Sera from sPrP+DnaK mice recognize total PrPSc and sPrP in western blots.

<p>A. 2.5 mg brain equivalent from terminally ill mice were blotted with 6H4 (lanes 1, 2), serum from a mouse immunized with sPrP+DnaK (lanes 3, 4) or with the secondary antibody alone (lanes 5, 6), prior (lanes 1, 3, 5) or ensuing (lanes 2, 4, 6) PrP^Sc enrichment. B. sPrP (1 µg) was blotted with serum from a mouse immunized with sPrP+DnaK (lane 7) or the secondary antibody alone (lane 8).</p

Recognition of PrP on the cell surface.

<p>Transgenic DT40 cells expressing PrP on their surface were stained with sera from 4 mice immunized with agPrP+FA (red, green, purple and cyan histograms) (A) or from 6 mice immunized with sPrP+DnaK+FA (red, green, purple, cyan, orange and brown histograms) (B), to evaluate recognition of PrP on the cell surface. Indigo; 6H4 staining, red negative control (secondary antibody only). Differences in the modes of the histograms between agPrP+FA and sPrP+DnaK+FA mice are statistically significant (T-test, P = 0.330).</p

sPrP is recognized with the immune sera in ELISAs.

<p>Sera from mice immunized with sPrP+FA, sPrP+DnaK+FA, PrP-DnaK+FA. agPrP+FA or FA alone were tested for their ability to recognize sPrP in ELISA in a 1∶100 (<i>v/v</i>) dilution. Each point corresponds to one individual. Line: average value; dotted line OD₄₀₅. of the positive control antibody (6H4, 0.2 µg/ml).</p

Splenic PrP^Sc accumulation.

<p>Early PrP^Sc accumulation in spleens from naive mice (lane 1), mice immunized with FA alone (lane 2), agPrP alone (3) or agPrP+FA (4), 40 (A) or 80 (B) days after challenge. Splenic samples from 3 mice per group were enriched in PrP^Sc and blotted with the polyclonal antibody SAL 1 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059143#pone.0059143-Sachsamanoglou1" target="_blank">[39]</a>. Equal amounts of total protein from three mice per group were processed.</p

Survival curves of immunized mice.

<p>Naive mice and mice immunized with sPrP+FA, agPrP+FA, PrP-DnaK+FA, sPrP+DnaK+FA or FA alone were challenged with a mouse adapted scrapie strain and sacrificed at terminal point. Mice immunized with agPrP+FA survive significantly longer than naive mice (Mantel-Cox test, P = 0.0033).</p

Regional and temporal-dependent neuropathological characteristics and miRNA signatures in the sCJD MM1 mouse model tg340-PRNP129MM.

<p>(A) tg340 mice were inoculated with control or sCJD MM1 homogenates; cortex and CB samples were collected at different time points: 120 dpi for pre-symptomatic phase and 160 dpi, 180 dpi and 210 dpi for symptomatic phase (n = 4–5 per group). Animals sacrificed at 210 dpi were inoculated with a 10–1 inoculum dilution. (B) PET-blot analysis for the detection of PrPSc in the cortex and CB of sCJD MM1 inoculated tg340 mice at clinical disease stage. (C) Densitometric analysis of western blots developed for PSD-95 and synaptophysin in the cortex and CB of tg340 samples at different disease stages. Significant alterations on PSD-95 and synaptophysin levels between control and sCJD inoculated animals is indicated. Statistical significance was set at *p<0.05, (n = 4–5 per group). (D) Heat map analysis of key inflammatory mediators and cytokines measured with RT-qPCR analysis in the cortex and CB of control and sCJD MM1 inoculated tg340 mice at different stages of the disease. Fold change between sCJD MM1 infected and control animals is shown. (E) Hematoxylin-eosin staining in the cortex and CB of control and sCJD MM1 infected tg340 animals. (F) RT-qPCR analysis of the miRNAs validated in human sCJD tissue in the cortex and CB of tg340 mice. Samples from different time points of disease progression were analyzed. Fold change between sCJD MM1 infected and control animals is shown. Results were normalized to the housekeeping gene U6 snRNA expression. U6 levels remained unaltered between groups. Normalization was performed relative to controls. Error bars indicate SD. In all cases, statistical significance (compared to controls) was set at *p<0.05.</p

Analysis of commonly altered miRNAs in sCJD, AD, DLB and FFI.

<p>(A) Venn diagrams of the comparison between altered miRNAs in AD and sCJD. Commonly deregulated miRNAs in the PFC of AD cases obtained from small RNA-seq analysis (20) (blue circles) and in the FC of sCJD cases obtained from small RNA-seq analysis in the present work (yellow circles). Common elements and percentage of maximal coincidence between groups are shown. Among these, the deregulated expression levels of miRNA-195-5p, miRNA-877-5p and miRNA-323a-5p (marked in red) were previously validated by qPCR in the FC of sCJD cases (<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006802#ppat.1006802.g002" target="_blank">Fig 2</a>). (B) RT-qPCR analysis for miRNA-146a-5p, miRNA-195-5p, miRNA-342-5p, miRNA-877-5p, miRNA-323a-5p and miRNA-5701 in the FC of controls (n = 5), AD (n = 8) and rpAD (n = 6) cases. (C) RT-qPCR analysis for miRNA-146a-5p, miRNA-195-5p, miRNA-342-5p, miRNA-877-5p, miRNA-323a-5p and miRNA-5701 in the FC of controls (n = 5) and DLB (n = 5) cases. (D) RT-qPCR analysis for miRNA-342-5p, miRNA-146a-5p, miRNA-195-5p and miRNA-5701 in the FC and CB of controls (n = 3) and FFI cases (n = 3). Results were normalized to the housekeeping U6 snRNA expression, which remained unaltered between groups. Normalization was performed relative to controls. Error bars indicate SD. In all cases, statistical significance (compared to controls) was set at *p<0.05.</p

MODELI ZA PROCJENU NEIZRAVNE ČVRSTOĆE VAPNENCA U SATURIRANOM STANJU

There are a number of methods of estimating physical and mechanical characteristics. Principally, the most widely used is the regression, but recently the more sophisticated methods such as neural networks has frequently been applied, as well. This paper presents the models of a simple and a multiple regression and the neural networks – types Radial Basis Function and Multiple Layer Perceptron, which can be used for the estimate of the Brazilian indirect tensile strength in saturated conditions. The paper includes the issues of collecting the data for the analysis and modelling and the overview of the performed analysis of the efficacy assessment of the estimate of each model. After the assessment, the model which provides the best estimate was selected, including the model which could have the most wide-spread application in the engineering practice.Potreba za procjenom neizravne vlačne čvrstoće koju inače određujemo brazilskim testom može se javiti pri idejnim rješenjima podzemnih radova u sredinama gdje je prisutna podzemna voda. Pregledom dostupne literature iz relevantnih izvora, koja se bavi utjecajem zasićenja na neizravnu vlačnu čvrstoću stijena koja se određuje brazilskim testom, utvrđeno je da se samo nekoliko radova bavi procjenom neizravne vlačne čvrstoće kod vapnenaca i pri tome se ne bave zasićenjem vodom. Isto tako, autori ovoga rada pregledom dostupne literature iz relevantnih izvora nisu naišli na rad koji bi se bavio procjenjivanjem neizravne vlačne čvrstoće vapnenca pomoću neuronskih mreža koje bi primjenjivale samo dva ulazna parametra, neizravnu vlačnu čvrstoću u suhome stanju i/ili šupljikavosti, stoga je bio razumljiv znanstveni interes za izradu i primjenu modela takva tipa. Skup podataka na temelju kojega je modelirano izrađen je jednim djelom od prikupljenih podataka iz objavljene literature gdje su navedeni rezultati ispitivanja poroznosti, indirektne vlačne čvrstoće u suhome i zasićenome stanju miocenskoga vapnenca, a drugi dio početnoga skupa bazira se na istraživanjima koja su provedena u Geomehaničkome laboratoriju RGN fakulteta u Zagrebu na vapnencima iz kamenoloma „Podberam” kod Pazina. U obama slučajevima ispitivanja su obavljena prema preporuci Međunarodnoga društva za mehaniku stijena pa je objedinjavanje bilo moguće. Na temelju prikupljenih podataka pomoću programskoga paketa Statistica 12 ukupno je napravljeno pet modela za procjenu neizravne vlačne čvrstoće. Modeli jednostruke regresije nose oznaku SR_1 (temelji se na jednostavnoj regresiji s poroznošću) i SR_2 koji je napravljen pomoću neizravne vlačne čvrstoće u suhome stanju. Model višestruke regresije nazvan je MR, a u njemu su nezavisne varijable šupljikavosti i neizravne vlačne čvrstoće u suhome stanju. Model neuronskih mreža s radijalnom baznom funkcijom nazvan je NN_RBF, a model tipa višeslojna mreža nosi oznaku NN_MLP. Uobičajeno se izrađeni modeli evaluiraju pomoću niza koeficijenata koji služe u tu svrhu: koeficijent koleracije (R), koeficijent determinacije (R2 ), korigirani R2 (R2 Adj) i korijen srednje kvadratne pogreške (RMSE). Prema parametrima ocjene najbolji je model NN_MLP, zatim slijedi model NN_RBF pa model MR te model SR_2 i na kraju model SR_1. Iako model NN_MLP najbolje procjenjuje neizravnu vlačnu čvrstoću u saturiranome stanju jer ima R = 0,987348; R2 = 0,974856; R 2 Adj = 0,974382 i RMSE = 0,272791, ipak prema mogućnosti šire primjene u inženjerskoj praksi model višestruke regresije najviše obećava jer za njegovu primjenu nisu potrebni složeni programski paketi. Modele iz ovoga rada treba primjenjivati samo kada su ulazni parametri u rasponu za indirektnu vlačnu čvrstoću u suhome stanju od 0,07 do 7,381 MPa

Altered expression levels of miRNA biogenesis components in sCJD.

<p>(A) Gene expression levels of Drosha (n = 10), DGCR8 (n = 10) and Dicer (n = 10) in the FC and CB of controls, sCJD MM1 and VV2 cases by RT-qPCR. Results were normalized to housekeeping genes GAPDH (figure) and GUSB with similar results. Housekeeping levels remained unaltered between groups. (B) Protein levels of Drosha, DGCR8, Dicer in the FC and CB of controls, sCJD MM1 and VV2 cases, by western blot analysis. Three representative cases per diagnostic group and brain region are shown in the western blot. Quantifications derived from densitometry analysis were performed in 15 cases per diagnostic group (n = 15/group). β-actin was used as a loading control. Densitometries of the western blots are shown. Normalization was performed relative to controls. Error bars indicate SD. In all cases, statistical significance (compared to controls) was set at *p<0.05.</p

Neural-type miRNA profiling in sCJD.

<p>(A) Heat map analysis of the neuron, microglia and astrocyte enriched miRNAs, whose levels were changed in the FC and CB of sCJD MM1 and VV2 cases by RNA-seq analysis. Neural-type enriched miRNAs were reported in the bibliography based on neural-type enrichment analysis (49). (B) In situ hybridization of miRNA-124-3p in the FC and CB of control and sCJD MM1 brain tissue, and of miRNAs 26a-5p and 146a-5p in the FC of sCJD MM1 brain tissue. (C) Quantification of miRNA-124-3p intensity in the FC and CB of control and sCJD MM1 neurons. >100 neurons in total were quantified for each group. Normalization was performed relative to controls. AU/neuron indicates arbitrary units quantified in the densitometry analysis for each neuron. Error bars indicate SD. Scale bar in FC = 30μm and in CB = 50μm. In all cases, statistical significance (compared to controls) was set at *p<0.05.</p