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Graphical abstract, Rotavirus disease is a leading global cause of mortality and morbidity in children under 5 years of age. The effectiveness of the two globally used oral rotavirus vaccines quickly became apparent when introduced into both developed and developing countries, with significant reductions in rotavirus-associated mortality and hospitalizations. However, the effectiveness and impact of the vaccines is reduced in developing country settings, where the burden and mortality is highest. New rotavirus vaccines, including live oral rotavirus candidates and non-replicating approaches continue to be developed, with the major aim to improve the global supply of rotavirus vaccines and for local implementation, and to improve vaccine effectiveness in developing settings. This review provides an overview of the new rotavirus vaccines in development by developing country manufacturers and provides a rationale why newer candidates continue to be explored. It describes the new live oral rotavirus vaccine candidates as well as the non-replicating rotavirus vaccines that are furthest along in development.

We determined baseline oral and cervicogenital human papillomavirus (HPV) prevalence and determinants of infection in the Michigan HPV and Oropharyngeal Cancer (MHOC) study. We enrolled 394 college-age and older participants of both sexes in Ann Arbor, Michigan and the surrounding area. All participants provided an oral sample at baseline, and 130 females provided a cervicogenital sample. Samples were tested for 18 HPV genotypes using polymerase chain reaction (PCR) MassArray. Participants filled out sociodemographic and behavioral questionnaires. Prevalence ratios for HPV oral or cervicogenital prevalence by predictor variables were estimated in univariable log-binomial models. Analysis was conducted 2018–20. In the full cohort, baseline oral HPV prevalence was 10.0% for any detected genotype (among the 338 valid oral tests at baseline) and 6.5% for high-risk types, and cervicogenital prevalence was 20.0% and 10.8%, respectively (among the 130 first valid cervicogenital tests). Oral HPV prevalence did not vary by sex, with 10.5% of women and 9.0% of men having an infection. We found a high prevalence of oral and cervicogenital HPV infection in college-age participants reporting no lifetime sexual partners. Reporting a single recent partner was associated with a lower oral HPV prevalence (PR 0.39, 95% CI: 0.16, 0.96) than reporting no recent (but at least one ever) partner. No similar protective effect was seen for cervicogenital HPV. Both oral and cervicogenital prevalence increased with the number of recent partners for most sexual behaviors. We observed an ecological fallacy masking the direction of impact of vaccination on HPV prevalence in the full cohort compared to the college-aged and the age 23+ populations considered separately. Substance use was not significantly associated with oral or cervicogenital HPV infection. Many studies report substantially higher oral HPV infection prevalence in men than in women. That difference may not be uniform across populations in the US.

Relational reasoning is a cornerstone of human cognition. Extensive work, drawing on the Relational Match to Sample paradigm (RMTS), has established that humans, at least above the age of five, are much more proficient relational reasoners than younger children or non-human animals. While sometimes differences between populations derive from differences in capacity (the capacity to create representations in a certain format or of a certain complexity, information processing capacity), other times such differences derive from different learning histories alone. Here we distinguish between two types of learning history explanations on the example of four-year-olds' failure on Premack's (1983) RMTS task: (1) that children four-year-olds have not yet created representations of the relations same and different with the properties need to support success on RMTS and (2) that four-year-olds have different inductive biases than do adults. Experiment 1 established that four-year-olds are at chance on the RMTS task we deploy as a transfer task in Experiment 2. Experiments 2A-C each provide children with a mere 8 trials of training on of one three MTS tasks (Number, Size and Identity MTS, respectively), none of which involves making matches of same to same or different to different. The very brief training (eight trials) on two of these tasks (Number MTS, Size MTS) leads to spontaneous success on RMTS in four-year-olds. Identity MTS has no effect on subsequent performance on RMTS. Given the brevity and non-relational nature of the training the successes after Number and Size MTS training must have resulted from changing inductive biases alone. Furthermore, the same two training tasks increased relational responding by adults on a related task (KroupinCarey, in press), whereas Identity MTS training did not, suggesting that the mechanisms through which the training changed inductive biases are at least partially continuous between ages four and adulthood.

Metastases and tumor recurrence have a major prognostic impact in head and neck squamous cell carcinoma (HNSCC); however, cellular models that comprehensively characterize metastatic and recurrent HNSCC are lacking. To this end, we obtained genomic, transcriptomic, and copy number profiles of the UM-SCC cell line panel, encompassing patient-matched metastatic and recurrent cells. UM-SCC cells recapitulate the most prevalent genomic alterations described in HNSCC, featuring common TP53, PI3K, NOTCH, and Hippo pathway mutations. This analysis identified a novel F977Y kinase domain PIK3CA mutation exclusively present in a recurrent cell line (UM-SCC14B), potentially conferring resistance to PI3K inhibitors. Small proline-rich protein 2A (SPRR2A), a protein involved in epithelial homeostasis and invasion, was one of the most consistently downregulated transcripts in metastatic and recurrent UM-SCC cells. Assessment of SPRR2A protein expression in a clinical cohort of patients with HNSCC confirmed common SPRR2A downregulation in primary tumors (61.9% of cases) and lymph node metastases (31.3%), but not in normal tissue. High expression of SPRR2A in lymph node metastases was, along with nonoropharyngeal location of the primary tumor, an independent prognostic factor for regional disease recurrence after surgery and radiotherapy (HR 2.81; 95% CI, 1.16–6.79; P = 0.02). These results suggest that SPRR2A plays a dual role in invasion and therapeutic resistance in HNSCC, respectively through its downregulation and overexpression. Implications: The current study reveals translationally relevant mechanisms underlying metastasis and recurrence in HNSCC and represents an adjuvant tool for preclinical research in this disease setting. Underlining its discovery potential this approach identified a PIK3CA-resistant mutation as well as SPRR2A as possible theragnostic markers.

Two proposed containers (50 kg-polypropylene sack and 50 kg-wooden crate) were compared with existing packaging containers (100 kg-polypropylene and jute sacks) to transport sweetpotato storage roots from major aggregation sites to distant urban market centers. The extent of breaks, bruises and the impacts, incurred by storage roots packaged in the different containers, were assessed. Additionally, at the urban market centers, the visual quality of the transported storage roots was evaluated by both aggregators and consumers. The benefit cost ratio (BCR) for each of packaging options was calculated to ascertain their profitability for sweetpotato roots transportation. The existing polypropylene/jute sacks resulted in significant major breakages in both years (p = 0.028, 0.016) after transportation for the Afram Plains-Accra route in truck. The donkey-driven carts or tricycles used for the Bawku-Bitou route did not show any significant (p > 0.05) influence on the storage roots contained in the existing polypropylene/jute sacks. The average impact recorded at both loading and offloading sites was significantly different (13.4 - 19.3 g vs. 0 - 30.0 g; p = 0.045) for all the containers. The proposed 50 kg-woodencrate had a significantly superior (mean rank of 127; p < 0.0001) visual quality compared with the other packages. All the packaging options showed profitability, because they had a BCR > 1.40, except for the 50 kg-wooden-crate. The 50 kg-polypropylene container delivered better quality roots to urban market centers than the existing packaging containers, and was more profitable than the 50 kg-wooden crates. The 50 kg-polypropylene container is recommended for the transport of sweetpotato storage roots in Ghana.

Objectives We sought to describe the genetic complexity of 14 UM-SCC oral cavity cancer cell lines that have remained uncharacterized despite being used as model systems for decades. Materials and Methods We performed exome sequencing on 14 oral cavity UM-SCC cell lines and denote the mutational profile of each line. We used a SNP array to profile the multiple copy number variations of each cell line and use immunoblotting to compare alterations to protein expression of commonly amplified genes (EGFR, PIK3CA, etc.). RNA sequencing was performed to characterize the expression of genes with copy number alterations. Results The cell lines displayed a highly complex network of genetic aberrations that was consistent with alterations identified in the HNSCC TCGA project including PIK3CA amplification, CDKN2A deletion, as well as TP53 and CASP8 mutations, enabling genetic stratification of each cell line in the panel. Copy number FISH and spectral karyotyping analysis demonstrate that cell lines retain chromosomal heterogeneity. Conclusions Collectively, we developed an important resource for future oral cavity HNSCC cell line studies and highlight the complexity of genomic aberrations in cell lines.

Effective marine habitat protection requires life history information, including identification of connected adult habitats and spawning sites, and movement information throughout those areas. Here, we implemented a mark-recapture study in the Bahamas Archipelago to estimate patterns of site fidelity, and to determine what homesites are connected to pre-spawning sites of economically important Bonefish (Albula vulpes) across multiple islands. We captured over 7000 Bonefish via seine netting, marked them with dart tags, and relied on fishing guides and anglers to report recaptures on Abaco, Grand Bahama, and Andros. Mark-recapture results from the three islands showed that 60–80% of Bonefish were recaptured within 5 km of their tagging site. Across the three islands, mean distance between mark and recapture was less than 11 km, suggesting space use that is tractable for effective marine reserve implementation. We also found that pre-spawning sites housed individuals from multiple homesites that were separated by distances up to 75 km. With these connections in mind, conserving Bonefish spawning biomass necessitates habitat protection in multiple home areas, along migratory corridors, and at pre-spawn and spawning locations. Our case study illustrates how mark-recapture of a C&R species can be used to identify habitats for protection. Information from this mark-recapture study contributed to the designation of six National Parks aimed at protecting habitats used by Bonefish, as well as other spatially overlapping species.

This study estimated the amount of loss in storage roots caused by various levels of damage caused by sweetpotato weevils (Cylas spp). Seven varieties of sweetpotato (Ipomoea batatas L. (Lam)) were evaluated in three production sites in northern Ghana for two years (2014 and 2015). Yield data for each experimental plot were collected. A regression analysis was carried out using the generalized linear model approach. In the study, nonmarketable roots were classified as all undersized roots (

Purpose: The response rates of Head and Neck Squamous Cell Carcinoma (HNSCC) to checkpoint blockade are below 20%. We aim to develop a mechanism-based vaccine to prevent HNSCC immune escape. Experimental Design: We performed RNA-Seq of sensitive and resistant HNSCC cells to discover central pathways promoting resistance to immune killing. Using biochemistry, animal models, HNSCC microarray, and immune cell deconvolution, we assessed the role of SOX2 in inhibiting STING-type I interferon (IFN-I) signaling-mediated antitumor immunity. To bypass SOX2-potentiated STING suppression, we engineered a novel tumor antigen–targeted nanosatellite vehicle to enhance the efficacy of STING agonist and sensitize SOX2-expressing HNSCC to checkpoint blockade. Results: The DNA-sensing defense response is the most suppressed pathway in immune-resistant HNSCC cells. We identified SOX2 as a novel inhibitor of STING. SOX2 facilitates autophagy-dependent degradation of STING and inhibits IFN-I signaling. SOX2 potentiates an immunosuppressive microenvironment and promotes HNSCC growth in vivo in an IFN-I-dependent fashion. Our unique nanosatellite vehicle significantly enhances the efficacy of STING agonist. We show that the E6/E7–targeted nanosatellite vaccine expands the tumor-specific CD8+ T cells by over 12-fold in the tumor microenvironment and reduces tumor burden. A combination of nanosatellite vaccine with anti-PD-L1 significantly expands tumor-specific CTLs and limits the populations expressing markers for exhaustion, resulting in more effective tumor control and improved survival. Conclusions: SOX2 dampens the immunogenicity of HNSCC by targeting the STING pathway for degradation. The nanosatellite vaccine offers a novel and effective approach to enhance the adjuvant potential of STING agonist and break cancer tolerance to immunotherapy. Clin Cancer Res; 24(17); 4242–55. ©2018 AACR.

Salivary duct carcinoma (SDC) constitutes one of the most aggressive cancers in the salivary gland and is associated with a poor prognosis; however, no established systemic therapy options are available. SDC exhibits biological similarity to prostate and breast cancers, therefore anti-hormone therapy and molecular target therapies are available, however with limited beneficial effects. Galanin and galanin receptors (GALRs) are well established as molecular biomarkers to predict the survival rate and risk of recurrence of head and neck squamous cell carcinoma. The present study investigated the clinicopathological features of patients with SDC and the methylation status of their galanin and GALR genes to demonstrate the prognostic value for this disease. The median overall survival (OS) was 37.2 months. T-stage, N-stage, disease stage, tumor size, and preoperative facial paralysis were significantly associated with OS, whereas human epidermal growth factor receptor 2 (HER2) overexpression was not. GALR1 and GALR2 methylation rates in tumor tissues were significantly increased compared with normal tissues with 9.85- and 4.49-fold increase, respectively. p27kip1 and p57kip2 expression significantly inversely correlated with the methylation rate of GALR1 and GALR2. In addition, the observed GALR1 and/or GALR2 methylation rates were significantly correlated with a decrease in OS. These results suggest that GALR1 and GALR2 may serve as potential prognostic factors and therapeutic targets in SDC.

Falls from residential roofs account for 80% of roofing industry fatalities. Furthermore, roofing work represents 44.7% of work in residual construction specialty trades and residential roofers count for 2.1% of overall workers in construction, with an anticipated growth in roofers of 14.9% by 2024. The purpose of the study was to evaluate the alterations in spatiotemporal gait parameters while traversing along a 6/12 pitched residential roof segment. Eighteen of the nineteen calculated spatiotemporal variables were statistically, significantly changed by walking across a 6/12 pitched simulated residential roof. The study clearly demonstrates that spatiotemporal gait variables increase and decrease while traversing across a residential roof. The changes in spatiotemporal parameters might suggest alterations to a person’s balance system resulting in an increased risk of falling. The knowledge generated in the current study will be relevant to the residential roofing industry when it can be used in educational materials to increase awareness of how a roofer’s altered gait while working on a pitched roof may increase their falling risk.

ObjectivesThe Michigan HPV and Oropharyngeal Cancer study aimed to evaluate patterns of oral and cervicogenital human papillomavirus (HPV) infection prevalence, incidence, and clearance as well as their relationship to sexual behaviours.DesignCohortSettingGeneral public in and around Ann Arbor, Michigan.Participants394 college-age and older-adult participants of both sexes provided oral samples, and 325 completed at least 2 visits. 130 who provided a cervicogenital samples, and 127 completed at least 2 visits.OutcomesIncidence and clearance rates as well as HRs for oral and cervicogenital HPV.ResultsOral HPV infections were transient, with only 16% of genotypes persisting to the next visit. The mean time to clearance of a genotype was 46 days (95% CI 37 to 58). In contrast, cervicogenital infections were more persistent, with 56% of genotypes persisting to the next visit. The mean time to clearance of a genotype was 87 days (95% CI 74 to 102). HPV vaccination was associated with reduced incidence of cervicogenital HPV infection (HR 0.63; 95% CI 0.47 to 0.83) but not oral HPV infection. Incidence of oral HPV infection was associated with 2+ recent deep kissing partners (HR 2.00; 95% CI 1.13 to 3.56). Incidence of both oral (HR: 1.70; 95% CI 1.08 to 2.68) and cervicogenital (HR 2.46; 95% CI 1.69 to 3.59) was associated with 2+ recent sexual partners.ConclusionsDetection of oral HPV was highly transient, but incidence was associated with recent deep kissing and sexual partners. Detection of cervicogenital HPV was more persistent, and incidence was positively associated with recent sexual partners and negatively associated with HPV vaccination.

Background Inverted sinonasal (Schneiderian) papilloma (ISP) is a locally aggressive neoplasm often associated with sinonasal squamous cell carcinoma (SNSCC). While the etiology of ISP is not well understood, human papillomavirus (HPV) has been detected in a subset of cases. Our group recently identified activating somatic EGFR mutations in the majority of ISP and ISP-associated SNSCC. However, the relationship between EGFR mutations and HPV infection has not been explored. Patients and methods We evaluated 58 ISP and 22 ISP-associated SNSCC (including 13 patients with matched ISP/SNSCC samples), as well as 14 SNSCC without clinical or pathologic evidence of an associated ISP. Formalin-fixed, paraffin-embedded samples were evaluated for EGFR mutations using Sanger sequencing and for HPV infection using GP5+/GP6+ PCR. HPV subtyping based on the L1 sequence was done for HPV positive cases including temporally distinct tumors for four patients. Clinicopathologic data including progression free survival was also analyzed. Results All ISP and ISP-associated SNSCC demonstrated either an EGFR mutation or HPV infection. HPV and EGFR mutation were mutually exclusive in all cases of ISP-associated SNSCC and all but one ISP; this case was only weakly HPV positive, and analysis of a prior temporally distinct ISP specimen from this patient failed to show HPV infection, suggesting transient infection/incidental colonization. HPV subtypes in ISP and ISP-associated SNSCC were predominantly low-risk, in contrast with SNSCC without ISP association, which showed frequent high-risk HPV. All paired ISP and associated SNSCC samples demonstrated concordant HPV status and EGFR genotypes. ISP progression to SNSCC was significantly associated with the presence of HPV infection and the absence of an EGFR mutation (log-rank = 9.620, P = 0.002). Conclusions Collectively our data show that EGFR mutations and HPV infection represent essential, alternative oncogenic mechanisms in ISP and ISP-associated SNSCC.

Human immunodeficiency virus (HIV)-infected individuals are at increased risk for developing several non-AIDS related malignancies and are often excluded from cancer immunotherapy regimens. To evaluate the immune competence of this cancer patient population, we evaluated HLA class I antigen presenting machinery (APM) component expression and PD-1:PD-L1 pathway upregulation in HIV(+) and HIV(−) head and neck cancers (HNCs). Sixty-two HIV(+) and 44 matched HIV(−) controls diagnosed with HNC between 1991 and 2011 from five tertiary care referral centers in the United States were identified. HLA class I APM component, PD-1, and PD-L1 expression were analyzed by immunohistochemical staining with monoclonal antibodies (mAbs). Clinical data was abstracted from the medical records. There was no significant difference between the cases and controls in LMP2, TAP1, HLA-A and HLA-B/C, as well as PD-1 and PD-L1 expression. Overall, 62% of all subjects had high PD-1 expression and 82% of the subjects expressed PD-L1 within the tumor microenvironment. LMP2, HLA-A and HLA-B/C expression were significantly associated with moderate to high PD-1 expression in the HIV(+) HNC cases (p = .004, p = .026, and p = .006, respectively) but not in the HIV(−) controls. In addition, HLA-A expression was significantly associated with PD-L1 expression in the HIV(+) HNC cases only (p = .029). HIV-infected individuals diagnosed with HNC do not have any detectable defects in HLA class I APM component expression and in PD-1:PD-L1 pathway activation. Given the current successes of HAART therapy in maintaining immune cell counts, HIV(+) patients diagnosed with cancer may benefit from the recently FDA-approved immune checkpoint blockade therapy.

Introduction: Recent genome wide association studies (GWAS) identified a novel susceptibility locus for thrombosis, harbouring the SLC44A2 gene which encodes the Solute Carrier Family 44 Member 2 protein (SLC44A2). Thus far, SLC44A2 has not been studied in the context of thrombosis, and may be a unique contributor to thrombotic disease. Here we utilize mice lacking SLC44A2 (Slc44a2(-/-)) to evaluate a possible role of SLC44A2 in hemostasis.Methods: Slc44a2(-/-) mice were evaluated in key aspects of normal hemostasis including a challenge of vascular damage by applying laser induced injury to the cremaster muscle arteriole.Results: Slc44a2(-/-) mice had comparable levels of thrombin generation and gene expression of coagulation related genes, as compared to littermate wild type controls. Lower levels of circulating plasma Von Willebrand factor (VWF) were measured in Slc44a2(-/-) mice, while no difference in VWF multimerization or vascular localization was detected. Upon in vivo laser injury of the cremaster arterioles, we detected an impairment of clot formation for Slc44a2(-/-) mice.Conclusions: Although mice lacking SLC44A2 are normal for several hemostasis parameters, we do observe a reduction of plasma VWF levels and an altered response upon vascular damage, which suggests that SLC44A2 contributes to hemostasis upon injury. These findings are in line with the reported GWAS data and support further research on SLC44A2 in thrombosis.

We conducted a critical review of human papillomavirus (HPV) integration into the host genome in oral/oropharyngeal cancer, reviewed the literature for HPV-induced cancers, and obtained current data for HPV-related oral and oropharyngeal cancers. In addition, we performed studies to identify HPV integration sites and the relationship of integration to viral-host fusion transcripts and whether integration is required for HPV-associated oncogenesis. Viral integration of HPV into the host genome is not required for the viral life cycle and might not be necessary for cellular transformation, yet HPV integration is frequently reported in cervical and head and neck cancer specimens. Studies of large numbers of early cervical lesions revealed frequent viral integration into gene-poor regions of the host genome with comparatively rare integration into cellular genes, suggesting that integration is a stochastic event and that site of integration may be largely a function of chance. However, more recent studies of head and neck squamous cell carcinomas (HNSCCs) suggest that integration may represent an additional oncogenic mechanism through direct effects on cancer-related gene expression and generation of hybrid viral-host fusion transcripts. In HNSCC cell lines as well as primary tumors, integration into cancer-related genes leading to gene disruption has been reported. The studies have shown that integration-induced altered gene expression may be associated with tumor recurrence. Evidence from several studies indicates that viral integration into genic regions is accompanied by local amplification, increased expression in some cases, interruption of gene expression, and likely additional oncogenic effects. Similarly, reported examples of viral integration near microRNAs suggest that altered expression of these regulatory molecules may also contribute to oncogenesis. Future work is indicated to identify the mechanisms of these events on cancer cell behavior.

Rivers draining high standing islands (HSIs) and small mountainous rivers (SMRs) are known to have extremely high sediment fluxes, and can also have high chemical weathering yields, which makes them potentially important contributors to the global riverine elemental flux to the ocean. This work reports on the riverine concentrations, ocean flux, and weathering yields of Molybdenum (Mo), Vanadium (V), and Uranium (U) in a large number of small but geochemically important rivers using 338 river samples from ten lithologically-diverse regions. These redox-sensitive elements are used extensively to infer paleo-redox conditions in the ocean, and Mo and V are also important rock-derived micronutrients used by microorganisms in nitrogen fixation. Unlike in large river systems, in which dissolved Mo has been attributed predominately to pyrite dissolution, Mo concentrations in these rivers did not correlate with sulfate concentrations. V was found to correlate strongly with Si in terrains dominated by silicate rocks, but this trend was not observed in primarily sedimentary regions. Many rivers exhibited much higher V/Si ratios than larger rivers, and rivers draining young Quaternary volcanic rocks in Nicaragua had much higher dissolved V concentrations (mean = 1306 nM) than previously-studied rivers. U concentrations were generally well below the global average with the exception of rivers draining primarily sedimentary lithologies containing carbonates and shales. Fluxes of U and Mo from igneous terrains of intermediate composition are lower than the global average, while fluxes of V from these regions are higher, and up to two orders of magnitude higher in the Nicaragua rivers. Weathering yields of Mo and V in most regions are above the global mean, despite lower than average concentrations measured in some of those systems, indicating that the chemical weathering of these elements are higher in these SMR watersheds than larger drainages. In regions of active boundaries with andesite/dacite lithologies, rivers draining young Pleistocene rocks had higher concentrations than did older Miocene-Pliocene rocks of a similar composition. This work shows that weathering yields of Mo, V, and U from SMRs are slightly higher than from large rivers, and the age of igneous lithologies in these regions exhibits a measurable control on riverine concentrations of these elements.

Advanced head and neck squamous cell carcinoma (HNSCC) remains a therapeutic challenge due to the development of therapy resistance. Several studies have implicated the development of cancer stem cells as a possible mechanism for therapy resistance in HNSCC. Heat shock protein 90’s (Hsp90’s) molecular chaperone function is implicated in pathways of resistance in HNSCC. Therefore, in the present study, we investigated the efficacy of novel C-terminal Hsp90 inhibitors (KU711 and KU757) in targeting HNSCC cancer stem cells (CSCs). Treatment of HNSCC human cell lines MDA1986, UMSCC 22B, and UMSCC 22B cisplatin-resistant cells with the KU compounds indicated complete blockage of self-renewal for the resistant and parent cell lines starting from 20 μM KU711 and 1 μM KU757. Dose-dependent decrease in the cancer stem cell markers CD44, ALDH, and CD44/ALDH double-positive cells was observed for all cell lines after treatment with KU711 and KU757. When cells were treated with either drug, migration and invasion were downregulated greater than 90% even at the lowest concentrations of 20 μM KU711 and 1 μM KU757. Western blot showed >90% reduction in client protein “stemness” marker BMI-1 and mesenchymal marker vimentin, as well as increase in epithelial marker E-cadherin for both cell lines, indicating epithelial to mesenchymal transition quiescence. Several CSC-mediated miRNAs that play a critical role in HNSCC therapy resistance were also downregulated with KU treatment. In vivo, KU compounds were effective in decreasing tumor growth with no observed toxicity. Taken together, these results indicate that KU compounds are effective therapeutics for targeting HNSCC CSCs.

Despite moderate heritability, only one study has identified genomewide significant loci for cannabis-related phenotypes. We conducted meta-analyses of genomewide association study (GWAS) data on 2,080 DSM-IV cannabis dependent cases and 6,435 cannabis exposed controls of European descent. A cluster of correlated single nucleotide polymorphisms (SNPs) in a novel region on chromosome 10 was genomewide significant (lowest p = 1.3E-8). Among the SNPs, rs1409568 showed enrichment for H3K4me1 and H3K427ac marks, suggesting its role as an enhancer in addiction-relevant brain regions, such as the dorsolateral prefrontal cortex and the angular and cingulate gyri. This SNP is also predicted to modify binding scores for several transcription factors. We found modest evidence for replication for rs1409568 in an independent cohort of African-American (896 cases and 1591 controls; p=0.03) but not European-American (781 cases and 1905 controls) participants. The combined meta-analysis (3,757 cases and 9,931 controls) indicated trend-level significance for rs1409568 (p=2.85E-7). No genomewide significant loci emerged for cannabis dependence criterion count (n=8,050). There was also evidence that the minor allele of rs1409568 was associated with a 2.1% increase in right hippocampal volume in an independent sample of 430 European-American college students (fwe-p=.007). The identification and characterization of genomewide significant loci for cannabis dependence is amongst the first steps towards understanding the biological contributions to the etiology of this psychiatric disorder, which appears to be rising in some developed nations.

Explore the potential of dual-source dual-energy (DSDE) computed tomography (CT) to retrospectively analyze the uniformity of iron distribution and establish iron concentration ranges and distribution patterns found in healthy livers.Ten mixtures consisting of an iron nitrate solution and deionized water were prepared in test tubes and scanned using a DSDE 128-slice CT system. Iron images were derived from a 3-material decomposition algorithm (optimized for the quantification of iron). A conversion factor (mg Fe/mL per Hounsfield unit) was calculated from this phantom study as the quotient of known tube concentrations and their corresponding CT values. Retrospective analysis was performed of patients who had undergone DSDE imaging for renal stones. Thirty-seven patients with normal liver function were randomly selected (mean age, 52.5 years). The examinations were processed for iron concentration. Multiple regions of interest were analyzed, and iron concentration (mg Fe/mL) and distribution was reported.The mean conversion factor obtained from the phantom study was 0.15 mg Fe/mL per Hounsfield unit. Whole-liver mean iron concentrations yielded a range of 0.0 to 2.91 mg Fe/mL, with 94.6% (35/37) of the patients exhibiting mean concentrations below 1.0 mg Fe/mL. The most important finding was that iron concentration was not uniform and patients exhibited regionally high concentrations (36/37). These regions of higher concentration were observed to be dominant in the middle-to-upper part of the liver (75%), medially (72.2%), and anteriorly (83.3%).Dual-source dual-energy CT can be used to assess the uniformity of iron distribution in healthy subjects. Applying similar techniques to unhealthy livers, future research may focus on the impact of hepatic iron content and distribution for noninvasive assessment in diseased subjects.

BACKGROUND Human immunodeficiency virus–infected individuals (HIVIIs) have a higher incidence of head and neck squamous cell carcinoma (HNSCC), and clinical and histopathological differences have been observed in their tumors in comparison with those of HNSCC patients without a human immunodeficiency virus (HIV) infection. The reasons for these differences are not clear, and molecular differences between HIV-related HNSCC and non–HIV-related HNSCC may exist. This study compared the mutational patterns of HIV-related HNSCC and non–HIV-related HNSCC. METHODS The DNA of 20 samples of HIV-related HNSCCs and 32 samples of non–HIV-related HNSCCs was sequenced. DNA libraries covering exons of 18 genes frequently mutated in HNSCC (AJUBA, CASP8, CCND1, CDKN2A, EGFR, FAT1, FBXW7, HLA-A, HRAS, KEAP1, NFE2L2, NOTCH1, NOTCH2, NSD1, PIK3CA, TGFBR2, TP53, and TP63) were prepared and sequenced on an Ion Personal Genome Machine sequencer. DNA sequencing data were analyzed with Ion Reporter software. The human papillomavirus (HPV) status of the tumor samples was assessed with in situ hybridization, the MassARRAY HPV multiplex polymerase chain reaction assay, and p16 immunostaining. Mutation calls were compared among the studied groups. RESULTS HIV-related HNSCC revealed a distinct pattern of mutations in comparison with non–HIV-related HNSCC. TP53 mutation frequencies were significantly lower in HIV-related HNSCC. Mutations in HIV+ patients tended to be TpC>T nucleotide changes for all mutated genes but especially for TP53. CONCLUSIONS HNSCC in HIVIIs presents a distinct pattern of genetic mutations, particularly in the TP53 gene. HIV-related HNSCC may have a distinct biology, and an effect of the HIV virus on the pathogenesis of these tumors should not be ruled out. Cancer 2017. © 2017 American Cancer Society.

Chemical weathering source provenance changes associated with Typhoon Mindulle (2004) were identified for the Choshui River Watershed in west-central Taiwan using radiogenic Sr isotope ( 87 Sr/ 86 Sr) and major ion chemistry analysis of water samples collected before, during, and following the storm event. Storm water sampling over 72 h was conducted in 3 h intervals, allowing for novel insight into weathering regime changes in response to intense rainfall events. Chemical weathering sources were determined to be bulk silicate and disseminated carbonate minerals at the surface and silicate contributions from deep thermal waters. Loss on ignition analysis of collected rock samples indicate disseminated carbonate can compose over 25% by weight of surface mineralogy, but typically makes up ∼2–3% of watershed rock. 87 Sr/ 86 Sr and major element molar ratios indicate that Typhoon Mindulle caused a weathering regime switch from normal flow incorporating a deep thermal signature to that of a system dominated by surface weathering. The data suggest release of silicate solute rich soil pore waters during storm events, creating a greater relative contribution of silicate weathering to the solute load during periods of increased precipitation and runoff. Partial depletion of this soil solute reservoir and possible erosion enhanced carbonate weathering lead to increased importance of carbonates to the weathering regime as the storm continues. Major ion data indicate that complex mica weathering (muscovite, biotite, illite, chlorite) may represent an important silicate weathering pathway in the watershed. Deep thermal waters represent an important contribution to river solutes during normal non-storm flow conditions. Sulfuric acid sourced from pyrite weathering is likely a major weathering agent in the Choshui River watershed.

Mirror Lake, one of the scenic locations on The Ohio State University's campus, experiences an intense bioturbation event as part of an annual tradition revolving around the rivalry football game against the University of Michigan. This tradition involves thousands of students jumping into the lake over one night in the week leading up to the football game. Water samples were collected from several locations in the lake before, during, and after the Mirror Lake Jump to determine the impact of this event on lake water chemistry. There were significant and systematic increases in the concentrations of Na+, K+, Cl−, total nitrogen, ammonia, and dissolved organic carbon (DOC) associated with the jump, especially in the eastern side of the lake where most of the students entered. Over the 3-h period from 10 p.m. to 1 a.m. on the eastern side of the lake, Na+, K+, and Cl− concentrations increased by about 2–4 ppm, 1.5–3 ppm, and 4–6 ppm, respectively. The total nitrogen concentration increased about five to six fold, from 450–500 ppb to 2300–2800 ppb over the height of the event on the eastern side of the lake. Similar increases were observed for DOC, increasing from 3.6 to 18 ppm. This DOC increase was coincident with a 5‰ shift in δ13C, from a mean of around −28‰ in the early hours of the evening to a maximum of −23‰, implying a large influx of isotopically heavy carbon into the lake. Ammonia concentrations varied substantially from year to year, but always showed a systematic increase in concentration during the event. Smaller changes in major ion and nutrient concentrations were observed in the middle and western side of the lake, where fewer students entered the lake. The changes in concentration and the timing and spatial distribution of these changes are primarily attributed to anthropogenic input from jumpers in the form of bodily fluids (e.g., evaporated sweat, sebum and urine). Over a single night, these anthropogenic event inputs represent roughly 10% of the annual nitrogen budget of the lake, emphasizing the direct impact humans can have on urban water bodies on short time scales.

Prior research has treated political experience as if it had similar effects for every candidate. However, recent studies suggest that the effects of political experience on trait judgments and candidate evaluations may vary depending on a candidate’s demographic characteristics. Accordingly, this study investigates whether the influence of prior experience varies depending on the racial and gender background of political candidates. To explore this topic, we employ an experiment with a 2 (Race: White and Black) × 2 (Sex: Male and Female) × 2 (Experience: Experienced and Inexperienced) factorial design. The expectation is that political experience will have the greatest impact for white male candidates when compared to female and African American candidates. Furthermore, the study explores the differential effects of political experience by examining whether the influence of experience on competence ratings varies depending on the negative racial and gender attitudes of participants. The findings ...

The advent of the first immortal human cancer cell line in 1951 (HeLa) had profound implications for cancer research.1 Historically, the list of translational cancer research discoveries generated from human-derived cancer cell lines such as HeLa cannot be overstated.2-4 In addition, the future of the research enterprise undoubtedly depends on continued access to the biospecimens that generate such lines. However, it was the 2010 book, The Immortal Life of Henrietta Lacks, and its compelling story of the woman behind HeLa, that initiated an impassioned debate on the ethics and limits of research with such tissue.5 Applied laboratory scientists have a moral and ethical obligation to respect and honor the person from whom biospecimens were derived, but how that respect should be demonstrated is a matter of debate. The Common Rule, initially adopted in 1991, created an overarching guideline for federally funded human subjects research to provide oversight both in response to prior ethical transgressions and to present a unified ethical and regulatory framework for the future. But, in the ensuing years, the research landscape has dramatically changed in ways that could not be anticipated two decades past. Thus, a contemporary update to the Common Rule has been long overdue. After almost 6 years of careful analysis and vetting, along with public commentaries and spirited debate, 16 federal departments and agencies, including the US Department of Health and Human Services, published the eagerly anticipated final rule for the Federal Policy for the Protection of Human Research Subjects (Common Rule) on January 18, 2017, with a plan for implementation in 2018.6-8 The field of cancer research is currently in a watershed, further stimulated by the Cancer Moonshot and Precision Medicine Initiative. The pace of discoveries with immediate translational potential, particularly with regard to tumor biology/immunology and genomics, is frenetic. The translation of new laboratory data to applications at the bedside has never been more dynamic or fluid. Much of this research falls under the purview of the Common Rule and is accordingly dependent on and accountable to its stipulations and revisions. The goals of the Common Rule revisions include to “enhance respect and safeguards for research participants and to increase research efficiency by reducing unnecessary burdens and calibrating oversight to the level of risk.”9(p2293) However, many stakeholders were concerned that several proposed changes would hinder the research enterprise unnecessarily, particularly in the field of oncology. For example, the proposed Common Rule changes in the notice of proposed rulemaking (NPRM), which preceded the final rulemaking, included efforts to require broad consent for all research with biospecimens. Under the previous version, biospecimen informed consent was only required if identifying information accompanied the sample.6 The intent of the proposal—which considers any human tissue to be a human subject triggering informed consent protections—was to respect participant autonomy, but it raised the possibility of serious unintended consequences. A lively discussion ensued regarding how best to balance the need to protect and respect current participants who provide their tissue to advance scientific knowledge while ensuring scientists have the ability to advance science for future patients using invaluable biologic specimens.9-11 Ultimately, the final Common Rule was receptive to such criticisms (Table 1).13 Table 1. Summary of Major Changes to the Final Common Rule

Background Problematic alcohol use in adolescence and adulthood is a common and often debilitating correlate of childhood attention-deficit/hyperactivity disorder (ADHD). Converging evidence suggests that ADHD and problematic alcohol use share a common additive genetic basis, which may be mechanistically related to reward-related brain function. In the current study, we examined whether polygenic risk for childhood ADHD is linked to problematic alcohol use in young adulthood through alterations in reward-related activity of the ventral striatum, a neural hub supporting appetitive behaviors and reinforcement learning. Methods Genomic, neuroimaging, and self-report data were available for 404 non-Hispanic European American participants who completed the ongoing Duke Neurogenetics Study. Polygenic risk scores for childhood ADHD were calculated based on a genome-wide association study meta-analysis conducted by the Psychiatric Genomics Consortium and tested for association with reward-related ventral striatum activity, measured using a number-guessing functional magnetic resonance imaging paradigm, and self-reported problematic alcohol use. A mediational model tested whether ventral striatum activity indirectly links polygenic risk for ADHD to problematic alcohol use. Results Despite having no main effect on problematic alcohol use, polygenic risk for childhood ADHD was indirectly associated with problematic alcohol use through increased reward-related ventral striatum activity. Conclusions Individual differences in reward-related brain function may, at least in part, mechanistically link polygenic risk for childhood ADHD to problematic alcohol use.

OBJECTIVE: Impairments generally persist when children diagnosed with attention-deficit/hyperactivity disorder (ADHD) mature into adolescence. To examine changes in ADHD care during the transition from childhood to adolescence, we conducted a retrospective, longitudinal cohort study of patients diagnosed with ADHD before the age of 10 years to assess changes from preadolescence through adolescence in (1) frequency by which primary care providers offer ADHD care to patients, (2) range of concerns assessed during patient encounters, and (3) treatments implemented or recommended. METHODS: We identified patients from 3 practices included in a large primary care network who (1) were born between 1996 and 1997, (2) were diagnosed with ADHD before the age of 10 years, and (3) received primary care continuously from age 9 through late adolescence. Clinical care was compared among patients in preadolescence (age 9–11), early adolescence (age 12–14), and late adolescence (age 15–18). RESULTS: Children diagnosed with ADHD before the age of 10 years were less likely to have a documented visit for ADHD during late adolescence (41% of patients) compared with preadolescence (63%, p < 0.001). Evidence of monitoring for depression, suicide, and substance abuse increased from preadolescence to adolescence (p < 0.001) and occurred in about 90% of adolescent patients. However, monitoring for risky sexual activity occurred in only about 50% of adolescents. Discussions of medication diversion and driver readiness were essentially not documented. CONCLUSION: The findings raise concerns about how primary care providers manage adolescents with a history of ADHD. Improving monitoring of risky sexual behavior and driver readiness and providing patient education about medication diversion are needed.

MC3 Working Group: Rehan Akbani21, Pavana Anur22, Matthew H. Bailey1,2,3, Alex Buchanan9, Kami Chiotti9, Kyle Covington12,23, Allison Creason9, Li Ding1,2,3,20, Kyle Ellrott9, Yu Fan21, Steven Foltz1,2, Gad Getz8,14,15,16, Walker Hale12, David Haussler24,25, Julian M. Hess8,26, Carolyn M. Hutter27, Cyriac Kandoth28, Katayoon Kasaian29,30, Melpomeni Kasapi27, Dave Larson1 , Ignaty Leshchiner8, John Letaw31, Singer Ma32, Michael D. McLellan1,3,20, Yifei Men32, Gordon B. Mills33,34, Beifang Niu35, Myron Peto22, Amie Radenbaugh24, Sheila M. Reynolds36, Gordon Saksena8, Heidi Sofia27, Chip Stewart8, Adam J. Struck31, Joshua M. Stuart24,37, Wenyi Wang21, John N. Weinstein38, David A. Wheeler12,13, Christopher K. Wong24,39, Liu Xi12 & Kai Ye40,41 21Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 22Molecular and Medical Genetics, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 23Castle Biosciences Inc, Friendswood, TX 77546, USA. 24UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 25Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 26Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02114, USA. 27National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA. 28Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. 29Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada. 30Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada. 31Computational Biology Program, School of Medicine, Oregon Health and Science University, Portland, OR 97239, USA. 32DNAnexus Inc, Mountain View, CA 94040, USA. 33Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA. 34Precision Oncology, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 35Computer Network Information Center, Chinese Academy of Sciences, Beijing, China. 36Institute for Systems Biology, Seattle, WA 98109, USA. 37Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 38Department of Bioinformatics and Computational Biology and Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 39Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 40School of Elect, PCAWG novel somatic mutation calling methods working group: Matthew H. Bailey1,2,3, Beifang Niu35, Matthias Bieg42,43, Paul C. Boutros6,44,45,46, Ivo Buchhalter43,47,48, Adam P. Butler49, Ken Chen50, Zechen Chong51, Li Ding1,2,3,20, Oliver Drechsel52,53, Lewis Jonathan Dursi6,7, Roland Eils47,48,54,55, Kyle Ellrott9, Shadrielle M. G. Espiritu6, Yu Fan21, Robert S. Fulton1,3,20, Shengjie Gao56, Josep L. l. Gelpi57,58, Mark B. Gerstein5,18,19, Gad Getz8,14,15,16, Santiago Gonzalez59,60, Ivo G. Gut52,61, Faraz Hach62,63, Michael C. Heinold47,48, Julian M. Hess8,26, Jonathan Hinton49, Taobo Hu64, Vincent Huang6, Yi Huang65,66, Barbara Hutter43,67,68, David R. Jones49, Jongsun Jung69, Natalie Jäger47, Hyung-Lae Kim70, Kortine Kleinheinz47,48, Sushant Kumar5,19, Yogesh Kumar64, Christopher M. Lalansingh6, Ignaty Leshchiner8, Ivica Letunic71, Dimitri Livitz8, Eric Z. Ma64, Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Michael D. McLellan1,3,20, Andrew Menzies49, Ana Milovanovic57, Morten Muhlig Nielsen73, Stephan Ossowski52,53,74, Nagarajan Paramasivam43,47, Jakob Skou Pedersen73,75, Marc D. Perry76,77, Montserrat Puiggròs57, Keiran M. Raine49, Esther Rheinbay8,14,72, Romina Royo57, S. Cenk Sahinalp62,78,79, Gordon Saksena8, Iman Sarrafi62,78, Matthias Schlesner47,80, Jared T. Simpson6,17, Lucy Stebbings49, Chip Stewart8, Miranda D. Stobbe52,61, Jon W. Teague49, Grace Tiao8, David Torrents57,81, Jeremiah A. Wala8,14,82, Jiayin Wang1,40,66, Wenyi Wang21, Sebastian M. Waszak60, Joachim Weischenfeldt60,83,84, Michael C. Wendl1,10,11, Johannes Werner47,85, Zhenggang Wu64, Hong Xue64, Sergei Yakneen60, Takafumi N. Yamaguchi6, Kai Ye40,41, Venkata D. Yellapantula20,86, Christina K. Yung76 & Junjun Zhang76, PCAWG Consortium: Lauri A. Aaltonen87, Federico Abascal49, Adam Abeshouse88, Hiroyuki Aburatani89, David J. Adams49, Nishant Agrawal90, Keun Soo Ahn91, Sung-Min Ahn92, Hiroshi Aikata93, Rehan Akbani21, Kadir C. Akdemir50, Hikmat Al-Ahmadie88, Sultan T. Al-Sedairy94, Fatima Al-Shahrour95, Malik Alawi96,97, Monique Albert98, Kenneth Aldape99,100, Ludmil B. Alexandrov49,101,102, Adrian Ally30, Kathryn Alsop103, Eva G. Alvarez104,105,106, Fernanda Amary107, Samirkumar B. Amin108,109,110, Brice Aminou76, Ole Ammerpohl111,112, Matthew J. Anderson113, Yeng Ang114, Davide Antonello115, Pavana Anur22, Samuel Aparicio116, Elizabeth L. Appelbaum1,117, Yasuhito Arai118, Axel Aretz119, Koji Arihiro93, Shun-ichi Ariizumi120, Joshua Armenia121, Laurent Arnould122, Sylvia Asa123,124, Yassen Assenov125, Gurnit Atwal6,126,127, Sietse Aukema112,128, J. Todd Auman129, Miriam R. Aure130, Philip Awadalla6,126, Marta Aymerich131, Gary D. Bader126, Adrian Baez-Ortega132, Matthew H. Bailey1,2,3, Peter J. Bailey133, Miruna Balasundaram30, Saianand Balu134, Pratiti Bandopadhayay8,135,136, Rosamonde E. Banks137, Stefano Barbi138, Andrew P. Barbour139,140, Jonathan Barenboim6, Jill Barnholtz-Sloan141,142, Hugh Barr143, Elisabet Barrera59, John Bartlett98,144, Javier Bartolome57, Claudio Bassi115, Oliver F. Bathe145,146, Daniel Baumhoer147, Prashant Bavi148, Stephen B. Baylin149,150, Wojciech Bazant59, Duncan Beardsmore151, Timothy A. Beck152,153, Sam Behjati49, Andreas Behren154, Beifang Niu35, Cindy Bell155, Sergi Beltran52,61, Christopher Benz156, Andrew Berchuck157, Anke K. Bergmann158, Erik N. Bergstrom101,102, Benjamin P. Berman159,160,161, Daniel M. Berney162, Stephan H. Bernhart163,164,165, Rameen Beroukhim8,14,82, Mario Berrios166, Samantha Bersani167, Johanna Bertl73,168, Miguel Betancourt169, Vinayak Bhandari6,44, Shriram G. Bhosle49, Andrew V. Biankin133,170,171,172, Matthias Bieg42,43, Darell Bigner173, Hans Binder163,164, Ewan Birney59, Michael Birrer72, Nidhan K. Biswas174, Bodil Bjerkehagen147,175, Tom Bodenheimer134, Lori Boice176, Giada Bonizzato177, Johann S. De Bono178, Arnoud Boot179,180, Moiz S. Bootwalla166, Ake Borg181, Arndt Borkhardt182, Keith A. Boroevich183,184, Ivan Borozan6, Christoph Borst185, Marcus Bosenberg186, Mattia Bosio52,53,57, Jacqueline Boultwood187, Guillaume Bourque188,189, Paul C. Boutros6,44,45,46, G. Steven Bova190, David T. Bowen49,191, Reanne Bowlby30, David D. L. Bowtell103, Sandrine Boyault192, Rich Boyce59, Jeffrey Boyd193, Alvis Brazma59, Paul Brennan194, Daniel S. Brewer195,196, Arie B. Brinkman197, Robert G. Bristow44,198,199,200,201, Russell R. Broaddus99, Jane E. Brock202, Malcolm Brock203, Annegien Broeks204, Angela N. Brooks8,24,37,82, Denise Brooks30, Benedikt Brors67,205,206, Søren Brunak207,208, Timothy J. C. Bruxner113,209, Alicia L. Bruzos104,105,106, Alex Buchanan9, Ivo Buchhalter43,47,48, Christiane Buchholz210, Susan Bullman8,82, Hazel Burke211, Birgit Burkhardt212, Kathleen H. Burns213,214, John Busanovich8,215, Carlos D. Bustamante216,217, Adam P. Butler49, Atul J. Butte218, Niall J. Byrne76, Anne-Lise Børresen-Dale130,219, Samantha J. Caesar-Johnson220, Andy Cafferkey59, Declan Cahill221, Claudia Calabrese59,60, Carlos Caldas222,223, Fabien Calvo224, Niedzica Camacho178, Peter J. Campbell49,225, Elias Campo226,227, Cinzia Cantù177, Shaolong Cao21, Thomas E. Carey228, Joana Carlevaro-Fita229,230,231, Rebecca Carlsen30, Ivana Cataldo167,177, Mario Cazzola232, Jonathan Cebon154, Robert Cerfolio233, Dianne E. Chadwick234, Dimple Chakravarty235, Don Chalmers236, Calvin Wing Yiu Chan47,237, Kin Chan238, Michelle Chan-Seng-Yue148, Vishal S. Chandan239, David K. Chang133,170, Stephen J. Chanock240, Lorraine A. Chantrill170,241, Aurélien Chateigner76,242, Nilanjan Chatterjee149,243, Kazuaki Chayama93, Hsiao-Wei Chen114,121, Jieming Chen218, Ken Chen50, Yiwen Chen21, Zhaohong Chen244, Andrew D. Cherniack8,82, Jeremy Chien245, Yoke-Eng Chiew246,247, Suet-Feung Chin222,223, Juok Cho8, Sunghoon Cho248, Jung Kyoon Choi249, Wan Choi250, Christine Chomienne251, Zechen Chong51, Su Pin Choo252, Angela Chou170,246, Angelika N. Christ113, Elizabeth L. Christie103, Eric Chuah30, Carrie Cibulskis8, Kristian Cibulskis8, Sara Cingarlini253, Peter Clapham49, Alexander Claviez254, Sean Cleary148,255, Nicole Cloonan256, Marek Cmero257,258,259, Colin C. Collins62, Ashton A. Connor255,260, Susanna L. Cooke133, Colin S. Cooper178,196,261, Leslie Cope149, Vincenzo Corbo138,177, Matthew G. Cordes1,262, Stephen M. Cordner263, Isidro Cortés-Ciriano264,265,266, Kyle Covington12,23, Prue A. Cowin267, Brian Craft24, David Craft8,268, Chad J. Creighton269, Yupeng Cun270, Erin Curley271, Ioana Cutcutache179,180, Karolina Czajka272, Bogdan Czerniak99,273, Rebecca A. Dagg274, Ludmila Danilova149, Maria Vittoria Davi275, Natalie R. Davidson276,277,278,279,280, Helen Davies49,281,282, Ian J. Davis283, Brandi N. Davis-Dusenbery284, Kevin J. Dawson49, Francisco M. De La Vega216,217,285, Ricardo De Paoli-Iseppi211, Timothy Defreitas8, Angelo P. Dei Tos286, Olivier Delaneau287,288,289, John A. Demchok220, Jonas Demeulemeester290,291, German M. Demidov52,53,74, Deniz Demircioğlu292,293, Nening M. Dennis221, Robert E. Denroche148, Stefan C. Dentro49,290,294, Nikita Desai76, Vikram Deshpande72, Amit G. Deshwar295, Christine Desmedt296,297, Jordi Deu-Pons298,299, Noreen Dhalla30, Neesha C. Dhani300, Priyanka Dhingra301,302, Rajiv Dhir303, Anthony DiBiase304, Klev Diamanti305, Li Ding1,2,3,20, Shuai Ding306, Huy Q. Dinh159, Luc Dirix307, HarshaVardhan Doddapaneni12, Nilgun Donmez62,78, Michelle T. Dow244, Ronny Drapkin308, Oliver Drechsel52,53, Ruben M. Drews223, Serge Serge49, Tim Dudderidge150,221, Ana Dueso-Barroso57, Andrew J. Dunford8, Michael Dunn309, Lewis Jonathan Dursi6,7, Fraser R. Duthie133,310, Ken Dutton-Regester311, Jenna Eagles272, Douglas F. Easton312,313, Stuart Edmonds314, Paul A. Edwards223,315, Sandra E. Edwards178, Rosalind A. Eeles178,221, Anna Ehinger316, Juergen Eils54,55, Roland Eils47,48,54,55, Adel El-Naggar99,273, Matthew Eldridge223, Kyle Ellrott9, Serap Erkek60, Georgia Escaramis53,317,318, Shadrielle M. G. Espiritu6, Xavier Estivill53,319, Dariush Etemadmoghadam103, Jorunn E. Eyfjord320, Bishoy M. Faltas280, Daiming Fan321, Yu Fan21, William C. Faquin72, Claudiu Farcas244, Matteo Fassan322, Aquila Fatima323, Francesco Favero324, Nodirjon Fayzullaev76, Ina Felau220, Sian Fereday103, Martin L. Ferguson325, Vincent Ferretti76,326, Lars Feuerbach205, Matthew A. Field327, J. Lynn Fink57,113, Gaetano Finocchiaro328, Cyril Fisher221, Matthew W. Fittall290, Anna Fitzgerald329, Rebecca C. Fitzgerald282, Adrienne M. Flanagan330, Neil E. Fleshner331, Paul Flicek59, John A. Foekens332, Kwun M. Fong333, Nuno A. Fonseca59,334, Christopher S. Foster335,336, Natalie S. Fox6, Michael Fraser6, Scott Frazer8, Milana Frenkel-Morgenstern337, William Friedman338, Joan Frigola298, Catrina C. Fronick1,262, Akihiro Fujimoto184, Masashi Fujita184, Masashi Fukayama339, Lucinda A. Fulton1 , Robert S. Fulton1,3,20, Mayuko Furuta184, P. Andrew Futreal340, Anja Füllgrabe59, Stacey B. Gabriel8, Steven Gallinger148,255,260, Carlo Gambacorti-Passerini341, Jianjiong Gao121, Shengjie Gao56, Levi Garraway82, Øystein Garred342, Erik Garrison49, Dale W. Garsed103, Nils Gehlenborg8,343, Josep L. l. Gelpi57,58, Joshy George110, Daniela S. Gerhard344, Clarissa Gerhauser345, Jeffrey E. Gershenwald346,347, Mark B. Gerstein5,18,19, Moritz Gerstung59,60, Gad Getz8,14,15,16, Mohammed Ghori49, Ronald Ghossein348, Nasra H. Giama349, Richard A. Gibbs12, Anthony J. Gill170,350, Pelvender Gill351, Dilip D. Giri348, Dominik Glodzik49, Vincent J. Gnanapragasam352,353, Maria Elisabeth Goebler354, Mary J. Goldman24, Carmen Gomez355, Santiago Gonzalez59,60, Abel Gonzalez-Perez298,299,356, Dmitry A. Gordenin357, James Gossage358, Kunihito Gotoh359, Ramaswamy Govindan3, Dorthe Grabau360, Janet S. Graham133,361, Robert C. Grant148,260, Anthony R. Green315, Eric Green27, Liliana Greger59, Nicola Grehan282, Sonia Grimaldi177, Sean M. Grimmond362, Robert L. Grossman363, Adam Grundhoff97,364, Gunes Gundem88, Qianyun Guo75, Manaswi Gupta8, Shailja Gupta365, Ivo G. Gut52,61, Marta Gut52,61, Jonathan Göke292,366, Gavin Ha8, Andrea Haake111, David Haan37, Siegfried Haas185, Kerstin Haase290, James E. Haber367, Nina Habermann60, Faraz Hach62,63, Syed Haider6, Natsuko Hama118, Freddie C. Hamdy351, Anne Hamilton267, Mark P. Hamilton368, Leng Han369, George B. Hanna370, Martin Hansmann371, Nicholas J. Haradhvala8,72, Olivier Harismendy102,372, Ivon Harliwong113, Arif O. Harmanci5,373, Eoghan Harrington374, Takanori Hasegawa375, David Haussler24,25, Steve Hawkins223, Shinya Hayami376, Shuto Hayashi375, D. Neil Hayes134,377,378, Stephen J. Hayes379,380, Nicholas K. Hayward211,311, Steven Hazell221, Yao He381, Allison P. Heath382, Simon C. Heath52,61, David Hedley300, Apurva M. Hegde38, David I. Heiman8, Michael C. Heinold47,48, Zachary Heins88, Lawrence E. Heisler152, Eva Hellstrom-Lindberg383, Mohamed Helmy384, Seong Gu Heo385, Austin J. Hepperla134, José María Heredia-Genestar386, Carl Herrmann47,48,387, Peter Hersey211, Julian M. Hess8,26, Holmfridur Hilmarsdottir320, Jonathan Hinton49, Satoshi Hirano388, Nobuyoshi Hiraoka389, Katherine A. Hoadley134,390, Asger Hobolth75,168, Ermin Hodzic78, Jessica I. Hoell182, Steve Hoffmann163,164,165,391, Oliver Hofmann392, Andrea Holbrook166, Aliaksei Z. Holik53, Michael A. Hollingsworth393, Oliver Holmes209,311, Robert A. Holt30, Chen Hong205,237, Eun Pyo Hong385, Jongwhi H. Hong394, Gerrit K. Hooijer395, Henrik Hornshøj73, Fumie Hosoda118, Yong Hou56,396, Volker Hovestadt397, William Howat352, Alan P. Hoyle134, Ralph H. Hruban149, Jianhong Hu12, Taobo Hu64, Xing Hua240, Kuan-lin Huang1,398, Mei Huang176, Mi Ni Huang179,180, Vincent Huang6, Yi Huang65,66, Wolfgang Huber60, Thomas J. Hudson272,399, Michael Hummel400, Jillian A. Hung246,247, David Huntsman401, Ted R. Hupp402, Jason Huse88, Matthew R. Huska403, Barbara Hutter43,67,68, Carolyn M. Hutter27, Daniel Hübschmann48,54,404,405,406, Christine A. Iacobuzio-Donahue348, Charles David Imbusch205, Marcin Imielinski407,408, Seiya Imoto375, William B. Isaacs409, Keren Isaev6,44, Shumpei Ishikawa410, Murat Iskar397, S. M. Ashiqul Islam244, Michael Ittmann411,412,413, Sinisa Ivkovic284, Jose M. G. Izarzugaza414, Jocelyne Jacquemier415, Valerie Jakrot211, Nigel B. Jamieson133,172,416, Gun Ho Jang148, Se Jin Jang417, Joy C. Jayaseelan12, Reyka Jayasinghe1 , Stuart R. Jefferys134, Karine Jegalian418, Jennifer L. Jennings419, Seung-Hyup Jeon250, Lara Jerman60,420, Yuan Ji421,422, Wei Jiao6, Peter A. Johansson311, Amber L. Johns170, Jeremy Johns272, Rory Johnson230,423, Todd A. Johnson183, Clemency Jolly290, Yann Joly424, Jon G. Jonasson320, Corbin D. Jones425, David R. Jones49, David T. W. Jones426,427, Nic Jones428, Steven J. M. Jones30, Jos Jonkers204, Young Seok Ju49,249, Hartmut Juhl429, Jongsun Jung69, Malene Juul73, Randi Istrup Juul73, Sissel Juul374, Natalie Jäger47, Rolf Kabbe47, Andre Kahles276,277,278,279,430, Abdullah Kahraman431,432,433, Vera B. Kaiser434, Hojabr Kakavand211, Sangeetha Kalimuthu148, Christof von Kalle405, Koo Jeong Kang91, Katalin Karaszi351, Beth Karlan435, Rosa Karlić436, Dennis Karsch437, Katayoon Kasaian29,30, Karin S. Kassahn113,438, Hitoshi Katai439, Mamoru Kato440, Hiroto Katoh410, Yoshiiku Kawakami93, Jonathan D. Kay117, Stephen H. Kazakoff209,311, Marat D. Kazanov441,442,443, Maria Keays59, Electron Kebebew444,445, Richard F. Kefford446, Manolis Kellis8,447, James G. Kench170,350,448, Catherine J. Kennedy246,247, Jules N. A. Kerssemakers47, David Khoo273, Vincent Khoo221, Narong Khuntikeo115,449, Ekta Khurana301,302,450,451, Helena Kilpinen117, Hark Kyun Kim452, Hyung-Lae Kim70, Hyung-Yong Kim415, Hyunghwan Kim250, Jaegil Kim8, Jihoon Kim453, Jong K. Kim454, Youngwook Kim455,456, Tari A. King457,458,459, Wolfram Klapper128, Kortine Kleinheinz47,48, Leszek J. Klimczak460, Stian Knappskog49,461, Michael Kneba437, Bartha M. Knoppers424, Youngil Koh462,463, Jan Komorowski305,464, Daisuke Komura410, Mitsuhiro Komura375, Gu Kong415, Marcel Kool426,465, Jan O. Korbel59,60, Viktoriya Korchina12, Andrey Korshunov465, Michael Koscher465, Roelof Koster466, Zsofia Kote-Jarai178, Antonios Koures244, Milena Kovacevic284, Barbara Kremeyer49, Helene Kretzmer164,165, Markus Kreuz467, Savitri Krishnamurthy99,468, Dieter Kube469, Kiran Kumar8, Pardeep Kumar221, Sushant Kumar5,19, Yogesh Kumar64, Ritika Kundra114,121, Kirsten Kübler8,14,72, Ralf Küppers470, Jesper Lagergren383,471, Phillip H. Lai166, Peter W. Laird472, Sunil R. Lakhani473, Christopher M. Lalansingh6, Emilie Lalonde6, Fabien C. Lamaze6, Adam Lambert351, Eric Lander8, Pablo Landgraf474,475, Luca Landoni115, Anita Langerød130, Andrés Lanzós230,231,423, Denis Larsimont476, Erik Larsson477, Mark Lathrop189, Loretta M. S. Lau478, Chris Lawerenz55, Rita T. Lawlor177, Michael S. Lawrence8,72,183, Alexander J. Lazar99,108, Xuan Le479, Darlene Lee30, Donghoon Lee5, Eunjung Alice Lee480, Hee Jin Lee417, Jake June-Koo Lee264,266, Jeong-Yeon Lee481, Juhee Lee482, Ming Ta Michael Lee340, Henry Lee-Six49, Kjong-Van Lehmann276,277,278,279,430, Hans Lehrach483, Dido Lenze400, Conrad R. Leonard209,311, Daniel A. Leongamornlert49,178, Ignaty Leshchiner8, Louis Letourneau484, Ivica Letunic71, Douglas A. Levine88,485, Lora Lewis12, Tim Ley486, Chang Li56,396, Constance H. Li6,44, Haiyan Irene Li30, Jun Li21, Lin Li56, Shantao Li5, Siliang Li56,396, Xiaobo Li56,396, Xiaotong Li5, Xinyue Li56, Yilong Li49, Han Liang21, Sheng-Ben Liang234, Peter Lichter68,397, Pei Lin8, Ziao Lin8,487, W. M. Linehan488, Ole Christian Lingjærde489, Dongbing Liu56,396, Eric Minwei Liu88,301,302, Fei-Fei Liu201,490, Fenglin Liu381,491, Jia Liu492, Xingmin Liu56,396, Julie Livingstone6, Dimitri Livitz8, Naomi Livni221, Lucas Lochovsky5,19,110, Markus Loeffler467, Georgina V. Long211, Armando Lopez-Guillermo493, Shaoke Lou5,19, David N. Louis72, Laurence B. Lovat117, Yiling Lu38, Yong-Jie Lu162,494, Youyong Lu495,496,497, Claudio Luchini167, Ilinca Lungu144,148, Xuemei Luo152, Hayley J. Luxton117, Andy G. Lynch223,315,498, Lisa Lype36, Cristina López111,112, Carlos López-Otín499, Eric Z. Ma64, Yussanne Ma30, Gaetan MacGrogan500, Shona MacRae501, Geoff Macintyre223, Tobias Madsen73, Kazuhiro Maejima184, Andrea Mafficini177, Dennis T. Maglinte166,502, Arindam Maitra174, Partha P. Majumder174, Luca Malcovati232, Salem Malikic62,78, Giuseppe Malleo115, Graham J. Mann211,246,503, Luisa Mantovani-Löffler504, Kathleen Marchal505,506, Giovanni Marchegiani115, Elaine R. Mardis1,193,507, Adam A. Margolin31, Maximillian G. Marin37, Florian Markowetz223,315, Julia Markowski403, Jeffrey Marks508, Tomas Marques-Bonet61,81,386,509, Marco A. Marra30, Luke Marsden351, John W. M. Martens332, Sancha Martin49,510, Jose I. Martin-Subero81,511, Iñigo Martincorena49, Alexander Martinez-Fundichely301,302,451 Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Charlie E. Massie223, Thomas J. Matthew37, Lucy Matthews178, Erik Mayer221,512, Simon Mayes513, Michael Mayo30, Faridah Mbabaali272, Karen McCune514, Ultan McDermott49, Patrick D. McGillivray19, Michael D. McLellan1,3,20, John D. McPherson148,272,515, John R. McPherson179,180, Treasa A. McPherson260, Samuel R. Meier8, Alice Meng516, Shaowu Meng134, Andrew Menzies49, Neil D. Merrett115,517, Sue Merson178, Matthew Meyerson8,14,82, William U. Meyerson4,5, Piotr A. Mieczkowski518, George L. Mihaiescu76, Sanja Mijalkovic284, Ana Mijalkovic Mijalkovic-Lazic284, Tom Mikkelsen519, Michele Milella253, Linda Mileshkin103, Christopher A. Miller1 , David K. Miller113,170, Jessica K. Miller272, Gordon B. Mills33,34, Ana Milovanovic57, Sarah Minner520, Marco Miotto115, Gisela Mir Arnau267, Lisa Mirabello240, Chris Mitchell103, Thomas J. Mitchell49,315,352, Satoru Miyano375, Naoki Miyoshi375, Shinichi Mizuno521, Fruzsina Molnár-Gábor522, Malcolm J. Moore300, Richard A. Moore30, Sandro Morganella49, Quaid D. Morris127,490, Carl Morrison523,524, Lisle E. Mose134, Catherine D. Moser349, Ferran Muiños298,299, Loris Mularoni298,299, Andrew J. Mungall30, Karen Mungall30, Elizabeth A. Musgrove133, Ville Mustonen525,526,527, David Mutch528, Francesc Muyas52,53,74, Donna M. Muzny12, Alfonso Muñoz59, Jerome Myers529, Ola Myklebost461, Peter Möller530, Genta Nagae89, Adnan M. Nagrial170, Hardeep K. Nahal-Bose76, Hitoshi Nakagama531, Hidewaki Nakagawa184, Hiromi Nakamura118, Toru Nakamura388, Kaoru Nakano184, Tannistha Nandi532, Jyoti Nangalia49, Mia Nastic284, Arcadi Navarro61,81,386, Fabio C. P. Navarro19, David E. Neal223,352, Gerd Nettekoven533, Felicity Newell209,311, Steven J. Newhouse59, Yulia Newton37, Alvin Wei Tian Ng534, Anthony Ng535, Jonathan Nicholson49, David Nicol221, Yongzhan Nie321,536, G. Petur Nielsen72, Morten Muhlig Nielsen73, Serena Nik-Zainal49,281,282,537, Michael S. Noble8, Katia Nones209,311, Paul A. Northcott538, Faiyaz Notta148,539, Brian D. O’Connor76,540, Peter O’Donnell541, Maria O’Donovan282, Sarah O’Meara49, Brian Patrick O’Neill542, J. Robert O’Neill543, David Ocana59, Angelica Ochoa88, Layla Oesper544, Christopher Ogden221, Hideki Ohdan93, Kazuhiro Ohi375, Lucila Ohno-Machado244, Karin A. Oien523,545, Akinyemi I. Ojesina546,547,548, Hidenori Ojima549, Takuji Okusaka550, Larsson Omberg551, Choon Kiat Ong552, Stephan Ossowski52,53,74, German Ott553, B. F. Francis Ouellette76,554, Christine P’ng6, Marta Paczkowska6, Salvatore Paiella115, Chawalit Pairojkul523, Marina Pajic170, Qiang Pan-Hammarström56,555, Elli Papaemmanuil49, Irene Papatheodorou59, Nagarajan Paramasivam43,47, Ji Wan Park385, Joong-Won Park556, Keunchil Park557,558, Kiejung Park559, Peter J. Park264,266, Joel S. Parker518, Simon L. Parsons124, Harvey Pass560, Danielle Pasternack272, Alessandro Pastore276, Ann-Marie Patch209,311, Iris Pauporté251, Antonio Pea115, John V. Pearson209,311, Chandra Sekhar Pedamallu8,14,82, Jakob Skou Pedersen73,75, Paolo Pederzoli115, Martin Peifer270, Nathan A. Pennell561, Charles M. Perou129,518, Marc D. Perry76,77, Gloria M. Petersen562, Myron Peto22, Nicholas Petrelli563, Robert Petryszak59, Stefan M. Pfister426,465,564, Mark Phillips424, Oriol Pich298,299, Hilda A. Pickett478, Todd D. Pihl565, Nischalan Pillay566, Sarah Pinder567, Mark Pinese170, Andreia V. Pinho568, Esa Pitkänen60, Xavier Pivot569, Elena Piñeiro-Yáñez95, Laura Planko533, Christoph Plass345, Paz Polak8,14,15, Tirso Pons570, Irinel Popescu571, Olga Potapova572, Aparna Prasad52, Shaun R. Preston573, Manuel Prinz47, Antonia L. Pritchard311, Stephenie D. Prokopec6, Elena Provenzano574, Xose S. Puente499, Sonia Puig176, Montserrat Puiggròs57, Sergio Pulido-Tamayo505,506, Gulietta M. Pupo246, Colin A. Purdie575, Michael C. Quinn209,311, Raquel Rabionet52,53,576, Janet S. Rader577, Bernhard Radlwimmer397, Petar Radovic284, Benjamin Raeder60, Keiran M. Raine49, Manasa Ramakrishna49, Kamna Ramakrishnan49, Suresh Ramalingam578, Benjamin J. Raphael579, W. Kimryn Rathmell580, Tobias Rausch60, Guido Reifenberger475, Jüri Reimand6,44, Jorge Reis-Filho348, Victor Reuter348, Iker Reyes-Salazar298, Matthew A. Reyna579, Sheila M. Reynolds36, Esther Rheinbay8,14,72, Yasser Riazalhosseini189, Andrea L. Richardson323, Julia Richter111,128, Matthew Ringel581, Markus Ringnér181, Yasushi Rino582, Karsten Rippe405, Jeffrey Roach583, Lewis R. Roberts349, Nicola D. Roberts49, Steven A. Roberts584, A. Gordon Robertson30, Alan J. Robertson113, Javier Bartolomé Rodriguez57, Bernardo Rodriguez-Martin104,105,106, F. Germán Rodríguez-González83,332, Michael H. A. Roehrl44,123,148,234,585,586, Marius Rohde587, Hirofumi Rokutan440, Gilles Romieu588, Ilse Rooman170, Tom Roques262, Daniel Rosebrock8, Mara Rosenberg8,72, Philip C. Rosenstiel589, Andreas Rosenwald590, Edward W. Rowe221,591, Romina Royo57, Steven G. Rozen179,180,592, Yulia Rubanova17,127, Mark A. Rubin423,593,594,595,596, Carlota Rubio-Perez298,299,597, Vasilisa A. Rudneva60, Borislav C. Rusev177, Andrea Ruzzenente598, Gunnar Rätsch276,277,278,279,280,430, Radhakrishnan Sabarinathan298,299,599, Veronica Y. Sabelnykova6, Sara Sadeghi30, S. Cenk Sahinalp62,78,79, Natalie Saini357, Mihoko Saito-Adachi440, Gordon Saksena8, Adriana Salcedo6, Roberto Salgado600, Leonidas Salichos5,19, Richard Sallari8, Charles Saller601, Roberto Salvia115, Michelle Sam272, Jaswinder S. Samra115,602, Francisco Sanchez-Vega114,121, Chris Sander276,603,604, Grant Sanders134, Rajiv Sarin605, Iman Sarrafi62,78, Aya Sasaki-Oku184, Torill Sauer489, Guido Sauter520, Robyn P. M. Saw211, Maria Scardoni167, Christopher J. Scarlett170,606, Aldo Scarpa177, Ghislaine Scelo194, Dirk Schadendorf68,607, Jacqueline E. Schein30, Markus B. Schilhabel589, Matthias Schlesner47,80, Thorsten Schlomm84,608, Heather K. Schmidt1 , Sarah-Jane Schramm246, Stefan Schreiber609, Nikolaus Schultz121, Steven E. Schumacher8,323, Roland F. Schwarz59,403,405,610, Richard A. Scolyer211,448,602, David Scott428, Ralph Scully611, Raja Seethala612, Ayellet V. Segre8,613, Iris Selander260, Colin A. Semple434, Yasin Senbabaoglu276, Subhajit Sengupta614, Elisabetta Sereni115, Stefano Serra585, Dennis C. Sgroi72, Mark Shackleton103, Nimish C. Shah352, Sagedeh Shahabi234, Catherine A. Shang329, Ping Shang211, Ofer Shapira8,323, Troy Shelton271, Ciyue Shen603,604, Hui Shen615, Rebecca Shepherd49, Ruian Shi490, Yan Shi134, Yu-Jia Shiah6, Tatsuhiro Shibata118,616, Juliann Shih8,82, Eigo Shimizu375, Kiyo Shimizu617, Seung Jun Shin618, Yuichi Shiraishi375, Tal Shmaya285, Ilya Shmulevich36, Solomon I. Shorser6, Charles Short59, Raunak Shrestha62, Suyash S. Shringarpure217, Craig Shriver619, Shimin Shuai6,126, Nikos Sidiropoulos83, Reiner Siebert112,620, Anieta M. Sieuwerts332, Lina Sieverling205,237, Sabina Signoretti202,621, Katarzyna O. Sikora177, Michele Simbolo138, Ronald Simon520, Janae V. Simons134, Jared T. Simpson6,17, Peter T. Simpson473, Samuel Singer115,458, Nasa Sinnott-Armstrong8,217, Payal Sipahimalani30, Tara J. Skelly390, Marcel Smid332, Jaclyn Smith622, Karen Smith-McCune514, Nicholas D. Socci276, Heidi J. Sofia27, Matthew G. Soloway134, Lei Song240, Anil K. Sood623,624,625, Sharmila Sothi626, Christos Sotiriou244, Cameron M. Soulette37, Paul N. Span627, Paul T. Spellman22, Nicola Sperandio177, Andrew J. Spillane211, Oliver Spiro8, Jonathan Spring628, Johan Staaf181, Peter F. Stadler163,164,165, Peter Staib629, Stefan G. Stark277,279,618,630, Lucy Stebbings49, Ólafur Andri Stefánsson631, Oliver Stegle59,60,632, Lincoln D. Stein6,126, Alasdair Stenhouse633, Chip Stewart8, Stephan Stilgenbauer634, Miranda D. Stobbe52,61, Michael R. Stratton49, Jonathan R. Stretch211, Adam J. Struck31, Joshua M. Stuart24,37, Henk G. Stunnenberg396,635, Hong Su56,396, Xiaoping Su99, Ren X. Sun6, Stephanie Sungalee60, Hana Susak52,53, Akihiro Suzuki89,636, Fred Sweep637, Monika Szczepanowski128, Holger Sültmann67,638, Takashi Yugawa617, Angela Tam30, David Tamborero298,299, Benita Kiat Tee Tan639, Donghui Tan518, Patrick Tan180,532,592,640, Hiroko Tanaka375, Hirokazu Taniguchi616, Tomas J. Tanskanen641, Maxime Tarabichi49,290, Roy Tarnuzzer220, Patrick Tarpey642, Morgan L. Taschuk152, Kenji Tatsuno89, Simon Tavaré223,643, Darrin F. Taylor113, Amaro Taylor-Weiner8, Jon W. Teague49, Bin Tean Teh180,592,640,644,645, Varsha Tembe246, Javier Temes104,105, Kevin Thai76, Sarah P. Thayer393, Nina Thiessen30, Gilles Thomas646, Sarah Thomas221, Alan Thompson221, Alastair M. Thompson633, John F. Thompson211, R. Houston Thompson647, Heather Thorne103, Leigh B. Thorne176, Adrian Thorogood424, Grace Tiao8, Nebojsa Tijanic284, Lee E. Timms272, Roberto Tirabosco648, Marta Tojo106, Stefania Tommasi649, Christopher W. Toon170, Umut H. Toprak48,650, David Torrents57,81, Giampaolo Tortora651,652, Jörg Tost653, Yasushi Totoki118, David Townend654, Nadia Traficante103, Isabelle Treilleux655,656, Jean-Rémi Trotta61, Lorenz H. P. Trümper469, Ming Tsao124,539, Tatsuhiko Tsunoda183,657,658,659, Jose M. C. Tubio104,105,106, Olga Tucker660, Richard Turkington661, Daniel J. Turner513, Andrew Tutt323, Masaki Ueno376, Naoto T. Ueno662, Christopher Umbricht151,213,663, Husen M. Umer305,664, Timothy J. Underwood665, Lara Urban59,60, Tomoko Urushidate616, Tetsuo Ushiku339, Liis Uusküla-Reimand666,667, Alfonso Valencia57,81, David J. Van Den Berg166, Steven Van Laere307, Peter Van Loo290,291, Erwin G. Van Meir668, Gert G. Van den Eynden307, Theodorus Van der Kwast123, Naveen Vasudev137, Miguel Vazquez57,669, Ravikiran Vedururu267, Umadevi Veluvolu518, Shankar Vembu490,670, Lieven P. C. Verbeke506,671, Peter Vermeulen307, Clare Verrill351,672, Alain Viari177, David Vicente57, Caterina Vicentini177, K. Vijay Raghavan365, Juris Viksna673, Ricardo E. Vilain674, Izar Villasante57, Anne Vincent-Salomon635, Tapio Visakorpi190, Douglas Voet8, Paresh Vyas311,351, Ignacio Vázquez-García49,86,675,676, Nick M. Waddell209, Nicola Waddell209,311, Claes Wadelius677, Lina Wadi6, Rabea Wagener111,112, Jeremiah A. Wala8,14,82, Jian Wang56, Jiayin Wang1,40,66, Linghua Wang12, Qi Wang465, Wenyi Wang21, Yumeng Wang21, Zhining Wang220, Paul M. Waring523, Hans-Jörg Warnatz483, Jonathan Warrell5,19, Anne Y. Warren352,678, Sebastian M. Waszak60, David C. Wedge49,294,679, Dieter Weichenhan345, Paul Weinberger680, John N. Weinstein38, Joachim Weischenfeldt60,83,84, Daniel J. Weisenberger166, Ian Welch681, Michael C. Wendl1,10,11, Johannes Werner47,85, Justin P. Whalley61,682, David A. Wheeler12,13, Hayley C. Whitaker117, Dennis Wigle683, Matthew D. Wilkerson518, Ashley Williams244, James S. Wilmott211, Gavin W. Wilson6,148, Julie M. Wilson148, Richard K. Wilson1,684, Boris Winterhoff685, Jeffrey A. Wintersinger17,127,384, Maciej Wiznerowicz686,687, Stephan Wolf688, Bernice H. Wong689, Tina Wong1,30, Winghing Wong690, Youngchoon Woo250, Scott Wood209,311, Bradly G. Wouters44, Adam J. Wright6, Derek W. Wright133,691, Mark H. Wright217, Chin-Lee Wu72, Dai-Ying Wu285, Guanming Wu692, Jianmin Wu170, Kui Wu56,396, Yang Wu179,180, Zhenggang Wu64, Liu Xi12, Tian Xia693, Qian Xiang76, Xiao Xiao66, Rui Xing497, Heng Xiong56,396, Qinying Xu209,311, Yanxun Xu694, Hong Xue64, Shinichi Yachida118,695, Sergei Yakneen60, Rui Yamaguchi375, Takafumi N. Yamaguchi6, Masakazu Yamamoto120, Shogo Yamamoto89, Hiroki Yamaue376, Fan Yang490, Huanming Yang56, Jean Y. Yang696, Liming Yang220, Lixing Yang697, Shanlin Yang306, Tsun-Po Yang270, Yang Yang369, Xiaotong Yao408,698, Marie-Laure Yaspo483, Lucy Yates49, Christina Yau156, Chen Ye56,396, Kai Ye40,41, Venkata D. Yellapantula20,86, Christopher J. Yoon249, Sung-Soo Yoon463, Fouad Yousif6, Jun Yu699, Kaixian Yu700, Willie Yu701, Yingyan Yu702, Ke Yuan223,510,703, Yuan Yuan21, Denis Yuen6, Takashi Yugawa617, Christina K. Yung76, Olga Zaikova704, Jorge Zamora49,104,105,106, Marc Zapatka397, Jean C. Zenklusen220, Thorsten Zenz67, Nikolajs Zeps705,706, Cheng-Zhong Zhang8,707, Fan Zhang381, Hailei Zhang8, Hongwei Zhang494, Hongxin Zhang121, Jiashan Zhang220, Jing Zhang5, Junjun Zhang76, Xiuqing Zhang56, Xuanping Zhang66,369, Yan Zhang5,708,709, Zemin Zhang381,710, Zhongming Zhao711, Liangtao Zheng381, Xiuqing Zheng381, Wanding Zhou615, Yong Zhou56, Bin Zhu240, Hongtu Zhu700,712, Jingchun Zhu24, Shida Zhu56,396, Lihua Zou713, Xueqing Zou49, Anna deFazio246,247,714, Nicholas van As221, Carolien H. M. van Deurzen715, Marc J. van de Vijver523, L. van’t Veer716 & Christian von Mering433,717, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

The incidence of human papillomavirus–positive (HPV(+)) head and neck squamous cell carcinoma (HNSCC) has surpassed that of cervical cancer and is projected to increase rapidly until 2060. The coevolution of HPV with transforming epithelial cells leads to the shutdown of host immune detection. Targeting proximal viral nucleic acid–sensing machinery is an evolutionarily conserved strategy among viruses to enable immune evasion. However, E7 from the dominant HPV subtype 16 in HNSCC shares low homology with HPV18 E7, which was shown to inhibit the STING DNA-sensing pathway. The mechanisms by which HPV16 suppresses STING remain unknown. Recently, we characterized the role of the STING/type I interferon (IFN-I) pathway in maintaining immunogenicity of HNSCC in mouse models. Here we extended those findings into the clinical domain using tissue microarrays and machine learning–enhanced profiling of STING signatures with immune subsets. We additionally showed that HPV16 E7 uses mechanisms distinct from those used by HPV18 E7 to antagonize the STING pathway. We identified NLRX1 as a critical intermediary partner to facilitate HPV16 E7–potentiated STING turnover. The depletion of NLRX1 resulted in significantly improved IFN-I–dependent T cell infiltration profiles and tumor control. Overall, we discovered a unique HPV16 viral strategy to thwart host innate immune detection that can be further exploited to restore cancer immunogenicity.

Objective: Our objective is to describe the development of the New Jersey Safety and Health Outcomes (NJ-SHO) data warehouse, a unique and comprehensive data source that integrates various state-level administrative databases in New Jersey to enable the field of traffic safety to address critical, high-priority research questions.Methods: We have obtained full identifiable data from the following statewide administrative databases for the state of New Jersey: (1) driver licensing database; (2) Administration Office of the Courts data on traffic-related citations; (3) police-reported crash database; (4) birth certificate data; (5) death certificate data; and (6) hospital discharge data as well as (7) childhood electronic records from New Jersey residents who were patients of the Children's Hospital of Philadelphia pediatric health care network and (8) census tract-level indicators. We undertook an iterative process to develop a linkage algorithm in LinkSolv 9.0 software using records for individuals born in select birth years (1987 and 1988) and subsequently execute the linkage for the entire study period (2004-2017). Several metrics were used to evaluate the quality of the linkage process.Results: We identified a total of 62,685,619 records and 19,247,363 distinct individuals; 10,352,998 of these individuals had more than one record brought together during the linkage process. Our evaluation of this linkage suggests that the linkage was of high quality.Conclusions: The resulting NJ-SHO data warehouse will be one of the most comprehensive and rich traffic safety data warehouses to date. The warehouse has already been utilized for numerous studies and will be fully primed to support a host of rigorous studies, both in and beyond the field of traffic safety.

With a newly World Health Organization (WHO)–prequalified typhoid conjugate vaccine (TCV), Gavi funding for eligible countries, and a WHO policy recommendation for TCV use, now is the time for countries to introduce TCVs as part of an integrated typhoid control program, particularly in light of the increasing burden of antimicrobial resistance. Continued vaccine development efforts will lead to secure supply of low-cost vaccines, and ongoing vaccine studies will provide critical vaccine performance data and inform optimal deployment strategies, in both routine use and in outbreak settings. TCV programs should include thoughtful communication planning and community engagement to counter vaccine hesitancy.

IntroductionCervical cancer disproportionately burdens low-income and middle-income countries (LMICs) such as Guatemala. Self-collection testing for human papillomavirus (HPV) has been suggested as a form of cervical cancer screening to facilitate access in LMICs. This study assessed and compared the acceptability of self-collection HPV testing in two rural, indigenous and ethnically distinct communities in Guatemala: Santiago Atitlán, Sololá and Livingston, Izabal.MethodsAll participants, women between the ages of 18 and 60, completed a questionnaire. Eligible participants were also asked to self-collect a vaginal sample and complete a questionnaire regarding comfort and acceptability. Self-collected samples were tested for high-risk HPV using the real-time PCR Hybribio kit.ResultsIn the indigenous community of Santiago Atitlán, of 438 age-eligible participants, 94% completed self-collection. Of those, 81% found it comfortable and 98% were willing to use it as a form of screening. In the multiethnic (Afro-Caribbean, indigenous) community of Livingston, of 322 age-eligible participants, 53% chose to self-collect. Among those who took the test, 83% found it comfortable and 95% were willing to use it as a form of screening. In Livingston, literacy (can read and/or write vs cannot read or write) was higher in women who chose to self-collect (prevalence ratio 2.25; 95% CI 1.38 to 3.68). Ethnicity, history of screening and reproductive history were not associated with willingness to self-collect in Livingston. Women in Santiago reported less prior use of healthcare than women in Livingston. Overall, 19% (106/549) of samples tested positive for high-risk HPV.ConclusionAmong women willing to self-collect in rural and indigenous communities in Guatemala, self-collection for HPV testing is highly acceptable. However, willingness to try self-collection might vary across communities and settings. Women from a community that used less healthcare were more likely to choose self-collection. Further research is necessary to determine what factors influence a woman’s choice to self-collect.

The Typhoid Surveillance in Africa Program (TSAP) and the Severe Typhoid Fever in Africa (SETA) program have refined our understanding of age and geographic distribution of typhoid fever and other invasive salmonelloses in Africa and will help inform future typhoid control strategies, namely, introduction of typhoid conjugate vaccines.

Background Laryngeal squamous cell carcinomas (LSCCs) have a high risk of recurrence and poor prognosis. Patient-derived cancer cell lines remain important preclinical models for advancement of new therapeutic strategies, and comprehensive characterization of these models is vital in the precision medicine era. Methods We performed exome and transcriptome sequencing as well as copy number analysis of a panel of LSCC-derived cell lines that were established at the University of Michigan and are used in laboratories worldwide. Results We observed a complex array of alterations consistent with those reported in The Cancer Genome Atlas head and neck squamous cell carcinoma project, including aberrations in PIK3CA, EGFR, CDKN2A, TP53, and NOTCH family and FAT1 genes. A detailed analysis of FAT family genes and associated pathways showed disruptions to these genes in most cell lines. Conclusions The molecular profiles we have generated indicate that as a whole, this panel recapitulates the molecular diversity observed in patients and will serve as useful guides in selecting cell lines for preclinical modeling.

Experimental error, especially through genotype misclassification and pedigree errors, negatively affects breeding decisions by creating ‘noise’ that compounds the genetic signals for selection. Unlike genotype-by-environment interactions, for which different methods have been proposed to address, the effect of ‘noise’ due to pedigree errors and misclassification has not received much attention in most crops. We used two case studies in sweetpotato, based on data from the International Potato Center’s breeding program to estimate the level of phenotype misclassification and pedigree error and to demonstrate the consequences of such errors when combining phenotypes with the respective genotypes. In the first case study, 27.7% phenotype misclassification was observed when moving genotypes from a diversity panel throughin-vitro, screenhouse and field trialing. Additionally, 22.7% pedigree error was observed from misclassification between and within families. The second case study involving multi-environment testing of a full-sib population and quantitative trait loci (QTL) mapping showed reduced genetic correlations among pairs of environments in mega-environments with higher phenotype misclassification errors when compared to the mega-environments with lower phenotype misclassification errors. Additionally, no QTL could be identified in the low genetic correlation mega-environments. Simulation analysis indicated that phenotype misclassification was more detrimental to QTL detection when compared to missingness in data. The current information is important to inform current and future breeding activities involving genomic-assisted breeding decisions in sweetpotato, and to facilitate putting in place improved workflows that minimize phenotype misclassification and pedigree errors.

Expansins comprise a superfamily of plant cell wall loosening proteins that can be divided into four individual families (EXPA, EXPB, EXLA and EXLB). Aside from inferred roles in a variety of plant growth and developmental traits, little is known regarding the function of specific expansin clades, for which there are at least 16 in flowering plants (angiosperms); however, there is evidence to suggest that some expansins have cell-specific functions, in root hair and pollen tube development, for example. Recently, two duckweed genomes have been sequenced (Spirodela polyrhiza strains 7498 and 9509), revealing significantly reduced superfamily sizes. We hypothesized that there would be a correlation between expansin loss and morphological reductions seen among highly adapted aquatic species. In order to provide an answer to this question, we characterized the expansin superfamilies of the greater duckweed Spirodela, the marine eelgrass Zostera marina and the bladderwort Utricularia gibba. We discovered rampant expansin gene and clade loss among the three, including a complete absence of the EXLB family and EXPA-VII. The most convincing correlation between morphological reduction and expansin loss was seen for Utricularia and Spirodela, which both lack root hairs and the root hair expansin clade EXPA-X. Contrary to the pattern observed in other species, four Utricularia expansins failed to branch within any clade, suggesting that they may be the result of neofunctionalization. Last, an expansin clade previously discovered only in eudicots was identified in Spirodela, allowing us to conclude that the last common ancestor of monocots and eudicots contained a minimum of 17 expansins.

Genome-wide association studies (GWAS) of alcohol dependence (AD) have reliably identified variation within alcohol metabolizing genes (eg, ADH1B) but have inconsistently located other signals, which may be partially attributable to symptom heterogeneity underlying the disorder. We conducted GWAS of DSM-IV AD (primary analysis), DSM-IV AD criterion count (secondary analysis), and individual dependence criteria (tertiary analysis) among 7418 (1121 families) European American (EA) individuals from the Collaborative Study on the Genetics of Alcoholism (COGA). Trans-ancestral meta-analyses combined these results with data from 3175 (585 families) African-American (AA) individuals from COGA. In the EA GWAS, three loci were genome-wide significant: rs1229984 in ADH1B for AD criterion count (P = 4.16E-11) and Desire to cut drinking (P = 1.21E-11); rs188227250 (chromosome 8, Drinking more than intended, P = 6.72E-09); rs1912461 (chromosome 15, Time spent drinking, P = 1.77E-08). In the trans-ancestral meta-analysis, rs1229984 was associated with multiple phenotypes and two additional loci were genome-wide significant: rs61826952 (chromosome 1, DSM-IV AD, P = 8.42E-11); rs7597960 (chromosome 2, Time spent drinking, P = 1.22E-08). Associations with rs1229984 and rs18822750 were replicated in independent datasets. Polygenic risk scores derived from the EA GWAS of AD predicted AD in two EA datasets (P

Background The human papillomavirus (HPV) is the most common sexually transmitted infection and is linked to several types of cancer. HPV vaccination uptake in the U.S. is relatively low, despite the vaccine’s high efficacy. Some parents of adolescents have concerns that vaccination will encourage sexual behavior and therefore choose not to vaccinate. Previous studies investigating vaccination and sexual behavior have included only young women and girls. Methods The objective of this study is to assess associations between HPV-vaccination and sexual behavior in a college-age cohort of both men and women. We analyzed questionnaire data collected from the Michigan HPV and Oropharyngeal Cancer Study, a cohort study designed to investigate HPV infection and its association with sexual behavior (data collected 2015–17, Ann Arbor, MI). Here, we consider vaccination status, sexual behavior, and substance use among 241 college-aged men and women. Logistic, Poisson, and Cox regression were used to determine the relationship between probability of sexual debut, number of sexual partners, and HPV vaccination status at baseline as well as between age at sexual debut and vaccination status at debut. Results HPV vaccination status was not significantly associated with an increased likelihood of sexual debut (odds ratio: 0.80 (95% CI: 0.41–1.58), decreased age of sexual debut (hazard ratio: 0.81 (95% CI: 0.65–1.00), nor an increased number of sexual partners (per year sexually active; incidence rate ratio: 1.27 (95% CI: 0.86–1.87)) in this cohort, after controlling for age, race, sex, and substance use. Instead, race or alcohol use were independent predictors of sexual behavior. Conclusions Concerns about the influence of the HPV vaccine on sexual behavior are likely unfounded for both men and women. These results can aid in increasing vaccine acceptability, inform and strengthen physician recommendations, and ultimately reduce the burden of HPV and HPV-related cancers in the U.S. Electronic supplementary material The online version of this article (10.1186/s12889-019-7134-1) contains supplementary material, which is available to authorized users.

OBJECTIVES:To compare monthly rates of specific types of crashes, violations, and license suspensions over the first years of licensure for drivers with and without attention-deficit/hyperactivity disorder (ADHD).METHODS:We identified patients of New Jersey primary care locations of the Children’s Hospital of Philadelphia who were born in 1987–1997, were New Jersey residents, had their last primary care visit at age ≥12 years, and acquired a driver’s license (N = 14 936). Electronic health records were linked to New Jersey’s licensing, crash, and violation databases. ADHD diagnosis was based on International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes. We calculated monthly per-driver rates of crashes (at fault, alcohol related, nighttime, and with peers), violations, and suspensions. Adjusted rate ratios were estimated by using repeated-measures Poisson regression.RESULTS:Crash rates were higher for drivers with ADHD regardless of licensing age and, in particular, during the first month of licensure (adjusted rate ratio: 1.62 [95% confidence interval: 1.18−2.23]). They also experienced higher rates of specific crash types: their 4-year rate of alcohol-related crashes was 2.1 times that of drivers without ADHD. Finally, drivers with ADHD had higher rates of moving violations (for speeding, seat belt nonuse, and electronic equipment use) and suspensions. In the first year of driving, the rate of alcohol and/or drug violations was 3.6 times higher for adolescents with ADHD.CONCLUSIONS:Adolescents with ADHD are at particularly high crash risk in their initial months of licensure, and engagement in preventable risky driving behaviors may contribute to this elevated risk. Comprehensive preventive approaches that extend beyond current recommendations are critically needed.