For example, C. jejuni adhesion to Caco-2 cell receptors was inhibited by certain lectins [9]. Campylobacter is capable of producing a variety of glycoproteins, some of which are

cell-surface Protein Tyrosine Kinase inhibitor located [10]. Inactivation of the N-linked glycosylation system reduces bacterial ability to adhere to epithelial cells and thereby colonise the gastrointestinal tract [11, 12]. These findings suggest a possible role of some bacterial cell surface surface-located bacterial N-linked glycoproteins in interaction with host cell receptors. Van Sorge and colleagues [13] demonstrated interaction of N-linked glycoproteins of C. jejuni with C-type lectins of Macrophage Galactose-type lectins (MGL). In similarity with other pathogens, the production of cell surface structures interacting with C-type lectins may assist C. jejuni in the evasion of the host immune response [14, 15]. Another cell surface structure that may affect bacterial interaction with host cell receptors is a capsular polysaccharide (CPS) [16–19]. Inactivation of the capsule production machinery in strain 81–176 led to a two-fold decrease in adhesion to INT407 cells [20]. Similar findings were observed in another capsule Z-VAD-FMK cell line deficient mutant, 81116/kpsE[21].

However, these data were not supported by complementation studies. Moreover, they are in disagreement with other studies where the absence of capsule showed increased adhesion of C. jejuni strain 11168H to Caco-2 cells [16]. The contradictory results may be a consequence of differences in assay conditions, bacterial strains and tissue cell lines. In general, the capsules may play different roles in bacterial

attachment. This depends on the nature of a bacterial pathogen, and on the structural features of the capsules and adhesins. For example, F1 capsule of a Yersinia pestis prevents fimbrial CYTH4 adhesins from interaction with host cell receptors [22], while production of a capsule by Neisseria meningitidis does not affect PilC1 adhesin-mediated bacterial attachment [23]. In this study we developed and evaluated an in vitro ELISA-like assay for the investigation of C. jejuni interaction with host cell receptors. The assay was successfully used to study a role of capsule in attachment using SBA (Soya bean agglutinin) lectin as an analogue of a host cell receptor. In addition, using targeted mutagenesis (supported by complementation analysis) we investigated a role of PEB3 and JlpA adhesins in this interaction. Furthermore, using real time PCR, we found that peb3 and a capsule-related gene are differentially expressed. The results of these experiments suggest an interplay between bacterial capsule and adhesins in interaction with host cells. Results Dose-dependent specific binding of C. jejuni cells to immobilised SBA lectin In order to investigate the mechanisms and factors involved in C.

Agric Ecosyst Environ 1990, 28:409–414.CrossRef 40. Schlatter DC, Samac DA, Tesfaye M, Kinkel LL: Rapid and specific method for evaluating Streptomyces competitive dynamics in complex soil communities. Appl Environ Microbiol 2010, 76:2009–2012.PubMedCrossRef 41. Nodwell JR: Novel links between antibiotic resistance and antibiotic production. J Bacteriol 2007, 189:3683–3685.PubMedCrossRef 42. Frey-Klett P, Burlinson P, Deveau A, Barret M, Tarkka M, Sarniguet A:

Bacterial-fungal interactions: hyphens between agricultural, clinical, environmental, and food microbiologists. Microbiol Mol Biol Rev 2011, 75:583.PubMedCrossRef 43. Schrey SD, Erkenbrack E, Früh E, Fengler S, Hommel K, Horlacher N, Schulz D, Ecke M, Kulik A, Fiedler R788 ic50 H-P, et al.: Production of fungal and bacterial growth modulating secondary metabolites is widespread among mycorrhiza-associated streptomycetes. BMC Microbiol 2012., 12: 44. Berg G, Smalla K: Plant species and soil type cooperatively shape the structure and function of microbial communities in the rhizosphere. FEMS Microbiol Ecol 2009, 68:1–13.PubMedCrossRef 45. Dennis PG, Miller AJ, Hirsch PR: Are root exudates more important than other sources of rhizodeposits in structuring rhizosphere bacterial communities? GSK-3 activity FEMS Microbiol Ecol 2010, 72:313–327.PubMedCrossRef 46. Phillips DA, Fox TC, King MD, Bhuvaneswari TV, Teuber LR: Microbial products trigger amino acid exudation

from plant roots. Plant Physiol 2004, 136:2887–2894.PubMedCrossRef 47. Herrmann S, Oelmuller R, Buscot F: Manipulation of the onset of ectomycorrhiza formation by indole-3-acetic acid, activated charcoal or relative humidity in the association between oak microcuttings and Piloderma croceum : influence on plant development and photosynthesis. J Plant Physiol 2004, 161:509–517.PubMedCrossRef 48. Rosenberg K, Bertaux J, Krome K, Hartmann A, Scheu S, Bonkowski M: Soil amoebae rapidly change bacterial community composition in the rhizosphere of Arabidopsis thaliana . Isme J 2009, 3:675–684.PubMedCrossRef 49. Shirling EB, Gottlieb D: Methods for characterization of Streptomyces species. Int J Syst Bacteriol 1966, 16:313–340.CrossRef

50. Fulton TM, Chunwongse J, Tanksley SD: Microprep protocol for extraction of DNA from tomato and other herbaceous Ureohydrolase plants. Plant Mol Biol Rep 1995, 13:207–209.CrossRef 51. Rozen S, Skaletsky H: Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol 2000, 132:365–386.PubMed Competing interests The authors declare that they have no competing interests. Authors’ contributions FK conducted the molecular studies and drafted the manuscript. KZ participated in the quantification experiments. LF performed the AcH 505 genome assembly. TRN helped with the confocal laser scanning microscopy. TWe did the GFP labelling of AcH 505. VK participated in the electron scanning microscopy studies. TWu carried out the AcH 505 genome sequencing.

Figure 1 HRXRD results for the SrRuO 3 /SrTiO 3 (001) substrate. (a) XRD θ to 2θ DAPT scan patterns. The left inset shows the rocking curve of the SrRuO3 (200)c peak. FWHM was as small as 0.057°. The right inset shows good oscillations at low angles due to the uniform thickness of about 38 nm. (b) X-ray reciprocal space mapping around the STO (114) plane showed well-developed peaks for SrRuO3 in the lower region and two strong substrate

peaks in the upper region. Figure 2 shows HRXRD results for the SRO111 film. There was a strong SRO film peak near 2θ = 85.03° together with the strongest substrate peak near 2θ = 86.21°. (The peak near 2θ = 85.80° was not due to impurities but to spurious light from the X-ray source.) The calculated lattice constant of the SRO was Epigenetics inhibitor d 222 = 1.140 Å = 3.949 Å/2√3, again indicating a high-quality film. The high

crystallinity of the SRO111 film was also confirmed by the value of the full width at half maximum of the SRO (222) peak. This value was as small as 0.052°, smaller than that of the SRO100 film. The right inset of Figure 2 shows good oscillations at low angles due to the uniform thickness of about 37 nm. X-ray reciprocal space mapping around the STO (312) plane shown in Figure 2b contains well-developed peaks for the SRO111 film in the lower region and two strong substrate peaks in the upper region. The strong peaks for SRO were well centered and the obtained d 111 was consistent with the d 222 obtained in the θ to 2θ scan. The position of the film peak along the horizontal Q x axis was the same as that of the substrate peak, indicating that the SRO111 film was grown

coherently on the STO (111) PD184352 (CI-1040) substrate, with the same in-plane lattice constant. This indicated that the SRO111 film was under compressive strain. When we compared the HRXRD data of the two films, we found that the unit cell volume of the SRO111 film was nearly equal to that of the SRO100 film (V pseudocubic = 3.9052 × 3.949 Å3) and with comparable thicknesses. Figure 2 HRXRD results for the SrRuO 3 /SrTiO 3 (111) substrate. (a) XRD θ to 2θ scan patterns. The left inset shows the rocking curve of the SrRuO3 (222) peak. FWHM was as small as 0.052°. The right inset shows good oscillations at low angles due to the uniform thickness of about 38 nm. (b) X-ray reciprocal space mapping around the STO (312) plane showed well-developed peaks for SrRuO3 in the lower region and two strong substrate peaks in the upper region. We used AFM to observe the surface of the STO (111) substrate, which was used for the growth of the SRO thin film, as shown in Figure 3a. A step-and-terrace structure comparable to that reported previously by harsh etching could be clearly seen [17]. Figures 3b,c shows the surface morphologies of the SRO100 film and the SRO111 film, respectively.

Conversely, media inoculated with protozoan isolates showed the highest removal of only Ni (12%) and Zn (18%) for only dead Peranema sp. Statistical evidence revealed no significant difference (p > 0.05) between the heavy metal removal in the media inoculated with both dead-bacterial and dead-protozoan

isolates. None of the dead-test isolates was able to remove more than 25% of the heavy metal in the culture media, with Aspidisca sp. indicating the highest of all (Ti-23%). This could have been due to the presence of several metals and high concentrations. However, when comparing the removal efficiency of both dead and living test isolates, statistical evidence revealed significant differences (p < 0.05). Figure 3 The percentage removal of Talazoparib manufacturer heavy metals from the industrial wastewater samples by heat-killed microbial isolates (n = 3). To evaluate the click here resistance ability of the microbial isolates and whether the heavy-metal removal ability of test isolates is active, the genomic DNA was amplified with specific genes such as copA, copB and copC (Cu-resistance), nccA (Ni, Co, Cd-resistance), cnrA3 and cnrC2 (Ni and Co-resistance), chrB (Cr-resistance) and czcD (Co, Zn,

Cd-resistance) using the conventional PCR (Figure  4). Of all the genes targeted in the gDNA of microbial isolates, nccA, cnrA3, chrB and copC were the only genes to show positive amplification. For bacterial isolates (Pseudomonas putida, Bacillus licheniformis and Brevibacillus laterosporus), amplified products of approximately 400 bp, 450 bp, 1141 bp Histidine ammonia-lyase and 1447 bp revealing the presence of copC (Cu sequestration

and transport), chrB, nccA and cnrA3 genes were reproductively detected, whereas, the metal-resistant genes such as copA, copB, cnrC2 and czcD were not found. However, for protozoan isolates (Peranema sp., Trachelophyllum sp. and Aspidisca sp.), amplified products of approximately 400 bp, 450 bp and 1447 bp revealing the presence of copC, chrB and cnrA3 genes were found. Peranema sp. was the only protozoan isolate with the gene cnrA3 (RND (Efflux)). None of the protozoan isolates revealed the presence of copA, copB, cnrC2, czcD and nccA. Figure 4 Agarose gel electrophoresis of PCR products of total genomic DNAs with primer pair nccA -fwd and nccA -rev, primer pair copC- fwd and copC -rev, primer pair copB- fwd and copB -rev, primer pair czcD -fwd and czcD -rev, primer pair cnrA3 -fwd and cnrA3 -rev and primer pair chrB- fwd and chrB -rev. Lanes: M: DNA ladder (Marker), N: Negative (No template DNA), 1 to 6, amplified PCR product of: Pseudomonas putida (1), Bacillus licheniformis (2), Brevibacillus laterosporus (3), Trachelophyllum sp. (4), Peranema sp. (5) and Aspidisca sp. (6).

Fresh faecal samples were collected with sterile swab sticks and conveyed promptly to the Department of Microbiology Laboratory (OAU) for microbiological analysis. Isolation and identification of S. aureus isolates The swab stick was inserted into a test tube containing 3 ml of sterile nutrient broth (Biolab, supplied by Merck, Johannesburg, South Africa), swirled Inhibitor Library research buy briefly to discharge the contents into the medium, and the culture was incubated at 37°C overnight. Thereafter, a loopful was

streaked on mannitol salt agar (MSA) (Biolab, supplied by Merck, Johannesburg, South Africa) and incubated at 37°C for 48 hours. Preliminary identification of S. aureus was based on positive Gram stain, and positive results for catalase, coagulase (tube method) and DNase tests. The procedure described previously [32] was employed for DNA

isolation. In summary, a single colony was suspended to a McFarland 1.0 standard in 100 μl of TE buffer (10 mM Tris, 1 mM EDTA, pH 8.0) with 10 U of achromopeptidase (Wako Chemical, Co. Ltd.), and the suspension was incubated at 55°C for 10 min. The supernatant was used as crude DNA for PCR. Molecular identification and confirmation of the isolates was based on sequencing analysis of the hsp60 gene as previously reported [33]. PCR products were sequenced by using a Big Dye Terminator (version 3.1) cycle sequencing kit (Applied Biosystems, Foster City, CA) with an ABI Prism 3100 genetic analyzer (Applied Biosystems). Antibiotic susceptibility testing The susceptibility testing of the isolates to 11 antibiotics was performed using selleckchem the disk diffusion method and the following antibiotics were tested: penicillin (10 units), oxacillin (1 μg), cefoxitin (30 μg), erythromycin (15 μg), clindamycin (2 μg), tetracycline (30 μg), ciprofloxacin (5 μg), chloramphenicol (30 μg), fusidic

acid (10 μg) gentamicin (10 μg) and mupirocin (5 μg and 200 μg). S. aureus ATCC 25923 was the control Mirabegron strain for the susceptibility testing. The result was interpreted as resistant or susceptible based on the interpretative standard according to the Clinical Laboratory Standards Institute (CLSI) manual for bacterial isolates from animals [34]. Interpretative zone diameter for resistance and susceptibility breakpoints to fusidic acid and mupirocin which are not stated in the CLSI guidelines were considered as described previously [35, 36]. The D-test for determining inducible resistance of clindamycin using erythromycin was performed. A truncated or blunted clindamycin zone of inhibition (D-Shape) indicated inducible resistance. Constitutive resistance was recognized by a clindamycin zone diameter of ≤14 mm [37]. Molecular characterization of the S. aureus isolates Characterization of 70 isolates was determined by detection of the Panton Valentine Leukocidin (PVL) gene [38], agr[39] and coa gene typing [40].

Primers stm0551-F and stm0551-R external to stm0551 amplified a 0.5-kb DNA fragment from S. Typhimurium LB5010 genomic

DNA, while the same primer set generated a 1.3-kb DNA fragment from genomic DNA of the S. Typhimurium stm0551 mutant strain, indicating a kanamycin cassette inserted into the stm0551 gene. This DNA fragment was also sequenced to determine its identity. The confirmed stm0551 mutant strain was then designated S. Typhimurium Δstm0551. S. Typhimurium LB5010 mediated yeast agglutination and guinea pig erythrocyte when cultured in static LB broth, whereas agglutination was not detected when cells were collected from LB agar (Table 3). In contrast, the S. Typhimurium Δstm0551 strain mediated agglutination when grown on LB agar. Nonetheless the degree Rapamycin of agglutination was not as strong as the same strain grown in static LB broth. Transformation of the pSTM0551 plasmid that contains the coding sequence of stm0551 conferred on S. Typhimurium Δstm0551 strain the ability to inhibit type 1 fimbrial expression in both culture conditions, while the S. Typhimurium Δstm0551 strain carrying a plasmid that possessed a stm0551 coding sequence with the glutamic acid (E) at position 49 replaced with an alanine (A), or a pACYC184 cloning

vector exhibited the same phenotype as the S. Typhimurium Δstm0551 strain. The Figure 3 demonstrated the yeast agglutination tests performed on glass slides. Table 1 Bacterial strains and plasmids used in this study Name Description a Reference or source Salmonella enterica check details serotype Typhimurium LB5010 Wild type S. enterica serotype Typhimurium LT2 strain, fimbriate with the complete fim gene cluster [21] Δstm0551 stm0551 deletion mutant; Kanr Present study Escherichia coli strain One Shot® TOP10 chemically competent E. coli F- mcrA Δ(mrr-hsdRMS-mcrBC) Φ80lacZΔM15 ΔlacX74 recA1 araD139Δ(ara-leu)7697 galU galK rpsL (StrR) endA1 nupG Invitrogen BL21Star™ (DE3) One Shot® chemically competent E. coli F- ompT hsdS B (rB – mB -) gal dcm (DE3) Invitrogen Plasmids pSTM0551 A 0.5-kb DNA fragment possessing the stm0551 coding sequence cloned into the pACYC184 vector; Cmr Present

study pSTM0551E49A PAK5 A 0.5-kb DNA fragment possessing the stm0551 coding sequence with glutamic acid (E) at position 49 replaced with an alanine (A) cloned into the pACYC184 vector; Cmr Present study pACYC184 Tetr, Cmr, cloning vector; w/p15A ori ATCC, Manassas, VA pET101/D-TOPO Ampr, 6xHis tag expression vector Invitrogen pKD46 Ampr, express λ Red recombinase system, temp- sensitive replicon [22] pKD13 Plasmid carrying Kanr cassette [22] a Amp r ampicillin resistant; Cm r chloramphenicol resistant; Kan r kanamycin resistant; Tet r tetracycline resistant Table 2 Primers used in the present study Purpose and name Sequence (5′ to 3′) Description Construction of the stm0551 mutant stm0551pKD13-F GCTCTGATGTTTCAATGCCTTCCATCAGC ATTAACTGATTCCGGGGATCCGTCGACC Annealing Temp.

Int J Vitam Nutr Re 2009, 79 (3) : 131–141.CrossRef 24. Bloomer RJ, Smith WA, Fisher-Wellman KH: Glycine propionyl-L-carnitine increases plasma nitrate/nitrite in resistance trained men. J Int Soc Sports Fostamatinib price Nutr 2007, 4: 22.PubMedCrossRef 25. Edwards DG, Schofield RS, Lennon SL, Pierce GL, Nichols WW, Braith RW: Effect of exercise training on endothelial function in men with coronary artery disease. Am J Cardiol 2004, 93 (5) : 617–620.PubMedCrossRef 26. Poveda JJ, Riestra A, Salas E, Cagigas ML, Lopez-Somoza C, Amado JA, Berrazueta JR: Contribution of nitric oxide to exercise-induced changes in healthy volunteers: effects of acute exercise and long-term physical training. Eur J Clin Inves 1997, 27

(11) : 967–971.CrossRef Competing interests RJB has received research funding or acted as consultant to nutraceutical and dietary supplement companies. All other authors declare no competing interests. Authors’ contributions RJB was responsible for the study designs, overseeing data collection, biochemical work, statistical analysis, and preparation of the manuscript. TMF,

JFT, CGM, and REC were responsible for data collection/entry and assistance with manuscript preparation. All authors read and approved the final manuscript.”
“Introduction Among adults 20 years or older, living in the United States, 65.1% are classified as overweight or obese [1]. Furthermore, there is no indication that this trend is improving [1]. Excess body fat has potential physical and psychological health implications as well as potential negative influences

on sport performance as Sinomenine well. The various dietary aspects that are associated with overeating and obesity are not well understood Selleckchem PF 01367338 [2]. One debated area that is often purported to play a role in body weight/composition changes is meal frequency. The amount and type of calories consumed, along with the frequency of eating, is greatly affected by sociological and cultural factors [3]. Recent evidence suggests that the frequency in which one eats may also be, at least in part, genetically influenced [4]. Infants have a natural desire to eat small meals (i.e., nibble) throughout the day [5]. However, as soon as a child reaches a certain age he/she is trained to consume meals in a generally predictable manner [5]. In the modernized world, meal frequency is affected by cultural/social norms as well as an individual’s personal beliefs about his/her health or body composition. According to a study utilizing data from the 1987-1988 Nationwide Food Consumption Survey (NFCS), the average daily meal frequency for the 3,182 American adults that completed the study was 3.47 [6]. If meals that consisted of less than or equal to 70 kcals, (primarily consisting of tea, coffee, or diet beverages) were excluded from the analysis, the number decreased to 3.12 meals per day. These habits closely mirror the traditional three meals per day pattern (i.e., breakfast, lunch, and dinner) that is common throughout the industrialized world.

4 1.89 1.88 EC23 Establishment of hedgerow trees by tagging T <0.1 0.89 0.90 EC24 Hedgerow tree buffer strips on cultivated

land A <0.1 1.78 1.81 EC25 Hedgerow tree buffer strips on grassland G <0.1 1.78 1.81 EE1/2 2/4 m buffer strips on cultivated land A 3 1.50 1.54 EE3 6 m buffer strips on cultivated land A 6 1.44 1.50 EE4/5/6 2/4/6 m buffer strips on intensive grassland G 0.7 1.44 1.50 EF1 Field corner management A 7.3 1.67 1.75 EF2/3 Wild bird seed mixture A 2.7 1.50 1.65 EF4/5 Nectar flower mixture A see more 1.2 2.83 2.83 EF6 Over-wintered stubbles A 5 0.44 0.44 EF7 Beetle banks A 0.1 1.17 1.13 EF8 Skylark plots T 0.1 0.61 0.63 EF9 Cereal headlands for birds A <0.1 0.83 0.83 EF10 Unharvested cereal headlands for birds & rare plants A <0.1 0.89 0.96 EF11 Uncropped, cultivated margins for rare plants A 0.1 1.78 1.81 EF13 Uncropped cultivated areas for ground-nesting PD-0332991 purchase birds A 0.1 1.17 1.17 EF15 Reduced herbicide cereal crop preceding over-wintered stubble A 0.1 0.61 0.60 EF22 Extended

overwintered stubbles A 1.6 0.50 0.50 EG1 Under sown spring cereals A 0.4 0.51 0.54 EG4 Cereals for whole crop silage followed by over-wintered stubbles A 0.1 0.33 0.33 EK1 Take field corners out of management G 0.2 1.39 1.40 EK2 Permanent grassland with low inputs G 18.4 1.33 1.31 EK3 Permanent grassland with very low inputs G 13.8 1.72 1.77 EK4 Manage rush pastures G 0.5 0.67 0.63 Key 2012 Pts the % of total ELS points (among the options considered) accounted for by the option(s) in 2012, Type option category, H Hedge/ditch, A arable, G grassland, P plot/tree, PHB the unweighted mean PHB values from all 18 experts, WPHB the mean PHB values of all 18 experts following weighting Table 3 Number GABA Receptor of units

of each ELS option after redistribution ELS option Type Baseline Model A Model B Model C     Units Units % change Units % change Units % change EB1/2 H 106.1 M 17.9 M −83 25.0 M −76 20.3 M −81 EB3 H 27.9 M 44.3 M 59 26.7 M −4 21.7 M −22 EB6 H 17.8 M 17.8 M <1 18.7 M 5 15.3 M −14 EB7 H 9.1 M 6.0 M −34 19.0 M 110 15.5 M 71 EB8/9 H 11.5 M 34.8 M 202 25.6 M 122 20.8 M 81 EB10 H 4.6 M 60.3 M 1,221 27.3 M 497 22.2 M 386 EB12/13 H 7.3 M 9.1 M 24 21.9 M 200 17.8 M 144 EC1 T 28,005 105,209 276 71,613 156 110,965 296 EC2 T 154,668 75,345 −51 74,596 −52 115,589 −25 EC3 H 7.4 M 1.5 M 41 9.4 M 34 7.

No statistically significant difference in chi-square indicates that the more parsimonious model explains the data equally well compared to the more complex model with additional paths (Kline 1998). Additionally, the other fit indices were used to choose the final best fitting model. Results In

Table 1, descriptive statistics, reliabilities R788 molecular weight and inter-correlations among all study variables are presented. As can be seen from the table, the reliabilities were acceptable. Overall variables had test–retest reliabilities of at least .46 (see Fig. 1). The highest test–retest reliabilities resulted for emotional exhaustion and performance-based self-esteem. The internal consistencies for all constructs per measurement wave were satisfactory (α ≥ .85). In order to provide the basis for testing the relations of emotional exhaustion, work–family conflict and performance-based self-esteem over time, we performed a procedure recommended by Brown (2006) to test for longitudinal invariance. Neither of the steps tested and compared to each other resulted in a CFI difference that exceeded .01. Thus, we can assume that the constructs included in this study are invariant over time (Cheung and Rensvold 2002). In accordance

with recommendations from Little and Card (2013), the constraints of weak factorial invariance were maintained for the subsequent testing of our research questions. Table 1 Correlations and descriptive GSK-3 inhibitor statistics   M(SD) 1 2 3 4 5 6 7 8 9 10 1. Age 47.40 (10.05) –                   2. Gender (female) .53 (–)

.01 –                 3. University education .37 (–) −.05* .13* –               4. Having Ureohydrolase children .52 (–) −.30* −.02 .05* –             5. Work–family conflict T1 2.13 (1.04) −.10* .05* .15* .10* –           6. Emotional exhaustion T1 1.63 (1.47) .00 .12* .03 −.01 .49* .87         7. Performance-based self-esteem T1 3.59 (1.44) −.09* .05* .10* .01 .32* .32* .85       8. Work–family conflict T2 2.11 (1.05) −.13* .06* .17* .12* .54* .34* .27* –     9. Emotional exhaustion T2 1.71 (1.46) −.02 .13* .04* −.01 .37* .67* .26* .47* .87   10. Performance-based self-esteem T2 3.31 (1.40) −.11* .06* .13* .04* .30* .28* .66* .31* .28* .87 Listwise; n = 3,387. * p < .05; – not applicable. The scales ranged from 1 to 5 except gender (men = 0 and women = 1), age (in years), university education (which was coded 1 = university education, 0 = lower levels of education) and having children living at home (0 = no. 1 = yes). In the diagonal in italic: Cronbach’s alpha Fig. 1 Reciprocal model (Model 4): standardized coefficients. Notes *p < .05, dotted line for non-significant path, WFC work–family conflict, EE emotional exhaustion, PBS performance-based self-esteem In Table 2, the fit statistics for our four cross-lagged models are shown.

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the

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