9,520 research outputs found
Successful elimination of AthCV1 with cycloheximide (PCR confirmation): lane M = 1 kb plus DNA ladder, lane 1 = ITS1 & ITS2 DNA band confirms competence of PCR in virus-free culture, lane 2 = ITS1 & ITS2 negative PCR control (RNA replaced with ultrapure water), lane 3 = virus-specific band in virus-infected line used as +ve control, lane 4 = No virus-specific band in virus-free line, lane 5 = ITS DNA band confirms competence of PCR in virus-infected line.
No full textSuccessful elimination of AthCV1 with cycloheximide (PCR confirmation): lane M = 1 kb plus DNA ladder, lane 1 = ITS1 & ITS2 DNA band confirms competence of PCR in virus-free culture, lane 2 = ITS1 & ITS2 negative PCR control (RNA replaced with ultrapure water), lane 3 = virus-specific band in virus-infected line used as +ve control, lane 4 = No virus-specific band in virus-free line, lane 5 = ITS DNA band confirms competence of PCR in virus-infected line.</p
Numerical and experimental study of a droplet-based PCR chip
No full textA two-temperature continuous-flow polymerase chain reaction (PCR) polymer chip has been constructed that takes advantage of droplet technology to avoid sample contamination and adsorption at the surface. Samples contained in aqueous droplets are continuously moved by an oil carrier-fluid through various temperature zones, introducing the possibility of real-time quantitative PCR. In the present paper, we investigate many of the factors affecting droplet-based PCR chip design, including thermal mass, flow rate, and thermal resistance. The study focuses particularly on the fluid and substrate temperature distribution within the PCR chip and the droplet residence times in critical temperature zones. The simulations demonstrate that the flow rate strongly affects the temperature field within the carrier-fluid. Above a critical flow rate, the carrier-fluid fails to achieve the required temperatures for DNA amplification. In addition, the thermal resistances of the different layers in the chip are shown to have a major impact on the temperature profile in the channel
PCR-RFLP analysis of <i>NPY</i> exon 2 (+1128; T/C), <i>NPY</i> promoter (-399; T/C) and <i>IL1B</i> promoter (-511; C/T) polymorphisms.
No full text(A) PCR-RFLP analysis of NPY exon 2 (+1128; T/C) polymorphism on 2.0% agarose gel: lanes: 1 and 5 show homozygous (TT) genotypes; lane: 2 and 6 show heterozygous (TC) genotypes; lane: 3 shows homozygous (CC) genotype; lane: 4 shows 100 bp DNA ladder. (B) PCR-RFLP analysis of NPY promoter (-399; T/C) polymorphism on 3.5% polyacrylamide gel: lanes: 1, 3 and 4 show heterozygous (TC) genotypes; lanes: 2, 5 and 6 show homozygous (TT) genotypes; lane: 3 shows homozygous (TT) genotype; lane: 7 shows 100 bp DNA ladder. (C) PCR-RFLP analysis of IL1B promoter (-511; C/T) polymorphism on 2.0% agarose gel: lanes: 1 and 6 show homozygous (CC) genotypes; lanes: 2, 3 and 5 show heterozygous (CT) genotypes; lane: 4 shows homozygous (TT) genotype.</p
Gel picture showing multiplex PCR amplification of virulence genes; lane 3: <i>inlA</i> (256pb), lane 4: <i>inlB</i> (272bp), lane 5: <i>inlC</i> (517bp), lane 6: <i>inlJ</i> (238bp), lane 7: <i>actA</i> (650bp), lane 8: <i>hylA</i> (404bp), lane 9: <i>plcA</i> (326bp), lane 10: <i>plcB</i> (289bp), lane 11: <i>iap</i> (131bp), lane 1 and 12 represents 100bp DNA ladder and lane 2 represents negative control.
No full textGel picture showing multiplex PCR amplification of virulence genes; lane 3: inlA (256pb), lane 4: inlB (272bp), lane 5: inlC (517bp), lane 6: inlJ (238bp), lane 7: actA (650bp), lane 8: hylA (404bp), lane 9: plcA (326bp), lane 10: plcB (289bp), lane 11: iap (131bp), lane 1 and 12 represents 100bp DNA ladder and lane 2 represents negative control.</p
PCR-RFLP results of MTHFR C677T polymorphisms.
No full textLane 1 is DNA marker. Lane 4, 10 and 15 are wild type genotype (CC). Lane 1, 3, 6, 9, 13, and 17 are heterozygous mutant genotype (CT). Lane 2, 5, 7, 8, 11, 12, 14 and 16 are homozygous mutant genotype (TT).</p
The complete gel image with all different size of bands of ladder; Lane M: DNA ladder with 100 bp, Lane1: ACE genotype (II) with PCR products 490 bp, Lane 2: ACE genotype (ID) with PCR products 490&190 bp, Lane 3: ACE genotype (DD) with PCR products 190 bp.
No full text<p>The complete gel image with all different size of bands of ladder; Lane M: DNA ladder with 100 bp, Lane1: ACE genotype (II) with PCR products 490 bp, Lane 2: ACE genotype (ID) with PCR products 490&190 bp, Lane 3: ACE genotype (DD) with PCR products 190 bp.</p
PCR-RFLP confirmation of the presence of serotype-specific chromosomes in three AD hybrid strains
No full textAgarose gels are shown in which lane 1 for each contains size markers (1 kilobase [kb] ladder); lanes 2, 4, 6, 8, and 10 contain undigested PCR fragments; and the remaining lanes contain the same fragments after restriction enzyme digestion. Digestion of PCR fragments (primers CNA01230 F/R) from chromosome (chr) 1 with I (left panel) or I (right panel). Digestion of PCR fragments (primers CNE04380 F/R) from chromosome 5 with I (left panel) or III (right panel). Digestion of a PCR fragment (primers CNB01970 F/R) from chromosome 2 with I (left panel) and a fragment (primers acidphos F/R) from chromosome 3 with I (right panel).<p><b>Copyright information:</b></p><p>Taken from "Comparative hybridization reveals extensive genome variation in the AIDS-associated pathogen "</p><p>http://genomebiology.com/2008/9/2/R41</p><p>Genome Biology 2008;9(2):R41-R41.</p><p>Published online 22 Feb 2008</p><p>PMCID:PMC2374700.</p><p></p
Multi-task learning and transfer: The effect of algorithm representation
No full textExploring multiple classes of learning algorithms for those algorithms which perform best in multiple tasks is a complex problem of multiple-criteria optimisation. We use a genetic algorithm to locate sets of models which are not outperformed on all of the tasks. The genetic algorithm develops a population of multiple types of learning algorithms, with competition between individuals of different types. We find that inherent differences in the convergence time and performance levels of the different algorithms leads to misleading population effects. We explore the role that the algorithm representation and initial population has on task performance. Our findings suggest that separating the representation of different algorithms is beneficial in enhancing performance. Also, initial seeding is required to avoid premature convergence to non-optimal classes of algorithms
PCR-RFLP typing of the <i>p1</i> gene.
No full textM. pneumoniae isolates from 419 patients in this study were classified into eight p1 gene types by PCR-RFLP analysis. The RFLP patterns of the RepMP4 region (lanes 1 to 8) and the RepMP2/3 region (lanes 9 to 16) that represent eight p1 gene types are shown. p1 gene types corresponding to RFLP patterns are indicated below the gel image. NT indicates non-typable strain M241 (see text). Lane M contains size markers (200 bp ladder). Type 2b is also referred as type 2V in other reports [26,49]. The original electrophoresis image is shown in S3 Fig).</p
PCR identification of recombinant plasmids.
No full textLane M: DNA marker. Lane 1: PCR product of pcDNA3.1-TsCRT+TsSP1.1. Lane 2: PCR product of pcDNA3.1-TsCRT. Lane 3: PCR product of pcDNA3.1-TsSP1.1. Lane 4: PCR product of pcDNA3.1 using TsCRT+TsSP1.1 primers. Lane 5: PCR product of pcDNA3.1 with TsCRT primers. Lane 6: PCR product of pcDNA3.1 with TsSP1.1 primers.</p
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