Received: 27 November 2019; Accepted: 14 January 2020; Published: 19 January 2020 Abstract: Objective: Aortic size-based criteria are of limited value in the prediction of aortic events, while most aortic events occur in patients with proximal aortic diameters < 50 mm. Serological biomarkers and especially circulating microRNAs (miRNAs) have been proposed as an elegant tool to improve risk stratification in patients with different aortopathies. Therefore, we aimed to evaluate the levels of circulating miRNAs in a surgical cohort of patients presenting with bicuspid aortic valve disease and distinct valvulo-aortic phenotypes. Methods: We prospectively examined a consecutive cohort of 145 patients referred for aortic valve surgery: (1) Sixty three patients (mean age 47 ± 11 years, 92% male) with bicuspid aortic valve regurgitation and root dilatation (BAV-AR), (2) thirty two patients (mean age 59 ± 11 years, 73% male) with bicuspid aortic valve stenosis (BAV-AS), and (3) fifty patients (mean age 56 ± 14 years, 55% male) with tricuspid aortic valve stenosis and normal aortic root diameters (TAV-AS) who underwent aortic valve+/-proximal aortic surgery at a single institution. MicroRNAs analysis included 11 miRNAs, all published previously in association with aortopathies. Endpoints of our study were (1) correlation between circulating miRNAs and aortic diameter and (2) comparison of circulating miRNAs in distinct valvulo-aortic phenotypes. Results: We found a significant inverse linear correlation between circulating miRNAs levels and proximal aortic diameter in the whole study cohort. The strongest correlation was found for miR-17 (r = −0.42, p < 0.001), miR-20a (r = −0.37, p < 0.001), and miR-106a (r = −0.32, p < 0.001). All miRNAs were significantly downregulated in BAV vs. TAV with normal aortic root dimensions Conclusions: Our data demonstrate a significant inverse correlation between circulating miRNAs levels and the maximal aortic diameter in BAV aortopathy. When comparing miRNAs expressionpatterns in BAV vs. TAV patients with normal aortic root dimensions, BAV patients showed significant downregulation of analyzed miRNAs as compared to their TAV counterparts. Further multicenter studies in larger cohorts are needed to further validate these results.
Published online: 10 November 2017
# The Author(s) 2017. This article is an open access publication
Abstract The larval brain of the fruit fly Drosophila melanogaster is a small, tractable model system for neurosci- ence. Genes for fluorescent marker proteins can be expressed in defined, spatially restricted neuron populations. Here, we introduce the methods for 1) generating a standard template of the larval central nervous system (CNS), 2) spatial mapping of expressionpatterns from different larvae into a reference space defined by the standard template. We provide a manually annotated gold standard that serves for evaluation of the regis- tration framework involved in template generation and map- ping. A method for registration quality assessment enables the automatic detection of registration errors, and a semi-automatic registration method allows one to correct registrations, which is a prerequisite for a high-quality, curated database of expres- sion patterns. All computational methods are available within
„Ich, Jing Du, versichere an Eides statt durch meine eigenhändige Unterschrift, dass ich die vorgelegte Dissertation mit dem Thema: Expressionpatterns of EphA2 tyrosine kinase receptor in human digestive system organs and tumors selbstständig und ohne nicht offengelegte Hilfe Dritter verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel genutzt habe. Alle Stellen, die wörtlich oder dem Sinne nach auf Publikationen oder Vorträgen anderer Autoren beruhen, sind als solche in korrekter Zitierung (siehe „Uniform Requirements for Manuscripts (URM)“ des ICMJE -www.icmje.org) kenntlich gemacht. Die Abschnitte zu Methodik (insbesondere praktische Arbeiten, Laborbestimmungen, statistische Aufarbeitung) und Resultaten (insbesondere Abbildungen, Graphiken und Tabellen) entsprechen den URM (s.o) und werden von mir verantwortet.
Neurodevelopmental disorders, such as ASD and ADHD, affect males about three to four times more often than females. 16p11.2 hemideletion is a copy number variation that is highly associated with neurodevelopmental disorders. Previous work from our lab has shown that a mouse model of 16p11.2 hemideletion (del/+) exhibits male- speciﬁc behavioral phenotypes. We, therefore, aimed to investigate with magnetic resonance imaging (MRI), whether del/+ animals also exhibited a sex-speciﬁc neuroanatomical endophenotype. Using the Allen Mouse Brain Atlas, we analyzed the expressionpatterns of the 27 genes within the 16p11.2 region to identify which gene expressionpatterns spatially overlapped with brain structural changes. MRI was performed ex vivo and the resulting images were analyzed using Voxel-based morphometry for T1-weighted sequences and tract-based spatial statistics for diffusion-weighted images. In a subsequent step, all available in situ hybridization (ISH) maps of the genes involved in the 16p11.2 hemideletion were aligned to Waxholm space and clusters obtained by sex-speci ﬁc group comparisons were analyzed to determine which gene(s) showed the highest expression in these regions. We found pronounced sex-speci ﬁc changes in male animals with increased fractional anisotropy in medial ﬁber tracts, especially in those proximate to the striatum. Moreover, we were able to identify gene expressionpatterns spatially overlapping with male-speci ﬁc structural changes that were associated with neurite outgrowth and the MAPK pathway. Of note, previous molecular studies have found convergent changes that point to a sex-speciﬁc dysregulation of MAPK signaling. This convergent evidence supports the idea that ISH maps can be used to meaningfully analyze imaging data sets.
Interestingly, all PR proteins mentioned in Table 5 were detected upregulated at 4 DPI in the foliar infection, while 2 DPI and root PR protein expressionpatterns did not overlap, with only two (BdiBd21-3.2G0114800 and BdiBd21-3.1G0165000) upregulated at 2 DPI, and three (BdiBd21-3.4G0068000, BdiBd21-3.1G0772600, BdiBd21- 3.1G0772700) in the root datasets. Similarly, the strongest and most widespread upregulation in the other pathogen sensing / defense-related genes was observed at 4 DPI, with an upregulation of transcription factors belonging to MYB, WRKY and NAC families consistent with the upregulation observed in Bd after F. pseudograminearum infection (Powell et al., 2017) and the knowledge that these families regulate a variety of plant responses, including to biotic stresses (Ambawat et al., 2013; Bakshi et al., 2014; Murozuka et al., 2018). In line with the considerable overlap in Mo gene expressionpatterns between 4 DPI leaf and root setups, majority of genes found upregulated in Bd roots (80.9%) are also detected upregulated in the foliar necrotrophic datasets, compared to 18% shared with the 2 DPI samples. Altogether, these results highlight differences in the upregulation of specific protein family members depending on the infected tissue and fungal lifestyle, while confirming the relevance of these families upregulation in response to Mo infections.
ZC3H11A is a poorly characterized zinc finger protein that belongs to the CCCH- type zinc finger family with 58 known members in mouse, most of them still uncharacterized (Andersson et al., 2010). ZC3H11A protein contains in its structure three tandem CCCH- zinc finger domains. Members of this family are identified as RNA-binding protein where zinc finger domains facilitate direct binding to mRNA. For instance, U2AF1 and Cpf4 are essential for regulating pre-mRNA splicing. Other proteins in this family increase the rate of mRNA turnover by removing the poly A tail from mRNAs that contain AU-rich elements (Liang et al., 2008). The molecular function of ZC3H11A was investigated using RNA interference. Silencing or reducing the normal level of a gene of interest can provide information about function through the evaluation of effects of silencing on other parameters such as morphological changes in cell culture and changes in expressionpatterns of other genes. In this project, we silenced ZC3H11A in a mouse myoblast cell line using small interfering RNA. Thereafter, the expression levels of mRNAs of interest were analyzed by real-time PCR to explore the influence of ZC3H11A transcript levels on abundance of mRNA for other genes. Afterwards, the proliferation and differentiation rate of myoblasts were assessed 48 h after the transfection with mouse ZC3H11A-specific siRNA oligonucleotides. In addition, the splice junctions of putative target genes were evaluated by reverse transcription PCR including primers that were designed for specific locations close to splice junction sites (Figure13). Furthermore, we used immunohistochemistry (IHC) to determine the localization of ZC3H11A during embryonic development.
For the simplest distinction between RA and other conditions, we provide two classification models. The genes used in the models might not be causative or functionally most related, but are a minimal set of genes to classify the data, which classification in that way is also significant at 10-fold cross-validation. The pre-selection of genes based on intersecting single-variable comparisons is needed for escaping the curse of dimensionality for multivariable classification methods. This pre-selection has some limitations: it has itself no internal validation and the gene sets from the single-variable comparisons are differently solid, as there are conditions with different sample sizes (smallest: 6 samples of UA and 10 of arthralgia). This increases the chance to lose the ’best’ (= most likely causative) predictors and getting instead the most corre- lated (to the ’best’ predictors) variables in the model. This pre-selection weakens the validity of the internal cross-fold validation. The used classification method (PART [ 50 ], a tree learner based rule generator) is likely over-simplifying RA. For final assessments of the particular— potential causal—functions of the selected predictors, dedicated wet lab experiments are needed. The presented classification models are only intended for a distinction between RA and other conditions as simple as possible based on gene expression.
al., 2016). Detailed quantitative analysis of the regions relevant for the development of temporal lobe epilepsy confirmed these findings, and added specific information regarding changes in the expression following status epilepticus. All regions analysed showed a noticeable induction of HSPA1, with the effect especially pronounced in hippocampal subregions and in the piriform cortex, areas prone to neuronal cell damage as the consequence of SE. This regulation seems to be in accordance with the role of HSPA1 as an inhibitor of apoptosis (BENARROCH, 2011; KIM et al., 2018) and seems to act as a protective mechanism following the insult and the subsequent cell stress and damage. HSPA1 overexpression has already proven to exert neuroprotective effects and to increase neuronal survival in stroke and epilepsy models (YENARI et al., 1998). Chemical induction of SE triggers a rapid increase in HSPA1 expression rates in several studies (VASS et al., 1989; YANG et al., 2008; LIVELY & BROWN, 2011). Those previous studies were not however based on unbiased stereological cell quantification, which was utilised in our project. The electric SE model used for purposes of this study excludes also possible direct effects of chemoconvulsants, providing unambiguous confirmation of findings in abovementioned experiments.
Performing the Human Cytokines & Chemokines RT 2
Proﬁler PCR Array, the expression of various cytokines and chemokines for each of the cell lines was analyzed compared to the nonmalignant cell line RC-124. The following 32 cyto- kines and chemokines were not expressed: ADIPQ, BMP7, CCL1, CCL17, CCL18, CCL19, CCL22, CCL24, CCL3, CCL8, CD40LG, CXCL13, CXCL9, FASLG, IFNG, IL10, IL12B, IL13, IL16, IL17A, IL17F, IL21, IL22, IL24, IL3, IL4, IL5, IL9, LTA, THPO, TNFSF11, and XCL1.
cells suppresses transformation and tumorigenity. 140 All these data suggest that there might reside one or more potent tumor suppressors on 1p36, but despite intensive investigations a defined 1p tumor suppressor could not be identified so far. Recently Chromodomain Helicase DNA binding domain 5 (CHD5) was proposed as a candidate tumor suppressor gene. CHD5 was absent in neuroblastoma cell lines and a large percentage of primary tumors. 141 In a group of 99 neuroblastoma patients, CHD5 expression correlated with the event-free survival independently from a deletion of the short arm of chromosome 1 (1p) but correlated with amplified N-Myc and age. 142 The prognostic impact of CHD5 is further supported by a recent publication of Garcia et al 143 , demonstrating low or absent CHD5 expression in high-risk neuroblastoma and intense nuclear CHD5 staining in low-risk tumors. These findings suggest a possible clinical utility to distinguish between low-risk stage 4s and high-risk stage 4 tumors in infants. According to the International Neuroblastoma Staging System (INSS), stage 4 neuroblastomas include metastasized tumors, usually with an unfavourable prognosis. In contrast, Stage 4S denotes a specific metastatic stage of neuroblastomas in children younger than one year with small primary tumors and metastases in liver, skin, or bone marrow that spontaneously regress in most cases. 144 To distinguish between stage 4 and stage 4S is important for a treatment decision (ranging from aggressive multimodal treatment to watch-and-wait strategy) but can be difficult. Thus, a molecular marker that improves the differentiation between these two stages would be of great clinical advantage.
HSP70, an inducible molecular chaperone, has been found to be up-regulated in the cochlea by potentially damaging types of stress including heat [Dechesne et al., 1992], ischemia [Myers et al., 1992], noise [Lim et al., 1993] and cisplatin [Oh et al., 2000]. Moreover, HSP70 has been indicated to have a protective function in the cochlea [Altschuler et al., 1996]. HSF1, the major transcription factor regulating expression of stress-induced heat shock proteins (e.g. HSP70) is present in rodent cochlea (hair cells, spiral ganglion neurons and stria vascularis) [Fairfield et al., 2002]. The importance of heat shock system was demonstrated using knock-out Hsf1-/- mice, in which HSP induction through Hsf1-dependent stress pathway is eliminated. After exposure to noise, the knock-out mice had greater hearing loss and greater outer hair cell loss than Hsf1+/+ mice, providing evidence for the critical role of HSF1 and HSP in cochlear protection and recovery [Fairfield et al., 2005]. In addition, it has been demonstrated that heat shock protected from aminoglycoside-induced utricular hair cells loss in wild-type mice, but not HSP70 double knock out mice. Moreover, the HSP70-overexpressing utricles of transgenic mice were significantly protected against aminoglycoside-induced hair cell death, compared with utricles from wild-type littermates [Taleb et al., 2008].
The extent of differential expression alone does not indicate experiment spe- cific involvement of genes. Based on the prediction performance we identified specific candidates genes that exhibit experiment specific expression, i.e., expres- sion changes that cannot be explained (predicted) by our models. This analysis is related to co-expression studies and complements differential expression analy- sis. It enables to focus on concise candidate lists for follow-up studies that con- sist of experiment-specific candidates only. We screened for filter thresholds and estimated Padesco’s performance from permutation tests as comprehensive gold standards for the experiment specific expression of genes are not available. This newly devised simulation approach suggests that specific candidates are identified reliably by Padesco (> 85% precision at padscore > 1.5) even if they show only marginal levels of differential expression. On the other hand, more than 90% of the genes selected by differential expression alone exhibit only generic expressionpatterns and could be excluded from further studies. Specific candidates are likely to represent characteristic features of the corresponding experimental conditions.
In chapter 2, we define the functionals S euc , S hyp , and S sph for euclidean, hyperbolic, and spherical circle patterns. The functional S sph is not convex. Thus, we cannot use it to prove existence and uniqueness theorems. The variables are (up to a coordinate transformation) the (euclidean, hyperbolic, or spherical) radii of the circles. A Legendre transformation of these functionals (section 3.1) leads to a new variational principle involving one new functional b S for all geometries (euclidean, hyperbolic, and spherical). The variables of b S are certain angles; and the variation is constrained to coherent angle systems. Depending on whether the constraint involves euclidean, hyperbolic, or spherical coherent angle systems (section 2.7), the critical points correspond to euclidean, hyperbolic, or spherical circle patterns. Colin de Verdi` ere first used a variational principle to prove existence and uniqueness for circle packings . He constructs two functionals, one for the euclidean case, one for the hyperbolic case. The variables are the radii of the cir- cles. Critical points correspond to circle packings. Explicit formulas are given only for the derivatives of the functionals, not for the functionals themselves. In sec- tion 3.2, we derive Colin de Verdi` ere’s functionals from our functionals S euc and S hyp . In particular, this effects the integration of Colin de Verdi` ere’s differential formulas.
Secondly, most of the student teachers indicated that they preferred to have pupils interpret the patterns and trends themselves. In other words, instead of directly explain- ing what is shown in the maps, graphs and tables, they firstly asked them what they saw in the maps and what they believed these maps etc. indicated. However, they state that students were not successful at drawing conclusions and making generalisations using patterns and trends. Nevertheless, we also know that it is not a good idea to present information directly to pupils for the purposes of this project. That is why we believe that providing student teachers with some useful hints how to encourage pupils to find the information on patterns and trends on their own might be a good idea. In this way, we would not only realise deductive learning but we would foster critical thinking as well. Additionally, student teachers can fall back on these hints when students get stuck while interpreting patterns and trends.
Analyses of crash data-bases may search for patterns that can be exploited for prevention of future crashes. There are well-known approaches for this that range from simple tables (e.g. reports as the ones published by statistical authorities) and contingency tables (see Tunaru (1999) or Kateřina et al (2019)), to so- phisticated models for crash likelihood (Mannering (2018)) that try to summarize these data into models whose parameters are estimated from the data.
The synchronized dynamics given by Eq. ( 5.31 ) is equivalent to a system of two cou- pled nodes with self-feedback. In [ Schöll et al. , 2009 ; Panchuk et al. , 2013 ] it was shown that depending on the delay times, the coupling strength, and the strength of the self- feedback different dynamical scenarios, i.e., in-phase synchronization, anti-phase syn- chronization, or bursting can arise. Figure 5.4 shows the MSF in panels (a)-(c) for in- phase synchronization, anti-phase synchronization and for synchronization in two burst- ing groups, respectively. The right hand panels of Fig. 5.4 depict the corresponding time series: In panels (d), (f), and (h) for the activator and in panels (e), (g), and (i) for the inhibitor for in-phase, anti-phase, and bursting dynamics, respectively. Obvi- ously, the different synchronization scenarios yield very different MSFs. Thus, some topologies might show stable synchronization for one of the patterns but not for the oth- ers.
programs p. Even if the set of all p is countably infinity it is practically very hard to feasibly determine the optimal p under ϕ. If a certain pattern from a realistic example is given and we have a lot of computational power at hand, it may still be take millions of years until even our best computers made a decision about the optimal program to compress the pattern x in question. But this is not the way we (including non-human agents) epistemically talk about patterns. Usually, when we refer to a statistical or visual pattern, we are able to provide a (maybe vague) description of it in the first hand. We know that ‘house’ is a pattern to us English speakers, since we already have a list of vocabulary at hand. It is not the case that we see ‘house’ and then think about every possible combination of five letters, find possible references for all of these mostly made-up words and finally find out that houses are objects that can be referenced very easily. The pattern that is shown in the top left image from figure 4.6 (p. 119 ) is a pattern for us since we can construct the depicted geometric object very easily from everyday geometry by referring to rectangles and lines and not by going through every possible arrangement of black and white pixles, and then find out that it might be a pragmatically good idea to talk about lines and rectangles specifically. This route of explicating complexity is therefore not a good approach to provide a descriptive epistemological account of what patterns in science are; this inadequateness holds for all relevant agents (e.g. humans; AIs; aliens). Again, Dennett is right regarding his neo-Kantian implications, but he is wrong by his restriction to some kind of epistemically fixed human agent and the ontological implications.