This paper proposes a mixed decision strategy for freight and passenger transportation in metro systems during off-peak hours (MTS-OPH). The definition of the mixed decision strategy is proposed, and fixed and flexible loading modes are considered for different passenger flow volumes. A mathematical model of the MTS-OPH is proposed and solved using an improved variable neighborhood search algorithm. Case studies demonstrate the performance and applicability of the proposed model and algorithm, and the MTS-OPH is discussed for different delivery distances, passenger flows, and metro network types. The proposed strategy is suitable for long-distance delivery, and the proposed model framework can be applied to different types of metro networks with different levels of complexity. The mixed decision strategy provides a decision support tool for metro and freight companies and can propose corresponding solutions according to different passenger flows. With the continuous development of e-commerce and home deliveries, urban freight transport has emerged as a key link in urban economic and social development , 2. RoadAs mentioned above, the freight transportation needs to change towards more efficient and sustainable transportation systems to cope with increasing demand for freight transportation in urban areas. The metro has the advantages of high efficiency, large capacity, and sustainability, but most metro networks suffer from insufficient utilization of metro trains due to the low passenger flow during off-peak hours . TherefoThe purpose of this study is to combine the existing metro network with the first- and last-mile delivery services operated by logistics companies and propose a feasible passenger and freight flow mixed transport strategy for metros during off-peak hours (MTS-OPH). The paper considers fixed and flexible loading modes under different passenger flows and analyzes different cargo characteristics and delivery time requirements. A model for quantitatively evaluating the mixed transportation strategy is established, and an improved variable neighborhood search (VNS) algorithm is designed. They are then applied to the cargo transportation of Ningbo and Beijing metro networks, respectively, and the mixed transportation strategy under different delivery distances, passenger flows, and metro network types is analyzed. The model and method can also be applied to the metro network of other rail transit cities.The remainder of this paper is organized as follows: Nash  first prThere are some successful cases of urban passenger and freight transportation. In Dresden, the tram line from the Volkswagen warehouse to the city center can transport 300,000 tons of goods a year, 10 times a day, which significantly reduces carbon dioxide emissions . In PariThe feasibility and application prospects of urban metro freight have been studied in a few research papers. Rijsenbrij and Pielage  discusseIn addition, a few studies focused on metro freight. Brice et al.  reportedLocation and route selection have long been the significant issues in the freight and passenger transportation domain. Fatnassi et al.  proposedLikewise, time window constraint is a critical issue along with the rapid increase in freight demand during recent years. Behiri et al.  studied In addition, the development of solving algorithms has attracted the attention of researchers and practitioners. Bräysy  introducWe propose a general theoretical framework of MTS-OPH. This framework includes new concept and transportation standards of MTS-OPH. This definition clarifies the process and applicable time of mixed transportation. Relative to previous study on the types of mixed transportation goods , 29, MTSWe formulate a nonlinear programing model for the MTS-OPH. Based on the research of Fatnassi et al.  and ZhaoWe presented the real case study of the Ningbo and Beijing metro network to verify the practicality and efficiency of the proposed model. The applicability of the model is discussed from the distribution distance, off-peak passenger flow, and metro network type. Our results show that the proposed model can be applied to different metro networks. Furthermore, the mixed transportation mode in the metro systems has the advantages of high speed, high punctuality, low economic investment, low environmental impact, and low energy consumption –33.The main contributions of this study are summarized as follows:This section provides a detailed description of the MTS-OPH, analyzes the types of goods suitable for mixed transportation, and provides different mixed transportation methods based on different load rates of passenger flow during off-peak hours. Finally, a nonlinear programing model of a mixed transportation strategy is constructed.MTS-OPH integrates the existing urban metro network with the first- and last-mile delivery services operated by logistics firms. The key aspect of this strategy is to transport goods and passengers together without affecting the metro passenger flow. Thus, the transportation standard of separate loading of passengers and cargo and priority transportation of passenger flow should be considered. First, metro train carriages are divided into passenger carriages and freight carriages, similar to the passenger carriages and female carriages set in the Shenzhen metro trains in China . Differetinterval represents the headway of metro trains during off-peak hours.Second, to satisfy the passenger flow priority transportation standard without changing the headway and stop time of metro trains during off-peak hours, this study proposes different mixed transportation methods based on different load rates of passenger flow during off-peak hours. When the number of passengers and freight demand is greater than the metro capacity, each train adopts a mixed passenger and cargo transportation mode during off-peak hours, as shown in Method 1  in In summary, MTS-OPH is a transportation strategy based on the aforementioned mixed transportation standard, which satisfies the optimal distribution cost of the cargo flow under the condition of determining the origin and terminal stations of the goods. The transportation strategy is to use the metro passenger transportation network, which is composed of cargo distribution centers, metro stations, terminal cargo stations, metro trains, and freight vehicles, as shown in In In the first stage, the cargo is packed in freight parcels, placed in freight boxes, loaded onto transportation vehicles, and delivered to the departure metro station via freight vehicles. Then, the freight boxes are unloaded from the vehicle and loaded on the trolley. In the second stage, the freight boxes are transported to the metro platform via trolleys and transported to the metro freight carriage when the train enters the platform. In the third stage, freight boxes are transported on the metro network (transfers are performed via trolleys). Here, the train operation mode is from the first station to the last station regardless of the train service route. The freight boxes enter the fourth stage after being transported via the metro train. The freight boxes are unloaded from the metro freight carriage and transported via trolleys to the arrival metro station. In the last stage, the freight boxes are loaded onto the freight vehicle and transported to the corresponding terminal cargo station. All the aforementioned stages constitute the MTS-OPH operation process, while the third stage of the operation period in MTS-OPH is the off-peak hours of metro operation.The freight is placed in a standardized unit parcel to measure the arrival demand of the terminal cargo stations.There is no storage function at the metro exit station, and freight vehicles are arranged for delivery immediately after the cargo arrives at the metro exit station.The freight vehicles used for transportation are of the same model with the same fuel consumption and load capacity.The freight vehicles run at a uniform velocity without consideration of the road conditions. Furthermore, after the freight is transported, the vehicles are not required to return to the cargo distribution center or arrival metro stations.Up to two freight transfers occur in the urban metro network.The MTS-OPH model can be described as the process of delivering multiple freight stations from a cargo distribution center with the optimal delivery cost as the goal. The number of terminal cargo stations is determined, but the freight stations are located in different geographical locations. All transportation paths are based on the actual shortest distance of the road network or metro network. Thus, certain assumptions have been considered as follows:x) represents the smallest integer greater than x).Equation  determinr=1 is a fixed loading mode; that is, each train uses a mixed passenger and freight transportation mode during off-peak hours; r=2 is a flexible loading mode; that is, one of every two trains chooses to use a mixed transportation mode and the other for passenger transportation.The freight loading mode is selected by Equation . Among tVehicles in the “first mile and last-mile” distribution network should meet vehicle capacity constraints, vehicle number constraints, and line capacity constraints.Equation  assigns The goods in the metro network by train should meet the train capacity constraint and the number of transfer constraints.Equation  expresseThe mixed transportation is based on the off-peak hours of urban rail transit, and the departure time of mixed transportation trains shall not be earlier than the start time of off-peak hours.ts represents the running time between S and S − 1 when the train is at station S, and when s=1, ts=0. Equation  is as shown inThe transportation cost of vehicles is mainly composed of the transportation distance, number of vehicles, number of freight parcels, and fixed operating cost of vehicles. Therefore, the transportation cost fvij clearly, Equation  can be obtained similarly.Therefore, the vehicle transportation cost In summary, Equation  represenfn.The number of freight parcels and frequency of transfer constitute the transit cost. The number of transfers is mainly determined by the number of times the cargo is loaded and unloaded; the completion of one loading and unloading of cargo is regarded as one transfer. Equation  shows thfd, as inThe delay cost is caused by the freight arriving at the terminal cargo station in an unexpected time window. The delivery time window of MTS-OPH is based on the off-peak start time, so the delay cost will only be calculated if the delivery time window is exceeded. This is expressed with Because only part of the metro carriages is used for freight, the weight of the cargo is much smaller than that of the metro. Therefore, the delivery cost of MTS-OPH is not affected by metro fixed operating cost and metro transportation distance.fC is the sum of the vehicle transportation cost fv, node transit cost fn, and delay cost fd, i.e., fC=fv+fn+fd. Hence, the mathematical formulation of the MTS-OPH model is built as follows:In summary, the delivery cost Equation  denotes In the MTS-OPH model, the pickup and delivery constraints of the time window and transshipment value are considered , 35, 36 Zc) in Equation  process. We use The shaking process is a perturbation operator in the VNS. The process is used to generate different neighborhood solutions. The remaining initial solution and VND process are described in detail in the next section.R of the MTS-OPH is formed by constructing a line of length 2I′ according to the number i′ of a terminal cargo station. The initial route R is mainly composed of i′ departure metro stations and i′ arrival metro stations shown in ji′ in  corresponds to each ji′′ in  individually, and a group  constitutes a metro distribution route. The following conditions should be met: j ∈ J, j′ ∈ J′,  and J=J′.The initial delivery route Two types of neighborhood structures are applied. The first consists of neighbors which exchange strategies on existing delivery routes. The second consists of neighbors obtained by updating the distribution strategy on the existing route. The methods for generating neighbors for the first type of neighborhood structure are Swap-2 and Inserting-t . For thet times on the basis of Insertion-1. As shown in ji′ in the initial solution and selects a new number from the set J to replace ji′. Alter-t is to repeat the Alter-1 operation t times. In addition, to prevent the value of t from being too large and destroying the stability of the obtained solution structure, the value of t is controlled to be in the range of  in the insertion operation and change operation of this study. The iterations of repeated deletions, changes, and insertions let the algorithm search in a larger solution space, thereby enhancing the ability of the neighborhood search algorithm to move away from the local optimal region.Swap-2 refers to the random exchange of two adjacent or nonadjacent rows in the initial solution, as shown in G = {Alter−3, Alter−4} as the set of neighborhood structures in the shaking procedure. For each structure Gv ∈ G, it maps a given solution r to a series of neighborhoods Gv(c). When the shaking procedure is applied, a solution will be randomly chosen from the neighborhoods. Accordingly, the detailed procedure is given in Algorithm 2.We use During a local search in VND, when a better solution than the current solution cannot be found in this neighborhood, the search is continued by moving to the next neighborhood solution. Contrarily, if a better solution than the current solution is found in this neighborhood, the first neighborhood solution will be returned to restart the search. For a better solution, the first neighborhood solution should be returned and the search should be started again. The local optimal solution obtained through such a search process is likely to be the global optimal solution. A detailed operation of the VND process is provided in Algorithm 3.Case studies of the Ningbo metro network and Beijing metro network were conducted to evaluate the accuracy and efficiency of the proposed model and method. Examples of the application in different delivery distances, different passenger flows, and different types of metro networks were illustrated. The proposed algorithm framework was coded in MATLAB 10.0 on a Window 10 personal computer with 4.0 GB processor. The MTS-OPH problem is solved by IBM CPLEX 12.5 Academic Version on the same platform.I and the six cargo stations are named A, B, C, D, E, and F, respectively, i.e., i′={1,2,3,4,5,6}, i′ ∈ I′. The geographical location of freight stations is evenly distributed, and the receipt volume of each cargo station obeys the uniform distribution of . The metro network of the Ningbo Urban Rapid Rail Transit Construction Plan (2013−2020) [In this section, based on the logistics information of a certain express company in Ningbo, we considered a distribution situation between the express delivery distribution center and six terminal express delivery stations. For convenience, the cargo distribution center is represented by 13−2020)  was consThe airport logistics park near the metro line was selected as the express delivery distribution center, which is represented by a red star in The average speed of freight vehicles was 20 km/h , and theIn the algorithm parameter setting process, this study sets the number of neighborhood solutions in one iteration to 100 and the total number of iterations to 50 . The neiFor related problems in route planning and distribution, the genetic algorithm (GA) is widely used –47. TherIn order to further prove the effectiveness of the improved VNS algorithm, we first give the actual maximum cross-section passenger flow to Equation , making Finally, the optimal solution for the delivery of vehicles is calculated. Meanwhile, the optimal transportation strategy during off-peak hours for the individual distribution of freight vehicles is calculated; this transportation strategy is called VTS-OPH. As evident from The delivery route is shown in To study the applicability of the MTS-OPH for different delivery distances, we divide the actual express delivery information provided by the airport logistics park into three different distribution range data tables. The metro network of Ningbo is shown in According to the metro network and express delivery information data, Ningbo is divided into three areas with different distribution scopes as S1, S2, and S3. Twenty delivery destinations  are selected with uniform locations in each area, as shown in In the experiment, the time horizon is considered to be 9:00−12:00, which is the off-peak period of metro operation. In addition, the metro model in Ningbo is type B composed of six carriages with a total capacity of 1,460 people. According to statistics from the Ningbo Rail Transit Group, the maximum load rate during off-peak hours in the Ningbo metro network is 90%. Hence, at least five metro carriages are required for passenger transportation during off-peak hours, and the remaining one carriage is used for goods transportation. The remaining parameter values and algorithm parameter settings are consistent with the small-scale case study presented in The demand and time window of the terminal express station in S1 are listed in The data in In The demand and time window of the terminal express station in S2 are listed in Similarly, the data in As shown in Combining the results listed in Tables The demand and time window of the terminal express station in S3 are shown in According to the above experimental data, the VNS algorithm is used to solve the two transportation strategies of MTS-OPH and VTS-OPH 20 times and the optimal solution obtained is shown in As shown in Tables Concurrently, by comparing the calculation results in Tables fcm represents the delivery cost of MTS-OPH, fcv represents the delivery cost of VTS-OPH, Q is the number of express parcels, Cv is the fixed operating cost of the vehicle, capV is the capacity of freight vehicles, L is the vehicle transportation distance between two points, Co is per unit cargo transfer cost after one transfer, and O is the number of transfers between two stations.To further explore the relationship between the MTS-OPH and VTS-OPH under different delivery distances, we assumed that there was one terminal express station, did not consider the time window constraints, and quantitatively analyzed the delivery costs of the two transportation strategies.The delivery costs of the two transportation strategies are shown in Equations  and 29)29). AssuEquation  shows thIn this section, we analyze the impact of different load rates of passenger flow on MTS-OPH. We selected case data in S3 for analysis, the total number of express deliveries is 975 packages, and three train carriages are required as freight carriages. This determines the 50% full-load rate during off-peak hours as the boundary. Concurrently, following the principle of passenger and cargo diversion, according to the statistics of Ningbo Rail Transit Group, the maximum passenger flow load rate of the Ningbo metro network during off-peak hours is 90% and 5 train carriages are required as passenger carriages. Therefore, 90% of the passenger flow load rate is determined as upper limit. When the full-load rate of passenger flow during the off-peak hours is greater than 90%, the MTS-OPH is not selected, as shown in To further compare the two transportation methods in the MTS-OPH, with the load rates of passenger flow of 50% and 90% as the boundary, the VNS algorithm was run 20 times to obtain the optimal results, as shown in In In order to further prove the applicability and feasibility of the model, we selected the Beijing metro network for numerical experiments. The Beijing metro network is one of the most complex metro networks in China, with 24 metro lines totaling 331 stations, including 62 transfer stations, as shown in In the experiment, the considered time horizon is set as 9:00–12:00, which is the off-peak period of metro operation. According to the data of Beijing Subway Operation Company, the maximum passenger load rates of passenger flow in the Beijing metro network during off-peak hours is 94.3%. The metro train is composed of 6 carriages, and it needs to occupy 5 carriages for passenger transportation. Thus, the loading mode of Method 1 for mixed transportation is selected. Some parameters in the experiments are set as follows. That is, the delivery time window is set to 2 hours or 3 hours, and the demand and time windows of each terminal express station are shown in The experimental data in In According to the case analysis results in Tables This paper proposes a new mixed transport strategy based on the metro network during off-peak hours to determine the freight mode and its distribution cost under off-peak metro passenger flow. The mixed transportation standard of passenger flow priority and separate transportation of passenger and cargo flows of the same train are proposed. According to the aforementioned criteria, a nonlinear programing model of the mixed transport strategy is constructed. In addition, an improved VNS algorithm is designed to solve the model. Finally, considering the Ningbo and Beijing metro network as an example, it is verified that the proposed model and mixed transport strategy can provide decision support for logistics companies. The main contributions of the study are as follows.A theoretical framework of the mixed transport strategy for different metro passenger flows during off-peak hours was developed via comparisons with related studies , 20, 29.In practice, the model of the mixed transportation strategy proposed in this study can provide decision support for logistics companies based on different delivery distances, different off-peak passenger flows, and different types of metro networks. First, when the vehicle transportation distance under separate VTS-OPH is greater than the sum of 1.45 and the vehicle transportation distance of MTS-OPH, the MTS-OPH should be adopted; otherwise, the VTS-OPH should be selected. Second, when the number of passengers and freight transportation demand are greater than the metro capacity, the fixed loading mode of the MTS-OPH should be selected for transportation; otherwise, the flexibility loading mode of the MTS-OPH should be selected for transportation. Finally, the proposed model framework can be applied to different types of metro networks with different levels of complexity.This study has some limitations to be further solved, such as freight vehicle scheduling and route planning and metro station and line performance evaluation , 54. The


As part of an NIA-supported effort to develop an online course to train individuals to lead the evidence-based Savvy Caregiver program and to orient sponsoring organizations to the program, we conducted semi-structured interviews to assess success and sustainability “best practices”. Interviews were conducted with 17 leaders and trainers from eleven Savvy-providing organizations. Analysis of these interviews identified two main themes associated with successful program implementation: leadership commitment and trainer ownership. Paramount to success appears to be leaders’ clear understanding of and enthusiastic commitment to the value of the Savvy program to the organization’s constituents. This translated to careful selection, training, management and on-going development of Savvy program trainers. It contributed to leaders’ appreciation of Savvy as a gateway for clients to seek out other programs and services from the organization, while the gathering of meaningful evaluation data (using established outcome-assessment instruments) contributed, in several cases, to garnering more lasting support to deliver the program. Organizations’ commitment to the program was demonstrated by securing the kinds of adequate and appropriate training, typically involving both instruction and modeling, for Savvy program leaders. These efforts fostered a sense of ownership among the leaders – the sense that the program had positive value for the caregivers served. These findings should be of interest both to scholars engaged in the development of interventions and for organizations implementing them. Taken together, the themes highlight several factors for program implementation that maximize the chances of maintaining fidelity to core program principles and ensuring its sustainability.


Anti-modified protein antibodies (AMPA) targeting citrullinated, acetylated and/or carbamylated self-antigens are hallmarks of rheumatoid arthritis (RA). Although AMPA-IgG cross-reactivity to multiple post-translational modifications (PTMs) is evident, it is unknown whether the first responding B cells, expressing IgM, display similar characteristics or if cross-reactivity is crucially dependent on somatic hypermutation (SHM). We now studied the reactivity of (germline) AMPA-IgM to further understand the breach of B cell tolerance and to identify if cross-reactivity depends on extensive SHM. Moreover, we investigated whether AMPA-IgM can efficiently recruit immune effector mechanisms.Polyclonal AMPA-IgM were isolated from RA patients and assessed for cross-reactivity towards PTM antigens. AMPA-IgM B cell receptor sequences were obtained by single cell isolation using antigen-specific tetramers. Subsequently, pentameric monoclonal AMPA-IgM, their germline counterparts and monomeric IgG variants were generated. The antibodies were analysed on a panel of PTM antigens and tested for complement activation.Pentameric monoclonal and polyclonal AMPA-IgM displayed cross-reactivity to multiple antigens and different PTMs. PTM antigen recognition was still present, although reduced, after reverting the IgM into germline. Valency of AMPA-IgM was crucial for antigen recognition as PTM-reactivity significantly decreased when AMPA-IgM were expressed as IgG. Furthermore, AMPA-IgM was 15- to 30-fold more potent in complement-activation compared to AMPA-IgG.We provide first evidence that AMPA-IgM are cross-reactive towards different PTMs, indicating that PTM (cross-)reactivity is not confined to IgG and does not necessarily depend on extensive somatic hypermutation. Moreover, our data indicate that a diverse set of PTM antigens could be involved in the initial tolerance breach in RA and suggest that AMPA-IgM can induce complement-activation and thereby inflammation.The online version contains supplementary material available at 10.1186/s13075-021-02609-5. The presence of autoantibodies is an immunological hallmark of rheumatoid arthritis (RA). About 50–70% of RA patients harbour anti-citrullinated protein antibodies (ACPA), directed against citrullinated proteins generated by the conversion of arginine to citrulline . ACPA reSimilarly, it has been described that ACPA-IgM recognize several citrullinated antigens on the polyclonal level –16. HoweFurthermore, it remains unknown whether the emergence of autoreactivity through the recognition of PTM-self-antigens relies on somatic hypermutations (SHM). Interestingly, ACPA-IgG have undergone extensive SHM, carrying on average 50 IGHV nucleotide mutations , 17, 18.Peripherial blood samples were obtained from RA patients visiting the outpatient clinic of the Rheumatology department of the Leiden University Medical Center. All RA-patients were RF-IgM positive and showed high ACPA levels (> 340 U/ml) or detectable AAPA levels from the IMPROVED clinical trial .PBMCs were isolated using Ficoll-Paque and stained with Live/dead Fixable Aqua dead cell stain kit 405 nm (life technologies), CD3-PB , CD14-PB , CD19-APC-Cy7 SJ25C1, BD), CD20-AF700  and CD27-PE-Cy7. Antigen-specific staining was performed using CCP2-BV605, CCP2-APC and CArgP2-PE, or HC55-APC and HC55-PE C1, BD, C. RNA isoTM 293-F cells (Gibco) using Opti-MEM® (Gibco) medium and 293Fectin (Thermo Fisher). The supernatants were harvested 5–6 days post transfection. IgG1 monoclonal antibodies (mAbs) with identical V-genes were cloned, produced and purified as previously described [Codon optimized AMPA heavy chain (HC) and light chain (LC) variable (V)-gene sequences, coupled to the IGHM or the IGLC3/IGKC constant regions (UniProt), respectively, the Kozak sequence and the HVAT20 leader peptide were designed in GeneArt (Life Technologies) and ordered at IDT. The constructs, as well as the codon-optiomized J-chain (UniProt) used for the generation of pentameric molecules, were cloned into a pcDNA3.1 (+) expression vector. The IgM HC, LC and J-chain constructs were transfected into Freestyleescribed  .Experimental procedures for protein modification, peptide synthesis, antigen labelling and antibody purification are given in the Variable (V), diversity (D) and joining (J) genes were identified by alignment with the respective germline sequences of the IMGT reference directory that shows the highest identity using IMGT/V-QUEST  Table S. The ‘GePeptide-, protein- and cross-inhibition ELISAs were performed as previously described , 10. The2CO3 0.1 M NaHCO3 in MQ) + 1%BSA at 37 °C, samples were incubated for 2 h at 37 °C. Monoclonal IgM binding was detected using a HRP-conjugated Goat-anti-human IgM secondary antibody .For the Tetanus Toxoid (TT) ELISA, 1.5 LF/ml TT was coated to Nunc Maxisorp plates (Thermo Scientific) and incubated overnight at RT. After 1 h blocking in coating buffer (0.1 M Na2+ and Mg2+) buffer was added as a source of all complement components to allow C3c-deposition. EDTA, which chelates Ca2+ and Mg2+ and thereby inhibits complement activation, was added as a negative control [2O2.For the complement ELISAs, CCP2/CHcitP2 (1 μg/ml) or cit-vimentin 59-74 (10 μg/ml) were coated on streptavidin plates . All steps were performed for 1 h at 37 °C. Monoclonal antibodies were diluted in PBT  and added to the plate. C-active normal human serum (NHS) in GVB++ . Interestingly, 2D5 recognized not only the citrullinated, but also the homocitrullinated version of this peptide. Moreover, the 1G8, also derived from a CCP2-reactive B cell, recognized the citrullinated, homocitrullinated and acetylated version of the peptide, although acetyllysine was recognized to a lesser extent. In contrast, the recognition profile of 1E3 was restricted to the acetyllysine modification  sequence Table . Two GL Next, we wished to investigate whether the pentameric structure of the IgM antibodies influences the extent to which different PTM antigens are recognized. Therefore, the pentameric IgM mAbs  were expressed as IgG , leaving the variable domain unaffected. The respective size was confirmed by analytical SEC Fig. A. RecognAs IgM is typically the first isotype to appear during an antibody response, we wished to determine whether AMPA-IgM could, potentially, initiate inflammation. Although, it is known that IgM can activate the complement system efficiently, it is unclear if or how efficiently AMPA-IgM can activate complement, as compared to AMPA-IgG. Therefore, we investigated the potential of AMPA-IgM to activate the classical complement pathway as measured by C3c deposition. Indeed, binding of 2D5, but not of the anti-TT-IgM as control, to citrulline- and homocitrulline-containing antigens led to deposition of C3c in the presence of normal human serum (NHS)  protein 3 have been reported to lose reactivity to DSG3 when reverted to germline . SimilarIn RA, there has been a major focus on AMPA-IgG as this is the predominant isotype found in sera of RA patients. However, IgM ACPA are also present in a substantial number of CCP+ RA-patients, especially in synovial fluid in which elevated levels of IgM ACPA have been described . We now A limitation of the study is that we succeeded in producing only a limited number of AMPA-IgM. This is partly explained by our observation that the number of AMPA-IgM expressing B cells in the circulation of RA patients is low. Additionally, production of antigen-specific IgMs is challenging, as also evidenced by a recent study in which 46 IgM sequences from COVID-19-specific B cells were tested as IgG antibodies because of the difficulty in producing IgM pentamers . ClearlyCollectively, our study shows that the breach of B cell tolerance against PTM antigens could already occur before the B cells have undergone (extensive) SHM and class switch recombination. Moreover, we show a broad PTM antigen recognition profile of AMPA-IgM, indicating that a variety of antigens could be involved in the initial B cell activation and/or the perpetuation of the IgM response in the inflamed joint. Likewise, our results indicate that AMPA-IgM could be involved in synovial inflammation by facilitating complement activation.Additional file 1. Supplementary material and methods.Additional file 2. Figure S1.Additional file 3. Figure S2.Additional file 4. Figure S3.Additional file 5. Figure S4.Additional file 6. Figure S5.Additional file 7. Figure S6.


Digital health programs offer numerous psychological and physical health benefits. To date, digital programs have been aimed broadly at younger participants, yet older individuals may also benefit. Our study sought to demonstrate user feasibility and satisfaction in a digital wellness program for older adults. We conducted a retrospective analysis of 140 participants in a digital health wellness application that integrated guided exercises, nutrition planning and health education. Primary outcomes were active participant retention, engagement in the mobile program and user satisfaction as operationalized by NPS scores. Among 140 participants, median age was 59.82 (50–80), 61% female, in a sample taken in the United States. Engagement was high and sustained, with more than 65% participants engaged, operationalized as at least completing one task activity a month over 17 weeks. Participants were also satisfied with the program, reporting NPS scores of 43 on day 30 of the program. Secondary health outcomes included 3.44 pound weight change during the first month. User feasibility and satisfaction was demonstrated in a sample of older participants for this novel digital health wellness program. Future work focused on older adult users may result in improvements in patient health outcomes and improved preventive medicine strategies. Over the last decade, digital programs aimed at patients with chronic diseases and overall physical and psychological well-being have becoming increasingly common and popular . Within This was a retrospective study of anonymized and deidentified data on participants who were enrolled in Mighty Health, a mobile based health wellness program with an older-aged focused program integrating physical exercises, coach support, and health lifestyle strategies. The program encompasses a mobile app with participants encouraged to create and follow a personalized well-being plan including a virtual coach and structured lesson and weekly goals aimed at guided exercises for improving physical health, nutrition, and general health habits such as sleep hygiene and mental health. Age specific efforts to increase usability and interest/engagement amongst older participants included larger font size, high contrast font color text and large tap areas, joint-friendly exercises, cardiovascular/diabetes focused nutrition plans, and general health content material for the older population. Inclusion criteria included users of Mighty health from the dates 10 June 2019 to 25 October 2020 over the age 50, who completed at least two tasks weekly (out of a possible average of four tasks per week) in the first month of the program. For measuring inclusion and user engagement we followed past investigations in the digital health literature ,22, nameDescriptive demographic data was collected. Primary outcomes were user retention and overall satisfaction with the program within a 4 months (17 weeks) timeframe. Participant satisfaction was assessed using net promoter scores (NPS), a management tool popular in industry that assesses customer experience and satisfaction and examines the percentage of participants rating their likelihood of recommending the service/product to a friend or colleague ,24.There were 150 subscribers in the digital program, of which 140 ultimately met inclusion criteria for this analysis .Participants characteristics are summarized in 2 = 0.29, p = 0.59) and overall satisfaction . Additionally, when stratified by age groups , no significant differences were seen with participants stratified by age (X2 = 0.84 p = 0.359) and overall satisfaction .No sex differences were seen between male and female participants with regards to retention (XWhile not a primary outcome of our feasibility study, on average participants in the program completed 412,295.46 steps. Additionally, of the 140 participants 19 had weight inputs in the first and last month. For these, the average weight loss was 3.44 pounds.Our study found that older patients were successfully engaged in a general wellness mobile app and reported high degrees of satisfaction with the usability and overall program. This finding was seen both in men and women, and even in participants in the upper range of our sample with regards to chronological age.Older individuals represent an important and increasingly large proportion of the general population. Digital health and wellness programs offer the potential for an amplification and increased facilitation of support and healthy preventive strategies in the general population, but older patients encounter numerous challenges with regards to potential usability and retention. Our findings on older adult adherence with regards to mobile adoption were similar to adherence rates previously published on the general population, arguing for the notion that older adults represent a particularly promising group of patients who may benefit from the design and implementation of digital programs aimed at their demographic . The useMany of the digital offerings today both in the private and public marketplace should also emphasize broader integration, complementing existing medical system infrastructure. The data provided by such digital applications may provide primary care providers and gerontologists with additional critical data with regards to activity and behavior that may lead to adjustments in treatment strategies or approaches . Future Our study had several limitations. First, while this study was broadly inclusive of all interested participants in the mobile platform, recruitment was done via active users for the program, so a selection/motivation bias may have been present. Additionally, as this was a naturalistic observation report, we did not have an a priori comparison group, although our comparisons to extant literature on user retention and satisfaction with mobile apps supported our conclusion that older adult users adopted the mobile technologies at similar rates . FinallyIn conclusion our study found that older adults had high and sustained engagement in a digital wellness app/program. Our work suggests that digital health and wellness programs should not be limited to younger age demographics and can be adopted by older adults. The expansion of a breadth of digital healthcare products for the general population offers the promise of improving the adoption of healthy lifestyles and behavior that can ultimately positively impact user well-being. Older individuals in particular may stand to benefit from such programs. Moving forward, it is vital to put forth a program of work aimed at understanding the unique challenges and needs of older individuals, particularly within the digital health sphere. By doing so, clinicians, researchers, and industry may help bridge any potential digital divide and provide broad based, tailored interventions to improve care and patient well-being across the age spectrum.


Chronic wasting disease (CWD) is a prion disease circulating in wild and farmed cervid populations throughout North America (United States and Canada), Europe , and South Korea. CWD is a long-term threat to all cervid populations and to cervid hunting heritage, with the potential to cause substantial economic losses across multiple sectors. In North America, hunting and farming industries focused on the processing and consumption of white-tailed deer (WTD) venison are particularly vulnerable to CWD prion contamination, as millions of WTD are consumed annually. Real-time quaking-induced conversion (RT-QuIC) is a highly sensitive assay amplifying misfolded CWD prions in vitro and has facilitated CWD prion detection in a variety of tissues and excreta. To date, no study has comprehensively examined CWD prion content across bulk skeletal muscle tissues harvested from individual CWD infected WTD. Here, we use RT-QuIC to characterize prion-seeding activity in a variety of skeletal muscles from both wild and farmed CWD-positive WTD. We successfully detected CWD prions in muscles commonly used for consumption  as well as within tongue and neck samples of WTD. Our results suggest that CWD prions are distributed across the skeletal muscles of infected WTD. We posit that RT-QuIC will be a useful tool for monitoring CWD prions in venison and that the method  could be used to reduce and/or prevent CWD prions from entering animal and human food chains. Odocoileus virginianus), mule deer, elk, red deer, caribou, reindeer, and moose. The disease is a direct threat to a number of cervid-related multibillion-dollar economic sectors, including both agricultural and hunting industries, and it is now prevalent in the USA and Canada with additional cases in Korea, and Scandinavian regions1. As with other transmissible spongiform encephalopathies3, CWD prion seeds (PrPCWD) consist of misfolded cellular prion protein (PrPC) which form β-sheet-rich amyloid fibrils through inducing conformational change and polymerization of native PrPC. The central nervous system (CNS) typically contains the highest load of prions in a terminally diseased animal in comparison to peripheral tissues and body excreta due to the abundance of PrPC in nervous tissues4.Chronic wasting disease (CWD) is an infectious and fatal prion disease transmitted among cervids, including white-tailed deer  and Food Safety and Inspection Service, United States Department of Agriculture  consider venison from CWD-positive animals as adulterated and unsuitable for consumption8. While there is no evidence of CWD transmission to humans1, the National Institutes of Health and Centers for Disease Control and Prevention suggests that people should not consume known CWD-infected venison.Recent studies have shown that there are compelling reasons to suggest that CWD poses a non-zero risk to a variety of mammals, including humansCWD by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC)9. These standardized methods for detecting CWD are designed to have consistent protocols with quantified estimates of test accuracy that are scalable to meet the needs of agencies conducting surveillance and monitoring to manage the disease. However, there are limitations to the existing antibody-based diagnostic approaches, namely relatively poor sensitivity as well as the inability to screen biofluids and environmental samples. In the past two decades, the detection of prion seeding activity has been greatly enhanced by highly sensitive methods involving amplification of protein misfolding in vitro, such as protein misfolding cyclic amplification (PMCA) and real-time quaking-induced conversion (RT-QuIC)10. PMCA uses rodent brain homogenates as the substrate to amplify misfolded prions and Western Blotting as the output12. RT-QuIC utilizes recombinant PrPC, commonly from rodent sources, as the substrate for prion amyloid formation, the real-time reporting of which is enabled by thioflavin T (ThT) binding and detection15. Although RT-QuIC demonstrates unparalleled detection sensitivity and specificity for brain and lymphoid tissues, it has lower sensitivity for other sample types; this has in-part been ascribed to lower prion density and RT-QuIC reaction inhibitors16. Importantly, the inhibitory effect of certain tissues—likely due to their biochemical compositions17, such as blood20 and saliva, seemed to be specific for RT-QuIC but not PMCA16. Dilutions (diluting out inhibitory effects) and phosphotungstic acid (PTA) precipitation are commonly used to increase RT-QuIC sensitivity by enriching for prions and overcoming effects of RT-QuIC inhibitors20, although other methods exist21.Currently, CWD diagnosis relies on the identification of Proteinase K (PK)-resistant PrP25. Prior studies focused on the detection of CWD prions in skeletal muscle using immunodetection methods have produced mixed results29. PMCA was used to amplify CWD prions in hindlimb muscles from two WTD30. Skeletal muscle tissues from CWD-infected deer contain infectious prions as determined in transgenic mice bioassay29. Despite clear advantages of RT-QuIC as a screening method32, no comprehensive reports are available for detecting CWD prions using RT-QuIC in skeletal muscle.CWD prions have previously been identified in a variety of tissue types and excreta using RT-QuIC, such as the CNS, third eyelids, and feces1. Underscoring this statistic was a well-documented 2005 exposure event in which over 200 participants at a Sportsmen’s feast consumed CWD-positive venison33. Current estimates indicate a 20–50% CWD prevalence rate in harvested WTD from focal areas of southern Wisconsin, however, only 1 out of 3 are tested for the disease33. Collectively, these observations highlight the need for post-harvest production-level monitoring of cervid products used for human and animal consumption.Cervid skeletal muscles are consumed by a growing population of hunters and restaurant clientele and have become a common ingredient in pet food . At the time of this publication, there are no guidelines regarding venison-based detection of CWD and associated food-product surveillance. This observation, combined with the limitations of existing CWD diagnostic tools , has resulted in a situation whereby venison processing can occur without the knowledge of an animal’s CWD status, and it is estimated that at least 15,000 CWD positive cervids are consumed in the USA annuallybrachiocephalicus/sternocephalicus) of wild WTD with known CWD status. Further, we investigated whether CWD prion deposition is limited to certain groups of muscles or if it is more generalized by using multiple WTD skeletal muscle groups across the body, including muscles from the tongue, forelimb (suprascapularis), backstrap (longissimus dorsi), tenderloin (psoas major), and hindlimb (semimembranosus/semitendinosus) from both wild and farmed CWD positive animals independently determined by ELISA and/or IHC.Here, we examine the utility of RT-QuIC for the detection of CWD prions within a broad set of WTD skeletal muscle tissues, including those frequently used for both human and animal consumption. We report the RT-QuIC results for muscles sampled from the neck  of 10 CWD-positive and 10 CWD-negative wild WTD  in addition to experimental design and species differences. It is also possible that particular CWD prion seeds within our samples were partially degraded during autolysis (discussed further below).We then compared the rate of amyloid formation (RAF) among muscles, blood, and lymphoid tissues, all of which were processed using mechanical extraction methods; with methods and results of blood and lymphoid tissues reported by Schwabenlander et al.suprascapularis), backstrap (longissimus dorsi), tenderloin (psoas major), and hindlimb (semimembranosus/semitendinosus). In the blinded run, we were able to detect at least one significantly RT-QuIC positive sample in all the muscle groups tested  of CWD positive animals  selected for testing of neck muscles were strongly positive across multiple tissues and likely were in relatively advanced, yet pre-clinical stages of the disease 32. The stability of prions may vary depending on strains36 and, to date, no RT-QuIC method is available to detect particular CWD strain differences. Further, the progression of CWD affects the deposition of prions in peripheral tissues and it is unclear at what time in the disease progression that prions accumulate in WTD muscles. We note the neck muscles used herein were frozen less than 12 h after collection; however, the other muscle tissues were at various stages of decomposition and underwent multiple freeze–thaw cycles prior to our possession. This difference in tissue preservation and quality potentially accounts for the reduced sensitivity of RT-QuIC upon application, an observation that suggests an altered balance of RT-QuIC inhibitors and active prion seeds and/or degradation of particular CWD prion strains in decaying tissue. Thus, we recommend muscles for RT-QuIC-based analyses of CWD prions be frozen (at either –20 °C or –80 °C) as soon as possible after collection, ideally less than 24 h.It remains to be determined whether CWD prions are detectable in skeletal muscles that were not sampled herein or in similar studies using amplification-based methods, such as PMCA and RT-QuIC. Although we were unable to detect PrP28. However, the cellular origin of PrPCWD in skeletal muscle, whether in myocytes, erythrocytes, neurons, epithelial cells, or any other cell type, is inconsequential to the recommendations of not consuming venison from CWD-positive animals or the potential for RT-QuIC-based venison screening as venison products are a matrix of multiple tissues and cell types.Based on the results from well-preserved neck muscles, we posit that the freeze–thaw method has the most potential for large-scale diagnostic screening of venison, as it is cheaper and easier to perform. For samples with heavy prion loads, such as tongue, all methods used in this study agreed on the positivity of prion-seeding activity. For poorly preserved sample types, collagenase A outperformed the freeze–thaw method and trypsin digestion in terms of identifying more RT-QuIC positive muscle samples from CWD positive animals. Surprisingly, trypsin digestion yielded a high RAF and did not require additional dilutions of the final resuspension as needed by other methods. This could be due to the digestion of protein inhibitors by trypsin and/or superior ability of trypsin to free prions from examined tissues. Additional optimization of the methods presented here is needed for protocols focused on suboptimal sample types. It is possible that the prion seeding activity we detected in the collected muscle tissues is from non-muscle cell types as reported by Daus et al.Our findings suggest that CWD prions occur throughout an array of WTD muscles and further investigation, from an anatomical perspective, is needed to understand the extent of this distribution. Future studies focusing on larger sample sizes with systematic, bilateral samplings of well-preserved muscle samples throughout the body are needed to assess, validate, and improve the presented method for its application, as well as quantify the load of CWD prions present. Longitudinal characterization of prion deposition  in a variety of high-quality muscle samples, such as those conducted for saliva, lymphoid tissues, and feces is needed to better understand the pathophysiology of CWD in deer and other cervids. Our study provides the foundation for the development of RT-QuIC-based screening of venison and venison-related products associated with food processing pipelines for CWD-prions.32. To blind investigators, researcher “A” subsampled approximately 300 mg of each sample, placed them individually in 1.5 ml tubes, and re-labeled them in a randomized numerical order. Researcher “B” carried out the muscle processing and RT-QuIC and was blinded to the original identity of the samples. ELISA and IHC results for animals examined herein are presented in Supplementary Table The RT-QuIC muscle protocols  were initially used on a small subset of CWD positive and not-detected neck muscle tissue samples. After refining our methods, we then tested the protocol on a larger set of neck muscles from ten CWD positive and ten CWD not detected deer, with CWD status determined by ELISA, IHC, and RT-QuIC analyses on lymphoid tissues from the animals reported by Schwabenlander et al.brachiocephalicus/sternocephalicus) tissue samples collected from wild WTD through 2019 agency culling operations in southeast Minnesota conducted by the Minnesota Department of Natural Resources in conjunction with USDA APHIS Wildlife Services as described by Schwabenlander et al.32  muscle homogenates in 1× PBS were prepared in tubes with 1.5 mm diameter zirconium oxide beads using a Beadbug homogenizer at top speed for 180 s. The homogenates underwent three cycles of flash freeze–thaw consisting of 3 min in dry ice and 3 min at 37 °C. The homogenates were subjected to additional homogenization at top speed for 180 s using the Beadbug homogenizer. The mixtures were then centrifuged at 5000 rpm for 3 min. 500 µl of supernatants were used for centrifugation at 15,000 rpm, 4 °C for 40 min. The resultant pellets were resuspended in 100 µl of 1× PBS then incubated with 7 μl of 4% (w/v) phosphotungstic acid (Sigma-Aldrich) in 0.2 M magnesium chloride. The mixtures were then incubated at 37 °C and 1500 rpm for 1 h in a ThermoMixer (Eppendorf) before being subjected to centrifugation for 30 min at 15,000 rpm, 4 °C. Pellets were resuspended in 10 µl of 0.1% (v/v) SDS/PBS/N2. 2 μl of 10-1 diluted resuspension was used for optimal result.This method was inspired by a combination of existing RT-QuIC protocols28. 10%  muscle homogenates and 180-s homogenization were carried out as described above. 350 μl homogenates were mixed with equal volume of 2× collagenase A  or trypsin (Gibco) solutions. The mixture was incubated at 37 °C, 700 rpm for four hours. After being homogenized again for 90 s, the mixtures were centrifuged at 5000 rpm for 3 min at 4 °C. The supernatant was then transferred to another tube and mixed with an equal volume of 2× protease inhibitor cocktail (Sigma-Aldrich). This was followed by steps including centrifugation at 15,000 rpm for 40 min as the freeze–thaw method. 2 μl of the final suspensions were diluted tenfold and added to the RT-QuIC reaction. The additional dilution was not necessary for trypsin digestion.This method for RT-QuIC was modified from the PMCA method developed by Daus et al.32. All ingredients of RT-QuIC master mix  were filter-sterilized through 0.22 µm PVDF filters. 98 µL of the master mix was pipetted into wells of 96-well black clear bottoms plates. The plate was sealed with clear tape after 2 µL samples were added. Plates were then shaken on BMG FLUOstar Omega microplate readers  at 700 rpm . Fluorescence was recorded after 21 shake/rest cycles using a 450 nm excitation filter and 480 nm emission filter. The gain was set to 1600. The machine performed 21 flashes/well and no well-scan was conducted. 45 °C, 50 °C, and 55 °C were used. 55 °C was only used for investigating whether decomposing tissues would have converging dilutions. 50 °C was used for enzymatic digestions.Recombinant hamster PrP  production and filtration followed the methods of Schwabenlander et al.www.graphpad.com. RT-QuIC data from four or eight replicates were used for calculating the rate of amyloid formation (RAF) for muscles, which is defined by the inverse of the time to reach the fluorescent threshold15. The threshold was calculated as ten standard deviations above the average baseline fluorescence unless otherwise specified. We observed variable RAF values across the four microplate readers used for our analyses . In no instance did this impact our positive or negative controls. However, due to RAF differences among plate readers, this threshold could not be applied to all plates. In these rare circumstances, the threshold was calculated as two times the background fluorescence in each well. The differences in RAF calculated by these two methods for a true RT-QuIC positive sample is usually less than 0.01, therefore not influencing general comparisons of RAF among plates. The one-tailed Mann–Whitney unpaired u-test was used to test the average difference between samples and corresponding negative controls on the same plates. Quantitative analysis of CWD prion load in muscles was conducted as described by Henderson et al.15.Statistical analysis and plotting of fluorescence data from RT-QuIC were conducted using GraphPad Prism version 9.0 for Windows, GraphPad Software, San Diego, California USA, https://research.umn.edu/units/iacuc/submit-maintain-protocols/overview). All CWD positive deer were submitted to the University of Minnesota College of Veterinary Medicine for disposal of infectious prions and were sampled prior to their disposal. White-tailed deer were euthanized by the Minnesota Department of Natural Resources (MN DNR) for annual culling efforts to control the spread of CWD in Minnesota following MN DNR state regulations and euthanasia guidelines established by the Animal Care and Use Committee of the American Society of Mammalogists37. All methods and all experimental procedures carried out during the course of this research followed University of Minnesota guidelines and regulations as approved by the Institutional Biosafety Committee under protocol #1912-37662H. This study was also carried out in compliance with the ARRIVE guidelines (https://arriveguidelines.org). We confirm that no human tissues were used for the research performed herein.No white-tailed deer were euthanized specifically for the research conducted herein and all tissues were secured from dead animals or loaned for RT-QuIC analyses. For these reasons, the research activities conducted herein are exempt from review and approval by the University of Minnesota Institutional Animal Care and Use Committee (as specified CWD negative animals were euthanized by the Minnesota Department of Natural Resources for routine annual culling efforts to control the spread of CWD in Minnesota and were not sampled specifically for the current study. Tissue samples were provided by the MN DNR.Supplementary Figures.Supplementary Table 1.


Responsive methods and measures are needed to bridge research to practice and address public health issues, such as older adults’ need for multicomponent physical activity. The objective of this study was to detail the longitudinal, quasi-experimental work that spans 5 years to describe outcomes across RE-AIM  dimensions of integrating a physical activity intervention for older adults into the Cooperative Extension System through the assess, plan, do, evaluate, report (APDER) cycle.The participant-level intervention is Lifelong Improvements through Fitness Together (LIFT), an 8-week, group dynamics-based, strength-training program with 16 in-person sessions. The implementation intervention applies the iterative APDER cycle based on feedback for each dimension of RE-AIM. Each year, the APDER cycle was used to embed data collection procedures at the instructor and participant level to reveal the next evolution of the program.Each evolution of LIFT was measured through a pretest and posttest quasi-experimental design. Data were collected on each RE-AIM dimension through participant surveys and functional fitness assessments, number and representativeness of trainees, and process evaluation.Overall, LIFT was expanded to 4 states with 275 instructors, reaching 816 older adults; consistently improved functional fitness outcome measures; demonstrated strong program adherence; and was seen as feasible and enjoyable by instructors and participants. LIFT is now undergoing adaptations for virtual delivery as well as updating the exercise protocol to introduce yoga postures that target flexibility and balance.Overall, ongoing adaptations were necessary to ensure the program continued to fit the mission, values, and resources of the delivery system. Public health implications to support the need for ongoing adaptation include embedding pragmatic measures of adaptations and RE-AIM into standard evaluation pathways and using iterative APDER cycles. Multicomponent physical activity interventions are needed to increase the proportion of older adults meeting the Physical Activity Guidelines for Americans.Because a one-size-fits-all approach has shown to thwart the translation of evidence-based programs into practice, a focus on intervention core elements and adaptability has emerged.Based on the needs of different audiences, researchers are called to train and support delivery staff in their ability to adapt, implement, and evaluate community-based efforts.The lofty goal of integrating evidence-based interventions into community settings—and all the models, measures, and methods available for this task—leaves one wondering if this effort is a service for improving the lives of participants. A disconnect exists between the outcomes valued by the systems that house researchers and those of community stakeholders. Academics are pushed within a publish-or-perish cycle , whereasTo address this need for pragmatism, generalizability, comprehensive planning, and evaluation , the RE-These responsive methods and measures can be used to address one of the most prominent public health issues affecting the health of the aging population: the need for social engagement and multicomponent physical activity. Low physical activity compliance indicates that efficacious exercise programs for older adults are not readily translated into sustained practice . AlthougFew studies have detailed the long-term process of delivering interventions in the real world, including using an iterative process to document and respond to adaptations through a research practice–partnership . The purThe APDER  process was collaboratively conducted by a university-based exercise specialist, graduate research assistants, and the Physical Activity Leadership Team  . To suppLIFT is an 8-week, group dynamics-based strength-training program that has 16 in-person sessions . During Repetition of LIFT exercises in each class  and across the 8 weeks allows participants to become familiar with the routine over time. Participants are asked to engage in aerobic activity to reach a minimum of 150 minutes of moderate-to-vigorous aerobic activity per week outside LIFT class time. Participants who were previously inactive, however, are encouraged to move more as they progress to meet recommendations. Instructors facilitate goal setting, feedback, and self-monitoring to increase aerobic activity levels. Ultimately, core elements of LIFT provide opportunities for group engagement , experiential learning for strength training exercises (repetition), and promotion of behavior change strategies .LIFT was tested in 1 state system before its national launch. Based on the success of the program to retain participants, objectively measured functional fitness improvements, and ease and enjoyment of program delivery, PALT adopted LIFT as a statewide program ,26. OnlyP = .045), to feel that the physical activity interventions are not part of their job (P = .04), and to report that they are not physically active, so do not feel comfortable delivering a physical activity intervention (P = .001). Deliverers were significantly more likely (P = .02) to be preparing to deliver a physical activity intervention than their nondeliverer counterparts.In a complementary investigation, a survey was distributed and semistructured interviews were conducted to determine why educators who attended LIFT training chose to deliver the program or not. Intent to deliver LIFT was based on the Stages of Change  and a 5-Overall, deliverers and nondeliverers reported high training satisfaction, the need for structured peer support, and a desire for ongoing training. Frequently reported barriers to implementation included the complexity of the intervention, cost of equipment, and low self-efficacy in physical activity and physical activity delivery. Frequently reported facilitators to adoption included assistance from the research team and other Cooperative Extension staff to reduce delivery burden, positive perceptions of pragmatic fit of the intervention, and positive perceptions of the effectiveness of the intervention. Nondeliverers were more likely to report barriers than facilitators, although deliverers reported both barriers and facilitators.Based on older adult efficacy and agent feedback and enthusiasm, a standardized training protocol was developed and vetted through PALT. The training program involves detailed explanation of underlying program principles  and experiential learning to practice the exercises and fitness assessments in small groups. After the 8-hour, in-person training, ongoing assistance and support was provided by use of web conferencing. This assistance aligned with Cooperative Extension’s standards of ongoing implementation for peer education, program support, and specialists’ availability.Older adults (aged ≥65 y) with a working comprehension of English  and residents of participating counties were eligible to join the program. Cooperative Extension provides open-access programming to all Americans as part of its civil rights mandate, including, for example, programs designed for Hispanic audiences ,29. MoreParticipants completed the Physical Activity Readiness Questionnaire for Everyone, which was developed for inclusion of older adults who might benefit from participating in physical activity, but who have a managed chronic condition. Agents recruited cohorts of older adults from within the counties they serve. Each agent used a variety of methods for recruitment including targeted mailings, newsletters and newspapers, word of mouth, flyers, and presentations at existing programs. Agents also leveraged existing community ties to recruit from local retirement and assisted living facilities. The Virginia Tech Institutional Review Board approved the entirety of this work.Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) data collection methods and adaptations to LIFT core components were determined through annual reviews of LIFT program evaluation data, captured in Cooperative Extension annual reports. These reports were based on data acquired through a pragmatic, quasi-experimental, mixed-methods evaluation protocol implemented from 2016 through 2020. Each year, research team members collated individual-level outcome data  as well as number and representativeness of trainees and process evaluation . RE-AIM annual reports were developed based on national requirements of Cooperative Extension impact statements, which discuss relevance, response, and results. Impact statements are a combination of quantitative and qualitative data. More specific data analysis, based on measurement, are reported in primary outcome articles elsewhere ,26,30.We present adaptations based on RE-AIM dimensions  and a raFrom 2016 through 2018, LIFT was evaluated in its original state, reaching 258 participants using 21 trained educators. In 2016, 139 older adults participated; in 2017, 63 participated; and 56 participated in 2018. Participants were predominantly White (70%) and aged 73, with a body mass index of 31. Overall, participants provided positive feedback about LIFT. Data were used in annual impact statements required by the state system that include program relevance, response, and results. Reach, effect , and illustrative quotes were the data used to drive decision making.Program results (2016–2018) were considered strong for a Cooperative Extension program and from 2018 through 2019, 3 additional states were trained for LIFT: Wyoming, Pennsylvania, and North Carolina. Through these partnerships, an additional 269 LIFT instructors (agents and community partners) were trained: 24 in North Carolina, 13 in Wyoming, 114 in Pennsylvania, and 83 additional instructors in Virginia .www.parcilab.org/lift. The repository is updated as needed and contains all paper and electronic versions of data collection tools, training slide decks, and all program materials.Although functional fitness assessment  remainedTo produce an annual national impact statement, all state LIFT coordinators were asked to complete a 5-minute report — based on Adaptome  and RE-AAs with many other public health interventions, LIFT was adapted to virtual delivery in response to COVID-19. In summer 2020, a pilot project to examine the feasibility and effects of delivering LIFT by web conference was conducted through the Virginia Cooperative Extension. The project resulted in 11 participants with a weekly attendance average of  participants. Through process evaluation, autoethnographic field notes, and participant tracking during the program, we detected that group dynamics strategies needed adaptation and that participants facilitated discussion by using audio and video. We anticipate that when in-person rapport is challenging, online LIFT delivery will encourage use of audio and video for additional contact with the instructor outside-of-class through social media posts, emails, and optional telephone calls. .Testing the adapted and newly packaged LIFT program took 5 years, a substantial decrease from the 17- to 24-year lag time for translation of research to practice . OverallFirst, we propose pragmatic measures of adaptations and RE-AIM that can be embedded within the standard evaluation pathway ,8,12. AlSecond, we acknowledge the importance of the iterative cycle of assess, plan, do, evaluate, report and the nonlinear timeline ; a full-Third, we aim to remove academic control of a community-based physical activity program. We do this, in part, by providing an open-access program repository that includes materials on how to be a state administrator, how to provide training, and how to deliver and evaluate LIFT. This access is unique because 1) many evidence-based program repositories exist, but practitioners cannot always readily download materials to deliver the intervention ; 2) manyFinally, intervention costs are often a barrier to increasing the scale of a program . The opeAs another example, agents in another state were trained in and delivered Strong Women, but the cost was prohibitive and a similar program, Extension Get Fit, was developed. Extension Get Fit was originally based on the same core exercises as Strong Women. However, program drift occurred over the years until agents and state-level staff were unclear as to the purpose of the program, the primary audience to focus on , or intended outcomes . As the primary outcome of the program, functional fitness test results were reported as indicators in required national-level reports. Fewer participants improved in the aerobic endurance and agility portions of the functional fitness test than in the strength training components, likely because an aerobic warm-up was not consistently included as part of the Extension Get Fit program. Rather than incorporate aerobic activity as part of Extension Get Fit, as was incorporated into LIFT, staff created an additional circuit-training program that included aerobic activity. Participants also expressed interest in yoga and flexibility, and similarly, instead of incorporating a flexibility component into Extension Get Fit, another program focusing on chair yoga was added. The state system was ultimately supporting 3 separate programming efforts. County residents chose among the programs and did not receive an evidence-based program that included the comprehensive functional fitness components of strength training, aerobic activity, and flexibility. Multicomponent programs align with the national physical activity recommendations for older adults (ages ≥65 y) and have been shown to be more effective at improving physical activity outcomes .Our study has limitations. First, all of the studies  discussed and designed were quasi-experimental, meaning that no randomization or causation could be explored. Second, as with any community work, representativeness and recruitment are limitations, as efforts to recruit undergo continuous improvement to reach intended audiences . The stuCommunities desire interventions that are easy to deliver and have strong evaluation protocols, but they need assistance in the selection, adaptation, delivery, and evaluation of these interventions. Although it is an implementation laboratory, even the Cooperative Extension is not able to adopt and adapt interventions with fidelity without effective dissemination and intervention testing. More work should be directed to the continued testing, adapting, reporting, and accessibility of evidence-based interventions. This evaluation helps demonstrate ways in which intervention information and adaptations can be conducted, presented, and made available. Generally, we suggest that other organization and integration efforts use RE-AIM and APDER cycles to track changes. Specifically, we demonstrate that the core elements of a behavioral intervention for physical activity promotion among older adults can adapt over time while continuously supporting functional fitness.


This presentation describes how we plan to address the challenges of testing an evidence-based caregiver program in a real-world setting without the infrastructure and personal contact of a typical RCT. Instead of screening participants for eligibility, clinic staff will pre-identify participants whom clinicians then confirm. Each clinic will include Tele-Savvy as standard of care; we will thus be able to obtain IRB approval for a waiver of consent. By securing agreement from each clinic to incorporate a small set of standard instruments  into their standard operating procedure of routinely collecting caregiver data gathering, we will be able to eliminate the need for a central research staff to conduct baseline and follow-up interviews and will, instead, collect key outcome data through the electronic health record. Instead of in person training of Tele-Savvy facilitators, we will rely on an online training program and facilitator manuals.


A). The medial head of gastrocnemius separates the popliteal vein and the occluded (entrapped) popliteal artery. CT also shows entrapment of the right popliteal artery, due to extrinsic compression by the abnormally sited tendon of the medial head of gastrocnemius, which separates the artery and vein, mirroring the muscular anatomy on the left (B/Cover).A 63-year-old asymptomatic man with unlimited exercise tolerance is investigated for suspected popliteal aneurysms, due to absent pedal pulses and prominent popliteal pulsations. Contrast-enhanced computed tomography (CT) shows occlusion of the left popliteal artery with geniculate collaterals surrounding the popliteal vein (C). Axial balanced flow fast field echo magnetic resonance images and corresponding CT axial images demonstrate that the left medial head of gastrocnemius passes between the popliteal artery and popliteal vein. However, the aneurysmal right popliteal artery and the right popliteal vein are both located medial to, and are not separated by, the medial head of gastrocnemius (D).A second 55-year-old man, normally walking 10-12 miles per day without restriction, presents with acute right leg claudication at 200 m. Contrast-enhanced CT demonstrates left popliteal artery stenosis with post-stenotic dilatation and right distal popliteal embolic occlusion due to a popliteal aneurysm with thrombus secondary to bilateral popliteal entrapment syndrome (PAES) .Both patients consented to the publication of the case details and relative images.


Background: An increase in opioid use has led to an opioid crisis during the last decade, leading to declarations of a public health emergency. In response to this call, the Houston Emergency Opioid Engagement System (HEROES) was established and created an emergency access pathway into long-term recovery for individuals with an opioid use disorder. A major contributor to the success of the program is retention of the enrolled individuals in the program. Methods: We have identified an increase in dropout from the program after 90 and 120 days. Based on more than 700 program participants, we developed a machine learning approach to predict the individualized risk for dropping out of the program. Results: Our model achieved sensitivity of 0.81 and specificity of 0.65 for dropout at 90 days and improved the performance to sensitivity of 0.86 and specificity of 0.66 for 120 days. Additionally, we identified individual risk factors for dropout, including previous overdose and relapse and improvement in reported quality of life. Conclusions: Our informatics approach provides insight into an area where programs may allocate additional resources in order to retain high-risk individuals and increase the chances of success in recovery. According to the U.S. Department of Health and Human Services (HHS), an estimated 10.1 million people aged 12 or older used opioids in the United States in 2019, and 1.6 million people had a diagnosed opioid use disorder (OUD) [The Houston Emergency Opioid Engagement System (HEROES) was established in 2018 and created rapid access to a long-term recovery pathway for individuals with OUD. The program includes access to board-certified physicians for initiation of an approved medication for opioid use disorder (buprenorphine), plus additional comprehensive care that incorporates peer recovery coaching, individual and group counseling, and navigation to other services and resources based upon need, including recovery housing, employment, and support for justice-involved individuals [As has been previously demonstrated, longer treatment retention is associated with a greater likelihood of abstinence from opioids . HoweverPrevious studies have focused on identifying factors that reduce dropout rate. Two studies of 78 and 202 participants focused on short-term dropout  ,10. The Machine learning methods for developing prediction models are data-driven and growing in their application to substance use treatment analysis . For exaTherefore, we decided to utilize machine learning methods to improve retention rates in our program and to inform the literature on treatment retention. Leveraging this approach may offer program administrators and clinicians the opportunity to divert resources and engage participants at the highest risk for drop out early in the program. We introduced a machine learning model to a retrospective database of over 700 enrolled patients to identify individuals at higher risk of dropping from the program after 90 and after 120 days. The benefit of our approach over previous methods is that we are using a richer set of information on each participant in the program, including demographic, clinical, behavioral/mental health, and extensive history about prior substance use and criminal activity. Furthermore, as the program is ongoing, we can directly implement an intervention program to retain those at high risk for early dropout (after 90 and 120 days). Thus, our encouraging model performance in detecting the set of risk factors in these high-risk individuals provides a tool for our program and like-programs across the U.S. for retention and ultimately for improving recovery for individuals suffering with OUD, as they are retained longer in the program.As of May 2021 (here forth termed “index date”), the program database included 715 individuals that had joined more than 90 days before the index date and 691 individuals that had joined more than 120 days prior to the index date. The data are collected through self-reported questionnaires and through a health evaluation by a nurse practitioner or physician assistant. Data are stored in a Research Electronic Data Capture (REDCap) project database  see Sup. Out of We tested several machine learning classifiers, including logistic regression, radial basis support vector machine, random forest , and five different variants of ensemble based on boosting algorithms based on decision trees, including Adaptive boosting (AdaBoost), Gentle Boost, LogitBoost, Robust Boosting, and totally corrective boosting ,16,17,18q-values  false discovery rate) of .05 were selected.We estimated the predictor importance by permutation of out-of-bag predictor observations in the random forest classifier model. Additionally, we verified that these ranking were consistent with the association in statistical tests, where we used Mann–Whitney U test between the retained and dropped out groups for continuous factors and Fisher exact test for dichotomous factors. Significant factors with We evaluated the dropout rate in increments of 30 days , identifWe tested several machine learning classifiers to predict dropout Methods, , selectiWe next identified factors associated with dropout using ranked predictor importance in the classification model using out-of-bag predictor observations technique and verified using statistical tests on each independent factor (Methods). There were 27 factors that passed the false discovery rate of 0.05 at both time points .p < e−15), improvement in quality of life , and whether they relapsed since joining the program , see Three factors were consistently ranked high in both the 90- and 120-day check dates, identified both by statistical test and predictor importance in the prediction model. These features include whether the individual have overdosed in the past -adjusted, The top factor was whether the individual had overdosed in the past. Individuals who dropped out had 3.2 to 4.8 times higher incidence of past overdosing . The second top factor was improvement in quality of life. More than 94% of the individuals who dropped out have reported improvement in their quality of life while only 64% (90 days)–59% (120 days) in the retained group reported improved quality of life. Finally, the group of individuals who dropped out had a 1.8–2 times higher incidence of reported relapses since joining the program.We have presented a model for predicting early dropout from a long-term recovery program for opioid use disorder at 90 and 120 days. Our model obtained good sensitivity and specificity and enables the identification of the top contributing factors. Overall, analyses of treatment dropout rates were low for program participants, with 85% active and engaged in treatment at 90 days and 76% active at 120 days post enrollment. Compared to a recent systematic and meta-analysis review of dropout rates that reports average dropout rates for targeted opioid treatment programs (39%) and target heroin treatment programs (26%), overall retention was high for participants in the analyzed program model . While rSome variables were significantly related to retention probability. The top contributing factor was whether the individual had overdosed in the past. Individuals who dropped out of the program had overdosed in the past more than those who were retained, suggesting that individuals with an extensive history of substance use may need additional support maintaining engagement in an outpatient program. A recent study found individuals who experienced a non-fatal overdose were at increased risk of successive overdose and were more likely to engage in polysubstance use ,21. MoreThe second top factor was improvement in quality of life. More than 94% of those who dropped out reported an improvement in their quality of life, while only 64% (90 days)–59% (120 days) in the retained group reported improvements, per the quality-of-life survey. We estimate that individuals who had experienced improvements in their quality of life may hold the perception of doing well and feel that they do not need the same level of treatment to maintain their recovery, or they may have transitioned to longer-term programs with less intensity. This type of non-adherence to treatment or medication protocols when one is feeling better is not isolated to OUD. Similar studies focused on patients with depression have found that individuals stop taking their medications when they are feeling better . While mFinally, individuals who dropped out had higher incidence of relapses since joining the program, which is likely an indication they needed increased accountability, additional or varied support, or would benefit from a referral to a higher level of care . OUD is Recovery from addiction is multifactorial and may take multiple attempts for an individual. Treatment that includes MOUD, behavioral health, and social support is widely accepted as the most effective treatment; yet, a considerable number of individuals receiving treatment perpetually relapse and often overdose, suggesting treatment resistance in some patients with OUD . There ap < 0.008), but did not reach the top ranked features listed in Previous studies have identified younger age, cocaine and heroin use, lower doses of methadone, criminal activity/incarceration, and negative attitudes to methadone maintenance treatment as associated factors ,44. WhilWhile we obtained good prediction performance, there could be factors that were not collected on these individuals that affect their choice to drop out of the program. One limitation of our model is that we use only structured factors. However, the program also collects free text information on participants that could potentially be converted to additional features that will enhance the model for future studies. Overall, our findings are consistent with previous research on treatment retention and support further exploration of treatment-resistant opioid use disorder.The findings from this research support the concept of using a tiered risk approach, ranging from high to low risk of early dropout. A predictive model may be developed with a greater understanding of the factors that influence patient participation choices. The model allows for a system of classification; therefore, resources can be allocated efficiently, and treatment plans can be tailored to the individual. For example, participants in the highest risk group may receive more intensive follow-up from peer recovery coaches multiple times per week and might be required to attend additional group counseling and one-on-one counseling. Higher risk groups may also be required to submit urine drug tests on a regular basis to confirm abstinence from illicit substances, while participants in the lowest risk group may receive follow up from a peer recovery coach less often and be required to attend group counseling and one-on-one counseling every few weeks. By customizing the treatment and care provided to participants within each group, it becomes possible to provide participants with the greatest needs with the attention and resources required.In this research, we analyzed variables for persistence in treatment for a cohort of individuals engaging in a program for OUD. We developed a data-driven prediction model using machine learning techniques and found that individuals with prior medication for OUD and multiple relapses may be considered higher risk and more likely to drop out of the program. Further qualitative research is needed to determine the optimal timing of interventions and the varied services needed for individuals to persist in treatment.