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.

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.

Cardiac remodeling after tricuspid valve repair in Ebstein's anomaly: a magnetic resonance study.

OBJECTIVES: We aimed to evaluate immediate and midterm cardiac remodeling after surgery by cardiac magnetic resonance (CMR) in Ebstein's anomaly (EA), and also to investigate preoperative predictors of right ventricular (RV) normalization. METHODS: We retrospectively analyzed CMR parameters of the whole heart in adult patients with EA before surgery, at discharge and follow-up. RESULTS: A total of 26 patients were included and performed CMR at 7 days (interquartile range, 3-13 days) before surgery. Immediate postoperative CMR was finished at discharge (median: 8 [7-9] days; n = 18) and follow-up CMR at 187 days (interquartile range, 167-356 days; n = 17). RV and right atrial (RA) volumes promptly decreased immediately after surgery and at follow-up (all p < 0.05). RV ejection fraction decreased significantly at discharge (p < 0.05) but recovered at follow-up (p = 0.18). However, RV global longitudinal strain and RA reservoir strain were significantly impaired immediately and midterm after surgery (all p < 0.05). Indexed left ventricular (LV) end-diastolic volume, stroke volume, as well as global longitudinal strain increased from preoperative to follow-up (all p < 0.05). Patients who achieved normalization of RV volumes after surgery had smaller severity index and RV and RA volumes and higher LV ejection fraction and RA reservoir strain at baseline than patients without RV normalization (all p < 0.05). CONCLUSIONS: Reverse biventricular remodeling took place in EA after tricuspid valve surgery. Tricuspid valve reconstruction should be performed before deterioration of RV volume overload and LV function to achieve reverse RV remodeling. Key Points • After removing the volume load of tricuspid regurgitation in Ebstein's anomaly, reverse remodeling was detected by CMR in both left and right heart at midterm follow-up. • Tricuspid valve reconstruction should be performed before deterioration of RV volume overload and LV function to achieve reverse RV remodeling.

Reverse remodeling of left atrium assessed by cardiovascular magnetic resonance feature tracking in hypertrophic obstructive cardiomyopathy after septal myectomy.

BACKGROUND: Assessing the structure and function of left atrium (LA) is crucial in hypertrophic obstructive cardiomyopathy (HOCM) because LA remodeling correlates with atrial fibrillation. However, few studies have investigated the potential effect of myomectomy on LA phasic remodeling in HOCM after myectomy using cardiovascular magnetic resonance (CMR) feature tracking (FT). This study aims to evaluate the LA structural and functional remodeling with HOCM after myectomy by CMR-FT and to further investigate the determinants of LA reverse remodeling. METHODS: In this single-center study, we retrospectively studied 88 patients with HOCM who received CMR before and after myectomy between January 2011 and June 2021. Preoperative and postoperative LA parameters derived from CMR-FT were compared, including LA reservoir function (total ejection fraction [EF], total strain [εs], peak positive strain rate [SRs]), conduit function (passive EF, passive strain [εe], peak early negative strain rate [SRe]) and booster function (booster EF, active strain [εa], late peak negative strain rate [SRa]). Eighty-six healthy participants were collected for comparison. Univariate and multivariate linear regression identified variables associated with the rate of change of εa. RESULTS: Compared with preoperative parameters, LA reservoir function (total EF, εs, SRs), booster function (booster EF, εa, SRa), and SRe were significantly improved after myectomy (all P < 0.05), while no significant differences were observed in passive EF and εe. Postoperative patients with HOCM still had larger LA and worse LA function than healthy controls (all P < 0.05). After analyzing the rates of change in LA parameters, LA boost function, especially εa, showed the most dramatic improvement beyond the improvements in reservoir function, conduit function, and volume. In multivariable regression analysis, minimum LA volume index (adjusted ß = - 0.39, P < 0.001) and Δleft ventricular outflow tract (LVOT) pressure gradient (adjusted ß = - 0.29, P = 0.003) were significantly related to the rate of change of εa. CONCLUSIONS: Patients with HOCM after septal myectomy showed LA reverse remodeling with a reduction in LA size and restoration in LA reservoir and booster function but unchanged LA conduit function. Among volumetric and functional changes, booster function had the greatest improvement postoperatively. Besides, preoperative LAVmin index and ΔLVOT might be potential factors associated with the degree of improvement in εa.

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.

Correlation between left ventricular fractal dimension and impaired strain assessed by cardiac MRI feature tracking in patients with left ventricular noncompaction and normal left ventricular ejection fraction.

OBJECTIVES: To investigate the correlation between the extent of excessive trabeculation assessed by fractal dimension (FD) and myocardial contractility assessed by cardiac MRI feature tracking in patients with left ventricular noncompaction (LVNC) and normal left ventricular ejection fraction (LVEF). METHODS: Forty-one LVNC patients with normal LVEF (≥ 50%) and 41 healthy controls were retrospectively included. All patients fulfilled three available diagnostic criteria on MRI. Cardiac MRI feature tracking was performed on cine images to determine left ventricular (LV) peak strains in three directions: global radial strain (GRS), global circumferential strain (GCS), and global longitudinal strain (GLS). The complexity of excessive trabeculation was quantified by fractal analysis on short-axis cine stacks. RESULTS: Compared with controls, patients with LVNC had impaired GRS, GCS, and GLS (all p < 0.05). The global, maximal, and regional FD values of the LVNC population were all significantly higher than those of the controls (all p < 0.05). Global FD was positively correlated with the end-diastolic volume index, end-systolic volume index, and stroke volume index (r = 0.483, 0.505, and 0.335, respectively, all p < 0.05), but negatively correlated with GRS and GCS (r = - 0.458 and 0.508, respectively, both p < 0.001). Moreover, apical FD was also weakly associated with LVEF and GLS (r = - 0.249 and 0.252, respectively, both p < 0.05). CONCLUSION: In patients with LVNC, LV systolic dysfunction was detected early by cardiac MRI feature tracking despite the presence of normal LVEF and was associated with excessive trabecular complexity assessed by FD. KEY POINTS: • Left ventricular global strain was already impaired in patients with extremely prominent excessive trabeculation but normal left ventricular ejection fraction. • An increased fractal dimension was associated with impaired deformation in left ventricular noncompaction.

Deep learning algorithm to improve hypertrophic cardiomyopathy mutation prediction using cardiac cine images.

OBJECTIVES: The high variability of hypertrophic cardiomyopathy (HCM) genetic phenotypes has prompted the establishment of risk-stratification systems that predict the risk of a positive genetic mutation based on clinical and echocardiographic profiles. This study aims to improve mutation-risk prediction by extracting cardiovascular magnetic resonance (CMR) morphological features using a deep learning algorithm. METHODS: We recruited 198 HCM patients (48% men, aged 47 ± 13 years) and divided them into training (147 cases) and test (51 cases) sets based on different genetic testing institutions and CMR scan dates (2012, 2013, respectively). All patients underwent CMR examinations, HCM genetic testing, and an assessment of established genotype scores (Mayo Clinic score I, Mayo Clinic score II, and Toronto score). A deep learning (DL) model was developed to classify the HCM genotypes, based on a nonenhanced four-chamber view of cine images. RESULTS: The areas under the curve (AUCs) for the test set were Mayo Clinic score I (AUC: 0.64, sensitivity: 64.29%, specificity: 47.83%), Mayo Clinic score II (AUC: 0.70, sensitivity: 64.29%, specificity: 65.22%), Toronto score (AUC: 0.74, sensitivity: 75.00%, specificity: 56.52%), and DL model (AUC: 0.80, sensitivity: 85.71%, specificity: 69.57%). The combination of the DL and the Toronto score resulted in a significantly higher predictive performance (AUC = 0.84, sensitivity: 83.33%, specificity: 78.26%), compared with Mayo I (p = 006), Mayo II (p = 022), and Toronto score (p = 0.029). CONCLUSIONS: The combination of the DL model, based on nonenhanced cine CMR images and the Toronto score yielded significantly higher diagnostic performance in detecting HCM mutations. KEY POINTS: • Deep learning method could enable the extraction of image features from cine images. • Deep learning method based on cine images performed better than established scores in identifying HCM patients with positive genotypes. • The combination of the deep learning method based on cine images and the Toronto score could further improve the performance of the identification of HCM patients with positive genotypes.

A prognostic five long-noncoding RNA signature for patients with rectal cancer.

This study aimed to identify prognostic long noncoding RNAs (lncRNAs) signature for predicting the prognosis of patients with rectal cancer. LncRNA-sequencing data and clinicopathological data of patients with rectal cancer were retrieved from The Cancer Genome Atlas database. Univariate and multivariate Cox proportional hazards regression analysis, the least absolute shrinkage, and selection operator analysis and the Kaplan-Meier curve method were employed to identify prognostic lncRNAs and construct multi-lncRNA signature. Finally, five lncRNAs (AC079789.1, AC106900.2, AL121987.1, AP004609.1, and LINC02163) were identified to construct a five-lncRNA signature. According to the five-lncRNA signature, patients with rectal cancer were divided into a high-risk group and low-risk group. Patients with rectal cancer had significantly poorer overall survival in the high-risk group than in the low-risk group. We used a time-dependent receiver operating characteristic curve to assess the power of the five-lncRNA signature by calculating the area under the curve (AUC). The AUCs for predicting 3-year survival and 5-year survival were 0.742 and 0.935, respectively, which indicated a good performance of the five-lncRNA signature. The five-lncRNA signature was independently associated with the prognosis of patients with rectal cancer through using univariate and multivariate Cox regression analysis. The biological function of the five lncRNAs was enriched in some cancer-related biological processes and pathways by performing functional enrichment analysis of their correlated protein-coding genes. In conclusion, we developed a five-lncRNA signature as a potential indicator for rectal cancer.

Identification of Key Genes in Thyroid Cancer Microenvironment.

BACKGROUND Tumor microenvironment (TME) plays important roles in the development of cancer. However, the roles of TME in thyroid cancer are not well studied. In our study, we aimed to identify genes related to thyroid cancer microenvironment. MATERIAL AND METHODS We combined The Cancer Genome Atlas (TCGA) and Estimation of STromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) datasets to identify differentially expressed genes in thyroid cancer microenvironment. Then, using these differentially expressed genes, we constructed protein-protein interaction (PPI) network and conducted functional enrichment analysis. Genes with degree beyond 12 in the PPI network were regarded as hub genes. Finally, we conducted Kaplan-Meier curve and log-rank test and functional enrichment analysis on these hub genes. RESULTS There were 793 differentially expressed genes identified to be associated with immune score and stromal score in thyroid cancer microenvironment. We screened out 30 hub genes by construction of PPI network. The functions of these hub genes were enriched in immune cell activity, cytokine and chemokine activity, cell adhesion molecules, and extracellular matrix, which provided further insight into the roles of these genes in the tumor microenvironment. CXCL10, with the highest degrees in the PPI network, were positively related to overall survival of thyroid cancer patients (P=0.02467). CONCLUSIONS We identified 30 tumor microenvironment related genes in thyroid cancer. Among these hub genes, CXCL10 can be regarded as a prognostic biomarker in thyroid cancer.

Cancer-Associated Fibroblasts Autophagy Enhances Progression of Triple-Negative Breast Cancer Cells.

BACKGROUND Cancer-associated fibroblasts (CAFs) are key factors in malignant tumor initiation, progression, and metastasis. However, the effect of CAFs autophagy on triple-negative breast cancer (TNBC) cells is not clear. In this study, the growth effect of TNBC cells regulated by CAFs autophagy was evaluated. MATERIAL AND METHODS CAFs were obtained from invasive TNBC tumors and identified by Western blot and immunofluorescence staining assay. CAFs were co-cultured with TNBC cells, and migration and invasion were evaluated by Matrigel-coated Transwell and Transwell inserts. TNBC cells growth was detected by MTT assay, and epithelial-mesenchymal transition (EMT) regulated by CAFs was evaluated by Western blot assay. RESULTS CAFs were identified by the high expression of α-smooth muscle actin (α-SMA) protein. Autophagy-relevant Beclin 1 and LC3-II/I protein conversion levels in CAFs were higher than those in NFs (P<0.05). TNBC cells migration, invasion, and proliferation levels were significantly improved in the CAFs-conditioned medium (CAFs-CM) group, compared with the other 3 groups (P<0.05). TNBC cells vimentin and N-cadherin protein levels were upregulated and E-cadherin protein level was downregulated in the CAFs-CM group compared with the control group (P<0.05). Further study indicated b-catenin and P-GSK-3ß protein levels, which are the key proteins in the Wnt/ß-catenin pathway, were upregulated in the CAFs-CM group compared with the control group (P<0.05). CONCLUSIONS Our data demonstrated CAFs autophagy can enhance TNBC cell migration, invasion, and proliferation, and CAFs autophagy can induce TNBC cells to engage in the EMT process through the Wnt/ß-catenin pathway.

Selenate and Nitrate Bioreductions Using Methane as the Electron Donor in a Membrane Biofilm Reactor.

Selenate (SeO4(2-)) bioreduction is possible with oxidation of a range of organic or inorganic electron donors, but it never has been reported with methane gas (CH4) as the electron donor. In this study, we achieved complete SeO4(2-) bioreduction in a membrane biofilm reactor (MBfR) using CH4 as the sole added electron donor. The introduction of nitrate (NO3(-)) slightly inhibited SeO4(2-) reduction, but the two oxyanions were simultaneously reduced, even when the supply rate of CH4 was limited. The main SeO4(2-)-reduction product was nanospherical Se(0), which was identified by scanning electron microscopy coupled to energy dispersive X-ray analysis (SEM-EDS). Community analysis provided evidence for two mechanisms for SeO4(2-) bioreduction in the CH4-based MBfR: a single methanotrophic genus, such as Methylomonas, performed CH4 oxidation directly coupled to SeO4(2-) reduction, and a methanotroph oxidized CH4 to form organic metabolites that were electron donors for a synergistic SeO4(2-)-reducing bacterium.

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.

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.

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.

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.

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.

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.

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.

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.

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.