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UV-B radiation can induce the accumulation of many secondary metabolites, including flavonoids, in plants to protect them from oxidative damage. BRI1-EMS-SUPPRESSOR1 (BES1) has been shown to mediate the biosynthesis of flavonoids in response to UV-B. However, the detailed mechanism by which it acts still needs to be further elucidated. Here, we revealed that UV-B significantly inhibited the transcription of multiple transcription factor genes in tobacco, including NtMYB27, which was subsequently shown to be a repressor of flavonoids synthesis in tobacco. We further demonstrated that NtBES1 directly binds to the E-box motifs present in the promoter of NtMYB27 to mediate its transcriptional repression upon UV-B exposure. The UV-B-repressed NtMYB27 could bind to the ACCT-containing element (ACE) in the promoters of Nt4CL and NtCHS and served as a modulator that promoted the biosynthesis of lignin and chlorogenic acid (CGA) but inhibited the accumulation of flavonoids in tobacco. The expression of NtMYB27 was also significantly repressed by heat stress, suggesting its putative roles in regulating heat-induced flavonoids accumulation. Taken together, our results revealed the role of NtBES1 and NtMYB27 in regulating the synthesis of flavonoids during the plant response to UV-B radiation in tobacco.
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BACKGROUND AIMS: Studies have shown that blocking the PD-1/PD-L1 pathway may lead to a potential cure for HBV infections. ASC22 (Envafolimab) is a humanized, single-domain PD-L1 antibody administered subcutaneously. This study aimed to evaluate the efficacy and safety of ASC22 in virally suppressed chronic hepatitis B (CHB) patients on nucleos(t)ide analogs (NAs). APPROACH AND RESULTS: This randomized, single-blind, phase IIb trial enrolled CHB patients in two cohorts for a 24-week treatment with ASC22 or placebo (PBO) once every 2 weeks and 24-week follow-up. In total, 60, 59, and 30 patients were treated with 1.0, 2.5 mg/kg ASC22 and PBO, respectively. The mean HBsAg changes from baseline at week 24 and 24 week follow-up periods were -0.309 (p<0.001) and -0.272 (p<0.023) log10 IU/mL in the 1.0 mg/kg ASC22 group, -0.231 (p=0.007) and -0.205 (p=0.12) log10 IU/mL in the 2.5 mg/kg ASC22 group, and-0.003 and -0.063 log10 IU/mL in the PBO group, respectively (ITT population). Three out of ten patients with baseline HBsAg levels ≤100 IU/mL in the 1.0 mg/kg group obtained on-treatment HBsAg loss. Most AEs were mild (97.9%). There were no study drug-related serious AEs in the 1.0 mg/kg ASC22 group. CONCLUSIONS: Subcutaneous administration of 1.0 mg/kg ASC22 Q2W for 24 weeks was shown to be safe and well tolerated in virally suppressed CHB patients on NAs and can induce HBsAg decline, especially in patients with HBsAg ≤100 IU/mL.
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Early onset familial Alzheimer's disease (FAD) with APP, PS1/2 (presenilins) mutation accounts for only a small portion of AD cases, and most are late-onset sporadic. However, majority of AD mouse models are developed to mimic the genetic cause of human AD by overexpressing mutated forms of human APP, PS1/2, and/or Tau protein, though there is no Tau mutation in AD, and no single mouse model recapitulates all aspects of AD pathology. Here, we report Thy1-ApoE4/C/EBPß double transgenic mouse model that demonstrates key AD pathologies in an age-dependent manner in absence of any human APP or PS1/2 mutation. Using the clinical diagnosis criteria, we show that this mouse model exhibits tempo-spatial features in AD patient brains, including progressive cognitive decline associated with brain atrophy, which is accompanied with extensive neuronal degeneration. Remarkably, the mice display gradual Aß aggregation and neurofibrillary tangles formation in the brain validated by Aß PET and Tau PET. Moreover, the mice reveal widespread neuroinflammation as shown in AD brains. Hence, Thy1-ApoE4/C/EBPß mouse model acts as a sporadic AD mouse model, reconstituting the major AD pathologies.
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Antipsychotic-induced weight gain (AIWG) is a common side effect of antipsychotic medication and may contribute to diabetes and coronary heart disease. To expand the unclear genetic mechanism underlying AIWG, we conducted a two-stage genome-wide association study in Han Chinese patients with schizophrenia. The study included a discovery cohort of 1936 patients and a validation cohort of 534 patients, with an additional 630 multi-ancestry patients from the CATIE study for external validation. We applied Mendelian randomization (MR) analysis to investigate the relationship between AIWG and antipsychotic-induced lipid changes. Our results identified two novel genome-wide significant loci associated with AIWG: rs10422861 in PEPD (P = 1.373 × 10-9) and rs3824417 in PTPRD (P = 3.348 × 10-9) in Chinese Han samples. The association of rs10422861 was validated in the European samples. Fine-mapping and functional annotation revealed that PEPD and PTPRD are potentially causal genes for AIWG, with their proteins being prospective therapeutic targets. Colocalization analysis suggested that AIWG and type 2 diabetes (T2D) shared a causal variant in PEPD. Polygenic risk scores (PRSs) for AIWG and T2D significantly predicted AIWG in multi-ancestry samples. Furthermore, MR revealed a risky causal effect of genetically predicted changes in low-density lipoprotein cholesterol (P = 7.58 × 10-4) and triglycerides (P = 2.06 × 10-3) caused by acute-phase of antipsychotic treatment on AIWG, which had not been previously reported. Our model, incorporating antipsychotic-induced lipid changes, PRSs, and clinical predictors, significantly predicted BMI percentage change after 6-month antipsychotic treatment (AUC = 0.79, R2 = 0.332). Our results highlight that the mechanism of AIWG involves lipid pathway dysfunction and may share a genetic basis with T2D through PEPD. Overall, this study provides new insights into the pathogenesis of AIWG and contributes to personalized treatment of schizophrenia.
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OBJECTIVE: Hepatitis B surface antigen (HBsAg) loss is the optimal outcome for patients with chronic hepatitis B (CHB) but this rarely occurs with currently approved therapies. We aimed to develop and validate a prognostic model for HBsAg loss on treatment using longitudinal data from a large, prospectively followed, nationwide cohort. DESIGN: CHB patients receiving nucleos(t)ide analogues as antiviral treatment were enrolled from 50 centres in China. Quantitative HBsAg (qHBsAg) testing was prospectively performed biannually per protocol. Longitudinal discriminant analysis algorithm was used to estimate the incidence of HBsAg loss, by integrating clinical data of each patient collected during follow-up. RESULTS: In total, 6792 CHB patients who had initiated antiviral treatment 41.3 (IQR 7.6-107.6) months before enrolment and had median qHBsAg 2.9 (IQR 2.3-3.3) log10IU/mL at entry were analysed. With a median follow-up of 65.6 (IQR 51.5-84.7) months, the 5-year cumulative incidence of HBsAg loss was 2.4%. A prediction model integrating all qHBsAg values of each patient during follow-up, designated GOLDEN model, was developed and validated. The AUCs of GOLDEN model were 0.981 (95% CI 0.974 to 0.987) and 0.979 (95% CI 0.974 to 0.983) in the training and external validation sets, respectively, and were significantly better than those of a single qHBsAg measurement. GOLDEN model identified 8.5%-10.4% of patients with a high probability of HBsAg loss (5-year cumulative incidence: 17.0%-29.1%) and was able to exclude 89.6%-91.5% of patients whose incidence of HBsAg loss is 0. Moreover, the GOLDEN model consistently showed excellent performance among various subgroups. CONCLUSION: The novel GOLDEN model, based on longitudinal qHBsAg data, accurately predicts HBsAg clearance, provides reliable estimates of functional hepatitis B virus (HBV) cure and may have the potential to stratify different subsets of patients for novel anti-HBV therapies.
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Trichoderma is an excellent biocontrol agent, but most Trichoderma genomes remained at the scaffold level, which greatly limits the research of biocontrol mechanism. Here, we reported the chromosome-level genome of Trichoderma harzianum CGMCC20739 (Tha739), T. asperellum CGMCC11653 (Tas653) and T. atroviride CGMCC40488 (Tat488), they were assembled into 7 chromosomes, genome size were 40 Mb (10,611 genes), 37.3 Mb (10,102 genes) and 36.3 Mb (9,896 genes), respectively. The positive selected genes of three strains were associated to response to stimulus, signaling transduction, immune system and localization. Furthermore, the number of transcription factors in Tha739, Tas653 and Tat488 strains had significant difference, which may contribute to the differential biocontrol function and stress tolerance. The genes related to signal transduction and gene clusters related to antimicrobial compounds in Tha739 were more than those in Tas653 and Tat488, which showed Tha739 may keenly sense other fungi and quickly secret antimicrobial compounds to inhibit other fungi. Tha739 also contained more genes associated to detoxification, antioxidant and nutrition utilization, indicating it had higher stress-tolerance to hostile environments. And the substrate for synthesizing IAA in Tha739 was mainly 3-indole acetonitrile and indole acetaldehyde, but in Tat488, it was indole-3-acetamide, moreover, Tha739 secreted more phosphatase and phytase and was more related to soil phosphorus metabolism, Tat488 secreted more urease and was more related to soil nitrogen metabolism. These candidate genes related to biocontrol function and stress-tolerance laid foundations for construction of functional strains. All above proved the difference in biocontrol function of Tha739, Tas653 and Tat488 strains, however, the defects in individual strains could be compensated for through Trichoderma-biome during the commercial application process of biocontrol Trichoderma strains.
Subject(s)
Genome, Fungal , Trichoderma , Genome, Fungal/genetics , Trichoderma/genetics , Transcription Factors/genetics , Fungal Proteins/genetics , Fungal Proteins/metabolism , Multigene Family/genetics , Hypocreales/geneticsABSTRACT
PURPOSE: Positron emission tomography/magnetic resonance imaging (PET/MRI) is a powerful tool for brain imaging, but the spatial resolution of the PET scanners currently used for brain imaging can be further improved to enhance the quantitative accuracy of brain PET imaging. The purpose of this study is to develop an MR-compatible brain PET scanner that can simultaneously achieve a uniform high spatial resolution and high sensitivity by using dual-ended readout depth encoding detectors. METHODS: The MR-compatible brain PET scanner, named SIAT bPET, consists of 224 dual-ended readout detectors. Each detector contains a 26 × 26 lutetium yttrium oxyorthosilicate (LYSO) crystal array of 1.4 × 1.4 × 20 mm3 crystal size read out by two 10 × 10 silicon photomultiplier (SiPM) arrays from both ends. The scanner has a detector ring diameter of 376.8 mm and an axial field of view (FOV) of 329 mm. The performance of the scanner including spatial resolution, sensitivity, count rate, scatter fraction, and image quality was measured. Imaging studies of phantoms and the brain of a volunteer were performed. The mutual interferences of the PET insert and the uMR790 3 T MRI scanner were measured, and simultaneous PET/MRI imaging of the brain of a volunteer was performed. RESULTS: A spatial resolution of better than 1.5 mm with an average of 1.2 mm within the whole FOV was obtained. A sensitivity of 11.0% was achieved at the center FOV for an energy window of 350-750 keV. Except for the dedicated RF coil, which caused a ~ 30% reduction of the sensitivity of the PET scanner, the MRI sequences running had a negligible effect on the performance of the PET scanner. The reduction of the SNR and homogeneity of the MRI images was less than 2% as the PET scanner was inserted to the MRI scanner and powered-on. High quality PET and MRI images of a human brain were obtained from simultaneous PET/MRI scans. CONCLUSION: The SIAT bPET scanner achieved a spatial resolution and sensitivity better than all MR-compatible brain PET scanners developed up to date. It can be used either as a standalone brain PET scanner or a PET insert placed inside a commercial whole-body MRI scanner to perform simultaneous PET/MRI imaging.
Subject(s)
Magnetic Resonance Imaging , Positron-Emission Tomography , Humans , Equipment Design , Positron-Emission Tomography/methods , Phantoms, Imaging , Brain/diagnostic imagingABSTRACT
BACKGROUND AND AIMS: Porto-sinusoidal vascular disease (PSVD) is an under-recognized and under-diagnosed disease. The purpose of this study was to investigate the clinical features and prognosis of PSVD. METHODS: The patients who underwent liver biopsies were analyzed retrospectively. The clinical and pathological data were reviewed and screened according to the latest diagnostic criteria of PSVD. RESULTS: A total of 234 patients were diagnosed as PSVD, including 103 patients presented with portal hypertension (PH) and 131 patients without PH. At baseline, the alanine aminotransferase (ALT) and γ-glutamyl transpeptidase (GGT) levels were higher in the no-PH group. The liver stiffness increased in the PH group. In histological review, obliterative portal venopathy, sinusoidal dilatation and architectural disturbance were more common in the PH group, while portal tract abnormalities were more widely distributed in the no-PH group. After a median follow-up of 43.6 months, the survival rate of patients with baseline liver decompensation was 76.0%, and that of patients at a liver compensated stage in the PH group was 98.7%. First variceal bleeding occurred in 13.8% of patients with gastric-oesophageal varices. None of the patients in the no-PH group developed portal hypertension during follow-up. CONCLUSIONS: PSVD can manifest as PH or mild liver enzyme abnormalities. There are significant differences in pathological features among patients with different clinical manifestations. Recurrent ascites are the main cause of death in PSVD patients. However, patients without PH have a slow disease progression, with recurrent elevated GGT levels being their main clinical feature.
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BACKGROUND AND AIMS: The International AIH Pathology Group (IAIH-PG) put forward the new histological criteria of autoimmune hepatitis (AIH) in 2022, which have not undergone adequate verification. In this study, we verified the applicability of the new histological criteria in the population of Chinese patients with chronic liver disease, comparing it with the simplified criteria. METHODS: The gold standard for diagnosis in all patients was based on histological findings, combined with clinical manifestations and laboratory tests and determined after a follow-up period of at least 3 years. A total of 640 patients with various chronic liver diseases from multiple centres underwent scoring using the new histological criteria and the simplified criteria, comparing their diagnostic performance. RESULTS: In this study, the new histological criteria showed a sensitivity of 73.6% and 100% for likely and possible AIH, with specificities of 100% and 69.0% respectively. The coincidence rates of possible AIH for the new histological criteria, simplified histological criteria and simplified score were 81.7%, 72.8% and 69.7% respectively. For likely AIH, the rates were 89.2%, 75.9% and 65.6% respectively. Based on the new histological criteria, all patients with AIH were correctly diagnosed. Specifically, 73.6% were diagnosed with likely AIH and 26.4% were possible AIH. Additionally, the simplified histological criteria achieved a diagnosis rate of 98.6% for AIH, while the simplified score could only diagnose 53.8% of AIH. CONCLUSIONS: Compared with the simplified score and simplified histological criteria, the sensitivity and specificity of the new histological criteria for AIH were significantly improved. The results indicate that the new histological criteria exhibit high sensitivity and specificity for diagnosing AIH in China.
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PURPOSE: To evaluate the diagnostic performance of contrast-enhanced (CE) ultrasound using Sonazoid (SNZ-CEUS) by comparing with contrast-enhanced computed tomography (CE-CT) and contrast-enhanced magnetic resonance imaging (CE-MRI) for differentiating benign and malignant renal masses. MATERIALS AND METHODS: 306 consecutive patients (from 7 centers) with renal masses (40 benign tumors, 266 malignant tumors) diagnosed by both SNZ-CEUS, CE-CT or CE-MRI were enrolled between September 2020 and February 2021. The examinations were performed within 7 days, but the sequence was not fixed. Histologic results were available for 301 of 306 (98.37%) lesions and 5 lesions were considered benign after at least 2 year follow-up without change in size and image characteristics. The diagnostic performances were evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and compared by McNemar's test. RESULTS: In the head-to-head comparison, SNZ-CEUS and CE-MRI had comparable sensitivity (95.60 vs. 94.51%, P = 0.997), specificity (65.22 vs. 73.91%, P = 0.752), positive predictive value (91.58 vs. 93.48%) and negative predictive value (78.95 vs. 77.27%); SNZ-CEUS and CE-CT showed similar sensitivity (97.31 vs. 96.24%, P = 0.724); however, SNZ-CEUS had relatively lower than specificity than CE-CT (59.09 vs. 68.18%, P = 0.683). For nodules > 4 cm, CE-MRI demonstrated higher specificity than SNZ-CEUS (90.91 vs. 72.73%, P = 0.617) without compromise the sensitivity. CONCLUSIONS: SNZ-CEUS, CE-CT, and CE-MRI demonstrate desirable and comparable sensitivity for the differentiation of renal mass. However, the specificity of all three imaging modalities is not satisfactory. SNZ-CEUS may be a suitable alternative modality for patients with renal dysfunction and those allergic to gadolinium or iodine-based agents.
Subject(s)
Contrast Media , Ferric Compounds , Iron , Kidney Neoplasms , Magnetic Resonance Imaging , Oxides , Tomography, X-Ray Computed , Ultrasonography , Humans , Kidney Neoplasms/diagnostic imaging , Kidney Neoplasms/pathology , Male , Female , Middle Aged , Prospective Studies , Ultrasonography/methods , Tomography, X-Ray Computed/methods , Magnetic Resonance Imaging/methods , Aged , Diagnosis, Differential , Adult , Aged, 80 and overABSTRACT
OBJECTIVES: Total-body PET/CT scanners with long axial fields of view have enabled unprecedented image quality and quantitative accuracy. However, the ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Therefore, we attempted to generate CT-free attenuation-corrected (CTF-AC) total-body PET images through deep learning. METHODS: Based on total-body PET data from 122 subjects (29 females and 93 males), a well-established cycle-consistent generative adversarial network (Cycle-GAN) was employed to generate CTF-AC total-body PET images directly while introducing site structures as prior information. Statistical analyses, including Pearson correlation coefficient (PCC) and t-tests, were utilized for the correlation measurements. RESULTS: The generated CTF-AC total-body PET images closely resembled real AC PET images, showing reduced noise and good contrast in different tissue structures. The obtained peak signal-to-noise ratio and structural similarity index measure values were 36.92 ± 5.49 dB (p < 0.01) and 0.980 ± 0.041 (p < 0.01), respectively. Furthermore, the standardized uptake value (SUV) distribution was consistent with that of real AC PET images. CONCLUSION: Our approach could directly generate CTF-AC total-body PET images, greatly reducing the radiation risk to patients from redundant anatomical examinations. Moreover, the model was validated based on a multidose-level NAC-AC PET dataset, demonstrating the potential of our method for low-dose PET attenuation correction. In future work, we will attempt to validate the proposed method with total-body PET/CT systems in more clinical practices. CLINICAL RELEVANCE STATEMENT: The ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Our CT-free PET attenuation correction method would be beneficial for a wide range of patient populations, especially for pediatric examinations and patients who need multiple scans or who require long-term follow-up. KEY POINTS: ⢠CT is the main source of radiation in PET/CT imaging, especially for total-body PET/CT devices, and reduced radiopharmaceutical doses make the radiation burden from CT more obvious. ⢠The CT-free PET attenuation correction method would be beneficial for patients who need multiple scans or long-term follow-up by reducing additional radiation from redundant anatomical examinations. ⢠The proposed method could directly generate CT-free attenuation-corrected (CTF-AC) total-body PET images, which is beneficial for PET/MRI or PET-only devices lacking CT image poses.
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BACKGROUND AND AIMS: There is no golden standard for the diagnosis of autoimmune hepatitis which still dependent on liver biopsy currently. So, we developed a noninvasive prediction model to help optimize the diagnosis of autoimmune hepatitis. METHODS: From January 2017 to December 2019, 1739 patients who had undergone liver biopsy were seen in the second hospital of Nanjing, of which 128 were here for consultation. Clinical, laboratory, and histologic data were obtained retrospectively. Multivariable logistic regression analysis was employed to create a nomogram model that predicting the risk of autoimmune hepatitis. Internal and external validation was both performed to evaluate the model. RESULTS: A total of 1288 patients with liver biopsy were enrolled (1184 from the second hospital of Nanjing, the remaining 104 from other centers). After the univariate and multivariate logistic regression analysis, nine variables including ALT, IgG, ALP/AST, ALB, ANA, AMA, HBsAg, age, and gender were selected to establish the noninvasive prediction model. The nomogram model exhibits good prediction in diagnosing autoimmune hepatitis with AUROC of 0.967 (95% CI: 0.776-0.891) in internal validation and 0.835 (95% CI: 0.752-0.919) in external validation. CONCLUSIONS: ALT, IgG, ALP/AST, ALB, ANA, AMA, HBsAg, age, and gender are predictive factors for the diagnosis of autoimmune hepatitis in patients with unexplained liver diseases. The predictive nomogram model built by the nine predictors achieved good prediction for diagnosing autoimmune hepatitis.
Subject(s)
Hepatitis, Autoimmune , Humans , Hepatitis, Autoimmune/complications , Hepatitis, Autoimmune/diagnosis , Retrospective Studies , Hepatitis B Surface Antigens , Nomograms , Immunoglobulin GABSTRACT
Alzheimer's disease can be detected early through biomarkers such as tau positron emission tomography (PET) imaging, which shows abnormal protein accumulations in the brain. The standardized uptake value ratio (SUVR) is often used to quantify tau-PET imaging, but topological information from multiple brain regions is also linked to tau pathology. Here a new method was developed to investigate the correlations between brain regions using subject-level tau networks. Participants with cognitive normal (74), early mild cognitive impairment (35), late mild cognitive impairment (32), and Alzheimer's disease (40) were included. The abnormality network from each scan was constructed to extract topological features, and 7 functional clusters were further analyzed for connectivity strengths. Results showed that the proposed method performed better than conventional SUVR measures for disease staging and prodromal sign detection. For example, when to differ healthy subjects with and without amyloid deposition, topological biomarker is significant with P < 0.01, SUVR is not with P > 0.05. Functionally significant clusters, i.e. medial temporal lobe, default mode network, and visual-related regions, were identified as critical hubs vulnerable to early disease conversion before mild cognitive impairment. These findings were replicated in an independent data cohort, demonstrating the potential to monitor the early sign and progression of Alzheimer's disease from a topological perspective for individual.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Humans , Alzheimer Disease/pathology , tau Proteins/metabolism , Amyloid beta-Peptides/metabolism , Cognitive Dysfunction/pathology , Brain/pathology , Biomarkers , Positron-Emission Tomography/methodsABSTRACT
Difficulties in parsing the multiaspect heterogeneity of schizophrenia (SCZ) based on current nosology highlight the need to subtype SCZ using objective biomarkers. Here, utilizing a large-scale multisite SCZ dataset, we identified and validated 2 neuroanatomical subtypes with individual-level abnormal patterns of the tensor-based morphometric measurement. Remarkably, compared with subtype 1, which showed moderate deficits of some subcortical nuclei and an enlarged striatum and cerebellum, subtype 2, which showed cerebellar atrophy and more severe subcortical nuclei atrophy, had a higher subscale score of negative symptoms, which is considered to be a core aspect of SCZ and is associated with functional outcome. Moreover, with the neuroimaging-clinic association analysis, we explored the detailed relationship between the heterogeneity of clinical symptoms and the heterogeneous abnormal neuroanatomical patterns with respect to the 2 subtypes. And the neuroimaging-transcription association analysis highlighted several potential heterogeneous biological factors that may underlie the subtypes. Our work provided an effective framework for investigating the heterogeneity of SCZ from multilevel aspects and may provide new insights for precision psychiatry.
Subject(s)
Magnetic Resonance Imaging , Schizophrenia , Humans , Magnetic Resonance Imaging/methods , Schizophrenia/diagnostic imaging , Neuroimaging , Cerebellum/diagnostic imaging , AtrophyABSTRACT
AIMS: Excess dietary sodium intake and retention lead to hypertension. Impaired dermal lymphangiogenesis and lymphatic dysfunction-mediated sodium and fluid imbalance are pathological mechanisms. The adenosine A2A receptor (A2AR) is expressed in lymphatic endothelial cells (LECs), while the roles and mechanisms of LEC-A2AR in skin lymphangiogenesis during salt-induced hypertension are not clear. METHODS AND RESULTS: The expression of LEC-A2AR correlated with lymphatic vessel density in both high-salt diet (HSD)-induced hypertensive mice and hypertensive patients. Lymphatic endothelial cell-specific A2AR knockout mice fed HSD exhibited 17 ± 2% increase in blood pressure and 17 ± 3% increase in Na+ content associated with decreased lymphatic density (-19 ± 2%) compared with HSD-WT mice. A2AR activation by agonist CGS21680 increased lymphatic capillary density and decreased blood pressure in HSD-WT mice. Furthermore, this A2AR agonist activated MSK1 directly to promote VEGFR2 activation and endocytosis independently of VEGF as assessed by phosphoprotein profiling and immunoprecipitation assays in LECs. VEGFR2 kinase activity inhibitor fruquintinib or VEGFR2 knockout in LECs but not VEGF-neutralizing antibody bevacizumab suppressed A2AR activation-mediated decrease in blood pressure. Immunostaining revealed phosphorylated VEGFR2 and MSK1 expression in the LECs were positively correlated with skin lymphatic vessel density and A2AR level in hypertensive patients. CONCLUSION: The study highlights a novel A2AR-mediated VEGF-independent activation of VEGFR2 signaling in dermal lymphangiogenesis and sodium balance, which might be a potential therapeutic target in salt-sensitive hypertension.
Subject(s)
Hypertension , Lymphangiogenesis , Mice , Animals , Receptor, Adenosine A2A/metabolism , Endothelial Cells/metabolism , Protein Kinase Inhibitors , Sodium/metabolismABSTRACT
BACKGROUND & AIMS: Current hepatocellular carcinoma (HCC) risk scores do not reflect changes in HCC risk resulting from liver disease progression/regression over time. We aimed to develop and validate two novel prediction models using multivariate longitudinal data, with or without cell-free DNA (cfDNA) signatures. METHODS: A total of 13,728 patients from two nationwide multicenter prospective observational cohorts, the majority of whom had chronic hepatitis B, were enrolled. aMAP score, as one of the most promising HCC prediction models, was evaluated for each patient. Low-pass whole-genome sequencing was used to derive multi-modal cfDNA fragmentomics features. A longitudinal discriminant analysis algorithm was used to model longitudinal profiles of patient biomarkers and estimate the risk of HCC development. RESULTS: We developed and externally validated two novel HCC prediction models with a greater accuracy, termed aMAP-2 and aMAP-2 Plus scores. The aMAP-2 score, calculated with longitudinal data on the aMAP score and alpha-fetoprotein values during an up to 8-year follow-up, performed superbly in the training and external validation cohorts (AUC 0.83-0.84). The aMAP-2 score showed further improvement and accurately divided aMAP-defined high-risk patients into two groups with 5-year cumulative HCC incidences of 23.4% and 4.1%, respectively (p = 0.0065). The aMAP-2 Plus score, which incorporates cfDNA signatures (nucleosome, fragment and motif scores), optimized the prediction of HCC development, especially for patients with cirrhosis (AUC 0.85-0.89). Importantly, the stepwise approach (aMAP -> aMAP-2 -> aMAP-2 Plus) stratified patients with cirrhosis into two groups, comprising 90% and 10% of the cohort, with an annual HCC incidence of 0.8% and 12.5%, respectively (p <0.0001). CONCLUSIONS: aMAP-2 and aMAP-2 Plus scores are highly accurate in predicting HCC. The stepwise application of aMAP scores provides an improved enrichment strategy, identifying patients at a high risk of HCC, which could effectively guide individualized HCC surveillance. IMPACT AND IMPLICATIONS: In this multicenter nationwide cohort study, we developed and externally validated two novel hepatocellular carcinoma (HCC) risk prediction models (called aMAP-2 and aMAP-2 Plus scores), using longitudinal discriminant analysis algorithm and longitudinal data (i.e., aMAP and alpha-fetoprotein) with or without the addition of cell-free DNA signatures, based on 13,728 patients from 61 centers across mainland China. Our findings demonstrated that the performance of aMAP-2 and aMAP-2 Plus scores was markedly better than the original aMAP score, and any other existing HCC risk scores across all subsets, especially for patients with cirrhosis. More importantly, the stepwise application of aMAP scores (aMAP -> aMAP-2 -> aMAP-2 Plus) provides an improved enrichment strategy, identifying patients at high risk of HCC, which could effectively guide individualized HCC surveillance.
Subject(s)
Carcinoma, Hepatocellular , Cell-Free Nucleic Acids , Hepatitis B, Chronic , Liver Neoplasms , Humans , Carcinoma, Hepatocellular/diagnosis , Carcinoma, Hepatocellular/epidemiology , Carcinoma, Hepatocellular/etiology , Liver Neoplasms/diagnosis , Liver Neoplasms/epidemiology , Liver Neoplasms/etiology , alpha-Fetoproteins , Cohort Studies , Liver Cirrhosis/diagnosis , Liver Cirrhosis/genetics , Liver Cirrhosis/complications , Hepatitis B, Chronic/complicationsABSTRACT
Immune dysregulation has been consistently reported in psychiatric disorders, however, the causes and mechanisms underlying immune dysregulation in psychiatric disorders remain largely unclear. Here we conduct a Mendelian randomization study by integrating plasma proteome and GWASs of schizophrenia, bipolar disorder and depression. The primate-specific immune-related protein BTN3A3 showed the most significant associations with all three psychiatric disorders. In addition, other immune-related proteins, including AIF1, FOXO3, IRF3, CFHR4, IGLON5, FKBP2, and PI3, also showed significant associations with psychiatric disorders. Our study showed that a proportion of psychiatric risk variants may contribute to disease risk by regulating immune-related plasma proteins, providing direct evidence that connect the genetic risk of psychiatric disorders to immune system.
Subject(s)
Bipolar Disorder , Mental Disorders , Animals , Proteome/genetics , Proteome/metabolism , Mendelian Randomization Analysis , Mental Disorders/genetics , Bipolar Disorder/genetics , Blood Proteins , Genome-Wide Association Study , Polymorphism, Single NucleotideABSTRACT
PURPOSE: The axial field of view (AFOV) of a positron emission tomography (PET) scanner greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) with a large AFOV is more sensitive, it is more expensive and difficult to widely use. Therefore, we attempt to utilize high-quality images generated by uEXPLORER to optimize the quality of images from short-axis PET scanners through deep learning technology while controlling costs. METHODS: The experiments were conducted using PET images of three anatomical locations (brain, lung, and abdomen) from 335 patients. To simulate PET images from different axes, two protocols were used to obtain PET image pairs (each patient was scanned once). For low-quality PET (LQ-PET) images with a 320-mm AFOV, we applied a 300-mm FOV for brain reconstruction and a 500-mm FOV for lung and abdomen reconstruction. For high-quality PET (HQ-PET) images, we applied a 1940-mm AFOV during the reconstruction process. A 3D Unet was utilized to learn the mapping relationship between LQ-PET and HQ-PET images. In addition, the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were employed to evaluate the model performance. Furthermore, two nuclear medicine doctors evaluated the image quality based on clinical readings. RESULTS: The generated PET images of the brain, lung, and abdomen were quantitatively and qualitatively compatible with the HQ-PET images. In particular, our method achieved PSNR values of 35.41 ± 5.45 dB (p < 0.05), 33.77 ± 6.18 dB (p < 0.05), and 38.58 ± 7.28 dB (p < 0.05) for the three beds. The overall mean SSIM was greater than 0.94 for all patients who underwent testing. Moreover, the total subjective quality levels of the generated PET images for three beds were 3.74 ± 0.74, 3.69 ± 0.81, and 3.42 ± 0.99 (the highest possible score was 5, and the minimum score was 1) from two experienced nuclear medicine experts. Additionally, we evaluated the distribution of quantitative standard uptake values (SUV) in the region of interest (ROI). Both the SUV distribution and the peaks of the profile show that our results are consistent with the HQ-PET images, proving the superiority of our approach. CONCLUSION: The findings demonstrate the potential of the proposed technique for improving the image quality of a PET scanner with a 320 mm or even shorter AFOV. Furthermore, this study explored the potential of utilizing uEXPLORER to achieve improved short-axis PET image quality at a limited economic cost, and computer-aided diagnosis systems that are related can help patients and radiologists.
Subject(s)
Deep Learning , Humans , Quality Improvement , Positron-Emission Tomography/methods , Brain , Phantoms, Imaging , Image Processing, Computer-Assisted/methodsABSTRACT
Glaucoma is often associated with elevated intraocular pressure (IOP), generally due to obstruction of aqueous humor outflow within the trabecular meshwork (TM). Despite many decades of research, the molecular cause of this obstruction remains elusive. To study IOP regulation, several in vitro models, such as perfusion of anterior segments or mechanical stretching of TM cells, have identified several IOP-responsive genes and proteins. While these studies have proved informative, they do not fully recapitulate the in vivo environment where IOP is subject to additional factors, such as circadian rhythms. Thus, rodent animal models are now commonly used to study IOP-responsive genes in vivo. Several single-cell RNAseq studies have been performed where angle tissue, containing cornea, iris, ciliary body tissue in addition to TM, is dissected. However, it is advantageous to physically separate TM from other tissues because the ratio of TM cells is relatively low compared to the other cell types. In this report, we describe a new technique for rat TM microdissection. Evaluating tissue post-dissection by histology and immunostaining clearly shows successful removal of the TM. In addition, TaqMan PCR primers targeting biomarkers of trabecular meshwork (Myoc, Mgp, Chi3l1) or ciliary body (Myh11, Des) genes showed little contamination of TM tissue by the ciliary body. Finally, pitfalls encountered during TM microdissection are discussed to enable others to successfully perform this microsurgical technique in the rat eye.
Subject(s)
Glaucoma , Trabecular Meshwork , Rats , Animals , Trabecular Meshwork/metabolism , Microdissection , Aqueous Humor/metabolism , Glaucoma/metabolism , Iris , Intraocular PressureABSTRACT
OBJECTIVES: PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric Ki provides better quantification and improve specificity for cancer detection. However, parametric imaging is difficult to implement clinically due to the long acquisition time (~ 1 h). We propose a dynamic parametric imaging method based on conventional static PET using deep learning. METHODS: Based on the imaging data of 203 participants, an improved cycle generative adversarial network incorporated with squeeze-and-excitation attention block was introduced to learn the potential mapping relationship between static PET and Ki parametric images. The image quality of the synthesized images was qualitatively and quantitatively evaluated by using several physical and clinical metrics. Statistical analysis of correlation and consistency was also performed on the synthetic images. RESULTS: Compared with those of other networks, the images synthesized by our proposed network exhibited superior performance in both qualitative and quantitative evaluation, statistical analysis, and clinical scoring. Our synthesized Ki images had significant correlation (Pearson correlation coefficient, 0.93), consistency, and excellent quantitative evaluation results with the Ki images obtained in standard dynamic PET practice. CONCLUSIONS: Our proposed deep learning method can be used to synthesize highly correlated and consistent dynamic parametric images obtained from static lung PET. KEY POINTS: ⢠Compared with conventional static PET, dynamic PET parametric Ki imaging has been shown to provide better quantification and improved specificity for cancer detection. ⢠The purpose of this work was to develop a dynamic parametric imaging method based on static PET images using deep learning. ⢠Our proposed network can synthesize highly correlated and consistent dynamic parametric images, providing an additional quantitative diagnostic reference for clinicians.