Active consideration of effective medications to treat alcohol use disorder (AUD) is a consensus standard of care, yet knowledge and use of these medications are very low across diverse settings. This study evaluated the overall effectiveness a multifaceted academic detailing program to address this persistent quality problem in the US Veterans Health Administration (VHA), as well as the context and process factors that explained variation in effectiveness across sites.An interrupted time series design, analyzed with mixed-effects segmented logistic regression, was used to evaluate changes in level and rate of change in the monthly percent of patients with a clinically documented AUD who received naltrexone, acamprosate, disulfiram, or topiramate. Using data from a 20 month post-implementation period, intervention sites (n = 37) were compared to their own 16 month pre-implementation performance and separately to the rest of VHA.From immediately pre-intervention to the end of the observation period, the percent of patients in the intervention sites with AUD who received medication increased over 3.4 % in absolute terms and 68 % in relative terms . This change was significant compared to the pre-implementation period in the intervention sites and secular trends in control sites. Sites with lower pre-implementation adoption, more person hours of detailing, but fewer people detailed, had larger immediate increases in medication receipt after implementation. The average number of detailing encounters per person was associated with steeper increases in slope over time.This study found empirical support for a multifaceted quality improvement strategy aimed at increasing access to and utilization of pharmacotherapy for AUD. Future studies should focus on determining how to enhance the programs effects, especially in non-responsive locations. Both psychosocial and pharmacological treatments for alcohol use disorder  have been found to be effective in reducing symptoms and improving functioning in diverse patient populations –5. In thSeveral medications are US Federal Drug Administration (FDA)-approved for the treatment of AUD, and/or have support of effectiveness from high-quality meta-analysis, namely naltrexone, acamprosate, disulfiram, and topiramate. These medications can be prescribed and managed in diverse clinical settings –3, allowNot only is the overall rate of medication receipt low for patients with AUD in VHA, there is substantial facility-level variability , 15. TheTo address this substantial and persistent quality gap, VHA’s Office of Patient Care Services funded the Academic Detailing for Mental Health Initiatives Program that developed and executed campaigns to improve implementation of pharmacological treatment for several mental health and addictive disorders, including tobacco dependence, schizophrenia, depression, posttraumatic stress disorder, and most recently, and the focus of this study, AUD. In 2013, this quality improvement program sent clinical pharmacy specialists (“academic detailers”) to clinical settings within two western VHA networks. The academic detailers strove to educate, motivate, and enable key health care providers to identify and address the spectrum of hazardous alcohol use, especially to facilitate more active consideration of pharmacological treatment options for AUD. The effectiveness of the AUD campaign of the Academic Detailing Program, and the context and process factors that might be associated with its effectiveness, have not been rigorously evaluated. Thus, the goal of the current study is to evaluate this multifaceted implementation strategy as means to increase utilization of pharmacotherapy for AUD, as well as to provide data that might inform and enhance the ongoing expansion of academic detailing programming across VHA.The primary goal of the Academic Detailing AUD Campaign was to increase the proportion of patients with AUD who were receiving treatment with naltrexone, acamprosate, disulfiram, or topiramate. Simple academic detailing interventions have been shown to have small but significant effects on prescribing practices . HoweverTable Academic detailers were recruited and selected with preference for previous training experience in mental health, board certification as pharmacotherapy specialists, post graduate residency training, and strong communication skills assessed during interview process. Due to the clinical service content of the detailing encounters, candidates were sought who had provided direct patient care as part of their previous professional experience with prescribing authority under a scope of practice. The Department of Veteran’s Affairs then contracted Alosa Foundation, a nonprofit organization that develops and implements academic detailing programs to improve prescribing, to provide a basic skills course in academic detailing to the six clinical pharmacists who were selected for VA facilities in California, Nevada and the Pacific Islands. In addition to Academic Detailing Basic Skills workshop, Motivational Interviewing training, adapted for use within the context of a provider outreach visit as opposed to a clinical treatment with a patient population, was another important aspect of detailer training. Campaign specific training on AUD was conducted through virtual seminars and one 3-day face-to-face conference, in which subject matter experts assisted in structuring the AUD campaign timeline and targeted goals.From April to December 2013, the AUD campaign of the Academic Detailing Program was implemented in two western VA networks, including over 37 medical centers and community-based outpatient clinics. Detailing sessions included predominantly in-person one-on-one sessions, in-person group sessions, and educational in-service sessions, with additional follow-up conducted by email, teleconference, and telephone. A wide variety of staff received detailing encounters including psychologists, psychiatrists, nurses, social workers, clinical pharmacists, primary physicians, clinical managers and other administrators.We evaluated the overall effectiveness of the program using a multi-site, interrupted time series design. The main outcome for the evaluation was the monthly proportion of patients with a clinical encounter in which AUD was documented who filled a prescription for one of the targeted medications: naltrexone, acamprosate, disulfiram, or topiramate. Intervention sites had 16 months of baseline pharmacy data prior to their first detailing contact, and were observed for 20 months thereafter. Mixed-effects segmented logistic regression  was usedWe then calculated and described facility-level variability in effectiveness, operationalized as the immediate pre-post implementation gaps and changes in slope. Then, we examined the context and process factors  that were associated with this variability and for which data were available from administrative sources or from Academic Detailing Program encounter logs. The main facility-level moderator examined was the pre-implementation rate of receipt of medications for AUD, calculated from VHA pharmacy data. Candidate mediators included total person-hours of detailing, total number of health care providers contacted by the program, and number of unique detailing sessions, all sourced from program encounter logs. We did not examine the effects of detailing encounter type  or provider type on effectiveness due to substantial within-site variability on these factors. All candidate predictors were entered into the mixed-effect regression model described above, restricted to sites with detailing encounters, and interacted with the immediate gap and change in slope.For simplicity of interpretation, we converted the mixed-effects segmented logistic regression estimates into percents and graphically represented them in Fig. To check that these changes did not just mimic secular trends in the rest of VHA, we fitted a model that explicitly compared the four parameters in the intervention sites to the same parameters in all other VA sites. As represented by the black line in Fig. In addition to these overall effects, significant variability among the 37 sites in the effects of the Academic Detailing Program were found, with some sites having much bigger or smaller gaps and changes in slope than the overall average. Figure We then examined moderators and mediators that might explain variation in gaps and/or changes in slopes, as indicated by significant interaction terms in the mixed-effects segmented logistic regression. Descriptive statistics for these variables are presented in Table In this study, we evaluated a multifaceted academic detailing program aimed at addressing a serious and persistent problem in healthcare quality—under-utilization of medications in the treatment of AUD. Despite strong evidence of clinical effectiveness of these medications, clinical and quality managers have thus far lacked evidence-based quality improvement strategies to increase access and utilization. Using a rigorous quasi-experimental design, we found that implementation of the Academic Detailing Program for AUD was associated with an overall immediate gap up in medication receipt as well a significant increase in the slope of adoption over time. From pre-intervention to the end of the follow-up period, the rate of medication receipt in the intervention sites increased approximately 3.4 % in absolute terms and 68 % in relative terms . Although the intervention sites overall had lower levels of utilization at baseline compared to the rest of VHA, levels of utilization in the intervention sites were higher by the end of the observation period. Extrapolating this effect to the entire VHA would mean that over 11,000 additional patients with AUD would receive these effective medications. To our knowledge, this is the first quality improvement strategy focused on increasing access to AUD medications to be implemented on a large scale and shown to be effective overall.Although the Academic Detailing Program increased prescribing of medications for treatment of AUD overall, the effect varied substantially across the intervention sites. In many sites, there was no improvement or even reductions in prescription fills. In an effort to explain some of this variability, we found that initially low performing facilities tended to improve the most. This result is encouraging and instructive. Although one might argue that those with lower baseline performance were more likely to improve due to regression to the mean , it is cSeveral questions are left unanswered by this investigation. First, there were many aspects of the detailing encounters for which data were unavailable, including prior knowledge level of the target clinician as well as skill and experience of the detailer. Many facilities received detailing encounters from multiple detailers making the direct examination of detailer effects difficult. Also, one aspect of detailer skill and potential impact is the ability to secure initial meetings with facility staff. We had data on completed detailing encounters but not encounter requests. These are important limitations that should be addressed in future implementations and evaluations. Second, data on use of the informatics tools was not analyzed. Qualitative interviews with detailers and detailed clinicians might have helped explain why sites varied in response to the Academic Detailing Program, and may have provided perspectives and data that could be used to refine the program. Third, the analyses were based on filled prescriptions not on written prescriptions, for which no data were available. We expect the impact of this limitation to be minimal because we have no reason to believe that reliance on outside pharmacies or the proportion of unfilled prescriptions would be different in the pre and post implementation periods. Fourth, the campaign also sought to improve rates of screening, brief intervention, and referral to specialty treatment, data for which was unavailable for evaluation. Fifth, sustainment of effects after the program stopped was not examined. Sixth, data on cost of the intervention was not collected, precluding any budget impact or other economic analyses. Finally, long-term sustainment or emergence of effects after the detailing encounters stop were not evaluated but should be investigated in future analyses.Even with these limitations and caveats, this study is perhaps the first to find empirical support for a multifaceted quality improvement strategy aimed at increasing access to and utilization of effective medications in the treatment of AUD. Following the conclusion to this western VHA regional pilot for Academic Detailing for Mental Health Initiatives, in March 2015 VHA leadership requested the 21 regional networks to develop academic detailing programming to impact two other key medication safety quality improvement programs in VHA, the Opioid Safety Initiative and the Psychotropic Drug Safety Initiative. Future studies should rigorously evaluate the program’s effects on other quality improvement targets, focus on determining how to enhance the program effects, especially in sites where effects are weak. It is possible that less expensive and less labor intensive strategies would be adequate in some locations while even more intensive strategies are needed elsewhere. Learning how to identify the site characteristics that might be matched to the most efficient quality improvement strategy is the overarching goal of this line of research.


Ground-motion prediction equations that are used to predict acceleration values are generally developed for a 5% viscous damping ratio. Special structures and structures that use damping devices may have damping ratios other than the conventionally used ratio of 5%. Hence, for such structures, the intensity measures predicted by conventional ground-motion prediction equations need to be converted to a particular level of damping using a damping reduction factor (DRF). DRF is the ratio of the spectral ordinate at 5% damping to the ordinate at a defined level of damping. In this study, the DRF has been defined using the spectral ordinate of pseudo-spectral acceleration and the effect of factors such as the duration of ground motion, magnitude, hypocenter distance, site classification, damping, and period are studied. In this study, an attempt has also been made to develop an empirical model for the DRF that is specifically applicable to the Himalayan region in terms of these predictor variables. A recorded earthquake with 410 horizontal motions was used, with data characterized by magnitudes ranging from 4 to 7.8 and hypocentral distances up to 520 km. The damping was varied from 0.5–30% and the period range considered was 0.02 to 10 s. The proposed model was compared and found to coincide well with models in the existing literature. The proposed model can be used to compute the DRF at any specific period, for any given value of predictor variables. The damping ratio depends on the structure, type of material, and ground shaking, among other characteristics . In real regions . In some regions ,14, the Lin et al.  have revA majority of the international codes have used the DRF to account for supplemental damping in the response of buildings. Newmark and Hall  is one oThere are two approaches to estimate the DRF: (1) to develop prediction equations that directly estimate spectral ordinates at various levels of damping, and (2) to develop scaling factors to convert the ordinates to other levels of damping. Most of the existing studies have used predictor variables of time and damping ratio, although a few researchers ,19 have The Indian seismic code IS 1893 (2002) has adopted the second aforementioned method, and has provided the average response acceleration coefficient for a critical damping of 5% for rock, medium soil, and soft soil. A set of multiplication factors has been specified as a function of the damping ratio alone in order to scale the response parameters. The DRFs found in the Indian seismic design codes may be based on limited recorded data from India, and hence, does not necessarily represent the Indian scenario or knowledge database. The objective of this study, therefore, is to derive DRFs for the Himalayan region based on PSA, and to study the influence of parameters like damping, period, duration of ground motion, moment magnitude, hypocentral distance, and site classification. The DRF at β% damping used in this study is derived as follows:An empirical model has also been developed for the prediction of the DRF in terms of these variables. In total, 410 horizontal accelerograms with a peak ground acceleration greater than 0.01 g, obtained from the Program for Excellence in Strong Motion Studies (PESMOS) at the Indian Institute of Technology, Roorkee has been used in this study. The data range across site classes A, B, and C with magnitudes ranging from 4 to 7.8, and hypocentral distances up to 500 km. The site classification set in Mittal et al.  has beenw > 6. w, hypocentral distance R (km), and site classification S. Moment magnitude has been used since it tied the magnitude directly to earthquake source processes, and does not saturate for magnitudes greater than 6. It is also directly proportional to the area of the fault plane that ruptured multiplied by the average displacement along the rupture plane [The recorded earthquake ground-motion data were obtained from the PESMOS at the Department of Earthquake Engineering, Indian Institute of Technology, Roorkee, India. The Department of Earthquake Engineering operates a network of about 300 strong motion accelerographs in the northern and northeastern parts of the country, which covers the entire Himalayan region. The network covers part of Himachal Pradesh, Punjab, Haryana, Uttaranchal, Uttar Pradesh, Bihar, West Bengal, Sikkim, and northeastern India. These stations are located in seismic zones V and IV, and include some heavily populated cities within seismic zone III as per the Indian seismic code IS:1893 2002), all within the Himalayan region . The Him02, all wre plane . Path paThe variables that might influence the DRF, and the trends observed between the variables and the DRF, are explained. The findings are then used to identify the potential predictor variables for the correlation. As mentioned earlier, damping ratio and spectral period are the principal variables, and these can be understood from the definition of DRF and the relation between PSA and period. The influence of damping and period on the DRF can be observed in The values of DRF have been plotted as a function of period at various levels of damping in a5–95% at damping ratios of 2, 20%, and a period of 1 s. An increasing trend is observed when the duration for damping is 2%, whereas a decreasing trend is observed at higher damping. The effect of duration on the DRF cannot be used in practice since duration is not of importance in the current design scenario. Hence, the influence of duration on DRF was captured by the inclusion of magnitude, distance, and site class in the current model. A strong positive correlation between duration and magnitude, and a moderate correlation with distance, is expected [Many researchers ,16,19 haexpected .A significant dependence between the DRF obtained from the PSA and the moment magnitude M can be observed in μ represents the mean of ln(DSF) and is a function of damping ratio β, spectral period T, source, site and path parameters such as moment magnitude, hypocentral distance, and site classification; b is the vector of regression coefficients.In this study, the general form of the equation to be used is as follows,M and R at specified T and damping.The DRF model was systematically built by trying various functions of the key predictor variables influencing the damping scaling. First, DRF was calculated for the R < 520 km records. For each combination of the 22 specified periods and 11 damping ratios, the data were analyzed and the dependence of the DRF on potential predictor variables  was investigated. Visual inspection of the plotted data revealed a strong logarithmic dependence of the DRF on duration and a strong possibly linear or quadratic dependence on the magnitude (stronger at longer periods), a weaker but noticeable dependence on distance, and negligible dependence on soil conditions. In order to capture the dependence on duration while including magnitude and distance in the model, ln (DRF) was regressed on the predictor variables For each combination of damping and period, the factors were regressed with magnitude, hypocentral distance, and site classification. The primary regression coefficients were then regressed with the damping ratio to find the final coefficients.ξ is the percentage damping ratio and bi, i = 0, 1….11 are the regression coefficients, which are listed in lnDRF) using least square analysis, which minimizes the sum of the squares of the errors made in the results. Based on that non-dependency of error on the predictor values, this method calculates the unbiased estimators. Further, based on the analysis, the error term (Є) was calculated, and is shown in Multiple linear step regression was carried out, and the final model was of the form:Since the proposed model is empirical, a close agreement between the model and the data should be expected. To visually validate the model against the data, plots similar to Lin et al.  emphasizSimilar models that used source, site parameters, damping, and period are selected for comparison with the proposed model. The model developed by Rezeian et al.  was compThere are no other studies that have considered both the effect of magnitude and distance in a model. Therefore, for the sake of comparison, models that have included the damping ratio and period have been selected and presented as supporting information. In addition to direct comparison of proposed model with recent study, proposed models are compared with models that have included the damping ratio and period and presented as Supporting Information. Newmark and Hall  is one oIdriss  has defiS2 FigTherefore, based on the results of a regression analysis and comparison, it can be concluded that the proposed models are capable of predicting DRF values for the Himalayan region with high accuracy. Given the magnitude, distance, and the site class of a region, the reduction factor can be calculated for a particular value of damping at any specific period. The DRF derived from the displacement response (or pseudo-acceleration response) can be used for the design of buildings with damping devices.In the present study, 206 horizontal acceleration time histories that were recorded until 2014 were used to develop an empirical relationship to estimate the DRF. The proposed relationship can be used to convert the PSA values at 5% damping to the PSA values of other damping values. The effect of parameters like moment magnitude, hypocentral distance, site classification, duration of ground motion, damping, and period was studied. Duration was found to be a parameter that strongly affects the reduction factor; however, since its usage is not ideal, the dependence is captured through the inclusion of magnitude, distance, and site classification, all of which affect duration. Regression analysis was carried out on reduction factors at 22 specific periods and 11 damping ratios. The dependence on magnitude, distance, and site classification was captured using a linear term and a logarithmic term. The proposed empirical equation was compared with computed values from the data, and with the existing literature. The model was found to have good predictive performance, and hence could be used for the prediction of the DRF in buildings with added dissipation devices. The model is applicable for damping ratios from 0.5 to 30%, magnitudes from 4 to 7.8, and distances less than 520 km.http://strongmotioncenter.org/vdc (last accessed August 2015). From the 192 ground-motion recordings, 124 were collected from the strong motion instrumentation network of Indian Institute of Technology, Roorkee that covers the Indian Himalayan range from Jammu and Kashmir to Meghalaya. This data is freely available and downloaded from the website http://www.pesmos.in (last accessed August 2015).The processed ground-motion parameters for earthquakes before 2005 were obtained from the Strong-motion Virtual Data Center—which was developed by the University of California, Santa Barbara—and incorporated as a part of the Centre for Engineering Strong Motion Data at S1 FigThe solid lines represent the proposed model and dotted lines denote the model developed in Newmark and Hall .(PDF)Click here for additional data file.S2 FigThe solid lines represent the proposed model, while the dotted lines represent the model developed by Idriss .(PDF)Click here for additional data file.


In Europe, 1.7 million persons of working age are diagnosed with cancer each year. During or after treatment, cancer survivors (CSs) are vulnerable for job loss, and many CSs struggle with return to work (RTW). When offering RTW interventions to CSs, it is important to conduct a process evaluation to assess such factors as the population reached and implementation problems. Recently, we developed an innovative RTW program, tailored specifically to the needs of CSs with job loss in the Netherlands. The aim of this study was to evaluate the likelihood of theory and implementation failure, as well as to evaluate procedures for recruitment, execution and implementation of the tailored RTW program for CSs with job loss.Six components were evaluated in the RTW program: Recruitment, Reach, Dosage, Implementation, Satisfaction, and Experienced Barriers. Data were provided by logbooks and questionnaires from participating CSs, occupational health care (OHC) professionals, and re-integration coaches and job hunting officers who delivered the RTW program. SPSS and Excel were used to conduct the analyses.85 CSs received the tailored RTW program. Their mean age was 47.9 years (SD 8.5). The majority were female (72 %), married (52 %), and of Dutch nationality (91 %). The program reached 88.2 % of the target population and 52 % of participants who started the program received the adequate dosage. The program implementation score was 45.9 %. Participants’ mean overall program duration remained within the protocol boundaries. Re-integration coaches were more satisfied with the program than job hunting officers or OHC professionals. Likewise, participants were more satisfied with the program delivery by the re-integration coaches than with the delivery by the job hunting officers. Reported barriers within the RTW program were a lack of communication, high program intensity and short program duration, and, with regard to the job hunting officers, a lack of experience with cancer-related RTW problems.Participants, OHC professionals, re-integration coaches and job hunting officers generally had positive experiences with the innovative tailored RTW program. Facilitating communication between the delivering parties, and engaging usual care during program delivery, could be key elements to improved program implementation.NTR3562, registered 07-08-2012.Dutch Trial Register, registration number  Each year, 3.45 million people are diagnosed with cancer in the European Union . Of thesA limited number of RTW interventions have been developed specifically for CSs , 11. A rThe first step to improving study procedures and program delivery is to evaluate the procedures of ongoing studies and programs, by conducting a process evaluation . ProcessRecently, a tailored RTW program was delivered to sick-listed CSs with job loss in the Netherlands . PreviouThis is one of the first studies in which an intervention for workers with job loss was developed, in cooperation with multiple organizations, and the occupational health services from the SSA. No previous studies of this kind were aimed at sick-listed workers due to cancer –23. TherThis study concerns a process evaluation of the recruitment procedures, execution and implementation of a tailored RTW program for CSs with job loss in the Netherlands, which was offered within an experimental setting. The full study procedures and design of the RTW program have been published previously . In summThe tailored RTW program consisted of three parts: an introductory interview, a “Preparation for RTW” part, and a “RTW” part. The tailored RTW program encouraged participants to engage in developing a consensus-based RTW plan, to actively participate in coaching sessions to prepare for RTW, and to explore opportunities for RTW in therapeutic work or paid employment. The tailored aspect of the program was embedded in participants’ ability to select various routes in the program, which matched the individually required level of RTW support. The program is presented in Fig. For all participants, the tailored RTW program started with an introductory interview with a re-integration coach. In this interview, the coach and participant identified obstacles and possibilities for RTW. Drawing on this assessment, they chose a suitable route through the intervention program, by discussing if the participant was ready to “RTW” or if “Preparation for RTW” was needed. In addition, the participant’s expectations and present RTW activities were discussed. Participants who were already actively applying for jobs started with the “RTW” part of the program , the coach and participant decided that the participant would start with the “Preparation for RTW” part (Route 2 in the program). A re-integration agency, specialized in RTW coaching for CSs, delivered this part of the program . The coaches from this re-integration agency also conducted the introductory interviews at the start of the program. In general, these coaches were mostly former cancer patients who had experience with cancer survivorship and job loss. They had participated in training and education to become a RTW coach for cancer survivors. The meetings for the “Preparation for RTW” part of the program were held at the participant’s home or at a nearby office of the re-integration agency.All program meetings between participants and re-integration coaches or job hunting agency personnel were face-to-face meetings. The program did not employ any peer-group activities. Alongside the “Preparation for RTW” part of the program, it was possible for participants to be referred to specialist physical or psychological care. This could happen if the participant and coaches concluded that the participant needed specialist care for such problems as extreme fatigue, psychological stress or trauma. Within the intervention program, the re-integration coaches registered when they referred participants to specialist care, but the content and duration of this care was not monitored as this was part of regular usual care within the Dutch healthcare system. The specific content of the program routes are described extensively below. The full content of the tailored RTW program was previously published as part of the study protocol .The coach and participant decided that the participant was ready to RTW. The coach contacted the researchers, who randomly assigned the participant to one of the two job hunting agencies (by using randomisation software). The participant and the selected agency held a meeting to explore job opportunities. According to the study protocol, the agency was expected to find at least two suitable jobs that matched the participants’ work profile, and their wishes for RTW. Further, these jobs could be either therapeutic or paid work, and had to be offered for at least three months. The protocol further dictated that the job hunting agencies should arrange for two job options within four weeks after the first meeting with the participant. If the agency was unable to meet these requirements, the second job hunting agency involved in this study joined the search for jobs.The coach and participant decided that the participant was not yet ready to RTW yet, and that (s)he needed preparation for RTW. In the following weeks, the participant and coach created a work profile, based on the participant’s wishes and needs for return to work. Also, the participant’s working experience and capabilities were taken into account. Alongside the development of the work profile, the re-integration coach held four to five individual coaching sessions with the participant. These sessions were scheduled to last for 1–1.5 h and were aimed at themes that the participant and the coach selected together. Within the protocol, eight predetermined themes were available, with the additional option to deviate from these themes if necessary. Examples of predetermined coaching themes were: “fatigue and managing energy levels and RTW”, “communication about cancer at work” and “stress, fluctuations in work ability and managing work, private life and recovery”. When the work profile and coaching sessions were completed, the participant and coach re-evaluated whether the participant was ready to RTW (Route 2A or Route 2B).Route 2A: The coach and participant decided that it was time to RTW. The coach contacted the researchers, after which a job hunting officer was randomly assigned to the case of the participant. This route is similar to Route 1 (described above).Route 2B: The coach and participant decided that the participant needed more preparation for RTW. The coach and participant held four to five additional coaching sessions focused on preferred themes. This process is similar to the process described in Route 2, with the exception that the work profile was completed at this stage. After participating in additional coaching sessions, the coach and participant re-evaluated if the participant was ready to RTW (Route 3A or Route 3B).Route 3A: The coach and participant decided that the participant was ready to RTW. The coach contacted the researchers, after which a job hunting agency was randomly assigned to the participant’s case. This route is similar to Route 1 (described above).Route 3B: It could be that the coach and the participant concluded that the participant was not ready to RTW after receiving the full “Preparation for RTW” part of the program. In that case, the intervention program was terminated and the participant’s case was referred to usual care for follow-up.The maximum duration of the tailored RTW program was 7 months. The maximum duration of the “Preparation for RTW” part was 3 months; the maximum duration of the “RTW” part was also 3 months, and 1 month delay was calculated to allow for unforeseen events, such as illnesses or holidays. After participants completed the tailored RTW program, the researchers sent process evaluation questionnaires to the teams of OHC professionals, the coaches and the job hunting agencies. For participants, process evaluation questionnaires were sent 6 months after the start of their RTW program. Additionally, the researchers, as well as the re-integration coaches and job hunting officers who delivered the RTW program, kept logbooks on their activities and progress during program delivery.The target group for the tailored RTW program were CSs who were 18–60 years of age, had completed intensive cancer treatment, and were registered at the SSA as recipients of sickness or disability benefits due to cancer. CSs had to be sick-listed for a period of minimum 12 months and maximum 36 months. The 12-month cut-off value was chosen in accordance with the Dutch social security legislation, in which eligibility for benefits has to be re-evaluated after 12 months of sick leave. The limit of 36 months was chosen because data past 36 months of sick leave were not accessible at the SSA. The complete inclusion and exclusion criteria for participation in the RCT were previously published as part of the study protocol [Recruitment‘Recruitment’ was defined as the result of all procedures to recruit eligible CSs for participation in the tailored RTW program. At the level of the participants, data regarding response were obtained from the research logbooks and displayed in a participant recruitment diagram. Recruitment was not evaluated at the organizational level , as the involvement of these organizations depended on the participant’s route through the intervention program.Reach‘Reach’ was defined as the proportion of the target group that participated in the tailored RTW program. Participation in the program was defined as participating at least in the introductory interview, because this step was crucial as a starting point for each participant’s program. These data were provided by the research and intervention logbooks from the researchers and re-integration coaches.Dosage‘Dosage’ was defined as the proportion of participants who started the program, who received an adequate dose of the tailored RTW program. Adequate dose was defined as having received a job offer through the services of the job hunting agency during the program. Participants who did not meet with the job hunting agency, because they had already found a job or decided to found their own company during the “preparation for RTW” part of the program, were also considered to have received an adequate dose.Further, the number of times each step in the RTW program was delivered, was described. Also, the mean overall duration of the RTW program, and range of duration between participants, was calculated. Additionally, it was reported if, and which, themes were discussed in the coaching sessions of the RTW program, and if the coaches referred participants to specialist physical or psychological rehabilitation care, alongside the RTW program. These data were provided by the intervention logbooks from the re-integration coaches and job hunting officers.Implementation‘Implementation’ was defined as a composite score of the results of the components ‘reach’ and ‘dosage’, and was calculated by multiplying these proportions.Satisfaction‘Satisfaction’ was defined as the extent to which the content, intensity, duration and delivery of the tailored RTW program was satisfactory according to the participants, OHC professionals, coaches and job hunting officers. Overall satisfaction and experience scores were calculated for each group. These data were captured by the process evaluation questionnaires. The OHC professionals, coaches and job hunting officers received one process evaluation questionnaire for each participant that was under their care.Experienced Barriers within the programThis component summarized the experienced barriers with regard to participation in, or execution of, the tailored RTW program, as experienced by participants, OHC professionals, coaches and job hunting officers. These data were provided by the logbooks, process evaluation questionnaires, and by minutes from meetings between the researchers, the SSA, re-integration coaches and job hunting officers.This process evaluation consisted of assessing six components within the tailored RTW program: Recruitment, Reach, Dosage, Implementation, Satisfaction, and Experienced Barriers. Relevant literature from Steckler and Linnan , as wellThe characteristics of participants in the tailored RTW program are described in Table In total, 2757 potential participants were invited to participate in the study, of whom 786 were interested in participating and returned the screening questionnaire. Among these, 312 did not meet the study inclusion criteria. The researchers contacted the remaining 474 potential participants by telephone. Of those, 291 did not continue the inclusion process due to various reasons: for example, 86 CSs did not meet the inclusion criteria for sickness or disability benefits and duration of sick leave, 58 CSs did not expect to be ready to RTW within six months, and 45 CSs were already involved or signed up for another re-integration or rehabilitation program. Also, 20 CSs had already returned to work or were in the process of RTW, and 35 CSs could not be reached. Of the 183 CSs who fulfilled the inclusion criteria and received a baseline questionnaire, 171 returned the questionnaire and were included in the study. After inclusion, none of the participants’ GPs reported a medical contra-indication for participation in the program. Of the 171 CSs in the study, 85 participants were randomly assigned to the tailored RTW program  in the program, such as social, financial or psychological problems. Additionally, one person reportedly quit the program because (s)he did not agree with the approach taken by the re-integration coach. Afterwards, the coach reported that, in her perception, the participant had some personal problems which interfered with the participant’s ability to follow the program according to schedule. Attempts of the coach to stimulate the participant could have backfired, resulting in the fact that this particular participant quit the program.To calculate the dosage, we assessed if jobs were offered to the participants by one or both of the job hunting agencies, which was the case for 30 participants, and if participants had already found employment, or decided to become an entrepreneur, before being transferred to a job hunting officer, which was true for nine participants. Ultimately 39 participants received the adequate dosage of the tailored RTW program (52 % of the 75 participants who started the program).For all 54 participants who participated in the program steps “Preparation for RTW ”, one or more themes were selected for the coaching sessions. Eight predefined themes were available during these steps in the program. The frequency of the chosen themes is presented in Table Of the 54 participants in the program steps “Preparation for RTW ”, 27 participants were referred to rehabilitation care alongside the RTW program. Among these, nine were referred to physical care, nine to psychological care, and another nine participants were referred to both physical and psychological care. Participants receiving professional physical care were generally referred to (oncology) physical therapy (13 participants). Participants receiving psychological help were generally referred to a psychologist (12 participants).The protocol of the tailored RTW program allowed for a maximum program duration of 7 months, or 210 days. That is, 90 days were available for “Preparation for RTW ”, another 90 days were available for “RTW”, and 30 days were calculated for potential delays during the program. In practice, the mean duration of the tailored RTW program across participants was 156 days (SD 90), which was within time according to protocol. It should be noted that the overall duration also included participants who did not continue to the “RTW” part of the program. For participants who participated in both “Preparation for RTW ”, and “RTW”, i.e., the most extensive route in the program, the overall duration was 199 days (SD 84), which was still within protocol time.Looking at the separate parts of the program, the mean duration of “Preparation for RTW ” was within the protocol deadline including delay, i.e., 117 days (SD 80). However, there was a large range in duration between the participants (7–373 days). The mean duration of “RTW” was 123 days (SD 59), which was longer than the protocol allowed, even with delay. Again, the range in duration of the RTW part was large (29–302 days).The implementation score was calculated by multiplying the percentage of the target group that was reached for the tailored RTW program, i.e., 88.2 %, with the percentage of participants who started the program, who received an adequate dosage of the program, i.e., 52 %. Therefore, the implementation score of the tailored RTW program was 45.9 %.Satisfaction was based on the process evaluation questionnaires. Of the 85 participants assigned to the RTW program, 68 participants returned the process evaluation questionnaire. Of those, five did not start participation in the RTW program. Their answers were therefore removed from the analysis.For participants, satisfaction and experiences with the RTW program are presented in Table Overall, the re-integration coaches reported the highest levels of satisfaction , and the highest overall experience score regarding the execution of the tailored RTW program  Table . On the Participants, re-integration coaches and job hunting officers reported that one of the main barriers within the RTW program was that the perceived duration of the program was too short, and that the perceived program intensity was too high. Specifically, some participants felt they needed more time to prepare for RTW, and they thought the “Preparation for RTW” part should be extended. Another important obstacle in the delivery of the program was the lack of clear communication between OHC professionals, re-integration coaches and job hunting officers. Specific barriers for communication among these parties were the large number of professionals involved and the fact that most communication went through digital channels . Also, the high workload of OHC professionals, and that a lot of participants’ files were frequently re-distributed within the SSA, e.g., when a new OHC team was assigned, or when the participant moved to a different district, contributed to these problems. As a result, some of the OHC professionals were not informed about the RTW program in an accurately or timely manner, and did not deliver the necessary documents to the re-integration coach. This delayed the start and progress of the RTW program for most of the participants.Another obstacle was that, in the experience of participants and re-integration coaches, the job hunting officers had little experience with the health problems and the RTW process of CSs. As a result, the job hunting officers were not always able to intervene adequately in case of cancer-related problems. Further, participants and re-integration coaches reported specific problems in the delivery of the program by the job hunting officers, i.e., a lack of initiative and a lack of interest in the participants’ situation. To illustrate, it was reported during two meetings with the research team that the job hunting officers sometimes did not respond in time or at all to transfer requests by the re-integration coaches. Also, necessary documents from the job hunting officers were generally delivered late or not at all, and the documents provided to them by the re-integration coaches were often not used. The researchers requested that the job hunting officers use the documents from the re-integration agencies and to deliver their documents in time. However, there seemed to be a lack of motivation in the job hunting officers to do so. This led to delays in the delivery of the program. Further, at least two participants reported they had actually quit the program because they felt discouraged by the job hunting officers. For example, one participant mentioned that a job hunting officer had said that it would be very hard to find a job for him/her. A number of participants mentioned that they felt that the job hunting officers were only operating from a commercial perspective. As a result of these actions and the lack of clear communication, the re-integration coaches mentioned during the meetings that they had lost confidence in the “RTW” part of the program.In contrast, many participants were very enthusiastic about program delivery by the re-integration coaches, and several participants gave them praise, such as that they felt they owed their new job to them. In two cases however, participants reported that the coach was not able to answer their questions, and that the program delivery was not person-oriented enough.The main results of this study are that the tailored RTW program reached 88.2 % of the target population, that more than half of the participants who started the program (52 %) received the adequate dosage, and that the implementation score was 45.9 %. The overall mean duration of the RTW program stayed within protocol boundaries; however, there was large variation between the participants in the program duration. Re-integration coaches reported the highest levels of satisfaction and positive experience with the program, compared to the job hunting officers or OHC professionals. Likewise, participants were more satisfied with the program delivery by the re-integration coaches than with the delivery by the job hunting officers. High program intensity and short program duration, as well as communication and cooperation problems, hindered the delivery of the RTW program.This was the first study to offer an innovative RTW program tailored to the needs of a specific subgroup of CSs, that is, CSs with job loss. In the Netherlands, previous studies were conducted that are, to some extent, comparable to the present study. For example, several RTW programs have been offered to sick-listed Dutch workers with distress, low back pain and musculoskeletal disorders , 27–29. In the present study, the implementation score (45.9 %), as well as the number of participants who received the adequate dosage (52 %), was only moderately good. This was mainly the result of the fact that only 49.4 % of the participants was referred to the job hunting agencies. It should be mentioned that we did not set a specific goal for the program implementation score or the dosage, but it was implicitly expected that a higher implementation score and better dosage would be reached. Theory and/or implementation failure may explain these results. With regard to theory failure, it could be that the RTW program was only suited for a particular subgroup of the target group. That is, it could be that mainly relatively healthy CSs with job loss successfully participated in the RTW program . The facFurther, we should consider that the present study may have suffered from implementation failure. For example, the duration of the RTW program varied greatly between participants, and several barriers for program delivery and participation were reported. An important barrier was the lack of clear communication between OHC professional, re-integration coaches and job hunting officers. A previous study by Anema et al. reported that cooperation and sharing information between OHC professionals and GPs can be problematic . PerhapsFurthermore, there were specific indicators that the RTW program was not well implemented with the job hunting officers, i.e., their program delivery was delayed, there had been cooperation problems, and reportedly they had little specific knowledge with regard to cancer-related health problems. Specifically job hunting officers’ lack of sensitivity or experience with regard to cancer-related problems could explain the lower levels of satisfaction with their program delivery. In comparison, in the study by Tamminga et al., a RTW program was delivered by nurses with cancer expertise. In that study, participants reported high satisfaction scores . It coulAn alternative explanation for the lack of transfers to the “RTW” part of the program could be that the “Preparation for RTW” part was quite successful. That is, the “Preparation for RTW” part was generally so well received by participants and professionals that some participants had already found employment and did not need the assistance of the job hunting officers anymore. This indicates that the “RTW” part of the program was in fact redundant for some participants.The key strength of this study is that data were obtained through various sources  in order to gain a full perspective on the process of delivering the RTW program. There are however several limitations to this study that should be mentioned. First of all only 63 out of 85 participants completed the process evaluation questionnaires. Further, in a few cases, data were missing on certain questions or dates, and the datasets for calculating satisfaction and experience scores were relatively small, especially for the job hunting officers, in which case the scores were based on 48 questionnaires. Additionally, we did not measure fidelity as a measure of the intervention program’s quality in this study. Because of the nature of the program, i.e., participants could choose their own route through the program, it was quite impossible to compare participants’ overall routes throughout the program. Therefore, we offered a comparison and evaluation of the program elements only, i.e., “Preparation for RTW” part and “RTW” part, instead of offering an overall interpretation on the program’s fidelity.These factors limit the generalizability of our results. Also, the intervention logbooks from the job hunting officers were generally delivered past schedule, which could have introduced recall bias in the data. The qualitative results with regard to experienced program barriers should be interpreted cautiously, as they were based on individual comments. In order to gain a more comprehensive perspective of the participants’ experiences, a qualitative study inquiring about specific barriers in the program, could be conducted in the future. Also, the tailored RTW program was offered in cooperation with the Dutch SSA. Therefore, our results should be interpreted in the context of the Dutch social security system: the fact that the program delivery and implementation relied heavily on the social security context, could mean that efforts to replicate this study in another social or political context may be only partly successful.This study demonstrated that, despite delays and several barriers in the program, CSs with job loss were generally satisfied with a RTW program tailored to their needs. The “Preparation for RTW” part of the program was the most appreciated element in the program. In order to prevent similar obstacles for program delivery in future studies, we would recommend that researchers introduce a pilot-phase in their studies, during which potential implementation problems can be identified and resolved . As therIn general, the participants, re-integration coaches, job hunting officers and OHC professionals had positive experiences with the innovative tailored RTW program. This program can be considered a first promising step towards tailored RTW support for CSs with job loss, and potentially for other sick-listed workers, with a significant challenge to labour market participation. Facilitating communication between the delivering parties, and engaging usual care during program delivery, could be key elements to improved program implementation.


A total of 49 schools participated in the Secondary 2 Program of the Experimental Implementation Phase of the Project P.A.T.H.S. . After completion of the program, 7,406 students completed a Subjective Outcome Evaluation Form (Form A) designed by the research team to reveal their comments about the program, instructors, and perceived effectiveness of the program. Based on the consolidated reports submitted by the schools, the research team aggregated the data to form a “reconstructed” overall profile on the perceptions of the program participants. Results showed that high proportions of the respondents had positive perceptions of the program and the instructors. About 80% of the respondents were satisfied with the program and regarded it as helpful to their overall development. The present findings provide support to the effectiveness of Secondary 2 Program of Project P.A.T.H.S. from the perspective of the program participants.


AbstractPycnodictyagalinierigalinieri  and its genus Pycnodictya Stål, 1873 (Orthoptera: Acrididae: Oedipodinae) are recorded for the first time for the Egyptian fauna. The species was collected from Gabal Elba, in the southeastern corner of Egypt. This record expands the known distributional range of Pycnodictyagalinieri towards the north of Africa. Descriptions of the genus and the Egyptian subspecies are given using multiple diagnostic characters. The descriptions are supplemented by drawings and photographs of the specimen collected. It is proposed that the genus Pycnodictya belongs to the tribe Locustini.The band-winged  Pycnodictya Stål, 1873 is a member of the subfamily Oedipodinae. At present it includes 14 species, one of which contains two subspecies  reaching the Arabian Peninsula .Previously, the subfamily gonotini  The genue tribes ; in thisPycnodictya was established by Pycnodictyaobscura Linnaeus, 1758 and Pycnodictyarosacea Serville, 1838, but the latter has been recently considered a synonym of the first .Sporadic faunistic investigations had been made to record Egyptian insect species in different regions of the country. Some information about the insect fauna of Gabal Elba was reported by 2, includes a group of six mountains, and is considered a distinct phytogeographic region of Egypt , which was described originally from Ethiopia and has been recorded further from Eritrea, Kenya, Oman, Somalia, South Africa, Sudan, Tanzania and Yemen Oedipodagalinieri Reiche & Fairmaire, 1849: 432.Humbehyalodes Karsch, 1896: 265.Humbeminiatipennis Karsch, 1896: 265.Muséum national d’Histoire naturelle Paris, France (MNHN).Unspecified male collected from Ethiopia deposited in 22°11'16"N, 36°22'14"E), 2003 .1♀, Halaib II in Gabal Elba  and stridulatory serration on the inner surface of hind femur of other subfamilies (e.g. Gomphocerinae and Eremogryllinae).The genus Pycnodictya is recorded here as its subspecies Pycnodictyagalinierigalinieri and new for the Egyptian fauna from Gabal Elba.The classification of Egyptian Pycnodictya by which it can easily be separated from related genera such as Chloebora Saussure, 1884 and Scintharista Saussure, 1884 (The expanded lower marginal area of the hind femur is very characteristic for re, 1884 .Pycnodictya are similar to one another in general appearance, and the most features used for their identification are the color of the hind wings and hind legs, which are easily viewed by eye (Pycnodictyagalinieri by Pycnodictyagalinierigalinieri is well-differentiated from other species of the genus by its characteristic hind wings with orange red bases, moderately narrow dark band with an anterior projection that is separated from the posterior margin, and the clearly dentate anterior margin of the pronotum. In addition, the hind tibia is blackish violet with a yellowish basal ring and the hind femur is blackish on its inner side.The different species of the genus d by eye . The prePycnodictyagalinieri has a dentate anterior margin of pronotum resembling the situation in Pycnodictyadentata Krauss, 1902 but lacks the sinuated posterior lower angle of the pronotal lateral lobes of the latter. However, Pycnodictyakelleri Schulthess and the other subspecies Pycnodictyagaliniericitrina Kevan, 1961 described from Somalia and restricted to it (Pycnodictyagalinierigalinieri with their sulphorous or yellowish wings, respectively. Only the two species Pycnodictyadiluta Ramme, 1929 and Pycnodictyazinae Uvarov, 1949 resemble Pycnodictyagalinieri in the purplish hind tibia, but Pycnodictyadiluta with disappeared fascia of the hind wings and Pycnodictyazinae with crested pronotal median carina. Moreover, Pycnodictyagracilis Uvarov and Pycnodictyakilosana Miller, 1929 distinguished from Pycnodictyagalinieri as their hind tibia is honey yellow or light brown not blackish violet as the latter.ed to it , differePycnodictyagalinieri is widespread along the eastern part of the African continent. The high mobility of Oedipodinae as very strong fliers (Pycnodictyagalinieri from South Africa to Egypt. It is not clear, whether the subspecies has so far been overlooked in Egypt or whether it has expanded its range. The new finding and previous new records from Egypt (Acridoidea in diverse regions of the country.g fliers  may explom Egypt  highlighPageBreak


Secondary dengue causes more severe disease than the primary. Early on, it is important to differentiate the two. We tried to find important clinical and laboratory differences between the two for the purpose of early differentiation.One hundred fourteen patients confirmed on reverse transcriptase-polymerase chain reaction (RT PCR) were studied. On day 2 of illness IgM and IgG indices were studied for calculation of IgG/IgM ratio. A one-step immunochromatographic assay was used for classification of patients into primary and secondary dengue. Patient characteristics were also studied.3/micl, p <0.0001) and a significantly higher percentage of Dengue hemorrhagic fever/Dengue shock syndrome . In early phase of dengue NS1 and PCR were found to be better tests for diagnosis and later IgM is better. The IgG/IgM ratio of ≥ 1.10 had a sensitivity of 100%, specificity of 97.4% and accuracy of 67.5% in differentiating secondary from primary dengue.Dengue serotype 1 was the most common found in 60.5% patients. 66.7% (76 patients) had secondary dengue. Secondary dengue cases had a higher mean temperature , lower platelet counts (50.51 ± 38.91 vs. 100.45 ± 38.66, x 10Early on in the clinical course, IgG/ IgM ratio can play an important role to differentiate the two. We found the ratio of ≥ 1.10 to be the best cut off for the same. Dengue is a viral disease that is transmitted by mosquitoes in tropical areas. India is one of the countries maximally affected by it. Dengue can either cause a self limiting fever with low platelets or a severe disease characterized by capillary leak, intravascular volume depletion, severely low platelet counts and a high grade fever. There are 4 distinct types of dengue viruses known to cause dengue. Infection with a particular kind of dengue virus builds lifelong immunity to it, but the person is still vulnerable to be infected with the other types of dengue viruses. Infection with other kinds of dengue viruses in a person who already had a dengue fever in the past is called secondary dengue and has been found to be severe. This is due to more severe immunological response in the body . In our Flavivirus. Dengue virus has 4 serotypes : 1,2,3,4. The WHO 2009 classification divides dengue depending on the severity of illness. It classifies dengue as with or without warning signs ; and severe dengue   testing were studied further. Thus only 114 patients were studied further. Patients were studied for clinical, laboratory and serological patterns.This study was conducted in two tertiary care hospitals in the National Capital Region of India. It was a prospective observational study done from July to December 2015 when the maximum numbers of dengue cases are recorded. Patients with suspected dengue fever who presented within 2 days of symptom onset were recruited in the study with proper informed consent. Two hundred twenty-five patients with suspected dengue were initially recruited in the study. Of these only those who tested positive for dengue on reverse transcriptase polymerase chain reaction (RT PCR) [SimplexaThe SD BIOLINE Dengue Duo rapid test kit produced by Standard Diagnostics was used for classification of patients into primary and secondary dengue. It is a one-step immunochromatographic assay designed for the detection of both dengue virus NS1 antigen and differential IgM/IgG antibodies to dengue virus in whole blood, serum, or plasma. For SD BIOLINE dengue NS1 Ag device, 100 μL of the test sample was added into the sample well (S). Test results were interpreted at 15–20 min. Similarly, for SD BIOLINE dengue IgG/IgM device, 10 μL of test sample was added into the sample well (S). This was followed by the addition of 4 drops (90–120 μL) of assay diluent to the round shaped assay diluent well. Results were interpreted at 15–20 min. The test results were examined and interpreted according to the manufacturer instructions by three different readers to avoid biasness.Primary infection was defined as an IgM-negative/IgG-negative; or IgM-positive/IgG-negative on the blood sample drawn within 3 days of symptom onset. Secondary infection was defined as an IgM-negative/IgG-positive or an IgM-positive/IgG-positive result on the blood sample drawn within 3 days of symptom onset. We could not differentiate secondary from tertiary or quarternary dengue so some patients classified as having secondary dengue could have had tertiary or quarternary dengue. Days of illness were calculated considering the day of onset of symptoms  as the first day. The sensitivity and specificity of the use of SD BIOLINE Dengue Duo rapid test kit to classify dengue cases into primary and secondary dengue infection is 94.2 and 96.4% respectively .Another blood sample was drawn on day 7 after symptom onset for IgM to detect the rise in the IgM positive patients tested on the SD BIOLINE Dengue Duo rapid test kit.TM were used. Both are Indirect Enzyme-linked immunosorbent assay (ELISA) tests. The IgM assay uses a flavivirus group monoclonal horseradish peroxidase conjugate with TMB as substrate. Each Capture Well is coated with antihuman IgM. The antigen solution contains equal proportions of inactivated DV types 1–4. The polystyrene microwells are coated with anti-human antibody specific for IgM (μ -chain). Diluted serum samples and controls are incubated in the wells, and IgM present in the sample binds to the anti-human antibody (IgM specific) in the wells. Dengue virus (DV) antigen is then added to the wells and incubated; and, if anti-DV IgM is present in the sample, the DV antigen binds to the anti-DV in the well. Mouse anti-DV conjugated with horseradish peroxidase is then added to the wells and incubated. Enzyme substrate and chromogen are added, and the color is allowed to develop. After adding the Stop Reagent, the resultant color change is quantified by a spectrophotometric reading of optical density (OD) which is directly proportional to the amount of antigen-specific IgM present in the sample. Sample optical density readings are compared with reference cut-off OD readings to determine results. An index value of > 1.00 is presumptive for the presence of IgM antibodies to dengue virus.The Focus Diagnostics Dengue Virus IgM and IgG Capture DxSelectIgG assay is also an indirect ELISA. The polystyrene microwells are coated with equal proportions of inactivated and purified Dengue virus types 1–4. Diluted serum samples and controls are incubated in the wells to allow specific antibody present in the samples to react with the antigen. Nonspecific reactants are removed by washing and peroxidase-conjugated anti-human IgG is added and reacts with specific IgG. Excess conjugate is removed by washing. Enzyme substrate and chromogen are added, and the color is allowed to develop. After adding the Stop Reagent, the resultant color change is quantified by a spectrophotometric reading whose principle is similar to the one described for IgM above. An index value of > 1.00 is presumptive for the presence of IgG antibodies to dengue virus.This was calculated by dividing the IgG index to the IgM index value for each sample. It is important to note that all the data related to this calculation was made on day 2 of the illness.P-values of 0.05 or less were considered statistically significant. Sensitivity, specificity, accuracy and likelihood ratios were determined for different IgG/IgM ratios and the best value was determined by looking at the combination of these parameters. Receiver operator curves were determined for the chosen ratio and area under the curve (AUC) determined. An AUC of more than 0.9 is considered excellent.Statistical analysis was done on an MS Windows-based PC computer. The data were first keyed into a Microsoft Excel spreadsheet and then analyzed by Statistical Package for the Social Sciences (SPSS), Version 20.0, from SPSS incorporation Chicago IL. We used mean, standard deviation/standard error of mean, and percentage when appropriate for the patient’s characteristic description. Group differences were compared using the Pearson χ2 or Fisher’s exact test for categorical variables, or the Student t test or the Mann–Whitney U test for continuous variables. The study was approved by Ethics approval boards of the hospitals where the study was conducted . Written informed consent was obtained from all the patients involved in the study.n = 69) (Fig. Of the 225 patients initially recruited 114 were confirmed by RT-PCR to be having dengue and were studied further. Dengue serotype 1 was the most common found in 60.5% patients (Table The early diagnosis of secondary dengue is important because it has been recognized as a significant risk factor for development of severe dengue . In our IgM tested on day 2 was positive in 51.8% only while it increased to 96.5% on day 7 of the illness. This result reiterates the well accepted dictum that IgM ELISA is the test of choice after first 5 days of Illness . NS1 is IgG/ IgM ratio has been studied in many studies for early differentiation of primary and secondary dengue. Ratios done at different time stages of the disease have revealed different proposed cut offs , 18, 28.One limitation of our study is that we have not differentiated between secondary, tertiary or quaternary dengue. We have primarily differentiated primary from non-primary dengue. We have assumed that the non-primary dengue was secondary dengue in most cases because of the rarity of clinically observed third and fourth infections , 30 and We found secondary dengue to cause a more severe disease than primary making the differentiation important. Early on IgG/ IgM ratio can play an important role to differentiate the two. We found the ratio of ≥ 1.10 on day 2 of illness to be the best cut off for the same.


SDEs) from aged patients with low bone density and their functions in bone remodeling remain to be fully elucidated. We present a quantitative proteomics analysis of exosomes purified from the serum of the elderly patients with osteoporosis/osteopenia and normal volunteers; these data are available via Proteome Xchange with the identifier PXD006463. Overall, 1,371 proteins were identified with an overlap of 1,160 Gene IDs among the ExoCarta proteins. Bioinformatics analysis and in vitro studies suggested that protein changes in SDEs of osteoporosis patients are not only involved in suppressing the integrin‐mediated mechanosensation and activation of osteoblastic cells, but also trigger the differentiation and resorption of osteoclasts. In contrast, the main changes in SDEs of osteopenia patients facilitated both activation of osteoclasts and formation of new bone mass, which could result in a compensatory elevation in bone remodeling. While the SDEs from aged normal volunteers might play a protective role in bone health through facilitating adhesion of bone cells and suppressing aging‐associated oxidative stress. This information will be helpful in elucidating the pathophysiological functions of SDEs and aid in the development of senile osteoporosis diagnostics and therapeutics.Exosomes are secreted into the blood by various types of cells. These extracellular vesicles are involved in the contribution of exosomal proteins to osteoblastic or osteoclastic regulatory networks during the failure of bone remodeling, which results in age‐related bone loss. However, the molecular changes in serum‐derived exosomes ( Thus, osteoporosis and osteopenia represent an important global public health issue that is associated with a persistent decrease in the quality of life of affected individuals, especially in the elderly  analyses and tandem mass tag (TMT) label‐based quantitation. Furthermore, we analyzed the phenotypes of osteoclast precursor peripheral blood mononuclear cells (PBMCs), RAW 264.7 cells or osteoblast precursor hFOB 1.19 cells, and MC3T3‐E1 cells following differentiation into mature osteoclasts or osteoblasts in the presence or absence of SDEs. Our study provides evidence that an understanding of the specific cargo of SDEs from patients might be useful for the early evaluation of senile osteoporosis and the development of novel diagnostics and therapeutics.22.1http://www.exocarta.org, release date: July 29, 2015) . The clusters were identified, and pathway analysis was performed for the proteins in each cluster using the WEB‐based GEne SeT AnaLysis Toolkit . Information on proteins and pathways in each cluster . In the network of the osteoporosis DEPs  represented hubs at which the protein interactions converged. These proteins potentially regulate more than six of the DEPs, most of which are involved in cytoskeletal organization and integrin signaling in cellular adhesion and mechanosensation. The upregulated proteins from SDEs of osteopenia  was employed to map the gene symbol of the DEPs to the Wiki pathway database  in the SDEs of patients with osteoporosis; the downstream of integrin‐linked protein kinase (ILK) and proto‐oncogene tyrosine‐protein kinase Src (SRC) were also downregulated. These results suggested that exosomes in the serum of osteoporosis patients might not be conducive to bone mineralization of osteoblasts in terms of the functional decline of components of the P13K/AKT pathways  into GO categories using bioinformatic tools. In terms of cellular components Figure A, the up2.4We used human PBMCs derived osteoclasts as a model. The number of TRAP‐positive multinucleated osteoclasts cultured with SDEs from osteoporosis or osteopenia patients was significantly higher than the number of osteoclasts cultured with SDEs from aged normal volunteers. Also, the area of rearrangement of TRAP‐positive osteoclasts cultured with SDEs from osteoporosis or osteopenia patients was significantly larger than that of osteoclasts cultured with SDEs from aged normal volunteers. However, there were no significant differences in the number and area of osteoclasts treated with either SDEs from young volunteers or SDEs from elderly normal volunteers. In addition, the bone resorption of osteoclasts cultured with SDEs from osteoporosis or osteopenia patients was significantly stronger than the resorption of osteoclasts cultured with SDEs from aged normal volunteers. We also found that SDEs derived from the elderly normal group had a slightly stronger effect on osteoclast resorption ability than the SDEs derived from younger volunteers. However, the promotion of osteoclast bone resorption by SDEs in the elderly normal group was much weaker than that induced by SDEs in the osteoporosis or osteopenia groups Figure a. RAW2642.5The alkaline phosphatase (ALP) levels of human osteoblastic cell line hFOB 1.19 cultured for 21 days with SDEs from osteopenia patients were higher than those in cells cultured with SDEs from aged normal volunteers. However, the ALP level in hFOB 1.19 cells cultured with SDEs from osteoporosis patients was significantly lower than that of cells cultured with SDEs from aged normal volunteers. In addition, the ALP levels of hFOB 1.19 cells cultured with SDEs from aged normal were higher than those in cells cultured with SDEs from young normal volunteers Figure a.At 15 days after induction of MC3T3‐E1 cells by osteogenic media containing vitamin C and β‐glycerol phosphate, mineralization nodules were first observed in the group cultured in the presence of SDEs from osteoporosis patients. Three days later, mineralization nodules were observed in all the groups, and the OD values of alizarin red staining in the Aged osteoporosis and osteopenia groups were higher than those of the Aged normal group. In the later stages of matrix mineralization on day 21, the OD value in the Aged osteoporosis group was lower than those in both the Aged normal and osteopenia groups. Moreover, the OD value in the Aged osteopenia group was higher than that in the Aged normal group. The OD value in the Young normal group was lower than that in the Aged normal group. The OD values of Alizarin Red staining in all these four groups were in accordance with the ALP levels detected in human osteoblastic cells  to process representative MS/MS spectral identification Figure A–D. In as Figure c.3Previous studies have demonstrated the multiple roles of bone‐derived exosomes in bone remodeling; however, none have been reported describing proteomics analysis of the differences between SDEs from aged patients with low bone density and normal volunteers. In the present study, we discovered that the SDEs from osteoporosis patients inhibited osteoblastic bone matrix mineralization and promoted osteoclast differentiation. In contrast, SDEs from osteopenia patients enhanced both osteoblast function and osteoclast activation, leading to a compensatory increase in bone remodeling. A comprehensive analysis of the changes in proteins in these exosomes was conducted by TMT‐based MS, which has the advantages of maximum protein coverage and precise quantification. The DEPs identified were involved in different processes and functions intrinsic to bone, including mechanosensation, inflammation, and cell senescence, which are the apparent protagonists in bone remodeling.3.11 and β3 integrins and CD34 were representatives of the downregulated proteins. Previous studies indicated that integrin αvβ3 is essential for mechanosensation and osteoblastic bone cells express integrin receptors αv, β1, and β3 , which is critical for shear induction of bone formation‐related genes in osteoblast‐like cells , nucleolin (NCL), and members of the cytoplasmic ribosomal proteins. APP and NCL have been reported to be involved in cellular adhesion and survival of osteoclasts. The abnormal APP/Aβ deposition in osteoporotic bone seems to be associated with potent enhancement of osteoclast differentiation and activation, suggesting an important role for Aβ in the pathogenesis of osteoporosis. These signaling cascades may initiate nuclear factor of activated T cells c1 (NFATc1) translocation into the nucleus, eventually inducing osteoclast‐specific gene transcription to allow osteoclast differentiation and activation . Additionally, fibrillin‐1 (FBN1) was constitutively upregulated in SDEs of osteopenia patients. FBN1 mediates cell adhesion via its binding to cell surface receptors integrin αvβ1 and selectively blunts expression of osterix, which is a transcriptional regulator of osteoblast maturation  and connective tissue growth factor (CTGF) are upregulated in SDEs of osteopenia patients and act as hubs in regulating the function of osteoblasts. VCAN is an ECM component that plays an essential role in transformed cell behavior. Increases in VCAN have been confirmed in human MSCs undergoing osteoblast differentiation . However, in premenopausal women, and men <50 years of age, the ethnicity or race adjusted Z‐scores were recommended by the International Society for Clinical Densitometry (ISCD) instead of T‐scores in the diagnostic classification . Informed consent was obtained from all patients and normal volunteers. The study was performed with the approval of the Ethics Committee of the PLAGH.The patients diagnosed with osteoporosis and osteopenia at the Chinese PLA General Hospital  were recruited to this study from September 2015 to December 2017. For quantitative proteomics analysis, serum samples from 31 osteoporosis patients, and 46 osteopenia patients (aged 55–84) were allocated to Aged osteoporosis and Aged osteopenia groups. Serum samples obtained from 26 elderly normal volunteers aged 56 to 70 and 36 normal volunteers aged 21 to 49 were allocated to Aged normal and Young normal groups, respectively  for pathway mapping. Pathways with at least three target genes and a p‐value of <.05 were considered to be statistically significant. Enriched pathways were visualized by Cytoscape (3.2.1) software. For Hierarchical clustering analysis, the MS proteomics data presented as the ratios to 131/127 and 130/127 were input into Hierarchical Clustering Explorer 3.5 with log transformation , and a heatmap was then constructed using the complete linkage method. At the beginning of the process, each element is in a cluster of its own. The clusters are then sequentially combined into larger clusters until all elements are combined as a single cluster. In each step, the two clusters separated by the shortest distance are combined . Cluster Analysis (Fourth ed.). London: Arnold. ISBN 0‐340‐76119‐9.). The STRING  database (http://string-db.org) was used for predicting protein networks. All STRING network analyses were performed using UniProt accession numbers as the input and with “Experimental” and “Database” evidence at medium (0.4) confidence level. The networks were downloaded as tab‐delimited text files, and visualized, and reorganized using Cytoscape (3.2.1) software. In addition, the MS proteomics data presented as the ratios to 131/127 and 130/127 were matched to these STRING networks with log2 transformation.The differential expression threshold was defined as a twofold change for both down‐ and upregulation of expression. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  or PBMCs; each group was prepared in triplicate. The culture medium was refreshed every other day. On day 5, cells were confirmed by TRAP staining and photographed for evaluation of numbers and area rearrangements. SDEs (200 μg) from each of the Young normal, Aged normal, Aged osteopenia, and Aged osteoporosis groups were added to MC3T3‐E1 cells (1.5 × 105 cells/cm2) or hFOB 1.19 cell lines; each group was prepared in triplicate. On days 15, 18, and 21, MC3T3‐E1 cells were photographed and confirmed by Alizarin Red staining, and the sample‐bound Alizarin Red staining of each group was solubilized for OD measurements. On day 21, ALP levels of hFOB 1.19 cells were assayed. The supplementary experimental procedures were shown in Appendix SDEs (200 μg) from each of the Young normal, Aged normal, Aged osteopenia, and Aged osteoporosis groups were added to RAW 264.7 cells  and Prism software . Unless otherwise indicated, data were analyzed using Student's t test, and p < .05 was considered to indicate statistical significance.Data are expressed as the mean ± The authors report no conflict of interest relevant to this article.P.T. and W.G. designed the research. Y.X., Y.G., and L.Z. performed the research. Y.X., Y.G., and Y.C. analyzed the data. L.Z. provided serum samples and reagents. Y.X. and Y.G. wrote the manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.