Although the current first‐line medicine, temozolomide (TMZ), promotes patient survival, drug resistance develops easily. Thus, it is important to investigate novel therapeutic reagents to solidify the treatment effect. β‐Elemene (bELE) is a compound from a Chinese herb whose anticancer effect has been shown in various types of cancer. However, its role in the inhibition of glioma stem‐like cells (GSLCs) has not yet been reported. We studied both the in vitro and the in vivo inhibitory effect of bELE and TMZ in GSLCs and parental cells and their combined effects. The molecular mechanisms were also investigated. We also optimized the delivery methods of bELE. We found that bELE selectively inhibits the proliferation and sphere formation of GSLCs, other than parental glioma cells, and TMZ exerts its effects on parental cells instead of GSLCs. The in vivo data confirmed that the combination of bELE and TMZ worked better in the xenografts of GSLCs, mimicking the situation of tumorigenesis of human cancer. Notch1 was downregulated with bELE treatment. Our data also demonstrated that the continuous administration of bELE produces an ideal effect to control tumor progression. Our findings have demonstrated, for the first time, that bELE could compensate for TMZ to kill both GSLCs and nonstem‐like cancer cells, probably improving the prognosis of glioma patients tremendously. Notch1 might be a downstream target of bELE. Therefore, our data shed light on improving the outcomes of glioma patients by combining bELE and TMZ. S The findings of the present study have demonstrated, for the first time, that β‐elemene (bELE) compensates for temozolomide (TMZ) to kill both glioma stem‐like cells (GSLCs) and nonstem‐like cancer cells, probably improving the prognosis of glioma patients tremendously. Notch1 might be a downstream target of bELE. Therefore, these data shed light on improving the outcomes of glioma patients by combining bELE and TMZ.Glioma is the most frequent primary central nervous system tumor, accounting for almost one half of all brain tumors. According to the guidelines of the World Health Organization, gliomas are classified into four types (grade I–IV). Grade IV glioma, also called glioblastoma (GBM), is the most malignant glioma, and the patient 5‐year survival rate is only 9.8% at best . With thThe current strategy for GBM is surgery, followed by concurrent ionizing radiation and chemotherapy. Temozolomide (TMZ), an oral alkylating agent, has been applied for newly diagnosed and recurrent malignant gliomas as the standard chemotherapeutic reagent. Stupp et al.  and HegiCurcuma wenyujin and includes three subtypes: β‐, γ‐, and δ‐elemene. β‐Elemene (bELE) is the main active component functioning in the anticancer process in various cancers [Elemene is an oil mixture extracted from the Chinese traditional medicine  cancers , 18. In  cancers . A prote cancers . The com cancers . In a mo cancers . In glio cancers , 24, 25.In the present study, we investigated the role of bELE in the proliferation and tumorigenesis of GSLCs in vitro and in vivo and the involved mechanisms. Our data demonstrated that bELE inhibited the proliferation of GSLCs selectively, without inhibition of non‐GSLCs. Therefore, our study has shed light on promoting the prognosis of glioma patients by the combination treatment of bELE and TMZ to eliminate both GSLCs and non‐GSLCs simultaneously.http://www.thermofisher.com) supplemented with 10% fetal bovine serum  and 1% penicillin‐streptomycin (Thermo Fisher Scientific Life Sciences) at 37°C in a humidified incubator with 5% CO2. Following the protocols from previous reports [2.We used the six following GBM cell lines for the study: U87, U373, SHG‐44, SKMG‐4 (with unmethylated MGMT promoter), U138, and T98G (with methylated MGMT promoter). U87, U373, SKMG‐4, and T98G were obtained from American Type Culture Collection and maintained at Sun Yat‐sen University Cancer Center (SYSUCC). U138 was a gift from Dr. Shing‐shun Tony To at the Department of Health Technology and Informatics, The Hong Kong Polytechnic University. SHG‐44 was a gift from Professor Ziwei Du at the Department of Neurosurgery, Soochow University School of Medical  . All cel reports , 28, U87http://www.sigmaaldrich.com) and bELE  were stored at −80°C. Before treatment, stock solutions were diluted into the indicated final concentrations in the culture medium. Control cells received an equivalent amount of DMSO. The parental cells  and induced GSLCs  were seeded into 96‐well plates in triplicate at a density of 2,000 and 10,000 cells per well, respectively. The next day, the cells were treated with bELE at a concentration gradient of 0, 2.5, 5, 10, 20, and 40 μg/ml; TMZ at a concentration gradient of 0, 125, 250, 500, 1,000, and 2,000 μM; or bELE (2.5 μg/ml) combined with TMZ at a concentration gradient of 0, 125, 250, 500, 1,000, and 2,000 μM. Cell viability was measured at 72 hours after treatment using the Cell Counting Kit 8  according to the manufacturer’s instructions. The optical density was measured at 450 nm using a spectrophotometric microplate reader (Thermo Fisher Scientific Life Sciences). Five replicate wells were designed for each cell sample.Chemotherapeutic sensitivity was detected following the protocols described previously . TMZ  was calculated using the data from the CCK8 assay , 31. Thehttp://www.bdbiosciences.com) at a density of 400 cells per well and then cultured with the GSLC culture medium. Four treatment groups were used. Group 1 (control group) was treated with solvent medium; group 2 was treated with bELE at 2.5, 5, 10, and 20 µg/ml; group 3 was treated with TMZ at 250, 500, 1,000, and 2,000 μM; and group 4 was treated with bELE, 2.5 μg/ml, combined with TMZ at 250, 500, 1,000, and 2,000 μM. The cells were treated for 72 hours, and then the medium was replaced with fresh DMEM. Spheres were then observed after culture for another 11 days using an inverted phase‐contrast microscope.To study the effect of bELE on sphere formation ability, U87/GSLCs were plated in low‐attached 12‐well plates  on ice [g for 15 minutes at 4°C, and the supernatants were collected. Equal amounts of protein (20 μg) were fractionated using SDS‐polyacrylamide gel electrophoresis and transferred onto nitrocellulose membranes . The membranes were blocked in 5% bovine serum albumin in Tris‐buffered saline with Tween‐20 at room temperature for 1 hour and probed with primary antibodies at 4°C overnight. The next day, membranes were incubated with secondary antibodies for 1 hour at room temperature and visualized using enhanced chemiluminescence (EMD Millipore). The following antibodies were used: rabbit anti‐Notch 1 , rabbit anti‐β‐catenin , rabbit anti‐Gli1 (Abcam), rabbit anti‐cyclin E1 (Abcam), mouse anti‐β‐actin , and goat anti‐mouse and mouse anti‐rabbit .Cells were washed twice with phosphate‐buffered saline and lysed in RIPA buffer containing 1 mM phenylmethylsulfonyl fluoride  on ice . The celhttp://www.gdmlac.com). The ethics review board of SYSUCC approved the present study. The mice were divided into eight groups with six mice in each group: four groups for the U87 xenograft model and four for the U87GSLC xenograft model. The cells were inoculated subcutaneously into the right armpit of the mice with U87 (1 × 107) or U87/GSLC (1 × 107), respectively. When the tumor volume reached approximately 3 mm3, the treatments were initiated in four groups for both U87 and U87/GSLC xenograft models: normal saline (0.2 ml), bELE (50 mg/kg), TMZ (5 mg/kg), and the combination of bELE (50 mg/kg) and TMZ (5 mg/kg) by intraperitoneal injection for 7 consecutive days. The tumor volumes were observed every 3 days using Vernier calipers. The tumor volumes were calculated using the formula , as previously reported [Four‐week‐old nude mice  were purchased from the Laboratory Medical Animal Center of Guangdong  were inoculated subcutaneously into the right armpit. When the tumor reached approximately 3 mm3, the mice were treated with bELE as follows: (a) delivery only during the first week, (b) delivery during the first and third weeks, and (c) delivery for 4 weeks continuously. The tumor volumes were measured every 3 days using Vernier calipers. The tumor volumes were calculated using the formula , as previously reported [To optimize the administration of bELE, we set up the xenograft mouse models and delivered bELE for three different intervals. The mice were first divided into three groups , and U87 cells .Differences between groups were calculated using Student’s p < .01 or p < .001; p < .05, p < .01, and p > .05, respectively; p < .05, p < .01, or p < .001; To check for differences in the treatment response of glioma parental cells and induced GSLCs to bELE and TMZ, we exposed both cell types to TMZ and bELE. As the currently routinely applied reagent, TMZ was tested first. U87, U373, SHG‐44, T98G, SKMG‐4, and U138 cells and the induced GSLCs were treated with TMZ in a concentration series. TMZ inhibited the proliferation of all five lines in a dose‐dependent manner. In U87, SHG‐44, and SKMG‐4 cells, the parental cells were more sensitive to TMZ than were the induced U87/GSLCs, SHG‐44/GSLCs, and SKMG‐4/GSLCs . TMZ also attenuated the colony formation ability of U87/GSLCs, although the effect was not as strong as that of bELE . The inhibition ability of TMZ was further enhanced when supplied with bELE . We also found that the colony numbers were significantly fewer when treated with the combination of TMZ and bELE than when treated with TMZ alone  and TMZ combination. We detected the expression of Notch1, Gli1, and β‐catenin. Notch1 expression in U87/GSLCs, but not in U87 cells, was dramatically reduced in a dose‐dependent manner with bELE treatment , left. S3 by 6 days after injection, and the U87 cells had grown to that volume after 9 days. The data also reflect the strong tumorigenesis ability of GSLCs. TMZ and/or bELE were then injected intraperitoneally into tumor‐bearing mice. The tumor size was measured every 3 days for 36 days after the initiation of drug administration , bELE is also extracted from plants and has a known molecular structure. bELE was found to be a major component of leaf oil from ra regia , 37, 38.ra regia , 38. Liura regia .0/G1 phase by bELE through the upregulation of phosphorylated MAPK levels [It has been found that bELE is a potent anticancer agent against multiple cancers in extensive clinical trials and experimental research in vivo and in vitro. Wu et al. found that bELE increased apoptosis and caused S phase arrest of several hepatocellular carcinoma cell lines in a dose‐dependent manner . In lungK levels . FurtherK levels . ThroughK levels .−/low) and sphere formation ability of the breast cancer cell line MCF‐7/ADM and reduces the drug‐resistant protein breast cancer resistance protein and P‐glycoprotein. Accompanied by downregulation of CD133/ABCG2 and upregulation of glial fibrillary acidic protein, bELE was shown to decrease the formation of spheres and inhibit the proliferation of glioma stem cells both in vitro and in vivo [+) in a dose‐dependent manner and attenuates angiogenesis [+ gastric cancer stem‐like cells proliferate faster than their CD44− counterparts and express a higher level of Notch1 [In addition, bELE plays a role in cancer stem cell modulation. Dong et al.  found th in vivo . Moreoveogenesis . Notch1 f Notch1 . The NotIn human non‐small cell lung cancer, bELE inhibits cell proliferation through the downregulation of DNA methyltransferase 1 (DNMT1), and forced expression of DNMT1 reverses the inhibition effect . AnotherIn our study, bELE inhibited the proliferation of GSLCs efficiently in vitro and in vivo. Although data indicated that the Notch1 and Wnt/β‐catenin pathways are involved in the process, the detailed mechanisms remain unclear. In addition, how to push forward the clinical application of bELE to treat glioma patients is another challenge. Our group has launched a phase III clinical trial through ClinicalTrials.gov (a service of the U.S. NIH), titled “a study on β‐elemene as maintain treatment for complete remission patients of newly diagnosed malignant gliomas following standard treatment”  on December 2015. This study will help determine whether bELE could be applied as a maintenance strategy for patients with complete remission of newly diagnosed malignant gliomas after standard treatment.In the present study, we demonstrated that bELE selectively attenuates proliferation, sphere formation, and the in vivo tumorigenesis of GSLC through the downregulation of Notch1. Based on the theory of cancer stem cells, GSLCs are responsible for the maintenance and recurrence of glioma. Thus, our data are significant for future clinical applications in which bELE facilitates TMZ to eliminate both GSLCs and nonstem cells to consolidate the therapeutic effect. Our findings also shed light on improving the prognosis of glioma patients in the near future.H.‐b.F., H.‐r.J., X.M., Y.‐y.Z., F.‐r.C., and Y.Q.: performance of experiments; J.W.: collection and assembly of data, data analysis and interpretation, manuscript writing, financial support; K.S., C.‐c.G., Q.‐y.Y., and Z.‐p.Z.: administrative support; Z.‐p.C.: conception and design, financial support, final approval of manuscript.The authors indicated no potential conflicts of interest.Supporting InformationClick here for additional data file.


JIA) comprises 7 heterogeneous categories of chronic childhood arthritides. Approximately 5% of children with JIA have rheumatoid factor (RF)–positive arthritis, which phenotypically resembles adult rheumatoid arthritis (RA). Our objective was to compare and contrast the genetics of RF‐positive polyarticular JIA with those of RA and selected other JIA categories, to more fully understand the pathophysiologic relationships of inflammatory arthropathies.Juvenile idiopathic arthritis (RF‐positive polyarticular JIA (n = 340) and controls  were genotyped using the Immunochip array. Single‐nucleotide polymorphisms were tested for association using a logistic regression model adjusting for admixture proportions. We calculated weighted genetic risk scores (wGRS) of reported RA and JIA risk loci, and we compared the ability of these wGRS to predict RF‐positive polyarticular JIA.Patients with HLA region was strongly associated with RF‐positive polyarticular JIA (P = 5.51 × 10−31). Nineteen of 44 RA risk loci and 6 of 27 oligoarticular/RF‐negative polyarticular JIA risk loci were associated with RF‐positive polyarticular JIA (P < 0.05). The RA wGRS predicted RF‐positive polyarticular JIA (area under the curve [AUC] 0.71) better than did the oligoarticular/RF‐negative polyarticular JIA wGRS (AUC 0.59). The genetic profile of patients with RF‐positive polyarticular JIA was more similar to that of RA patients with age at onset 16–29 years than to that of RA patients with age at onset ≥70 years.As expected, the RF‐positive polyarticular JIA is genetically more similar to adult RA than to the most common JIA categories and thus appears to be a childhood‐onset presentation of autoantibody‐positive RA. These findings suggest common disease mechanisms, which could lead to novel therapeutic targets and shared treatment strategies. Arthritis & Rheumatology web site at http://onlinelibrary.wiley.com/doi/10.1002/art.40443/abstract. The Immunochip is a custom microarray designed by the Immunochip Consortium to fine‐map autoimmune disease–associated loci from 11 autoimmune phenotypes including adult rheumatoid arthritis (RA) Juvenile idiopathic arthritis (JIA) is a heterogeneous collection of chronic arthropathies with distinct clinical and laboratory features, but all manifest with arthritis in one or more joints and present before the 16th birthday. The International League of Associations for Rheumatology (ILAR) criteria for JIA recognize 7 JIA categories Approximately 5% of children with JIA demonstrate the presence of RF and antibodies directed against citrullinated peptides, such as anti–cyclic citrullinated peptide (anti‐CCP) antibodies, which are characteristic biomarkers observed in adults with seropositive RA. These children and young people tend to present at a later age at onset than those with oligoarticular or RF‐negative polyarticular JIA, and often tend to have erosive disease with worse long‐term outcomes. Thus, children with RF‐positive polyarticular JIA phenotypically resemble adults with RA and could be considered to have childhood‐onset RA. In contrast to the robust genetic studies that include large cohorts of patients with RA and oligoarticular/RF‐negative polyarticular JIA, studies of children with RF‐positive polyarticular JIA have been limited to small‐scale candidate gene studies. These include investigations of association with the shared epitope encoding HLA–DRB1 alleles as well as several candidate loci associated with RA To progress beyond this limitation in cohort size and also advance the understanding of RF‐positive polyarticular JIA, we have used the Immunochip to compare and contrast the genetics of RF‐positive polyarticular JIA to other categories of JIA and RA. This may provide a greater understanding of the genetic architecture of RF‐positive polyarticular JIA.http://onlinelibrary.wiley.com/doi/10.1002/art.40443/abstract.All JIA patients had a diagnosis of polyarticular JIA according to the ILAR classification criteria http://onlinelibrary.wiley.com/doi/10.1002/art.40443/abstract).For comparison with groups of RA patients with different ages at onset, RA patients in the UK who had been genotyped on the Immunochip array were available from a cohort described previously To test for SNP association with RF‐positive polyarticular JIA, a logistic regression model was computed using Caucasian admixture proportions calculated by the program ADMIXTURE P < 5 × 10−8) associated with RA as reported by Eyre et al 2 > 0.8) were available for rs13397 at IRAK1, rs2240336 at PADI4, rs39984 at GIN1, or rs10683701 at KIF5A; therefore, there were 42 SNPs in the wGRS. The HLA region was captured through the HLA–DRB1 tag SNP rs660895 The 45 non‐HLA risk loci associated with RA using the Immunochip P < 1 × 10−6) associated with oligoarticular/RF‐negative polyarticular JIA as reported by Hinks et al IL2RA, rs2266959 at UBE2L3, and rs7069750 at FAS, so the final number of SNPs in the wGRS was 25. The HLA association was captured using the top SNP (rs7775055) in the region.The JIA wGRS analysis started with the 28 SNPs (including HLA)  a score based on the expectation from the allele frequency and assuming Hardy‐Weinberg equilibrium. Logistic regression was used to compare each wGRS between patients and controls. In addition, receiver operating characteristic (ROC) curves defined by the sensitivity and specificity of each wGRS were generated, and the area under the curve (AUC) was calculated. The GRS analysis did not include the imputed genotype data. Analysis was performed using Stata software, version 13.1 (StataCorp). We tested whether there was a difference between the areas under the 2 ROC curves using DeLong's method as implemented in SAS software (SAS Institute).After quality control there were 340 patients with RF‐positive polyarticular JIA (mean ± SD age at onset 10.2 ± 4.2 years) and 14,412 controls (Table P = 5.51 × 10−31), a SNP in strong LD (r2 = 0.88) with the HLA–DRB1 SNP reported in RA . These SNPs are tagging the HLA–DRB1*0401 classic allele P = 0.08).Despite the modest sample size, association with the HLA region was identified, with the most significant association at rs3129769, near HLA–DRB1 (P < 0.05) (see Supplementary Table http://onlinelibrary.wiley.com/doi/10.1002/art.40443/abstract). Of the 44 SNPs  most strongly associated with RA P < 0.05) (see Supplementary Table http://onlinelibrary.wiley.com/doi/10.1002/art.40443/abstract).The most significantly associated loci identified in the oligoarticular/RF‐negative polyarticular JIA and RA Immunochip study were assessed for association with RF‐positive polyarticular JIA. Of the 27 non‐HLA SNPs most strongly associated with oligoarticular/RF‐negative polyarticular JIA P = 8.26 × 10−33)   . Imputed SNP results were included when the imputed SNP had a better imputed P value than the most significant directly genotyped SNP in the region (see Supplementary Table http://onlinelibrary.wiley.com/doi/10.1002/art.40443/abstract). Supplementary Table 2 > 0.8) with some previous evidence for association with RA No region outside the HLA region reached genome‐wide significance; however, 13 regions had suggestive association . The results of the wGRS analysis generated from the top RA‐associated loci predicted RF‐positive polyarticular JIA case–control status better than did the wGRS generated from the oligoarticular/RF‐negative polyarticular JIA top hits.P < 0.05). There appears to be less overlap with the oligoarticular/RF‐negative polyarticular JIA loci since only 6 of the 27 oligoarticular/RF‐negative polyarticular JIA SNPs show evidence for association with RF‐positive polyarticular JIA. Formal testing for a difference in the 2 proportions using the likelihood ratio test yielded suggestive but not statistically significant results (P = 0.0676).We investigated whether any of the previously associated RA loci 2 = 0.88) with the most associated HLA SNP in RA. We have previously reported the HLA associations for all the categories of JIA As might be expected, the most significant association was within the HLA region, and the SNP is in strong LD r2 = 0.8 with thP < 1 × 10−4, which will need validation in an independent cohort to confirm. The strongest non‐HLA association for RF‐positive polyarticular JIA was rs9610687, which lies upstream of the RAC2 gene. Mutations within RAC2 are associated with neutrophil immunodeficiency syndrome. Polymorphisms within the IL2RB gene, close to RAC2, have previously been associated with oligoarticular/RF‐negative polyarticular JIA IL2RB was not significantly associated with RF‐positive polyarticular JIA (P = 0.70). In RA the most associated SNP (rs3218251) in this region again lies in the IL2RB gene, and this SNP is not in LD with the oligoarticular/RF‐negative polyarticular JIA–associated SNP.Other than the HLA region, we were unable to identify novel loci meeting genome‐wide levels of significance. This may be expected, as despite being the largest genetic study to date for RF‐positive polyarticular JIA, our study is still relatively underpowered to detect odds ratios of ~1.1–1.2, as are often observed in autoimmune diseases. We have identified 13 regions showing association at a significance level of Although this study has numerous important findings, there are some important limitations. First, the RA patients included in the wGRS analysis had a mixture of both seronegative and seropositive disease , potentially diluting or masking effect sizes. Second, the UK RA patients and controls included in these analyses are part of the RA Immunochip study by Eyre et al The current ILAR classification criteria We have now shown that RF‐positive polyarticular JIA is genetically more similar to adult RA than to the oligoarticular/RF‐negative polyarticular JIA categories. Demonstrating that RF‐positive polyarticular JIA genetically appears to be a childhood‐onset presentation of RA supports further investigation of this phenotype along with the factors influencing an early‐onset presentation. Broadly, our results suggest that genetic profiling might enhance our ability to classify and understand the different phenotypes of inflammatory arthritis. Our results also provide a rationale for studying both diseases together and for translating therapeutic trials of successful pharmacologic agents from adult RA to RF‐positive polyarticular JIA and vice versa.All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Prahalad had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.Hinks, Marion, Cobb, Langefeld, Thompson, Thomson, Prahalad.Hinks, Marion, Cobb, Comeau, Sudman, Ainsworth, Bowes, Becker, Bohnsack, Haas, Lovell, Mellins, Nelson, Nordal, Punaro, Reed, Rose, Rosenberg, Rygg, Smith, Stevens, Videm, Wallace, Wedderburn, Yarwood, Yeung, Langefeld, Thompson, Thomson, Prahalad.Hinks, Marion, Cobb, Comeau, Sudman, Ainsworth, Bowes, Langefeld, Thompson, Thomson, Prahalad. Click here for additional data file.


This study measured part of the in-hive pesticide exposome by analyzing residues from live in-hive bees, stored pollen, and wax in migratory colonies over time and compared exposure to colony health. We summarized the pesticide burden using three different additive methods: (1) the hazard quotient (HQ), an estimate of pesticide exposure risk, (2) the total number of pesticide residues, and (3) the number of relevant residues. Despite being simplistic, these models attempt to summarize potential risk from multiple contaminations in real-world contexts. Colonies performing pollination services were subject to increased pesticide exposure compared to honey-production and holding yards. We found clear links between an increase in the total number of products in wax and colony mortality. In particular, we found that fungicides with particular modes of action increased disproportionally in wax within colonies that died. The occurrence of queen events, a significant risk factor for colony health and productivity, was positively associated with all three proxies of pesticide exposure. While our exposome summation models do not fully capture the complexities of pesticide exposure, they nonetheless help elucidate their risks to colony health. Implementing and improving such models can help identify potential pesticide risks, permitting preventative actions to improve pollinator health. Apis mellifera) provide critical pollination services valued at over $200 billion worldwide56789101213152, and return with accumulated contaminants to the hive. A single colony, therefore, can act as a terrestrial sentinel, expanding radially into the surrounding environment to collect food resources and acquiring contaminants including pesticide-laced pollen that is then stored in the colony as “beebread.”The impact of pesticides on pollinators remains an ongoing concern, especially as new research highlights the complex web of pesticide residues entering the internal hive environment and colony food stream1Varroa destructor)910212324Commercial beekeepers have increasingly struggled with high rates of colony morbidity and mortality, in part because of increased pressure of the parasitic varroa mite , which are devoid of synergistic, cumulative, and sublethal effects on the colony. Chronic toxicity tests over 10 days are suggested, but the standardized tests for larvae and adult bees are still in development by the Organization for Economic Co-operation (OECD). Relatively little is known about the effects of multiple pesticide residues, their synergistic interactions, and the effects on different honey bee life stages or wild pollinators. Like most other insects, honey bees rely on detoxification enzymes, primarily the cytochrome P450s, to metabolize synthetic chemicals. The honey bee genomeUnderstanding and quantifying the risks of pesticides entering the hive environment is difficult and expensive29Bees are evolutionarily adapted to feed on pollen3637In a previous study50. All three models attempt to illustrate a simplified risk to bees from consuming contaminated food or living in a pesticide-rich environment. Using these three models, we describe the pesticide in-hive exposome experienced by bees, through contact with wax comb and consumption of beebread, in colonies during an entire beekeeping season as they were moved into different crops. Using the number of products and HQ model that encompasses contact and oral risk from multiple residues detected in different hive matrixes, we elucidate relationships among individual pesticides, categories of pesticides , pesticide MOA, and colony morbidity and mortality. This approach is an attempt to model the role that real-world pesticide exposure may have on colony health using admittedly oversimplified, additive models. While this approach makes certain assumptions and simplifications (see below), it is a first step toward evaluating the impacts of multiple residues in the colony environment on colony health.In this study, samples from various colony matrices  were collected for pesticide analysis. These samples were collected to document any changes in pesticide burden in colonies over time. Limited resources for pesticide analysis permitted us to only explore possible relationships between colony mortality and pesticide loads in beebread over time and to determine the impacts of pesticides in wax at the beginning and end of the study between colonies that varied in colony mortality and queen events. We summarize the overall pesticide burden using three different models: a Hazard Quotient (HQ)et al.et al.et al.A study was conducted to monitor the morbidity and mortality of honey bee colonies owned by three different migratory beekeepers moving colonies up the east coast of the United StatesBees: Samples of adult bees (~200) were collected from brood frames from individual colonies at each inspection period and placed in 50 ml tubes and stored on dry ice, then transferred to freezers (−80 °C) until processed. We analyzed a subset of these bees (n = 38), collected at the start of the study. However, because of the low rate of residue detection in these bees and limited resources, we did not analyze any other adult bee samples.Wax: a ~5 g sample of comb (wax) was collected from individual hives at each inspection. Whenever possible, samples were collected from an area of used brood comb that did not contain any beebread, honey, or brood. These samples were collected and stored on dry ice, then transferred into a freezer for long-term storage. Because OP2 managed their hives at the apiary level  rather than at the individual colony level (which does not), no wax samples from their operation were analyzed. Because of limited funds, we could only analyze a subset (n = 108) of all wax samples; we analyzed the wax samples of the first inspection period and a sample collected from the last time that colony was inspected while still alive.Beebread: Disposable wooden stir sticks were used, one per colony, to remove beebread from several cells of comb. Removed beebread was placed in 1.5 ml Eppendorf tubes and immediately stored on dry ice, then transferred to a freezer (−20 °C) until processing. Because of limited resources for sample processing and limited beebread availability, beebread samples collected on the same date were retroactively pooled within an individual operation by taking approximately equals amounts of beebread from 3 or 4 colonies that ended up dying at the same time or surviving the entire beekeeping season, resulting in 24 pooled samples monitored over the course of the study . For specific questions, relevant subsets of these 147 samples were used to analyze impacts of pesticide exposure on survival, crop, season, and colony type. For example, to determine the impact of the early pesticide exposure from March–June on established colonies that lived or died throughout the entire beekeeping season encompasses 34 relevant samples.et al.Bees, wax, and pooled beebread samples weighing approximately 3 grams were measured into 50 ml plastic centrifuge tubes and sent on ice to the USDA-AMS National Science Laboratory in Gastonia NC for multi-pesticide residue analysis. Samples were extracted and analyzed for 171 pesticides and associated degradates at the part per billion (ppb) level as described in Mullin et al.50 in μg/bee for each residue in a given sample. This provides an estimate of the frequency that 50% lethal dose equivalents for bees are present in the food, wax, or in bees themselves. Actual exposure from beebread depends on individual consumption rates. Residue detections are measured in μg/kg (ppb) divided by an LD50 in μg/bee. LD50 values (http://cfpub.epa.gov/ecotox/); the University of Hertfordshire Pesticide Properties DataBase ; and some additional primary literature394050, the LD50 of the respective parent compound was used in the HQ calculation. Assuming that a bee consumes at least its average body weight (~100 mg) in pollen during development36th—as does the European Food Safety Authority for setting a limit of concern for bee residues50 daily, which adds up to 10% of their LD50 during the 10 day nursing phase. Arguably, a more robust HQ calculation would use LD10, or no observable adverse effects levels (NOAEL) instead of LD50’s. However, these numbers are not available for all products detectedWe calculated the number of products found in each matrix and subsequently calculated the Hazard Quotient (HQ) for each matrix in each sample. The HQ was calculated using a similar method described in Stoner 0 values  represenBoth the number of products and HQ models are additive and over simplified models to quantify pesticide exposure. For instance, they do not account for synergistic or antagonistic effects of co-occurring pesticides, and they assume that pesticides do not degrade and are not detoxified when consumed. These assumptions are unrealistic, as some products are known to synergize and honey bees detoxify foreign substances4450, which corresponds to 0.5% during the 10-day nursing phase. We quantified the number of different products in a given matrix  as well as the number of products that contributed at least 50 points to a given samples total HQ score (50+). We considered a pesticide level as “elevated” if the total HQ in a sample was 1,000 or more. This level, assuming the pesticide accumulates over 10 days without degradation, is equivalent to a nurse bee consuming 1.0% of an LD50 per day or 10% of her LD50 during her nursing phase. Detected products were grouped by category; as either insecticides, fungicides, herbicides or varroacides, the latter being residues of products that beekeepers use to control Varroa. Further, for insecticides, varroacides, and fungicides, we categorized individual products by their mode of action (MOA)  see . The samAnalyses: HQ score, total residues and relevant residues (50+) were calculated as described above in Microsoft Excel . Statistical analysis was conducted using JMP® Pro 11.0.0 . To determine significance, we used a generalized linear model (GLM) with a Poisson or binomial distribution as necessary, and corrected for overdispersion if appropriate. Relevant model effects such as collection date, crop, environment, or operation were included, as described in the results and figures. Chi square results from these analyses are reported. In all figures, mean results are reported with S.E. indicated. Post-hoc analysis of significant differences are indicated by different letters (α = 0.05).General HQ, total residues, and 50+ pesticide residues: For beebread residues in individual operations, we determined differences in HQbbread and total number of pesticide residues by crop and sampling period. For wax, we determined HQwax, total pesticides, and 50+ residues with inspection period and colony survival as model effects. We then analyzed if the number of products with a given MOA had an effect on HQbbread or HQwax or varied by environment. Colony Survival: For wax samples, we examined the impact of total and 50+ residues on colony survival for each MOA. Further, we examined colony survival, including HQwax, sampling time, and colony type as model effects. Since there was a significant effect of colony type, we repeated the analysis for established colonies and packages separately. For bee bread samples, we analyzed HQbbread for the early beekeeping season (March through June) with collection date and survival as model effects. We repeated the analysis with colony type as an additional model effect, with similar results except that colony type (established vs. package) was also highly significant. We thus analyzed the HQbbread of packages separately for the summer beekeeping season (May-August) with collection date and survival as model effects. To determine if colonies that died during the beekeeping season differed in their HQpesticide categories we included collection date as a model effect. Due to numerous samples contaminated with chlorothalonil, we analyzed if HQbbread score contributed by chlorothalonil varied by colony survival. Imminent death: For bee bread samples, imminent death was defined as one or more of the colonies in a pool perishing within one month. We analyzed the impact of HQbbread, total and 50+ residues with collection date and imminent death as effects. To determine if HQfung varied with imminent death during the summer season (May-Aug) we included collection date and imminent death as model effects. We repeated the analysis, substituting crop for collection date. Queen events: For wax samples, we analyzed the impact of queen events, with collection order (first/last) and HQwax, total or 50+ residues as model effects. We repeated the analysis to determine if number of products with a given MOA had an impact on queen events.A total of 93 different pesticide residues were identified in the analyzed samples . A totalbee , primarily a result of contamination with fipronil detected at 9.9 ppb. With its low LD50, fipronil contributed 1,222 points to the HQbee. All other samples had an HQbee < 50.Bees: The maximum number of pesticides found in a single bee sample was 4. Five samples were pesticide-free, while all other bee samples (n = 33) had at least one product detected. Few pesticide residues were detected per bee sample (1.39 ± 0.15), with the main contributors being beekeeper-applied varroacides, coumaphos and fluvalinate, which were detected in 23.7% and 81.6% of samples, respectively . Across bbread score and were considered “relevant” . Insecticides were most commonly detected , followed by varroacides , fungicides , and lastly herbicides . The average HQbbread for all samples was 445 ± 62.8. The total HQbbread score was greater than 1,000 in 15% of samples (n = 22). Insecticides were the largest contributor to the total HQbbread score (85.9%) across all samples, followed by varroacides (10.6%), fungicides (3.5%), and herbicides that contributed only minimally (<0.01%). Fungicides were very common, appearing in 70.1% of all beebread samples (n = 103). In the current study, fungicide residues were detected 77 times at over 100 ppb (bbread score were found at more than 100 ppb. The majority (91.2%) contributed less than 50 points to the total HQbbread, generally because fungicides have relatively high LD50s that ranged from 25-2,430 ppb. Multiple fungicides in a single sample occurred frequently, with 44.9% (n = 66) of all samples tested having two or more fungicide residues  had at least one product detected. On average, each pooled sample had 7.22 ± 0.30 different pesticides or metabolites. Across all pooled beebread samples, 1,061 pesticides and their metabolites were detected see ; howeverelevant” . Sevente 100 ppb , over 2.residues .bbread scores were significantly elevated when more than two insecticides from group 1  occurred in the beebread sample . Samples with zero or one group 1 insecticide had a mean HQbbread = 139.7 ± 28.7, while samples with 2 + products had a mean HQbbread = 810.1 ± 119.5, ranging from 579.1 ± 140.7 to 895.1 ± 6167.4 depending on the number of products detected. One commonly detected varroacide, the organophosphate coumaphos, has a group 1 insecticide MOA; this product contributed 11.6% to the average HQbbread score of 228.9 contributed by this MOA group. Group 2 insecticides  had a similar impact , with HQbbread scores significantly lower when no group 2 insecticides were detected in beebread (mean HQbbread = 280.9 ± 71.3) compared to when group 2 products were present . No varroacides had a group 2 MOA.When grouped by their MOA, we found that HQwax and were considered relevant , regardless of colony survival . Total HQwax was above 1,000 for 77.98% (n = 85) and above 5,000 for 7.34% (n = 8) of wax samples. Residues that contributed more than 1,000 points to the HQwax score included the varroacides coumaphos, fluvalinate, and the amitraz breakdown product DMPF, as well as the insecticides deltamethrin, fenpropathrin, fipronil, and permethrin (see wax threshold (largely on account of its high LD50), the fungicide chlorothalonil was present in 68.8% of wax samples (n = 75) with a mean concentration of 1,635.0 ± 756.9 ppb, making it the most abundant wax contaminate after varroacides  were found in six wax samples; two were contaminated with imidacloprid at 2.4 and 13.6 ppb, contributing 60.3 and 341.7 points to the HQwax; four were contaminated with thiacloprid at 1.9 to 7.8 ppb, contributing 0.08 to 0.31 points to the HQwax. The mean HQwax score across all samples was 2,155 ± 192.4. The majority of this score came from the presence of varroacides (71.1%), followed by insecticides (28.3%) and fungicides (0.5%), while herbicides contributed minimally (<0.01%). Several MOA groups significantly increased the HQ when multiple products of that same MOA were detected. All wax samples had at least two group 1 acetylcholinesterase inhibiting products with a maximum of seven detected in a single sample. The HQwax increased significantly when more than two products were detected , raising the mean HQwax from 1,539.6 ± 168.9 to 2,416.4 ± 258.5. All wax samples had at least one product of MOA insecticide group 3  with up to 12 different products with this MOA detected in a single sample. In wax, 14.8% samples (n = 16) were free of MOA insecticide group 19  residues and had a mean HQwax = 1,335.8 ± 174.8, while 33.3% (n = 36) had one group 19 residue HQwax = 1,940.8 ± 272.3 and the remaining 51.9% had (n = 56) two detected with a HQwax = 2,545.6 ± 318.8. Seven wax samples were positive for an insecticide residue with an unknown MOA; these few samples had significantly elevated HQwax scores . Fungicide MOA did not influence the total HQwax score except for MOA fungicide group M  . When present, samples with group M fungicides had significantly elevated HQwax = 2,502.7 ± 267.7 compared to samples where they were absent HQwax = 1,429.2 ± 135.6.Wax: The maximum number of residues detected in a single wax sample was 39, with a mean of 10.17 ± 0.47 per sample. Of the 108 samples analyzed, all had at least three products detected. Altogether, 1,108 pesticide residues were detected, of which 32.3% (n = 358) contributed at least 50 points to the HQrelevant . Total Hhrin see . While nides see . In one bbread was not significantly different among operations but the number of total pesticide residues in beebread samples varied significantly  as did the total number of “relevant” pesticides χ2 = 44.89, df = 2, n = 147, p < 0.0001).The participating commercial beekeepers moved their colonies among three different foraging environments: crop pollination, honey production, and holding yards. Only beebread samples were regularly collected and analyzed across all sampling time points in this study. The average total HQbbread and number of residues detected occurred when colonies were in or had just been moved out of certain specialty crops, especially citrus, apple, cranberry, and cucumber . Of the beebread samples that had total HQbbread score greater than 1,000 , the majority were collected in March (n = 9) and May (n = 9) during pollination of apple or lowbush blueberry.Overall, the total HQbbread was subdivided into the four categories of insecticides, fungicides, herbicides, and varroacides, the trends of elevated risks during pollination were consistent across all pesticide groups except for varroacides (Varroa control.When the HQroacides . Varroacbbread > 50 (HQbbread fungicide range = 88.3–239.6), all were collected during blueberry (n = 9) and cranberry (n = 4) pollination. Total fungicide residues measured in ppb per sample for in-hive beebread and wax are frequently high , but were rarely detected in live in-house bees at the start of the season .Fungicide prevalence was low outside of pollination events and was completely absent in 54% and 44% of samples taken from colonies in holding yards and honey production yards, respectively. Only 9% of beebread samples taken from colonies during pollination events were absent of fungicides. These few fungicide-free beebread samples occurred early in the season during citrus and apple pollination. Of the 8.8% of analyzed samples that had a fungicide with an HQEnvironment strongly influenced the number of products of a specific MOA found in a beebread sample . For inswax at the start of the study did not differ among operations , although the total number of relevant pesticides varied between the wax of the two operations sampled , with significantly higher relevant residues in OP3 (mean = 4.22 ± 0.54) compared to OP1, both when the packages in OP1 were included (mean = 2.44 ± 0.17) or excluded (mean = 2.82 ± 0.27).HQet al.As previously reported in vanEngelsdorp 2 = 0.11, df = 1, n = 108, p = 0.736). This analysis included both established colonies and colonies that were installed as packages on drawn comb that had previously had only honey stored in it . Colonies established from packages had significantly fewer total and relevant residues in their wax  when compared to established colonies  at the first sampling period . Because of the differences in pesticide residues in packages and established colonies, we excluded packages from the analysis for colony survival. At the start of the study, HQwax was not significantly different between colonies that lived or died . However, established colonies that died during the season had significantly more total pesticide residues in their wax over all sampling periods than did colonies that lived . Increased exposure followed a similar pattern for relevant pesticides (Died: mean = 3.70 ± 0.27 vs. Survived: 3.0 ± 0.20), but was not significant statistically .The mean number of residues detected in brood nest wax samples at the start of the study did not differ between colonies that survived versus those that died over the course of the study . This group is exclusively comprised of the breakdown products of the varroacide amitraz, which likely reflects the use of this product for the control of Varroa over the course of the season. In colonies that died, the total number of group G fungicides (sterol biosynthesis in membranes) in wax increased between first and last sampling periods . A similar increase was seen in fungicides with group M (multi-site contact activity) MOA .Additionally, we analyzed the total pesticide residues by grouping them according to their MOA. The number of products that are MOA group 19 insecticides (octopamine receptor antagonists) increased from the first sampling period to the last sampling period, irrespective of whether colonies lived or died . The HQbbread varied significantly by collection date, with the highest scores detected in March . Insecticides were the greatest contributor to the HQbbread for these colonies, contributing 940.9 ± 157.6 points to colonies that died during the season compared to 448.5 ± 151.0 points to colonies that survived the entire beekeeping season. We separately analyzed the new colonies (packages) installed on drawn honey comb and determined that an elevated HQbbread was not associated with colony losses in these newly established packages early in the beekeeping season from March-June . However, later in the season (from June through September), packages showed a similar pattern of elevated HQbbread in colonies that perished , suggesting that any advantage to providing colonies with “clean” comb only slightly delayed possible links with pesticide buildup and colony mortality. The HQbbread scores in packages did not vary by collection date . We also examined if colonies that survived differed in their HQpesticide category compared to colonies that perished, and only fungicides were significant. Since fungicides are only detected during the active beekeeping season, we focused on samples collected between March-September. During this time period, HQbbread fung was lower in colonies that lived compared to levels in those that perished . Collection date had no significant influence on the model .Total HQbbread was not predictive of imminent (within ~30 days) colony loss . In contrast, the total number of products found in beebread trended toward being elevated in colonies that perished , while the number of relevant products contributing at least 50 points to the total HQbbread was significantly elevated in colonies that died before the next sampling period during the beekeeping season from April through September . Imminent colony death also varied by collection date , but there was no significant interaction of collection date and HQbbread .An elevated HQbbread, fungicides were significantly elevated during the summer season from May-August in colonies that died within ~30 days of sampling . The fungicide HQbbread varied significantly by collection date during that same period . No fungicides were detected during citrus pollination. Samples from citrus were thus excluded when determining how HQbbread Fung varied by crop. HQbbread Fung was elevated during blueberry and cranberry pollination compared to other crops , but only elevated fungicide scores associated with blueberry pollination were linked with imminent colony loss .Despite their low overall contribution to the HQ2 = 3.44, df = 1, n = 139, p = 0.063). A similar pattern was seen with insecticides categorized as an unknown MOA , which were somewhat elevated in colonies that died (mean = 0.14 ± 0.07) compared to those that lived (mean = 0.05 ± 0.02) to the next sampling period.To determine if the MOA of particular pesticides was implicated in imminent colony loss, we examined if the total number of products with the same MOA was elevated in beebread in colonies that perished before the next sampling period. No particular mode of action was significantly associated with imminent colony loss, though there was a trend toward elevated residues of insecticide MOA group 18 insecticides (ecdysone receptor agonists) in colonies that died (mean = 0.25 ± 0.08) compared to colonies that lived (mean = 0.10 ± 0.03) .The insecticide fipronil was found in one adult bee sample (see above), in one beebread sample, and in one wax sample. These samples came from different colonies, and in all cases the colony from which the sample was collected died before the next sampling event. The presence of the fungicide chlorothalonil in pooled beebread samples was common and often exorbitant. Of the 147 beebread samples analyzed, 87 had detectable levels of chlorothalonil, with 19.5% (n = 17) contaminated at more than 1,000 ppb and 13.8% (n = 12) at more than 10,000 ppb. In beebread, the maximum chlorothalonil residue was 26,600 ppb, eight times higher than the maximum varroacide residue detected . Colonies that perished during the beekeeping year had significantly higher HQet al.wax, total pesticide residues, and relevant residues) were higher in the wax of colonies that experienced queen events . All colonies with HQwax scores above 6,500 (n = 5) experienced queen events during the season. When analyzed by MOA, the number of group 3 insecticides (sodium channel modulators) was significantly higher in the wax of colonies that experienced a queen event than colonies that remained queenright .


Moreover, ≥3 CTCs/3.2 ml  and ≥5 CTCs/3.2 ml  were predictive of shorter overall survival. CTC assessment may help identify patients with ampullary cancer who are at high risk of an unfavorable outcome.Circulating tumor cells (CTCs) are an important topic of investigation for both basic and clinical cancer research. In this prospective study, we evaluated the clinical role of CTCs in ampullary cancer. We analyzed blood samples from 62 consecutively diagnosed patients with ampullary adenocarcinoma and 24 healthy controls for their CTC content. Combined data from immunostaining of CD45, 4′,6‐diamidino‐2‐phenylindole (DAPI), and fluorescence in situ hybridization with a chromosome 8 centromere (CEP8) probe were used to identify CTCs; cells that were CD45‐/DAPI+/CEP8>2 were considered CTCs. The Cox proportional hazards model was used to assess the relationship between CTCs, clinical characteristics, and patient outcomes. We detected ≥2 CTCs/3.2 ml whole blood in 43 of 62 patients (69.4%), as well as ≥5 CTCs/3.2 ml in 16 of these patients (25.8%). A CTC cutoff value of 2 cells/3.2 ml achieved 69.4% sensitivity and 95.8% specificity as a diagnostic tool; CTCs were associated with tumor burden. CTC levels ≥3/3.2 ml ,  AJCCAmerican Joint Committee on CancerCEAcarcinoembryonic antigenCEP8chromosome 8 centromereCIconfidence intervalCTCcirculating tumor cellDAPI4',6‐diamidino‐2‐phenylindoleDFSdisease‐free survivalEpCAMepithelial cell adhesion moleculesFISHfluorescence in situ hybridizationHCChepatocellular carcinomaHRhazard ratioISETisolation by size of epithelial tumor cellsOSoverall survivalPCRpolymerase chain reactionPFSprogression‐free survivalROCreceiver operating characteristicsSSCsaline‐sodium citrateUICCUnion for International Cancer Control1Ampullary cancers are rare malignant neoplasms that arise from the ampulla of Vater  are minute numbers of tumor cells that escape from primary tumors and metastatic foci and enter the bloodstream , and CEP8‐FISH. We further explored the relationships between CTCs and clinical parameters and outcomes.22.1This prospective study was restricted to consecutively diagnosed ampullary adenocarcinoma patients treated at the Fudan University‐Affiliated Huashan Hospital. Sixty‐two patients with pathologically proven ampullary adenocarcinoma and 24 healthy controls were enrolled between March 2012 and December 2015. Written informed consent was obtained from all subjects. Pathological and radiological examination provided evidence for the diagnosis of ampullary cancer. Data on clinical variables including sex, age, tumor grade, tumor size, lymph node invasion, distant metastases, and selected laboratory results were gathered. Ampullary cancer TNM staging was performed according to the American Joint Committee on Cancer (AJCC) 2010 criteria  were used to obtain 3.2 ml whole blood samples for CTC detection. All blood samples were processed within 48 hr of collection.Strategies for CTC isolation and detection were similar to those described previously  were subjected to the multivariate models. All statistical tests were two‐sided. p‐values less than 0.05 were considered significant.Statistical analyses were conducted using the SPSS Statistics 22.0 . Correlations of CTCs with clinicopathological characteristics were examined using the chi‐square test for categorical variables and one‐way ANOVA for continuous variables. Receiver operating characteristics (ROC) curves were plotted to assess the performance of CTCs in an ampullary cancer screening test. DFS and OS were analyzed by using the Kaplan–Meier method and compared via the log‐rank test. Cox's proportional hazards model was performed to identify factors influencing DFS and OS. Factors significantly associated with DFS and OS on univariate analysis   in patients with ampullary cancer and 0–2/3.2 ml  in healthy controls. The difference was statistically significant  Figure .p < 0.001). Youden's index was then used to select the optimum cutoff value with maximum sensitivity and specificity; this value was 2 CTCs/3.2 ml of whole blood, yielding a sensitivity of 69.4%, and specificity of 95.8%. One out of 24 healthy controls (4.2%) was found to be ‘CTC’‐positive, indicating that our method can yield false positive results.We further constructed ROC curves to assess the utility of CTCs as a diagnostic tool for ampullary cancer Figure b. The va3.4p = 0.002) and tended to be associated with higher tumor size (p = 0.078), lymph node invasion (p = 0.106), and distant metastasis (p = 0.083). These results demonstrated that higher CTC levels appear to correlate with a larger tumor burden. CTCs were not associated with elevated carcinoembryonic antigen (CEA) levels. This is consistent with a previous study that found aneuploidy not to be associated with CEA levels , cutoffs of ≥3 and ≥5 CTCs/3.2 ml were selected to investigate the influence of CTCs on DFS. Median DFS rates were 23.8 and 16.0 months in patients with <3 and ≥3 CTCs/3.2 ml, respectively (p = 0.033). The presence of ≥3 CTCs/3.2 ml was associated with poorer DFS on univariate analysis . The presence of ≥5 CTCs/3.2 ml was associated with poorer DFS on univariate analysis  and ≥3 CTCs/3.2 ml . When ≥5 CTCs/3.2 ml was substituted for ≥3 CTCs/3.2 ml in the multivariate models, ≥5 CTCs/3.2 ml  and lymph node invasion  remained independent predictors of DFS.The relationships between CTCs and DFS are shown in Figure 3.6p = 0.039). The presence of ≥3 CTCs/3.2 ml was associated with poorer OS on univariate analysis . The presence of ≥5 CTCs/3.2 ml was associated with poorer OS on univariate analysis , lymph node invasion , and distant metastasis . The presence of ≥3 CTCs/3.2 ml tended to be an independent predictor of poor OS . Additionally, ≥5 CTCs/3.2 ml was an independent predictor of OS on multivariate analysis . AJCC/UICC T staging , lymph node invasion , and distant metastasis  were also independent markers of poorer OS.The median OS rates were 29.4 and 18.0 months in patients with <3 and ≥3 CTCs/3.2 ml, respectively   (Oh, Kim, Lee, & Kim, The prognostic significance of CTC has been widely investigated in tumors. A prospective study of 302 patients with nonmetastatic breast cancer showed that ≥1 CTC/7.5 ml was a predictor of poorer PFS and OS (Lucci et al., To date, the most reliable prognostic variables in patients with ampullary cancer are lymph node invasion, TNM staging, histologic grade, and serum CEA level (Zhou et al., There are several limitations to our study. The power of our statistical analysis was limited by our small sample size. Furthermore, the CTCs detected in our study were circulating aneuploid cells, whereas circulating diploid tumor cells were not evaluated; therefore, the CTC count identified using our method might have been underestimated. Future research should attempt to improve CTC enumeration and detection methods. It is reassuring that only 1 of the 24 healthy control patients had ≥2 CTCs/3.2 ml; furthermore, 11 of the 62 patients had no detectable CTCs. These outcomes indicate that the incidence of false positive cases in our study was low. However, aneuploid cells are widely present in normal tissues and are associated with cell stress, aging, and other factors. Therefore, it is necessary to examine the role of aneuploid cells in the blood of patients with cholangitis, gastrointestinal inflammation, pancreatitis, and benign tumors to elucidate their roles in comparison to actual CTCs. Another limitation was that our findings may not be applicable to all patients with ampullary cancer since ours was a study at a single referral center. Hence, further studies are required for additional validation in an independent validation cohort. As we did not draw blood from patients after treatment, we did not determine the impact of surgery and chemotherapy on CTCs. Overall, the relationship between CTC trends and prognosis requires further study.5In summary, our data indicate a potential clinical value for CTCs based on their detection via combination CD45, DAPI, and CEP8‐FISH staining. CTC levels were shown to be associated with tumor extent, and served as prognostic factors in patients with ampullary cancer. The role of CTCs in identifying therapeutic targets and determining follow‐up treatment ought to be further investigated.This study was conducted with the approval of the Ethics Committee of Fudan University‐Affiliated Huashan Hospital.The datasets analyzed during the current study are available from the corresponding author on reasonable request.The authors declare that they have no conflicts of interest.


DNA copy number (mtDNA‐CN) estimated in whole blood is a novel marker of mitochondrial mass and function that can be used in large population‐based studies. Analyses that attempt to relate mtDNA‐CN to specific aging phenotypes may be confounded by differences in the distribution of blood cell types across samples. Also, low or high mtDNA‐CN may have a different meaning given the presence of diseases associated with mitochondrial damage. We evaluated the impact of blood cell type distribution and diabetes status on the association between mtDNA‐CN and aging phenotypes, namely chronologic age, interleukin‐6, hemoglobin, and all‐cause mortality, among 672 participants of the InCHIANTI study. After accounting for white blood cell count, platelet count, and white blood cell proportions in multivariate models, associations of mtDNA‐CN with age and interleukin‐6 were no longer statistically significant. Evaluation of a statistical interaction by diabetes status suggested heterogeneity of effects in the analysis of mortality (P < 0.01). The magnitude and direction of associations between mtDNA‐CN estimated from blood samples and aging phenotypes are influenced by the sample cell type distribution and disease status. Therefore, accounting for these factors may aid understanding of the relevance of mitochondrial DNA copy number to health and aging.Mitochondrial  Recently, relatively high‐throughput estimates of mitochondrial DNA copy number (mtDNA‐CN) have become feasible by quantitative PCR or extracting information from DNA microarray or sequencing data , hemoglobin, and all‐cause mortality were selected as outcomes because of their importance to gerontology and potential association with mitochondrial function. Initial models were adjusted for age, sex, study site, smoking status, and autosomal coverage as appropriate. Then, platelet and white blood cell counts, as well as neutrophil, lymphocyte, monocyte, and eosinophil percentages measured in a complete blood count, were introduced as covariates in the initial models. After adjusting for blood cell type distribution, mtDNA‐CN coefficients estimating the association with age, IL‐6, and mortality were substantially attenuated; coefficients were no longer significantly different from zero in age and IL‐6 models Table . On the P = 0.005) for nondiabetics and diabetics, and a consistent trend is observed for the association with hemoglobin  were financed by the U.S. National Institute on Aging (Contract: N01‐AG‐5‐0002), supported in part by the Intramural Research Program of the National Institute on Aging, National Institutes of Health, Baltimore, Maryland. Whole‐genome sequencing was supported by Wellcome Trust grants: 083270/Z/07/Z and 090367/Z/09/Z.AZM analyzed, interpreted, and drafted the manuscript. JD, MAT, and ARW involved in bioinformatics and reviewed the manuscript. SB, TMF, and LF designed the study and reviewed the manuscript.None declared.Appendix S1 Experimental procedures.Fig. S1 Distribution of white blood cell subpopulation proportions by mtDNA‐CN among InCHIANTI study participants in the study sample (n = 672).Fig. S2 Crude association between mtDNA‐CN and outcomes of interest among InCHIANTI study participants in the study sample stratified by diabetes status.Table S1 Characteristics of InCHIANTI study participants in the study sample (n = 672) by mtDNA‐CN category.Click here for additional data file.


For this, we isolated myofibers from mice with tissue‐specific inactivation (mKO) or inducible overexpression (imOX) of SIRT1 and analyzed the 3D organisation of myonuclei. In imOX mice, the number of nuclei was increased whilst the average MND size was decreased as compared to littermate controls. Our findings were the opposite in mKO mice. Muscle stem cell (satellite cell) numbers were reduced in mKO muscles, a possible explanation for the lower density of myonuclei in these mice; however, no change was observed in imOX mice, suggesting that other factors might also be involved, such as the functional regulation of stem cells/muscle precursors. Interestingly, however, the changes in the MND volume did not impact the force‐generating capacity of muscle fibers. Taken together, our results demonstrate that SIRT1 is a key regulator of MND sizes, although the underlying molecular mechanisms and the cause‐effect relationship between MND and muscle function remain to be fully defined.Skeletal muscle fibers are giant multinucleated cells wherein individual nuclei govern the protein synthesis in a finite volume of cytoplasm; this is termed the myonuclear domain (MND). The factors that control MND size remain to be defined. In the present study, we studied the contribution of the NAD Indeed, despite the absence of noticeable changes when PGC‐1α is specifically inactivated in muscles, its overexpression induces a dramatic increase in the number of myonuclei and thus a decrease in the MND volume  and SIRT1 muscle‐specific knockout mice (mKO) were generated as previously described  and 10−4.50 M (activating solution).Relaxing and activating solutions contained 4 mM Mg‐ATP, 1 mM free Mg2.3After dissection, the tibialis anterior (TA) muscle was treated with skinning solution  for 24 hr at 4 °C, after which they were transferred to −20 °C , single myofibers were randomly isolated. Arrays of approximately nine myofibers were prepared at room temperature (RT). For each myofiber, both ends were clamped to half‐split copper meshes designed for electron microscopy , which had been glued to cover slips . For the measurement of nuclear coordinates, fibers were mounted at a fixed sarcomere length of ≈2.20 μm. This was a prerequisite for exact determination of nuclei spatial organisation as it allowed accurate comparisons between myofibers  and analyzed with a custom‐made Matlab programme. A distribution score (“g”) is a measure of the regularity of spacing between nuclei; this was calculated as described before  and a theoretical random distribution (MR) were generated for each fiber, based on the numbers and coordinates of the corresponding myonuclei. This was compared with the experimental distribution (ME), and a “g” score was calculated with the equation: g = (ME−MR)/(MO−MR).Arrays were subsequently fixed in 4% PFA/PBS, and further permeabilized with 0.1% Triton‐X100/PBS for 10 min each. fibers were then subjected to actin staining  and nuclear staining . Images were acquired using a confocal microscope  equipped with CARV II confocal imager . To visualize muscle fibers in 3D, stacks of 100 images were acquired  and a lever arm system . Sarcomere length was set to ≈2.50 μm  and the temperature to 15 °C , followed by blocking for 1 hr in 10% goat serum/PBS. Antibodies to Pax7  and laminin  were applied overnight in 10% goat serum/PBS at dilutions of 1:10 and 1:500 respectively (temperature 4 °C). After washes, species and isotype specific secondary antibodies conjugated to Alexa 488 or 594 (Molecular Probes) were applied for 1 hr in 10% goat serum/PBS, with the addition of DAPI . After washing, slides were mounted in Fluoromount .For fiber type/myosin isoform staining: after rehydration as above, sections were blocked in 1% bovine serum albumin/PBS for 10 min. Antibodies directed against different myosin isoforms were then applied in blocking buffer at dilutions of 1:50, overnight at room temperature: mouse anti‐myosin slow/type I ; mouse anti‐myosin fast/type IIa ; mouse anti‐myosin fast/type IIx ; mouse anti‐myosin fast/type IIb . In addition, an antibody recognizing all fast/type II isoforms was utilized . Sections were then washed in PBS/0.025% Tween‐20, and incubated with isotype specific secondary antibodies conjugated to Alexa 488 or 594 in blocking buffer (dilution 1:500) for 1 hr. After washing in PBS, slides were mounted in Fluoromount. BA‐F8, SC‐71, and BF‐F3 were gifts from Dr. Stefano Schiaffino . 6H1 was a gift from Dr. Joseph Hoh .2.7p < 0.05).For all the parameters, no significant differences were observed between WT mice corresponding to the mKO or imOX groups, so all WT animals were pooled for data analysis. Additionally, within each group , no differences were found between animals, so all the individual data were pooled together. Data are presented as mean ± standard error of the mean (SEM). One‐way ANOVA with Tukey post‐correction was used to test for significance (3n = 27), mKO (n = 55), and WT mice (n = 103). We then membrane‐permeabilised the myofibers, generated confocal microscope reconstructions, and evaluated the 3D spatial arrangement of myonuclei . Additionally, there was a significant difference between elevations of the regression lines of both mKO and imOX compared to WT mice, indicating that: (1) across all fiber sizes, there were more nuclei per mm fiber length in imOX and fewer in mKO compared to WT rodents; and that (2), in accordance with this, MND sizes were larger in mKO and smaller in imOX compared to WT rodents  was evaluated , mKO (n = 12) and WT mice . We did not observe any significant differences among the groups  of muscle fibers , but unchanged in imOX muscles (p = 0.11) compared to WT mice  or overexpressed (imOX) specifically in skeletal muscle. Strikingly, we observed that the myonuclear number was significantly increased in imOX mice resulting in a decrease in the average MND size, whilst in mKO mice, nuclear number was decreased, resulting in increased MND size Figures .It is well known that slow‐twitch type I fibers have smaller myonuclear domains than fast‐twitch type II fibers, presumably to support the larger number of mitochondria in the former. Our results and those obtained previously suggest that the SIRT1‐dependent modulation of MND size is not dependent on fiber type or effects on mitochondrial biogenesis. This is supported by the following findings: (1) the mKO and imOX models have no alterations in the relative proportions of type I, IIa, IIx, and IIb fibers in TA muscles Figure ; and (2)Our previous results in mice with conditional knockout or overexpression of PGC‐1α in skeletal muscle mirror the current findings related to SIRT1; increasing the levels of PGC‐1α resulted in smaller MND sizes, and ablation resulted in larger MND sizes , it will be of interest in future studies to investigate SIRT1 as a therapeutic target, for diseases where nuclear alteration is part of the pathophysiology, such as in muscular dystrophies.The authors have no conflicts of interest to disclose.


An increased awareness of the health benefits of walking has emerged with the development and refinement of accelerometer equipment. Evidence is beginning to highlight the value of promoting walking, particularly focusing on the Japanese mark of obtaining 10,000 steps per day. Workplace based step challenges have become popular to engage large cohorts in increasing their daily physical activity in a sustainable and enjoyable way. Findings are now highlighting the positive health effects of these medium-term programs  in terms of cardiovascular health, reducing diabetes risk and improving lifestyle factors such as weight and blood pressure. As yet, research has not focused on whether similar improvements in psychological health and wellbeing are present.This study investigated the impact of a 100-day, 10,000 step program on signs of depression, anxiety and stress as well as general wellbeing using standardised psychological scales.The results indicated a small but consistent effect on all of these measures of mental health over the term of the program. This effect appeared irrespective of whether a person reached the 10,000 step mark.These results highlight improved mental health and wellbeing in people undertaking this 100-day 10,000 step program and indicates the efficacy and potential of these programs for a modest, yet important improvement in mental health. Notably, targets reached may be less important than participation itself. By 2030, mental illness is projected to cost the global community over US$ 6 T . This plPhysical activity likely exerts its impact on mood via reducing the activity of the sympathetic nervous system and associated hypothalamic-pituitary-adrenal axis reactivity in the brain . In termStress is a precipitating factor in susceptibility and exacerbation of mental health issues. Stress is more commonly experienced than depression and anxiety and is associated both with poorer mental health and wellbeing, an important linkage as wellbeing itself is associated with better physical and psychological health over the lifespan . NotablyThe World Health Organisation  has idenThe aim of this investigation was to assess the impact of a 100-day workplace based 10,000 step challenge on mental health and wellbeing in an international workplace community sample. Based on evidence indicating positive physical health effects from 10,000 step programs four hypotheses were developed. Firstly, it was hypothesised that participants involved in a 10,000 step program for 100 days would see benefits in their levels of depression, anxiety and stress and consequent improvements in wellbeing scores. Further, it was hypothesised that increasing amounts of exercise in these programs would lead to improved outcomes on these. Thirdly it was hypothesised that those who on average completed more than 10,000 steps per day throughout (the recommended level for these programs) would perform better in terms of mental health and wellbeing than those who did not reach this threshold. Finally, it was hypothesised that when controlling for demographic factors of age and gender, this improved outcome in people who engaged in more stepping exercise would be maintained.Of the 2379 respondents who consented to participate in this research, 1963 participants made up the final sample size. This number accounted for 416 who either did not complete 70% of the 100-day challenge or those who did not complete the demographic or mental health survey.Stepathlon is a company headquartered in Mumbai, India running globally organized team-based walking programs at participating workplaces. Stepathlon has also offices in Australia where the workplace health and wellbeing policies are developed. Hence, the study sample are predominantly from these two countries.http://www.stepathlon.com), routine data are obtained relating to age, gender, location and daily step counts as recorded by participants on a password protected website based on readings from pedometer (clip-on) or other fitness monitors (e.g. wrist accelerometer). On completion of the 100-day step challenge in 2015 and 2016, digital assets management staff of Stepathlon extracted de-identified data from their server and provided this de-identified database to Victoria University as per research agreement.Through the Stepathlon corporate challenge . The shThe Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) is a 14-item measure rated on a 1–5 scale . The scale focuses on positive elements of wellbeing and is positively worded throughout. The scale provides a one factor model for measuring wellbeing , 31. TheParticipants were recruited from the established international Stepathlon program. This workplace activity challenge was promoted at participating sites via posters, e-flyers, and through engagement of senior management through visits to sites by health & wellbeing managers.Participants of this workplace activity challenge were provided with a participant information and consent forms inviting them to this research charting the impacts of the 10,000 step challenge on their mental health and wellbeing. The project was approved by the Victoria University Human Research Ethics Committee (HRE15–168). All participants completed the standard demographics questionnaire and logged their daily step count for as many of 100 days during the challenge. Participants could use their own pedometer, or activity monitoring device throughout the challenge and recorded their daily totals via the Stepathlon user portal. Through this portal they received regular newsletters, updates and motivational articles for the duration of the challenge. In addition to the standard step challenge package, consenting participants completed a pre-and post 100-day challenge questionnaire regarding their mental health using the DASS-21 and WEMWBS questionnaires in English.The results of the study were analysed using a number of repeated measures ANOVAs. Firstly, the data were assessed to see if there were overall changes in mood and wellbeing from pre to post testing over the activity challenge. Following this, a repeated measures ANOVA focusing on the 10,000 step threshold (between subjects factor) and change over time (within subjects factor) was used to evaluate the 10,000 step criterion. Further, a series of Pearson product moment correlation coefficients were utilised to assess overall relationships between number of steps completed on average by participants and changes in mental health and wellbeing scores. Finally, a repeated measures ANCOVA was utilised to assess the factors in the 10,000 steps over time but covarying for age and gender. All analysis was conducted in SPSS version 21.The final sample of 1963 participants was screened for univariate outliers via box plot analysis on the outcome scales. Data inspection indicated no outliers (+ 2 SD) in the sample, presumably due to the large sample size. Data were assessed for the assumptions of normality and skewness. The data did not violate the assumptions of asymmetry and kurtosis of ±2 using threshold defined by Field . Tests on = 1610) and Australia (n = 227) along with 21 other countries.The final sample represented 1458 males and 505 females who ranged in age from 16 to 74 years . Participants represented numerous countries of origin with the majority being from India  = 67.385, p < .001, η2 = .033, power = 1.0. In relation to anxious symptoms, the data showed a 5.04% improvement after the 100 day challenge, reducing from an average of 4.56 (S.D. = 3.13) to 4.33 (S.D. = 3.08), F = 34.416, p < .001, η2 = .0017, power = 1.0. Stress symptoms were the most responsive to the 100-day challenge with the data showing an 8.96% improvement in stress levels on the DSS following the program. This equated to a reduction from an average of 5.47 (S.D. = 3.19) to 4.98 (S.D. = 3.05), F = 117.593, p < .001, η2 = .057, power = 1.0. Finally, there was a 2.13% improvement in overall wellbeing on the WEMWBS, associated with an increase in average wellbeing scores from 50.01 (S.D. = 10.29) to 51.08 (S.D. = 10.45), F = 103.555, p < .001, η2 = .050, power = 1.0.A repeated measures ANOVA demonstrated improvements on all measures of the DASS over the 100-day challenge period. This included a significant 7.6% improvement in levels of depressive symptoms based on a reduction from an average of 4.59 (S.D. = 3.52) to 4.24 (S.D. = 3.44), r2 = − 0.026, p = .254), anxiety , stress  and WEMWBS . While all measures trend in the direction of improvement with increasing steps, it is notable that the range  of steps taken on average varied markedly, impacting clear correlations.To investigate if these clear mental health improvements over the challenge were associated with increasing levels of walking exercise a series of correlation analyses were conducted contrasting change scores on each of these measures from pre to post testing versus the average number of steps taken per day. The results indicated no significant overall correlations between average steps and depression . These results are depicted in Table F  = 3.982, p = .046, η2 = .002, power = .514) with the participants who completed equal to or more than 10,000 steps showing a 10.13% improvement in stress levels whilst the individuals who completed less than 10,000 steps daily only achieved a 5.36% improvement.The results highlighted an interaction effect between group  and time (pre and post testing) for DASS stress . Interaction effects for depression and overall wellbeing scores were not evident in the analysis. Finally, between subjects differences profiling overall levels of psychological distress and wellbeing in those who did less than 10,000 steps on average versus those who did more showed that the participants in the greater than 10,000 steps group had better scores on wellbeing, F = 4.017, p = .045, η2 = .002, power = .517, and stress levels, F = 21.795, p < .001, η2 = .011, power = .997. There were no overall differences in anxiety, F = .001, p = .975, η2 = .000, power = .050 and depression scores, F  = 1.876, p = .171, η2 = .001, power = .278.Likewise, the interaction effect around anxiety showed that those who completed equal to or more than 10,000 steps daily had a significantly better improvement in anxiety over the challenge, improving their anxiety levels by 5.89% versus only 1.34% for those who completed less than 10,000 steps. (n = 519), 31–45 years (1096), 46–60 years (n = 292) and 60 plus (n = 24 years). This analysis continued to use pre and post-depression/anxiety/stress and WEMWBS levels as the within subjects factors and now included threshold  as the between subjects factor as above. Gender and age were covariates in the model.A final analysis was conducted to see if adding demographic factors other than the 10,000 steps model impacted the importance of meeting this threshold in relation to mental health and wellbeing. Gender was divided into male and female participants whilst age was categorised as 18–30 years  =13.402, p < .001, eta2 = .007, power .955 and F  =22.725, p < .001, eta2 = .012, power = .997 respectively. Whether people had reached 10,000 steps daily on average had no added significant effects. Finally, there were no interaction effects with the between subjects covariates and the 10,000 step threshold factor and change in depression levels over time.The ANCOVA analysis of depression continued to reflect no significant change in depression levels over time (within subjects factor) whilst gender and age category were both significant between subjects predictors of depression scores overall, F = 52.363, p < .001, eta2 = .026, power = 1 but no significant impacts from whether people achieve the 10,000 step threshold or their gender.The ANCOVA analysis of anxiety again revealed the overall decrease in anxiety over the challenge but no significant interactions between age, gender or the 10,000 step threshold in the changes observed in the within subjects analysis. In terms of between subjects effects of the threshold measure and the covariates of age and gender, the results highlight an overall impact of the age covariate, F = 13.707, p < .001, eta2.007, power = .959 and F = 23.616, p < .001, eta2 = .012, power = .998. Notably, the participants who were in the group that had averaged over 10,000 steps were those with lower stress levels overall.The ANCOVA related to stress highlighted that with the fuller model, the former significant change over time was no longer observable. Further, there were no significant interaction effects in relation to stress changes for whether people reached the 10,000 step threshold or related to the covariates age and gender. The between subjects analysis highlighted that age and whether people walked over 10,000 had significant impacts on stress levels. in terms of overall stress levels, both age and gender impacted, F = 56.608), p < .001, eta2 = .004, power = 1.0 and age F7.315, p = .007, eta2 = .004, power = .771. Notably, being in the above the 10,000 step threshold group did not infer any differences.Finally, wellbeing scores were assessed. The data from the WEMWBS indicated that the wellbeing scores were unchanged by participation in the program overall and there were no significant interactions between other factors and the results on this scale. Both covariates showed impacts on the between subjects results of the WEMWBS including those for gender, The results of this study highlight some psychological and wellbeing benefits of being engaged in work based 10,000 step programs. This effect appeared irrespective of the average number of steps achieved by the person over the program period. Mental health is related to a range of biopsychosocial factors and as a result a range of interventions and approaches may make up sustaining good mental health. This study demonstrated that engaging in a workplace based step program improved stress levels by 8.9%, signs of depression by 7.6%, anxiety by 5.0% and wellbeing by 2.1% from baseline. This reinforces the benefits of this type of exercise regimen as playing a small yet significant role in improving mental as well as physical health. It is notable that when considering the role of the 10,000 step threshold as a significant number to improve people on these psychological factors, there is little evidence from this study that this number holds any significant value. Further, evidence indicates that even the most basic demographic variables such as gender and age can impact the outcomes of this number of steps, again reinforcing the complex biopsychosocial milieu that makes up mental health and wellbeing.The lack of a dose response highlights there may be multiple factors that lead to improvements associated with these programs outside activity level per se. This may include the enjoyment and connection obtained from meaningful group participation, teamwork, improved friendship, interpersonal support and networking that has been shown to significantly improve mental health and wellbeing . FurtherThis workplace health challenge highlights the mental health benefits in a similar way to physical health benefits of these programs. This shows a greater impact than previously demonstrated. Mental health and wellbeing issues play a significant part in absenteeism, reduced productivity and overall decreased quality of life for many individuals. Cost savings for workplaces in terms of mental health are evident with these programs. In combination with other workplace mental health initiatives, these may contribute to the suite of different resources and approaches that improve mental health for those with sub threshold concerns and potentially some benefit for those with more serious mental health issues. This spectrum also requires further investigation.Evidence indicates that workplace based health promotion programs reduce absenteeism and organisational health care expenditure as described in a systematic review of interventions in large US based firms with an average program duration of 3 years: there the average employee health care costs fell by US$ 3.3 for every 1$ spent on employee wellness programs . HoweverOur research benefited from a large sample size of participants across a number of countries to fully assess the hypotheses. In terms of limitations, this study did not record diagnoses of mental health issues (including depression and anxiety) which would further elucidate the impact of the program on clinical levels of distress. Secondly, the research did not report on the individual’s overall level of activity. This may have been an important consideration as there are clearly individuals who were more active before commencing the program. Ideally this would be co-varied in future studies. Further, all activity levels are self-report and, as participants were involved in the challenge as teams, the data may reflect social desirability biases. Finally, longitudinal follow up of whether people continue to exercise and experience mental health benefits after participating in a workplace based activity challenge needs to be explored to ascertain the sustainability and return of investments of such workplace wellbeing programs. An eight-months follow-up evaluation after a comparable 4-months pedometer-based workplace health program has demonstrated sustained improvement in chronic disease risk factors indicating that such programs can have a long-term benefit .The increasing prevalence of non-communicable diseases such as mental ill health has heightened the need to change lifestyle behaviours and increase physical activity. With most adults spending at least half of their life working, the workplace is an important setting for promoting mental health and wellbeing change . The res


Conversely, Bland–Altman analysis indicated no bias between motion scans with PROMO, which have good image quality, and resting scans without PROMO. In addition, there was no bias between resting scans with and without PROMO. The use of PROMO facilitated more reliable brain structure measurements in subjects moving during data acquisition.PROspective MOtion correction (PROMO) can prevent motion artefacts. The aim of this study was to determine whether brain structure measurements of motion-corrected images with PROMO were reliable and equivalent to conventional images without motion artefacts. The following T1-weighted images were obtained in healthy subjects: (A) resting scans with and without PROMO and (B) two types of motion scans (“side-to-side” and “nodding” motions) with and without PROMO. The total gray matter volumes and cortical thicknesses were significantly decreased in motion scans without PROMO as compared to the resting scans without PROMO ( PROMO utilises three orthogonal 2D spiral navigator (S-NAV) acquisitions along with a flexible image-based tracking method for real-time motion measurement and correction8Previous studies reported that PROMO reduced artefacts in 3D-T1WI caused by head motions of school-age children81213Human experiments were carried out in accordance with the guidelines provided and approved by the Institutional Review Board of the University of Occupational and Environmental Health School of Medicine .The study cohort included seven healthy subjects (#1–7), consisting of four men and three women, aged 30–35 years. All participants provided written informed consent for participation in this study.Details of scan acquisitions are summarised in Second, five resting scans with and without PROMO of two subjects (#2 and #3) were acquired on the same day.Third, in five subjects (#3–7), one scan in each of the resting scans without PROMO and two types of motion scans with PROMO were acquired on the same day. After acquisitions, a neuroradiologist immediately checked image quality. To obtain good quality motion-corrected images, each motion scan was repeated until the image quality of the scan was judged as adequate . Quantitative motion measurements during acquisition were also confirmed.Magnetic resonance imaging (MRI) data were obtained using a 3.0-Tesla scanner  with a Magnetization-Prepared Rapid Acquisition Gradient Echo (MPRAGE) pulse sequence provided by GE Healthcare. The following parameters were used in scans with and without PROMO: repetition time, 2,300 ms; inversion time, 900 ms; echo time, 3 ms; flip angle, 8°; bandwidth, 31 kHz; field of view, 256 mm; section thickness, 1.0 mm; matrix, 256 × 256; and imaging time; 5 min 24 sec. If significant head motion was detected during scans with PROMO, the acquisition time was increased to rescan motion-corrupted data. Rescans were set to be triggered by a norm of ≥1 mm/degree in motion during acquisitionAll images were corrected for image distortion using Gradwarp, which is a system for specific correction of image geometry distortion due to gradient non-linearityTwo neuroradiologists, who were blinded to PROMO status (with vs. without) and motion status (resting vs. motion), rated image quality using a three-point scale as follows: adequate = little or no detectable motion artefact with adequate image quality for brain morphometry analysis; inadequate = detectable motion artefacts with inadequate image quality for brain morphometry analysis; and poor = extreme motion artefacts.et al.Freesurfer v5.3.0161617Second, repeatability of cortical structure measurements in the resting scans with and without PROMO of subjects #1–3 was analysed. A template was generated from the resting scans with and without PROMO, respectively. Longitudinal Processing was performed with the resting scans with and without PROMO, respectively. For subject #1, the difference in cortical thickness was calculated between two scans acquired in two continuous sessions . For subjects #2 and #3, the difference in cortical thickness was calculated between each two continuous scans . The absolute means and standard deviations of cortical thickness differences were calculated.For reliability and repeatability analyses, minimal manual editing was performed, including correction of errors in the cortical reconstructions.The “segment” algorithm in Statistical Parametric Mapping (SPM) 12 was used1921http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/first) was used as the brain extraction tool (with –f 0.2 and –B option) and FMRIB’s Automated Segmentation Tool (FAST) was used for GM segmentation23Functional MRI of the Brain (FMRIB) Software Library (FSL) v5.0.4  resting scans with PROMO were compared;  the “side to side” and “nodding” motion scans with PROMO were rated as adequate; (D) the combination of “side to side” and “nodding” motion scans with PROMO were rated as inadequate; and  the “side to side” and “nodding” motion scans without PROMO, respectively. Further, the distributions of the volume differences plotted against the volume means were examined by Bland–Altman analysisU test was used to compare the equality of variances in the absolute means of thickness differences.For the quantitative assessment in total GM volumes, statistically significant differences were examined using the paired Student’s p) value of <0.05 was considered statistically significant.All statistical analyses were performed with R statistical software . A probability  required for rescanning motion-corrupted data in the “side to side” and “nodding” motion scans with PROMO were 57.0 ± 6.1 and 59.1 ± 6.4 s for subject #1 and 58.6 ± 9.1 and 54.1 ± 10.3 s for subjects #3–7, respectively. No rescan was triggered for any resting scan with PROMO.Representative quantitative motion measurements obtained during the scans with PROMO are shown in p < 0.05).The image qualities are shown in The κ value for inter-observer variability between two radiologists was 0.98, which corresponded to excellent inter-observer agreement.For subjects #3–7, two “side to side” and two “nodding” motion scans with PROMO were rated as inadequate. Therefore, these scans were reacquired. All of the reacquired motion scans with PROMO were rated as adequate.The results of reliability analysis of total GM volume measurements are shown in p = 0.71; subject #2, p = 0.71; subject #3, p = 0.57, SPM12: subject #1, p = 0.45; subject #2, p = 0.78; subject #3, p = 0.61, FSL: subject #1, p = 0.78; subject #2, p = 0.94; subject #3, p = 0.98).There was no significant difference in total GM volumes in resting scans with and without PROMO for subjects #1–3 .There was no significant difference in total GM volumes in “side to side” and “nodding” motion scans with PROMO rated as adequate, as compared to resting scans without PROMO for subjects #1 and #3–7 .The total GM volume in motion scans with PROMO rated as inadequate was significantly underestimated, as compared to resting scans without PROMO for subject #1 and #3–7 .Total GM volume was significantly underestimated in motion scans without PROMO, as compared to resting scans without PROMO for subject #1 et al. (about 0.140 mm)There were some limitations to this study that should be addressed. First, since the data were not collected from a large cohort, it is unknown whether these results can be generalised to a larger population. Therefore, further studies with larger numbers of subjects are warranted to confirm these findings. An investigation of the relationship between motion severity and brain structure measurements in motion-corrected images is also needed. However, this relationship was not analysed in the present study because the degree of motion was not relatively significant. Second, the “side to side” and “nodding” motions in this study may differ from patient motions in clinical practice. Therefore, the use of PROMO in patients with dementia and Parkinson’s disease might be an interesting topic for further studies. In addition, comparisons of different motion correction approaches, such as the navigator method and optical tracking method, are expected. Although the optical tracking method requires implementation of a camera system, this method offers the benefit of a high frame rate and independent operation from the MRI scanning process2930In conclusion, PROMO reduced motion-induced bias. Using PROMO, more reliable brain structure measurements were obtained in a subject who moved during data acquisition. Furthermore, PROMO improved the repeatability of brain structure measurements even in resting scans, potentially correcting for small motions at rest. In addition, because even healthy subjects are susceptible to motion artefacts, the use of PROMO should be useful in routine MRI protocols.How to cite this article: Watanabe, K. et al. Utility of real-time prospective motion correction (PROMO) on 3D T1-weighted imaging in automated brain structure measurements. Sci. Rep.6, 38366; doi: 10.1038/srep38366 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.