Dion-Jacobson-Phase 2D Sn-Based Perovskite Comprising a High Dipole Moment of π-Conjugated Short-Chain Organic Spacers for High-Performance Solar Cell Applications.

The stability issue of Sn-based perovskite solar cells (PSCs) is expected to be resolved by involving a two-dimensional (2D) layered structure. However, Sn-based 2D PSCs, especially Dion-Jacobson (DJ)-phase ones with potentially good stability, have rarely been reported. Herein, superior DJ-phase Sn 2D perovskites with 3-aminobenzylamine (3ABA2+) or 4-aminobenzylamine (4ABA2+) π-conjugated short-chain ligands are reported to fabricate efficient 2D lead-free PSCs. Notably, the high dipole moment of the 3ABAI2 organic spacer is approved to possess faster charge transfer for forming (3ABA)FA4Sn5I16 2D perovskite with an extremely low exciton binding energy (only 84 meV). In combination with a diacetate partial substitution and methylamine iodide/bromide (MAI/MABr) post-treatment strategy to delay crystallization and improve compactness and coverage of the perovskite film, a record power conversion efficiency (PCE) of 6.81% and stability of 840 h (less than 5% degradation in a N2 atmosphere for unencapsulated devices) are acquired in eventual (3ABA)FA4Sn5I16 2D PSCs, which are among the highest PCE and the longest stability of Sn-based 2D PSCs reported to date. Our work provides a prospective molecule design and film preparation strategy of 2D Sn perovskites toward nontoxic high-performance tin-based PSCs, which pushes the almost stagnant research forward.

The gut microbiota-aromatic hydrocarbon receptor (AhR) axis mediates the anticolitic effect of polyphenol-rich extracts from Sanghuangporus.

Inflammatory bowel disease (IBD) is a significant global health concern. The gut microbiota plays an essential role in the onset and development of IBD. Sanghuangporus (SH), a traditional Chinese medicinal mushroom, has excellent anti-inflammatory effects and is effective at modulating the gut microbiota. Despite these attributes, the specific anticolitic effects of SH and the mechanisms through which the gut microbiota mediates its benefits remain unclear. Herein, we demonstrated that polyphenol-rich extract from SH effectively alleviated the pathological symptoms of dextran sodium sulfate (DSS)-induced colitis in mice by modulating the gut microbiota. Treatment with SH distinctly enriched Alistipes, especially Alistipes onderdonkii, and its metabolite 5-hydroxyindole-3-acetic acid (5HIAA). Oral gavage of live A. onderdonkii or 5HIAA potently mitigated DSS-induced colitis in mice. Moreover, both 5HIAA and SH significantly activated the aromatic hydrocarbon receptor (AhR), and the administration of an AhR antagonist abrogated their protective effects against colitis. These results underscore the potent efficacy of SH in diminishing DSS-induced colitis through the promotion of A. onderdonkii and 5HIAA, ultimately activating AhR signaling. This study unveils potential avenues for developing therapeutic strategies for colitis based on the interplay between SH and the gut microbiota.

Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention and intervention.

Identifying risk protein targets and their therapeutic drugs is crucial for effective cancer prevention. Here, we conduct integrative and fine-mapping analyses of large genome-wide association studies data for breast, colorectal, lung, ovarian, pancreatic, and prostate cancers, and characterize 710 lead variants independently associated with cancer risk. Through mapping protein quantitative trait loci (pQTL) for these variants using plasma proteomics data from over 75,000 participants, we identify 365 proteins associated with cancer risk. Subsequent colocalization analysis identifies 101 proteins, including 74 not reported in previous studies. We further characterize 36 potential druggable proteins for cancers or other disease indications. Analyzing >3.5 million electronic health records, we uncover five drugs (Haloperidol, Trazodone, Tranexamic Acid, Haloperidol, and Captopril) associated with increased cancer risk and two drugs (Caffeine and Acetazolamide) linked to reduced colorectal cancer risk. This study offers novel insights into therapeutic drugs targeting risk proteins for cancer prevention and intervention.

omicsMIC: a comprehensive benchmarking platform for robust comparison of imputation methods in mass spectrometry-based omics data.

Mass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in mass spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometry-based omics with Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. omicsMIC is freely available at https://github.com/WQLin8/omicsMIC.

Prognostic and predictive value of examined lymph node count in stage III colorectal cancer: a population based study.

BACKGROUND: The role of tumor-draining lymph nodes in the progression of malignant tumors, including stage III colorectal cancer (CRC), is critical. However, the prognostic and predictive value of the number of examined lymph nodes (ELNs) are not fully understood. METHODS: This population-based study retrospectively analyzed data from 106,843 patients with stage III CRC who underwent surgical treatment and registered in three databases from 2004 to 2021. The Surveillance, Epidemiology, and End Results (SEER) cohort was divided using into training and test cohorts at a ratio of 3:2. We employed restricted cubic spline (RCS) curves to explore nonlinear relationships between overall survival (OS) and ELNs counts and performed Cox regression to evaluate hazard ratios across different ELNs count subtypes. Additional validation cohorts were utilized from the First Affiliated Hospital, Sun Yat-sen University and The Cancer Genome Atlas (TCGA) under the same criteria. Outcomes measured included OS, cancer-specific survival (CSS), and progression-free survival (PFS). Molecular analyses involved differential gene expression using the "limma" package and immune profiling through CIBERSORT. Tissue microarray slides and multiplex immunofluorescence (MIF) were used to assess protein expression and immune cell infiltration. RESULTS: Patients with higher ELNs counts (≥ 17) demonstrated significantly better long-term survival outcomes across all cohorts. Enhanced OS, CSS, and PFS were notably evident in the LN-ELN group compared to those with fewer ELNs. Cox regression models underscored the prognostic value of higher ELNs counts across different patient subgroups by age, sex, tumor differentiation, and TNM stages. Subtype analysis based on ELNs count revealed a marked survival benefit in patients treated with adjuvant chemotherapy in the medium and large ELNs counts (≥ 12), whereas those with fewer ELNs showed negligible benefits. RNA sequencing and MIF indicated elevated immune activation in the LN-ELN group, characterized by increased CD3+, CD4+, and CD8 + T cells within the tumor microenvironment. CONCLUSIONS: The number of ELNs independently predicts survival and the immunological landscape at the tumor site in stage III CRC, underscoring its dual prognostic and predictive value.

Efficient Template-Catalyzed In Situ Polymerization for Carbon Xerogels with Large Specific Surface Area and High Adsorption.

The limited specific surface area (SSA), long preparation period, and high cost are significant challenges for carbon xerogels (CXs). To overcome these limitations, we propose an approach to prepare tannin-resorcinol-formaldehyde-based CXs through template-catalyzed in situ polymerization. ZnCl2 acts as a catalyst and significantly accelerates the polymerization reaction through the coordination of Zn2+ to the carbonyl group in formaldehyde, while atmospheric drying instead of special drying and without solvent exchange reduces the preparation period to 24 h. In addition, ZnCl2 acts as an activator for the formation of many pores. Plant-derived tannins not only reduce the preparation cost but also regulate the pore structure. The resulted CXs with hierarchical porous structures show an optimal SSA of 1308 m2/g, high adsorption capabilities (for cationic, nitrosoaniline dyes, metal, and nonmetallic ions, especially for methylene blue with 454.93 mg/g), low shrinkage down to 10%, and reusability with 92.9% retention after 5 cycles. This work provides a promising and cost-effective method for the large-scale preparation of porous carbon materials with large SSA, offering potential applications in adsorption, energy storage, and catalysis.

Comparing Sonazoid contrast-enhanced ultrasound to contrast-enhanced CT and MRI for differentially diagnosing renal lesions: a prospective multicenter study.

PURPOSE: To evaluate the diagnostic performance of contrast-enhanced (CE) ultrasound using Sonazoid (SNZ-CEUS) by comparing with contrast-enhanced computed tomography (CE-CT) and contrast-enhanced magnetic resonance imaging (CE-MRI) for differentiating benign and malignant renal masses. MATERIALS AND METHODS: 306 consecutive patients (from 7 centers) with renal masses (40 benign tumors, 266 malignant tumors) diagnosed by both SNZ-CEUS, CE-CT or CE-MRI were enrolled between September 2020 and February 2021. The examinations were performed within 7 days, but the sequence was not fixed. Histologic results were available for 301 of 306 (98.37%) lesions and 5 lesions were considered benign after at least 2 year follow-up without change in size and image characteristics. The diagnostic performances were evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and compared by McNemar's test. RESULTS: In the head-to-head comparison, SNZ-CEUS and CE-MRI had comparable sensitivity (95.60 vs. 94.51%, P = 0.997), specificity (65.22 vs. 73.91%, P = 0.752), positive predictive value (91.58 vs. 93.48%) and negative predictive value (78.95 vs. 77.27%); SNZ-CEUS and CE-CT showed similar sensitivity (97.31 vs. 96.24%, P = 0.724); however, SNZ-CEUS had relatively lower than specificity than CE-CT (59.09 vs. 68.18%, P = 0.683). For nodules > 4 cm, CE-MRI demonstrated higher specificity than SNZ-CEUS (90.91 vs. 72.73%, P = 0.617) without compromise the sensitivity. CONCLUSIONS: SNZ-CEUS, CE-CT, and CE-MRI demonstrate desirable and comparable sensitivity for the differentiation of renal mass. However, the specificity of all three imaging modalities is not satisfactory. SNZ-CEUS may be a suitable alternative modality for patients with renal dysfunction and those allergic to gadolinium or iodine-based agents.

Analysis of endophytic bacterial diversity in seeds of different genotypes of cotton and the suppression of Verticillium wilt pathogen infection by a synthetic microbial community.

BACKGROUND: In agricultural production, fungal diseases significantly impact the yield and quality of cotton (Gossypium spp.) with Verticillium wilt posing a particularly severe threat. RESULTS: This study is focused on investigating the effectiveness of endophytic microbial communities present in the seeds of disease-resistant cotton genotypes in the control of cotton Verticillium wilt. The technique of 16S ribosomal RNA (16S rRNA) amplicon sequencing identified a significant enrichment of the Bacillus genus in the resistant genotype Xinluzao 78, which differed from the endophytic bacterial community structure in the susceptible genotype Xinluzao 63. Specific enriched strains were isolated and screened from the seeds of Xinluzao 78 to further explore the biological functions of seed endophytes. A synthetic microbial community (SynCom) was constructed using the broken-rod model, and seeds of the susceptible genotype Xinluzao 63 in this community that had been soaked with the SynCom were found to significantly control the occurrence of Verticillium wilt and regulate the growth of cotton plants. Antibiotic screening techniques were used to preliminarily identify the colonization of strains in the community. These techniques revealed that the strains can colonize plant tissues and occupy ecological niches in cotton tissues through a priority effect, which prevents infection by pathogens. CONCLUSION: This study highlights the key role of seed endophytes in driving plant disease defense and provides a theoretical basis for the future application of SynComs in agriculture.

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC. SIGNIFICANCE: PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.

Oral bacteriome and mycobiome of patients with idiopathic membranous nephropathy with different tongue coatings treated with a Chinese herbal formula.

ETHNOPHARMACOLOGICAL RELEVANCE: Moshen Fuyuan Formula (MSFY) is one of the representative Chinese medicine compound for Idiopathic membranous nephropathy (IMN), that originate from Fang Ji Huang Qi decoction in the Han dynasty. IMN is usually accompanied by different tongue coatings in traditional Chinese medicine (TCM), and tongue microorganisms are important factors affecting the formation of the tongue coating. Recently, oral microbiomes, including bacteria and fungi, have been identified as pivotal factors that contribute to disease development. However, the regulation of oral microbiomes by MSFY has not been defined. AIM OF THE STUDY: In this work, we explore the characteristics of oral bacteria and fungi in IMN patients with different tongue coatings, and clarify the therapeutic effect of MSFY based on oral microbiome. MATERIALS AND METHODS: We enrolled 24 patients with IMN, including 11 with white tongue (IMN-W) and 13 with yellow tongue (IMN-Y), and recruited an additional 10 healthy individuals. Patients with IMN were treated with the MSFY. The oral bacteriome and fungi before and after treatment were detected using full-length 16S rRNA and internal transcribed spacer gene sequencing. RESULTS: The therapeutic effect of MSFY on patients with yellow tongue coating was more significant than that on patients with white tongue coating. In terms of oral bacteriome, Campylobacter bacteria were enriched in patients with yellow tongue and could be a promising biomarker for yellow coating. Enrichment of Veillonella parvula_A may partially account for the therapeutic effect of MSFY. As for oral fungi, Malassezia globosa was enhanced in patients with IMN-W and reduced in patients with IMN-Y. Notably, it was reduced by MSFY. We also found that mycobiome-bacteriome interactions were highly complex and dynamic in patients with IMN. CONCLUSION: The regulation of the dynamic balance between oral fungi and bacteria by MSFY contributes to the treatment of IMN. This study determined the oral bacteriome and mycobiome of patients with IMN with different tongue coatings before and after MSFY treatment, which aids in promoting personalized treatment in clinical TCM and provides direction for investigating the mechanism of Chinese herbal medicines.

Regional analysis to delineate intrasample heterogeneity with RegionalST.

MOTIVATION: Spatial transcriptomics has greatly contributed to our understanding of spatial and intra-sample heterogeneity, which could be crucial for deciphering the molecular basis of human diseases. Intra-tumor heterogeneity, e.g. may be associated with cancer treatment responses. However, the lack of computational tools for exploiting cross-regional information and the limited spatial resolution of current technologies present major obstacles to elucidating tissue heterogeneity. RESULTS: To address these challenges, we introduce RegionalST, an efficient computational method that enables users to quantify cell type mixture and interactions, identify sub-regions of interest, and perform cross-region cell type-specific differential analysis for the first time. Our simulations and real data applications demonstrate that RegionalST is an efficient tool for visualizing and analyzing diverse spatial transcriptomics data, thereby enabling accurate and flexible exploration of tissue heterogeneity. Overall, RegionalST provides a one-stop destination for researchers seeking to delve deeper into the intricacies of spatial transcriptomics data. AVAILABILITY AND IMPLEMENTATION: The implementation of our method is available as an open-source R/Bioconductor package with a user-friendly manual available at https://bioconductor.org/packages/release/bioc/html/RegionalST.html.

Thermal and Magnetic Dual-Responsive Catheter-Assisted Shape Memory Microrobots for Multistage Vascular Embolization.

Catheters navigating through complex vessels, such as sharp turns or multiple U-turns, remain challenging for vascular embolization. Here, we propose a novel multistage vascular embolization strategy for hard-to-reach vessels that releases untethered swimming shape-memory magnetic microrobots (SMMs) from the prior catheter to the vessel bifurcation. SMMs, made of organo-gel with magnetic particles, ensure biocompatibility, radiopacity, thrombosis, and fast thermal and magnetic responses. An SMM is initially a linear shape with a 0.5-mm diameter at 20 °C inserted in a catheter. It transforms into a predetermined helix within 2 s at 38 °C blood temperature after being pushed out of the catheter into the blood. SMMs enable agile swimming in confined and tortuous vessels and can swim upstream using helical propulsion with rotating magnetic fields. Moreover, we validated this multistage vascular embolization in living rabbits, completing 100-cm travel and renal artery embolization in 2 min. After 4 weeks, the SMMs maintained the embolic position, and the kidney volume decreased by 36%.

Prognostic value of right atrial strains in arrhythmogenic right ventricular cardiomyopathy.

OBJECTIVES: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by progressive fibrofatty infiltration of atrial and ventricular myocardium resulting in adverse cardiac events. Atrial function has been increasingly recognized as prognostically important for cardiovascular disease. As the right atrial (RA) strain is a sensitive parameter to describe RA function, we aimed to analyze the prognostic value of the RA strain in ARVC. METHODS: RA strain parameters were derived from cardiac magnetic resonance (CMR) images of 105 participants with definite ARVC. The endpoint was defined as a combination of sudden cardiac death, survival cardiac arrest, and appropriate implantable cardioverter-defibrillator intervention. Cox regression and Kaplan-Meier survival analyses were performed to evaluate the association between RA strain parameters and endpoint. Concordance index (C index), net reclassification index (NRI), and integrated discrimination improvement (IDI) were calculated to assess the incremental value of RA strain in predicting the endpoint. RESULTS: After a median follow-up of 5 years, 36 (34.3%) reaching the endpoint displayed significantly reduced RA strain parameters. At Kaplan-Meier analysis, impaired RA reservoir (RARS) and booster strains (RABS) were associated with an increased risk of the endpoint. After adjusting for conventional risk factors, RARS (hazard ratio [HR], 0.956; p = 0.005) and RABS (HR, 0.906; p = 0.002) resulted as independent predictors for endpoint at Cox regression analyses. In addition, RARS and RABS improved prognostic value to clinical risk factors and CMR morphological and functional predictors (all p < 0.05). CONCLUSION: RARS and RABS were independent predictors for adverse cardiac events, which could provide incremental prognostic value for conventional predictors in ARVC. CRITICAL RELEVANCE STATEMENT: We evaluated the prognostic value of right atrial strain in ARVC patients and suggested cardiologists consider RA strain as a predictive parameter when evaluating the long-term outcome of ARVC patients in order to formulate better clinical therapy. KEY POINTS: • Patients with ARVC had significantly reduced RA strain and strain rates compared with healthy participants. • Participants with lower RA reservoir and booster stains were associated with a significantly higher risk of adverse cardiac events. • RA booster and reservoir strain provide incremental value to conventional parameters.

Nilotinib in combination with sunitinib renders MCL-1 for degradation and activates autophagy that overcomes sunitinib resistance in renal cell carcinoma.

PURPOSE: Sunitinib is a recommended drug for metastatic renal cell carcinoma (RCC). However, the therapeutic potential of sunitinib is impaired by toxicity and resistance. Therefore, we seek to explore a combinatorial strategy to improve sunitinib efficacy of low-toxicity dose for better clinical application. METHODS: We screen synergistic reagents of sunitinib from a compound library containing 1374 FDA-approved drugs by in vitro cell viability evaluation. The synergistically antiproliferative and proapoptotic effects were demonstrated on in vitro and in vivo models. The molecular mechanism was investigated by phosphoproteomics, co-immunoprecipitation, immunofluorescence and western-blot assays, etc. RESULTS: From the four-step screening, nilotinib stood out as a potential synergistic killer combined with sunitinib. Subsequent functional evaluation demonstrated that nilotinib and sunitinib synergistically inhibit RCC cell proliferation and promote apoptosis in vitro and in vivo. Mechanistically, nilotinib activates E3-ligase HUWE1 and in combination with sunitinib renders MCL-1 for degradation via proteasome pathway, resulting in the release of Beclin-1 from MCL-1/Beclin-1 complex. Subsequently, Beclin-1 induces complete autophagy flux to promote antitumor effect. CONCLUSION: Our findings revealed that a novel mechanism that nilotinib in combination with sunitinib overcomes sunitinib resistance in RCC. Therefore, this novel rational combination regimen provides a promising therapeutic avenue for metastatic RCC and rationale for evaluating this combination clinically.

Sensitivity analysis with iterative outlier detection for systematic reviews and meta-analyses.

Meta-analysis is a widely used tool for synthesizing results from multiple studies. The collected studies are deemed heterogeneous when they do not share a common underlying effect size; thus, the factors attributable to the heterogeneity need to be carefully considered. A critical problem in meta-analyses and systematic reviews is that outlying studies are frequently included, which can lead to invalid conclusions and affect the robustness of decision-making. Outliers may be caused by several factors such as study selection criteria, low study quality, small-study effects, and so on. Although outlier detection is well-studied in the statistical community, limited attention has been paid to meta-analysis. The conventional outlier detection method in meta-analysis is based on a leave-one-study-out procedure. However, when calculating a potentially outlying study's deviation, other outliers could substantially impact its result. This article proposes an iterative method to detect potential outliers, which reduces such an impact that could confound the detection. Furthermore, we adopt bagging to provide valid inference for sensitivity analyses of excluding outliers. Based on simulation studies, the proposed iterative method yields smaller bias and heterogeneity after performing a sensitivity analysis to remove the identified outliers. It also provides higher accuracy on outlier detection. Two case studies are used to illustrate the proposed method's real-world performance.

Associations between genetically predicted plasma protein levels and Alzheimer's disease risk: a study using genetic prediction models.

BACKGROUND: Specific peripheral proteins have been implicated to play an important role in the development of Alzheimer's disease (AD). However, the roles of additional novel protein biomarkers in AD etiology remains elusive. The availability of large-scale AD GWAS and plasma proteomic data provide the resources needed for the identification of causally relevant circulating proteins that may serve as risk factors for AD and potential therapeutic targets. METHODS: We established and validated genetic prediction models for protein levels in plasma as instruments to investigate the associations between genetically predicted protein levels and AD risk. We studied 71,880 (proxy) cases and 383,378 (proxy) controls of European descent. RESULTS: We identified 69 proteins with genetically predicted concentrations showing associations with AD risk. The drugs almitrine and ciclopirox targeting ATP1A1 were suggested to have a potential for being repositioned for AD treatment. CONCLUSIONS: Our study provides additional insights into the underlying mechanisms of AD and potential therapeutic strategies.

The tRNA thiolation-mediated translational control is essential for plant immunity.

Plants have evolved sophisticated mechanisms to regulate gene expression to activate immune responses against pathogen infections. However, how the translation system contributes to plant immunity is largely unknown. The evolutionarily conserved thiolation modification of transfer RNA (tRNA) ensures efficient decoding during translation. Here, we show that tRNA thiolation is required for plant immunity in Arabidopsis. We identify a cgb mutant that is hyper-susceptible to the pathogen Pseudomonas syringae. CGB encodes ROL5, a homolog of yeast NCS6 required for tRNA thiolation. ROL5 physically interacts with CTU2, a homolog of yeast NCS2. Mutations in either ROL5 or CTU2 result in loss of tRNA thiolation. Further analyses reveal that both transcriptome and proteome reprogramming during immune responses are compromised in cgb. Notably, the translation of salicylic acid receptor NPR1 is reduced in cgb, resulting in compromised salicylic acid signaling. Our study not only reveals a regulatory mechanism for plant immunity but also uncovers an additional biological function of tRNA thiolation.

3D Fractal Dimension Analysis: Prognostic Value of Right Ventricular Trabecular Complexity in Participants with Arrhythmogenic Cardiomyopathy.

BACKGROUND: Arrhythmogenic cardiomyopathy (ACM) is characterized by progressive myocardial fibro-fatty infiltration accompanied by trabecular disarray. Traditionally, two-dimensional (2D) instead of 3D fractal dimension (FD) analysis has been used to evaluate trabecular disarray. However, the prognostic value of trabecular disorder assessed by 3D FD measurement remains unclear. PURPOSE: To investigate the prognostic value of right ventricular trabecular complexity in ACM patients using 3D FD analysis based on cardiac MR cine images. STUDY TYPE: Retrospective. POPULATION: 85 ACM patients (mean age: 45 ± 17 years, 52 male). FIELD STRENGTH/SEQUENCE: 3.0T/cine imaging, T2-short tau inversion recovery (T2-STIR), and late gadolinium enhancement (LGE). ASSESSMENT: Using cine images, RV (right ventricular) volumetric and functional parameters were obtained. RV trabecular complexity was measured with 3D fractal analysis by box-counting method to calculate 3D-FD. Cox and logistic regression models were established to evaluate the prognostic value of 3D-FD for major adverse cardiac events (MACE). STATISTICAL TESTS: Cox regression and logistic regression to explore the prognostic value of 3D-FD. C-index, time-dependent receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) to evaluate the incremental value of 3D-FD. Intraclass correlation coefficient for interobserver variability. P < 0.05 indicated statistical significance. RESULTS: 26 MACE were recorded during the 60 month follow-up (interquartile range: 48-67 months). RV 3D-FD significantly differed between ACM patients with MACE (2.67, interquartile range: 2.51 ~ 2.81) and without (2.52, interquartile range: 2.40 ~ 2.67) and was a significant independent risk factor for MACE (hazard ratio, 1.02; 95% confidence interval: 1.01, 1.04). In addition, prognostic model fitness was significantly improved after adding 3D-FD to RV global longitudinal strain, LV involvement, and 5-year risk score separately. DATA CONCLUSION: The myocardial trabecular complexity assessed through 3D FD analysis was found associated with MACE and provided incremental prognostic value beyond conventional ACM risk factors. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.