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We developed contingency tables to compare the independent variables with the outcome. Three bivariate analyses of independent variables and outcomes were done: being screened versus not being screened, which included all patients enrolled; refusing screening versus not being screening for unknown reasons, which included patients that were not screened; and HIV positive versus negative, which included all those screened. Odds ratios (OR) were calculated with 95% confidence intervals (CI). Two multivariate models were constructed using logistic regression, one for predictors of being screened for HIV, and one for predictors of opting out among those not screened for HIV. Both multivariate analyses were done in a stepwise backward manner. Variables associated with the outcome at a p < 0.2 significance as well as others relevant for each of the two outcomes were included in the multivariate model. We excluded missing data in the analysis of the determinants of not being screened for HIV. We included 1197 patients (98 were excluded for missing data: 88 on socio economic status and 10 for all other independent variables) in the multivariable model.

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The cohort study included 1295 patients and all were included in our analysis. Figure 1 describes the study population, those screened for HIV and the HIV screening results. Nine were aware of their HIV positive status before the TB diagnosis and fifteen were diagnosed with HIV during the TB episode. HIV prevalence was 1.9% (24/1295) among all TB patients, while it was 2.4% (24/988) among those with a known HIV status (excluding those not tested).Fig. 1Patients with a first episode of tuberculosis and HIV screening in San Juan de Lurigancho, 2010–2011

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Of all HIV screenings conducted among the study participants (76.1%, 979/1286): 81.2% (795/979) were done by the routine TB staff, 18.8% (184/979) were done by the study field workers. Therefore, if the study staff had not conducted additional efforts to those of the routine staff to screen TB patients for HIV, coverage of HIV screening among new TB patients would have been 61.8% (795/1286). Table 1 describes the characteristics of patients that were screened, of those opting out and of those not screened for unknown reasons.Table 1Characteristics of patients with a first episode of tuberculosis by their HIV screening status, San Juan de Lurigancho, 2010–2011CharacteristicsScreenedNot screened for unknown reasonsOpted out of screeningN (%)N (%)N (%)Sex Female394 (39.9%)69 (36.3%)39 (33.1%) Male593 (60.1%)121 (63.7%)79 (66.9%)Age, in years 18–34721 (73.0%)137 (72.1%)83 (71.0%) 35–49210 (21.3%)41 (21.6%)24 (20.5%) > 5057 (5.7%)12 (6.3%)10 (8.5%)Weight loss reported by the patient Yes798 (81.1%)162 (85.3%)94 (79.7%) No186 (18.9%)28 (14.7%)24 (20.3%)Location of health facility in district area Lowest area199 (20.2%)25 (13.2%)8 (6.8%) Middle area314 (31.8%)35 (18.4%)12 (10.2%) Highest area259 (26.2%)73 (38.4%)63 (53.4%) High area215 (21.8%)57 (30.0%)35 (29.6%)Education Primary school or less400 (40.6%)87 (45.8%)60 (50.8%) High school365 (37.0%)67 (35.3%)36 (30.6%) Higher education221 (22.4%)36 (18.9%)22 (18.6%)Socioeconomic status Poor240 (26.0%)48 (27.3%)30 (28.3%) Not poor685 (74.0%)128 (72.7%)76 (71.7%)Marital status Married / cohabiting369 (37.4%)65 (34.3%)53 (45.0%) Divorced72 (7.3%)16 (8.4%)5 (4.2%) Single521 (52.8%)101 (53.1%)56 (47.5%) Widow25 (2.5%)8 (4.2%)4 (3.3%)Illegal drug consumption No838 (84.9%)140 (73.7%)99 (83.9%) Yes149 (15.1%)50 (26.3%)19 (16.1%)Alcohol consumption (CAGE score) Alcoholism52 (8.9%)13 (10.7%)7 (9.3%) No alcoholism534 (91.1%)109 (89.3%)68 (90.7%)Ex prison inmate Yes49 (5.0%)8 (4.2%)4 (3.4%) No936 (95.0%)182 (95.8%)114 (96.6%)Diabetes mellitus, as reported by the patient Yes41 (4.2%)9 (4.7%)5 (4.2%) No944 (95.8%)181 (95.3%)113 (95.8%)Type of TB treatment regimen Regimen for drug sensitive TB970 (98.3%)189 (99.5%)116 (98.3%) Regimens for drug resistant TB17 (1.7%)1 (0.5%)2 (1.7%)Employment Yes695 (70.4%)138 (72.6%)83 (70.3%) No190 (19.3%)40 (21.1%)21 (17.8%) Student102 (10.3%)12 (6.3%)14 (11.9%)Study period 1261 (26.4%)39 (20.5%)34 (28.8%) 2233 (23.6%)42 (22.1%)28 (23.7%) 3258 (26.2%)64 (33.7%)18 (15.3%) 4235 (23.8%)45 (23.7%)38 (32.2%)Place of birth Coastal region611 (62.0%)116 (61.1%)74 (62.7%) Jungle region138 (14.0%)27 (14.2%)19 (16.1%) Andean region237 (24.0%)47 (24.7%)25 (21.2%)

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Among those screened for HIV, the median time between TB treatment initiation and HIV screening was 4 days (interquartile range 0–18 days). In 69.9% (684/979) patients, HIV screening was done before or within 15 days after TB treatment initiation -as per NTP guidelines- and after 15 days of starting TB treatment in 30.1% (295/979) patients.

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Table 2 shows the determinants of not being screened for HIV of the 1197 patients included in the analysis (98 were excluded for missing data: 88 on socio economic status and 10 on a single other variable). Receiving TB care in one of the health care facilities of the higher areas of the district (odds ratio (OR) = 3.38, confidence interval (CI) 95% 2.17–5.28, p < 0.0001 for the highest area and OR = 2.82, CI 95% 1.78–4.49, p < 0001, for the high area) as well as reporting illicit drug consumption (OR = 1.65, CI 95% 1.15–2.37, p = 0.0062) was associated to not being screened for HIV.Table 2Determinants of not being screened for HIV among 1197 patients with a first episode of smear positive pulmonary tuberculosis, San Juan de Lurigancho, 2010–2011CharacteristicsScreenedN(%)Not screenedN(%)Crude OR (95% CI) p Adjusted OR (95%CI) p Sex Female394 (78.5%)108 (21.5%)1 Male593 (74.8%)200 (25.2%)1.23 (0.94–1.63)0.136Age, in years 18–34721 (76.6%)220 (23.4%)0.94 (0.68–1.31)0.752 35–49210 (76.4%)65 (23.6%)1 > 5057 (72.1%)22 (27.9%)1.15 (0.63–2.09)Weight loss reported by the patient Yes798 (75.7%)256 (24.3%)1.07 (0.76–1.51)0.699 No186 (78.2%)52 (21.8%)1Location of health facility in district area Lowest area199 (85.8%)33 (14.2%)11 Middle area314 (87.0%)47 (13.0%)0.89 (0.54–1.47)0.90 (0.54–1.49)< 0.001 Highest area259 (65.6%)136 (34.4%)3.34 (2.15–5.21)3.38 (2.17–5.28) High area215 (70.0%)92 (30.0%2.8 (1.77–4.45)< 0.0012.82 (1.78–4.49)Education Primary or less400 (73.1%)147 (26.9%)1.23 (0.91–1.66)0.153 High School365 (78.0%)103 (22.0%)1 Higher221 (79.2%)58 (20.8%)0.88 (0.61–1.28)Socioeconomic status Poor240 (75.5%)78 (24.5%)1.09 (0.81–1.48)0.556 Not poor685 (77.0%)204 (23%)1Marital Status Married / cohabiting369 (75.8%)118 (2.2%)1.12 (0.84–1.49)0.523 Divorced72 (77.4%)21 (22.6%)0.88 (0.51–1.53) Single521 (76.8%)157 (23.2%)1 Widow25 (67.6%)12 (32.4%)1.57 (0.75–3.29)Illegal drug consumption Yes149 (68.3%)69 (31.7%)1.64 (1.16–2.32)0.0061.65 (1.15–2,37)0.006 No838 (77.8%)239 (22.2%)11Alcohol consumption (CAGE score) Yes52 (72.2%)20 (27.8%)1.28 (0.74–2.22)0.38 No534 (75.1%)177 (24.9%)1Ex prison inmate Yes49 (80.3%)12 (19.7%)0.68 (0.31–1.47)0.305 No936 (76.1%)296 (23.9%)1Diabetes Mellitus, as reported by the patient Yes41 (74.5%)14 (25.5%)1.12 (0.60–2.08)0.725 No944 (76.3%)294 (23.7%)1TB regimen Regimen for drug sensitive TB970 (76.1%)305 (23.9%)1 Regimens for drug resistant TB17 (85.0%)3 (15%)0.70 (0.20–2.44)0.556Employment Yes695 (75.8%)221 (24.2%)10.646 No190 (75.7%)61 (24.3%)0.99 (0.71–1.40) Student102 (79.7%)26 (20.3%)0.81 (0.50–1.28)Study Period 1261 (78.1%)73 (21.9%)1 2233 (76.9%)70 (23.1%)1.13 (0.76–1.67)0.431 3258 (75.9%)82 (24.1%)1.18 (0.80–1.73) 4235 (74.0%)83 (26.0%)1.37 (0.94–2.01)Place of birth Coastal region611 (76.3%)190 (23.7%)10.985 Jungle region138 (75.0%)46 (25.0%)0.97 (0.65–1.44) Andean region237 (76.7%)72 (23.3%)0.98 (0.71–1.35)

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Table 3 compares the characteristics of patients opting out of HIV screening to those of patients not screened for unknown reasons. Attending a health care facility in the highest area of the district was associated to opting out of screening. Patients reporting illegal drug consumption and those enrolled in the third period of the study were more likely not to be screened because of unknown reasons as compared to opting out of screening.Table 3Determinants of opting out of HIV screening as compared to not being screened for unknown reasons in 307 smear positive tuberculosis patients not screened for HIV, San Juan de Lurigancho 2010–2011CharacteristicsOpted out of screeningN (%)Not screened for unknown reasonsN (%)Crude OR (95% CI) p Adjusted OR (95%CI) p Sex Female39 (36.2%)69 (63.8%)1 Male79 (39.5%)121 (60.5%)1.14 (0.70–1.85)0.595Age, in years 18–3483 (37.7%)137 (62.27%)1.04 (0.58–1.84)0761 35–4924 (36.9%)41(63.1%)1 > 5010 (45.5%)12 (54.5%)1.42 (0.53–3.79)Weight loss reported by the patient Yes94 (36.7%)162 (63.3%)0.67 (0.37–1.22)0.194 No24 (46,2%)28 (53.8%)1Location of health facility in district area Lowest area8 (24.2%)25 (75.8%)11 Middle area12 (25.5%)35 (74.5%)1.07 (0.38–3.00)0.0221.21 (0.42–3.49) Highest area63 (46.3%)73 (53.7%)2.65 (1.12–6.30)3.28 (1.32–8.18) High area35 (38.0%)57 (62.0%)1.92 (0.78–4.72)2.18 (0.86–5.56)Education Primary or less60 (40.8%)87 (59.2%)1.28 (0.76–2.16)0.627 High School36 (35%)67 (65.0%)1 Higher22 (37.9%)36 (62.1%)1.09 (0.55–2.13)Marital Status Married / cohabiting53 (44.9%)65 (55.1%)1.44 (0.88–2.35)0.219 Divorced5 (23.8%)16 (76.2%)0.56 (0.20–1.62) Single56 (35.7%)101 (64.3%)1 Widow4 (33.3%)8 (66.7%)0.90 (0.26–3.13)Illegal drug consumption Yes19 (27.5%)50 (72.5%)0.54 (0.30–0.98)0.0370.43 (0.23–0.80) No99 (41.4%)140 (58.6%)1Alcohol consumption (CAGE score) Yes7 (35.0%)13 (65.0%)0.74 (0.29–1.88)0.524 No68 (38.4%)109 (61.6%)1Ex prison inmate Yes4 (46.7%)8 (53.3%)0.81 (0.24–2.74)0.726 No114 (38.5%)182 (61.5%)1Diabetes Mellitus, as reports by the patient Yes5 (35.7%)9 (64.3%)0.90 (0.29–2.75)0.849 No113 (38.4%)181 (61.6%)1TB regimen Regimen for drug sensitive TB116 (38.0%)189 (62.0%)1 Regimens for drug resistant TB2 (66.7%)1 (33.3%)3.29 (0.29–36.6)0.315Employment Yes83 (37.6%)138 (62.4%)1 No21 (34.4%)40 (65.6%)0.88 (0.49–1.60)0.217 Student14 (53.8%)12 (46.2%)1.96 (0.87–4.45)Study Period 134 (46.6%)39 (53.4%)11 228 (40.0%)42 (60.0%)0.79 (0.40–1.53)0.0030.65 (0.33–1.31) 318 (22.0%)64 (78.0%)0.33 (0.17–0.67)0.23 (0.11–0.49) 438 (45.8%)45 (54.2%)0.99 (0.53–1.88)0.71 (0.35–1.40)Place of birth Coastal region74 (39.0%)116 (61.0%)1 Jungle region19 (41.3%)27 (58.7%)1.10 (0.57–2.12)0.663 Andean region25 (34.7%)47 (65.3%)0.80 (0.45–1.42)

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In a bivariate analysis of the characteristics of HIV positivity (including both those diagnosed before the TB episode and those diagnosed during the TB episode) among the 988 patients screened, more men than women were HIV positive (18 (3.0%) vs. 6 (1.5%)), more adults than young adults (9 (4.3%) vs. and 15 (2.0%)) and more patients reporting illegal drug consumption were HIV positive than those reporting never having used illegal drugs (crude OR: 4.24, 95%CI 1.85–9.73). We had insufficient power to conduct a multivariate analysis of predictors of HIV positive status.

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Of the nine patients known to be HIV positive before the TB episode, eight were already on ART. Of the 15 patients diagnosed with HIV during the TB episode, we found evidence that 10 were affiliated to the Ministry of Health HIV program at a referral hospital and 9 were started on ART. We did not find evidence of HIV program enrollment in five patients. These patients may have been enrolled in an HIV program without it being registered in their TB clinical files, they may have attended a private HIV care facility where they have to pay for care and ART, or they may have not been enrolled in an HIV program. The median time between the result of the HIV screening and the first medical consultation of the HIV program, among those 10 patients, was 82 days (IQR, 32–414). The median time between the result of the HIV screening and ART initiation was 148.5 days (IQR, 32–500). The median CD4 cell count among patients enrolled in HIV care during the TB episode was 189 cells/mm3 (IQR, 55–312).

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We found an HIV screening coverage of 76.1% among patients recently diagnosed with smear positive pulmonary TB in an urban context of median TB incidence and low HIV prevalence. Factors associated to not being screened were illegal drug consumption and geographical location of the TB health facility within the study district. Fifteen TB patients were diagnosed with HIV during the TB episode, of which five did not have evidence of HIV program enrollment upon completion of TB treatment.

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In the Americas region, in 2016, 80% persons notified for TB had a documented HIV positive test result, which is above the global proportion for 2016 (57%). In the same year, HIV screening in Peru covered 84% of TB patients . In 2010 (when our study was conducted) the National TB Program reported that 76% of TB patients were screened for HIV . In our study, conducted between 2010 and 2011, we found a fairly high coverage, however, the study staff did additional efforts to screen those that had not being initially screened.

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Only 9.2% TB patients opted out of screening, while 14.7% were not screened for unknown reasons. Patients not screened without explicitly opting out may have not wanted to be screened but did not say so, or the screening may have been delayed or postponed for diverse reasons (patient’s reasons such as not being sure, or fearing HIV screening, or health system reasons such as inadequate follow up of screening request). In South Africa, voluntary counseling and testing was adopted in 2007 but less than half of the TB patient’s accepted HIV screening . In India, 60% of TB patients were screened for HIV and 33% of new HIV diagnoses would have been missed if screening during the TB episode were not done .

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Our finding that living in the higher areas of the district that lie by the hill as opposed to living in the middle and lower areas that are more urbanized, was associated to not being screened. Also, those living in the highest area were more likely to opt out of screening. This may be due to the fact that in higher areas of the district there are fewer health centers and road access may be more difficult. This area of the district has lower socioeconomic status, however, the association we found was independent of that factor and of level of education of the patient. This suggests that health care facility-related factors not measured in this study could be associated to screening coverage. Management of health facilities in Lima is organized in micronetworks within districts. There may be characteristics of these micronetworks in the higher area that do not favor screening, such as number of health staff dedicated to TB activities and poorer supervision practices. This should be further explored in future studies.

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The single patient related factor –among those measured by the study- associated to not being screened was illegal drug consumption. The screening strategy in this group (17% of the TB patients in our study reported use of illegal drugs) should be reinforced. The use of any illegal drug is associated with risk behaviors that may increase the likelihood of acquiring or transmitting HIV infection. In South Africa, fear, low perception of risk and the wish of being treated first and only for TB as well as not being offered screening, was associated to not been screened for HIV . In a similar study in India, uptake of HIV testing was significantly lower in older age groups and females . In Cambodia, married patients, those with a previous HIV screening, a higher level of education and with more access to a health facility were more likely to be screened while self-perceived stigma was associated to not being screened . Peru is a country with a median TB incidence and a concentrated HIV epidemic, but co-infection has increased in recent years. Despite the fact that since 2013, the NTP recommends that every patient diagnosed with TB have to be screened for HIV, 100% screening coverage has not yet been reached.

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Our findings suggest the need of strengthening the reference systems between TB and HIV programs. Despite having a small number of HIV positive patients, we detected a delay between HIV positive result and HIV program enrollment and ART initiation, and we did not find evidence of HIV program enrollment in five patients. The HIV and TB program in Peru are partially integrated but care for both infections is provided in different facilities. Obtaining an appointment at referral hospitals in Lima, where HIV diagnosis is confirmed and managed, can take long and that could be contributing to the delays found . Stigma has been cited in other settings as a cause that discouraged rapid linkage to care of recently diagnosed HIV-positive individuals . Prompt linkage to care for early ART initiation is important to achieve rapid virologic suppression and reduce mortality [30, 31]. A better integration of both programs could reduce barriers [32–34] for timely care and facilitate the initiation of ART. Decentralizing HIV care to peripheral health facilities where TB is managed may facilitate geographical access. Yet, if peripheral facilities are located at the patient’s neighborhoods it may increase stigma and fear of disclosure of HIV diagnosis.

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This operational study has some limitations. We did not obtain the exact reasons for why patients refused screening or why it was not done among those not opting out, which impedes a more precise explanation to our findings. Furthermore, we do not know which would have been the coverage if the study were not conducted. As we made additional efforts to those of the routine staff to screen patients for HIV, we probably overestimated the routine coverage. However, the coverage reported by this study, reflects the potential reach of HIV screening if it is systematically offered to all TB patients. We did not collect risk factors for HIV infection. If we had collected risk factors for HIV infection, we could compare the presence of risk factors among the patients screened, those that opted out and those that were not screened for unknown reasons. Opting out of HIV screening could result from a very low perception of risk or form fear of a positive result because of risk behavior. In studies in Ethiopia and South Africa, adults with TB thought that voluntary counseling and testing could delay TB treatment and that TB treatment should be prioritized . Finally, the small number of HIV TB co-infected patients did not allow a multivariate analysis to predict HIV infection among TB patients. Among the strengths of the study was that it included a large number of TB patients representative of the TB population in the district.

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We found that 76.1% patients recently diagnosed with TB, were screened for HIV. Patients that reported illegal drug use were less likely to be screened. Patients with a recent HIV diagnosis took long to be enrolled in a program for the initiation of antiretroviral treatment. This suggests a suboptimal integration of TB and HIV services since TB is managed in primary care centers and HIV is managed in referral centers such as hospitals. Most studies on HIV screening among TB patients are from countries with high HIV prevalence. HIV screening and management among TB patients in settings with low HIV prevalence (less than 1%), such as Peru should be enhanced to reduce mortality from co-infection.

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Heterogeneity of enterotoxigenic Escherichia coli (ETEC) bacterial virulence factors is a major challenge for vaccine development. ETEC bacteria that produce adhesins to attach to different host receptors and enterotoxins to disrupt fluid homeostasis in small intestinal epithelial cells, are a leading cause of diarrhea in children under the age of 5 years in developing countries and in children and adults traveling from developed countries to ETEC endemic regions [1–3]. Currently, there is no licensed vaccine to protect against ETEC-caused children’s diarrhea or travelers’ diarrhea [4–7]. Because adhesin-mediated bacterial adherence to host cell receptors initiates ETEC infection, vaccines that induce antibodies preventing ETEC bacteria from adhering to host cells have been long regarded effective against ETEC infection.

review

Developing vaccines to prevent ETEC bacteria adherence and colonization, however, is hampered by the heterogeneity of ETEC bacterial adhesins. Different ETEC strains produce immunologically heterogeneous adhesins [8–10]. Antibodies derived from one type of adhesin may not block attachment of ETEC bacteria expressing different adhesins. The conventional approach by mixing together several live or killed strains that express a few different adhesins led to vaccine candidates that induce antibodies against homologous adhesins [11–14]. Recently, a novel strategy using reverse vaccinology and computer-aided structure-based multiepitope fusion antigen (MEFA) vaccine design has been explored to develop a safer and more effective ETEC vaccine.

review

The MEFA technology intends to design structure-defined and epitope-based immunogens to induce broadly protective antibodies against heterogeneous ETEC adhesins , facilitating the development of broad-spectrum ETEC vaccines. We recently constructed 6xHis-tagged adhesin MEFA CFA/I/II/IV, by integrating epitopes (in silico predicted) from the major subunits of the seven most important ETEC adhesins [CFA/II (CS1, CS2, CS3) and CFA/IV (CS4, CS5, CS6)] into a single MEFA protein . Although that MEFA immunogen was shown to induce antibody responses to all seven ETEC adhesins, the 6xHis-tag (six histidines) carried by the recombinant MEFA immunogen may alter protein biochemistry properties . Poly-histidine tag may also induce anti-histidine antibodies against histidine to cause potential adverse effects to human health, thus his-tagged antigens are considered less desirable for human vaccines. Additionally, antigenic structure of that 6xHis-tagged MEFA protein was not characterized.

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Immunogen structure and antigenicity can be characterized empirically and also computationally. Recent advance in computational modeling and structural biology allows to assess structure properties of immunogens and to accelerate vaccine development . In the current study, we cloned the CFA/I/II/IV MEFA gene without the 6xHis-tag, applied computational modelling to in silico characterize the antigenic structure of a tag-less CFA/I/II/IV MEFA, and examined immunogenicity of the new MEFA antigen in mouse immunization. In addition, we examined computational data and empirical data for immunogenicity congruence to assess potential application of computation simulation for structure-based ETEC vaccine development, likely proof of concept of MEFA application in structural vaccinology.

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The tag-less CFA/I/II/IV MEFA chimeric gene was PCR amplified from 6xHis-tagged CFA/I/II/IV MEFA plasmid DNA with primers CFANcoI-F (5′-catgccatggaaatggctagcgcagtagaggat-‘3; NcoI site underlined) and T7-R (5′-tgctagttattggtcaggggt-‘3). PCR products were purified, digested with NcoI and EagI restriction enzymes (New England BioLabs, Ipswich, MA), and ligated into expression vector pET28α (Novagen, Madison, WI). The NcoI restriction site is located at the upstream of the 6xHis-tag region in vector pET28α, thus the new CFA/I/II/IV MEFA chimeric gene should not carry his-tag nucleotides. The cloned tag-less MEFA gene was DNA sequenced.

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Program Rosetta [20–22] was used to generate an initial structure for the tag-less CFA/I/II/IV MEFA protein based on amino acid sequence, with the structure of CFA/I major subunit CfaB (PDB ID 3F85) as the template. The fragment-based library was used to model segments of the tag-less MEFA that did not align with the template and to connect these segments to the aligned segments. A total of 50 comparative models were generated. The one with the top conformer score was selected as the final model, with each representing epitope specifically highlighted.

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Atomistic molecular dynamics (MD) simulations were performed in CHARMM , using CHARMM 36 force field to further relax homology models and to investigate secondary structure and dynamics of the tag-less MEFA protein. Protein model was first solved in a cubic box of TIP3P water , and the total protein charge was neutralized by adding sodium ions. The final box size was about 69 Å. After energy minimization, 5.0 ns (nanosecond) simulation was used to equilibrate the structure by gradually reducing the harmonic positional restrain imposed on the protein backbone. The final production simulation course lasted 350 ns. Langevin dynamics were performed at a constant temperature of 298 K and pressure of 1.0. SHAKE algorithm was applied to maintain the length of all hydrogen-containing bonds and to allow of 2.0 fs (femto second) timestep. Particle mesh Ewald was utilized for electrostatics with a real-space cutoff of 13 Å. Van der Waals interactions were gradually switched off between 12 Å and 13 Å.

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Refolded tag-less CFA/I/II/IV MEFA protein was examined in 12% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and immune blot assays as previously described . Protein purity and integrity were assessed in SDS-PAGE Coomassie blue staining and mass spectrophotometer under conditions of sinapinic acid (20 mg/ml) and a dilution of 50:50 with acetonitrile 0.1% trifluoroacetic acid (TFA).

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A group of 15 eight-week-old female BALB/c mice (Charles River Laboratories International, Inc., Wilmington, MA) was each intraperitoneally (IP) injected with 200 μg tag-less CFA/I/II/IV MEFA protein and 2 μg dmLT adjuvant (double mutant LT, LTR192G/L211A; provided by Walter Reed Army Institute of Research, Silver Spring, MD). IP route was used previously in mouse immunization with 6xHis-tagged CFA MEFA . Each mouse received two booster injections with the same dose of the primary, at an interval of two weeks. A group of 15 mice without immunization were used as the control. Mice were sacrificed two weeks after the second booster. Mouse immunization study was approved by Kansas State University IACUC and supervised by a staff veterinarian.

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To assess if removal of the 6xHis-tag affected immunogenicity of the MEFA protein, serum samples of the mice immunized with the newly constructed tag-less CFA/I/II/IV MEFA and of those previously immunized with the 6x His-tagged CFA/I/II/IV MEFA were comparatively examined.

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Serum samples from each immunized mouse and each control mouse were titrated for IgG antibodies specific to CFA/I, CS1, CS2, CS3, CS4 and CS5 in ELISAs as we previously described . Antibodies specific to CS6 were not examined due to a lack of CS6 coating antigens. Mouse serum samples were two-fold diluted and examined in triplicate. Antibody titers were calculated from the highest serum dilution that produced OD readings of >0.3 above the background (highest dilution multiplies by adjusted OD) and presented in log10 .

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Serum samples from the immunized mice or the control mice were examined for in vitro antibody activities against bacterial adherence as previously described . Briefly, ETEC bacteria expressing each CFA adhesin (3.5 × 106 CFUs; MOI of five bacteria per cell) pre-treated with 10% mannose were mixed with 20 μl serum from the immunized or the control mice and incubated on a shaker (50 rpm) for 1 h at room temperature. The bacteria/serum mixture (brought to 300 μl with PBS) was added to each well of a 24-well tissue culture plate which contains Caco-2 cells (ATCC, #HTB-37TM, 7 × 105 in confluent monolayer; in 700 μl cell culture medium) and incubated in a CO2 incubator (5% CO2) for 1 h at 37°C. After washes with PBS to remove non-adherent ETEC or E. coli bacteria, Caco-2 cells were dislodged with 0.5% triton X-100 (300 μl per well). Adherent ETEC or E. coli bacteria were collected by centrifugation (15,000 g for 10 min), suspended in 1 ml PBS, serially diluted, and plated on LB plates. Bacteria (CFUs) were counted after overnight growth at 37°C.

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Protein dynamics simulation data analyses and structural visualization were performed using CHARMM , VMD and R (http://www.R-project.org) programs. Protein secondary structure was calculated with STRIDE . The solvent accessible surface area (ASA) was calculated by CHARMM with a water probe size of 1.4 Å. Relative ASA for each epitope was calculated using ASA of individual epitope normalized by the total MEFA protein ASA.

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Mouse serum antibody titers expressed in log10 were analyzed using SAS for Windows, version 8 (SAS Institute, Cary, NC), with Student’s t-test for the significance of differences. Mouse serum antibody adherence inhibition activities were examined with non-parametric Mood’s Median Test at 95% confidence. Numeric results were presented as means and standard deviations. Calculated p values of less than 0.05 were considered significant when treatments were compared using two-tailed distribution and two-sample unequal variance.

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Transformation of E. coli BL21 with plasmids carrying the tag-less CFA/I/II/IV MEFA gene yielded recombinant strain 9472. Strain 9472 expressed tag-less CFA/I/II/IV MEFA protein as effectively as strain 9175 expressed 6xHis-tagged MEFA. Tag-less CFA/I/II/IV MEFA protein was extracted at an average yield of 150 mg per liter culture (an average of five purifications) after refolding. Coomassie blue staining showed the tag-less MEFA protein was extracted at an estimated purity of over 95% (Figure 1).

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Extracted protein was recognized by anti-CFA/I mouse antiserum (Figure 1). Matrix assisted laser desorption ionization-time of flight (MALDI-TOF) showed a predominant peak at a mass of 15,525 daltons for the tag-less CFA/I/II/IV protein (Figure 1), and 17,307 daltons for the 6xHis-tagged MEFA protein, the expected molecular mass for both proteins.

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A total of 50 models were generated for the tag-less CFA/I/II/IV MEFA proteins. The one with the top conformer score showed a structure similar to backbone CFA/I CfaB subunit (Figure 2). Epitopes of the CFA/I, CS1, CS2, CS3, CS4, CS5 and CS6 in the tag-less MEFA protein were surface-exposed (Figure 2).

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Molecular dynamics simulation of protein secondary structural and dynamic properties showed the tag-less CFA/I/II/IVMEFA proteins maintained stable secondary structure during the entire simulation, indicated by peptide segments maintained same structure (the same color) as simulation time evolved (Figure 3). The root mean square deviation (RMSD) from the initial model gradually increased to 0.29 nm but became stabilized after 70 ns of simulations, indicating that the simulation reached the equilibrium. Variable root mean square fluctuation (RMSF) calculated to quantify conformational flexibility indicated that all seven epitope domains of the tag-less MEFA protein were stable during the simulation. Little dynamics was observed from the target epitope regions (Figure 4). This suggested that insertion of these epitopes did not appear to alter the stability of the overall structure of the backbone.

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Accessible surface area (ASA) analyses showed that all representing epitopes in the tag-less MEFA protein were surface exposed (Figure 5). ASA comparative studies indicated that the CS1 (5.5%), CS2 (5.3%), CS3 (4.9%), CS5 (9.7%) and CS6 (4.6%) epitopes were relatively more exposed.

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Mice IP immunized with the tag-less CFA/I/II/IV MEFA protein developed antigen-specific antibodies (Figure 7). Anti-CFA/I, -CS1, -CS2, -CS3, -CS4/CS6 and anti-CS5/CS6 IgG antibody titers in serum samples of the immunized mice were 3.5 ± 0.15, 3.4 ± 0.25, 3.4 ± 0.27, 3.5 ± 0.20, 3.3 ± 0.23 and 3.1 ± 0.20 (log10). No antibodies were detected to these adhesins from the control mouse serum samples.

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The serum samples pooled from the mice immunized with the tagless MEFA significantly inhibited adherence of ETEC or E. coli bacteria expressing CFA/I, CS1, CS2, CS3, CS4/CS6, CS5/CS6, or CS6 to Caco-2 cells, compared to the control mouse serum samples (Table 1).

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Structure-based vaccine design or structural vaccinology aided by computational modeling and atomistic simulation provides a new tool to overcome antigen heterogeneity challenge in vaccine development [18,34–40]. For ETEC vaccine development, heterogeneity of ETEC bacterial virulence factors remains the key challenge. Different ETEC bacteria produce immunologically heterogeneous adhesins and enterotoxins. ETEC bacteria expressing any one or two types of these adhesins (over 23 ETEC adhesins have been identified) and either toxin (heat-labile toxin-LT or heat-stable toxin-STa) can cause diarrhea. Therefore, only vaccines inducing broad immunity against these adhesins and/or toxins are expected effective against ETEC . Conventional vaccine candidates mixing together of a few live or killed strains induce immunity against homologous adhesins . Excessive somatic antigens particularly harmful LPS carried by these cocktail products, however, could link to side effects, lower immune responses, and unsatisfied protection against ETEC diarrhea . Instead of combining different bacteria strains, structure-based technology allows to include representative antigenic elements or epitopes from various ETEC virulence factors into a single MEFA immunogen for precision and broad immunogenicity. In silico structure data, however, are more of prediction at present; validation from empirical data is still considered essential for structural vaccinology . The current study demonstrated that structural vaccinology helped to characterize structure and immunogenicity of the ETEC MEFA immunogen, and showed congruence between computational data and the empirical mouse immunization data at MEFA immunogenicity. That suggests the feasibility of applying structural vaccinology to assist ETEC vaccine development.

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This tag-less CFA/I/II/IV MEFA was constructed by: 1) in silico predicting B-cell epitopes of the major structural subunits of the seven most important ETEC adhesins (CFA/I, CS1–CS6), 2) selecting one subunit (CFA/I subunit CfaB in this study) as the backbone at the criteria that this backbone subunit is very stable and relatively small-sized but carries multiple discontinuous and well-separated epitopes, 3) substituting the less antigenic epitopes of CfaB backbone with the most antigenic epitopes of the heterogeneous CS1–CS6 major structural subunits, and 4) computational modeling to optimize epitope substitution for a stable-structured MEFA. Computational modeling from the current study indicated all seven representing epitopes in the tag-less CFA/I/II/IV MEFA were surface exposed and presented at the β-sheet or the extension coil. Molecular dynamics simulation observed a low level of dynamics for these epitopes in the MEFA immunogen, suggesting these epitopes were stably presented by this MEFA protein. That correlated to the robust immune responses to each adhesin in the mice immunized with this CFA/I/II/IV MEFA.

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Current data revealed removal of 6xHis-tag appeared not to affect the CFA/I/II/IV MEFA at protein expression, protein structure and stability, and immunogenicity. Data showed the tag-less and 6xHis-tagged CFA/I/II/IV MEFA proteins were expressed and extracted at the same yield (about 150 mg per liter culture medium) and purity (greater than 95%, based on PAGE Coomassie blue staining and mass spectrophotometer). Molecular dynamics simulation suggested a stable structure for the tag-less or the 6xHis-tagged MEFA (data not shown for the 6xHis-tagged MEFA). This tag-less CFA/I/II/IV MEFA showed equally or more immunogenic than the his-tagged CFA/I/II/IV MEFA (Figure 7), although the enhanced immunogenicity exhibited by the tag-less CFA/I/II/IV MEFA could be resulted from dmLT adjuvant, since dmLT was demonstrated to be equally or more effective (compared to Freund’s adjuvant) to immunoregulate parenterally immunized ETEC antigens . The 6xHis-tag typically sticks out at protein surface (designed for nickel ion attachment during protein purification process) and may affect the exposure of the adjacent epitopes, through such negative effect could be limited presumably because the his-tag consists of only six histidines and eleven other residues of expression vector pET28α. Data from the current study showed the tag-less CFA/I/II/IV MEFA displayed immunogenicity to each representing epitope computationally and empirically.

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Despite computational antigenicity prediction and empirical immunogenicity data from mouse immunization exhibited congruence, some variations were observed between in silico predicted accessible surface area (ASA) and in vitro antibody protection against bacterial adherence. CS5 epitope was calculated with a significant greater ASA (9.7%), but antibody protection against adherence of CS5/CS6 ETEC bacteria was the least efficient (41.6%), compared to antibody adherence inhibition against ETEC bacteria expressing the other six adhesins (an average of 52.8%). The CS5 epitope located close to the N-terminus likely allows it to be more surface accessible, and also more fluctuated as shown from dynamics simulation. In contrast, CS6 epitope showed a moderate ASA (4.6%); but antibody inhibition against adherence of CS6 ETEC bacteria was the most effective (75%). Similarly, the CFA/I epitope showed a significantly low ASA (0.93%), yet antibody protection against adherence of CFA/I ETEC H10407 (50.5%) was not noticeably lower than antibody inhibition against adherence of the other adhesins. The disagreement between a low CFA/I epitope ASA and a strong antibody protection against CFA/I bacteria adherence is explainable since other epitopes of the CfaB backbone also induce anti-CFA/I antibodies to additively protect against adherence of the CFA/I adhesin. The inconsistency of a high CS5 ASA and a below-an-average antibody protection against adherence of CS5 adhesin could suggest that the CS5 epitope is immunodominant but not necessarily strongly neutralizing; whereas differences between an average CS6 ASA and a greatest protection against adherence of CS6 ETEC bacteria may indicate that the CS6 epitope is strongly neutralizing. That also indicates future in vivo studies including colonization studies using a suitable animal model and even a controlled human challenge model, as well as immunization studies using other routes will be needed.

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Congruence at overall immunogenicity of this tag-less CFA/I/II/IV MEFA between computational data and empirical mouse immunization data suggest the potential application of structural vaccinology in ETEC vaccine development. Whether antigen immunogenicity congruence also occurs from data in human immunization studies will be revealed in future human volunteer studies. It should be noted that some inconsistency between the ASA predicted from molecular dynamics simulation and the in vitro antibody protection among two individual epitopes warrants further improvement of structural vaccinology including the prediction of neutralizing epitopes instead of immunodominant epitopes; in return, it may also validate the need of empirical studies to confirm computational data.

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A new generation of local drug release platforms with sustained and complex release profiles for reduced therapeutic doses has emerged to overcome the disadvantages of conventional treatments—generally oral or intravenous administrations—with considerable adverse effects .

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These local drug release platforms face important challenges to ensure efficient therapy: (i) efficient loading of drugs, (ii) sustained delivery, (iii) avoiding the ‘burst effect’ (high dose release within the first minutes), (iv) material stability (avoiding degradation), and (v) the possibility to chemically modify their surface for a selective release . Many types of materials are currently used for the development of these new drug delivery platforms, such as polymers , hydrogels , iron oxide , graphene , porous silicon , and mesoporous silica . However, most of these existing carrier materials rapidly degrade at physiological pH or/and show poor drug loading with drugs mainly attaching to external surfaces and leading to an intense initial “burst” release.

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Porous materials have attracted great interest for the development of controlled drug delivery platforms because of their high effective surface area and tunable pore size . The pore geometry is one of the main determining factors of the total drug load entering the pores and the release profile. Three-dimensional (3D) pore structures, with intricate pore geometries and increasing surface area are promising platform designs for sustained drug release. However, their fabrication can be expensive and complex.

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Nanoporous anodic alumina (NAA), readily and cost-effectively fabricated by electrochemical anodization, permits obtaining elaborate and reproducible 3D pore geometries. The many physical and chemical properties of NAA make this material a versatile and interesting platform for controlled drug release. NAA has a highly ordered pore distribution, and its well-known electrochemical fabrication techniques allow for the precise control of pore diameter, interpore distance, pore length, and pore geometry . NAA is highly stable at physiological pH, and has been successfully used in a wide array of medical and biological applications like orthopedic prosthetics, dental and coronary stents, cell culture scaffolds, immunoisolation devices, and biomolecular filtration .

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Its high effective surface area makes NAA an ideal material for drug delivery applications providing pores as nanocontainers with regular and controlled structural features for loading active agents like drugs or molecules . Moreover, the surface of NAA can be functionalized to be selective for specific molecules and covered with biodegradable, chemical, or pH responsive agents to trigger and regulate the release .

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In this work the drug release kinetics for simple and complex NAA pore structures is investigated. Pores with straight walls and 3D pore structures with multilayered funnel and inverted funnel geometries are fabricated by electrochemical anodization, resulting in complex NAA platforms for drug delivery. Using the chemotherapeutic Doxorubicin, the drug release of these different pore geometries is studied, and the release mechanism is modeled by mathematical expressions.

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All NAA porous structures were prepared by electrochemical anodization of high purity (99.999%) aluminum plates (Goodfellow, Huntingdon, UK) in phosphoric acid electrolyte. The aluminum plates were initially degreased with acetone and ethanol to eliminate organic impurities and electropolished in a mixture of perchloric acid and ethanol 1:4 (v/v) at a constant voltage of 20 V for 6 min. To suppress breakdown effects and to enable uniform oxide film growth under hard anodization conditions (194 V in phosphoric acid at −5 °C), a protective layer was pre-anodized at a lower voltage (174 V in phosphoric acid) for 180 min . Subsequently, the voltage was ramped up to 194 V at a constant rate of 0.05 V/s, and anodized for 20 h. After this first anodization step, the formed NAA layer was removed by wet chemical etching in a mixture of phosphoric acid (0.4 M), and chromic acid (0.2 M) at 70 °C for 4 h, resulting in a hexagonally-ordered pattern of the aluminum surface .

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A single hard anodization step was performed to obtain straight pores (SP) with a uniform pore diameter from top to bottom (Figure 1a). The length of the pores of all SP is 30 µm. To widen the pores, wet chemical etching with aqueous solution of 5% H3PO4 was performed for 0 (SP1), 45 (SP2), 90 (SP3), and 120 min (SP4).

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Normal Funnels (NF) were produced by a sequential combination of hard anodization and pore widening steps, and labeled according to the final number of layers. NF2 consist of a 15 µm thick top layer, widened in 5% H3PO4 for 90 min, and a 15 µm thick bottom layer. Similarly, NF3 consist of a 10 µm thick top layer widened for a total of 90 min (2 × 45 min), a middle layer of 10 µm widened for 45 min, and a bottom layer of 10 µm (Figure 1b).

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The fabrication of Inverted Funnels (IF) required a thermal treatment at 250 °C and 500 °C to change the crystallographic phase of the alumina. The inverted funnels were labeled IF2 and IF3 according to their respective total number of layers (Figure 1c). IF2 consisted of a top layer of 15 µm, followed by a thermal treatment at 500 °C. A subsequent anodization step added a 15 µm thick bottom layer. Similarly, IF3 consisted of 3 layers, each with a thickness of 10 µm. After the anodization of the top and middle layer a thermal treatment of 500 °C and 250 °C was applied, respectively. In a final wet chemical etching step, the pores of IF2 and IF3 were widened for 2 h.

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All NAA structures were characterized by Environmental Scanning Electron Microscopy (ESEM, FEI Quanta 600, FEI Co., Hillsboro, OR, USA). The wet chemical etch rate during the pore widening steps was estimated for samples with and without a 500 °C thermal treatment. For the calibration of the pore widening process, ESEM images were taken in 15 min etching intervals, and the pore diameter was estimated using a standard image processing package (ImageJ, version 1.51p, public domain program developed at the RSB of the NIH, Bethesda, Maryland, MD, USA) (Figure S1).

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Doxorubicin (DOX), a self-fluorescent chemotherapeutic agent, was selected as a model drug. Drug loading into NAA pores was performed through capillary action by immersing NAA into a DOX solution of 1 mg/mL. The suspension was stirred overnight in the dark with the NAA structures immersed. Subsequently, samples were washed with deionized water to remove any residual drug molecules on the surface of the sample and dried at an ambient temperature.

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The release studies were performed in vitro using phosphate-buffered saline (PBS), which is commonly employed to simulate in vivo conditions for drug release. DOX release was estimated by directly measuring the photoluminescence of the release medium. This in situ measurement process is ideal to understand the release kinetics and the short-term release effect since it allows for the fast and frequent collection of release data. Samples were immersed in 0.5 mL of PBS which was renewed after every measurement. The fluorescence of the buffer solution was measured at regular time intervals at room temperature using a fluorescence spectrophotometer from Photon Technology International Inc. (Birmingham, NJ, USA), with an Xe lamp as the excitation light source, an excitation wavelength of 480 nm and an emission wavelength of 590 nm. The drug release was monitored by DOX photoluminescence over 65 days. The fluorescence intensities were converted to the corresponding concentrations using a calibration curve. All the drug release measurements were taken in triplicates for every pore structure and statistical analysis was performed.

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Normal Funnels (NF) with two and three layers of different pore diameters were successfully fabricated. ESEM cross-section images of NF show straight pore growth with no discontinuities (i.e., occluded pores) despite the interruption of the anodization process between layers (Figure 2). The transition between adjacent layers of different pore sizes is smooth and shows a conical shape. The pore diameter and the thickness of each NF layer was estimated from ESEM images and summarized in Table S1.

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Inverted Funnels (IF) were also successfully fabricated, and their ESEM cross-section images are shown in Figure 3 (IF2) and Figure 4 (IF3). For both IF, parallel and perpendicular growth of the pores as well as conic and clear transitions between adjacent layers of different pore diameters can be observed. High magnification images show that these conic transitions between layers are more abrupt for IF than for NF. IF, NF, and SP were anodized to a total length of 30 µm for better comparability (Table S1).

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The two distinct pore diameters of the IF2 top and bottom layers suggest that the crystallographic structure of the top layer was successfully modified by the temperature treatment (500 °C). The same clear transitions between layers are observed in IF3 samples, demonstrating that the intermediate annealing temperature of 250 °C results in an intermediate pore widening rate.

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The effect of the temperature treatment on the pore widening process during IF fabrication was further assessed, and a calibration of the pore widening rates was determined. The pore diameters were estimated from ESEM images taken after consecutive 15 min pore widening steps for samples thermally treated at 500 °C, and for untreated samples. Figure S1 reveals that the thermally treated samples have a slower pore widening rate than untreated samples. The alumina matrix of untreated samples remained intact for up to 2 h of etching, but started to deteriorate after 2.5 h, and fully collapsed after 3 h due to over-etched pore walls. Consequently, to preserve full structural integrity of the thermally untreated samples, the pore widening was terminated after a maximum of 2 h. In contrast, the pore structure of thermally treated samples remains intact even after 3 h of etching.

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Figure S2 shows the estimated pore diameter as a function of pore widening time, revealing higher etch rates for the untreated samples (2.5 nm/min) than for the thermally treated samples (1.2 nm/min). These are brought about by the thermal annealing, which increases the crystallinity, and consequently, the stability of the alumina, and also further promotes anion diffusion . We further notice that the pore diameter linearly increases with the pore widening time until an inflection point, where the pore widening rate decreases considerably. This inflection point corresponds to an interface separating an outer region with concentrated anionic species from an inner region composed of pure alumina. The anion contaminated region is easily removed by the pore widening, whereas the region of pure alumina is more resistant to pore widening . The inflection point is observed after 90 min and 150 min of pore widening for non-treated samples and thermally treated samples, respectively.

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Figure 5a shows the pore diameter of the top layers of all the fabricated NAA structures. Increasing pore diameters of samples SP1–SP4 are directly related to the increasing widening time intervals (Table S1). NF2 and NF3 show top pore diameters similar to SP3 (around 300 nm), and IF2 and IF3 top diameters are similar to that of SP4 (around 200 nm). These similarities allow for studying the influence of the pore geometry on the release kinetics. Figure 5b shows the total volume of all of the samples. The pore volumes of SP1–SP4 are clearly related to the pore diameters, whereas the pore volumes of the layered samples NF and IF depend on the complex geometries of the pores.

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The relationship between the total amount of drug load and volume is shown in Figure 6. The total drug load of straight pores is linearly proportional to the pore volume, as indicated by the linear regression for SP1–SP4 (dotted line). Similarly, the total drug load of NF follows the trend of SP samples, though, with an increasing diversion from this trend with more funnel layers. Interestingly, the IF samples seem to hold a higher drug load per pore volume when compared to SP, indicating an influence of the pore geometry on the total drug load. This can be explained by the contour of the IF pores which encompasses small pore diameters of the top layer, wider pore diameters of deeper layers and a sharp elbow-like transitions between the adjacent layers (Figure 3c). This intricate geometry retains a higher total drug load within the pores, making IF structures more efficient for drug loading than SP structures.

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The influence of the pore geometry on short and long-term drug release has been studied for all fabricated NAA structures. Figure 7 and Figure S3 show the drug release response for the first 8 h, and for the complete release time of 1512 h (63 days). All of the NAA structures presented in this work can be considered as sustained drug delivery platforms due to very long drug release times. Interestingly, these NAA structures do not present a high initial drug release burst in the first minutes, in contrast to most drug delivery platforms in the literature . The absence of an initial release burst indicates that the drug delivery from these NAA platforms is more constant in time, and prevents an undesired high initial dosage. Both the sustained delivery, and the absence of initial burst are relevant and differentiating properties and address two of the main challenges of localized drug delivery.

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The drug release profile of all the pore geometries can be described by distinguishing two phases: (i) a short-term release with a higher release rate within the first 8 h, and (ii) a slow and sustained release where almost the entire drug load is delivered from the NAA after 63 days.

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Most of the NAA structures presented here release only around 25–30% of the total drug load during the short-term release, which is very low compared to the 80% and above of most conventional structures in the literature . Generally, the initial release is attributed to the fast diffusion of drug molecules residing on the NAA surface, rather than the diffusion of molecules attached to the walls within the pores. Here, this low short-term release indicates that most of the drug was loaded inside the pores during the incubation period.

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The pore geometries were found to influence the short-term release rates. The 200 nm pore diameter of the top layer of IF2 and IF3 is similar to SP2, however, their release rates are considerably lower than SP2. The pore opening of IF acts like a bottleneck for the infiltrating medium and the eluting drug, hindering the circulation of the medium inside the pore and slowing down the diffusion of the drug out of the alumina. This effect augments with increasing IF layers: the release rate of IF3 is lower than that of IF2.

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The experimental data for short- and long-term release were modeled to measure the kinetics and establish the mechanism of DOX release. For short-term release, the experimental data was modeled using a variation of the Higuchi equation :(1)Mt=M0+Kt where Mt is the cumulative release at time t, M0 is the intercept value at t = 0 and, K is the release constant that indicates the release velocity.

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The fitting of the experimental data for all pore geometries with Equation (1) is presented in Figure 8, where the cumulative DOX release is plotted against the square root of time during the short-term release. The fitting is in very good agreement with the experimental data for all pore geometries, demonstrating that the drug kinetics can be approximated by the square root of time. Table 1 shows the fitting parameters for each pore structure and Figure 9 depicts their release constant K depending on the top pore diameter and volume.

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During the short-term release, the release constant K for straight pore structures (SP1–SP4) is linearly proportional to the pore diameter, following the equation:K = 0.168 + 6.46 × 10−4·Dp(2) where K is the release constant in (µg/mL)/min1/2 and Dp is the pore diameter in nanometers.

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IF are the structures with the highest load efficiency, as they retain a higher quantity of drug inside of the pores than SP and NF, with the same volume or top pore diameter. During short-term release, IF structures show a lower release constant K than SP structures with the same top pore diameter. However, if the specific application requires a higher release rate, SP structures are favorable. Even though SP and NF present similar release rates, the fabrication of SP structures is not as complex as the fabrication of NF.

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For the long-term release the experimental data was modeled with the Korsmeyer–Peppas equation :(3)Mt=Mt0(tt0)n where Mt is the quantity of drug released at time t, Mt0 is the amount of drug released at the reference time t0 (day 1), t is time in days, and n is the release parameter related to the release rate.

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Table 2 shows the values of these parameters fitted for the release of all the pore structures. The release rate was calculated with the first derivative of Equation (3) . Figure 10 shows a good agreement between the experimental data and the fitting modeled with Equation (3).

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NF and SP3 have a similar top pore diameter and release rates. IF have slightly higher release rates than SP2, which is explained by the quantity of drug remaining inside the pores. During the short-term release, NF and SP delivered a higher part of their load than IF as their release rates were higher. Due to this, and the fact that drug loads were completely released from all the structures after 63 days, IF released greater loads during days 8–63 than the other structures, and therefore their release rate is slightly higher.

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The release profiles for the studied pore geometries revealed two interesting and promising properties: (i) very long drug release times determining the presented NAA as sustained drug delivery platforms, and (ii) a constant drug delivery free of an initial release burst to prevent undesired high initial drug delivery dosages. These findings are advancements to two of the main challenges of current platforms for advanced drug delivery systems.

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The obtained results reveal that the pore geometry influences the total drug load within the pores. IF retain a higher quantity of drug inside the pores than SP and NF with the same volume or top pore diameter. The pore geometry also influences the release kinetics. During the short-term release, IF showed lower release rates than SP with the same top pore diameter.

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Moreover, the dynamics of the release of all the pore structures were successfully modeled, and two different release regimes were differentiated: a short-term and a long-term release. The short-term release (first 8 h) was modeled by the Higuchi model, whereas for the long-term release the Korsmeyer–Peppas equations were used.

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Violence against women (VAW) is a major human rights and public health concern, with significant impacts on women’s health [1, 2], including increased vulnerability to HIV [3, 4]. Intimate partner violence (IPV) is the most common form of violence against women, with 30% of women globally experiencing it during their lifetime . There is now a growing body of evidence on the impact of prevention interventions on HIV and IPV in different contexts. In South Africa, the IMAGE Study assessed the impact of a combined microfinance programme and participatory gender and HIV training . The cluster randomized study found that the intervention led to a 55% reduction in past year IPV over two years and among younger participants was associated with increases in HIV testing and reduced prevalence of unprotected sex at last intercourse with a non-spousal partner . The programme has been scaled up in South Africa and is currently being replicated in Tanzania as part of the MAISHA study . Stepping Stones, a participatory HIV prevention programme which includes gender, relationship education and IPV content, has been used throughout Africa and evaluated extensively. A cluster randomized control study in South Africa found that after a two year follow up period there was no association between the intervention and a reduction in HIV, but there was an association with a 33% reduction in HSV-2 incidence. Reductions were also observed among men in reported levels of IPV perpetration against women and sexual risk behaviours . And, more recently a randomized control trial of the Bandebereho gender-transformative couples’ intervention in Rwanda found that compared to the control group, women in the intervention group reported less past-year physical (OR 0.37, p < 0.001) and sexual IPV (OR 0.34, p < 0.001) . The program engages men and their female partners (for some sessions) on topics including gender and power, IPV, couple communication and parenting.

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There has also been wide recognition that a range of public health issues centred within intimate relationships, such as HIV and partner violence, are influenced by broader community and societal factors [10–12]. In response a growing number of complex interventions combine mass media with community mobilisation efforts and/or community-based change agents to intervene at multiple levels [11, 13, 14]. Programme H a participatory intervention with young men uses interactive group education sessions and community wide social marketing to address the acceptability of violence among young men and transitional norms of masculinity. A quasi-experimental study in Brazil found significant reduction in reported inequitable gender norms, a decrease in reported STI symptoms, and an increase in reported condom use at last sex with a primary partner was observed after one year . SASA!, a combined HIV and VAW prevention programme uses multiple channels to catalyse community-led change of norms and behaviours that perpetuate gender inequality, violence and increased HIV vulnerability for women . It does this through engaging health workers and local authorities and training community activists (CA) who introduce concepts during informal activities in their communities using communication materials, media and advocacy and community based support over time. Others, such as Soul City and Sexto Sentido, use ‘edutainment’ to reinforce social change messages around HIV and partner violence through mass media messaging and radio and television dramas . Rigorous trials in Sub-Saharan Africa have also suggested community mobilisation and reflective strategies work to prevent IPV [17, 18].

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Research evaluating such interventions tends to focus on measuring their impact on intended outcomes and, in some cases, on establishing whether exposure to the intervention follows a typical dose response curve. While this is important, there is a paucity of research into the more nuanced roles intervention and social network factors may play in achieving these outcomes, making it difficult to understand how different aspects of the intervention worked (or did not), and how it could be improved or best adapted in different contexts. For example, while a number of studies on the Stepping Stones HIV intervention found it to be effective, Bradley et al.’s study on the diffusion of the intervention among social networks revealed important weaknesses. They observed that while Stepping Stones aims to have a community level effect, there was only diffusion of knowledge among personal contacts and limited community level diffusion. Examining diffusion provided key insights into how the intervention could further strengthen diffusion, increasing impact.

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Diffusion of innovations theory provides a useful framework for exploring how attributes of the individual, intervention, and social system, converge to allow the spread of new ideas/behaviours from a source (e.g. implementing organisation) to an individual (e.g. community members) via different communication channels (e.g. mass media, interpersonal communication) and influence . In this paper we use data from a multidisciplinary evaluation of SASA! to gain understanding of the communication channels and intervention attributes through which IPV interventions can stimulate behaviour changes in intimate relationships. The SASA! Study was conducted in Kampala, Uganda between 2008 and 2012 and comprised a cross-sectional cluster randomised control trial (RCT) , qualitative studies , a process evaluation and a costing study . The RCT showed the intervention to be associated with lower acceptability of IPV, as well as reductions in women’s experiences of IPV—past year experience of all types of IPV was lower in intervention compared to control communities, with statistically significant effects observed for past year experience of high intensity emotional aggression and controlling behaviours, and cessation of physical, sexual and emotional IPV where it was previously occurring . The aim of this paper is to examine through which communication channels SASA! diffused and the intervention attributes that contributed to its effect. Specifically, we analyse the associations between different communication channel exposures and reported positive change in relationship quality (as it is on the pathway to IPV cessation) from our larger quantitative survey sample. Qualitative data is examined to elucidate the intervention attributes that facilitated engagement with the intervention and uptake of new ideas and behaviours in intimate relationships.

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Diffusion of innovations theory focuses on the role different communication channels play in facilitating individuals’ ‘exposure’ (both ‘direct’ and ‘indirect’) to new ideas and their movement through a ‘innovation-decision process’ (knowledge, persuasion, decision, implementation, confirmation) . The term ‘diffusion’ in this context (and applied in this paper) includes not only the spreading of new ideas, but the entire process from direct or indirect exposure to adoption. ‘Adoption’ is defined as the uptake of the innovation, ideas or programme by the targeted audience . The theory has been applied in a variety of ways across public health—in particular in HIV prevention and family planning [25, 26]—and there is empirical support for aspects of the theory in the broader public health literature [20, 27]. It has not—to our knowledge—been applied to partner violence prevention interventions.

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SASA! is designed to diffuse new ideas and behaviours to community members directly through, 1) mass media channels: TV, radio and posters displayed in shops, on gates, at local authority offices, health centres and in the market; 2) mid media channels: videos or dramas performed in public spaces in the community; and, 3) interpersonal communication with change agents: quick chats, community conversations and card games facilitated by community activists trained in SASA!. SASA! also anticipates that community members will be indirectly exposed to messages through ‘interpersonal communication’ among social network members about SASA! (e.g. peers, neighbours, elders). According to the theory mass and mid media channels are most effective in generating awareness, identification and knowledge about new ideas and behaviours [20, 26]. Interpersonal communication about the new ideas is, in turn, influential in persuading individuals to adopt or reject new behaviours [25, 28] and those more ‘homophilious’ or similar, such as peers, have the greatest sway .

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Diffusion theorists have also identified key attributes of interventions or innovations that influence how quickly new ideas or behaviours are adopted and account for most of the variation between innovations that are adopted quickly and those that are not . For example, individuals need a sense that there is a ‘relative advantage’ to the new ideas or behaviours: a perceived personal, physical, social or economic benefit. Next, research has found people often carry out a small trial first to test out the relative advantages of a new behaviour or smaller change towards it before deciding to adopt (‘trialability’). It also needs to be compatible with their life, their perceived or ‘felt needs’ and existing sociocultural values (‘compatibility’). And, the perceived ‘complexity’ of applying new ideas and behaviours can influence how willing individuals are to try them. New behaviours are also more likely to be diffused if they are easily observed by others (‘observability’). Witnessing the positive experience and changes in others encourages individuals to try new behaviours/innovations themselves.

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Change agents are also evidenced to play an influential role in adoption. Rogers outlines seven roles a change agent ideally plays in introducing new ideas and behaviours within communities and facilitating adoption: develop a need for change; establish an information exchange relationship; diagnose problems; create an intent to change in individuals; translate intent into action; stabilise adoption and prevent discontinuation; and, achieve a terminal relationship by developing community members’ capacity to be their own change agents .

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Together the communication channels, intervention attributes and change agent roles can serve as a guide or starting point when evaluating interventions, and help illuminate what facilitated or prevented the intervention’s intended outcomes. In this paper we investigate three research questions using quantitative and qualitative data: 1) Through what communication channels is SASA! diffusing in intervention communities? 2) Is there a relationship between an individual’s specific communication channel exposure (e.g. mid media, interpersonal communication with peers or change agents) and experiencing positive changes in their relationship since being exposed to SASA!? 3) What intervention attributes facilitated engagement with SASA! and uptake of new ideas and behaviours in intimate relationships?

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The SASA! approach was developed by Raising Voices and implemented by the Center for Domestic Violence Prevention (CEDOVIP). The SASA! study was conducted in eight high-density, impoverished communities in Kampala, Uganda. Rates of HIV and IPV are high in Kampala, with 9.5% of women and 4.1% of men aged 15-49 estimated to be living with HIV and 45% of ever-married women reporting IPV at some point in their lives . Partner violence is closely linked to the changing gender roles and expectations around relationships in Uganda, as well as alcohol use and multiple sexual partners [31, 32].

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SASA! is a community mobilisation approach for preventing VAW and HIV. It is designed for catalysing community-led change of norms and behaviours that perpetuate gender inequality, violence and increased HIV vulnerability for women. SASA! means ‘Now’ in Kiswahili and is an acronym for the four phases of the approach - Start, Awareness, Support, Action. In the Start phase, an organization using SASA! begins by orienting staff to the approach and key concepts of power. They then select an equal number of female and male community activists (CAs)—well-known and respected people in the community (i.e. ‘opinion leaders’) selected for their interest in issues of violence, power and rights—and similarly select institutional activists, for example, from police, health care, local government and faith-based groups. All activists are introduced to the new ways of thinking about power and power imbalances in their own lives and within the community, and are mentored in the SASA! approach.

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With the support of staff, the activists then take the lead as the approach moves forward into the Awareness, Support and Action phases. In these phases, the activists lead informal, benefits-based activities within their existing social networks—fostering open discussions, critical thinking and supportive person-to-person and public activism among their families, friends, colleagues and neighbours. Together, they introduce the community and its institutions to the new concepts of power, encouraging a gendered analysis of power imbalances through four strategies: Local Activism, Media and Advocacy, Communication Materials, and Training. The combination of these strategies ensures that community members are repeatedly exposed to SASA! ideas in diverse ways within the course of their daily lives, from people they know and trust as well as from more formal sources within the community. Each phase builds on the other and addresses a different concept of power, with an increasing number of individuals and groups involved, strengthening a critical mass committed and able to create social norm change .

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This paper used both qualitative and quantitative data to extend the breadth and depth of understanding of diffusion within the context of the SASA! intervention. The quantitative and qualitative analyses were integrated to achieve complementarity through answering related questions using the type of data most suited to each question. Figure 1, presents a diagram of diffusion of innovations theory and indicates which constructs were analysed with each data set for this paper. Aspects of the theory such as movement through the innovation decision process could not be examined due to limitations of cross sectional data. The length of the survey instrument did not allow us to measure all constructs quantitatively, and some were explored in the qualitative component exclusively.Fig. 1Constructs from Diffusion of Innovation theory measured in the quantitative and qualitative data analyses

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The data for this analysis was collected during the follow-up survey of the SASA! RCT, described elsewhere in detail . Briefly, the survey was conducted in 2012 with 2532 community members in eight sites (four intervention, four control) following 2.8 years of programming. A person was eligible for inclusion in the survey if they usually lived in the household and shared food, had lived in the area for at least a year, and were 18-to 49-years old. A limit of one respondent per household was set out to protect respondent safety and confidentiality. The sample for this analysis was restricted to reflect the focus on relationship change linked to intervention exposure. Thus, it only included participants living in intervention communities who reported having a regular partner in the last twelve months and having had exposure or familiarity with SASA! (n = 929, with 358 women and 571 men) (Fig. 2). In the full dataset, 81% of men and 84% of women had a regular partner, and 91% of men and 68% of women in intervention communities reported SASA! exposure.Fig. 2Quantitative sampling diagram

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This analysis explored how exposure to SASA! through different communication channels (e.g. mid media, interpersonal communication) were associated with reporting positive change in the relationship since exposure to SASA!. This outcome was chosen as a proxy for movement on the continuum of change towards improved relationship quality and less violence based on the hypothesis that positive change in intimate partner relationships leads to reductions in IPV . It was measured by asking: 1. “Has anything changed in your relationship with your partner since you became involved in SASA!?” If they answered yes, they were asked, 2. “Did the changes include a. better communication, b. increased discussion on important decisions in the household, c. more closeness, d. more respect?” Nearly all respondents that reported yes to question one answered yes to each item in question two. Thus, question one was used in this analysis as the indicator of positive change in the relationship resulting from SASA! exposure.

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The exposure variables were chosen as indicators of the communication channels through which SASA! messaging may diffuse either directly from intervention exposure or indirectly via discussion about SASA! with different social network members. During the RCT the main forms of mass media in the SASA! Activist Kit (radio/TV) were not used to prevent contamination to control communities. Thus, for this analysis we measured material exposure (posters, comics, picture cards, information sheets), mid media exposure (dramas, audio plays), interpersonal communication (discussion activities with change agent, seeking change agent support, discussion about SASA! with social network members) and multi-channel exposure (having material and mid media/activity exposure) (Table 1). The analysis examined the independent effects of each type of intervention exposure separately as well as the effect of communication about SASA! among different social network members. It also tests the hypothesis that exposure to multiple channels (materials plus drama and/or discussion activities) would yield stronger associations with the outcome of interest than only materials exposure.Table 1Exposure variables and associated follow-up survey itemsExposure VariablesSurvey itemaCategories of exposurea:Intervention exposure Communication materials “How many times have you seen any of these materials about violence against women and relationships between men and women?” (the interviewer showed them a card with illustrations of SASA! posters, comics, picture cards, information sheets).Categorical variable:- 0-1 (reference group)−2-5- > 5 Mid media How many times have you been to a SASA!/CEDOVIP film, drama or listened to an audio play in your community about violence against women and relationships between women and men? Categorical variable:-never (reference group)-once-a few 2-5-many > 5 Interpersonal communication -at discussion activity w/ change agent How many times have you been to an activity or quick chat in your community where you looked at one of the SASA!/CEDOVIP materials (poster, comic, or picture card, etc) and talked about violence against women and relationships between women and men? -Sought CA advice How many times have you sought advice from a SASA! community activist? Binary variable-never (reference group)−1 or more timesInterpersonal Communication with different social network members:-Talked with Elders I) Have you talked with your parent about SASA!? If yes: II) How many times? Categorical variableb:-low (0-2 times) (reference group)-medium (3-5 times)-high (> 5 times) I) Have you talked with your in-law about SASA!? If yes: II) How many times? I) Have you talked with an elder about SASA!? If yes: II) How many times? -Talked with Peers I) Have you talked with a friend about SASA!? If yes: II) How many times? I) Have you talked with a neighbour about SASA!? If yes: II) How many times? -Talked with Partner I) Have you talked with your partner about SASA!? If yes: II) How many times? Multi-channel exposure “How many times have you seen any of these materials about violence against women and relationships between men and women?” (the interviewer showed them a card with illustrations of SASA! materials).Categorical variable:-materials (mass media) exposure only (reference group) -low ‘multi-channel’ exposure (exposed 1-4 times to activities and/or dramas/films)-high ‘multi-channel’ exposure (exposed > 5 times to activities and/or dramas/films) How many times have you been to a SASA!/CEDOVIP film, drama or listened to an audio play in your community about violence against women and relationships between women and men? How many times have you been to an activity or quick chat in your community where you looked at one of the SASA!/CEDOVIP materials (poster, comic, or picture card, etc) and talked about violence against women and relationships between women and men? aTo measure dose-response relationships frequency of exposure was captured using 4 categories: never, once, a few times (2-3), or many times (5+). Some variables were re-coded or re-categorised for statistical reasons for the regression analysisbComposite frequencies based on frequencies with which they spoke to each type of person

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The statistical analysis was conducted using STATA version 13.1. All analyses were conducted separately for men and women given that gendered variation in response patterns are frequently observed in IPV research . Clustering of the outcomes within the study sites was ‘small’ (< 0.1 intraclass correlation), hence the analysis did not adjust for the clustered sampling design . For each outcome, logistic regression was used to calculate unadjusted odds ratios (and 95% confidence intervals (CI)) comparing odds of the outcome in each of the higher exposure categories with that in the lowest exposure category. The likelihood ratio test (LRT) was used to compare models with and without each exposure.

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Multivariate logistic regression was used to further explore associations between the exposures and outcome. We first modelled the association between multi-channel exposure and the outcome, adjusted for potential confounders (age, marital status, socioeconomic status (SES) and education level). Separate models were then used to explore the independent effect of each of the single-channel exposures on the outcome, adjusted for the other channels of exposure and potential confounders. Variables for inclusion in the model were decided upon a priori based on conceptual considerations, however models were also checked for collinearity problems. As with the unadjusted analysis, 95% confidence intervals were calculated to estimate the precision of the adjusted odds ratio (aOR), and the overall p-value for each exposure generated using the LRT to test for model fit.

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Using data from the SASA! couples study, detailed elsewhere , the qualitative analysis examined participants’ engagement with the intervention and how different communication channel exposures to SASA! influenced relationship changes. Participants in the couples’ study were sampled purposively from the RCT follow up survey respondents. RCT participants that agreed to be contacted again were sampled using the following criteria: in current relationship since 2010 or before; IPV reported before the last 12 months, but not in the last 12 months; exposure to SASA! of any intensity (note their partner may not have been exposed); and, positive change in relationship since becoming involved in SASA!. Those reporting violence in the last twelve months were not selected as a safety precaution as interviewing them could incite further violence (i.e. if the man thought his partner had “told” on him). Initial efforts to recruit couples through contacting female RCT participants yielded only two couples. Therefore, eight couples were recruited through male RCT participants with further precautions taken to ensure their female partners were not pressured into participating. Couples were sampled between August-October 2012 from across the four intervention communities, with each partner interviewed separately using a semi-structured interview tool (20 interviews in total; 10 women and 10 men). The guide starts with general questions about the participant’s relationship and any changes they have observed. This allowed participants to first mention SASA! of their own accord as well as attribute any changes in their relationship to it (or not). Later in the guide there are more specific questions and probes about SASA! exposure and how it impacted their relationship. A participatory timeline was used to help with recall. Interviews were conducted, transcribed and translated from Luganda to English by bi-lingual research assistants and data were entered into NVIVO 10 software for coding and analysis by the first author. While couples were sampled, the unit of analysis for this investigation is the individual. Data were analysed using framework analysis, a method that allows the researcher to systematically organize and compare ‘raw’ data by theme and case using a framework matrix linked to the original transcripts .

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The World Health Organisation protocol for interviewing women on IPV was observed and each participant gave individual written informed consent to be interviewed and, in the qualitative study, to be audio recorded. The SASA! Study received ethical clearance from Institutional and National Review Boards. Couples were numbered with partners indicated by M for male, F for female (e.g. 1F, 1 M) and pseudonyms used to protect confidentiality.

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Detailed characteristics of the quantitative sample including intervention exposure are presented in Table 2. The majority of men and women lived in rented homes with access to electricity; water was from a public tap and sanitation facilities were mainly pit latrine toilets. The mean age was 28 for women and 29 for men. The largest proportion (35%) were Catholic, followed by Muslim and Protestant (25% each). The majority were literate (96% men, 89% women) and educated above the primary level (71% men, 66% women). 32% of men completed secondary school or higher compared with 20% of women. 93% of men versus 61% of women were employed. 83% of women and 65% of men had children and 39 and 17% respectively had three or more.Table 2Characteristics of the sample (i.e. partnered people with any SASA! exposure)Male (N = 571)Female(N = 358)Household & individual level:n (%)n (%) Electricity in home506(89%)297(83%) Water source: outside/public tap457(85%)291(81%) Toilet facility: ventilated/traditional pit latrine530(93%)299(84%) Lives in rented housing461(81%)268(75%)Age group mean = 29 mean = 28 18-24 yrs161(28%)128(36%) 25-34 yrs258(45%)171(48%) 35-49 yrs152(27%)59(17%)Lived in community more than 3 years462(81%)221(62%)Religion Catholic208(36%)123(34%) Muslim148(26%)86(24%) Protestant151(26%)86(24%) Born again52(9%)58(16%) Other12(2%)5(1%)Education None/Primary163(29%)123(34%) Some secondary/O level225(39%)162(45%) A level/vocational training/university183(32%)73(20%)Able to read546(96%)318(89%)Employed530(93%)217(61%)Number of children None199(35%)60(17%) 1-2207(36%)157(44%) 3 or more165(29%)141(39%) 3 or more165(29%)141(39%)Women’s past year physical IPV––32/354(9%)Women’s past year sexual IPV––58/354(16%)Relationship changed since exposed to SASA!491/518(95%)213/354(60%)SASA! Exposure:Communication materials/poster Never*3(1%)17(5%) 1 time94(17%)57(16%) A few times (2-4)301(53%)85(24%) Many times (5+)173(30%)199(56%)Drama/film (mid media) Never*99(17%)121(34%) 1 time177(31%)75(21%) A few times (2-4)198(35%)99(28%) Many times (5+)97(17%)63(18%)Discussion activity (Interpersonal communication) Never*60(11%)110(31%) 1 time179(31%)81(23%) A few times (2-4)237(42%)114(32%) Many times (5+)95(17%)53(15%)Sought CA advice (Interpersonal communication) Never*354(62%)286(80%) 1 time125(22%)20(6%) A few times (2-4)60(11%)36(10%) Many times (5+)32(6%)16(4%)Multi-channel exposure vs. mass media only (exposure to materials plus activities and/or films) None*1(%)2(1%) Mass media only28(5%)80(22%) Low multi-channel exposure283(50%)138(39%) High multi-channel exposure259(45%)138(39%)*Given the sample, 'never' category here indicates participants with some SASA! exposure, but no exposure to the specified channel

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In the quantitative sample, among partnered community members who reported at least some exposure to SASA!, nearly all had seen SASA! materials (e.g. posters) and 69% of women and 89% of men had been to a discussion activity at least once (Table 2). Drama exposure was also high (83% of men and 66% of women) and the majority had attended a few times at least. Nearly twice as many men (39%) report seeking advice from a community activist, compared to women (20%). And, most participants were exposed through multiple channels with 39% of women and 50% of men reporting low (1-4 times) ‘multi-channel’ exposure (materials plus drama and/or discussion activity exposure) and 45 and 39% (respectively) high exposure (5 or more times).

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In the qualitative sample, 18 of the 20 participants had been exposed through at least one communication route, with two women reporting no exposure at all (5F, 8F). The intensity and type of exposure to SASA! varied among participants. There were examples of couples and individuals that primarily had direct relationship support from a community activist (2 M, 10F, 10 M), and others who only had attended activities or dramas (1F, 1 M, 5 M, 7F, 9 M, 9F). The former case tended to be couples who had been experiencing violence and either went to the local council office for support, or sought support from a friend, neighbour or relative that was a community activist. One woman did not feel motivated to attend activities because she received intensive support from the CA:In that area [attending activities] I have been lazy, maybe it is because I was relying on [CA]...but still I cannot say that I am so informed about their activities...I get to hear about these things from [our CA]...he usually tells me that they have gone for training, things like that...but we have not been active in attending them. (10F).

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In that area [attending activities] I have been lazy, maybe it is because I was relying on [CA]...but still I cannot say that I am so informed about their activities...I get to hear about these things from [our CA]...he usually tells me that they have gone for training, things like that...but we have not been active in attending them. (10F).

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