Distinct Pathologies Research Articles

Neuronal α-synuclein toxicity is the key driver of neurodegeneration in multiple system atrophy.

Multiple system atrophy (MSA) is a rare, rapidly progressing neurodegenerative disorder often misdiagnosed as Parkinson's disease (PD). While both conditions share some clinical features, MSA is distinct in its pathological hallmark: oligodendroglial cytoplasmic α-synuclein (α-Syn) inclusions, known as glial cytoplasmic inclusions (GCIs). These GCIs are pathognomonic for MSA, but they do not lead to significant oligodendroglial cell loss. Instead, MSA is characterised by a substantially greater loss of non-dopaminergic neurons in the nigrostriatal and olivopontocerebellar systems compared to PD. This widespread neuronal degeneration, which is not seen to the same extent in PD, plays a critical role in MSA's clinical presentation and is important to consider if PD is to be redefined as a neuronal α-Syn disease. It also raises the question of differences in the potential toxicity of lesions in MSA and the underlying cause of neuronal death in MSA. By combining an N-terminus α-Syn antibody that reveals more α-Syn pathology and super-resolution microscopy, we identified α-Syn fibrils in MSA neurons penetrating the nucleus from the cytoplasm, leading to nuclear destruction and neuronal death. Our data indicate an early invasion of neuronal nuclei by α-Syn pathology in MSA, precipitating rapid nuclear envelope destruction, as observed through significant structural damage, including the loss of Lamin integrity. Although the progression of α-Syn pathology from the cytoplasm to the nucleus may be similar in oligodendroglia and neurons, the aggregation state of the α-Syn proteoforms involved differs as proteolytic resistance of α-Syn inclusions is significantly higher in neurons and the nucleus is destroyed. We describe the progressive impact of α-Syn nuclear pathology on MSA neurons and show that this is a more detrimental and rapid pathology driving neurodegeneration. Our data suggest that oligodendroglial inclusions contain more soluble, less toxic α-Syn proteoforms, consistent with two distinct α-Syn filaments in MSA. We propose renaming MSA as a neuronal nuclear and oligodendroglial α-synucleinopathy to better reflect these two distinct pathologies.

Allosteric modulation of NF1 GAP: Differential distributions of catalytically competent populations in loss-of-function and gain-of-function mutants.

Neurofibromin (NF1), a Ras GTPase-activating protein (GAP), catalyzes Ras-mediated GTP hydrolysis and thereby negatively regulates the Ras/MAPK pathway. NF1 mutations can cause neurofibromatosis type 1 manifesting tumors, and neurodevelopmental disorders. Exactly how the missense mutations in the GAP-related domain of NF1 (NF1GRD) allosterically impact NF1 GAP to promote these distinct pathologies is unclear. Especially tantalizing is the question of how same-domain, same-residue NF1GRD variants exhibit distinct clinical phenotypes. Guided by clinical data, we take up this dilemma. We sampled the conformational ensembles of NF1GRD in complex with GTP-bound K-Ras4B by performing molecular dynamics simulations. Our results show that mutations in NF1GRD retain the active conformation of K-Ras4B but with biased propensities of the catalytically competent populations of K-Ras4B-NF1GRD complex. In agreement with clinical depiction and experimental tagging, compared to the wild type, NF1GRD E1356A and E1356V mutants effectively act through loss-of-function and gain-of-function mechanisms, leading to neurofibromatosis and developmental disorders, respectively. Allosteric modulation of NF1GRD GAP activity through biasing the conformational ensembles in the different states is further demonstrated by the diminished GAP activity by NF1GRD isoform 2, further manifesting propensities of conformational ensembles as powerful predictors of protein function. Taken together, our work identifies a NF1GRD hotspot that could allosterically tune GAP function, suggests targeting Ras oncogenic mutations by restoring NF1 catalytic activity, and offers a molecular mechanism for NF1 phenotypes determined by their distinct conformational propensities.

Thymus Hyperplasia and Thymoma Type B in Patients with Myasthenia Gravis: Two case reports and Literature Review

Introduction: The thymus gland plays a pivotal role in immune system regulation, but conditions such as thymic hyperplasia (TH) and thymoma pose distinct clinical challenges due to their rarity and complex presentation in surgical practice. Both conditions can mimic similar symptoms, particularly in patients with Myasthenia Gravis (MG), where surgery serves as both a diagnostic and therapeutic intervention. This report presents the surgical management and outcomes of two MG patients with distinct thymic pathologies: TH and Type B thymoma, alongside a review of the relevant literature. Two MG patients were referred to our clinic for surgical intervention. The first patient underwent a standard sternotomy for the resection of TH, while the second patient underwent a mini-sternotomy for thymectomy targeting a Type B thymoma. Both procedures were completed successfully with uneventful postoperative courses. Surgical resection remains the gold standard for the treatment and definitive diagnosis of thymic gland abnormalities. Advances in surgical techniques, including minimally invasive approaches, offer excellent outcomes with reduced morbidity, providing a viable alternative to traditional methods. Conclusion: The cases underscore the critical role of surgical intervention in managing thymic pathologies in MG patients. Both traditional and minimally invasive techniques yield excellent clinical outcomes, reinforcing their importance in the treatment paradigm for thymic hyperplasia and thymoma. Further studies are needed to refine surgical approaches and optimize patient outcomes.

Flow cytometry immunophenotyping in diagnosed cases of B-cell chronic lymphoproliferative disorders

Objectives Mature B-cell neoplasms consist of a diverse group of disorders with distinct clinical presentations, pathology, and outcomes. This article aims to describe the clinical, morphological, and flow cytometry immunophenotypic findings of 30 diagnosed patients with B-cell lymphoproliferative disorders (B-CLPDs) in a tertiary care hospital in Sri Lanka. Material and Methods A descriptive cross-sectional study, including 30 cases of BCLPDs diagnosed over a period of 6 months, was analyzed. Diagnosis of BCLPDs was made by morphology of peripheral blood, bone marrow, and the immunophenotypic analysis by multiparametric flow cytometry on bone marrow aspirates or peripheral blood. Results CD5-/CD10- BCLPD with negative hairy cell markers was the most common subtype (30%), followed by chronic lymphocytic leukemia (CLL) at 26.6% and mantle cell lymphoma (MCL) at 20%. Persistent lymphocytosis was the most frequent clinical finding across BCLPD cases, while hepatomegaly was common in the cases of the CD5-/CD10- BCLPD with negative hairy cell markers. This category appears distinct from other known subtypes like splenic marginal zone lymphoma (SMZL) or hairy cell leukemia (HCL), suggesting a unique clinical profile. Conclusion The study highlights distinct immunophenotypic and clinical profiles across BCLPD subtypes, with CD5-/CD10- BCLPD subtype with negative hairy cell markers emerging as the most prevalent and showing unique marker patterns that may aid in differential diagnosis.

Harnessing machine learning in diagnosing complex hoarseness cases

PurposeTraditional vocal fold pathology recognition typically requires expertise of laryngologists and advanced instruments, primarily through direct visualization. This study aims to augment this conventional paradigm by introducing a parallel diagnostic procedure. Our objective is to harness a machine-learning algorithm designed to discern intricate patterns within patients' voice recordings to distinguish not only between healthy and hoarse voices but also among various specific disorders. Materials and methodsWe employed a machine-learning algorithm, utilizing transfer learning on the HuBERT model with Saarbruecken Voice Database samples. The study was conducted in two stages: a binary classifier distinguishes healthy and hoarse voices, while a subsequent multi-class classifier identifies specific voice disorders. Data from 2103 sessions, including over 25,000 components, representing diverse pathologies and healthy individuals, was analyzed. The models were trained, validated, and tested with a focus on robustness and accuracy in diagnosis. ResultsThe binary classifier achieved 82 % accuracy in distinguishing healthy from pathological voices. The multi-class algorithm which aims to identify specific laryngeal disorders obtained the highest accuracy (>93 %) for Laryngeal Dystonia. Noteworthy is the persistent challenge posed by Laryngeal Dystonia, a condition lacking a definitive diagnostic modality. ConclusionsOur findings demonstrate the feasibility of utilizing machine-learning algorithms to process voice samples, categorizing them into distinct pathologies. This approach holds potential for enhance patient triage, streamline diagnostics, and elevate overall patient care. Particularly valuable for challenging diagnoses, such as Laryngeal Dystonia, this method underscores the transformative role of machine learning in optimizing healthcare practices.

Pineal region tumors: prognostic stratification based on magnetic resonance imaging features-a retrospective cohort study.

Pineal region tumors encompass a wide range of pathologies, presenting challenges in pre-surgical characterization and exhibiting variable prognostic outcomes across different tumor types. This study aims to identify key imaging features from pre-treatment magnetic resonance imaging (MRI) of pineal region tumors to aid in prognostic analysis. We retrospectively enrolled 33 patients with pineal region tumors who underwent pre-treatment imaging at the Seventh Medical Center of the Chinese PLA General Hospital between January 2010 and June 2023. Two radiologists assessed imaging features including lesion morphology, border delineation, intensity, enhancement pattern, maximum tumor diameter, and secondary changes such as intratumoral hemorrhage and cystic changes. Tumor prognoses were categorized based on reported overall survival rates from recent literature as either good (overall survival rate ≥90%) or poor (overall survival rate <90%). Significant imaging features were selected using one-way analysis of variance (ANOVA) and binary logistic regression. The study cohort comprised 33 patients (27 males), aged 1 to 72 years [mean ± standard deviation (SD), 26.4±17.7 years]. We identified 13 distinct pathology types, with 15 cases classified as having a good prognosis and 18 cases as having a poor prognosis. A significant feature identified through one-way ANOVA was intratumoral hemorrhage (P=0.017). Binary logistic regression also highlighted intratumoral hemorrhage as a significant independent predictor of prognosis, irrespective of age and other factors. Tumors with intratumoral hemorrhage had a nearly 19-fold (P=0.015, 95% CI: 1.780-202.798) higher likelihood of an unfavorable prognosis compared to those without. Intratumoral hemorrhage emerges as a significant indicator of poor prognosis in pineal region tumors. This finding underscores the importance of incorporating specific imaging features, particularly intratumoral hemorrhage, into the prognostic evaluation of pineal region tumors.

Predicting Future Development of Stress-Induced Anhedonia From Cortical Dynamics and Facial Expression.

The current state of mental health treatment for individuals diagnosed with major depressive disorder leaves billions of individuals with first-line therapies that are ineffective or burdened with undesirable side effects. One major obstacle is that distinct pathologies may currently be diagnosed as the same disease and prescribed the same treatments. The key to developing antidepressants with ubiquitous efficacy is to first identify a strategy to differentiate between heterogeneous conditions. Major depression is characterized by hallmark features such as anhedonia and a loss of motivation1,2, and it has been recognized that even among inbred mice raised under identical housing conditions, we observe heterogeneity in their susceptibility and resilience to stress3. Anhedonia, a condition identified in multiple neuropsychiatric disorders, is described as the inability to experience pleasure and is linked to anomalous medial prefrontal cortex (mPFC) activity4. The mPFC is responsible for higher order functions5-8, such as valence encoding; however, it remains unknown how mPFC valence-specific neuronal population activity is affected during anhedonic conditions. To test this, we implemented the unpredictable chronic mild stress (CMS) protocol9-11 in mice and examined hedonic behaviors following stress and ketamine treatment. We used unsupervised clustering to delineate individual variability in hedonic behavior in response to stress. We then performed in vivo 2-photon calcium imaging to longitudinally track mPFC valence-specific neuronal population dynamics during a Pavlovian discrimination task. Chronic mild stress mice exhibited a blunted effect in the ratio of mPFC neural population responses to rewards relative to punishments after stress that rebounds following ketamine treatment. Also, a linear classifier revealed that we can decode susceptibility to chronic mild stress based on mPFC valence-encoding properties prior to stress-exposure and behavioral expression of susceptibility. Lastly, we utilized markerless pose tracking computer vision tools to predict whether a mouse would become resilient or susceptible based on facial expressions during a Pavlovian discrimination task. These results indicate that mPFC valence encoding properties and behavior are predictive of anhedonic states. Altogether, these experiments point to the need for increased granularity in the measurement of both behavior and neural activity, as these factors can predict the predisposition to stress-induced anhedonia.

Extensive tumoral calcinosis of cervical spine in systemic sclerosis – A rare entity

Tumoral calcinosis (TC) is a distinct pathology with etiologies ranging from primary hereditary forms to secondary underlying conditions, most common being chronic renal failure. Systemic sclerosis (SSc) is often affected by calcinosis, however limited to the subcutaneous tissue. Paraspinal soft tissue is a rare location for tumor like calcific masses in SSc. This case report describes the imaging features of TC in a female patient with SSc.

AD-Like Neuropsychiatric Dysfunction in a Mice Model Induced by a Combination of High-Fat Diet and Intraperitoneal Injection of Streptozotocin.

Increasing data suggest a crucial relationship between glycolipid metabolic disorder and neuropsychiatric injury. The aim of this study is to investigate the behavioral performance changes and neuropathological injuries in mice challenged with high-fat diet (HFD) and streptozotocin (STZ). The glucose metabolism indicators and behavioral performance were detected. The mRNA expression of IL-1β, IL-6, TNF-α, ocln, zo-1, and clnds and protein expression of APP, p-Tau, p-IRS1, p-AKT, p-ERK, and TREM1/2 were measured. The fluorescence intensities of MAP-2, NeuN, APP, p-Tau, GFAP, and IBA-1 were observed. The results showed that combination of HFD and STZ/I.P. could induce glucose metabolic turmoil and Alzheimer's disease (AD)-like neuropsychiatric dysfunction in mice, as indicated by the increased concentrations of fasting blood glucose and impaired learning and memory ability. Moreover, the model mice presented increased levels of APP, p-Tau, p-IRS1, TREM2, IL-1β, IL-6, TNF-α, ocln, zo-1, and clnds; decreased levels of p-AKT, p-ERK, and TREM1; and neuron damage and the hyperactivation of astrocytes and microglia in the hippocampus as compared with control mice. Only male mice were used in this study. Although AD and type 2 diabetes mellitus (T2DM) are distinct pathologies, our results suggested that combination of HFD and STZ/I.P., a widely used T2DM modeling method, could successfully induce AD-like behavioral impairments and neuropathological injuries in mice; the mechanism might be involved with neuroinflammation and its associated dysfunction of IRS1/AKT/ERK signaling pathway. Our findings further support the potential overlap between T2DM and AD pathophysiology, providing insight into the mechanisms underlying the comorbidity of these diseases.

Divergent changes in complement pathway gene expression in schizophrenia and bipolar disorder: Links to inflammation and neurogenesis in the subependymal zone

Deficits in neurogenesis markers in the subependymal zone (SEZ) are associated with elevated inflammation in schizophrenia and bipolar disorder. However, the extent to which complement factors are also changed in the SEZ of these major psychiatric disorders and their impact on neurogenesis remains poorly understood. We extracted RNA from the SEZ of 93 brains, including controls (n = 32), schizophrenia (n = 32), and bipolar disorder (n = 29) cases. Quantitative RT-PCR measured 13 complement transcripts encoding initiators, convertases, effectors or inhibitors. Differences in abundance were analysed by diagnosis and inflammatory subgroups (high- or low-inflammation), which were previously defined by SEZ cytokine and inflammation marker expression.Complement mRNAs C1QA (p = 0.011), C1QB (p < 0.001), C1R (p = 0.027), and Factor B (p = 0.025) were increased in high-inflammation schizophrenia versus low-inflammation controls. Conversely, high-inflammation bipolar cases had decreased C1QC (p = 0.011) and C3 (p = 0.003). Complement mRNAs C1R (SCZ, p = 0.010; BD, p = 0.047), C1S (SCZ, p = 0.026; BD, p = 0.017), and Factor B (BD, p = 0.025) were decreased in low-inflammation schizophrenia and bipolar subgroups versus low-inflammation controls. Complement inhibitors varied by subgroup: Factor H was increased in high-inflammation schizophrenia (p < 0.001), and CD59 in high-inflammation bipolar disorder (p = 0.020). Complement activator and inhibitor mRNAs were positively correlated with quiescent neural stem cell marker GFAPD (q < 0.05) but negatively with immature neuron markers DLX6-AS1 (q < 0.05) and DCX (q < 0.05).These findings suggest altered complement cascade expression in the SEZ in high- and low-inflammation schizophrenia and bipolar disorder, with opposite directional changes suggesting distinct molecular pathology. Complement activation may promote stem cell quiescence and reduce differentiation or survival of newborn neurons.

Lewy-MSA hybrid fold drives distinct neuronal α-synuclein pathology.

The ordered assembly of α-synuclein protein into filaments encoded by SNCA characterizes neurodegenerative diseases called synucleinopathies. Lewy body disease (LBD) shows predominantly neuronal α-synuclein pathology and multiple system atrophy (MSA) predominantly oligodendrocytic α-synuclein pathology affecting subcortical brain structures. Based on cryo-electron microscopy, it was reported that structures of α-synuclein filaments from LBD differ from MSA and juvenile onset synucleinopathy (JOS) caused by a 21-nucleotide duplication in the second exon of one allele of SNCA gene1-3. Importantly, a rare subtype of MSA, called atypical MSA4 shows abundant neuronal argyrophilic α-synuclein inclusions in the limbic system. Current concepts indicate that disease entities are characterized by unique protofilament folds. Here we demonstrate that in addition to the MSA fold, α-synuclein can form a new Lewy-MSA hybrid fold in the same brain region, leading to the atypical histopathological form of MSA. Distinct biochemical characteristics of α-synuclein, as demonstrated by protease-sensitivity digestion assay, seed amplification assays (SAAs) and conformational stability assay (CSA), are also linked to cytopathological differences (e.g. neuronal or oligodendroglial). We expand the current structure-based classification of α-synucleinopathies and propose that cell-specific protein pathologies can be associated with distinct filament folds.

Pathologic differences between systemic sclerosis-associated and idiopathic pulmonary arterial hypertension.

Advances in pulmonary arterial hypertension therapies have led to improvements in the quality of life and survival for patients with idiopathic pulmonary arterial hypertension, but these trends have not uniformly translated to patients with systemic sclerosis-associated pulmonary arterial hypertension. In order to better understand the heterogeneity in treatment response and survival, we aimed to examine the histological and immunophenotypic differences between the systemic sclerosis-associated pulmonary arterial hypertension and idiopathic pulmonary arterial hypertension pulmonary vasculopathies. We performed a semi-quantitative lung morphometry-based analysis comparing sections obtained from systemic sclerosis-associated pulmonary arterial hypertension (n = 24), idiopathic pulmonary arterial hypertension (n = 9), and control (n = 13) bio-banked lung tissue specimens. H&E (Hematoxylin and Eosin) and VVG (Verhoeff-Van Gieson)-stained lung sections were analyzed for interstitial and vascular pathology. Immunohistochemistry was used to stain for an array of inflammatory and fibrosis mediators. Baseline demographic and hemodynamic data for each patient were collected via chart review at the time of lung explantation. Plexiform lesions were present in 5/9 (55%) of idiopathic pulmonary arterial hypertension samples, but absent in all systemic sclerosis-associated pulmonary arterial hypertension samples (0/24). Systemic sclerosis-associated pulmonary arterial hypertension lungs demonstrated significantly worse interstitial fibrosis (p = 0.0001) and interstitial cellularity (p = 0.0002) compared to idiopathic pulmonary arterial hypertension lungs. The degree of smooth muscle hypertrophy and pulmonary artery intimal proliferation were not different between systemic sclerosis-associated pulmonary arterial hypertension and idiopathic pulmonary arterial hypertension lungs. Immunohistochemistry analysis revealed that systemic sclerosis-associated pulmonary arterial hypertension lungs exhibited increased interstitial infiltration of CD3 T-cells (p = 0.009), CD20 B-cells (p = 0.01), and CD163 macrophages (p = 0.048) when compared to idiopathic pulmonary arterial hypertension and control lungs. Systemic sclerosis-associated pulmonary arterial hypertension lungs display a distinct pulmonary vascular pathology as well as significant interstitial fibrosis when compared to idiopathic pulmonary arterial hypertension lungs.

Pediatric Traumatic Brain Injury and Microvascular Blood-Brain Barrier Pathology

Pediatric traumatic brain injury (TBI) is a major cause of morbidity and mortality, with an increased risk of catastrophic outcome compared with adult TBI, including diffuse brain swelling and so-called second impact syndrome. Nevertheless, the biological substrates driving adverse outcomes in pediatric TBI remain poorly described. To compare neuropathological evidence of brain swelling and blood-brain barrier (BBB) disruption after moderate or severe acute TBI in adult vs pediatric case material. In this retrospective case series, cases of pediatric (aged 3-18 years) and adult (aged ≥19 years) TBI were accrued from January 1, 1979, to December 31, 2005, and underwent laboratory-based assessment of autopsy material from the Glasgow TBI Archive. Data analysis was performed from January 2019 to January 2024. Single moderate or severe TBI. Evaluation of representative brain tissue sections stained for markers of endothelia (CD34) and BBB integrity (fibrinogen and immunoglobin G). Eighty-one pediatric patients (mean [SD] age, 12.1 [4.6] years; 50 [62%] male) and 62 adult patients (mean [SD] age, 38.7 [12.9] years; 35 [56%] male) were studied. At autopsy, when present, brain swelling was more often diffuse and bilateral among pediatric patients (64 of 81 cases [83%]) when compared with adult patients (21 of 62 [34%]) (P < .001). Histologic evidence of BBB disruption was common in material from both adult (57 of 62 [91%]) and pediatric (65 of 81 [80%]) (P = .06) patients. In pediatric patients, however, this was a predominantly microvascular, capillary-level pathology, which was a less common finding in adult case material (mean [SD], 84.7% [8.6%] vs 31.2% [7.7%]; P < .001). This autopsy case series of patients dying in the acute phase after single moderate or severe TBI provides neuropathological evidence of age-dependent differences in vascular pathology. Specifically, although BBB disruption in pediatric material was typically confined to microvascular, capillary-level vessels, in adult case material, BBB disruption more typically involved larger-diameter vessels. This observation of distinct microvascular pathology in pediatric acute TBI requires further investigation. In the meantime, this study presents an intriguing potential candidate pathology contributing to diffuse brain swelling in this age group.

Genetic variants associated with age-related episodic memory decline implicate distinct memory pathologies.

Approximately 40% of people aged ≥ 65 experience memory loss, particularly in episodic memory. Identifying the genetic basis of episodic memory decline is crucial for uncovering its underlying causes. We investigated common and rare genetic variants associated with episodic memory decline in 742 (632 for rare variants) Ashkenazi Jewish individuals (mean age 75) from the LonGenity study. All-atom molecular dynamics simulations were performed to uncover mechanistic insights underlying rare variants associated with episodic memory decline. In addition to the common polygenic risk of Alzheimer's disease, we identified and replicated rare variant associations in ITSN1 and CRHR2. Structural analyses revealed distinct memory pathologies mediated by interfacial rare coding variants such as impaired receptor activation of corticotropin releasing hormone and dysregulated L-serine synthesis. Our study uncovers novel risk loci for episodic memory decline. The identified underlying mechanisms point toward heterogenous memory pathologies mediated by rare coding variants. We demonstrated the contribution of the common polygenic risk of Alzheimer's disease to episodic memory decline. We discovered and replicated two risk genes associated with episodic memory declineimplicated by rare variants, were discovered and replicated. We demonstrated molecular mechanisms and potential novel memory pathologies underlying interfacial rare coding variants. Molecular dynamics simulations were performed to understand the downstream effects of risk rare coding variants.

Distinct tau pathologies in the nucleus basalis of Meynert between early-onset and late-onset Alzheimer's disease patients revealed by positron emission tomography.

Tau accumulation in the nucleus basalis of Meynert (nbM) has been documented in Alzheimer's disease (AD), but its relationship to neuropathological changes in other brain regions and cognitive deficits remains unclear, particularly between early-onset AD (EOAD) and late-onset AD (LOAD). To evaluate tau accumulation patterns in the nbM and other brain regions in EOAD and LOAD using 18F-florzolotau PET and examine correlations with cognitive function. Thirty-eight amyloid-positive AD patients (15 EOAD, 23 LOAD) and 46 healthy controls underwent 18F-florzolotau PET. Tau levels were quantified in the nbM and Braak-staging regions. Postmortem brain samples were examined to assess 18F-florzolotau binding to tau deposits. EOAD showed a higher overall tau burden, including in the nbM, compared with LOAD. However, nbM tau levels correlated more strongly with cognitive decline in LOAD than EOAD. The relationship between nbM tau and neocortical tau differed between EOAD and LOAD. Histopathology revealed abundant 18F-florzolotau labeling of neurofibrillary tangles (NFTs) and ghost tangles in AD nbM samples. This study provides the first in vivo PET evidence of differential nbM tau pathology between EOAD and LOAD, with higher accumulation but weaker correlation to cognition in EOAD. The distinct relationships between nbM and cortical tau in EOAD and LOAD suggest divergent pathological trajectories. 18F-florzolotau PET successfully visualized NFTs and extracellular ghost tangles in the nbM across AD stages. These findings highlight the importance of considering age of onset when evaluating tau pathology and its clinical correlates in AD.

Chronic overlapping pain conditions and nociplastic pain

Chronic Overlapping Pain Conditions (COPCs) are a subset of chronic pain conditions commonly comorbid with one another and more prevalent in women and assigned female at birth (AFAB) individuals. Pain experience in these conditions may better fit with a new mechanistic pain descriptor, nociplastic pain, and nociplastic pain may represent a shared underlying factor among COPCs. We applied GenomicSEM common-factor genome wide association study (GWAS) and multivariate transcriptome-wide association (TWAS) analyses to existing GWAS output for six COPCs in order to find genetic variation associated with nociplastic pain, followed by genetic correlation (linkage-disequilibrium score regression), gene-set and tissue enrichment analyses. We found 24 independent single nucleotide polymorphisms (SNPs), and 127 unique genes significantly associated with nociplastic pain, and showed nociplastic pain to be a polygenic trait with significant SNP-heritability. We found significant genetic overlap between multisite chronic pain and nociplastic pain, and to a smaller extent with rheumatoid arthritis and a neuropathic pain phenotype. Tissue enrichment analyses highlighted cardiac and thyroid tissue, and gene set enrichment analyses emphasized potential shared mechanisms in cognitive, personality, and metabolic traits and nociplastic pain along with distinct pathology in migraine and headache. We use a well-powered network approach to investigate nociplastic pain using existing COPC GWAS output, and show nociplastic pain to be a complex, heritable trait, in addition to contributing to understanding of potential mechanisms in development of nociplastic pain.

ValveVision AI - a multimodal language model for qualitative reporting of the aortic valve in echocardiography

Abstract Background The precise assessment of the aortic valve via echocardiography is critical for early detection and management of aortic valve diseases. Until recently, previous studies have examined machine learning models to estimate individual measurements and severity of aortic stenosis (AS) from echocardiographic images. These image processing algorithms, while precise in their narrow focus, fall short in mirroring the holistic and interconnected clinical judgment typical of human echocardiographers in producing a qualitative report. Large language models (LLMs), particularly image-to-text multi-modal LLMs, are a fundamental advance in the field of deep learning with implications for a host of applications in medical imaging. They promise to encapsulate not just discrete data points typical in traditional machine learning, but also the complex contextual interrelations in clinical diagnosis. Methods In this study, a large-scale heterogeneous database of echocardiographic images containing over 90,681 studies with textual descriptors of the aortic valve was used to train a single, image-to-text multimodal LLM called ValveVision AI. The ground truth textual summaries were drafted by level III echocardiographers in a clinical setting between 2015-2020. BLEU and ROUGE score was calculated. The models were retrospectively assessed on a holdout dataset. Reviewing physicians compared the generated summary to the ground truth and binarily agreed or rejected it. Receiver Operating Characteristics (ROC) for distinct pathologies were also assessed (Figure I). Results ValveVision AI performed with a BLEU score of 0.45 and a ROUGE score of 0.49. The performance of the model in reporting on classification of moderate/severe vs none/mild AS in concordance with the validation protocol described above achieved a specificity of 91.98% and a sensitivity of 83.89%, along with more precise qualitative description. Qualitatively, the model exhibited the capability of zero-shot learning in certain instances, however, this result remains an area of exploration. Conclusion This study represents to our knowledge, the first attempt at an image-representation to text-tokenizer deep learning model architecture to mimic the thought and subtlety of echocardiographic qualitative analysis of the aortic valve. The results suggest that this multimodal LLM has sufficient accuracy to create a preliminary textual summary of the aortic valve that, if paired with a point of care ultrasound (POCUS) device in a primary care setting, may facilitate case triage, increase efficiency, and determine a more precise care pathway for patients.

External validation of SpineNetV2 on a comprehensive set of radiological features for grading lumbosacral disc pathologies

BackgroundIn recent years, the integration of Artificial Intelligence (AI) models has revolutionized the diagnosis of Low Back Pain (LBP) and associated disc pathologies. Among these, SpineNetV2 stands out as a state-of-the-art, open-access model for detecting and grading various intervertebral disc pathologies. However, ensuring the reliability and applicability of AI models like SpineNetV2 is paramount. Rigorous validation is essential to guarantee their robustness and generalizability across diverse patient cohorts and imaging protocols. MethodsWe conducted a retrospective analysis of MRI images of 1747 lumbosacral intervertebral discs (IVDs) from 353 patients (mean age, 54 ± 15.4 years, 44.5% female) with various spinal disorders, collected between September 2021 and February 2023 at X-Ray Service s.r.l. The SpineNetV2 system was used to grade 11 distinct lumbosacral disc pathologies, including Pfirrmann grading, disc narrowing, central canal stenosis, spondylolisthesis, (upper & lower) endplate defects, (upper & lower) marrow changes, (right & left) foraminal stenosis, and disc herniation, using T2-weighted sagittal MR images. Performance metrics included accuracy, balanced accuracy, precision, F1 score, Matthew's Correlation Coefficient, Brier Score Loss, Lin's concordance correlation coefficients, and Cohen's kappa coefficients. Two expert radiologists provide annotations for these discs. The evaluation of SpineNetV2′s grading is compared against expert radiologists' assessments. ResultsSpineNetV2 demonstrated strong performance across various metrics, with high agreement scores (Cohen's Kappa, Lin's Concordance, and Matthew's Correlation Coefficient exceeding 0.7) for most pathologies. However, lower agreement was found for foraminal stenosis and disc herniation, underscoring the limitations of sagittal MR images for evaluating these conditions. ConclusionsThis study highlights the importance of external validation, emphasizing the need for comprehensive assessments of deep learning models. SpineNetV2 exhibits promising results in predicting disc pathologies, with findings guiding further improvements. The open-source release of SpineNetV2 enables researchers to independently validate and extend the model's capabilities. This collaborative approach promotes innovation and accelerates the development of more reliable and comprehensive deep learning tools for the assessment of spine pathology.

Cluster-Based White Matter Signatures and the Risk of Dementia, Stroke, and Mortality in Community-Dwelling Adults.

Markers of white matter (WM) injury on brain MRI are important indicators of brain health. Different patterns of WM atrophy, WM hyperintensities (WMHs), and microstructural integrity could reflect distinct pathologies and disease risks, but large-scale imaging studies investigating WM signatures are lacking. This study aims to identify distinct WM signatures using brain MRI in community-dwelling adults, determine underlying risk factor profiles, and assess risks of dementia, stroke, and mortality associated with each signature. Between 2005 and 2016, we measured WMH volume, WM volume, fractional anisotropy (FA), and mean diffusivity (MD) using automated pipelines on structural and diffusion MRI in community-dwelling adults aged older than 45 years of the Rotterdam study. Continuous surveillance was conducted for dementia, stroke, and mortality. We applied hierarchical clustering to identify separate WM injury clusters and Cox proportional hazard models to determine their risk of dementia, stroke, and mortality. We included 5,279 participants (mean age 65.0 years, 56.0% women) and identified 4 distinct data-driven WM signatures: (1) above-average microstructural integrity and little WM atrophy and WMH; (2) above-average microstructural integrity and little WMH, but substantial WM atrophy; (3) poor microstructural integrity and substantial WMH, but little WM atrophy; and (4) poor microstructural integrity with substantial WMH and WM atrophy. Prevalence of cardiovascular risk factors, lacunes, and cerebral microbleeds was higher in clusters 3 and 4 than in clusters 1 and 2. During a median 10.7 years of follow-up, 291 participants developed dementia, 220 had a stroke, and 910 died. Compared with cluster 1, dementia risk was increased for all clusters, notably cluster 3 (hazard ratio [HR] 3.06, 95% CI 2.12-4.42), followed by cluster 4 (HR 2.31, 95% CI 1.58-3.37) and cluster 2 (HR 1.67, 95% CI 1.17-2.38). Compared with cluster 1, risk of stroke was higher only for clusters 3 (HR 1.55, 95% CI 1.02-2.37) and 4 (HR 1.94, 95% CI 1.30-2.89), whereas mortality risk was increased in all clusters (cluster 2: HR 1.27, 95% CI 1.06-1.53, cluster 3: HR 1.65, 95% CI 1.35-2.03, cluster 4: HR 1.76, 95% CI 1.44-2.15), compared with cluster 1. Models including clusters instead of an individual imaging marker showed a superior goodness of fit for dementia and mortality, but not for stroke. Clustering can derive WM signatures that are differentially associated with dementia, stroke, and mortality risk. Future research should incorporate spatial information of imaging markers.

Gut commensal Alistipes as a potential pathogenic factor in colorectal cancer

Although previous research has shown that inflammation is associated with development of colorectal cancer (CRC), questions remain about whether inflammatory factor-secreting bacteria play a crucial role in CRC development. The potential role of gut microbiota in secreting inflammatory factors involved in the carcinogenesis of CRC among Chinese patients was explored in this study. 16S rRNA sequencing was utilized to evaluate the distinct microbial characteristics between patients with CRC and colorectal adenoma. The serum levels of TNF-α, IL-6 and IL-10 were measured using Enzyme-linked immunosorbent assay (ELISA), while the expression of LRG1 and TGF-β1 in tissues was evaluated by immunohistochemistry. The correlation between gut microbiota and inflammatory factor signaling was analyzed. Compared with the adenoma group, CRC patients exhibit distinct pathologies. Moreover, elevated levels of CEA, erythrocytes and haemoglobin in the blood of CRC patients were found. In addition, CRC patients have significantly higher levels of TNF-α, IL-6, IL-10, LRG1 and TGF-β1. Spearman correlation analysis revealed that LRG1 was positively related to IL-6 and TNF-α, respectively. The correlation analysis results of TGF-β1 were consistent with the above. The abundance of Blautia and Streptococcus was lower in CRC patients, while the relative abundance of Alistipes, Peptostreptococcus and Porphyromonas was significantly elevated. Moreover, positive correlations between Alistipes and inflammatory factor signaling were also found. Our results suggest that gut commensal Alistipes is a key bacterium with pro-inflammatory properties in the CRC carcinogenesis. TNF-α and IL-6 associated with Alistipes might activate LRG1/TGF-β1 signaling which contributed to the carcinogenesis of CRC.