(b) I-V characteristics of the Ag/ZnO/Ag memristor. (c) The distribution of the set and reset voltages. Results and discussion Figure 1a shows the SEM image of a typical ZnO microwire, whose length is about 1.5 mm and diameter is about 20 μm. Interestingly, as clearly confirmed by the upper inset of Figure 1a, hierarchical structures can be observed

in the microwire. The formation of such ZnO hierarchical microwires can be attributed to the fast growth habit in <001 > direction and second nucleation on the side surfaces. Figure 1b presents the typical unipolar RS behaviors of the device. First, electrical stress was loaded through a 1.5-V-forming voltage to induce an LRS. The current compliance was restricted at 1 mA to prevent permanent breakdown. Subsequently, in such an LRS, when the voltage was swept from zero to positive values (1 V), the leakage current increased approximately linearly Androgen Receptor Antagonist and then very abruptly dropped

approaching to zero at 0.8 V (reset voltage, V reset). Such an abrupt current drop indicated that the device had been switched into HRS, which is a nonvolatile off state and will be inherited in the early stage of the next voltage sweeping. Finally, during the second voltage sweep, a sudden current increase at about 0.2 V (set voltage, V set) appeared. Such a sudden increase see more over the compliance value demonstrated that the device was switched into LRS again, which is the nonvolatile on state and can also be memorized in the following cycle. Furthermore, when sweeping the voltage to negative voltages, BCKDHA similar RS behaviors, including on-off switching and state memorizing, were also observed. Besides the above typical RS, some unusual phenomena were also observed. First, V reset was found to be always larger than V set as shown in Figure 1c, which is entirely different from the reported unipolar RS

from MIM thin films [3]. Second, V reset and V set distribute in 0.62 to 0.8 V and 0.19 to 0.4 V, respectively. Both of them are less than 1 V, which will be very beneficial for the future application with low energy cost. Importantly, there is no overlap between these two ranges. Such obviously separated V reset and V set warrant a high reliability for device operation and, hence, also beneficial to application. Finally, the V set distribution width is slightly larger than that of the V reset, which demonstrates that conducting filaments (CF) dominate the RS of such ZnO microwire memristors prepared in this study. According to the CF model [3, 11, 12], the formation of filaments (set) is more random than their rupture (reset) process due to the competition of different filamentary paths during the formation process. These ZnO microwire memristors exhibited very high stability as shown in Figure 2. The on and off resistance values were read at 0.1 V in 100 DC sweeping cycles. The reading values of HRS appear to fluctuate from 1.

7%) even at the highest concentration (3,000 μg/ml), we could conclude reasonably that the low cell selleck inhibitor viability (68.5%) which resulted from C-dot treated at the same concentration comes not from the

bare C-dots but from RNase A on the surface via its ribonuclease-mediated toxicity. So, by MTT assay, we have validated the potential of the RNase A@C-dots in cancer therapy. Figure 6 Cytotoxicity assay results. (a) MTT assay determined cytotoxicity profile of RNase A, C-dots, and RNase A@C-dots after 24 h incubation with MGC-803 cells at varied concentrations (sample size N = 3). (b) Dynamic monitoring cytotoxic response of MGC803 cells to RNase A, C-dots, and RNase A@C-dots. While MTT assay only gave the information of cytotoxicity at fixed time points, the time-dependent cell response profiling was performed using real-time cell electronic sensing

(RT-CES). Without cell labeling, the RT-CES learn more assay directly reflected changes in cell biological status including cell viability, cell number, morphology, and adhesion [36]. Briefly, increasing in cell adhesion or cell spread will result in a larger cell/electrode contact area which is presented by a larger cell index (CI) value, while on the other hand, toxicity induced cells can round up leading to a smaller CI [37]. In good accordance with the MTT, RNase A (150 μg/ml) or RNase A@C-dots with the same RNase A concentration (150 μg/ml) were used based on the results of MTT assay. RNase A alone can inhibit and kill cancerous cells with a final CI value very close to zero (Figure 6b), and RNase A@C-dots also show competent ability in killing cancer cells with a CI value of around 0.2 compared to 1.8 of cells alone. In fact, RNase A and C-dots featured some differences concerning their performances. After adding of RNase A, the CI value increased a little bit in the first 4 h and then decreased continuously, while the adding of RNase A@C-dots

resulted in a nearly unchanged CI value until about 50 h and then a decrease in CI value until the end. We suggest that this might have resulted from the difference of migration rate. In order to inhibit the cancerous cells, RNase A must enter cells and mount to Branched chain aminotransferase a certain concentration. Suffering from a lower migration rate, it takes more time for RNase A@C-dots to concentrate into the cells compared to RNase A. As expected, RNase A@C-dots could hardly be considered as toxic as the CI value kept increasing at the beginning of nearly 50 h. However, after 50 h, the CI value became lower than that of the control group. This may be caused by the concentration accumulative effect of RNase A@C-dots in the cells which could have an impact over the status of the cells within an acceptable range. So it is proven that the RNase A@C-dots could kill cancerous cells with its ribonuclease-mediated toxicity from surface-doped RNase A, and not C-dots itself.

CrossRefPubMed 20. Drath DB, Kahan BD: Phagocytic cell function in response to immunosuppressive therapy. Arch Surg 1984, 119:156–160.PubMed 21. Othieno-Abinya NA, Nyabola LO, Nyong’o AO, Baraza R: Nadir neutrophil counts in patients treated for breast

cancer with doxorubicin and cyclophosphamide. East Afr Med J 2001, 78:370–372.PubMed 22. Lacki JK, Mackiewicz SH, Leszczyński P, Muller W: The effect of intravenous cyclophosphamide pulse on peripheral blood lymphocytes in lupus erythematosus patients. Rheumatol Int 1997, 17:55–60.CrossRefPubMed 23. Leandro MJ, Edwards JC, Cambridge G: Clinical outcome in 22 patients with rheumatoid arthritis treated with B lymphocyte depletion. Ann Theum Dis 2002, 61:883–888.CrossRef 24. Weiner HL, Cohen JA: Treatment of multiple sclerosis selleck screening library with cyclophosphamide: critical review of clinical and immunologic effects. Mult Scler 2002, 8:142–154.CrossRefPubMed 25. Asou N, Suzushima H, Hishimura S, Okubo T, Yamasaki H, Osato M, Hoshino K, Takatsuki K, Mitsuya H: Long-term remission in an elderly patients with mantle cell leukemia treated with low-dose cyclophosphamide. Am J Haematol 2000, 63:35–37. PublisherFullTex​t CrossRef 26. Shalit I, Kletter Y, Halperin D, Waldman D, Vasserman E, Nagler A, Fabian I: Immunomodulatory effects of moxifloxacin in comparison to ciproflaxin and G-CSF in a murine model of cyclophosphamide-induced leucopenia. Eur J Haematol

2001, 66:287–296.CrossRefPubMed Torin 2 research buy 27. Artym J, Zimecki M, Paprocka M, Kruzel ML: Orally administered lactoferrin restores humoral immune response in immunocompromised mice. Immunol Lett 2003, 89:9–15.CrossRefPubMed 28. Artym J, Zimecki M, Kruzel ML:

Reconstitution of the cellular immune response by lactoferrin in cyclophosphamide-treated mice is correlated with renewal of T cell compartment. Immunobiology 2003, 207:197–205.CrossRefPubMed 29. Artym J, Zimecki M, Kruzel ML: Normalization of peripheral blood cell composition in cyclophosphamide treated mice by lactoferrin. Med Methane monooxygenase Sci Monit 2004, 10:BR84–89.PubMed 30. Zimecki M, Weber-Dąbrowska B, Łusiak-Szelachowska M, Mulczyk M, Boratyński J, Poźniak G, Syper D, Górski A: Bacteriophages provide regulatory signals in mitogen-induced murine splenocyte proliferation. Cell Mol Biol Lett 2003, 8:699–711.PubMed 31. Espevik T, Nissen-Meyer J: A highly sensitive cell line, WEHI 164 clone 13, for measuring cytotoxic factor/tumor necrosis factor from human monocytes. J Immunol Methods 1986, 95:99–105.CrossRefPubMed 32. Van Snick J, Cayphas S, Vink A, Uyttenhove C, Coulie PG, Rubira MR, Simpson RJ: Purification and NH2-terminal amino acid sequence of a T-cell-derived lumphokine with growth factor activity for B-cell hybridomas. Proc Natl Acad Sci USA 1986, 83:9679–9683.CrossRefPubMed 33. Buhles WC Jr, Shifrine M: Increased bone marrow production of granulocytes and mononuclear phagocytes induced by mycobacterial adjuvants: improved recovery of leucopoiesis in mice after cyclophosphamide treatment.

smegmatis) triggered this phenomenon because heat-treated bacteria did not induce any fluid-phase uptake (data not shown). Figure 2 Fluid-phase uptake by Raji B cells induced by different treatments. B cells were infected with M. tuberculosis (MTB), M. smegmatis (MSM), and S. typhimurium (ST), or treated with phorbol 12-myristate 3-acetate (PMA), M. tuberculosis culture supernatant (MTB-SN), or M. smegmatis culture supernatant selleck chemical (MSM-SN). The fluorescent fluid-phase uptake was determined by the quantification of the relative fluorescence units (RFU) at several time points (15, 60, 90, 120, and 180 min). B cells

that were not treated served as the control (CONTROL) for each treatment. The effect of several inhibitors on the fluid-phase uptake was also monitored. Each of the inhibitors (cytochalasin (CD), wortmannin (WORT), and amiloride (AMIL) was individually added to the following

treatments/infections: a) PMA treatment, b) ST, c) MTB, d) MTB-SN, e) MSM, f) MSM-SN. Each bar represents the mean of four different measurements. There were statistically significant differences (p <0.01) when the infected, PMA-treated and SN-treated B cells were compared with i) the control cells, ii) the infected cells in the presence of the inhibitors, and iii) the PMA-treated or SN-treated cells in the presence of the inhibitors. The experiment presented is representative of three independent repetitions. Effect of inhibitors on bacterial and fluid-phase uptake by I-BET151 B cells To determine the pathway responsible for the bacterial and fluid-phase uptake that was previously observed in the B cells, several classical endocytic inhibitors were employed [26], including AMIL (macropinocytosis), CD, and WORT (macropinocytosis and phagocytosis). In addition, bacterial infections and soluble treatments (PMA or mycobacterial supernatants) were Wnt inhibitor used in these experiments. The fluid-phase uptake induced during bacterial infections was completely abolished by AMIL, WORT, and CD (Figures 2a through f), and this inhibition was observed throughout the experiment. Similarly, the fluid-phase intake triggered by PMA, M. tuberculosis, or the M. smegmatis supernatant

was suppressed by these inhibitors (Figures 2a, 2d and 2f). The inhibition in all these cases was statistically significant. In addition, the bacterial uptake was inhibited with amiloride at all concentrations used (Figure 3). The ST and MSM uptakes were the most affected. Even at the lowest inhibitor concentration used (1 mM), a high uptake inhibition was observed with all bacteria. These observations indicated that macropinocytosis was responsible for the uptake of bacteria into these cells. Figure 3 Bacterial uptake by Raji B cells is inhibited by amiloride treatment. B cells were infected with M. tuberculosis (MTB), M. smegmatis (MSM), and S. typhimurium (ST) for 90 min. The cells were treated with 1, 3 or 5 mM amiloride before and during the infection.

g. Hawksworth 1991, 2001). Species accumulation curves LY3023414 are frequently used to analyse biodiversity data (Schmit and Lodge 2005) and rank-abundance graphs are among the best methods to demonstrate variation

in species richness and species abundances between the various plots studied and in the absence of a proper model for species abundance distributions (Magurran 2004). It is important to note that in our plots all species accumulation curves are still increasing, and hence, are not saturated. Similarly, species richness curves in tropical cloud forests in Mexico remained unsaturated (Gómez-Hernández and Williams-Linera 2011). Our observations suggest that many species still need to be discovered from the forest plots that we studied. Eighty six percent of the macrofungal species were found in just one of the 11

plots studied indicating a relative high level of differentiation in species composition between the plots. This was not only observed for forests from two distantly located regions (viz., Araracuara versus Amacayacu), but also for those occurring within each region. Our observations are in agreement with Lodge (1997) who noted that fungal communities in lowland forests BI 2536 cost in Ecuador can widely differ at short distances of even a few meters. The observation that the macrofungal species composition differs between the various forest types may be a consequence of ecological specializations of the species involved. Ectomycorrhizal relationships are an example of such an ecological specialization (Alexander and Selosse 2009, Smith et al. 2011). The putative ectomycorrhizal relationship between some groups of macrofungi and Pseudomonotes tropenbosii (Dipterocarpaceae) in AR-PR constitutes an ecological variable needed to understand the observed fungal biodiversity of this forest type. All other plots apparently lacked ectomycorrhizal trees and fungi, and, therefore, this unique feature of the AR-PR plot contributed to the noted macrofungal species diversity of this forest. Singer and Aguiar (1979) emphasized

that ectomycorrhizal species occur on sandy soils in the Amazon and the AR-PR plot seems to support this suggestion. The many wood-inhabiting fungi MYO10 that occurred after cutting down the trees in AR-1 yr (see also above) and that seem to form sporocarps under more dry conditions are another example of a specific guild of fungi. However, the rarity of many species, expressed here as singletons in the analysis, indicates that the species richness estimators have to be interpreted with caution as they may have rather broad confidence limits as asserted by Magurran and Queiroz (2010). It is unlikely that a single model explains the patterns that influence species diversity for any group of organisms in different ecosystems. Many hypotheses resulting from meta studies explain the distribution and patterns of species richness of birds (Davies et al. 2007; Rahbek et al.

Potential factors affecting menstrual cycle include various SB202190 mouse genetic, neuroendocrine and metabolic aspects. It seems that in the specific population included in our studies, all above mentioned factors, predisposing to such disorders, are present. Nattiv et al. [10] and Manore et al. [15] emphasized that an appropriately balanced diet with reduced training volume and intensity is the only possible way to alleviate menstrual disorders in female athletes. The present study is valuable because it is based on an individual, non-pharmacological diet

intervention taking into account everyday burden of an intense physical effort without reduction of intensity and volume of everyday activities, which could be, according to authors’ knowledge, a potential cause of subject’s withdrawal from the study. In case of female athletes aiming to achieve desired results, the limitation of training sessions intensity is potentially difficult to accept intervention, therefore it was not suggested to study participants. This study has several limitations. Firstly, LH and FSH

concentrations were assessed only once before the start of dietary intervention, and then after three months. We did not determinate the pulsatile nature of those hormones, thus AZD3965 price an assessment of the presence of ovulatory cycles in menstruating women was impossible. Secondly, the body composition was determined using the electrical bioimpedance method, which potentially raises some controversies. However, DEXA method was not used due to young age of study participants, tests frequency, and potential

adverse (UV) effects. Conclusion This report provides for further support for the role of energy deficiency in menstrual disorders among young female athletes and the benefits of an adequate energy intake and energy availability on hormones concentration. Continuation controlled dietary intervention is needed to assess the extent to which long-term improvement in the nutritional status results in improvements in the hormonal status of female athletes, to an extent that would allow the regulation of the menstrual cyclity. Acknowledgement The project was financed by Ministry of Science and Higher Education under a number N N312 239738. References 1. Mudd LM, Fornetti W, Pivarnik JM: Bone mineral density in collegiate female athletes comparisons among sports. J Athl Train 2007,42(3):403–408.PubMedCentralPubMed 2. Klentrou P, Plyley M: Onset of puberty, menstrual frequency, and body fat in elite rhythmic gymnasts compared with normal controls. Br J Sports Med 2003, 37:490–494.PubMedCentralPubMedCrossRef 3. Torstveit MK, Sundgot-Borgen J: Participation in leanness sports but not training volume is associated with menstrual dysfunction: a national survey of 1276 elite athletes and controls. Br J Sports Med 2005, 39:141–147.PubMedCentralPubMedCrossRef 4.

7 (1.8) vs. 5.6 (2.1) ***  Identity: 5.8 (2.4) vs. 7.1 (2.1)***  Concern: 5.2 (2.6) vs. 6.1 (2.6) ***  Comprehensibility: 7.1 (2.0) vs. 6.6 (2.3)*  Emotional response: 5.1 (2.6) vs. 6.0 (2.5)***   A? B? C+ D+ E− Higher scores on the subscales of IPQ refer to a stronger belief in serious

consequences of the disease; a stronger belief in a chronic or more changing time course; a stronger belief that the illness is controllable either by self-care or by medical care; and a better understanding of the illness respectively. Daporinad in vitro Statistical significance at * P < 0.05; ** P < 0.01; *** P < 0.001. Study quality scores depict whether criterion (A) study sample representativeness, (B) loss to follow up/response rate, (C) measurement of illness perception (dimensions), (D) measurement of work participation, or (E) accounting for potential confounders is fulfilled (+), not fulfilled (−) or unclear (?) Data analyses and outcomes Regardless of the analyses methods used, all studies report statistically see more significant findings for one or more illness perception dimensions (Table 1). A few studies did not use all illness dimensions of the IPQ or subsequent versions in the analyses hence some dimensions are more frequently reported, including the ‘consequences’ dimension, ‘timeline’ dimension, and the ‘control’ dimension. Although the direction of the effects for the individual illness perception dimensions was generally in the same SPTLC1 direction,

some

were significant in one study but not in the other study. As data analyses, data presentation and study quality varied considerably, direct comparisons between studies presenting absolute point estimates and studies presenting regression parameters are less informative. Considering the heterogeneity between studies, we considered pooling of the results not feasible and evaluated the results of the studies qualitatively. In the three studies reporting descriptive analyses, overall higher scores on the dimension consequences, timeline, identity and concern were observed in the non-working groups reflecting a negative relationship, whereas higher scores on the dimensions’ control and coherence reflected a positive relationship on work participation as seen in the working group (Petrie et al. 1996; Boot et al. 2008; Sluiter and Frings-Dresen 2008). The result of the causal dimension was not reported in most studies, except for the study by Boot et al. (2008) because this scale often consisted of open questions. Although all illness dimensions showed differences of various magnitudes indicating more maladaptive beliefs in the non-working group, some were not statistically significant. The magnitude of the differences between groups were small; for example, those who did not work rated the consequences of their disease on average between 1 and 2 points more severe (on 0–10 scale) (Boot et al. 2008; Sluiter and Frings-Dresen 2008) compared to those who did work.

Since the envelope of all nuclei of all tumors was stained, nuclear intensity was determined on the degree of staining of the nucleoplasm. Where discrepancies arose between the staining of scores from the same tumor, an average of the scores was taken, with confirmation by two observers using a double-headed microscope with a consensus decision taken in all cases. Tissue stromal cells, normal epithelium

or lymph follicles served DNA Damage inhibitor as positive internal controls to ascertain the quality of the staining. To distinct microsatellite instable (MSI) from microsatellite stable (MSS) tumors, the TMA was stained for mismatch repair proteins MLH1 and PMS2, as previously described [25]. MLH1 and PMS2 are deficient in sporadic MSI tumors. Therefore, the expression of these proteins was used to differentiate MSI and MSS rectal cancers. Tissue stromal cells, normal epithelium or lymph follicles served as positive

internal controls when analyzing MLH1, PMS2 expression. The expression of MLH1 and PMS2 was scored positive if tumor cells showed expression, and negative if tumor cells showed no expression of either MLH1 or PMS2, provided that tissue stromal cells did show expression, indicating MSS and MSI tumors, respectively [26]. Statistical Analysis All analyses were performed with SPSS statistical software (version 12.0 for Windows, SPSS Inc, Chicago, USA). Mann-Whitney U test (M-W) was used to compare variables. Kaplan-Meier analyses were performed to analyze patient survival. The entry date for the survival analyses was the time of surgery of the primary tumor. Events for disease selleck chemicals llc free survival and overall survival were defined as follows: from time of surgery to time of disease relapse or death by any cause (for disease free survival) and time of

death by any cause (for overall survival), respectively. Patients were first separately analyzed in univariate analysis in addition, variables with a P value of <0.10 in the univariate analyses were subjected to a multivariate analysis. Cox’ regression Neratinib supplier analyses were used to calculate hazard ratios (HR) with 95% confidence intervals (CI). Results Low Levels of CXCR4 RNA Expression Predict Good Prognosis The RNA level of CXCR4 was determined in primary tumor tissue of a cohort of 70 colorectal cancer patients using quantitative RT-PCR and linked to clinical follow-up data. The impact of high versus low expression of CXCR4 was assessed using the 50th percentile cut-off point as previously defined [10, 14]. The characteristics of the cohort colorectal cancer patients, included in this study are summarized in Table 1. To evaluate whether CXCR4 and clinicopathological features were associated, the level of CXCR4 was correlated to each feature. CXCR4 expression was not associated with any of the clinicopathological variables (Table 1). Univariate cox regression analyses were performed to identify prognostic factors for disease free survival and overall survival (Table 1).

During their initial familiarization session, participants completed a questionnaire concerning their current use

of sport beverages. Anthropometric data and reported exercise frequency and duration are listed in Table 1. The study was approved by, and conducted in accordance with, guidelines of the University of Alabama’s Institutional Review Board, and participants provided written informed consent prior to beginning any study procedures. Table 1 Characteristics of participants   Men(n  =  23) Women(n  =  13) Total(n  =  36) Age (years) 23 ± 3 24 ± 3 23 ± 3 Height (cm) 177 ± 7 165 ± 5 173 ± 9 Weight (kg) 77.6 ± 8.9 60.5 ± 9.1 71.4 ± 12.1 Body Mass Index (kg/m2) 24.6 ± 2.2 Selleck Rabusertib 22.3 ± 2.9 23.8 ± 2.7 Body Fat (%) 10.3 ± 4.8 18.2 ± 4.6 13.2 ± 6.0 Aerobic Exercise Sessions (per week) 3.8 ± 1.1 4.5 ± 1.0 4.1 ± 1.1 Average Exercise Session Duration (minutes) 48.2 ± 20.5 57.3 ± 19.0 51.6 ± 20.1 Data are mean  ±  SD. Familiarization session Prior to beginning experimental trials, participants completed a familiarization

session designed to acquaint them with the exercise protocols and subjective rating scales. This session also permitted the estimation of total 1-h exercise sweat loss, as determined by body weight buy BAY 11-7082 change, which was used to control fluid intake in all subsequent treatment sessions. Participants were instructed to drink ~500 mL of water between their last meal and the time they went to bed the night before testing and a second 500 mL of water during the 2 hours before reporting to the laboratory. They were also instructed to avoid alcohol and caffeine during the 24-h period prior to experimental trials and to arrive at the laboratory at least 2 hours

after eating. Upon arrival, body weight while wearing shorts, a t-shirt, and undergarments was measured using a beam-balance scale. Height was measured using PTK6 a stadiometer integrated with the scale (Detecto, Webb City, MO) and body mass index (kg/m2) was recorded. The sum of skinfolds from three sites (Lange Caliper, Beta Technology Inc., Deer Park, NY) were recorded in accordance with American College of Sports Medicine guidelines [27] and used to estimate body fat percentage [28]. Heart rate (HR) was recorded (Team System Monitor, Polar Electro Oy, Kempele, Finland) continuously in 5-s intervals while subjects sat quietly for 15 min in a dimly lit room. The average HR from min 5 to 15 was determined. At the end of the 15– min rest period, a capillary blood sample was collected using the finger prick method. Whole blood was collected in a 100–μL fluoride/heparin/nitrite-containing capillary tube and mixed for 3 min before being analyzed in triplicate (PGM7 Analyzer, Analox Instruments, Lunenburg, MA) to confirm participants exhibited a normal blood glucose profile. The average of the 2 closest measurements was recorded. A Profile of Mood States-Brief questionnaire (POMS) [29] was administered prior to exercise.

Γ* values obtained from our own measurements were, 21.3 and 37.0 mol mol−1 for 10 and 22 °C respectively. Values for in vivo Rubisco kinetics parameters k c and k o , 40.1 Pa and 27.59 kPa at 25 °C, and their temperature dependence were obtained GSK690693 purchase from Bernacchi et al. (2002). Distinction between V Cmax limited, J max limited and TPU limited C i trajectories was done by eye. The model was fitted to the data using the solver module in Excel 2007 for the V Cmax and J max limited

C i ranges only. Electron transport rate (ETR) was calculated according to Genty et al. (1989) from the photochemical efficiency in the light (\( \varphi_\textII = \Updelta F/F_\textm^\prime \)) PF-6463922 datasheet as measured by chlorophyll fluorescence, photon flux density

(PFD) and leaf absorptance (abs) as ETR = φ II PFD abs 0.5. Absorptance was estimated from the chlorophyll content (chl) as abs = chl/(chl + 76) (Evans and Poorter 2001). Data are presented as means with standard deviation (SE). The SE was calculated as the standard deviation divided by the square root of the sample size (n). Further statistical analysis was by three-way ANOVA using accession, growth temperature and growth irradiance as fixed factors (SPSS 18.0). All variables were log10 transformed prior to analysis in order to investigate relative effects and to obtain a better homogeneity of variances. Only IMP dehydrogenase variables that were already relative expressions were not transformed (chlorophyll a/b ratio, C i /C a ratio, and O2 sensitivity of A growth and ETR). Results and discussion The two Arabidopsis accessions showed remarkably similar responses to growth temperature and irradiance for many of the variables (Table 1). Therefore, the comparison between the accessions is addressed at the end of this section, where also possible implications for climate adaptation are discussed. Table 1 Results of a 3-way ANOVA for variables shown in the Figures and Table 2   Accession Temp. Light A × T A × L T × L A × T × L Fig. 1  A sat/LA

10 °C 7.4* 320*** 934*** 1.9ns 0.0ns 0.8ns 0.8ns  A sat/LA 22 °C 0.0ns 79.9*** 403*** 0.5ns 0.4ns 18.7*** 0.9ns  A growth/LA 10 °C 5.8* 213*** 1162*** 0.2ns 0.9ns 13.1** 0.4ns  A growth/LA 22 °C 3.2ns 10.1** 1855*** 0.3ns 0.0ns 2.4ns 0.1ns  ETR/LA Lgrowth 10 °C 4.5* 138*** 5062*** 9.0** 0.9ns 26.1*** 0.7ns  ETR/LA Lgrowth 22 °C 3.0ns 21.4*** 17965*** 8.5** 3.9ns 2.9ns 0.1ns  ETR/LA Lsat 10 °C 2.0ns 140*** 660*** 6.1* 1.2ns 0.4ns 0.3ns  ETR/LA Lsat 22 °C 0.6ns 90*** 977*** 7.3* 0.7ns 8.8** 0.1ns Fig. 3  V Cmax/Rubisco 10 °C 0.5ns 6.1* 26.7*** 0.9ns 5.9* 0.1ns 0.0ns  V Cmax/Rubisco 22 °C 0.5ns 1.0ns 43.5*** 2.5ns 11.0** 6.4* 0.1ns Fig. 4                C i at co-limitation 22 °C 0.6ns 5.9ns 3.0ns 0.6ns 1.2ns 50.7*** 0.2 Fig.