Incremental prognostic value of left atrial strain in apical hypertrophic cardiomyopathy: a cardiovascular magnetic resonance study.

OBJECTIVES: This study aimed to evaluate the prognostic value of left atrial (LA) strain in patients with apical hypertrophic cardiomyopathy (ApHCM), as assessed by cardiac magnetic resonance (CMR) imaging. METHODS: Four hundred and five consecutive patients with ApHCM who underwent CMR examination were retrospectively included. The study endpoint included all-cause death, heart transplant, aborted sudden cardiac death, hospitalization for heart failure, stroke, and new-onset atrial fibrillation (AF). RESULTS: After a median follow-up of 97 months, 75 patients (18.5%) reached the endpoint. Patients were divided into two groups based on the median LA reservoir strain of 29.4%. The group with lower LA reservoir strain had thicker maximum wall thickness, greater late gadolinium enhancement extent, and smaller end-diastolic volume index, stroke volume index, and cardiac index (all p < 0.02). For LA parameters, this subgroup showed greater diameter and volume index and worse ejection fraction, reservoir, conduit, and booster strain (all p < 0.001). In the multivariable model, age (HR 1.88, 95% CI: 1.06-3.31, p = 0.030), baseline AF (HR 2.95, 95% CI: 1.64-5.28, p < 0.001), LA volume index (LAVi) (HR 2.07, 95% CI: 1.21-3.55, p = 0.008) and LA reservoir strain (HR 2.82, 95% CI: 1.51-5.26, p = 0.001) were all associated with the outcome. Adding LAVi and LA reservoir strain in turn to the multivariable model (age and baseline AF) resulted in significant improvements in model performance (p < 0.001). CONCLUSION: In ApHCM patients, LA reservoir strain is independently associated with cardiovascular risk events and has an incremental prognostic value. CLINICAL RELEVANCE STATEMENT: Left atrial reservoir strain measured by cardiac magnetic resonance is highly correlated with the prognosis of apical hypertrophic cardiomyopathy and has potential incremental value in the prognosis of major adverse cardiac events. KEY POINTS: Left atrial (LA) strain parameters may be useful for risk stratification and treatment of apical hypertrophic cardiomyopathy (ApHCM). Apical hypertrophic cardiomyopathy (ApHCM) is independently associated with LA morphology and function. Cardiac MR examination, especially its feature-tracking technology, provides the possibility to prognosticate ApHCM at an early stage.

Machine Learning in Hypertrophic Cardiomyopathy: Nonlinear Model From Clinical and CMR Features Predicting Cardiovascular Events.

BACKGROUND: The cumulative burden of hypertrophic cardiomyopathy (HCM) is significant, with a noteworthy percentage (10%-15%) of patients with HCM per year experiencing major adverse cardiovascular events (MACEs). A current risk stratification scheme for HCM had only limited accuracy in predicting sudden cardiac death (SCD) and failed to account for a broader spectrum of adverse cardiovascular events and cardiac magnetic resonance (CMR) parameters. OBJECTIVES: This study sought to develop and evaluate a machine learning (ML) framework that integrates CMR imaging and clinical characteristics to predict MACEs in patients with HCM. METHODS: A total of 758 patients with HCM (67% male; age 49 ± 14 years) who were admitted between 2010 and 2017 from 4 medical centers were included. The ML model was built on the internal discovery cohort (533 patients with HCM, admitted to Fuwai Hospital, Beijing, China) by using the light gradient-boosting machine and internally evaluated using cross-validation. The external test cohort consisted of 225 patients with HCM from 3 medical centers. A total of 14 CMR imaging features (strain and late gadolinium enhancement [LGE]) and 23 clinical variables were evaluated and used to inform the ML model. MACEs included a composite of arrhythmic events, SCD, heart failure, and atrial fibrillation-related stroke. RESULTS: MACEs occurred in 191 (25%) patients over a median follow-up period of 109.0 months (Q1-Q3: 73.0-118.8 months). Our ML model achieved areas under the curve (AUCs) of 0.830 and 0.812 (internally and externally, respectively). The model outperformed the classic HCM Risk-SCD model, with significant improvement (P < 0.001) of 22.7% in the AUC. Using the cubic spline analysis, the study showed that the extent of LGE and the impairment of global radial strain (GRS) and global circumferential strain (GCS) were nonlinearly correlated with MACEs: an elevated risk of adverse cardiovascular events was observed when these parameters reached the high enough second tertiles (11.6% for LGE, 25.8% for GRS, -17.3% for GCS). CONCLUSIONS: ML-empowered risk stratification using CMR and clinical features enabled accurate MACE prediction beyond the classic HCM Risk-SCD model. In addition, the nonlinear correlation between CMR features (LGE and left ventricular pressure gradient) and MACEs uncovered in this study provides valuable insights for the clinical assessment and management of HCM.

Host-virus coevolution drives soil microbial function succession along a millennium land reclamation chronosequence.

INTRODUCTION: Gene exchange between viruses and hosts plays an important role in driving virus-host coevolution, enabling adaptation of both viruses and hosts to environmental changes. However, the mechanisms and functional significance of virus-host gene exchanges over long-term scales remain largely unexplored. OBJECTIVE: The present study aimed to gain insights into the role of viruses in virus-host interactions and coevolution by monitoring virome dynamics along a millennium-long land reclamation chronosequence. METHODS: We collected 24 soil samples from 8 stages of a millennium-long land reclamation chronosequence, including non-reclamation, and reclamation periods of 10, 50, 100, 300, 500, 700, and 1000 years. We characterized their metagenomes, and identified DNA viruses within these metagenomes. RESULTS: Our findings reveal a significant shift in viral community composition after 50 years of land reclamation, but soil viral diversity reached a stable phase approximately 300 years after the initial reclamation. Analysis of the virus-host network showed a scale-free degree distribution and a reduction in complexity over time, with generalist viruses emerging as key facilitators of horizontal gene transfer. CONCLUSION: These findings highlight the integral role of viruses, especially generalist types, in mediating gene exchanges between viruses and hosts, thereby influencing the coevolutionary dynamics in soil ecosystems over significant timescales. This study offers novel insights into long-term virus-host interactions, showing how the virome responds to environmental changes, driving shifts in various microbial functions in reclaimed land.

Advancing presurgical non-invasive molecular subgroup prediction in medulloblastoma using artificial intelligence and MRI signatures.

Global investigation of medulloblastoma has been hindered by the widespread inaccessibility of molecular subgroup testing and paucity of data. To bridge this gap, we established an international molecularly characterized database encompassing 934 medulloblastoma patients from thirteen centers across China and the United States. We demonstrate how image-based machine learning strategies have the potential to create an alternative pathway for non-invasive, presurgical, and low-cost molecular subgroup prediction in the clinical management of medulloblastoma. Our robust validation strategies-including cross-validation, external validation, and consecutive validation-demonstrate the model's efficacy as a generalizable molecular diagnosis classifier. The detailed analysis of MRI characteristics replenishes the understanding of medulloblastoma through a nuanced radiographic lens. Additionally, comparisons between East Asia and North America subsets highlight critical management implications. We made this comprehensive dataset, which includes MRI signatures, clinicopathological features, treatment variables, and survival data, publicly available to advance global medulloblastoma research.

Right Ventricular Strain Derived from Cardiac MRI Feature Tracking for the Diagnosis and Prognosis of Arrhythmogenic Right Ventricular Cardiomyopathy.

Purpose To demonstrate the myocardial strain characteristics of patients with arrhythmogenic right ventricular cardiomyopathy (ARVC), based on revised Task Force Criteria (rTFC), and to explore the prognostic value of strain analysis in ARVC. Materials and Methods This retrospective study included 247 patients (median age, 38 years [IQR, 28-48 years]; 167 male, 80 female) diagnosed with ARVC, based on rTFC, between 2014 and 2018. Patients were divided into "possible" (n =25), "borderline" (n = 40), and "definite" (n = 182) ARVC groups following rTFC. Biventricular global strain parameters were calculated using cardiac MRI feature tracking (FT). The primary outcome was defined as a composite of cardiovascular events, including cardiovascular death, heart transplantation, and appropriate implantable cardioverter defibrillator discharge. Univariable and multivariable cumulative logistic regression and Cox proportional hazards regression analysis were used to evaluate the diagnostic and prognostic value of right ventricle (RV) strain parameters. Results Patients with definite ARVC had significantly reduced RV global strain in all three directions compared with possible or borderline groups (all P < .001). RV global longitudinal strain (GLS) was an independent predictor for disease (odds ratio, 1.09 [95% CI: 1.02, 1.16]; P = .009). During a median follow-up of 3.4 years (IQR, 2.0-4.9 years), 55 patients developed primary end point events. Multivariable analysis showed that RV GLS was independently associated with the occurrence of cardiovascular events (hazard ratio, 1.15 [95% CI: 1.07, 1.24]; P < .001). Kaplan-Meier analysis showed that patients with RV GLS worse than median had a higher risk of combined cardiovascular events (log-rank P < .001). Conclusion RV GLS derived from cardiac MRI FT demonstrated good diagnostic and prognostic value in ARVC. Keywords: MR Imaging, Image Postprocessing, Cardiac, Right Ventricle, Cardiomyopathies, Arrhythmogenic Right Ventricular Cardiomyopathy, Revised Task Force Criteria, Cardiovascular MR, Feature Tracking, Cardiovascular Events Supplemental material is available for this article. © RSNA, 2024.

Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging.

Cardiac magnetic resonance imaging (CMR) is the gold standard for cardiac function assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However, its widespread application has been limited by the heavy resource burden of CMR interpretation. Here, to address this challenge, we developed and validated computerized CMR interpretation for screening and diagnosis of 11 types of CVD in 9,719 patients. We propose a two-stage paradigm consisting of noninvasive cine-based CVD screening followed by cine and late gadolinium enhancement-based diagnosis. The screening and diagnostic models achieved high performance (area under the curve of 0.988 ± 0.3% and 0.991 ± 0.0%, respectively) in both internal and external datasets. Furthermore, the diagnostic model outperformed cardiologists in diagnosing pulmonary arterial hypertension, demonstrating the ability of artificial intelligence-enabled CMR to detect previously unidentified CMR features. This proof-of-concept study holds the potential to substantially advance the efficiency and scalability of CMR interpretation, thereby improving CVD screening and diagnosis.

Heterosis of endophytic microbiomes in hybrid rice varieties improves seed germination.

Seed endophytic microbiomes are shaped by host and environmental factors and play a crucial role in their host growth and health. Studies have demonstrated that host genotype, including hybridization, affects seed microbiomes. Heterosis features are also observed in root-associated microbiomes. It remains unclear, however, whether heterosis exists in seed endophytic microbiomes and whether hybrid microbiota provide noticeable advantages to host plant growth, especially to seed germination. Here, we investigated the structure of seed endophytic bacterial and fungal communities from three hybrid rice varieties and their respective parents using amplicon sequencing targeting 16S rRNA and ITS2 genes. Heterosis was found in diversity and composition of seed endophytic microbiomes in hybrids, which hosted more diverse communities and significantly higher abundances of plant growth-promoting taxa, such as Pseudomonas and Rhizobium genera compared with their parental lines. Co-occurrence network analysis revealed that there are potentially tighter microbial interactions in the hybrid seeds compared with their parent seeds. Finally, inoculation of seed-cultivable endophytes, isolated from hybrids, resulted in a greater promotion of seed germination compared with those isolated from parent lines. These findings suggest that heterosis exists not only in plant traits but also in seed endophytic microbiota, the latter in turn promotes seed germination, which offers valuable guidance for microbiome-assisted rice breeding.IMPORTANCEGenetic and physiological changes associated with plant hybridization have been studied for many crop species. Still, little is known about the impact of hybridization on the seed microbiota. In this study, we indicate that hybridization has a significant impact on the endophytic bacterial and fungal communities in rice seeds. The seed endophytic microbiomes of hybrids displayed distinct characteristics from those of their parental lines and exhibited potential heterosis features. Furthermore, the inoculation of seed-cultivable endophytes isolated from hybrids exhibited a greater promotion effect on seed germination compared with those isolated from the parents. Our findings make a valuable contribution to the emerging field of microbiome-assisted plant breeding, highlighting the potential for a targeted approach that aims to achieve not only desired plant traits but also plant-beneficial microbial communities on the seeds.

Biogeographic patterns and drivers of soil viromes.

Viruses are crucial in shaping soil microbial functions and ecosystems. However, studies on soil viromes have been limited in both spatial scale and biome coverage. Here we present a comprehensive synthesis of soil virome biogeographic patterns using the Global Soil Virome dataset (GSV) wherein we analysed 1,824 soil metagenomes worldwide, uncovering 80,750 partial genomes of DNA viruses, 96.7% of which are taxonomically unassigned. The biogeography of soil viral diversity and community structure varies across different biomes. Interestingly, the diversity of viruses does not align with microbial diversity and contrasts with it by showing low diversity in forest and shrubland soils. Soil texture and moisture conditions are further corroborated as key factors affecting diversity by our predicted soil viral diversity atlas, revealing higher diversity in humid and subhumid regions. In addition, the binomial degree distribution pattern suggests a random co-occurrence pattern of soil viruses. These findings are essential for elucidating soil viral ecology and for the comprehensive incorporation of viruses into soil ecosystem models.

Exploring metal(loid)s dynamics and bacterial community shifts in contaminated paddy soil: Impact of MgO-laden biochar under different water conditions.

In this study, a soil incubation experiment was conducted to explore the influence MgO-treated corn straw biochar (MCB) on the bioavailability and chemical forms of cadmium (Cd), lead (Pb), and arsenic (As), alongside the impact on the bacterial community within paddy soil subjected to both flooded and non-flooded conditions. Raw corn straw biochar (CB) served as the unmodified biochar control, aiding in the understanding of the biochar's role within the composite. The results showed that even at a minimal concentration of 0.5 %, MCB exhibited higher effectiveness in reducing the bioavailability of Pb and Cd compared to 1 % CB. In non-flooded conditions, 0.5 % MCB reduced the bioavailable Pb and Cd by 99.7 % and 87.4 %, respectively, while NaH2PO4-extracted As displayed a 14.5 % increase. With increasing MCB concentrations (from 0.5 % to 1.5 %), soil pH, DOC, EC, available phosphorus, and bioavailable As increased, while bioavailable Pb and Cd exhibited declining tendencies. Flooding did not notably alter MCB's role in reducing Pb and Cd bioavailability, yet it systematically amplified As release. Heavy metal fractions extracted by acetic acid increased in the MCB groups under flooding conditions, especially for As. The inclusion of 0.5 % MCB did not noticeably affect bacterial diversity, whereas higher doses led to reduced diversity and substantial changes in community composition. Specifically, the groups with MCB showed an increase in the Bacteroidetes and Proteobacteria phyla, accompanied by a decrease in Acidobacteria. These alterations were primarily attributed to the increased pH and EC resulting from MgO hydrolysis. Consequently, for Pb/Cd stabilization and soil bacterial diversity, a low dosage of MgO-treated biochar is recommended. However, caution is advised when employing MgO-treated biochar in soils with elevated arsenic levels, particularly under flooded conditions.

Association between left atrial myopathy and sarcomere mutation in patients with hypertrophic cardiomyopathy: insights into left atrial strain by MRI feature tracking.

OBJECTIVES: Left atrial (LA) myopathy, characterized by LA enlargement and mechanical dysfunction, is associated with worse prognosis in hypertrophic cardiomyopathy (HCM) while the impact of sarcomere mutation on LA myopathy remains unclear. We aimed to assess the association between LA myopathy and sarcomere mutation and to explore the incremental utility of LA strain in mutation prediction. METHODS: A total of 105 consecutive HCM patients (mean age 47.8 ± 11.9 years, 71% male) who underwent HCM-related gene screening and cardiac MRI were retrospectively enrolled. LA volume, ejection fraction and strain indices in reservoir, conduit, and booster-pump phases were investigated respectively. RESULTS: Fifty mutation-positive patients showed higher LA maximal volume index (59.4 ± 28.2 vs 43.8 ± 18.1 mL/m2, p = 0.001), lower reservoir (21.3 ± 7.9 vs 26.2 ± 6.6%, p < 0.001), and booster-pump strain (12.1 ± 5.4 vs 17.1 ± 5.0%, p < 0.001) but similar conduit strain (9.2 ± 4.5 vs 9.1 ± 4.5%, p = 0.909) compared with mutation-negative patients. In multivariate logistic regression, LA booster-pump strain was associated with sarcomere mutation (odds ratio = 0.86, 95% confidence interval: 0.77-0.96, p = 0.010) independent of maximal wall thickness, late gadolinium enhancement, and LA volume. Furthermore, LA booster-pump strain showed incremental value for mutation prediction added to Mayo II score (AUC 0.798 vs 0.709, p = 0.024). CONCLUSIONS: In HCM, mutation-positive patients suffered worse LA enlargement and worse reservoir and booster-pump functions. LA booster-pump strain was a strong factor for sarcomere mutation prediction added to Mayo II score. CLINICAL RELEVANCE STATEMENT: The independent association between sarcomere mutation and left atrial mechanical dysfunction provide new insights into the pathogenesis of atrial myopathy and is helpful to understand the adverse prognosis regarding atrial fibrillation and stroke in mutation-positive patients. KEY POINTS: • In patients with hypertrophic cardiomyopathy, left atrial (LA) reservoir and booster-pump function, but not conduit function, were significantly impaired in mutation-positive patients compared with mutation-negative patients. • LA booster-pump strain measured by MRI-derived feature tracking is feasible to predict sarcomere mutation with high incremental value added to Mayo II score.

Incremental Diagnostic Value of Right Ventricular Strain Analysis in Arrhythmogenic Right Ventricular Cardiomyopathy.

BACKGROUND: Strain analysis is a sensitive method for the assessment of ventricular structural or functional alterations. The authors aimed to determine whether right ventricular (RV) strain parameters can discriminate patients with revised Task Force Criteria-diagnosed arrhythmogenic RV cardiomyopathy (ARVC) incremental to the existing cardiovascular magnetic resonance (CMR) criteria, thus improving the diagnostic yield of CMR in ARVC. METHODS AND RESULTS: A total of 74 patients with revised Task Force Criteria-diagnosed ARVC (37 borderline and 37 definite) and 37 controls were retrospectively enrolled for analysis. Using CMR feature tracking, RV global longitudinal (GLS), circumferential, and radial strain of all participants were evaluated. Compared with controls, the study patients demonstrated significantly impaired global biventricular strain in all 3 directions (all P<0.001). Receiver operating characteristic curve analysis indicated that RV GLS was the strongest discriminator among all RV strain parameters for the identification of patients with ARVC (area under the curve, 0.92). Using the Youden index, the authors determined RV GLS ≥-19.95% as the diagnostic criterion of ARVC. In patients diagnosed with borderline ARVC according to revised Task Force Criteria but with no or only minor CMR criteria, there were >50% presenting with impaired RV GLS. When both conventional criteria and RV GLS were considered together, this new diagnostic method demonstrated an overall diagnostic accuracy of 90%. The likelihood ratio test showed a significant incremental diagnostic value of RV GLS (P=0.02) over the existing CMR major criteria. CONCLUSIONS: The current study showed an improved diagnostic accuracy when both RV GLS and the existing CMR criteria were considered together, especially for patients with borderline diagnosis, suggesting the incremental value of strain analysis to the initial assessment of ARVC.

Ecology and risks of the global plastisphere as a newly expanding microbial habitat.

Plastic offers a new niche for microorganisms, the plastisphere. The ever-increasing emission of plastic waste makes it critical to understand the microbial ecology of the plastisphere and associated effects. Here, we present a global fingerprint of the plastisphere, analyzing samples collected from freshwater, seawater, and terrestrial ecosystems. The plastisphere assembles a distinct microbial community that has a clearly higher heterogeneity and a more deterministically dominated assembly compared to natural habitats. New coexistence patterns-loose and fragile networks with mostly specialist linkages among microorganisms that are rarely found in natural habitats-are seen in the plastisphere. Plastisphere microbiomes generally have a great potential to metabolize organic compounds, which could accelerate carbon turnover. Microorganisms involved in the nitrogen cycle are also altered in the plastisphere, especially in freshwater plastispheres, where a high abundance of denitrifiers may increase the release of nitrite (aquatic toxicant) and nitrous oxide (greenhouse gas). Enrichment of animal, plant, and human pathogens means that the plastisphere could become an increasingly mobile reservoir of harmful microorganisms. Our findings highlight that if the trajectory of plastic emissions is not reversed, the expanding plastisphere could pose critical planetary health challenges.

Biodegradation in oil sands process-affected water: A comprehensive laboratory analysis of the in situ biodegradation of dissolved organic acids.

Oil sands process-affected water (OSPW) is a by-product of the extraction of bitumen, and volumes of OSPW have accumulated across the Alberta oil sands region due to the governments zero-discharge policy. Some dissolved organics in OSPW, including toxic naphthenic acids (NAs), can be biodegraded in oxic conditions, thereby reducing the toxicity of OSPW. While there has been much focus on degradation of NAs, the biodegradation of other dissolved organic chemicals by endogenous organisms remains understudied. Here, using the HPLC-ultrahigh resolution Orbitrap mass spectrometry, we examined the microbial biodegradation of dissolved organic acids in OSPW. Non-targeted analysis enabled the estimation of biodegradation rates for unique heteroatomic chemical classes detected in negative ion mode. The microcosm experiments were conducted with and without nutrient supplementation, and the changes in the microbial community over time were investigated. Without added nutrients, internal standard-adjusted intensities of all organics, including NAs, were largely unchanged. The addition of nutrients increased the biodegradation rate of O2- and SO2- chemical classes. While anoxic biodegradation can occur in tailings ponds and end pit lakes, microbial community analyses confirmed that the presence of oxygen stimulated biodegradation of the OSPW samples studied. We detected several aerobic hydrocarbon-degrading microbes (e.g., Pseudomonas and Brevundimonas), and microbes capable of degrading sulfur-containing hydrocarbons (e.g., Microbacterium). Microbial community diversity decreased over time with nutrient addition. Overall, the results from this study indicate that toxic dissolved organics beyond NAs can be biodegraded by endogenous organisms in OSPW, but reaffirms that biological treatment strategies require careful consideration of how nutrients and dissolved oxygen may impact efficacy.

Incremental prognostic value of left atrial and biventricular feature tracking in dilated cardiomyopathy: a long-term study.

BACKGROUND: Despite the use of cardiovascular magnetic resonance (CMR) feature tracking (FT) imaging to detect myocardial deformation, the optimal strain index in dilated cardiomyopathy (DCM) is unclear. This study aimed to determine whether atrial and biventricular strains can provide the greatest or joint incremental prognostic value in patients with DCM over a long follow-up period. METHODS: Four hundred-twelve DCM patients were included retrospectively. Comprehensive clinical evaluation and imaging investigations were obtained, including measurements of CMR-FT derived left atrial (LA) reservoir, conduit, booster strain (εs, εe, εa); left ventricular (LV) and right ventricular (RV) global longitudinal, radial, circumferential strain (GLS, GRS, GCS). All patients were followed up for major adverse cardiac events (MACE) including all-cause mortality, heart transplantation, and implantable cardioverter defibrillator discharge. The predictors of MACE were examined with univariable and multivariable Cox regression analysis. Subsequently, nested Cox regression models were built to evaluate the incremental prognostic value of strain parameters. The incremental predictive power of strain parameters was assessed by Omnibus tests, and the model performance and discrimination were evaluated by Harrell C-index and integrated discrimination improvement (IDI) analysis. Patient survival was illustrated by Kaplan-Meier curves and differences were evaluated by log-rank test. RESULTS: During a median follow-up of 5.0 years, MACE were identified in 149 (36%) patients. LAεe, LVGLS, and RVGLS were the most predictive strain parameters for MACE (AUC: 0.854, 0.733, 0.733, respectively). Cox regression models showed that the predictive value of LAεe was independent from and incremental to LVGLS, RVGLS, and baseline variables (HR 0.74, 95% CI 0.68-0.81, P < 0.001). In reclassification analysis, the addition of LAεe provided the best discrimination of the model (χ2 223.34, P < 0.001; C-index 0.833; IDI 0.090, P < 0.001) compared with LVGLS and RVGLS models. Moreover, LAεe with a cutoff of 5.3% further discriminated the survival probability in subgroups of patients with positive LGE or reduced LVEF (all log-rank P < 0.001). CONCLUSION: LAεe provided the best prognostic value over biventricular strains and added incremental value to conventional clinical predictors for patients with DCM.

Cardiac MRI-derived Myocardial Fibrosis and Ventricular Dyssynchrony Predict Response to Cardiac Resynchronization Therapy in Patients with Nonischemic Dilated Cardiomyopathy.

Purpose: To determine the association of myocardial fibrosis and left ventricular (LV) dyssynchrony measured using cardiac MRI with late gadolinium enhancement (LGE) and feature tracking (FT), respectively, with response to cardiac resynchronization therapy (CRT) for nonischemic dilated cardiomyopathy (DCM). Materials and Methods: This retrospective study included 98 patients (mean age, 59 years ± 10 [SD]; 54 men) who had nonischemic DCM, as assessed with LGE cardiac MRI before CRT. Cardiac MRI FT-derived dyssynchrony was defined as the SD of the time-to-peak strain (TTP-SD) of the LV segments in three directions (longitudinal, radial, and circumferential). CRT response was defined as a 15% increase in LV ejection fraction (LVEF) at echocardiography at 6-month follow-up, and then, long-term cardiovascular events were assessed. The likelihood ratio test was used to evaluate the incremental prognostic value of LGE and dyssynchrony parameters. Results: Seventy-one (72%) patients showed a favorable LVEF response following CRT. LGE presence (odds ratio: 0.14 [95% CI: 0.04, 0.47], P = .002; and hazard ratio: 3.52 [95% CI: 1.37, 9.07], P = .01) and lower circumferential TTP-SD (odds ratio: 1.04 [95% CI: 1.02, 1.07], P = .002; and hazard ratio: 0.98 [95% CI: 0.96, 1.00], P = .03) were independently associated with LVEF nonresponse and long-term outcomes. Combined LGE and circumferential TTP-SD provided the highest discrimination for LVEF nonresponse (area under the receiver operating characteristic curve [AUC]: 0.89 [95% CI: 0.81, 0.94], sensitivity: 84.5% [95% CI: 74.0%, 92.0%], specificity: 85.2% [95% CI: 66.3%, 95.8%]) and long-term outcomes (AUC: 0.84 [95% CI: 0.75, 0.91], sensitivity: 76.9% [95% CI: 56.4%, 91.0%], specificity: 87.0% [95% CI: 76.7%, 93.9%]). Conclusion: Myocardial fibrosis and lower circumferential dyssynchrony assessed with pretherapy cardiac MRI were independently associated with unfavorable LVEF response and long-term events following CRT in patients with nonischemic DCM and may provide incremental value in predicting prognosis.Keywords: MR Imaging, Cardiac, Outcomes Analysis Supplemental material is available for this article. © RSNA, 2023.

A genomic catalogue of soil microbiomes boosts mining of biodiversity and genetic resources.

Soil harbors a vast expanse of unidentified microbes, termed as microbial dark matter, presenting an untapped reservo)ir of microbial biodiversity and genetic resources, but has yet to be fully explored. In this study, we conduct a large-scale excavation of soil microbial dark matter by reconstructing 40,039 metagenome-assembled genome bins (the SMAG catalogue) from 3304 soil metagenomes. We identify 16,530 of 21,077 species-level genome bins (SGBs) as unknown SGBs (uSGBs), which expand archaeal and bacterial diversity across the tree of life. We also illustrate the pivotal role of uSGBs in augmenting soil microbiome's functional landscape and intra-species genome diversity, providing large proportions of the 43,169 biosynthetic gene clusters and 8545 CRISPR-Cas genes. Additionally, we determine that uSGBs contributed 84.6% of previously unexplored viral-host associations from the SMAG catalogue. The SMAG catalogue provides an useful genomic resource for further studies investigating soil microbial biodiversity and genetic resources.

Assessment of late gadolinium enhancement in hypertrophic cardiomyopathy improves risk stratification based on current guidelines.

BACKGROUND AND AIMS: Identifying patients with hypertrophic cardiomyopathy (HCM) who are candidates for implantable cardioverter defibrillator (ICD) implantation in primary prevention for sudden cardiac death (SCD) is crucial. The aim of this study was to externally validate the 2022 European Society of Cardiology (ESC) model and other guideline-based ICD class of recommendation (ICD-COR) models and explore the utility of late gadolinium enhancement (LGE) in further risk stratification. METHODS: Seven hundred and seventy-four consecutive patients who underwent cardiac magnetic resonance imaging were retrospectively enrolled. RESULTS: Forty-six (5.9%) patients reached the SCD-related endpoint during 7.4 ± 2.5 years of follow-up. Patients suffering from SCD had higher ESC Risk-SCD score (4.3 ± 2.4% vs. 2.8 ± 2.1%, P < .001) and LGE extent (13.7 ± 9.4% vs. 4.9 ± 6.6%, P < .001). Compared with the 2014 ESC model, the 2022 ESC model showed increased area under the curve (.76 vs. .63), sensitivity (76.1% vs. 43.5%), positive predictive value (16.8% vs. 13.6%), and negative predictive value (98.1% vs. 95.9%). The C-statistics for SCD prediction of 2011 American College of Cardiology (ACC)/American Heart Association (AHA), 2014 ESC, 2020 AHA/ACC, and 2022 ESC models were .68, .64, .76 and .78, respectively. Furthermore, in patients without extensive LGE, LGE ≥5% was responsible for seven-fold SCD risk after multivariable adjustment. Whether in ICD-COR II or ICD-COR III, patients with LGE ≥5% and <15% showed significantly worse prognosis than those with LGE <5% (all P < .001). CONCLUSIONS: The 2022 ESC model performed better than the 2014 ESC model with especially improved sensitivity. LGE enabled further risk stratification based on current guidelines.

Equilibrated Zeroth-Order Unrolled Deep Network for Parallel MR Imaging.

In recent times, model-driven deep learning has evolved an iterative algorithm into a cascade network by replacing the regularizer's first-order information, such as the (sub)gradient or proximal operator, with a network module. This approach offers greater explainability and predictability compared to typical data-driven networks. However, in theory, there is no assurance that a functional regularizer exists whose first-order information matches the substituted network module. This implies that the unrolled network output may not align with the regularization models. Furthermore, there are few established theories that guarantee global convergence and robustness (regularity) of unrolled networks under practical assumptions. To address this gap, we propose a safeguarded methodology for network unrolling. Specifically, for parallel MR imaging, we unroll a zeroth-order algorithm, where the network module serves as a regularizer itself, allowing the network output to be covered by a regularization model. Additionally, inspired by deep equilibrium models, we conduct the unrolled network before backpropagation to converge to a fixed point and then demonstrate that it can tightly approximate the actual MR image. We also prove that the proposed network is robust against noisy interferences if the measurement data contain noise. Finally, numerical experiments indicate that the proposed network consistently outperforms state-of-the-art MRI reconstruction methods, including traditional regularization and unrolled deep learning techniques.