Citations

Abstract Background Optimal treatment following first-line immunotherapy for advanced hepatocellular carcinoma (HCC) remains uncertain. This study evaluated futibatinib, a pan-FGFR inhibitor, combined with pembrolizumab in previously treated patients with FGF19-expressing HCC. Methods Eligible patients were ≥18 years old with advanced HCC, prior systemic therapy, Child-Pugh A-B7 liver function, ECOG 0–2, and FGF19 overexpression. Patients received futibatinib 20 mg orally daily plus pembrolizumab 200 mg intravenously every 3 weeks. The primary endpoint was progression-free survival at 6 months (PFS6). Secondary endpoints included overall survival (OS), objective response rate (ORR), quality of life, and safety. Results Between August 2021 and March 2024, 14 patients enrolled and 13 were evaluable. Median age was 72 years (range, 60–87), 53.8% were male, 92.3% had Child-Pugh A liver function, and all had received prior immunotherapy. Median progression-free survival was 15 weeks (95% CI, 9.0–NE), with a PFS6 rate of 23.1% (95% CI, 8.6–62.3%). ORR was 0% (95% CI, 0–24.7%), while stable disease was observed in 53.9% of patients. Median OS was 55.7 weeks (95% CI, 47.3–NE). Grade ≥3 adverse events occurred in 69.2% of patients, and grade ≥4 adverse events in 15.4%. One grade 5 event (acute-on-chronic kidney injury) was deemed unrelated to treatment. Common adverse events included hyperphosphatemia, fatigue, diarrhea, elevated transaminases, dry eye, nail changes, rash, and oral mucositis. Conclusions Futibatinib plus pembrolizumab demonstrated an acceptable safety profile but did not meet efficacy thresholds supporting further study in FGF19-expressing HCC. Effective post-immunotherapy treatment strategies remain an unmet need.

Background: Increased arterial stiffness, a marker of cardiovascular disease (CVD), is prevalent among African American (AA) adults and contributes to persistent CVD disparities. The Cardio-Ankle Vascular Index (CAVI) is a validated measure of arterial stiffness and predictor of adverse CVD outcomes. However, its relationship with the novel American Heart Association’s Life’s Essential 8 (LE8) cardiovascular health (CVH) construct has not been examined among AAs. Hypothesis: We hypothesized that increased arterial stiffness would be associated with lower CVH among AA adults. Methods: We analyzed baseline data from AA adults in the Techquity by FAITH! Trial, a 2-arm cluster randomized controlled trial conducted across 18 AA churches in Rochester and Minneapolis–St. Paul, Minnesota. Eligible participants (age ≥18 years with suboptimal diet or physical activity [PA]) completed validated electronic surveys (e.g., PA patterns) and clinical assessments (e.g., blood pressure [BP], lipids). CAVI was summarized as mean and categorized as normal (<8), borderline (8 to <9), or abnormal (≥9). CVH was assessed using the LE8 score (range 0-100 points) and categorized as low (<50), moderate (50-79), or high (≥80). Associations between CAVI and LE8 were assessed using multivariable linear regression adjusted for age, sex, and income (continuous) and Fisher’s exact test (categorical). LE8 components were compared across CAVI categories using Kruskal–Wallis tests. Results: Among 140 participants (mean age 53.0 years [SD 14.6]; 68% female), the mean LE8 score was 62.7 (SD 14.0). Nicotine exposure LE8 score was the highest (84.6 [SD 26.6]) and diet was the lowest (40.7 [SD 13.7]). Mean CAVI was 7.9 (SD 1.5), with 50% of participants classified as normal, 22% borderline, and 28% abnormal. No association between continuous CAVI and LE8 scores was observed after adjustment (unadjusted R 2 = 3.5%). All participants with high LE8 had normal CAVI, while abnormal CAVI was more prevalent among those with low (40%) and moderate (30%) LE8 scores (p<0.001). LE8 scores differed across CAVI categories for BP (median 50 in normal CAVI vs 30 in borderline/abnormal CAVI; p=0.003) and glucose LE8 scores (median 100 vs 60; p=0.014). Conclusions: Greater arterial stiffness was associated with lower CVH categories, with notable component-level differences in BP and glucose. Although not independently associated with overall LE8, integrating CAVI and LE8 categories may improve CVD risk stratification among AAs.

Abstract Background Lysosomal dysfunction plays a crucial role in the pathogenesis of Parkinson’s disease (PD), particularly among GBA1 mutation carriers. Beyond GBA1 , genes such as TMEM175 , SCARB2 , and CTSB identified in genome-wide association studies (GWAS) are also implicated in lysosomal pathways contributing to PD risk, although their functional effects in patients remain unclear. Proteins encoded by these lysosome-related genes have been explored as potential therapeutic targets in experimental models. Biomarker profiles, including clinical measures, α-syn seeding activity, lysosomal proteins, and sphingolipids, may facilitate patient stratification and support therapeutic monitoring in future clinical trials. Aim The aim of this study is to investigate the impact of genetic variants of three lysosomal-related genes ( TMEM175 , SCARB2 , and CTSB ) on biomarker profiles in PD with and without GBA1 variants. Cross-sectional data from two German cohorts: the Tuebingen Parkinson Cohort (TUEPAC) and the DESCRIBE PD cohort of the German Center for Neurodegenerative Diseases were used as explorative cohorts, and data from Accelerating Medicines Partnership® Parkinson’s Disease (AMP-PD) were used as a validation cohort. The ultimate goal is to provide new data for patient stratification based on genetics, which might serve as a readout for target engagement and treatment efficiency assessment. Methods Three cohorts were analyzed: TUEPAC, DESCRIBE PD, and AMP-PD. TUEPAC and DESCRIBE PD were combined into a single German discovery cohort (TUEPAC-DESCRIBE-PD), while AMP-PD served as an independent validation cohort. Within each cohort, for subgroup analyses, PD patients were classified as the overall PD cohort (PD all ), and further stratified by GBA1 mutation status into PD patients without GBA1 mutations (PD GBA1 _wildtype ), and PD patients carrying GBA1 mutations (PD GBA1 ). We evaluated cognitive and motor function, as well as depression using the Montreal Cognitive Assessment (MoCA), Unified Parkinson Disease Rating Scale-part I II (UPDRS III), and Beck Depression Inventory-II(BDI-II) scales. Analyzed biomarkers included CSF α-syn seeding activity using seed amplification assay (SAA), CSF lysosomal protein levels of lysosomal integral membrane protein 2 (LIMP2), also known as SCARB2, cathepsin B (CTSB) and lysosome-associated membrane protein 2 (LAMP2), blood-based enzyme activity of the lysosomal glucocerebrosidase (GCase), and CSF sphingolipid profiles. PD patients carrying risk alleles in TMEM175 , SCARB2 , and CTSB were compared to non-carriers. Results Genotype-phenotype correlation analysis in TUEPAC-DESCRIBE-PD and AMP-PD revealed: (1) In PD all , the TMEM175 p.M393T risk variant was nominally associated with decreased cognitive function when adjusted for GBA1 mutation status in TUEPAC-DESCRIBE-PD; this association could not be replicated, although a similar trend was observed in the slightly smaller, but multicentric AMP-PD cohort; TMEM175 p.M393T was not significantly associated with BDI-I I or UPDRS-III scores in either cohort. (2) In PD GBA1 _wildtype , GCase activity was significantly lower in PD patients with SCARB2 rs6812193 risk allele in TUEPAC-DESCRIBE-PD, while a similar but non-significant trend was observed in AMP-PD; (3) In PD all , CSF levels of CTSB were nominally lower in carriers of CTSB rs1293298 risk allele compared to carriers of CTSB rs1293298 protective allele in TUEPAC-DESCRIBE-PD; in PD GBA1 _wildtype , LAMP2 was significantly lower in carriers of CTSB rs1293298 risk allele compared to carriers of CTSB rs1293298 protective allele in TUEPAC-DESCRIBE-PD; (4) In PD all , TMEM175 p.M393T risk allele was nominally associated with altered sphingolipid profiles across both TUEPAC-DESCRIBE-PD and AMP-PD cohorts. Conclusion These findings demonstrate that genetic variants in lysosomal-related genes ( TMEM175 , SCARB2 , and CTSB ) have a functional impact on biomarker profiles in PD patients. Integrating genetic characterization with biochemical profiling provides a framework for patient stratification and may serve as a translational strategy to monitor target engagement and evaluate treatment efficacy in future clinical trials.

Abstract Background Markerless tumor tracking (MTT) using single‐energy (SE) kilovoltage (kV) imaging has been proposed as a technique for lung tumor motion management. However, bony structures can obscure the tumor and make tracking challenging. Dual‐energy (DE) subtraction imaging can suppress the bone and therefore enhance tumor visibility, potentially improving tracking accuracy. Purpose To develop a machine learning model that predicts the reliability of MTT for SE and DE imaging using phantom and patient data. Methods Images were collected at high and low energy (120/60 kV) using fast‐kV switching on dynamic thorax phantom with 5–15 diameter targets and 20 lung cancer patients, including one patient with two tumor locations. DE images were then generated off‐line using weighted logarithmic subtraction. Separately, a template‐based tracking algorithm was used to track the tumor on both phantom and patient images. For phantom data, the ground truth (GT) was defined by the cos 4 waveform programmed into the motion controller. Since the GT was unknown for patient data, it was estimated using a Kalman filter and further refined using visual inspection. The tracking success rate (TSR) was subsequently calculated. Based on TSR, patients were stratified into three tracking groups: good, moderate, and poor. A logistic regression (LR) model was implemented with tracking features, including match score, peak to side‐peak ratio (PSR), x ‐ and y ‐velocity. To address the distribution differences between phantom and patient data, a domain indicator and interaction features were also incorporated. The model was trained on phantom and 17 patient data using leave‐one‐out cross‐validation, and its performance was evaluated on three held‐out patients, one from each tracking group. Separate LR models were developed for each imaging modality, resulting in SE‐LR and DE‐LR models. For each held‐out patient, the confusion matrix, sensitivity, and specificity were reported. Results For both SE‐LR and DE‐LR models, PSR has the largest coefficient value, indicating that it is the most influential factor when determining the reliability of tracking. At a specificity of 95%, the DE‐LR model achieved significantly higher sensitivity than the SE‐LR model (0.908 vs. 0.731, p < 0.01 for phantom data and 0.657 vs. 0.589, p < 0.01 for patient data). In the three held‐out patients, the DE‐LR model outperformed the SE‐LR model across all metrics. The largest gains were found in the patient with good tracking quality. Conclusions The proposed LR models successfully predicted the reliability of SE‐ and DE‐MTT. Across phantom and patient datasets, the DE‐LR model consistently demonstrated improved performance compared with the SE‐LR model, suggesting that DE imaging may be beneficial for MTT applications.

ABSTRACT BACKGROUND Increasing evidence suggests that accurate prediction of Alzheimer’s disease (AD) symptom onset requires more than amyloid- and tau-centric biomarkers such as cerebrospinal fluid (CSF) Aβ42/40, total tau and p-tau181 and plasma p-tau217. Autosomal dominant AD (ADAD), caused by pathogenic PSEN1, PSEN2 and APP mutations with predictable age at symptom onset, presents a unique opportunity to characterize the chronological changes in proteins beyond amyloid and tau and clarify them as early biomarkers of disease onset or as biomarkers related to disease staging and progression monitoring. METHODS We measured 972 CSF samples corresponding to 484 participants of the Dominantly Inherited Alzheimer Disease Network (DIAN) using the NULISASeq 120 CNS Disease Panel. We first benchmarked the technology against gold-standard measurements followed by the identification of proteins that were differentially abundant in relation to mutation status and symptomatology. Next, we determined the chronological emergence of protein changes in relation to the estimated years to onset (EYO). Finally, we assessed whether specific protein measures improved the prediction of EYO in the ADAD. FINDINGS NULISA measurements were comparable to those previously published. We demonstrated that known early alterations in CSF amyloid and tau were followed by inflammatory and neurodegenerative responses suggesting that clinical manifestation of AD happens before the inflammatory processes is fully developed. Finally, we found a multi-protein composite approach for predicting EYO that outperformed single biomarker values. INTERPRETATION Our results suggest that the main CSF proteomic landscape changes in ADAD are due to the presence of a pathogenic mutation and occur prior to symptom onset. Improved performance of multi-protein composite to predict EYO compared to single biomarker values highlights the added value of multiplex proteomic signatures for biomarker panel development. FUNDING National Institute on Aging, Alzheimer’s Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea, Spanish Institute of Health Carlos III.

Abstract Background and Aims Stroke and systemic embolism are recognized but poorly characterized complications of atrial fibrillation (AF) and left atrial flutter (AFL) catheter ablation. Their incidence, outcomes, and procedural associations remain insufficiently defined. Methods Retrospective global registry was initiated by the European Heart Rhythm Association Scientific Committee. A secure database captured data from ablation centres worldwide on general AF and left AFL ablation activity, as well as detailed information on patients with symptomatic embolic events between 2017 and 2024. Results Overall, 204 centres reported 335 743 ablation procedures and 550 embolic events (incidence 0.16%). Centre-level rate ranged from 0% to 3.1%. Most events were cerebral (94%), followed by peripheral (5%), and combined (1%). Coronary air embolism accounted for 62% of all peripheral events. Intraprocedural events occurred in 93 patients (17%), within 72 h in 357 (78%) and beyond 72 h in 100 (22%); 128 cases (23%) were diagnosed after hospital discharge. Nonparoxysmal AF (0.23% vs 0.15%; P &lt; .001), centre experience, and ablation energy source (radiofrequency, 0.16%; cryoballoon, 0.16%; pulsed field ablation, 0.25%; laserballoon, 0.88%; P &lt; .001) were associated with embolic risk. Median NIHSS score after stroke was 4 (interquartile range, 2–9). Three-month follow-up was available for 518 patients with embolism (95%): 181 (35%) had sequelae and 16 (3%) died. Conclusions Symptomatic embolic events are infrequent but associated with significant morbidity and mortality. Most events occur early, though a substantial proportion arise later. Higher event rates were observed with laser and possibly with pulsed field ablation. A greater centre experience was associated with a lower embolism incidence.

ABSTRACT Background Sunlight has profound impacts on physical and mental health, beyond vision, including effects on circadian rhythms, alertness, mood, and sleep. A family history of any mood disorders is strongly associated with psychiatric disorders including bipolar disorder. The purpose of this study was to evaluate the association between a family history of any mood disorder in patients with bipolar I disorder and solar insolation at varied international onset locations. Methods Data for this analysis were available from 5842 patients with a diagnosis of bipolar I disorder obtained at 83 collection sites in both hemispheres. This included 4752 patients from 71 collection sites in the northern hemisphere and 1090 patients from 12 collection sites in the southern hemisphere. Patient data variables were obtained from records or interviews. Solar insolation data were obtained from The National Aeronautics and Space Administration (NASA) Power database for each onset location, and the ratio of the mean monthly minimum/mean monthly maximum solar insolation was calculated. Typically, the ratio is largest near the equator (little yearly change in solar insolation) and smallest near the poles (large yearly change in solar insolation). Results A significant relationship was found between a family history of any mood disorder, the ratio of the mean monthly minimum/mean monthly maximum solar insolation, and gender. The odds of a family history of mood disorder increased as patient location nears the poles and decreased near the equator. Female gender also increased the odds of having a family history of a mood disorder. Conclusions This study highlighted the association between family history, solar insolation, and gender in international patients with bipolar I disorder. Given the profound effects of sunlight on human health, the family of patients with bipolar disorder who live in the same location with the same solar insolation, and especially females, may be at increased risk for a mood disorder.

Background Predictive models employing machine learning algorithms are increasingly being used in clinical decision making, and improperly calibrated models can result in systematic harm. We sought to investigate the impact of class imbalance correction, a commonly applied preprocessing step in machine learning model development, on calibration and modelled clinical decision making in a large real-world context. Methods A histogram boosted gradient classifier was trained on a highly imbalanced national dataset of >1.8 million patients undergoing surgery, to predict the risk of 90-day mortality and complications after surgery. Class imbalance correction strategies including random oversampling, synthetic minority oversampling technique, random under-sampling, and cost-sensitive learning were compared to the natural distribution ('natural'). Models were tested and compared with classification metrics, calibration plots, decision curve analysis, and simulated clinical impact analysis. Results The natural model demonstrated high performance (AUROC 0.94, 95% CI 0.94--0.95 for mortality; 0.84, 95% CI 0.84--0.85 for complications) and calibration (log loss 0.05, 95% CI 0.04--0.05 for mortality; 0.23, 95% CI 0.23--0.24 for complications). Class imbalance mitigation (CSL, ROS, RUS, and SMOTE) did not improve AUROC or AUPRC but increased recall and F1 scores at the expense of precision and accuracy. However, these methods severely compromised model calibration, leading to significant over-prediction of risks (up to a 62.8 % increase) as further evidenced by increased log loss across all mitigation techniques. Decision curve analysis and clinical scenario testing confirmed that the natural model provided the highest net benefit. Conclusion Class imbalance correction methods result in significant miscalibration, leading to possible harm whenused for clinical decision making.

ABSTRACT Brain lesions classically cause contralateral sensorimotor and postural deficits, attributed to the decussation of descending neural pathways. However, recent findings reveal that, beyond neural mechanisms, contralateral effects can also be mediated by the neuroendocrine system via humoral pathways. This raises the possibility that the brain regulates left- and right-sided peripheral processes through hypothalamic neurohormones released into the bloodstream. For such spatially targeted endocrine signaling to occur, hemisphere-specific neural activity must be encoded into side-specific hormonal output—requiring a lateralized organization of hypothalamic neuroendocrine systems. Here, we report molecular asymmetries in the rat hypothalamus that support this mechanism. Transcriptomic analysis revealed asymmetric expression of eleven neurohormonal genes, including Gnrh1 , Cck , and Trh , along with distinct left-right side-specific gene co-expression networks. Chemogenetic stimulation of Arg-vasopressin neurons in vasopressin-hM3Dq-mCherry transgenic rats produced generalized changes in these networks—predominantly in the right hypothalamus—suggesting that hypothalamic neurohormonal circuits function as integrated, lateralized ensembles. Stereological analysis revealed asymmetric coordination of vasopressin neurons within the paraventricular nucleus, with the left rostral region decoupled from the right rostral and caudal subregions. Functionally, gonadotropin-releasing hormone, cholecystokinin-8, and thyrotropin-releasing hormone—administered intracisternally in rats with complete spinal cord transection—elicited side-specific peripheral responses, measured as hindlimb postural asymmetry in a binary left–right output model. These neurohormonal effects were therefore transmitted via the humoral route. These findings suggest that multiple hypothalamic neurohormones and their integrated networks are asymmetrically organized, and that their lateralization may be necessary for hemisphere-specific hormonal regulation of peripheral systems.