Adolescents and young adult cancer survivors are vulnerable to psychological distress after completing cancer treatment. Telehealth (online videoconferencing) interventions may be able to address the gap in tailored, evidence-based supportive interventions. We evaluated an online, group-based, videoconference-delivered cognitive-behavioral therapy intervention (‘Recapture Life’) in a randomized trial. Forty cancer survivors between the ages of 15–25 years participated. No positive impacts on participants’ quality of life emerged immediately following the intervention, but Recapture Life participants reported using more adaptive coping skills. Recapture Life participants also reported higher negative impact of cancer, anxiety and depression at a 12-month follow-up. Additional analyses suggested that survivors benefitted differently from the two online interventions (Recapture Life vs. peer-support group) depending on how recently they had completed their cancer treatment. Our data highlight that different survivor sub-groups may find group-based, telehealth psychological interventions more or less helpful at different points in survivorship.age = 20.6 years) within 24-months of completing treatment participated, together with 18 support persons. No groupwise impacts were measured immediately after the six-week intervention. However, Recapture Life participants reported using more CBT skills at the six-week follow-up  than peer-support controls. Recapture Life participants reported higher perceived negative impact of cancer, anxiety and depression at 12-month follow-up, compared to peer-support controls. Post-hoc analyses suggested that AYAs who were further from completing cancer treatment responded better to Recapture Life than those who had completed treatment more recently. While online telehealth interventions hold promise, recruitment to this trial was challenging. As the psychological challenges of cancer survivorship are likely to evolve with time, different support models may prove more or less helpful for different sub-groups of AYA survivors at different times.Telehealth interventions offer a practical platform to support adolescent and young adult (AYA) cancer survivors’ mental health needs after treatment, yet efficacy data are lacking. We evaluated an online, group-based, videoconferencing-delivered cognitive-behavioral therapy (CBT) intervention (‘Recapture Life’) in a 3-arm randomized-controlled trial comparing Recapture Life with an online peer-support group, and a waitlist control, with the aim of testing its impact on quality of life, emotional distress and healthcare service use. Forty AYAs (M Adolescent and young adult (AYA) cancer survivors experience high rates of common mental health difficulties, such as depression and anxiety disorders ,2. For tConsiderable advances have been made in the development and implementation of age-appropriate, AYA-specific clinical and hospital-based services over the past decade ,13,14,15Online telehealth interventions offering community-based mental health care using videoconferencing technology have proliferated in recent years, and appear ideally placed to meet the unique needs of AYA cancer survivors ,20,21. CClinical and research communities have welcomed online interventions, including in oncology ,32. EarlFurthermore, it is likely that some individuals may respond better to online telehealth interventions than others , but theWe aimed to fill these evidence gaps through a rigorous evaluation of the Recapture Life intervention . RecaptuWe have previously reported that Recapture Life is feasible and safe to deliver, as well as acceptable to AYAs and psychologists ,36. HerePsychological outcomes: Depression and anxiety symptoms;Psychological processes/mechanisms: Coping skills, family functioning, cancer-related identity;Intervention delivery: Fidelity, group cohesion, and working (therapeutic) alliance;Health economics: AYA real-world functioning (including engagement in productive activities such as work and study), health service use, and medication use, costs of delivering Recapture Life, and any averted travel costs for AYA participants.Compared to an active (peer-support group) and a waitlist control, the primary outcome of this study was to measure the impact of Recapture Life on quality of life at six-weeks (end-of-treatment) and 12-months later. Given the preventative, resilience-focused approach taken, the primary outcome of quality of life was designed to capture the potential for this support model to ameliorate the impact of cancer on a range of important facets of AYAs’ psychosocial adjustment into early survivorship. Secondary outcome measures were:This paper presents the Recapture Life RCT data addressing the primary and all secondary outcomes up to 12 months post-intervention.Randomization involved two separate algorithms, both generated by staff at the School of Psychology, UNSW . An algorithm was used to generate a random sequence (n = 15) of the three trial arms , equally divided across the three arms. Groups of five consecutively recruited participants were allocated to each randomly-generated condition, before moving to the next with the subsequent group of five participants. This approach minimizes the waiting time for individual participants before an online group matching their allocation can be run with sufficient participant numbers, reducing drop-out and participant burden . Waitlisd = 0.65  on the primary outcome variable (QoL) to be detected with a power of 80% at a two-tailed significance level of 0.05. This clinically-significant . Ou. Ou36]. n = 21, 52%). Half of the sample had been diagnosed with a hematological malignancy . We have previously reported clinical challenges experienced during the trial [n = 12, 67%). Support persons had a mean age of 43.9 years . As previously published , the AYAhe trial , and whin = 14, 38.0%) reported having consulted mental health professionals at any time since their diagnosis, and prior to the study’s baselineMost of our AYA sample  reported never having consulted mental health professionals prior to their cancer diagnosis . However, over one-third  and two-way analyses (Recapture Life vs. peer-support group control 12-month post-intervention).p-values ≥ 0.46) or negative  impact of cancer over the 6-week intervention period  and impact on the cancer-related uncertainties subscale than peer-support group participants at 12 months post-intervention , p = 0.009; However, Recapture Life participants reported higher perceptions of experiencing an overall negative impact of cancer , F = 2.88, p = 0.096); younger AYAs allocated to Recapture Life reported higher positive impact of cancer compared to peer support group control, with little difference between treatment arms for older AYAs . Focusing just on the two online interventions, adjusting for baseline, individuals allocated to Recapture Life had higher levels of anxiety at 12-weeks (p = 0.046), and 12-months post-intervention (p = 0.041), and higher levels of depression at 12-months (p = 0.041), compared to those in the peer-support group .On average, participants across groups reported mean scores reflecting depression and anxiety symptoms in the normal range of the DASS-21 at each trial time point . Three-wrt group . There w1 = 5.52, p = 0.023), but not depression (p = 0.10). These analyses suggested that the peer-support group intervention yielded better improvements in anxiety outcomes for AYAs closer to treatment completion, and that these participants gained more of this advantage over time (up to the 12-month follow-up). For AYAs further into survivorship post-treatment, Recapture Life appeared relatively more beneficial than the peer-support group in improving anxiety symptoms .Centrality of events. On average, AYAs’ scores indicated a high degree of illness centrality at each trial timepoint . There wp-values ≥ 0.55).Survivor identity scale. At baseline, most participants indicated that they leant towards the “survivor” end of the scale, with 87.2% scoring themselves higher than 5 . While Recapture Life participants identified more strongly as ‘cancer survivors’ at each follow-up timepoint than peer-support group control participants, there was no evidence of significant group differences over time . On average, participants in both interventions reported increased use of coping strategies at the 6-week post-intervention follow-up, and then subsequently decreased their use of coping strategies at the later 12-week and 12-month follow-ups (p = 0.043). This pattern persisted with a similar effect size, though was no longer significant 12-months post-intervention , 12-weeks  and 12-months . Looking at the total number of different coping strategies used, there was no evidence of differences between the three groups immediately following the intervention . In relation to participants’ self-reported actual use of CBT strategies, across each time point, Recapture Life participants reported ‘actually using’ a greater number of CBT strategies, relative to peer-support group controls. There was strong evidence that Recapture Life participants also used a higher number of CBT skills at the 6-week follow-up . CBT skills. Overall, Recapture Life participants reported feeling capable of using a greater number of CBT skills, relative to peer-support group control participants , nor two-way analyses up to 12-months  showed any evidence of groupwise differences in any changes to general, problem-solving, or communication-related family functioning.AYA outcomes. Across groups, AYAs’ mean scores on perceived family functioning indicated functioning in the adaptive range on average at almost all trial time-points. At the 12-month follow-up, only the communication subscale for the peer-support group control remained in the maladaptive/problematic functioning range . Neitherp = 0.045), however no other significant effects of group or time emerged from either three- or two-way analyses.Support person outcomes. Three-way analyses indicated there was some evidence that the support people allocated to the peer-support group control reported more adaptive general family functioning relative to the waitlist group at the 6-week follow-up . Support person unmet cancer needs. At baseline, the top three high unmet needs (ranked as high/very high needs) by support person participants were all related to their worries, about ‘test results’ , ‘cancer returning’ , and whether ‘treatment worked’ . The number of perceived cancer-needs mostly declined over time for support people  but therX2(1) = 0.07, p = 0.80). Two cases of ‘manual deviations’ were reported, both in peer-support group sessions, involving unintended provision of coping skills. Treatment fidelity of recorded sessions, as rated by two independent raters, was also acceptable: Psychologists adhered to the manualized intervention components (specific to either Recapture Life or peer-support group control) in 97% of sessions and the blinded assessors correctly identified the intervention arm on 15/16 occasions (94%).Manual fidelity. Reflecting the acceptability of Recapture Life, psychologists reported adhering to all session components in 82% of sessions, with no evidence of differences between Recapture Life and peer-support control online groups  or group cohesion .Therapeutic working alliance and group cohesion. Across the intervention period, AYAs in both Recapture Life  and peer-support group arms  rated therapeutic alliance with their group facilitator positively . Likewise, group cohesion scores were positive across the follow-up period . We observed no evidence of differences between Recapture Life and peer-support interventions in either the average score or change over time for working alliance (p < 0.01). There were no between-group differences in perceived benefit over time (p = 0.93). The majority of AYAs also indicated low burden at all timepoints, with no evidence that this changed over time either between (p = 0.55), or across groups (p = 0.78). Perceived benefit and burden of intervention. (i) AYA participants. Across both Recapture Life and peer-support control groups, the majority of AYAs reported high perceived benefit at each time point, with a slight decline over time across both groups  between 6–12 months post-intervention compared to peer-support group control participants, after adjusting for reported use in the 6 months prior to baseline. There were no between-group differences on mental-health service use. Examined according to specific health-service type, the only significant finding was that Recapture Life participants reported accessing/seeing their GP significantly more often relative to the peer-support group at the 12-month follow-up  compared with 0% of peer-support group (95% CI: 0–26%); Likelihood Ratio Test = 5.87; Medication use. Over half of all participants in the waitlist (73%), peer-support (70%) and Recapture Life (56%) arms reported taking any medications at baseline. Two-way analyses comparing only the two online interventions indicated that while a higher proportion of the peer-support group controls reported taking medications at baseline relative to the Recapture Life group (72% compared to 58%) this pattern reversed somewhat over the intervention period . At baseCost of delivery. Our modelling indicated that the cost of delivering Recapture Life ranged between an estimated AU$485–540 per participant. By contrast, the peer-support group control cost less to deliver, at an estimated AU$365–415 per participant.Cost to AYAs and estimated travel costs saved. We estimated that on average, our participants avoided AU$260 in travel costs in terms of fuel costs alone, though there was a large range .Coined the ‘lost tribe’ in supportive cancer care , AYAs exOur data provided a mixed picture of the benefit of online psychological interventions, and specifically Recapture Life, at different time-points. We did not find improvements in our primary outcome  over the intervention period. Indeed, contrary to our hypotheses, in the follow-up period, AYAs allocated to the Recapture Life intervention demonstrated increased perceptions of the negative impact of cancer. Similarly, while depression and anxiety scores remained in the normal  range across the intervention and study period, the data suggested that the Recapture Life group reported higher depression and anxiety symptoms at follow-up. When length of time since treatment was taken into account, AYAs closer to treatment completion appeared to garner the greatest benefit from non-directive peer-support-groups, in terms of anxiety symptom improvement, while AYAs further from treatment completion responded better to Recapture Life. Participants in Recapture Life also reported significantly greater self-efficacy and use of coping strategies relative to peer-support participants, although these coping-skill gains were not maintained by the 12-month follow-up.poorer quality of life over time, compared to AYAs who had received no care in such age-appropriate spaces [It is possible that our quality of life evaluations of Recapture Life were susceptible to the documented psychometric phenomenon of ‘response shift’ . Response spaces . The potRecapture Life participants reported higher perceived negative impact of cancer, depression, and anxiety at follow-up; as such, it is possible that the skills-based model of group psychological intervention delivered through Recapture Life is not helpful for all AYA cancer survivors. Our data suggested, however, that AYA survivors may benefit from different types of online interventions at different points throughout the survivorship trajectory. Post-hoc analyses, taking into account the length of time since treatment-completion, suggested that our two intervention models may have been differentially beneficial for AYAs according to their passage through survivorship. Specifically, AYAs closer to treatment completion appeared to obtain more psychological benefits from the non-directive peer-support model of supportive discussion, while AYAs further into the post-treatment survivorship period appeared to derive more benefit from the CBT-based model accessed through Recapture Life. This finding warrants further investigation.The finding that AYAs closer to treatment completion appeared to benefit the most from the non-directive peer-support model is consistent with extensive literature documenting AYAs’ unmet needs for peer-support ,102,103 The selective-prevention approach used in Recapture Life aimed to equip AYAs with coping strategies to bolster quality of life at a known point of risk (cancer treatment completion and early survivorship). In the years since we developed Recapture Life, large-scale reviews have suggested that, while there may be some evidence to support the efficacy of selective-prevention interventions in reducing the severity of mental health disorders in the short term, longer-term data is more mixed, as is data on the efficacy of selective-preventative interventions in preventing the onset of mental health disorders ,10. Our Related to this, it is worth considering whether the demands of the multi-session intervention, together with the time and organizational skills required to participate in the trial (with multiple questionnaires across a 12-month period) may have similarly skewed our cohort towards more high-functioning individuals. Although randomized-controlled trials are considered the methodological gold-standard, researchers have also highlighted how the rigors of the recruitment processes and study designs can inadvertently impact the extent to which study findings can be generalized to the real world, over and above the role of the eligibility criteria . Future Although as a group, AYA cancer survivors share unique mental health risks and developmental vulnerabilities, our data echoes previous reports highlighting the considerable variability in survivors’ functioning and psychological needs ,87. For The lessons learned through this trial need to be placed in the context of several limitations. Due to recruitment challenges, our trial was ultimately under-powered to detect clinically-meaningful differences in our primary outcome measure, quality of life. The significant delays we experienced in our trial to receiving ethical approval across all sites  ,94 had aOur choice of quality of life as the primary outcome measure may also have been misaligned with the CBT skills-based processes targeted within our intervention. Among psychometric measures validated for AYAs, there is a predominance of quality of life measures , which aParticipants’ medical risk across this early survivorship period is a relevant consideration within this trial, which included participants who had completed cancer treatment with curative intent and achieved remission. In retrospect, this likely resulted in treating our sample as more uniform than it may have been, in terms of short- versus long-term risk of relapse. Our experiences documented here, and previously , in termThere are several implications of these medical risks. Firstly, it is possible that variables that we did not measure—such as fear of cancer recurrence, or post-traumatic stress symptoms—may have explained the observed increases in perceived negative impact of cancer, depression, and anxiety. Recent research has highlighted the prevalence of fear of recurrence for AYA cancer survivors and the impacts of this on long-term adjustment ; it is pOur relatively small number of support person participants constrained our ability to quantify, either the benefit of the intervention to them, or the impact of their inclusion for AYAs and the family system (through broader dissemination of coping skills through AYAs’ support networks). Parents and caregivers play an important role in assisting AYAs to negotiate the disruption caused by cancer ,122, andOur study contributes to a growing evidence base regarding online psychological interventions for AYAs living with cancer, which has been of particular interest during the global COVID-19 pandemic ,23. EvenOur findings on cost indicate that although online programs may be deliverable at modest per-participant costs, they still involve considerable time and resources to deliver. It remains unclear what level of ‘cost’ versus ‘benefit’ may be acceptable, and feasible, within public health contexts, as well as in not-for-profit, community-based settings where much psychosocial support in cancer survivorship is provided. Although health economic data highlights the considerable social burden of AYA cancer in terms of the quality of life years lost , little Beyond AYAs’ preferences for support models, the question remains as to which model(s) of mental health support may be most effective and appropriate in cancer survivorship, as mental health concerns among AYA cancer survivors are prevalent ,2, and aMore broadly, the development and implementation of psychological interventions, such as the CBT-based intervention tested here, takes the approach of targeting modifiable factors at the individual level. While important, this individually-oriented approach may overlook broader contextual and social factors that are critical for good mental health at the population level . There iThis trial demonstrated that AYAs engaged well with online, supportive interventions in the first two years following cancer treatment, though recruitment was a major challenge. We did not find a positive impact of Recapture Life on quality of life, assessed as perceived impacts of cancer in the short term, which may reflect the impact of recruitment on study power. AYAs who participated in Recapture Life reported higher perceived negative impacts of cancer, anxiety, and depression at follow-up compared to a peer-support group control. Our data suggest that AYA cancer survivors may respond differently to different models of online support according to how recently they completed treatment. Understanding how best to engage AYA cancer survivors in psychological support, and at which points in time, remains a challenge for the field.


Data are emerging on 10-year mortality comparing coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) with stenting for multivessel disease (MVD) without left main (LM) involvement. We conducted an updated two-stage meta-analysis using reconstructed individual patient data to compare long-term mortality between CABG and PCI for patients with MVD without significant LM coronary disease.Medline and Embase databases were searched for articles comparing CABG with PCI for MVD. A two-stage meta-analysis was conducted using reconstructed patient level survival data for all-cause mortality with subgroups by SYNTAX score. The shared-frailty and stratified Cox models were fitted to compare survival endpoints.p < 0.001) compared with CABG. In patients with low SYNTAX score, 10-year all-cause mortality after PCI was comparable to CABG . However, in patients with moderate to high SYNTAX score, 10-year all-cause mortality was significantly higher after PCI compared with CABG .We screened 1,496 studies and included six randomized controlled trials with 7,181 patients. PCI was associated with greater 10-year all-cause mortality risk (HR: 1.282, CI: 1.118–1.469, This updated reconstructed individual patient-data meta-analysis revealed a sustained lower cumulative all-cause mortality of CABG over PCI for multivessel disease without LM involvement. Coronary artery disease (CAD) remains the leading cause of death worldwide . CurrentPrevious meta-analyses comparing survival outcomes between PCI and CABG for MVD have utilized a standard meta-analytical approach –5. Head With reference to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines , a searcThe primary outcome of the meta-analysis was all cause mortality. The secondary outcomes of the meta-analysis were repeat revascularization and myocardial infarction (MI). All-cause mortality was defined as any death events after intervention. MI included both procedural and non-procedural infarctions. Subgroup analyses were also performed based on the Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) scores, and stratified into low (0–22), moderate (23–32), and severe risk (>32).The present RCTs have been limited by the lack of power to achieve significance, and often adopt the composite endpoint of major cerebrovascular and cardiac adverse events. Although composite outcomes may be helpful in allowing the individual studies to achieve statistically and clinically significant results, it limits the ability of the individual study to detect differences within each individual clinical outcome . TherefoThree reviewers  independently extracted the baseline characteristics and outcome measure in blinded pairs. To obtain individual patient data, Kaplan–Meier curves from the individual studies was performed using the methods of Guyot et al. . BrieflyTwo reviewers (CNH and JK) independently assessed the risk of bias of included RCTs using the Cochrane Risk-of-Bias tool , which evia the involvement of random-effects term that models patients within the individual studies as being similarly failure-prone as other subjects within the same study (via the random effects trim-and-fill (R0 estimator) procedure. Statistical significance was considered for outcomes with a p value ≤ 0.05. Statistical heterogeneity was assessed via I2 and Cochran Q test values  and Stata (16.1 StataCorp). The statistical analysis was conducted with a two-stage meta-analysis in hazard ratios (HR) for all-cause mortality with visual representation from a Kaplan–Meier curve. The primary analysis was conducted with a conventional frequential shared frailty model in gamma distribution which best accounts for study heterogenicity and assumes that individual patients within each study are similarly failure-prone as other individuals within that study , 23–25. me study , 19. Prome study . When a me study  to pool t values , where aectively , 29. A COf the total of 1,496 articles included in the initial search after removal of duplicates, 28 were selected for full text review. Six RCTs met the final inclusion criteria . There wp < 0.001). Sensitivity analysis using a Bayesian shared frailty with uninformative priors yielded similar results . The stratified Cox regression  yielded consistent results with the shared frailty models. In a two-stage analysis, both the fixed  and random effects  yielded significantly increase in all-cause mortality with PCI compared to CABG. The reconstructed 10-year Kaplan–Meier curve for all-cause mortality shows similar mortality following PCI and CABG within the first year, with gradual divergence of the time-to-event curves beyond 2 years .There was a total of 3,230 and 3,246 patients treated with PCI and CABG with a mean survival time of 5.4 and 5.4 years, respectively. The mean follow up time was 4.3 years, with 2 trials providing 10-year follow-up data , 10, 1 w 2 years . Low hetp = 0.516). Heterogeneity detected in this analysis was low . However, patients with moderate and severe SYNTAX score were found to have increased all-cause mortality following PCI when compared to CABG  with low heterogeneity .A subgroup analysis was performed based on the SYNTAX score. The mortality following PCI and CABG among patients with low SYNTAX risk was not significantly different . Incidence of MI could be evaluated in 2,196 patients treated with PCI and 2,197 patients treated with CABG. MI estimates from the fixed effect showed a 67% increase in MI in the PCI arm compared to the CABG arm  with the random effects showing similar estimates . A summary of the results for revascularization and MI are found in Data on repeat revascularization were available for 1,982 and 1,958 patients treated with PCI and CABG, respectively. There was a significant increase in repeat revascularization following PCI when compared to CABG based on the shared frailty model (HR: 3.234, CI: 2.624–3.986, This meta-analysis of six RCTs compares longer-term outcomes of PCI with stents versus CABG for the treatment of MVD without LM CAD –34. BuilWith the advancement of PCI including stent design, higher risk patients with more complex coronary lesions have been included in RCTs. As such, we have observed a larger relative 10-year mortality benefit of CABG over PCI in our study, particularly in those with more complex CAD. Our findings are in line with the shorter-term outcomes reported by previous meta-analysis  and largThe lower mortality with CABG compared to PCI is consistent with the SYNTAX trial that used first-generation  and the A higher SYNTAX score has been associated with poorer prognosis in patients undergoing revascularization  and subgOne of the well-established benefits of CABG over PCI is its favorable incidence of repeat revascularization. The higher risk of repeat revascularization in the PCI group, compared to the CABG group, found in our study is consistent with the current literature . ObservaThe ongoing debate between cardiologists and cardiac surgeons on revascularization strategy is partly due to the lack of long-term follow-up in comparative PCI and CABG trials, and this updated meta-analysis aims to fill such gap. The profound importance of heart team remains the core in deciding optimal revascularization strategy for patients with MVD in the absence of LM CAD. Current longer-term evidence from the latest RCTs suggests that CABG is preferred to PCI in cases when the SYNTAX score is >22 for survival benefit. Our findings also reinforce the favorable repeat revascularization and MI profile of CABG over PCI in patients with MVD.This meta-analysis used reconstructed individual patient data and rigorous statistical methods on 7,181 participants of RCTs for 10-year all-cause mortality. However, our study has the following limitations. First, in some of the RCTs . Fourth,In conclusion, this reconstructed individual patient data meta-analysis of 7,181 patients provides updated evidence on the significant mortality benefit of CABG over PCI in patients with MVD, extending up to 10-years of follow-up. This mortality benefit was observed particularly amongst patients with moderate to high SYNTAX score. However, PCI and CABG conferred similar survival benefit in patients with low SYNTAX score. Although the results match reasonably well with the current guideline recommendations, the study offers a robust and up-to-date appraisal of longer-term outcomes of the revascularization strategies with the inclusion of the recent 10-year trials. The longer term survival analysis on this important topic will facilitate the Heart team in making informed decisions in the outcomes of each revascularization strategy.The original contributions presented in the study are included in the article/JK, NC, and CN: conceptualization, data curation, and writing original draft. JK, NC, CN, DT, JY, CL, OL, YC, and DL: formal analysis. KC, P-HL, AL, C-HL, H-CT, and MC: supervision and validation. DT, JY, CL, OL, YC, DL, KC, P-HL, AL, C-HL, H-CT, and MC: writing, review, and editing. All authors have read and approved the final version of the manuscript for submission.MC received speaker’s fees and research grants from Astra Zeneca, Abbott Technologies, and Boston Scientific. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Flowering locus T (FT) mRNA despite the continuous debate about its mobility and biological relevance to the control of flowering time in plants. Nevertheless, accumulating evidence supports the notion of the long-distance movement of FT mRNA from leaf to shoot apex meristem and its role in flowering. In this review, we discuss the discovery of florigenic FT, the initial debate on long-distance movement of FT mRNA, emerging evidence to prove its mobility, and the use of mobile FT mRNA to generate heritable transgenerational gene editing in plants. We elaborate on evidence from virus-based RNA mobility assay, plant grafting, RNA with fluorescent protein labeling, and CRISPR/Cas9 gene-editing technology, to demonstrate that the FT mRNA besides the FT protein can move systemically and function as an integral component of the florigenic signal in flowering. We also propose a model to prompt further research on the molecular mechanism underlying the long-distance movement of this important mobile signaling RNA in plants.Many systemically mobile mRNAs have been revealed in phloem. However, very few of them have been found to be of clear signaling functions. One of such rare examples is the mobile  Wheat, rice, and maize are the three most important crops which produce seeds as food to feed people globally . To prodFlowering Locus T (FT), the initial debate on long-distance movement of FT mRNA and its biological relevance to flowering, emerging evidence to prove FT mRNA mobility, and the application of mobile FT mRNA to generate heritable transgenerational gene editing. We also discuss ideas to prompt further investigation into the molecular mechanisms underlying the long-distance movement of this important mobile signaling RNA in plants.To flower, plants perceive the day-length changes in leaves and synthesize a flowering messenger. This signal molecule, dubbed florigen, a theoretical flowering initiation switch, moves long-distance from leave to shoot apical meristem (SAM) through the phloem vascular system to induce flowering . HoweverFlowering Locus T encodes mobile florigen to induce plant flowering  mapping of the recombinant inbred line populations, FT coding sequence. Tissue-specific expression assays by dissecting the FT promoter activities also reveal that FT transcription is under the control of CONSTANS, and this occurs only in leaf veins but not the shoot meristem (FT transcript level increases under long-day (LD) but decreases under the short-day (SD), consistent with that Arabidopsis plants flowered much earlier in LD than SD growth conditions  can spread from cell to cell and over long-distance in plants. For instance, plant RNA and DNA viruses are long known to move their RNA and DNA genomes intercellular and systemically. Moreover, viruses express movement proteins that are required to promote the intercellular and systemic spread of viral RNA or DNA in plants  by virus-encoded movement proteins. Thus, defects in viral movement proteins can rid viruses of intercellular and systemic mobility whilst such movement-deficient viruses can still replicate in single infected cells. Based on these, two plant RNA viruses, i.e., s X PVX,  and Turnrus TCV; , were morus TCV; . By engig leaves . Secondl - Nicotiana benthamiana (as scion) system  system . However studies . To avoijunction . Furthererminant , consisterminant .FD-GFP was much longer than MS2SV40-GFP. FD-GFP, and chimeric SL-FT mRNA. Through fluorescent imaging, the SL-FT mRNA was found to move intracellularly and mainly accumulated at the plasmodesmata sites; however, the dynamic process of the SL-FT mRNA moving from one cell to another was not observed (The bacteriophage coat protein MS2 can bind its target RNAs “stem-loop repeats (SL).” The MS2-GFP fusion protein is often used to label and image RNAs in different organisms . Howeverobserved .Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISRP/Cas9) gene editing system has revolutionized targeted gene editing . This geFT RNA can facilitate RNA virus entering SAM (Tobacco rattle virus (TRV) to deliver sgRNA-tagged with the mobile FT RNA into SAM. In the way, the mutant progeny of Nicotiana benthamiana were recovered in next-generation at frequencies ranging from 65 to 100%; and due to sgRNA-targeting of PDS gene, the transgenerational seedlings with albino phenotype resulted from the PDS gene editing via TRV/(m)FT-sgRNA were statistically different compared with the mock control -mediated ViGE system was also developed. In this case, sgRNAs were fused to the 102-nt V genome . TogetheFlowering Locus T is one of six phosphatidyl ethanolamine-binding protein (PEBP) family members and the other five are TERMINAL FLOWER1 (TFL1) LIKE, MOTHER OF FT AND TFL1 (MFT), BROTHER OF FT AND TFL1 (BFT), ARABIDOPSIS THALIANA CENTRORADIALIS (ATC), and TWIN SISTER OF FT (TSF) in Arabidopsis  does not change the FT protein amino acid sequence but alters the RNA sequence. ft-1 with an expression cassette in which synFT contains 171 (of 175) codon substitutions. In grafting experiments where ft-1 was used as a recipient stock and transgenic synFT/ft-1 as a donor scion, the synFT mRNA was not detectable in the ft-1 shoot apical region. These experiments also suggest that changes in the FT RNA sequence did not affect the FT protein movement . Among these mobile tRNAs, their distributions are uneven. For example, no Ile-tRNA or very few Arg-tRNA but a few Asp-tRNA molecules were detected; however, Cys, Leu, Phe, Try, Trp, and Ser tRNAs were predominantly present in the phloem sap  family member, AtSRBP1, was found to mediate small RNA movement. AtSRBP1, a glycine-rich (GR) RNA-binding protein, also named AtGRP7, can bind to single-stranded siRNA    and a vifficking . In Arabed siRNA . It is potein(s) .6A) and 5-methylcytosine (m5C) play crucial and dynamic roles in embryo development, leaf morphogenesis, and root development (5C have been found to be linked with RNA mobility and m5C RNAs are predominant in the phloem (5C methylation-deficient mutants, mobile TRANSLATIONALLY CONTROLLED TUMOR PROTEIN 1 and HEAT SHOCK COGNATE PROTEIN 70.1 mRNAs become immobile (5C or other types of epigenetic modifications may play a role in FT mRNA mobility.Numerous RNA modifications have been reported  and someelopment . Recentle phloem . Interesimmobile . We specvia plasmodesmata (via the phloem-transportation highway, emerging evidence demonstrates that FT RNA can also undergo the same voyage en route to SAM. Therefore, it is possible that both FT mRNA and FT protein contribute to the florigen signal. Based on recent findings on the relevance of epigenetic RNA modifications, primary ribonucleotide sequences, secondary structures, and RNA binding proteins to RNA mobility, we propose a model for FT mRNA signaling in flowering (FT mRNAs is produced in companion cells, FT mRNAs may be epigenetically modified and form specific structures such as tRNA-like structures. Structured FT RNAs may then be recognized by RNA-binding proteins and transported through plasmodesmata into sieve tube. Along with the FT protein, FT mRNAs will move across sieve plates through phloem to germline cells in shoot apical meristem to induce flowering together with other floral induction factors. This model explains the possible movement of FT mRNA from specific companion cells to sieve tubes, then to distal SAM where they coordinate with other flowering induction factors to induce flowering (Specificized xylem and phloem are two conduits of the plant transportation system. They not only provide physical support for plants, but also are crucial to transport nutrients, minerals, and various signaling molecules in plants . Phloem odesmata . While llowering . Once FTlowering . This moZY and WC conceived the idea and wrote the draft of the manuscript. YH revised and finalized the manuscript. YW, PZ, and NS were involved in the discussion and helped to wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Single-cell sequencing technologies are growing, advancing, and supporting new opportunities to better understand cancer. A variety of technologies are available that analyze the human transcriptome, genome, epigenome, and proteome, enabling integrated datasets. As a result, these integrated datasets contribute to new mechanistic insights and areas with therapeutic potential. This review summarizes the various single-cell sequencing techniques and provides examples of recent high-impact findings from the utilization of these technologies. Additionally, the translational relevance of these technologies and their use in clinical trials is described, along with the future potential for novel findings using these innovative methods.Single-cell sequencing encompasses a variety of technologies that evaluate cells at the genomic, transcriptomic, epigenomic, and proteomic levels. Each of these levels can be split into additional techniques that enable specific and optimized sequencing for a specialized purpose. At the transcriptomic level, single-cell sequencing has been used to understand immune-malignant cell networks, as well as differences between primary versus metastatic tumors. At the genomic and epigenomic levels, single-cell sequencing technology has been used to study genetic mutations involved in tumor evolution or the reprogramming of regulatory elements present in metastasized disease, respectively. Lastly, at the proteomic level, single-cell sequencing has been used to identify biomarkers important for predicting patient prognosis, as well as biomarkers essential for evaluating optimal treatment strategies. Integrated databases and atlases, as a result of large sequencing experiments, provide a vast array of information that can be applied to various studies and accessed by researchers to further answer scientific questions. This review summarizes recent, high-impact literature covering these aspects, as well as single-cell sequencing in the translational setting. Specifically, we review the potential that single-cell sequencing has in the clinic and its implementation in current clinical studies. Single-cell sequencing evaluates heterogeneity in cellular populations at the transcriptomic, genomic, epigenomic, and proteomic levels ,2. This Transcriptomic Analysis: Unlike RNA sequencing (RNA-seq) that measures transcripts in a group of different cell types, single-cell RNA sequencing (scRNA-seq) evaluates the transcriptomic status of specific populations of single cells [Cancer Cell analyzed the transcriptome of mouse lung tumors using scRNA-seq. The transcriptome was analyzed starting from the pre-neoplastic state all the way to advanced states, such as adenocarcinoma [le cells ,4. Microle cells . Technolle cells ,3,5. Thele cells . A recenle cells . Interesle cells . Howeverarcinoma . The autarcinoma . Tumor aarcinoma . Cancer Genomic Analysis: Single-cell whole-genome sequencing (scWGS) methods are used to evaluate germline or somatic mutations [utations . More sputations ,3. Approutations ,3,12. Byutations . Interesutations . This woEpigenomic Analysis: The cell lineage and differentiation status of individual cells can be analyzed using single-cell sequencing epigenomic technologies investigating DNA methylation and chromatin states [n states . Single-n states . To measn states ,3. To stn states . There an states ,3. Epigen states . In addin states . AltogetProteomic Analysis: Single-cell proteome sequencing is more difficult to accomplish. One reason for this is that proteins cannot be amplified like mRNA or DNA [A or DNA ,18. HoweA or DNA . ResultsA or DNA ,20. For A or DNA . The CanA or DNA . New corLarge Integrated Databases and Atlas Projects: With the development of new single-cell sequencing techniques and the generation of large data sets, there has been collaboration and integration to produce publicly available databases. The Human Cell Atlas (HCA) was designed to generate reference maps of all human cells by providing open single-cell genomics data sharing [https://data.humancellatlas.org/explore/projects, accessed on 14 January 2022. Single cell sequencing data compiled by the HCA reflects information for many diseases, including cancer. For example, a recent cervical cancer study included in the HCA project compared tumor-derived endothelial cells to normal endothelial cells. With the use of scRNA-seq, this study identified that there was a higher expression of metabolism-related genes in tumor-derived endothelial cells [ sharing . The manal cells . Overallal cells . IncreasAn extensive cell atlas of the human lung was created using droplet- and plate-based single cell RNA sequencing of 75,000 human cells across all lung tissue compartments, along with a multi-pronged cell annotation approach . This luMultiple other single-cell atlases have also been created to study the composition of normal tissues and to better understand the physiology of healthy states versus disease states. One study combined human liver scRNA-seq data to characterize heterogeneity between the different datasets and define dominant phenotypes across immune cell populations . This woNot only has single-cell transcriptome profiling been used to study a single organ at a time, it has also been implemented to identify the characteristics of 15 different human organs . This heAs previously mentioned, single-cell sequencing data can help predict alterations present at the transcriptomic, genomic, epigenomic, and proteomic levels in healthy versus malignant cells. There are several reports using single-cell analysis to analyze the tumor microenvironment  and to mSingle-cell sequencing has also been used to study circulating tumor cells. Specific modifications of single-cell sequencing technologies have been produced to better handle these studies. A new technology that is termed Hydro-seq has been optimized to surpass issues of blood contamination frequently observed when using scRNA-seq. Hydro-seq can be used when studying circulating tumor cells and allows for high throughput analysis of these cells . As show+ tumor-infiltrating lymphocytes (untreated controls or PDL1 and AB680 CD73 inhibitor treated) to find that CD73 inhibition is distinct from PDL1 inhibition [Combinational strategies are often needed, and single-cell analysis may help identify potential combinational therapies. Identifying new combinations helps tremendously with immunotherapy strategies where most patients do not respond to monotherapy as a first-line treatment . In a rehibition . This wohibition . A singlhibition . There ihibition .Clinicaltrials.gov, accessed on 14 January 2022; Identifier NCT04927611), single-cell sequencing technology is being used to study the molecular features, tumor heterogeneity and cell subtypes of neuroendocrine neoplasms (NENs). Another trial (NCT04162691) aims to understand how genetics play a role in thymoma by understanding intratumoral heterogeneity using scRNA-seq. Lung cancer patients with bone metastases are being studied to identify a risk prediction model of bone-related events that can be based on single-cell sequencing (NCT04568291). Another ongoing trial is evaluating the proteomic and phenotypic signatures of prostate needle-core biopsies to better understand the malignant progression of prostate cancer (NCT02313623). Immune cell composition of bronchoalveolar lavage fluid from cancer patients diagnosed with cancer-therapy induced pneumonitis is being evaluated in the NCT04807127 trial to identify diagnostic biomarkers and therapeutic targets. A single-cell approach is being studied in NCT04807114 to identify biomarkers of efficacy and toxicity for immune checkpoint inhibitors in non-small cell lung cancer. Single-cell RNA sequencing is being used to explore the heterogeneity, identify tumor specific markers and explore the tumor microenvironment composition of lymphoma (NCT04434833). Gene expression at the single cell level is being analyzed in nasal and bronchial samples to understand the immune environment and complex interactions present in the respiratory tract (NCT04204291). Other trials are investigating the heterogeneity of dendritic cells in the colon and non-small cell lung cancer tumor microenvironment (NCT04789252) or the immune microenvironment in non-Hodgkin’s lymphoma patients (NCT04696692). Clinicaltrials.gov NCT04261010).There are currently a handful of clinical trials being conducted world-wide that are implementing single-cell sequencing technology. In one clinical trial , manifold learning and metric learning are being implemented to overcome this issue . With an


Patient medical out-of-pocket expenses are thought to be rising worldwide yet data describing trends over time is scant. We evaluated trends of out-of-pocket expenses for patients in Australia with one of five major cancers in the first-year after diagnosis.n = 1965). Medicare claims data on out-of-pocket expenses were analysed using a two-part model adjusted for year of diagnosis, health insurance status, age and education level. Fisher price and quantity indexes were also calculated to assess prices and volumes separately.Participants from the QSKIN Sun and Health prospective cohort Study with a histologically confirmed breast, colorectal, lung, melanoma, or prostate cancer diagnosed between 2011 and 2015 were included . Out-of-pocket expenses were higher overall for individuals with private health insurance. For prostate cancer, expenses increased for those without private health insurance over time (mean AU$1586 in 2011 to AU$4748 in 2014) and remained stable for those with private health insurance (AU$4397 in 2011 to AU$5623 in 2015). There were progressive increases in prices and quantities of medical services for patients with melanoma, breast and lung cancer. For all cancers, prices increased for medicines and doctor attendances but fluctuated for other medical services.Out-of-pocket expenses for patients with cancer have increased substantially over time. Such increases were more pronounced for women with breast cancer and those without private health insurance. Increased out-of-pocket expenses arose from both higher prices and higher volumes of health services but differ by cancer type. Further efforts to monitor patient out-of-pocket costs and prevent health inequities are required.The online version contains supplementary material available at 10.1186/s12885-021-08756-x. The societal cost of cancer is rising rapidly in many countries. In Australia, more than 145,000 people are expected to be diagnosed with cancer in the year 2020 (excluding non-melanoma or keratinocyte skin cancers) . While mMedical out-of-pocket expenses can be categorised into direct expenses, which include patient co-payments toward consultations, tests, procedures and medications, and indirect or non-medical expenses, including transport, parking, and accommodation costs necessary to receive healthcare. While the direct medical out-of-pocket expenses have commonly been estimated in the immediate period following a cancer diagnosis, the indirect costs are also substantial and can quickly accummulate. Overall, patients with cancer use a high number of healthcare services and medicines and have higher medical out-of-pocket expenses compared with patients without cancer, irrespective of whether they have private health insurance or not , 7. The Financial hardship has been shown to affect patients‘access and adherence to treatment with some patients missing appointments, delaying, or foregoing treatment, which may lead to poorer health outcomes –15. The Australia has a mixed public-private health system whereby medical services provided outside of public hospitals are delivered privately. Medicare is Australia’s universal health insurance scheme available to all Australian citizens and permanent residents. It covers medical services listed in the Medical Benefits Schedule (MBS) and prescription medicines listed in the Pharmaceutical Benefits Scheme (PBS). Medicare does not cover services in public hospitals which are funded through individual State governments. Doctors and other health professionals operating in private practice may charge what they believe is fair and reasonable . Each seDespite patients with cancer having high medical costs, there is very little research on whether out-of-pocket medical expenses have changed over time. There are also few routinely reported statistics on out-of-pocket expenses to inform policy . Thus, wn = 40,438) gave consent to provide linked Medicare data [n = 1965) and no patients had died within the first year. We excluded individuals with two or more cancer types, different from melanoma, diagnosed within one year and those with missing health insurance status or level of education (n = 196).In 2010–2011, the QSKIN study recruited 43,794 residents of Queensland, Australia, aged 40–69 years selected at random from the Queensland Electoral Roll, 92% of whom , patient out-of-pocket cost, and date of service. The data incorporated all consultations, tests, imaging, procedures and pharmaceuticals billed through Medicare. All MBS and PBS items for each patient, rather than cancer-specific items, were used for this analysis because it is not possible to attribute generically worded items specifically to cancer. Out-of-pocket amounts are recorded for each service or medicine recorded by Medicare. However, for therapeutic services conducted in a private setting , the amounts are prior to reimbursement by private health insurers. For the majority of the items, insurers do not reimburse out-of-hospital services such as doctors’ visits, medications, community-based imaging, pathology, or any out-of-pocket hospital services covered by Medicare. All costs were inflated to 2016 prices. The study was approved by the QIMR Berghofer Human Ethics Research Committee and all participants provided informed written consent to take part.Descriptive analyses were used to present the cancer type by year of diagnosis and their baseline socio-demographic characteristics using frequencies and percentages for categorical data and means and standard deviations for continuous variables. Chi-square tests and Fisher’s tests were performed to identify statistically significant differences in the baseline variables across cancer groups.p < 0.05.We calculated the total out-of-pocket expenses for all patients during the first year after diagnosis, and the mean cost per patient per year of diagnosis to evaluate annual fluctuations between 2011 and 2015 for those patients with out-of-pocket expenses. Patient out-of-pocket expenses were presented using medians and interquartile ranges (IQR) as well as means and standard deviations. To measure differences in out-of-pocket expenses each year, we performed a two-part model analysis  to accouCalculating trends in out-of-pocket expenses can be attributed to rising prices and/or higher quantities of services or products (existing or new). To evaluate whether prices were rising for each category of service, the year-to-year average change from the base year was calculated using the Fisher Price Index, a measure of the average price level based on a basket of goods that allow us to estimate movements in the price over time , 28. Simn = 63, 3.2%) had zero out-of-pocket expenses for MBS services. Those diagnosed between 2013 and 2015, or who had private health insurance or a diagnosis of breast cancer, were up to six times more likely to have paid out-of-pocket expenses than patients diagnosed in 2011–2012, without private health insurance and with a diagnosis other than breast cancer. Adjusting for private health insurance status, year of diagnosis, age and level of education, mean out-of-pocket expenses for the first 12 months after diagnosis were highest for patients with prostate cancer , colorectal cancer  and lung cancer   patients with melanoma, 451 23%) with prostate cancer, 396 (19%) with breast cancer, 160 (8%) with colorectal cancer and 106 (5%) with lung cancer  proportion of patients with zero expenses than in earlier years  in our analysis. Colorectal cancer mean estimates  were comparable with €1589 (AU$3242) reported in Europe [A detailed report on 1919 Australian patients with breast cancer, surveyed in 2016, found mean 5-year costs of $4809 with an interquartile range from $1510 to $17,200 . Some ofOur study showed that out-of-pocket costs were substantially higher in patients with private health insurance but they were stable over time, whereas out-of-pocket costs increased for those without private health insurance. We also show that patients without private health insurance, usually made up of more individuals from lower socio-economic backgrounds, have a higher proportion of their healthcare expenditure going towards medicines which are already heavily subsidised for Australians. Rana et al.  reportedThere are some limitations of our study. Our data is now five years old and changes to Medicare items and PBS medications introduced since 2015 were not captured. Also, the introduction or exclusion of items during 2011–2015 could not be included in the price and quantity index analyses and additional items will have influenced cost differences between 2011 and 2015. We contend this will be small contributor to overall costs since, firstly, these apply to patients with metastatic cancer only and secondly, PBS medicines only attract a small co-payment. Overall, surgical procedures are the key cost drivers of overall out-of-pockets and these have not changed during this period. The out-of-pocket expenses listed in our data do not include reimbursements made by private health insurance companies although these would only apply to therapeutic procedures in private hospitals. In addition, indirect medical expenses were not reported here such as the additional costs such as travel, parking, paid home help, childcare services and income lost through needing time off work. These additional costs can mount quickly and are distressing especially for individuals living in rural areas needing to travel long distances to treatment centers. In this sense, our overall patient expenses reported here are conservative. The analyses could have used a GLM model after removing the small proportion of patients with zero costs in the Medicare dataset. However, since there is no stated percentage of zeros when an analyst should use a two-part model , we chosAlthough the distribution of the cancer types in this study do not represent the relative incidence of these five cancers according to Queensland cancer registrations, our objective was to assess changes over time by cancer type rather than observe incidence-based costs of our cancer sample. Furthermore, we cannot rule out potential differences in provider fees charged in other metropolitan and regional settings around Australia, which impact on the out-of-pocket findings in our study. These provider fees have been found to be higher in New South Wales and Victoria . We acknIt is important to routinely monitor out-of-pocket medical expenses as an essential part of assessing health system performance, even in countries with universal health care . One stuAmong patients diagnosed with one of the five prevalent cancers in Australia, overall first-year out-of-pocket medical expenses increased 70% from 2011 to 2015. Patients with breast cancer and melanoma experienced the largest increases in out-of-pocket spending while prostate cancer and colorectal cancer had high overall mean expenses during 2011–2015. Those without private health insurance faced expenses progressively and significantly higher over time and may be at risk of reduced access to healthcare.Additional file 1. Density plots for the tested gamma, lognormal and normal distributions.Additional file 2. Calculation of the Fisher indices.Additional file 3. Adjusted and unadjusted mean out-of-pocket expenses per year per cancer type.Additional file 4. Generalized Liner Model (GLM) results for all cancers.Additional file 5. First part of two-part model by cancer type.Additional file 6. Price and Quantity Index.


Degraded landscapes and soil water stress are long-standing problems to smallholder agriculture in the drylands. Despite the important roles of zai technology in restoring degraded landscapes and improving agricultural productivity, the technology is yet to be adopted to its fullest extent. This can be attributed to gender-linked disparities in agricultural technology utilization. The study, therefore, sought to determine gender-specific determinants of zai technology choice and use-intensity. A multistage sampling technique was employed in randomly selecting 133 female-headed households and 267 male-headed households in Tharaka South sub-county. Quantitative data were collected in a cross-sectional survey using an interviewer-administered questionnaire. Using sex-disaggregated data, Chi-square and t-test statistic were employed to test the statistical significance of dummy and mean value of continuous variables, respectively. Gender specific determinants of zai technology choice and use-intensity were determined using the Heckman-two-step econometric model. The results revealed that, more women farmers (44%) were using zai technology as compared to men (38%). Among women farmers, total cultivated land, access to animal-drawn farm implements, and group membership had an influence on zai technology choice. For men, total cultivated land, group membership and access to extension services positively influenced choice of zai technology. With regard to zai technology use-intensity, total land cultivated, livestock densities, group membership and frequency of trainings on soil and water management were important determinants among women farmers. For men, zai technology use-intensity was determined by total cultivated land and farmers’ perceptions on soil erosion. We recommend that, gender-sensitive farm-level policies oriented towards farmer socioeconomic profiles are important deliberations towards choice and intense application of soil and water conservation strategies such as the zai technology. Male-headed households, Female-headed households, Choice, Heckman-two-step selection model. Correspondingly, in sub-Sahara Africa (SSA), there is a high incidence of food insecurity where rain-fed subsistence agriculture remains a predominant livelihood strategy for most people residing in the drylands  in the Tharaka South sub-county were selected using a sampling framework. In the third stage; at ward level, sample households were randomly selected. A list of 4,000 farmers was obtained from Tharaka South Sub-county agricultural office. The basic element in the sampling frame was the farm household. A probability proportional to size sampling technique was employed to determine the number of households sampled per ward . A samplThe sample size was determined using We used semi-structured questionnaires with modules on-farm and farmer's socioeconomic characteristics and institutional factors to collect quantitative data at the household level in a cross-sectional survey. We programmed the questionnaire into an electronic format using Open Data Kit (ODK) software and sufficiently pre-tested for reliability and validity and corrected for errors. Trained enumerators were used in administering the questionnaires.2.3Livestock densities were determined for each unit following 2.42.4.1u) that an individual (m) gains from utilizing (n) soil and water conservation technologies can be defined by v) is the utility determinants and (Ɛ)is the error term.The study followed random utility maximization theory, which postulates that, a rational farmer will choose a given innovation or a bundle of innovations if the benefits derived from their choice exceed the benefits derived from not choosing . The utiu) depends on individual preferences from a package of (n) soil and water management alternatives m is the soil and water conservation strategy, and zn are farmers' desired technology-specific attributes and farmer characteristics.We assumed that ((n) soil and water conservation innovations. The choice of innovation (n) is dependent on expected higher benefits when compared to other innovations .. Among other factors, specific characteristics of an innovation influence levels of satisfaction an individual derives from utilizing an innovation. Chances that an individual A farmer with the intention of maximizing present farm productivity through increased soil and water conservation will select preferred strategy among a set of (Ɛ), included in the utility function.Variations in choice are accounted for by a random element 2.4.2We employed the Heckman's two step selection model to obtain unbiased estimates at the second stage of decision making. In the Heckman's selection model, we presumed that, sample selection bias existed necessitating unbiased estimation in the second stage (use-intensity) . FurtherA two-step estimation procedure was followed. In the first step, we estimated the probability of zai choice and obtained the Inverse Mill's Ratio (IMR). The IMR was incorporated in estimating the second step as a remedy for sample selection bias. Heckman's model is anchored on two latent variables . The firHypothetical variable (The second equation is linear representing the use-intensity The error terms λi is the IMR and given as (The use-intensity  is used :(8)E=(Yigiven as :(9)λi=ϕWIn estimating the second stage, IMR, given as .(10)Yi=XThis gives rise to self-selection bias when 2.4.3th farmer to use zai technology.th farmer.th farmer choosing zai technology.In Heckman's selection model, the first step dependent variable was dummy in nature (whether a farmer was using zai technology or not), and was explained using a set of independent variables, namely age, education, household size, off-farm income, total land cultivated, land ownership, access to farm implements, livestock densities, perceptions on soil fertility and soil erosion, farmer training, group membership, access to relief, frequency of training, the number of groups, household head received credit, access to labour, distance to main market and frequency of extension services. The algebraic representation of Heckman's probit selection model was given in th farmer use-intensityIn Heckman's outcome model, the dependent variable was continuous (proportion of cultivated land under zai technology). It was also explained using a set of relevant independent variables, namely age, education, household size, off-farm income, total land cultivated, land ownership, access to farm implements, livestock densities, farmer perceptions on soil erosion, access to training, group membership, access to relief, number of groups, household received credit, access to labour, distance to main market and frequency of extension :(12)Yi=θ2.4.4We conducted preliminary diagnostics for statistical problems of multicollinearity. Inter-correlation among dependent variables was tested using the Variance Inflation Factor (VIF). The VIF values obtained were below 10, hence the conclusion that, their existed weak inter-association among the explanatory variables. To validate Heckman's 2-stage selection model viability, golden standards in applying the model were observed. Inverse Mills Ratio (Lambda), a function of the correlation coefficient between first and second stage error terms (rho) that accounts for potential sample selection bias was significant; an indication that sample selection bias was resolved for . We, the2.4.5Choice of variables was guided by relevant theories and past studies . However2.4.5.1The first stage dependent variable was a dummy variable (whether a farmer chose to use zai technology or not). It takes the value of 1 if yes and 0 otherwise. The second stage dependent variable was a continuous variable and defined as the proportion of cultivated land (ha) dedicated to zai technology. Past studies have conceptualized intensification as the area of land in hectares planted with improved seeds, fertilizer application rate per acre and number of technologies adopted . Additio2.4.5.2This information could be found in the supplementary materials see .Table 2S33.1Among the interviewed households, (44%) female-headed households and (38%) male-headed households were utilizing zai technology . On averThere existed a significant relationship between group membership and choice and use-intensity of zai technology in male-headed households and female-headed households at the 1% level. About (53%) of zai technology users in female-headed households were members of a farmer group compared to (47%) non-users. For male-headed households, (46%) users had group membership compared to (54%) of non-users . Within Results also show a significant relationship at 5% level between access to relief and use of zai technology in male-headed households. Some (47%) non-users of zai technology had received government relief compared with (53%) users . On aver3.2Further, the results indicated that, age of the household head negatively and significantly  and  influenced zai technology use-intensity among female-headed households and male-headed households, respectively. Years of education negatively predicted zai technology use-intensity within female-headed households . The study found a significant and positive relationship with zai technology use-intensity concerning livestock densities within female-headed households . The coefficient of farmers' perception of soil erosion severity was significantly and positively associated with zai technology use-intensity among male-headed households . The study also established a positive and significant relationship within female-headed households  between the frequency of training on conservation practices and zai technology use-intensity.44.1A majority of the interviewed households were male-headed. This finding collaborates with other studies conducted in the region by Farming experience has been found to positively as well as negatively influence the likelihood of adopting agricultural technologies . This coResults showed that users of zai technology were members of farmer groups, accessed extension services, and participated in soil and water conservation training. These findings may be co-attributed to farmer groups, extension services, and training, providing capacity-building avenues to disseminate information to farmers on agricultural innovations. As was noted by 4.2For both genders, membership in a farmer group increased the likelihood of choosing zai technology. Group membership and other social forums could provide linkage to access agricultural information through extension contacts and other farmers' interactions where they exchange ideas and practically demonstrate agricultural innovations. Also, farmer groups are target points for researchers' and other development agents disseminating research findings. These results are consistent with the finding of Among male-headed households, access to extension increased the likelihood of choosing zai technology. Extension services bridge farmers’ knowledge gaps on improved farming practices and application modalities. Our finding was in agreement with several other studies, for example, Within male-headed and female-headed households, total land cultivated positively influenced the choice of zai technology. This was an indication that larger farm sizes increased the likelihood of choosing zai technology. This could be attributed to flexibility of devoting a portion of land for new technologies increasing with increase in land size. Our results corroborate with the findings of Ownership and access to farm implements  within female-headed households increased the likelihood of choosing zai technology. This could be due to the availability of farm implements, which save on both time and labour costs for women farmers trapped in drudgery rural agriculture. This agrees with In female-headed households, training on soil and water conservation increased the likelihood to use zai technology intensely. Training increases farmers’ knowledge on agricultural technologies application modalities. Additionally, frequent knowledge-refreshing increase the chances of continued adoption after try-out stage. Well-versed farmers make accurate estimates of expected returns, a cushion from frustrations of returns overestimation resulting in stagnating and abandoning technologies. The results are consistent with We established a negative relationship between years of education and zai technology use-intensity, suggesting that more educated farmers were more inclined towards non-farming activities. The findings were consistent with those of Male-headed households who perceived soil erosion to be severe were more likely to use zai technology intensely. An implication is that, zai technology has the water-holding capacity and when applied together with manure, soil water infiltration and porosity improve and, subsequently, reduces water loss. Low soil fertility occurs as a result of soil loss, among other factors; hence farmers who experience soil loss adopt zai technology more . A studyIn terms of total livestock densities, we found a positive relationship with zai technology use-intensity within female-headed households. Livestock ownership signifies women's empowerment in agriculture, translating to household wellbeing . Proceed5The study supports the hypothesis that there are gender specific determinants of zai technology choice and use-intensity in Upper Eastern Kenya's drylands. In particular, within male-headed households, we found that efforts to promote zai technology should consider the total cultivated land, farmers' perceptions on soil erosion, group membership, and access to extension services. For female-headed households, total land cultivated, livestock densities, group membership, and frequency of training and ownership and access to farm implements were important determinants of zai technology choice and use-intensity. Livestock ownership, access to land, and farm implements are proxy measures for women's empowerment in agriculture, driving utilization of agricultural innovations intensely. This calls for the need to develop gender-sensitive policies that advocate equitable and secure ownership of productive assets. Such policy frameworks could be embraced as a guideline to women's empowerment in agriculture. Moreover, the study recommends that extension systems need to be reformed and tailored to serve men and women farmers' specific needs and preferences with regard to utilization of agricultural innovations. This will enable both women and men farmers, to choose and use zai technology as an adaptation strategy to climate shocks in sub-Saharan Africa's drylands.Amos Mwenda Ndeke: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Wrote the paper.Jayne Njeri Mugwe; Hezron Mogaka; George Nyabuga: Conceived and designed the experiments; Wrote the paper.Milka Kiboi; Felix Ngetich; Monicah Mucheru-Muna; Isaya Sijali; Daniel Mugendi: Contributed reagents, materials, analysis tools or data; Wrote the paper.Flemish Interuniversity Council-University Development Co-operation through the .This work was supported by the Data will be made available on request.The authors declare no conflict of interest.No additional information is available for this paper.


Associations between age, concerns or history of falling, and various gait parameters are evident. Limited research, however, exists on how such variables moderate the age-related decline in gait characteristics. The purpose of the present study was to investigate the moderating effects of concerns of falling , history of falls & diseases, and sociodemographic characteristics on changes in gait characteristics with increasing age in the elderly.n = 125 females) from 60 to 94 years of age were analysed . Dependent variables were major spatiotemporal gait characteristics, assessed using a capacitive force measurement platform (zebris FDM-T). Age (independent variable) and the moderating variables concerns of falling (FES-I), gender/sex, history of falls and fall-related medical records, number of drugs daily taken, and body mass index were used in the statistical analysis. Hierarchical linear mixed moderation models  with stepwise (forward) modelling were performed.In this individual participant level data re-analysis, data from 198 participants (p < .05). Overall and specific situation-related concerns of falling (estimates: −.0012 to −.07) were significant moderators. History of potentially gait- and/or falls-affecting diseases accelerated the age-related decline in gait speed (−.002) and its variability (.03). History of falls was, although non-significant, a relevant moderator (in view of increasing the model fit) for cadence (.058) and gait speed (−.0027). Sociodemographics and anthropometrics showed further moderating effects . .Decreases of gait speed , absolute (− 1.4) and gait speed-normalized (−.52) stride length, step width (−.08), as well as increases in speed normalized cadence (.65) and gait speed variability (.15) are all age-related  by history of falls, significantly by history of diseases, and sociodemographic characteristics in 60–94 years old adults. Knowing the interactive contributions to gait impairments could be helpful for tailoring interventions for the prevention of falls.Re-analysis of [21–24]. The risk for falls increases with increasing age, in particular above the age of 65 years , 2. One To prevent falls, modifiable causes and risk factors for a fall, as well as their interaction and pathways must be known and targeted in effective strategies . Beyond These different risk factors must be treated interactively and not as isolated contributors. Mobility and physical function impairments, often operationalised by spatiotemporal gait parameters , for exaConclusively, ageing leads to age-related, less than age-related, or beyond age-related declines in  gait characteristics. This association may be moderated by numerous risk factors for falls. The interactive association of ageing, falls-related functional changes and biopsychosocial risk factors for falls has, however, not yet been finally delineated. The purpose of the present analysis was to provide further evidence on this complex interactive structure. In line with the above-mentioned rationale, analyses on the temporal structure (ageing is followed by gait changes) and the most plausible interaction structure is missing so far. In this study, we investigated the moderating effects of concerns of falling, history of falls & diseases, and sociodemographic characteristics on gait changes with increasing age in the elderly. We hypothesise that age-related declines in spatiotemporal gait characteristics are moderated by numerous fall risk factors like concerns of falling, polypharmacy, a history of falls, and having a history of potentially fall-related diseases.In this cross-sectional retrospective trial, all data included were obtained from previously published research or study samples included in the publishing process . Individual participant data were obtained from three multicentre randomized trials –24 and rThe analysis was conducted using anonymized individual participants’ data. All underlying studies have been approved by an ethical review committee for research . They, further,were conducted in accordance to the ethical standards set by the declaration of Helsinki . The possibility to re-analyse the assessed but anonymised data was provided by the institutional review boards’ positive hearing.Inclusion criteria were consistent in the three samples: age 60 years and above, being capable of walking, and living in a community dwelling, assisted living facility, or nursing residence housing situation. Exclusion criteria consists of uncorrected visus impairments, dementia, acute injuries or infections, or further severe diseases like unstable angina pectoris, vascular disease of the extremities, or severe cardiopulmonary dysfunction. More details on the exclusion criteria have been described elsewhere . FollowiRecruitment was conducted by personal contact, by flyers and newspaper bulletins. The participants were recruited in senior residence institutions –24 and iThe independent variable was age [years]. Moderators were sociodemographic & anthropometric data , concerns of falling (sum score and during specific situations), history of fall-related diseases, multi-medication/polypharmacy, and history of fall(s). The dependent variables (different models) were the spatiotemporal gait characteristics variables.Age and moderating sociodemographic characteristics were asked first, followed by the questionnaires ; the assessment was completed assessing the gait characteristics in conclusion.The history of potentially gait-affecting disease  and medication intake were assessed by means of a structured interview. Diseases were afterwards simply dichotomised as: yes = participant has a history of potentially gait-affecting disease versus no = no history of such disease(s) reported. The same was done for the multi-medication: yes = more than three different drugs versus no = intake of three or less different drugs .History of falls in the last 6 months was assessed with a self-report questionnaire by means of a structured interview. Sufficient validity of this retrospective procedure against a prospective calendar-reported method is given . For theActivity-related concerns of falling were captured by means of the German version of the Falls Efficacy Scale (Short FES-I). The FES-I assesses one’s confidence  in performing different basic or more demanding physical and social activities of daily living without falling. A sum score is built by simply sum these numbers up. The 7-item short version  or the 1The same setting and device were used for all gait data assessed. A 10-m ground level distance walkway was used. In between the two 4-m acceleration/deceleration walkways, a capacitive force measurement platform of 2-m length was placed .The participants walked over the walkway in their habitual/comfortable walking speed. A familiarization trial was followed by 2  to 5 2121 test tAll data were displayed descriptively. Interval and pseudo interval scaled data are displayed as means and standard deviations, nominal scaled data as numbers and percentage distributions, ordinal scaled data as percentage distributions.Linear mixed moderation models  investigated the impact of the independent variable age on the dependent variables (gait characteristics). Concerns of falling, history of falls & diseases (including multi-medication), and participants characteristics  were considered as potential mediators of the association of age and gait characteristics. A stepwise (forward) modelling was performed. During the modelling, all potentially relevant moderating variables , concerns of falling (sum score and during specific situations), history of fall-related diseases, multi-medication/polypharmacy, and history of fall(s)) were prospectively modelled to find the model with the best fit. Variables were excluded if they were not significant within the total model or if they were only non-relevant contributors to the model fit (as displayed by the within-model by the 2-restricted Log Likelihood). Only the final models (those with the best model fit) are displayed. The linear mixed model’s estimates displays the slope (strength of the relationship per respective unit of mass) of the association and can be interpreted like classic regression coefficients.P-values below 5% are defined as statistically significant.All analyses were performed using SPSS . For all inference statistical analyses, an alpha-error of 5% was considered as a valid cut-off for significance testing. Overall, 198 participants were included. Sixty-three thereof live in nursing homes, the other 135 were community-dwelling or independently-living. The age (independent variable) ranged between 60 and 94 years. Detailed sociodemographic and anthropometric characteristics (moderators) of the participants are given in Table The Figs. Age-related declines in spatiotemporal gait characteristics were moderated by numerous fall risk factors. Single and sum scores of concerns of falling, having a history of potentially fall-related diseases  and (non-significantly) a history of falls moderated one or more gait characteristics in 60–94 years old adults. As some of these factors were found to be additional moderators on the decline of gait characteristics with increasing age, the effects are always depend on which gait characteristics is referred to. Our hypothesis could thus be partially verified.Considering the simple direct effects of aging, decreases of the absolute and gait speed-normalized stride length and gait speed, as well as increases in cadence and gait speed variability were all age-related. Ageing leads to declines in sensory systems and to a reduced ability to adapt to changes in the environment and therefore limits the ability to maintain balance . Gait, iWith focus on the multilevel moderation, we found that the associations of increasing age and impairments in gait characteristics were partially (negatively) moderated by overall and specific situation-related concerns of falling. A history of potentially gait- or falls affecting diseases further accelerated the age-related decline in gait characteristics such as gait speed and gait speed variability. In contrast, history of falls showed only non-significant contributions on the association of age and gait cadence and gait speed. Our data underlines that the different risk factors found in the present study and known in the literature must be rated interactively and not as isolated contributors. The association of concerns of falling we found, for example, confirms the literature on findings of fall concern-associated gait impairments like decreased gait speed, stride length (sum score only non-significantly in our findings), and double limb support time (sum score only non-significantly in our findings) , 16. In Our results suggest a temporal relation beyond simple age-gait-associations for certain gait characteristics and moderators. It seems likely that both, the pathway of how ageing leads to declines in gait characteristics and the magnitude of these declines are moderated by at least one of the moderators investigated . Gait assessments and in particular gait variability outcomes are sensitive to identify neural changes . IncreasModifiable risk factors for falls and their interaction and pathways must be targeted to prevent a fall . To addrMobility and physical function impairments are often operationalised by spatiotemporal gait parameters . UnimodaSociodemographic and anthropometric characteristics showed minor contributions . The impact of height on the age-gait-relation is somewhat new as a finding. The relevance of sex , BMI . The construct itself and most of the items remains the same for the two types. However, that and the retrospectively collected falls need to be considered as limitations of the present study. As we have not investigated fall risk prospectively, a transfer of our results to fall risk must be considered as theoretical.Gait and falls are both complex matter and have many contributors. Some were assessed as independent or moderating variables in the present study, some  were exclusion criteria . Assessing potential further contributors to falls and gait characteristics such as sensory function, alcohol abuse, orthostasis, hip and knee osteoarthritis  would haAge-related declines in spatiotemporal gait characteristics are moderated by numerous factors in 60–94 years old adults. Concerns of falling, history of falls & diseases, and anthropometric-sociodemographic characteristics were found to be moderators to one or more of the associations between age and gait characteristics. Decreases of absolute and gait speed-normalized stride length, gait speed and step width, as well as increases in speed normalized cadence and gait speed variability are all age-related. Overall or specific situation-related concerns of falling were significant moderators of stride length, speed, variability of gait speed, and double stance time. History of potentially gait- or fall- affecting diseases accelerated the age-related decline in gait speed and its variability. History of falls (gait speed and cadence) was a non-significant moderator. Sociodemographic-anthropometric characteristics were further significant  moderators. The knowledge of these interactions may be helpful in unravelling the complexity of the interaction of gait, ageing, and risk factors for falls. Knowing the interactive contributions to gait impairments could be helpful for tailoring future interventions addressing falls.