Non-invasive differential diagnosis of teratomas from other intracranial germ cell tumours using MRI-based fractal and radiomic analyses.

OBJECTIVES: The histologic subtype of intracranial germ cell tumours (IGCTs) is an important factor in deciding the treatment strategy, especially for teratomas. In this study, we aimed to non-invasively diagnose teratomas based on fractal and radiomic features. MATERIALS AND METHODS: This retrospective study included 330 IGCT patients, including a discovery set (n = 296) and an independent validation set (n = 34). Fractal and radiomic features were extracted from T1-weighted, T2-weighted, and post-contrast T1-weighted images. Five classifiers, including logistic regression, random forests, support vector machines, K-nearest neighbours, and XGBoost, were compared for our task. Based on the optimal classifier, we compared the performance of clinical, fractal, and radiomic models and the model combining these features in predicting teratomas. RESULTS: Among the diagnostic models, the fractal and radiomic models performed better than the clinical model. The final model that combined all the features showed the best performance, with an area under the curve, precision, sensitivity, and specificity of 0.946 [95% confidence interval (CI): 0.882-0.994], 95.65% (95% CI: 88.64-100%), 88.00% (95% CI: 77.78-96.36%), and 91.67% (95% CI: 78.26-100%), respectively, in the test set of the discovery set, and 0.944 (95% CI: 0.855-1.000), 85.71% (95% CI: 68.18-100%), 94.74% (95% CI: 83.33-100%), and 80.00% (95% CI: 58.33-100%), respectively, in the independent validation set. SHapley Additive exPlanations indicated that two fractal features, two radiomic features, and age were the top five features highly associated with the presence of teratomas. CONCLUSION: The predictive model including image and clinical features could help guide treatment strategies for IGCTs. CLINICAL RELEVANCE STATEMENT: Our machine learning model including image and clinical features can non-invasively predict teratoma components, which could help guide treatment strategies for intracranial germ cell tumours (IGCT). KEY POINTS: • Fractals and radiomics can quantitatively evaluate imaging characteristics of intracranial germ cell tumours. • Model combing imaging and clinical features had the best predictive performance. • The diagnostic model could guide treatment strategies for intracranial germ cell tumours.

Systemic immune response of rainbow trout exposed to Flavobacterium psychrophilum infection.

Bacterial cold-water disease (BCWD) caused by Flavobacterium psychrophilum is one of the most serious bacterial diseases leading to significant economic loss for rainbow trout (Oncorhynchus mykiss) aquaculture. However, little is known about the systemic immune response of rainbow trout against F. psychrophilum infection. This study investigated the immune response of rainbow trout to F. psychrophilum infection using multiple experiments, including bacterial load detection, phagocyte activity assessment, enzyme activity evaluation, and gene expression profiling. Results showed that the spleen index and intestinal pathogen load reached a peak at 3 days post-infection, with strong pro-inflammatory gene expression observed in rainbow trout. Leukocytes RBA and PKA were significantly elevated in the spleen, blood and intestine at 7 days post-infection. Heat map analysis demonstrated that the spleen had a more substantial pro-inflammatory response compared to the intestine post-infection and exhibited higher expression levels of immune-related genes, including IgM, il1ß, il6, cd4, cd8a, cd8b, c1q, chathelicidin, inos, and lysozyme. Both Th1 and Th2 polarized responses in the spleen were activated, with Th2 (il4/13a, gata3) (FC > 4) being more intense than Th1 (tnfα, t-bet) (FC > 2). Tight junction proteins exhibited down-regulation followed by up-regulation post-infection. Collectively, the results of this study expand our current understanding of the immune response of rainbow trout post F. psychrophilum infection but also provide new avenues for investigation in salmonid aquaculture.

The genetic and phenotypic spectra of adult genetic leukoencephalopathies in a cohort of 309 patients.

Genetic leukoencephalopathies (gLEs) are a highly heterogeneous group of rare genetic disorders. The spectrum of gLEs varies among patients of different ages. Distinct from the relatively more abundant studies of gLEs in children, only a few studies that explore the spectrum of adult gLEs have been published, and it should be noted that the majority of these excluded certain gLEs. Thus, to date, no large study has been designed and conducted to characterize the genetic and phenotypic spectra of gLEs in adult patients. We recruited a consecutive series of 309 adult patients clinically suspected of gLEs from Beijing Tiantan Hospital between January 2014 and December 2021. Whole-exome sequencing, mitochondrial DNA sequencing and repeat analysis of NOTCH2NLC, FMR1, DMPK and ZNF9 were performed for patients. We describe the genetic and phenotypic spectra of the set of patients with a genetically confirmed diagnosis and summarize their clinical and radiological characteristics. A total of 201 patients (65%) were genetically diagnosed, while 108 patients (35%) remained undiagnosed. The most frequent diseases were leukoencephalopathies related to NOTCH3 (25%), NOTCH2NLC (19%), ABCD1 (9%), CSF1R (7%) and HTRA1 (5%). Based on a previously proposed pathological classification, the gLEs in our cohort were divided into leukovasculopathies (35%), leuko-axonopathies (31%), myelin disorders (21%), microgliopathies (7%) and astrocytopathies (6%). Patients with NOTCH3 mutations accounted for 70% of the leukovasculopathies, followed by HTRA1 (13%) and COL4A1/2 (9%). The leuko-axonopathies contained the richest variety of associated genes, of which NOTCH2NLC comprised 62%. Among myelin disorders, demyelinating leukoencephalopathies (61%)-mainly adrenoleukodystrophy and Krabbe disease-accounted for the majority, while hypomyelinating leukoencephalopathies (2%) were rare. CSF1R was the only mutated gene detected in microgliopathy patients. Leukoencephalopathy with vanishing white matter disease due to mutations in EIF2B2-5 accounted for half of the astrocytopathies. We characterized the genetic and phenotypic spectra of adult gLEs in a large Chinese cohort. The most frequently mutated genes were NOTCH3, NOTCH2NLC, ABCD1, CSF1R and HTRA1.

The usefulness of [68 Ga]Ga-DOTA-JR11 PET/CT in patients with meningioma: comparison with MRI.

PURPOSE: Clinical studies of PET imaging using SSTR2 agonists have demonstrated high accuracy and correlation with SSTR2 expression in meningiomas. However, the usefulness of the SSTR2 antagonist with [68 Ga]Ga-DOTA-JR11 is uncertain. To evaluate the diagnostic performance of [68 Ga]Ga-DOTA-JR11 PET/CT and to clarify tumor characteristics in patients with suspected meningiomas. MATERIALS AND METHODS: Patients with suspected de novo or recurrent meningioma in complex locations or atypical images were enrolled from August 2021 to October 2022 in prospective study. All patients underwent contrast-enhanced MRI (CE-MRI), [68 Ga]Ga-DOTA-JR11 PET/CT, and histopathological evaluation. Tumor uptake of [68 Ga]Ga-DOTA-JR11 was measured by SUVmax and tumor-endocranium ratio (TBR). Diagnostic performance was compared between PET and MRI. RESULTS: Of 36 (50.0 ± 13.0 years of age, 20 women) patients, 32 were histopathologically confirmed meningiomas and four with other tumors. [68 Ga]Ga-DOTA-JR11 uptake was significantly higher in meningioma patients than in those with other tumors (SUVmax: 13.6 ± 7.7 vs. 5.2 ± 3.0, P < 0.001; TBR: 64.2 ± 27.7 vs. 25.0 ± 18.9, P = 0.001). [68 Ga]Ga-DOTA-JR11 PET/CT detected 31 meningiomas, while CE-MRI detected 17 meningiomas of 25 initial diagnosis and 11 recurrent tumors; [68 Ga]Ga-DOTA-JR11 PET had an incremental diagnostic value of 24% (6/25) over MRI in the group of initial diagnosis. There was no statistically significant difference in diagnostic efficacy between PET and MRI (P = 0.45) for all 36 patients. In skull base meningiomas, PET provided a more definitive diagnosis of pituitary involvement (in 12, not in12), compared to MRI (in eight, possible in six, possible not in six, not in four). PET revealed bone involvement in all 14 patients proven by pathology, while MRI identified only 11. CONCLUSIONS: [68 Ga]Ga-DOTA-JR11 PET/CT provided high image quality and presented an ideal diagnostic performance in detecting meningioma and evaluating the involvement of the pituitary and bone. The study provides valuable evidence for the use of [68 Ga]Ga-DOTA-JR11 PET/CT as a complementary imaging modality to CE-MRI in the evaluation of meningiomas.

Implication of Cerebral Small-Vessel Disease on Perihematomal Edema Progress in Patients With Hypertensive Intracerebral Hemorrhage.

BACKGROUND: Perihematomal edema (PHE) is an important determinant of outcome in spontaneous intracerebral hemorrhage (ICH) due to cerebral small vessel disease (CSVD). However, it is not known to date whether the severity of CSVD is associated with the extent of PHE progression in the acute phase. PURPOSE: To investigate the association between the magnetic resonance imaging (MRI) marker of severe chronic-ischemia cerebral small vessel changes (sciSVC) and PHE growth or hematoma absorption among ICH patients with hypertension. STUDY TYPE: Retrospective. POPULATION: Three hundred and sixty-eight consecutive hypertensive ICH patients without surgical treatment. FIELD STRENGTH/SEQUENCE: 3 T; spin-echo echo-planar imaging-diffusion-weighted imaging (DWI); T2-weighted, fluid-attenuated inversion recovery (FLAIR), T2*-weighted gradient-recalled echo and T1-weighted. ASSESSMENT: The hematoma and PHE volumes at 24 hours and 5 days after symptom onset were measured in 121 patients with spontaneous ICH who had been administered standard medical treatment. Patients were grouped into two categories: those with sciSVC and those without. The imaging marker of sciSVC was defined as white matter hyperintensities (WMHs) Fazekas 2-3 combined cavitating lacunes. STATISTICAL TESTS: Univariable analyses, χ2 test, Mann-Whitney U test, and multiple linear regression. RESULTS: The presence of sciSVC (multiple lacunes and confluent WMH) had a significant negative influence on PHE progress (Beta = -5.3 mL, 95% CI = -10.3 mL to -0.3 mL), and hematoma absorption (Beta = -3.2 mL, 95% CI = -5.9 mL to -0.4 mL) compared to that observed in the absence of sciSVC, as determined by multivariate linear regression analysis. DATA CONCLUSIONS: The presence of sciSVC (multiple lacunes and confluent WMH) negatively influenced hematoma absorption and PHE progress in ICH patients. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

USPIO-SWI Shows Fingolimod Enhanced Alteplase Action on Angiographic Reperfusion in eMCAO Rats.

BACKGROUND: Noninvasive evaluation of the status of cerebral arteriole perfusion remains a practical challenge in murine stroke models, because conventional magnetic resonance imaging (MRI) is no longer capable of capturing these very small vessels. PURPOSE: To investigate the feasibility of ultrasmall superparamagnetic iron oxide particles (USPIO)-based susceptibility weighted imaging (SWI)-MRI (USPIO-SWI) and T2* map-MRI (USPIO-T2* map) for monitoring angiographic perfusion in stroke rats. STUDY TYPE: A preclinical randomized controlled trial. ANIMAL MODEL: Normal rats (N = 9), embolic middle cerebral artery occlusion (eMCAO) rats (N = 66). FIELD STRENGTH/SEQUENCE: 7 T; T2* map (multigradient echo), SWI (3D gradient echo). ASSESSMENT: Experiment 1: To develop a method for angiographic reperfusion evaluation with USPIO-SWI. Normal rats were used to optimize the USPIO dosage (5.6, 16.8, and 56 mg/kg ferumoxytol) as well as scan time points for cerebral arterioles. Contrast-to-noise ratio (CNR) was measured. Stroke rats were further used and the number of visual cortical vessels were counted. Experiment 2: To examine whether fingolimod (lymphocytes inhibitor) enhances the action of tissue plasminogen activator (tPA) in eMCAO rats on cerebral angiographic reperfusion. STATISTICAL TESTS: Mann-Whitney test and two way-ANOVA were used. P < 0.05 was considered statistically significant. RESULTS: CNR values of cerebral cortical penetrating arteries in normal rats were significantly increased to 4.4 ± 0.5 (5.6 mg/kg), 6.1 ± 0.5 (16.8 mg/kg), and 3.4 ± 0.9 (56 mg/kg) after USPIO injection. The number of visual cortical vessels on USPIO-SWI images in ischemic regions was significantly less than in control regions (5 ± 2 vs. 56 ± 20) of eMCAO rats. Compared with eMCAO rats who received tPA only, eMCAO rats who received the combination of fingolimod and tPA exhibited significantly higher proportion of complete angiographic reperfusion (69% vs. 17%). DATA CONCLUSION: This study supports the feasibility of angiographic perfusion evaluation with USPIO-SWI in stroke rats. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Molecular subtyping of diffuse gliomas using magnetic resonance imaging: comparison and correlation between radiomics and deep learning.

OBJECTIVES: The molecular subtyping of diffuse gliomas is important. The aim of this study was to establish predictive models based on preoperative multiparametric MRI. METHODS: A total of 1016 diffuse glioma patients were retrospectively collected from Beijing Tiantan Hospital. Patients were randomly divided into the training (n = 780) and validation (n = 236) sets. According to the 2016 WHO classification, diffuse gliomas can be classified into four binary classification tasks (tasks I-IV). Predictive models based on radiomics and deep convolutional neural network (DCNN) were developed respectively, and their performances were compared with receiver operating characteristic (ROC) curves. Additionally, the radiomics and DCNN features were visualized and compared with the t-distributed stochastic neighbor embedding technique and Spearman's correlation test. RESULTS: In the training set, areas under the curves (AUCs) of the DCNN models (ranging from 0.99 to 1.00) outperformed the radiomics models in all tasks, and the accuracies of the DCNN models (ranging from 0.90 to 0.94) outperformed the radiomics models in tasks I, II, and III. In the independent validation set, the accuracies of the DCNN models outperformed the radiomics models in all tasks (0.74-0.83), and the AUCs of the DCNN models (0.85-0.89) outperformed the radiomics models in tasks I, II, and III. DCNN features demonstrated more superior discriminative capability than the radiomics features in feature visualization analysis, and their general correlations were weak. CONCLUSIONS: Both the radiomics and DCNN models could preoperatively predict the molecular subtypes of diffuse gliomas, and the latter performed better in most circumstances. KEY POINTS: • The molecular subtypes of diffuse gliomas could be predicted with MRI. • Deep learning features tend to outperform radiomics features in large cohorts. • The correlation between the radiomics features and DCNN features was low.

Molecular characterization and expression analysis of claudin-4-like in rainbow trout involved in Flavobacterium psychrophilum infection.

The claudin family of proteins are pivotal components of tight junction (TJ) participating in the epithelial barrier function in fish. Our previous studies indicated that one of the claudins, claudin-4-like (OmCLDN4L) was differentially expressed in rainbow trout (Oncorhynchus mykiss) spleen post infection of Flavobacterium psychrophilum, which is the causative pathogen of bacterial coldwater disease (BCWD). However, little is known about the function of OmCLDN4L in rainbow trout against bacterial infection. In the present study, the OmCLDN4L was identified and functionally characterized from rainbow trout. The OmCLDN4L has an open reading frame (ORF) of 668 bp, encoding a 22.86 kDa four-transmembrane protein with function of bicellular tight junction and apical tight junction. OmCLDN4L has the highest similarity with CLDN28a, CLDN28b and CLDN30 in amino acid sequence. Phylogenetic analysis showed that all of CLDN4 and CLDN4-like from fish clustered together but diverged from their counterparts in mammals, with main differences lying in their N-terminus. RT-qPCR results indicated that OmCLDN4L was constitutively expressed in all tissues investigated under healthy conditions, primarily in mucus, liver, skin and intestine. The expression of OmCLDN4L in rainbow trout intestine was slightly down-regulated at day 1 while up-regulated at day 3 and day 7 post F. psychrophilum infection, with the similar profiling of CLDN30 and CLDN10e. The expression level of inflammatory cytokines TNF-α, IL4/13A, IL-6 and pattern recognition receptor TLR-2 showed the same trend with OmCLDN4L in the intestine at day 3 and day 7 post F. psychrophilum infection. Collectively, these findings demonstrate that OmCLDN4L participates in the immune response to bacterial infection, offering new insights into the molecular mechanism of intestinal barrier in rainbow trout against F. psychrophilum infection.

Functional reorganization of contralesional networks varies according to isocitrate dehydrogenase 1 mutation status in patients with left frontal lobe glioma.

PURPOSE: The study aimed to assess how isocitrate dehydrogenase 1 (IDH1) mutation status in patients with glioma may alter functional connectivity (FC) in the default mode network (DMN) and fronto-parietal network (FPN). METHODS: Using resting-state functional magnetic resonance imaging, a seed-based FC analysis was employed to investigate connectivity within and between networks in seventeen patients with IDH1-mutant glioma (IDH1-M), eleven patients with IDH1-wildtype glioma (IDH1-WT), and nineteen healthy controls (HC). RESULTS: For FC within the DMN, compared to HC, both IDH1-M and IDH1-WT exhibited significantly increased FC between the posterior cingulate cortex (PCC) and the right retrosplenial cortex, right precuneus/cuneus, and right middle cingulate cortex and between the right lateral parietal cortex (LP_R) and the right middle temporal gyrus. For FC within the FPN, compared with HC, IDH1-M showed significantly greater FC between the right posterior parietal cortex (PPC_R) and the right inferior, right medial, and right middle frontal gyrus, and IDH1-WT showed significantly increased FC between the PPC_R and the right middle frontal gyrus. For FC between the DMN and FPN, relative to IDH1-WT and HC, IDH1-M exhibited significantly increased FC between the LP_R and the right superior frontal gyrus and between the PPC_R and the right precuneus/cuneus. In contrast, compared to IDH1-M and HC, IDH1-WT showed significantly reduced FC between the PPC_R and the right angular gyrus. CONCLUSION: The preliminary findings revealed that there should be differences in the patterns of network reorganization between IDH1-M and IDH1-WT with different growth kinetics.

Characterization of the complete mitochondrial genome of Nippotaenia mogurndae Yamaguti and Miyata, 1940 (Cestoda: Nippotaeniidae).

In this study, we report the first complete mitochondrial genome of the tapeworm Nippotaenia mogurndae in the order Nippotaeniidea Yamaguti, 1939. This mitogenome, which is 14,307 base pairs (bp) long with an A + T content of 72.2%, consists of 12 protein-coding genes, 22 transfer RNA (tRNA) genes, two rRNA genes, and two non-coding regions. Most tRNAs have a conventional cloverleaf structure, but trnS1 and trnR lack dihydrouridine arms of tRNA. The two largest non-coding regions, NCR1 (220 bp) and NCR2 (817 bp), are located between trnY and trnS2 and between nad5 and trnG, respectively. Phylogenetic analyses of mitogenomic data indicate that N. mogurndae is closely related to tapeworms in the order Cyclophyllidea.

Transcriptome profiling of immune response to Yersinia ruckeri in spleen of rainbow trout (Oncorhynchus mykiss).

BACKGROUND: Yersinia ruckeri is a pathogen that can cause enteric redmouth disease in salmonid species, damaging global production of economically important fish including rainbow trout (Oncorhynchus mykiss). Herein, we conducted the transcriptomic profiling of spleen samples from rainbow trout at 24 h post-Y. ruckeri infection via RNA-seq in an effort to more fully understand their immunological responses. RESULTS: We identified 2498 differentially expressed genes (DEGs), of which 2083 and 415 were up- and down-regulated, respectively. We then conducted a more in-depth assessment of 78 DEGs associated with the immune system including CCR9, CXCL11, IL-1ß, CARD9, IFN, TNF, CASP8, NF-κB, NOD1, TLR8α2, HSP90, and MAPK11, revealing these genes to be associated with 20 different immunological KEGG pathways including the Cytokine-cytokine receptor interaction, Toll-like receptor signaling, RIG-I-like receptor signaling, NOD-like receptor signaling, and MAPK signaling pathways. Additionally, the differential expression of 8 of these DEGs was validated by a qRT-PCR approach and their immunological importance was then discussed. CONCLUSIONS: Our findings provide preliminary insight on molecular mechanism underlying the immune responses of rainbow trout following Y. ruckeri infection and the base for future studies of host-pathogen interactions in rainbow trout.

Genotypic and Phenotypic Characteristics of Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy from China.

BACKGROUND AND PURPOSE: Studies have shown characteristics of genotypes and phenotypes in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). This study aimed to describe the clinical and genetic characteristics of and correlations between the genotypes and phenotypes observed in CADASIL in China on the basis of exon classification. METHODS: Consecutive Chinese patients with CADASIL were evaluated. The detailed clinical and genetic features of CADASIL patients were collected. Genotypic and phenotypic characteristics were compared among 3 CADASIL groups: group 1 included patients with NOTCH3 mutations in exons 3-4, group 2 included those with NOTCH3 mutations in exon 11, and group 3 included those with NOTCH3 mutations in other exons. RESULTS: A total of 46 patients with CADASIL were evaluated. A comparison of 3 groups with mutations in different NOTCH3 exons revealed that individuals with exon 11 mutations were diagnosed at the oldest age, had the lowest modified Rankin Scale (mRS) scores, and were most likely to have basal ganglia (BG) enlarged perivascular spaces (EPVS) > 20 and atrophy. There were no significant clinical or neuroimaging differences between patients with mutations in exons 3-4 and those with mutations in other exons. CONCLUSIONS: Clinical and neuroimaging features are different among Chinese patients with mutations in exons 3-4, exon 11, or other exons. Exon 11 showed characterized phenotype (the oldest age at diagnosis, the lowest mRS scores, and were most likely to have BG EPVS > 20 and atrophy), there were no significant differences between exons 3-4 and other exons.

MR imaging based fractal analysis for differentiating primary CNS lymphoma and glioblastoma.

OBJECTIVES: The aim of this study was to differentiate primary central nervous system lymphoma (PCNSL) from glioblastomas (GBM) using the fractal analysis of conventional MRI data. MATERIALS AND METHODS: Sixty patients with PCNSL and 107 patients with GBM with MRI data available were enrolled. Fractal dimension (FD) and lacunarity values of the tumour region were calculated using fractal analysis. A predictive model combining fractal parameters and anatomical characteristics was built using logistic regression. The role of FD, lacunarity and the predictive model in differential diagnosis was evaluated using receiver-operating characteristic (ROC) curve analysis. The association between fractal parameters and anatomical characteristics of tumours was also investigated. RESULTS: PCNSL had lower FD values (p < 0.001) and higher lacunarity values (p < 0.001) than GBM. ROC curve analysis revealed that FD, lacunarity, and the predictive model could distinguish PCNSL from GBM (area under the curve: 0.895, 0.776, and 0.969, respectively). The following associations were observed between fractal parameters and anatomical characteristics: multiple lesions were significantly associated with higher lacunarity (p = 0.024), necrosis with higher FD (p = 0.027), corpus callosum involvement with higher lacunarity (p < 0.001) in PCNSL and subventricular zone involvement with higher FD (p < 0.001) in GBM. CONCLUSIONS: The findings of the study indicate that fractal analysis on conventional MRI performs well in distinguishing PCNSL from GBM. KEY POINTS: • Fractal dimension and lacunarity were capable of differentiating PCNSL from GBM. • PCNSL and GBM exhibited different anatomical characteristics. • Fractal parameters were associated with some of these anatomical characteristics.

A transcriptome analysis focusing on splenic immune-related mciroRNAs of rainbow trout upon Aeromonas salmonicida subsp. salmonicida infection.

MicroRNAs (miRNAs) are a class of small non-coding RNAs that can regulate the immune responses during pathogen infection. Aeromonas salmonicida (A. salmonicida) subsp. salmonicida is the causative agent of furunculosis in salmon and trout. To identify the miRNAs and investigate the specific miRNAs in rainbow trout upon A. salmonicida subsp. salmonicida infection, we performed high throughput sequencing using the spleens of rainbow trout infected with and without an A. salmonicida subsp. salmonicida clinical isolate. A total of 381 known miRNAs and 926 novel miRNAs were identified. Eleven known and 16 novel miRNAs were found to be differentially expressed upon infection. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that the target genes of the differentially expressed miRNAs were closely associated with immune responses and biological regulations. Additionally, over- and suppressed expression of miR-155-5p significantly enhanced and reduced the IL-2 and IL-1ß expressions in RTG-2 cells induced by A. salmonicida, respectively. To our knowledge, this is the first experimental study on the miRNAs of rainbow trout upon A. salmonicida infection. The results here might lay a foundation for the further understanding of the roles of miRNAs in the immune responses during A. salmonicida infection in rainbow trout.

Radiogenomic analysis of PTEN mutation in glioblastoma using preoperative multi-parametric magnetic resonance imaging.

PURPOSE: PTEN mutation status is a pivotal biomarker for glioblastoma. This study aimed to establish a radiomic signature to predict PTEN mutation status in patients with glioblastoma, and to investigate the genetic background behind this radiomic signature. METHODS: In this study, a total of 862 radiomic features were extracted from each patient. The training (n = 69) and validation (n = 40) sets were retrospectively collected from the Cancer Genome Atlas and the Chinese Glioma Genome Atlas, respectively. The minimum redundancy maximum relevance (mRMR) algorithm was used to select the best predictive features of PTEN status. A machine learning model was then built with the selected features using a support vector machine classifier. The predictive performance of each selected feature and the complete model were evaluated via the area under the curve from receiver operating characteristic analysis in both the training and validation sets. The genetic background underlying the radiomic signature was determined using radiogenomic analysis. RESULTS: Six features were selected using the mRMR algorithm, including two features derived from contrast-enhanced images and four features derived from T2-weighted images. The predictive performance of the machine learning model for the training and validation sets were 0.925 and 0.787, respectively, which were better than the individual features. Radiogenomics analysis revealed that the PTEN-associated biological processes could be described using the radiomic signature. CONCLUSION: These results show that radiomic features derived from preoperative MRI can predict PTEN mutation status in glioblastoma patients, thus providing a novel noninvasive imaging biomarker.

Research on the Algorithm Model for Measuring Ocean Waves Based on Satellite GPS Signals in China.

In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the GPS wave buoy is to calculate the movement velocity of the buoy using the Doppler frequency shift of satellite GPS signals, and then to calculate the wave parameters from the movement velocity according to ocean wave theory. The shortage of the GPS wave buoy is the occasional occurrence of some unusual values in the movement velocity. This is mainly due to the fact that the GPS antenna is occasionally covered by sea water and cannot normally receive high-quality satellite GPS signals. The traditional solution is to remove these unusual movement velocity values from the records, which requires furthering extend the acquisition time of satellite GPS signals to ensure there is a large enough quantity of effective movement velocity values. Based on the traditional GPS wave measurement technology, this paper presents the algorithmic flow and proposes two improvement measures. On the one hand, the neural network algorithm is used to correct the unusual movement velocity data so that extending the acquisition time of satellite GPS signals is not necessary and battery power is saved. On the other hand, the Gaussian low-pass filter is used to correct the raw directional wave spectrum, which can further eliminate the influence of noise spectrum energy and improve the measurement accuracy. The on-site sea test of the SBF7-1A GPS wave buoy, developed by the National Ocean Technology Center in China, and the gravity-acceleration-type DWR-MKIII Waverider buoy are highlighted in this article. The wave data acquired by the two buoys are analyzed and processed. It can be seen from the processed results that the ocean wave parameters from the two kinds of wave buoys, such as wave height, wave period, wave direction, wave frequency spectrum, and directional wave spectrum, are in good consistency, indicating that the SBF7-1A GPS wave buoy is comparable to the traditional gravity-acceleration-type wave buoy in terms of its accuracy. Therefore, the feasibility and validity of the two improvement measures proposed in this paper are confirmed.

A combined diffusion tensor imaging and Ki-67 labeling index study for evaluating the extent of tumor infiltration using the F98 rat glioma model.

Diffusion tensor imaging (DTI) has been proven to be a sophisticated and useful tool for the delineation of tumors. In the present study, we investigated the predictive role of DTI compared to other magnetic resonance imaging (MRI) techniques in combination with Ki-67 labeling index in defining tumor cell infiltration in the peritumoral regions of F98 glioma-bearing rats. A total of 29 tumor-bearing Fischer rats underwent T2-weighted imaging, contrast-enhanced T1-weighted imaging, and DTI of their brain using a 7.0-T MRI scanner. The fractional anisotropy (FA) ratios were correlated to the Ki-67 labeling index using the Spearman correlation analysis. A receiver operating characteristic curve (ROC) analysis was established to evaluate parameters with sensitivity and specificity in order to identify the threshold values for predicting tumor infiltration. Significant correlations were observed between the FA ratios and Ki-67 labeling index (r = - 0.865, p < 0.001). The ROC analysis demonstrated that the apparent diffusion coefficient (ADC) and FA ratios could predict 50% of the proliferating cells in the regions of interest (ROI), with a sensitivity of 88.1 and 81.3%, and a specificity of 86.2 and 90.2%, respectively (p < 0.001). Meanwhile, the two ratios could also predict 10% of the proliferating cells in the ROI, with a sensitivity of 82.5 and 94.9%, and a specificity of 100 and 88.9%, respectively (p < 0.001). The present study demonstrated that the FA ratios are closely correlated with the Ki-67 labeling index. Furthermore, both ADC and FA ratios, derived from DTI, were useful for quantitatively predicting the Ki-67 labeling of glioma cells.

MRI features can predict EGFR expression in lower grade gliomas: A voxel-based radiomic analysis.

OBJECTIVE: To identify the magnetic resonance imaging (MRI) features associated with epidermal growth factor (EGFR) expression level in lower grade gliomas using radiomic analysis. METHODS: 270 lower grade glioma patients with known EGFR expression status were randomly assigned into training (n=200) and validation (n=70) sets, and were subjected to feature extraction. Using a logistic regression model, a signature of MRI features was identified to be predictive of the EGFR expression level in lower grade gliomas in the training set, and the accuracy of prediction was assessed in the validation set. RESULTS: A signature of 41 MRI features achieved accuracies of 82.5% (area under the curve [AUC] = 0.90) in the training set and 90.0% (AUC = 0.95) in the validation set. This radiomic signature consisted of 25 first-order statistics or related wavelet features (including range, standard deviation, uniformity, variance), one shape and size-based feature (spherical disproportion), and 15 textural features or related wavelet features (including sum variance, sum entropy, run percentage). CONCLUSIONS: A radiomic signature allowing for the prediction of the EGFR expression level in patients with lower grade glioma was identified, suggesting that using tumour-derived radiological features for predicting genomic information is feasible. KEY POINTS: • EGFR expression status is an important biomarker for gliomas. • EGFR in lower grade gliomas could be predicted using radiogenomic analysis. • A logistic regression model is an efficient approach for analysing radiomic features.

Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature.

OBJECTIVES: To predict ATRX mutation status in patients with lower-grade gliomas using radiomic analysis. METHODS: Cancer Genome Atlas (TCGA) patients with lower-grade gliomas were randomly allocated into training (n = 63) and validation (n = 32) sets. An independent external-validation set (n = 91) was built based on the Chinese Genome Atlas (CGGA) database. After feature extraction, an ATRX-related signature was constructed. Subsequently, the radiomic signature was combined with a support vector machine to predict ATRX mutation status in training, validation and external-validation sets. Predictive performance was assessed by receiver operating characteristic curve analysis. Correlations between the selected features were also evaluated. RESULTS: Nine radiomic features were screened as an ATRX-associated radiomic signature of lower-grade gliomas based on the LASSO regression model. All nine radiomic features were texture-associated (e.g. sum average and variance). The predictive efficiencies measured by the area under the curve were 94.0 %, 92.5 % and 72.5 % in the training, validation and external-validation sets, respectively. The overall correlations between the nine radiomic features were low in both TCGA and CGGA databases. CONCLUSIONS: Using radiomic analysis, we achieved efficient prediction of ATRX genotype in lower-grade gliomas, and our model was effective in two independent databases. KEY POINTS: • ATRX in lower-grade gliomas could be predicted using radiomic analysis. • The LASSO regression algorithm and SVM performed well in radiomic analysis. • Nine radiomic features were screened as an ATRX-predictive radiomic signature. • The machine-learning model for ATRX-prediction was validated by an independent database.

CFHR1-Modified Neural Stem Cells Ameliorated Brain Injury in a Mouse Model of Neuromyelitis Optica Spectrum Disorders.

A major hurdle for effective stem cell therapy is ongoing inflammation in the target organ. Reconditioning the lesion microenvironment may be an effective way to promote stem cell therapy. In this study, we showed that engineered neural stem cells (NSCs) with complement factor H-related protein 1, a complement inhibitor protein, can attenuate inflammatory infiltration and immune-mediated damage of astrocytes, an important pathogenic progress in patients with neuromyelitis optica spectrum disorders. Furthermore, we demonstrated that transplantation of the complement factor H-related protein 1-modified NSCs effectively blocked the complement activation cascade and inhibited formation of the membrane attack complex, thus contributing to the protection of endogenous and transplanted NSC-differentiated astrocytes. Therefore, manipulation of the lesion microenvironment contributes to a more effective cell replacement therapeutic strategy for autoimmune diseases of the CNS.