Wild animals have been used as food since ancient times and, currently, the consumption of unconventional animals is increasing worldwide. The process of cooking meat using traditional recipes includes a variety of ingredients, which can influence the total metal intake from the diet. In this study, the concentrations of eight essential  and six non-essential  trace elements were determined in home-processed food obtained from snails and from three common species of game animals , seasoned with anchovies, mushrooms, and different vegetables using inductively coupled plasma mass spectrometry (ICP-MS). In general, Fe was the most abundant trace element, ranging from 18 ± 8 µg/g in pheasant to 99 ± 76 µg/g in snail, and Co was the least abundant, ranging from 0.007 ± 0.003 µg/g in hare to 0.093 ± 0.048 µg/g in snail. Regarding the non-essential trace elements, Pb concentrations showed wide variations, reaching a concentration of 17.30 µg/g in hare, while Cd concentrations were higher in snail, ranging from 0.18 to 0.46 µg/g. These alternative food sources can offer an important contribution to the human nutritional requirements of essential trace elements, in particular of Fe. The high concentrations of Pb and Cd present in some samples should be considered as potentially dangerous for the consumers. Human diets include a myriad of animal sources, which vary widely in different countries. Wild animals have been used as food since ancient times and, currently, the consumption of unconventional animals from different taxa is increasing worldwide. Insects , molluskThe nutrient quality of food can be altered by different methods of food processing such as steaming or oven cooking. In particular, the loss of trace elements may be caused by their outflow from the food during cooking ,3. SimilMany unconventional animals are traditionally and locally used as a source of food, however, their contribution to the dietary intake of trace elements has not yet received sufficient attention. In this study, the concentrations of eight essential  and six non-essential  trace elements were determined in processed food obtained from snails and from three species of game animals , which are among the most commonly consumed in Italy . The samThe concentrations of essential trace elements are reported in Due to the ease of sampling, the snails were also analyzed as raw uncooked samples . Trace eOf the essential trace elements, Fe, Cu, Zn, and Mn were present in detectable concentrations in all the samples, while Ni, Mo, Se, and Co were below the limit of quantification (<LOQ) in a few samples of seasonings and mushrooms. With the exception of Se, the essential trace elements presented higher concentrations in both the raw and the processed samples of snails; in particular, the viscera showed the highest concentrations of trace elements.p < 0.05). In the mushrooms and seasonings, the levels were significantly lower (p < 0.05) than in the viscera of raw snails.Iron was the most abundant element, reaching its highest concentrations in snails: 99.64 ± 76.47 µg/g in cooked snails and 334.6 ± 402.3 µg/g in the viscera of raw snails. Regarding the other samples, Fe concentrations followed this decreasing order: woodcock (63.49 ± 23.80 µg/g), hare (33.74 ± 16.40 µg/g), and pheasant . Manganese concentrations ranged from 0.678 ± 0.419 µg/g in pheasant to 25.49 ± 12.55 µg/g in snails, significantly higher than in pheasant and hare samples (p < 0.05). In the seasonings, the concentrations of Cu and Mn were generally lower than in the processed meat.Zinc concentrations presented a narrow range of concentrations in all the samples analyzed, ranging from 10.44 ± 1.35 µg/g in woodcock to 23.90 ± 6.539 µg/g in snails. Copper and Mn concentrations had a pattern similar to Fe. The lowest mean Cu concentration was detected in pheasant (1.373 ± 1.097 µg/g) and the highest in snails (75.13 ± 43.03 µg/g), significantly higher than in hare and pheasant samples (p < 0.05). Selenium was also abundant in commercial anchovies, with a mean concentration of 0.553 ± 0.027 µg/g. Vegetable seasonings showed Se concentrations close to the LOQ, while, in mushrooms, the values ranged from 0.014 µg/g to 0.855 µg/g. Of the cooked meat, the highest Ni concentrations were found in snails while, in the other samples, the metal content was lower. The viscera of raw snails had a Ni concentration significantly higher than the foot (p < 0.05). The highest Mo concentrations were measured in seasonings; however, high concentrations were also found in cooked snails (0.331 ± 0.049 µg/g), which were significantly higher (p < 0.05) than in hare. Finally, Co was the essential trace element present in the lowest concentrations in all the samples analyzed, ranging from 0.007 ± 0.003 µg/g in hare to 0.093 ± 0.048 µg/g in cooked snails; the latter value was significantly higher than those determined in pheasant and hare (p < 0.05).Of the other trace elements, Se presented the highest concentrations in processed meat, with a maximum value of 0.583 ± 0.154 µg/g in woodcock and a minimum value of 0.215 ± 0.148 µg/g in hare. In snails, the Se concentration was lower and, in the raw snails, it was significantly lower in the foot than in the viscera (The percentages of the adequate intake (AI) calculated for a consumption of 100 g of processed meat varied according to the species and the element analyzed . The higp < 0.01) different between the two sampling sites of the Quaderna Valley.Lead concentrations were, in general, higher in the game animals than in the snails and mushrooms. The values also showed wide variations among the samples obtained from the same species, ranging from 0.01 to 0.470 µg/g in pheasant, from 0.407 to 2.421 µg/g in woodcock, and from 0.019 to 17.30 µg/g in hare. In addition, in raw snail viscera, Pb concentrations were significantly (p < 0.05) in the processed snails than in pheasant and hare, ranging from 0.180 to 0.460 µg/g. In woodcock, the Cd levels were lower than in snails, but significantly (p < 0.05) higher than in hare, reaching a mean value of 0.141 ± 0.086 µg/g.Cadmium concentrations were significantly higher  and in one sample of pheasant preparation seasoned with mushrooms M1 (0.179 µg/g). In addition, in woodcock preparations seasoned with anchovies, the Hg concentrations varied from 0.043 to 0.069 µg/g while, in the anchovy fillets, it varied from 0.121 to 0.143 µg/g.p < 0.05) higher than those detected in pheasant and hare preparations. Chromium was present at detectable concentrations in all the samples analyzed, with the highest values in snails (0.339 ± 0.245 µg/g), followed by woodcock, mushrooms, hare, and pheasant.Aluminum presented the highest concentrations compared to the other non-essential trace elements in all the samples analyzed, with the sole exception of anchovies. Aluminum concentrations varied widely from 1.464 ± 1.167 µg/g in pheasant to 41.11 ± 52.56 µg/g in snails. Very low concentrations of As were detected in the samples analyzed, with the exception of anchovies (2.693 ± 1.567 µg/g) and woodcock (0.528 ± 0.243 µg/g), as the concentrations in woodcock were significantly  and cytochrome-c-oxidase, respectively . MoreoveThe homogeneity of Zn concentrations in the samples analyzed is due to the essential role of Zn in a wide range of biochemical systems shared by the majority of living organisms ,24. ConsNickel, Mo, and Co presented one-to-two orders of magnitude lower concentrations due to their limited involvement in the biochemical processes.H. pomatia from Poland [The Pb and Cd concentrations determined in the raw foot of snails are low and of the same order of magnitude as those reported in raw meat samples of m Poland . Ziomek m Poland  reportedIt is known that the wide variability of Pb concentrations in samples from game animals is due to the impossibility of removing all Pb gunshots or, alternatively, removing the contaminated meat ,28. AccoThe richness of the non-essential trace elements Cd, Al, As, and Hg in the woodcock pâtè could be considered a paradigm of how the different ingredients used for dish preparations, including seasonings, could influence the total metal intake. Therefore, in addition to raw material, it is also essential to determine the metal concentrations in processed food. In this case, Cd and Al derived from the woodcock viscera included in the food preparation while As and Hg came from the anchovies. It is well known that in vertebrates the liver and the kidney are the target organs of Cd accumulation due to the induction of metallothioneins ,37,38. IAssessment of the benefit–risk balance is an essential issue when evaluating the nutritional quality of food. Meat has been consumed for thousands of years and is considered an important source of proteins, vitamins, and essential trace elements. In the following paragraphs, the most relevant issues related to the samples analyzed in the present study will be discussed.It has been estimated that more than two billion individuals from both developing and industrialized countries suffer from Fe deficiency, with the emphasis on young women . At the Snail processed meat contains high Cu concentrations. Considering the mean Cu level of 75.1 µg/g and assuming a consumption of 100 g of food, a total metal intake of 7.51 mg is obtained. This value represents 468% of the AIof 1.6 mg/day reported by EFSA for Cu in adult men. An even worse situation occurs for women, as the value represents 550% of the AI of 1.3 mg/d . In bothAs discussed above, Zn concentrations are homogeneous, though not particularly high, satisfying at least 19% of AI in case of snails. Other sources, such as beef meat  and oystThe percentages of AI for Fe, Zn, and Cu were also calculated for cooked beef sirloin and pork loin, based on the data reported by Lombardi-Boccia et al. . All samDue to its toxicity, Pb was included on the list of 10 chemicals of major public health concern by the World Health Organization (WHO) . The mosA considerable amount of information exists regarding the detrimental effects of Cd on human health, and chronic Cd exposure has been associated with kidney disease, osteoporosis, cardiovascular diseases, and cancer . In partAll the samples analyzed were obtained from the Quaderna Valley, a restricted area of the Bologna District (Castel San Pietro-Ozzano Emilia) characterized by low anthropogenic impact, with few exceptions: one pool of snails came from the Treviso District (Silea) and one sample of mushrooms (M1) from the Trento District (Molveno). The anchovy fillets and capers were commercial products. The snails were collected from the wild, while the woodcocks, pheasants, and hares were obtained from local hunters and were shot with Pb-based ammunition. When possible, the shot pellets were removed prior to meal preparation. The pheasants and hares were immediately eviscerated, while the woodcocks were left intact. All the animals were stored frozen at −20 °C. The samples analyzed were prepared using a cooking process following traditional Italian recipes. All the raw samples were manipulated without gloves, washed in tap water, and cooked in steel pans, simulating domestic cooking procedures.Helix pomatia) were kept at 15–20 °C for 10–12 days to purge the digestive tract. The metal analyses were carried out either on snail samples obtained without any processing (raw meat) or on processed meat. In the first case, five snails were collected from two different sites of the Quaderna Valley and the foot was separated from the viscera while, in the second case, the entire body was used. The snails (five pools of 10 specimens each) were boiled for 20 min, and the soft body was then removed from the shell and cooked again for 30 min in 10 mL of olive oil with 2 g of garlic and 0.5 g of parsley.Before freezing, the wild snails  were roasted separately for two hours in 10 mL of olive oil with 1 g of garlic, 1 g of rosemary and sage. To prepare the woodcock pâtè, the soft part of the cooked meat and the viscera were separated from the bones and blended with 28 g of anchovy fillets and 55 g of capers.The plucked whole bodies (250–350 g) of the woodcocks  were roasted separately as previously described for 10 min; 50 g of minced carrot, 50 g of minced onion, 20 g of minced celery, and 150 mL of white wine were then added to the preparation, and it was cooked for two hours. Sample P4 was also seasoned with 200 g of mushrooms obtained from sample M1.The eviscerated and plucked pheasants  were seasoned separately with one liter of red wine, 100 g of minced carrots, 100 g of minced onions, and 10 g of garlic, and left to marinate for 36 h at 4 °C. The meat was then roasted as described above for 10 min; the marinade was added to the meat and the preparation was cooked for an additional two hours.The eviscerated and skinned hares  from a mixture of 50% Macrolepiota procera and 50% Boletus edulis (M1), Cyclocybe aegerita (M2 and M6), Boletus edulis (M3), Pleurotus ostreatus (M4), Armillaria mellea (M5), and Cantharellus cibarius (M7) were cooked for 30 min in 10 mL of olive oil with 2 g of garlic and 0.5 g of parsley.Fresh mushrooms . The analyses were carried out using inductively coupled plasma mass spectrometry  with an ASX-500 CETAC Autosampler . The operating parameters included an Rf power of 1.55 kW, a plasma (Ar) gas flow of 15 L/min, a carrier gas flow (Ar) of 1.01 mL/min, a cell gas flow (He) for “He” mode of 5 mL/min and a gas flow for “HeHe” mode of 10 mL/min. In the “No gas mode”, no He flow passed through the cell. The isotopes (m/z) monitored in the “No gas mode” were 27Al, 60Ni, 63Cu, and 111Cd; the isotopes (m/z) monitored in the “He mode” were 55Mn, 59Co, 66Zn, 78Se, 98Mo, 202Hg, and 208Pb, while 52Cr, 56Fe, and 75As were monitored in the “HeHe” mode. The concentrations were calculated using solvent calibration curves. The calibration standards were from Agilent Technologies Inc. . A mixture of internal standards (each one having a concentration of 1 µg/mL) was infused continuously by an alternative means of entrance using ICP-MS  to quantify the samples.The samples were digested using a wet procedure in polypropylene tubes . Ten mL of 70% nitric acid  were added, and the tubes were placed in Digi-Prep graphite Digestion Blocks  at 75 °C overnight. After cooling, the clear solutions were diluted to 20 mL with high purity deionized water . The samples were additionally diluted with a solution of 2% nitric acid and 0.5% hydrochloric acid  in each batch. The concentration values of the reference materials fell within the confidence interval given by the Joint Research Centre . For each series of analyses, a white sample  was mineralized and treated as described above; the limit of quantification (LOQ) was 0.005 µg/g, and the limit of detection (LOD) was 0.003 µg/g for each element analyzed. The results were expressed in µg/g wet weight (ww).p-values were calculated for multiple comparison, and values lower than 0.05 were considered statistically significant. Spearman correlation coefficients (r) among the elements were also reported with their p-values. As regards the benefit-risk calculations, the exposure to the non-essential trace elements Pb and Cd from the dietary source of a 70 kg male (assuming 100 g of the specific processed and cooked meat) was simulated.The mean, median, standard deviation, and minimum and maximum values were calculated for the descriptive statistics. Values below the limit of quantification (0.05 µg/g) were set at 0.5 LOQ to carry out the statistical analyses on all the data available. The Kruskal–Wallis rank sum test was applied to compare the concentration of each element among all the groups of raw and processed samples ; adjusted Discussion regarding the benefits and the risks associated with the consumption of meat from unconventional animals is still in its infancy. The increasing demand for food will prompt both producers and consumers to seek alternative food sources of high nutritional value; in particular, snails could be considered as a good candidate with, however, avoiding the viscera, which contain high concentrations of non-essential trace elements, such as Al, Cr, Cd, and Pb. Moreover, non-lead ammunition is recommended to ensure not only the health protection of the consumer but also that of the terrestrial and aquatic fauna.The analyses of metal concentrations in home-processed food deserve more attention, since the use of particular seasonings in preparing certain dishes can add an unexpected metal burden, as evidenced in the case of woodcock pâtè. Therefore, one must be careful in reaching conclusions regarding the dietary metal intake of a food, beginning with the data obtained from raw sources.


In this study, we examined the ability of Lactobacillus acidophilus NCFM to bind B(a)P in the simulated PM2.5 environment. Among the tested 5 strains, Lactobacillus acidophilus NCFM exhibited the best capacity to bind B(a)P, and its B(a)P binding percentage was 60.00%. Simulations of organic and inorganic systems which represent PM2.5 indicated that B(a)P could be absorbed by strain L. acidophilus NCFM. For the inorganic system of pH 5, L. acidophilus NCFM bound 92.74% B(a)P with a cell concentration of 1 × 1010 cfu/mL at 37°C for 8 hr. Regarding the organic system with pH 6, 73.00% B(a)P was bound by strain L. acidophilus NCFM after this bacterium was incubated at 37°C for 10 min. A quick B(a)P binding by this probiotic bacterium took place in the organic system. The removal of B(a)P from PM2.5 was significantly related to incubation time, cultivation temperature, pH, and cell concentration. Thus, our finding shows that long-term consumption of L. acidophilus NCFM is beneficial for the reduction of B(a)P towards the population who are exposed to PM2.5, although the ability of this bacterium to adsorb B(a)P is partly affected by the differences in the origin of PM2.5.The objective of this work was to explore the ability of lactic acid bacteria strains to bind benzo(a)pyrene (B(a)P) existing in PM The simulated organic system of B(a)P was composed of 100 μL PHAs (100 μg/mL) and 900 μL sterile water.Regarding the organic compositions of PMμg/mL, and the detection limit of B(a)P was 0.90 μg/mL [The separation of sixteen kinds of PAHs within 35 min showed good linearity in the range of 0.10–5.00 90 μg/mL , 19.μL) plus 900 μL sterilized water, containing 1.0 μg/mL B(a)P, was added to 1.0 mL bacterial suspension. After incubation at 37°C for 4 hr, the supernatant was collected by centrifugation . Chloroform (500 μL) was added to the supernatant to produce the organic phase for the detection of B(a)P. The control was designed as 1.0 μg/mL aqueous solution of B(a)P without bacterial cell addition. For each sample, B(a)P was detected by HPLC with the following conditions: UV detection of 290 nm wavelength, mobile phase of pure methanol, selection of room temperature as column temperature, flow rate of 1.0 mL/min, and injection volume of 20.0 μL [The artificial inorganic system P existing in the supernatant collected by centrifugation  was detected by HPLC. The control was 1.0 μg/mL PHAs (1.0 mL) without bacterial cell addition. B(a)P was UV-detected at 290 nm wavelength by HPLC. Acetonitrile and water were used as the mobile phase. Column temperature was room temperature with a flow rate of 1.0 mL/min as well as injection volume of 20.0 μL. For gradient elution analysis, A was acetonitrile and B was water. 60% A plus 40% B was used for isocratic elution for 1 min. After A was elevated from 60% to 100% within 20 min, eluting with 100% A was kept for at least 22 min. Then, elution A was reduced to 60% in 8 min and equilibrated with 60% A for 10 min.We selected 100 Br represents the binding rate of the tested bacterial cells to B(a)P (%); Bs indicates the level of B(a)P from the sample blank (μg/mL); and S is the level of B(a)P for each supernatant harvested from the tested bacterial cultivation (μg/mL).The binding percentage of the tested bacteria to B(a)P was calculated according to the following equation:L. acidophilus NCFM was grown in both systems for the observation of its B(a)P binding ability under different incubation times at 37°C. After incubated in two simulated systems for 10 min, 60 min, 240 min, 480 min, 1080 min, and 1440 min, respectively, the percentage of strain NCFM to bind B(a)P was detected.For either of the simulated inorganic or organic system, L. acidophilus NCFM was cultivated in the two simulated systems for the observation of its B(a)P binding ability under different incubation temperatures. The ability of L. acidophilus NCFM to bind B(a)P was evaluated after this strain was incubated at 4°C, 15°C, 23°C, and 37°C for 8 hr, respectively.For either of the simulated inorganic or organic system, L. acidophilus NCFM was cultured in the two simulated systems for the observation of its B(a)P binding ability under different pH values at 37°C. The ability of L. acidophilus NCFM to bind B(a)P was evaluated after this strain was incubated at pH 3, 4, 5, 6, 7, 8, and 9 for 8 hr, respectively. The sample was adjusted to a specific pH value using a degassed phosphate buffer solution.For either of the simulated inorganic or organic system, L. acidophilus NCFM was grown in the two simulated systems for the observation of its B(a)P binding ability under cell concentrations. L. acidophilus NCFM was inoculated into the two simulated systems at cell concentrations of 1 × 108 cfu/mL, 1 × 109 cfu/mL, and 1 × 1010 cfu/mL, respectively. Estimation of cell concentrations during cultures was done by turbidimetry [For either of the simulated inorganic or organic system, idimetry . After iL. acidophilus NCFM was cultured in the optimal conditions to calculate the best binding percentages of B(a)P.According to Section 2.5, the optimal conditions are obtained from two simulated systems. L. acidophilus NCFM (109 cfu/mL) to bind B(a)P. Four groups were prepared as follows. The first group was the inorganic system which contains 10 μg/mL B(a)P and strain NCFM; the second was the organic system with 10 μg/mL B(a)P and strain NCFM; the third was 10 μg/mL B(a)P solution plus strain NCFM; and the fourth was only bacterial suspension as the control. These mixtures were incubated at 37°C for 1 hr and then diluted to a final concentration of 10 μg/mL. 5 μL was sampled and dispersed onto a mica carrier (PELCO mica disc 10 mm) for drying at room temperature. AFM images were captured by using a scanning probe microscope  in the tapping mode.Atomic force microscopy was used to observe the possibility of P ≤ 0.05 takes place.Three replicates for each experiment were done. Statistical analyses (ANOVA) were performed using SPSS 19.0 statistical software. Results are expressed as means ± standard deviation (SD). Statistical differences are considered to be significant when L. acidophilus NCFM showed the best capacity for the adsorption of B(a)P, followed by strain 121, strain ML32, strain DM1-2, and strain 412. 60.00% B(a)P was bound by L. acidophilus NCFM in the present study. It was seen that the ability of lactic acid bacteria to bind B(a)P was strain-dependent. To better understand the roles of various factors in determining the efficiency of B(a)P binding, only L. acidophilus strain NCFM was chosen for further study.As shown in L. acidophilus NCFM to bind B(a)P in PM2.5, we designed two simulated systems, i.e., inorganic and organic systems, as imaginary PM2.5 to observe the B(a)P adsorbing ability of this strain was subjected to various variables.Several factors including incubation time, incubation temperature, pH, and cell concentrations have been reported to directly affect the possibility of potential probiotic bacteria to bind B(a)P if they were presented to different media . To showL. acidophilus NCFM to B(a)P was a quite quick process. It only took 10 min for this bacterium to bind most B(a)P. 25.66% B(a)P was absorbed by this strain after 10 min incubation. It was seen that the binding percentage of strain NCFM to B(a)P in the inorganic system was higher than that in the organic system at the same incubation time. Thus, the component's complex from PM2.5 might significantly affect the adsorption of strain NCFM to B(a)P.As shown in L. acidophilus NCFM to bind B(a)P in PM2.5 (L. acidophilus NCFM to bind more B(a)P.The temperature ranges from 4°C to 37°C were chosen to investigate the role of incubation temperature in affecting the ability of in PM2.5 . 85.64% L. acidophilus NCFM when pH of both simulated systems was 5 (L. acidophilus NCFM to bind more B(a)P from PM2.5, although this bacterium bound B(a)P more in the simulated inorganic system than in the simulated organic system.As the pH ranges from 3 to 9 were concerned, most B(a)P was bound by ms was 5 . Strain 10 cfu/mL in the simulated inorganic system, while 41.85% B(a)P was bound in the same cell concentration.It is apparent that the higher the L. acidophilus NCFM cell concentrations are in both simulated systems, the more B(a)P will be bound . About 510 cfu/mL at 37°C for 8 hr in the inorganic system of pH 5, strain NCFM bound the highest B(a)P (92.74%). The optimal parameters for strain NCFM to bind B(a)P were 1 × 1010 cfu/mL cell concentration and 37°C for 10 min of incubation in the organic system of pH 6. About 73.00% B(a)P was absorbed by this strain under the optimal conditions. It was seen from our present data that at least 60.00% B(a)P could be removed in the presence of L. acidophilus NCFM. Obviously, L. acidophilus NCFM strain might have an ability to remove B(a)P from PM2.5. Thus, consumption of this probiotic bacterium should be beneficial for humans to reduce the damage of PM2.5.Summary of the aforementioned available data indicated that strain NCFM was able to bind B(a)P either in the inorganic or organic system. When this bacterium was incubated with a cell concentration of 1 × 10Lactobacilli cells P binding ability.Currently, public sectors take regulation actions to reduce emissions and prevent inhalation in order to cope with the PM problem , but theurifiers . Lactobar medium . Our preLactobacillus plantarum 121, Leuconostoc mesenteroides DM1-2, Lactobacillus acidophilus NCFM, Lactobacillus paralimentarius 412, and Lactobacillus pentosus ML32 had good adsorption effects on B(a)P [L. acidophilus NCFM has the best ability to bind B(a)P (60.0%). As potential decontaminating agents of aflatoxin B1 (AFB1) and B(a)P, the removal ability of lactic acid bacteria to the mutagenic compounds differs from strain to strain in various medium surroundings. Our results are in accordance with what have been reported so far [Our previous studies confirmed that d so far , 24.2.5, it includes sulfate, nitrate, ammonium salts, carbonaceous particles, metal particles, minerals, and the polycyclic aromatic hydrocarbon (PAH) family. The current studies have implicated that B(a)P is one of the causative agents in colon cancer [Lactobacillus mostly colonized rats' colon and ileum and has shown promise in preventing colon carcinomas in rats [Lactobacillus kefir strains were reported to interact with metal ions via their binding ability [Lactobacilli strains had good ability to bind various chemicals in various simulated environments [Lactobacillus cell structures. Several reports have shown that the adsorption of mycotoxins to the cell wall of Lactobacillus was attributable to their surface properties and mainly to their hydrophobicity [Lactobacillus is dependent on the hydrophobicity and cell wall structure. A note of caution is due to the limited binding site on the cell wall since binding efficiency changes with different environments. Most components in PM2.5 could be absorbed by Lactobacillus cells, but previous studies have not reported how the organic and inorganic systems which resemble PM2.5 affect Lactobacillus strains to bind with B(a)P. Dutton et al. directly simplified the most complex component environments into two types, i.e., organic and inorganic systems [2.5 supplemented with B(a)P. In our case, we used the organic and inorganic systems which were supplemented with B(a)P in vitro to simulate PM2.5. Then, the ability of the tested L. acidophilus NCFM to bind B(a)P was evaluated in PM2.5. It was seen that the tested L. acidophilus NCFM bound B(a)P, and its B(a)P binding percentages were high in the simulated organic and inorganic systems. Thus, it is presumed from our in vitro test that use of selected lactic acid bacterial strains as a biofilter agent should have potential in removing the toxicity of PM2.5.Regarding the composition of PMn cancer . Epidemin cancer . On the n cancer , 28. Lac in rats . In addi ability . Similarronments , 31. Inthobicity , 33. In hobicity –36. Ther systems . The simLactobacillus is associated with incubation time [10 cfu/mL for the inorganic system. In this case, 92.74% B(a)P is removed by L. acidophilus NCFM. For the organic system with pH of 6, L. acidophilus NCFM binds 73.00% B(a)P only within 10 min when this strain is cultured at 37°C with a cell concentration of 1 × 1010 cfu/mL. In vivo, pH of the colon is stable at around 6.8, and the imbalance of pH in tissues is directly linked to diseases such as cancer [Lactobacillus acidophilus NCFMTM may potentially prevent colon cancer development, and Lactobacillus acidophilus NCFMTM significantly suppressed AOM-induced colon carcinogenesis in a dose-dependent manner [Numerous studies state that the roles of lactic acid bacteria in absorbing various chemicals such as ochratoxin A and aflatoxins depend largely on parameters such as incubation time, cultivation temperature, pH values, and viable cell counts . The staion time . Piotrowion time . Aflatoxion time , 41. Bacion time . Studiesion time . Thus, ts cancer . These rt manner . This co2.5 caused the B(a)P-binding cells to be changed in their morphology, as observed in our study P environment only. Thus, analysis of AFM further proved that our selected NCFM strain was possible to be used as a precautionary agent for the reduction of PM2.5 pollutants due to its B(a)P binding ability.The presence of PMur study . A simil defects . Importa defects . This alL. acidophilus NCFM exhibited the best capacity to bind B(a)P. At least 60% B(a)P was bound by this probiotic bacterium. This process of L. acidophilus NCFM to bind B(a)P was affected by incubation time, cultivation temperature, pH, and cell concentration. The simplification of PM2.5 into inorganic and organic systems provided a model for us to evaluate the roles of lactic acid bacteria strains in reducing the damage of the polluted environments to human beings. There were significant differences in the binding percentage of L. acidophilus NCFM to B(a)P between the two simulated systems, but our in vitro data indicated that strain NCFM exhibited good possibility to remove B(a)P existing in simulated PM2.5. Currently, environmental pollution situation becomes more and more serious, and thus, using probiotic bacteria to relieve environmental hazards will be a new attempt.Five tested lactic acid bacteria strains showed ability to bind B(a)P to some certain extent, but


Schistosoma mansoni in comparison with apparently healthy individuals (control group) in Sanja town, northwest Ethiopia.  Schistosomiasis is a parasitic disease that resides in the vascular system of vertebrates, causing a chronic, debilitating disease that affects more than 200 million people and 800,000 deaths per year in over 70 countries. This parasite causes liver dysfunction and disorders normal hematological and biochemical profiles in addition to portal vein hypertension syndrome, ascites, and liver fibrosis. The general objective of the current study is to assess hematological and biochemical profiles of patients infected with S. mansoni-infected patients attending Sanja hospital and apparently healthy (control group) from Sanja town community. A total of 220 participants, 110 from the S. mansoni-infected and 110 from the control group, were enrolled using convenient sampling technique. Three grams of stool and six milliliters of blood samples were collected from each study participant. Stool samples were processed using the Kato–Katz technique to determine infection and count parasite density. The blood sample was processed for the analysis of hematological and biochemical profiles using Cell Dyn 1800  and iChem535 chemistry analyzer, respectively. All data were analyzed using SPSS version 20, and P value less than 0.05 was taken as statistically significant.  A comparative cross-sectional study was conducted from February to April 2019 among microscopically confirmed Schistosoma mansoni-positive group as compared with the control group with statistically significant value (P ≤ 0.05). However, the mean values of blood glucose, red blood cell, packed cell volume, and granulocyte count difference were not statistically significant (P ≥ 0.05). The mean value of hemoglobin, red blood cells, blood glucose, mean corpuscular hemoglobin concentration, total protein, total cholesterol, and total white blood cell was significantly dropped in the moderate and heavy S. mansoni parasitic load patients as compared with the control group and light S. mansoni parasite density patients. However, the mean of AST and ALT progressively elevated as the burden of S. mansoni increased. Conclusion. Most hematological and biochemical profiles were significantly lower in the Schistosoma mansoni-positive group as compared with the control group. Most hematological and biochemical profiles decline significantly as the parasite density increased. Hence, with Schistosoma treatment, supportive treatment against hematological and biochemical disorders is recommended. This study showed that the mean values of serum alanine aminotransferase, aspartate aminotransferase, total protein, total cholesterol, hemoglobin, mean corpuscular hemoglobin concentration, and total white blood cell count were different in the  Schistosoma which belongs to the Schistosomatidae family, namely, Schistosoma mansoni, Schistosoma hematobium, Schistosoma intercalatum, Schistosoma mekongi, and Schistosoma japonicum [Schistosomiasis is a chronic parasitic disease caused by a trematode blood fluke of the genus aponicum . Schistoaponicum . This paaponicum  and causaponicum . Clinicaaponicum .Schistosoma pathogenesis is mainly associated with the host's responses to Schistosoma egg antigens to form granulomas usually in the intestines and the liver where the eggs are trapped [ trapped . Schisto trapped .S. mansoni-infected patients is anemia [S. mansoni-infected patients as compared with the control group [Chronic egg-induced granulomas can lead to chronic hepatitis, portal hypertension, bleeding esophageal varices, liver failure, and eventually may lead to death . Anothers anemia . The ints anemia . Consequs anemia . Schistos anemia . A wide s anemia , and reds anemia . Previous anemia . A studyol group .Schistosoma mansoni are conducted in the current study area, there is no report on hematological and biochemical profiles of patients infected with S. mansoni. Hence, the objective of the current study was to assess hematological and biochemical profiles of patients infected with Schistosoma mansoni in comparison with apparently healthy individuals (control group) in Sanja town, northwest Ethiopia.Although different epidemiological research studies on The study was conducted in Sanja town, located about 792 km away from Addis Ababa in Amhara region, northwest Ethiopia. The area has an altitude of 1,800 m above sea level with N 12°59′E 37°18′ coordinates, and its annual rainfall and average temperature range from 800 to 1,800 mm and 25°C to 42°C, respectively . A totalS. mansoni patients attending Sanja hospital and apparently healthy individuals (control group) from Sanja town community.A comparative cross-sectional study was conducted from February 2019 to March 2019 among microscopically confirmed Schistosoma mansoni-positive subjects whose age is 5 years and above attending Sanja hospital and apparently healthy subjects in the community were considered as the study population.All S. mansoni infection and 110 S. mansoni-negative control groups were enrolled.Double population means (sample size for each group) formula was used. A minimum of 110 participants positive for N = (S12 + S22) /(U1 − U2)2, was used to calculate sample size where β = 0.1 (power 90) and α = 5%  two side t test f  = (Zα/2 + Zβ)2 = (1.96 + 1.28)2 = 10.5 for two sided test= (0.22)2 + (0.23)2 (1.96 + 1.28)2/(2.2–2.3)2 = 100 for each group 100 study participants needed, total = 200, then 10% nonresponse rate was added 200 ∗ 10/100 = 20. The total sample size was 220, and U1 and S12 are the mean and the variance of the control group, respectively. U2 and S22 are the mean and the variance of the S. mansoni-infected group, respectively [The formula ectively .S. mansoni ova for infected participants [Three grams of the fresh stool sample were collected using clean, dry, and screw-capped plastic containers labeled with unique identification. Stool samples were processed through the direct wet mount for detection of parasites and Kato–Katz technique using a standardized template measuring 41.7 mg of the stool to prepare a thick smear for detection and quantification of the density of icipants .Six milliliters of venous blood was collected by experienced blood collectors using a sterile disposable plastic syringe after cleaning the venous puncture site with 70% ethanol. Three milliliters of blood was transferred into the ethylene diamine tetra acetic acid (EDTA) test tube for hematological profile analysis. The remaining 3 ml was placed in a plane test tube for analysis of biochemical profiles , 19.The 3 ml blood in the EDTA tube was dispensed and analyzed by Cell Dyn 1800  for the determination of complete blood cell count .Three milliliters of blood in the anticoagulant-free (plane) test tube was allowed to clot at bench top at least for 30 minutes. Then, it was centrifuged at 2,500 revolutions per minute for 4 minutes, and serum was aliquot by an Eppendorf tube. Then, serum was analyzed by using iChem535 chemistry analyzer for serum level of AST, ALT, blood glucose, total protein, and serum total cholesterol .t-test and one-way ANOVA. The P value with 95% of confidence interval was used to determine the association between the dependent and independent variables. Statistical significance was considered at a 95% level of confidence and P value less than 0.05.Data were registered into Statistical Package for Social Sciences (SPSS) version 20 for statistical analysis of mean and standard deviations, while the differences between the study and the control groups were assessed using the independent The study was conducted after ethical approval was obtained from the Research and Ethics committee of the School of Biomedical and Laboratory Sciences, College of Medicine & Health Sciences, University of Gondar. Moreover, letter of support was secured from the Sanja district health office and community leader. Before starting the actual data collection, permission was obtained from the hospital director. Additionally, after explaining the purpose, benefits, and the possible risks of the study, informed written consent was obtained from the study participants or their guardians. All laboratory results were kept confidential. Apparently, those positive for parasite and with hematological and biochemical abnormality were linked to the hospital and health center for appropriate treatment. The treatment cost was covered by communicating with the zonal and district health administrators.S. mansoni-positive, and the remaining were apparently healthy control group. Age ranged from 8 to 60 years with a mean age of 30.90 ± 9.11 for S. mansoni positive and 31.11 ± 13.20 for the control group. Half (110/220) of the participants were males and rural in residence. The majority (69.1%) of S. mansoni-positive individuals had a light parasite density , respectively, without a statistically significant association (P > 0.05). However, the mean serum total protein was significantly lower in the S. mansoni-infected group (68.70 ± 3.20) than the control group (69.76 ± 3.03). The mean serum AST level was elevated in S. mansoni-infected individuals (24.84 ± 2.19) compared with the control group (23.86 ± 2.22). The mean ALT level in S. mansoni-positive subjects was elevated (22.67 ± 4.66) compared with the control group (21.15 ± 2.27) (The mean blood glucose level was lower in the  ± 2.27) .P < 0.05) declines with increasing of parasite intensity. The mean value of HGB, HCT, MCH, MCHC, blood glucose, total protein, total cholesterol, and total WBC was significantly (P < 0.05) dropped in the moderately and heavily S. mansoni-infected patients compared with the control group and those with light S. mansoni egg density (P < 0.05). However, the mean value of AST was progressively elevated as the intensity of S. mansoni infection increased (P < 0.001)  .S. mansoni infection was 69.1% light, 28.2% moderate, and 2.7% heavy. This result is nearly similar to the result that is previously reported from Azezo, northwest Ethiopia, 67.8%, 19.8%, and, 3.1% light, moderate, and heavy intensity, respectively [Schistosomiasis remains one of the most important but neglected tropical diseases in Ethiopia . In the ectively . The curectively . Anotherectively . There wectively . The posS. mansoni-positive subjects had significantly (P < 0.001) lower mean of total WBC count as compared with the control group. This result is nearly comparable to the results of previously reported findings from a study in Nigeria, 2.5 × 103 ± 0.12 and 8.0 × 103 ± 2.10, S. mansoni-positive and the control group, respectively [P < 0.05) dwindled the mean total WBC in severely and moderately infected subjects as compared with the mildly infected group. The current study result was quite lower from a report from Sudan whose mean value of WBC in mild (7.5319 × 103) and severe (6.884 × 103) infected patients was high [Schistosoma mansoni like other helminth parasites manipulates the host immune response toward their comfortable condition. Therefore, observed changes in circulating total WBC numbers following S. mansoni infection are linked to the basic immune response to the parasite and also to induced biased proliferation or decrease in specific immune cells according to the disease stage and density [P < 0.05) degree elevation of the granulocyte (neutrophil and eosinophil) in the S. mansoni-infected subject as compared with the control group. During the acute infections with tissue-migrating larvae or following the sudden release of antigens from parasites dying either spontaneously or following chemotherapy is characterized by Schistosoma-induced eosinophil elevation [In the present study, the ectively . In the was high . Schisto density . The curlevation .P > 0.05) decrease in the mean erythrocytic parameters  below the normal range in the S. mansoni-infected subject as compared with the control group. The risk is also negatively associated with the burden of the parasite density. This result was slightly lower from a previous study in China with means of RBC 4.64 × 106/UL (Schistosoma-positive) and 4.7 × 106/UL (control group) [S. mansoni worms [In the present study, there was no significant (l group) . The decni worms , and enhni worms , 32.P < 0.001) dropped mean Hgb concentration with a cutoff point (<12) suggesting for anemia in S. mansoni-positive individuals as compared with the control group. This finding is in agreement with a result reported from west Burkina Faso which showed a mean value of HGB (g/dL) 11.57 ± 0.7 6 in Schistosoma-positive and 11.86 ± 1.51 in the control group [P < 0.001) dropped as the intensity of infection increased. Subjects with heavy infection density were more anemic than those with light and moderate infection. This finding is supported by other findings from western Kenya with a mean Hgb (g/dL) 11.6 in the control group and with light (11.9), moderate (11.3), and (10.9) heavy Schistosoma mansoni infection [The result from this study showed significantly  lower in the S. mansoni-positive group as compared with the control group. This finding was comparable with another recent report from Ghanaian study that showed mean of MCH 23.72 ± 0.43 in the S. mansoni-positive group and 26.21 ± 0.31 in the control group and mean of MCHC 31.25 ± 0.27 in the S. mansoni-positive group and 32.21 ± 0.19 in the control group [S. mansoni-positive group and 27.12 ± 2.82 in the control group, while the MCHC value was 33.02 ± 0.61 and 32.98 ± 0.72 in the S. mansoni-positive and control group, respectively [In the present study basic results, the mean MCH and MCHC were significantly (ol group . A studyP > 0.05) decreased in the S. mansoni-positive group as compared with the control group. Previous study in China reported a mean blood glucose level of 5.33 mmol/L (96 mg/dl) and 5.56 mmol/L (100.1 mg/dl) in the Schistosoma-positive group and the control group, respectively [The results from this present study showed that the mean blood glucose level was not significantly (ectively . Howeverectively .P < 0.05) declined in the S. mansoni-positive group as compared with the control group. This finding agrees with a study from Sudan where a mean total protein of 68 ± 0.1 and 76 ± 0.1 in the S. mansoni-positive and control group, respectively, was reported [S. mansoni-infected and control group, respectively [The current result shows mean of total protein was significantly  and in the control group (6.2 ± 0.18 and 7.1 ± 0.2), respectively [The present study showed an elevated mean value of ALT and AST in the ectively . The posectively , 40.P < 0.05) dropped in the S. mansoni-infected subject as compared with the control group in the current study. This finding is supported by a study from Brazil, which reported a mean total cholesterol level of 123.90 ± 21.52 and 156.31 ± 41.50 for the S. mansoni-positive group and the control group, respectively [Schistosoma did not synthesize cholesterol de novo, it is completely dependent on the host cholesterol and fatty acids [The mean total cholesterol level was significantly (ty acids .S. mansoni-infected patients as compared with the control group.In the present study, the mean concentrations of ALT, AST, Hgb, MCH, MCHC, total protein, total cholesterol, and WBC count were significantly altered in the Schistosoma mansoni were impaired compared with the normal level and control group. Therefore, schistosomiasis control programs should be strengthened in the study area and elsewhere to decrease its transmission. Other than treatment with Praziquantel, supportive treatment to alleviate health impairment due to hematological and biochemical disorders induced by S. mansoni infection should be considered.Severely parasitized patients showed a significant reduction in their mean MCH, MCHC, Hgb, blood glucose, total protein, and total cholesterol when compared with mildly and moderately infected study subjects. In general, the study showed that the hematological and biochemical profiles of patients infected with


Bos taurus cattle. In this study, body temperature increased, regardless of sex or temperament traits, characterizing SIH. Nevertheless, both flight speed (FS) and crush score (CS) were associated with an elevated rectal temperature (TREC) 30 min prior to the handling procedure, and this continued from the start of handling (T0) to 10 min post-handling (T10). The results from this study suggest that temperament may be related to variation in SIH in cattle during handling. Understanding the variation in behavioral and physiological response to stressful events may enable the development of new measures for genetic selection in cattle. Understanding animal responses to stressful stimuli is a fundamental aspect to evaluating animal welfare. Stress-induced hyperthermia (SIH) is a term used to describe a short-term increase in body temperature that occurs in response to stressful stimuli. Recently there has been increasing interest in SIH as a physiological measure of psychological stress in livestock species. Previously, studies have suggested that cattle with more excitable temperaments exhibit an increased stress response. This study evaluated the influence of temperament on SIH, during a standardized handling procedure in REC, °C) of 60 purebred Angus cattle  were recorded at 20 s intervals from 30 min prior to handling until two hours post handling. All cattle were exposed to a standardized handling procedure consisting of (i) being restrained in a weighing box for 30 s; (ii) being held within the crush for 30 s; and then (iii) being restrained in a head bail for 60 s. Cattle temperaments were evaluated via three traits: (1) agitometer score (AG); (2) crush score (CS); and (3) flight speed (FS) during the handling procedure. Agitometer scores and FS measures were used to describe an AG category (AGCAT) and an FS category (FSCAT) that were used to classify animals into three temperament categories: 1, calm; 2, intermediate; and 3, temperamental. Pearson’s correlation coefficients were used to evaluate the associations between (i) AG, CS, FS, and TREC 30 min prior to entry into the weighing box (T-30) and then at 1 min intervals between time of entry into the weighing box (T0) until 10 min post-weighing (T10); and (ii) the relationship between AG, CS, and FS. The relationship between TREC and temperament traits over the 2.5 h were modeled by using a first-order autoregressive repeated measures model. Flight speed had strong to moderate associations with TREC at T-30  and between T0 and T10 . There were moderate associations amongst TREC between T0 and T10 and CS . A weak relationship existed with CS . There were no associations between AG and TREC at T-30  or between T0 and T10 . Rectal temperature, irrespective of sex and temperament traits, was influenced by time (p < 0.0001), and maximum TREC (39.3 ± 0.04 °C) occurred between 4 and 5.7 min after entry into the weighing box. In addition, CS (p = 0.007) influenced TREC in these cattle. There were also time × temperament trait × sex interactions with the CS (p = 0.0003) and FSCAT (p = 0.043) categories; however, time × temperament trait interactions were not statistically significant. Results from this study suggest that cattle with excitable temperaments, as evaluated by FS and CS, have a greater increase in TREC. In addition, these results suggest that a relationship exists between basal TREC and FS and CS. Together, these results highlight that temperament, as assessed by FS and CS, influences both basal TREC and the peak temperature recorded following handling but does not influence the magnitude of change in TREC post handling. Previous studies have indicated that cattle with more excitable temperaments exhibit an increased stress response. The objective of this study was to investigate the relationship between temperament traits, handling, and stress-induced hyperthermia (SIH) in beef cattle. Rectal temperatures (T In livestock production enterprises, temperament is an important consideration, as individuals that are classified to have more excitable temperaments have been associated with decreased average daily gain ,2; reducREC, °C) in tropical environments have been reported to have calmer temperaments, greater reproductive efficiency, better growth rate, and a greater resistance to ticks [REC [Bos indicus [Bos taurus [Cattle with a lower rectal temperature  weather station (ID056238), located at Armidale Airport . During the handling procedure, average (±SEM) ambient temperature, dew point temperature, relative humidity, and wind speed were 12.3 ± 0.81 °C, 3.1 ± 0.81 °C, 57.2 ± 6.23%, and 2.4 ± 0.12 m/s, respectively.This study was conducted with the approval of the CSIRO McMaster Laboratory Animal Ethics Committee (ARA18-04), in accordance with the guidelines of the Australian National Health and Medical Research Council . Data weMedicago sativa) and lucerne-based pelleted concentrate. After weaning, and throughout the study, cattle were group-housed as a contemporary cohort on grazing pastures . During the study, cattle were relocated to a paddock adjacent to the cattle-handling facilities and were supplemented with approximately 1.5 kg/head of whole cotton seed (Gossypium spp.) daily.Thirty purebred Angus heifers (226.2 ± 5.01 kg) and 30 purebred Angus steers (244.3 ± 8.59 kg), aged between 7 and 10 months, were sourced from the FD McMaster Research Laboratory Angus performance-recorded herd and used in the study. Prior to this study, the FD McMaster Research Laboratory Angus performance-recorded herd was managed as a single herd. Cattle used in this study had previously been yard-weaned over a seven-day period, nine weeks prior to the study. Weaning occurred in a different handling facility to the one used in the current study. During weaning, cattle were fed a mix of lucerne hay  to attach the exposed end of the logger to the underside of the tail. After intra-rectal loggers were in place, all cattle (n = 60) were returned to grazing pasture adjacent to the handling facility. Data loggers were programed to record TREC at 20 s intervals from 08:00 h on day 2, 1 h prior to the handling procedure until 2 h post handling. On day 1, cattle were relocated from a paddock adjacent to the handling facility and intra-rectal data loggers were placed into the rectal cavity of all animals (n = 60). The handling facility was the same facility used for the handling procedure (see below) on day 2. Intra-rectal loggers were prepared and placed in situ using a technique modified from Lea et al. . BrieflyAt 08:00 h, on day 2, cattle were relocated from the adjoining paddock and marshalled into holding yards within the cattle handling facility, used on day 1. Cattle were given 30 min to settle down and return to basal activity prior to marshalling into a single-file race. Cattle were then exposed to a standardized handling procedure, typical of routine husbandry, consisting of three components: (1) cattle being confined in a single animal-weighing box  with solid sides, for 30 s (stage 1); then (2) being confined within a crush  for 30 s (stage 2); and then (3) being restrained in a head bail for 60 s (stage 3). The duration of the handling procedure was 2.3 min for each animal. A similar procedure utilized by Lee et al. , involviDuring the handling procedure on day 2, cattle temperaments were evaluated by utilizing three methodologies: (1) agitometer score (AG), (2) crush score (CS), and (3) flight speed (FS). Agitometer scores were determined via a purposely built agitometer attached to the weigh box via a metal bracket, modified from Blache and Ferguson . The agiCrush scores were evaluated by a single trained observer over the entire 30 s period, whilst the cattle remained unrestrained within the crush, during stage 2 of the standardized handling procedure, as described above, in Flight speeds were determined for all cattle on exit from the crush. Flight times were recorded for the time taken for cattle to traverse through two pairs of infrared sensors 1.8 m apart . These data were used to calculate FS (m/s) as described by Burdick et al.  . Rectal temperatures were aligned for each animal, so that time zero (T0) occurred at entry into the weighing box. Individual TCAT): 1, calm, ≤33 ; 2, intermediate, 45 ≤ 82 ; and 3, temperamental, ≥86 . Similarly, FS were then classified into three temperament categories (FSCAT): 1, calm, ≤1.6 m/s ; 2, intermediate, 1.7 m/s ≤2.5 m/s ; and 3, temperamental, ≥2.6 m/s . Agitometer and flight speed categories were developed by applying a percentile ranking technique, based on the data generated within this study [Agitometer scores were used to categorize animals into three temperament categories  and TREC measures, the relationship between TREC, sex, and temperament traits  were modeled by using a first-order autoregressive repeated measures model, within the “nlme” package [REC were investigated individually, as previous studies have established correlations between temperament traits. Each model incorporated time ; a temperament trait ; sex; time × sex; time × temperament trait ; and time × temperament trait  × sex as fixed effects. Animal identification was incorporated as a random effect in all models. Initially live weight was evaluated as a covariate within all models, but did not contribute significance (p ≥ 0.05); thus, live weight was excluded from the final models. Due to the proximate relationship and highly correlated nature of T package . The infp < 0.05, and tendencies were determined if p ≥ 0.05 and ≤ 0.10. The strength of the Pearson’s correlation coefficients was identified as weak (r ≤ 0.30), moderate (r = 0.30 ≤ 0.50), and strong (r ≥ 0.50), as described by Cohen [Statistical significance was set at by Cohen . p < 0.0001). Pooled TREC data indicated that maximum TREC (39.3 ± 0.04 °C) occurred 4 min after entry into the weighing box  and remained elevated until 5.7 min. There were no differences in the TREC between heifers (39.4 ± 0.07 °C) and steers  and heifers (0.28 °C), respectively, although the change in TREC of heifers was 0.27 °C between 4.3 and 5.3 min (REC showed a steady rate of decline (−0.01 °C) between 6.0 and 90.4 min, stabilizing at 38.9 ± 0.03 °C  or FS and AG . Heifers had greater CS (p = 0.017) and FS (p = 0.008) when compared to steers, however, there were no sex differences in AG . There was a weak relationship between CS and T-30 TREC . However, there were no relationships with T-30 TREC and AG .There were strong to moderate associations between T-30 Tp ≤ 0.0001) and TREC between T0 and T10  at any time point between T0 and T10, highlighting that the correlations are not changing over this period . There were limited differences between the TREC of CS scores 1  and 2 (slightly restless), where the minimum and maximum temperature differences were −0.10 and 0.11 °C, respectively  when compared with cattle scored as category 4 , where cattle that were scored in category 1 exhibited a 0.18 °C increase in TREC, whilst cattle scored within category 4 had a TREC increase of 0.44 °C  to influence TREC  were inclined to have higher TREC than cattle with lower (≤ 33) and higher (≥ 86) AG scores (Agitometer category had a tendency (nce TREC . InteresG scores . CAT had a tendency to influence TREC (p = 0.080) in these cattle (CAT 3 (FS ≥ 2.6 m/s) generally had higher TREC when compared with FSCAT 1 (FS ≤ 1.6 m/s) and 2 (FS 1.7 ≥ 2.5 m/s). The influence of FS on TREC appears to exist between FSCAT 1 and 2 in comparison to FSCAT 3, where cattle that were within FSCAT 1 and 2 exhibited a 0.22 and 0.24 °C increase in TREC, whilst cattle within category 3 had a TREC increase of 0.36 °C. Similarly, FSe cattle . Cattle REC when modeled with AGCAT (p = 0.178), CS (p = 0.306), or FSCAT (p = 0.126). There were no interactions between time × temperament trait, time × sex, or temperament trait × sex within the AGCAT, FSCAT, or CS models  occurred between 4 and 5.7 min after entry into the weighing box (T0), and then exhibited a steady rate of decline until 90.4 min, stabilizing at 38.9 ± 0.03 °C. The handling procedure had a total duration of 2.3 min; thus, TREC peaked 2 to 3.7 min after the conclusion of the handling procedure. These results indicate that the change in TREC from the onset of handling was characterizing SIH in these cattle via the short-term increase in TREC that occurred within minutes of the handling procedure commencing [Handling cattle can be considered a stressor eliciting a series of responses to stressful stimuli, including SIH ,30,32,35mmencing ,44,45. Tmmencing , concludmmencing ,30,32,35There have been numerous studies investigating the impact of various stressors on body-temperature responses in cattle ,30,46,47REC. When evaluating the impact of CS on TREC, there was a clear divergence in TREC responses of cattle across the CS categories. This is particularly evident when comparing the TREC of cattle that were scored within category 1  and category 4 . Similarly, Burdick et al. [REC. However, the magnitude of TREC increase was comparable between temperament classes [Within the current study, CS appeared to have the greatest influence on Tk et al. , establi classes , which w classes  suggest Recently, there has been some conjecture regarding what aspects of temperament FS and CS are evaluating ,52,53,54REC in these cattle, regardless of temperament traits, nor were there time × sex or temperament trait × sex influences  prior to transportation. Similarly, Burdick et al. [REC in Brahman bulls, where bulls classified as temperamental had higher TREC (p < 0.001) prior to a lipopolysaccharide challenge. The relationship between T-30 TREC and FS and CS within this study suggests that these temperament traits may have systemic influence on body temperature regulation, i.e., that cattle with faster FS and higher CS have higher body temperature when not being handled or exposed to stressful stimuli. This may provide a biological rationalization for the elevated TREC in bulls classified as temperamental prior to transport and a lipopolysaccharide challenge as described by Burdick et al. [REC, suggesting that cattle with lower TREC have higher flight time. However, the correlations described by Burrow [REC is collected after cattle have been exposed to ambient temperatures ≥ 30 °C, without access to shade, for a minimum of 3 h [REC may have been confounded by heat load [REC, which may indicate that these animals may have an increased susceptibility to heat load. However, further studies are required to quantify the relationship between temperament and body temperature, and the influence that this may have on an animals’ susceptibility to heat load. In this study, there were strong to moderate associations of Tk et al.  also estk et al.  establisk et al.  concludek et al.  and Burdk et al. . Burrow k et al.  reportedy Burrow  were colm of 3 h ; thus, Teat load ,61,62. Teat load ,16,17,18eat load , as the REC 120 min post-handling was 0.13 °C lower than 30 min prior to the handling procedure. Intra-rectal loggers were inserted the day prior to handling, to negate handling and data logger insertion influences on TREC. However, these cattle were kept in grazing pastures adjacent to the handling facility and required mustering from the paddock prior to the commencement of the handling procedure. Beatty et al. [REC described within this study does not provide a true estimate of basal TREC, as the TREC presented here may be confounded by relocation and handling events prior to the commencement of the handling procedure. Thus, it is anticipated that this accounts for the elevated TREC prior to the commencement of the handling procedure. Additionally, it is important to consider that body temperature exhibits a circadian rhythm [Interestingly, within the current study, Ty et al.  highlighy et al.  reportedn rhythm ,65,66, wn rhythm , understn rhythm , and redREC observed within this study suggest that the standardized handling procedure elicited a temperature response that was characteristic of SIH associated with psychological stress. Basal TREC differed between temperament classes within FS and CS traits, suggesting that there is an underlying influence of temperament traits on body temperature. Cattle with excitable temperaments, as evaluated by FS and CS, had higher TREC following handling; however, the magnitude of the temperature increase was comparable across temperament classes. Further studies are required to definitively quantify the relationship between temperament traits, body temperature, and SIH. Additionally, these results suggest that the impact of relocation, handling and temperament need to be considered when evaluating body temperature in cattle. Overall, these results further highlight the importance of selecting animals for calm temperaments, as cattle with excitable temperaments may exhibit a greater stress response during routine handling procedures.The variations in T


The present research examines the role of individual differences in self‐regulation  on initiative to resume an interrupted task.N1 = 208, 55% male, Mage = 33.2; N2 = 457, 62% male, Mage = 31.7; N3 = 210, 60% male, Mage = 32.6), participants were notified about a network interruption while playing a computer game. Participants could dismiss the interrupting notification by clicking a continue button or wait until the notification timed out. We manipulated demand by presenting notifications during (demand) versus after game rounds (no demand).In three studies . Exposure through repetition resulted in adaptation (Study 3).The findings suggest that people with lower action orientation have less self‐regulatory ability to initiate goal‐directed action and resume interrupted tasks—even if they are just a click away. Findings are discussed within the framework of Personality Systems Interactions theory. How we handle small hassles and interruptions has implications on how we function, including effects on our mood  versus after tasks (no demand). Then, we assessed participants' self‐regulatory abilities to initiate by measuring whether or not they clicked on the “continue” button, which dismissed the notification and allowed the player to resume, and measuring the time between presenting the interruption and clicking the button. We expected action‐ compared to state‐oriented individuals to show more initiative under this small‐scale demand that people experience frequently in daily life. Such a differential effect would emphasize volitional over motivational determinants of coping with interruptions. From an applied point of view, understanding the determinants of coping with interruptions would be informative because training self‐regulatory abilities (volition) requires a different type of intervention compared to the enhancement of task motivation  or better able to regulate themselves (volition)? To better understand the determinants of initiative, we presented an interrupting system notification during computer use that required no action other than to dismiss the notification. We created a subtle manipulation of demand by presenting notifications 1.1The personality disposition of action versus state orientation captures individual differences in self‐regulation. Demand‐related action orientation is the ability to self‐generate positive affect, to easily decide between action alternatives, and to quickly initiate the implementation of intentions under demanding conditions  that suffice to disrupt volitional action control in state‐oriented individuals, it is important to look for factors that can reduce the impact of such demands and improve initiative. Training self‐regulatory competence would be the method of choice to improve initiative in the long run and across contexts , and we presented a notification in the form of a simulated network interruption that paused game play. Participants could dismiss the notification by clicking a button or could wait until the notification timed out to continue playing. As a primary task, we chose a game that is known to be engaging to increase the likelihood that participants would be intrinsically motivated to resume the task and would desire to dismiss the notification. Games offer significant motivational pull and are able to satisfy basic psychological needs to experience competence, autonomy, and relatedness  versus after a game round (no demand). Note that although the latter does not interrupt an ongoing game round, it still interrupts the game—albeit at a more natural point for a break. We assessed initiative by measuring clicking (yes vs. no) and latencies (in seconds) for selecting the “continue” button, which dismissed the notification and allowed the player to resume. Our hypothesis was that action orientation would predict higher initiative when interrupted during a game round, when controlling for initiative after a game round.We experimentally manipulated demand by presenting the notification Note that there are multiple factors that may influence whether individuals click on the continue button or not . However, all of these factors should have the same effect for interruptions during and after tasks. In contrast, our hypothesis for action orientation is specific for interruptions during a task, when controlling for interruptions after a task. Furthermore, interruptions during a task create a demand rather than a threat. Therefore, we expected demand‐ but not by threat‐related action orientation to predict initiative.2http://www.bejeweled.com) that requires constant attention and is known to be engaging, which helps to ensure that the interruption is meaningful. We interrupted participants twice with a simulated network interruption notification: during and after a game round. Participants could either dismiss the notification or wait 60 s for the notification to time out and return to the game. We expected demand‐related action orientation to increase the probability of dismissal during a game round when controlling for dismissal after a game round.In Study 1, our goal was to demonstrate the differential effect of action–state orientation when interrupting participants during a game round. We developed a clone of the popular Match‐3 game Bejeweled  measure of initiative across the full sample. We expected action orientation to be associated with higher initiative . Our second strategy was to exclude all participants who did not dismiss both notifications (during and after a task) to further explore the decision process. We expected that action orientation is not associated with a more deliberate and time‐consuming decision process.2.12.1.1R2 = 0.06), the action orientation and demand interaction accounted for a small (0.02) to medium (0.13) amount of variance  for the expected interaction and used a power of 0.80. The power analysis suggested a total sample size of 200 participants. We invited a slightly higher number of participants (N = 230) to compensate for potential drop‐out. From this sample, 22 participants were excluded from further analysis as recommended in best practices for online behavioral studies  remained. Participants played games frequently (94.2% played a few times a month or more frequently).A power analysis was conducted prior to data collection using G*Power 3 , a game in which the goal is to swap adjacent gems to align gems of the same color. The game is easy to learn and there is a high degree of familiarity with the game mechanics in the general population, as many popular casual games are variants of the match‐3 game mechanic . We presented participants with an 8 by 8 grid of gems in one of five colors. Participants clicked or dragged adjacent gems to swap their locations and make matches. Participants gained 5 points for each gem when 3 or more gems of the same color were aligned. While three‐of‐a‐kind matches only gave points, four‐of‐a‐kind matches created special pieces that destroyed all adjacent pieces; five‐of‐a‐kind matches in “L,” “T,” or “+”‐shapes created special pieces that destroyed gems in a horizontal and vertical line; five‐of‐a‐kind matches in one line destroyed all gems in the matched color. We instructed participants on how to play the game using an avatar, who was present during game play and the simulated network interruption. We allowed half of the participants to customize their avatar as to foster motivation , which matches workers to requesters of work through an online platform. MTurk has been shown to be robust for conducting experiments with human participants  and threat‐related  action orientation. An example item for AOD is “When I am facing a big project that has to be done: (a) I often spend too long thinking about where I should begin, or (b) I don't have any problems getting started.” An example item for AOT is “When I have lost something that is very valuable to me and I can't find it anywhere: (a) I have a hard time concentrating on something else, or (b) I put it out of my mind after a little while.” In both items, options “a” represent the state‐oriented and options “b” the action–oriented response alternatives. In each scales, action‐oriented response alternatives were counted so that the scale ranged from 0 to 12, with lower scores indicating state orientation  and higher scores indicating action orientation. For further information on reliability and validity of the scale, see Kuhl and Beckmann , perceived competence , effort–importance , and pressure–tension . Agreement with items was assessed using a 5‐point scale . The IMI has previously been used to describe game experience , and gaming experience .2.22.2.1Correlations, means, and standard deviations are listed in Table 2.2.2p = .035. The finding is consistent with the assumption that task interruption does indeed create a demand that interferes with active task resumption.An exact McNemar's test determined that there was a significant difference in the proportion of participants who dismissed notifications during a task (89.42%) compared to after task (93.75%), 2.2.3B = −3.89, SE = 0.74, Wald (1) = 27.74, p < .001, OR = 0.02. Step 1 significantly improved the goodness of fit compared to a model containing only the constant, 2χ (2) = 39.20, p < .001. Gaming experience, performance, and motivational variables were not significantly associated with dismissal during a task. Step 2 did not significantly improve the goodness of fit, 2χ (6) = 4.27, p = .640. Consistent with expectations, demand‐related action orientation was significantly associated with dismissal during a task, B = 0.17, SE = 0.08, Wald (1) = 4.62, p = .042, OR = 1.19. The odd ratio (OR) of 1.19 indicates that a one unit increase in demand‐related action orientation corresponded to a 1.19 times (19%) higher probability of dismissing the notification during a task. Step 3 significantly improved the goodness of fit, 2χ (1) = 4.96, p = .026. Overall, the model explained 42% of variance in dismissal versus nondismissal.To test whether demand‐related action orientation predicted initiative under demanding conditions, we conducted a binary logistic regression analysis with dismissal  during a task as the dependent variable. In Step 1, we controlled for dismissal after a task (as a baseline) and order of the two interruptions (after/during vs. during/after). In Step 2, we entered gaming experience, game performance score, and four motivational variables. In Step 3, we entered demand‐related action orientation. Results are listed in Table B = 0.14, SE = 0.08, Wald (1) = 2.72, p = .099, OR = 1.15. Step 3 did not significantly improve the goodness of fit, 2χ (1) = 2.93, p = .087. Thus, the effect is specific for demand‐related action orientation and occurred over and above of gaming experience, performance, and motivational variables. To further illustrate the finding  and action‐oriented .In an additional binary logistic regression analysis, we entered threat‐ instead of demand‐related action orientation in Step 3 as a test of discriminant validity. Consistent with expectations, threat‐related action orientation was not associated with a higher probability of dismissing the notification during a task, 2.2.4M = 10.38 s, SD = 13.96). As listed in Table β = 0.51, t = 8.68, p < .001, and order, β = −0.25, t = −4.19, p < .001. Gaming experience, performance, and motivational variables were not significantly associated with dismissal latencies during a task. Consistent with expectations, demand‐related action orientation was associated with faster dismissal during a task, β = −0.15, t = −2.46, p = .015, and accounted for additional variance, ∆R2 = 0.020, ∆F = 6.06, p = .015. Consistent with expectations, there was no significant effect when entering threat‐ instead of demand‐related action orientation, β = 0.04, t = 0.57, p = .569. Findings indicate that this continuous measure of initiative  yielded effects that were similar to the binary measure .To create a more continuous measure of initiative, we set nondismissals to 60 s and conducted a hierarchical regression analysis on latencies . As listed in Table slower dismissal during a task, β = 0.03, t = 0.40, p = .688, indicating that decision processes were not more deliberate.To further explore the decision process, we excluded the 25 participants who did not dismiss both notifications. In the subsample of 2.3The results of our first experiment show that action orientation was associated with a higher probability of dismissing the notification during a task. The finding is consistent with the assumption that action‐oriented participants are better able to initiate goal‐directed action under demand. We controlled for several alternative explanations. First, we controlled for dismissal after a task . Although many factors may influence clicking the continue button , none of these can easily explain the difference in probability of dismissing an interruption during versus after a task.task ability  and task motivation  in the regression model. Third, the effect occurred for demand‐related (self‐regulation of positive affect) but not threat‐related action orientation (self‐regulation of negative affect). When a subtle demand hampers positive affect, demand‐related action orientation helps to self‐generate the positive affect needed to initiate the necessary action for task resumption. Fourth, the effect held across binary  and continuous  measures of initiative. Finally, action‐oriented participants did not engage in more deliberate and time‐consuming decision processes. These results support our hypothesis that action orientation is associated with greater self‐regulatory ability to initiate action under demand, even when the demand itself is subtle and the measurement of initiative is fine grained.Second, the effect of action orientation occurred when controlling for the effects of M + 1 SD) of dismissal latencies in Study 1 .Because the notification was presented for 60 s, we observed a very high probability of dismissal (92%). This ceiling effect indicates that we created a situation in which most participants eventually clicked the continue button. In Study 2, we therefore aimed at creating a situation that yields probabilities for dismissal closer to 50% by setting the notification timeout around the mean . Second, we obtained a highly significant order effect in dismissal latencies in Study 1. Therefore, we roughly doubled the number of participants to be able to detect the expected effect with a small effect size over and above order effects.3.1α) were sufficient for demand‐ and threat‐related action orientation  and the four motivational variables of interest/enjoyment (0.86), perceived competence (0.88), effort/importance (0.82), and tensions/pressure (0.86).The methods for Study 2 were identical to those of Study 1, except that the interrupting notification was set to count down from 10 (rather than 60) s before automatically being dismissed. Internal consistencies . Participants were again familiar with playing digital games (91.9% played a few times a month or more frequently). Data were treated in the same way as in Study 1.Five hundred participants were recruited through Amazon Mechanical Turk. From this sample, 43 were removed from subsequent analyses as described in Study 1, leaving 457 participants  compared to after a task (71.77%), 3.2.3B = −2.76, SE = 0.27, Wald (1) = 104.56, p < .001, OR = 0.06. Participants were more likely to dismiss notifications during a task when notified for the second time (order: after/during) compared to the first time (order: during/after), B = −0.90, SE = 0.26, Wald (1) = 11.91, p < .001, OR = 0.41. Step 1 significantly improved the goodness of fit compared to a model containing only the constant, 2χ (2) = 134.17, p < .001. Performance, gaming experience, and motivational variables were not significantly associated with dismissal during a task. Step 2 did not significantly improve the goodness of fit, 2χ (6) = 12.31, p = .055. Consistent with expectations, demand‐related action orientation was associated with dismissal during a task, B = 0.08, SE = 0.03, Wald (1) = 4.94, p = .026, OR = 1.08. One unit increase in demand‐related action orientation corresponded to a 1.08 times (8%) higher probability of dismissal during a task. Step 3 significantly improved the goodness of fit, 2χ (1) = 5.02, p = .025. Overall, the model explained 40% of variance in dismissal versus nondismissal.We conducted a binary logistic regression analysis with dismissal versus nondismissal of the notification during a task as the dependent variable  = 0.06, p = .802, OR = 1.01, and did not significantly improve the goodness of fit, 2χ (1) = 0.06, p = .802. Thus, the effect is specific for demand‐related action orientation and occurred when controlling for gaming experience, performance, and motivational variables. To further illustrate the finding  and action‐oriented .In an additional binary logistic regression analysis, we entered threat‐ instead of demand‐related action orientation in Step 3. Consistent with expectations, threat‐related action orientation was not associated with dismissal of notifications during a task, 3.2.4M = 5.28 s (SD = 2.93). As listed in Table β = 0.59, t = 14.70, p < .001, order, β = −0.39, t = −9.65, p < .001, and performance, β = −0.13, t = −3.27, p < .001. Gaming experience and motivational variables were not significantly associated with dismissal latencies during a task. Consistent with expectations, demand‐related action orientation was associated with faster dismissal during a task, β = −0.11, t = −2.20, p = .028, and accounted for additional variance, ∆R2 = 0.008, ∆F = 2.70, p = .028. Consistent with expectations, there was no significant effect when entering threat‐ instead of demand‐related action orientation, β = 0.09, t = 1.89, p = .059. Findings indicate that the continuous measure of initiative  yielded similar effects to the binary measure .When setting latencies for nondismissal to 10 s, average dismissal latencies were  SD = 2.9. As listM = 3.17 s (SD = 1.16). As listed in Table β = 0.25, t = 4.07, p < .001, and order effects, β = −0.66, t = −10.96, p < .001. No other effects were significant. Consistent with expectations, demand‐related action orientation was not associated with significantly slower dismissal during a task, β = 0.09, t = 1.59, p = .113. Findings do not suggest that action‐oriented participants engaged in more deliberative and time‐consuming decision processes.When including only the 247 participants who dismissed both notifications, average dismissal latencies were 3.3Shortening the time frame for initiative from 60 to 10 s decreased the overall probability of dismissal from 92% in Study 1 to 70% in Study 2. When eliminating the ceiling effect, we replicated the results of our first experiment that action‐oriented participants were more likely to dismiss notifications during a task. Again, we controlled for dismissal after a task  as well as task ability and task motivation. Furthermore, we replicated that the effect is specific for demand‐related rather than threat‐related action orientation. Finally, the findings with dismissal latencies (a continuous measure of initiative) complemented our findings for dismissal and did not suggest that action‐oriented participants engaged in more deliberate decision processes.In Studies 1 and 2, we demonstrated the detrimental effect of demand‐related state orientation on initiative under a minor demand in the context of computer use. Because of these observed effects, we were next interested in exploring how we can reduce the effect of state orientation on initiative under minor demands. Previous work on task interruption has shown that repetition can foster adaptation Monk, . In a si4The goal of Study 3 was to establish how fast people are able to adapt and become initiative under demand. Research has shown that people adapt to interruptions when the frequency of exposure is increased Monk, , and thaBecause our study is the first to test this hypothesis, we did not know how fast adaption would occur. To be on the safe side, we explored several repetitions. In contrast to Studies 1 and 2, all participants experienced an interruption under no demand first , followed by five interruptions under demand , which were presented every second round. We expected that state‐oriented participants are less likely to dismiss than action‐oriented participants under demand. However, we also expected that the differential effect would disappear after repeated exposure.4.1α) were sufficient for demand‐ and threat‐related action orientation  and the four motivational variables of interest/enjoyment (0.92), perceived competence (0.91), effort/importance (0.78), and tensions/pressure (0.83).The methods were similar to those of Studies 1 and 2, with the exception of the sequence of interruptions. In Study 3, we presented 12 one‐minute rounds of Bejeweled. We interrupted all participants after Round 1  and during Rounds 3, 5, 7, 9, and 11 . As in Study 2, the notification counted down from 10 s before being automatically dismissed. Internal consistencies . Participants were again generally familiar with games (90% played games a few times a month or more frequently). Data were treated in the same way as in Studies 1 and 2.We aimed at a similar sample size as in Study 1 because we held the order of interruptions (after/during tasks) constant across participants. Two hundred and sixteen participants were recruited. From this sample, 6 participants were excluded using the method described in Study 1. The remaining 210 participants  had a mean age of 32.66 years  and effort/importance . Overall, 70.57% (SD = 41.32) of the participants dismissed notifications. The overall probability for dismissal versus nondismissal did not correlate with any study variable.Demand‐related action orientation correlated positively with threat‐related action orientation  = 45.82, p < .001, OR = 0.10. Step 1 significantly improved the goodness of fit compared to a model containing only the constant, 2χ (1) = 54.85, p < .001. Gaming experience, performance, and motivational variables were not significantly associated with dismissal during Task #3. Step 2 did not significantly improve the goodness of fit, 2χ (6) = 2.32, p = .889. Consistent with expectations, demand‐related action orientation was associated with dismissal during a task, B = 0.10, SE = 0.05, Wald (1) = 4.44, p = .035, OR = 1.11. One unit increase in demand‐related action orientation corresponded to a 1.11 times (11%) higher probability of dismissal during a task. Step 3 significantly improved the goodness of fit, 2χ (1) = 4.58, p = .032. Overall, the model explained 35% of variance in dismissal versus nondismissal. Entered threat‐ instead of demand‐related action orientation in Step 3 did not yield a significant effect, B = 0.04, SE = 0.05, Wald (1) = 0.71, p = .400, OR = 1.04. Thus, the effect during Task #3 was specific for demand‐related action orientation and occurred when controlling for dismissal after Task #1, gaming experience, performance, and task motivation.We conducted a binary logistic regression analyses with dismissal versus nondismissal when interrupted during Task #3 as the dependent variable  = 0.31, p = .575, OR = 1.03, Task #7, B = 0.02, SE = 0.05, Wald (1) = 0.18, p = .676, OR = 1.02, Task #9, B = 0.03, SE = 0.05, Wald (1) = 0.54, p = .464, OR = 1.03, and Task #11, B = 0.01, SE = 0.05, Wald (1) = 0.07, p = .781, OR = 1.01. Thus, repetition of task interruptions led to fast adaptation. To further illustrate the finding  and action‐oriented .In binary logistic regression analyses with dismissal versus nondismissal during Tasks #5–#11 as a dependent variable, there were no significant effects in Steps 2 and 3. Specifically, participants with higher action orientation were not more likely to dismiss the notifications during Task #5, 4.2.4M = 4.84 s (SD = 3.08). As listed in Table β = 0.48, t = 7.87, p < .001. There were no significant effects of gaming experience, performance, and motivational variables. Consistent with expectations, demand‐related action orientation was associated with faster dismissal of the notification during Task #3, β = −0.13, t = −2.01, p = .046, and accounted for additional variance, ∆R2 = 0.015, ∆F = 4.03, p = .046. There was no significant effect when entering threat‐ instead of demand‐related action orientation, β = −0.06, t = −0.85, p = .397. In regression analyses with dismissal latencies during Tasks #5–#11 as a dependent variable, there were no significant effects in Steps 2 and 3. Findings indicate that this more continuous measure of initiative yielded similar effects to dismissal versus nondismissal.When setting latencies for nondismissal to 10 s, average dismissal latencies were 4 s SD = .08. As lM = 2.29 s (SD = 0.70). As listed in Table β = 0.25, t = 2.38, p = .019. There were no further significant effects. Specifically, demand‐related action orientation was not associated with slower (and descriptively even faster) dismissal during Task #3, β = −0.22, t = −1.95, p = .055. Regression analyses with dismissal latencies during Tasks #5–#11 as a dependent variable did not show any significant effects in Steps 2 and 3. Findings do not suggest that action‐oriented participants engaged in more deliberate decision processes.When including only the 88 participants who dismissed all notifications, average dismissal latencies were 4.3In Study 3, we again replicated our central finding. Action orientation was associated with higher probability to dismiss the notification during a task (under demand), when controlling for dismissal after a task (no demand). In addition, after the first repetition, state‐oriented participants had effectively adapted to the demand and were as likely to dismiss notifications during tasks as were action‐oriented participants.5during game rounds (under demand), controlling for initiative when interrupted after game rounds (no demand). Our findings extend classical findings of Ovsiankina , and across two different measures for initiative . This methodological convergence increases confidence in the robustness of our findings. Furthermore, the findings remained significant when controlling for task ability (gaming experience and performance) and several indicators of task motivation. Thus, state‐oriented participants' lower probability of dismissal under demand cannot be easily explained by less familiarity with computers, lower interest in the game, or greater tension that may call for taking a break. Dismissal latencies of the subsamples of participants who dismissed notifications do not indicate that state‐ and action‐oriented participants differed in deliberate decision processes that may have biased them toward dismissal or nondismissal. Instead, the findings are consistent with the large body of research indicating that state‐ and action‐oriented individuals differ in the In the context of our studies, waiting a few seconds longer to continue a fun game may not appear dramatic or disadvantageous. However, our differential effect unravels a more general mechanism: A negligible demand suffices to hamper initiative for participants who have lower action orientation . This may have important consequences in other contexts and widen the intention–behavior gap. Therefore, it is important to elaborate why exactly interruptions during game rounds are so demanding. One possible (affective) explanation is that they elicit more feelings of annoyance and frustration  whenever an action cannot be carried out immediately through automatic behavioral programs  and their lower ability to self‐generate the positive affect needed to actually carry them out. Both mechanisms are mutually intensifying and have been shown to be a risk factor in the development, chronicity, and recurrence of depression  suggests that our setting has induced an “implemental mind set” that is well suited to tease out volitional determinants of initiative . However, participants have little control over the frequency of interruptions in daily life. Future studies should look for mitigating factors that are less externally controlled and more easily applied as a self‐help technique. For example, visualising an accepting (vs. demanding) person and thinking of similarities (vs. differences) with a close other has been found to reduce the detrimental effects of stress on state‐oriented individuals' well‐being (Chatterjee, Baumann, & Koole, 7Task interruptions occur frequently in daily life Almeida, , but wheThe differential ability to initiate under minor demands has major implications. State‐oriented individuals tend to activate intentions under demand, but are less capable of generating the positive affect needed to carry them out (Goschke & Kuhl, The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.