RESUMEN
BACKGROUND: Liver fibrosis is characterized by macromolecule depositions. Recently, a novel technology termed macromolecular proton fraction quantification based on spin-lock magnetic resonance imaging (MPF-SL) is reported to measure macromolecule levels. HYPOTHESIS: MPF-SL can detect early-stage liver fibrosis by measuring macromolecule levels in the liver. STUDY TYPE: Retrospective. SUBJECTS: Fifty-five participants, including 22 with no fibrosis (F0) and 33 with early-stage fibrosis (F1-2), were recruited. FIELD STRENGTH/SEQUENCE: 3 T; two-dimensional (2D) MPF-SL turbo spin-echo sequence, 2D spin-lock T1rho turbo spin-echo sequence, and multi-slice 2D gradient echo sequence. ASSESSMENT: Macromolecular proton fraction (MPF), T1rho, liver iron concentration (LIC), and fat fraction (FF) biomarkers were quantified within regions of interest. STATISTICAL TESTS: Group comparison of the biomarkers using Mann-Whitney U tests; correlation between the biomarkers assessed using Spearman's rank correlation coefficient and linear regression with goodness-of-fit; fibrosis stage differentiation using receiver operating characteristic curve (ROC) analysis. P-value < 0.05 was considered statistically significant. RESULTS: Average T1rho was 41.76 ± 2.94 msec for F0 and 41.15 ± 3.73 msec for F1-2 (P = 0.60). T1rho showed nonsignificant correlation with either liver fibrosis (ρ = -0.07; P = 0.61) or FF (ρ = -0.14; P = 0.35) but indicated a negative correlation with LIC (ρ = -0.66). MPF was 4.73 ± 0.45% and 5.65 ± 0.81% for F0 and F1-2 participants, respectively. MPF showed a positive correlation with liver fibrosis (ρ = 0.59), and no significant correlations with LIC (ρ = 0.02; P = 0.89) or FF (ρ = 0.05; P = 0.72). The area under the ROC curve was 0.85 (95% confidence interval [CI] 0.75-0.95) and 0.55 (95% CI 0.39-0.71; P = 0.55) for MPF and T1rho to discriminate between F0 and F1-2 fibrosis, respectively. DATA CONCLUSION: MPF-SL has the potential to diagnose early-stage liver fibrosis and does not appear to be confounded by either LIC or FF. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.
Asunto(s)
Cirrosis Hepática , Protones , Humanos , Estudios Retrospectivos , Cirrosis Hepática/diagnóstico por imagen , Cirrosis Hepática/patología , Imagen por Resonancia Magnética/métodos , Hígado/diagnóstico por imagen , Hígado/patología , Fibrosis , Sustancias Macromoleculares , BiomarcadoresRESUMEN
The red imported fire ant (Solenopsis invicta Buren) is a social pest species with a robust reproductive ability that causes extensive damage. Identification of the genes involved in queen fertility is critical in order to better understand the reproductive biology and screening for the potential molecular targets in S. invicta. Here, we used the mRNA deep sequencing (RNA-seq) approach to identify differentially expressed genes (DEGs) in the transcriptomes of three reproductive caste types of S. invicta, including queen (QA) and winged female (FA) and male (MA) ants. The genes that were specific to and highly expressed in the queens were then screened, and the Vg2 and Vg3 genes were chosen as targets to explore their functions in oogenesis and fertility. A minimum of 6.08 giga bases (Gb) of clean reads was obtained from all samples, with a mapping rate > 89.78%. There were 7524, 7133, and 977 DEGs identified in the MA vs. QA, MA vs. FA, and FA vs. QA comparisons, respectively. qRT-PCR was used to validate 10 randomly selected DEGs, including vitellogenin 2 (Vg2) and 3 (Vg3), and their expression patterns were mostly consistent with the RNA-seq data. The S. invicta Vgs included conserved domains and motifs that are commonly found in most insect Vgs. SiVg2 and SiVg3 were highly expressed in queens and winged females and were most highly expressed in the thorax, followed by the fat body, head, and epidermis. Evaluation based on a loss-of-function-based knockdown analysis showed that the downregulation of either or both of these genes resulted in smaller ovaries, less oogenesis, and less egg production. The results of transcriptional sequencing provide a foundation for clarifying the regulators of queen fertility in S. invicta. The functions of SiVg2 and SiVg3 as regulators of oogenesis highlight their importance in queen fecundity and their potential as targets of reproductive disruption in S. invicta control.
Asunto(s)
Hormigas , Vitelogeninas , Animales , Femenino , Masculino , Vitelogeninas/genética , Vitelogeninas/metabolismo , Hormigas de Fuego , Reproducción/genética , Fertilidad/genética , Hormigas/genéticaRESUMEN
PURPOSE: Quantitative T1ρ imaging is an emerging technique to assess the biochemical properties of tissues. In this paper, we report our observation that liver iron content (LIC) affects T1ρ quantification of the liver at 3.0T field strength and develop a method to correct the effect of LIC. THEORY AND METHODS: On-resonance R1ρ (1/T1ρ ) is mainly affected by the intrinsic R2 (1/T2 ), which is influenced by LIC. As on-resonance R1ρ is closely related to the Carr-Purcell-Meiboom-Gill (CPMG) R2 , and because the calibration between CPMG R2 and LIC has been reported at 1.5T, a correction method was proposed to correct the R2 contribution to the R1ρ . The correction coefficient was obtained from the calibration results and related transformed factors. To compensate for the difference between CPMG R2 and R1ρ , a scaling factor was determined using the values of CPMG R2 and R1ρ , obtained simultaneously from a single breath-hold from volunteers. The livers of 110 subjects were scanned to validate the correction method. RESULTS: LIC was significantly correlated with R1ρ in the liver. However, when the proposed correction method was applied to R1ρ , LIC and the iron-corrected R1ρ were not significantly correlated. CONCLUSION: LIC can affect T1ρ in the liver. We developed an iron-correction method for the quantification of T1ρ in the liver at 3.0T.
Asunto(s)
Sobrecarga de Hierro , Hierro , Calibración , Humanos , Sobrecarga de Hierro/diagnóstico por imagen , Sobrecarga de Hierro/tratamiento farmacológico , Hígado/diagnóstico por imagen , Imagen por Resonancia Magnética/métodosRESUMEN
Ascoviruses are fatal double-stranded DNA viruses with a special pathogenesis in which cells are converted into vesicles with virions. Several closely related ascovirus isolates that shared more than 90% genomic DNA identity showed different pathogenic courses in previous studies. To investigate the pathogenic differences between the related ascovirus isolates, Heliothis virescens ascovirus 3i (HvAV-3i) and Heliothis virescens ascovirus 3j (HvAV-3j) were used to inoculate four noctuid pest species (Helicoverpa armigera, Mythimna separata, Spodoptera frugiperda, and Spodoptera litura), and the pathogenic indexes were recorded. The mortality of HvAV-3i infected H. armigera and S. frugiperda was approximately 60%, while the other HvAV-infected larvae had mortality rates above 90%. The maximum lethal dilution ratios of HvAV-3i in H. armigera, M. separata, S. frugiperda, and S. litura were 1.90 × 107, 1.90 × 103, 1.90 × 108, and 1.90 × 104 viral genome DNA copies/mL, respectively, while the ratios of HvAV-3j were 8.22 × 106, 8.22 × 102, 8.22 × 105, and 8.22 × 103 viral genome DNA copies/mL, respectively. Extended larval survival time was found in the HvAV-infected larvae; median survival time of the HvAV-infected larvae ranged from 13 to 19 days. An additional larval instar was found in HvAV-infected M. separata, S. frugiperda, and S. litura. Larval growth and food intake were significantly inhibited from 2 days post-infection (dpi) in the tested H. armigera, S. frugiperda, and S. litura after infection with HvAV-3i or HvAV-3j. The detoxification enzyme activity of host larvae was influenced after infection with HvAVs, and two different regulation patterns were detected, one in infected H. armigera and M. separata and the other in S. frugiperda and S. litura. The results obtained in this study provide insights into the pathogenic characteristics of ascoviruses.
Asunto(s)
Ascoviridae , Mariposas Nocturnas , Animales , Ascoviridae/genética , ADN Viral/genética , Larva , SpodopteraRESUMEN
Masked image modeling (MIM) has been considered as the state-of-the-art (SOTA) self-supervised learning (SSL) technique in terms of visual pretraining. The impressive generalization ability of MIM also paves the way for the remarkable success of large-scale vision foundation models. In this article, we further discuss the validity and advantages of implementing MIM techniques in the reproducing kernel Hilbert spaces (RKHSs) and we associate the analysis with a novel MIM method named R-MIM (short for RKHS-MIM). Through the careful construction of an augmentation graph and by using spectral decomposition techniques, we establish a systematic theoretical understanding between the proposed R-MIM's generalization ability and the choice of kernel function used during training. Specifically, we reach a conclusion that both of the local Lipschitz constant of the resultant R-MIM model and the corresponding expected pretraining error can have a strong composite effect on bounding downstream task error, depending on the kernel options. We demonstrate that under mild mathematical assumptions, R-MIM method is guaranteed to return a lower bound on downstream tasks in comparison to vanilla MIM techniques, such as masked autoencoder (MAE) and SimMIM. Empirical justification well corroborates our theoretical hypothesis and analysis in showing the superior generalization of the proposed R-MIM and the theoretical link to kernel choices. The code is available at: https://github.com/yurui-q/R-MIM.
RESUMEN
PURPOSE: T1rho imaging is a promising MRI technique for imaging of brain disease. This study aimed to assess the repeatability of quantitative T1rho imaging in the normal brain grey and white matter. METHODS: The study prospectively recruited 30 healthy volunteers without a history of neurological diseases or brain injury, and T1rho was performed and quantified from three imaging sessions. Repeat measures analysis of variance (ANOVA) and within-subject coefficients of variation (wCoV) was used to detect differences in T1rho values between the three scans. RESULTS: The results showed low wCoVs of less than 4.3% (range 0.92-4.27%) across all the brain structures. No significant differences were observed in T1rho measurement between the three scans (p > 0.05). The amygdala and hippocampus showed the highest T1rho values of 91.79 ± 2.55 msec and 91.07 ± 2.11 msec respectively, and the palladium and putamen had the lowest values of 67.60 ± 1.84 msec and 71.83 ± 1.85 msec respectively. CONCLUSION: T1rho shows high test-retest repeatability for whole brain imaging in serial imaging sessions, indicating it to be a reliable sequence for quantitative brain imaging.
Asunto(s)
Encéfalo , Imagen por Resonancia Magnética , Humanos , Imagen por Resonancia Magnética/métodos , Encéfalo/diagnóstico por imagen , Reproducibilidad de los ResultadosRESUMEN
Multi-parametric mapping of MRI relaxations in liver has the potential of revealing pathological information of the liver. A self-supervised learning based multi-parametric mapping method is proposed to map T1ρ and T2 simultaneously, by utilising the relaxation constraint in the learning process. Data noise of different mapping tasks is utilised to make the model uncertainty-aware, which adaptively weight different mapping tasks during learning. The method was examined on a dataset of 51 patients with non-alcoholic fatter liver disease. Results showed that the proposed method can produce comparable parametric maps to the traditional multi-contrast pixel wise fitting method, with a reduced number of images and less computation time. The uncertainty weighting also improves the model performance. It has the potential of accelerating MRI quantitative imaging.
Asunto(s)
Concienciación , Imagen por Resonancia Magnética , Humanos , Incertidumbre , Imagen por Resonancia Magnética/métodos , Hígado/diagnóstico por imagen , Aprendizaje Automático SupervisadoRESUMEN
Objective.T1ρmapping is a promising quantitative MRI technique for the non-invasive assessment of tissue properties. Learning-based approaches can mapT1ρfrom a reduced number ofT1ρweighted images but requires significant amounts of high-quality training data. Moreover, existing methods do not provide the confidence level of theT1ρestimation. We aim to develop a learning-based liverT1ρmapping approach that can mapT1ρwith a reduced number of images and provide uncertainty estimation.Approach. We proposed a self-supervised neural network that learns aT1ρmapping using the relaxation constraint in the learning process. Epistemic uncertainty and aleatoric uncertainty are modelled for theT1ρquantification network to provide a Bayesian confidence estimation of theT1ρmapping. The uncertainty estimation can also regularize the model to prevent it from learning imperfect data. Main results. We conducted experiments onT1ρdata collected from 52 patients with non-alcoholic fatty liver disease. The results showed that when only collecting twoT1ρ-weighted images, our method outperformed the existing methods forT1ρquantification of the liver. Our uncertainty estimation can further regularize the model to improve the performance of the model and it is consistent with the confidence level of liverT1ρvalues.Significance. Our method demonstrates the potential for accelerating theT1ρmapping of the liver by using a reduced number of images. It simultaneously provides uncertainty ofT1ρquantification which is desirable in clinical applications.