The college experience is often the first time when young adults live independently and make their own lifestyle choices. These choices affect dietary behaviors, exercise habits, techniques to deal with stress, and decisions on sleep time, all of which direct the trajectory of future health. There is a need for effective strategies that will encourage healthy lifestyle choices in young adults attending college.This preliminary randomized controlled trial tested the effect of coaching and text messages  on self-selected health behaviors in the domains of diet, exercise, stress, and sleep. A second analysis measured the ripple effect of the intervention on health behaviors not specifically selected as a goal by participants.Full-time students aged 18-30 years were recruited by word of mouth and campuswide advertisements  at a small university in western Pennsylvania from January to May 2015. Exclusions included pregnancy, eating disorders, chronic medical diagnoses, and prescription medications other than birth control. Of 60 participants, 30 were randomized to receive a single face-to-face meeting with a health coach to review results of behavioral questionnaires and to set a health behavior goal for the 8-week study period. The face-to-face meeting was followed by SMS text messages designed to encourage achievement of the behavioral goal. A total of 30 control subjects underwent the same health and behavioral assessments at intake and program end but did not receive coaching or SMS text messages.The texting app showed that 87.31% (2187/2505) of messages were viewed by intervention participants. Furthermore, 28 of the 30 intervention participants and all 30 control participants provided outcome data. Among intervention participants, 22 of 30 (73%) showed improvement in health behavior goal attainment, with the whole group (n=30) showing a mean improvement of 88% (95% CI 39-136). Mean improvement in any behavioral domains was not seen in the control group. Intervention participants also increased their exercise significantly compared with controls, regardless of their self-selected goal category. The increased exercise was paralleled by significantly lower fasting glucose levels.The health coaching session plus tailored SMS text messages improved self-selected health behaviors with a modest ripple effect to include unselected health behaviors.Clinicaltrials.gov NCT02476604; https://clinicaltrials.gov/ct2/show/NCT02476604 (Archived by WebCite at http://www.webcitation.org/6qAAryS5t) During the transition to campus life, college students face challenges related to eating behaviors, physical activity, stress, and sleep -4. NumerMobile technology is commonplace today, particularly on college campuses . As defiThis preliminary randomized controlled trial aimed to evaluate the effect of a single coaching session bolstered by tailored text messages on self-selected health goals (described in further detail in the Methods section) in a sample of college students. We hypothesized that the coaching plus text message–based intervention would result in students successfully attaining their specified goals in the intervention group, which was randomly selected from interested participants. In this study, we also performed a comparison with a control group to determine whether or not the goal-oriented improvements would be associated with improvements in other lifestyle behaviors to benefit the students’ health in areas beyond their self-selected area of focus. The study also incorporated objective tests (serum glucose and cholesterol) that may be responsive to improved lifestyle behaviors.This study was conducted at a small university in western Pennsylvania from January 2015 to May 2015 in collaboration with the Integrative Cardiac Health Project, Walter Reed Military Medical Center in Bethesda, Maryland. The university Institutional Review Board and the Human Research Protection Office of the US Army Medical Research and Materiel Command approved the study protocol for human subject research. The study protocol was registered on ClinicalTrials.gov with trial number 375278-3 . Written informed consent was obtained from eligible participants before enrolment. The full trial protocol may be obtained by written request to the corresponding author.Participants were recruited using various strategies such as classroom announcements, posted advertisements, flyers, and booths located in student common areas on the university campus. Students were eligible to participate if they were full-time students at the university and did not have any exclusion criteria. The exclusion criteria included (1) age less than 18 years and greater than 30 years; (2) pregnancy, suspected pregnancy, or plans to become pregnant; (3) diagnosis of a chronic medical condition; (4) history of an eating disorder; and (5) taking any prescribed medication other than an oral contraceptive.A comprehensive health evaluation was performed by certified health coaches at enrolment in the study. Health coach certification was conferred by the American Council on Exercise, an accredited body that teaches skills for active listening and providing motivational feedback. The coaching skill set is applicable for a variety of health topics including diet, exercise, stress management, and sleep habits. The comprehensive evaluation upon enrolment in the study included a focused physical assessment and collection of information such as past medical history, current medications, and a review of systems using typical demographic forms. At baseline and following the 8-week intervention period, participants completed validated behavioral surveys (described in detail below) assessing dietary habits, exercise activity, levels of perceived stress, and sleep practices. Blood testing for fasting glucose and cholesterol was also performed before and after the intervention (details below).r=.4-.5 (P<.001), on a range of specific dietary variables [(1) Rate Your Plate  (RYP) diariables .(2) International Physical Activity Questionnaire  (IPAQ): (3) Perceived Stress Scale  (PSS 14)P<.001) [(4) Pittsburgh Sleep Quality Index  (PSQI): P<.001) .(5) Epworth Sleepiness Scale  (ESS): T(6) Visual Analog Fatigue Scale  (FS): ThA certified phlebotomist collected two blood samples from each participant, one sample upon enrolment in the study and the second sample at the end of the 8-week study period. Participants in both the intervention arm and the control arm received a US $50.00 payment for each of the two blood samples taken. Participants were asked to fast for 12 hours before blood collection. All blood collections occurred between 7:00 AM and 9:00 AM. Serum samples were collected in vacutainers and separated by centrifuging at 4150 rpm for 5 minutes using a Sorvall Legend Mach 1.6 centrifuge (Thermo Fisher Scientific Inc). Samples were stored at 22°C and analyzed for total cholesterol and glucose at a regional commercial laboratory.The participants were randomly assigned in a one-to-one ratio by a computer program to one of two groups for the duration of the study. As part of the informed consent procedure, participants were made aware that the study involved a flip-of-the-coin chance that they may experience different components of the study compared with another participant. After randomization, participants were further informed regarding the particulars of their expected experience. One group received the intervention of behavioral goal setting with a health coach (certified by the American Council on Exercise) followed by text messaging throughout the 8-week study period (described in detail below). The other group served as controls, receiving their baseline survey results and blood test results in writing but not setting behavioral goals with the health coach and not receiving text messages during the study period.Following baseline data collection, results were aggregated so that study participants could compare their results to normative standards. This allowed participants to visualize potential areas of their health behaviors that would benefit from improvement. Participants were sent their health assessment to review in preparation for a meeting in person with the health coach. During the face-to-face meeting with the health coach, participants in the intervention group were asked to set one behavioral goal in a domain of diet, exercise, stress management, or sleep. The behavioral goal represented an actionable behavior that the participant could work to improve. . The dialogue captured during these focus groups suggested that college students preferred a mix of action-oriented, informational, and motivational messages that were succinct and sent no more than three times per week . The invThe RYP dietary assessment tool served as an outcome measure to determine the sample size estimation because the investigators had a past experience with the RYP tool and could estimate an effect size of the intervention on this parameter. It was assumed that similar responsiveness in the other outcome measures would be seen and that by using a general “improvement score” for each behavioral dimension, participants could be offered the freedom to choose any of the four behaviors for concentration of their improvement efforts. Dietary changes in RYP were expected to average 10 (SD 2) points for the intervention group compared with zero change (same standard deviation) for the control group. With a power of 90% for rejecting the null hypothesis and using a one-sided test with alpha = 2.5% , the sample size was found to be 25 participants in each arm of the study. Accounting for a 30% dropout rate, a total of 70 participants would be recruited, 35 participants for each arm.t tests or chi-square tests as appropriate, with a P value <.05 indicating statistical significance.Statistical analysis was performed using SPSS for Macintosh version 22.0.0.0 . Descriptive statistics were calculated for variables including means, standard deviations, medians, and minimum and maximum values. Skewness and kurtosis values of the dependent variables were analyzed for significant deviation from a normal distribution. Further comparisons between participants randomized to the intervention group and those serving as controls were made using two-sample Because participants set unique behavioral goals, we used a standardized indicator that operationalized “success” as the percentage of each participant’s goal that was attained at the conclusion of the study. For example, at intake one participant completed 7758 steps per day. She set a goal of 10,000 steps per day, and by the completion of the study, she had completed 9008 steps per day. Thus, she attained 56%  of her goal. The intervention would be considered successful if the mean percentage of goal attainment was statistically significantly greater than 0.A total of 84 potential participants were screened for eligibility to participate in the study. Following baseline data collection, 3 participants were released due to prescription medication usage and 1 because baseline blood pressure results showed hypertension deserving medical attention. Other attrition factors included withdrawing from the university, change in student status, electing not to participate in the study due to time constraints, or other personal reasons . Of 60 eDemographic information on the 60 participants is presented in The computer server was queried to compile information on messaging. During the course of the study, 1160 messages were sent to intervention participants and 982 messages (85%) were viewed.27=.95, P=.19; skewness=0.28, SE=0.45; and kurtosis=1.18, SE=0.87). Of the 30 participants who received the intervention, 22 (73%) showed improvements in their self-declared behavioral goal, 6 of 30 (20%) did not make gains toward their behavioral goal, and 2 (7%) did not provide data that could be evaluated. For analysis, the 2 participants who failed to complete end-of-study assessments were assigned zero values for behavioral goal attainment and were therefore considered failures of the intervention. For the entire intervention group (n=30), the success rate of 88% was calculated by averaging the percentages of each participant’s goal  that was attained at the conclusion of the study. For the 6 participants who did not make gains toward their goals, 1 reported no change and 5 reported negative movement, that is, movement away from their goals, averaging negative 66%. A one-sample t test on participants’ percent of goal attainment scores was used to determine whether or not their mean was significantly greater than 0 . The one-sample t test indicated that the percent of goal attainment of 88% (for n=30) was significantly greater than 0 . Our hypothesis that the coaching plus text intervention would help participants’ goal attainment was supported by the data.Values for goal attainment were acceptable for a normal distribution . The breakdown in the percentages of goal attainment across the 4 categories was diet (131%), exercise (75%), stress management (69%), and sleep (98%).Additionally, data were examined to determine whether or not the participants’ success depended upon the category of their self-selected behavioral goal. Of the 30 participants in the intervention group, 10 selected dietary goals, 8 selected exercise goals, whereas there were 6 participants each who selected goals in stress management and in sleep. Based upon the category of behavioral goal, there were no differences in means for percentage of goal attainment .Since the control participants did not establish behavioral goals, it was not possible to measure control group progress toward a composite behavioral goal at the outcome of the study as was done for the intervention participants. However, the validated behavioral surveys were completed by control participants at baseline and at the outcome date of the study. As was anticipated, control participants did not show statistically significant changes in any of the behavioral domains , while cholesterol levels were not different .The main research hypothesis of this study was that a single counseling session followed by a text message–based intervention would result in the attainment of a self-selected health behavior goal. A secondary analysis was performed to determine whether or not the intervention directed at a particular behavior might also have a broader effect by encouraging other healthful behavior changes outside of the behavior goal of choice.Similar to many previous studies -28, thisThe importance of the improved exercise habits is underscored by the clinically relevant improvement in fasting glucose levels in the intervention group compared with the control group. These objective data were validating for the subjective self-reported exercise levels. Although the absolute decrease in serum glucose values appears to be modest (on average 4.6 mg/dL for the intervention participants), there is epidemiological evidence supporting the clinical relevance of this amount of glucose lowering when sustained over time. A recent prospective study in healthy individuals who did not have diabetes or cardiovascular disease showed that each 3 mg/dL increase in fasting glucose, even in the clinically accepted normal range, predicted a 1% increased risk of developing coronary disease over a mean of 4.3 years . This fiResearchers conducting numerous systematic reviews and meta-analyses analyzing text message–based studies have concluded that despite findings that text message interventions do work to encourage adherence to therapy, there are methodological issues with research in this area ,25,37,38Another methodological design issue that the current protocol was designed to address was the use of objective data collection to evaluate outcome measures in tandem with subjective self-report progress toward their goal. To this end, fasting glucose values in the intervention group were significantly lower compared with the control group, in parallel with the increased exercise levels attained.There are limitations to this study. One limitation in the study design is that the intervention comprised two components: (1) a single counseling session with goal setting and (2) an 8-week period of SMS text message support. It is therefore not possible to determine which of these components singly or together was responsible for the positive effects of the intervention. Limiting the intervention to one of these components would have enabled the investigators to report the effect of counseling or of text messaging. Future research on text messaging would benefit from unbundling such an intervention, perhaps by providing the counseling session to both the intervention and the control arms of the study. By setting the intervention to a single component such as text message support, it would be feasible to investigate the different effects of generic text messages versus texts with tailored, personalized feedback. Such an investigation is worthy of attention because generic texts can be automated for distribution, a much less time-consuming process than providing texts with personalized content.The study did have statistical power to demonstrate a significant change in overall healthy behaviors in response to the intervention. However, the study may have been underpowered to find significant changes for the different individually selected behaviors with sample sizes of 6-10 participants. The small sample sizes likely explain why none of the analyses for separate behaviors were significant.a priori an overall 8-week outcome to the intervention. However, future studies may find this information helpful to interpret how well the individualized or customized the text messages worked. It may also be useful to interpret the overall burden of the intervention as experienced by the participants.Another limitation of this report is the lack of analysis of the reports received by the health coaches for weekly behavioral compliance of the participants. This lack of analysis stemmed from the decision to specify The study intervention lasted only 8 weeks, a trial period that was insufficient to capture significant improvements in some measures such as cholesterol changes. With this short study duration, it was also not possible to determine whether or not behavioral gains would be maintained over longer periods.By design and in order to avoid confounding variables, the study excluded participation by students who had chronic illnesses or who took prescription medications other than for birth control. Furthermore, the enrolled population was predominantly white women. These factors do limit the ability to generalize the findings of this study to the student population at large.The findings from this SHUPEP study do support the current body of literature evaluating the utility and effectiveness of tailored mobile-based health communications as a successful strategy for improving health behaviors -39. A ne


A meta-analysis concluded that there was no effect of the femoral head ossification and the incidence of osteonecrosis in the treatment of developmental dysplasia of the hip (DDH), unless only osteonecrosis grades II-IV were considered. The meta-analysis, limited due to the small number of studies available at that time, identified a need for an update as further research emerges. We observed a trend in recent years towards delaying treatment of DDH in the absence of an ossified nucleus. Numerous new publications on this topic encouraged us to update the 2009 meta-analysis.We performed a systematic review of the literature from 1967 to 2016 and included studies that reported on the treatment of DDH, the ossific nucleus and osteonecrosis. Two independent reviewers evaluated all articles. We performed a meta-analysis with the main outcome defined as the development of osteonecrosis of the femoral head at least two years after closed or open reduction.Of four prospective and ten retrospective studies included in the systematic review, 11 studies  met the inclusion criteria for the meta-analysis. There was no significant effect of the ossific nucleus on the development of all grades of osteonecrosis  or osteonecrosis grades II–IV . In closed reductions, the ossific nucleus halved the risk for developing osteonecrosis grades II–IV .Based on current evidence there does not appear to be a protective effect of the ossific nucleus on the development of osteonecrosis. In contrast to the previous meta-analysis, this update demonstrates that this remains the case irrespective of the grade of osteonecrosis considered relevant. This updated meta-analysis is based on twice as many studies with a higher quality of evidence.The online version of this article (doi:10.1186/s12891-017-1468-6) contains supplementary material, which is available to authorized users. Some surgeons believe that in the treatment of developmental dysplasia of the hip (DDH), osteonecrosis may be avoided by intentionally delaying a closed or open reduction until the appearance of the ossific nucleus –3. ResulA previous meta-analysis of six observational studies  concludeThis study aimed (i) to determine the effect of the presence of the ossific nucleus on the development of osteonecrosis and (ii) to assess whether the type of reduction performed or the grade of osteonecrosis considered relevant would affect the conclusion.ossific, nucleus, hip and dislocation. We also searched the DARE database and Cochrane Library.We updated a previous (1960–2007) systematic review with an electronic search of the literature for the period of May 2007 to November 2016. We identified articles reporting on any association between the ossific nucleus and osteonecrosis. In line with the PRISMA  statement , we inclTwo reviewers  independently screened titles and abstracts of eligible citations and determined if they met the inclusion criteria. Selected articles were evaluated independently and disagreements resolved in consensus. In this process both reviewers demonstrated substantial  agreemenThis systematic review included studies of any design reporting on (i) the presence or absence of the ossific nucleus of the proximal femoral epiphysis on pre-reduction radiographs or ultrasound and (ii) osteonecrosis as an outcome of the treatment of DDH in children up to 18 years. We included studies which defined osteonecrosis by radiographic criteria  independently extracted all data relevant for systematic review and meta-analysis with use of a data collection form , ensurinstudy design, study quality, consistency and directness. We used clinical homogeneity as a criterion for pooling data between studies. We defined clinically homogeneous studies as those with comparable populations, interventions and outcomes measured at a similar time point. We also tested for statistical homogeneity as described below.We assessed the quality of evidence using the four domains of the GRADE  statement : study d2 statistic to determine the percentage of total variation across studies due to heterogeneity [2 < 50%) and random-effect models if there was statistical heterogeneity. However, we also performed additional fixed and random effects models on all groups analysed for data comparison. We performed subgroup analyses based on grade of osteonecrosis and based on closed and open reductions. Funnel plots used to test publication bias were generated using the RevMan 5.3 software.We quantified agreement between reviewers with the simple kappa statistic  and repoogeneity . RevMan The electronic search revealed 97 studies Fig. , of whicThe prevalence of osteonecrosis ranged from 6 to 48% across the 14 studies. Nine studies (64%) , 19 showWe identified one prospective cohort study , eleven We found consistency among all studies in that neuromuscular hip disease, teratological dislocation and cases with missing imaging were not included. Other exclusion criteria were failed surgical treatment prior to admission , 14, 16 The number of participants in single studies varied from 23 to 148, the average number being 67. There were 166 cases of bilateral DDH . The mean age at hip reduction was 8.6 months . Four studies (29%) included patients treated by closed reduction only, with a mean age at reduction of 8.9 months  . Four stSix studies 43%) , 14, 16 3% , 14, All studies identified age at reduction as a potential confounder; however only ten studies (72%) –8, 12–14p = 0.007). Pospischill et al. [p < 0.05).Carney et al.  found anl et al.  found anThe use of harness treatment, preoperative traction and adductor tenotomy was not universal across all studies. In ten studies 72%) , 16, 20 2% , 16, Five studies 36%) [6% 3, 7,,7, 8, 13A meta-analysis of 11 studies 1,021 hips) [1 hips 2, 19, 20 An analysis of osteonecrosis grades II–IV included six studies 471 hips) [ hips 1,, 12. 33/In 253 hips treated by closed reduction only, the ossific nucleus reduced the risk for osteonecrosis of grades II-IV by 50%. 14/153 (9%) hips with an ossific nucleus developed osteonecrosis compared with 20/100 (20%) in the group without an ossific nucleus  Fig. .Fig. 4FoThe generated Begg’s funnel plots showed points that were evenly distributed and symmetrical Fig. . This shStudies about the role of the femoral head ossific nucleus in preventing osteonecrosis following treatment of DDH reported conflicting results, but a 2009 meta-analysis concluded that there was no such effect unless only osteonecrosis grades II-IV were considered , 3, 21. With 11 studies or 1021 infants, this updated meta-analysis included twice as many studies and three times as many infants as the one published previously . The priThe 2009 study showed a 60% reduction in the relative risk for developing osteonecrosis grade II or worse if the nucleus was ossified at the time of hip reduction  , which wThe 2009 meta-analysis [By contrast, infants treated with closed reductions (253 hips from four studies) , 2, 7, 9We noticed inconsistencies in the reported prevalence of osteonecrosis, which ranged from 6 to 48%. Those studies that reported a prevalence of 6 to 7% , 20 inclp = 0.0066). In the study of Pospischill et al. [p = 0.003) when a concomitant osteotomy was done. Only two studies (14%) performed multivariate analyses [All included studies identified the age at reduction as a potential confounder in the relationship between osteonecrosis and an ossific nucleus; however, only ten studies (72%) –8, 12–14l et al.  osteonecanalyses .Our study has limitations. In four studies 29%) the presence of the ossific nucleus was determined solely or in select cases by ultrasound. Because previous research has demonstrated that in 93% of cases an ossific nucleus that is visible on ultrasound is also visible on radiographs  we inclu% the preBased on current evidence there does not appear to be a protective effect of the ossific nucleus on the development of osteonecrosis. In contrast to the previous meta-analysis, this update demonstrates that this remains the case irrespective of the grade of osteonecrosis considered relevant. This updated meta-analysis is based on twice as many studies with a higher quality of evidence and therefore provides more robust conclusions. There does appear to be a protective effect against the development of grade II-IV osteonecrosis when closed reductions are performed. Caution must be exercised as the number of studies on which this conclusion is based is small and the clinical implication is unclear since the likelihood of successful closed reduction reduces with time. We therefore conclude that the practice of delaying open reduction until the appearance of the femoral ossific nucleus is not currently supported by the literature. However this meta-analysis is based on exclusively retrospective studies and the quality of evidence remains moderate. It is the opinion of these authors that the question of whether delaying the treatment of a dislocated hip in the absence of the ossific nucleus can mitigate the risk for osteonecrosis would be best answered by a randomized clinical trial.


Results of an observational, descriptive study quantifying topography characteristics of twenty first generation electronic nicotine delivery system users in their natural environment for a one week observation period are presented. The study quantifies inter-participant variation in puffing topography between users and the intra-participant variation for each user observed during one week of use in their natural environment. Puff topography characteristics presented for each user include mean puff duration, flow rate and volume for each participant, along with descriptive statistics of each quantity. Exposure characteristics including the number of vaping sessions, total number of puffs and cumulative volume of aerosol generated from ENDS use (e-liquid aerosol) are reported for each participant for a one week exposure period and an effective daily average exposure. Significant inter-participant and intra-participant variation in puff topography was observed. The observed range of natural use environment characteristics is used to propose a set of topography protocols for use as command inputs to drive machine-puffed electronic nicotine delivery systems in a controlled laboratory environment. ENDS are reported as the most commonly used tobacco product among youth in the U.S. , suggestet al. ..29].95% Confidence Interval on the mean and variance and creates interval plots, box plots and frequency distributions. Optional statistical tests may be computed with the TAP, comparing mean puff duration, puff flow rate, and puff volume of any participant with those of any other participant in the study cohort. The TAP includes a parameter enabling the analyst to set a “maximum duration” cut-off on any individual puff so that descriptive statistics can be presented on a subset of topographies determined by the analysist to be indicative of reasonable participant use behavior. The analysis code reports details of all data and files processed and excluded including puffs that are eliminated under the “maximum duration” cut-off conditions. Neither the wPUM nor the TAP impose an inherent limit on the maximum duration of puffs. The ability to articulate a maximum puff duration in the analysis permits the analyst to conduct sensitivity analyses of topography parameters in relation to the maximum duration permitted. Results presented herein are subject to a 20 [s] maximum puff duration. A preliminary sensitivity analysis confirmed that reducing the maximum puff duration below 20 [s] could have an observable influence on the resulting mean puff duration and volume. Conversely, puffs above 20 [s] were clearly outliers and had minimal impact.The TAP plots out the raw signal measured for every session (puff flow rate versus time) overlaid with the derived puffing topography based on the TAP analysis . For eacENDS products, 4 did not respond to the pre-enrollment email and 1 did not meet the inclusion criteria. Twenty five participants were schedule for appointments to be enrolled in the study; 4 individuals did not appear for their enrollment appointment and 1 individual cancelled his enrollment appointment because he decided to wait for the next study.A total of 47 respondents requested information about study participation. The progress of these 47 individuals through the screening process and into the study is shown in Of the 20 participants completing final enrollment, 19 were male and 1 was female, and they ranged in age from 18 to 22 years. Two participants had never smoked traditional cigarettes before, and 10 participants had smoked traditional cigarettes for at least one year. Of the 18 participants who had smoked traditional cigarettes before, 9 were former smokers, 1 was current smoker on a daily basis, and the remaining 8 reported less-than-daily use of combustible cigarettes. Each participant indicated the brand of disposable or rechargeable ENDS they would be using for the duration of the week long natural use environment observation period and prior ENDS brand(s) used. Information collected from each participant during the enrollment interview is presented in 7 day observation period were downloaded from the wPUM for preliminary analysis. During the preliminary analysis process data files were screened to insure data integrity. Only those files deemed to include quality puffing data were read by the TAP and included in the topography statistics. The wPUMs were collected from each participant at the conclusion of the week-long observation period. Data files for the When Participant 7 returned the wPUM to the lab, the technician observed that a hose connected to one end of the orifice plate inside the wPUM had become disconnected. This was evident in 16 files from the later portion of the week, so those files were excluded from the analysis for Participant 7. Participant 12 presented 18 files exhibiting significant drift in the baseline voltage recorded with the wPUM during the first half of the week. During a mid-week consultation with Participant 12, a calibration was conducted on the wPUM, and a droplet of e-liquid was observed to be entrained in the wPUM tubing. The wPUM was cleaned, calibrated, and returned to the user. Participant 12 files for the remainder of the week were observed to contain expected characteristics typical of puffing. Participant 6 presented 14 files having apparently inverted puff profiles, dissimilar to topography data previously observed with the wPUM in a controlled laboratory setting, so those files were excluded from the analysis for Participant 6, pending further investigation. Participant 2 presented 20 files observed to have a combination of the baseline drift evident in the files of Participant 12 and inverted profiles evident in the files of Participant 6. Participant 14 presented 13 files having a similar combination of baseline drift and inverted profiles. Participants 5, 8, 11, 13, 16 and 18 presented a small number of files exhibiting baseline drift and occasional inverted profiles, resulting in 2% to 10% of those participant’s files being excluded from the statistical analysis presented herein. After the observation period concluded, an investigation was conducted to reproduce the source of voltage bias and inverted profiles. Preliminary results of that investigation, supported by the ability to reproduce such characteristics in a controlled setting, suggest that the voltage bias and inverted puff profile may be the result of ENDS liquid entrained in or condensed within the wPUM. Work is currently under way to compensate for condensate in an effort to recover partially useful information from the excluded files.The TAP program was run on the 922 files that passed the initial data integrity check. The TAP identified 134 of the 922 files as containing zero puffs. Close inspection of these 134 data files indicated that the wPUM was turned on but no actual vaping session took place. These “zero-puff” files were not counted in the participants’ vaping session totals. Note that as a result, the total vaping sessions per participant is less than the total number of files analyzed by the TAP. Also note, preliminary analysis revealed that in some cases a participant turned on the wPUM, took some puffs during a short time interval, left the device on for an extended period of time, and then took a few more puffs during a short time interval before turning the wPUM off. Such an event is reported as a single vaping session in this study. In summary, data included in the topography characteristics and cumulative exposure assessment were analyzed and deemed to be measures of actual vaping activity and analyzed accordingly.One exemplar puffing session is presented here for each of the 20 participant in Figs 20 Participants over the course of the 7 day observation period. 98.5% of puffs were observed to have durations less than 20 seconds, puffs with durations longer than 20 seconds were considered outliers and omitted from this analysis. The total number of puffs omitted was 153 (1.6%) of the 9694 puffs initially identified. Puff duration frequency distributions are shown in Participant-specific frequency distributions of puff duration, flow rate and volume were used to evaluate intra-participant variability exhibited by each of the 0.8 to 4.1 seconds for puff duration, 6 to 23 ml/s for puff flow rate and 24 to 164 ml for puff volume.The extent of intra-participant variability appears to be participant dependent, with some participants exhibiting a relatively wide spread in topography characteristics while other have relatively low variation. The degree of intra-participant variability for each topography characteristic is quantified by participant-specific standard deviations provided in 7 day observation period. All puffs over 20 sec in duration were omitted for reasons mentioned previously. The observed standard error of the means (SE Mean) suggests the data observed for each participant over the 7 day period was sufficient to characterize the mean values.Inter-participant variability was evaluated by comparing the participant-specific mean topography characteristics across the 20 participant cohort. Participant-specific mean topography characteristics are listed in 0.5 sec to 2.5 sec, with a cohort mean of 2.0 (SE Mean 0.1). Median puff flow rates ranged from 17 mL/sec to 52 mL/sec. with a cohort mean of 30.4 (SE Mean 2.0). Median puff volumes ranged from 24 mL to 120 ml, with a cohort mean of 65.4 (SE Mean 5.5).Boxplots are presented in 95% CI in the mean to illustrate the inter-participant variability in mean topography characteristics. Mean puff durations ranged from 1.0 sec to 3.0 sec, mean puff flow rates ranged from 24 mL to 114 mL mean puff volumes ranged from 19 mL/sec to 60 mL/sec. A pair-wise 2-sided t-test comparison of topography characteristics between participants, as reflected by the interval plots, indicate significant variations in means across the cohort for puff duration, flow rate and volume. This complete set of t-test comparisons was conducted to explore potential unknown, or not predicted, patterns in participant vaping behavior. The left panel of 1.8 sec, a “moderate” mean puff duration of approximately 2 sec, and a “long” mean puff duration of approximately 2.5 sec. The mean puff flow rate, illustrated in the middle panel of Interval plots are presented in 7-day study. An effective number of monitoring days was determined by reducing the observational period from 7 days in proportion to the number of files included as input to the TAP . The effective total number of puffs ranged from 14 puffs/day to 275 puffs/day, with a cohort-mean of 78 ± 18 puffs/day (mean ± SE Mean). The effective volume of e-liquid aerosol inhaled per day ranged from 0.6 liters to over 18 liters, with a cohort-mean of 4.6 ± 1.1 liters (mean ± SE Mean).The effective number of vaping sessions per day ranged from less than 7 days of monitoring, the effective per-day participant averages may be extrapolated to estimate a weekly exposure. For those participants with 7 days of effective monitoring, the data provided in As a first approximation, for those participants with The total number of vaping sessions presented in the third column of Results from this study provide the first glimpse into how user behaviors vary over the course of a week in their natural environment. Significant intra-participant variability was observed for all three topography characteristics. Large standard deviations in participant-specific topography characteristics imply that there may be some affects related to time-of-day and day-of-the-week worth further investigation. Further evidence of such affects is seen by participant-specific frequency distributions exhibiting bi-modal distributions of topography data. Such detailed topography data, with standard deviations describing intra- and inter- participant variability inform human participant study design protocols for product safety testing, switching studies or initiation patterns of naïve users.There may be a tendency to define topography protocols in terms of the “cohort-mean” values of puff duration, flow rate or puff volume. The possibility that ENDS aerosol production might be dependent upon both puffing topography itself  as well as the significant heterogeneity observed between individual participants suggests that it would be advantageous to utilize puffing protocols that encompass the range of user behaviors found in the natural environment. To that end, data from the current study lends itself to proposing such a protocol.0.6 (s) to a high of 3.4 (s) while the observed mean puff flow rates range from a low of 19 (mL/s) to a high of 60 (mL/s), and the observed puff volumes range from a low of 24 (ml) to a high of 114 (mL). Similarly, There is a tendency to estimate total exposure by total number of vaping sessions per day or total number of puffs per day. However, the ambiguous terminology for how users define a vaping session may lead to inaccurate self-reported exposures. Indeed, in the current study, it was observed that for some users a significant amount of time passed between “sets” of puffs, which one user might define as one session, whereas another might define as multiple sessions. The number of sessions computed in this study represents the current best estimate for number of sessions as reflected by number of files with actual puffing data. In reality, it is possible that continued analysis in the future will show that it is quite common for multiple puffing sessions to be present within a single data file, and this will give rise to the need to define what is meant by a session; where one session concludes and another begins. The current body of knowledge and results of the current study support the recommendation that the “number of vaping sessions” based on users’ self-reported data or based on monitoring data, should not be used as a measure of ENDS exposure.Similarly, there is a tendency to estimate total e-liquid aerosol exposure by self-reported number of puffs taken per day. It is unknown whether ENDS users accurately recall the total number of puffs per day, but such a study is worth undertaking. However, even if the total number of puffs per day could be accurately recalled by the user, number of puffs alone does not quantify exposure in any meaningful way. Based on the results of the current study, it is recommended that total exposure be reported as the cumulative volume of aerosol inhaled over a defined period of time. This study demonstrated a methodical procedure for determining cumulative exposure of inhaled e-liquid aerosol based on precise measurement and rigorous analysis of topography characteristics.While this study adds valuable data to the field of ENDS topography, there are several limitations unique to the study which are worth noting. (1) Only ‘cigalike’ devices were tested and therefore the topography presented should not be generalized to second or third generation devices. Indeed, as users move on to more sophisticated devices their topography should be re-assessed. (2) The study demographics were limited to college students between the ages of 18 and 21 and all but one participant was male. Therefore, the topography and exposure results may not represent lifetime smokers using ENDS in an attempt to quit smoking. Further study is needed to determine the impact of demographics on topography and use behavior. (3) Although participants agreed to use the wPUM for every puff taken over the 7-day monitoring period, there was no secondary measure to guarantee compliance with the protocol. In addition, the impact of the wPUM itself on topography and behavior is not known. The investigators acknowledge that this creates some uncertainty in the topography characteristics and the estimated cumulative weekly exposure reported herein. (4) Some study participants reported being dual users of ENDs and conventional tobacco products. Therefore, the estimate of e-liquid consumed over the 7-day period is only part of the nicotine exposure for these users. A future observational study is planned in which dual use of products will be monitored.Several important questions emerged as result of this study which warrant further investigation. (1) The study did not quantify the amount of nicotine consumed by each participant, since such an estimate requires knowledge of the transfer efficiency of each ENDs device utilized in the study  which isResults of this study indicate significant intra- and inter-participant variability with regard to puffing topography characteristics, suggesting that multi-day monitoring periods are advantageous for characterizing ENDS use behavior. Results imply such monitoring is enhanced when carried out in the natural environment and that monitoring in the laboratory environment has inherent limitations. Realistic topography protocols presented in this study are recommended for machine-driven aerosol emissions testing of new products to inform regulatory science. Cumulative volume of inhaled e-liquid aerosol, calculated by direct measurement of puff duration and flow rate are more meaningful measure of exposure than counting puffs or counting sessions. Methods presented in this study permit robust statistical characterization of ENDS topography and exposure to e-liquid aerosol. The results provided in this study should not be generalized to other ENDS designs, brands, or demographic populations. Other ENDS device types and various brands of each ENDS device type should be tested and compared to determine the effect of device design on puffing topography, frequency of use and cumulative exposure.S1 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 1, as shown graphically in Figs (CSV)Click here for additional data file.S2 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 2, as shown graphically in Figs (CSV)Click here for additional data file.S3 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 3, as shown graphically in Figs (CSV)Click here for additional data file.S4 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 4, as shown graphically in Figs (CSV)Click here for additional data file.S5 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 5, as shown graphically in Figs (CSV)Click here for additional data file.S6 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 6, as shown graphically in Figs (CSV)Click here for additional data file.S7 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 7, as shown graphically in Figs (CSV)Click here for additional data file.S8 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 8, as shown graphically in Figs (CSV)Click here for additional data file.S9 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 9, as shown graphically in Figs (CSV)Click here for additional data file.S10 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 10, as shown graphically in Figs (CSV)Click here for additional data file.S11 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 11, as shown graphically in Figs (CSV)Click here for additional data file.S12 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 12, as shown graphically in Figs (CSV)Click here for additional data file.S13 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 13, as shown graphically in Figs (CSV)Click here for additional data file.S14 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 14, as shown graphically in Figs (CSV)Click here for additional data file.S15 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 15, as shown graphically in Figs (CSV)Click here for additional data file.S16 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 16, as shown graphically in Figs (CSV)Click here for additional data file.S17 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 17, as shown graphically in Figs (CSV)Click here for additional data file.S18 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 18, as shown graphically in Figs (CSV)Click here for additional data file.S19 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 19, as shown graphically in Figs (CSV)Click here for additional data file.S20 FileThis data file contains the flow rate and cumulative volume vs. time for Participant 20, as shown graphically in Figs (CSV)Click here for additional data file.


Chlamydomonas flagella. Anterograde trains split apart and IFT complexes mix with each other at the tip to assemble retrograde trains. Dynein-1b is carried to the tip by kinesin-II as inactive cargo on anterograde trains. Unlike dynein-1b, kinesin-II detaches from IFT trains at the tip and diffuses in flagella. As the flagellum grows longer, diffusion delays return of kinesin-II to the basal body, depleting kinesin-II available for anterograde transport. Our results suggest that dissociation of kinesin-II from IFT trains serves as a negative feedback mechanism that facilitates flagellar length control in Chlamydomonas.Intraflagellar transport (IFT) is essential for the elongation and maintenance of eukaryotic cilia and flagella. Due to the traffic jam of multiple trains at the ciliary tip, how IFT trains are remodeled in these turnaround zones cannot be determined by conventional imaging. Using PhotoGate, we visualized the full range of movement of single IFT trains and motors in  Cilia and flagella are hair-like structures that protrude from nearly every human cell and play a number of roles including transmitting signals and enabling cells to move. These structures lengthen when new material is deposited at their tip by a process called intraflagellar transport (IFT). In this process, protein complexes known as IFT trains carry cargo along tracks that run along the length of each flagellum. Different motor proteins power the IFT trains in different directions: kinesin moves IFT trains from the base to the tip, while dynein moves them back in the opposite direction.When IFT trains arrive at the tip of the flagellum, they release their cargo and undergo a major reorganization process in which the trains switch motors in order to move back to the base. Because the many IFT trains at the tip form a kind of ‘traffic jam’, standard imaging techniques have been unable to distinguish exactly what happens during this reorganization.A new imaging method called PhotoGate microscopy can track individual molecules inside crowded cells. Chien, Shih et al. have now used this method to visualize the full range of movements made by IFT trains and motors in the flagella of a species of single-celled algae. This revealed that at the tip of the flagellum, IFT trains split apart and mix with each other to assemble into new trains, which move back to the base. In addition, kinesin carries dynein to the tip as inactive cargo, detaches from IFT trains at the tip and diffuses back to the base of the flagellum. This delays kinesin’s return and causes it to accumulate in the flagellum, which helps to explain why flagella assemble more slowly as they lengthen: as the flagellum grows longer, less kinesin is available at the base to transport material to the tip. Thus kinesin diffusion helps the algae to regulate the length of their flagella.Further research is now needed to study whether similar mechanisms control the length of flagella in other organisms. Defects in the intraflagellar transport process have been linked to a range of human diseases known as ciliopathies, and so the results presented by Chien, Shih et al. could also help us to uncover the causes and potential treatments for these conditions. Cilia  are hair-like organelles that extend from the plasma membrane of nearly all mammalian cells. The core structural component of a cilium is the axoneme, a ring of nine unipolar doublet microtubules surrounding a central pair of singlet microtubules. Cilia play essential roles in cell motility, generate the movement of fluids over multiciliated surfaces, and sense extracellular signals . To asseChlamydomonas, and it remains unclear how kinesin-II returns to the basal body  that readily adhere to the glass surface, enabling us to monitor IFT under total internal reflection (TIR) illumination  than the ratio of retrograde to anterograde train frequencies  at the tip . When on process . We also process . Because process , revealiWhen two or three fluorescent anterograde trains were allowed to pass through the gate, Δt became shorter , suggesting that rapid turnover of IFT trains depends on dynein activity.We also tested whether extracellular calcium and the dynein inhibitor ciliobrevin D  affect td1blic mutant phenotypes , which assembles into the dynein-1b complex and rescues enotypes . In the T trains   within the flagellum after it departs from the tip  of KAP-GFPs simultaneously departed from the tip in a single step . BecauseWe next investigated whether KAP slides linearly along the microtubule track, similar to the non-processive, microtubule-depolymerizing kinesin MCAK . In thisd1blic mutant with both D1bLIC-crCherry and KAP-GFP constructs and simultaneously tracked the movement of KAP and D1bLIC subunits in the rescued cells . Both tagged motors were expressed at near wild-type levels , whereas the KAP intensity was depleted at the basal body  and the retrograde motor dynein-1b (with D1bLIC-Cherry) has further revealed significant differences in how these motors are recycled back and forth within a flagellum. Kinesin-II drives anterograde trains in a highly processive fashion and then dissociates from the IFT trains when they reach at the flagellar tip. KAP-GFP then returns to the flagellar base by diffusing within the flagellum, similar to the diffusion of kinesin-1 in mammalian neurons  and in cThe retrograde motor dynein-1b is transported to the flagellar tip on anterograde trains . BecauseChlamydomonas, the axoneme contains nine doublet microtubules, each composed of a complete A-tubule (with 13 protofilaments) and an incomplete B-tubule (with 10 protofilaments). The B-tubule terminates before the A-tubule less than 1 µm from the flagellar tip . These cilia also employ two different kinesin-II motors for anterograde IFT  after crossing the IFT27-GFP transgene into the pf18 background as previously described . The d1blic::D1bLIC-crCherry KAP-GFP strain was generated as described below. These strains were not authenticated or tested for mycoplasma contamination. Strains were maintained on plates of TAP media containing 1% agar. For light microscopy, vegetative cells were resuspended in liquid TAP media at 22°C for 24–48 hr and passaged to fresh liquid TAP before introduction into a flow chamber.The escribed . The iftP strain  was obta:KAP-GFP  and d1blbLIC-GFP  strains D1bLIC-crCherry construct was generated by subcloning a Chlamydomonas codon-optimized version of the Cherry tag into a genomic copy of the D1bLIC gene (AscI site located in the last exon of D1bLIC. The D1bLIC-crCherry construct was linearized with BamHI and co-transformed into d1blic (CC-4487) with the selectable marker pSI103 and plated on TAP medium plus 10 μg/ml paromomycin. 960 transformants were picked into TAP media and screened for changes in colony morphology. 84 colonies were further examined by both phase contrast and fluorescence microscopy for rescue of flagellar assembly and expression of Cherry. Isolated flagella from four colonies were analyzed by Western blot for the presence of full-length D1bLIC-Cherry. A single colony was selected for a second round of transformation using the KAP-GFP construct . For dynein-1b inhibition assays, a final concentration of 100 µM ciliobrevin D was added to the TAP media, and the data was collected within 5–10 minof the treatment.0.34 mM Ca+ treatment, 50 mM LiCl was added to liquid cell suspensions, and cells were incubated for 2 hr before fixation and imaging.For cycloheximide treatment, cells were deflagellated by pH shock and cycloheximide was added to a final concentration of 1.5 µg/ml immediately afterwards. Cells were allowed to regrow flagella for 2 hr before fixation and imaging. For Lifla3::KAP-GFP cells, we deflagellated cells in TAP media using shear force by rapidly pushing them through a 20G1 ½ syringe. Cells regenerating flagella were imaged in the following hour. For imaging the accumulation of GFP signal at the basal body region and in regenerating flagella, fla3::KAP-GFP and IFT20::IFT20-GFP cells were deflagellated with pH shock by adding 60 µl 0.5 N acetic acid to 1 ml of cells in TAP media, waiting 45 s, and adding 60 µl 0.5 N KOH. Cells were fixed 15, 30, 45, 60, and 75 min after pH shock. Fixation was done by pipetting 200 µl of liquid TAP cell culture onto a poly-lysine treated coverslip for 1 min, then gently treating the coverslip with 4% paraformaldehyde in water for 10 min. Afterwards, the coverslip was treated twice with 100% methanol chilled to −20 °C for 5 min. Coverslips were dipped in water to remove methanol, mounted in a flow chamber with TAP media, and then imaged immediately.For imaging the diffusion gradient in live A custom-built objective-type TIR fluorescence microscope was set up using a Nikon TiE inverted microscope equipped with a perfect focusing unit, bright-field illumination, and a 100-X 1.49 NA PlanApo oil immersion objective . 488 nm and 561 nm solid state lasers  were used for GFP and crCherry excitation, respectively. The angle of incident light was adjusted lower than the critical angle to illuminate a deeper field (~300 nm) near the coverslip surface. The fluorescent signal was recorded by an iXon 512 × 512 electron-multiplied charge-coupled device (EM-CCD) camera . 1.5x extra magnification was used to obtain an effective pixel size of 106 nm. Data were collected at 10 Hz. Excitation laser beams were controlled by shutters . Because the CCD image saturates under intense laser illumination of the focused gate beam, shutter timing was synchronized with the camera acquisition by a data acquisition card  to minimize the number of saturated frames in recorded movies. For two-color imaging, GFP and crCherry fluorescence were separated into two channels on a CCD camera using Optosplit II . To avoid bleed-through between channels, movies were acquired using time-sharing between the 488 nm and 561 nm laser beams, synchronized with camera acquisition at 60 ms frame time. The effective pixel size was 160 nm.−2) to the image plane and steered with a fast piezo-driven mirror . The piezo-driven mirror was mounted at a position conjugate to the back-focal plane of the objective to ensure that the tilting of the mirror resulted in pure translation of the focused beam in the image plane. The mirror provided a usable travel range of 30 µm x 30 µm area at the image plane. The mirror’s angle was updated via analog output channels of a data acquisition card  and controlled by software custom-written in LabVIEW.The PhotoGate system was assembled as previously described . Briefly−1). The trajectories of these trains can be distinguished from each other as they move at different speeds along the flagellum. The locations of flagellar tips were determined by brightfield imaging (data not shown). In two-color photogate experiments, the focused 488 nm laser beam was used to bleach both GFP and crCherry, and 488 and 561 beams were used in a time-sharing mode for TIR excitation.Flagellar orientation of surface adhered cells was visualized by TIR imaging. Initially, the gate beam was placed at the tip of flagellum and moved along the flagellar orientation to prebleach the distal half of the flagellum. The gate beam was turned off when it was positioned near the base of the flagellum to allow a single fluorescent anterograde train to enter the flagellum. Occasionally (<5%), two anterograde trains overlapped and entered the flagellum simultaneously. The gate beam was then turned on for 0.2 s of every 1 s to bleach other anterograde trains. Based on the size of the gate beam in the image plane, gating frequency was adjusted such that less than 1% of anterograde IFT trains moved faster than the cutoff speed (3.0 µm sfla3::KAP-GFP strain were performed by photobleaching the center part of the flagellum (5 µm in length) for 200 ms at 25 kW cm−2 in the epifluorescence mode. The recovery of fluorescence signal in the bleached area was simultaneously monitored by imaging with a 100 W cm−2 TIR excitation. The analysis was performed by measuring the total fluorescence intensity within the bleached area. Fluorescent signal of anterograde transport was manually excluded from the analysis. Thirteen different recovery traces were used in the MSD analysis. The intensity of each trace was normalized according to the initial and final intensity.FRAP assays on the fla3::KAP-GFP and IFT20::IFT20-GFP cells were fixed with paraformaldehyde and imaged on a confocal microscope using 488 nm laser excitation . Images were recorded with 560 nm z step, 63 nm pixel size, and 1.58 µs photon collection per pixel. Fluorescence in basal body and flagellum was quantified using ImageJ. The ratio of flagellar to basal-body KAP-GFP fluorescence in confocal images was similar to that of live cell imaging under TIR excitation, indicating that the fixation protocol did not result in the loss of diffusing KAP-GFP signal from the flagella.α-1e-λt, where α and λ are shape and rate parameters, respectively.Anterograde and retrograde trajectories were manually assigned from kymographs. After the arrival of a single anterograde particle at the tip, the departure of fluorescent retrograde trains was determined at single pixel and frame resolution. The tip resting time for each retrograde train was defined as the duration between the arrival of the fluorescent anterograde train and the departure of the retrograde train from the tip. Tip resting time histograms were constructed and fitted to a Gamma function using MATLAB. The Gamma function was defined as Γ(t) = tFor single particle tracking analysis, the positions of fluorescent spots were determined by a 2D Gaussian fitting algorithm. The positions were fitted throughout the movie except at the frames when the gate beam was on or the frames in which the tracked particle overlapped with other fluorophores. The intensity of the fluorescent spots was estimated by the volume of the 2D Gaussian peak. In a typical assay, we adjusted excitation power to achieve 20 nm localization accuracy at 10 Hz image acquisition rate. Individual GFP particles were tracked for 5 s on average before photobleaching and the diffusion constant was obtained by MSD analysis of individual spots. In certain kymographs, diffusion of individual KAPs within a flagellum could not be resolved due to the diffraction limit.fla3::KAP-GFP cells were manually removed using custom ImageJ plugins. The remaining pixels were averaged over the kymograph’s time axis, giving a time-averaged plot of the KAP-GFP background over the flagellum length. The cells were grouped by flagellar length. The background intensity and flagellum length of each cell were normalized. The average background intensity along the length of the flagellum was calculated for each group of cells.To determine the distribution of the KAP-GFP background in flagella, anterograde trajectories in kymographs of 2 s−1). To calculate KAP-GFP influx, the KAP-GFP background was subtracted from the kymographs. Then, the average intensity of anterograde trains was multiplied by the train frequency (1.3 trains s−1) to calculate the influx.KAP-GFP efflux from the flagellum was calculated using Fick’s law. The slope of the KAP-GFP background over the length of a flagellum was multiplied by the diffusion constant  under TIR illumination was accounted for in simulations and trains with at least one fluorescent GFP upon leaving the tip were marked detectable.We estimated that each anterograde train contains six fluorescent GFPs by comparing the fluorescent intensities of anterograde trains in the P strain . Each re−1)   and the −1)  were use)  The results testing various agents to see if they affect the tip turnaround dynamics are interesting but raise many questions. For ciliobrevin, there is an increase in the return time of IFT27 and KAP. The authors should explain better what effect ciliobrevin has on anterograde and retrograde IFT and the number of these events. Furthermore, assuming that KAP dissociates from IFT complexes and returns to the cell body by diffusion, it is not clear why ciliobrevin affects its return time.2+”, last paragraph), as it results in increased cAMP levels (which of course do increase PKA activity). H-8 is a kinase inhibitor that affects PKA, PKG and to some extent PKC and other kinases. The paper does not make clear how this relates to the statement about Ca2+ effects. Could the negative results with IBMX be because this reagent is not effective at this concentration in Chlamy? This is especially important since the literature has identified several kinases that directly affect IFT motors or at least affect IFT and cilia length, including kinases in the CDK, CaMK, and MOK families . As a way of addressing this point, the authors could report how strongly other IFT parameters are affected, especially for H8. The key question that the authors need to address while revising this section is: do the treatments act directly on the machinery controlling return time, or reflect more general ciliary/IFT perturbation?For IBMX and H-8, these appear to be very blunt tools. What kinases are affected? IBMX is probably better described as a phosphodiesterase inhibitor rather than a kinase (type unspecified) activator (subsection “IFT tip turnaround is regulated by dynein activity and extracellular Ca2) It is stated as fact that the IFT complexes mix at the tip (in the Abstract and elsewhere), but the data supporting these statements do not seem conclusive. This conclusion thus should be strengthened by additional data . Alternatively, mixing should be mentioned as a plausible suggestion rather than a stated fact.The main argument for mixing is that the number of retrograde trains departing the tip is not strictly proportional to the number of incoming anterograde trains. However, there seem to be caveats that prevent this from being the direct test desired:a) Concurrent arrival of two trains. Given the relatively uniform velocity of anterograde IFT trains, it seems plausible that the PhotoGate will occasionally allow simultaneous entry of two trains that will remain in the same diffraction limited spot during transit to the tip, giving the appearance of one (bright) train. Inclusion of these events in the analysis could break strict proportionality without invoking mixing. The authors may be able to use simulation or analysis of train intensity to comment on the likelihood of this possibility. In general, a clear example of one anterograde train splitting into three or more retrograde trains is lacking from the manuscript.b) Photobleaching. As the authors show, photobleaching has a large bearing on the observations  and accoc) The finding that the average number of retrograde trains (2.4) per anterograde train is "significantly higher than the measured ratios of retrograde to anterograde train frequencies (~1.6) " is used as supporting evidence for mixing. However, the ratios in the cited papers are from a variety of species and differ widely (from 1 – 3.4). What is the ratio in the authors' experiments? In what sense is the difference "significant"; if statistically, what is the test and p-value?3) A number of questions were raised regarding the proposed model for kinesin diffusion and flagella length control. At the very least, the questions below should be addressed by better discussion.a) If the kinesin diffusion model for control of flagellar length is correct, that would presumably mean that mutants with long flagella (>20 um) have enhanced levels of kinesin compared to the strain used here. This seems an easy prediction to test.Chlamydomonas can regrow approximately 1/2 length flagella after deflagellation in the absence of any additional protein synthesis (i.e. in cycloheximide). This can be tested in the KAP-GFP system.b) It is not clear that the decrease in KAP at the basal body is really the limiting factor. The residual amount of KAP at the basal body likely is sufficient for some flagellar regrowth as Chlamydomonas. An interesting observation is that the KAP spot (presumably consisting of multiple copies of the protein) does not split into smaller species, implying that Kap3 diffuses from the tip in the same oligomeric state as it arrives. This raises a number of questions:c) Oligomeric status of kinesin-II during diffusion needs to be addressed more clearly. The authors nicely show that KAP departs the ciliary tip by diffusion in - How many copies of KAP are present per train, based on calibrated fluorescence intensities ?- What would hold KAP in oligomeric form if the train splits apart and mixes; do some components of the train remain intact?- Why does the model of d) The authors claim that the anterograde transport and retrograde diffusion can explain the increasing fluorescence of KAP towards the tip. Do the other kinesin-2 subunits show a similar gradient along the flagellum? Is this seen for kinesin-2 motors in other systems?4) Manuscript writing and organization.a) The manuscript reads as a fusion of two pieces of work: one on IFT machinery dynamics at the tip , and a second on kinesin-II diffusion and ciliary length control (which confusingly resumes with new results following the first discussion). Please combine all discussion in one place, and work on the cohesion of the two pieces.b) The nomenclature that the authors use to describe events at the cilium tip is difficult to follow. In c) The differences among species and earlier work need to be discussed better.Chlamydomonas i.e. "facilitates flagellar length control in Chlamydomonas." The finding that diffusion of KAP from the tip is so far unique to Chlamydomonas is not a weakness of the work, showing the interesting diversity of the IFT system, and does not need to be hidden.- It needs to be more clearly stated that kinesin-II returns from the tip by active transport (rather than diffusion) in all metazoan cilia studied to date. Currently, this is buried in a confusing paragraph about kinesin-2 and Kif17/OSM-3. Similarly, in the last sentence of the Abstract it needs to be stated that dissociation of kinesin-II is so far specific to - In relation to earlier work, a larger decrease in KAP intensity at the flagellar base between short and full-length cilia is reported compared to Ludington et al. 2015. In addition, the authors do not find that the amount of IFT20-GFP in the flagellum is constant during regeneration, differing from Marshall and Rosenbaum's findings with IFT52, and a central feature of the balance point model. No explanation is offered for these differences.d) The three paragraphs at the end of the section "Kinesin-2 carries dynein-2 as an inactive passenger during anterograde IFT" belong in the Discussion. In particular, the last of these paragraphs which discusses the differences between Chlamy, worm, and mammalian IFT processes, concerns one of the most important findings of the paper and needs to be prominently and thoroughly discussed. Essential revisions:1) The results testing various agents to see if they affect the tip turnaround dynamics are interesting but raise many questions. For ciliobrevin, there is an increase in the return time of IFT27 and KAP. The authors should explain better what effect ciliobrevin has on anterograde and retrograde IFT and the number of these events.eLife. In that work “we varied ciliobrevin D concentration between 0–150 μM and monitored IFT 2 min after drug treatment in cells adhered both of their flagella to surface. We observed that both anterograde and retrograde IFT train frequencies dropped with increasing concentrations of ciliobrevin D, and at >100 μM ciliobrevin D we observed accumulation of IFT trains at the flagellar tip. At 150 μM ciliobrevin D, retrograde IFT frequency was reduced by 92%. The velocities of retrograde and anterograde trains also decreased by 60% and 36%, respectively.” See We previously published the effect of ciliobrevin D in IFT movement in Shih et al. 2013 In this work, we used 100 μM ciliobrevin D, in which dynein motors are partially inactivated within 2-10 min of drug treatment. This concentration of ciliobrevin D results in 50% reduction in the frequency of retrograde and anterograde trains. It also leads to 50% and 28% reduction in retrograde and anterograde train velocities, respectively . We found that ciliobrevin D addition extends the tip resting time for a few seconds, suggesting that dynein activity is critical for the departure of IFT trains from the tip. The results are also consistent with tip accumulation of IFT trains and reduction in the frequency of retrograde trains in Shih et al. However, this delay in tip turnaround is not responsible for the observed reduction in train velocity and frequency, which must be related to the defects in retrograde transport.−4), suggesting that rapid turnover of IFT trains depends on dynein activity.”We clarified the effect of ciliobrevin D in IFT motility in the main text by adding: “Addition of 0.1 mM ciliobrevin D to media results in 50% reduction in the frequency of retrograde and anterograde trains, and 50% and 28% reduction in retrograde and anterograde train velocities, respectively . In thisFurthermore, assuming that KAP dissociates from IFT complexes and returns to the cell body by diffusion, it is not clear why ciliobrevin affects its return time.In the revised version of our manuscript, we replaced “return time” with “tip resting time” to avoid confusion. We do not claim that ciliobrevin affects return of KAP to the base by diffusion. Instead, our results imply that ciliobrevin affects the time KAP remains at the tip before it starts diffusing in flagellum.2+”, last paragraph), as it results in increased cAMP levels (which of course do increase PKA activity). H-8 is a kinase inhibitor that affects PKA, PKG and to some extent PKC and other kinases. The paper does not make clear how this relates to the statement about Ca2+ effects. Could the negative results with IBMX be because this reagent is not effective at this concentration in Chlamy? This is especially important since the literature has identified several kinases that directly affect IFT motors or at least affect IFT and cilia length, including kinases in the CDK, CaMK, and MOK families . As a way of addressing this point, the authors could report how strongly other IFT parameters are affected, especially for H8. The key question that the authors need to address while revising this section is: do the treatments act directly on the machinery controlling return time, or reflect more general ciliary/IFT perturbation?For IBMX and H-8, these appear to be very blunt tools. What kinases are affected? IBMX is probably better described as a phosphodiesterase inhibitor rather than a kinase (type unspecified) activator (subsection “IFT tip turnaround is regulated by dynein activity and extracellular CaWe did not observe any significant changes in IFT velocity and frequency in IBMX and H-8 treated cells (not shown). We agree with the reviewers’ concern that it is not clear which regulatory proteins are specifically affected with these treatments and whether these concentrations in extracellular medium are sufficient to achieve the desired effect in the first 5-20 minutes of treatment, which is the time period we collected our movies. Because of these shortcomings and the fact that these results are not critical for our conclusions, we removed the IBMX and H-8 data from the manuscript.2) It is stated as fact that the IFT complexes mix at the tip (in the Abstract and elsewhere), but the data supporting these statements do not seem conclusive. This conclusion thus should be strengthened by additional data . Alternatively, mixing should be mentioned as a plausible suggestion rather than a stated fact.The main argument for mixing is that the number of retrograde trains departing the tip is not strictly proportional to the number of incoming anterograde trains. However, there seem to be caveats that prevent this from being the direct test desired:a) Concurrent arrival of two trains. Given the relatively uniform velocity of anterograde IFT trains, it seems plausible that the PhotoGate will occasionally allow simultaneous entry of two trains that will remain in the same diffraction limited spot during transit to the tip, giving the appearance of one (bright) train. Inclusion of these events in the analysis could break strict proportionality without invoking mixing. The authors may be able to use simulation or analysis of train intensity to comment on the likelihood of this possibility.The probability that two IFT trains overlap within a diffraction limited distance (~300 nm) along the length of a flagellum and their velocities are similar such that the distance between them does not increase over 300 nm during 10 µm travel along a flagellum is lower than 2%. Because the likelihood of such events is quite low, they do not affect the results in our simulations.In general, a clear example of one anterograde train splitting into three or more retrograde trains is lacking from the manuscript.We added an example kymograph to b) Photobleaching. As the authors show, photobleaching has a large bearing on the observations  and acco-1 in vitro .We calculated GFP photobleaching rate by immobilizing recombinantly expressed GFP at the coverslip surface and monitor the decrease of their fluorescence under our imaging conditions. Exponential fit of the signal over time revealed that the photobleaching rate is 0.05 sChlamydomonas cells, because multiple GFPs coexist on a single train. In addition, these trains move, sometimes overlap with each other, and they assemble/disassemble at the tip. To address the concern of the reviewers, we measured the decrease in fluorescence intensity of anterograde trains until they reach the tip. Exponential fit to this data revealed that the photobleaching rate is 0.07 ± 0.01 s-1 in cells  The finding that the average number of retrograde trains (2.4) per anterograde train is "significantly higher than the measured ratios of retrograde to anterograde train frequencies (~1.6) " is used as supporting evidence for mixing. However, the ratios in the cited papers are from a variety of species and differ widely (from 1 – 3.4). What is the ratio in the authors' experiments? In what sense is the difference "significant"; if statistically, what is the test and p-value?-20. We have clarified this section as follows:We found the retrograde-to-anterograde ratio to be 1.15, consistent with previous reports that retrograde frequencies are higher than anterograde trains. We ran a t-test to test the significance of the difference between retrograde-to-anterograde ratio and the number of retrograde trains per anterograde trains in PhotoGate experiments. The p-value is 10-20) than the ratio of retrograde to anterograde train frequencies in conventional kymographs  A number of questions were raised regarding the proposed model for kinesin diffusion and flagella length control. At the very least, the questions below should be addressed by better discussion.a) If the kinesin diffusion model for control of flagellar length is correct, that would presumably mean that mutants with long flagella (>20 um) have enhanced levels of kinesin compared to the strain used here. This seems an easy prediction to test.The kinesin diffusion model states that kinesin-II available at the basal body becomes limiting as the flagella reach its full length. In this case, most KAP are trapped in flagella and their return is delayed by diffusion. There is also significant amount of kinesin-II available in the cytoplasm, even when cells fully grow their flagella. While the cytoplasmic pool of kinesin-II exchanges with the flagellar pool, the exchange rate is rather slow (unpublished observations) compared to the exchange between basal body and the flagellum. The model assumes that total amount of KAP localized to the flagellar compartment  determines its length, while the cytoplasmic pool has no direct effect in length. Therefore, enhanced expression of kinesin-II would be one way to increase the equilibrium length, but this is not the only way. It is also possible to reach longer equilibrium length by reducing the flagellar disassembly rate, enhancing the recruitment of kinesin-II and other IFT components from the basal body to the flagella or affecting other pathways that are involved in flagellar length control. It is not clear by which specific mechanism lf mutations generate a long flagella phenotype.We attempted the experiments the reviewers suggested by generating crosses of the KAP-GFP and lf strains to monitor KAP intensity in the lf background. In our preliminary observations, we found significant variability in individual cells, in terms of their flagellar length and KAP-GFP expression. In addition, IFT movement and tip turnaround behavior are significantly altered in some of the strains. Because of these complications, we feel that it will be difficult to compare KAP distribution in the lf background to the KAP-GFP cell line.Chlamydomonas grows longer flagella in the presence of Li+. This occurs by recruiting flagellar proteins from the cell body pool into the flagella  rather than requiring new protein synthesis , because addition of Li+ to cells that already grew their flagella leads to a 50% increase in flagellar length even in the presence of the protein synthesis inhibitor cycloheximide. Based on these results, addition of Li+ is expected to increase available KAP for flagella to 1.5X compared to control cells. Because these assays can be performed using the same strain, they are more likely to yield interpretable observations.We have designed an alternative experiment to test the predictions of our model. It is previously shown that + and in regular TAP media. In addition, we deflagellated cells and regrew their flagella in the presence of cycloheximide. Consistent with previous observations, cells grew their flagella to 1.5X of their normal length in Li+. After these cells reached their steady state length, we calculated the total KAP intensity at the basal body and the flagellum. Consistent with our model, we observed that KAP gets depleted at the basal body at equilibrium. The KAP fluorescence localized to a flagellum correlated strongly with flagellar length, similar to untreated cells. The total KAP fluorescence was 50% higher in Li+ treated cells than untreated cells. These experiments support the predictions of our model that altering the amount of KAP available for the flagellar compartment positively correlates with the flagellar length and that the equilibrium length is set when KAP gets depleted below a certain threshold at the basal body.We grew the KAP-GFP strain in 50 mM LiIn the revised manuscript, we showed these results in Chlamydomonas can regrow approximately 1/2 length flagella after deflagellation in the absence of any additional protein synthesis (i.e. in cycloheximide). This can be tested in the KAP-GFP system.b) It is not clear that the decrease in KAP at the basal body is really the limiting factor. The residual amount of KAP at the basal body likely is sufficient for some flagellar regrowth as KAP intensity localized to the flagellum after regrowth is several fold higher than KAP localized to the basal body in a steady state. Therefore, the majority of the material required for regrowth is supplemented from the cytoplasmic pool, not from the residual amount left in the basal body.Chlamydomonas can grow half-length flagella after deflagellation, suggesting that the cytoplasmic pool of flagellar proteins is at least one half of that localized to the flagellar compartment. This material can be effectively recruited to the basal body after deflagellation even in the absence of new protein synthesis. This treatment is expected to decrease available KAP to 0.5X for the flagellar compartment. Consistent with previous observations, cells grew their flagella to 0.5X of their normal length in cycloheximide. In a steady state, we observed that KAP gets depleted at the basal body at equilibrium. The KAP fluorescence localized to a flagellum correlated strongly with flagellar length similar to untreated cells. The total KAP fluorescence was 50% lower in cycloheximide treated cells than untreated cells.In the presence of cycloheximide, In the revised manuscript, we showed these results in Chlamydomonas. An interesting observation is that the KAP spot (presumably consisting of multiple copies of the protein) does not split into smaller species, implying that Kap3 diffuses from the tip in the same oligomeric state as it arrives. This raises a number of questions:c) Oligomeric status of kinesin-II during diffusion needs to be addressed more clearly. The authors nicely show that KAP departs the ciliary tip by diffusion in 2/s). Therefore, we have strong evidence to suggest that KAP departs together from the tip and in certain cases they diffuse together at the first few seconds after departure. It is also likely that KAP diffuses individually in other cases.We are also surprised by this observation. We have strong evidence that KAP molecules from a single anterograde train depart from the tip simultaneously (i.e. within a 100 ms frame time), because in most cases the KAP intensity at the tip decreases to background levels in a single frame. After departure, KAP starts rapidly diffusing in the flagellum. In some cases, we observe a single fluorescent spot to diffuse for at least 5-10 s after departure. In other cases, the KAP-GFP signal spreads up quickly along the length of a flagellum, presumably because KAPs split apart and diffuse alone. In the latter case, it is not possible for us to resolve individual molecules because of diffraction-limited resolution (250 nm) of the tracking approach, low fluorescent signal, and limited time resolution (0.1 s) compared to rapid diffusion of the molecules  of KAP-GFPs simultaneously departed from the tip in a single step . […] The- How many copies of KAP are present per train, based on calibrated fluorescence intensities ?Based on the photobleaching analysis , we anticipate that there are 6 fluorescent GFPs on each anterograde KAP particles. We note that this is the lower boundary estimate for the number of KAP subunits per train because significant fraction of GFPs remain non-fluorescent in physiological conditions ). In addition, some GFPs may photobleach before we start recording movies or may not be detected.- What would hold KAP in oligomeric form if the train splits apart and mixes; do some components of the train remain intact?We do not know whether KAP oligomerizes on its own or some components of the train also dissociate and oligomerize with KAP. We feel it would be too speculative to comment on this point in the manuscript because observed oligomerization may be short lived and occurs in only a subset of the traces, while in other cases KAP may diffuse individually.In the Discussion, we added: “In certain cases, KAP-GFP appears to diffuse in an oligomeric form. It remains to be studied what holds KAPs together and whether other components of the IFT trains diffuse with KAP clusters after splitting and mixing at the tip.”- Why does the model of We showed KAP diffusing as a cluster and individually in the revised model.d) The authors claim that the anterograde transport and retrograde diffusion can explain the increasing fluorescence of KAP towards the tip. Do the other kinesin-2 subunits show a similar gradient along the flagellum? Is this seen for kinesin-2 motors in other systems?Chlamydomonas strains with fluorescent fusions to these subunits do not exist. However, several observations suggest that other subunits also return to the base without a need for retrograde IFT. In Discussion, we wrote: “We propose that the diffusion of KAP-GFP represents the movement of the entire heterotrimeric kinesin-II complex because KAP and the kinesin-II motor subunits co-sediment in sucrose density gradients of purified flagella extracts  and neither KAP nor FLA10 accumulate in flagella during inactivation of retrograde transport .”We do not have direct ways to test whether other subunits show a similar gradient along the flagellum, because If only KAP were to dissociate from IFT but the heavy chains return to the base with retrograde IFT, FLA10 would be expected to remain in flagellum after inactivation of retrograde IFT.4) Manuscript writing and organization.a) The manuscript reads as a fusion of two pieces of work: one on IFT machinery dynamics at the tip , and a second on kinesin-II diffusion and ciliary length control (which confusingly resumes with new results following the first discussion). Please combine all discussion in one place, and work on the cohesion of the two pieces.We combined these two sections under Discussion as requested.b) The nomenclature that the authors use to describe events at the cilium tip is difficult to follow. In We apologize for this confusion. As reviewers suggested, we defined each parameter in a schematic in new c) The differences among species and earlier work need to be discussed better.- It needs to be more clearly stated that kinesin-II returns from the tip by active transport (rather than diffusion) in all metazoan cilia studied to date. Currently, this is buried in a confusing paragraph about kinesin-2 and Kif17/OSM-3.Chlamydomonas, kinesin-II returns from the tip by active transport, rather than diffusion, in all metazoan cilia studied to date.”We added the following sentence to Discussion: “Unlike Chlamydomonas i.e. "facilitates flagellar length control in Chlamydomonas." The finding that diffusion of KAP from the tip is so far unique to Chlamydomonas is not a weakness of the work, showing the interesting diversity of the IFT system, and does not need to be hidden.Similarly, in the last sentence of the Abstract it needs to be stated that dissociation of kinesin-II is so far specific to We made this change in the Abstract as suggested.- In relation to earlier work, a larger decrease in KAP intensity at the flagellar base between short and full-length cilia is reported compared to Ludington et al. 2015.Our results largely agree with Ludington et al. 2015, except we see a ~4-fold decrease while Ludington et al. reported a ~2-fold decrease in KAP intensity at the base. Although the underlying reason for this difference remains unclear, it may be related to different procedures used in fixation, parameters used in confocal imaging or background correction.In addition, the authors do not find that the amount of IFT20-GFP in the flagellum is constant during regeneration, differing from Marshall and Rosenbaum's findings with IFT52, and a central feature of the balance point model. No explanation is offered for these differences.We also noticed that this result contradicts with W. Marshall’s Western Blot analysis of IFT139 and IFT81, and immunolabeling results of IFT52. To ensure that we see an increase in IFT20-GFP accumulation in flagellum during regrowth, we have repeated our measurements See . We haveWe added “This discrepancy may be related to differences in methods for quantifying IFT components in flagella.”A central feature of the balance point model is that at least one component of the IFT machinery becomes limited as the flagella elongate and this leads to the reduction of the flagellar assembly rate. When the assembly rate becomes as low as the length-independent disassembly rate, elongation stops and equilibrium length is reached. The model would be void if there is an infinite pool of components available in the cytoplasm and this pool maintains the number of particles at the basal body. Our model is consistent with the postulations of the balance-point model and shows that KAP gets depleted at the basal body, not maintained, as the flagella elongate. Therefore, our results explain which IFT component becomes limited as flagella elongate and why this specific component gets depleted instead of others (i.e. diffusion).d) The three paragraphs at the end of the section "Kinesin-2 carries dynein-2 as an inactive passenger during anterograde IFT" belong in the Discussion.We moved this section to Discussion.In particular, the last of these paragraphs which discusses the differences between Chlamy, worm, and mammalian IFT processes, concerns one of the most important findings of the paper and needs to be prominently and thoroughly discussed.Chlamydomonas in Discussion.We expanded this section to clearly identify differences between IFT and ciliary length control in