MiR-204 regulates type 1 IP3R to control vascular smooth muscle cell contractility and blood pressure

MiR-204 is expressed in vascular smooth muscle cells (VSMC). However, its role in VSMC contraction is not known. We determined if miR-204 controls VSMC contractility and blood pressure through regulation of sarcoplasmic reticulum (SR) calcium (Ca²⁺) release. Systolic blood pressure (SBP) and vasoreactivity to VSMC contractile agonists (phenylephrine (PE), thromboxane analogue (U46619), endothelin-1 (ET-1), angiotensin-II (Ang II) and norepinephrine (NE) were compared in aortas and mesenteric resistance arteries (MRA) from miR-204^−/− mice and wildtype mice (WT). There was no difference in basal systolic blood pressure (SBP) between the two genotypes; however, hypertensive response to Ang II was significantly greater in miR-204^−/− mice compared to WT mice. Aortas and MRA of miR-204^−/− mice had heightened contractility to all VSMC agonists. In silico algorithms predicted the type 1 Inositol 1, 4, 5-trisphosphate receptor (IP₃R1) as a target of miR-204. Aortas and MRA of miR-204^−/− mice had higher expression of IP₃R1 compared to WT mice. Difference in agonist-induced vasoconstriction between miR-204^−/− and WT mice was abolished with pharmacologic inhibition of IP₃R1. Furthermore, Ang II-induced aortic IP₃R1 was greater in miR-204^−/− mice compared to WT mice. In addition, difference in aortic vasoconstriction to VSMC agonists between miR-204^−/− and WT mice persisted after Ang II infusion. Inhibition of miR-204 in VSMC in vitro increased IP₃R1, and boosted SR Ca²⁺ release in response to PE, while overexpression of miR-204 downregulated IP₃R1. Finally, a sequence-specific nucleotide blocker that targets the miR-204-IP₃R1 interaction rescued miR-204-induced downregulation of IP₃R1. We conclude that miR-204 controls VSMC contractility and blood pressure through IP₃R1-dependent regulation of SR calcium release.     

A Comparison of Bone Mineral Density and Its Predictors in HIV-Infected and HIV-Uninfected Older Men

ObjectiveBone health in older individuals with HIV infection has not been well studied. This study aimed to compare bone mineral density (BMD), trabecular bone score (TBS), and bone markers between HIV-infected men and age- and body mass index (BMI)-matched HIV-uninfected men aged ≥60 years. We investigated the associations of risk factors related to fracture with BMD, TBS, and bone markers in HIV-infected men.MethodsThis cross-sectional study included 45 HIV-infected men receiving antiretroviral therapy and 42 HIV-uninfected men. Medical history, BMD and TBS measurements, and laboratory tests related to bone health were assessed in all the participants. HIV-related factors known to be associated with bone loss were assessed in the HIV-infected men.ResultsThe mean BMD, TBS, and osteopenia or osteoporosis prevalence were similar among the cases and controls. The HIV-infected men had significantly higher mean N-terminal propeptide of type 1 procollagen and C-terminal cross-linking telopeptide of type I collagen levels. Stepwise multiple linear regression analysis demonstrated that low BMI (lumbar spine, P = .015; femoral neck, P = .018; and total hip, P = .005), high C-terminal cross-linking telopeptide of type I collagen concentration (total hip, P = .042; and TBS, P = .010), and low vitamin D supplementation (TBS, P = .035) were independently associated with low BMD and TBS.ConclusionIn older HIV-infected men with a low fracture risk, the mean BMD and TBS were similar to those of the age- and BMI-matched controls. The mean bone marker levels were higher in the HIV group. Traditional risk factors for fracture, including low BMI, high C-terminal cross-linking telopeptide of type I collagen level, and low vitamin D supplementation, were significant predictors of low BMD and TBS.     

Isolation and characterization of the plasma membrane from the yeast Pichia pastoris

Despite similarities of cellular membranes in all eukaryotes, every compartment displays characteristic and often unique features which are important for the functions of the specific organelles. In the present study, we biochemically characterized the plasma membrane of the methylotrophic yeast Pichia pastoris with emphasis on the lipids which form the matrix of this compartment. Prerequisite for this effort was the design of a standardized and reliable isolation protocol of the plasma membrane at high purity. Analysis of isolated plasma membrane samples from P. pastoris revealed an increase of phosphatidylserine and a decrease of phosphatidylcholine compared to bulk membranes. The amount of saturated fatty acids in the plasma membrane was higher than in total cell extracts. Ergosterol, the final product of the yeast sterol biosynthetic pathway, was found to be enriched in plasma membrane fractions, although markedly lower than in Saccharomyces cerevisiae. A further characteristic feature of the plasma membrane from P. pastoris was the enrichment of inositol phosphorylceramides over neutral sphingolipids, which accumulated in internal membranes. The detailed analysis of the P. pastoris plasma membrane is discussed in the light of cell biological features of this microorganism especially as a microbial cell factory for heterologous protein production.     

Mapping economic trait loci for somatic cell score in Holstein cattle using microsatellite markers and selective genotyping

Marker-assisted selection (MAS) uses genetic marker genotypes to predict an animal's production potential and will provide additional selection information for progeny testing. With the discovery of highly polymorphic microsatellite markers, the tools now exist to begin the search for economic trait loci (ETL), which is the first step toward MAS. The objective of this study was to identify ETL for somatic cell score in an existing Holstein population. Using the granddaughter design, sons from seven grandsire families were genotyped with 20 autosomal microsatellites from five chromosomes (4, 8, 13, 17, 23), with an emphasis on chromosome 23, which is the location of the bovine major histocompatibility complex (BoLA). Selective genotyping was used to reduce the number of genotypes required, in which the 10 highest and 10 lowest sons from the phenotypic distribution curve were tested (140 sons in seven families). One marker (513), located near BoLA, showed evidence of an ETL in three of five polymorphic families. Additional sons were genotyped from the five families to estimate the effect and to compare selective and ‘complete’ genotyping. Both methods detected an ETL at marker 513, but in different families. This study provides evidence of the usefulness of microsatellite markers and the granddaughter design in the detection of ETL; however, additional markers need to be evaluated to determine the usefulness of selective genotyping. Based on the results from the 20 studied markers, the most likely position of a somatic cell score ETL lies near marker 513, located on chromosome 23.     

Plasma membrane block to sperm entry occurs in mouse eggs upon parthenogenetic activation

The ability of parthenogenetically activated mouse eggs to establish a plasma membrane (PM) block to sperm penetration was studied. Zona-free eggs preloaded with Hoechst 33342 were activated by exposure to ethanol or OAG (1-oleoyl-2-acetyl-sn-glycerol) and inseminated after different periods. Eggs challenged with sperm at 30- or 60-min postactivation displayed a fertilization frequency significantly lower than that of control eggs. Conversely, when insemination was carried out at 120-min postactivation, the proportion of fertilized eggs was equivalent to that observed in the control group. Moreover, we report that when the eggs were induced to resume meiosis without any notable loss of CGs (egg exposure to OAG at 100 μM external Ca²⁺ or to heat shock), a normal ability to be penetrated was recorded at 30-min postactivation. Similar behaviour was exhibited by eggs that underwent a CG exocytosis close to that triggered by sperm in absence of nuclear activation (microinjection of inositol 1,4,5-trisphosphate into the egg at 1 μM cytosolic concentration). Present data support the conclusion that parthenogenetically activated mouse eggs are capable of a transitory PM block response that requires both CG exocytosis and meiosis resumption to occur. © 1994 Wiley-Liss, Inc.     

Cross-trait prediction accuracy of summary statistics in genome-wide association studies

In the era of big data, univariate models have widely been used as a workhorse tool for quickly producing marginal estimators; and this is true even when in a high-dimensional dense setting, in which many features are “true,” but weak signals. Genome-wide association studies (GWAS) epitomize this type of setting. Although the GWAS marginal estimator is popular, it has long been criticized for ignoring the correlation structure of genetic variants (i.e., the linkage disequilibrium [LD] pattern). In this paper, we study the effects of LD pattern on the GWAS marginal estimator and investigate whether or not additionally accounting for the LD can improve the prediction accuracy of complex traits. We consider a general high-dimensional dense setting for GWAS and study a class of ridge-type estimators, including the popular marginal estimator and the best linear unbiased prediction (BLUP) estimator as two special cases. We show that the performance of GWAS marginal estimator depends on the LD pattern through the first three moments of its eigenvalue distribution. Furthermore, we uncover that the relative performance of GWAS marginal and BLUP estimators highly depends on the ratio of GWAS sample size over the number of genetic variants. Particularly, our finding reveals that the marginal estimator can easily become near-optimal within this class when the sample size is relatively small, even though it ignores the LD pattern. On the other hand, BLUP estimator has substantially better performance than the marginal estimator as the sample size increases toward the number of genetic variants, which is typically in millions. Therefore, adjusting for the LD (such as in the BLUP) is most needed when GWAS sample size is large. We illustrate the importance of our results by using the simulated data and real GWAS.     

Multikink quantile regression for longitudinal data with application to progesterone data analysis

Motivated by investigating the relationship between progesterone and the days in a menstrual cycle in a longitudinal study, we propose a multikink quantile regression model for longitudinal data analysis. It relaxes the linearity condition and assumes different regression forms in different regions of the domain of the threshold covariate. In this paper, we first propose a multikink quantile regression for longitudinal data. Two estimation procedures are proposed to estimate the regression coefficients and the kink points locations: one is a computationally efficient profile estimator under the working independence framework while the other one considers the within-subject correlations by using the unbiased generalized estimation equation approach. The selection consistency of the number of kink points and the asymptotic normality of two proposed estimators are established. Second, we construct a rank score test based on partial subgradients for the existence of the kink effect in longitudinal studies. Both the null distribution and the local alternative distribution of the test statistic have been derived. Simulation studies show that the proposed methods have excellent finite sample performance. In the application to the longitudinal progesterone data, we identify two kink points in the progesterone curves over different quantiles and observe that the progesterone level remains stable before the day of ovulation, then increases quickly in 5 to 6 days after ovulation and then changes to stable again or drops slightly.     

Enhancing estimation methods for integrating probability and nonprobability survey samples with machine-learning techniques. An application to a Survey on the impact of the COVID-19 pandemic in Spain

Web surveys have replaced Face-to-Face and computer assisted telephone interviewing (CATI) as the main mode of data collection in most countries. This trend was reinforced as a consequence of COVID-19 pandemic-related restrictions. However, this mode still faces significant limitations in obtaining probability-based samples of the general population. For this reason, most web surveys rely on nonprobability survey designs. Whereas probability-based designs continue to be the gold standard in survey sampling, nonprobability web surveys may still prove useful in some situations. For instance, when small subpopulations are the group under study and probability sampling is unlikely to meet sample size requirements, complementing a small probability sample with a larger nonprobability one may improve the efficiency of the estimates. Nonprobability samples may also be designed as a mean for compensating for known biases in probability-based web survey samples by purposely targeting respondent profiles that tend to be underrepresented in these surveys. This is the case in the Survey on the impact of the COVID-19 pandemic in Spain (ESPACOV) that motivates this paper. In this paper, we propose a methodology for combining probability and nonprobability web-based survey samples with the help of machine-learning techniques. We then assess the efficiency of the resulting estimates by comparing them with other strategies that have been used before. Our simulation study and the application of the proposed estimation method to the second wave of the ESPACOV Survey allow us to conclude that this is the best option for reducing the biases observed in our data.