Citations

Background: Sexual dimorphism in the facial skeleton is fundamental to aesthetics and gender perception. This study employs AI-assisted three-dimensional (3D) imaging to analyze morphological differences between males and females in the upper, mid, and lower facial regions. Methods: A retrospective analysis was conducted on 280 high-resolution craniofacial CT scans (147 females, 133 males) of adults aged 20 years and older. AI-assisted segmentation and modeling were performed using Materialise Mimics and 3-Matic software. The facial skeleton was divided into upper, mid, and lower regions for detailed morphometric evaluation. Statistical shape modeling (SSM) and heatmaps were used to visualize surface projection differences across age groups. Statistical comparisons were conducted to assess gender-based variation. Results: Significant sexual dimorphism was observed across all facial regions. In the upper face, males had greater interorbital width, frontotemporal brow width, inter-medial canthi distance, and more prominent frontal bossing. In the midface, males exhibited increased width, depth, and vertical height, with the most pronounced differences occurring in middle age. The lower face showed larger mandibular dimensions in males, including bigonial width, ramus height, and a sharper mental angle, while females had a more rounded chin and smoother mandibular contour. Heatmaps confirmed greater surface projection in male skeletons, particularly in the gonial and midfacial regions, with dimorphism decreasing with age. Conclusion: This represents the first large-sample CT study utilizing AI to comprehensively quantify facial skeletal dimorphism. Findings support the importance of gender-specific planning in facial reconstructive and aesthetic procedures.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Background: Patients with cervical artery dissection (CAD) have a higher prevalence of cerebral aneurysms, likely due to underlying vasculopathies. Understanding risk factors and outcomes in this population may inform screening and management strategies. Methods: We conducted a post-hoc analysis of the STOP-CAD study, a multicenter international registry of patients with non-major trauma-related CAD across 63 centers. Cerebral aneurysms were identified based on medical history and intracranial vascular imaging obtained for dissection diagnosis. We compared demographic, clinical, laboratory, and imaging characteristics between patients with and without aneurysms. Variables with p<0.05 in univariate analysis were entered into a multivariable binary logistic regression to identify independent predictors. Clinical outcomes including ischemic stroke and symptomatic intracranial hemorrhage at follow-up were compared between both groups. Results: Out of 4023 patients included in the STOP-CAD study, 116 (2.9%) had at least one incidental cerebral aneurysm. In adjusted binary logistic regression, patients with cerebral aneurysm were more likely to have a history of migraine (aOR 1.78 95% CI 1.15-2.75, p=0.009), history of hypertension (aOR 1.65 95% CI 1.12-2.43, p = 0.010), known connective tissue disorder (aOR 3.47 95% CI 1.71-7.03), history of dissection (aOR 2.63 95% CI 1.31-5.28, p = 0.007), and a dissecting aneurysm at the site of the dissection (aOR 1.94 95% CI 1.25-3.01, p = 0.003). At follow-up, the presence of a cerebral aneurysm was not associated with ischemic stroke (7.8% vs. 5.6% p>0.1), but with a trend towards increased odds of symptomatic intracranial hemorrhage (3.4% vs. 1.2%, p = 0.062). Conclusions: Patients with CAD and concurrent incidental cerebral aneurysm were more likely to have a history of migraine headaches and markers of underlying vasculopathy and had a non-significantly increased risk of intracranial hemorrhage at follow-up. Further studies are needed to identify best practices for surveillance and risk stratification in this subgroup.

Abstract Recent updates to monocyte count thresholds recognize oligomonocytic chronic myelomonocytic leukemia (OM-CMML) as an early form of CMML. However, the clinical validity of these changes remains uncertain without incorporating biological and genomic factors. In this study, we analyzed a cohort of 911 patients (249 with OM-CMML, 359 with overt CMML, and 303 with myelodysplastic syndromes) using unsupervised clustering to evaluate the role of genomic determinants in refining CMML diagnosis. Our findings show that CMML molecular signatures (biallelic TET2 mutations or SRSF2-TET2 comutations) are linked to a distinct transcriptome, monocytic bias, classical monocytosis, and a higher risk of progression to overt CMML in OM-CMML cases. We developed a weighted genomic model and diagnostic workflow showing that combining genomic signatures with bone marrow monocyte frequencies in OM-CMML more accurately predicts progression to overt CMML. These findings support integrating genomic determinants and our clinic-ready diagnostic workflow into the CMML diagnostic framework to improve accuracy. Significance: Through comprehensive clinical and genomic profiling of a large patient cohort, alongside immunophenotypic and transcriptional cellular analyses, this study provides evidence that incorporating genomic determinants into the diagnostic criteria for OM-CMML improves diagnostic accuracy and refines the identification of early-stage CMML, thereby preventing misclassification.

Abstract Neuroendocrine prostate cancer (NEPC) is an increasingly prevalent manifestation of acquired resistance to next generation AR signaling inhibitors (ARSI), that arises via transformation from advanced prostate adenocarcinoma (PRAD) through a mechanism called lineage plasticity. Through characterization of isogenic PRAD and NEPC mouse tumoroid models generated using human-relevant driver mutations (Pten-/-;Rb1-/-;Trp53-/-), we revealed an extensive epigenetic reprogramming in NEPC versus PRAD, particular at enhancers. CRISPR screens focused on TFs and coactivators revealed a NEPC lineage TF survival network comprised of ASCL1, NFIB, SOX1/11, FOXA1/2 and MYCL with exquisite dependency on the TIP60 acetyltransferase complex. During the PRAD-to-NEPC transition, FOXA1, NFIB and TIP60 chromatin binding redistributes to NEPC specific enhancers, resulting in expression of NEPC target genes in a coordinate fashion with ASCL1 functioning as master regulator, culminating in activation of MYCL. MYCL then directly recruits the TIP60 complex to target sites, where it acts as a requisite MYCL coactivator for target gene activation for NEPC growth/survival. The acetyltransferase activity of TIP60 and acetylation of its substrate H2A.Z are both required for NEPC survival, as well as two chromatin reader subunits of the TIP60 complex, BRD8 and YEATS4. Targeted chemical degradation of TIP60 revealed &gt;500-fold dependency in NEPC relative to normal prostate, credentialing the TIP60 complex as a potential therapeutic target in NEPC. Citation Format: Zhen Sun, Jimmy L. Zhao, Wazim M. Ismail, Zahra F. Khan, Teng Han, Subhiksha Nandakumar, Serina Young, Matthew Lange, Richard Koche, Alexandre Gaspar-Maia, Charles L. Sawyers. The TIP60 acetyltransferase complex is a critical dependency in neuroendocrine prostate cancer through its role as a critical coactivator of MYCL downstream of ASCL1 [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr PR036.

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen's kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure 1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure 1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure 2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure 2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

Objectives: To identify factors associated with short-term mortality among patients receiving microaxial flow pump (mAFP) therapy for acute myocardial infarction-related cardiogenic shock (AMI-CS). Data Sources: We searched four databases (MEDLINE, Embase, CENTRAL, and Scopus) from January 1, 2004, to January 1, 2025. Study Selection: We selected English-language studies that included adults with AMI-CS receiving mAFP and evaluated factors associated with short-term mortality. We excluded patients receiving concurrent venoarterial extracorporeal membrane oxygenation, as well as studies that solely included patients presenting with out-of-hospital cardiac arrest. Data Extraction: Two authors performed citation screening and data extraction. For each factor evaluated in at least two studies, we performed meta-analyses of adjusted odds ratios (aORs) using a random-effects model. Risk of bias was evaluated using the Quality in Prognosis Studies tool, and the certainty of evidence was evaluated using Grading of Recommendations, Assessment, Development, and Evaluations methodology. Data Synthesis: Our primary analysis included 18 studies, encompassing 20,617 patients. Median short-term mortality across studies was 50.7% (interquartile range 38.4–55.3%). Factors associated with short-term mortality based on high-certainty evidence included: increased age (aOR, 1.04 per year [95% CI, 1.03–1.05 per year] or ≥ 65 yr (aOR, 2.42 yr [95% CI, 0.77–7.64 yr]), female sex (aOR, 1.26 [95% CI, 1.09–1.45]), higher body mass index (aOR, 1.05 per point [95% CI, 1.04–1.07 per point]), higher heart rate (aOR, 1.02 per beats/min [95% CI, 1.01–1.02 per beats/min]), higher serum creatinine (aOR, 1.35 per mg/dL [95% CI, 1.08–1.70 per mg/dL]), mechanical ventilation (aOR, 2.53 [95% CI, 1.82–3.53]), vasopressors (aOR, 1.52 [95% CI, 1.11–2.08] for any vasopressors and aOR, 1.37 [95% CI, 1.18–1.58] per each vasopressor), presentation with ST-elevation myocardial infarction (aOR, 1.59 [95% CI, 1.11–2.26]), cardiac arrest (aOR, 2.85 [95% CI, 2.22–3.64]), and hypoxic-ischemic brain injury (aOR, 5.36 [95% CI, 3.03–9.47]). Conclusions: We identified several prognostic factors associated with short-term mortality in AMI-CS patients receiving mAFP support. This work may help inform clinicians, patients, and families regarding utilization of mAFP in AMI-CS.

Abstract Background Frontotemporal dementia (FTD) with right anterior temporal lobe (RATL) predominant atrophy is an emerging area of interest. Recent findings by the International Working Group (IWG) have identified this subtype as having a distinct clinical profile within the FTD spectrum (Ulugut et al., 2024, A&D). However, its genetic and pathological underpinnings remain unexplored in large, multicultural cohorts. Methods Retrospective analyses encompassing clinical, genetic, pathological, and neuroimaging data from 23 IWG sites across 13 countries in Asia, Middle East, Europe, North and South America were conducted. The study included 444 patients with FTD exhibiting predominant RATL atrophy. Results Genetic screening was performed on 51% ( n = 225) of the cohort for at least the major frontotemporal lobar degeneration (FTLD) mutations including microtubule‐associated protein tau ( MAPT ), progranulin ( GRN ), and chromosome 9 open reading frame 72 ( C9orf72 ), or dementia panels encompassing extended sets of genes. Of these, 81% were sporadic, showing negative results for the screened genes and a modified Goldman Score of ≥ 3, indicating a negative family history for dementia. The MAPT mutation was the most common genetic variant, identified in 7% of the screened cases (Figure 1). Pathological confirmation was available for 63 patients. Among the sporadic cases, transactive response DNA‐binding protein 43 type C (TDP‐C) pathology was most prevalent (60%, n = 32), while tau‐MAPT pathology was most common in the genetic cases (38%, n = 16). Fifteen cases did not fit neatly into genetic or sporadic categories, displaying heterogeneous pathologies (Figure 2). At the initial visit, compared to genetic cases, patients with TDP‐C pathology were older, and more frequently exhibited semantic deficits, with less frequent attention difficulties and executive dysfunction. No differences were observed in sex distribution, symptom duration or disease severity between genetic and sporadic TDP‐C cases. However, left handedness was more common in TDP‐C cases (14%) compared to genetic cases (5%). Conclusion While FTD with RATL atrophy primarily appears sporadic, a significant proportion of cases exhibit genetic variants. These sporadic and genetic subtypes display distinct neuropathological features and clinical manifestations. Given the implications for therapeutic strategies, precise clinical and molecular subtyping is critical for enhancing patient management and ensuring appropriate enrollment in clinical trials.

Abstract Background In aging and dementia research, the relationships between modifiable risk factors and biomarkers often vary across cohorts. We aim to evaluate the consistency and generalizability of the association between the area deprivation index (ADI) ‐ an indicator of socioeconomic/resource disadvantage within a specific area ‐ and cognition and Alzheimer's disease (AD) biomarkers across three distinct research cohorts, two from the U.S. (U.S. POINTER Imaging, ADNI) and one from Spain (UBRAIN). Method We included a total of 3091 participants without dementia, 1879 from U.S. POINTER Imaging, 282 from ADNI and 930 from UBRAIN (Table 1). The ADI was calculated using validated indices from the US and Spain, with neighborhood deprivation ranked as Low, Moderate, and High in the US, and Low and High in Spain. Outcomes of interest included (1) the preclinical Alzheimer's cognitive composite (PACC‐5), (2) MRI‐derived gray matter volumes in AD‐vulnerable regions and (3) PET or CSF‐derived amyloid status (+/‐). We ran logistic regression models with ADI level as predictor adjusted by sex, age, and APOE4 and considered education and race or ethnicity (only US cohorts) in our analyses. Result Participants in more deprived areas had lower education across cohorts and were more likely to be female (U.S. POINTER) and African American (U.S. POINTER and ADNI, Table 1). Independent of age, sex and APOE4 status, higher ADI was associated with lower PACC in U.S. POINTER (Moderate: β=‐0.165, p <0.001; High β=‐0.412, p <0.001) and UBRAIN (ADI: High β=‐0.096, p = 0.022) but not in ADNI (Figure 1). After controlling for education, this association remained significant in U.S. POINTER (Moderate: β=‐0.166, p = 0.002; High: β=‐0.248, p = 0.007) but not in UBRAIN (β=‐0.021, p = 0.66). In U.S. POINTER, there was a trend towards an association of higher ADI with lower GM volume in AD‐vulnerable regions (β=‐0.126, p = 0.089) that was not observed in ADNI or UBRAIN (Figure 2). No associations between ADI and amyloid status were found across cohorts. Conclusion We observed differing associations in neighborhood deprivation and cognition across US cohorts, as well as between the US and Spain cohorts. Country‐specific factors and sample representativeness must be considered when investigating the pathophysiologic mechanisms underlying social determinants and disparities in AD.

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen’s kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure‐1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure‐1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure‐2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure‐2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.