatment were included. SAA- and SAA+ patients were matched on sex, age, and disease duration at treatment initiation. Motor severity was assessed using MDS-UPDRS Part III, with proportional and absolute responsiveness derived from ON and OFF medication states. Motor complications were assessed using MDS-UPDRS Part IV, and dopaminergic dysfunction was quantified using caudate DAT-SPECT. Linear mixed-effects models examined longitudinal differences as a function of SAA status. FindingsIn this analysis, 40 SAA- patients were compared to 183 matched SAA+ patients. SAA+ patients showed a slower rate of ON-state motor progression than SAA- patients (0.87 vs 3.47 points/year; p = 0.01). Consistently, proportional levodopa responsiveness increased over time in SAA+ patients while declining in SAA- patients (p = 0.036). These differences were accompanied by lower caudate DAT binding at treatment initiation in SAA- patients (p = 0.002) and faster dopaminergic decline over time (p = 0.008). Although SAA+ patients had fewer motor complications at treatment initiation, their progression was similar. InterpretationCSF -synuclein SAA status is associated with divergent levodopa response in PD, with SAA+ patients showing sustained and progressively greater motor benefit, while SAA- patients show declining responsiveness. Faster dopaminergic denervation in SAA- patients may underlie this difference. SAA status captures clinically relevant heterogeneity that may inform patient stratification and therapeutic decision-making.

BackgroundEpidemiological studies show an inverse association between cigarette smoking and Parkinsons disease (PD), suggesting a potential protective effect of smoking on PD incidence, despite the well-established and overwhelming harms of smoking to human health. We integrated genomic and proteomic approaches to investigate the causality and molecular basis of this potential relationship. MethodsWe analyzed summary statistics from genome-wide association studies (GWAS) of smoking initiation (SmkInit), smoking intensity, and PD. Two-sample Mendelian randomization (MR) tested whether genetic liability to smoking behaviors causally influences PD risk. Shared genomic architecture was quantified using MiXeR, and conjunctional false discovery rate (conjFDR) analysis identified loci jointly associated with smoking and PD, which were then mapped to genes and tested for tissue enrichment. To identify mediating proteins, we integrated dorsolateral prefrontal cortex proteomic data with GWAS using proteome-wide association studies (PWAS), summary-based MR, heterogeneity in dependent instruments testing, and colocalization. Finally, the druggability of convergent genes was evaluated. ResultsMR analyses indicated a protective effect of genetic liability to SmkInit on PD risk (OR = 0.78, 95% CI: 0.67-0.91, P = 1.5 x 10-3), which was consistent across sensitivity analyses and not suggestive of directional pleiotropy. However, no significant effect of genetic liability to cigarettes per day (CigDay) on PD risk was found. MiXeR revealed modest polygenic overlap between SmkInit and PD (13.9%; genetic correlation rg = -0.16) and between CigDay and PD (22.9%; rg = -0.09). ConjFDR identified 95 shared loci for SmkInit-PD and 26 for CigDay-PD. SmkInit-PD loci mapped to genes involved in neurotrophic signaling, synaptic organization, microglial modulation, and mitochondrial stress responses, with expression enriched in substantia nigra, basal ganglia, and interconnected cortical regions. PWAS identified 11 proteins shared by PD and SmkInit and 5 shared with CigDay, several of which (AKT3, MAPT, RIT2, EXD2, and PPP3CC) were supported by both genomic and proteomic analyses. Druggability assessment highlighted six proteins with existing pharmacologic modulation potential, spanning neurotrophic, microglial, proteostatic, and ion-channel pathways. ConclusionsGenetic liability to smoking initiation appears to confer modest protection against PD. Integrative genomic and proteomic evidence converges on neurotrophic, synaptic, microglial, and mitochondrial pathways as shared mechanisms, identifying biologically coherent potential therapeutic targets for advancing smoke-free neuroprotective strategies in PD.

BackgroundPhenoconversion to Parkinsons disease (PD) or dementia with Lewy bodies (DLB) currently relies on established clinical diagnostic criteria. Availability of in vivo biomarkers--CSF -synuclein seed amplification assay (CSFaSynSAA) and dopamine transporter (DAT) imaging--offer the opportunity to investigate congruency between clinical phenoconversion and biologically defined disease. MethodsWe analyzed Parkinso[n]s Progression Markers Initiative participants who phenoconverted to PD, DLB, multiple system atrophy (MSA), Alzheimers disease (AD) or other dementias from prodromal and non-manifesting genetic carrier (NMC) groups and controls. Site investigators determined phenoconversion based on established diagnostic criteria. All phenoconverters with [≥]1 annual follow-up visit, with available biomarkers and persistent clinically defined diagnosis at last observation were included. Neuronal alpha-Synuclein Disease Integrated Staging System (NSD-ISS) staging was applied. ResultsAmong 121 phenoconverters, 103 had evaluable CSFaSynSAA and DAT data and were included in analysis: 92 PD, 7 DLB, 2 MSA, 2 AD/other dementias. Phenoconversion annual rates varied widely across groups: iRBD 7.9%, hyposmia 4.2%, GBA1 0.3%, LRRK2 1.3%, LRRK2+GBA1 0.9%, and controls 0.5%. Median time from baseline to phenoconversion ranged from 13-14 months in iRBD and hyposmia to 36-85 months in NMCs. The expected biomarker profile (CSFaSynSAA+/DAT+) for clinically-diagnosed synucleinopathy occurred in 74 (71.8%) participants. Biological alignment (CSFaSynSAA+/DAT+) was present in 87% hyposmics and 72% iRBD phenoconverters. CSFaSynSAA negativity was high among LRRK2 phenoconverters (67%), who also were more likely to have a preserved sense of smell (83%). Phenoconversion occurred later than onset of functional impairment: 15/47 (31.9%) iRBDs and 7/38 (18.4%) hyposmics were already NSD-ISS stage [≥]4 at time of phenoconversion. ConclusionsClinical phenoconversion did not necessarily align with biological evidence of synucleinopathy or dopaminergic loss and can be delayed compared to onset of meaningful functional impairment. Longitudinal follow up on converters without biological evidence of PD is required to confirm conversion diagnosis and evaluate for a later occurrence of biomarker positivity.

Parkinson's Disease (PD) is a complex neurodegenerative disorder that manifests through systemic, large-scale physiological reorganizations. While research often focuses on region-specific neural changes, there is a growing need for multidomain approaches to capture the complexity of the disease and its clinical heterogeneity. This study proposes an analytical pipeline to evaluate Brain-Heart Interplay (BHI) as a novel systemic biomarker for neurodegeneration and healthy ageing. In this study we assessed BHI across three open-source datasets (EEG and ECG signals). We compared Healthy Young, Healthy Elderly, and PD patients in resting state to investigate the effects of ageing and cognitive performance. Additionally, we studied BHI trends in PD patients in the moment of freezing of gait (FOG). Methodologically, brain network organization was quantified using coherence-based EEG connectivity and graph theory, while heart activity was analyzed through Poincare plot-derived measures of cardiac autonomic activity. The coupling between these two systems was measured using the Maximal Information Coefficient to capture linear and non-linear dependencies between global cortical organization and cardiac autonomic outflow. The results demonstrate that BHI is a sensitive biomarker for detecting early multisystem dysfunction in both neurodegeneration and ageing. Furthermore, the identification of specific BHI trends during FOG onset suggests new opportunities for understanding the physiological mechanisms driving motor complications in PD. Our proposed pipeline provides a guiding tool for large-scale physiological assessment in clinical research.

Motor neuron (MN) loss is a hallmark of neurodegenerative disorders, yet its assessment remains variable, confounding mechanistic and therapeutic interpretation. To address this, we conducted a systematic review and meta-analysis of spinal muscular atrophy (SMA) mouse studies, revealing 60% variability in reported MN loss, largely attributable to nonspecific spinal cord sampling. Using a whole-segment approach with tissue clearing, MN tracing, and multimodal imaging, we confirmed segment-dependent differences in MN counts. Common MN markers (SMI-32, Nissl) lacked specificity, whereas choline acetyltransferase (ChAT) provided robust labeling in murine and human spinal cords. Deep learning-based whole-mount segmentation enabled unbiased MN quantification and validated manual counts. Integrating analysis with computational modeling established segment sampling as a key driver of variability and revealed degeneration patterns: widespread MN loss in amyotrophic lateral sclerosis (ALS), selective MN loss in severe SMA, and preservation in mild SMA models. These findings establish a framework for reproducible MN quantification. HighlightsO_LISpinal cord segment-specific analysis reduces variability and allows accurate MN quantification C_LIO_LIChAT is the most reliable MN marker in murine and human spinal cords C_LIO_LIDeep learning-based segmentation enables unbiased MN quantification in intact spinal cords C_LIO_LIMN degeneration is widespread in ALS but restricted to pools innervating proximal muscles in severe SMA C_LI

BackgroundTau aggregation is the defining feature of tauopathies, however, the mechanisms by which distinct tau strains drive disease-specific responses remain unclear. Existing models largely rely on recombinant tau seeding or tau overexpression, which fail to capture the biochemical diversity of pathological tau. The aim of this study was to develop a robust and reproducible human cell-based model of disease-specific tau pathology and to use this model to determine how tau from unique diseases impact tau accumulation and lysosomal dysfunction. MethodsPatient-derived tau aggregates were enriched from post-mortem brain tissue obtained from sporadic Alzheimers disease (AD), Picks disease (PiD), progressive supranuclear palsy (PSP), and control cases using phosphotungstic acid precipitation. Patient-derived tau preparations were biochemically characterised by immunoblotting and mass spectrometry and normalised for tau content prior to seeding. Patient-derived tau aggregates were seeded into multiple human immortalised cell lines (SH-SY5Y, M03.13, U-87 MG, and U-118 MG cells) and iPSC-derived astrocytes. Tau seeding efficiency, aggregate morphology, and integrity of the autophagy-lysosomal pathway was assessed using quantitative imaging approaches. ResultsPatient-derived tau seeds retained disease-specific phosphorylation patterns and isoform composition and led to reproducible, dose-dependent insoluble tau accumulation in all cell lines tested. Despite equivalent tau input and similar background protein composition, PiD-derived tau had the most aggressive pathological signature, showing the highest number of tau aggregates per cell and inducing system wide disruptions in the autophagy lysosomal system including increased SQSTM1 puncta and lysosomal damage markers. Seeding with AD-derived tau led to a high number of tau aggregates per cell and more specifically depleted the lysosomal protease CTSD and uniquely co-seeded A{beta} pathology. Seeding with PSP-derived tau resulted in only a moderate number of tau aggregates per cell and uniquely caused increased lysosomal biogenesis. ConclusionsTogether, these results demonstrate that intrinsic properties of human tau strains drive disease-specific cellular responses and establish a scalable, physiologically relevant platform for dissecting tau-cell interactions and screening therapeutics across tauopathies.

Background: Sleep wake and circadian disturbances are increasingly recognised in people living with amyotrophic lateral sclerosis (plwALS), but endogenous circadian phase timing and its prognostic significance in early disease remain unclear. We assessed whether salivary dim-light melatonin onset (DLMO), an objective marker of central circadian phase, is altered in early plwALS and whether it provides prognostic information. Methods: In this prospective longitudinal observational study, plwALS within 18 months of symptom onset underwent home-based salivary melatonin sampling under dim light conditions at six predefined time points around habitual sleep onset (HSO). Melatonin profiles were modeled using cubic smoothing splines, and DLMO was defined as the first time the fitted curve reached 3 pg/mL. Clinical, respiratory, and sleep assessments were collected at baseline (T0) and after 6 months (T6); a subgroup repeated saliva sampling at T6. Age and sex matched controls underwent melatonin profiling. Associations with disease progression, incident respiratory symptoms, and survival/tracheostomy were examined using regressions and survival analyses. Results: Fifty plwALS were enrolled. Compared with controls, plwALS showed an earlier DLMO (20:24 vs 20:58; p=0.028) despite similar HSO and chronotype. Within ALS cohort, a later baseline DLMO correlated with worse functional/motor status, faster progression of disease, incident dyspnea/orthopnea by T6 (adjusted OR 3.02; p=0.017), and poorer survival/tracheostomy-free outcome. In re-sampled subgroup (n=28), DLMO and other melatonin-derived metrics did not change over 6 months. Conclusions: Circadian phase alterations are detectable in early ALS. Baseline DLMO may represent a non-invasive prognostic biomarker for progression, respiratory symptom emergence and survival, warranting validation in larger multicentre cohorts.

Objectives: To evaluate the diagnostic performance of the -synuclein seed amplification assay (SAA) and characterize the impact of -synuclein co-pathology on cognitive and biological profiles in routine clinical practice. Methods: We included 398 patients from the prospective multicenter ALZAN cohort recruited from memory clinics in Montpellier, Nimes, and Perpignan. All participants underwent CSF and blood sampling with measurement of CSF biomarkers (A{beta}42/40, tau, ptau181) and plasma biomarkers (A{beta}42/40, ptau181, ptau217, GFAP, NfL). Cognitive assessment was performed using the Mini-Mental State Examination (MMSE). Clinical diagnoses were independently confirmed by two senior neurologists. Syn status was determined by SAA (RT-QuIC). Results: Of 398 patients, 19 out of 20 patients with Lewy body dementia (LBD) (95.0%) and 32 out of 203 patients with AD (15.8%) were SAA+. SAA-positivity presented a sensitivity of 95% and a specificity of 93.5% for distinguishing LBD from patients without LBD or AD. In the entire cohort, SAA+ patients showed lower MMSE scores (p<0.01), lower CSF A{beta}42/40 ratio (p<0.01), and elevated plasma GFAP (p<0.05). Within the AD group, no significant differences in CSF or blood biomarkers were observed between SAA+ and SAA- patients. Within the AD subgroup, no significant differences in CSF or blood biomarkers were observed between SAA+ and SAA- patients, except for a lower CSF A{beta}42/40 ratio in SAA+ patients (p<0.01). Interpretation: SAA demonstrates good diagnostic capabilities for detecting LBD and confirms notable Syn co-pathology in AD. This study highlights the limitations of routine CSF and emerging blood biomarkers in capturing Syn pathology and the value of integrating SAA into routine neurodegenerative disease assessment.

Extracellular vesicles (EVs) mediate intercellular transfer of lipids, proteins, and nucleic acids between nearly all cell types. We previously showed that astrocyte-derived EVs modulate neuronal mitochondria in vitro, but whether endogenous astrocytic EVs are trafficked to neuronal mitochondria in vivo remained unknown. To address this, we generated an EV reporter mouse, Aldh1l1-Cre; CD9-tGFPfl/fl, in which astrocyte-secreted EVs are labeled with a CD9-turboGFP fusion protein (CD9-tGFP). Astrocyte-specific expression of CD9-tGFP was verified in brain tissue and isolated EVs, comprising 13.2 {+/-} 1.6% of total brain EVs. In primary glial cultures, CD9-tGFP was restricted to astrocytes, localizing to vesicular compartments and cell protrusions (filopodia and cilia), with 89.3 {+/-} 2.2% of astrocyte-derived EVs carrying the label. These EVs were enriched with the sphingolipid ceramide, consistent with its co-distribution with CD9-tGFP in astrocytic cell protrusions. In the cortex, hippocampus, and cerebellum, CD9-tGFP was predominantly detected in astrocytic processes co-labeled with GLAST1 and GFAP, forming contacts with laminin-positive capillaries and parvalbumin-positive neurons. CD9-tGFP-labeled EVs were detected inside capillaries and neurons, and super-resolution STED microscopy revealed partial overlap with neuronal mitochondria. Live-cell spinning disk confocal imaging and AI-assisted proximity analysis confirmed uptake of CD9-tGFP EVs by neuronal cells and trafficking of their cargo to mitochondria in vitro. Biochemical isolation of synaptic and non-synaptic mitochondria confirmed EV-derived cargo on mitochondria in vivo, with 3-fold higher association of CD9-tGFP with synaptic than non-synaptic mitochondria. Together, these findings validate the Aldh1l1-Cre; CD9-tGFPfl/fl reporter mouse as a powerful tool for tracking astrocyte-derived EVs in vivo and provide direct evidence that their cargo is preferentially trafficked to synaptic mitochondria. Graphical AbstractAstrocyte-derived extracellular vesicles target neuronal mitochondria in vivo O_FIG O_LINKSMALLFIG WIDTH=156 HEIGHT=200 SRC="FIGDIR/small/718987v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@174d92aorg.highwire.dtl.DTLVardef@5d8248org.highwire.dtl.DTLVardef@114483borg.highwire.dtl.DTLVardef@924d55_HPS_FORMAT_FIGEXP M_FIG C_FIG

Progranulin (PGRN) is a neurotrophic and anti-inflammatory factor produced mainly by neurons and microglia in the central nervous system. Progranulin haploinsufficiency causes frontotemporal dementia (FTD). In a previous study we showed that transgenic restoration of progranulin in neurons in progranulin knockout mice (NestinGrn KOBG knockout background) did not prevent the dementia-like phenotype. Here, we assessed if pharmacologic microglia depletion via PLX3397-diet (CSF1R-antagonist) had therapeutic value in these mice. Microglia depletion and spontaneous repopulation was confirmed in immunofluorescence and rtPCR studies. There was no difference in depletion or repopulation efficiency between NesGrn KOBG, PGRN KO and heterozygous (het) PGRN mice, but microglia repopulated faster than in control Grn-flfl mice, and the morphology of primary PGRN deficient microglia during repopulation was closer to homeostatic microglia, and it was accompanied by a remarkable restoration of dendritic spines and synaptic structures. Regardless of these positive effects, NesGrn KOBG and PGRN het mice experienced serious side effects during microglia depletion which peaked around the microglia nadir. Overactivity and excessive grooming escalated and caused serious skin lesions. Bulk transcriptomic and metabolomic studies in the brain taken 8 weeks after the end of PLX-diet clearly revealed differences between genotypes but mostly no lasting impact of PLX-diet, except for a further increase of proinflammatory genes, cathepsins and complement factors in PLX-treated groups. Cell type specific lipidomic studies revealed a time dependent switch not only in microglia but also astrocytes upon PLX3397 treatment. While nadir-microglia were triglyceride-laden, repopulated microglia returned to normal TG levels but were enriched in ether-bound phosphatidylcholines (PC-O) and lysophosphatidylglycerol species which are pro-inflammatory lipids; and astrocytes overtook the TG burden during repopulation. Our data suggest that microglia depletion may cause a deterioration in progranulin-deficiency.

Type 2 diabetes mellitus (T2DM) is a progressive metabolic disorder characterized by persistent hyperglycemia, insulin resistance, and chronic low-grade inflammation. Despite the widespread use of established therapies such as metformin, long-term glycemic control remains suboptimal, and disease progression is often not adequately prevented. This highlights the need for novel therapeutic strategies that address both metabolic dysfunction and the underlying immunometabolic components of the disease. In this study, GLX10 (GLXM100) was evaluated as a novel immune modulator in a high-fat diet (HFD) and low-dose streptozotocin (STZ)-induced rat model of T2DM over a 91-day period. Glycemic outcomes were assessed using terminal random blood glucose and oral glucose tolerance testing (OGTT), with glucose exposure quantified by area under the curve (AUC 0-120). Complementary in vitro investigations were performed in hepatic and macrophage cell models to assess cytocompatibility, nitric oxide production, and modulation of pro-inflammatory cytokines, including IL-6 and TNF-. GLX10 treatment resulted in a significant reduction in random blood glucose levels and a marked improvement in glucose tolerance compared to diabetic control animals. Importantly, GLX10 demonstrated greater improvement in OGTT AUC compared to metformin under the same experimental conditions, indicating enhanced dynamic glucose regulation. In vitro, GLX10 maintained viability in normal hepatic cells while significantly suppressing nitric oxide production and inflammatory cytokine outputs in macrophages, supporting a favorable safety and immune profile. Collectively, these findings demonstrate that GLX10 exerts robust antidiabetic activity through a dual mechanism involving metabolic regulation and suppression of inflammatory signaling. The integration of in vivo efficacy with supportive in vitro safety and mechanistic data provides a strong preclinical foundation and supports the further development of GLX10 as a promising therapeutic candidate for T2DM.

ObjectivePathological beta-band oscillations (13 to 30 Hz) in the subthalamic nucleus (STN) are a hallmark of Parkinsons disease and a primary target for deep brain stimulation therapy, yet the specific pattern of synaptic reorganization that drives their emergence remains incompletely understood. We developed a GPU-accelerated computational framework to systematically investigate combinations of synaptic changes across basal ganglia pathways that produce Parkinsonian beta oscillations while satisfying literature-based electrophysiology constraints. ApproachWe implemented a biophysically detailed spiking network model of the STN, external globus pallidus (GPe), and internal globus pallidus (GPi) in JAX (a high-performance numerical computing Python library), achieving a 490-fold speedup over conventional CPU-based simulation. Using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) we optimized 10 network parameters across two stages: first establishing a healthy baseline matching primate electrophysiology data, then searching within biologically motivated bounds for synaptic modifications that reproduce Parkinsonian firing rates and beta power. Fixed in-degree connectivity ensured optimized parameters produced scale-invariant dynamics from 450 to 45000 neurons. All simulations ran on a single cloud GPU instance at 84 cents per hour. Main ResultsThe optimizer converged on a coordinated pattern of synaptic reorganization dominated by asymmetric changes within the STN-GPe reciprocal loop: STN to GPe excitation increased 2.21-fold while GPe to STN inhibition collapsed to 0.11-fold of its healthy value. STN to GPi and GPe to GPi pathways changed minimally (1.06-fold and 1.45-fold respectively). This configuration transformed asynchronous firing (beta: 0.4 percent of spectral power) into synchronized bursting with prominent beta oscillations (49.4 percent), with firing rate changes matching experimental observations. Network dynamics were invariant across a 100-fold range of network sizes (firing rate deviation less than 2.4 Hz; all metrics p less than 0.001 across 10 random seeds at 45000 neurons). We implemented a simplified deep brain stimulation model for validation purposes, which achieved complete beta suppression (49.4 percent to 0.0 percent) and restored GPi output to healthy levels. SignificanceThese results suggest that pathological beta oscillations emerge from a specific pattern of synaptic reorganization, namely the reduction of GPe inhibitory feedback to STN. The GPU-accelerated optimization framework, running on commodity cloud infrastructure, demonstrates an accessible platform for parameter exploration in neural circuit models and a foundation for generating synthetic training data for adaptive deep brain stimulation algorithms.

Myelin is a highly complex membranous structure wrapped around axons by oligodendrocytes or Schwann cells in the central and peripheral nervous system, respectively. Fluorescent labeling is widely used to study the structure and dynamics of myelin. Combining structural with functional imaging requires labeling of myelin with red fluorescence, as many functional sensors, including Ca2+ indicators and genetically encoded metabolite sensors, fluoresce in the green spectral range. However, in vivo tools enabling red fluorescent labeling of myelinating cells and their myelin sheaths remain limited. Here, we generated a set of seven transgenic mouse lines expressing a membrane-targeted variant of the red fluorescent protein tdTomato in myelinating oligodendrocytes and Schwann cells throughout the nervous system. The mouse lines provide a variety of expression patterns ranging from wide-spread labeling of myelin to a rather sparse expression, the latter enabling visualization of individual oligodendrocytes and their associated myelin sheaths. In the peripheral nervous system, the pattern of fluorescence in sciatic nerves indicates predominant localization of tdTomato to non-compact myelin compartments including the inner and outer tongues, paranodal loops and Schmidt-Lanterman incisures. In summary, our work provides a set of novel mouse lines with myelin labeled by red fluorescence, which are compatible with diverse imaging modalities in the green spectral range enabling integrated structural and functional imaging. Main PointsO_LITransgenic mouse lines expressing membrane-targeted tdTomato in myelin enable imaging of myelin in the red spectral range C_LIO_LIDistinct expression patterns range from wide-spread labeling to sparse single-cell resolution, supporting diverse imaging applications C_LI

1.Quantitative neuropathology has advanced through whole-slide imaging and digital histology platforms. Yet, these measurements rarely align with neuroimaging coordinate frameworks that may be useful for spatial modeling and other applications. QNPtoVox, short for quantitative neuropathology to voxels, is a reproducible, modular pipeline that transforms quantitative metrics generated by digital pathology software (HALO) into voxel-based maps registered to a standard common coordinate (MNI) template. The workflow integrates digital histopathology, gross tissue photography, ex-vivo MRI, and nonlinear registration to generate spatially standardized 3D pathology representations. This Methods article provides a complete procedural description, including required materials, step-wise instructions, operator-dependent checkpoints, expected outputs, reproducibility evaluation, and troubleshooting. QNPtoVox enables voxel-level integration of neuropathology with neuroimaging tools, unlocking existing histopathology datasets for computational modeling and cross-cohort harmonization.

Technological advances in biomedical sciences have accelerated multi-omics research, enabling high-resolution spatial mapping of diverse molecular compound classes. However, integrating spatial omics often requires serial tissue sections, limiting the alignment correlation across modalities. We present a single-section integrative multi-omics (SIMO) workflow that combines metabolite and lipid imaging with histopathology and region-specific proteomics. Using MALDI-MSI, tissue staining, and laser microdissection (LMD), SIMO delivers comprehensive metabolic, lipidomic, and proteomic insight from the same sample. Using mouse cardiac tissue we develop, control, and validate the methodology resulting in [~]60 imaged lipids and [~]60 imaged metabolites at 20 {micro}m pixel size and subsequently spatial proteomics by LMD, detecting over 5,000 proteins from the same tissue. To demonstrate the capabilities of the workflow in preclinical context, we apply SIMO to a metastasizing melanoma PDX model, identifying over 100 spatially localized lipids and metabolites, and over 5,000 proteins across metastases and non-tumor tissues in liver. SIMO enables precise ROI selection, statistical comparison of protein regulation, and alignment of metabolic and lipidomics pathways across spatial omics and region-specific proteomics, demonstrating its value as a spatial multi-omics platform.

Electroencephalography (EEG) preprocessing is a critical yet time-consuming step that often relies on expert-driven, semi-automatic pipelines, limiting scalability and reproducibility across large datasets. In this work, we present sEEGnal, a fully automated and modular pipeline for EEG preprocessing designed to produce outputs comparable to expert-driven analyses while ensuring consistency and computational efficiency. The pipeline integrates three main modules: data standardization following the EEG extension of the Brain Imaging Data Structure (BIDS), bad channel detection, and artifact identification, combining physiologically grounded criteria with independent component analysis and ICLabel-based classification. Performance was evaluated against manual preprocessing performed by EEG experts at two complementary levels: preprocessing metadata (bad channels, artifact duration, and rejected components) and EEG-derived measures. In addition, test-retest analyses were conducted to assess the stability of the pipeline across repeated recordings. Results show that sEEGnal achieves performance comparable to expert-driven preprocessing while preserving key neurophysiological features. Furthermore, the pipeline demonstrates reduced variability and increased consistency compared to human experts. These findings support sEEGnal as a robust and scalable solution for automated EEG preprocessing in both research and large-scale applications. HighlightsFully automated and modular EEG preprocessing pipeline. Benchmarked against expert-driven preprocessing. Comparable performance in metadata and EEG-derived measures. Demonstrates stable performance in test-retest recordings. BIDS-based framework for reproducible EEG data handling.

Standard analysis of amyotrophic lateral sclerosis (ALS) clinical trials evaluates therapeutic efficacy by comparing linear slopes of total ALS Functional Rating Scale (ALSFRS) scores between treatment arms. This approach compresses multidomain ordinal data into a single scalar trajectory, discarding distributional structure. When subgroup-level trends differ in timing or direction, such aggregation can attenuate or eliminate them, a phenomenon known as Simpsons paradox. Here we apply Shannon entropy, computed from item-level score distributions within each ALSFRS functional domain following the framework established in [8], to the PRO-ACT database, stratified by treatment arm (Active: n = 4,581; Placebo: n = 2,931; 19 monthly time points). The entropy trajectories of drug-treated and placebo populations diverge visibly and systematically across all four functional domains (Bulbar, Fine Motor, Gross Motor, Respiratory). In the Fine Motor domain, the placebo population reaches peak entropy at month 8 and reverses, while the active population does not peak until month 13, a five-month delay in the populations transit toward functional loss. This divergence is model-independent: it is present in the raw Shannon entropy trajectories before any dynamical model is applied. A permutation test shuffling patient-level arm labels (n = 1,000 permutations) confirms that the total integrated absolute divergence across all four domains exceeds the null distribution at p < 0.001 (observed: 4.48; null: 2.03 {+/-} 0.33; 7.5 standard deviations above the null mean), with Fine Motor (p = 0.001) and Respiratory (p < 0.001) individually significant. The quantity that differs between arms, the shape and timing of the populations distributional evolution, does not exist as a measurable quantity in the total-score linear-slope framework used to evaluate these trials. Whether this signal reflects genuine treatment effects, compositional artifacts from pooling heterogeneous trials, or both cannot be determined from the anonymized public database alone. What can be determined is that the standard ALS clinical trial endpoint makes an implicit assumption, that the distributional information it discards is uninformative, and the present results demonstrate empirically that this assumption is false.

Alzheimers disease (AD) is characterized by the accumulation of amyloid-{beta} (A{beta}) peptides, which are a key factor in its pathogenesis. In this study, we present the design and evaluation of {gamma}-amino-L-proline peptides as metabolically stable, cell-penetrating molecules that can modulate amyloidogenic processing. We screened a library of {gamma}-peptides in primary neuronal cultures to determine their effects on endogenous A{beta}1-42 production, cytotoxicity, and {beta}-secretase (BACE1) activity. Comparative analysis of structurally related analogues enabled the identification of molecular features associated with A{beta}-lowering activity, establishing a qualitative structure-activity relationship. Peptide 33 (P33) emerged as a lead candidate, selectively reducing BACE1 activity without significantly inhibiting the homologous enzyme, BACE2. In vitro blood-brain barrier (BBB) assays revealed that P33 exhibits favorable transendothelial permeability. Intraperitoneal administration of P33 in APP/PS1 mice decreased A{beta} levels, reduced amyloid plaque burden, and improved performance in a behavioral recognition task without inducing cytotoxicity or systemic toxicity. These results define cis-{gamma}-amino-L-proline peptides as a bioorganically distinct and modular scaffold for the development of intracellular modulators of A{beta} production. HighlightsO_LI{gamma}LJAminoLJLLJproline peptides as metabolically stable modulators of A{beta} production. C_LIO_LIP33 showed BBB permeability and BACE1 inhibition in primary cortical neurons. C_LIO_LIIn APP/PS1 mice, P33 lowers amyloid burden and improves cognition. C_LIO_LIP33 shows good biocompatibility, supporting its therapeutic potential in AD C_LI

Alzheimer's disease (AD) is increasingly recognized to have systemic physiological correlates alongside central neurodegeneration. Here, we explored brain-organ network (BON) connectivity in AD (n=28) and healthy controls (n=23) using time-resolved quasi-dynamic analysis of plateau-phase total-body 18F-tau-PET. We found that AD-related pathophysiology was linked not only to cerebral tau aggregation, but also to altered signal synchronization across the brain-organ network, despite comparable body tracer distribution. Network topology analyses revealed the occipitotemporal cortex and the spinal cord as key nodes in this altered systemic network. Furthermore, exploratory mediation analyses demonstrated that BON dysregulation is cross-sectionally linked to cognitive deficits, with statistical associations observed for both cortical tau burden and imaging markers of impaired glymphatic clearance. This total-body PET study provides first-ever direct evidence repositioning AD as a multi-organ disorganization disease. These findings provide a novel framework for investigating brain-body interactions and systemic vulnerabilities in neurodegenerative disorders.

Scratching provides transient relief from itch, yet the neural circuit mechanisms that transform scratching into itch relief remain poorly understood. Midbrain dopaminergic neurons and their downstream targets in the lateral shell of the nucleus accumbens (NAc LaSh) are implicated in itch-scratch processing. Previous studies show that pharmacological manipulation of dopamine D1 and D2 receptors in the NAc LaSh alters scratching behavior, but the specific contributions of D1R- and D2R-expressing neurons during acute and chronic itch remain unclear. Here, we show that NAc LaShD1R and D2R neurons bidirectionally regulate scratching behavior across itch states. NAc LaShD1R neurons activity promotes scratching bouts, whereas NAc LaShD2R neurons preferentially facilitate scratch termination. Anterograde viral tracing revealed distinct brain-wide projection patterns of NAc LaShD1R and D2R neurons, which we functionally tested using projection-specific optogenetic manipulations. We found that NAc LaShD2R neurons terminate scratching by inhibiting neurons in the lateral parabrachial nucleus (LPBN), a key hub for itch processing. Furthermore, dopamine levels in the NAc LaSh were elevated during chronic itch compared with acute itch, suggesting enhanced dopaminergic signaling contributes to persistent scratching. Together, these findings identify circuit mechanisms linking reward pathways to itch regulation.