Comparison of clinical and MRI features of brain metastases between ALK+ and ALK- NSCLC.

BACKGROUND: Non-small-cell lung cancer (NSCLC) is the primary cause of brain metastases (BM). This study aimed to investigate differences in clinical and magnetic resonance imaging (MRI) features of BM between anaplastic lymphoma kinase (ALK) gene fusion (ALK+) and ALK wild-type (ALK-) NSCLC, and to preliminarily assess the efficacy of radiotherapy for treating BM. METHODS: A retrospective analysis included 101 epidermal growth factor receptor (EGFR)- NSCLC patients with BM: 41 with ALK gene fusion and 60 being ALK-. The brain MRI and clinical features were compared between different ALK status using the multivariate analysis, and a nomogram was constructed to predict ALK gene fusion. Fifty-six patients who did not undergo cerebral surgery and had complete pre- and post- treatment data were further divided based on whether they received radiotherapy. Log-rank test was used to compare the short-term effect of treatment between the two groups under different genotypes. RESULTS: ALK+ BM exhibited decreased peritumoral brain edema size, lower peritumoral brain edema index (PBEI), and a more homogeneous contrast enhancement pattern compared to ALK- BM. Age (OR = 1.04; 95%CI: 1.02-1.06), time to BM (OR = 1.50; 95% CI: 1.04-2.14), PBEI (OR = 1.26; 95% CI: 0.97-1.62), smoking status (smoking index >400 vs. non-smoking status: OR = 1.42; 95% CI: 0.99-2.04) and contrast enhancement pattern (OR = 1.89; 95% CI: 1.28-2.78) were associated with ALK gene fusion. A nomogram based on these variables demonstrated acceptable predictive efficiency (AUC = 0.844). In the ALK+ group, patients who received radiotherapy did not show increased disease control rate (DCR) or progression-free survival (PFS). In contrast, in the ALK- group, those who received radiotherapy had improved objective response rate (ORR), DCR, and PFS compared to those who were only treated with systemic therapy. CONCLUSIONS: The clinical and MRI features of BM can indicate the status of ALK in NSCLC. In the ALK- group, patients who received radiotherapy showed higher ORR, DCR, and PFS compared to those who did not.

Prediction of histopathologic grades of bladder cancer with radiomics based on MRI: Comparison with traditional MRI.

PURPOSE: To compare biparametric magnetic resonance imaging (bp-MRI) radiomics signatures and traditional MRI model for the preoperative prediction of bladder cancer (BCa) grade. MATERIALS AND METHODS: This retrospective study included 255 consecutive patients with pathologically confirmed 113 low-grade and 142 high-grade BCa. The traditional MRI nomogram model was developed using univariate and multivariate logistic regression by the mean apparent diffusion coefficient (ADC), vesical imaging reporting and data system, tumor size, and the number of tumors. Volumes of interest were manually drawn on T2-weighted imaging (T2WI) and ADC maps by 2 radiologists. Using one-way analysis of variance, correlation, and least absolute shrinkage and selection operator methods to select features. Then, a logistic regression classifier was used to develop the radiomics signatures. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic abilities of the radiomics and traditional MRI models by the DeLong test. Finally, decision curve analysis was performed by estimating the clinical usefulness of the 2 models. RESULTS: The area under the ROC curves (AUCs) of the traditional MRI model were 0.841 in the training cohort and 0.806 in the validation cohort. The AUCs of the 3 groups of radiomics model [ADC, T2WI, bp-MRI (ADC and T2WI)] were 0.888, 0.875, and 0.899 in the training cohort and 0.863, 0.805, and 0.867 in the validation cohort, respectively. The combined radiomics model achieved higher AUCs than the traditional MRI model. decision curve analysis indicated that the radiomics model had higher net benefits than the traditional MRI model. CONCLUSION: The bp-MRI radiomics model may help distinguish high-grade and low-grade BCa and outperforming the traditional MRI model. Multicenter validation is needed to acquire high-level evidence for its clinical application.

Meta-analysis of dynamic contrast enhancement and diffusion-weighted MRI for differentiation of benign from malignant non-mass enhancement breast lesions.

Purpose: The objective of this study was to conduct a meta-analysis comparing the diagnostic efficacy of models based on diffusion-weighted imaging (DWI)-MRI, dynamic contrast enhancement (DCE)-MRI, and combination models (DCE and DWI) in distinguishing benign from malignant non-mass enhancement (NME) breast lesions. Materials and methods: PubMed, Embase, and Cochrane Library were searched, from inception to January 30, 2023, for studies that used DCE or DWI-MRI for the prediction of NME breast cancer patients. A bivariate random-effects model was used to calculate the meta-analytic sensitivity, specificity, and area under the curve (AUC) of the DCE, DWI, and combination models. Subgroup analysis and meta-regression analysis were performed to find the source of heterogeneity. Results: Of the 838 articles screened, 18 were eligible for analysis (13 on DCE, five on DWI, and four studies reporting the diagnostic accuracy of both DCE and DWI). The funnel plot showed no publication bias (p > 0.5). The pooled sensitivity and specificity and the AUC of the DCE, DWI, and combination models were 0.58, 0.72, and 0.70, respectively; 0.84, 0.69, and 0.84, respectively; and 0.88, 0.79, 0.90, respectively. The meta-analysis found no evidence of a threshold effect and significant heterogeneity among trials in terms of DCE sensitivity and specificity, as well as DWI specificity alone (I2 > 75%). The meta-regression revealed that different diagnostic criteria contributed to the DCE study's heterogeneity (p < 0.05). Different reference criteria significantly influenced the heterogeneity of the DWI model (p < 0.05). Subgroup analysis revealed that clustered ring enhancement (CRE) had the highest pooled specificity (0.92) among other DCE features. The apparent diffusion coefficient (ADC) with a mean threshold <1.3 × 10-3 mm2/s had a slightly higher sensitivity of 0.86 compared to 0.82 with an ADC of ≥1.3 × 10-3 mm2/s. Conclusion: The combination model (DCE and DWI) outperformed DCE or DWI alone in identifying benign and malignant NME lesions. The DCE-CRE feature was the most specific test for ruling in NME cancers.

IodoTMT-labeled redox proteomics reveals the involvement of oxidative post-translational modification in response to para-hydroxybenzoic acid and hydrogen peroxide stresses in poplar.

Poplar is widely planted as an economic and ecological tree species. However, accumulation of the phenolic acid allelochemical para-hydroxybenzoic acid (pHBA) in soil is a severe threat to the growth and productivity of poplar. pHBA stress leads to excessive production of reactive oxygen species (ROS). However, it is unclear which redox-sensitive proteins are involved in the pHBA-induced cellular homeostasis regulatory mechanism. We here identified reversible redox-modified proteins and modified cysteine (Cys) sites in exogenous pHBA- and hydrogen peroxide (H2O2)-treated poplar seedling leaves by using the iodoacetyl tandem mass tag-labeled redox proteomics method. In total, 4786 redox modification sites were identified in 3176 proteins, with 104 and 91 proteins being differentially modified at 118 and 101 Cys sites in response to pHBA and H2O2 stresses, respectively. The differentially modified proteins (DMPs) were predicted to be mainly localized in the chloroplast and cytoplasm, with most proteins being enzymes with catalytic activities. The KEGG enrichment analysis of these DMPs revealed that proteins related to the MAPK signaling pathway, soluble sugar metabolism, amino acid metabolism, photosynthesis, and phagosome pathways were extensively regulated by redox modifications. Moreover, combined with our previous quantitative proteomics data, 8 proteins were upregulated and oxidized under both pHBA and H2O2 stresses. Reversible oxidation of Cys sites in these proteins might be actively responsible for the regulation of tolerance to pHBA-induced oxidative stress. Based on the aforementioned results, a redox regulatory model activated by pHBA- and H2O2-induced oxidative stress was proposed. This study conducts the first redox proteomics analysis of poplar in response to pHBA stress and provides a new insight into the mechanistic framework of reversible oxidative post-translational modifications to gain a better understanding of pHBA-induced chemosensory effects on poplar.

An MRI-based radiomics nomogram in predicting histologic grade of non-muscle-invasive bladder cancer.

Background: Non-muscle-invasive bladder cancer (NMIBC) is categorized into high and low grades with different clinical treatments and prognoses. Thus, accurate preoperative evaluation of the histologic NMIBC grade through imaging techniques is essential. Objectives: To develop and validate an MRI-based radiomics nomogram for individualized prediction of NMIBC grading. Methods: The study included 169 consecutive patients with NMIBC (training cohort: n = 118, validation cohort: n = 51). A total of 3148 radiomic features were extracted, and one-way analysis of variance and least absolute shrinkage and selection operator were used to select features for building the radiomics score(Rad-score). Three models to predict NMIBC grading were developed using logistic regression analysis: a clinical model, a radiomics model and a radiomics-clinical combined nomogram model. The discrimination and calibration power and clinical applicability of the models were evaluated. The diagnostic performance of each model was compared by determining the area under the curve (AUC) in receiver operating characteristic (ROC) curve analysis. Results: A total of 24 features were used to build the Rad-score. A clinical model, a radiomics model, and a radiomics-clinical nomogram model that incorporated the Rad-score, age, and number of tumors were constructed. The radiomics model and nomogram showed AUCs of 0.910 and 0.931 in the validation set, which outperformed the clinical model (0.745). The decision curve analysis also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model. Conclusion: A radiomics-clinical combined nomogram model has the potential to be used as a non-invasive tool for the differentiating low-from high-grade NMIBCs.

MRI-Based Radiomics Nomogram for Predicting Prostate Cancer with Gray-Zone Prostate-Specific Antigen Levels to Reduce Unnecessary Biopsies.

OBJECTIVE: The aim of this study was to establish a predictive nomogram for predicting prostate cancer (PCa) in patients with gray-zone prostate-specific antigen (PSA) levels (4-10.0 ng/mL) based on radiomics and other traditional clinical parameters. METHODS: In all, 274 patients with gray-zone PSA levels were included in this retrospective study. They were randomly divided into training and validation sets (n = 191 and 83, respectively). Data on the clinical risk factors related to PCa with gray-zone PSA levels (such as Prostate Imaging Reporting and Data System, version 2.1 [PI-RADS V2.1] category, age, prostate volume, and serum PSA level) were collected for all patients. Lesion volumes of interest (VOI) from T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) imaging were annotated by two radiologists. The radiomics model, clinical model, and combined prediction model, which was presented on a nomogram by incorporating the radiomics signature and clinical and radiological risk factors for PCa, were developed using logistic regression. The area under the receiver operator characteristic (AUC-ROC) and decision, calibration curve were used to compare the three models for the diagnosis of PCa with gray-zone PSA levels. RESULTS: The predictive nomogram (AUC: 0.953) incorporating the radiomics score and PI-RADS V2.1 category, age, and the radiomics model (AUC: 0.941) afforded much higher diagnostic efficacy than the clinical model (AUC: 0.866). The addition of the rad score could improve the discriminatory performance of the clinical model. The decision curve analysis indicated that the radiomics or combined model could be more beneficial compared to the clinical model for the prediction of PCa. The nomogram showed good agreement for detecting PCa with gray-zone PSA levels between prediction and histopathologic confirmation. CONCLUSION: The nomogram, which combined the radiomics score and PI-RADS V2.1 category and age, is an effective and non-invasive method for predicting PCa. Furthermore, as well as good calibration and is clinically useful, which could reduce unnecessary prostate biopsies in patients having PCa with gray-zone PSA levels.

A meta-analysis of MRI-based radiomic features for predicting lymph node metastasis in patients with cervical cancer.

PURPOSE: To evaluate the ability of preoperative MRI-based radiomic features in predicting lymph node metastasis (LNM) in patients with cervical cancer. METHODS: PubMed, Embase, Web of Science, Cochrane Library databases, and four Chinese databases were searched to identify relevant studies published up until October 22, 2021. Two reviewers screened all papers independently for eligibility. We included diagnostic accuracy studies that used radiomics-MRI for LNM in patients with cervical cancer, using histopathology as the reference standard.Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Radiomics Quality Score. Overall diagnostic odds ratio (DOR), sensitivity, specificity and area under the curve (AUC) were calculated to assess the prediction efficacy of MRI-based radiomic features in patients with cervical cancer. Spearman's correlation coefficient was calculated and subgroup analysis performed to investigate causes of heterogeneity. RESULTS: Twelve studies comprising 793 female patients were included. The pooled DOR, sensitivity, specificity, and AUC of radiomics in detecting LNM were 12.08 [confidence interval (CI) 8.18, 17.85], 80% (72%, 87%), 76% (72%, 80%), and 0.83 (0.76, 0.89), respectively. The meta-analysis showed significant heterogeneity among the included studies. No threshold effect was detected. Subgroup analysis showed that multiple sequences, and radiomics combined with clinical factors, radiomics approach [DOR:15.49 (6.06, 39.62), 18.93 (8.46, 42.38), and 10.63 (6.23, 18.12), respectively] could slightly improve diagnostic performance compared with apparent diffusion coefficient-based radiomic features, T2 + dynamic contrast-enhanced MRI-based radiomic features, T2 images-based radiomic features, single radiomics, and human reading [DOR: 4.9 (1.91, 12.74), 7.63 (3.78, 15.38), 8.31 (3.05, 22.61), 16.10 (9.10, 28.47), and 6.46 (3.08, 13.56), respectively]. CONCLUSION: Our meta-analysis showed that preoperative MRI-based radiomic features performs well in predicting LNM in patients with cervical cancer. This noninvasive and convenient tool may be used to facilitate preoperative identification of LNM.

The Diagnostic Performance of Machine Learning-Based Radiomics of DCE-MRI in Predicting Axillary Lymph Node Metastasis in Breast Cancer: A Meta-Analysis.

OBJECTIVE: The aim of this study was to perform a meta-analysis to evaluate the diagnostic performance of machine learning(ML)-based radiomics of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) DCE-MRI in predicting axillary lymph node metastasis (ALNM) and sentinel lymph node metastasis(SLNM) in breast cancer. METHODS: English and Chinese databases were searched for original studies. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Radiomics Quality Score (RQS) were used to assess the methodological quality of the included studies. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were used to summarize the diagnostic accuracy. Spearman's correlation coefficient and subgroup analysis were performed to investigate the cause of the heterogeneity. RESULTS: Thirteen studies (1618 participants) were included in this meta-analysis. The pooled sensitivity, specificity, DOR, and AUC with 95% confidence intervals were 0.82 (0.75, 0.87), 0.83 (0.74, 0.89), 21.56 (10.60, 43.85), and 0.89 (0.86, 0.91), respectively. The meta-analysis showed significant heterogeneity among the included studies. There was no threshold effect in the test. The result of subgroup analysis showed that ML, 3.0 T, area of interest comprising the ALN, being manually drawn, and including ALNs and combined sentinel lymph node (SLN)s and ALNs groups could slightly improve diagnostic performance compared to deep learning, 1.5 T, area of interest comprising the breast tumor, semiautomatic scanning, and the SLN, respectively. CONCLUSIONS: ML-based radiomics of DCE-MRI has the potential to predict ALNM and SLNM accurately. The heterogeneity of the ALNM and SLNM diagnoses included between the studies is a major limitation.

Long non-coding RNA ABHD11-AS1 promotes colorectal cancer development through regulation of miR-133a/SOX4 axis.

Recently, lncRNA has been verified to regulate the development and progression of tumor. LncRNA ABHD11-AS1 has been proven to serve as an oncogene in several cancers. However, the role of ABHD11-AS1 in colorectal cancer remains totally unknown. In the present study, qRT-PCR assay revealed that ABHD11-AS1 expression was markedly higher in colorectal cancer tissues and cell lines. In addition, patients who displayed overexpression of ABHD11-AS1 showed a significantly poorer progression free survival (PFS) and overall survival (OS) by Kaplan-Meier analysis. Loss-of-function experiments suggested that silencing of ABHD11-AS1 expression could significantly reduce the proliferation, colony formation, migration and invasion of colorectal cancer cells, and increase cell apoptosis. Moreover, bioinformatics analysis, biotin pull-down assay, luciferase reporter assay, and RIP assay disclosed that ABHD11-AS1 straightly interacted with miR-133a. We also found that SOX4 was a downstream target of miR-133a and ABHD11-AS1 subsequently exerted its biological effects via modulating the expression of SOX4 in colorectal cancer cells. Collectively, these findings manifested that the ABHD11-AS1/miR-133a/SOX4 axis may be a cogitable and promising therapeutic target for colorectal cancer.

A meta-analysis of use of Prostate Imaging Reporting and Data System Version 2 (PI-RADS V2) with multiparametric MR imaging for the detection of prostate cancer.

OBJECTIVES: This meta-analysis was undertaken to review the diagnostic accuracy of PI-RADS V2 for prostate cancer (PCa) detection with multiparametric MR (mp-MR). METHODS: A comprehensive literature search of electronic databases was performed by two observers independently. Inclusion criteria were original research using the PI-RADS V2 system in reporting prostate MRI. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Data necessary to complete 2 × 2 contingency tables were obtained from the included studies. RESULTS: Thirteen studies (2,049 patients) were analysed. This is an initial meta-analysis of PI-RADs V2 and the overall diagnostic accuracy in diagnosing PCa was as follows: pooled sensitivity, 0.85 (0.78-0.91); pooled specificity, 0.71 (0.60-0.80); pooled positive likelihood ratio (LR+), 2.92 (2.09-4.09); pooled negative likelihood ratio (LR-), 0.21 (0.14-0.31); pooled diagnostic odds ratio (DOR), 14.08 (7.93-25.01), respectively. Positive predictive values ranged from 0.54 to 0.97 and negative predictive values ranged from 0.26 to 0.92. CONCLUSION: Currently available evidence indicates that PI-RADS V2 appears to have good diagnostic accuracy in patients with PCa lesions with high sensitivity and moderate specificity. However, no recommendation regarding the best threshold can be provided because of heterogeneity. KEY POINTS: • PI-RADS V2 shows good diagnostic accuracy for PCa detection. • Initially pooled specificity of PI-RADS v2 remains moderate. • PCa detection is increased by experienced radiologists. • There is currently a high heterogeneity in prostate diagnostics with MRI.

The utility of diffusion MRI with quantitative ADC measurements for differentiating high-grade from low-grade cerebral gliomas: Evidence from a meta-analysis.

OBJECTIVE: The aim of this meta-analysis was to predict the grades of cerebral gliomas using quantitative apparent diffusion coefficient (ADC) values. MATERIALS AND METHODS: A comprehensive search of the PubMed, EMBASE, Web of Science, and Cochrane Library databases was performed up to 8, 2016. The quality assessment of diagnostic accuracy studies (QUADAS 2) was used to evaluate the quality of studies. Statistical analyses included pooling of sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio' (NLR), diagnostic odds ratio (DOR), and diagnostic accuracy values of the included studies using the summary receiver operating characteristic (SROC). All analyses were conducted using STATA (version 12.0), RevMan (version 5.3), and Meta-Disc 1.4 software programs. RESULTS: Fifteen studies were analyzed and included a total of 821 patients and 821 lesions. In regards to the diagnostic accuracy of ADC maps, the pooled SEN, SPE, PLR, NLR, and DOR with 95%CIs were 0.82 [95%CI: 0.76, 0.87] and 0.75 [95%CI: 0.67, 0.81], 3.24 [95%CI: 2.48, 4.24], 0.24 [95%CI: 0.17, 0.33], and 13.60 [95%CI: 8.37, 22.07], respectively. The SROC curve showed an AUC of 0.85. Deeks testing confirmed no significant publication bias in all studies. CONCLUSION: Our findings indicate that quantitative ADC values have high accuracy in separating high-grade from low-grade cerebral gliomas. Further studies using a standardized methodology may help guide the use of ADC values for clinical decision-making.

Relationship between genotypes and clinical manifestation, pathology, and cccDNA in Chinese children with hepatitis B virus-associated glomerulonephritis.

BACKGROUND: Hepatitis B virus-associated glomerulonephritis (HBV-GN) is one of the extrahepatic manifestations after HBV infection, which would cause great clinical harm to people. The present study was undertaken to investigate the HBV-GN genotypes and its clinical relevance in Chinese children. METHODS: A total of 41 HBV-infected children diagnosed with HBV-GN were enrolled in the study. All patients underwent liver and kidney biopsy. The genotypes and cccDNA were detected in their serum samples to analyze the relationship between HBV genotypes and clinical characteristics, cccDNA, and pathology. RESULTS: Among the 41 children with HBV-GN, 29 (70.7%) had genotype C, 10 (24.4%) had genotype B, 2 (4.9%) had genotype B/C, and none of them had genotype non-B/C. Most children had genotypes B or C; moreover, the genotype C was the most frequent one. The incidence of hematuria and albuminuria, reduction in complement C3, increase in serum alanine aminotransferase levels and renal insufficiency in the children with genotype C were significantly higher than those in the children with genotype B (P<0.05); however, there was no statistically significant difference in hypertension and hepatomegaly (P>0.05). The frequency of HBV cccDNA positive in the genotype C group was significantly higher than that in the genotype B group (72.4% vs. 30.0%, P<0.05). No difference was observed in hepatic inflammation grades and stages of fibrosis between the two groups (P>0.05). CONCLUSIONS: Genotype C was the most frequent genotype in the described group of patients with HBV-GN, and the liver and kidney damage indicators were more likely to occur in patients with genotype C.

Health Insurance and Health Status: Exploring the Causal Effect from a Policy Intervention.

Whether health insurance matters for health has long been a central issue for debate when assessing the full value of health insurance coverage in both developed and developing countries. In 2007, the government-led Urban Resident Basic Medical Insurance (URBMI) program was piloted in China, followed by a nationwide implementation in 2009. Different premium subsidies by government across cities and groups provide a unique opportunity to employ the instrumental variables estimation approach to identify the causal effects of health insurance on health. Using a national panel survey of the URBMI, we find that URBMI beneficiaries experience statistically better health than the uninsured. Furthermore, the insurance health benefit appears to be stronger for groups with disadvantaged education and income than for their counterparts. In addition, the insured receive more and better inpatient care, without paying more for services. Copyright © 2015 John Wiley & Sons, Ltd.

Accuracy of combined dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging for breast cancer detection: a meta-analysis.

BACKGROUND: Magnetic resonance imaging (MRI) is increasingly being used to examine patients with suspected breast cancer. PURPOSE: To determine the diagnostic performance of combined dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) for breast cancer detection. MATERIAL AND METHODS: A comprehensive search of the PUBMED, EMBASE, Web of Science, and Cochrane Library databases was performed up to September 2014. Statistical analysis included pooling of sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and diagnostic accuracy using the summary receiver operating characteristic (SROC). All analyses were conducted using STATA (version 12.0), RevMan (version 5.2), and Meta-Disc 1.4 software programs. RESULTS: Fourteen studies were analyzed, which included a total of 1140 patients with 1276 breast lesions. The pooled sensitivity and specificity of combined DCE-MRI and DWI were 91.6% and 85.5%, respectively. The pooled sensitivity and specificity of DWI-MRI were 86.0% and 75.6%, respectively. The pooled sensitivity and specificity of DCE-MRI were 93.2% and 71.1%. The area under the SROC curve (AUC-SROC) of combined DCE-MRI and DWI was 0.94, the DCE-MRI of 0.85. Deeks testing confirmed no significant publication bias in all studies. CONCLUSION: Combined DCE-MRI and DWI had superior diagnostic accuracy than either DCE-MRI or DWI alone for the diagnosis of breast cancer.

[Clinical and pathological differences between children with various genotypes of hepatitis B virus-associated glomerulonephritis].

OBJECTIVE: To compare the clinical and pathological features between children with various genotypes of hepatitis B virus-associated glomerulonephritis (HBV-GN). METHODS: Forty-one children with HBV-GN concurrently undergoing liver and renal biopsy were randomly selected. Serum specimens were collected for genotyping and hepatitis B virus (HBV) cccDNA assay. The clinical, pathological, and HBV cccDNA differences between HBV-GN children of various genotypes were analyzed. RESULTS: Among the 41 HBV-GN children, 29 (71%) were genotype C, 10 (24%) were genotype B, and 2 (5%) were genotype B/C. The incidence rates of hematuria, albuminuria, complement 3 decrease, alanine transaminase increase, and renal insufficiency in the genotype C group were significantly higher than those in the genotype B group (P<0.05). Similarly, the HBV cccDNA positive rate was significantly higher in the genotype C group than that in the genotype B group. No difference was observed in the distribution of pathological types of renal tissues betwee the two geonotype groups. There were no significant differences in the degrees of hepatic inflammation and fibrosis between the two groups. CONCLUSIONS: Mainly genotypes C and B occur in children with HBV-GN and the former genotype is dominant. The clinical symptoms of patients with genotype C are more serious than those with genotype B. However, there is no difference in the pathological features between them.

Upregulation of microRNA 181c expression in gastric cancer tissues and plasma.

OBJECTIVE: To test the microRNA-181c (miR-181c) expression in tissues and plasma of gastric cancer (GC) cases, analyze any correlations, and explore the possibility of miR-181c as a potential molecular marker for GC diagnosis. MATERIALS AND METHODS: Relative miR-181c expression levels in cancers and plasma from 30 GC patients was tested using reverse transcription?real-time fluorescent quantitation PCR and compared to that in samples from 30 gastric ulcer and 30 chronic gastritis patients. RESULTS: The miR-181c expression level in the GC tissues was significantly higher than that in the gastric ulcer and chronic gastritis tissues (P = 0.000), as was the miR-181c expression level in the GC plasma (P = 0.000). We determined that miR-181c expression in GC plasma was positively correlated to its expression in the GC tissues (P = 0.000). CONCLUSIONS: The expression of miR-181c is upregulated in GC tissues and plasma, and the miR-181c expression level in GC plasma is positively correlated to that in the corresponding cancer tissues. Plasma miR-181c is possibly a new serological marker for GC diagnosis.

[Relationship between B/C genotype of hepatitis B virus and hepatitis B virus related-nephritis in children].

OBJECTIVE: To investigate the relationship between genotype of hepatitis B virus and hepatitis B virus related-glomerular nephritis in (HBV-GN) children. METHOD: Totally 176 HBV-DNA positive children with chronic hepatitis B were randomly collected. Among the 176 patients, 92 were HBV carriers, 84 were cases with chronic hepatitis. The genotypes of their serum HBV, liver function, and HBV-DNA load were detected. When children showed nephrotic syndrome, renal biopsy was performed. RESULT: Of the serum samples of 176 cases, 85 (48.3%) were genotype C, 72 (40.9%) were genotype B, 13 (7.4%) were genotype B/C, and 6 (3.4%) were non-B/C genotype which were excluded. Among the analyzed 157 cases, the ratio of HBV-GN in the HBeAg positive group (78.3%) was significantly higher than that in the negative group (21.7%) (χ(2) = 18.301, P < 0.001). And, the ratio of HBV-GN in the genotype C group (73.9%) was significantly higher than that in the genotype B group (26.1%) (P < 0.039). The ratio of hematuria or proteinuria in the genotype C group (20%, 18.8%) was significantly higher than that in the genotype B group (8.3%, 5.6%) (P < 0.039; P value = 0.013); and the alteration of ALT or C3 in the genotype C group (10.2%, 15.3%) was more frequent than those in the genotype B group (2.8%, 2.8%) (P = 0.005; P = 0.008). There were no significant differences in kidney dysfunction or hepatomegaly. Further, the ratio of HBV-GN was more significantly frequent in HBV-DNA highly loading group (79.2%) than which in HBV-DNA lowly loading group (20.8%) (P = 0.000). Finally, in HBV-GN group, genotype C cases (88.2%) more frequently had high HBV-DNA load condition than genotype B cases (11.8%) (P = 0.021). CONCLUSION: Children with HBV infection in Gansu province showed mainly genotypes C or B, while genotype C seemingly predominant. Patients with genotype C more frequently showed proteinuria or hematuria. The high HBV-DNA load may be related with HBV-GN. It is a potential reason in the mechanism of HBV-GN that patients with genotype C had more possibility to have HBV-DNA high load. Analysis of HBV genotype for HBV patients maybe helpful in diagnosis and treatment.

The New Cooperative Medical Scheme in rural China: does more coverage mean more service and better health?

This paper explores the impact of the New Cooperative Medical Scheme (NCMS), a newly adopted public health insurance program in rural China. Using a longitudinal sample drawn from the China Health and Nutrition Survey (CHNS), we employed multiple estimation strategies (individual fixed-effect models, instrumental variable estimation, and difference-in-differences estimation with propensity score matching) to correct the potential selection bias. We find that participating in the NCMS significantly decreases the use of traditional Chinese folk doctors and increases the utilization of preventive care, particularly general physical examinations. However, we do not find that the NCMS decreases out-of-pocket expenditure nor do we find that it increases utilization of formal medical service or improves health status, as measured by self-reported health status and by sickness or injury in the past four weeks. Our study indicates that despite the wide expansion of coverage, the impact of the NCMS is still limited.

A novel radio over fiber system with DWDM mm-wave generation and wavelength reuse for upstream data connection.

We proposed and experimentally demonstrated a novel radio-over-fiber architecture using an electrical mixer and an optical intensity modulator based on double side-band modulation scheme to generate dense wavelength-division multiplexing (DWDM) optical millimeter for carrying downstream data and centralized lightwave for carrying upstream data. Since the remaining optical carriers with high power have been reused, the optical power is effectively utilized; therefore the system cost can be reduced.