NO ‘positive’ cell concentrations were highest especially during late exponential and stationary phases when NO2 -, the likely substrate for NO production, concentrations were the highest (Figure 3 A3-C3). The more gradual increase in the proportion of NO positive cells at DO = 0.5 mgO2/L paralleled the trend in peak headspace NO concentrations (Figures 2, 3). Figure 3 NO profiles and fraction of NO containing cells (A3-C3), and gene expression (A4-C4) during exponential phase and stationary phase at DO = 0.5 mg/L (A), 1.5 mg/L (B) and 3 mg/L (C) for cultures shown in Figure 2. The impact of operating DO concentrations MK 8931 cost on gene transcript profiles, determined using primer sets described in Table

1, was dependent upon the physiological growth phase. In exponential phase cell samples, amoA and hao relative mRNA concentrations statistically decreased with increasing reactor DO concentrations (Figure 3, A4-C4, Table 2). A systematic impact of growth phase on nirK and norB relative mRNA concentrations was not observed during exponential phase. The relative mRNA concentrations for both genes during exponential phase were statistically similar for DO = 0.5 and 1.5 mg O2/L and statistically

higher (for nirK) or lower (for norB) at DO = 3.0 mg O2/L (Figure 3, A4-C4, Table 2). In direct contrast, during stationary www.selleckchem.com/products/sbe-b-cd.html phase, the relative mRNA concentrations of amoA, hao and nirK all statistically increased with increasing DO concentrations. Additionally, the relative mRNA concentrations of norB at DO = 1.5 mg O2/L were statistically higher than at DO = 0.5 mg O2/L, but statistically similar to those at DO = 3.0 mg O2/L (Table 2). Table 1 Endpoint and real-time PCR primers employed in this study Primer Sequence (5′-3′) Position Target gene Reference Endpoint PCR A189 amoA2R’

GGHGACTGGGAYTTCTGG CCTCKGSAAAGCCTTCTTC 151-168 802-820 amoA [36, 37] HAO1F HAO1R TCAACATAGGCACGGTTCATCGGA ATTTGCCGAACGTGAATCGGAACG 203-226 1082-1105 hao [38] NirK1F NirK1R TGCTTCCGGATCAGCGTCATTAGT Interleukin-3 receptor AGTTGAAACCGATGTGGCCTACGA 31-54 selleck chemicals 809-832 nirK [38] NorB1F NorB1R CGGCACTGATGTTCCTGTTTGCTT AGCAACCGCATCCAGTAGAACAGA 479-502 1215-1238 norB [38] KNO50F KNO51R TNANACATGCAAGTCGAICG GGYTACCTTGTTACGACTT 49-68 1492-1510 Eubacterial 16S rRNA gene [39] Quantitative PCR amoAFq amoARq GGACTTCACGCTGTATCTG GTGCCTTCTACAACGATTGG 408-426 524-543 amoA [15] HAO1Fq HAO1Rq TGAGCCAGTCCAACGTGCAT AAGGCAACAACCCTGCCTCA 266-285 331-350 hao [38] NirK1Fq NirK1Rq TGCAGGGCATACTGGACGTT AGGTGAACGGGTGCGCATTT 182-201 291-310 nirK [38] NorB1Fq NorB1Rq ACACAAATCACTGCCGCCCA TGCAGTACACCGGCAAAGGT 958-977 1138-1157 norB [38] EUBF EUBR TCCTACGGGAGGCAGCAGT GGACTACCAGGGTATCTAATCCTGTT 339-357 780-805 Eubacterial 16S rRNA gene [34] Table 2 Statistical comparison of the impact of DO concentrations on relative mRNA concentrations in exponential (E) and stationary (S) phase cultures (p values < 5.0 × 10-2 indicate statistically significant differences).

The availability of both disruption and complementation mutants will facilitate further research on the function of the GerA receptor of B. licheniformis MW3, as well as its potential involvement in germination triggered by alternative nutrients and cooperation with other germinant receptors. Further bioinformatic CYT387 solubility dmso and phenotypic WZB117 molecular weight investigations are in progress in our laboratory and might eventually

provide insight relevant for improved spore decimation techniques by the use of induced germination. Methods Bacterial strains and DNA extraction The strains used in this study were B. licheniformis MW3 [50], B. subtilis B252 [71] and the B. cereus type-strain ATCC 14579 [72, 73] (Table 1). B. licheniformis MW3 is a mutant created from B. licheniformis DSM13 (isogenic to ATCC 14580) with targeted deletions of the hsdR loci of two type I restriction modification systems making the strain readily transformable. B. licheniformis MW3 was used as host for creating disruption and complementation mutants of the gerA locus. When not stated otherwise, bacteria were cultured at 37 °C on LB agar or broth containing appropriate selective antibiotics (Table 1). Genomic DNA for PCR amplifications and sequencing was extracted from B. licheniformis MW3 and B. licheniformis NVH-1307 by a method slightly modified from [71], as follows. An overnight culture was transferred to fresh growth medium and grown at 37 °C, 225

rpm (HT-Infors AG CH-4103, Bottmingen, Switzerland), to turbidity (4-5 h). Cells from 1 check details ml culture was harvested by centrifugation (3 min at 16.100 × g), and the pellet was frozen at -20 °C. Thawed pellet was resuspended in 495 µl SET buffer (75 mM NaCl, 25 mM EDTA, 20 mM Tris, pH 7.5) and 50 µl 10 mg/ml lysozyme before incubation at 37 °C for 1 h. Further, 50 µl 10% sodium dodecyl sulfate and 5 µl 25 mg/ml proteinase K was added, and the sample was incubated at 50 °C for 2 h. At room temperature (RT), the sample was mixed with 200 µl 5 M NaCl and

700 µl of chloroform-isoamyl alcohol (24:1), and incubated with frequent inversions for 30 min. The aqueous many phase was separated by centrifugation (20-30 min at 16.100-20.800 × g), transferred to a fresh tube, and DNA was precipitated by addition of an equal volume of isopropanol followed by centrifugation (20 min at 16.100-20.800 × g). The precipitate was washed with 70% ethanol and centrifuged (15 min at 16.100-16.500 × g), and the supernatant was removed before the precipitate was left to air dry. DNA was resuspended in 100 µl 10 mM Tris HCl buffer (pH 8.5). Plasmid DNA was purified according to the manual provided with the Plasmid Mini/Midi kits (QIAGEN®). Table 1 Strains and plasmids used in this study strain or plasmid description, phenotype or genotype relevant for this study a reference Strains     Escherichia coli TOP10 One Shot® TOP10 electro/chemically competent E. coli for cloning Invitrogen MW3 Bacillus licheniformis DSM13 (ΔhsdR1, ΔhsdR2) [50] NVH-1307 B.

Assignment to an experimental group was conducted in an alternating fashion, based upon arrival time. The study consisted of two experimental groups. In the low dose group, participants received a dose of 800 mg/day. The high dose group received a dose of 1200 mg/day. CX-6258 Study participants were asked to self-administer two to three (depending on their experimental group) soft-gelatin capsules daily containing either 400 mg of Resettin® (Resettin®/MyTosterone™; Triarco Industries, Wayne, NJ) or lecithin, which was used as the placebo. Participants were randomized into either the 800 mg/day or 1200 mg/day Resettin®/MyTosterone™

treatment group. After a 14-day treatment period, participants discontinued placebo or Resettin®/MyTosterone™ treatment for a consecutive 14 days. Following this 14-day washout period, participants were crossed over within their respective group to either

Resettin®/MyTosterone™ or the lecithin placebo for 14 days. Blood was collected on days 0, 3, 7 and 14 days following the initiation of treatment. Serum hormone levels were collected and analyzed. Patterns of hormonal response were compared across the treatment groups in a pairwise manner. Researchers attempted to collect blood samples from all of the participants at approximately the same time of day in order to minimize circadian variations in serum hormone levels. Participants EPZ015938 in vitro Methisazone A total of forty sedentary, healthy men between the ages of 21 and 68 met inclusion criteria and were enrolled

for this study. Enrollment was voluntary, and participants signed informed consent statements in compliance with the Human Subjects Guidelines of Western Institutional Review Board and the American College of Sports Medicine. Participants were excluded from study if they had a history of smoking, pulmonary disease, hypertension, hepatorenal disease, musculoskeletal disorders, neuromuscular or neurological diseases, autoimmune diseases, cancer, peptic ulcers, or anemia. Participants were also excluded if they exhibited repeated signs of benign prostate hypertrophy, regularly consumed commercially available products containing saw palmetto or AX, were taking ergogenic levels of nutritional supplements that may affect muscle mass, such as creatine, or exhibited anabolic hormone levels, such as androstenedione or dehydroepiandrosterone. Participants taking prescription medication for a heart condition, pulmonary or thyroid problem were also excluded from the study. Participants on anti-hyperlipidemia, hypoglycemic, anti-hypertensive, endocrinologic, psychotropic, neuromuscular/neurological, or androgenic medications were also not invited to enroll in the study. After a selleck kinase inhibitor 10-hour fast of all food or drink with caloric value along with a 48-hour rest from strenuous exercise, participants were phlebotomized.

However, the implementation of MS as a routine CAL101 diagnostic tool clearly depends on good inter-day reproducibility of the method. Three

aliquots of a serum specimen from one tumor patient were randomly integrated into small series of serum specimens from patients and control individuals on four consecutive days. The median concentration of CP-AP was 31.9 μmol/L with SD of 3.3 μmol/L and CV of 10.2% (Additional file 3: Figure S3). As expected, the inter-day reproducibility is not as good as the intra-day reproducibility (see Figure 3B). However, CVs of 10% or even more are acceptable for many routine laboratory assays [19]. Serum specimens from patients with metastatic colorectal tumors (TP = 30), patients without malignant disease but elevated acute Crenigacestat phase protein CRP (IC = 30) and healthy controls (HC = 30) were spiked with CP-RP and internal standard (IS). Samples were incubation for 22 h and sample preparation prior to LC-MS was performed as described in materials and methods. The median concentrations of CP-AP in the collectives of healthy controls (HC), inflammatory controls (IC) and tumor patients (TP) were 10.3 (SD 3.1), 11.1 (SD 6.1) and 17.6 (SD 9.0) respectively (Figure 5A). The D’Agostino-Pearson test was used to asses the normal distribution within the Selleck Ralimetinib reporter peptide concentrations. For HC and IC the p-values were

higher than 0.05 indicating a normal distribution. However, for TU the p-value was <0.05 and the hypothesis that the distribution of the observations in the sample is normal, was rejected. Accordingly, further data analysis was performed with the non-parametric Mann–Whitney test. The concentrations of CP-AP were not significantly different, when HC versus IC was compared with the Mann–Whitney test (p = 0.337). In contrast, the comparison of HC versus TP and IC versus TP showed statistically significant differences with p values below 0.005 (Figure Etomidate 5A). The diagnostic accuracy for discrimination of healthy controls and tumor patients was calculated with receiver operating characteristics (ROC)

that had an area under the curve (AUC) of 0.89. The ROC-AUC for discrimination of inflammatory controls and tumor patients had a value of 0.77. The 95% confidence intervals ranged from 0.787 to 0.958 and from 0.646 to 0.871 respectively. In contrast, inflammatory controls and healthy controls could not be differentiated with a ROC-AUC of 0.57 with 95% confidence interval ranging from 0,438 to 0,699 (Figure 5B). These data suggest that the activity of the tumor-associated endoprotease cancer procoagulant is increased in serum specimens of tumor patients when compared to healthy and inflammatory controls. Figure 5 Proof-of-concept experiment for functional protease profiling with reporter peptide spiking.

Nature 1994, 369:756–758.PubMedCrossRef

14. Hashemolhosseini S, Nagamine Y, Morley SJ, Desrivieres S, Mercep L, Ferrari S: Rapamycin inhibition of the G1 to S transition is mediated by effects on cyclin D1 mRNA and protein stability. J Biol Chem 1998, 273:14424–14429.PubMedCrossRef 15. Lei W, Jia T, Su Z, Wen W, Zhu X: Combined effect of rapamycin and cisplatin on survival of Hep-2 cells in vitro. Oncol Res 2009, 18:73–81.PubMedCrossRef 16. Calabro A, Tai J, Allen SL, Budman DR: In-vitro synergism of m-TOR inhibitors, statins, and classical chemotherapy: potential implications in acute leukemia. Anticancer Drugs 2008, 19:705–712.PubMedCrossRef 17. Xu RH, Pelicano H, Zhang H, Giles FJ, Keating MJ, Huang P: Synergistic effect of targeting mTOR by rapamycin and depleting ATP by inhibition of glycolysis in lymphoma and leukemia cells. Leukemia 2005, 19:2153–2158.PubMedCrossRef check details find more 18. Takeuchi H, Kondo Y, Fujiwara K, Kanzawa T, Aoki H, Mills GB, Kondo S: Synergistic augmentation of rapamycin-induced autophagy in malignant glioma cells by phosphatidylinositol

3-kinase/protein kinase B inhibitors. Cancer Res 2005, 65:3336–3346.PubMed 19. Mondesire WH, Jian W, Zhang H, Ensor J, Hung MC, Mills GB, Meric-Bernstam F: Targeting mammalian target of rapamycin synergistically enhances chemotherapy-induced cytotoxicity in breast cancer cells. Clin Cancer Res 2004, 10:7031–7042.PubMedCrossRef 20. Zeng Q, Yang Z, Gao YJ, Yuan H, Cui K, Shi Y, Wang H, Huang X, Wong ST, Wang Y, et al.: mTOR inhibitor Treating triple-negative

breast cancer by a combination of rapamycin and cyclophosphamide: an in vivo bioluminescence imaging study. Eur J Cancer 2010, 46:1132–1143.PubMedCrossRef Carbohydrate 21. Yang Z, Lei Z, Li B, Zhou Y, Zhang GM, Feng ZH, Zhang B, Shen GX, Huang B: Rapamycin inhibits lung metastasis of B16 melanoma cells through down-regulating alphav integrin expression and up-regulating apoptosis signaling. Cancer Sci 2010, 101:494–500.PubMedCrossRef 22. Niu H, Li H, Xu C, He P: Expression profile of RhoGDI2 in lung cancers and role of RhoGDI2 in lung cancer metastasis. Oncol Rep 2010, 24:465–471.PubMed 23. Di Maio M, Chiodini P, Georgoulias V, Hatzidaki D, Takeda K, Wachters FM, Gebbia V, Smit EF, Morabito A, Gallo C, et al.: Meta-analysis of single-agent chemotherapy compared with combination chemotherapy as second-line treatment of advanced non-small-cell lung cancer. J Clin Oncol 2009, 27:1836–1843.PubMedCrossRef 24. Ramalingam SS, Harvey RD, Saba N, Owonikoko TK, Kauh J, Shin DM, Sun SY, Strychor S, Tighiouart M, Egorin MJ, et al.: Phase 1 and pharmacokinetic study of everolimus, a mammalian target of rapamycin inhibitor, in combination with docetaxel for recurrent/refractory nonsmall cell lung cancer. Cancer 2010, 116:3903–3909.PubMedCrossRef 25. Nicholson KM, Anderson NG: The protein kinase B/Akt signalling pathway in human malignancy. Cell Signal 2002, 14:381–395.PubMedCrossRef 26.

Due to low α-amylase sensitivity, stress influences might cause a less regulated cell proliferation in F344 breast tissue. In contrast to this, mammary Lewis cell proliferation was well regulated showing rather soon signs of senescence. These considerations are supported by the observation that

F344 cells attached easier and grew faster than Lewis cells (Figure 1a & b). α-Amylase was detected in both, F344 and Lewis buy Apoptosis Compound Library primary mammary epithelial cells (Figure 1c & d) CA3 without obvious differences. Moreover, we recently determined amylase enzyme activity in the mammary gland tissue of F344 and Lewis rats and observed no differences in activity between both rat strains (unpublished data). These findings indicate that other factors than α-amylase protein expression and activity must underlie the observed differences. Thus, the α-amylase efficacy on its targets is probably altered in F344 cells participating in less Selleck CX5461 regulation of cellular proliferation. However, the enzymatic preparation of mammary gland tissue

might alter cell surface and therefore influence adhesion properties in vitro. Microenvironmental influences in the breast tissue, which strongly affect cellular behavior [46–48] and which are absent or at least altered in our primary cultures in vitro, should also be considered. Currently, the possible mechanisms underlying antiproliferative effects of α-amylase remain unclear. However, some sources in literature can be found that allow considerations about a possible mechanism and probable α-amylase targets. α-Amylase might act on molecules, which mediate cell adhesion,

and stimulate detachment and death of cells called anoikis, a type of apoptosis Ribonucleotide reductase [49, 50]. In our experiments, the proportion of dead cells reflects the sensitivity to trypsin used for cell detachment prior to counting. If α-amylase induces anoikis by action on cellular adhesion, a more pronounced trypsin effect would have been expected that is negatively correlated with number of cells. This was not the case in either, F344 and Lewis cells. Furthermore, α-amylase could probably stimulate cellular differentiation or senescence. Investigations of cell senescence by SA-β-gal assay presented here did not show a strong impact of α-amylase on senescence, particularly not in combination with the effect on cell growth. α-Amylase also exerts antibacterial effects, which are either drawn back to an inhibition of bacteria growth by diminishing nutrients [10] or to a direct interaction with α-amylase [11]. Regarding cell culture, known α-amylase-substrates, like starch, are usually not present in cell culture media, but an α-amylase effect by metabolism of nutrients cannot be completely excluded.

The mean immunoscore was similar in the fibroblastic stroma of the normal breast in reduction specimens and the benign tissue from breast NCT-501 datasheet cancer patients, stained with either antibody (Fig. 3a). Table 1 Stromal immunoscores for FBLN1 in 32 matching pairs of benign breast and breast cancer Benign/cancer pair Antibody A311 Benign/cancer pair Antibody B-5 Stromal immunoscore Stromal immunoscore Benign Cancer Fold differencea Benign Cancer Fold differencea A 0.53 0.04 13.13 A 1.00 0.18 5.71 B 1.00 0.13 7.69 C 1.80 0.63 2.88 C 1.15 0.18 6.27 B 1.50 0.65 2.31 D 1.18 0.33 3.62 G 1.60 www.selleckchem.com/products/Trichostatin-A.html 0.85 1.88 E 1.24 0.47 2.64 P 1.55 0.83 1.88 F 1.75 0.70 2.50 S 2.20 1.40 1.57 G 1.05 0.43 2.47 I 1.80 1.15 1.57 H 1.10 0.50 2.20 V 1.60 1.08 1.49 I 1.35 0.63 2.16 F 1.60 1.13 1.42 J 0.76 0.36 2.10 J 1.46 1.06 1.38 K 0.96 0.48 2.02 N 1.90 1.40 1.36 L 1.50 0.75 2.00 Q 1.50 1.13 1.33 M 1.21 0.71 1.70 H 1.10 0.85 1.29 N 1.23 0.83 1.48 D 1.35 1.05 1.29 O 1.70 1.15 1.48 O 1.48 1.15 1.28 P 0.95 0.65 1.46 T 1.60 1.25 1.28 Q 1.35 0.93 1.46 Z 1.88 1.50 1.25 R 0.85 0.60 1.42 E 0.85 0.75 1.13 S 1.30 0.93 1.41 BB 1.28 1.13 1.13 T 1.25 0.93 1.35 M 1.40 1.27 1.11 U 1.13 0.90 1.25 L 2.33 2.33 1.00 V 0.90 0.80 1.13 R 1.35 1.40 0.96 W 1.05 0.99 1.07

W 1.73 1.85 0.93 X 1.08 1.05 1.02 X 1.45 PF01367338 1.60 0.91 Y 0.53 0.53 1.00 U 1.48 1.65 0.89 Z 1.03 1.05 0.98 CC 1.60 1.90 0.84 AA 1.00 1.23 0.82 DD 1.20 1.45 0.83 BB 0.71 0.98 0.72 AA 1.40 1.80 0.78 CC 0.95 1.35 0.70 Y 0.75 1.00 0.75 DD 0.93 1.35 0.69 FF 0.80 1.08 0.74 EE 0.93 1.65 0.56 EE 1.35 2.05 0.66 FF 0.59 1.15 0.51 K 0.65 1.25 0.52 aBenign/Cancer We also noted that the cytoplasm of epithelial cells in some breast cancers stained more strongly than the epithelium in the histologically normal counterpart. The normal or benign epithelium did aminophylline not

stain with the B-5 antibody, whereas there was cytoplasmic staining of epithelium using the A311 antibody (Fig. 3b).

Clin Sci 1992, 83:367–374.PubMed 28. Powers ME, Arnold BL, Weltman AL, Perrin DH, Mistry D, Kahler DM, Kraemer W, Volek J: Creatine supplementation increases total

body water without altering fluid distribution. J Athl Train 2003, 38:44–50.PubMed 29. TSA HDAC Latzka WA, Sawka MN, Montain SJ, Skrinar GS, Fielding RA, Matott RP, Pandolf KB: Hyperhydration: GW-572016 manufacturer Tolerance and cardiovascular effects during uncompensable exercise-heat stress. J Appl Physiol 1998, 84:1858–1864.PubMed 30. Deschamps A, Levy RD, Cosio MG, Marliss EB, Magder S: Effect of saline infusion on body temperature and endurance during heavy exercise. J Appl Physiol 1989, 66:2799–2804.PubMed 31. Luetkemeier MJ, Thomas EL: Hypervolemia and cycling time trial performance. Med Sci Sports Exerc 1994, 26:503–509.PubMed 32. Nadel ER, Fortney SM, Wenger CB: Effect of hydration state of circulatory and thermal regulations. J Appl Physiol 1980, 49:715–721.PubMed 33. Nose H, Mack GW, Shi XR, Morimoto

K, Nadel ER: Effect of saline infusion during exercise on thermal and circulatory regulations. J Appl Physiol 1990, 69:609–616.PubMed see more 34. Ekelund LG: Circulatory and respiratory adaptation during prolonged exercise. Acta Physiol Scand Suppl 1967, 292:1–38.PubMed 35. Rauch LH, Rodger I, Wilson GR, Belonje JD, Dennis SC, Noakes TD, Hawley JA: The effects of carbohydrate loading on muscle glycogen content and cycling performance. Int J Sport Nutr 1995, 5:25–36.PubMed 36. Tarnopolsky MA, Zawada C, Richmond LB, Carter S, Shearer J, Graham T, Phillips SM: Gender differences in carbohydrate loading are related to energy intake. J Appl Physiol 2001, 91:225–230.PubMed 37. Hargreaves M, McConell G, Proietto J: Influence of muscle glycogen on glycogenolysis

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Job autonomy, time pressure, and emotional demands scales were constructed on the basis of, respectively, 5, 11, and 7 questions with answering options that ranged from ‘1-never’ to ‘4-always’. Job autonomy is derived from the Job Content Questionnaire JCQ (Karasek et al. 1998; Van den Bossche et al. 2006, 2007). The time pressure and emotional demands scales are derived from the questionnaire on the experience and evaluation of work (VBBA) (Van Veldhoven et al. 2002). Several studies showed that construct validity, predictive validity, and internal consistency of the scales are fair to good (Karasek et al. 1998; Van Veldhoven et

al. 2002). The scale scores were calculated by averaging the answers to the separate questions. Cronbach’s alpha for these scales are 0.85, 0.87, and 0.80, respectively. Separate dichotomous items were used to measure workplace violence and harassment click here by patients, students or passengers (external; three items; α = 0.70), and for workplace violence, and

harassment by colleagues or superiors (internal; three items; α = 0.59). For internal and external workplace violence, questions were asked about unwanted sexual attention, intimidation, and physical violence in the past 12 months. If the answer to at least one of these three questions was ‘yes’, a BAY 11-7082 ic50 positive scale score was given. Satisfaction with working conditions and self-rated health were assessed with single item questions with five answering categories (1 = very dissatisfied to 5 = very satisfied). Work-related Sclareol fatigue We measured work-related fatigue with the need for recovery after work scale

(NFR) with 11 yes/no items (α = 0.87) (Van Veldhoven and Broersen 2003). An example item is as follows: “I find it difficult to relax at the end of a working day.” In this study, we dichotomized NFR scores as high and low. Employees with six or more positive responses are considered to have high NFR which identifies the high-risk group for NFR in the best possible way (Van Veldhoven 2008; Broersen et al. 2004). At this cutoff point, selleck compound sensitivity and specificity of the scale are 79 and 72%, and people with NFR ≥ 6 have a higher risk of receiving treatment for psychological health complaints than people with a score <6. Test–retest reliability of NFR over a 2-year interval is good when applied in stable work environments and poor to fair when applied in unstable work environments, in truck drivers as well as in nurses (De Croon et al. 2006). Unstable work environments refer to changes for instance in supervisor or management, reorganizations, position, or working hours. The predictive value of NFR is confirmed for coronary heart disease (Van Amelsvoort et al. 2003), accidents at work (Swaen et al. 2003), as well as emotional exhaustion and sleeping problems (Sluiter et al. 2003).