Hypoxia and low temperature upregulate transferrin to induce hypercoagulability at high altitude.

Studies have shown significantly increased thromboembolic events at high altitude. We recently reported that transferrin could potentiate blood coagulation, but the underlying mechanism for high altitude-related thromboembolism is still poorly understood. Here, we examined the activity and concentration of plasma coagulation factors and transferrin in plasma collected from long-term human residents and short-stay mice exposed to varying altitudes. We found that the activities of thrombin and factor XIIa (FXIIa) along with the concentrations of transferrin were significantly increased in the plasma of humans and mice at high altitudes. Furthermore, both hypoxia (6% O2) and low temperature (0°C), 2 critical high-altitude factors, enhanced hypoxia-inducible factor 1α (HIF-1α) levels to promote the expression of the transferrin gene, whose enhancer region contains HIF-1α binding site, and consequently, to induce hypercoagulability by potentiating thrombin and FXIIa. Importantly, thromboembolic disorders and pathological insults in mouse models induced by both hypoxia and low temperature were ameliorated by transferrin interferences, including transferrin antibody treatment, transferrin downregulation, and the administration of our designed peptides that inhibit the potentiation of transferrin on thrombin and FXIIa. Thus, low temperature and hypoxia upregulated transferrin expression-promoted hypercoagulability. Our data suggest that targeting the transferrin-coagulation pathway is a novel and potentially powerful strategy against thromboembolic events caused by harmful environmental factors under high-altitude conditions.

Comparative study of ultrasound attenuation analysis and controlled attenuation parameter in the diagnosis and grading of liver steatosis in non-alcoholic fatty liver disease patients.

PURPOSE: To assess the diagnostic performance of Ultrasound Attenuation Analysis (USAT) in the diagnosis and grading of hepatic steatosis in patients with non-alcoholic fatty liver disease (NAFLD) using Controlled Attenuation Parameters (CAP) as a reference. MATERIALS AND METHODS: From February 13, 2023, to September 26, 2023, participants underwent CAP and USAT examinations on the same day. We used manufacturer-recommended CAP thresholds to categorize the stages of hepatic steatosis: stage 1 (mild) - 240 dB/m, stage 2 (moderate) - 265 dB/m, stage 3 (severe) - 295 dB/m. Receiver Operating Characteristic curves were employed to evaluate the diagnostic accuracy of USAT and determine the thresholds for different levels of hepatic steatosis. RESULTS: Using CAP as the reference, we observed that the average USAT value increased with the severity of hepatic steatosis, and the differences in USAT values among the different hepatic steatosis groups were statistically significant (p < 0.05). There was a strong positive correlation between USAT and CAP (r = 0.674, p < 0.0001). When using CAP as the reference, the optimal cut-off values for diagnosing and predicting different levels of hepatic steatosis with USAT were as follows: the cut-off value for excluding the presence of hepatic steatosis was 0.54 dB/cm/MHz (AUC 0.96); for mild hepatic steatosis, it was 0.59 dB/cm/MHz (AUC 0.86); for moderate hepatic steatosis, it was 0.73 dB/cm/MHz (AUC 0.81); and for severe hepatic steatosis, it was 0.87 dB/cm/MHz (AUC 0.87). CONCLUSION: USAT exhibits strong diagnostic performance for hepatic steatosis and shows a high correlation with CAP values.

Development and validation of nomograms using photoacoustic imaging and 2D ultrasound to predict breast nodule benignity and malignancy.

BACKGROUND: The application of photoacoustic imaging (PAI), utilizing laser-induced ultrasound, shows potential in assessing blood oxygenation in breast nodules. However, its effectiveness in distinguishing between malignant and benign nodules remains insufficiently explored. PURPOSE: This study aims to develop nomogram models for predicting the benign or malignant nature of breast nodules using PAI. METHOD: A prospective cohort study enrolled 369 breast nodules, subjecting them to PAI and ultrasound examination. The training and testing cohorts were randomly divided into two cohorts in a ratio of 3:1. Based on the source of the variables, three models were developed, Model 1: photoacoustic-BIRADS+BMI + blood oxygenation, Model 2: BIRADS+Shape+Intranodal blood (Doppler) + BMI, Model 3: photoacoustic-BIRADS+BIRADS+ Shape+Intranodal blood (Doppler) + BMI + blood oxygenation. Risk factors were identified through logistic regression, resulting in the creation of three predictive models. These models were evaluated using calibration curves, subject receiver operating characteristic (ROC), and decision curve analysis. RESULTS: The area under the ROC curve for the training cohort was 0.91 (95% confidence interval, 95% CI: 0.88-0.95), 0.92 (95% CI: 0.89-0.95), and 0.97 (95% CI: 0.96-0.99) for Models 1-3, and the ROC curve for the testing cohort was 0.95 (95% CI: 0.91-0.98), 0.89 (95% CI: 0.83-0.96), and 0.97 (95% CI: 0.95-0.99) for Models 1-3. CONCLUSIONS: The calibration curves demonstrate that the model's predictions agree with the actual values. Decision curve analysis suggests a good clinical application.

A validation of an entropy-based artificial intelligence for ultrasound data in breast tumors.

BACKGROUND: The application of artificial intelligence (AI) in the ultrasound (US) diagnosis of breast cancer (BCa) is increasingly prevalent. However, the impact of US-probe frequencies on the diagnostic efficacy of AI models has not been clearly established. OBJECTIVES: To explore the impact of using US-video of variable frequencies on the diagnostic efficacy of AI in breast US screening. METHODS: This study utilized different frequency US-probes (L14: frequency range: 3.0-14.0 MHz, central frequency 9 MHz, L9: frequency range: 2.5-9.0 MHz, central frequency 6.5 MHz and L13: frequency range: 3.6-13.5 MHz, central frequency 8 MHz, L7: frequency range: 3-7 MHz, central frequency 4.0 MHz, linear arrays) to collect breast-video and applied an entropy-based deep learning approach for evaluation. We analyzed the average two-dimensional image entropy (2-DIE) of these videos and the performance of AI models in processing videos from these different frequencies to assess how probe frequency affects AI diagnostic performance. RESULTS: The study found that in testing set 1, L9 was higher than L14 in average 2-DIE; in testing set 2, L13 was higher in average 2-DIE than L7. The diagnostic efficacy of US-data, utilized in AI model analysis, varied across different frequencies (AUC: L9 > L14: 0.849 vs. 0.784; L13 > L7: 0.920 vs. 0.887). CONCLUSION: This study indicate that US-data acquired using probes with varying frequencies exhibit diverse average 2-DIE values, and datasets characterized by higher average 2-DIE demonstrate enhanced diagnostic outcomes in AI-driven BCa diagnosis. Unlike other studies, our research emphasizes the importance of US-probe frequency selection on AI model diagnostic performance, rather than focusing solely on the AI algorithms themselves. These insights offer a new perspective for early BCa screening and diagnosis and are of significant for future choices of US equipment and optimization of AI algorithms.

The research on artificial intelligence-assisted breast diagnosis often relies on static images or dynamic videos obtained from ultrasound probes with different frequencies. However, the effect of frequency-induced image variations on the diagnostic performance of artificial intelligence models remains unclear. In this study, we aimed to explore the impact of using ultrasound images with variable frequencies on AI's diagnostic efficacy in breast ultrasound screening. Our approach involved employing a video and entropy-based feature breast network to compare the diagnostic efficiency and average two-dimensional image entropy of the L14 (frequency range: 3.0-14.0 MHz, central frequency 9 MHz), L9 (frequency range: 2.5-9.0 MHz, central frequency 6.5 MHz) linear array probe and L13 (frequency range: 3.6-13.5 MHz, central frequency 8 MHz), and L7 (frequency range: 3-7 MHz, central frequency 4.0 MHz) linear array probes. The results revealed that the diagnostic efficiency of AI models differed based on the frequency of the ultrasound probe. It is noteworthy that ultrasound images acquired with different frequency probes exhibit different average two-dimensional image entropy, while higher average two-dimensional image entropy positively affect the diagnostic performance of the AI model. We concluded that a dataset with higher average two-dimensional image entropy is associated with superior diagnostic efficacy for AI-based breast diagnosis. These findings contribute to a better understanding of how ultrasound image variations impact AI-assisted breast diagnosis, potentially leading to improved breast cancer screening outcomes.

EGF Suppresses the Initiation and Drives the Reversion of TGF-ß1-induced Transition in Hepatic Oval Cells Showing the Plasticity of Progenitor Cells.

Transforming growth factor-ß1 (TGF-ß1) induces hepatic progenitors to tumor initiating cells through epithelial-mesenchymal transition (EMT), thus raising an important drawback for stem cell-based therapy. How to block and reverse TGF-ß1-induced transition is crucial for progenitors' clinical application and carcinogenic prevention. Rat adult hepatic progenitors, hepatic oval cells, experienced E-cadherin to N-cadherin switch and changed to α-smooth muscle actin (α-SMA) positive cells after TGF-ß1 incubation, indicating EMT. When TGF-ß1 plus EGF were co-administrated to these cells, EGF dose-dependently suppressed the cadherin switch and α-SMA expression. Interestingly, if EGF was applied to TGF-ß1-pretreated cells, the cells that have experienced EMT could return to their epithelial phenotype. Abruption of EGF receptor revealed that EGF exerted its blockage and reversal effects through phosphorylation of ERK1/2 and Akt. These findings suggest an important attribute of EGF on opposing and reversing TGF-ß1 effects, indicating the plasticity of hepatic progenitors.

Antifibrotic effects of a recombinant adeno-associated virus carrying small interfering RNA targeting TIMP-1 in rat liver fibrosis.

Elevated tissue inhibitor of metalloproteinase 1 (TIMP-1) expression contributes to excess production of extracellular matrix in liver fibrosis. Herein, we constructed a recombinant adeno-associated virus (rAAV) carrying siRNA of the TIMP-1 gene (rAAV/siRNA-TIMP-1) and investigated its effects on liver fibrosis in rats. Two models of rat liver fibrosis, the carbon tetrachloride and bile duct ligation models, were treated with rAAV/siRNA-TIMP-1. In the carbon tetrachloride model, rAAV/siRNA-TIMP-1 administration attenuated fibrosis severity, as determined by histologic analysis of hepatic collagen accumulation, hydroxyproline content, and concentrations of types I and III collagen in livers and sera. Levels of mRNA and active matrix metalloproteinase (MMP) 13 were elevated, whereas levels of mRNA and active MMP-2 were decreased. Moreover, a marked decrease was noted in the expression of α-smooth muscle actin, a biomarker of activated hepatic stellate cells (HSCs), and transforming growth factor-ß1, critical for the development of liver fibrosis. Similarly, rAAV/siRNA-TIMP-1 treatment significantly alleviated bile duct ligation-induced liver fibrosis. Furthermore, this treatment dramatically suppressed TIMP-1 expression in HSCs from both model rats. These data indicate that the administration of rAAV/siRNA-TIMP-1 attenuated liver fibrosis by directly elevating the function of MMP-13 and diminishing activated HSCs. It also resulted in indirect decreased expression of type I collagen, MMP-2, and transforming growth factor-ß1. In conclusion, rAAV/siRNA-TIMP-1 may be an effective antifibrotic gene therapy agent.

Multimodal PA/US imaging in Rheumatoid Arthritis: Enhanced correlation with clinical scores.

Background: Accurate assessment of Rheumatoid Arthritis (RA) activity remains a challenge. Multimodal photoacoustic/ultrasound (PA/US) joint imaging emerges as a novel imaging modality capable of depicting microvascularization and oxygenation levels in inflamed joints associated with RA. However, the scarcity of large-scale studies limits the exploration of correlating joint oxygenation status with disease activity. Objective: This study aimed to explore the correlation between multimodal PA/US imaging scores and RA disease activity, assessing its clinical applicability in managing RA. Methods: In this study, we recruited 111 patients diagnosed with RA and conducted examinations of seven small joints on their clinically dominant side using a PA/US imaging system. The PA and power Doppler ultrasound (PDUS) signals were semi-quantitatively assessed using a 0-3 grading system. The cumulative scores for PA and PDUS across these seven joints (PA-sum and PDUS-sum) were calculated. Relative oxygen saturation (So2) values of inflamed joints on the clinically dominant side were measured, and categorized into four distinct PA+So2 patterns. The correlation between PA/US imaging scores and disease activity indices was systematically evaluated. Results: Analysis of 777 small joints in 111 patients revealed that the PA-sum scores exhibited a strong positive correlation with standard clinical scores for RA, including DAS28 [ESR] (ρ = 0.682), DAS28 [CRP] (ρ = 0.683), CDAI (ρ = 0.738), and SDAI (ρ = 0.739), all with p < 0.001. These correlations were superior to those of the PDUS-sum scores (DAS28 [ESR] ρ = 0.559, DAS28 [CRP] ρ = 0.555, CDAI ρ = 0.575, SDAI ρ = 0.581, p < 0.001). Significantly, in patients with higher PA-sum scores, notable differences were observed in the erythrocyte sedimentation rate (ESR) (p < 0.01) and swollen joint count 28 (SJC28) (p < 0.01) between hypoxia and intermediate groups. Notably, RA patients in the hypoxia group exhibited higher clinical scores in certain clinical indices. Conclusion: Multi-modal PA/US imaging introduces potential advancements in RA assessment, especially regarding So2 evaluations in synovial tissues and associated PA scores. However, further studies are warranted, particularly with more substantial sample sizes and in multi-center settings. Summary: This study utilized multi-modal PA/US imaging to analyze Rheumatoid Arthritis (RA) patients' synovial tissues and affected joints. When juxtaposed with traditional PDUS imaging, the PA approach demonstrated enhanced sensitivity, especially concerning detecting small vessels in thickened synovium and inflamed tendon sheaths. Furthermore, correlations between the derived PA scores, PA+So2 patterns, and standard clinical RA scores were observed. These findings suggest that multi-modal PA/US imaging could be a valuable tool in the comprehensive assessment of RA, offering insights not only into disease activity but also into the oxygenation status of synovial tissues. However, as promising as these results are, further investigations, especially in larger and diverse patient populations, are imperative. Key points: ⸸ Multi-modal PA/US Imaging in RA: This novel technique was used to assess the So2 values in synovial tissues and determine PA scores of affected RA joints.⸸ Correlation significantly with Clinical RA Scores: Correlations significantly were noted between PA scores, PA+So2 patterns, and standard clinical RA metrics, hinting at the potential clinical applicability of the technique.

Assessment of Oxygen Saturation in Breast Lesions Using Photoacoustic Imaging: Correlation With Benign and Malignant Disease.

BACKGROUND: Hypoxia is a hallmark of breast cancer (BC). Photoacoustic (PA) imaging, based on the use of laser-generated ultrasound (US), can detect oxygen saturation (So2) in the tissues of breast lesion patients. PURPOSE: To measure the oxygenation status of tissue in and on both sides of the lesion in breast lesion participants using a multimodal Photoacoustic/ultrasound (PA/US) imaging system and to determine the correlation between So2 measured by PA imaging and benign or malignant disease. MATERIALS AND METHODS: Multimodal PA/US imaging and gray-scale US (GSUS) of breast lesion was performed in consecutive breast lesion participants imaged in the US Outpatient Clinic between 2022 and 2023. Dual-wavelength PA imaging was used to measure the So2 value inside the lesion and on both sides of the tissue, and to distinguish benign from malignant lesions based on the So2 value. The ability of So2 to distinguish benign from malignant breast lesions was evaluated by the receiver operating characteristic curve (ROC) and the De-Long test. RESULTS: A total of 120 breast lesion participants (median age, 42.5 years) were included in the study. The malignant lesions exhibited lower So2 levels compared to benign lesions (malignant: 71.30%; benign: 83.81%; P < .01). Moreover, PA/US imaging demonstrates superior diagnostic results compared to GSUS, with an area under the curve (AUC) of 0.89 versus 0.70, sensitivity of 89.58% versus 85.42%, and specificity of 86.11% versus 55.56% at the So2 cut-off value of 78.85 (P < .001). The false positive rate in GSUS reduced by 30.75%, and the false negative rate diminished by 4.16% with PA /US diagnosis. Finally, the So2 on both sides tissues of malignant lesions are lower than that of benign lesions (P < .01). CONCLUSION: PA imaging allows for the assessment of So2 within the lesions of breast lesion patients, thereby facilitating a superior distinction between benign and malignant lesions.

Diagnostic Performance of Deep Learning in Video-Based Ultrasonography for Breast Cancer: A Retrospective Multicentre Study.

OBJECTIVE: Although ultrasound is a common tool for breast cancer screening, its accuracy is often operator-dependent. In this study, we proposed a new automated deep-learning framework that extracts video-based ultrasound data for breast cancer screening. METHODS: Our framework incorporates DenseNet121, MobileNet, and Xception as backbones for both video- and image-based models. We used data from 3907 patients to train and evaluate the models, which were tested using video- and image-based methods, as well as reader studies with human experts. RESULTS: This study evaluated 3907 female patients aged 22 to 86 years. The results indicated that the MobileNet video model achieved an AUROC of 0.961 in prospective data testing, surpassing the DenseNet121 video model. In real-world data testing, it demonstrated an accuracy of 92.59%, outperforming both the DenseNet121 and Xception video models, and exceeding the 76.00% to 85.60% accuracy range of human experts. Additionally, the MobileNet video model exceeded the performance of image models and other video models across all evaluation metrics, including accuracy, sensitivity, specificity, F1 score, and AUC. Its exceptional performance, particularly suitable for resource-limited clinical settings, demonstrates its potential for clinical application in breast cancer screening. CONCLUSIONS: The level of expertise reached by the video models was greater than that achieved by image-based models. We have developed an artificial intelligence framework based on videos that may be able to aid breast cancer diagnosis and alleviate the shortage of experienced experts.

Optimizing breast cancer diagnosis with photoacoustic imaging: An analysis of intratumoral and peritumoral radiomics.

Background: The differentiation between benign and malignant breast tumors extends beyond morphological structures to encompass functional alterations within the nodules. The combination of photoacoustic (PA) imaging and radiomics unveils functional insights and intricate details that are imperceptible to the naked eye. Purpose: This study aims to assess the efficacy of PA imaging in breast cancer radiomics, focusing on the impact of peritumoral region size on radiomic model accuracy. Materials and methods: From January 2022 to November 2023, data were collected from 358 patients with breast nodules, diagnosed via PA/US examination and classified as BI-RADS 3-5. The study used the largest lesion dimension in PA images to define the region of interest, expanded by 2 mm, 5 mm, and 8 mm, for extracting radiomic features. Techniques from statistics and machine learning were applied for feature selection, and logistic regression classifiers were used to build radiomic models. These models integrated both intratumoral and peritumoral data, with logistic regressions identifying key predictive features. Results: The developed nomogram, combining 5 mm peritumoral data with intratumoral and clinical features, showed superior diagnostic performance, achieving an AUC of 0.950 in the training cohort and 0.899 in validation. This model outperformed those based solely on clinical features or other radiomic methods, with the 5 mm peritumoral region proving most effective in identifying malignant nodules. Conclusion: This research demonstrates the significant potential of PA imaging in breast cancer radiomics, especially the advantage of integrating 5 mm peritumoral with intratumoral features. This approach not only surpasses models based on clinical data but also underscores the importance of comprehensive radiomic analysis in accurately characterizing breast nodules.

The effect of image resolution on convolutional neural networks in breast ultrasound.

Purpose: The objective of this research was to investigate the efficacy of various parameter combinations of Convolutional Neural Networks (CNNs) models, namely MobileNet and DenseNet121, and different input image resolutions (REZs) ranging from 64×64 to 512×512 pixels, for diagnosing breast cancer. Materials and methods: During the period of June 2015 to November 2020, two hospitals were involved in the collection of two-dimensional ultrasound breast images for this retrospective multicenter study. The diagnostic performance of the computer models MobileNet and DenseNet 121 was compared at different resolutions. Results: The results showed that MobileNet had the best breast cancer diagnosis performance at 320×320pixel REZ and DenseNet121 had the best breast cancer diagnosis performance at 448×448pixel REZ. Conclusion: Our study reveals a significant correlation between image resolution and breast cancer diagnosis accuracy. Through the comparison of MobileNet and DenseNet121, it is highlighted that lightweight neural networks (LW-CNNs) can achieve model performance similar to or even slightly better than large neural networks models (HW-CNNs) in ultrasound images, and LW-CNNs' prediction time per image is lower.

A microsphere nanoparticle based-serum albumin targeted adsorption coupled with surface-enhanced Raman scattering for breast cancer detection.

The serum albumin level is inseparable associated with survival in patients with breast cancer, and simultaneously serve as a good indicator of prognosis of cancer. Here, we proposed a novel extraction-isolation analysis method of albumin for breast cancer detection utilizing hydroxyapatite particles (HAp) to targeted adsorb albumin from serum relying on its specific adsorption capacity. An ideal protein-release reagent was used for isolating albumin from the surface of HAp, and meanwhile ensuring that the structure and property of albumin was not suffered damage. The surface-enhanced Raman scattering (SERS) signal of extracted albumin was obtained, and partial least squares (PLS) and linear discriminant analysis (LDA) analysis approach were employed to analyze SERS spectra data, with the aim to assess the capability of HAp method for identifying breast cancer, yielding an ideal diagnostic accuracy of 98.6%, demonstrating promising potential as a non-invasive and sensitive nanotechnology for breast cancer screening.

Label-free diagnosis of breast cancer based on serum protein purification assisted surface-enhanced Raman spectroscopy.

Serum protein is generally used to assess the severity of disease, as well as cancer progression and prognosis. Herein, a simple and rapid serum proteins analysis method combined with surface-enhanced Raman spectroscopy (SERS) technology was applied for breast cancer detection. The cellulose acetate membrane (CA) was employed to extract human serum proteins from 30 breast cancer patients and 45 healthy volunteers and then extracted proteins were mixed with silver nanoparticles for SERS measurement. Additionally, we also mainly assessed the use of different ratios of proteins-silver nanoparticles (Ag NPs) mixture to generate maximum SERS signal for clinical samples detection. Two multivariate statistical analyses, principal component analysis-linear discriminate analysis (PCA-LDA) and partial least square-support vector machines (PLS-SVM) were used to analyze the obtained serum protein SERS spectra and establish the diagnostic model. The results demonstrate that the PLS-SVM model provides superior performance in the classification of breast cancer diagnosis compared with PCA-LDA. This exploratory work demonstrates that the label-free SERS analysis technique combined with CA membrane purified serum proteins has great potential for breast cancer diagnosis.

Primary isolated hepatic oval cells maintain progenitor cell phenotypes after two-year prolonged cultivation.

BACKGROUND & AIMS: Although expandable hepatic progenitors provide renewable cell sources for treatment of hepatic disorders, long-term cultivation of hepatic progenitors may affect proliferation and differentiation abilities, and even initiate the formation of malignant cancer stem cells. This study aims to determine characteristics of primary cultured hepatic oval cells after prolonged cultivation in vitro. METHODS: Hepatic oval cells isolated from rats fed with a choline-deficient, ethionine-supplemented diet were continuously propagated every 5-7 days, to 100 passages over two years. Hepatocytic differentiation was induced by sodium butyrate and characterized using western blot, periodic acid Schiff assays, albumin secretion and urea production. Proliferation capacity was evaluated using growth-curve and cell-cycle analysis; anchorage-independent growth and tumorigenicity were determined using soft agar and xenograft assay. RESULTS: After 2 years of serial passages, hepatic oval cells with typical epithelial morphology continuously expressed OV-6, BD-1, BD-2, and Dlk as markers for hepatic progenitors, cytokeratin 19 as a cholangiocyte marker, and alpha-fetoprotein and albumin as hepatocyte markers. Furthermore, sodium butyrate could induce these cells to become glycogen-storage cells with the functions of albumin secretion and ureagenesis from ammonia clearance, indicating hepatocytic differentiation. Although proliferation slightly accelerated after the 50th passage, hepatic oval cells stayed diploid cells with features of chromosomal stability, which did not acquire anchorage-independent growth capacity and caused no tumor in immunodeficient mice, suggesting no spontaneous malignant transformation. CONCLUSIONS: Hepatic oval cells retain the progenitor cell features without spontaneous malignant transformation after prolonged cultivation, and thus may serve as an expandable cell source for future exploitation of stem cell technology.

[Comparison between the suppression of tissue inhibitor of metalloproteinase-1 gene expression by recombinant adeno-associated virus carrying antisense RNA and small interfering RNA (siRNA) of TIMP-1 in rat hepatic stellate cells].

OBJECTIVES: Elevated tissue inhibitor of metalloproteinase-1 (TIMP-1) expression contributes to excess extracellular matrix in liver fibrosis. This study was designed to construct two recombinant adeno-associated viruses (AAV) carrying antisense RNA and small interfering RNA (siRNA) of TIMP-1 (rAAV/ANTI-TIMP-1/neo and rAAV/siRNA-TIMP-1/neo), and then to compare the suppression of TIMP-1 gene expression on rat hepatic stellate cell (HSC)-T6 cells infected by these two types of viruses in vitro. METHODS: Antisense RNA amplified by rat HSC-T6 and U6 promoter followed by the annealing siRNA were cloned into the AAV vector (pdl6-95/neo) and packed in 293 cells to construct the recombinants rAAV/ANTI-TIMP-1/neo and rAAV/siRNA-TIMP-1/neo. Rat HSC-T6 cells were infected with these recombinant AAVs and selected by using G418, and real-time PCR after reverse transcription and Western blot were performed to detect the transcription and expression level of TIMP-1 gene in these cells. RESULTS: The results of PCR, restrictive enzyme digestion and gene sequencing confirmed that the pdl6-95/ANTI-TIMP-1/neo and pdl6-95/siRNA-TIMP-1/neo had been reconstructed successfully. After they had been packed in 293 cells to form rAAV/ANTI-TIMP-1/neo and rAAV/siRNA-TIMP-1/neo, they were used to infect HSC-T6. Thirty days after the infection, the transcription level of TIMP-1 in HSC-T6 cells infected by rAAV/siRNA-TIMP-1/neo decreased dramatically compared with the mock control and normal HSC-T6 cells (P less than 0.01), and the expression level of TIMP-1 gene in HSC-T6 cells decreased significantly (60%), while the transcription and expression level of TIMP-1 in HSC-T6 cells infected by rAAV/ANTI-TIMP-1/neo had no significant difference with mock control and normal HSC-T6 cells (P more than 0.05). CONCLUSION: RNA interference can exert a suppression of TIMP-1 gene in rat HSC, and when this function combines with AAV infection, it can suppress the specific gene expression for a long time by chromosomal integration.

[Recombinant adeno-associated virus carrying hepatitis B virus C gene (rAAV-HBV-C) effectively pulses dendritic cells (DC) without affecting their maturity].

OBJECTIVE: Recombinant virus pulsated dendritic cells (DCs) may affect their survival, growth and maturity. This study is to test the infection efficiency of recombinant adeno-associated virus carrying hepatitis B core antigen (rAAV-HBV-c) to DCs and the growth and maturity of them. METHODS: Peripheral blood mononuclear cells (PBMCs) were isolated from healthy blood donors. Adherent monocytes were pulsed by rAAV-HBV-c and 293 lysate as controls on the first day of isolation. DCs were cultivated in AIM-V media with 1000 u/ml granulocyte macrophage stimulating factor (GM-CSF), 1000 u/ml interleukin-4 (IL-4) and 50 ng/ml tumor necrosis factor-alpha (TNFalpha) separately in vitro. DCs were examined at different times and the expressions of several clusters of differentiations (HLADR, CD14, CD80, CD83, CD86) were studied using FACS after being cultured for 7 days. The transcription and expression of HBV-C gene were analyzed by reverse transcription-polymerase chain reaction (RT-PCR) and intracellular staining fluorescence activated cell sorter (FACS), respectively. RESULTS: The rAAV-HBV-c infected and uninfected monocytes gradually matured and their morphology had no significant differences. The CDs expressed on the surfaces of the two groups of DCs were also similar (HLADR: 96.1% vs. 94.5%; CD86: 87.7% vs. 89.8%; CD83: 75.6% vs. 78%; CD80: 52% vs. 54.3%; CD14: 6.4% vs. 4.5%). HBV-C gene mRNA expression was measured using RT-PCR and 89.5% of the rAAV-HBV-c infected DCs showed their protein expression using FACS. CONCLUSION: rAAV-HBV-c can effectively pulse DCs without affecting the growth and maturity of them.

[Binding and inhibition of adeno-associated virus Rep78 protein with hepatitis B virus C promoter].

OBJECTIVES: Adeno-associated virus (AAV) Rep78 is known for its inhibitory effects on replication of several viruses and oncogenes transformations. The study was to investigate the effect of Rep78 on hepatitis B virus C (HBV-C) gene and the mechanism of it. METHODS: HBV-C promoter and HBV-C gene with its promoter were amplified by PCR and labeled with 32P-ATP. Electrophoretic mobility shift assay (EMSA) and in vitro transcription were utilized to detect the binding of MBP-Rep78 with HBV-C promoter and the transcription of HBV-C gene. RESULTS: EMSA showed that by increasing the amount of Rep78 protein from 0.1 microg to 1.0 microg, the binding bands got stronger in a dose-dependent manner. In addition, Rep78 antibody was used to certify the specificity of this binding. The compound of Rep78, Rep78 antibody and HBV-C promoter were seen as super shift bands in EMSA. Meanwhile, HBV-C gene transcription was significantly inhibited by in vitro transcription which meant that Rep78 could not only bind with HBV-C promoter, but also could inhibit the transcription of HBV-C gene. CONCLUSION: AAV Rep78 could inhibit the transcription of HBV-C gene through its binding with HBV-C promoter.

[Prospective clinical study on serum immunity in IgG-antibodies positive patients convalescent from severe acute respiratory syndrome].

OBJECTIVE: To investigate the serum immunological characteristics in patients convalescent from severe acute respiratory syndrome (SARS). METHODS: In the 1 st, 3 rd, 6 th month after their discharge, eg. SARS-IgG, T cell subsets, blood routine, and the blood biochemistry were systemically determined in SARS convalescent patients. RESULTS: The SARS-antibodies could be used as the diagnostic evidence. During the 6 months after discharge, the titers of SARS-antibodies were high, but they lowered along with passage of time. At the first recheck, the CD4(+) lymphocyte count was lower than normal level in 55.9% of patients, the CD3(+) lymphocyte count was lower than normal level in 31.2% of patients, and the CD8(+) lymphocyte count was lower than normal level in 14.0% of patients. At the second recheck, the levels of T cell subsets recovered to normal level in the most patients. CONCLUSION: T cell subsets, and the number of leukocyte are abnormal in some patients convalescent from SARS. All the indexes examined recover to normal levels half year after discharge. Therefore, it is necessary to follow up the changes in the levels of SARS-antibodies.

[Sodium butyrate induces rat hepatic oval cells differentiating into mature hepatocytes in vitro].

OBJECTIVE: To elucidate the effects of sodium butyrate on rat hepatic oval cell differentiation in vitro. METHODS: Hepatic oval cells were isolated from rats fed with a choline-deficient diet supplemented with 0.1% (w/w) ethonine for 4 to 6 weeks. The cultured hepatic oval cells were identified by immunohistochemistry and reverse transcription-polymerase chain reaction (RT-PCR). After hepatic oval cells were treated with sodium butyrate, the morphological changes were studied through Giemsa staining and the albumin expression level was tested by Western blot. RESULTS: Immunohistochemical results showed the isolated cells were positive for both mature hepatocyte marker albumin and bile duct cell marker cytokeratin-19. Furthermore, RT-PCR results showed that the cells expressed stem cell marker c-kit, but not hematopoietic stem cell marker CD34. In short, the isolated cells were rat hepatic oval cells. 0.75 mmol/L sodium butyrate induced obvious phenotype changes of hepatic oval cells, including enlargement of the oval cells, a decrease in nucleus to cytoplasm ratio, and a 50% increase in the number of binucleated cells. Western blot results showed that 0.75 mmol/L sodium butyrate markedly raised the expression of albumin. CONCLUSION: Sodium butyrate, a differentiation promoting agent, can induce rat hepatic oval cells (liver progenitor cells) to differentiate into mature hepatocytes in vitro.