Search PubMed⌕ Search

Biomedical subjects

Xia Hong

Publications and source records attributed to Xia Hong.

At least 19 recordsLinked to original sources
PubMed2006

Socio-demographic variation of dementia subtypes in china: Methodology and results of a prevalence study in Beijing, Chengdu, Shanghai, and Xian.

OBJECTIVE: To characterize sociodemographic variations in the prevalence of AD and VaD in China. METHODS: Data were collected in a 1997-1998, cross-sectional, door-to-door prevalence survey of 34,807 community residents ages > or =55 years in Beijing, Shanghai, Chengdu and Xian. Initial diagnoses of AD and VaD were assessed by clinicians using standardized protocols, according to the NINCDS-ADRDA and NINDS-AIREN criteria; diagnoses were confirmed after 6 months by repeating neuropsychological evaluations. Prevalence odds ratios were estimated in logistic models adjusting for survey design, age, and other sociodemographic factors. RESULTS: We identified 732 prevalent cases of AD and 295 cases of VaD. Adjusting for all sociodemographic factors concurrently, prevalence odds of AD and VaD were higher in northern versus southern China. Age trends for AD appeared different in western and eastern China. AD also showed an age-adjusted elevation among women and, in the fully adjusted model, a gender education interaction indicating a female preponderance in the highest education group. North-south variation for VaD was age-dependent. In the fully adjusted model, for AD, widowed had significantly higher prevalence odds; for VaD, widowed persons and minorities had significantly lower prevalence odds; professionals had statistically significant and borderline lower prevalence odds for both VaD and AD; sales-service occupations had significantly lower odds for AD only. CONCLUSION: We observed variations in prevalence for AD and VaD in different regions and demographic groups in China that persisted after controlling for potential confounding factors. Sociodemographic factors are probable surrogates for conditions such as lifestyle, environment, comorbidities, and life expectancy.

Age Factors↗
PubMed2006

Low concentrations mono-butyl phthalate stimulates steroidogenesis by facilitating steroidogenic acute regulatory protein expression in mouse Leydig tumor cells (MLTC-1).

Di-n-butyl phthalate (DBP) is one of the most dominant phthalate esters and is widely distributed environmental contaminant. Although previous studies have demonstrated that DBP led to a variety of male reproductive abnormalities similar to those caused by androgen receptor antagonists, DBP and its active metabolite, mono-butyl phthalate (MBP), have been demonstrated no affinity for the androgen receptor, but rather exert anti-androgenic effect by altering testosterone biosynthesis. Furthermore, all these results were obtained from very high administrations of DBP or MBP. The purpose of this study was to determine the onset and the site of action of relatively low concentration of MBP on steroidogenesis in vitro. The mouse Leydig tumor cells (MLTC-1) was employed as a cellular model to investigate the effect of MBP on steroidogenesis. Various concentrations of MBP (1, 10, 100 and 1000nmol/l) and its solvent dimethyl sulfoxide (DMSO) were added to the medium for 24h followed by stimulation of some compounds such as human chorionic gonadotrophin (hCG), cholera toxin (CT), forskolin, cAMP analog 8-Br-cAMP, 22(R)-hydroxycholesterol (22R-HC) and pregnenolone. Progesterone in the medium and amounts of intracellular cAMP were measured by RIA. Expression of steroidogenic acute regulatory protein (StAR) was monitored by real-time PCR and Western blotting. The results revealed that the increases of progesterone production in the presence of hCG, CT, forskolin and 8-Br-cAMP were augmented by MBP. In contrast, the levels of intracellular cAMP exhibited no statistical significance when MLTC-1 cells were treated as above. These results implied that the site in the steroid biosynthesis pathway affected by MBP occurs after PKA activation in MLTC-1 cells. Moreover, supplementing the medium with 22R-HC and pregnenolone as progesterone precursors for P450 side chain cleavage enzyme (P450scc) and 3beta-hydroxysteroid dehydrogenase (3beta-HSD), respectively, resulted in no rise in progesterone production, making clear that MBP did not influence the P450scc and 3beta-HSD but on the rate-limiting step, cholesterol transportation into mitochondria. In fact, the above results were confirmed by the upgraded StAR expression in MBP-treated cells. These data support that MBP promotes steroid hormone production by facilitating StAR expression in MLTC-1 cells.

17-Hydroxysteroid Dehydrogenases↗
PubMed2006

Antiandrogenic activity of pyrethroid pesticides and their metabolite in reporter gene assay.

Many pesticides possess hormonal activity and have thus been classified as endocrine disruptors. Pyrethroids are commonly used pesticides worldwide, but little has been done to characterize their antiandrogenic activity potential. We tested three frequently encountered pyrethroids (fenvalerate, cypermethrin, permethrin) and their metabolite 3-phenoxybenzoic acid (3-PBA) for antiandrogenic and androgenic activity using a human androgen receptor (AR) mediated luciferase reporter gene assay in CV-1 African green monkey kidney cell. The assay displayed appropriate response to the known AR agonist 5alpha-dihydrotestosterone and AR antagonist nilutamide and flutamide. At 0.1mM, all the three tested pyrethroids significantly suppressed the luciferase expression. Further, their metabolite 3-PBA also showed antagonist activity. None of the test chemicals showed androgenic activity. Through the antiandrogenic pathways, exposure to certain pyrethroids may contribute to the damage of reproductive system. In conclusion, pyrethroid pesticides can act as antiandrogen in vitro, and metabolizing to 3-PBA cannot eliminate the antagonist activity. This result provides useful information for risk assessment of pyrethroid pesticides.

Androgen Antagonists↗
PubMed2006

Structural insights into histone demethylation by JMJD2 family members.

Posttranslational modifications of histones regulate chromatin structure and gene expression. Histone demethylases, members of a newly emerging transcription-factor family, remove methyl groups from the lysine residues of the histone tails and thereby regulate the transcriptional activity of target genes. JmjC-domain-containing proteins have been predicted to be demethylases. For example, the JmjC-containing protein JMJD2A has been characterized as a H3-K9me3- and H3-K36me3-specific demethylase. Here, structures of the catalytic-core domain of JMJD2A with and without alpha-ketoglutarate in the presence of Fe2+ have been determined by X-ray crystallography. The structure of the core domain, consisting of the JmjN domain, the JmjC domain, the C-terminal domain, and a zinc-finger motif, revealed the unique elements that form a potential substrate binding pocket. Sited-directed mutagenesis in conjunction with demethylase activity assays allowed us to propose a molecular model for substrate selection by the JMJD2 histone demethylase family.

Amino Acid Sequence↗
PubMed2006

Carbaryl inhibits basal and FSH-induced progesterone biosynthesis of primary human granulosa-lutein cells.

Carbaryl is known to impede female reproductive function, however, the mechanisms through which the adverse effects are mediated are not clearly elucidated. In order to get insight into the mechanisms, this study was conducted to raise fresh concerns about the potential effects of carbaryl on steroidogenesis by primary human granulosa-lutein cells (hGLCs) and explore the possible nature of this action. hGLCs were co-incubated with various concentrations of carbaryl at 0, 1, 5, 25, 125 micromol/L for 24 h to examine effects of this carbamate pesticide on progesterone accumulation. We observed that the carbaryl inhibited basal and FSH-induced progesterone production in a dose-dependent manner. We also investigated the effects of carbaryl on 22(R)-hydroxycholesterol (22R-HC)-stimulated progesterone yield, basal and FSH-stimulated StAR gene expression and cyclic adenosine monophosphate (cAMP) production, as well as forskolin (non-specific activator of adenylyl cyclase)-induced progesterone and cAMP production of hGLCs. We found that the decreased progesterone biosynthesis was accompanied with a reduced cAMP abundance on both basal and FSH-induced condition. Furthermore, our results demonstrated that the 22R-HC could remove the carbaryl-induced restraint of progesterone biosynthesis, suggesting that carbaryl caused a disruption of cholesterol transport across mitochondrial membranes, which was further confirmed by the observation that carbaryl inhibited the gene expression of steroidogenic acute regulatory protein (StAR). In addition, the inhibitory effects of carbaryl on progesterone and cAMP production were completely reversed by addition of forskolin to the cell culture, which indicated a repaired site on the upstream components of adenylate cyclase or adenylate cyclase per se by carbaryl in the cAMP-mediated signal pathway. All the effects mentioned above were not due to a detrimental action of carbaryl on cell viability by MTS assay. In conclusion, carbaryl may inhibit steroidogenesis, at least in part, by obstructing the delivery of cholesterol over mitochondrial membranes and attenuating cAMP generation.

Carbaryl↗
PubMed2006

A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

Algorithms↗
PubMed2006

[The relationship between hormesis of proliferation and oxidative stress induced by sodium arsenite in human embryo lung fibroblasts].

OBJECTIVE: To investigate the relationship between the hormesis of proliferation and oxidative stress induced by sodium arsenite (Na(2)AsO(2)) in human embryo lung fibroblasts (HELF). METHODS: HELF were treated with Na(2)AsO(2) of 0.0, 0.1, 0.5, 1.0, 5.0 and 10.0 micromol/L for 4 hours or 24 hours, respectively. The cell proliferation, the reactive oxygen species (ROS) level, the malondialdehyde (MDA) content and the activity of glutathione peroxide (GSH-Px) and the superoxide dismutase (SOD) in HELF were detected respectively. RESULTS: The HELF proliferation induced by 0.1 and 0.5 micromol/L Na(2)AsO(2) was significantly higher than that in the control group (P < 0.01). The HELF proliferation induced by 5.0 and 10.0 micromol/L Na(2)AsO(2) was significantly lower than that in the control group (P < 0.01) with the dose-effect relation of an inverted U curve. The ROS level induced by Na(2)AsO(2) of between 0.5 and 10.0 micromol/L was significantly increased (P < 0.05, P < 0.01). The positive correlation was found between the ROS level and the exposure dose of Na(2)AsO(2) (r = 0.934, P < 0.01). The 5.0 and 10.0 micromol/L Na(2)AsO(2) induced the significant increase of the MDA contents (P < 0.01) and the significant decrease of the GSH-Px activity compared to those in the control group (P < 0.01). The SOD activity in 0.5 micromol/L Na(2)AsO(2) group was significantly higher than that in the control group (P < 0.01) while the SOD activity induced by 5.0 and 10.0 micromol/L Na(2)AsO(2) was significantly decreased (P < 0.01) if compared with the control group with the dose-effect relation of an inverted U curve. CONCLUSION: The sodium arsenite can induce the hormesis of proliferation in HELF with the dose-effect relation of an inverted U curve. The mechanisms probably relates to different levels of oxidative stress induced by sodium arsenite of different concentrations.

Arsenites↗
PubMed2005

Prototype of immunochromatographic assay strips using colloidal CdTe nanocrystals as biological luminescent label.

Colloidal semiconductor nanocrystals have attracted considerable attention as a novel biological luminescent label. The bioinorganic conjugates of luminescent CdTe nanocrystals and protein, including CdTe/BSA (bovine serum albumin) and CdTe/MAB (mouse monoclonal antibody against hepatitis B surface antigen), were formed via electrostatic/coordination self-assembly. Pure CdTe nanocrystals, CdTe/BSA and CdTe/MAB were used in the immunochromatographic assay experiments, respectively. And the results indicated that CdTe nanocrystals could be used and developed as a novel label with good stability, high sensitivity and facile determination of several analytes in immunochromatographic assay strips.

Animals↗
PubMed2005

Dementia subtypes in China: prevalence in Beijing, Xian, Shanghai, and Chengdu.

BACKGROUND: Prevalences of Alzheimer disease (AD) and vascular dementia (VaD) in China reportedly differ from those in Western countries. OBJECTIVE: To estimate prevalence of AD and VaD in 4 regions of China. DESIGN: Cross-sectional, population-based prevalence survey with a stratified, multistage cluster sampling design. SETTING: Rural (n = 99) and urbanized (n = 71) communities of Beijing, Xian, Shanghai, and Chengdu. PARTICIPANTS: A sample of 34 807 community residents (94% of those eligible) 55 years or older. MAIN OUTCOME MEASURES: Participants were screened with the Chinese Mini-Mental State Examination. Those who screened positive (n = 3950) underwent a standardized diagnostic workup. Screening sensitivity was assessed in a 3.3% random sample (n = 1008 of the 30 857 who passed the screening). Diagnoses of AD and VaD were made according to National Institute of Neurological and Communicative Diseases and Stroke-Alzheimer Disease and Related Disorders Association and National Institute of Neurological Disorders and Stroke-Association Internationale pour la Recherche et l'Enseignement en Neurosciences criteria, respectively. Final diagnoses were made after a 6-month confirmation interval. RESULTS: We identified 732 AD cases and 295 VaD cases. Prevalence in persons 65 years or older was 3.5% (95% confidence interval, 3.0%-3.9%) for AD and 1.1% (95% confidence interval, 0.9%-1.1%) for VaD. After post hoc correction for negative screening errors, prevalence increased to 4.8% for AD and remained at 1.1% for VaD. CONCLUSION: Prevalence of dementia subtypes in China is comparable with that in Western countries.

Aged↗
PubMed2005

Progression of mild cognitive impairment to Alzheimer's or vascular dementia versus normative aging among elderly Chinese.

To compare differences in evolutionary progressions from Mild Cognitive Impairment (MCI) to dementia of Alzheimer's type (DAT) or to vascular dementia (VaD) versus normal aging, subjects identified as MCI or as cognitively normal (CN) during standard cognitive evaluations among a large epidemiological study designed to determine prevalence and incidence of dementia and its major subtypes in Beijing, China were re-examined after an interval of approximately 3 years, repeating the same investigation protocol as at baseline. MCI subjects meeting criteria for dementia and the two major subtypes, DAT and VaD were identified at follow-up evaluation. Annual conversion rates for combined dementias and for major subtypes of DAT and VaD, from MCI, were compared with conversion rates among CN subjects. Relative risks for conversion from MCI to major subtypes of dementia were also compared with CN subjects by Cox regression models. 175 MCI and 400 CN subjects were identified at baseline. Among 121 MCI subjects available at follow-up, 51 were diagnosed with dementia (29 with DAT, 18 with VaD and 4 with other dementias), compared with 14(10 DAT, 3 VaD and 1 other type dementia) diagnosed as dementia among 281 CN subjects available at follow-up. Annual conversion rates calculated from MCI to all dementias, compared with conversion rates from CNs, were 14.1% versus 1.6%. Specifically for DAT, annual conversion rates were 8.0% versus 1.1% and for VaD were 5.0% versus 0.3%. Relative risks for developing all dementias, DAT and VaD among MCI subjects were 9, 6 and 5 times greater than among CN subjects. Conversion rates among MCI subjects to dementia, and major subtypes, for elderly Chinese residents of Beijing were comparable with results reported among similar studies worldwide. Risks of developing dementia, and major subtypes, among MCI subjects in Beijing were significantly higher than among normal subjects. Identification of MCI among elderly populations provides the possibilities for dementia prevention and treatment within prodromal stages.

Age Distribution↗
PubMed2004

Posterior screw placement on the lateral mass of atlas: an anatomic study.

STUDY DESIGN: An anatomic study evaluating the feasibility of posterior screw fixation on the lateral mass of the atlas and comparing the pullout force of C1 posterior lateral mass screws with that of occipital and C2 pedicle screws. OBJECTIVES: To study the feasibility, anatomy, and biomechanics of posterior screw fixation within the lateral mass of the atlas. SUMMARY OF BACKGROUND DATA: Occipitocervical fusion is a common choice for atlantoaxial dislocations. After that the movement of occipitocervical region will be restricted. If screws could be placed in the lateral mass of the atlas, 1) the movement of C0-C1 junction will be preserved; 2) through the screw the dislocated atlas could be pulled backward; and 3) the fractured lateral mass can be fixed using the posterior lateral mass screw directly. METHODS: Thirty atlas specimens of native adults were used to measure pertinent clinical data. Six fresh upper cervical specimens were used to observe the association of the C2 nerve and the lateral mass of the atlas. The pullout force of the C1 lateral mass was measured and compared with that of screws placed into the occiput and C2 pedicle, respectively. RESULTS: The distances from the midline to the midpoint of the C1 lateral mass, to the inner wall of the transverse foramen, and to the inner edge of the pedicle were 17.6 +/- 1.2 mm, 23.0 +/- 1.7 mm, and 14.2 +/-1.1 mm, respectively. The width and height of the C1 lateral mass were 11.6 +/- 1.4 mm and 12.7 +/- 1.0 mm, respectively. The distance between the inferior midpoint of the C1 lateral mass in the transverse plane of the midposterior arch of the atlas to the edge of the inferior atlas joint line was 4.1 +/- 0.7 mm. The width of the posterior arch at the point of vertebral artery overpass was 4.7 +/- 1.0 mm. The observation on the fresh specimens showed that the C2 nerve passes inferolateral to the C1-C2 joint and could be pulled sideways. The screw pullout force within the lateral mass of the atlas was 1818.16 +/- 422.67 N. This is significantly less than that of screws within the occiput, and there was no difference with that of a C2 pedicle screw. CONCLUSION: The width and height of the atlas lateral mass were larger than that of the C2 pedicle, and there was enough space to insert a 3.5-mm diameter screw in the atlas lateral mass over the C2 nerve. The pullout force of the screw on the lateral mass of the atlas was the same as that of the C2 pedicle screw. It is possible toinsert a 3.5-mm screw in the lateral mass of the atlas. The direction of the screw should be about 20 degrees anterosuperior in the vertical plane and 15 degrees inward in the horizontal plane. The suitable length of the screw should be approximately 22 mm inside the lateral mass.

Anthropometry↗
PubMed2004

Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality.

A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules. Based on a Takagi-Sugeno (T-S) inference mechanism a one to one mapping between a fuzzy rule base and a model matrix feature subspace is established. This link enables rule based knowledge to be extracted from matrix subspace to enhance model transparency. In order to achieve maximized model robustness and sparsity, a new robust extended Gram-Schmidt (G-S) method has been introduced via two effective and complementary approaches of regularization and D-optimality experimental design. Model rule bases are decomposed into orthogonal subspaces, so as to enhance model transparency with the capability of interpreting the derived rule base energy level. A locally regularized orthogonal least squares algorithm, combined with a D-optimality used for subspace based rule selection, has been extended for fuzzy rule regularization and subspace based information extraction. By using a weighting for the D-optimality cost function, the entire model construction procedure becomes automatic. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Journal Article↗
PubMed2004

Sparse modeling using orthogonal forward regression with PRESS statistic and regularization.

The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test error also known as the predicted residual sums of squares (PRESS) statistic, without resorting to any other validation data set for model evaluation in the model construction process. Computational efficiency is ensured using an orthogonal forward regression, but the algorithm incrementally minimizes the PRESS statistic instead of the usual sum of the squared training errors. A local regularization method can naturally be incorporated into the model selection procedure to further enforce model sparsity. The proposed algorithm is fully automatic, and the user is not required to specify any criterion to terminate the model construction procedure. Comparisons with some of the existing state-of-art modeling methods are given, and several examples are included to demonstrate the ability of the proposed algorithm to effectively construct sparse models that generalize well.

Journal Article↗
PubMed2004

Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization.

This paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the algorithm incrementally minimizes the leave-one-out test score. A local regularization method is incorporated naturally into the density construction process to further enforce sparsity. An additional advantage of the proposed algorithm is that it is fully automatic and the user is not required to specify any criterion to terminate the density construction procedure. This is in contrast to an existing state-of-art kernel density estimation method using the support vector machine (SVM), where the user is required to specify some critical algorithm parameter. Several examples are included to demonstrate the ability of the proposed algorithm to effectively construct a very sparse kernel density estimate with comparable accuracy to that of the full sample optimized Parzen window density estimate. Our experimental results also demonstrate that the proposed algorithm compares favorably with the SVM method, in terms of both test accuracy and sparsity, for constructing kernel density estimates.

Algorithms↗