human
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: In the current work we asked whether executive function , as measured by tests of working memory capacity , might benefit from an acute bout of exercise and , more specifically , whether individuals who are lower or higher in working memory to begin with would be more or less affected by an exercise manipulation . Healthy adults completed working memory measures in a nonexercise ( baseline ) session and immediately following a 30-min self-paced bout of exercise on a treadmill ( exercise session ) . Sessions were conducted 1 week apart and session order was counterbalanced across participants . A significant Session x Working Memory interaction was obtained such that only those individuals lowest in working memory benefited from the exercise manipulation . This work suggests that acute bouts of exercise may be most beneficial for healthy adults whose cognitive performance is generally the lowest , and it demonstrates that the impact of exercise on cognition is not uniform across all individuals Background Although basic research has uncovered biological mechanisms by which exercise could maintain and enhance adult brain health , experimental human studies with older adults have produced equivocal results . Purpose This r and omized clinical trial aim ed to investigate the hypotheses that ( a ) the effects of exercise training on the performance of neurocognitive tasks in older adults is selective , influencing mainly tasks with a substantial executive control component and ( b ) performance in neurocognitive tasks is related to cardiorespiratory fitness . Methods Fifty-seven older adults ( 65–79 years ) participated in aerobic or strength- and -flexibility exercise training for 10 months . Neurocognitive tasks were selected to reflect a range from little ( e.g. , simple reaction time ) to substantial ( i.e. , Stroop Word – Color conflict ) executive control . Results Performance in tasks requiring little executive control was unaffected by participating in aerobic exercise .  Improvements in Stroop Word – Color task performance were found only for the aerobic exercise group . Changes in aerobic fitness were unrelated to changes in neurocognitive function . Conclusions Aerobic exercise in older adults can have a beneficial effect on the performance of speeded tasks that rely heavily on executive control . Improvements in aerobic fitness do not appear to be a prerequisite for this beneficial effect We investigated the cross-sectional and prospect i ve associations between different sedentary behaviors and cognitive function in a large sample of adults with data stored in the UK Biobank . Baseline data were available for 502,643 participants ( 2006 - 2010 , United Kingdom ) . Cognitive tests included  prospect  i  ve memory  ( baseline only : n = 171,585 ) , visual-spatial memory ( round 1 : n = 483,832 ; round 2 : n = 482,762 ) , fluid intelligence ( n = 165,492 ) , and short-term numeric memory ( n = 50,370 ) . After a mean period of 5.3 years , participants ( numbering from 12,091 to 114,373 , depending on the test ) also provided follow-up cognitive data . Sedentary behaviors ( television viewing , driving , and nonoccupational computer-use time ) were measured at baseline . At baseline , both television viewing and driving time were inversely associated with cognitive function across all outcomes ( e.g. , for each additional hour spent watching television , the total number of correct answers in the fluid intelligence test was 0.15 ( 99 % confidence interval : 0.14 , 0.16 ) lower . Computer-use time was positively associated with cognitive function across all outcomes . Both television viewing and driving time at baseline were positively associated with the odds of having cognitive decline at follow-up across most outcomes . Conversely , computer-use time at baseline was inversely associated with the odds of having cognitive decline at follow-up across most outcomes . This study supports health policies design ed to reduce television viewing and driving in adults Adults are sedentary for an alarming 9 to 10 hours per day ( 1 ) . Accordingly , the popular press has coined the phrase sitting is the new smoking to describe a current epidemic of developed nations ( 24 ) . Evidence indicates that sedentary time is associated with incident cardiovascular disease , incidence of cardiovascular diseaserelated risk factors , and mortality ( 5 , 6 ) . Of note , the risk conferred by prolonged sedentariness is eliminated only by high levels of moderate- to vigorous-intensity physical activity ( MVPA ) ( about 60 to 75 min/d ) , which exceed physical activity recommendations ( 7 , 8) . As such , sedentary behavior is now believed to represent a clinical ly important aspect of a person 's physical activity profile and is no longer considered simply the extreme low end of the physical activity continuum ( 5 ) . Studies linking sedentary behavior to health outcomes have relied almost exclusively on self-reported  sedentary time  , which is subject to reporting bias and measurement error ( 9 ) . A 2015 systematic review ( 5 ) identified only 1 study ( NHANES [ National Health and Nutrition Examination Survey ] ) that examined the association between objective ly measured sedentary time and health outcomes , a study limited by a small event rate ( 10 ) . New studies using NHANES data have since been published , with longer follow-up and higher event rates ( 1115 ) . However , some of these studies have reported an association between objective ly measured sedentary time and mortality ( 11 , 14 , 15 ) , but others have not ( 12 , 13 ) . Additional cohort studies are thus needed to rectify evidence gaps . Furthermore , studies using accelerometers to objective ly measure sedentary behavior conventionally operationalize sedentary time as the total number of sedentary minutes per day . This approach ignores patterns of accumulated sedentary behavior over time . For example , accumulation of sedentary time in a few long bouts or many short bouts represents 2 distinct patterns of sedentary time accrual . Experimental studies have shown that acute periods of prolonged , uninterrupted sedentary behavior cause greater detrimental cardiometabolic effects than sedentary behavior that is periodically interrupted ( 1618 ) , suggestive that it is not just total sedentary time that is relevant to health outcomes , but also the manner in which it is accumulated . Few longitudinal studies , however , have explored the association between prolonged , uninterrupted sedentary behavior and mortality to corroborate these findings . To inform guidelines on reducing sedentary behavior ( target reductions in overall sedentary time or target interruption of prolonged sedentary bouts ) , evidence from prospect i ve studies is needed to 1 ) confirm the association between total sedentary time and mortality using objective measures , 2 ) determine whether prolonged sedentary bouts confer risk for death , and 3 ) eluci date whether the total volume of sedentary time and its pattern of accumulation individually or jointly contribute to risk for death . The purpose of this study , therefore , was to examine the association between objective ly measured sedentary time ( both total volume and accrual in prolonged bouts ) and all-cause mortality in a national cohort of U.S. middle-aged and older adults enrolled in the REGARDS ( Reasons for Geographic and Racial Differences in Stroke ) study . Methods Study Population REGARDS is a population -based study design ed to examine racial and regional disparities in stroke . It comprises 30239 white and black adults aged 45 years or older enrolled between 2003 and 2007 from across the contiguous United States ( 19 , 20 ) . Detailed design and methods for REGARDS are described elsewhere ( 21 ) . Briefly , demographic and cardiovascular risk factor data were collected by telephone interview and an in-home physical assessment on enrollment . A detailed summary of baseline measures is provided in the Supplement . Participants ( or their proxies ) were then followed for 6-month intervals to ascertain vital status . Objective measurements of sedentary behavior were collected from active REGARDS participants from 2009 to 2013 ( mean time from study enrollment , 5.7 years [ SD , 1.5 ] ; range , 1.9 to 9.5 years ) ( 22 ) . A total of 7985 participants adhered to accelerometer wear requirements ( 4 days with accelerometer wear 10 hours ) , provided follow-up data , and were available for the current analyses ( Supplement Figure 1 ) . Supplement Table 1 shows the characteristics of included versus excluded REGARDS participants . The REGARDS study protocol was approved by the institutional review boards of participating institutions . All participants provided informed consent . Supplement . Supplementary Material Accelerometer Data Collection Methods for accelerometer data collection are described elsewhere ( 22 ) . Briefly , participants were fitted with an Actical ( Philips Respironics ) accelerometer secured to their right hip using a nylon belt and were instructed to wear the device during waking hours for 7 consecutive days . The Actical had been vali date d formeasurement of physical activity and sedentary behavior and was shown to have acceptable reliability ( 2325 ) . Activity counts were summed over 1-minute epochs . Nonwear periods were defined as at least 150 consecutive minutes of 0 activity counts . This nonwear algorithm was previously vali date d against daily log sheets in REGARDS participants ( 26 ) . Measurements of 0 to 49 , 50 to 1064 , and at least 1065 counts per minute were defined as sedentary behavior , light-intensity physical activity , and MVPA , respectively , as determined in a laboratory-based calibration study ( 27 ) . A sedentary bout was defined as consecutive minutes in which the accelerometer registered fewer than 50 counts per minute . A sedentary break was defined as at least 1 minute in which 50 or more counts per minute were registered after a sedentary bout . Both sedentary bouts and breaks were exclusively continuous periods , with no interruptions or nonwear intervals allowed in the definition . Outcome Ascertainment All-cause mortality was the primary outcome , defined as any death after completion of the accelerometer protocol regardless of cause . Date s of death were confirmed through review of death certificates , medical records , and administrative data bases . Deaths through 4 September 2015 were included in the current analysis . Statistical Analysis Sedentary and physical activity variables were averaged across compliant days ( 10 hours of wear ) . Because of a high correlation between total sedentary time and wear time ( Supplement Figure 2 ) , we corrected for the influence of wear time by st and ardizing total sedentary time to 16 hours of wear time per day using the residuals obtained when regressing total sedentary time on wear time ( see Methods section of the Supplement ) ( 2830 ) . Participants were stratified into quartiles according to total sedentary time and , separately , mean sedentary bout duration ( a measure of overall prolonged , uninterrupted sedentary behavior ) . Cox proportional hazards regression modeling was used to calculate the hazard ratio ( HR ) for all-cause mortality associated with quartiles of total sedentary time ( and separately , mean sedentary bout length ) . Crude HRs were initially calculated . Subsequent HRs were calculated after adjustment for age , race , sex , region of residence , education , and season the accelerometer was worn ( model 1 ) , with further adjustment for current smoking , alcohol use , body mass index ( BMI ) , diabetes , hypertension , dyslipidemia , estimated glomerular filtration rate less than 60 mL/min/1.73 m2 , atrial fibrillation , history of coronary heart disease , and history of stroke ( model 2 ) . Models were additionally adjusted for MVPA expressed continuously ( model 3 ) . Tests for linear trend across quartiles were conducted by including the quartile for each participant as an ordinal variable in regression models . Proportional hazards assumptions were confirmed with a Kolmogorov-type supremum test ( 31 ) . The above analyses were then repeated in a fully adjusted model , testing interactions for age ( < 65 and 65 years ) , sex ( male and female ) , race ( black and white ) , BMI category ( normal weight and overweight or obese ) , and MVPA category ( < 150 min/wk and 150 min/wk ) . As a secondary analysis , we examined the continuous doseresponse relationship between each sedentary characteristic and all-cause mortality in a fully adjusted model ( model 3 ) using restricted cubic splines ( 32 ) . Cubic polynomials were fitted with the mean of each sedentary characteristic set as the reference and knots placed at the 5th , 35th , 65th , and 95th percentiles ( 33 ) . Nonlinear associations were evaluated using the likelihood ratio test . For nonlinear associations , spline models were used to describe the associations and when the association was determined to be linear , a linear model was used . Because of multicollinearity between total sedentary time and mean sedentary bout duration ( r= 0.61 ) , both variables were not included in the same model . Alternatively , to examine the individual and joint associations of total sedentary time and prolonged , uninterrupted sedentary behavior with mortality , participants were classified into 4 categories : low total sedentary time ( < 750 min/d ) and low prolonged sedentary bout time ( < 10 min/bout ) , low total sedentary time  and high prolonged sedentary bout time  ( 10 min/bout ) , high total sedentary time  ( 750 min/d ) and low prolonged sedentary bout time , and high total sedentary time and high prolonged sedentary bout time . Hazard ratios for all-cause mortality were calculated for each joint category in comparison with the lowlow group in a fully adjusted model ( model 3 ) . Thresholds for total sedentary time ( 750 min/d ) and mean sedentary bout duration ( 10 min/bout ) were selected on the basis of the restricted cubic splines and were confirmed using a method described by Contal and O'Quigley ( see Methods section of the Supplement ) ( 34 ) . To allow for the possibility that sedentary bouts Abstract Recent attention has highlighted the importance of reducing sedentary time for maintaining health and quality of life . However , it is unclear how changing sedentary behavior may influence 
    Output:
    
agent
Conclusion : These data suggest that sedentary behavior is not associated with changes in cognitive performance in interventions that intend to reduce sedentary behavior .
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: In the current work we asked whether executive function , as measured by tests of working memory capacity , might benefit from an acute bout of exercise and , more specifically , whether individuals who are lower or higher in working memory to begin with would be more or less affected by an exercise manipulation . Healthy adults completed working memory measures in a nonexercise ( baseline ) session and immediately following a 30-min self-paced bout of exercise on a treadmill ( exercise session ) . Sessions were conducted 1 week apart and session order was counterbalanced across participants . A significant Session x Working Memory interaction was obtained such that only those individuals lowest in working memory benefited from the exercise manipulation . This work suggests that acute bouts of exercise may be most beneficial for healthy adults whose cognitive performance is generally the lowest , and it demonstrates that the impact of exercise on cognition is not uniform across all individuals Background Although basic research has uncovered biological mechanisms by which exercise could maintain and enhance adult brain health , experimental human studies with older adults have produced equivocal results . Purpose This r and omized clinical trial aim ed to investigate the hypotheses that ( a ) the effects of exercise training on the performance of neurocognitive tasks in older adults is selective , influencing mainly tasks with a substantial executive control component and ( b ) performance in neurocognitive tasks is related to cardiorespiratory fitness . Methods Fifty-seven older adults ( 65–79 years ) participated in aerobic or strength- and -flexibility exercise training for 10 months . Neurocognitive tasks were selected to reflect a range from little ( e.g. , simple reaction time ) to substantial ( i.e. , Stroop Word – Color conflict ) executive control . Results Performance in tasks requiring little executive control was unaffected by participating in aerobic exercise .  Improvements in Stroop Word – Color task performance were found only for the aerobic exercise group . Changes in aerobic fitness were unrelated to changes in neurocognitive function . Conclusions Aerobic exercise in older adults can have a beneficial effect on the performance of speeded tasks that rely heavily on executive control . Improvements in aerobic fitness do not appear to be a prerequisite for this beneficial effect We investigated the cross-sectional and prospect i ve associations between different sedentary behaviors and cognitive function in a large sample of adults with data stored in the UK Biobank . Baseline data were available for 502,643 participants ( 2006 - 2010 , United Kingdom ) . Cognitive tests included  prospect  i  ve memory  ( baseline only : n = 171,585 ) , visual-spatial memory ( round 1 : n = 483,832 ; round 2 : n = 482,762 ) , fluid intelligence ( n = 165,492 ) , and short-term numeric memory ( n = 50,370 ) . After a mean period of 5.3 years , participants ( numbering from 12,091 to 114,373 , depending on the test ) also provided follow-up cognitive data . Sedentary behaviors ( television viewing , driving , and nonoccupational computer-use time ) were measured at baseline . At baseline , both television viewing and driving time were inversely associated with cognitive function across all outcomes ( e.g. , for each additional hour spent watching television , the total number of correct answers in the fluid intelligence test was 0.15 ( 99 % confidence interval : 0.14 , 0.16 ) lower . Computer-use time was positively associated with cognitive function across all outcomes . Both television viewing and driving time at baseline were positively associated with the odds of having cognitive decline at follow-up across most outcomes . Conversely , computer-use time at baseline was inversely associated with the odds of having cognitive decline at follow-up across most outcomes . This study supports health policies design ed to reduce television viewing and driving in adults Adults are sedentary for an alarming 9 to 10 hours per day ( 1 ) . Accordingly , the popular press has coined the phrase sitting is the new smoking to describe a current epidemic of developed nations ( 24 ) . Evidence indicates that sedentary time is associated with incident cardiovascular disease , incidence of cardiovascular diseaserelated risk factors , and mortality ( 5 , 6 ) . Of note , the risk conferred by prolonged sedentariness is eliminated only by high levels of moderate- to vigorous-intensity physical activity ( MVPA ) ( about 60 to 75 min/d ) , which exceed physical activity recommendations ( 7 , 8) . As such , sedentary behavior is now believed to represent a clinical ly important aspect of a person 's physical activity profile and is no longer considered simply the extreme low end of the physical activity continuum ( 5 ) . Studies linking sedentary behavior to health outcomes have relied almost exclusively on self-reported  sedentary time  , which is subject to reporting bias and measurement error ( 9 ) . A 2015 systematic review ( 5 ) identified only 1 study ( NHANES [ National Health and Nutrition Examination Survey ] ) that examined the association between objective ly measured sedentary time and health outcomes , a study limited by a small event rate ( 10 ) . New studies using NHANES data have since been published , with longer follow-up and higher event rates ( 1115 ) . However , some of these studies have reported an association between objective ly measured sedentary time and mortality ( 11 , 14 , 15 ) , but others have not ( 12 , 13 ) . Additional cohort studies are thus needed to rectify evidence gaps . Furthermore , studies using accelerometers to objective ly measure sedentary behavior conventionally operationalize sedentary time as the total number of sedentary minutes per day . This approach ignores patterns of accumulated sedentary behavior over time . For example , accumulation of sedentary time in a few long bouts or many short bouts represents 2 distinct patterns of sedentary time accrual . Experimental studies have shown that acute periods of prolonged , uninterrupted sedentary behavior cause greater detrimental cardiometabolic effects than sedentary behavior that is periodically interrupted ( 1618 ) , suggestive that it is not just total sedentary time that is relevant to health outcomes , but also the manner in which it is accumulated . Few longitudinal studies , however , have explored the association between prolonged , uninterrupted sedentary behavior and mortality to corroborate these findings . To inform guidelines on reducing sedentary behavior ( target reductions in overall sedentary time or target interruption of prolonged sedentary bouts ) , evidence from prospect i ve studies is needed to 1 ) confirm the association between total sedentary time and mortality using objective measures , 2 ) determine whether prolonged sedentary bouts confer risk for death , and 3 ) eluci date whether the total volume of sedentary time and its pattern of accumulation individually or jointly contribute to risk for death . The purpose of this study , therefore , was to examine the association between objective ly measured sedentary time ( both total volume and accrual in prolonged bouts ) and all-cause mortality in a national cohort of U.S. middle-aged and older adults enrolled in the REGARDS ( Reasons for Geographic and Racial Differences in Stroke ) study . Methods Study Population REGARDS is a population -based study design ed to examine racial and regional disparities in stroke . It comprises 30239 white and black adults aged 45 years or older enrolled between 2003 and 2007 from across the contiguous United States ( 19 , 20 ) . Detailed design and methods for REGARDS are described elsewhere ( 21 ) . Briefly , demographic and cardiovascular risk factor data were collected by telephone interview and an in-home physical assessment on enrollment . A detailed summary of baseline measures is provided in the Supplement . Participants ( or their proxies ) were then followed for 6-month intervals to ascertain vital status . Objective measurements of sedentary behavior were collected from active REGARDS participants from 2009 to 2013 ( mean time from study enrollment , 5.7 years [ SD , 1.5 ] ; range , 1.9 to 9.5 years ) ( 22 ) . A total of 7985 participants adhered to accelerometer wear requirements ( 4 days with accelerometer wear 10 hours ) , provided follow-up data , and were available for the current analyses ( Supplement Figure 1 ) . Supplement Table 1 shows the characteristics of included versus excluded REGARDS participants . The REGARDS study protocol was approved by the institutional review boards of participating institutions . All participants provided informed consent . Supplement . Supplementary Material Accelerometer Data Collection Methods for accelerometer data collection are described elsewhere ( 22 ) . Briefly , participants were fitted with an Actical ( Philips Respironics ) accelerometer secured to their right hip using a nylon belt and were instructed to wear the device during waking hours for 7 consecutive days . The Actical had been vali date d formeasurement of physical activity and sedentary behavior and was shown to have acceptable reliability ( 2325 ) . Activity counts were summed over 1-minute epochs . Nonwear periods were defined as at least 150 consecutive minutes of 0 activity counts . This nonwear algorithm was previously vali date d against daily log sheets in REGARDS participants ( 26 ) . Measurements of 0 to 49 , 50 to 1064 , and at least 1065 counts per minute were defined as sedentary behavior , light-intensity physical activity , and MVPA , respectively , as determined in a laboratory-based calibration study ( 27 ) . A sedentary bout was defined as consecutive minutes in which the accelerometer registered fewer than 50 counts per minute . A sedentary break was defined as at least 1 minute in which 50 or more counts per minute were registered after a sedentary bout . Both sedentary bouts and breaks were exclusively continuous periods , with no interruptions or nonwear intervals allowed in the definition . Outcome Ascertainment All-cause mortality was the primary outcome , defined as any death after completion of the accelerometer protocol regardless of cause . Date s of death were confirmed through review of death certificates , medical records , and administrative data bases . Deaths through 4 September 2015 were included in the current analysis . Statistical Analysis Sedentary and physical activity variables were averaged across compliant days ( 10 hours of wear ) . Because of a high correlation between total sedentary time and wear time ( Supplement Figure 2 ) , we corrected for the influence of wear time by st and ardizing total sedentary time to 16 hours of wear time per day using the residuals obtained when regressing total sedentary time on wear time ( see Methods section of the Supplement ) ( 2830 ) . Participants were stratified into quartiles according to total sedentary time and , separately , mean sedentary bout duration ( a measure of overall prolonged , uninterrupted sedentary behavior ) . Cox proportional hazards regression modeling was used to calculate the hazard ratio ( HR ) for all-cause mortality associated with quartiles of total sedentary time ( and separately , mean sedentary bout length ) . Crude HRs were initially calculated . Subsequent HRs were calculated after adjustment for age , race , sex , region of residence , education , and season the accelerometer was worn ( model 1 ) , with further adjustment for current smoking , alcohol use , body mass index ( BMI ) , diabetes , hypertension , dyslipidemia , estimated glomerular filtration rate less than 60 mL/min/1.73 m2 , atrial fibrillation , history of coronary heart disease , and history of stroke ( model 2 ) . Models were additionally adjusted for MVPA expressed continuously ( model 3 ) . Tests for linear trend across quartiles were conducted by including the quartile for each participant as an ordinal variable in regression models . Proportional hazards assumptions were confirmed with a Kolmogorov-type supremum test ( 31 ) . The above analyses were then repeated in a fully adjusted model , testing interactions for age ( < 65 and 65 years ) , sex ( male and female ) , race ( black and white ) , BMI category ( normal weight and overweight or obese ) , and MVPA category ( < 150 min/wk and 150 min/wk ) . As a secondary analysis , we examined the continuous doseresponse relationship between each sedentary characteristic and all-cause mortality in a fully adjusted model ( model 3 ) using restricted cubic splines ( 32 ) . Cubic polynomials were fitted with the mean of each sedentary characteristic set as the reference and knots placed at the 5th , 35th , 65th , and 95th percentiles ( 33 ) . Nonlinear associations were evaluated using the likelihood ratio test . For nonlinear associations , spline models were used to describe the associations and when the association was determined to be linear , a linear model was used . Because of multicollinearity between total sedentary time and mean sedentary bout duration ( r= 0.61 ) , both variables were not included in the same model . Alternatively , to examine the individual and joint associations of total sedentary time and prolonged , uninterrupted sedentary behavior with mortality , participants were classified into 4 categories : low total sedentary time ( < 750 min/d ) and low prolonged sedentary bout time ( < 10 min/bout ) , low total sedentary time  and high prolonged sedentary bout time  ( 10 min/bout ) , high total sedentary time  ( 750 min/d ) and low prolonged sedentary bout time , and high total sedentary time and high prolonged sedentary bout time . Hazard ratios for all-cause mortality were calculated for each joint category in comparison with the lowlow group in a fully adjusted model ( model 3 ) . Thresholds for total sedentary time ( 750 min/d ) and mean sedentary bout duration ( 10 min/bout ) were selected on the basis of the restricted cubic splines and were confirmed using a method described by Contal and O'Quigley ( see Methods section of the Supplement ) ( 34 ) . To allow for the possibility that sedentary bouts Abstract Recent attention has highlighted the importance of reducing sedentary time for maintaining health and quality of life . However , it is unclear how changing sedentary behavior may influence 
    Output:
    