Declining semen quality: Can the past inform the present?

By using instrumentation initially designed for counting white blood cells, sperm counts have been utilized by clinicians since 1929, particularly to evaluate cases of suspected infertility. Although this basic biological parameter might be assumed to be stable over time, several studies over the past 20 years have suggested a decline in sperm count or density. The most controversial of these analyses was published in 1992. A flood of criticism followed this analysis of 61 studies that found a 50% decline in sperm density between 1938 and 1990. Critics suggested that historical methods (of counting sperm or conducting studies) were variable and unreliable, differing from modern methods both qualitatively and quantitatively. To address this issue we analyzed these studies for trends in counting methods or their variability. We found neither. Alternative analyses produced some differences in trend estimates, but statistical factors alone could not account for the total decline in sperm density. We reviewed study populations to identify trends in population characteristics, such as abstinence time, that might explain the decline. However, controlling analytically for such factors only increased the rate of decline. We conclude that historical data on sperm density, despite large random error, are surprisingly reliable. Nonetheless, understanding causes of temporal and geographic differences in sperm density must await contemporary data. BioEssays 21:614–621, 1999. © 1999 John Wiley & Sons, Inc.     

Biomarkers: in combination they may do better

The field of biomarkers is a growing one, particularly in osteoarthritis (OA). OA is the most common disabling condition in older persons and a major cause of morbidity. While the debate continues about which of the involved tissues - cartilage, bone or synovium - is the most important in OA aetiology, there is no doubt that the three develop abnormalities in concert; perhaps a truly useful biomarker will reflect just that. While efforts continue to identify reliable biomarkers useful for characterising the status, prognosis and measurement of treatment response in OA, combining existing biomarkers to improve their accuracy looks promising.     

Mammalian target of rapamycin inhibition in macrophages of asymptomatic HIV+ persons reverses the decrease in TLR-4-mediated TNF-α release through prolongation of MAPK pathway activation

TLR-4-mediated signaling is significantly impaired in macrophages from HIV(+) persons, predominantly owing to altered MyD88-dependent pathway signaling caused in part by constitutive activation of PI3K. In this study we assessed in these macrophages if the blunted increase in TLR-4-mediated TNF-α release induced by lipid A (LA) is associated with PI3K-induced upregulation of mammalian target of rapamycin (mTOR) activity. mTOR inhibition with rapamycin enhanced TLR-4-mediated TNF-α release, but suppressed anti-inflammatory IL-10 release. Targeted gene silencing of mTOR in macrophages resulted in LA-induced TNF-α and IL-10 release patterns similar to those induced by rapamycin. Rapamycin restored MyD88/IL-1R-associated kinase interaction in a dose-dependent manner. Targeted gene silencing of MyD88 (short hairpin RNA) and mTOR (RNA interference) inhibition resulted in TLR-4-mediated 70-kDa ribosomal protein S6 kinase activation and enhanced TNF-α release, whereas IL-10 release was inhibited in both silenced and nonsilenced HIV(+) macrophages. Furthermore, mTOR inhibition augmented LA-induced TNF-α release through enhanced and prolonged phosphorylation of ERK1/2 and JNK1/2 MAPK, which was associated with time-dependent MKP-1 destabilization. Taken together, impaired TLR-4-mediated TNF-α release in HIV(+) macrophages is attributable in part to mTOR activation by constitutive PI3K expression in a MyD88-dependent signaling pathway. These changes result in MAPK phosphatase 1 stabilization, which shortens and blunts MAPK activation. mTOR inhibition may serve as a potential therapeutic target to upregulate macrophage innate immune host defense responsiveness in HIV(+) persons.     

Comparing genomic prediction accuracy from purebred,crossbred and combined purebred and crossbred reference populations in sheep

Background

The accuracy of genomic prediction depends largely on the number of animals with phenotypes and genotypes. In some industries, such as sheep and beef cattle, data are often available from a mixture of breeds, multiple strains within a breed or from crossbred animals. The objective of this study was to compare the accuracy of genomic prediction for several economically important traits in sheep when using data from purebreds, crossbreds or a combination of those in a reference population.

Methods

The reference populations were purebred Merinos, crossbreds of Border Leicester (BL), Poll Dorset (PD) or White Suffolk (WS) with Merinos and combinations of purebred and crossbred animals. Genomic breeding values (GBV) were calculated based on genomic best linear unbiased prediction (GBLUP), using a genomic relationship matrix calculated based on 48 599 Ovine SNP (single nucleotide polymorphisms) genotypes. The accuracy of GBV was assessed in a group of purebred industry sires based on the correlation coefficient between GBV and accurate estimated breeding values based on progeny records.

Results

The accuracy of GBV for Merino sires increased with a larger purebred Merino reference population, but decreased when a large purebred Merino reference population was augmented with records from crossbred animals. The GBV accuracy for BL, PD and WS breeds based on crossbred data was the same or tended to decrease when more purebred Merinos were added to the crossbred reference population. The prediction accuracy for a particular breed was close to zero when the reference population did not contain any haplotypes of the target breed, except for some low accuracies that were obtained when predicting PD from WS and vice versa.

Conclusions

This study demonstrates that crossbred animals can be used for genomic prediction of purebred animals using 50 k SNP marker density and GBLUP, but crossbred data provided lower accuracy than purebred data. Including data from distant breeds in a reference population had a neutral to slightly negative effect on the accuracy of genomic prediction. Accounting for differences in marker allele frequencies between breeds had only a small effect on the accuracy of genomic prediction from crossbred or combined crossbred and purebred reference populations.     

Single-cell enabled comparative genomics of a deep ocean SAR11 bathytype

Bacterioplankton of the SAR11 clade are the most abundant microorganisms in marine systems, usually representing 25% or more of the total bacterial cells in seawater worldwide. SAR11 is divided into subclades with distinct spatiotemporal distributions (ecotypes), some of which appear to be specific to deep water. Here we examine the genomic basis for deep ocean distribution of one SAR11 bathytype (depth-specific ecotype), subclade Ic. Four single-cell Ic genomes, with estimated completeness of 55%–86%, were isolated from 770 m at station ALOHA and compared with eight SAR11 surface genomes and metagenomic datasets. Subclade Ic genomes dominated metagenomic fragment recruitment below the euphotic zone. They had similar COG distributions, high local synteny and shared a large number (69%) of orthologous clusters with SAR11 surface genomes, yet were distinct at the 16S rRNA gene and amino-acid level, and formed a separate, monophyletic group in phylogenetic trees. Subclade Ic genomes were enriched in genes associated with membrane/cell wall/envelope biosynthesis and showed evidence of unique phage defenses. The majority of subclade Ic-specfic genes were hypothetical, and some were highly abundant in deep ocean metagenomic data, potentially masking mechanisms for niche differentiation. However, the evidence suggests these organisms have a similar metabolism to their surface counterparts, and that subclade Ic adaptations to the deep ocean do not involve large variations in gene content, but rather more subtle differences previously observed deep ocean genomic data, like preferential amino-acid substitutions, larger coding regions among SAR11 clade orthologs, larger intergenic regions and larger estimated average genome size.     

Karl Popper,Forensic Science,and Nested Codes

This paper utilizes the framework of Karl Popper’s 3-world ontology to make the case that forensic science is a specialized coding system that establishes meaningful connections between the world of biology (world 1) and the world of human society (world 3). Forensic science is a cross-disciplinary endeavor that uses scientific methods to determine what transpired in a crime so the legal system can determine how to prosecute the offender(s). On a Popperian analysis of forensic science, world 1 consists of evidence gathered at the crime scene, which enables investigators to develop a detailed reconstruction of the incident for consideration under the legal and ethical codes of society, which are products of world 3. Understanding forensic science in this way serves two purposes: first, it extends Marcello Barbieri’s code biology into the realm of philosophical considerations in science, law and ethics; and second, it situates forensic science within the larger context of debates in contemporary philosophy of science.     

Binding Mode Analyses and Pharmacophore Model Development for Stilbene Derivatives as a Novel and Competitive Class of α-Glucosidase Inhibitors

Stilbene urea derivatives as a novel and competitive class of non-glycosidic α-glucosidase inhibitors are effective for the treatment of type II diabetes and obesity. The main purposes of our molecular modeling study are to explore the most suitable binding poses of stilbene derivatives with analyzing the binding affinity differences and finally to develop a pharmacophore model which would represents critical features responsible for α-glucosidase inhibitory activity. Three-dimensional structure of S. cerevisiae α-glucosidase was built by homology modeling method and the structure was used for the molecular docking study to find out the initial binding mode of compound 12, which is the most highly active one. The initial structure was subjected to molecular dynamics (MD) simulations for protein structure adjustment at compound 12-bound state. Based on the adjusted conformation, the more reasonable binding modes of the stilbene urea derivatives were obtained from molecular docking and MD simulations. The binding mode of the derivatives was validated by correlation analysis between experimental K_i value and interaction energy. Our results revealed that the binding modes of the potent inhibitors were engaged with important hydrogen bond, hydrophobic, and π-interactions. With the validated compound 12-bound structure obtained from combining approach of docking and MD simulation, a proper four featured pharmacophore model was generated. It was also validated by comparison of fit values with the K_i values. Thus, these results will be helpful for understanding the relationship between binding mode and bioactivity and for designing better inhibitors from stilbene derivatives.