Spatial functional reorganizations can serve as potential biomarkers of post facial palsy synkinesis.

Facial palsy can result in a serious complication known as facial synkinesis, causing both physical and psychological harm to the patients. There is growing evidence that patients with facial synkinesis have brain abnormalities, but the brain mechanisms and underlying imaging biomarkers remain unclear. Here, we employed functional magnetic resonance imaging (fMRI) to investigate brain function in 31 unilateral post facial palsy synkinesis patients and 25 healthy controls during different facial expression movements and at rest. Combining surface-based mass-univariate analysis and multivariate pattern analysis, we identified diffused activation and intrinsic connection patterns in the primary motor cortex and the somatosensory cortex on the patient's affected side. Further, we classified post facial palsy synkinesis patients from healthy subjects with favorable accuracy using the support vector machine based on both task-related and resting-state functional magnetic resonance imaging data. Together, these findings indicate the potential of the identified functional reorganizations to serve as neuroimaging biomarkers for facial synkinesis diagnosis.

Predicting meningioma grades and pathologic marker expression via deep learning.

OBJECTIVES: To establish a deep learning (DL) model for predicting tumor grades and expression of pathologic markers of meningioma. METHODS: A total of 1192 meningioma patients from two centers who underwent surgical resection between September 2018 and December 2021 were retrospectively included. The pathological data and post-contrast T1-weight images for each patient were collected. The patients from institute I were subdivided into training, validation, and testing sets, while the patients from institute II served as the external testing cohort. The fine-tuned ResNet50 model based on transfer learning was adopted to classify WHO grade in the whole cohort and predict Ki-67 index, H3K27me3, and progesterone receptor (PR) status of grade 1 meningiomas. The predictive performance was evaluated by the accuracy and loss curve, confusion matrix, receiver operating characteristic curve (ROC), and area under curve (AUC). RESULTS: The DL prediction model for each label achieved high predictive performance in two cohorts. For WHO grade prediction, the area under the curve (AUC) was 0.966 (95%CI 0.957-0.975) in the internal testing set and 0.669 (95%CI 0.643-0.695) in the external validation cohort. The AUC in predicting Ki-67 index, H3K27me3, and PR status were 0.905 (95%CI 0.895-0.915), 0.773 (95%CI 0.760-0.786), and 0.771 (95%CI 0.750-0.792) in the internal testing set and 0.591 (95%CI 0.562-0.620), 0.658 (95%CI 0.648-0.668), and 0.703 (95%CI 0.674-0.732) in the external validation cohort, respectively. CONCLUSION: DL models can preoperatively predict meningioma grades and pathologic marker expression with favorable predictive performance. CLINICAL RELEVANCE STATEMENT: Our DL model could predict meningioma grades and expression of pathologic markers and identify high-risk patients with WHO grade 1 meningioma, which would suggest a more aggressive operative intervention preoperatively and a more frequent follow-up schedule postoperatively. KEY POINTS: WHO grades and some pathologic markers of meningioma were associated with therapeutic strategies and clinical outcomes. A deep learning-based approach was employed to develop a model for predicting meningioma grades and the expression of pathologic markers. Preoperative prediction of meningioma grades and the expression of pathologic markers was beneficial for clinical decision-making.

Treatment effects of low-frequency repetitive transcranial magnetic stimulation combined with motor relearning procedure on spasticity and limb motor function in stroke patients.

Objective: Limb paralysis, which is a sequela of stroke, limits patients' activities of daily living and lowers their quality of life. The purpose of this study was to investigate the effects of repetitive transcranial magnetic stimulation (rTMS) combined with a motor relearning procedure (MRP) on motor function and limb spasticity in stroke patients. Methods: Stroke patients were randomly divided into a combined treatment group (rTMS + MRP) and a control group (MRP) (n = 30 per group). The control group was given MRP in addition to conventional rehabilitation, and the combined treatment group was given 1 Hz rTMS combined with MRP. The treatment efficacy was assessed by the modified Ashworth scale (MAS), Fugl-Meyer motor function scale, and motor evoked potential (MEP) testing. Results: After 4 weeks of treatment, the Brunnstrom score, Fugl-Meyer lower extremity motor function, and Fugl-Meyer balance function were significantly higher in the combination treatment group compared to the control group, while the MAS score was lower in the combination treatment group compared to the control group. The MEP extraction rate was higher in the combined treatment group compared to the control group, while the threshold and central motor conduction time (CMCT) were lower in the combined treatment group compared to the control group. Conclusion: Low-frequency rTMS combined with MRP had better efficacy on spasticity and motor function in stroke patients with hemiparesis than MRP alone.

Quantitative assessment of articular cartilage degeneration using 3D ultrashort echo time cones adiabatic T1ρ (3D UTE-Cones-AdiabT1ρ) imaging.

OBJECTIVES: To evaluate articular cartilage degeneration using quantitative three-dimensional ultrashort-echo-time cones adiabatic-T1ρ (3D UTE-Cones-AdiabT1ρ) imaging. METHODS: Sixty-six human subjects were recruited for this study. Kellgren-Lawrence (KL) grade and Whole-Organ Magnetic-Resonance-Imaging Score (WORMS) were evaluated by two musculoskeletal radiologists. The human subjects were categorized into three groups, namely normal controls (KL0), doubtful-minimal osteoarthritis (OA) (KL1-2), and moderate-severe OA (KL3-4). WORMS were regrouped to encompass the extent of lesions and the depth of lesions. The UTE-Cones-AdiabT1ρ values were obtained using 3D UTE-Cones data acquisitions preceded by seven paired adiabatic full passage pulses that corresponded to seven spin-locking times (TSLs) of 0, 12, 24, 36, 48, 72, and 96 ms. The performance of the UTE-Cones-AdiabT1ρ technique in evaluating the degeneration of knee cartilage was assessed via the ANOVA comparisons with subregional analysis and Spearman's correlation coefficient as well as the receiver-operating-characteristic (ROC) curve. RESULTS: UTE-Cones-AdiabT1ρ showed significant positive correlations with KL grade (r = 0.15, p < 0.05) and WORMS (r = 0.57, p < 0.05). Higher UTE-Cones-AdiabT1ρ values were observed in both larger and deeper lesions in the cartilage. The differences in UTE-Cones-AdiabT1ρ values among different extent and depth groups of cartilage lesions were all statistically significant (p < 0.05). Subregional analyses showed that the correlations between UTE-Cones-AdiabT1ρ and WORMS varied with the location of cartilage. The AUC value of UTE-Cones-AdiabT1ρ for mild cartilage degeneration (WORMS=1) was 0.8. The diagnostic threshold value of UTE-Cones-AdiabT1ρ for mild cartilage degeneration was 39.4 ms with 80.8% sensitivity. CONCLUSIONS: The 3D UTE-Cones-AdiabT1ρ sequence can be useful in quantitative evaluation of articular cartilage degeneration. KEY POINTS: • The 3D UTE-Cones-AdiabT1ρ sequence can distinguish mild cartilage degeneration from normal cartilage with a diagnostic threshold value of 39.4 ms for mild cartilage degeneration with 80.8% sensitivity. • Higher UTE-Cones-AdiabT1ρ values were observed in both larger and deeper lesions in the articular cartilage. • UTE-Cones-AdiabT1ρ is a promising biomarker for quantitative evaluation of early cartilage degeneration.

Quantitative 3D Ultrashort Echo Time Magnetization Transfer Imaging for Evaluation of Knee Cartilage Degeneration In Vivo.

BACKGROUND: Recent studies suggest that macromolecular fraction (MMF) derived from three-dimensional ultrashort echo time magnetization transfer (UTE-MT) imaging is insensitive to the magic angle effect. However, its clinical use in osteoarthritis (OA) remains to be investigated. PURPOSE: To investigate the feasibility of 3D UTE-MT-derived MMF in differentiating normal from degenerated cartilage. STUDY TYPE: Prospective. SUBJECTS: Sixty-two participants (54.8 ± 16.7 years, 30 females) with and without OA, plus two healthy volunteers (mean age 35.0 years) for reproducibility test. FIELD STRENGTH/SEQUENCE: 3 T/UTE-MT sequence. ASSESSMENT: A 3D UTE-MT sequence was employed to calculate MMF based on a two-pool model. Kellgren-Lawrence (KL) grade and Whole-Organ Magnetic Resonance Imaging Score (WORMS) were evaluated by three experienced musculoskeletal radiologists. KL grade was condensed into three groups: KL0, KL1-2, and KL3-4. WORMS was regrouped based on extent of lesion (extent group) and depth of lesion (depth group), respectively. The performance of MMF at evaluating the degeneration of cartilage was assessed via Spearman's correlation coefficient and the area under the curve (AUC) calculated according to the receiver-operating characteristic curve. STATISTICAL TESTS: After normality check, one-way analysis of variance was used to evaluate the performance. Tukey-Kramer test was performed for post hoc testing. RESULTS: MMF showed significant negative correlations with KL grade (r = -0.53, P < 0.05) and WORMS (r = -0.49, P < 0.05). Significantly lower MMFs were found in subjects with greater KL grade (11.8 ± 0.8% for KL0; 10.9 ± 0.9% for KL1-2; 10.6 ± 1.1% for KL3-4; P < 0.05) and in cartilage with greater extent (12.1 ± 1.6% for normal cartilage; 10.9 ± 1.6% for regional lesions; 9.6 ± 1.7% for diffuse lesions; P < 0.05) and depth (12.1 ± 1.6% for normal cartilage; 10.6 ± 1.6% for partial-thickness lesions; 8.8 ± 1.7% for full-thickness lesions; P < 0.05) of lesions. AUC values of MMF for doubtful-minimal OA (KL1-2) and mild cartilage degradation (WORMS1-2) were 0.8 and 0.7, respectively. DATA CONCLUSION: This study highlights the clinical potential of MMF in the detection of early OA. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Automated cartilage segmentation and quantification using 3D ultrashort echo time (UTE) cones MR imaging with deep convolutional neural networks.

OBJECTIVE: To develop a fully automated full-thickness cartilage segmentation and mapping of T1, T1ρ, and T2*, as well as macromolecular fraction (MMF) by combining a series of quantitative 3D ultrashort echo time (UTE) cones MR imaging with a transfer learning-based U-Net convolutional neural networks (CNN) model. METHODS: Sixty-five participants (20 normal, 29 doubtful-minimal osteoarthritis (OA), and 16 moderate-severe OA) were scanned using 3D UTE cones T1 (Cones-T1), adiabatic T1ρ (Cones-AdiabT1ρ), T2* (Cones-T2*), and magnetization transfer (Cones-MT) sequences at 3 T. Manual segmentation was performed by two experienced radiologists, and automatic segmentation was completed using the proposed U-Net CNN model. The accuracy of cartilage segmentation was evaluated using the Dice score and volumetric overlap error (VOE). Pearson correlation coefficient and intraclass correlation coefficient (ICC) were calculated to evaluate the consistency of quantitative MR parameters extracted from automatic and manual segmentations. UTE biomarkers were compared among different subject groups using one-way ANOVA. RESULTS: The U-Net CNN model provided reliable cartilage segmentation with a mean Dice score of 0.82 and a mean VOE of 29.86%. The consistency of Cones-T1, Cones-AdiabT1ρ, Cones-T2*, and MMF calculated using automatic and manual segmentations ranged from 0.91 to 0.99 for Pearson correlation coefficients, and from 0.91 to 0.96 for ICCs, respectively. Significant increases in Cones-T1, Cones-AdiabT1ρ, and Cones-T2* (p < 0.05) and a decrease in MMF (p < 0.001) were observed in doubtful-minimal OA and/or moderate-severe OA over normal controls. CONCLUSION: Quantitative 3D UTE cones MR imaging combined with the proposed U-Net CNN model allows a fully automated comprehensive assessment of articular cartilage. KEY POINTS: • 3D UTE cones imaging combined with U-Net CNN model was able to provide fully automated cartilage segmentation. • UTE parameters obtained from automatic segmentation were able to reliably provide a quantitative assessment of cartilage.

Localization of myocardial infarction with multi-lead ECG based on DenseNet.

BACKGROUND AND OBJECTIVE: Myocardial infarction (MI) is a critical acute ischemic heart disease, which can be early diagnosed by electrocardiogram (ECG). However, the most research of MI localization pay more attention on the specific changes in every ECG lead independent. In our study, the research envisages the development of a novel multi-lead MI localization approach based on the densely connected convolutional network (DenseNet). METHODS: Considering the correlation of the multi-lead ECG, the method using parallel 12-lead ECG, systematically exploited the correlation of the inter-lead signals. In addition, the dense connection of DenseNet enhanced the reuse of the feature information between the inter-lead and intra-lead signals. The proposed method automatically captured the effective pathological features, which improved the identification of MI. RESULTS: The experimental results based on PTB diagnostic ECG database showed that the accuracy, sensitivity and specificity of the proposed method was 99.87%, 99.84% and 99.98% for 11 types of MI localization. CONCLUSIONS: The proposed method has achieved superior results compared to other localization methods, which can be introduced into the clinical practice to assist the diagnosis of MI.

Myelin Imaging in Human Brain Using a Short Repetition Time Adiabatic Inversion Recovery Prepared Ultrashort Echo Time (STAIR-UTE) MRI Sequence in Multiple Sclerosis.

Background Water signal contamination is a major challenge for direct ultrashort echo time (UTE) imaging of myelin in vivo because water contributes most of the signals detected in white matter. Purpose To validate a new short repetition time (TR) adiabatic inversion recovery (STAIR) prepared UTE (STAIR-UTE) sequence designed to suppress water signals and to allow imaging of ultrashort T2 protons of myelin in white matter using a clinical 3-T scanner. Materials and Methods In this prospective study, an optimization framework was used to obtain the optimal inversion time for nulling water signals using STAIR-UTE imaging at different TRs. Numeric simulation and phantom studies were performed. Healthy volunteers and participants with multiple sclerosis (MS) underwent MRI between November 2018 and October 2019 to compare STAIR-UTE and a clinical T2-weighted fluid-attenuated inversion recovery sequence for assessment of MS lesions. UTE measures of myelin were also performed to allow comparison of signals in lesions and with those in normal-appearing white matter (NAWM) in patients with MS and in normal white matter (NWM) in healthy volunteers. Results Simulation and phantom studies both suggest that the proposed STAIR-UTE technique can effectively suppress long T2 tissues with a broad range of T1s. Ten healthy volunteers (mean age, 33 years ± 8 [standard deviation]; six women) and 10 patients with MS (mean age, 51 years ± 16; seven women) were evaluated. The three-dimensional STAIR-UTE sequence effectively suppressed water components in white matter and selectively imaged myelin, which had a measured T2* value of 0.21 msec ± 0.04 in the volunteer study. A much lower mean UTE measure of myelin proton density was found in MS lesions (3.8 mol/L ± 1.5), and a slightly lower mean UTE measure was found in NAWM (7.2 mol/L ± 0.8) compared with that in NWM (8.0 mol/L ± 0.8) in the healthy volunteers (P < .001 for both comparisons). Conclusion The short repetition time adiabatic inversion recovery-prepared ultrashort echo time sequence provided efficient water signal suppression for volumetric imaging of myelin in the brain and showed excellent myelin signal contrast as well as marked ultrashort echo time signal reduction in multiple sclerosis lesions and a smaller reduction in normal-appearing white matter compared with normal white matter in volunteers. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Messina and Port in this issue.

Volumetric imaging of myelin in vivo using 3D inversion recovery-prepared ultrashort echo time cones magnetic resonance imaging.

Direct myelin imaging is promising for characterization of multiple sclerosis (MS) brains at diagnosis and in response to therapy. In this study, a 3D inversion recovery-prepared ultrashort echo time cones (IR-UTE-Cones) sequence was used for both morphological and quantitative imaging of myelin on a clinical 3 T scanner. Myelin powder phantoms with different myelin concentrations were imaged with the 3D UTE-Cones sequence and it showed a strong correlation between concentrations and UTE-Cones signals, demonstrating the ability of the UTE-Cones sequence to directly image myelin in the brain. Quantitative myelin imaging with multi-echo IR-UTE-Cones sequences show similar T2 * values for a D2 O-exchanged myelin phantom (T2 * = 0.33 ± 0.04 ms), ex vivo brain specimens (T2 * = 0.20 ± 0.04 ms) and in vivo healthy volunteers (T2 * = 0.254 ± 0.023 ms), further confirming the feasibility of 3D IR-UTE-Cones sequences for direct myelin imaging in vivo. In ex vivo MS brain study, signal loss is observed in MS lesions, which was confirmed with histology. For the in vivo study, the lesions in MS patients also show myelin signal loss using the proposed direct myelin imaging method, demonstrating the clinical potential for MS diagnosis. Furthermore, the measured IR-UTE-Cones signal intensities show a significant difference between normal-appearing white matter in MS patients and normal white matter in volunteers, which cannot be found in clinical used T2 -FLAIR sequences. Thus, the proposed 3D IR-UTE-Cones sequence showed clinical potential for MS diagnosis with the capability of direct myelin detection of the whole brain.

[Detection of inferior myocardial infarction based on densely connected convolutional neural network].

Inferior myocardial infarction is an acute ischemic heart disease with high mortality, which is easy to induce life-threatening complications such as arrhythmia, heart failure and cardiogenic shock. Therefore, it is of great clinical value to carry out accurate and efficient early diagnosis of inferior myocardial infarction. Electrocardiogram is the most sensitive means for early diagnosis of inferior myocardial infarction. This paper proposes a method for detecting inferior myocardial infarction based on densely connected convolutional neural network. The method uses the original electrocardiogram (ECG) signals of serially connected Ⅱ, Ⅲ and aVF leads as the input of the model and extracts the robust features of the ECG signals by using the scale invariance of the convolutional layers. The characteristic transmission of ECG signals is enhanced by the dense connectivity between different layers, so that the network can automatically learn the effective features with strong robustness and high recognition, so as to achieve accurate detection of inferior myocardial infarction. The Physikalisch Technische Bundesanstalt diagnosis public ECG database was used for verification. The accuracy, sensitivity and specificity of the model reached 99.95%, 100% and 99.90%, respectively. The accuracy, sensitivity and specificity of the model are also over 99% even though the noise exists. Based on the results of this study, it is expected that the method can be introduced in the clinical environment to help doctors quickly diagnose inferior myocardial infarction in the future.

Overexpression of GBP1 predicts poor prognosis and promotes tumor growth in human glioblastoma multiforme.

OBJECTIVE: Guanylate binding protein-1 (GBP1) is highly associated with cell proliferation, and can modulate growth and invasiveness of gliomas. The relationship between GBP1 expression and the prognosis of glioma patients is further evaluated for the purpose of investigating whether GBP1 can serve as an predictor for evaluating prognosis of glioma patients. METHODS: GBP1 expression in 528 glioblastoma multiforme (GBM) patients of The Cancer Genome Atlas (TCGA) database were investigated, then 103 surgical specimens from glioma patients in our center were further evaluated. The effect of GBP1 on proliferation, invasion and migration of glioma cells in vitro was analyzed, and the effects of GBP1 on sensitivity of radiotherapy and chemotherapy on glioma cells in vitro were also analyzed. GBP1 associated signaling pathways were identified with Gene Set Enrichment Analysis (GSEA). Besides, the effect of GBP1 expression on proliferation of glioma cells in vivo was analyzed. RESULTS: In both TCGA database and our clinical data, GBM tissues exhibited increased mRNA expression of GBP1 gene, its expression level was co-related to PETN deletion and EGFR amplification, and was associated with prognosis of GBM patients. GBP1 overexpression can enhance migration and invasion ability of tumor cells in vitro, and in vivo studies showed that GBP1 can promote tumor proliferation, decrease survival in tumor-bearing mice. GSEA analysis predicted that GBP1 may play its biological roles via toll-like receptor pathway. CONCLUSION: This study provides new insights and evidences that high level expression of GBP1 is significantly correlated with progression and prognosis in GBMs. Furthermore, transfection of GBP1 revealed its regulation on migration and invasiveness of glioma cells, decreasing sensitivity of chemotherapeutic agent, shortening survival of tumor-bearing animals. These data demonstrate that GBP1 may serve as a novel prognostic biomarker and a potential therapeutic target for gliomas.

Prognostic value of NUSAP1 in progression and expansion of glioblastoma multiforme.

Nucleolar and spindle-associated protein (NUSAP1) is a microtubule and chromatin-binding protein that stabilizes microtubules to prevent depolymerization, maintains spindle integrity. NUSAP1 could cross-link spindles into aster-like structures, networks and fibers. It has also been found to play roles in progression of several cancers. However, the potential correlation between NUSAP1 and clinical outcome in patients with glioblastoma multiforme (GBM) remains largely unknown. In the current study, we demonstrated that NUSAP1 was significantly up-regulated in GBM tissues compared with adult non-tumor brain tissues both in a validated cohort and a TCGA cohort. In addition, Kaplan-Meier analysis indicated that patients with high NUSAP1 expression had significantly lower OS (P = 0.0027). Additionally, in the TCGA cohort, NUSAP1 expression was relatively lower in GBM patients within the neural and mesenchymal subtypes compared to other subtypes, and associated with the status of several genetic aberrations such as PTEN deletion and wild type IDH1. The present study provides new insights and evidence that NUSAP1 over-expression was significantly correlated with progression and prognosis of GBM. Furthermore, knockdown of NUSAP1 revealed its regulation on G2/M progression and cell proliferation (both in vitro and in vivo). These data demonstrate that NUSAP1 could serve as a novel prognostic biomarker and a potential therapeutic target for GBM.

Human glioma stem-like cells induce malignant transformation of bone marrow mesenchymal stem cells by activating TERT expression.

We investigated whether glioma stem-like cells (GSCs) malignantly transformed bone marrow mesenchymal stem cells (tBMSCs) in the tumor microenvironment. Transplantation of enhanced green fluorescence protein (EGFP)-labeled BMSCs into irradiated athymic nude mice was followed by intracranial injection of red fluorescent protein-expressing glioma stem-like cells (SU3-RFP-GSCs). Singly cloned EGFP-BMSCs, harvested from the intracranial tumors showed TERT overexpression, high proliferation, colony formation and invasiveness in Transwell matrigel assays. Transfection of normal BMSCs with TERT (TERT-BMSCs) enhanced proliferation, colony formation and invasiveness, though these characteristics remained lower than in tBMSCs. The tBMSCs and TERT-BMSCs showed high surface expression of CD44, CD105, CD29 and CD90 and an absence of CD31, CD34, CD45, and CD11b, as in normal BMSCs. Alizarin red S and oil red O staining confirmed tBMSCs and TERT-BMSCs transdifferentiated into osteocytes and adipocytes, respectively. When normal BMSCs were indirectly co-cultured in medium from SU3-RFP-GSCs, they exhibited increased growth and proliferation, suggesting paracrine factors from GSCs induced their malignant transformation. Tumorigenicity assays in athymic nude mice showed that transplanted tBMSCs and TERT-BMSCs generated 100% and 20% subcutaneous tumors, respectively, while normal BMSCs generated no tumors. GSCs thus induce malignant transformation of BMSCs by activating TERT expression in BMSCs.

A preliminary examination of the diagnostic value of deep learning in hip osteoarthritis.

Hip Osteoarthritis (OA) is a common disease among the middle-aged and elderly people. Conventionally, hip OA is diagnosed by manually assessing X-ray images. This study took the hip joint as the object of observation and explored the diagnostic value of deep learning in hip osteoarthritis. A deep convolutional neural network (CNN) was trained and tested on 420 hip X-ray images to automatically diagnose hip OA. This CNN model achieved a balance of high sensitivity of 95.0% and high specificity of 90.7%, as well as an accuracy of 92.8% compared to the chief physicians. The CNN model performance is comparable to an attending physician with 10 years of experience. The results of this study indicate that deep learning has promising potential in the field of intelligent medical image diagnosis practice.

Incidence and risk factors for myelofibrotic transformation among 272 Chinese patients with JAK2-mutated polycythemia vera.

Post-polycythemia vera myelofibrosis (post-PV MF) is a critical hematologic evolution of polycythemia vera (PV). The main purpose of the present study was to identify the possible risk factors for the occurrence and prognosis of post-PV MF in Chinese patients with PV. A cohort of 272 Chinese PV patients with JAK2(V617F) or exon12 mutation was retrospectively analyzed. Of the 272 patients with PV, 63 developed post-PV MF. Platelet count >550 × 10(9) /L and splenomegaly were identified as independent risk factors for post-PV MF. The median duration of survival for post-PV MF patients was 8 years. Anemia and age >65 years at diagnosis of post-PV MF were identified as significant predictors for the poor prognosis of post-PV MF. In conclusion, platelet counts and splenomegaly were significant predictors for the transformation to post-PV MF, while anemia (hemoglobin levels <100 g/L) and age>65 years were significant predictors for poor prognosis of post-PV MF in Chinese PV patients with JAK2(V617F) or exon12 mutation.

[Survival and prognosis of patients with polycythemia vera: a study of 816 patients in a single Chinese center].

OBJECTIVE: To explore the survival and the risk factors of poor prognosis in Chinese patients with polycythemia vera (PV). METHODS: A total of 816 patients with a definite diagnosis of PV were enrolled from August 1983 to June 2013 into this study. The standardized mortality ratio (SMR) was calculated by comparing the cumulative survival of 816 PV patients with age- and sex- and calendar year-matched healthy Chinese population from the national bureau of statistics of the People's Republic of China. The clinical features of diagnosis and prognosis of PV patients were analyzed by Cox regression to identify risk factors for the poor prognosis of PV and to develop a dynamic prognostic model in Chinese patients. The effects of different treatments on the development of acute myelocytic leukemia (AML) and post-PV myelofibrosis (post-PV MF) were determined by Kaplan-Meier analysis. JAK2 V617F allele burden (V617F%) was determined by quantitative real-time PCR in 104 patients. RESULTS: The median follow-up time was 6 (1-42) years. The 10-, 15- and 20-year overall survival (OS) was 89.50%, 76.70% and 64.70%, respectively. The SMR was 17.40 (95% CI: 13.71-21.78). Cox regression analysis revealed that white blood cell (WBC) count>10×10(9)/L (HR=3.10, 95% CI: 1.47-6.53, P=0.003), age>60 years (HR=2.89, 95% CI: 1.84-4.53, P<0.001) and prior thrombosis (HR=2.66, 95% CI: 1.65-4.29, P<0.001) were significant predictors for the poor prognosis of PV. Based on the hazard radio, 816 patents were allocated into 4 categories with significantly different survival: low (sum of points=0; median survival no reached), intermediate 1 (sum of points=1; median survival 33.10 (28.20-38.00) years), intermediate 2 (sum of points=2; median survival 23.00 (16.08-29.92) years), high (sum of points=3; median survival 13.00 (10.58-15.42) years). The mortality of high risk group was 5.37 fold higher than low risk patients. The 10- and 20-year survival of no post-PV MF were 89.50% and 79.60%, respectively, for interferon α (IFN-α); 73.80% and 43.50%, respectively, for hydroxyurea treatment; 82.20% and 71.40%, respectively, for alkylating agent treatment; and 80.00% and 38.20%, respectively, for no cytoreductive treatment. The treatment of exposure to IFN-α associated with a higher rate of no-post-PV MF survival (Log-rank=9.79, P=0.020). There were more post-PV MF patients with V617F%≥50% compared with those V617F%<50% (P<0.001). CONCLUSIONS: The mortality of PV patients is significantly higher than that of healthy Chinese population. The WBC count>10×10(9)/L, age>60 years, and prior thrombosis are identified as significant predictors for the prognosis of PV. The risk of post-PV MF transformation may be ameliorated by IFN-α via decreasing the burden of JAK2 V617F mutation.

[Efficiency of hemoperfusion on clearing thallium based on atomic absorption spectrometry].

OBJECTIVE: To determine thallium in whole blood by atomic absorption detection method, and to investigate the eliminating effect of hemoperfusion (HP) for thallium in blood. METHODS: The blood of Beagle dogs which had not exposed to thallium before were obtained for preparation of thallium nitrate ( TlNO3 )-containing solution in three concentrations according to the conversion formula based on animal weight and volume of blood. HP was performed in the simulated in vivo environment. The content of TlNO3 in blood of the next group was determined on the amount of TlNO3 for the last HP of the former dose group. Thallium quantity in different samples was measured with atomic absorption spectrometer blood samples before and after HP. Finally, the thallium concentration in blood was analyzed statistically. RESULTS: Thallium concentrations showed a good linear relationship in the range of 0-200 µg/L (r = 0.998 4). The intra-day precision (RSD) was lower than 4.913%, the intra-day recovery rate was 96.2%-111.9%; the inter-day precision (RSD) was lower than 7.502%, the inter-day recovery rate was 89.6%-105.2%. The concentration of thallium in blood was significantly reduced after HP per time in high, middle, and low dose groups [(453.43 ± 27.80) mg/L to (56.09 ± 14.44) mg/L in high dose group, F = 8.820, P = 0.003; (64.51 ± 13.60) mg/L to (3.19 ± 0.23) mg/L in middle dose group, F = 36.312, P = 0.000; (5.40 ± 0.98) mg/L to (0.38 ± 0.25) mg/L in low dose group, F = 46.240, P = 0.000 ]. The adsorption rate of four times of HP in high, middle and low dose group were (87.63 ± 2.48 )%, (95.06 ± 1.54 )% and (92.76 ± 4.87)%, respectively, without significant difference (F = 4.231, P = 0.070). CONCLUSIONS: The method for measuring thallium was established, and it shows a very stable, simple, sensitive for determination of thallium. HP can effectively remove thallium from blood. Thallium concentration can be reduced by 90% after four times of HP. HP is also effective even when thallium concentration is not high.

[Nasal mucosa remodeling in chronic rhinosinusitis without nasal polyps].

OBJECTIVE: To explore the feature of nasal mucosa remodeling in chronic rhinosinusitis without nasal polyps (CRSsNP). METHOD: Histological specimens from 30 selected patients with CRSsNP who underwent endoscopic sinus surgery and 10 control subjects were studied. The paraffin sections were stained with hematoxylin-eosin(HE), alcian blue-periodic acid-Schiff (AB-PAS), Masson trichrome (MT) and Picric acid-Sirius red. The damage of epithelium, goblet cells and gland hyperplasia, deposition of collagen in extracellular matrix, the thickness of basement membrane and the type of collagen were observed respectively. RESULT: Grade 0, Grade 1, Grade 2 and Grade 3 of epithelial damage were significantly different in the CRSsNP group when compared with the control group (P < 0.01 or P < 0.05). Evident mucus gland hyperplasia and collagen deposition in extracellular matrix were observed in CRSsNP group (P < 0.01). The number of goblet cells and the thickness of basement membrane were increased obviously in CRSsNP group (P < 0.01). The collagen deposited in extracellular matrix was mainly composed of collagen type I. Collagen type III and collagen type IV was much less than collagen type I. CONCLUSION: The nasal mucosa remodeling was observed in CRSsNP group and was characterized by epithelial damage, basement membrane thickening, deposition of collagen in extracellular matrix, goblet cells and mucus gland hyperplasia.

Bioactive molecules of Taenia solium metacestode, a causative agent of neurocysticercosis.

Neurocysticercosis (NC), an infection of the CNS with Taenia solium metacestode, exemplifies formidable public health concerns associated with significant morbidity and mortality. The disease is a complex phenomenon involving molecular cell biological cross-talks between the parasite and human host. To effectively combat NC, specific diagnosis and proper management are prerequisites. Bioactive molecules implicated in host-parasite interactions and parasitic homeostasis should be elucidated. This article provides an overview of currently available serological biomarkers, especially those comprising low-molecular-weight proteins, and discusses available immunoproteomics for identification of such molecules. T. solium metacestode bioactive molecules, which might be critically implicated in the progression of NC disease, are summarized. Comprehensive understanding of the biochemical properties and biological functions of bioactive molecules may contribute to the development of novel intervention strategies against NC.