„Der epidurale Blood Patch: ein Auftrag für den versierten Anästhesisten?“

Die Anaesthesiologie -     

Divergence in the spatial pattern of gene expression between human duplicate genes

Microarray gene expression data provide a wealth of information for elucidating the mode and tempo of molecular evolution. In the present study,we analyze the spatial expression pattern of human duplicate gene pairs by using oligonucleotide microarray data,and study the relationship between coding sequence divergence and expression divergence. First,we find a strong positive correlation between the proportion of duplicate gene pairs with divergent expression (as presence or absence of expression in a tissue) and both synonymous (K(S)) and nonsynonymous divergence (K(A)). The divergence of gene expression between human duplicate genes is rapid, probably faster than that between yeast duplicates in terms of generations. Second,we compute the correlation coefficient (R) between the expression levels of duplicate genes in different tissues and find a significant negative correlation between R and K(S). There is also a negative correlation between R and K(A), when K(A) 相似文献   

Platelets in atherothrombosis--diagnostic and prognostic value of platelet activation in patients with atherosclerotic diseases

Platelets and their activation have a pivotal role in the development of atherosclerotic diseases such as acute myocardial infarction (AMI), stroke and peripheral arterial occlusion. Biomarkers of platelet activation are making inroads into clinical studies and may serve as promising agents upstream to established downstream markers of myocardial necrosis such as troponin and creatin kinase. Targeting the degree of platelet activation assessed by the key collagen receptor of platelet activation, glycoprotein VI (GPVI), may have diagnostic and prognostic value for the assessement of high-risk groups of patients with symptomatic coronary artery disease and ischemic stroke and may be worthwhile to help to facilitate clinical decision-making and to rapidly initiate adequate therapy. The concert of platelet count, platelet activation, platelet aggregation and subsequent inflammation has had a significant impact on the clinical outcome in patients with atherosclerotic diseases. For a therapeutical approach to ameliorate prognosis, the use of antiplatelet treatment in particular in AMI patients with low response to clopidogrel has partly been overcome by novel second antiplatelet drugs on top of aspirin such as prasugrel and ticagrelor. Antiplatelet therapy may be adapted according to a GPVI-based platelet activity monitoring along with aggregometry of residual platelet aggregation. Other approaches using protease-activated receptor- 1 antagonists vorapaxar or atopaxar, which inhibit the platelet thrombin receptor, soluble GPVI called Revacept?, which blocks the collagen binding sites at the vascular lesion and anopheline saliva protein derived from the malaria vector mosquito, a platelet adhesion inhibitor independent of a GPVI mechanism, still wait for their breakthrough.     

Lipopolysaccharide (LPS) directly suppresses growth hormone receptor (GHR) expression through MyD88-dependent and -independent Toll-like receptor-4/MD2 complex signaling pathways

INTRODUCTION: Sepsis is associated with growth hormone (GH) insensitivity and in the intact animal the major surface component of the bacterial cell wall, lipopolysaccharide (LPS), inhibits GH receptor (GHR) gene expression. The prevailing explanation for LPS-induced effects on the GHR promoter is that this effect is indirect via generation of cytokines. Our recent studies demonstrate that saturated free fatty acids (FFAs) inhibit the activity of the murine GHR promoter. Saturated FFAs are an essential component of the lipid A moiety of LPS required for biological activity of LPS. HYPOTHESIS: LPS directly modulates the activity of the dominant GHR promoter via interaction with Toll-like receptor(s) (TLR)/MD2 complex and activation of cognate signaling pathway(s). RESULTS: In transient transfection experiments with RAW 264.7 cells which express endogenous TLR4 and MD2, LPS treatment inhibited GHR promoter activity. Co-transfection of dominant negative TLR4 abrogated this effect on GHR promoter activity. In HEK 293T cells, which are devoid of endogenous TLR4 or MD2, ectopic expression of TLR4 and MD2 resulted in LPS-induced inhibition of the GHR promoter activity. The inhibition of GHR promoter activity was demonstrable by 5-6h after exposure to LPS and persisted at 24h. Fatty-acid free LPS failed to elicit a similar effect on the GHR promoter and the effect of LPS was abrogated by Polymyxin B. The essential role of the cofactor MD2 on the effect of LPS on the GHR promoter was established in experiments using ectopic expression of wild type and mutant MD2. Cotransfection of CD14 in these cells failed to alter the effect of LPS on the activity of the GHR promoter. Analysis of cell culture supernatant excluded the possibility that the effect of LPS was secondary to release of cytokines from the transfected cells. The effect of LPS on the endogenous GHR promoter activity and protein expression was confirmed in F442A preadipocyte cells. In HEK 293T cells, ectopic expression of mutant MyD88 or mutant TRIF abrogated the effect of LPS on the GHR promoter, suggesting that the effect of LPS on the GHR promoter was via both MyD88-dependent and -independent pathways. CONCLUSIONS: LPS acts through both MyD88-dependent and -independent TLR4 signaling pathways to directly inhibit GHR gene expression. Our results establish a novel cytokine-independent mechanism for decrease in GHR expression in bacterial sepsis.     

Characterization of BASP1-mediated neurite outgrowth

The brain acid-soluble protein BASP1 (CAP-23, NAP-22) belongs to the family of growth-associated proteins, which also includes GAP-43, a protein recently shown to regulate neural cell adhesion molecule (NCAM)-mediated neurite outgrowth. Here, the effects of BASP1 overexpression were investigated in PC12E2 cells and primary hippocampal neurons. BASP1 overexpression stimulated neurite outgrowth in both cell types. The effects of BASP1 and trans-homophilic NCAM interactions were additive, and BASP1-induced neurite outgrowth was not inhibited by ectopic expression of cytoplasmic NCAM domains. Furthermore, inhibition of signaling via the fibroblast growth factor receptor, Src-family nonreceptor tyrosine kinases, protein kinase C, or GSK3beta, and expression of constructs of the cytoskeletal proteins spectrin and tau inhibited NCAM- but not BASP1-induced neurite outgrowth. Expression of BASP1 mutated at the serine-5 phosphorylation site stimulated neurite outgrowth to a degree comparable to that observed in response to overexpression of wild-type BASP1, whereas expression of BASP1 mutated at the myristoylation site at glycine-1 completely abrogated the stimulatory effects of the protein on neurite outgrowth. Finally, coexpression experiments with dominant negative and wild-type versions of GAP-43 and BASP1 demonstrated that the two proteins could substitute for each other with respect to induction of NCAM-independent neurite outgrowth, whereas BASP1 was unable to replace the stimulatory effect of GAP-43 on NCAM-mediated neurite outgrowth. These observations demonstrate that BASP1 and GAP-43 have overlapping, but not identical, functions in relation to neurite outgrowth and indicate that the main function of BASP1 is to regulate the organization and morphology of the plasma membrane.     

Abnormal vaginal microbioma is associated with severity of localized provoked vulvodynia. Role of aerobic vaginitis and <Emphasis Type="Italic">Candida</Emphasis> in the pathogenesis of vulvodynia

Localized provoked vulvodynia (LPV) causes introital dyspareunia in up to 14% of premenopausal women. Vaginal infections like candidosis may play a initiating role. The aim of this study was to test a possible association of vaginal microbiota alternations such as Candida vaginitis (CV), aerobic vaginitis (AV) and bacterial vaginosis (BV) with severity of vulvodynia and painful intercourse. In an observational study, Q-tip touch test (score 1 (no pain) to 10 (worst possible pain)) was performed on seven vestibular locations in 231 LPV patients presenting in the Vulvovaginal Disease Clinics in Tienen, Leuven and Antwerp, Belgium. Severity of pain upon attempting sexual intercourse was recorded in a similar scale. Both scales were compared to results from fresh wet mount phase contrast microscopy on vaginal fluid smears tested for abnormal vaginal flora (AVF), BV, AV and CV according the standardized microscopy method (Femicare). Fisher’s exact test was used. Average age was 31.3?±?11.6 years, and 58.8% (n?=?132) had secondary vestibulodynia. There was an inverse relation between the presence of Candida in the vaginal smears and pain score (p?=?0.03). There was no relation of pain score, nor Q-tip score with BV. LPV patients with Q-tip score above 7 at 5 and/or 7 o’clock or at 1 and/or 11 o’clock had more often AV than women with lower pain scores (30 vs 14.5%, p?=?0.01, and 39 vs 14.7%, p?<?0.005, respectively). Detailed study of the vaginal microflora in patients demonstrates that the most severe patients suffer more from AV and less from Candida. These abnormalities need to be actively looked for and corrected before considering surgery or other therapies.     

Segmenting the human genome based on states of neutral genetic divergence

Many studies have demonstrated that divergence levels generated by different mutation types vary and covary across the human genome. To improve our still-incomplete understanding of the mechanistic basis of this phenomenon, we analyze several mutation types simultaneously, anchoring their variation to specific regions of the genome. Using hidden Markov models on insertion, deletion, nucleotide substitution, and microsatellite divergence estimates inferred from human–orangutan alignments of neutrally evolving genomic sequences, we segment the human genome into regions corresponding to different divergence states—each uniquely characterized by specific combinations of divergence levels. We then parsed the mutagenic contributions of various biochemical processes associating divergence states with a broad range of genomic landscape features. We find that high divergence states inhabit guanine- and cytosine (GC)-rich, highly recombining subtelomeric regions; low divergence states cover inner parts of autosomes; chromosome X forms its own state with lowest divergence; and a state of elevated microsatellite mutability is interspersed across the genome. These general trends are mirrored in human diversity data from the 1000 Genomes Project, and departures from them highlight the evolutionary history of primate chromosomes. We also find that genes and noncoding functional marks [annotations from the Encyclopedia of DNA Elements (ENCODE)] are concentrated in high divergence states. Our results provide a powerful tool for biomedical data analysis: segmentations can be used to screen personal genome variants—including those associated with cancer and other diseases—and to improve computational predictions of noncoding functional elements.Whole-genome sequencing studies have demonstrated that divergence estimates for several mutation types (e.g., nucleotide substitutions, insertions, and deletions) vary substantially across the human genome. This phenomenon has been studied at various genomic scales and evolutionary distances (reviewed in ref. 1), and—whereas initially of interest solely to evolutionary biologists—is now entering the purview of main biomedical research. Specifically, human population (e.g., ref. 2) and cancer (3, 4) genome resequencing projects have revealed that incidences of single nucleotide polymorphisms (SNPs), insertions and deletions (indels), and copy number variants (CNVs) vary across the genome. Divergence estimates for different mutation types also covary across the genome (5, 6)—e.g., substitution rates increase in regions with high indel rates (7)—suggesting that regional variation is an important and general characteristic of mutations.Variation in divergence is often linked to genomic landscape features such as base composition, replication timing, and recombination rates (1). For instance, nucleotide substitution rates are elevated in late-replicating regions because of an accumulation of single-stranded DNA susceptible to endogenous damage (8) and are affected by chromatin structure (9) and recombination as a result of either biased gene conversion (BGC) (10) or the mutagenicity of recombination (2). Moreover, nucleotide substitution rates depend nonlinearly on guanine and cytosine (GC) content (11) and are affected by methylation levels and GC content at cytosine—phosphate—guanine (CpG) sites (12) and by replication timing and distance to telomeres at non-CpG sites (13). Covariation in divergence among rates of different mutation types can also be at least partly attributed to the influence of a common genomic landscape (5). Importantly, we note that, whereas selection may indeed operate in noncoding regions, it is unlikely to explain the large degree of variation and covariation in divergence estimates computed from putatively neutral sequences (1, and references therein). Divergence computed for neutral DNA ought to reflect mutation, BGC, and—for relatively distant species—only a minimal amount of diversity.Anchoring variation and covariation of divergence estimates for different mutation types to specific regions of the genome is crucial for elucidating how biochemical processes—e.g., replication and recombination—drive mutagenesis (8, 10) and for understanding genome evolution. Such a “geographic” characterization may correlate with the spatial distribution of genes; for instance, cellular receptor and housekeeping genes tend to locate, respectively, in high and low nucleotide substitution rate regions (14). It may also aid prediction of noncoding functional elements (15, 16) and studies of the genetic basis of disease. For instance, it could assist in (i) discerning whether a locus exhibits an excess of mutations because it resides in a hotspot, thus preventing false positive associations with a disease; and (ii) identifying loci with mutational signatures typical of a disease, e.g., explaining frequent coincidence in tumors of sites prone to DNA damage and chromosomal instability (17).With this motivation, we used hidden Markov models (HMMs) (18), a well-established statistical tool, to analyze human divergence for different mutation types. An HMM models a sequence of observations as governed by underlying states that are not directly observable (hidden) but can be inferred based on the data. These states alternate along the sequence following a Markovian structure, i.e., the state governing a given observation may depend on the state governing the preceding observation. Maximum likelihood techniques are used to select an appropriate number of states, characterize them, and partition the sequence into contiguous segments governed by each state.In genomics, HMMs have been used to model stretches of DNA—the sequences of observations—in a variety of applications ranging from gene finders (19) to epigenomic segmentations (20, 21). In our study, we compute divergence estimates for four mutation types—substitutions, insertions, deletions, and microsatellite repeat number alterations—in nonoverlapping windows of neutrally evolving sequences present in human–orangutan genomic alignments. Modeling the resulting observations with HMMs, we identify distinct divergence states characterized by biologically meaningful combinations of elevated, average, or depressed divergence levels for the four mutation types, e.g., a state where only microsatellite mutations are elevated, whereas the other divergence types are average; one where substitutions, insertions, and deletions are all elevated, whereas microsatellite divergence is average, etc. Correspondingly, we partition the genome into chromosomal segments governed by these states. Our analysis departs from previous applications in considering several mutation types simultaneously—thus accounting for their interdependencies—and in generating segmentations not on a small 100-bp scale (22), but on a larger 1-Mb scale that robustly captures variation in divergence for mammalian genomes (11, 23). Additionally, we investigate whether divergence states differ in genomic landscape features that proxy underlying mutagenic processes, correlate with the spatial organization of functional elements, and persist when assessed from human diversity estimates or for varying genomic scales.     

Coping with antibiotic resistance: combining nanoparticles with antibiotics and other antimicrobial agents

The worldwide escalation of bacterial resistance to conventional medical antibiotics is a serious concern for modern medicine. High prevalence of multidrug-resistant bacteria among bacteria-based infections decreases effectiveness of current treatments and causes thousands of deaths. New improvements in present methods and novel strategies are urgently needed to cope with this problem. Owing to their antibacterial activities, metallic nanoparticles represent an effective solution for overcoming bacterial resistance. However, metallic nanoparticles are toxic, which causes restrictions in their use. Recent studies have shown that combining nanoparticles with antibiotics not only reduces the toxicity of both agents towards human cells by decreasing the requirement for high dosages but also enhances their bactericidal properties. Combining antibiotics with nanoparticles also restores their ability to destroy bacteria that have acquired resistance to them. Furthermore, nanoparticles tagged with antibiotics have been shown to increase the concentration of antibiotics at the site of bacterium-antibiotic interaction, and to facilitate binding of antibiotics to bacteria. Likewise, combining nanoparticles with antimicrobial peptides and essential oils generates genuine synergy against bacterial resistance. In this article, we aim to summarize recent studies on interactions between nanoparticles and antibiotics, as well as other antibacterial agents to formulate new prospects for future studies. Based on the promising data that demonstrated the synergistic effects of antimicrobial agents with nanoparticles, we believe that this combination is a potential candidate for more research into treatments for antibiotic-resistant bacteria.