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Background and Aims: It is not clear how a polygenic risk score (PRS) can be best combined with guideline-recommended tools for cardiovascular disease (CVD) risk prediction, e.g. SCORE2., Methods: A PRS for coronary artery disease (CAD) was calculated in participants of UK Biobank (n = 432 981). Within each tenth of the PRS distribution, the odds ratios (ORs)-referred to as PRS-factor-for CVD (i.e. CAD or stroke) were compared between the entire population and subgroups representing the spectrum of clinical risk. Replication was performed in the combined Framingham/Atherosclerosis Risk in Communities (ARIC) populations (n = 10 757). The clinical suitability of a multiplicative model 'SCORE2 × PRS-factor' was tested by risk reclassification., Results: In subgroups with highly different clinical risks, CVD ORs were stable within each PRS tenth. SCORE2 and PRS showed no significant interactive effects on CVD risk, which qualified them as multiplicative factors: SCORE2 × PRS-factor = total risk. In UK Biobank, the multiplicative model moved 9.55% of the intermediate (n = 145 337) to high-risk group increasing the individuals in this category by 56.6%. Incident CVD occurred in 8.08% of individuals reclassified by the PRS-factor from intermediate to high risk, which was about two-fold of those remained at intermediate risk (4.08%). Likewise, the PRS-factor shifted 8.29% of individuals from moderate to high risk in Framingham/ARIC., Conclusions: This study demonstrates that absolute CVD risk, determined by a clinical risk score, and relative genetic risk, determined by a PRS, provide independent information. The two components may form a simple multiplicative model improving precision of guideline-recommended tools in predicting incident CVD., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Importance: Yarrowia lipolytica , also known as Candida lipolytica , is an emerging opportunistic "rare pathogenic yeast". Due to the limited data on its antifungal susceptibility, the clinical treatments become challenging. Based on the China Hospital Invasive Fungal Surveillance Network (2009-2022), we conducted a comprehensive multi-method study on clinical isolates from various central hospitals. This study is currently the largest study carried out to assess the antifungal susceptibility of Y. lipolytica . It is also the first to establish local epidemiological cut-off values (L-ECOFFs), identify its ERG11 mutations, and assess the consistency between the three prevalent commercial antifungal susceptibility testing methods and the broth microdilution method. We recommend the Sensititre YeastOne as the best option for antifungal susceptibility testing for Y. lipolytica , followed by the ATB FUNGUS 3. Nevertheless, practitioners should use the MIC test strip with discretion., Competing Interests: The authors declare no conflict of interest.

Background: The joint contribution of genetic and environmental exposures to noncommunicable diseases is not well characterized., Objectives: We modeled the cumulative effects of common risk alleles and their prevalence variations with classical risk factors., Methods: We analyzed mathematically and statistically numbers and effect sizes of established risk alleles for coronary artery disease (CAD) and other conditions., Results: In UK Biobank, risk alleles counts in the lowest (175.4) and highest decile (205.7) of the distribution differed by only 16.9%, which nevertheless increased CAD prevalence 3.4-fold (p < 0.01). Irrespective of the affected gene, a single risk allele multiplied the effects of all others carried by a person, resulting in a 2.9-fold stronger effect size in the top versus the bottom decile (p < 0.01) and an exponential increase in risk (R > 0.94). Classical risk factors shifted effect sizes to the steep upslope of the logarithmic function linking risk allele numbers with CAD prevalence. Similar phenomena were observed in the Estonian Biobank and for risk alleles affecting diabetes mellitus, breast and prostate cancer., Conclusions: Alleles predisposing to common diseases can be carried safely in large numbers, but few additional ones lead to sharp risk increments. Here, we describe exponential functions by which risk alleles combine interchangeably but multiplicatively with each other and with modifiable risk factors to affect prevalence. Our data suggest that the biological systems underlying these diseases are modulated by hundreds of genes but become only fragile when a narrow window of total risk, irrespective of its genetic or environmental origins, has been passed., (© 2022. The Author(s).)

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD., (© 2022. The Author(s).)

The majority of risk loci identified by genome-wide association studies (GWAS) are in non-coding regions, hampering their functional interpretation. Instead, transcriptome-wide association studies (TWAS) identify gene-trait associations, which can be used to prioritize candidate genes in disease-relevant tissue(s). Here, we aimed to systematically identify susceptibility genes for coronary artery disease (CAD) by TWAS. We trained prediction models of nine CAD-relevant tissues using EpiXcan based on two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these prediction models, we imputed gene expression of respective tissues from individual-level genotype data on 37,997 CAD cases and 42,854 controls for the subsequent gene-trait association analysis. Transcriptome-wide significant association (i.e. P < 3.85e-6) was observed for 114 genes. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel. Stepwise analyses were performed to study their plausibility, biological function, and pathogenicity in CAD, including analyses for colocalization, damaging mutations, pathway enrichment, phenome-wide associations with human data and expression-traits correlations using mouse data. Finally, CRISPR/Cas9-based gene knockdown of two newly identified TWAS genes, RGS19 and KPTN, in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Our CAD TWAS work (i) prioritized candidate causal genes at known GWAS loci, (ii) identified 18 novel genes to be associated with CAD, and iii) suggested potential tissues and pathways of action for these TWAS CAD genes., (© 2022. The Author(s).)

Coronary atherosclerosis results from the delicate interplay of genetic and exogenous risk factors, principally taking place in metabolic organs and the arterial wall. Here we show that 224 gene-regulatory coexpression networks (GRNs) identified by integrating genetic and clinical data from patients with ( n = 600) and without ( n = 250) coronary artery disease (CAD) with RNA-seq data from seven disease-relevant tissues in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study largely capture this delicate interplay, explaining >54% of CAD heritability. Within 89 cross-tissue GRNs associated with clinical severity of CAD, 374 endocrine factors facilitated inter-organ interactions, primarily along an axis from adipose tissue to the liver ( n = 152). This axis was independently replicated in genetically diverse mouse strains and by injection of recombinant forms of adipose endocrine factors (EPDR1, FCN2, FSTL3 and LBP) that markedly altered blood lipid and glucose levels in mice. Altogether, the STARNET database and the associated GRN browser (http://starnet.mssm.edu) provide a multiorgan framework for exploration of the molecular interplay between cardiometabolic disorders and CAD., Competing Interests: Competing interests J.L.M.B. is the founder of Clinical Gene Networks (CGN). J.L.M.B. (chair) and A.R. are on CGN’s board of directors. J.L.M.B., A.R. and T.M. are shareholders in CGN. J.L.M.B. receives financial compensation as a consultant for CGN. CGN has an invested interest in STARNET that is regulated in an agreement with the Icahn School of Medicine at Mount Sinai. Neither the Icahn School of Medicine at Mount Sinai nor CGN have made claims to results presented in this study. E.E.S. is the CEO of Sema4. C.W. and L.-M.G. are employees of AstraZeneca. No funding for this study was received from Sema4. AstraZeneca supported this study through independent grants to J.L.M.B. at the Karolinska Institutet (ICMC). The remaining authors declare no competing interests.

Background: Epidemiological studies have repeatedly observed a markedly higher risk for coronary artery disease (CAD) in Scotland as compared to England. Up to now, it is unclear whether environmental or genetic factors might explain this phenomenon., Methods: Using UK Biobank (UKB) data, we assessed CAD risk, based on the Framingham risk score (FRS) and common genetic variants, to explore the respective contribution to CAD prevalence in Scotland (n = 31,963) and England (n = 317,889). We calculated FRS based on sex, age, body mass index (BMI), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), antihypertensive medication, smoking status, and diabetes. We determined the allele frequency of published genome-wide significant risk CAD alleles and a weighted genetic risk score (wGRS) for quantifying genetic CAD risk., Results: Prevalence of CAD was 16% higher in Scotland as compared to England (8.98% vs. 7.68%, P < 0.001). However, the FRS only predicted a marginally higher CAD risk (less than 1%) in Scotland (12.5 ± 10.5 vs.12.6 ± 10.6, P = 0.03). Likewise, the overall number of genome-wide significant variants affecting CAD risk (157.6 ± 7.7 and 157.5 ± 7.7; P = 0.12) and a wGRS for CAD (2.49 ± 0.25 in both populations, P = 0.14) were remarkably similar in the English and Scottish population. Interestingly, we observed substantial differences in the allele frequencies of individual risk variants. Of the previously described 163 genome-wide significant variants studied here, 35 variants had higher frequencies in Scotland, whereas 37 had higher frequencies in England (P < 0.001 each)., Conclusions: Neither the traditional risk factors included in the FRS nor a genetic risk score (GRS) based on established common risk alleles explained the higher CAD prevalence in Scotland. However, we observed marked differences in the distribution of individual risk alleles, which emphasizes that even geographically and ethnically closely related populations may display relevant differences in the genetic architecture of a common disease., (© 2021. The Author(s).)

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Non-coding RNAs have already been linked to CVD development and progression. While microRNAs (miRs) have been well studied in blood samples, there is little data on tissue-specific miRs in cardiovascular relevant tissues and their relation to cardiovascular risk factors. Tissue-specific miRs derived from Arteria mammaria interna (IMA) from 192 coronary artery disease (CAD) patients undergoing coronary artery bypass grafting (CABG) were analyzed. The aims of the study were 1) to establish a reference atlas which can be utilized for identification of novel diagnostic biomarkers and potential therapeutic targets, and 2) to relate these miRs to cardiovascular risk factors. Overall, 393 individual miRs showed sufficient expression levels and passed quality control for further analysis. We identified 17 miRs-miR-10b-3p, miR-10-5p, miR-17-3p, miR-21-5p, miR-151a-5p, miR-181a-5p, miR-185-5p, miR-194-5p, miR-199a-3p, miR-199b-3p, miR-212-3p, miR-363-3p, miR-548d-5p, miR-744-5p, miR-3117-3p, miR-5683 and miR-5701-significantly correlated with cardiovascular risk factors (correlation coefficient >0.2 in both directions, p -value ( p < 0.006, false discovery rate (FDR) <0.05). Of particular interest, miR-5701 was positively correlated with hypertension, hypercholesterolemia, and diabetes. In addition, we found that miR-629-5p and miR-98-5p were significantly correlated with acute myocardial infarction. We provide a first atlas of miR profiles in IMA samples from CAD patients. In perspective, these miRs might play an important role in improved risk assessment, mechanistic disease understanding and local therapy of CAD.

Aims: Inflammation plays an important role in cardiovascular disease (CVD) development. The NOD-like receptor protein-3 (NLRP3) inflammasome contributes to the development of atherosclerosis in animal models. Components of the NLRP3 inflammasome pathway such as interleukin-1β can therapeutically be targeted. Associations of genetically determined inflammasome-mediated systemic inflammation with CVD and mortality in humans are unknown., Methods and Results: We explored the association of genetic NLRP3 variants with prevalent CVD and cardiovascular mortality in 538 167 subjects on the individual participant level in an explorative gene-centric approach without performing multiple testing. Functional relevance of single-nucleotide polymorphisms on NLRP3 inflammasome activation has been evaluated in monocyte-enriched peripheral blood mononuclear cells (PBMCs). Genetic analyses identified the highly prevalent (minor allele frequency 39.9%) intronic NLRP3 variant rs10754555 to affect NLRP3 gene expression. rs10754555 carriers showed significantly higher C-reactive protein and serum amyloid A plasma levels. Carriers of the G allele showed higher NLRP3 inflammasome activation in isolated human PBMCs. In carriers of the rs10754555 variant, the prevalence of coronary artery disease was significantly higher as compared to non-carriers with a significant interaction between rs10754555 and age. Importantly, rs10754555 carriers had significantly higher risk for cardiovascular mortality during follow-up. Inflammasome inducers (e.g. urate, triglycerides, apolipoprotein C3) modulated the association between rs10754555 and mortality., Conclusion: The NLRP3 intronic variant rs10754555 is associated with increased systemic inflammation, inflammasome activation, prevalent coronary artery disease, and mortality. This study provides evidence for a substantial role of genetically driven systemic inflammation in CVD and highlights the NLRP3 inflammasome as a therapeutic target., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2021. For permissions, please email: journals.permissions@oup.com.)

Background: Coronary artery disease (CAD) is a multifactorial condition with both genetic and exogenous causes. The contribution of tissue-specific functional networks to the development of atherosclerosis remains largely unclear. The aim of this study was to identify and characterize central regulators and networks leading to atherosclerosis., Methods: Based on several hundred genes known to affect atherosclerosis risk in mouse (as demonstrated in knockout models) and human (as shown by genome-wide association studies), liver gene regulatory networks were modeled. The hierarchical order and regulatory directions of genes within the network were based on Bayesian prediction models, as well as experimental studies including chromatin immunoprecipitation DNA-sequencing, chromatin immunoprecipitation mass spectrometry, overexpression, small interfering RNA knockdown in mouse and human liver cells, and knockout mouse experiments. Bioinformatics and correlation analyses were used to clarify associations between central genes and CAD phenotypes in both human and mouse., Results: The transcription factor MAFF (MAF basic leucine zipper transcription factor F) interacted as a key driver of a liver network with 3 human genes at CAD genome-wide association studies loci and 11 atherosclerotic murine genes. Most importantly, expression levels of the low-density lipoprotein receptor (LDLR) gene correlated with MAFF in 600 CAD patients undergoing bypass surgery (STARNET [Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task]) and a hybrid mouse diversity panel involving 105 different inbred mouse strains. Molecular mechanisms of MAFF were tested in noninflammatory conditions and showed positive correlation between MAFF and LDLR in vitro and in vivo. Interestingly, after lipopolysaccharide stimulation (inflammatory conditions), an inverse correlation between MAFF and LDLR in vitro and in vivo was observed. Chromatin immunoprecipitation mass spectrometry revealed that the human CAD genome-wide association studies candidate BACH1 (BTB domain and CNC homolog 1) assists MAFF in the presence of lipopolysaccharide stimulation with respective heterodimers binding at the MAF recognition element of the LDLR promoter to transcriptionally downregulate LDLR expression., Conclusions: The transcription factor MAFF was identified as a novel central regulator of an atherosclerosis/CAD-relevant liver network. MAFF triggered context-specific expression of LDLR and other genes known to affect CAD risk. Our results suggest that MAFF is a missing link between inflammation, lipid and lipoprotein metabolism, and a possible treatment target.

Background: Epidemiological studies have shown inverse association between intelligence and coronary artery disease (CAD) risk, but the underlying mechanisms remain unclear., Methods: Based on 242 SNPs independently associated with intelligence, we calculated the genetic intelligence score (gIQ) for participants from 10 CAD case-control studies (n = 34,083) and UK Biobank (n = 427,306). From UK Biobank, we extracted phenotypes including body mass index (BMI), type 2 diabetes (T2D), smoking, hypertension, HDL cholesterol, LDL cholesterol, measured intelligence score, and education attainment. To estimate the effects of gIQ on CAD and its related risk factors, regression analyses was applied. Next, we studied the mediatory roles of measured intelligence and educational attainment. Lastly, Mendelian randomization was performed to validate the findings., Results: In CAD case-control studies, one standard deviation (SD) increase of gIQ was related to a 5% decrease of CAD risk (odds ratio [OR] of 0.95; 95% confidence interval [CI] 0.93 to 0.98; P = 4.93e-5), which was validated in UK Biobank (OR = 0.97; 95% CI 0.96 to 0.99; P = 6.4e-4). In UK Biobank, we also found significant inverse correlations between gIQ and risk factors of CAD including smoking, BMI, T2D, hypertension, and a positive correlation with HDL cholesterol. The association signals between gIQ and CAD as well as its risk factors got largely attenuated after the adjustment of measured intelligence and educational attainment. The causal role of intelligence in mediating CAD risk was confirmed by Mendelian randomization analyses., Conclusion: Genetic components of intelligence affect measured intelligence and educational attainment, which subsequently affect the prevalence of CAD via a series of unfavorable risk factor profiles.

Hepatocellular carcinoma (HCC) is a heterogeneous disease with various genetic and epigenetic abnormalities. Previous studies of HCC driver genes were primarily based on frequency of mutations and copy number alterations. Here, we performed an integrative analysis of genomic and epigenomic data from 377 HCC patients to identify driver genes that regulate gene expression in HCC. This integrative approach has significant advantages over single-platform analyses for identifying cancer drivers. Using this approach, HCC tissues were divided into four subgroups, based on expression of the transcription factor E2F and the mutation status of TP53. HCC tissues with E2F overexpression and TP53 mutation had the highest cell cycle activity, indicating a synergistic effect of E2F and TP53. We found that overexpression of the identified driver genes, stratifin (SFN) and SPP1, correlates with tumor grade and poor survival in HCC and promotes HCC cell proliferation. These findings indicate SFN and SPP1 function as oncogenes in HCC and highlight the important role of enhancers in the regulation of gene expression in HCC.

A missense variant of the sushi, von Willebrand factor type A, EGF and pentraxin domain containing protein 1 (SVEP1) is genome-wide significantly associated with coronary artery disease. The mechanisms how SVEP1 impacts atherosclerosis are not known. We found endothelial cells (EC) and vascular smooth muscle cells to represent the major cellular source of SVEP1 in plaques. Plaques were larger in atherosclerosis-prone Svep1 haploinsufficient (ApoE -/- Svep1 +/- ) compared to Svep1 wild-type mice (ApoE -/- Svep1 +/+ ) and ApoE -/- Svep1 +/- mice displayed elevated plaque neutrophil, Ly6C high monocyte, and macrophage numbers. We assessed how leukocytes accumulated more inside plaques in ApoE -/- Svep1 +/- mice and found enhanced leukocyte recruitment from blood into plaques. In vitro, we examined how SVEP1 deficiency promotes leukocyte recruitment and found elevated expression of the leukocyte attractant chemokine (C-X-C motif) ligand 1 (CXCL1) in EC after incubation with missense compared to wild-type SVEP1. Increasing wild-type SVEP1 levels silenced endothelial CXCL1 release. In line, plasma Cxcl1 levels were elevated in ApoE -/- Svep1 +/- mice. Our studies reveal an atheroprotective role of SVEP1. Deficiency of wild-type Svep1 increased endothelial CXCL1 expression leading to enhanced recruitment of proinflammatory leukocytes from blood to plaque. Consequently, elevated vascular inflammation resulted in enhanced plaque progression in Svep1 deficiency.

The estrogen receptor (ER)-negative breast cancer subtype is aggressive with few treatment options available. To identify specific prognostic factors for ER-negative breast cancer, this study included 705,729 and 1034 breast invasive cancer patients from the Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases, respectively. To identify key differential kinase-substrate node and edge biomarkers between ER-negative and ER-positive breast cancer patients, we adopted a network-based method using correlation coefficients between molecular pairs in the kinase regulatory network. Integrated analysis of the clinical and molecular data revealed the significant prognostic power of kinase-substrate node and edge features for both subtypes of breast cancer. Two promising kinase-substrate edge features, CSNK1A1-NFATC3 and SRC-OCLN, were identified for more accurate prognostic prediction in ER-negative breast cancer patients., (Copyright © 2020. Published by Elsevier B.V.)

HCV p7 protein is a cation-selective ion channel, playing an essential role during the life cycle of HCV viruses. To understand the cation-selective mechanism, we constructed a hexameric model in lipid bilayers of HCV p7 protein for HCB JFH-1 strain, genotype 2a. In this structural model, His9 and Val6 were key factors for the HCV cation-selective ion channel. The histidine residues at position 9 in the hexameric model formed a first gate for HCV p7 channel, acting as a selectivity filter for cations. The valines mentioned above formed a second gate for HCV p7 channel, serving as a hydrophobic filter for the dehydrated cations. The binding pocket for the channel blockers, e.g., amantadine and rimantadine, was composed of residues 20-26 in H2 helix and 52-60 in H3 helix in i + 2 monomer. However, the molecular volumes for both amantadine and rimantadine were too small for the binding pocket of HCV p7 channel. Thus, designing a compound similar with rimantadine and having much larger volume would be an effective strategy for discovering inhibitors against HCV p7 channel. To achieve this point, we used rimantadine as a structural template to search ChEMBL database for the candidates employing favorable binding affinities to HCV p7 channel. As a result, six candidates were identified to have potential to be novel inhibitors against HCV p7 channel.

Although numerous studies on kidney renal clear cell carcinoma (KIRC) were carried out, the dynamic process of tumor formation was not clear yet. Inadequate attention was paid on the evolutionary paths among somatic mutations and their clinical implications. As the tumor initiation and evolution of KIRC were primarily associated with SNVs, we reconstructed an evolutionary process of KIRC using cross-sectional SNVs in different pathological stages. KIRC driver genes appeared early in the evolutionary tree, and the genes with moderate mutation frequency showed a pattern of stage-by-stage expansion. Although the individual gene mutations were not necessarily associated with survival outcome, the evolutionary paths such as VHL-PBRM1 and FMN2-PCLO could indicate stage-specific prognosis. Our results suggested that, besides mutation frequency, the evolutionary relationship among the mutated genes could facilitate to identify novel drivers and biomarkers for clinical utility.

Recent cancer researches pay more attention to younger patients due to the variable treatment response among different age groups. Here we investigated the effectiveness of neoadjuvant radiation on the survival of younger and older patients in stage II/III rectal cancer. Data was obtained from Surveillance, Epidemiology, and End Results (SEER) database (n = 12801). Propensity score matching was used to balance baseline covariates according to the status of neoadjuvant radiation. Our results showed that neoadjuvant radiation had better survival benefit (Log-rank P = 3.25e-06) and improved cancer-specific 3-year (87.6%; 95% CI: 86.4-88.7% vs. 84.1%; 95% CI: 82.8-85.3%) and 5-year survival rates (78.1%; 95% CI: 76.2-80.1% vs. 77%; 95% CI: 75.3-78.8%). In older groups (>50), neoadjuvant radiation was associated with survival benefits in stage II (HR: 0.741; 95% CI: 0.599-0.916; P = 5.80e-3) and stage III (HR: 0.656; 95% CI 0.564-0.764; P = 5.26e-08). Interestingly, neoadjuvant radiation did not increase survival rate in younger patients (< = 50) both in stage II (HR: 2.014; 95% CI: 0.9032-4.490; P = 0.087) and stage III (HR: 1.168; 95% CI: 0.829-1.646; P = 0.372). Additionally, neoadjuvant radiation significantly decreased the cancer-specific mortality in older patients, but increased mortality in younger patients. Our results provided new insights on the neoadjuvant radiation in rectal cancer, especially for the younger patients.

Luminescent quantum dots (QDs) with unique optical properties have potential applications in bio-imaging. The interaction between QDs and bio-molecules is important to the biological effect of QDs in vivo. In this paper, we have employed fluorescence correlation spectroscopy (FCS) to probe the temperature- and pH-dependent interactions between CdSe QDs with carboxyl (QDs-COOH) and bovine serum albumin (BSA) in buffer solutions. The results have shown that microscopic dissociation constant K' D is in the range of (1.5 ± 0.2) × 10 -5 to (8.6 ± 0.1) × 10 -7 M, the Hill coefficient n is from 0.4 to 2.3, and the protein corona thickness is from 3.0 to 9.4 nm. Variable-temperature measurements have shown both negative values of ∆ H and ∆ S for BSA adsorption on QDs-COOH, while pH has a profound effect on the adsorption. Additional, FCS measurement QDs-COOH and proteins in whole mice serum and plasma samples has also been conducted. Finally, simulation results have shown four favored QD binding sites in BSA.

Many cell activities are organized as a network, and genes are clustered into co-expressed groups if they have the same or closely related biological function or they are co-regulated. In this study, based on an assumption that a strong candidate disease gene is more likely close to gene groups in which all members coordinately differentially express than individual genes with differential expression, we developed a novel disease gene prioritization method GroupRank by integrating gene co-expression and differential expression information generated from microarray data as well as PPI network. A candidate gene is ranked high using GroupRank if it is differentially expressed in disease and control or is close to differentially co-expressed groups in PPI network. We tested our method on data sets of lung, kidney, leukemia and breast cancer. The results revealed GroupRank could efficiently prioritize disease genes with significantly improved AUC value in comparison to the previous method with no consideration of co-expressed gene groups in PPI network. Moreover, the functional analyses of the major contributing gene group in gene prioritization of kidney cancer verified that our algorithm GroupRank not only ranks disease genes efficiently but also could help us identify and understand possible mechanisms in important physiological and pathological processes of disease.