N = 10, age 85–105 years old) and compare them to young adults  and older adults . All subjects underwent full-night polysomnography, 1-week of actigraphic recording and peripheral blood collection. Sleep electroencephalogram spectral analysis was also performed. The oldest old individuals showed lower sleep efficiency and REM sleep when compared to the older adults, while stage N3 percentage and delta power were similar across the groups. Oldest old individuals maintained strictly regular sleep-wake schedules and also presented higher HDL-cholesterol and lower triglyceride levels than older adults. The present study revealed novel data regarding specific sleep patterns and maintenance of slow wave sleep in the oldest old group. Taken together with the favorable lipid profile, these results contribute with evidence to the importance of sleep and lipid metabolism regulation in the maintenance of longevity in humans.Some individuals are able to successfully reach very old ages, reflecting higher adaptation against age-associated effects. Sleep is one of the processes deeply affected by aging; however few studies evaluating sleep in long-lived individuals (aged over 85) have been reported to date. The aim of this study was to characterize the sleep patterns and biochemical profile of oldest old individuals ( Sleep is essential for physical and mental well-being and is one of the most important factors responsible for the maintenance of a healthy organism, thus representing a homeostatic need required for life , as well as a decrease in total sleep time (TST), sleep efficiency, slow wave sleep and REM sleep have been reported to be associated with aging .The study protocol was approved by the Research Ethics Committee of the Universidade Federal de São Paulo (CEP 1990/08) and all volunteers read and signed the informed consent form, according to the Declaration of Helsinki. This study is also part of a larger study registered in ClinicalTrials.gov ; (2) Older adult ; and (3) Young adult . All participants were invited to spend one night at the Sleep Institute in São Paulo, Brazil, where they were informed about the study protocol, underwent standardized questionnaire data collection, full-night polysomnography (PSG) and blood collection. After up to 23 weeks, the participants of the young adult and older adult groups were contacted again, underwent a second night of PSG, and were invited to use an actigraph and complete a sleep diary for 1 week starting from this second night. Due to limitations associated with their age (the mobility difficulty and the need of a relative to be with them during the PSG), individuals from the oldest old group underwent only one night of PSG. These individuals were also invited to use the actigraph and complete the sleep diary for 1 week after the PSG night.One hundred and thirty-two young adult (20–30 years old) and older adult (over 60 years old) males, drawn either from ongoing epidemiological studies in São Paulo, Brazil  or recruited through local advertising underwent a phone or in person interview about health and lifestyle habits. Only male individuals were selected in order to reduce the effects of female reproductive cycle on sleep  , mean oxygen saturation  and minimum oxygen saturation .Young adult and older adult individuals underwent two non-consecutive full-night PSGs and oldest old individuals underwent a single night of measurements. PSG were performed using the digital system EMBLA® S7000 . Biological variables were monitored continuously using electroencephalography , electrooculography, submental and anterior tibialis electromyography and electrocardiogram (V2 derivation). Airflow was measured using a thermocouple and pressure transducer and respiratory effort was detected using chest and abdominal piezoelectric sensors. Oxygen saturation and pulse were recorded with a pulse oximeter. Sleep scoring and associated events were performed by an experienced sleep technician following the recommended criteria of the American Academy of Sleep Medicine Manual for Scoring Sleep and Associated Events , median, and interquartile range] from each 30 s window were calculated, and the 5% of time windows with the highest signal amplitude at each sleep stage were considered as outliers and excluded from analysis.The spectral analysis of sleep EEG was performed as previously described  for 1 week, following the second night of PSG for the young adult and older adult groups or after the single night for the oldest old group. Data acquisition was performed using the zero-crossing mode in 1-min epochs according to a previously published validation study  or the single night (oldest old group), peripheral blood was collected to measure the following levels using standard routine methodologies as indicated in parenthesis: fasting glucose (enzymatic colorimetric), urea (enzymatic colorimetric), creatinine (colorimetric), albumin (colorimetric), total cholesterol (enzymatic colorimetric), LDL-cholesterol (enzymatic colorimetric), HDL-cholesterol (enzymatic colorimetric), VLDL-cholesterol (enzymatic colorimetric), and triglycerides (enzymatic colorimetric). All samples were collected between 06:00 and 08:00 AM while individuals were fasting and biochemical analyses were performed using automated dosages with an Advia® 1650 chemistry system .post-hoc test or Kruskal–Wallis test followed by pairwise Mann–Whitney test comparisons. Spectral analysis results were Z-score standardized and the effects of age on frequency specific spectral power at each sleep stage and at each derivation were verified using One-Way ANOVA with Bonferroni post-hoc test. All statistical analyses were performed using PASW Statistics 18  and the significance level was set at 0.05. Results are mainly represented by mean ± SD.A Shapiro–Wilk test was performed for all continuous variables to verify normality of the data. The questionnaire outcomes, polysomnographic, and actigraphic sleep parameters, as well as the biochemical levels were compared among young adult, older adult and oldest old groups using One-Way analysis of variance (ANOVA) with Bonferroni SD age for young adult, older adult, and oldest old individuals was 24.33 ± 2.19, 65.54 ± 3.05, and 91.9 ± 6.06 years, respectively. Body mass index was 24.04 ± 2.74 for young adult, 25.87 ± 3.56 for older adult, and 24.96 ± 3.55 for oldest old, and did not statistically differ among groups . Six individuals from the older adult group and five from the oldest old group showed controlled chronic diseases  and were taking medications at the time of the PSG.The studied sample consisted of male individuals from three distinct age groups. Mean ± 2 = 4.308, p = 0.116), ISI , ESS applied in the first visit  and ESS applied in the second visit . Nevertheless, the HO morningness eveningness questionnaire revealed significant differences among the groups . Both older adults (67.9 ± 12.8) and oldest old (66.8 ± 9.0) individuals showed higher scores than young adults  indicating that the aging is associated with morning chronotype while young individuals tend to have an evening chronotype. No significant difference between older adult and oldest old groups was found for this outcome.To assess subjective sleep quality and verify the effect of aging and longevity on these patterns a variety of validated questionnaires were applied in the three studied groups. No significant differences were found for the outcomes of the following questionnaires among young adult, older adult and oldest old individuals, respectively: PSQI . More specifically, three individuals from the oldest old group presented at least one degree of dependence and only one presented dependence in three activities. Moreover, oldest old individuals showed significantly lower MMSE scores (22.8 ± 5.6) and higher GDS scores (2.8 ± 2.1) than older adults . These results indicate a slight impairment in cognitive, physical and behavioral aspects specific to older ages that should be taken into account when investigating the parameters of sleep quality and quantity in these individuals. However, differences in geriatric-specific questionnaires did not modify the association results described in the following sections (data not shown).Geriatric-specific questionnaires were also applied for the older adult and oldest old groups in order to better evaluate their status. Significant differences were found between groups for the Katz Index of Independence in ADL , no trend toward significant decrease was detected when older adult and oldest old subjects were compared. The present findings on the macrostructure of sleep indicate that overall, oldest old individuals showed decreased sleep quality parameters compared to the other groups, but maintained some specific parameters such as stage N3.The PSG parameters used to verify the effect of aging and longevity were derived from the first PSG night for all individuals. Table p = 0.001 and p = 0.012, respectively) and F4-M1 derivations . In addition, older adults showed lower delta power in stage N2 than young adults , and oldest old individuals . Theta power in young adults was significantly lower than in oldest old individuals in stage N2  and lower than older adults in stage N3 . Interestingly, no significant differences in stage N3 delta power among groups in all studied derivations were found (p > 0.05).The spectral analysis of sleep EEG was also performed using data derived from the first PSG night. Figure Fast EEG waves  also showed specific patterns in longevity . Oldest old individuals also had significantly more naps (3.71 ± 2.36) than young adults . Nap start and end times, duration and their respective CV did not differ between older adult and oldest old , total cholesterol (p = 0.030), and VLDL-cholesterol levels (p = 0.010) than young adults. Furthermore, HDL-cholesterol levels in the oldest old group were higher than both young (p = 0.032) and older adults (p = 0.020). Additionally, young adults showed lower glucose levels than older adults (p = 0.004) and oldest old individuals (p = 0.003) and higher albumin levels than oldest old individuals (p = 0.007). Taken together, these findings suggest that the oldest old individuals present a more favorable lipid profile than older adults.Table The characterization of the physiological aspects of sleep in oldest old individuals has brought some new insights to the understanding of the role of sleep in maintaining the functioning organism in very old age. The main findings of the present study were that, although oldest old individuals showed poorer sleep quality, no significant differences in the percentage of stage N3 or in stage N3 delta power were detected when compared to the older adult group. In addition, the actigraphic measurements revealed that oldest old individuals maintain strictly regular sleep and wake schedules and laboratory examinations showed that these individuals also presented a better lipid profile than older adults in our study.Alterations in sleep architecture are expected with aging and might be related to a reduction in the ability to sleep, rather than a decrease in the need for sleep itself  found a significant increase in stages N1 and N2 with aging. In the study, when only elderly individuals were investigated, the slow wave sleep amount did not decrease with increasing aging, agreeing with our findings (Ohayon et al., Regarding the other frequency bands, our results have shown specific patterns of theta waves in stage N1 as well as alpha and beta waves mainly in stages N3 and REM in the oldest old individuals, a potential indicative of specific sleep EEG signature in longevity. Cortical activation is directly related to increase in power of high frequency bands in EEG, and previous studies showed that increasing age was associated with higher power in the beta range (Carrier et al., Another interesting feature observed was the phase advance phenomenon, which was clearly characterized in the oldest old individuals, both by the HO morningness and eveningness questionnaire and by the actigraphic recordings. This event has been described in the literature and although it is poorly understood, it is thought to be associated with the inability to maintain sleep at specific circadian phases or as a consequence of alterations in the circadian regulation of physiological processes with aging (Edwards et al., In addition, we observed the interesting co-occurrence of the maintenance of slow wave sleep, regular sleep patterns and a favorable lipid profile in the oldest old. It is known that HDL has antioxidant proprieties, and higher HDL-cholesterol levels are associated with antiatherogenic effects (Kontush and Chapman, Drosophila, high calorie diet, besides reducing lifespan, accelerated age-related process, including sleep changes (Yamazaki et al., Interestingly, experimental and epidemiological evidence suggests that impairment in slow wave sleep is responsible for a lack of hormonal regulation and has been associated as a risk factor for metabolic syndrome features such as type 2 diabetes and obesity (Van Cauter et al., The relationship between sleep and aging has been extensively studied. A number of age-related factors such as inflammation, increased oxidative stress, mitochondrial decline and cellular senescence have been recently described to be affected by sleep and sleep deprivation (Singh et al., In conclusion, three major features were associated with longevity in this study: the maintenance of slow wave sleep in oldest old individuals when compared to older adults, the existence of strictly regular sleep patterns among oldest old individuals and the occurrence of a favorable lipid profile in these individuals. In addition, signatures of sleep EEG in the brain of oldest old individuals were also described. These findings support the role of sleep and lipid metabolism control in the maintenance of longevity in humans.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background. The availability of environmental energy, as measured by temperature, is expected to limit the abundance and distribution of endotherms wintering at temperate latitudes. A prediction of this hypothesis is that birds should attain their highest abundances in warmer areas. However, there may be a spatial mismatch between species preferred habitats and species preferred temperatures, so some species might end-up wintering in sub-optimal thermal environments.Methods. We model the influence of minimum winter temperature on the relative abundance of 106 terrestrial bird species wintering in peninsular Spain, at 10 ×10 km2 resolution, using 95%-quantile regressions. We analyze general trends across species on the shape of the response curves, the environmental preferred temperature (at which the species abundance is maximized), the mean temperature in the area of distribution and the thermal breadth (area under the abundance-temperature curve).Results. Temperature explains a low proportion of variation in abundance. The most significant effect is on limiting the maximum potential abundance of species. Considering this upper-limit response, there is a large interspecific variability on the thermal preferences and specialization of species. Overall, there is a preponderance of positive relationships between species abundance and temperature; on average, species attain their maximum abundances in areas 1.9 °C warmer than the average temperature available in peninsular Spain. The mean temperature in the area of distribution is lower than the thermal preferences of the species.Discussion. Many species prefer the warmest areas to overwinter, which suggests that temperature imposes important restrictions to birds wintering in the Iberian Peninsula. However, one third of species overwinter in locations colder than their thermal preferences, probably reflecting the interaction between habitat and thermal requirements. There is a high inter-specific variation in the versatility of species using the available thermal space, and the limited effect of temperature highlights the role of other environmental factors determining species abundance. The distribution of overwintering animals is assumed to be strongly influenced by environmental energy availability, notably in regions with a marked year-round seasonality such as temperate ecosystems. Peninsular Spain is an important destination for many avian populations of the southwestern Palearctic during the winter , 1972, wMoreover, while the abundance of species may be limited by temperature at some points, it might be further limited by other environmental factors related to species-specific habitat or trophic preferences at other locations , 2015. TTMEAN) do not coincide with the preferred temperature at which the species abundance is maximized (TPREF). Finally, we analyze the interspecific variation on the level of specialization to use the available thermal space  that the maximum abundance of species will correlate positively with minimum winter temperature, (2) that, on average, species will prefer temperatures above the mean environmental temperature available in the region. The second goal is to test the hypothesis that as a consequence of species being limited by other factors , mean temperatures at which species are found (TPREF), and the ‘thermal breadth’ of species, calculated as the area under the response curve relative to the maximum abundance of the species .We obtained field data from the national-scale project conducted by www.aemet.es) provided updated GIS temperature data covering the whole Iberian Peninsula, from which we calculated the average minimum winter temperature of each UTM cell as the daily averages during the period of study (mid-November to mid-February 2007–2010). Average minimum winter temperature during the study period in the 1,689 UTM cells considered was highly correlated with average winter temperature (r = 0.978) and average maximum winter temperature (r = 0.909). The average minimum winter temperature was selected as a measurement of the thermal state of the environment more probably constraining bird distribution and abundance, considering its functional meaning related to maximum thermoregulatory costs. Moreover, minimum temperatures usually occur at night, which is the most constraining period for diurnal species during winter, considering the long duration of nights, foraging inactivity and the lack of heat production from locomotion  on the relative abundance (A) of each species using quantile regression models at percentiles 50th, 75th, 90th and 95th . We standardized the original temperature variable T, and its squared term T2, to mean = 0 and sd = 1 prior to data analyses, in order to obtain standardized regression coefficients, also called beta regression coefficients. Under this standardization, the magnitude of beta coefficients allows to compare the relative contribution of each independent variable in the prediction of the response variable because predictors are on the same measurement scale. We estimated pseudo-R2 for each quantile regression model as a goodness-of-fit measure . In addition, we calculated the increase in AIC of these models with respect to the null model as a measure of the likelihood of the model  by solving the equation dA⋅dT−1 = 0 in quadratic 95%-quantile regression models. Then, we calculated the mean temperature in the area of distribution (TMEAN) as the weighted average of the winter minimum temperature of the UTM cells where the species were present, using the relative occurrence of species in the sixty 15-min transects. Finally, we obtained the thermal breadth of species (TBREADTH) by integrating A⋅dT in quadratic 95%-quantile regression models between −2 and 10 °C, standardizing the maximal abundances of all species to 1 , 4.8% (0.773), 7.1% (0.924) and 8.7% (0.964) of species abundances using quantile regression models at percentiles 50%, 75%, 90% and 95%, respectively .Relationships between average winter minimum temperature and abundance show a wedge-shaped point cloud in all species, with values varying from zero to an upper limit of abundance  and 2. MIn 93 out of 103 species, the 95%-quantile regression models including the linear and quadratic terms of temperature attain AIC figures that are 13.82 units lower than those AIC figures obtained for 95%-quantile null regression models , defining a hump-shaped relationship between temperature and the relative abundance of bird species. Linear terms b have larger absolute values than the quadratic terms c . Therefore, the linear increase of relative abundance with winter temperature is, on average, positive and more important than the curvilinear pattern defining maxima.Standardized lineal regression coefficients TPREF is 4.36 °C for 93 species with “significant” 95%-quantile regression models . TPREF is lower than 0 °C in 24 out of 93 species , while it is higher than 5 °C in 40 species  is 2.75 °C for the 103 studied species , with 35 bird species whose distribution correspond to colder conditions than average, and 42 species inhabiting warmer areas than average. Other 26 species do not show any clear, significant, preference for warmer or colder areas in peninsular Spain.Mean temperature in the area of distribution . In fact, there are 32 species with TPREF > 8 °C that show a TMEAN 4.5–8.3 °C colder. Conversely, there are 21 species with TPREF = − 2°C and a TMEAN 1.8–4.1 °C higher.TBREADTH is on average 0.64 for all studied species  in species such as Accipiter nisus, Turdus merula, Parus major, Corvus monedula, Carduelis cannabina, Fringilla coelebs , mountain streams (Cinclus cinclus), or alpine rock outcrops  that grows in highlands of continental cold climate . The steady increase of pseudo-R2 from the median (50% quantile) to the maximum response (95% quantile) shows that the influence of temperature on bird distribution is more clearly revealed at the upper edge of the wedge-shaped pattern of covariation abundance—temperature, where the limiting effect of temperature surpasses that of other factors affecting bird abundance . That sample unit will occupy a low position in the wedge-shaped pattern depicted by TMEAN) and the preferred temperature (TPREF) derived from quadratic 95%-quantile regression models  from the minimum to the maximum response , 2003. Tn models . Althougures see , probablures see , 2008.Upupa epops, Ptynoprogne rupestris, Troglodytes troglodytes, Luscinia svecica, Cisticola juncidis, Phylloscopus collybita, Sylvia melanocephala, S. atricapilla). In the same vein, Anthus pratensis and Phylloscopus collybita) will broaden their distribution ranges into the cold highland expanses typical of the western Mediterranean. ‘Space-for-time’ substitution when forecasting temporal trends from spatial climatic gradients must be taken with care (The general preference for warmer environments that we found suggest that winters will be less restrictive for most birds wintering in the Iberian peninsula under future climate warming scenarios , 2013, tith care , 2009, aith care , 2013. Nith care , 2015.This study highlights the high interspecific variability on the response to temperature and thermal tolerance. Bird species wintering in peninsular Spain range from the coldest to the warmest thermal preferences and from thermal specialists to generalists. Nevertheless, the general trend is to select the warmest areas, so that abundance of most species increases with temperature and is predicted to reach its maximum at temperatures higher than the average available temperature in the study region. Even though species attain their maximum abundances at warm areas, a large proportion of the area of distribution of the studied species is in colder locations, probably reflecting a limitation of sites combining thermal optima with other environmental preferences of a species. Our results suggest that minimum winter temperature functions as a physiological constraint on the maximum potential abundance attainable by a species at a certain location, though other environmental factors may be more relevant than temperature defining the biogeographical patterns of species.10.7717/peerj.2156/supp-1Text S1Click here for additional data file.10.7717/peerj.2156/supp-2Data S1Click here for additional data file.10.7717/peerj.2156/supp-3Table S1Click here for additional data file.


The aim of the study was to elucidate pretreatment factors that can predict the outcome of neoadjuvant chemoradiotherapy or chemotherapy (NAC(R)T) and help us choose treatment strategies appropriate for individual patients.Few studies have investigated whether clinical data obtainable before the treatment can predict the efficacy of NAC(R)T.Of 1540 patients treated for esophageal squamous cell carcinoma (ESCC) at our department between January 2000 and June 2014, those who underwent surgical resection of cStage II or more advanced ESCC after NAC(R)T (113 NACRT and 146 NACT patients) were enrolled in this study. Information all available before the treatment was analyzed to extract factors that can predict the effectiveness of NAC(R)T. NAC(R)T was considered effective when Grade 2 or greater treatment efficacy was achieved based on the histological grading system.NACRT was effective in 51 (45%) of 113 patients. The analysis of 35 pretreatment factors showed that female sex , absence of dyslipidemia , and histologically poorly differentiated tumor  were factors predicting NACRT effectiveness. On the other hand, NACT was effective in 21 (14%) of 146 patients. The analysis of pretreatment factors showed that absence of dyslipidemia  and therapy with docetaxel, cisplatin, and 5-fluorouracil  were factors predicting NACT effectiveness.The findings of this study investigating factors that could predict the outcome of NAC(R)T suggest that the prevalence of dyslipidemia influences the outcome of NAC(R)T for ESCC. Findings from the histopathological examination of esophageal cancer resected after CRT are extremely useful in judging CRT efficacy and selecting additional therapies and consequently in predicting the prognosis.8 Several studies investigated the predictors of post-CRT prognosis,11 whereas others analyzed pretreatment imaging findings and histopathological findings to reveal the predictors of CRT efficacy.16 As in CRT, several studies reported the efficacy of neoadjuvant chemotherapy (CT), making it standard treatment for esophageal cancer.21 However, except the studies using pretreatment imaging findings, no studies used pretreatment factors such as patient background and hematological findings to predict the outcomes of NAC(R)T. The discovery of pretreatment clinical or biopsy findings that can predict or enhance the efficacy of CRT or CT would enable us to establish more effective and individualized treatment strategies. In this study, we assessed the independent factors that can predict the outcome of NAC(R)T  applied to the patients with ESCC.Esophageal squamous cell carcinoma (ESCC) is the most dangerous form of gastrointestinal cancer.2 5-fluorouracil [FU], 80 mg/m2 cisplatin) in 28 patients; low-dose FP  in 66; and docetaxel, cisplatin, and 5-fluorouracil (DCF)  in 19. The dose of radiation was >50 Gy and ≤50 Gy in 11 and 102 patients, respectively. Data obtainable before therapy were analyzed to extract factors predicting CRT effectiveness.Of 1540 patients treated for esophageal cancer at our hospital between January 2000 and June 2014, 113 patients with cStage II or above ESCC who had undergone CRT as the first therapy and then esophageal resection were enrolled in this study. Neoadjuvant CT regimens in the CRT protocol were high-dose FP  in 95 patients; DCF  in 38; and FAP  in 13.Similarly, 146 patients who had undergone esophageal resection after NACT were analyzed to reveal factors that can predict efficacy specific to CT. Neoadjuvant CT regimens in this group were high dose FP (800 mg/m22 C(R)T was considered to be effective when the resected specimen was diagnosed to show Grade 2 or greater treatment effect by histopathological assessment. The histopathological effects of NAC(R)T was defined according to the Japanese Classification of Esophageal Cancer, 10th edition.23 The grading systems—Grade 0: ineffective, no recognizable cytological or histological therapeutic effect. Grade 1: slightly effective, apparently viable cancer cells account for 1/3 or more of the tumor tissue, but there is some evidence of degeneration of the cancer tissue or cells. Grade 1a: viable cancer cells accounting for 2/3 or more tumor tissue. Grade 1b: viable cancer cells accounting for 1/3 or more, but <2/3, of tumor tissue. Grade 2: moderately effective, viable cancer cells account for <1/3 of the tumor tissue, whereas the other cancer cells are severely degenerated or necrotic. Grade 3: markedly effective, no viable cancer cells are evident.23 In this study, the routine pathology was performed by multiple pathologist. However, in our hospital, a single chief pathologist reviewed all pathological materials and routinely made a definitive diagnosis of the histopathological response grade 0 to 3 of NACRT or NACT. This study was approved by the Institutional Review Board of our hospital.The analysis items were 35 factors  and 33 factors in total  were analyzed to extract factors predicting NACRT and NACT effectiveness, respectively. In our hospital, the tumor grading was performed in accordance with American Joint Committee on Cancer (AJCC) guidelines.P < 0.10 in the simple Cox proportional hazards models were entered into multiple Cox proportional hazards models. In multiple Cox proportional hazards models, P < 0.05 was considered significant. Statistical analysis was performed using the SPSS ver.19 , with significance set at P < 0.05. Staging was performed in accordance with the Union for International Cancer Control TNM Classification of Malignant Tumors (version 7).24Cumulative overall survival (OS) was analyzed by the Kaplan–Meier method. A difference between 2 groups was analyzed using the Chi-square and Mann–Whitney U tests, and multiple regression analysis was used to reveal factors predicting C(R)T effectiveness. All variables with significance of P < 0.001) higher than those of patients with a histological grade of 0–1 . On the other hand, the actuarial survival rates of patients who underwent NACRT with a histological grade 2 or greater  were significantly (P = 0.010) higher than those of patients with a histological grade of 0 to 1 .The overall survival curves of patients who underwent NACRT or NACT are shown in Figure 26 This study included patients who had been undergoing drug therapy for dyslipidemia.We first examined 113 patients who had undergone NACRT at our hospital and revealed that 51 (45 %) patients had achieved Grade 2 or greater treatment efficacy using the histological grading system for post-treatment evaluation. The univariate analysis between 62 patients with a histological grade of 0 to 1 and 51 patients with a grade of 2 or greater showed a significant difference in 3 factors: female sex, absence of dyslipidemia, and poorly differentiated tumor  patients had postoperatively achieved Grade 2 or above treatment efficacy. The univariate analysis between 125 patients with a histological grade of 0–1 and 21 patients with a grade of 2 or above showed a significant difference in 2 factors: absence of dyslipidemia and DCF therapy Table .Multivariate analysis was performed using the results of the univariate analysis Table . The sel11 In a study of esophageal resection after CRT, Swisher et al reported that 3-year survival rates were significantly higher among patients who had smaller remnant tumors in postoperative histopathological examination.8 In addition, Law et al showed that pN0, female sex, and R0 were statistically significant good prognostic factors.9 According to Schneider et al10 and Okumura et al,11 after R0 resection surgery, prognosis was significantly better among patients with shrunken tumors or with N0 classification. In the present study also, NAC(R)T, when resulted in downstaging due to tumor shrinkage and achieved Grade 2 or greater treatment efficacy based on the histological grading system, increasing survival rates were revealed. These findings therefore showed that it is highly feasible to predict the outcome of NAC(R)T preoperatively. If such prediction is possible, we can select therapy that is more suitable to each patient. In this study, we therefore investigated pretreatment factors associated with the tumor-shrinking effects of NAC(R)T and revealed that factors predicting NACRT effectiveness were female sex, absence of dyslipidemia, and histologically poorly differentiated tumor, whereas factors predicting NACT effectiveness were the absence of dyslipidemia and DCF therapy.In general, a postoperative increase in survival rates among patients treated with NACRT or NACT is attributed to the tumor-shrinking effect of NAC(R)T.16 According to Owaki et al, endoscopic ultrasound performed before and early after CRT predicted treatment outcome accurately with sensitivity of 85 % and specificity of 95 %, which was comparable with histopathological evaluations.12 In addition, Okumura et al performed preoperative combination examination of esophagography and endoscopy and showed that combination examination predicted histopathological outcomes with ≥80% accuracy.13 However, these studies predicted histopathological treatment outcome using imaging data obtained before and after CRT, but real prediction based solely on patient background factors, biochemical data, or preoperative evaluation items which are available before the treatment is started, has not been performed. Other studies performed positron emission tomography-computed tomography before treatment to show the correlation between the accumulation of fluoro-D-glucose (FDG) and the histological grading of treatment outcome.16 However, no correlation between the preoperative accumulation of FDG and histopathological findings was observed in the database at our hospital. In this study, we therefore used only pretreatment factors such as patient background, pre-CRT biochemical data, and tumor and treatment factors to reveal factors associated with Grade 2 or above treatment outcome. As shown in Tables To date, several studies have reported imaging findings as the predictors of the effectiveness of CRT.P < 0.001), and first of all, this might have been a reason for female sex being a significant factor even though the Brinckman index which was included in the initial patient factors was not the factor predicting the CRT effectiveness. The Brinckman Index was obtained using the following equation: number of cigarettes smoked per day × number of years smoked.27 Smoking is known to induce systemic hypoxia which decreases the radiosensitivity of cells as well as tumors.34 In addition, nicotine was reported to induce radioresistance.35 Therefore, a higher smoking rate in our male patients than in female patients may have contributed to the suppression of CRT efficacy because of a reduction in radiosensitivity due to hypoxia and an increasing radioresistance due to nicotine. Second, female hormone estrogens have beneficial effects on plasma lipid and lipoprotein concentrations and reduce arteriosclerosis extent on a number of animal models.38 Although the arteriosclerotic disease generally increase significantly after menopause, the incidence of arteriosclerotic disease among female was much lower until at least age 75.40 In this study, the age of the patients were around 60; therefore, the risk of arteriosclerosis of the female patients is lower than male patients. A relation between arteriosclerosis and treatment resistance is indicated on the following paragraph. In this regard, however these 2 reasons are only a hypothesis thoroughly. If we can accumulate more cases, a more precise analysis might show strong similarities.However, no previous study has shown that CRT is more effective in female than in men. In this study, the rate of smoking was significantly lower in female patients than in male patients T, because of tumor hypoxia enhanced by arteriosclerosis and the expression of p66Shc. Our study is the first clinical, but not basic, study to report similar findings.A novel finding of this study is that the prevalence of dyslipidemia affects the efficacy of NAC(R)T. We can guess arteriosclerosis are strongly related between the efficacy of NAC(R)T and dyslipidemia. In the past reports, it is well known that the arteriosclerosis is strongly associated with dyslipidemia.The limitation of this study was possible bias in the selection of surgery and neoadjuvant therapy because this was a retrospective study of NAC(R)T. The treatment applied is rather heterogeneous. NACT is the standard treatment for advanced esophageal carcinoma  in our hospital. On the other hand, there is a tendency to indicate NACRT in patients with relatively advanced cancer . In fact, NACRT is an accepted standard of treatment with locally advanced esophageal cancer. In addition, this study enrolled patients with esophageal cancer who had successfully undergone surgery after NACRT, indicating that these patients had relatively good general conditions and cancer had progressed only up to a certain point. Furthermore, at our hospital, we tend to select DCF therapy for patients with highly advanced cancer, indicating that clinical stage is less severe in patients undergoing NACT with FP than those undergoing NACT with DCF. Finally, no review pathology was performed, but routine pathology assessed in this study.The findings of this study revealed that female sex, absence of dyslipidemia, and poorly differentiated tumor are the predictors of NACRT efficacy, with the absence of dyslipidemia also being a significant factor for NACT. The elucidation of clinicopathological factors that can predict the outcome of neoadjuvant therapy will help us establish a more effective treatment plan for each patient.


Objective. Increased coagulation activation may contribute to the high incidence of cardiovascular complications observed in obese and type 2 diabetes (T2D) subjects. Although tissue factor (TF), the primary initiator of coagulation is increased in obesity, its expression in adipose tissues and its association with metabolic parameters are unclear. We sought to compare TF expression in plasma and adipose tissues of obese subjects with and without T2D, its correlation with metabolic parameters, and regulation in response to antidiabetic drugs. Methods Subjects were recruited from diabetes clinics and adipose tissue was obtained by needle biopsy of lower subcutaneous abdominal depot. For the intervention study, subjects were randomized into treatment groups with rosiglitazone or metformin for 4 months. Results. Plasma TF antigen, activity, and adipose TF mRNA were greater in obese T2D subjects compared with obese nondiabetics. Plasma TF activity correlated with fasting insulin, glucose, and free fatty acids, (FFAs), and adipose TF mRNA correlated with plasma FFA. Plasma TF activity was reduced by metformin and increased with rosiglitazone treatment. Conclusions. Specific diabetes-related metabolic parameters, but not obesity per se, are correlated with TF expression. Regulation of TF activity by different classes of antidiabetic drugs may relate to protective or adverse cardiovascular outcomes. Obesity is a major risk factor for the development of type 2 diabetes (T2D), and clinical studies have established an increased incidence of thrombosis and cardiovascular disease as a primary cause of mortality in diabetic patients , 2. T2D TF is the primary initiator of the coagulation pathway and is the cell surface receptor for coagulation factors VII and VIIa. Cell surface or microparticle- (MP-) associated TF-FVIIa complex triggers extrinsic coagulation leading to FXa-mediated generation of the downstream coagulation protease thrombin, fibrin deposition, and platelet activation. Higher plasma concentrations of FVII , increasWhereas plasma TF activity and antigen levels have been shown to be increased in obese subjects as well as in patients with T2D, whether its expression is higher in obese diabetics compared with obese nondiabetics is unclear. This is especially important since all obese subjects are not necessarily diabetic. In genetically or high fat diet induced obese mice that are also diabetic, TF activity is increased in the blood and its activity and gene expression increased in adipose tissues –17. Howe2) > 30 as previously described [Human subject protocols were approved by the Committee on Human Investigation at the University of California, San Diego (UCSD), and all subjects provided written informed consent. Subjects were recruited from diabetes clinics and classified as diabetic or nondiabetic by their response to a 75 g oral glucose tolerance test according to the American Diabetes Association criteria and classified as obese if their BMI . Statistical analysis was evaluated using the GraphPad Prism program . The statistical significance of differences within and between groups was analyzed by the Student's paired and unpaired t-tests. Correlations were calculated using the Pearson correlation. A P value < 0.05 was considered as the level of significance.Plasma TF antigen was determined using the IMUBIND Tissue Factor ELISA kit, and TF procoagulant activity in plasma was determined using the chromogenic Actichrome TF activity assay according to manufacturer's instructions . Adipose TF gene expression was determined by real-time quantitative RT-PCR as previously described . cDNA sy2) were 35.6 ± 5.6 and 35.6 ± 7.1, respectively. Fasting levels of plasma glucose, insulin, free fatty acids (FFAs), and HbA1c were significantly higher in the obese diabetic cohorts, while no differences were observed for plasma triglycerides between the two groups. Plasma TF activity, plasma TF antigen, and adipose TF mRNA expression were significantly increased in obese diabetics compared with obese nondiabetics  plasma samples are directly incubated with FVIIa, FX, and a chromogenic substrate for FXa. A limitation of this assay is that the values obtained tend to be somewhat overestimated. However, regardless of the absolute levels of TF activity, we believe that, on a relative basis, the observation that plasma TF activity is higher in obese T2D relative to obese nondiabetics is relevant. In the plasma, TF exists in the form of microparticles shed from apoptotic or activated cells, as well as an alternately spliced soluble form of TF. It should be noted that the TF activity and antigen assays used did not discriminate between these various forms of TF but rather measured total plasma TF.Since metabolic changes observed in T2D may contribute to elevated TF expression, we determined the correlation of TF expression with a number of metabolic parameters. As indicated in Hyperinsulinemia is associated with insulin resistance and T2D, and insulin administration has been demonstrated to increase circulating TF in healthy and T2D subjects , 20 and κB (NF-κB) and Jun N-terminal kinase (JNK) signaling pathways [κB and JNK signaling cascades. A role for FFA in TF induction was confirmed by our finding that TF expression in adipocytes is increased by palmitate , the most abundant plasma FFA in obesity.In this study, the metabolic parameter that showed the strongest correlation with plasma TF activity and antigen and the only correlate associated with adipose TF expression was FFA . Obesitypathways . It is tMetformin, a member of the biguanide family, is one of the most commonly used antidiabetic drugs and is highly effective in lowering blood glucose and improving peripheral insulin sensitivity in patients with T2D . In addiγ (PPARγ) are potent insulin sensitizers and highly effective oral medications for T2D [Thiazolidinediones (TZDs) that act through the nuclear receptor peroxisome proliferator-activated receptor- for T2D . However for T2D . While t for T2D . To dete for T2D . DespiteIn conclusion, our study shows that plasma and adipose TF expression is increased in obese T2D compared to obese nondiabetic subjects and significantly correlated with FFA. Regulation of TF activity by different classes of antidiabetic drugs may relate to protective or adverse cardiovascular outcomes.


Dairy cows mobilize large amounts of body fat during early lactation to overcome negative energy balance which typically arises in this period. As an adaptation process, adipose tissues of cows undergo extensive remodeling during late pregnancy and early lactation. The objective of the present study was to characterize this remodeling to get a better understanding of adaptation processes in adipose tissues, affected by changing metabolic conditions including lipid mobilization and refilling as a function of energy status. This was done by determining adipocyte size in histological sections of subcutaneous and retroperitoneal adipose tissue biopsy samples collected from German Holstein cows at 42 days prepartum, and 1, 21, and 100 days postpartum. Characterization of cell size changes was extended by the analysis of DNA, triacylglycerol, and protein content per gram tissue, and β-actin protein expression in the same samples. In both adipose tissue depots cell size was becoming smaller during the course of the study, suggesting a decrease in cellular triacylglycerol content. Results of DNA, triacylglycerol, and protein content, and β-actin protein expression could only partially explain the observed differences in cell size. The retroperitoneal adipose tissue exhibited a greater extent of time-related differences in cell size, DNA, and protein content, suggesting greater dynamics and metabolic flexibility for this abdominal depot compared to the investigated subcutaneous depot. Energy metabolism of dairy cows is continuously subjected to adjustments driven by the varying energy status of the lactation cycle. Consequently, this adaptation process substantially affects the metabolism of adipose tissue as the main organ for energy storage –3. Late Within the lactation cycle, the early postpartum period is of special importance in terms of adipose tissue metabolism, as this time period is often affected by pathophysiological events ,9. Well-Studying the changes of indicative components of adipose tissues and relating these to changes of adipocyte size would help further improve our understanding of the dynamic process of adipose tissue remodeling. Therefore, the present study aimed to describe adipocyte size  and composition  of adipose tissues at 4 distinctive time points in the course of the periparturient period: 42 days (d) prepartum, and 1 d, 21 d, and 100 d postpartum. These measurements were conducted on consecutively collected biopsy samples from the same animals, allowing the description of dynamic changes proceeding during the periparturient period within the adipose depots of individual animals. Both subcutaneous (SCAT) and retroperitoneal adipose tissues (RPAT) were studied to gain more information on depot-selective characteristics of adipose tissue cellularity and remodeling. Results of the present study provide a deeper insight to the structural aspects of adipose tissue plasticity in response to the dynamic changes of energy homeostasis throughout the periparturient period in dairy cows.Twenty German Holstein cows were used for tissue sampling. The study was conducted at the Institute of Animal Nutrition, Federal Research Institute for Animal Health , and was approved by the Lower Saxony State Office for Consumer Protection and Food Safety  in agreement with the German Animal Welfare Act (permit number: 33.9-42502-04-11/0444). All surgery was performed under local anesthesia, and all efforts were made to avoid suffering of the animals during the study.Cows were in their second, third, or fourth lactation, and were selected for this study to achieve homogeneity in body weight, BCS, and milk yield of previous lactation, in order to attenuate possible effects of different condition and merit. All animals were kept in a freestall housing system, were clinically healthy, and were dried off 8 weeks before the expected date of parturition. Cows were fed ad libitum and had free access to water. Diets were formulated as a grass-silage and corn-silage based total mixed ration according to the recommendations of the Society of Nutrition Physiology  for transition cows. The study period started when cows reached 42 d prepartum and ended at 100 d postpartum. Body condition score of the cows was registered according to the 5-point scale 42 d prepartum and 1 d, 21 d, and 100 d postpartum.Adipose tissue biopsy samples were collected from all 20 cows from the SCAT and the RPAT depot 42 d before the expected time of parturition  as well as 1 d, 21 d, and 100 d postpartum, according to ,18. Afte2) of 164 ± 13 (mean ± SEM) cells was measured in ImageJ 1.48. Cross-sectional area of cell was assessed by histomorphometry and was referred to as ‘cell size’ throughout the manuscript.Histological sections of SCAT and RPAT samples obtained from 13 out of the 20 cows were prepared using a Leica Jung CM3000 cryostat at -30°C. In case of all 4 time points the samples of the same 13 cows were used. The samples of the remaining 7 cows were not suitable for histomorphometric evaluation due to technical reasons. Tissue samples embedded in Tissue Tek were cut into 10 μm sections. Six non-adjacent sections of each sample were mounted onto glass slides . Sections were fixated in 4% formaldehyde for 10 min and then hematoxylin-eosin stained. Meyer’s Hemalaun solution  was applied for 5 min, and 0.25% eosin solution  was applied for 2 min to the sections. After dehydration in ethanol and clearing in xylol, sections were covered with a cover slip attached with Depex . Tissue sections were visualized using an Olympus IX70 microscope and digitally captured using a Leica DFC 290 camera. Exemplary pictures of hematoxylin-eosin stained tissue slides are shown in To gain additional information on changes of adipose tissue composition in the course of the periparturient period, DNA, TAG, and total protein content, and β-actin protein expression was quantified in the SCAT and RPAT samples of all 20 cows.To isolate DNA from the samples, 100 mg of tissue was homogenized in 1 ml of DNAzol reagent  using an Eppendorf pestle. Homogenates were incubated at 60°C for 5 min with continuous shaking at 350 rpm and briefly ultrasonicated to ensure complete cell lysis. Centrifugation at 10,000 g for 10 min at 4°C was performed in order to remove insoluble tissue fragments. DNA in the supernatant was precipitated, washed and then resuspended in 8 mM NaOH solution according to the manufacturer’s protocol. Finally, measured DNA concentrations were corrected for wet weight of the tissue sample and results were expressed as μg DNA per g tissue.Triacylglycerol content of tissue samples was measured using a colorimetric kit . To prepare homogenates, approximately 500 mg tissue was ground in liquid nitrogen. From this tissue powder, a representative aliquot of 50 mg was weighed and mixed with 1 ml 5% Nonidet P40 detergent solution . This mixture was further homogenized with a FastPrep-24 tissue homogenizer  and incubated at 99°C for 5 min with continuous shaking at 300 rpm. Afterwards, samples were centrifuged at 10,000 g for 2 min and the sediment was discarded. Incubation and centrifugation were repeated to maximize lipid extraction yield. Triacylglycerol concentration in the lipid extract was measured according to the manufacturer’s protocol with a spectrophotometer. The measurement was based on the enzymatic hydrolysis of TAG and the colorimetric detection of the released glycerol after oxidation. Finally, measured TAG concentrations were corrected for tissue wet weight and results were expressed as mmol TAG per g tissue.Total protein concentration was determined based on the Bradford method. To extract proteins, the same tissue powder was used as for the TAG content measurement. One hundred milligram of this powder was homogenized in a lysis buffer  with a FastPrep-24 tissue homogenizer . Protein extracts were centrifuged at 10,000 g for 5 min at 4°C. Protein concentration was measured in the corresponding fraction by using Bradford reagent (Serva Electrophoresis GmbH) according to the manufacturer’s protocol. Finally, measured protein concentrations were corrected for wet weight of the sample and results were expressed as mg total protein per g tissue.Protein extracts prepared for protein content measurement were used to quantify β-actin expression by Western blotting. Samples were diluted to 0.5 mg total protein per ml in loading buffer  and heated at 95°C for 5 min. Twenty microliter of the diluted samples were separated by SDS-PAGE on 8.1% hand casted gels and transferred to nitrocellulose membranes by using a Trans-Blot Turbo Transfer System . Membranes were blocked in a PBS-based solution containing 5% fat-free milk powder (Carl Roth GmbH) and 0.1% Tween 20 (Sigma-Aldrich) for 1 h at room temperature. Blocked membranes were incubated for 1 h at room temperature with a mouse monoclonal anti-β-actin antibody . Afterwards, membranes were incubated with a peroxidase conjugate anti-mouse secondary antibody  at room temperature for 1 hour. Immunodetection was performed by incubating the membranes with LumiGlo reagent  and chemiluminescence was detected by a ChemiDoc XRS+ system (Bio-Rad Laboratories GmbH). Exemplary pictures of membranes are shown in 2), medium , big , or large . The distribution pattern between time points were analyzed both in SCAT and in RPAT by a one-way ANOVA with a Tukey’s multiple comparison test. Cell size and tissue composition data were tested for normal distribution by the Shapiro-Wilk test. The median of the measured cell size values within each sample was registered and assigned to the corresponding sample as a single ‘cell size’ value. Cell size, DNA content, TAG content, total protein content, and β-actin protein expression of SCAT and RPAT samples were analyzed by a two-way ANOVA for factors ‘time related to parturition’ and ‘tissue depot’ with a Tukey’s multiple comparison test. Level of statistical significance was set at P < 0.05. Statistical tests were performed in GraphPad Prism 6.0.Cell size data were analyzed for relative (%) frequency distribution, with classification of cells as small  as shown in The overall decrease in adipose cell size was in agreement with the change from anabolism to catabolism in adipose tissue metabolism of periparturient cows ,7,20,21,The increased number of small cells registered on 100 d postpartum shown in  could beDNA quantification revealed that the DNA content of RPAT was greater 100 d postpartum than during early lactation (P < 0.05) as shown in In contrast to our expectations, TAG content per tissue wet weight was not significantly different between the observed time points . HoweverTotal protein content was lower at all the postpartum time points in SCAT (P < 0.05), and was lower at d 21 postpartum in RPAT compared to the other time points (P < 0.01) as shown in As shown in The current findings extended previous work investigating adipose tissue of slaughtered cows, by tracking the dynamic changes proceeding during the periparturient period in the same individual animals. However, as a limitation of the study, it has to be noted that the analysis of biopsy samples still provided information of single time points only as snapshots. Consequently, it could not be extrapolated how the studied variables were changing in the time frames between the samplings. Still, studying adipose tissue morphology at these critical time points provided data that allow us to characterize remodeling of SCAT and RPAT in a descriptive manner. Additionally, further mechanistic studies should be conducted addressing the dynamics of metabolic processes that account for the observed differences in adipose tissue morphology.In conclusion, RPAT was suggested to undergo a more dynamic remodeling process during the periparturient period, implying a higher plasticity of RPAT compared to SCAT.S1 FigMeasure bar indicates 100 μm.(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.


The long-term effects on bone health of nutritional status in adolescence are unclear. The impact of adolescent and current body mass on bone mass in young adulthood in rural India was assessed. Current lean mass was a more important determinant of bone mass than thinness during adolescence in this population.Adolescence is a crucial period for skeletal growth. However, the long-term effects on bone health of nutritional status in adolescence, particularly in the context of nutritional transition, are unclear. The current manuscript assessed the impact of adolescent and current body size on bone mass in young adulthood in an Indian rural community that is undergoing rapid socioeconomic changes.The Andhra Pradesh Children and Parents Study is a prospective cohort study in Hyderabad, India. In 2003–2005, the study collected anthropometric and cardiovascular data on adolescents (mean age = 16 years old). The second and third waves of the study in 2009–2012 collected data on current anthropometric measures, areal bone mineral density (aBMD) in hip and lumbar spine (L1–L4) measured by dual-energy X-ray absorptiometry, and living standards of the trial participants who were now young adults (mean age = 22 years old).2 during adolescence, while the median BMI as young adults was 19.3 kg/m2. Lower aBMD during adulthood was associated with lower adolescent BMI  for hip aBMD 0.017 (0.013 to 0.022) and LS aBMD 0.012 (0.008 to 0.016)). This association was attenuated upon adjustment for current fat and lean mass (β (95 % CI) for hip aBMD 0.00 (−0.005 to 0.005) and LS aBMD 0.005 (0.000 to 0.01)). There was clear evidence for positive associations between aBMDs and current lean mass.The median body mass index (BMI) of the 722 participants included in this analysis was 16.8 kg/mCurrent lean mass was a more important determinant of bone mass than thinness during adolescence in this population. Weight gain during late adolescence and young adulthood coupled with improvement in lean mass may help to mitigate any adverse effects that pre-adulthood undernutrition may have on bone mass accrual. Suboptimal peak bone mass is associated with higher risk of osteoporotic fractures in later life , 2. StudUndernutrition is commonly observed in low and middle income countries (LMICs). In India, the prevalence of undernutrition remains high although it has been slowly declining over the last 2 decades , 6. As aA number of studies have suggested positive associations between adult bone mass and birthweight as well as weight during infancy –10. On tWhile studies have generally found a positive association between body mass and bone mass, fat and lean mass may be differently associated with bone mass –15. LeanThe Andhra Pradesh Children and Parents Study (APCAPS) is a prospective cohort study from southern India. The study community has been experiencing nutritional transition due to urbanization over the past decade. The current manuscript assessed whether being underweight during adolescence is associated with lower peak bone mass in young adults, some of whom have experienced improvements in nutritional status since adolescence.The analyses in this study used data from three waves of data collection  of the APCAPS study, established through long-term follow up of the Hyderabad Nutrition Trial (HNT). The HNT studied impact of the Integrated Child Development Services (ICDS) scheme, a national community outreach program providing food supplementation along with health, hygiene, and nutrition education, immunization, anemia control, and basic health care to pregnant and lactating women and children under the age of 6 years .p=0.007) increase in the birth weight of the offspring [p = 0.007) taller and had more favorable measures of insulin resistance and arterial stiffness as shown by a 20 %  lower homoeostasis model assessment score, which describes levels of insulin resistance, and 3.3 %  lower augmentation index.A detailed description of the initial trial (HNT) and the first wave of data collection (the first follow-up of the HNT) have previously been published . Brieflyffspring . During ffspring . The adoSince the second and third waves of data collection were conducted within a relatively short period of time (2009–2012), the analyses in this manuscript combined data from these two waves of data collection (W2/3). W2/3 examined markers for chronic diseases affecting cardiovascular, musculoskeletal, and mental health. All consenting participants underwent DXA measurements at the National Institute of Nutrition (NIN), Hyderabad, and physical measurements at NIN (W2) or the village clinics (W3). In cases where participants attended both waves of data collection, the data from the third wave were used, unless there were artifacts in DXA scans from the W3, which prompted the use of data from W2.The present analyses were restricted to participants from the first wave of data collection who also underwent DXA scans during W2/3.A semi-structured questionnaire was administered to all participants by a trained interviewer. A subset of questions (14/29) from the Standard of Living Index (SLI) in the National Health Family Survey-2, a summary measure of household level asset-based scale devised for Indian surveys, was used to estimate socioeconomic position, as joint family structures are common in rural India . We collFour puberty stages were set based on sexual maturation on the basis of time since the onset of menstruation (girls) and testicular volume (boys) . The boy2). Cutoff points of BMI ≤17.0 and ≤18.5 were used for underweight in adolescence and adulthood respectively [Weight was measured to the nearest 0.1 kg with a digital SECA balance, and standing height was measured to the nearest 1 mm with a plastic stadiometer (Leicester height measure). Measurements were taken twice, and the average of two values was used in the analysis . Body mass index (BMI) was calculated as weight (kg)/height  was calculated from bone mineral content (BMC in g) and bone area (BA in cm2) for total hip and lumbar spine (L1–L4). Fat and lean mass indexes (FMI and LMI) were based on fat and lean mass (kg) from whole-body scans/height (m2). Major movements were counted as artifacts and removed from analysis with fat and lean mass.Bone mass measurements were assessed with DXA on a Hologic Discovery A model. The whole body scan was performed with the participant supine on the scanning bed with their arms resting by their sides. On the basis of repeated measurements for 30 participants with Hologic Discovery A, the coefficients of variation were determined to be 0.7 % for hip bone mineral density (BMD), 1.3 % for LS aBMD, and 0.9 % for whole-body aBMD. Women suspected of pregnancy were excluded from DXA scanning, and the scans were taken only after confirming the negative pregnancy by conducting urine pregnancy test. Standard Hologic software options were used to define regions of the body . Scans were coded for artifacts by a visual inspection, and those with major movement as well as incomplete scans were excluded from the present analyses. For lumbar spine (LS) scans, pathological changes such as osteoarthritis affecting two or more vertebrae were excluded; if only one vertebra was affected, the scan was reanalyzed after the affected part was excluded . Areal bDescriptive statistics were calculated for each sex. The associations of hip and lumbar spine BA, BMC, and aBMD with adolescent body size were modeled in multilevel regression models that accounted for village clusters (29 villages). FMI was log-transformed because it had a positively skewed distribution. Complete-case analysis was used.β: 0.08; p = 0.04). Residuals from the multilevel models were checked for normality (Shapiro-Wilk test) and heteroscedasticity and found reasonably normally distributed and homoscedastic at each level.Four models were fitted for each of the two outcome variables (hip and LS aBMD): Model 1 assessed each of the explanatory variables  BMI, current FMI, current LMI), adjusting for sex, age at W1, age at W2/3, height at W1 (cm), and height at W2/3 (cm). Model 2 examined the association between aBMD and adolescent BMI, adjusting for current BMI, age at W1, age at W2/3, sex, height at W1, and height at W2/3. In model 3, current BMI in model 2 was replaced with current FMI and LMI. Model 4 replaced current BMI in model 2 with conditional BMI to examine the effect of change in BMI, by using residuals from a regression model in which current BMI was regressed on adolescent BMI. We also adjusted model 3 for other potential confounders such as puberty stages at W1, adolescent height, current height, adolescent SLI, current SLI, and current tobacco use. Interaction terms between sex and adolescent BMI, current FMI, current LMI, and change in BMI were examined in models 3 and 4. There was weak evidence for an interaction with current FMI for LS aBMD, where the effect of FMI was slightly higher in female , the Indian Council of Medical Research (ICMR), Centre for Chronic Disease Control, and London School of Hygiene and Tropical Medicine . Approval was also sought from the village heads and their panchayats in each of the 29 villages. Written informed consent or witnessed thumbprint if illiterate was obtained from the participants prior to their inclusion in the study.Of the 1165 participants of the first wave of data collection (W1), 722 participants (62 %) had their height and weight measured both as adolescents and as young adults and also underwent DXA scans during the second and third waves of data collection (W2/3). Of those, scans without major artifacts were available in 710 (98 %) participants for hip aBMD and 715 (99 %) for lumbar spine aBMD. Eighty-seven percent of the participants also had scans without major artifacts for whole-body estimation of fat and lean mass. Information on the other variables including SLI and occupation was available for ≥99 % of the participants.Table Positive association between current aBMD and adolescent BMI was attenuated upon adjustment for current BMI in hip, but the association remained for lumbar spine Tables  and 4. TThere were less underweight young adults from this transitional rural community compared to during adolescence. Although these young adults on average had low bone mass, there was no clear evidence for an association between bone mass during young adulthood and thinness during adolescence when adjusted for current fat and lean mass. There was stronger evidence for a positive association between bone mass and lean mass than fat mass in young adulthood.2 for boys and 15.4 kg/m2 for girls) at age 11, although by age 33–39, the average BMI had increased to above 25. The study found positive associations between femoral neck and lumbar spine BMC and aBMD during adulthood and BMI at age 11, but similarly to our findings, these associations were attenuated upon adjustment for adult BMI. They also assessed changes in BMI in infancy, childhood, and adolescence and found that the change in BMI during adolescence was most strongly associated with adulthood bone mass. In our previous analyses, we found no strong evidence for a positive association between areal bone mineral density as young adults and early life nutritional supplementation [While there are a number of studies examining association between bone mass in later life and birthweight, there are relatively few studies focusing on the long-term effects of nutritional status during adolescence on adult bone mass . The Newentation .The study subjects in the APCAPS gained weight between late adolescence and young adulthood. The Penn State Young Women’s Health Study compared healthy women who gained weight in late adolescence (17–22 years) to those who had stable weight . Those wStudies have suggested different patterns of associations between aBMD and fat and lean mass , 28–30. It is important to note that aBMD in this study population was generally lower than values for bone mass values for young adults reported in a national DXA study in India . The indThe main strength of this study is the availability of longitudinal data on height and weight, allowing the assessment of long-term effects of undernutrition during adolescence on bone mass in young adulthood. The study subjects experienced a unique circumstance where nutritional status of the study subjects improved greatly toward the end of the skeletal growth phase due to socioeconomic development in their villages. This setting allowed for an assessment of potential mitigation of the effects of undernutrition in early adolescence through improved nutritional status in late adolescence and young adulthood. Another strength of the study was the use of fat and lean mass from DXA scans to understand how different types of body mass may be distinctly associated with bone mass.The study also had some limitations. The DXA measurements were not performed during adolescence, making it less clear whether and how bone mass improved, as weight, fat mass, and lean mass increased during adolescence. However, the association between body size and bone mass has been shown repeatedly in previous studies , 27, andIn healthy individuals, much of bone mass accrual occurs during adolescence. As socioeconomic development continues in low- and middle-income countries, many children and adolescents are experiencing the effects of nutritional transition. Our findings suggest that weight gain combined with improvement in lean mass in young adulthood may be able to help mitigate adverse effects of undernutrition during adolescence on bone mass in young adulthood.


The aim of our study was to evaluate the histological characteristics andprognosis of gastric cancer.Clinicopathlogical variables of 932 patients with gastric carcinoma admittedto the Department of Surgical Oncology at the First Hospital of China MedicalUniversity were analyzed retrospectively. Different histological characteristicsof gastric cancer were summarized and assigned score according to the malignancydefined by WHO classification, the scores were stratified into 4 stage, theprognosis of different stages were analyzed by Kaplan-Meier analysis and coxregression.Among the 932 patients, 246 (26.39%) had mixed histology type of gastriccancer. Compared to the pure histological type, mixed histological type of gastriccancer was significant associated with tumor size, lymph node metastasis and depthof invasion . The 5-year survival rates of advanced and earlygastric cancer patients with mixed type were 40.8% and 83.5% respectively, whichwere lower than those with pure type . Statisticallysignificant difference with stratification of early and advanced stage could beobserved between patients with the histological grading score. The data showedthat the histological score could be the independent factor of prognosis.The histological score is an independent factor of gastric cancer, it exertsan excellent ability to classify survival of patients with gastric carcinoma. Italso provides a new strategy and parameter for evaluating the biological behaviorand prognosis of gastric cancer. It might be easily thought out that tumor-related factors such as tumor size,lymphatic invasion, and venous invasion could be an indicator for progressivepotential of malignant tumors –3. HowevHistopathological type is an important prognosis factor, it is also to determinethe extent of surgical resection and formulated the basis for reasonable surgicalplan , 5. It pThe coexistence of different histological types of gastric cancer determines thethe complex characteristics of clinical behavior and prognosis, the mixedhistological type accounted for over 25% of all gastric cancer , 10. SinIn this study, we attempted to evaluate the histological characteristics andestablish simple criteria using the results of histopathological tumor-relatedfactors to predict prognosis of patients with gastric carcinoma.th UICC/AJCC (2012) stagingsystems.All patients with gastric cancer who underwent surgery at the Department ofSurgical Oncology, First Hospital of China Medical University, during January 1980to December 2006 were entered into a prospectively maintained database. Ethicalapproval for this research was obtained from the Research Ethics Committee ofChina Medical University, China. In total, 1077 patients underwent D2lymphadenectomy and achieved radical (R0) resection for histologically provengastric carcinoma. Follow-up was complete for the entire study population to June2005. Among them, 24 died in the postoperative period and 43 were lost tofollow-up. Thus, 145 patients were excluded. Of the remaining 932 patients, Medianand mean follow-up period were 31 and 54 months (range: 3–313 months),respectively. Patients were treated exclusively by total or subtotal gastrectomywith lymphadenectomy, according to tumor location, adjuvant therapy orpostoperative chemotherapy was not administered to any patient. Cancer-specificsurvival was calculated from the date of primary surgical resection to the date ofgastric cancer associated death or to the date of recorded cancer progression.Tumor invasion (T), lymph node involvement (N) and TNM stage were classifiedaccording to the 7According to the previous studies of histological differentiation andmalignant degree of gastric carcinoma, non-mucinous adenocarcinoma were assigned as 1–3 points, respectively. Mucinousadenocarcinoma was assigned as 3 points, signet ring cell carcinoma wasassigned as 4 points, undifferentiated carcinoma was assigned as 4 points,a special type of stomach cancer as 4 points (these score still needsfurther refinement) Histological grading stage (H Stage) was divided into four groupsaccording to their scores, as follows: H1 (≤2 points), H2 (2–3 points), H3(3–4 points) and H4 (4–5 points).Each variable was used as an independent variable in a Cox proportionalhazards analysis run using the Kaplan-Meier method. This was done to screen thevariables for later inclusion in a multivariable model. To be included in themultivariable analysis, a variable had to be significant at α of 0.1 for the Waldtest. This was a test of the null hypothesis that the coefficient for all levelsof the variable of interest was equal to zero.All significant variables of the univariate analysis were included in thefirst run of a multivariable Cox proportionate hazard regression. In subsequentCox regressions, significantly different variables in their hazard ratios wereremained sequentially based on the z-statistic for the individual levels of eachcategorical variable. To remain in the final model, a variable had to besignificant at α of 0.05 at all levels.As stated above, the study included 932 patients undergoing gastrectomy forgastric carcinoma from 1980 to 2005. All patients followed until death or for amaximum 313 months. The overall 5-year survival rate was 41.1%. Adjuvant andchemotherapy treatment was rarely applied in this series. The frequencies of patientcharacteristics and epidemiological results are summarized in Table  Difference of survival reflected by tumor-related factors such as tumor size,tumor depth, lymph node metastasis was shown in Table  Patients stratified by Histological grading of 214 (55.9%), 182 (28.4%), 492(15.7%) and 44 (28.4%) defined Histological stage I, II, III and IV, respectively.Statistically significant difference with stratification of early and advanced stagecould be observed between patients with the histological grading score,respectively. Mixed histological type gastric cancer had worse prognosis in earlyand advanced stage Table  .Table 4The multivariate Cox stepwise proportional hazard model identified Macroscopictype , Histological grading , Tstage , N stage  as independentpredictors of prognosis. In the early gastric cancer, Histological grading , Tumor size  and N stage  as independent predictors of prognosis, histological grading were provedto be the highest HR ,superficial (>4 cm) and PenA, PenB may have a low incidence of lymph nodemetastasis with good prognosis after surgery . There iOf course, TNM classification system could exert an excellent ability toclassify survival of patients with gastric carcinoma also in the current study.Therefore, H grading system newly devised as well as TNM classification systemcould classify the prognosis of patients with gastric carcinoma with a strictstratification. This score system would provide objective information regardingthe outcome of patients treated with curative resection for gastriccarcinoma.In conclusion, H Stage that can be utilized in the majority of the instituteswould be quite simple criteria to predict prognosis of gastric carcinoma with astrict stratification.The histological score that we developed in the research exert an excellentability to classify survival of patients with gastric carcinoma, it could classifythe prognosis of patients with gastric carcinoma with a strict stratification. Thehistological score is an independent factor of gastric cancer. It also provides anew strategy and parameter for evaluating the biological behavior and prognosis ofgastric cancer.


Burkholderia glumae, is a destructive disease of rice. Because BGR tends to be highly affected by environmental conditions such as temperature and humidity, it is difficult to evaluate BGR resistance of diverse cultivars with different heading dates by using field inoculation. Molecular tagging of genes involved in BGR is an important objective for rice breeding.Bacterial grain rot (BGR), caused by the bacterial pathogen indica) that originated in India, and Hitomebore, a susceptible modern lowland cultivar (temperate japonica) from Japan. Second, by comparing the susceptibility of Kele and Hitomebore spikelets before and up to 3 days after anthesis, we found a dramatic decline in susceptibility at 1 day after anthesis in Kele but not in Hitomebore. Thus, we applied a modified method by inoculating spikelets at 1 day after anthesis for further analysis. To search for QTLs associated with BGR resistance, we measured the ratio of diseased spikelets  and the ratio of diseased spikelet area (RDSA) in 110 backcrossed inbred lines (BILs) derived from a cross between Kele and Hitomebore. One major QTL associated with both RDS and RDSA was detected on the long arm of chromosome 1. This QTL explained 25.7% and 12.1% of the total phenotypic variance in RDS and RDSA in the BILs, respectively, and the Kele allele increased BGR resistance.In this study, we mapped a quantitative trait locus (QTL) for BGR resistance by a modified cut-panicle inoculation method. First, we assessed the levels of BGR resistance in 84 cultivars by a standard cut-panicle inoculation technique, in which panicles are harvested and inoculated in the laboratory under controlled conditions. For the genetic analysis, we selected two cultivars: Kele, a resistant traditional lowland cultivar  contains supplementary material, which is available to authorized users. Burkholderia glumae causes bacterial grain rot (BGR) and seedling rot in rice (Oryza sativa L.), which are increasingly important diseases in global rice production , plants that are located near the diseased primary-infected plants are also attacked by the pathogen, thus establishing secondary infection. After infection, the color of the spikelets changes from the normal green color to reddish brown. Eventually, the infection may cause unfilled or aborted grains  , cut-panicle inoculation is recognized as a useful method for evaluating BGR resistance  derived from a cross between Kele (resistant) and Hitomebore (susceptible). To minimize the effect of heading date on BGR and to obtain the greatest degree of discrimination between susceptible and resistant plants, we employed a modified assessment method for BGR resistance during the genetic analysis. By using this method, we successfully mapped a major BGR-resistance QTL on chromosome 1.indica, 15 cultivars of tropical japonica, and 14 cultivars of temperate japonica , from 2.7 to 8.0 , and from 6.5 to 8.3 (temperate japonica), with Kele (indica) and Nishihomare (temperate japonica) being the most resistant and the most susceptible cultivars, respectively  from Japan with good eating quality, and it is widely grown in Japan. Kele is a traditional lowland cultivar that originated in India. Six days after cut-panicle inoculation, many spikelets of Hitomebore had brown lesions; in contrast, few spikelets of Kele had brown lesions, and most spikelets had no lesions at all . Although the scores of pot inoculation were lower than those of cut-panicle inoculation, the means and standard errors of RDS of Hitomebore and Kele by pot inoculation were 50.4 ± 12.3% and 26.0 ± 12.2%, respectively, and the difference was significant (P < 0.01). During maturation, RDS of Kele of 20 days after pot inoculation remained lower than that of Hitomebore, and the grain sterility rate of Kele of 30 days after pot inoculation was lower than that of Hitomebore  and Hitomebore  Figure B. HitomeP < 0.05). Therefore, we concluded that inoculating panicles containing only spikelets at 1 day after anthesis  would improve the sensitivity of BGR screening.In the standard cut-panicle inoculation method, the panicles are inoculated 3 days after the first spikelets undergo anthesis. Because spikelets within the same panicle are not synchronized on the day of inoculation, the panicles contain spikelets before anthesis and spikelets 0, 1, 2, and 3 days after anthesis. We measured RDS of Kele and Hitomebore by inoculating panicles containing only spikelets before anthesis or spikelets at 0, 1, 2, or 3 days after anthesis . Culm length, panicle length, number of panicles, spikelet length, and spikelet width were not significantly correlated with either RDS or RDSA. The correlation between heading date and RDSA was negative and significant at the 5% level (r = −0.247), but the correlation between heading date and RDS was not significant.For QTL analysis, we measured the ratio of diseased spikelet area (RDSA) as well as RDS. The inoculated spikelets were imaged by using a scanner and RDSA was calculated by SmilePlant (Software of Measuring Image for Lesion Estimation), which we developed for this analysis. One drawback to this method was that in Kele, the spikelet color changes from green to deep purple during maturation . This characteristic was also seen in some of the BILs. In most cases, we could measure RDS and RDSA until 8 days after inoculation, because the biological color change had not yet begun. However, in some cases, the biological color change starts just after heading when the plant is exposed to environmental conditions such as strong winds from a typhoon. In this study, once any biological color change had occurred, we could no longer measure RDSA. As a result, we could acquire data for RDS from 100 lines and for RDSA from 79 lines. The BILs showed a wide range of variation for both RDS (11.9% to 100%), and RDSA (5.5% to 71.0%) Figure . The BILTo genotype the BIL population, we used a 384-plex set of single-nucleotide polymorphism (SNP) markers that were selected by using diverse accessions of cultivated Asian rice , we expect that this modified method allowed us to detect differences in BGR resistance among the BILs with greater precision than the standard method. By using this method, we were able to detect a QTL for BGR resistance on chromosome 1.In this study, we slightly modified the screening method from that reported by Miyagawa and Kimura . AccordiThe reason for the quick decline of susceptibility in Kele between anthesis and 1 day after anthesis is still unknown. One hypothesis is that the lemma and palea close more quickly in Kele than in Hitomebore, so that Kele is protected physically from the pathogen by 1 day after anthesis. Another hypothesis is that physiological factors such as accumulation of compounds related to resistance were induced in Kele shortly after anthesis.indica and tropical japonica cultivars, whereas the temperate japonica cultivars were all susceptible . Furthermore, additional resistance genes will be required to breed stable BGR-resistant cultivars. Thus, it is necessary to test resistant cultivars other than Kele to search for new QTLs.We measured the panicle disease scores among 84 cultivars by the standard cut-panicle inoculation method and found a wide range of variation for BGR resistance among the e Figure B. Thus, We mapped a QTL for BGR resistance on the long arm of chromosome 1 by using BILs derived from a cross between Kele and Hitomebore. The Kele allele at the QTL decreased both RDS and RDSA. By further analysis of the QTL, we could not only reveal the genetic mechanism of BGR resistance, but also advance the marker-assisted selection in rice breeding programs.Oryza sativa L.) cultivars were grown in paddy fields at NIAS in Tsukuba, Japan. Seeds from the WRC were obtained from the Gene Bank of the NIAS. WRC cultivars were categorized into indica, temperate japonica  with Kele and were used to construct a linkage map and to search for QTLs for resistance to BGR.Eighty-four rice  equipment for those cultivars to promote heading. The SD equipment was set up in the field; the cover of the apparatus, which was able to shut out sunlight, automatically closed at 1700 hours and opened at 0800 hours. Cultivars were categorized by heading date and inoculated on different dates (from July 30 to August 23).Eighty-four rice cultivars were grown in paddy fields in 2010. Thirty-day-old seedlings were transplanted at a density of one seedling per hill on 19 May. Each cultivar was planted in a single row of 10 hills at a spacing of 15 cm between hills and 30 cm between rows. Basal fertilizer was applied at a rate of 56 kg N, 56 kg P, and 56 kg K haFusarium head blight resistance in barley , Kyu82-34-2 (MAFF 302744), which possessed stable virulence and was maintained at the National Institute of Agro-Environmental Sciences, was used as a source of inoculum. Bacterial inocula were incubated on agar-solidified LB medium (2% agar) at 28°C for 4 days and suspended in sterilized, distilled water at a concentration of 108 per ml. Before inoculation, 0.01% Tween-20 was added to the suspension to increase adhesion of inocula on the panicles. Panicles were spray-inoculated with a freshly prepared inoculum suspension (approximately 1.7 to 2 ml per panicle) by a small sprayer. The inoculated panicles were then placed in a plant growth chamber maintained at 25°C and 100% humidity for 20 h. After the infection period, the panicles were covered with a transparent plastic bag and moved to another growth chamber maintained at 27°C and >80% relative humidity for 6 days under a 14-h photoperiod with light intensity of 1000 lux. Three panicles per cultivar were inoculated, and disease symptoms were scored 6 days after inoculation using a 0–10 scale, where 0 indicated 0% infected spikelets per panicle (resistant), and 10 indicated over 90% infected spikelets per panicle (susceptible).We measured resistance to bacterial grain rot in these cultivars by a cut-panicle inoculation method. This was based on the reported method for rice  in 18-cm-diameter plastic pots. Plants were cultivated in a greenhouse at 25°C from November to April, and inoculation experiments were conducted in March. Bacterial inocula were prepared as described above. After inoculation, the pots were placed in a plant growth chamber maintained at 25°C and 100% humidity for 20 h. After the infection period, the inoculated plants were then returned to the greenhouse. For both of Kele and Hitomebore, eight plants (over ten panicles) were used for pot inoculation and at least six panicles were used for standard cut-panicle inoculation. Disease symptoms were scored 6 days after standard cut-panicle inoculation and disease symptoms were scored 6 days and 20 days after pot inoculation. Several types of spikelets were observed: (1) spikelets with no symptoms, (2) spikelets whose palea and lemma had reddish-brown lesions but diseased area <50% of spikelet area, and (3) spikelets with diseased area ≥50% (severe disease infection). Therefore, the RDS was determined as follows:0 = number of spikelets with no symptomsN1 = number of spikelets whose palea and lemma had reddish-brown lesions but diseased area <50% of spikelet areaN2 = number of spikelets with diseased area ≥50% (severe disease infection)NIn order to compare the resistance to BGR between Kele and Hitomebore during grain filling process, the grain sterility rate of 30 days after pot inoculation was also scored. The each grain sterility rate of Kele and Hitomebore was compensated by the each sterility rate of spikelets without inoculation.In 2011, we compared the BGR susceptibility among spikelets at several time points before or shortly after anthesis. Methods of plant cultivation were essentially the same as in 2010. In most cultivars, anthesis starts in the morning and ends around early afternoon, and each spikelet is open for approximately 50 to 80 minutes . Following the results from the inoculation timing experiments, we used a modified cut-panicle inoculation method in which panicles containing only spikelets at 1 day after anthesis were harvested and inoculated. Three panicles (ca. 40–60 spikelets) per each line were inoculated, and RDS and RDSA (described below) were scored 6 to 8 days after inoculation. The mean RDS and RDSA scores for each BIL were used for QTL analysis. Each inoculation test was confirmed by inclusion of Kele and Hitomebore as controls.In the BIL study, three plants per line were measured for culm length, panicle length, number of panicles, and heading date. Heading date means days to heading from sowing. Three panicles (ca. 40–60 spikelets) per line were measured for spikelet length and width by using SmilePlant (described below).For the QTL analysis, we measured the RDSA as well as RDS. The inoculated spikelets were removed from the panicle and scanned with an EPSON GT-X820 scanner . RDSA was calculated by SmilePlant (Software of Measuring Image for Lesion Estimation), which we developed for this analysis. SmilePlant was developed based on SmartGrain, high-throughput phenotyping software for measuring seed shape using image analysis .We performed linkage mapping using version 3.0 of MAPMAKER/EXP Additional file 2: Table S2: Comparison of BGR resistance between Kele and Hitomebore. (XLS 8 KB)Additional file 3: Figure S1: Frequency distributions of agronomic traits of BILs derived from a cross between Kele and Hitomebore. White and black arrowheads indicate mean values for Hitomebore and Kele, respectively. (TIFF 193 KB)Additional file 4: Figure S2: Linkage map for BILs derived from a cross between Kele and Hitomebore. The numbers on the left-hand side of each chromosome indicate map distances (cM) obtained using the Kosambi function. SNP marker names are shown on the right-hand side of each chromosome. Marker names are presented as abbreviations, which are defined in Additional file 2: Table S2. chr, chromosome number. (TIFF 2 MB)Additional file 5: Table S3: List of SNP markers used in the QTL analysis of BILs derived from a cross between Kele and Hitomebore. The SNP markers were selected from genome-wide SNP marker data  and ratio of diseased spikelet area (RDSA), measured by the modified method of cut-panicle inoculation, in BILs derived from a cross between Kele and Hitomebore. LOD score profiles of each chromosome (from chromosome Ch1 to Ch12) are oriented with the short arm of each chromosome at the left. Blue LOD curve indicates RDS; red LOD curve indicates RDSA. The LOD threshold used to declare putative QTLs for RDS and RDSA is indicated by the horizontal lines. (TIFF 194 KB)Additional file 7: Figure S4: Log-likelihood (top) and additive-effect plots (bottom) across (A) all 12 rice chromosomes and (B) chromosome 1 from the QTL analyses for BGR resistance (RDS and RDSA) and agronomic traits in BILs derived from a cross between Kele and Hitomebore. The LOD threshold used to declare putative QTLs in each population is indicated by the horizontal line. RDS: ratio of diseased spikelets, RDSA: ratio of diseased spikelet area, CL: culm length, PL: panicle length, NP: number of panicles, SL: spikelet length, SW: spikelet width, HD: heading date. (TIFF 2 MB)Authors’ original file for figure 1Authors’ original file for figure 2Authors’ original file for figure 3Authors’ original file for figure 4Authors’ original file for figure 5Below are the links to the authors’ original submitted files for images.