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Abstract Background Oligometastatic disease (OD) is usually defined arbitrarily as a condition in which there are ≤ 5 metastases. Given limited disease, it is expected that patients with OD should have better prognosis compared to other metastatic patients and that they can potentially benefit from metastasis-directed therapy (MDT). In this study, we attempted to redefine OD based upon objective evidence that fulfill these assumptions. Methods Chest CTSs of 773 patients with 15,947 lung metastases originating from ten malignancy types were evaluated. The number and largest diameter of each metastasis was recorded. Metastatic cluster was defined as a cluster of two or more metastases with diameter difference ≤ 1 mm. The prognostic power of seven statistical models on overall survival (OS) was analyzed. Findings Both the number of metastases and metastatic clusters had a highly significant impact on OS (p

Background Linear and parallel are the two leading models of metastatic progression. In this study we propose a simple way to differentiate between them. While the linear model predicts accumulation of genetic and epigenetic alterations within the primary tumor by founder cells before spreading as waves of metastases, the parallel model suggests preclinical distribution of less advanced disseminated tumor cells with independent selection and expansion at the ectopic sites. Due to identical clonal origin and time of dispatching, linear metastases are expected to have comparable diameters in any specific organ while parallel metastases are expected to appear in variable sizes. Methods and findings Retrospective revision of chest CT of oncological patients with lung metastases was performed. Metastasis number and largest diameters were recorded. The sum number of metastases with a similar diameter (c) and those without (i) was counted and the linear/parallel ratio (LPR) was calculated for each patient using the formula (∑c-∑i)/(∑c+∑i). A LPR ratio of 1 implies pure linear progression pattern and -1 pure parallel. 12,887 metastases were measured in 503 patients with nine malignancy types. The median LPR of the entire group was 0.71 (IQR 0.14–0.93). In carcinomas of the pancreas, prostate, and thyroid the median LPR was 1. Median LPRs were 0.91, 0.65, 0.60, 0.58, 0.50 and 0.43 in renal cell carcinomas, melanomas, colorectal, breast, bladder, and sarcomas, respectively. Conclusions Metastatic spread of thyroid, pancreas, and prostate tumors is almost exclusively by a linear route. The spread of kidney, melanoma, colorectal, breast, bladder and sarcoma is both linear and parallel with increasing dominance of the parallel route in this order. These findings can explain and predict the clinical and genomic features of these tumors and can potentially be used for evaluation of metastatic origin in the individual patient.

Current research and policy literature indicate an increase in remediation courses nationwide (Tierney & Garcia, 2011; Parsad & Lewis, 2003). However, the most critical theme in research suggests variability and possible inaccuracies in remedial and developmental education data (Kirst, 2007; Venezia, Kirst & Antonio, 2004). In particular, there is little current research surrounding the actual costs of remedial education (Kirst, 2007; The Institute for Higher Education Policy, 1998). The significance of inaccurate remediation costs means that education leaders and policy makers could perceivably be making decisions based upon poor data (Attewell, Lavin, Domain & Levey, 2006). In addition, research indicates that education finance and budget policy is affected by increases in remediation (Jenkins & Boswell, 2002). Jenkins and Boswell (2002) reported that universities are not given adequate financial incentive to provide remedial education. This may prove true especially for community colleges since they bear the burden of providing most remedial education in postsecondary education (Boylan & Saxon, 1999). Overall, in order to formulate sound remediation cost policy, education leaders and policy makers need reliable information.

Abstract Background Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank. Results Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation. Conclusion We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single “optimal” pubertal growth pattern.

Abstract Mechanochemical reactions at the sliding interface between a single-crystalline silicon (Si) wafer and a silica (SiO2) microsphere were studied in three environmental conditions: humid air, potassium chloride (KCl) solution, and KCl solution with an applied voltage. Compared to that from humid air, mechanochemical material removal from the silicon surface increased substantially in the KCl-immersed condition, and further increased when electrochemistry was introduced into the tribological system. By measuring the load dependence of the material removal rate and analyzing the results using a mechanically assisted Arrhenius-type kinetic model, the activation energy (E a) and the mechanical energy (E m), by which this energy is reduced by mechanical activation, were compared qualitatively under different environmental conditions. In the KCl-immersed condition, mechanochemistry may decrease the required effective energy of reactions (E eff = E a − E m) and promote material removal mainly through improved catalysis of the mechanochemical reactions facilitated by greater availability of water molecules compared to the humid air condition. Thus, the effectiveness of the mechanochemistry is improved. In the electrochemical condition, electrochemically-accelerated oxidation of the silicon surface was confirmed by the X-ray photoelectron spectroscopy (XPS) characterization. The results strongly suggest that electrochemistry further stimulates mechanochemical reactions primarily by increasing the initial energy state of the surface via the facilitated formation of interfacial bonding bridges, i.e., a surface oxidation/hydroxylation process.

Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

In the pre-sliding friction regime, interfaces partially stick and partially slip. The pre-slip is thought to be locally initiated at regions of the interface where the ratio of shear stress to normal stress exceeds a critical value. The displacements involved in pre-slip can be limited to the nanoscale, especially for stiff interfaces. Furthermore, little is known experimentally about the interplay between surface topography, pre-sliding behavior and wear. In this work, we introduce a pre-sliding tribometer that enables the study of how the pre-sliding friction at various types of ball-on-flat interfaces evolves as a function of wear. Polytetrafluoroethylene-on-silicon (PTFE-on-Si) pre-sliding measurements covering interfacial displacements up to 50 nm, conducted with the new instrument, show good agreement with Mindlin theory predictions, without adjustable parameters.

Friction originates at the area of real contact which depends on the (changing) surface topography. Observing and measuring the area of real contact at multi-asperity interfaces is difficult, making it challenging to quantitatively study the interplay between the frictional force and surface topography. In this paper, we systematically manipulate surface topography and use a fluorescence microscopy-based contact visualization technique to reveal this interplay. We demonstrate good agreement between elastoplastic boundary element method contact calculations and experimental visualization of the area of real contact. While the area of real contact and thus contact pressure could be varied by a factor of 4 through control of the surface topography, this had only a modest effect on the coefficient of friction (CoF). We do find a small but systematic increase in the proportionality constant between frictional force and normal force (CoF) with decreasing surface roughness. The observation that smoother surfaces have a greater CoF is due to capillary adhesion between the two surfaces. We quantitatively model this behavior using a simple capillary adhesion model without adjustable parameters. Our results provide quantitative insights into the interplay between contact mechanics, friction, and capillary adhesion. A predictive understanding of this interplay is essential to demanding applications such as precision positioning.

[This corrects the article DOI: 10.1371/journal.pgen.1007813.].

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health.

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.