Distribution-Invariant Differential Privacy.

Differential privacy is becoming one gold standard for protecting the privacy of publicly shared data. It has been widely used in social science, data science, public health, information technology, and the U.S. decennial census. Nevertheless, to guarantee differential privacy, existing methods may unavoidably alter the conclusion of original data analysis, as privatization often changes the sample distribution. This phenomenon is known as the trade-off between privacy protection and statistical accuracy. In this work, we mitigate this trade-off by developing a distribution-invariant privatization (DIP) method to reconcile both high statistical accuracy and strict differential privacy. As a result, any downstream statistical or machine learning task yields essentially the same conclusion as if one used the original data. Numerically, under the same strictness of privacy protection, DIP achieves superior statistical accuracy in a wide range of simulation studies and real-world benchmarks.

Modeling Pregnancy Outcomes through Sequentially Nested Regression Models.

The polycystic ovary syndrome (PCOS) is a most common cause of infertility among women of reproductive age. Unfortunately, the etiology of PCOS is poorly understood. Large scale clinical trials for Pregnancy in Polycystic Ovary Syndrome (PPCOS) were conducted to evaluate the effectiveness of treatments. Ovulation, pregnancy, and live birth are three sequentially nested binary outcomes, typically analyzed separately. However, the separate models may lose power in detecting the treatment effects and influential variables for live birth, due to decreased sample sizes and unbalanced event counts. It has been a long-held hypothesis among the clinicians that some of the important variables for early pregnancy outcomes may continue their influence on live birth. To consider this possibility, we develop an ℓ 0-norm based regularization method in favor of variables that have been identified from an earlier stage. Our approach explicitly bridges the connections across nested outcomes through computationally easy algorithms and enjoys theoretical guarantee of estimation and variable selection. By analyzing the PPCOS data, we successfully uncover the hidden influence of risk factors on live birth, which confirm clinical experience. Moreover, we provide novel infertility treatment recommendations (e.g., letrozole vs clomiphene citrate) for women with PCOS to improve their chances of live birth.

RA Fibroblast-Like Synoviocytes Derived Extracellular Vesicles Promote Angiogenesis by miRNA-1972 Targeting p53/mTOR Signaling in Vascular Endotheliocyte.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammatory in joints. Invasive pannus is a characteristic pathological feature of RA. RA fibroblast-like synoviocytes (FLSs) are showed tumor-like biological characters that facilitate pannus generation. Importantly, it has been documented that extracellular vesicle (EVs) derived microRNAs have a vital role of angiogenesis in various immune inflammatory diseases. However, whether RA FLSs derived EVs can facilitate angiogenesis and the underlying mechanism is undefined. Herein, we aim to investigate the key role of RA FLSs derived EVs on angiogenesis in endothelial cells (ECs). We indicate that RA FLSs derived EVs promote ECs angiogenesis by enhancing migration and tube formation of ECs in vitro. Also, we confirm that RA FLSs derived EVs can significantly facilitate ECs angiogenesis with a matrigel angiogenesis mice model. In terms of the mechanisms, both RNAs and proteins in EVs play roles in promoting ECs angiogenesis, but the RNA parts are more fundamental in this process. By combining microRNA sequencing and qPCR results, miR-1972 is identified to facilitate ECs angiogenesis. The blockage of miR-1972 significantly abrogated the angiogenesis stimulative ability of RA FLSs derived EVs in ECs, while the overexpression of miR-1972 reversed the effect in ECs. Specifically, the p53 level is decreased, and the phosphorylated mTOR is upregulated in miR-1972 overexpressed ECs, indicating that miR-1972 expedites angiogenesis through p53/mTOR pathway. Collectively, RA FLSs derived EVs can promote ECs angiogenesis via miR-1972 targeted p53/mTOR signaling, targeting on RA FLSs derived EVs or miR-1972 provides a promising strategy for the treatment of patients with RA.

LncRNA NEAT1_1 suppresses tumor-like biologic behaviors of fibroblast-like synoviocytes by targeting the miR-221-3p/uPAR axis in rheumatoid arthritis.

Fibroblast-like synoviocytes (FLSs) are the predominant effector cells in the pathological progression of rheumatoid arthritis (RA). Therefore, elucidating the underlying molecular mechanism of the biologic behaviors in RA-FLSs will be helpful in developing the potent targets for the treatment of RA. We have previously documented that the tumor-like biologic behaviors of RA-FLSs are exacerbated by urokinase-type plasminogen activator receptor (uPAR), a specifically up-regulated receptor in RA-FLSs. Here, we investigate the further mechanism of uPAR and clarify its function in RA-FLSs. We demonstrate that miR-221-3p positively correlates to uPAR and regulates uPAR level in RA-FLSs. Simultaneously, one long noncoding RNA, nuclear paraspeckle assembly transcript 1_1 (NEAT1_1) is identified, which can predictively target miR-221-3p at three sites, indicating a strong possibility of being a competing endogenous RNA in RA-FLSs. Interestingly, NEAT1_1 and miR-221-3p can colocate in the nucleus and cytoplasm in RA-FLSs. Importantly, NEAT1_1 can act as a rheostat for the miR-221-3p/uPAR axis and the downstream JAK signaling. In line with the biologic function, NEAT1_1 negatively regulates the tumor-like characters, and cytokine secretions of RA-FLSs. Collectively, our data provide new insight into the mechanisms of NEAT1_1 in modulating RA-FLSs tumor-like behaviors. The targeting of NEAT1_1 and miR-221-3p/uPAR axis may have a promising therapeutic role in patients with RA.

Data Flush.

Data perturbation is a technique for generating synthetic data by adding "noise" to raw data, which has an array of applications in science and engineering, primarily in data security and privacy. One challenge for data perturbation is that it usually produces synthetic data resulting in information loss at the expense of privacy protection. The information loss, in turn, renders the accuracy loss for any statistical or machine learning method based on the synthetic data, weakening downstream analysis and deteriorating in machine learning. In this article, we introduce and advocate a fundamental principle of data perturbation, which requires the preservation of the distribution of raw data. To achieve this, we propose a new scheme, named data flush, which ascertains the validity of the downstream analysis and maintains the predictive accuracy of a learning task. It perturbs data nonlinearly while accommodating the requirement of strict privacy protection, for instance, differential privacy. We highlight multiple facets of data flush through examples.

Brain Regions Identified as Being Associated with Verbal Reasoning through the Use of Imaging Regression via Internal Variation.

Brain-imaging data have been increasingly used to understand intellectual disabilities. Despite significant progress in biomedical research, the mechanisms for most of the intellectual disabilities remain unknown. Finding the underlying neurological mechanisms has been proved difficult, especially in children due to the rapid development of their brains. We investigate verbal reasoning, which is a reliable measure of individuals' general intellectual abilities, and develop a class of high-order imaging regression models to identify brain subregions which might be associated with this specific intellectual ability. A key novelty of our method is to take advantage of spatial brain structures, and specifically the piecewise smooth nature of most imaging coefficients in the form of high-order tensors. Our approach provides an effective and urgently needed method for identifying brain subregions potentially underlying certain intellectual disabilities. The idea behind our approach is a carefully constructed concept called Internal Variation (IV). The IV employs tensor decomposition and provides a computationally feasible substitution for Total Variation (TV), which has been considered in the literature to deal with similar problems but is problematic in high order tensor regression. Before applying our method to analyze the real data, we conduct comprehensive simulation studies to demonstrate the validity of our method in imaging signal identification. Then, we present our results from the analysis of a dataset based on the Philadelphia Neurodevelopmental Cohort for which we preprocessed the data including re-orienting, bias-field correcting, extracting, normalizing and registering the magnetic resonance images from 978 individuals. Our analysis identified a subregion across the cingulate cortex and the corpus callosum as being associated with individuals' verbal reasoning ability, which, to the best of our knowledge, is a novel region that has not been reported in the literature. This finding is useful in further investigation of functional mechansims for verbal reasoning.

[Clinical study of digital clear aligner treatment of 33 adult periodontal disease patients with malocclusion].

PURPOSE: The purpose of this study was to investigate the periodontal status in adult periodontal disease patients with malocclusion treated with digital clear aligners. METHODS: Thirty-three patients with periodontal disease who needed orthodontic treatment were selected. The patients were randomly divided into 2 groups, digital clear aligners group (experimental group, 16 patients) and fixed appliances group (control group, 17 patients). Bleeding index (BI), probing depth(PD), plaque index(PLI) and gingival index(GI) were recorded at baseline and 1, 3, 6 and 9 months during orthodontic treatment. SPSS 17.0 software package was used to analyze and compare the data of periodontal status between two groups. RESULTS: 1, 3, 6, and 9 months after orthodontic treatment, clinical parameters of the control group were significantly higher than baseline(P<0.05). The same measurements of the experimental group showed no significant differences at 1, 3, 6, and 9 months of treatment (P>0.05). After 1, 3, 6, and 9 months of treatment, the clinical parameters of BI, PLI and GI in the experimental group were significantly lower than the control group(P<0.05); PD in the experimental group was smaller than the control group, but there was no significant difference(P>0.05). CONCLUSIONS: Compared with conventional fixed appliance, clear aligner of digitalization can more effectively maintain periodontal heath in adult periodontal disease patients with malocclusion.

LncRNA PICSAR promotes cell proliferation, migration and invasion of fibroblast-like synoviocytes by sponging miRNA-4701-5p in rheumatoid arthritis.

BACKGROUND: Long non-coding RNAs (lncRNAs) have drawn increasing attention because they play a pivotal role in various types of autoimmune diseases, including rheumatoid arthritis (RA). Fibroblast-like synoviocytes (FLSs), a prominent component of hyperplastic synovial pannus tissue, are the primary effector cells in RA synovial hyperplasia and invasion which can lead to joint destruction. In this study, we investigated whether lncRNAs could act as competing endogenous RNAs to regulate the pathological behaviors of RA-FLSs. METHODS: LncRNA microarray was conducted to establish lncRNA expression profiles in FLSs isolated from RA patients and healthy controls (HCs). Differentially expressed lncRNAs were verified by quantitative real-time PCR (qRT-PCR) on RA-FLSs and synovial fluid. The functional role of lncRNA PICSAR downregulation was evaluated in RA-FLSs. We conducted molecular biological analysis to predict miRNAs which have a potential binding site for PICSAR and further refined the results by qRT-PCR. Luciferase reporter assay was adopted to validate the interaction of lncRNA PICSAR and miR-4701-5p. Western Blot and qPCR were used to identify the target gene and protein. The functional role of miR-4701-5p upregulation was examined in RA-FLSs. FINDINGS: We identified a long intergenic non-protein-coding RNA162 (LINC00162), also known as lncRNA PICSAR (p38 inhibited cutaneous squamous cell carcinoma associated lincRNA), has significantly higher expression in RA-FLSs and RA synovial fluid. The cell proliferation, migration, invasion and proinflammatory cytokines production of RA-FLSs showed significant alterations after the lncRNA PICSAR suppression. Mechanistically, lncRNA PICSAR functioned through sponging miR-4701-5p in RA-FLSs. INTERPRETATION: Our results reveal PICSAR may exert an essential role in promoting synovial invasion and joint destruction by sponging miR-4701-5p in RA and that lncRNA PICSAR may act as a biomarker of RA.

Common genetic variants have associations with human cortical brain regions and risk of schizophrenia.

Schizophrenia is a highly heritable mental disorder and is reported to be associated with measurements in cortical regions of the human brain. In this study, we considered genome-wide association studies to uncover genetic effects on cortical regions and prodromal symptoms of schizophrenia. Specifically, area, thickness, and volume of 66 cortical regions derived from magnetic resonance imaging scans of 1,445 children and adolescents from the Philadelphia Neurodevelopmental Cohort were studied. Two common variants were identified as being associated with two prefrontal cortical regions (one significant variant rs11601331 on chromosome 11p11 for right rostral middle frontal gyral area, p = 1.97 × 10 -8 ; one suggestive variant rs2345981 on chromosome 6q11 for left frontal pole gyral volume, p = 2.07 × 10 -7 ), where the significance of rs11601331 was independently replicated on the Pediatric Imaging, Neurocognition, and Genetics study of size 1,239 (p = 9.19 × 10 -3 ). Moreover, genetic effects on schizophrenia were investigated based on a sample of 8,719 subjects. The two identified variants rs11601331 and rs2345981 showed significant association with the longest prodromal symptoms duration (p = 0.048 and p = 0.027, respectively).

Helios but not CD226, TIGIT and Foxp3 is a Potential Marker for CD4+ Treg Cells in Patients with Rheumatoid Arthritis.

BACKGROUND/AIMS: Rheumatoid arthritis (RA) is a progressive, chronic, even disabling systemic autoimmune disease. Imbalance between pathogenic immune cells and immunosuppressive cells is associated with the pathogenesis and development of RA and other autoimmune diseases. As Foxp3 is also expressed on activated CD4+ cells in the presence of inflammation, the identification of Treg cells in patients with RA remains a challenge. METHODS: Comprehensive analyses were carried out by Flow cytometry. Expression of Helios, CD226, T cell immunoreceptor with Ig and ITIM domains clinical samples and healthy controls. RESULTS: We have systemically examined three potential markers, Helios, CD226 and TIGIT, that are possibly related to Treg identification, and found that Helios expression on CD4+Foxp3+cells was decreased and negatively correlated with the disease activity of RA patients, while CD226 and TIGIT both showed elevated expression levels in CD4+Foxp3+cells in RA patients and they were not associated with disease activity of RA patients. CONCLUSION: Taken together, our findings indicate that CD4+CD25hiCD127low/-Foxp3+Helios+ may represent the real Treg cell population in patients with RA.

A systematic study of the genus Atlanticus Scudder, 1894 from Zhejiang, China (Orthoptera: Tettigoniidae: Tettigoniinae).

Six species of genus Atlanticus have been recorded from Zhejiang, China prior to this study. We describe 2 new species, A. fallax sp. nov. and A. interval. sp. nov. Their morphology, songs, COI genes and distributions are compared. The type specimens are deposited in East China Normal University, Biology of History Museum (ECNU).

Long Non-Coding RNA GAPLINC Promotes Tumor-Like Biologic Behaviors of Fibroblast-Like Synoviocytes as MicroRNA Sponging in Rheumatoid Arthritis Patients.

Rapidly accumulating evidence has now suggested that the long non-coding RNAs (LncRNAs), a large and diverse class of non-coding transcribed RNA molecules with diverse functional roles and mechanisms, play a major role in the pathogenesis of many human inflammatory diseases. Although some LncRNAs are overexpressed in plasma, T cell, and synovial tissues of patients with rheumatoid arthritis (RA), there is a dearth of knowledge in what role these transcripts play in fibroblast-like synoviocytes (FLSs) of these patients. Here, our studies showed that GAPLINC, a newly identified functional LncRNA in oncology, displayed a greater degree of expression in FLSs from RA than in patients with traumatic injury. GAPLINC suppression in RA-FLS cells revealed significant alterations in cell proliferation, invasion, migration, and proinflammatory cytokines production. Additionally, we performed a preliminary bioinformatics analysis of GAPLINC gene sequence in order to find its target molecules, using miRanda, PITA, RNAhybrid algorithms, Kyoto encyclopedia of genes and genomes, and gene ontology analysis. Since the results predicted that some of microRNAs and mRNA may interact with GAPLINC, we simulated a gene co-action network model based on a competitive endogenous RNA theory. Further verification of this model demonstrated that silencing of GAPLINC increased miR-382-5p and miR-575 expression. The results of this study suggest that GAPLINC may function as a novel microRNAs sponging agent affecting the biological characteristics of RA-FLSs. Additionally, GAPLINC may also promote RA-FLS tumor-like behaviors in a miR-382-5p-dependent and miR-575-dependent manner. Based upon these findings, LncRNA GAPLINC may provide a novel valuable therapeutic target for RA patients.

Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence.

We propose a novel multivariate model for analyzing hybrid traits and identifying genetic factors for comorbid conditions. Comorbidity is a common phenomenon in mental health in which an individual suffers from multiple disorders simultaneously. For example, in the Study of Addiction: Genetics and Environment (SAGE), alcohol and nicotine addiction were recorded through multiple assessments that we refer to as hybrid traits. Statistical inference for studying the genetic basis of hybrid traits has not been well-developed. Recent rank-based methods have been utilized for conducting association analyses of hybrid traits but do not inform the strength or direction of effects. To overcome this limitation, a parametric modeling framework is imperative. Although such parametric frameworks have been proposed in theory, they are neither well-developed nor extensively used in practice due to their reliance on complicated likelihood functions that have high computational complexity. Many existing parametric frameworks tend to instead use pseudo-likelihoods to reduce computational burdens. Here, we develop a model fitting algorithm for the full likelihood. Our extensive simulation studies demonstrate that inference based on the full likelihood can control the type-I error rate, and gains power and improves the effect size estimation when compared with several existing methods for hybrid models. These advantages remain even if the distribution of the latent variables is misspecified. After analyzing the SAGE data, we identify three genetic variants (rs7672861, rs958331, rs879330) that are significantly associated with the comorbidity of alcohol and nicotine addiction at the chromosome-wide level. Moreover, our approach has greater power in this analysis than several existing methods for hybrid traits.Although the analysis of the SAGE data motivated us to develop the model, it can be broadly applied to analyze any hybrid responses.

Cross-Foster Rederivation Compared with Antibiotic Administration in the Drinking Water to Eradicate Bordetella pseudohinzii.

Bordetella pseudohinzii is a microbial agent of potential importance in mice and has confounded pulmonary research at our institution. The purpose of this study was to evaluate cross-foster rederivation and antibiotic administration in the drinking water as methods to eradicate B. pseudohinzii. To evaluate the efficacy of cross-foster rederivation, 29 litters representing 16 strains of mice were cross-fostered from cages positive for B. pseudohinzii to B. pseudohinzii-negative Crl:CD1-Elite surrogate dams. To evaluate antibiotic administration, sulfamethoxazole and trimethoprim (TMS; 0.66 and 0.13 mg/mL, respectively) and tetracycline (4.5 mg/mL) were administered in the drinking water. We assessed 3 antibiotic treatment groups with 12 B. pseudohinzii-positive cages per group (6 cages of CD1 and 6 cages of C57BL/6 mice): TMS for 4 wk, TMS for 6 wk, and tetracycline for 6 wk. Of the 29 litters that underwent cross-foster rederivation, 24 were negative for B. pseudohinzii. Five of the 12 cages treated with TMS for 4 wk and 1 of the 12 cages treated with TMS for 6 wk were negative for B. pseudohinzii at 2 wk after treatment. Three of the 12 cages treated with tetracycline were negative for B. pseudohinzii at 2 wk after treatment. Pearson χ2 analysis revealed significant association between the method of eradication (cross-foster rederivation compared with antibiotic administration) and B. pseudohinzii infection, and an odds-ratio estimate from a logistic regression demonstrated that cross-foster rederivation was more successful. Whereas antibiotic administration in the drinking water failed to eradicate B. pseudohinzii, cross-foster rederivation was successful and has been used to establish a B. pseudohinzii-negative barrier.

Evolution and Vaccination of Influenza Virus.

In this study, we present an application paradigm in which an unsupervised machine learning approach is applied to the high-dimensional influenza genetic sequences to investigate whether vaccine is a driving force to the evolution of influenza virus. We first used a visualization approach to visualize the evolutionary paths of vaccine-controlled and non-vaccine-controlled influenza viruses in a low-dimensional space. We then quantified the evolutionary differences between their evolutionary trajectories through the use of within- and between-scatter matrices computation to provide the statistical confidence to support the visualization results. We used the influenza surface Hemagglutinin (HA) gene for this study as the HA gene is the major target of the immune system. The visualization is achieved without using any clustering methods or prior information about the influenza sequences. Our results clearly showed that the evolutionary trajectories between vaccine-controlled and non-vaccine-controlled influenza viruses are different and vaccine as an evolution driving force cannot be completely eliminated.

Genome-wide mediation analysis of psychiatric and cognitive traits through imaging phenotypes.

Heritability is well documented for psychiatric disorders and cognitive abilities which are, however, complex, involving both genetic and environmental factors. Hence, it remains challenging to discover which and how genetic variations contribute to such complex traits. In this article, they propose to use mediation analysis to bridge this gap, where neuroimaging phenotypes were utilized as intermediate variables. The Philadelphia Neurodevelopmental Cohort was investigated using genome-wide association studies (GWAS) and mediation analyses. Specifically, 951 participants were included with age ranging from 8 to 21 years. Two hundred and four neuroimaging measures were extracted from structural magnetic resonance imaging scans. GWAS were conducted for each measure to evaluate the SNP-based heritability. Furthermore, mediation analyses were employed to understand the mechanisms in which genetic variants have influence on pathological behaviors implicitly through neuroimaging phenotypes, and identified SNPs that would not be detected otherwise. Our analyses found that rs10494561, located in the intron region within NMNAT2, was associated with the severity of the prodromal symptoms of psychosis implicitly, mediated through the volume of the left hemisphere of the superior frontal region ( P=2.38×10-8). The gene NMNAT2 is known to be associated with brainstem degeneration, and produce cytoplasmic enzyme which is mainly expressed in the brain. Another SNP rs2285351 was found in the intron region of gene IFT122 which may be potentially associated with human spatial orientation ability through the area of the left hemisphere of the isthmuscingulate region ( P=3.70×10-8). Hum Brain Mapp 38:4088-4097, 2017. © 2017 Wiley Periodicals, Inc.

Feasibility and validity of a statistical adjustment to reduce self-report bias of height and weight in wave 1 of the Add Health study.

BACKGROUND: Bias in adolescent self-reported height and weight is well documented. Given the importance and widespread use of the National Longitudinal Study of Adolescent to Adult Health (Add Health) data for obesity research, we developed and tested the feasibility and validity of an empirically derived statistical correction for self-report bias in wave 1 (W1) of Add Health, a large panel study in the United States. METHODS: Participants in grades 7-12 with complete height and weight data at W1 were included (n = 20,175). We used measured and self-reported (SR) height and weight and relevant biopsychosocial factors from wave 2 (W2) of Add Health (n = 14,190) to identify sources of bias and derive the most efficient sex-specific estimates of corrected height and weight. Measured, SR, and corrected W2 BMI values were calculated and compared, including sensitivity and specificity. Final correction equations were applied to W1. RESULTS: After correction, weight status misclassification rates among those who underestimated their weight status were reduced from 6.6 to 5.7 % for males and from 8.0 to 5.6 % for females compared to self-report; and the correlation between SR and measured BMI in W2 increased slightly from 0.92 to 0.93. Among females, correction procedures resulted in a 3.4 % increase in sensitivity to detect overweight/obesity (BMI ≥ 25) and 5.9 % increase in sensitivity for obesity (BMI ≥ 30). CONCLUSIONS: Findings suggest that application of the proposed statistical corrections can reduce bias of self-report height and weight in W1 of the Add Health data and may be useful in some analyses. In particular, the corrected BMI values improve sensitivity --the ability to detect a true positive-for overweight/obesity among females, which addresses a major concern about self-report bias in obesity research. However, the correction does not improve sensitivity to identify underweight or healthy weight adolescents and so should be applied selectively based on research questions.

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

[RAPD analysis and construction of specific DNA probes between Pinellia ternata and Typhonium flagelliforme].

OBJECTIVE: To establish a molecular marking method to identify Pinellia ternata and Typhonium flagelliforme. METHODS: Twenty-two random oligonucleotide primers were used in RAPD analysis on the genomic DNA of two types of Pinellia ternata in Sichuan and two types of Typhonium flagelliforme in Guangxi. The special fragments were sequenced, marked as probes and then conducted Southern blot. RESULTS: A great deal of special bands was found between Pinellia ternata and Typhonium flagelliforme. A Pinellia ternata specific molecule was screened. CONCLUSION: RAPD analysis and specific DNA probes show potential value in the identification of Pinellia ternata and Typhonium flagelliforme.

Down-regulation of Bcl-XL by RNA interference suppresses cell growth and induces apoptosis in human esophageal cancer cells.

AIM: To determine the inhibitory effect of the vector-generated small interfering RNAs (siRNAs) on the expression of the Bcl-X(L) gene in established human esophageal cancer cells, and to investigate the effect of the Bcl-X(L) siRNAs on cell growth and apoptosis in esophageal cancer cells. METHODS: Three siRNA-expressing vectors targeting different sites of the Bcl-X(L) gene were constructed from pTZ-U6+1 vector. Cultured esophageal cancer cells were transfected with the siRNA-expressing vector (or the control vector) using lipofectamine 2000. Bcl-X(L) gene expression was determined with semiquantitative RT-PCR assay and Western blotting. Among the three siRNA-expressing vectors, the most highly functional vector and its effect on cell growth and apoptosis in esophageal cancer cells was further analyzed. RESULTS: Of the three siRNA-expressing vectors, siRNA-expressing vector No.1 was the most potent one which suppressed Bcl-X(L) mRNA production to 32.5% of that in the untreated esophageal cancer cells. Western blotting analysis showed that siRNA-expressing vector No.1 markedly down-regulated the expression of Bcl-X(L) in human esophageal cancer cells. Treatment of esophageal cancer cells with siRNA-expressing vector No.1 resulted in inhibition of cell growth and induction of apoptosis. CONCLUSION: Down-regulation of Bcl-X(L) by vector-generated small interfering RNAs can suppress cell growth and induce apoptosis in human esophageal cancer cells.