Global health practitioners are increasingly advocating for the integration of community-based health-care platforms as a strategy for increasing the coverage of programs, encouraging program efficiency, and promoting universal health-care goals. To leverage the strengths of compatible programs and avoid geographic and temporal duplications in efforts, the Tanzanian Ministry of Health and Social Welfare coordinated immunization and neglected tropical disease programs for the first time in 2014. Specifically, a measles and rubella supplementary vaccine campaign, mass drug administration (MDA) of ivermectin and albendazole, and Vitamin A were provisionally integrated into a shared community-based delivery platform. Over 21 million people were targeted by the integrated campaign, with the immunization program and MDA program reaching 97% and 93% of targeted individuals, respectively. The purpose of this short report is to share the Tanzanian experience of launching and managing this integrated campaign with key stakeholders. The neglected tropical diseases (NTDs) contribute to extensive disease and disability globally. The United Republic of Tanzania is endemic for all five NTDs for which preventive chemotherapy via mass drug administration (MDA) is standard of care. In 2013, over 40 million Tanzanians required MDA for onchocerciasis, lymphatic filariasis (LF), soil-transmitted helminths (STHs), schistosomiasis, or trachoma.4Vaccination campaigns delivered according to the Expanded Program on Immunizations (EPI) schedule have consistently attained high coverage in Tanzania due to the availability of funding from the Gavi Vaccine Alliance and the launch of the Reaching Every Child approach. EPI services in Tanzania target children under 24 months of age with a nine-vaccine package, and in 2011, EPI programs integrated the distribution of mebendazole to children under 5 years of age for STH control. Some vaccine-preventable illnesses such as measles and rubella (MR) require supplementary campaigns every 3 years to ensure that epidemics do not occur in areas with low coverage or inadequate seroconversion rates.Although experts suggest that NTD programs consider coordinating with other community-based public health programs to maximize coverage and efficiency, community-wide MDA and EPI campaigns typically operate independently.The coordinated campaign was conceived during a weekly preventive services meeting in 2014, when NTD and immunization program managers were planning interventions with similar targeted age groups in many congruent geographies. The immunization program was scheduled to deliver a supplementary MR vaccination campaign to children 9 months to 15 years of age along with mebendazole for children under 5 years of age. The NTD MDA campaign was scheduled to distribute ivermectin and albendazole to individuals over 5 years of age for the treatment of onchocerciasis, LF, and STH. The MR campaign targeted 27 of the country's implementation units, with 16 of the areas also targeted by the NTD campaign. Thus, the hypothesis driving the integrated campaign was that coordinated delivery in cotargeted areas would efficiently use limited resources and, relative to vertical campaigns, increase coverage.Activities conducted in coordination with one another included planning exercises, community sensitization and media campaigns, codistribution of drugs and vaccines, and monitoring and evaluation. The codistributed interventions targeted over 21 million people and are depicted in To facilitate delivery, 12,824 stationary and mobile vaccine posts were established. Each health post required seven people, including two health-care workers providing immunization services, two community drug distributors (CDDs) conducting MDA, two health workers (often school teachers) serving as data recorders, and one community leader mobilizing communities. A total of 1,886 council team supervisors were deployed to supervise the integrated teams.The Tanzanian immunization program utilizes a “proxy system” whereby the population size and the number of people targeted are used to calculate daily coverage benchmarks. Daily benchmarks outline the number of days it will take to fully immunize the target population in each geography, and the number of people to reach per day. This system was adopted by the coordinated MR-MDA campaign, helping both programs to estimate the materials needed and the number of fixed or mobile teams required.The coordinated campaign lasted for 7 days, followed by program-specific mop-up activities. In comparison, the 2013 MDA campaigns were conducted from August to December, typically spanning 7 days each in any given district. The 7 days were intensive, requiring daily travel and communication between health workers and supervisors. Coverage data from health posts were transferred to the national level daily. This was important in that remedial action was taken when daily coverage benchmarks were not reached. For example, if coverage was low due to a shortage of medications, it could be addressed within 24 hours, rather than at the end of the campaign as customary during routine MDA implementation.Favorable changes in the primary outcome of interest, that is, program coverage, were observed. Routinely reported program coverage  of the LF MDA program increased from 86% in 2013 to 93% in 2014 following additional mop-up activities. MR vaccination coverage remained high with 97% coverage in 2014 relative to the previous campaign in 2011 that achieved 96% coverage , but also by the accuracy of CDDs in reporting the number of people treated during a campaign. Because the health workers involved in the coordinated campaign had more extensive training than CDDs involved in vertical MDA campaigns, it is possible that the data collected during the coordinated campaign were more accurate than that reported during previous vertical MDA campaigns.The secondary outcome of interest, that is, program costs, may have increased with the coordinated campaign. Macro costing budgets were prepared at the district level, identifying cost inputs such as personnel allowances, transportation fuel costs, supplies, etc. The total budgeted cost of implementing the last round of both programs separately (measles supplementary campaigns in 2011 and MDA in 2013) was US$6.04 million, whereas in 2014, the total joint cost was US$7.19 million. This observed increase in budgeted financial costs is probably due to a number of factors: rubella vaccines were not offered jointly with measles in 2011, a wider range of age groups were provided services in 2014 relative to earlier years, Vitamin A was not offered jointly with immunizations in 2011, and there are unique start-up costs associated with launching a newly integrated program. It was not possible to compare the disaggregated expenditures of the campaigns given that itemized activity and input costing exercises were not conducted.There were a number of challenges to coordinated implementation, as identified during daily feedback meetings with districts mid-campaign and postcampaign debriefs. Because MDA was not conducted in all areas targeted by MR campaigns, the immunization program had to conduct separate immunization campaigns in 11 areas. In addition, per diems from NTD MDA campaigns are an income source for CDDs; however, few were involved in the coordinated MR-MDA campaign due to vaccine delivery training requirements. To counter any resulting loss to CDD retention, the MOH required different CDDs to be involved on different days to allow more volunteers to participate and benefit from daily per diems. In addition, many of the CDDs were engaged in community mobilization rather than intervention delivery. Accordingly a significant proportion of joint funds were proactively set aside for mobilization activities.To our knowledge, this is the first national-level program to coordinate immunization activities with MDA for LF and STH, and there were a number of lessons learned relevant to other coendemic country governments and partners. First, Gavi activities are highly amenable to multisectorial coordination as integrated community-based activities are valued by the organization. Second, integration of child survival interventions minimized redundancies by removing repeat activities  in the same target populations in the same time period. Third, leveraging the existing infrastructure by conducting activities in a mix of health-care posts including schools, health facilities, and community vaccination posts was critical in reaching all target populations. Fourth, reviewing data quality and completion at the end of each day was time consuming for supervisors but allowed for problems to be addressed immediately and rectified without delay. Most importantly, the programs found that coordinated coimplementation is a potential and often overlooked solution for increasing the coverage of community-based programs without compromising quality. This coordinated approach is also important for health systems strengthening, where cross-sector activities can be used to drive broader system improvements.The primary limitation of this work is that routine outcomes and data collection measures were used to assess intervention efficiency. With the addition of a rigorous research protocol, the intervention could have been tested using a multistage rollout scheme and counterfactual. Future iterations of this intervention will use such methods, and it is our hope that other endemic countries and partners interested in coordinated community-based activities learn from these experiences.


Cumulative sum (CUSUM) analysis can be used to continuously monitor the performance of an individual or process and detect deviations from a preset or standard level of achievement. However, no previous study has evaluated the utility of CUSUM analysis in facilitating timely environmental assessment and interventions to improve performance of linear-probe endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). The aim of this study was to evaluate the usefulness of combined CUSUM and chronological environmental analysis as a tool to improve the learning environment for EBUS-TBNA trainees.This study was an observational chart review. To determine if performance was acceptable, CUSUM analysis was used to track procedural outcomes of trainees in EBUS-TBNA. To investigate chronological changes in the learning environment, multivariate logistic regression analysis was used to compare several indices before and after time points when significant changes occurred in proficiency.P = 0.019). Other factors, including presence of an on-site cytopathologist and dose of sedatives used, were not significantly associated with duration of nonproficiency.Presence of an additional attending bronchoscopist was inversely associated with nonproficiency (odds ratio, 0.117; 95% confidence interval, 0–0.749; Combined CUSUM and chronological environmental analysis may be useful in hastening interventions that improve performance of EBUS-TBNA. Cumulative sum (CUSUM) analysis is a method of monitoring the performance of an individual or process and detect deviations from a preset or standard level of achievement , 2. It hLinear-probe endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a bronchoscopic technique that uses ultrasound to visualize and guide sampling of mediastinal and hilar lymph nodes , 4. KempThis study investigated whether CUSUM analysis could be used to monitor individual and institutional proficiency in linear EBUS-TBNA and improve the quality of the learning environment for EBUS-TBNA. CUSUM analysis was used to monitor EBUS-TBNA performance of bronchoscopists during training and investigate the relationship between change in performance and changes in the characteristics of the learning environment in the bronchoscopy suite.Linear-probe EBUS-TBNA bronchoscopy has been performed since March 2008 at our institution, the Saint Louis University Hospital. All attending bronchoscopists had more than 5 years of experience in bronchoscopy without EBUS and had received less than 1 week of EBUS-TBNA training before EBUS-TBNA was initiated at our center. We analyzed data from 131 patients evaluated from March 2008 to September 2010 by 3 bronchoscopists . All procedures utilized 22G needles.Charts and procedure notes were examined to collect information on patient demographics, EBUS-TBNA indications, the procedures , sampled lymph nodes, complications), final cytology results of transbronchial needle aspiration for each node, pathology results for mediastinoscopy, CT-guided lymph node biopsy, video-assisted thoracic surgery and thoracotomy, findings of subsequent imaging studies, and final clinical diagnosis.Information on bronchoscopy suite conditions that was available retrospectively included the name of the main attending bronchoscopist , the names of attending bronchoscopists who assisted the main bronchoscopist, the doses of sedatives and opiates used during each procedure, and the presence of cytopathologists for rapid on-site evaluation of specimens. Two bronchoscopy nurses were present for all procedures. This observational chart review was approved by the Institutional Review Board at Saint Louis University.Kemp et al. defined success on EBUS-TBNA as a true positive or true negative for malignancy, and failure as a false positive or false negative for malignancy. However, a procedure that successfully samples a lymph node but yields a false negative should not be defined as operator failure, as it represents a limitation of the EBUS-TBNA technique itself rather than a lack of operator skill. We believe that procedure failure should instead be defined as absence of lymphocytes, malignant cells, or granuloma in a specimen. In other words, a procedure is successful when the lymph node is adequately visualized and sampled, as determined by the presence of diagnostic cells or lymphocytes in the sample.The primary outcome was sampling failure or success. Each sampled lymph node was used as the unit for determining success or failure. A lymph node sampling was defined as successful if 1 or more cytology slides showed lymphocytes, granulomas, or malignant cells.s is the CUSUM score given for each success and is calculated using the equation:CUSUM analysis has been used to continuously monitor procedural outcomes of trainees, to determine if performance is acceptable . In thisThus:On CUSUM analysis, a trainee was considered “proficient” when the line on the graph descended and crossed 2 boundary lines on a downward slope. A trainee was considered “nonproficient” if the line ascended and crossed 2 boundary lines on an upward slope, which could prompt an intervention such as retraining of the operator. The assessment was considered “inconclusive” if the line remained between the 2 boundary lines. In such cases, additional attempts are necessary in order to determine competence , 7. H0 dThus, in our series:P value of <0.05 (2-tailed). STATA 12.0 software was used for all analyses.To investigate chronological changes in learning environment, multivariate logistic regression analysis was used to compare each index before and after time points when significant proficiency changes occurred. To evaluate factors associated with a worsening interval, a multivariate-adjusted logistic regression model was constructed by including the presence of additional attending bronchoscopists or on-site cytopathologists, sedative dose (midazolam dose of ≥10 mg vs a lower dose), and opiate dose (fentanyl dose of ≥300 μg vs a lower dose). For measures of association, 95% confidence intervals were computed, and statistical significance was set at a Figure P = 0.019). Other factors were not significantly associated with nonproficiency, including presence of on-site cytopathologists , use of a midazolam dose of ≥10 mg , and use of a fentanyl dose of ≥200 μg . The numbers of procedures performed by operators A and B did not significantly differ in any interval. Operator C performed fewer procedures than the other operators during intervals 1 (P < 0.016), 3  (P < 0.045), and 4 (P < 0.075).In the analysis of institutional EBUS-TBNA proficiency, we divided the study period into 4 intervals, namely, the intervals between cases 1 and 26 , between cases 27 and 51 , between cases 52 and 73 , and after case 73 . To identify factors associated with success rate, we compared indices during the worsening interval (between cases 52 and 73) with those during the other intervals. A multivariate-adjusted logistic regression model was used to analyze the effects of the presence of additional attending bronchoscopists and on-site cytopathologists and higher doses of sedatives (≥10 mg of midazolam) and opiates (≥300 microgram of fentanyl). Comparison of the worsening interval with the other intervals revealed that presence of an additional attending bronchoscopist was inversely associated with nonproficiency (odds ratio [OR], 0.117; 95% confidence interval [CI], 0–0.749; A previous study using CUSUM analysis of the EBUS-TBNA learning curve found that the learning rate varied, even among experienced bronchoscopists . In addiThe findings of this pilot study indicate that CUSUM analysis was useful in detecting deviations in bronchoscopist performance and identifying environmental factors associated with such performance. This is the first study to show that CUSUM analysis could be used to investigate the EBUS-TBNA learning environment and identify possible causes for performance declines. We believe that CUSUM analysis can hasten intervention when changes in performance levels are detected.Both individual and institutional factors affect successful performance of EBUS-TBNA. In this study, we found that presence of additional assisting attending bronchoscopists was associated with successful performance of EBUS-TBNA, which suggests that having an assisting attending bronchoscopist was associated with successful procedures during the institutional learning phase at our center. During the study period, additional attending physicians assisted in identifying target lymph nodes and needle activation. When an assisting attending physician was not present, a respiratory therapist or fellow physician assisted with the procedures. It is possible that the presence of an assisting attending physician resulted in better identification of target lymph nodes, better sampling technique, or both. Operator B exhibited the steepest learning curve, while operator A had the slowest learning curve among the operators. Further quality improvement efforts could attempt to use the present results for detailed investigation and comparison of the learning environments of these 2 operators. For example, operator B might have had greater input from other bronchoscopists. Interestingly, the presence of cytopathologists for rapid on-site evaluation in the bronchoscopy suite did not seem to affect the likelihood of a successful procedure. This finding contradicted our expectations, as we had assumed that the availability of a cytopathologist for rapid on-site evaluation would positively affect performance because lymph node sampling could then be repeated until satisfactory samples were obtained. The change in proficiency during the worsening interval did not appear to coincide with the change in the ratio of procedures performed by the bronchoscopist.We used new definitions of EBUS-TBNA success and failure. We believe that these definitions are better for determining bronchoscopic proficiency than those used by Kemp et al. , as our This study has several limitations, which are mainly the result of its retrospective design. We were able to obtain information on only a limited number of environmental factors in our bronchoscopy suite. In particular, we lacked data on the technique and performance-based factors. We also had no information on changes in bronchoscopist lifestyle that might have affected performance. Additionally, we had no way of determining the “degree of difficulty” for each attempted sample. The presence of subcentimeter lymph nodes in less accessible locations might decrease success rate, even for a moderately proficient bronchoscopist. To address these limitations and increase the feasibility of this method for quality improvement, our next investigation will be a prospective study. The variables assessed will be more comprehensive, including bronchoscopist work hours, sleep hours, technique and performance-based factors, teaching methods, location and size of lymph nodes, and factors involved in specimen processing.Combined CUSUM and environmental analysis is a promising method for monitoring and improving performance in EBUS-TBNA.


B'N Fit POWER initiative as a middle school-based comprehensive wellness program that integrates weight management programming into existing onsite preventive and clinical services. Consistent with the existing implementation science literature, we focused on both the organizational structures that facilitate communication and the development of trust among stakeholders, students, and families and the development of realistic and timely goals to implement and integrate all aspects of the program. New implementation and programming strategies were developed and tested to increase the proportion of students screened, support the linkage of students to care, and streamline the integration of program clinical and afterschool components into routine services already offered at the school. We report on our initial implementation activities using the Standards for Reporting Implementation Studies (StaRI) framework using hybrid outcomes combining the Reach element from the RE-AIM framework with a newly conceptualized Wellness Cascade.Effective obesity prevention and treatment interventions are lacking in the United States, especially for impoverished minority youths at risk for health disparities, and especially in accessible community-based settings. We describe the launch and pilot implementation evaluation of the first year of the  While 17% of 2–19-year-old children and adolescents are affected by obesity in the United States , 4. DespIntensive pediatric weight management programs featuring physical activity, nutrition, and sedentary behavior reduction counseling, parental involvement, and cultural tailoring –11 can dThe Bronx Nutrition and Fitness Initiative for Teens (B'N Fit) was developed in 2005 by the Children's Hospital at Montefiore (CHAM) in partnership with the Mosholu Montefiore Community Center (MMCC) as a 9-month weight-loss program to address health disparities and treat obesity in adolescents from a low-income minority community. B'N Fit was a hybrid approach which included comprehensive obesity evaluation and treatment plans in a hospital ambulatory care service venue combined with community-based nutrition and physical activity education. Barriers to retention and achieving obesity-related recommendations included low motivation to change behaviors and the home and community environment. Nonetheless, B'N Fit decreased the rate of weight gain and changed behaviors in adolescents with high rates of severe obesity (67%) and obesity-related comorbidities (57%) . HoweverB'N Fit POWER initiative as a school-based comprehensive program that integrates weight management into programming accessible to all students with an emphasis on strategies for sustaining such programming in a low-resource middle school setting.Translating the program to a school setting for all students was a potential solution for addressing these issues. There is an abundance of literature evaluating school-based weight management intervention effectiveness, but there is relative paucity of implementation studies addressing how programs were implemented and whether their feasibility was evaluated and the Community Preventive Task Force has found insufficiency evidence to recommend school-based obesity programs to prevent or reduce overweight and obesity among children and adolescents –28. FollB'N Fit POWER uses this framework and integrates several elements of successful intensive and school-based obesity prevention and treatment interventions by providing onsite medical care and youth-focused afterschool programming to teach and model healthy lifestyle behaviors and incorporating youth-centered outcome metrics to evaluate the program  theory to emphasize adolescent strengths and promote positive adolescent development and health behaviors that lead to a healthy weight, rather than avoidance of risks and negative behaviors [B'N Fit POWER's implementation occurred at Public School/Middle School–95 (PS/MS-95), a kindergarten through 8th grade school that has both an onsite School-Based Health Center (SBHC) operated by the Montefiore School Health Program (MSHP) and an afterschool program run by the Mosholu Montefiore Community Center (MMCC). Working with existing services provided by involved stakeholders, the program offered comprehensive wellness-focused medical assessments as part of routine SBHC clinical practice, and enhanced the MMCC afterschool group-based provision of services to provide healthy lifestyle behavior change education, cooking classes, and daily physical activity opportunities . Childhood poverty is 43%, and school absenteeism is high, as is the prevalence of obesity , 40, 41.B'N Fit POWER survey data, which include assessment of the 7 Target Behaviors, nutrition knowledge, and outcome expectancy. The 7 Target Behaviors, which were developed, following the Expert Committee Recommendations, USDA MyPlate dietary guidelines, and NHLBI sleep recommendations [Program outcome metrics were selected if they could be commonly utilized by all partners and if they could be accurate, credible, and reproducible measures of progress. Primary outcomes included the following: (1) Height and weight determinations done at the SBHC using a Scaletronix® scale as per routine clinic assessment. (2) The NYC Fitnessgram: the current measure of fitness for all NYC public school students  . Studentndations –48, are Our implementation outcome metrics employed a hybrid strategy that combined elements of the RE-AIM framework and a Wellness Adaptation of the HIV cascade. The RE-AIM approach to evaluating the public health impact of health promotion interventions is based on 5 factors: reach, efficacy, adoption, implementation, and maintenance . The undB'N Fit POWER to compare students receiving B'N Fit POWER to students who chose not to enroll in the program and receive standard of care to address the following specific aims: (1) to determine whether B'N Fit POWER is effective in improving fitness, healthy weight attainment, and 7 target behaviors; (2) to assess the impact of moving the B'N Fit program into a school setting on participant engagement; and (3) to assess the mediating pathways associated with program effects. Following an initial health screening, students voluntarily enrolled in B'N Fit POWER (Group 1) were to receive comprehensive medical assessments at the MSHP integrated with MMCC afterschool programming that incorporates a curriculum focusing on 7 Target Behaviors during weekly leadership sessions and daily physical activity. The comparison group consisting of all other students not enrolling in B'N Fit POWER (Group 2) would receive the standard of care (standard MSHP and MMCC afterschool program).To evaluate the feasibility of implementing the program and secondarily to evaluate its effectiveness, we designed a quasiexperimental trial of B'N Fit POWER survey data were conducted by a physical activity specialist and youth leaders during afterschool program physical activity and leadership sessions, respectively. Students then received printed materials supporting healthy diet and physical activity behaviors. In addition, to improve access for youths who were not in afterschool, BMIs of all students registered in the MSHP SBHC were reviewed as part of the electronic medical record (EMR) review. These students, if not already registered in the afterschool program, did not undergo the screening. Although open to all, students whose BMI ≥ 85th percentile for sex and age were actively recruited and approached about enrolling in the program during the course of routine interactions with both MMCC and MSHP staff as well as via telephone outreach by the B'N Fit Staff. Additionally, distribution of flyers in the SBHC and to MMCC settings and a family information session promoted awareness about the program at the school. Emphasis was placed on explaining the physical activity and health benefits of participating in B'N Fit POWER rather than focusing on BMI and the need for weight loss. The target enrollment was to recruit at least 85% of program participants to have a BMI ≥ 85th percentile.Using the MMCC Afterschool program DYCD database, an opt-out letter was sent home to all MMCC afterschool program participants who would be incoming middle school students in the 2016/2017 school year inviting them to participate in a health assessment in the spring of 2016. The screening consisted of the following: (1) height and weight assessments were done in the MSHP SBHC, and BMI was calculated by the PI and (2) NYC Fitnessgram and B'N Fit POWER protocol, students were invited to enroll in B'N Fit POWER if they were 11 to 14 years, going to be in the 6th–8th grade in the fall of 2016, able to register in both the MMCC afterschool program, and in the MSHP SBHC, and a parent or guardian was available in person or by phone for clinic visits. Students were excluded if they had a mental illness that would render them incapable of consenting for the research or complying with the B'N Fit POWER afterschool program protocol or had medical problems that made it unsafe for them to participate in the program. The study was approved by the Institutional Review Board. Parents signed informed consent, and HIPAA authorization and participants provided assent at their initial SBHC visit. Once enrolled in B'N Fit POWER, students underwent the 60-minute baseline SBHC-adapted B'N Fit POWER wellness assessment during the summer months. The rationale for conducting the baseline assessment over the summer was to limit the time taken out of class for the initial assessment during the school year. During the initial assessment, a brief 2-page weight history questionnaire and the 7 Target Behavior questionnaire would be filled out by the patient and entered into the EMR that is on the Epic (onsite EMR) platform [Once screened as per the platform  by the lB'N Fit POWER leadership sessions which included the B'N Fit POWER leadership curriculum, cooking class, and core physical activity education; and (2) attend at least 5 hours of physical activity programming each week. Attendance at all afterschool activities was tracked as per routine.Following their initial assessment, students participated in the MMCC afterschool program which provides afterschool programming for elementary and middle school students conducted from 3 to 6 pm daily from Monday through Friday throughout the school year. Similar to the other students in the afterschool program, who are required to attend 3 hours of Leadership each week, students enrolled in B'N Fit had the option of creating their own schedule with some minimum requirements: (1) attend three hours of B'N Fit POWER afterschool sessions was taken as per routine in the MMCC program supporting a sustainable method for tracking attendance and compliance with B'N Fit POWER leadership and physical activity requirements and supported a built-in structure for the program evaluation. Existing monthly onsite Wellness Council meetings provided a forum for discussing progress at each stage of the PDSA cycle with all stakeholders.To evaluate the implementation feasibility, we collaboratively developed a strategy to integrate program metrics into the SBHC, MMCC afterschool, and school work-flows of onsite community partners using a Plan-Do-Study-Act (PDSA) cycle that followed the school year schedule . ProgramIn the following results section, we describe the strategies used to maximize and optimize the screening for overweight and obesity, establish the feasibility of diagnosing students with overweight and obesity, facilitate enrollment and linkage to care, and program implementation. Results related to efficacy, receiving and completing therapy, and attainment of successful outcomes will be discussed elsewhere.We recruited students from the SBHC and MMCC afterschool programs. In the spring of 2016, 204 students in 5th–7th grade were registered in afterschool and 91 students completed screening during afterschool program hours, and of these, 42 (46%) met BMI criteria (BMI ≥ 85th percentile). An additional 63 students identified from the SBHC EMR review met BMI criteria. Of approximately 420 middle school students attending the school, we were able to obtain screening BMI data on 154 youths (37%), and of these, 105 met the BMI criteria of having a BMI ≥ 85th percentile. Of these students diagnosed with overweight or obesity, 55 (52%) were interested in the program  . Of thesOur process evaluation identified challenges that included the following: (1) Identifying students from the afterschool program who achieved a low screening yield (91/420 students) and recruiting via the EMR to identify that elevated BMI did not align with efforts to reduce stigma and demedicalize the program for youths not already in the afterschool program. (2) Inadequate B'N Fit staff training limited opportunities to organizing training sessions; per diem youth leader staff had time committed to other activities. (3) The questionnaire was perceived as lengthy and difficult for students and MMCC staff to understand and complete. In addition, offsite PI obtained weight and height assessments during afterschool hours (as SBHC staff were unavailable during this time), and telephone outreach by offsite B'N Fit staff were unsustainable protocols. (4) The lack of a formalized communication protocol between SBHC (who worked during the school day) and MMCC afterschool staff (who worked during afterschool hours) delayed students enrolling through MMCC getting into the SBHC and delayed students enrolling through the SBHC getting into MMCC.The process evaluation was used to develop new strategies for subsequent screenings . StakehoB'N Fit POWER program, were diagnosed and enrolled in both settings. Utilizing the schoolwide NYC Fitnessgram data to identify all middle school students with a BMI > the 85th percentile, the PI provided a list to the MMCC staff who focused on recruiting students enrolled in afterschool and the SBHC staff who focused on all others. As students enrolled for the afterschool program in the fall, MMCC staff spoke individually with students and their parents diagnosed with a BMI > 85th percentile about registering in both MMCC and SBHC for enrollment in B'N Fit POWER. The SBHC staff conducted Brief Health Assessments (BHA)  on students diagnosed with a BMI > 85th percentile and would similarly speak with students and their parents about enrollment in the program. A per diem program monitor was hired by the MMCC afterschool program in the fall of September 2017 to create a protocol to facilitate these bidirectional referrals and as of the writing of this protocol, 35 youths have enrolled in both the SBHC and afterschool program with 11 referred through the SBHC and 24 referred through the afterschool program.Conducting the screening during the school day as proposed has been approved by the IRB and is currently being initiated. A bidirectional referral system involving the SBHC and the MMCC afterschool program staff was developed to ensure that overweight or obese youths, who might not otherwise join the B'N Fit POWER, similar to the other students in the afterschool program, had the option of creating their own schedule with some minimum requirements. All students in the afterschool were assigned to leadership groups which consist of approximately 15 to 20 youths who stay together for the entire year. The structure of the MMCC afterschool program allowed for a seamless integration of the B'N Fit POWER participants into the program with other afterschool participants, particularly because there is overlap with many of the nonleadership classes and physical activity opportunities. The integration of B'N Fit POWER into the existing afterschool structure required no additional need to enter B'N Fit POWER attendance into a separate database.Of the 35 youths with IRB consent, 30 engaged in the program and attended elements of the program throughout the school year. To address stigma, youths in Challenges affecting implementation of a comprehensive weight management assessment in the busy SBHC and ensuring student engagement into the program included the following: (1) Lack of parental availability to obtain written consent during the school day resulted in research staff spending an unsustainable amount of time and effort to meet parents onsite and even offsite to ensure that written consents were completed. (2) Limited availability of students and families to undergo clinical assessments over the summer due to family vacations and lack of availability resulted in only 13 students undergoing their initial clinical assessments during the summer months. (3) The 60-minute initial visit was lengthy and difficult to implement during the fall school schedule during busy clinic schedule. (4) Lack of highly trained and specialized nutritionists onsite to support healthy lifestyle education placed the burden of nutrition education on the onsite medical provider, who often had little formal nutrition education and limited time to see patients. (5) While we had initially planned to do four additional follow-up visits throughout the year, the length of time it took to complete all initial visits due to high staff turnover and hospital-wide implementation of Epic in the fall requiring extensive offsite employee training  made this impractical to achieve.The process evaluation was used to develop new strategies for subsequent clinic visits to ensure engagement into the program . In discB'N Fit POWER into the afterschool setting included the following: (1) Lack of highly specialized and trained staff to teach the B'N Fit POWER comprehensive healthy lifestyle curriculum during leadership sessions and the need for youth leader training. (2) Importantly, the clinician designed B'N Fit POWER curriculum lessons were often lengthy and not well understood by youth leaders, who typically had a high school education and limited prior nutrition and healthy lifestyle education or experience. (3) Further, recipes contained within the B'N Fit POWER curriculum were also not well accepted by staff and youths because they used ingredients that were generally not readily available in the neighborhood surrounding the school. (4) Finally, the busy afterschool setting made it difficult for staff to receive training related to the curriculum and adapt recipes to better reflect cultural preferences and neighborhood grocery availability.The main challenges affecting the implementation of The process evaluation was used to develop new strategies to support student engagement into the program implementation for the 2017/2018 school year . With muB'N Fit POWER. We initiated protocols to support engagement into the school, piloted implementation of program components, and utilized our Wellness Cascade strategy to evaluate four successive steps of our program implementation corresponding to screening, diagnosis, enrollment, and engagement. While we have met a number of challenges related to the implementation process, we have developed strategies moving forward for (1) increasing the proportion of students screened from focusing on about a quarter of the middle school population to the entire middle school population; (2) ensuring that there is a mechanism for communicating with all students whose BMI > 85th percentile that there is healthy lifestyle programming available at their school and supporting linkage to care; and (3) supporting the feasibility of integrating clinical and afterschool components of the program into routine services offered at the school.To address health disparities in our community, we successfully engaged with a school and its onsite stakeholders and completed our first year of implementing B'N Fit POWER program was that stakeholder collaboration provided the foundation for developing B'N Fit POWER, which included components of both successful hospital-based intensive and school-based interventions. These components included comprehensive clinical services, afterschool school program with participatory/hands on skill building student activities to teach strategies for improving dietary intake, increased physical activity, and behavioral techniques  and to provide a daily dose of physical activity. B'N Fit POWER also included teacher training, providing a program for a duration of a year or longer, tailoring for cultural relevance, and involving parents as essential stakeholders [The overarching lesson learned during the pilot implementation of the eholders , 35, 36.B'N Fit POWER by focusing on collaborative decision-making approach [B'N Fit POWER programming within the school calendar and work plans, for example, shared planning and program execution, working together to develop policies and procedures that systematized the coordination of services. Finally, support for the interprofessional team via the development of a training infrastructure facilitated more efficient use of resources and a further building of trust thereby also integrating staff engagement and empowerment into the program resulting in improved service for our target audience.The B'N Fit staff has begun to earn the trust of the various stakeholders, especially with respect to “doing research” on approach , 58. We approach  and actiB'N Fit POWER, we learned that if we are a patient and focus on success with smaller goals, over time, we will empower the entire team to move forward to achieve larger goals and continue to make sustainable changes.Drawing on the widely used SMART  goal setting  approachB'N Fit POWER in the future will further increase the proportion of at risk students who have access to this program.A final lesson learned related to acknowledging student stakeholder identified barriers, namely the stigma that accompanies obesity, to program enrollment. Our prior experience in B'N Fit with provider referrals based on BMI cutoffs resulted in youths enrolling in the B'N Fit program at the urging of their family members or provider, with a majority (70%) being in either the precontemplation or contemplation stage of change related to their interest in attending the program and making lifestyle changes;  most didB'N Fit POWER to those students at the same school not in the program and who receive standard of care. The lack of the use of a RCT introduces selection bias, and the availability of overlapping programming activities introduces contamination thus affecting the robustness of the evaluation. Taking into consideration, however, the need for efficient use of resources and building stakeholder trust to prioritize a sustainable service for the youths, it has become clear that establishing the feasibility and acceptability of implementing the program and designing a realistic evaluation strategy is a necessary first step to designing an effectiveness trial for the program. While we conducted a process evaluation for engagement into care, we did not describe results related to actual number of students attending various components of the program as a measure of engagement and program compliance. Although attendance data were available, it was not readily accessible from the DYCD database, and the development of a protocol for accessing this data on a regular basis is necessary to track afterschool program attendance and compliance and is currently under development during the second year of the program implementation.Transferring the acquisition of the data from the afterschool setting to the school day setting has limitations related to the timing and accuracy of the data. Afterschool screening Fitnessgram, height and weight, and questionnaire data were obtained in April, May, and June annually, which was used for the pre- and postprogram evaluation. However, screening data are typically collected as per school protocol during physical education and health education classes from October through April. Thus, our approach for increasing the reach and efficiency for screening students does not necessarily align with a baseline and follow-up evaluation. Although the timing of the data collection conducted by the school may be viewed as a limitation, an assessment of overall school health and the impact of the interventions can be evaluated on an annual basis, and the use of this method already systematized by the school ensures sustainability of the screening process. An additional limitation relates to the use of a quasiexperimental trial to compare students receiving Moving forward the identification of individual stakeholders who will take on the role of all onsite training staff, implementation of quality assurance and quality control procedures, as well as the establishment of protocols to ensure collaboration among interprofessional teams will facilitate the clinical-community integration process. Utilization of tools for measuring the interprofessional collaboration and refinement of the Wellness Cascade strategy for measuring the impact of the collaboration will strengthen the integration process. Results related to engagement and completion of the program and attainment of successful outcomes will be reported in terms of the Wellness Cascade and further inform future implementation efforts.


Vitis species, including grapevine, produce a class of secondary metabolites called stilbenes that are important for plant disease resistance and can have positive effects on human health. Mitogen-activated protein kinase (MAPK) signaling cascades not only play key roles in plant defense responses but also contribute to stilbene biosynthesis in grapevine. MAPKKKs function at the upper level of the MAPK network and initiate signaling through this pathway. In this study, a Raf-like MAPKKK gene, VqMAPKKK38, was identified and functionally characterized from the Chinese wild grapevine V. quinquangularis accession ‘Danfeng-2’. We observed that VqMAPKKK38 transcript levels were elevated by powdery mildew infection, high salinity conditions and chilling stresses, as well as in response to treatments by the hormones salicylic acid (SA), methyl jasmonate (MeJA), ethylene (Eth) and abscisic acid (ABA). In addition, based on both transient overexpression and gene suppression of VqMAPKKK38 in grapevine leaves, we found that VqMAPKKK38 positively regulates stilbene synthase transcription and stilbene accumulation probably by mediating the activation of the transcription factor MYB14. In addition, both hydrogen peroxide (H2O2) and calcium influx activated VqMAPKKK38 expression and stilbene biosynthesis, which suggests that VqMAPKKK38 may be involved in the calcium signaling and ROS signaling pathways. For example, the mitogen-activated protein kinase (MAPK) cascade is commonly used by eukaryotes to transduce extracellular stimuli into intracellular responses.Arabidopsis thaliana showed that the MAPKKK17/18-MKK3-MPK1/2/7/14 cascade operates downstream from abscisic acid (ABA)-induced stress signaling6 and plays an important role in ABA-modulated leaf senescence.7 The AIK1-MKK5-MPK6 module was shown to be activated by ABA and to regulate ABA responses, including root development and stomatal behavior.8 Furthermore, two MAPK cascades, MEKK1-MKK1/2-MPK4 and MEKK1-MKK4/5-MPK3/6, have been shown to play a role in flagellin-induced signal transmission,9 while the CTR1-MKK9-MPK3/6 cascade is involved in ethylene-regulated signaling.10 In addition, in tobacco, the two modules, MAPKKKα-MEK2-SIPK and NPK1-MEK1/NQK1-NTF6/NRK1, contribute to pathogen defense and plant cytokinesis,11–13 and tomato (Solanum lycopersicum) MAPKKKα-MKK2/MKK4-MPK2/MPK3 is a component of the Pto-mediated effector triggered immunity (ETI) pathway.14Several three-kinase modules have been functionally characterized in plants. Recent studies in A. thaliana, while the grapevine (Vitis vinifera) genome contains 14 MAPKs, five MAPKKs and 62 MAPKKKs.15–17 The MAPKKKs of a given species show enhanced sequence diversity compared to members of the MAPKK or MAPK families.18 On the basis of the sequence in the conserved kinase domain, the MAPKKK family in higher plants has been classified into three clades: the MEKK-like subfamily has a conserved signature (G(T/S)Px(W/Y/F)MAPEV); the ZIK subfamily contains a GTPEFMAPE(L/V)Y sequence, and the Raf-like subfamily has a specific GTxx(W/Y)MAPE signature.19 MEKK1 is the most thoroughly studied MAPKKK in A. thaliana and is known to be involved in multiple stress responses, including flagellin signaling,9 wounding,20 and cold and salt stimuli.21 Two well-known Raf-like MAPKKKs, CTR1 (Constitutive Triple Response 1) and EDR1 (Enhanced Disease Resistance 1), function as negative regulators of the ethylene 22 and pathogen defense responses,23 respectively. In cotton (Gossypium hirsutum), GhRaf19 has been shown to enhance the tolerance to chilling stress but to decrease drought and salt stress resistance,24 while GhMKK5 is significantly triggered by salicylic acid (SA) and induces the transcription of pathogenesis-related (PR) genes.25 Recently, A. thaliana AIK1 and MAPKKK17/18 were identified as key regulators of ABA signal transduction,8 but relatively little information is available regarding MAPKKKs in grapevine. A genome-wide analysis of MAPK cascades in V. vinifera revealed 21 MEKKs, 12 ZIKs and 29 Rafs among the 62 MAPKKKs.16 Expression profiles of 45 grapevine MAPKKK genes following exposure to various stress conditions suggested that these candidate MAPKKK genes may participate in responses to powdery mildew, drought, SA, ethylene (Eth) and hydrogen peroxide (H2O2).26 However, a more detailed characterization of individual MAPKKKs is required to better define their biological and physiological roles.Whole-genome sequencing of numerous plant species has generated a valuable resource in the form of an inventory of MAPK families from those species. For instance, there are 20 MAPKs, 10 MAPKKs and at least 80 MAPKKKs in Vitis,27 and Chinese wild grapevines provide valuable gene pools with a number of resistance factors that are thought to be important for pathogen immunity. The Chinese wild grapevine species V. quinquangularis, particularly the accession ‘Danfeng-2’, has attracted attention because of its high level of resistance to pathogen infection and its high content of stilbene-type phytoalexins.28–30 Stilbenes are secondary metabolites that help promote resistance to a diverse range of pathogens, and they also have pharmacological value.31–33 The accumulation of stilbenes can be induced by factors such as pathogen infection,32 ozone damage,34 wounding,35 salt stress36 and UV irradiation.37 Perhaps the most widely studied stilbene, resveratrol, is synthesized by a side branch of the well-characterized phenylalanine/polymalonate pathway where the final step is catalyzed by stilbene synthase (STS).38 The R2R3-MYB-type transcription factors MYB14 and MYB15 are thought to regulate the biosynthesis of stilbenes by up-regulating STS transcription.39 It has also been suggested that MAPK cascades are required for stilbene biosynthesis, and a specific MAPK cascade inhibitor (PD98059) can efficiently suppress the activation of STS by flagellin 22 (flg22), a bacterial elicitor harpin,40 or by SA.41 PD98059 can also block the induction of MYB14 by flg22 in grapevine cell suspension cultures.42China is a major biodiversity center for V. quinquangularis. We focused on VqMAPKKK38, a Raf-like subfamily member that is responsive to various stressors and examined its role in signal transduction and stilbene biosynthesis. We present functional studies involving transient overexpression and suppression using RNAi in grapevine leaves and propose a mechanism by which VqMAPKKK38 promotes stilbene biosynthesis, as well as how its involvement in signaling is triggered by calcium and reactive oxygen species (ROS).In this study, we sought to identify genes in the MAPK pathway that are involved in the regulation of stilbene accumulation in V. quinquangularis accession Danfeng-2 was cultivated in the grape germplasm resources garden at the Northwest A&F University, Yangling, Shaanxi, China. Samples of young leaves (the second to fourth leaf from the tip), mature leaves (dark-green leaves collected when berries were enlarging), stems (the woody stem), inflorescences (with single flowers in dense groups), young berries  and mature berries  were collected for expression analyses.Chinese wild Erysiphe necator) inoculation was carried out as described previously,43 and inoculated leaves were collected at 0, 12, 24, 48, 72, 96 and 120 h post-inoculation. For abiotic stress treatments, young leaves were either wounded with sterile scissors, sprayed with aqueous 250 mM NaCl, or exposed to low (4 °C) or high temperature (37 °C) for 0, 0.5, 1, 2, 6 or 10 h. Treatment with the signaling molecules was carried out by spraying the young leaves with one of the following solutions: 100 μM SA, 100 μM MeJA, 100 μM Eth, 100 μM ABA, 5 mM CaCl2 or 1% H2O2 (w/v). The leaves were harvested at 0, 0.5, 1, 2, 6 and 10 h post-treatment. The leaves were pretreated with 20 μM GdCl3 for 30 min before 5 mM CaCl2 was administered to study the roles of Ca2+ and ROS. Dimethylthiourea (DMTU), an H2O2 scavenger, was used to pretreat the leaves for 30 min before 1% H2O2 was administered. GdCl3 or DMTU was also added without a subsequent treatment to assess the effect of the inhibitors on the leaves. Leaves treated with the solvent in which the elicitors were dissolved served as negative controls. Three samples were treated in each treatment, and each treatment was repeated three times.Fresh young leaves were collected and subjected to different forms of stress. Powdery mildew  and EF1γ (GenBank accession no. AF176496) as internal standards. Each experiment was carried out with three biological replicates, and each biological sample was analyzed in three technical replicates.Total RNA was extracted from leaves with the EZNA Total RNA kit II (Omega Bio-Tek) and reverse-transcribed into complementary DNA (cDNA) using Prime Script Reverse Transcriptase (TaKaRa) following the manufacturer’s instructions. Semi-quantitative reverse transcription-PCR was performed with the following parameters: 94 °C for 3 min followed by 30 cycles of 94 °C for 30 s, 58 °C for 30 s and 72 °C for 1 min. The amplified products were separated on a 1% agarose gel and visualized with ethidium bromide. Quantitative real-time PCR (qRT-PCR) was carried out as described previously.VqMAPKKK38 cDNA (see V. vinifera cv. ‘Pinot Noir’ clone P40024.45 The VqMAPKKK38 gene is located on the fifth chromosome according to a BLAST search in the Genoscope Genome Browser (http://www.genoscope.cns.fr/blat-server/cgi-bin/vitis/webBlat). DNAMAN software was used to carry out amino-acid sequence alignment analyses of four Raf proteins, including VqMAPKKK38, VviRaf23 (Gene ID: VIT05s0094g01080), AtRaf23 (Gene ID: At2G31800) and BnaRaf23 (GenBank: AHL77715.1). The phylogenetic tree was constructed using MEGA 7 software to analyze the evolutionary relationship between these proteins.The specific primers used to isolate the full-length cDNA see  were desVqMAPKKK38) was inserted into the pART-CAM-S vector46 after digestion with SacI and ClaI. To create the silencing construct, a fragment from 545 to 1405 bp of VqMAPKKK38 was isolated as sense and antisense sequences. Both sense and antisense sequences were cloned into pKANNIBAL,47 and then into pART27 48 after restriction digestion by NotI. Each sequenced plasmid was transformed separately into Agrobacterium tumefaciens strain GV3101 using electroporation and then introduced into 8-week-old V. quinquangularis leaves by Agrobacterium-mediated transient expression as described previously.44To generate the over-expression construct, the amplified product  with a detection wavelength of 306 nm. The mobile phase was 0.5% (v/v) formic acid and acetonitrile (ACN). The mobile phase elution procedure was carried out as follows: 0–8 min, 10–18% ACN; 8–10 min, 18% ACN; 10–15 min, 18–25% ACN; 15–18 min, 25–35% ACN; 18–25 min, 35% ACN; 25–30 min, 35–70% ACN. The sample peaks and standard chemical peaks were calculated using trans-resveratrol and trans-piceid  as external standards. We obtained the cis-piceid standard by the photoisomerization of trans-piceid under UV irradiation. The 50% ethanol solution containing 400 μM of trans-piceid was irradiated at 366 nm for 3 h, and the resulting cis-piceid standard was stored in total darkness.37Stilbene levels in the transgenic leaves were measured as described previouslyVqMAPKKK38 was amplified by PCR with specific primers using the cDNA derived from leaves of V. quinquangularis accession Danfeng-2. The PCR-amplified fragment was 1,419 bp in length and predicted to encode a 472-amino-acid protein with a catalytic kinase domain from residue Gln203 to Leu450 and a Ser/Thr kinase active site  revealed 100% identity, so the fragment was named VqMAPKKK38 and considered to be a member of the Raf-like subfamily. A phylogenetic analysis with other MAPKKK proteins and alignment with other Raf-like protein sequences further supported the classification of VqMAPKKK38 (The open reading frame (ORF) of MAPKKK38 .VqMAPKKK38 transcripts were expressed in all of the organs tested, including young leaves, mature leaves, stems, inflorescences, young berries and mature berries. Since the highest levels were observed in young leaves , the expression of VqMAPKKK38 remained at basal levels until 72-hour post inoculation (hpi), and then increased at 96 and 120 hpi.  or suppress via RNA interference (RNAi) VqMAPKKK38 expression in grapevine leaves. pART-CAM-S and pART27 without a target gene served as negative controls. Both semi-quantitative reverse transcription-PCR and qRT-PCR analysis confirmed that VqMAPKKK38 was successfully overexpressed or silenced (M SA treatment by high-performance liquid chromatography (HPLC). As indicated in trans-resveratrol and trans-piceid levels increased after VqMAPKKK38 was overexpressed. In addition, after SA treatment, the VqMAPKKK38 overexpressor accumulated significantly higher levels of these compounds than the control. This suggested that VqMAPKKK38 promotes stilbene accumulation in grapevine. A transient silencing assay further confirmed this hypothesis, since RNAi-VqMAPKKK38 leaves exposed to the SA treatment contained much less trans-resveratrol and trans-piceid than the control leaves. Glucoside cis-piceid was also detected in all overexpressing/silenced leaves but showed the same levels as those observed in the controls.Our previous studies of grapevine suspension culture cells showed that MAPK signaling is necessary for the activation of silenced . We measVqMAPKKK38 overexpression was linked to the activation of STS, the expression of several VqSTS genes was determined. qRT-PCR data showed that the expression of the VqSTS genes was significantly induced in OE-VqMAPKKK38 leaves, especially after SA treatment  and sampled at 0.5, 1, 2, 6 and 10 h post-treatment. qRT-PCR analysis revealed that VqMAPKKK38 expression was significantly induced by exposure to either CaCl2 or H2O2  on the activation of VqMAPKKK38 by H2O2. Compared to the solvent controls, the accumulation of VqMAPKKK38 transcripts significantly increased after adding either CaCl2 or H2O2 for 2 h , and VqMAPKKK38 was predicted to play a role in the regulation of stilbene accumulation (unpublished). In this study, we investigated the involvement of VqMAPKKK38 in stilbene biosynthesis and signal transduction.The resistance to pathogen attack of Chinese wild 39 As previously reported, MAPK signaling can mediate the activation of STS transcription.41 Consistent with this, Duan et al.42 confirmed that MAPK cascades are essential in the activation of grapevine MYB14.42 In this study, we show that VqMAPKKK38 overexpression in grapevine leaves can significantly enhance SA-induced stilbene accumulation, accompanied by the strong induction of STS and MYB14 expression. We also observed that the accumulation of stilbenes was almost abolished in RNAi-VqMAPKKK38 transgenic leaves, showing that VqMAPKKK38 is required for stilbene biosynthesis and that a MAPKKK38-based cascade is likely to be involved in this process.In grapevine, the biosynthesis of resveratrol is catalyzed by the key enzyme STS that is specifically activated by MYB14.56 The levels of Ca2+ and ROS  are maintained at low levels in plant cells under normal physiological conditions. However, environmental signals can trigger rapid calcium fluxes and increases in the levels of ROS.58 Either of these responses can activate a number of molecular processes, including MAPK signaling.54 In this study, we found that the exposure of young grapevine leaves to either exogenous Ca2+ or H2O2 increased VqMAPKKK38 expression and that this effect was the most pronounced after 1 and 2 h, respectively. Since the influx of Ca2+ and the generation of ROS can directly induce each other,52 we used GdCl3 and DMTU to generate additional evidence for the induction of VqMAPKKK38 by calcium and H2O2. Taken together, our results demonstrate that VqMAPKKK38 functions downstream of both the Ca2+ and the ROS signaling pathways and that it responds most rapidly to Ca2+-mediated signaling.The rapid influx of calcium and the generation of ROS are among the earliest cellular responses to biotic and abiotic stresses.60 The signaling events are often shared among different induction processes, but different elicitors can generate different types of stilbene output, mainly due to the relative sequence of calcium influx and an apoplastic burst.40 Since we found that both calcium and the ROS signaling operate upstream of VqMAPKKK38, we examined the effects of calcium and ROS on STSs transcription and stilbene biosynthesis. The observation that both the expression of STS genes and the accumulation of stilbenes were elevated by Ca2+/H2O2 and could also be inhibited by Ca2+/H2O2 blockers suggested the involvement of Ca2+ and ROS signaling in the regulation of stilbene biosynthesis.The regulation of stilbene accumulation by signaling events has been widely studied in grapevine suspension cell lines. A number of pathogen elicitors can induce stilbene accumulation, including flg22 and harpin, as can hormones such as SA and JA. This inducibility requires an influx of calcium, an oxidative burst and MAPK cascades.V. rupestris suspension cells.60 In this study, we found that VqMAPKKK38 is involved in the ROS signaling pathway, raising the possibility that endogenous stilbenes may in turn regulate the upstream acting VqMAPKKK38. We therefore measured the accumulation of VqMAPKKK38 transcripts in VqSTS6-, VqSTS23-, or VqSTS32-overexpressing transgenic grapevine plants both before and after powdery mildew treatment. However, since we observed no difference in the expression of VqMAPKKK38 between transgenic and non-transgenic plants . qRT-PCR analysis revealed that VviMAPKKK38 expression is strongly induced by Erysiphe necator, SA, ethylene and H2O2,26 which is consistent with our report of the expression of VqMAPKKK38 being induced in response to biotic (E. necator) and abiotic  stresses, as well as defense-related hormone  treatments. Since the expression profile may be an indicator of gene function, we hypothesize that VqMAPKKK38 is a stress-inducible gene that is recruited for effective defense against a range of stressors. The evidence from the over- and RNAi-expression experiments with grapevine leaves indicates that VqMAPKKK38 is involved in a stilbene-type phytoalexin biosynthesis by mediating the transcription of STS genes and MYB14. Future studies will focus on identification of the VqMAPKKK38-mediated expression module and on the use of this gene for molecular breeding of grapevine.In conclusion, this study provides new insights into the biological roles of a grapevine MAPKKK gene,


Program synthesis is the mechanized construction of software, dubbed ‘self-writing code’. Synthesis tools relieve the programmer from thinking about how the problem is to be solved; instead, the programmer only provides a description of what is to be achieved. Given a specification of what the program should do, the synthesizer generates an implementation that provably satisfies this specification. From a logical point of view, a program synthesizer is a solver for second-order existential logic. Owing to the expressiveness of second-order logic, program synthesis has an extremely broad range of applications. We survey some of these applications as well as recent trends in the algorithms that solve the program synthesis problem. In particular, we focus on an approach that has raised the profile of program synthesis and ushered in a generation of new synthesis tools, namely counter-example-guided inductive synthesis (CEGIS). We provide a description of the CEGIS architecture, followed by recent algorithmic improvements. We conjecture that the capacity of program synthesis engines will see further step change, in a manner that is transparent to the applications, which will open up an even broader range of use-cases.This article is part of the themed issue ‘Verified trustworthy software systems’. Yet, there is a high barrier to entry into programming such devices. The traditional workflow for programming a computer to solve a given problem is illustrated in Automated program synthesis has the potential to change the way general-purpose computational devices are used by enabling non-expert users to solve problems in an automated fashion without designing and implementing a new algorithm. Essentially, program synthesis generates an implementation of the program that satisfies a given correctness specification. Consequently, it enables the workflow illustrated in Notably, the program synthesis-based approach has the additional advantage that subsequent changes to the problem specification can easily be integrated into the final implementation. Such changes are transparent to the program synthesizer and only require adapting the description of the expected result.P1 ranges over functions, each Q is either ∃ or ∀, x ranges over ground terms and σ is a quantifier-free formula. A program synthesizer finds a satisfying model for formulae of this kind. Such a satisfying model must map each of the second-order variables P to some function of the appropriate type and arity. Program synthesis generates programs that compute these functions.Foundational research in the area of program synthesis has been exceptionally fruitful, beginning with Alonzo Church's work on the Circuit Synthesis Problem in the Sixties . AlgoritThe research community has spent the last decades improving first the techniques for propositional satisfiability (SAT) and later for satisfiability modulo theories (SMT), and as a result, recent methods are able to solve instances of industrial interest. We now have the momentum to advance the two tightly related areas of second-order solving and program synthesis.This paper. In this paper, we will focus on one of the recent directions that greatly raised the profile of program synthesis and ushered in a generation of new synthesis tools, namely counter-example-guided inductive synthesis (CEGIS). We provide an introduction to CEGIS-based techniques and then identify open challenges and discuss some promising directions.The paper is organized as follows. We start by describing a few applications where program synthesis is valuable. We then introduce the CEGIS architecture as well as some of its most successful applications. After discussing the limitations of the state-of-the-art techniques, we suggest some possible directions for future improvements.2.We give exemplars of applications of program synthesis. Program synthesis has direct applications for various classes of users, from software developers to end-users that are not expert programmers: enabling people with no programming background to develop utility programs, helping regular programmers to automatically improve their code and even teaching.(a)During the development process, very frequently situations arise where long-term code quality is traded for short-term gain. Under the pressure of deadlines, developers find quick solutions for fixing bugs or adding support for new functionality which result in code that is too complex, bloated by duplication and hard to understand. This leads to what is known as technical debt, a metaphor introduced to indicate ‘not quite right code which we postpone making it right’ ,5. In orBesides code refactoring, software developers can use program synthesis to verify the correctness of their code. Program synthesis has been used to check termination/non-termination of programs, as well as to prove program safety and find bugs –10.(b)digital controllers; for example, cars, TVs and even toasters contain fully functional CPUs and are controlled by software. Implementing a digital controller for such a system is a difficult task as it requires understanding the subtle interaction between the continuous behaviour of the physical machine and the discrete behaviour of the controller. Program synthesis can be used by control engineers to automatically produce correct implementations of digital controllers. Examples of applying synthesis techniques to such controllers are  in L's  termination.To prove  termination of UT] as the input specification (where G and T are replaced correspondingly), then the general-purpose program synthesizer in . If, as shown below, we augment the previous example with an initial state and an assertion, then the program synthesizer in  in L was non-terminating.For illustration, we will look again at program termination. Recall from §4c that we reduce the termination of a simple loop with no nesting to the satisfiability of the formula  in definition 5.1: N is reachable from an initial state x0, implies the guard and all its successors are still in the recurrence set  and ∃N, x0·∀x, x′·ψ .Now, we can construct two formulae: one that is satisfiable if and only if loop R·∀x, x′·φ)∨).We can combine these: ∨ψ.Which simplifies to: ∃L either terminates or does not terminate, this formula must have a satisfying model. Thus, either R or N must exist.Since We have used the same approach to build a safety prover/bug finder: a program is either correct as witnessed by a safety invariant or it has a bug shown by an error trace . In both(ii)As mentioned in §4, current CEGIS-based techniques constrain the instruction set and correspondingly the solution space to be searched by supplementing the logical specification with a syntactic template that limits the space of allowed implementations. However, there are two disadvantages to this approach: (i) the applicability of such synthesis techniques is limited to areas where the user knows in advance how the expected solution looks like and (ii) the instruction set is fixed for the whole problem, although certain sub-problems might require different instruction sets.operation depends on member variable suffixSize of class Spec. This is known as an unnecessary dependency and can be removed without affecting any of the functionality through the refactoring given in operation depends only on the public methods of class Spec.For illustration, let us consider that we are using program synthesis for program refactoring (details of program refactoring can be found in §2) and, in particular, let us look at the program in Spec. Note that this will also impact the methods that the synthesizer can call, which, for large applications has the potential to seriously reduce the size of the solution space.When using program synthesis to automatically generate this refactoring, we would want the considered instruction set to be constrained to instructions that return an integer and do not directly access any member variables of class However, we do not want the user to provide any specialized templates/instruction sets. Given that the same tool will be used for different refactorings in different parts of the code that might work with different types, we cannot expect the user to provide help for each individual scenario. The solution is using a dynamic instruction set that automatically adapts during the synthesis process based on context information. For the current example, we use the type information to restrict the instruction set such that the result computed by the refactored code is an integer.While the introduction of dynamic instruction sets can be viewed as an engineering enhancement, we believe it can have a huge impact on the performance as well as the ease of use of program synthesizers.(iii)While the previous two directions were related to the size of the solution space, in this section, we discuss the actual search strategy and in particular a technique we found critical for the performance of the program synthesizer described in §4c. Remember that the target language in this work is the Parametrizing the Program length (l). The first parameter we introduce is program length, denoted by l. At each iteration we synthesize programs of length exactly l. We start with l = 1 and increment l whenever we determine that no program of length l can satisfy the specification. When we do successfully synthesize a program, we are guaranteed that it is of minimal length because we have previously established that no shorter program is correct.— Word width (w). An word width, that is, the number of bits in each internal register and immediate constant.— Number of constants (c). Instructions in l is at most l. By minimizing the number of constants appearing in a program, we are able to use a particularly efficient program encoding that speeds up the synthesis procedure substantially.— We now adapt the CEGIS loop as illustrated in Adjusting the search parameters. The key to our automation approach is to come up with a sensible way in which to adjust the l was too small, or the number of allowed constants c was. If c < l, we just increment c and try another round of synthesis, but allowing ourselves an extra program constant. If c = l, there is no point in increasing c any further. This is because no minimal c > l, for if it did there would have to be at least one instruction with two constant operands. This instruction could be removed (at the expense of adding its result as a constant), contradicting the assumed minimality of the program. So if c = l, we set c to 0 and increment l, before attempting synthesis again.After each round of inductive generalization, we may need to adjust the parameters. The logic for these adjustments is given as a tree in validate in validate succeeds but validate general fails in If the inductive generalization succeeds but the first verification fails , we need some way of deriving n-bit wide numbers from k-bit ones. We have several strategies for this and just try each in turn. Our strategies are shown in BV denotes an n-bit wide bitvector holding the value v and b·c means the concatenation of bitvectors b and c. For example, the first rule says that if we have the 8-bit number with value 8, and we want to extend it to some 32-bit number, we would try the 32-bit number with value 32. These six rules are all heuristics that we have found to be fairly effective in practice.The only wrinkle here is that we will sometimes synthesize a program containing constants. If we have synthesized a program with (iv)L as in §4c with initial states Init and assertion A. Similarly to §4c, we prove that L terminates by finding a ranking function, and that it is safe by finding a safety invariant. Correspondingly, we need to synthesize two programs, one computing the ranking function and one computing the safety invariant. The full specification is given in definition 5.2  and, in particular, for proving total correctness of a program, i.e. proving that the program always terminates without any assertion violations. For this purpose, we consider the specification for the same loop tion 5.2 , where RI is a safety invariant and (ii) a counter-example disproving that R is a ranking function. This ensures that the inductive generalization component receives sufficient information at each iteration to refine both synthesized programs, I and R.Given that synthesizing multiple programs makes the solution space grow exponentially, we have to come up with heuristics that facilitate concurrent synthesis of multiple programs. One such heuristic is described in  and consThe different types of counter-examples play an important role in the genetic programming backend (described in §3), which considers these counter-examples in its selection and crossover operators. Namely, candidate programs that satisfy the problem specification for inputs corresponding to distinct sets of counter-examples have a higher probability of selection as crossover partners in order to produce solutions that satisfy the specification for all possible inputs. This is preferable over fitness values based solely on the number of inputs for which the candidate is correct, since it avoids local minima where candidates may be correct for a multitude of inputs of one particular kind. In our experiments, we found that this choice of selection and crossover operators had considerably improved the performance of the inductive generalization phase.(v)The counter-examples provided by the verification oracle are used as the inputs of the inductive generalization engine. These counter-examples direct the inductive generalization process and, consequently, dictate how fast the CEGIS loop converges with a solution. The number of necessary counter-examples is related to the notion of teaching dimension from the learning theory. Informally, the teaching dimension of a concept class is the minimum number of instances a teacher must reveal to uniquely identify any target concept chosen from the class .Our aim is to obtain a final solution in as few iterations as possible, i.e. we want to minimize the difference between the number of inputs required by the inductive generalization to find a solution and the teaching dimension. While Goldman & Kearns  showed tBehavioural inductive synthesis. Existent techniques using genetic programming as an inductive generalization strategy conventionally evaluate candidate programs using scalar performance measures that capture the number of passed or failed tests. While this is a natural objective measure of a program's performance, it does not make use of more detailed information on the program's behavioural characteristics. Thus, in order to drive the search process more efficiently, we suggest employing notions from behavioural program synthesis, which argues that programs are complex combinatorial structures that exhibit complex input–output behaviour that cannot be effectively reflected by a single scalar objective [bjective .Counter-example generalization. Whenever the candidate solution found in the inductive generalization phase is not a solution for the whole problem , we need strategies for generalizing the counter-examples returned by the validation oracle in order to prune the search space as much as possible. One of the obvious candidate strategies for this is interpolation, which has been used in SAT-based model checking [checking .Statistical fault localization. Another technique that is worth investigating for its abilities to improve the inductive generalization strategy comes from statistical fault localization [lization . This ha(b)CEGIS-based tools make heavy use of SAT/SMT solvers in the inductive generalization and validation phases in order to generate test inputs and find candidate solutions, respectively. Consequently, the solving process tends to be the most time-consuming part of the whole CEGIS process. In this section, we focus on ways of reducing the time taken by the solving process.(i)One direction we are currently investigating is exploiting the incremental solving support offered by modern SAT/SMT solvers . IncremeP·∀x ∈ inputs·σ. Then, if we assume this to be the formula checked in round n of the CEGIS loop, the formula in round n + 1 isi is the additional counter-example found in the validation phase of round n. These constraints can be rewritten asRecall from §3 that the formula whose satisfiability is checked by the inductive generalization phase is ∃n + 1 are identical with those generated in round n plus an extra conjunct. The search strategy that can directly employ incremental solving in order to take advantage of this similarity is the BMC backend. We believe that this has the potential to greatly improve performance.Note that the constraints generated in round (ii)While in the previous section we discussed a way of providing better solver support, in this section, we focus on simplifying the constraints that get sent to the solver.For illustration, let us consider again using program synthesis in order to refactor code, and, in particular, we refer to our work in , where wNearly every modern Java application constructs and processes collections. A key algorithmic pattern when using collections is iteration over the contents of the collection. We distinguish external from internal iteration. To enable external iteration, a Collection provides the means to enumerate its elements by implementing Iterable. Clients that use an external iterator must advance the traversal and request the next element explicitly from the iterator. The alternative to external iteration is internal iteration, where instead of controlling the iteration, the client passes an operation to perform to an internal iteration procedure, which applies that operation to the elements in the collection based on the algorithm it implements. In order to enable internal iteration, Java SE 8 introduces a new abstraction called Stream that lets users process data in a declarative way. The Stream package provides implementations of common internal iteration algorithms such as foreach, find and sort using optimized iteration orders and even concurrency where applicable. This enables users to leverage multicore architectures transparently without having to write multithread code.We are interested in refactoring Java code handling collections to use Streams. For this purpose, the specification provided to the program synthesizer must check that the original and the refactored code are observationally equivalent. The challenge is that, while the actual code that gets refactored is generally not very large, the observational equivalence check may need to consider much larger units of code.removeNeg that removes the negative values in the list received as argument, which we later call for the list data. Now, let us assume that we want to refactor removeNeg, which currently uses external iteration to use streams. The question is which lines of code do we consider for the equivalence check? Is it just lines 3–5 that actually iterate over the collection, the whole removeNeg method or the whole code in data contains only positive values, applying removeNeg does not have any effect. Thus, for this particular calling context, we could refactor the body of removeNeg to a NO-OP. While this refactoring is correct for the code given in For illustration, let us look at the example in In order to simplify the equivalence check and consequently, the constraints to be solved by the validation oracle, we decided to synthesize general refactorings that are correct independent of their context. This enables the equivalence checking procedure to only consider the actual code being refactored (lines 3–5 in the current example) and completely ignore the rest.For this purpose, we over-approximate the context of the code to be refactored by nondeterministically picking the initial configuration . For the current example, this means that we nondeterministically pick the contents of the list l. This over-approximates the context in the sense that it may require us to consider more initial configurations than those reachable at the start of the actual user code to be refactored. Consequently, when checking equivalence, we only need to consider the variables (and collections) that are accessed by the exact code to the refactored .p that is not directly used by the code to be refactored Code, are the following:p points to a collection that is modified by Code. As the refactoring is going to perform an equivalent transformation in-place, the refactoring will be transparent to p.(1) p is an iterator over a collection accessed by Code. Then, if Code modifies the collection, so will the refactored code, which will result in p being invalidated in both scenarios. Contrary, if Code does not modify the collection, neither will the refactored code, and p will not be affected in either one of the cases.(2) While our decision to only consider general refactorings drastically reduced the time taken by the solving process, there were certain aspects that we had to consider, with the main one being aliasing: are any side-effects due to aliasing that we are not considering? The answer is no, our approach is safe for pointer variables. The reason is that the only two potential aliasing scenarios involving a pointer variable removeNeg in p points to some list and we create an alias P′ of P:Next, we illustrate scenario 1 by considering again method removeNeg is:At a first glance, a potential refactoring for lines 3–5 in P points to is correct, the list pointed by P′ is not updated. Thus, after the call to premoveNeg,  will correctly point to the filtered list, whereas P′ will continue pointing to the old unfiltered list. To avoid such situations, we perform refactorings of code that mutates collections in-place. Thus, a correct refactoring for method removeNeg is:However, this is incorrect when using the refactored function in the calling context mentioned above: While the list copy of l. After performing the filtering on copy, we use forEachOrdered, provided by the Stream API, to add each element of the temporary stream back to the list pointed to by l (in the order encountered in the stream). Thus, we are not creating a new list with a new reference, but using the original one, which makes the refactoring transparent to the rest of the program, regardless of potential aliases.Here, we first create a 6.In this paper, we discussed one of the recent directions in program synthesis, namely counter-example guided inductive synthesis (CEGIS). While program synthesis has the advantage of generality by providing a unified solution to a very large class of problems, the downside is that it may be challenging for program synthesis-based tools to match the performance of their special-purpose counterparts. After looking at ways in which current CEGIS-based approaches tackle this performance issue, we discussed some other potential directions to follow up on. These directions are based on our experience with CEGIS and our conjecture is that further investigating them will help reduce the performance penalty specific to program synthesis in a manner that is transparent to the user and does not restrict the class of program synthesis applications.