Genetic parameters and trends for Johne's disease in US Holsteins: An updated study.

Johne's disease (JD) is an infectious enteric disease in ruminants, causing substantial economic loss annually worldwide. This work aimed to estimate JD's genetic parameters and the phenotypic and genetic trends by incorporating recent data. It also explores the feasibility of a national genetic evaluation for JD susceptibility in Holstein cattle in the United States. The data were extracted from a JD data repository, maintained at the Council on Dairy Cattle Breeding, and initially supplied by 2 dairy record processing centers. The data comprised 365,980 Holstein cows from 1,048 herds participating in a voluntary control program for JD. Two protocol kits, IDEXX Paratuberculosis Screening Ab Test (IDX) and Parachek 2 (PCK), were used to analyze milk samples with the ELISA technique. Test results from the first 5 parities were considered. An animal was considered infected if it had at least one positive outcome. The overall average of JD incidence was 4.72% in these US Holstein cattle. Genotypes of 78,964 SNP markers were used for 25,000 animals randomly selected from the phenotyped population. Variance components and genetic parameters were estimated based on 3 models, namely, a pedigree-only threshold model (THR), a single-step threshold model (ssTHR), and a single-step linear model (ssLR). The posterior heritability estimates of JD susceptibility were low to moderate: 0.11 to 0.16 based on the 2 threshold models and 0.05 to 0.09 based on the linear model. The average reliability of EBVs of JD susceptibility using single-step analysis for animals with or without phenotypes varied from 0.18 (THR) to 0.22 (ssLR) for IDX and from 0.14 (THR) to 0.18 (ssTHR and ssLR) for PCK. Despite no prior direct genetic selection against JD, the estimated genetic trends of JD susceptibility were negative and highly significant. The correlations of bulls' PTA with economically important traits such as milk yield, milk protein, milk fat, somatic cell score, and mastitis were low, indicating a nonoverlapping genetic selection process with traits in current genetic evaluations. Our results suggest the feasibility of reducing the JD incidence rate by incorporating it into the national genetic evaluation programs.

Integrating mRNA transcripts and genomic information into genomic prediction.

Genomic prediction has emerged as a pivotal technology for the genetic evaluation of livestock, crops, and for predicting human disease risks. However, classical genomic prediction methods face challenges in incorporating biological prior information such as the genetic regulation mechanisms of traits. This study introduces a novel approach that integrates mRNA transcript information to predict complex trait phenotypes. To evaluate the accuracy of the new method, we utilized a Drosophila population that is widely employed in quantitative genetics researches globally. Results indicate that integrating mRNA transcript data can significantly enhance the genomic prediction accuracy for certain traits, though it does not improve phenotype prediction accuracy for all traits. Compared with GBLUP, the prediction accuracy for olfactory response to dCarvone in male Drosophila increased from 0.256 to 0.274. Similarly, the accuracy for cafe in male Drosophila rose from 0.355 to 0.401. The prediction accuracy for survival_paraquat in male Drosophila is improved from 0.101 to 0.138. In female Drosophila, the accuracy of olfactory response to 1hexanol increased from 0.147 to 0.210. In conclusion, integrating mRNA transcripts can substantially improve genomic prediction accuracy of certain traits by up to 43%, with range of 7% to 43%. Furthermore, for some traits, considering interaction effects along with mRNA transcript integration can lead to even higher prediction accuracy.

Neuronal MeCP2 in the dentate gyrus regulates mossy fiber sprouting of mice with temporal lobe epilepsy.

Sprouting of mossy fibers, one of the most consistent findings in tissue from patients with mesial temporal lobe epilepsy, exhibits several uncommon axonal growth features and has been considered a paradigmatic example of circuit plasticity that occurs in the adult brain. Clarifying the mechanisms responsible may provide new insight into epileptogenesis as well as axon misguidance in the central nervous system. Methyl-CpG-binding protein 2 (MeCP2) binds to methylated genomic DNA to regulate a range of physiological functions implicated in neuronal development and adult synaptic plasticity. However, exploring the potential role of MeCP2 in the documented misguidance of axons in the dentate gyrus has not yet been attempted. In this study, a status epilepticus-induced decrease of neuronal MeCP2 was observed in the dentate gyrus (DG). An essential regulatory role of MeCP2 in the development of functional mossy fiber sprouting (MFS) was confirmed through stereotaxic injection of a recombinant adeno-associated virus (AAV) to up- or down-regulate MeCP2 in the dentate neurons. Chromatin immunoprecipitation sequencing (ChIP-seq) was performed to identify the binding profile of native MeCP2 using micro-dissected dentate tissues. In both dentate tissues and HT22 cell lines, we demonstrated that MeCP2 could act as a transcription repressor on miR-682 with the involvement of the DNA methylation mechanism. Further, we found that miR-682 could bind to mRNA of phosphatase and tensin homolog (PTEN) in a sequence specific manner, thus leading to the suppression of PTEN and excessive activation of mTOR. This study therefore presents a novel epigenetic mechanism by identifying MeCP2/miR-682/PTEN/mTOR as an essential signal pathway in regulating the formation of MFS in the temporal lobe epileptic (TLE) mice. SIGNIFICANCE STATEMENT: Understanding the mechanisms that regulate axon guidance is important for a better comprehension of neural disorders. Sprouting of mossy fibers, one of the most consistent findings in patients with mesial temporal lobe epilepsy, has been considered a paradigmatic example of circuit plasticity in the adult brain. Although abnormal regulation of DNA methylation has been observed in both experimental rodents and humans with epilepsy, the potential role of DNA methylation in this well-documented example of sprouting of dentate axon remains elusive. This study demonstrates an essential role of methyl-CpG-binding protein 2 in the formation of mossy fiber sprouting. The underlying signal pathway has been also identified. The data hence provide new insight into epileptogenesis as well as axon misguidance in the central nervous system.

Estimating test-day milk yields by modeling proportional daily yields: Going beyond linearity.

In the United States, lactation milk yields are not measured directly but are calculated from the test-day milk yields. Still, test-day milk yields are estimated from partial yields obtained from single milkings. Various methods have been proposed to estimate test-day milk yields, primarily to deal with unequal milking intervals dating back to the 1970s and 1980s. The Wiggans model is a de facto method for estimating test-day milk yields in the United States, which was initially proposed for cows milked 3 times daily, assuming a linear relationship between a proportional test-day milk yield and milking interval. However, the linearity assumption did not hold precisely in Holstein cows milked twice daily because of prolonged and uneven milking intervals. The present study reviewed and evaluated the nonlinear models that extended the Wiggans model for estimating daily or test-day milk yields. These nonlinear models, except step functions, demonstrated smaller errors and greater accuracies for estimated test-day milk yields compared with the conventional methods. The nonlinear models offered additional benefits. For example, the locally weighted regression model (e.g., locally estimated scatterplot smoothing) could utilize data information in scalable neighborhoods and weigh observations according to their distance in milking interval time. General additive models provide a flexible, unified framework to model nonlinear predictor variables additively. Another drawback of the conventional methods is a loss of accuracy caused by discretizing milking interval time into large bins while deriving multiplicative correction factors for estimating test-day milk yields. To overcome this problem, we proposed a general approach that allows milk yield correction factors to be derived for every possible milking interval time, resulting in more accurately estimated test-day milk yields. This approach can be applied to any model, including nonparametric models.

Identification of microRNA-target genes in mice hippocampus at 1 week after pilocarpine-induced status epilepticus.

MicroRNAs (miRNA) are believed to play a crucial role in the cause and treatment of temporal lobe epilepsy (TLE) by controlling gene expression in different stages of the disease. To investigate role of miRNA in the latent stage following status epilepticus, we first compared microRNA expression profiles in mice hippocampus at 1 week after pilocarpine-induced status epilepticus (SE) vs. controls in hippocampal tissues using Exiqon miRCURY LNA™ miRNAs Array. Then, the target genes of altered miRNAs were predicted using both TargetScan 7.1 and miRDB V5, and were further selected by intersecting with another independent mRNA expression profile dataset from the samples at the same time point. We found out 14 common genes as down miRNA target (up-mRNA) and 4 common genes as up miRNA target (down mRNA) in SE mice. miR-669m-3p-TRHR (thyrotropin releasing hormone receptor), miR-669m-3p-B3galt2 (ß-1,3-Galactosyltransferase 2), miR-105-PDPN (Podoplanin) and miR-883b-3p-CLEC-2 (C-type-lectin-like-2) were found to be potential molecular mechanisms to modulate the calcium signaling pathway, glycosylation pathways and chemokine mediated inflammatory processes in mice hippocampus at 1 week after pilocarpine-induced SE, respectively. Our results offered potential novel insights into the cellular events in the mice hippocampus mediated by miRNASs-target genes that shape SE-evoked epileptogenesis.

LncRNA MALAT1 Promotes STAT3-Mediated Endothelial Inflammation by Counteracting the Function of miR-590.

The excessive production of inflammatory mediators by vascular endothelial cells (ECs) greatly contributes to the development of atherosclerosis. In this study, we explored the potential effect of lncRNA MALAT1 on endothelial inflammation. First, the EC inflammation model was constructed by treating human umbilical vein ECs (HUVECs) and human coronary artery ECs (HCAECs) with oxidized low-density lipoprotein (ox-LDL), which confirmed the role of MALAT1 in the inflammatory activity. Then MALAT1 was overexpressed in HUVECs and HCAECs, and the levels of inflammatory mediators and nitric oxide (NO) were examined by Western blotting, ELISA, and NO detection assay. The migration ability was confirmed by wound healing assay. The interactions among MALAT1, miR-590, and STAT3 were predicted by bioinformatics analysis and verified by qRT-PCR, Western blotting, or dual-luciferase reporter assay. MALAT1 was upregulated in ECs treated with ox-LDL, and knockdown of MALAT1 significantly inhibited ox-LDL-induced inflammation. MALAT1 overexpression potentiated the inflammatory activities of ECs, including enhanced production of inflammatory cytokines (IL-6, IL-8, and TNF-α) and adhesion molecules (VCAM1 and ICAM1), and decreased NO level and cell migratory ability. Mechanistically, MALAT1 could directly downregulate miR-590, and miR-590 could bind to the 3'-UTR of STAT3 to repress its expression. Additionally, overexpression of MALAT1-mediated inflammation was largely abrogated by the concomitant overexpression of miR-590. miR-590 knockdown activated the inflammatory response, which was reversed by STAT3 inhibition. Thus, MALAT1 serves as a proinflammatory lncRNA in ECs through regulating the miR-590/STAT3 axis, suggesting that MALAT1 may be a promising therapeutic target during the treatment of atherosclerosis.

Synthesis and mass spectra of rearrangement bio-signature metabolites of anaerobic alkane degradation via fumarate addition.

Metabolite profiling in anaerobic alkane biodegradation plays an important role in revealing activation mechanisms. Apart from alkylsuccinates, which are considered to be the usual biomarkers via fumarate addition, the downstream metabolites of C-skeleton rearrangement can also be regarded as biomarkers. However, it is difficult to detect intermediate metabolites in both environmental samples and enrichment cultures, resulting in lacking direct evidence to prove the occurrence of fumarate addition pathway. In this work, a synthetic method of rearrangement metabolites was established. Four compounds, namely, propylmalonic acid, 2-(2-methylbutyl)malonic acid, 2-(2-methylpentyl)malonic acid and 2-(2-methyloctyl)malonic acid, were synthesized and determined by four derivatization approaches. Besides, their mass spectra were obtained. Four characteristic ions were observed at m/z 133 + 14n, 160 + 28n, 173 + 28n and [M - (45 + 14n)]+ (n = 0 and 2 for ethyl and n-butyl esters, respectively). For methyl esterification, mass spectral features were m/z 132, 145 and [M - 31]+, while for silylation, fragments were m/z 73, 147, 217, 248, 261 and [M - 15]+. These data provide basis on identification of potential rearrangement metabolites in anaerobic alkane biodegradation via fumarate addition.

Superconductivity in an organometallic compound.

Organometallic compounds constitute a very large group of substances that contain at least one metal-to-carbon bond in which the carbon is part of an organic group. They have played a major role in the development of the science of chemistry. These compounds are used to a large extent as catalysts (substances that increase the rate of reactions without themselves being consumed) and as intermediates in the laboratory and in industry. Recently, novel quantum phenomena such as topological insulators and superconductors were also suggested in these materials. However, there has been no report on the experimental exploration of the topological state. Evidence for superconductivity from the zero-resistivity state in any organometallic compound has not been achieved yet, though much effort has been made. Here we report the experimental realization of superconductivity with a critical temperature of 3.6 K in a potassium-doped organometallic compound, i.e. tri-o-tolylbismuthine, with evidence of both the Meissner effect and the zero-resistivity state through dc and ac magnetic susceptibility measurements. The obtained superconducting parameters classify this compound as a type-II superconductor. The benzene ring is identified to be the essential superconducting unit in such a phenyl organometallic compound. The superconducting phase and its composition are determined by combined studies of X-ray diffraction and theoretical calculations as well as Raman spectroscopy measurements. These findings enrich the applications of organometallic compounds in superconductivity and add a new electron-acceptor family of organic superconductors. This work also points to a large pool for finding superconductors from organometallic compounds.

[Methods and applications of animal genomic mating].

Genomic selection (GS) is a powerful tool which can be used to estimate the breeding value of individual animals by using the molecular markers of the animal's entire genome. GS improves the accuracy and intensity of selection, reduces the interval of generation, and realizes the effects of early accuracy selection contributing to a significant evolution in animal breeding. In the past decade, GS was successfully applied in the genetic improvement of dairy animals with improved selection accuracy and genetic gain of breeding animals. However, GS focuses on the genetic gain of target traits while it ignores the genetic relationship between mating pairs such that it ignores long term genetic merits such as an increase in inbreeding coefficient of offspring population, a decrease of genetic diversity and the homozygous presentation of harmful genes. In 2016, genomic mating (GM) was proposed as a sustainable genetic selection method using genomic information of the breeding candidate individuals to optimize selection and mating with resultant control of the growth rate of population inbreeding coefficient and achieving long-term and sustainable genetic progress. Therefore, GM is more suitable for modern animal breeding than GS, especially for the genetic improvement of indigenous species. In this review, we summarize the basic concepts, methods, and applications of GM, and then present examples comparing the effects of six simulated mating schemes. This review serves as a valuable reference for the applications of animal breeding methods.

[Impacts of SNP genotyping call rate and SNP genotyping error rate on imputation accuracy inHolsteincattle].

Single nucleotide polymorphism (SNP) chips have been widely used in genetic studies and breeding applications in animal and plant species. The quality of SNP genotypes is of paramount importance. More often than not, there are situations in which a number of genotypes may fail, requiring them to be imputed. There are also situations in which ungenotyped loci need to be imputed between different chips, or high-density genotypes need to be imputed based on low-density genotypes. Under these circumstances, the validity and reliability of subsequent data analyses is subject to the accuracy of these imputed genotypes. For justifying a better understanding of factors affecting imputation accuracy, in the present study, the impacts of SNP genotyping call rate and SNP genotyping error rate on the accuracy of genotype imputation were investigated under two scenarios in 20 116 U.S. Holstein cattle, each genotyped with a GGP 50K SNP chip. When the two factors were not correlated in scenario 1, simulated genotyping call rate varied from 50% to 100% and simulated genotyping error rate changed from 0% to 50%, with both factors being independent of each other. In scenario 2, genotyping error rates were correlated with genotyping call rate, and the relationship was set up by fitting a linear regression model between the two variables on a real dataset. That is, the simulated SNP call rate varied from 100% to 50% whereas the SNP genotyping rate changed from 0% to 13.55%. Finally, a 5-fold cross-validation was used to assess the subsequent imputation accuracy. The results showed that when original SNP genotyping call rate were independent of SNP genotyping error rate, the imputation accuracy did not change significantly with the original genotyping call rate (P>0.05), but it decreased significantly as the genotyping error rate increased (P<0.01). However, when original genotyping call rate was negatively correlated with genotyping error rate, the imputation error increased with elevated original genotyping error rate. In both scenarios, genotyping call rate needs to be no less than 0.90 in order to obtain 98% or higher genotype imputation accuracy. The present results can provide guidance for establishing quality assurance criteria for SNP genotyping in practice.

Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins.

SNP chips are commonly used for genotyping animals in genomic selection but strategies for selecting low-density (LD) SNPs for imputation-mediated genomic selection have not been addressed adequately. The main purpose of the present study was to compare the performance of eight LD (6K) SNP panels, each selected by a different strategy exploiting a combination of three major factors: evenly-spaced SNPs, increased minor allele frequencies, and SNP-trait associations either for single traits independently or for all the three traits jointly. The imputation accuracies from 6K to 80K SNP genotypes were between 96.2 and 98.2%. Genomic prediction accuracies obtained using imputed 80K genotypes were between 0.817 and 0.821 for daughter pregnancy rate, between 0.838 and 0.844 for fat yield, and between 0.850 and 0.863 for milk yield. The two SNP panels optimized on the three major factors had the highest genomic prediction accuracy (0.821-0.863), and these accuracies were very close to those obtained using observed 80K genotypes (0.825-0.868). Further exploration of the underlying relationships showed that genomic prediction accuracies did not respond linearly to imputation accuracies, but were significantly affected by genotype (imputation) errors of SNPs in association with the traits to be predicted. SNPs optimal for map coverage and MAF were favorable for obtaining accurate imputation of genotypes whereas trait-associated SNPs improved genomic prediction accuracies. Thus, optimal LD SNP panels were the ones that combined both strengths. The present results have practical implications on the design of LD SNP chips for imputation-enabled genomic prediction.

Comparing SNP panels and statistical methods for estimating genomic breed composition of individual animals in ten cattle breeds.

BACKGROUND: SNPs are informative to estimate genomic breed composition (GBC) of individual animals, but selected SNPs for this purpose were not made available in the commercial bovine SNP chips prior to the present study. The primary objective of the present study was to select five common SNP panels for estimating GBC of individual animals initially involving 10 cattle breeds (two dairy breeds and eight beef breeds). The performance of the five common SNP panels was evaluated based on admixture model and linear regression model, respectively. Finally, the downstream implication of GBC on genomic prediction accuracies was investigated and discussed in a Santa Gertrudis cattle population. RESULTS: There were 15,708 common SNPs across five currently-available commercial bovine SNP chips. From this set, four subsets (1,000, 3,000, 5,000, and 10,000 SNPs) were selected by maximizing average Euclidean distance (AED) of SNP allelic frequencies among the ten cattle breeds. For 198 animals presented as Akaushi, estimated GBC of the Akaushi breed (GBCA) based on the admixture model agreed very well among the five SNP panels, identifying 166 animals with GBCA = 1. Using the same SNP panels, the linear regression approach reported fewer animals with GBCA = 1. Nevertheless, estimated GBCA using both models were highly correlated (r = 0.953 to 0.992). In the genomic prediction of a Santa Gertrudis population (and crosses), the results showed that the predictability of molecular breeding values using SNP effects obtained from 1,225 animals with no less than 0.90 GBC of Santa Gertrudis (GBCSG) decreased on crossbred animals with lower GBCSG. CONCLUSIONS: Of the two statistical models used to compute GBC, the admixture model gave more consistent results among the five selected SNP panels than the linear regression model. The availability of these common SNP panels facilitates identification and estimation of breed compositions using currently-available bovine SNP chips. In view of utility, the 1 K panel is the most cost effective and it is convenient to be included as add-on content in future development of bovine SNP chips, whereas the 10 K and 16 K SNP panels can be more resourceful if used independently for imputation to intermediate or high-density genotypes.

Superconductivity at 3.5 K and/or 7.2 K in potassium-doped triphenylbismuth.

We develop a two-step synthesis method-ultrasound treatment and low temperature annealing to explore superconductivity in potassium-doped triphenylbismuth, which is composed of one bismuth atom and three phenyl rings. The combination of dc and ac magnetic measurements reveals that one hundred percent of synthesized samples exhibit superconductivity at 3.5 K and/or 7.2 K at ambient pressure. The magnetization hysteresis loops provide a strong piece of evidence of type-II superconductors. It is found that the doped materials crystallize into the triclinic P1 structure, with a mole ratio of 4:1 between potassium and triphenylbismuth. Both the calculated electronic structure and measured Raman spectra indicate that superconductivity is realized by transferring electrons from the K-4s to C-2p orbital. Our study opens an encouraging window for the search of organic superconductors in organometallic molecules.

[Estimating genomic breed composition of individual animals using selected SNPs].

Natural and artificial selection, geographical segregation and genetic drift can result in differentiation of allelic frequencies of single nucleotide polymorphism (SNP) at many loci in the animal genome. For individuals whose ancestors originated from different populations, their genetic compositions exhibit multiple components correlated with the genotypes or allele frequencies of these breeds or populations. Therefore, by using an appropriate statistical method, one can estimate the genomic contribution of each breed (ancestor) to the genome of each individual animal, which is referred to as the genomic breed composition (GBC). This paper reviews the principles, statistical methods and steps for estimating GBC of individual animals using SNP genotype data. Based on a linear regression model and an admixture model respectively, the protocols were demonstrated by the breed characterization of 198 purported Akaushi cattle, which included selection of reference SNPs and reference individual animals, and computing GBC for animals to be evaluated. The reference populations consist of 36 574 cattle from five cattle breeds (Akaushi, Angus, Hereford, Holstein and Jersey), each genotyped on either a 40K or 50K SNP chip. Four common SNP panels scanned from commercial chips for estimating GBC of individual animals are optimally selected, thereby expanding the functionalities of the currently available commercial SNP chips. It remains to be explored in future studies as to how estimated GBC can be incorporated to improve the accuracies on genomic prediction in purebred animals and crossbreds as well.

A nonsense mutation in DHTKD1 causes Charcot-Marie-Tooth disease type 2 in a large Chinese pedigree.

Charcot-Marie-Tooth (CMT) disease represents a clinically and genetically heterogeneous group of inherited neuropathies. Here, we report a five-generation family of eight affected individuals with CMT disease type 2, CMT2. Genome-wide linkage analysis showed that the disease phenotype is closely linked to chromosomal region 10p13-14, which spans 5.41 Mb between D10S585 and D10S1477. DNA-sequencing analysis revealed a nonsense mutation, c.1455T>G (p.Tyr485(∗)), in exon 8 of dehydrogenase E1 and transketolase domain-containing 1 (DHTKD1) in all eight affected individuals, but not in other unaffected individuals in this family or in 250 unrelated normal persons. DHTKD1 mRNA expression levels in peripheral blood of affected persons were observed to be half of those in unaffected individuals. In vitro studies have shown that, compared to wild-type mRNA and DHTKD1, mutant mRNA and truncated DHTKD1 are significantly decreased by rapid mRNA decay in transfected cells. Inhibition of nonsense-mediated mRNA decay by UPF1 silencing effectively rescued the decreased levels of mutant mRNA and protein. More importantly, DHTKD1 silencing was found to lead to impaired energy production, evidenced by decreased ATP, total NAD(+) and NADH, and NADH levels. In conclusion, our data demonstrate that the heterozygous nonsense mutation in DHTKD1 is one of CMT2-causative genetic alterations, implicating an important role for DHTKD1 in mitochondrial energy production and neurological development.

Animal QTLdb: an improved database tool for livestock animal QTL/association data dissemination in the post-genome era.

The Animal QTL database (QTLdb; http://www.animalgenome.org/QTLdb) is designed to house all publicly available QTL and single-nucleotide polymorphism/gene association data on livestock animal species. An earlier version was published in the Nucleic Acids Research Database issue in 2007. Since then, we have continued our efforts to develop new and improved database tools to allow more data types, parameters and functions. Our efforts have transformed the Animal QTLdb into a tool that actively serves the research community as a quality data repository and more importantly, a provider of easily accessible tools and functions to disseminate QTL and gene association information. The QTLdb has been heavily used by the livestock genomics community since its first public release in 2004. To date, there are 5920 cattle, 3442 chicken, 7451 pigs, 753 sheep and 88 rainbow trout data points in the database, and at least 290 publications that cite use of the database. The rapid advancement in genomic studies of cattle, chicken, pigs, sheep and other livestock animals has presented us with challenges, as well as opportunities for the QTLdb to meet the evolving needs of the research community. Here, we report our progress over the recent years and highlight new functions and services available to the general public.

Treatment strategies for huge central neurocytomas.

Central neurocytomas (CNs), initially asymptomatic, sometimes become huge before detection. We described and analyzed the clinical, radiological, operational and outcome data of 13 cases of huge intraventricular CNs, and discussed the treatment strategies in this study. All huge CNs (n=13) in our study were located in bilateral lateral ventricle with diameter ≥5.0 cm and had a broad-based attachment to at least one side of the ventricle wall. All patients received craniotomy to remove the tumor through transcallosal or transcortical approach and CNs were of typical histologic and immunohistochemical features. Adjuvant therapies including conventional radiation therapy (RT) or gamma knife radiosurgery (GKRS) were also performed postoperatively. Transcallosal and transcortical approaches were used in 8 and 5 patients, respectively. Two patients died within one month after operation and 3 patients with gross total resection (GTR) were additionally given a decompressive craniectomy (DC) and/or ventriculoperitoneal shunt (VPS) as the salvage therapy. Six patients received GTR(+RT) and 7 patients received subtotal resection (STR)(+GKRS). Eight patients suffered serious complications such as hydrocephalus, paralysis and seizure after operation, and patients who underwent GTR showed worse functional outcome [less Karnofsky performance scale (KPS) scores] than those having STR(+GKRS) during the follow-up period. The clinical outcome of huge CNs seemed not to be favorable as that described in previous reports. Surgical resection for huge CNs should be meticulously considered to guarantee the maximum safety. Better results were achieved in STR(+GKRS) compared with GTR(+RT) for huge CNs, suggesting that STR(+GKRS) may be a better treatment choice. The recurrent or residual tumor can be treated with GKRS effectively.

Antagonism of Ca2+ influx via L-type Ca2+ channels mediates the vasorelaxant effect of Catharanthus roseus-derived vindorosine in rat renal artery.

Catharanthus roseus is a traditional herbal medicine used in Asian and African countries for the treatment of various diseases including hypertension. The present study examined possible cellular mechanisms for the relaxation of rat renal arteries induced by vindorosine extracted from C. roseus. Intrarenal arteries were isolated from 200-300 g male Sprague-Dawley rats and treated with different pharmacological blockers and inhibitors for the measurement of vascular reactivity on a Multi Myograph System. Fluorescence imaging by laser scanning confocal microscopy was utilized to determine the intracellular Ca(2+) level in the vascular smooth muscles of the renal arteries. Vindorosine in micromolar concentrations relaxes renal arteries precontracted by KCl, phenylephrine, 11-dideoxy-9α,11α-epoxymethanoprostaglandin F2α, and serotonin. Vindorosine-induced relaxations were unaffected by endothelium denudation or by treatment with the nitric oxide synthase inhibitor N (G)-nitro-L-arginine methyl ester hydrochloride, the guanylyl cyclase inhibitor 1H-[1, 2, 4]oxadiazolo[4,3-a]quinoxalin-1-one, the cyclooxygenase inhibitor indomethacin, or K(+) channel blockers such as tetraethylammonium ions, glibenclamide, and BaCl2. Vindorosine-induced relaxations were attenuated in the presence of 0.1 µM nifedipine (an L-type Ca(2+) channel blocker). Vindorosine also concentration-dependently suppressed contractions induced by CaCl2 (0.01-5 mM) in Ca-free 60 mM KCl solution. Furthermore, fluorescence imaging using fluo-4 demonstrated that 30 min incubation with 100 µM vindorosine reduced the 60 mM KCl-stimulated Ca(2+) influx in the smooth muscles of rat renal arteries. The present study is probably the first report of blood vessel relaxation by vindorosine and the possible underlying mechanisms involving the inhibition of Ca(2+) entry via L-type Ca(2+) channels in vascular smooth muscles.

Dopamine receptor 3 might be an essential molecule in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced neurotoxicity.

BACKGROUND: 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) induces Parkinson's disease (PD)-like neurodegeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc) via its oxidized product, 1-methyl-4-phenylpyridinium (MPP+), which is transported by the dopamine (DA) transporter into DA nerve terminals. DA receptor subtype 3 (D3 receptor) participates in neurotransmitter transport, gene regulation in the DA system, physiological accommodation via G protein-coupled superfamily receptors and other physiological processes in the nervous system. This study investigated the possible correlation between D3 receptors and MPTP-induced neurotoxicity. A series of behavioral experiments and histological analyses were conducted in D3 receptor-deficient mice, using an MPTP-induced model of PD. RESULTS: After the fourth MPTP injection, wild-type animals that received 15 mg/kg per day displayed significant neurotoxin-related bradykinesia. D3 receptor-deficient mice displayed attenuated MPTP-induced locomotor activity changes. Consistent with the behavioral observations, further neurohistological assessment showed that MPTP-induced neuronal damage in the SNpc was reduced in D3 receptor-deficient mice. CONCLUSIONS: Our study indicates that the D3 receptor might be an essential molecule in MPTP-induced PD and provides a new molecular mechanism for MPTP neurotoxicity.