Proteins commonly identified in all conditions.

<p>Protein and gene names, molecular weight in daltons, cellular localization, function/structure, Uniprot accession number, protein identification probability from iProphet and unique number of identified peptides for each individual protein are shown.</p

Uniquely identified proteins in anti-CD4 co-immunoprecipitations in induced CD4 internalization and degradation in Mφ (Condition 2).

<p>Protein and gene names, molecular weight in Daltons, cellular localization, function/structure, Uniprot accession number, protein identification probability from iProphet and unique number of identified peptides for each individual protein are shown.</p

Gene Ontology (GO) annotations of the uniquely identified proteins in anti-CD4 immunoprecipitations in Mφ.

<p>Protein identifications from the three different conditions were exported from the in-house developed Central Proteomics Facilities data analysis pipeline (CPFP) and uploaded to ProteinCenter software. <b>A</b> illustrates the percentage of protein identifications versus protein cellular localizations (GO cellular annotations); <b>B</b> illustrates the percentage of protein identifications versus protein molecular functions (GO molecular annotations) and <b>C</b> illustrates the percentage of protein identifications versus protein biological functions (GO biological annotations). Blue bars represent the percentage of unique proteins identified in condition 1 (Resting macrophages); Red bars represent the percentage of unique proteins identified in condition 2 (Induced CD4 internalization and degradation); Green bars represent the percentage of unique proteins identified in condition 3 (Induced CD4 internalization and blocked degradation).</p

CD4 is internalized and degraded after treatment with conditioned media from activated T cells.

<p>Mφ were treated with conditioned media from activated T cells for 18 hours or left untreated, followed by flow cytometry staining with directly conjugated mAb to CD4. <b>A</b> Black histogram represents the appropriate isotype control. Histograms show the intensity of the signal on the X-axis with a log₁₀-scale and the percentage of maximum expression on the Y-axis. Representative staining of more than five donors tested (n>5). <b>B</b> Bars represent the mean percentage of Mφ expressing surface CD4 with SD error bars from ten independent donors (n = 10). <b>C</b> Total CD4 expression levels (surface + intracellular) were determined by dividing the geometrical MFI of the antibody staining over the MFI of the isotype control. Bars represent the mean values of five independent donors (n = 5) with SD error bars. In <b>B</b> and <b>C</b>, black bar corresponds to untreated Mφ and white bar corresponds to conditioned media treated Mφ (T cell Sup).</p

Western blot analysis of CD4 co-immunoprecipitates in Mφ.

<p>A total of 1×10⁷ Mφ were left untreated (Condition 1, blue), treated for 18 hours with supernatants from activated T cells (Condition 2, red), treated for 18 hours with supernatants from activated T cells in the presence of 5 µM MG132 and 100 nM BafA1 (Condition 3, green), lysed and anti-CD4 immunoprecipitation reactions were carried out. Isotype control immunoprecipitations were also performed to show background protein binding. Immunoisolates were resuspended in Laemmli sample buffer under reducing and denaturing conditions and resolved on a SDS-PAGE gel. Membranes were incubated with antibodies against CD4, clathrin heavy chain (HC) 1, E3 Ubiquitin (Ub) ligase Itch, CD9 and CCR5. Primary antibodies were detected and scanned using the quantitative western blotting imaging Odyssey System. A representative blot of three different blood donors is shown (n = 3).</p

Uniquely identified proteins in anti-CD4 co-immunoprecipitations in induced CD4 internalization and blocked degradation in Mφ (Condition 3).

<p>Protein and gene names, molecular weight in Daltons, cellular localization, function/structure, Uniprot accession number, protein identification probability from iProphet and unique number of identified peptides for each individual protein are shown.</p

Calculation of the number of novel proteins that can be produced by ambiguous decoding of high CAI mRNAs

<p><b>Copyright information:</b></p><p>Taken from "A genetic code alteration generates a proteome of high diversity in the human pathogen "</p><p>http://genomebiology.com/2007/8/10/R206</p><p>Genome Biology 2007;8(10):R206-R206.</p><p>Published online 4 Oct 2007</p><p>PMCID:PMC2246281.</p><p></p> Number of novel proteins synthesized by ambiguous CUG decoding of genes with high codon adaptation index (CAI) value in the different physiologic conditions indicated. The gene, which contains three CUG codons, was used as an example of a gene with a high CAI value (CAI= 0.694) for . This set of genes produces approximately 50,000 protein molecules in yeasts [24]. Table showing the number of different protein molecules that arise from ambiguous CUG decoding of , following the methodology described in the Materials and methods section. In this case, for 2.9% of CUG ambiguity, of the 50,000 Cdc3p molecules synthesized, 45,691 are wild type whereas 4,306 are novel molecules (8.6%), containing a combination of 1, 2, or 3 leucines at the three CUG positions. The data show that proteins are quasi-species [43] and that its proteome has a statistical nature

Calculation of the number of novel proteins that can be produced by ambiguous decoding of low CAI mRNAs

<p><b>Copyright information:</b></p><p>Taken from "A genetic code alteration generates a proteome of high diversity in the human pathogen "</p><p>http://genomebiology.com/2007/8/10/R206</p><p>Genome Biology 2007;8(10):R206-R206.</p><p>Published online 4 Oct 2007</p><p>PMCID:PMC2246281.</p><p></p> Novel proteins arising from ambiguous decoding of mRNAs encoded by genes with low codon adaptation index (CAI) value in the different physiologic conditions indicated. The gene, containing three CUG codons, was used as an example of a gene with a low CAI, because its CAI value falls within the range of values exhibited by the 10% of genes with lowest CAI value in (CAI= 0.448). This set of genes produce approximately 5,000 protein molecules in yeast [24]. Total number of different proteins that can be generated from ambiguous CUG decoding. The probability of different proteins that arise from genes containing CUGs, caused by serine or leucine insertion at CUG positions, was calculated as described in the Materials and methods section. In this case, of the 5,000 Ra17p molecules synthesized, 4,569 are wild-type and 429 are novel molecules (8.6%). The data unequivocally show that proteins are quasi-species [43] and that its proteome has a statistical nature

FIRST IMPRESSIONS FROM FACES: IDEAL PARTNER PREFERENCES DOMINATED BY ATTRACTIVENESS-RELATED CONCERNS

When people first encounter a potential partner, they derive a wealth of objective and subjective impressions simply from their faces (e.g., age, gender, attractiveness, trustworthiness). Facial first impressions are consequential, for instance, impacting on decisions to approach a potential partner. Hence, it is relevant to have a solid theoretical understanding of how first impressions relate to ideal partner preferences, particularly as romantic relationship researchers primarily use verbal measures. The current research revealed that individuals can perceive traits and factors related to their ideal partner preferences in highly variable everyday face images, and these factors overlapped largely (although not completely) with those identified by face perception researchers. Partner preferences for face images were dominated by attractiveness-related concerns in both sexes. Further, a minimum-exposure paradigm revealed that, even in some non-romantic contexts, attractiveness is particularly salient in face images. Yet, these findings could not be attributed to an attractiveness halo effect, given that attractiveness did not dominate all non-romantic first impressions of face images (e.g., evaluations of faces in terms of occupations). There are multiple potential reasons why individuals might prioritise facial attractiveness (e.g., from an evolutionary perspective, attractiveness is a cue to fertility and resistance to environmental and genetic stressors). Of note, though, a verbal measure of partner preferences revealed that individuals prioritised warmth-trustworthiness, suggesting that face images and verbal measures may capture different elements of preferences. Therefore, these findings attest the relevance of using face images to complement verbal measures of partner preferences

Summary of N-terminal modifications.

<p>A: detected in influenza A virus.</p><p>B: detected in influenza B virus.</p