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Abstract Objectives To investigate the feasibility of a deep learning-constrained compressed sensing (DL-CS) method in non-contrast-enhanced modified DIXON (mDIXON) coronary magnetic resonance angiography (MRA) and compare its diagnostic accuracy using coronary CT angiography (CCTA) as a reference standard. Methods Ninety-nine participants were prospectively recruited for this study. Thirty healthy subjects (age range: 20–65 years; 50% female) underwent three non-contrast mDIXON-based coronary MRA sequences including DL-CS, CS, and conventional sequences. The three groups were compared based on the scan time, subjective image quality score, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The remaining 69 patients suspected of coronary artery disease (CAD) (age range: 39–83 years; 51% female) underwent the DL-CS coronary MRA and its diagnostic performance was compared with that of CCTA. Results The scan time for the DL-CS and CS sequences was notably shorter than that of the conventional sequence (9.6 ± 3.1 min vs 10.0 ± 3.4 min vs 13.0 ± 4.9 min; p

PurposeTo compare the ability of diffusion parameters obtained by stretched-exponential and kurtosis models of diffusion-weighted imaging (DWI) to distinguish between patients with primary aldosteronism (PA) and healthy controls (HCs) in renal assessment.Materials and methodsA total of 44 participants (22 patients and 22 HCs) underwent renal MRI with an 11 b-value DWI sequence and a 3 b-value diffusion kurtosis imaging (DKI) sequence from June 2021 to April 2022. Binary logistic regression was used to construct regression models combining different diffusion parameters. Receiver-operating characteristic (ROC) curve analysis and comparisons were used to evaluate the ability of single diffusion parameters and combined diffusion models to distinguish between the two groups.ResultsA total of six diffusion parameters (including the cortical anomalous exponent term [α_Cortex], medullary fractional anisotropy [FA_Medulla], cortical FA [FA_Cortex], cortical axial diffusivity [Da_Cortex], medullary mean diffusivity [MD_Medulla] and medullary radial diffusivity [Dr_Medulla]) were included, and 10 regression models were studied. The area under the curve (AUC) of Dr_Medulla was 0.855, comparable to that of FA_Cortex and FA_Medulla and significantly higher than that of α_Cortex, Da_Cortex and MD_Medulla. The AUC of the Model_all parameters was 0.967, comparable to that of Model_FA (0.946) and Model_DKI (0.966) and significantly higher than that of the other models. The sensitivity and specificity of Model_all parameters were 87.2% and 95%, respectively.ConclusionThe Model_all parameters, Model_FA and Model_DKI were valid for differentiating between PA patients and HCs with similar differentiation efficacy and were superior to single diffusion parameters and other models.

Diseases caused by begomoviruses such as tomato yellow leaf curl disease (TYLCD) are major constraints in agriculture. While the interactions between plants and monopartite begomoviruses during TYLCD pathogenesis have been explored extensively, how bipartite begomoviruses interact with tomato plants are understudied. Here we first found that a bipartite begomovirus tomato yellow leaf curl Thailand virus (TYLCTHV) induced stunted growth, leaf curl and yellowing in tomato plants. We then profiled the tomato transcriptomic changes in response to TYLCTHV infection. In total, we identified 2322 upregulated and 1377 downregulated genes. KEGG enrichment analysis of the differentially expressed genes (DEGs) revealed that many KEGG pathways regulating plant photosynthesis processes and defenses were enriched. Specifically, TYLCTHV infection disrupted the expression of DEGs that function in the light-harvesting chlorophyll protein complex, photosystem I and II, cytochrome b6/f complex, photosynthetic electron transport and F-type ATPase. Additionally, the expression of many DEGs regulating plant defenses including pathogen-associated molecular pattern (PAMP)-triggered immunity, effector-triggered immunity and hypersensitive response was upregulated upon TYLCTHV infection. Taken together, we found that during the pathogenesis of TYLCD induced by TYLCTHV, the virus actively disrupts plant photosynthesis processes and induces defense responses. Our findings add to our knowledge of TYLCD pathogenesis and plant–virus interactions in general.