NSAIDs inhibit tumorigenesis in gastrointestinal tissues and have been proposed as coadjuvant agents to chemotherapy. The ability of cancer epithelial cells to adapt to the tumour environment and to resist cytotoxic agents seems to depend on rescue mechanisms such as autophagy. In the present study we aimed to determine whether an NSAID with sensitizing properties such as indomethacin modulates autophagy in gastric cancer epithelial cells. We observed that indomethacin causes lysosomal dysfunction in AGS cells and promotes the accumulation of autophagy substrates without altering mTOR activity. Indomethacin enhanced the inhibitory effects of the lysosomotropic agent chloroquine on lysosome activity and autophagy, but lacked any effect when both functions were maximally reduced with another lysosome inhibitor (bafilomycin B1). Indomethacin, alone and in combination with chloroquine, also hindered the autophagic flux stimulated by the antineoplastic drug oxaliplatin and enhanced its toxic effect, increasing the rate of apoptosis/necrosis and undermining cell viability. In summary, our results indicate that indomethacin disrupts autophagic flux by disturbing the normal functioning of lysosomes and, by doing so, increases the sensitivity of gastric cancer cells to cytotoxic agents, an effect that could be used to overcome cancer cell resistance to antineoplastic regimes. Additionally, NSAIDs have been tested as coadjuvants to antineoplastic regimes, with promising results obtained6. Both the abovementioned gastrointestinal toxicity and potential antineoplastic effect seem to be related with a reduction in the ability of epithelial cells of either normal or cancerous origin, to circumvent the damaging effects of aggressive digestive juices in the former case and scarcity of nutrients and cytotoxic treatments in the latter. In cells exposed to such challenging situations, the occurrence or avoidance of apoptosis often depends on the activation of rescue mechanisms like macroautophagy (hereafter referred to as autophagy)7. In fact, recent evidence suggests that the resistance to some cytotoxic agents is subject to the activation of autophagy8.Epithelial cells of the gastrointestinal system are targets for non-steroidal anti-inflammatory drugs (NSAIDs). When used to treat pain and inflammation these drugs exert a deleterious effect on digestive epithelia, which constitutes their main side effect. However, this activity of NSAIDs has a knock-on positive effect by inhibiting tumorigenesis in gastrointestinal tissues, the underlying mechanisms of which are poorly characterized7. Indeed, in the case of aspirin, we have observed that inhibition of this process contributes to the drug’s gastrotoxicity9. However, autophagy has also been implicated in cell death, and recent studies have linked it to the deleterious action of another classical NSAID, indomethacin, in primary gastric10 and intestinal cells11. Taking into consideration that indomethacin has shown potential as a sensitizing agent with regard to the cytotoxic effects of anticancer drugs15, in the present study we aimed to determine the effects of this NSAID on autophagy in gastric cancer epithelial cells and how they influence cell sensitivity to an antineoplastic agent.The objective of autophagy is to degrade superfluous and damaged organelles, cytosolic proteins and invasive microbes by forming a double-membrane sequestering compartment termed the phagophore, which matures into an autophagosome. Once the cargo has been delivered to the lysosome and degraded, the resulting macromolecules are released back into the cytosol and used as macromolecular constituents and energy sources in order to maintain cell viability, thus constituting the predominant role of autophagyFirst, we determined protein levels of several autophagic markers  in AGS cells after 24-hour treatment with indomethacin. The LC3-I cytosolic form is transformed by lipidation on the autophagosome component LC3-II which, once this vesicle has fused with the lysosome, is degraded or recycled. LC3-II protein levels in AGS cells were increased by indomethacin, which may have been a consequence of either induction of autophagy or inhibition of lysosomal-dependent autophagic degradation Fig. .Figure 1The p62 and NBR1 proteins are autophagy receptors that attract specific autophagy targets to the autophagosome by interacting with them and with LC3-II protein. Eventually enclosed within the autophagosome/autolysosome, they are degraded by lysosomal proteases. Treatment of AGS cells with indomethacin resulted in the accumulation of both p62 and NBR1 proteins Fig. , suggest), while the indomethacin-induced accumulation of LC3-II, but not of p62, was reduced when cells were treated in the presence of wortmannin, a general PI3K inhibitor whose action downstream from mTOR is capable of inhibiting basal autophagy , and observed a significant reduction of this enzymatic activity in cells treated with indomethacin for 6 or 20 hours Fig. . This suTo further examine the role of lysosomes in the actions of indomethacin, we analyzed the effects of the NSAID in the presence of two different lysosome inhibitors: chloroquine and bafilomycin B1. Treatment with chloroquine alone induced a slight reduction in Lysotracker fluorescence Fig.  and lysoStatic cytometry performed at the end of the treatment period revealed that indomethacin had produced a dose- and time- dependent toxicity, manifested as a progressive reduction in the number of cells per field. This toxicity was enhanced by co-treatment with lysosome inhibitors, especially with chloroquine, the doses of which were reduced as the treatment period was extended in order to perform the analysis in comparable circumstances . None of these effects was enhanced by co-treatment with indomethacin, which suggests that the disruption of lysosomal function by bafilomycin outweighs the activity of indomethacin and further supports the hypothesis that lysosomes are the target of indomethacin.To further analyze the role of the lysosomal actions of indomethacin on autophagic inhibition we evaluated its effects in the presence of two lysosomal inhibitors: bafilomycin B1 and chloroquine. The first possesses a well-characterized dual mechanism of action involving the blockade of both the V-ATPase responsible for lysosomal acidification and lysosome-autophagosome fusion20, it is possible that chloroquine, alone or in combination with indomethacin, provokes non-canonical LC3 lipidation21, a process that would not occur in the presence of bafilomycin B1 because it depends on V-ATPase activity. Notwithstanding, as a whole, our results indicate that indomethacin potentiates the effects of chloroquine, a drug that is traditionally used against malaria and is undergoing clinical trials as a coadjuvant to antineoplastic regimes23. In accordance with our results, previous studies report a parallelism between indomethacin and chloroquine with regard to their effects on cancer epithelial cells24 and a synergy between the two drugs in their action against malaria25.The combination of indomethacin and chloroquine appears to generate a more complex situation. Chloroquine induced a mild lysosomal dysfunction that was potentiated by indomethacin. Accordingly, the accumulation of p62 induced by bafilomycin B1 was higher than that induced by chloroquine, but it was equalled by the combination of chloroquine and indomethacin. With regard to LC3-II, the effects of chloroquine were comparable to those induced by bafilomycin B1 and, even so, LC3-II levels tended to be higher in cells treated with the combination of chloroquine and indomethacin. In fact, this combination of drugs resulted in the accumulation of a higher number of LC3-II puncta. Since an activation of autophagic flux as a compensatory response to lysosomal blockade seems unlikely in light of the results obtained with bafilomycin B1 and the unchanged mTOR activity23. We have observed that oxaliplatin, an antineoplastic drug commonly used in gastric cancer, tends to increase the presence of LC3-II puncta in AGS cells, and that this increase is more pronounced in the presence of indomethacin, alone or combined with chloroquine. It seems, therefore, that oxaliplatin promotes autophagy in these gastric cancer cells and that indomethacin, alone and especially in the presence of chloroquine, inhibits the degradation of the newly formed autophagosomes. When we added indomethacin to the culture media after a period in the presence of oxaliplatin, this NSAID enhanced the toxic effect of oxaliplatin and produced a concomitant decrease in autophagic activity, which may explain the synergy observed between the two drugs in the present study and previously in an in vivo model of cancer26. Thus, inhibition of lysosomal function and the consequent interference with autophagic degradation may be partly responsible for the beneficial effects of indomethacin in cancerous processes reported in some studies27.The rationale for incorporating chloroquine into antineoplastic regimes is based on the fact that autophagy occurs as a mechanism of cancer cell resistance to cytotoxic drugs28. These studies show that inhibition of autophagy by pharmacological or genetic means protected cells against indomethacin’s cytotoxicity and assumed that indomethacin causes damage by stimulating autophagy. However, some of their results challenge the idea of an activated autophagy. Indomethacin-treated cells presented a higher LC3-II/LC3-I ratio and increased levels of LC3-II, total LC3 and ATG511, perhaps due to induction of autophagy or inhibition of autophagic degradation. To determine which of the two is responsible, autophagic flux needed to be evaluated in the presence of a lysosomal inhibitor7. The only result reported in this respect advocates an inhibitory action, since indomethacin failed to increase the number of autophagosomes in chloroquine-treated cells10. This was corroborated by the reported accumulation of ubiquitinated proteins in cells treated with indomethacin28. Other studies using the COX-1 inhibitor SC-56029 or sulindac30 have proposed a stimulatory effect on autophagy without analyzing autophagic flux, which makes them inconclusive. On the other hand, a well-contrasted stimulatory action of the COX-2 inhibitor celecoxib on this process has been observed in several human colorectal cell lines31. Thus, the effects of NSAIDs on autophagy in gastrointestinal epithelial cells are far from clear, but would seem to be drug-specific.In contrast to that, which occurs in cancerous gastric epithelial cells, a toxic effect of autophagy has been reported in non-transformed gastric and intestinal cells28 is intriguing. It is possible that the inhibition of autophagic degradation and consequent accumulation of autophagosomes/autolysosomes provoke a toxic effect that is diminished by preventing the formation of these structures, despite an accumulation of autophagic substrates in the cytosol. In line with this argument, different autophagy inhibitors may have varying effects on cell survival depending on the phase (early or late) of the process targeted. This needs to be addressed to reveal further knowledge about the complex relationship between autophagy and cell survival/death, especially in the context of cancer33. Our results point to the well-known NSAID indomethacin, alone or combined with the classic drug chloroquine, as a candidate drug whose ability to sensitize cancer cells to cytotoxic agents should be tested further.Regardless of indomethacin’s impact on autophagic flux, the fact that inhibition of autophagy exerts a protective effect against its deleterious actionAGS cells (ATCC) were cultured in F12K medium (Life Technologies) supplemented with 10% inactivated FBS, 100 U/ml penicillin, 100 μg/ml streptomycin, and 100 mM sodium pyruvate. HT29 cells (ATCC) were cultured in McCoy’s 5 A medium (Life Technologies) supplemented with 10% inactivated FBS, 100 U/ml penicillin, 100 μg/ml streptomycin, and 2 mM glutamine.9 using Lipofectamine-2000 (Life Technologies). Following transfection, positive cells were selected by adding 250 µg/mL of the antibiotic G418 (Sigma-Aldrich) to the culture medium. After several passages, cells were sorted with FACSAria III (BD) to obtain a pure culture of green cells, which were maintained in medium supplemented with G418.In order to obtain cells with a stable expression of a fluorescence-labelled LC3B protein, we transfected AGS cells with the p3xFLAG/EmGFP/LC3B plasmidFor treatment purposes, cells were incubated in culture medium with reduced serum (0.5% of inactivated FBS).Cells were homogenized in lysis buffer containing proteases  and phosphatase inhibitors. Equal amounts of protein were loaded onto SDS-PAGE gels and analyzed by Western blot . Nine photographs (20×) per well were taken and the number of cells with autophagosomes and the amount of LC3-puncta per cell were counted by an observer unaware of the treatment administered.Immunocytochemistry for LAMP2 was performed in formalin-fixed AGS cells. After blocking with BSA and goat serum, cells were incubated with the primary antibody  followed by a texas red - conjugated secondary antibody and 5 µM of Hoechst 33342   and ScanFor lysosomal pH analysis, AGS cells were incubated for 30 min with LysoTracker® Red DND99  or with Acridine Orange . LAMP2 expression was detected as described above.The rate of apoptosis/necrosis was analyzed by means of the Apoptosis Detection Kit (Abcam), which detects phosphatidylserine exteriorization in apoptotic cells with AnnexinV-fluorescein and cell permeability to the chromatin-detecting dye propidium iodide in dead or damaged cells.Supernatant from AGS cell lysates was incubated with the Ommicathepsin fluorogenic substrate  for 30 min at 37 °C. Fluorescence emitted by released AMC was quantified in a plate reader  and normalized by total protein content.Cell viability in AGS cells was detected by the Cell Proliferation Kit I  following the manufacturer’s instructions.Data are expressed as mean ± S.E.M. In some cases, data are expressed as percentage or fold-induction vs respective control values in order to obtain more illustrative graphs. However, in all cases statistical analyses were performed for absolute values. Data were compared by one way-ANOVA/repeated measures one way-ANOVA with a Newman-Keuls post hoc correction for multiple comparisons, by two way-ANOVA or by Student’s t-test when appropriate. A P value < 0.05 was considered to be statistically significant.Indomethacin (I7378), chloroquine (C6628), bafilomycin B1 (11707), and wortmannin (W1628) were obtained from Sigma-Aldrich. Oxaliplatin (ab141054) was obtained from Abcam. Rapamycin was kindly provided by Pfizer.The authors agree to make materials, data and associated protocols promptly available to readers.Supplementary Information


Zimbabwe aims to increase circumcision coverage to 80% among 13- to 29-year-olds. However, implementation data suggest that high coverage among men ages 20 and older may not be achievable without efforts specifically targeted to these men, incurring additional costs per circumcision. Scale-up scenarios were created based on trends in implementation data in Zimbabwe, and the cost-effectiveness of increasing efforts to recruit clients ages 20–29 was examined.Zimbabwe voluntary medical male circumcision (VMMC) program data were used to project trends in male circumcision coverage by age into the future. The projection informed a base scenario in which, by 2018, the country achieves 80% circumcision coverage among males ages 10–19 and lower levels of coverage among men above age 20. The Zimbabwe DMPPT 2.0 model was used to project costs and impacts, assuming a US$109 VMMC unit cost in the base scenario and a 3% discount rate. Two other scenarios assumed that the program could increase coverage among clients ages 20–29 with a corresponding increase in unit cost for these age groups.When circumcision coverage among men ages 20–29 is increased compared with a base scenario reflecting current implementation trends, fewer VMMCs are required to avert one infection. If more than 50% additional effort (reflected as multiplying the unit cost by >1.5) is required to double the increase in coverage among this age group compared with the base scenario, the cost per HIV infection averted is higher than in the base scenario.Although increased investment in recruiting VMMC clients ages 20–29 may lead to greater overall impact if recruitment efforts are successful, it may also lead to lower cost-effectiveness, depending on the cost of increasing recruitment. Programs should measure the relationship between increased effort and increased ability to attract this age group. In 2011, the World Health Organization (WHO) and the Joint United Nations Programme on HIV and AIDS (UNAIDS) released the “Joint Strategic Action Framework to Accelerate the Scale-Up of Voluntary Medical Male Circumcision for HIV Prevention in Eastern and Southern Africa 2012–2016” . In respAs of June 2015, the national VMMC program had circumcised 509,753 males, of whom 441,133 were ages 13–29, representing 34% of the national VMMC target of 1.3 million males in this age group. The circumcisions conducted by the end of 2014 in Zimbabwe were projected to avert 6,300 HIV infections by 2025, with coverage estimated at 19% among 10- to 29-year-olds and 18% among 15- to 29-year-olds [As implementers rolled out VMMC programs in Zimbabwe and the other VMMC priority countries in eastern and southern Africa, it became evident that recruiting adolescents ages 10–19 was much easier than recruiting adult men for VMMC, and that few men over the age of 35 were accessing VMMC services , 8. In sThe five DMPPT 2.0 country application papers in this collection –17 all cZimbabwe VMMC program trends suggest that if the VMMC program in Zimbabwe continues without any specific efforts to attract older men, coverage will likely plateau at a lower level for the men ages 20 and above. We used data on coverage trends by age for the national VMMC program in Zimbabwe to make predictions about the level at which coverage would plateau in the different age groups: the base scenario for our analyses. We projected the impact and cost-effectiveness of this scenario, which we considered more realistic than previous explorations that assume it is possible to reach 80% coverage in any age group without any additional investment in attracting the older men to services. We then assessed the primary research question in this paper: How would expending greater effort (and therefore funds) to increase coverage among clients ages 20–29 affect the impact and cost-effectiveness of the VMMC program? Because no data about the relationship between cost and increasing coverage by age group are available, we created modeling scenarios to explore this question based on arbitrary assumptions about how increased effort may lead to increased coverage. We contrast these more realistic scenarios with one that assumes that reaching 80% coverage among all males ages 10–29 can be achieved with the same VMMC unit cost across all age groups .The DMPPT 2.0 model is described in detail in Kripke, Opuni, Schnure, et al. . BrieflyThe DMPPT 2.0 model is populated with population, mortality, and HIV incidence and prevalence projections from an external source. For the Zimbabwe country application, we used the national Spectrum/AIM model , which pNumbers of VMMCs conducted in the country each year through December 2014, disaggregated by client age, were provided by the Zimbabwe Ministry of Health and Child Care (MOHCC) on October 18, 2015 . The MC To estimate the impact of scaling up MC to 80% coverage in separate five-year age groups, the model scaled up MC coverage within each individual five-year age group from the baseline level in 2014 to the target in 2018 while holding coverage constant at the baseline MC prevalence for the other age groups. The scale-up applied a linear interpolation between the baseline MC prevalence for each age group in 2014 and the 80% target coverage in 2018. After 2018, the coverage for each age group was maintained at 80%. For more details on the methods behind the results in this paper surrounding modeled incidence reduction from providing VMMC to individual age groups, and modeled impact of scaling up VMMC to progressively lower age groups, see Kripke, Chen, and Vazzano, et al. .t and age group a  is given by the baseline MC prevalence for age group a plus the MC coverage resulting from the VMMC program for age group a:The remainder of this paper is based on scenarios derived by projecting historical trends in MC coverage by age group and year from Zimbabwe’s VMMC program. Total MC coverage in year CVMMC,a,t) is the MC coverage in age group a in year t resulting from the VMMC program,  is the number of males in age group a in year t who at some point in time had been circumcised through the VMMC program, and  is the number of males in the population in age group a in year t.Male circumcision coverage resulting from the VMMC program was calculated from the age-disaggregated VMMC program statistics presented in MVMMC,a,t is calculated as follows:a at the beginning of year t was the number at the beginning of the previous year t-1, plus new VMMCs performed during year t-1 and net VMMCs aging into and out of group a, all adjusted for mortality.The number of circumcised males in age group t (It) is given by:The increase in MC coverage in year To assess the impact, cost, and cost-effectiveness of increasing MC coverage among males ages 10–29 above what historical program trends would indicate, we used four scenarios. The first scenario assumed scale-up to 80% coverage among males ages 10–29, with the same unit cost ($109) for each five-year age group. Scale-up was linear from baseline levels in 2014 to 80% in 2018 and was maintained at 80% thereafter.increase in MC coverage rather than the annual MC coverage, because we observed that the VMMC program was expanding exponentially each year, and we wished to project the level at which MC coverage would plateau in each age group if the program continued to expand at the same rate in each age group until it reached saturation, which we defined as 80% MC coverage among males ages 10–19.The base scenario was created as follows: For each age group , we plotted the annual increase in MC coverage, calculated from the VMMC program data as described above, for each year from 2011 to 2014. We plotted the annual 2 values for each trend line. In the base scenario, the increases in MC coverage for 2015–2018 for each age group were projected based on the indicated equation, with maximum possible MC coverage set to 80%. Based on this projection, the 10–14 and 15–19 year age groups reached 80% coverage by the end of 2017. We assumed that once the program reached 80% coverage of 10- to 19-year-olds, it would no longer be possible to increase MC coverage in the older age groups without additional demand creation and program modifications specifically targeted to these age groups. Therefore, in the base scenario, target coverage in the model from 2018 on was maintained constant for all age groups based on the coverage achieved by the end of 2017 ; the total cost of the VMMC program; the percentage of HIV infections averted; the number of VMMCs per HIV infection averted; and the cost per HIV infection averted. Costs, numbers of circumcisions, and infections averted were all discounted at a rate of 3% per year.Prior analyses in other countries  projecteThe age distribution of VMMC clients in Zimbabwe has been biased toward adolescents. Clients ages 10–19 have been coming in at a higher rate and clients ages 20 and older have been coming in at a lower rate than would be expected based on the age distribution of uncircumcised men . AlthougFurthermore, the relative proportion of clients ages 10–14 has been increasing over time, whereas the proportion of clients over age 20 has been decreasing. The proportion of clients ages 15–19 appears to have stabilized in the past four years .Given trends in the distribution of VMMCs by age group, we projected that implementers would not reach 80% MC coverage among the age groups above age 19 without significant additional effort and cost to recruit adults to access VMMC services. We asked at what level of MC coverage each age group would plateau if current trends continue. We assumed that as services continued to expand throughout the country, demand would saturate in each age group either when MC coverage reached 80% in a given age group or when MC coverage reached 80% in the 10–19 year age group, whichever came first . The assWe then hypothesized that it would be possible to increase coverage of the 20–29 year age group, by putting increased effort and resources into interventions tailored to this age group. In the absence of costing data by age segment, we made an arbitrary assumption that a linear relationship exists between the unit cost for clients ages 20–29 (a proxy for effort) and the percentage of the target population ages 20–29 circumcised each year, such that doubling the VMMC unit cost would double the percentage of the target population circumcised, and so on. Thus we created two additional scenarios, as While No data are currently available about the relationship between cost and increased coverage for a specific age group, so the unit cost assumptions used in Scenarios A and B in If no additional cost per VMMC is required to increase coverage among males ages 20–29 , the total cost of Scenario A is $420 million—the same as for the 80% scenario, but with fewer HIV infections averted, because Scenario A does not reach 80% coverage among males ages 25–29.  The cost per HIV infection averted for Scenario A in this case is $5,400, which is higher than that of the 80% scenario but lower than that of the base scenario. When the cost per VMMC for males ages 20–29 is 50% higher than in the base scenario , the cost per HIV infection averted in Scenario A, $6,000, is the same as in the base scenario, and the total cost of Scenario A, $468 million, is higher than that of the 80% scenario. If the unit cost required to increase coverage among males ages 20–29 is more than 50% higher than that of the base scenario, the cost per HIV infection averted is higher than that of the base scenario.This study has several limitations. The general limitations of the DMPPT 2.0 model are discussed in the methods paper in this collection  and theyIn this paper, we predicted that VMMC coverage in the age groups above age 19 would plateau at a lower level than in the younger age groups, based on historical trend data from the VMMC program and knowledge of the sociocultural factors that make VMMC more desirable to adolescents. If our prediction turns out to be the case, the relative contribution of each age group to HIV incidence reduction will be based on a combination of the level of coverage at which the program plateaus for each age group and the HIV incidence in that age group and the next higher age group. In the base scenario explored in this paper, the greatest contribution to HIV incidence reduction comes from circumcising males between the ages of 15 and 19. Increasing coverage among males ages 20–24 and 25–29 increases the contribution of these age groups to HIV incidence reduction.No data have been published or are otherwise available showing how much it costs to increase coverage among males ages 20 and above. We hypothesized that it would be possible to increase coverage of the 20–29 year age group by putting increased effort and resources into demand creation interventions tailored to this age group, such as outreach to specific locations where older men (20–29) convene. In addition, increased uptake of services among this older age group would likely entail structural changes at service delivery sites to make them more attractive to the older males, such as “VIP services,” offering extended hours, and separate transport and waiting areas for adults, who are often embarrassed to mix with adolescents. Additional formative research could be conducted to tailor campaigns to the factors that motivate the older males in their specific contexts, including socioemotional factors that may move them to action.In the absence of actual data about the cost required to increase coverage among 20- to 29-year-olds, we conducted an analysis using an arbitrary assumption that a linear relationship exists between the age-specific unit cost and the percentage of the target population ages 20–29 circumcised in each year, for the sake of exploring what might happen. Given this assumption, our analysis demonstrated that increased coverage among these age groups would lead to higher costs per HIV infection averted (lower cost-effectiveness) of the VMMC program than did scenarios that assumed the cost to reach men ages 20–29 would be the same as the cost to reach adolescents ages 10–14. In Scenarios A and B, in which increased resources were used to increase coverage among the population ages 20–29 compared to the base scenario, the number and percentage of HIV infections averted, total cost, and cost per HIV infection averted were progressively higher than in the base scenario, while the numbers of VMMCs per HIV infection averted were progressively lower.A sensitivity analysis in which the unit cost for circumcising males ages 20–29 was varied for Scenario A showed that the cost per HIV infection averted was equal in the base scenario and Scenario A when the unit cost of circumcising males ages 20–29 in Scenario A was 1.5 times that of the base scenario. Below this threshold, the cost per HIV infection averted was lower in Scenario A than in the base scenario, and vice versa. Therefore, if additional resources are available to increase coverage among men ages 20–29, it might be possible to increase the overall impact of the VMMC program, and doing so could also make the program either more or less cost-effective. The actual relationship between cost and increased recruitment of clients in the 20- to 29-year age group will determine whether these efforts make the program more cost-effective or less cost-effective, so collecting these data is crucial.Zimbabwe is trying to increase representation of men ages 20–29 among VMMC clients. In order to scale up demand and encourage men, especially those 20–29 years old, to get circumcised, the country began a comprehensive research program in 2015 to map a man’s journey to circumcision and identify points at which interventions could be strategically placed to increase demand for circumcision. Based on this research, the Government and implementing partners developed a detailed communications and marketing strategy targeting specific segments of men. In 2016, the country began implementing that strategy, accompanied by costing studies. The data collected can shed insights on the feasibility of this strategy and inform further analyses about cost-effectiveness of increasing demand among 20- to 29-year-old men.To date, seven countries  have completed detailed country DMPPT 2 model applications to reexamine their age-targeting strategies for VMMC –17,21,22The modeling presented here demonstrates that cost-effectiveness analyses of age targeting by VMMC programs need to take two related factors into account that were not considered previously: (1) the feasibility of reaching high levels of coverage among specified target age groups, and (2) if reaching these high levels of coverage is possible at all, how much that will cost, in comparison with the costs of programs as currently implemented. Zimbabwe is modifying its VMMC program to attract more males ages 20–29. Even if the country’s age-specific recruitment efforts are successful, increasing the program’s overall impact on HIV incidence, the added investment required may also lead to lower cost-effectiveness. Data collected from this program in Zimbabwe and similar efforts in other countries can be applied to cost-effectiveness analyses to inform future age-specific VMMC strategies in Zimbabwe and in other VMMC priority countries.S1 TableNote: Data were obtained from national program records. Because VMMCs for ages 30–49 were not available disaggregated by five-year age groups, they were disaggregated based on the age distribution of circumcisions conducted in Malawi in PEPFAR FY 2013, based on PEPFAR program data. VMMCs for ages 50+ were put into the 50–54 age group in the DMPPT 2.0 model.(XLSX)Click here for additional data file.S2 TableThe x-values in the equation represent the year minus 2010 (the first year of the curve projection).(DOCX)Click here for additional data file.S1 FigEach solid line presents data from a specific VMMC client age group. Male circumcision (MC) coverage is measured at the beginning of each year. Trend lines (dotted lines) were generated from Microsoft Excel 2013 using an exponential fit.(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.


These methods were subsequently applied to the AhR and Nrf2 signalling pathways and altered expression of the predicted target genes was validated by qPCR in Caco-2 cells exposed to coffee extracts, known to activate both AhR and Nrf2 pathways. The datasets and in silico method(s) to identify and predict responsive target genes can be used to more efficiently design experiments to study Caco-2/intestinal epithelial-relevant biological processes.Intestinal epithelial cells, like Caco-2, are commonly used to study the interaction between food, other luminal factors and the host, often supported by microarray analysis to study the changes in gene expression as a result of the exposure. However, no compiled dataset for Caco-2 has ever been initiated and Caco-2-dedicated gene expression networks are barely available. Here, 341 Caco-2-specific microarray samples were collected from public databases and from in-house experiments pertaining to Caco-2 cells exposed to pathogens, probiotics and several food compounds. Using these datasets, a gene functional association network specific for Caco-2 was generated containing 8937 nodes 129711 edges. Two  Such networks can be usefully exploited to gain key insights into biological systems3. Exploration of tissue and cell type specific networks has demonstrated the effects of tissue specific regulation on the remodelling of biological networks4. Differential network analysis has also been used to compare topological characteristics of networks corresponding to normal or tumorous cells and to isolate characteristics of distinct cancer subtypes, which in turn has led to the prediction of cancer subtype-specific drug targets5. One important biological system is the epithelial cells lining the small and large intestine. The role of diet and the response of host towards diet and its compounds is challenging to be studied in vivo due to the complexity of biological systems and inter-individual variability. Thus, a reductionist approach using the human Caco-2 intestinal epithelial cell line is a widely accepted laboratory model to understand the response of intestinal enterocytes exposed to nutrition and microbes8. Although Caco-2 cells were derived from a colon carcinoma, when cultured as confluent monolayers for 2–3 weeks, they functionally resemble the enterocytes lining the small intestine9. Caco-2 cells have been used in numerous experiments to study effects of food products and compounds13, probiotics14, pathogens17 and other studies20, using microarrays. Comparative proteomic analysis of Caco-2 cells and scrapings of the human intestinal epithelium support the usability of this invitro model21, although Caco-2 cells appear to over-express as well as under-express certain proteins which needs to be considered in the interpretation of in vitro data and translation of results to the in vivo situation21.Biological networks are representational interactions between genes, proteins, and other biomolecules. Different kinds of biological networks  represent different features of a cell24 are present, to the best of our knowledge, no broad compendium of Caco-2 microarray experiments has been initiated, limited data on metabolic networks is available26 and no gene/protein association networks are available for Caco-2/intestinal enterocytes. Another commonly faced problem is the identification of Genes Of Interest (GOI) in the pathways investigated for a specific cell type. Thus identification of candidate sets of GOI could help study the impact of treatments on specific pathways of interest in a given cell type.A compendium of Caco-2 gene expression profiles under a broad number of conditions can be instrumental in building dedicated network models describing gene interactions in human intestinal enterocytes and in providing new insights on their functioning. Although, gene profiles tuned for selected tissues28, play an important role in the exclusion or detoxification of xenobiotics and regulating oxidative stresses. The AhR and Nrf2 pathways are involved in the metabolism of xenobiotics and protection against oxidative stress30. AhR is an important regulator of Phase I and Phase II enzymes and other enzymes which metabolize compounds such as dioxins, polycyclic aromatic hydrocarbons, plant polyphenols and tryptophan photoproducts31. Nrf2 has been designated the “master regulator” of the adaptive response to oxidative stress29 and regulates the expression of antioxidant proteins that protect against oxidative damage triggered by injury and inflammation.Intestinal epithelial cells, apart from major functions like digestion and absorption of nutrients, minerals and waterhttp://semantics.systemsbiology.nl/index.php/download-page/ with a working example.In this study, we aim to i) exploit the knowledge accumulated in the publicly available datasets on Caco-2 cells exposed to different treatments in order to generate a dedicated network model accounting for gene associations specific to intestinal enterocytes and ii) to develop workflows to reliably select genes for studying intestinal enterocyte-specific pathways. The proposed strategies were experimentally validated by focussing on GOI in the Nrf2 and AhR pathways using Caco-2 cells exposed to coffee to induce the gene responses within these pathways. The obtained networks are provided as supplementary files (Caco2_Network) and R scripts for the identification of GOI are made available at 32. Coffee extracts have a great chemical diversity and the components vary according to the cultivar, treatment, processing, storage and others36. We have tested induction of these pathways using four coffee types.In this study, we develop strategies to generate dedicated gene network models for Caco-2 and identify specific gene responses to nutrition related exposures. This was illustrated using Ahr and Nrf2 pathways. We have independently validated our results through a new experimental setup on which Caco-2 cells were exposed to coffee extracts, which have previously been shown to induce the Ahr and Nrf2 pathways-p-dioxin) or coffee. 16 genes that are frequently used as indicators for AhR and Nrf2 signalling, were selected from the literature  expression in our compendium. However, even after this reduction, still large number of genes remain (77 nodes for Nrf2 pathway and 42 nodes for AhR pathway) to probe for each pathway and therefore we wanted to optimize our approach to identify GOI.i.e. genes well known to be responsive in Caco-2 cells to a specific perturbation). In order to identify Caco-2 responsive genes within the Nrf2 pathway, we used a full list of genes that are involved in this pathway (derived from generic IPA consensus pathway). SQSTM1, HMOX1, NRF2, ABCC1, DNAJB1 and ENC1 were selected as seed genes. The seed genes were used to identify co-expressed genes within the compendium of microarrays. The initial average correlation threshold for array selection was set at 0.75 . In this way, only arrays that showed a high degree of correlation with the seed genes were included for GOI identification.The biclustering method works based on identification of genes that are co-expressed with seed genes  to 229 arrays and the following genes were obtained as GOI: CDC34, DNAJC4, GTR, ATF4, GSTA2 and GSTM4. Together with the seed genes this resulted in a total of 12 potential responsive genes for the Nrf2 pathway  associated with Nrf2 and AhR pathways which are responsive to altered pathway activity. SQSTM1, NQO1 and HMOX1, involved in the Nrf2 pathway were used as seed genes for the DECA algorithm. 2834 genes were found to have correlation values or significance fractions above the 0.6 threshold against each seed gene. The genes were ranked as mentioned in Materials and Methods section and top ranked genes were considered for further analysis. From this list, GCLM43, EREG44, RND3, CHMP1B were chosen for experimental verification as evidence from scientific literature associated few of them with the AhR pathway. ATP9A was randomly selected as a negative control . Differences could be attributed to different selection procedures or experimental approaches. Additionally, the gene list and network provided in this paper are based on a compendium of transcriptomics data from exposure of Caco-2 cells to different nutrients and stimuli.Initially we focussed on developing an intestinal enterocyte-specific association network using expression data from Caco-2 cells exposed to different nutrients and stimuli. The network was constructed by selecting 12849 genes (actively) expressed in Caco-2 based on UPC filtering. This is consistent with previous observations of 11559When applying our Caco-2-specific selection to STRING network the number of edges and nodes was reduced considerably (~50%). The number of connected components is reduced by over 60% and the local network structure is preserved with similar values of clustering coefficient, which suggests a more compact network, as expected for gene that are functionally closely related. The degree assortativity decreases indicating less redundancy on gene associations when the network is restricted to Caco-2. Incidentally STRING could support dedicated data analysis by enabling seamless tissue specific gene selection.46, instead they generally try to find biclusters that cover either a broad range of genes or conditions. Similarly WGCNA based clustering does not focus on a particular pathway but looks for modules of co-expressed genes that may belong to more than one pathway. Here we present a biclustering approach, that represents a modification of that in van dam et al., that allows the user to select or pre-select the seed genes and thus a pathway47. Nevertheless, biclustering performed poorly as the identified GOI did not show significant DE, indicating little responsiveness of Caco-2 cells to coffee exposures.Biclustering simultaneously clusters both genes and samples to arrive at the identification of genes with similar expression profiles in a subset of the samples. Existing biclustering algorithms do not allow targeting a particular pathway40. KCTD5 is likely to have an indirect interaction mediated by CUL341 and BAG3 (negative control gene) has been associated with Nrf2 pathway42 while we find that only Turkish coffee induces this gene. Similarly for the genes predicted for AhR pathway, UGCG is indirectly linked to AhR pathway via ARNT43 and EREG is reported as a target gene for AHR44.Therefore, DECA algorithm was used, resulting in a list of responsive gene candidates and a set of criteria to further rank them. From the ranked list, genes were selected for experimental verification in Caco-2 cells exposed to coffee and we found association with AhR and Nrf2 pathways. The verified genes were not in these pathways as defined in IPA. It might be that some of these genes have an indirect association to these pathways. The DECA ranking can be combined with existing knowledge, for instance, adding weight to genes on the basis of literature evidence. Of the 5 genes predicted for Nrf2 pathway, GCLM and TXNRD1 are previously known downstream gene targets of NRF2Seed genes play a critical role in predicting responsive genes in a certain pathway and should be carefully considered and accurately selected. As an example, Nrf2 gene was initially included among the seed genes for the biclustering algorithm. However, experimental verification showed transcript levels of this gene not to be responsive to coffee exposure. It was later not used as seed gene for DECA algorithm and was replaced with NQO1. One optimal way to select seed genes is to select two or three highly differentially expressed genes (Fold Change > 3) associated to the pathway of interest from literature (eg. CYP1A1 and TIPARP for AhR pathway), verify their altered expression in response to activation or repression of the pathway and use these as seed genes.49. Instead, we have used a higher level integration approach, in which data from each study is compared with the corresponding control. This way we bypass the need for additional batch corrections as we study only correlations between changes in gene expression.The biclustering algorithm requires a further selection of genes to be considered, the gene pool set. This selection was performed by aggregating non cell type specific pathway level information. On the other hand, DECA has no such constraint and the whole set of expressed genes are considered. Therefore DECA is our method of choice to identify GOI in pathways for which little information is available. One could also argue that, when combining such a large set of array data collected over different batches, batch correction techniques should be applied. However, here each experiment has its own control in the same batch. As a result batch effects and experimental effects might be confounded and usually applied correction methods such as ComBat and SVA are not effective50 and thus could select food components that have effects on certain genes and pathways. Such datasets can also be used to predict key regulators and/or gene hubs2. Additionally, the database can be expanded further by adding data from future experiments, even from technologies like RNAseq. The provided Caco-2 specific network also serves as a platform to understand future experiments. Gene expression data from a new experiment could be integrated with this network by using algorithms for network mining and active module identification3. The Caco-2 cell type specific network can also be used to develop networks associated to different conditions such as Caco-2 exposure to pathogens or pathogenic toxins, then these networks can be used to identify potential drug targets by applying statistical methods and identifying hub genes using similar strategies as the one successfully used in cancer research51. This paper can therefore be seen as a first important step to improve current analysis tools for Caco-2 and thereby elicit a better understanding of the interaction between our intestinal epithelium and luminal  compounds.In addition to predicting GOI, the compendium presented in this paper can be used for other purposes. For instance, a systematic categorization of the treatments based on expression profile, similar to the approach taken in Connectivity mapin vivo. As the availability of experimental datasets will grow further we believe that this work is the first step in generation of a Caco-2 specific database and tissue specific research tools and strategies to extract more knowledge from these data. One of the research tools for which we make an important step is the dedicated protein-protein association network using gene expression data for Caco-2. The network provided in this paper could be the basis to be implemented in other software tools like IPA and STRING and can be further updated when more data become available in the future. The modified biclustering and DECA methods should additionally provide the necessary tools to extract genes of a desired pathways and can be applied, by the codes provided, to a similar dataset of any cell type of interest.Caco-2 cell lines are increasingly used as model systems to study the interaction of food and other luminal factors with the intestinal system of the host, which is difficult to study In the future, a comprehensive Caco-2 transcriptome database should include microarray data from other platforms such as Agilent, Illumina, etc but more importantly should include RNAseq data which will provide additional information on splice isoforms. We believe that such a cohesive database would provide finer results regarding the genes of interest in Caco-2 and can support the analysis and understanding of future Caco-2 cell based analysis. The dataset can additionally be used for building classifiers using genetic profiling and in finding therapeutic food solutions.www.ebi.ac.uk/arrayexpress) and from in-house experiments performed using Affymetrix© 1.1 ST array platform. In-house data was obtained by exposure of Caco-2 cells grown on transwells with different preparations of food-related compounds in experiments conducted over several years. Publicly available data was restricted to experiments on Affymetrix platform. Data and associated metadata were manually curated using the following inclusion criteria: i) experiments that did not induce genetic mutations, ii) experiments performed on Caco-2 cell monolayers that were grown for at least seven days and iii) arrays probing for at least 17000 genes (annotated in Chip Definition Files), thereby leaving out old arrays. Based on these criteria 341 arrays were selected corresponding to 22 experimental batches encompassing 85 different treatments  analysis, as it is considered as standard for this calculation53. All the normalization procedures were performed using R Bioconductor packages SCAN.UPC54 and affy55. Microarray probes were matched to gene identifiers using the CDF array annotation (version 18) provided by the University of Michigan microarray© lab56. After both normalization procedures, a combined set of 21996 genes was obtained. All statistical programming were performed using statistical language R (version 3.2.3).The consolidated data of 341 arrays were normalized using the SCAN algorithm before network construction and biclustering analysis, as this is a method that performs well for cross comparison54. Genes with a UPC value greater than 0.5 in at least one array were considered to be expressed in Caco-2 cells and therefore used in the analysis. This step was applied to the matrix of 21996 genes and 341 arrays reducing it to a matrix of 12849 genes and 341 arrays. In this matrix there were some genes with some values missing, likely due to platform differences. Therefore, genes with missing values in more than half the total number of arrays (ie. 170 arrays) were discarded. Remaining missing values were imputed using KNN algorithm from the ‘impute’ R package in refs Universal exPression Code (UPC) was used to obtain a standardized score describing the active/inactive state of each gene in each array of our data compendium59 was used for the retrieval of high confidence human specific protein association and a combined score cut-off value of 700 was used as recommended by STRING. Nodes representing genes identified as not being expressed by Caco-2 cells were removed from the network. The network (in edgelist format) is available as supplementary file (Caco2_Network). Edgelist contains pairs of interacting genes (first two columns) and in this file genes are denoted by their Entrez Ids. The third column refers to the weight of each edge, which is however empty in the given file, as the edges have no weights. The networkx (python package) was used for network topological analysis60.The database STRING (version 10)45 adapted by van Dam et al.47 was used to find biclusters (i.e. groups of co-expressed genes in a subset of conditions62). In our implementation a pre-defined set of genes, called seed genes, together with additional genes from a second list called gene pool were used to find biclusters. Seed genes were selected using the following two approaches: i) from literature on Caco-2 expression in response to different types of coffee . ii) from Weighted Gene Correlation Network Analysis63 (WGCNA). The WGCNA method partitions genes expressed in Caco-2 cell lines into groups enriched for topological overlap based on their expression profiles. These groups were then assessed for enrichment in genes belonging to the selected pathways using Ingenuity Pathways Analysis (IPA) . Genes assigned to the selected pathways in the enriched modules (FDR < 0.05) were further included in the seed gene list (DNAJB1 and ENC1 for Nrf2 pathway and ARNT and PRKCA for AhR pathway). To build the gene pool, genes expected to be in the pathway of interest were retrieved from pathway database IPA (Ahr and Nrf2 consensus pathway).The gene pool list contained 87 genes for Nrf2 pathway and 48 genes for AhR pathway.The Biclustering algorithm of cMonkeyT = 0.75 or half of the initial arrays have been removed.Biclustering was performed using R implementing the iterative procedure depicted in Fig. Once the reduced array set has been established, an additional iterative procedure to search for candidate genes is performed. In the initialisation step, a new list of genes is built containing the seed genes. Then a new gene is selected from the gene pool and the mean correlation between this new gene along with the genes in the current list is calculated. If such correlation value is greater than previous correlation value, the new gene is added. This procedure is iterated till no new genes remain. The full procedure of array reduction and gene addition is continued until a bicluster with the desired properties is obtained.limma64. Following this, UPC filtering was applied and the DE matrix  was reduced to 12849 genes. Genes that were missing expression values for more than 56 conditions (roughly two third conditions) were excluded and then remaining missing data were imputed using KNN impute as mentioned above. This resulted in a matrix of DE values for 12462 genes and 85 conditions. All corresponding missing p-values were substituted with 1.We implemented a new algorithm, Differential Expression Correlation Analysis (DECA) to find GOI using DE values from microarray datasets. The DECA algorithm works by calculating correlation values between seed genes and other DE genes identified using the UPC algorithm. DE values were calculated for 85 experimental setups (3 of which could not be used as they lacked sufficient replicates or controls) giving a total of 21996 genes. For each of these genes the treatments were compared to their respective controls using Bioconductor package The next step in DECA is the selection of seed genes from literature. Seed genes were chosen in such a way that they showed strong and significant  DE in stimulations associated to the chosen pathway .2n ranks (where n is the number of seed genes). A final rank was calculated by estimating the geometric mean of the 2n ranks for each gene.The workflow of the procedure is described in Fig. http://semantics.systemsbiology.nl/index.php/download-page/.All R scripts used in this paper are available at 67. The genes associated to each of the 10 pathways were selected form KEGG pathway database38. For each of these pathways, 3 seed genes were chosen at random. The chosen seed genes were ensured for significant differential expression in at least 15 experiments. The seed genes were then used in DECA and the resulting gene list was ranked as mentioned above. The number of genes present in the top 10% of the ranked list belonging to the pathway were calculated. In addition to this, a Welch two sample t-test was performed to assess if the average ranks of the pathway related genes had a better rank compared against the average ranks of the rest of the genes in the ranked list. The protocol was iterated 10 times for each pathway. The results are provided in Supplementary Table 10 pathways were chosen at random for assessment of DECA algorithm. These pathways are ABC transporters pathway, Adherens junction pathway, Fat Absorption pathway, Gap junction pathway, Glycerolipid metabolism pathway Glycerophospholipid metabolism pathway, Nfk-β signalling pathway, p53 signalling pathway, PPAR signalling pathway and TLR signalling pathway. Some of these pathways are known to be associated with intestinal epitheliaThe Caco-2 cells were cultured for 7 days until they reach confluence in DMEM (Dulbecco’s Modified Eagle Medium) (Control media) prior to exposure to coffee extracts  or TCDD. The RNA was harvested and primers were developed for qPCR. The detailed description of the protocol is provided in Supplementary Text The sources of datasets analysed during the current study are listed in Supplementary Table Supplementary Table S1Supplementary Table S2Supplementary Table S3Supplementary Text F1Caco2_Network


Background: A HIV positive-to-positive program was started in South Africa in 2008. The program was started because dialysis is not freely available to everyone, but severely limited and only available to a selected group of patients. Patients and Methods: Between September 2008 and March 2015, 29 patients were transplanted from HIV-positive brain-dead donors at Groote Schuur Hospital transplant team. Donors were either naïve to anti-retroviral therapy or on first line therapy. The recipients were selected to have undetectable plasma HIV type 1 RNA levels and be on a stable antiretroviral regimen. CD4+ T-cell counts of at least 200/mm3 in last 6 months prior to transplant, with no previous serious opportunistic infections. Results: Survivors in the study were followed for a median of 2.4 years. The rate of patient survival was 84% at 1 year and 74% at 5 years. The corresponding graft survival rate was 93% and 84%. Conclusion: Using HIV-positive donors might resolve some of the problems we are experiencing in getting enough donors for our patients wit ESRD. In the USA the HOPE act was accepted in 2014 and this might now also impact on the use of HIV positive donors elsewhere in the world. Abstract.  South Africa currently offers dialysis and transplantation as a treatment option for patients with end stage renal disease (ESRD). However, dialysis is not freely available to everyone, but severely limited and only available to a selected group of patients. This means that patients get assessed when they present with ESRD and they only get accepted onto a dialysis program if they fulfil certain criteria. These criteria are criteria to assess the patient’s medical fitness in general as well as social criteria to assess whether the patient will be compliant with follow-up. In most state hospitals, patients will only be accepted onto a dialysis program if they are also fit to receive a transplant in the long run. The idea is that dialysis programs should naturally feed into transplant programs. Therefore, a patient who is not a suitable transplant candidate will normally be turned down for dialysis. In 2008, when the HIV positive-to-positive program started, patients with ESRD and HIV would be turned down for dialysis. The reason was that they were seen as unfit for transplantation and therefore not suitable dialysis patients. This meant that anybody with HIV and ESRD was doomed to die. This situation remained unchallenged for a number of years, especially as the rollout of antiretroviral therapy was quite slow in the state sector. The HIV population with ESRD started to grow dramatically in 2008 in South Africa. A major problem with having HIV is that a large percentage of these people will develop HIV-associated nephropathy (HIVAN). Histologically, HIVAN is a collapsing form of focal sclerosing glomerulosclerosis (FSGS), which can be distinguished from idiopathic FSGS by the presence of microcystic tubular dilatation and interstitial inflammation . Modelling the incidence of ESRD and HIV in Sub Sahara Africa we know that we have at least 20.9 million people over the age of 15 years with HIV-related chronic kidney disease (CKD), according to UNAIDS prevalence statistics. It is estimated that ~ 60% of these people are treated with anti-retroviral therapy. Whether or not an individual is receiving treatment influences the rate of mortality in the HIV-CKD population, and also affects the rate of progression to ESRD in the population with HIVAN. Although the proportion of HIV-CKD that is attributable to HIVAN is variable, biopsy studies have reported that ~ 30% of CKD in the HIV positive South African population is attributable to HIVAN, and that treatment reduces the risk of developing ESKD in HIVAN by ~ 60% , 3. Because of very high HIV rates in the country, more and more HIV-positive brain-dead donors presented to the Groote Schuur Hospital Transplant team. These donors were mostly brain-dead people who were worked up for organ donation (after consent was obtained from the family) and who then turned out to be HIV positive. In 2008 it made sense to try and marry this supply of donors with the group of HIV positive patients without any treatment options in the country. Concerns about a second viral strain remained a problem. In the literature the outcomes and reports of HIV-positive patients with super-infections are difficult to interpret as there are a lot of methodological difficulties which often yield conflicting results , 5. WhenIn South Africa we have a unique situation in view of the fact that we have low antiretroviral therapy resistance rates , 7, 8, 9The HIV positive-to-positive program in Cape Town is a deceased donor program where the donors are HIV positive and selected according to the following criteria: ART-naïve donor If on ART, must be on first line treatment with no resistance Normal serum creatinine No proteinuria Protocol biopsy on reperfusion of kidney No donor with the following problems is used: Active viral/fungal/parasitic infection Malignancies Sepsis Possible HIVAN present 3 in last 6 months prior to transplant, with no previous serious opportunistic infections. If a patient had previous tuberculosis infection, it must be fully treated. Recipients are selected to have undetectable plasma HIV type 1 RNA levels and be on a stable antiretroviral regimen. CD4+ T-cell counts of at least 200/mmAspergillosis and Klebsiella Pneumonia sepsis. Two patients lost their grafts in the 1st week after transplantation: 1 with venous thrombosis of the graft and 1 with acute severe rejection within 1 week after transplantation. A 3rd patient lost her graft with chronic vascular rejection and fibrosis of the graft 2 years after her transplant. The risk of rejection in this patient population group is higher than expected in HIV-negative patients. In the Cape Town study, rejection took place on 8 occasions in 5 of the patients, which gives an acute rejection rate of 18%. This happened despite induction therapy with thymoglobuline. A dysregulated immune response might be the reason for high rejection rates despite potent immunosuppression, and similar high rejection episodes were reported in the NIH study using HIV-negative donors for HIV-positive recipients [In the study we have enrolled 29 patients over the last 5 years. Five patients died after transplant. The reasons for death were myocardial infarction, lung squamous cell cancer, pancreatitis with a duodenal perforation, disseminated cipients . Using HIV-positive donors might resolve some of the problems we are experiencing in getting enough donors for our patients with ESRD. In the USA, the HOPE act was accepted in 2014 and this might now also impact on the use of HIV-positive donors elsewhere in the world. None.


Type 1 diabetes is an autoimmune disease arising from the destruction of pancreatic insulin-producing beta cells. The disease represents a continuum, progressing sequentially at variable rates through identifiable stages prior to the onset of symptoms, through diagnosis and into the critical periods that follow, culminating in a variable depth of beta cell depletion. The ability to identify the very earliest of these presymptomatic stages has provided a setting in which prevention strategies can be trialled, as well as furnishing an unprecedented opportunity to study disease evolution, including intrinsic and extrinsic initiators and drivers. This niche opportunity is occupied by Type 1 Diabetes TrialNet, an international consortium of clinical trial centres that leads the field in intervention and prevention studies, accompanied by deep longitudinal bio-sampling. In this review, we focus on discoveries arising from this unique bioresource, comprising more than 70,000 samples, and outline the processes and science that have led to new biomarkers and mechanistic insights, as well as identifying new challenges and opportunities. We conclude that via integration of clinical trials and mechanistic studies, drawing in clinicians and scientists and developing partnership with industry, TrialNet embodies an enviable and unique working model for understanding a disease that to date has no cure and for designing new therapeutic approaches.The online version of this article (doi:10.1007/s00125-017-4384-2) contains a slideset of the figures to download, which is available to authorised users. Type 1 diabetes, a complex, three-stage, chronic autoimmune disease, accounts for 5–10% of all cases of diabetes. It is estimated that, worldwide, ~78,000 individuals under age 20 years are diagnosed with the disease annually, as well as a comparable number of adults. This disease rate has doubled every two decades since the middle of the last century and shows little sign of abating . But behThe 1974 discovery did not just achieve the subdivision of a syndrome—it is also of great practical importance. Autoantibodies directed against specific targets in the beta cell show high sensitivity and specificity for the identification of individuals at risk of future development of type 1 diabetes, in the absence of blood glucose abnormalities   of the National Institutes of Health and the JDRF, with the objective of developing a clinical network approach to type 1 diabetes prevention, while at the same time promoting studies of disease pathogenesis . In thisType 1 Diabetes TrialNet  has developed into an international network of researchers who are exploring ways to prevent, delay and reverse the progression of type 1 diabetes. TrialNet was established in response to the Surgeon General’s Report ‘Healthy People 2000’. This report identified diabetes as a US national health objective and in response the US Congress created the Diabetes Research Working Group (DRWG). One of this group’s earliest recommendations was the setting up of a programme of research studies and clinical trials to prevent type 1 diabetes .www.trialnet.org/our-research). One of the lynchpin programmes is the Pathway to Prevention study (protocol TN01), through which relatives of individuals with type 1 diabetes are screened for the presence of circulating autoantibodies. Those identified as being at increased risk  are followed up and offered clinical trial opportunities. During follow-up, individuals attend regular assessment visits that include the collection of blood for continued evaluation of islet cell autoantibody status and the collection of longitudinal samples for mechanistic studies, as well as determination of metabolic status  and systematic collection of metadata . These Since inception, TrialNet has thus assembled an enviable bioresource of longitudinal samples and metadata, which is open to access by the global research community through an ancillary studies programme. The collection contains over 70,000 samples gathered from over 7500 donors at various follow-up time points and includes genomic DNA, whole-blood RNA, serum, plasma and peripheral blood mononuclear cells. Further, specialised sampling and additional metadata can also be acquired in real-time studies. This is the ‘living biobank’ approach, which provides investigators with the opportunity to obtain on-demand biological samples from selected individuals who are engaged in TrialNet protocols. Studying these samples offers opportunities for natural history studies and can provide critical understanding as to how or why specific intervention strategies did or did not deliver a specified primary study outcome.As of 31 December 2016, more than 25,500 archived samples have been distributed to 35 laboratories for 48 ancillary studies  but there are also studies on beta cells as well as studies utilising multi-dimensional platform technologies (‘omics’) Fig. a. Serum The TrialNet programme of ancillary studies has provided more than 40 investigators with more than 25,500 samples and as such there is a wealth of information from work already done addressing important questions. Of relevance is the presence of more than 2900 donors who were analysed by different TrialNet investigators to address various scientific questions  that are likely to be related to each other and to variable rates of disease progression. Despite the fact that formal proof of such a link is still lacking–since blood and pancreas samples were collected from distinct individuals–this study provides the first example of a pathophysiological basis for disease heterogeneity that may have direct relevance to stratification for therapeutic trials [From a clinical standpoint, it is obvious that type 1 diabetes is a heterogeneous disease. For example, it can manifest very aggressively in a 3-year-old child who has rapid symptomatic onset, type-1-diabetes-associated autoantibodies, exceedingly low C-peptide levels, disease-predisposing HLA genes and an associated inflammatory process such as coeliac disease. But type 1 diabetes can also occur in a 40-year-old individual with limited HLA risk, detectable C-peptide, a mild, indolent onset and no other autoimmune diseases. With insulin replacement by injection being the only approved therapy for type 1 diabetes, there has seemed little need to identify disease heterogeneity from a clinical–pathological perspective . Howeverphocytes . Thus, tc trials .INS DNA) in the circulation. This analysis involves quantitative PCR amplification of INS DNA, with epigenetic marks that identify the DNA source as cells that actively transcribe insulin. Since the only significant source of non-methylated INS DNA in the body is the beta cell, the level of unmethylated INS DNA in the circulation reflects the active rate of beta cell death [INS DNA’ assay has yet to be fully validated [Another important gap in type 1 diabetes research remains the lack of biomarkers that reflect an authentic signature of beta cell death and/or stress. Resolving this issue may also improve our ability to optimally time immunomodulatory treatments and other forms of interventions in type 1 diabetes. Several investigators have recently developed methods for assessing beta cell death in vivo by measuring the relative amount of beta cell-derived insulin encoding DNA  T cells and concomitant increase in CD4+CD45R0−CD62L+ naive T cells. These changes reverted after treatment cessation, supporting a direct drug effect. Importantly, the study also revealed that in placebo-treated individuals there was an increase in the number of circulating CM CD4+ T cells and a decrease in CD4-naive/CM T cell ratio, significantly associated with a subsequent rise in the rate of C-peptide decline. Abatacept treatment significantly altered this association. Mechanistically, this implies that the effect of co-stimulation blockade on naive/CM status of CD4+ T cells is linked to its therapeutic effect [www.trialnet.org/our-research/prevention-studies)  in individuals newly diagnosed with type 1 diabetes (TN09). Two years of continuous treatment was associated with a slower decline of beta cell function and the beneficial effect was sustained for at least 1 year after therapy cessation . To bettc effect . These d+ B cells. Those receiving active treatment showed reduced decline in C-peptide secretion in the year following introduction of therapy and better glycaemic control with reduced requirements for exogenous insulin [Type 1 diabetes is typically described as an immune-mediated disease in which T cells drive the specific destruction of pancreatic insulin-producing beta cells. Recent data arising from TrialNet ancillary studies indicate that this T cell-centric view may need broadening. The role of B lymphocytes in type 1 diabetes is poorly understood despite autoantibodies being known robust predictive biomarkers. From results of studies making use of TrialNet samples, it is now becoming apparent that a breach in B lymphocyte tolerance is also a major contributor to type 1 diabetes. The trigger for these findings is the success of TN05, a clinical trial in individuals with new-onset type 1 diabetes, using monoclonal anti-CD20 antibody therapy (rituximab) to deplete CD20 insulin . Disappo insulin . Meffre  insulin , investiIn accordance with this view, Cambier and colleagues demonstrated that high-affinity insulin-binding B cells are present in healthy individuals exclusively in the anergic naive compartment, while these insulin-binding B cells lose their anergic phenotype in individuals who are at risk of diabetes (TN01 participants) or who have new-onset (< 1 year) type 1 diabetes . These fA further, often neglected, component of the immune responses in individuals with type 1 diabetes has been that of innate immune pathways. A careful examination of the peripheral blood of relatives of individuals with type 1 diabetes (TN01) and of individuals with established disease has revealed a reduced number of circulating neutrophils. Indeed, the higher the risk of progression to diabetes, the more pronounced the reduction. This observation was possible through direct access to fresh blood from donors participating in TN01 using the Living Biobank approach. The observed reduction in circulating neutrophils is accompanied by the novel finding that neutrophils infiltrate the pancreas of individuals with type 1 diabetes, studied as cadaveric organ donors, suggesting that a disturbance in peripheral neutrophil regulation arises in parallel with neutrophil pancreas marginalisation . ReducedHLA-DR3 and/or -DR4 haplotypes, respectively), the signatures of these healthy cohorts were also distinct from one another [Additional evidence pointing to the presence of innate immune mechanisms during the early stage of the disease (stage 1) comes from Hessner’s group . They us another . Notably another . These rThe studies outlined above clearly provide important breakthroughs but thus far ancillary studies have been predominantly single-centre, focused on one hypothesis/question and generated from samples obtained from a few selected donors. In the era of team science, ‘big data’ and systems biology approaches allied with high-throughput technology, TrialNet will best move forwards by fostering models for mechanistic studies that are bigger in scope and represent and integrate different investigators and the myriad of data opportunities. One approach that is gaining considerable attraction and will become a future focus is to assemble these technologies to address fundamentally important questions relevant to the TrialNet mission, such as the discovery of biomarkers and mechanisms of progression through the disease stages. TrialNet will be able to play a major role in coordinating external collaborations and data integration to achieve this goal but success will also depend upon engagement with the relevant experts. The revised model envisages mechanistic studies that will be considered an integral, core part of TrialNet activity and no longer ‘ancillary’.Overall, our perspective on the achievements of the TrialNet model of conducting wide-ranging studies ancillary to its trials is that it has pushed the field forwards in multiple directions, and has begun to reveal biomarkers and deliver the mechanistic understanding required to combat this complex and heterogeneous disease. We anticipate that the findings expected to emerge soon from multi-dimensional analyses addressing key transition points in the disease will build on this platform, maximising the opportunities provided by this precious resource.ESM Downloadable slideset(PPTX 586 kb)


Neurofibromatosis type 1 (NF1) is a rare multisystem genetic disorder. During the course of the disease it can be rarely complicated with pulmonary hypertension (PH) which confers a dismal prognosis.We describe the case of a 57-year-old female patient with NF1 complicated by severe precapillary PH despite dual disease-specific oral combination therapy. The patient was treated with initial atrial septostomy followed by administration of high-dose subcutaneous treprostinil with a favorable medium-term clinical and hemodynamic response.PH secondary to NF1 may be successfully treated with the combination of atrial septostomy and PH targeted therapy in selected patients. Neurofibromatosis type 1 (NF1) is a genetic disease with a prevalence of 1:3500 in the general population, transmitted with the autosomal dominant inheritance pattern and with full penetrance characterized by prominent skin features , optical tumors and other central nervous system tumors, certain bony abnormalities, some learning deficits and an increased risk of certain non-nervous system cancers .A rare still morbid complication of NF1 is pulmonary hypertension (PH) which confers a dismal prognosis overall. To the best of our knowledge this is the first documented report of successful treatment of PH secondary to NF1 with atrial septostomy followed by escalation of PH targeted treatment.A 57-year-old female patient with a history of NF1 and PH initially diagnosed 3 years ago, already on conventional treatment with supplemental oxygen and anticoagulation, as well as disease-specific double oral combination therapy  was admitted to the hospital because of worsening dyspnea on mild exertion and a presyncopal episode.Her past medical history was notable for surgically repaired pyloric stenosis and 2 abortions during the third trimester of gestation due to intrauterine fetal death, followed by a successful pregnancy. The patient had already undergone an extensive workup which excluded known causes of PH. Lung ventilation/perfusion scan was not suggestive for chronic thromboembolic disease and high-resolution CT of the lungs was negative for interstitial lung disease. Blood tests excluded other causes of pulmonary hypertension.Considering the patient’s clinical deterioration, the decision was made to proceed immediately with atrial septostomy, due to inherent difficulties in the reimbursement of prostanoids in our hospital at that time. The patient had an uneventful procedure with graded balloon dilation of the interatrial septum with gradually increasing inflated balloons diameter of 6, 8 and 10 mm. A moderate decrease in right atrial pressure  and NT-proBNP at 2 months, access to prostanoids was eventually gained and the patient was started on subcutaneous treprostinil with gradual increase in the administered dose up to 100 ng/kg/min in a time period of 7 months.The patient during a follow-up period of 2 years demonstrated gradual improvement and at present remains in World Health Organization class 2 with significant hemodynamic improvement Table . A recenA few cases suggesting an association of NF1 gene mutation and precapillary PH have been published , 4. PlexHerein, we report a case of a patient with NF1 and severe precapillary PH, without parenchymal lung disease, yet with prominent pulmonary vascular involvement, treated with atrial septostomy, followed by the administration of subcutaneous treprostinil. The medium-term clinical response after 2 years was impressive with improvement in her functional class, 6MWT distance, hemodynamic parameters and NT-proBNP. To the best of our knowledge this is the first published case of PH secondary to neurofibromatosis treated successfully with the combination of atrial septostomy and aggressive PH targeted therapy.The favorable clinical response of our patient to the atrial septostomy and the further gradual, but more pronounced, improvement with the chronic administration of subcutaneous treprostinil suggests that pulmonary vasculopathy is the underlying mechanism of PH in these patients. The creation of a shunt that decreases the preload of the right ventricle and increases that of the left ventricle with concomitant increase in the cardiac output makes it easier to initiate and uptitrate the prostanoid infusion. The long-term effect of the persistence of the shunt in our case, following the decrease in the right sided pressures on chronic treprostinil therapy, is not known; whether the reversal of the shunt during exercise by decreasing the load on the right ventricle will continue to be beneficial, despite the arterial oxygen desaturation, is not clear .There are very few cases in the literature with the utilization of PAH-targeted therapies in these patients –9. Our pThis report demonstrates the successful management of a patient with PH secondary to NF1 with atrial septostomy in conjunction with PAH targeted therapy. Looking ahead, national and international prospective registries will shed light on the pathophysiology, and especially optimal therapy and prognosis of neurofibromatosis-associated PH especially in the modern era of targeted PAH treatment.


Drosophila trained to avoid deuterated odorants could respond to a molecule bearing a nitrile group, which shares the vibrational stretch frequency with the CD bond. Here, we reproduce and extend this finding by showing analogous olfactory responses of Drosophila to the chemically vastly different functional groups, thiols and boranes, that nevertheless possess a common vibration at 2600 cm−1. Furthermore, we show that Drosophila do not respond to a cyanohydrin structure that renders nitrile groups invisible to IR spectroscopy. We argue that the response of Drosophila to these odorants which parallels their perception in humans, supports the hypothesis that odor character is encoded in odorant molecular vibrations, not in the specific shape-based activation pattern of receptors.A remarkable feature of olfaction, and perhaps the hardest one to explain by shape-based molecular recognition, is the ability to detect the presence of functional groups in odorants, irrespective of molecular context. We previously showed that  Drosophila. We show for the first time that Drosophila respond to vibrational frequencies characterizing functional groups. Boranes (-BH) and thiols (-SH) vibrate at the same frequency and flies respond to boranes as if they were thiols strongly suggesting that functional groups of similar enough vibrational frequencies have similar odor character in Drosophila. In accord with theoretical predictions, although flies readily detect nitriles, they fail to respond to nitrile groups in molecular configurations that render them undetectable to infrared (IR) spectroscopy. We conclude that the behavioral response of Drosophila to these odorant functional groups is consistent with the notion that their character is encoded in their molecular vibrations.To gain mechanistic insights we address predictions of vibrational olfaction in A currently unresolved and enduringly controversial  issue inDrosophila  is also mutant in a Ionotropic Receptor coreceptor  per experimental condition were used in all experiments. Animals (50–70) of the first experimental condition  chose for 90 s between the converging odorants or odorant and air, as specified, without any prior training. At the end of the 90 s, the flies were trapped in the arms (each arm is 10.5 cm in length and 1.5 cm in diameter), counted and performance indexes (PIs) were calculated by subtracting the number of flies in the control (unscented) arm from those in the opposite arm and dividing by the total. Animals of the second experimental condition were placed in the electric grid-lined training arm and were presented with the training odorant (at 550 ml/min) for 1 min while simultaneously receiving 12 electric foot shocks of 90 V DC of 1.2 s each. Subsequently, the flies were transferred to the choice point at the convergence of the two testing arms and allowed to choose for 90 s between the testing odorant and air or two converging odorants as specified. The 50–70 flies of the third experimental condition were trained by footshocks in the presence of the complementary odorant and tested likewise. For example, flies trained either with β-mercaptoethanol or decaborane were tested for their level of avoidance of β-mercaptoethanol versus air. Avoidances of trained animals were compared to those of naïve flies. Moreover, in the complementary experiment, flies trained with β-mercaptoethanol or decaborane were tested for avoidance (or attraction) of decaborane versus air and compared to the performance of naïve animals. Each experimental condition represented in the bar graphs of the figures is constructed by at least seven repetitions each containing 50–70 animals. The total number of animals used to construct each bar is shown in the relevant figure legend.Because of the potency of β-mercaptoethanol and boranes, we tested whether odors linger on the maze and delivery tubes by testing fly behavior with used maze arms and tubing without odorants. Flies distributed equally in previously used and new arms and tubing indicating that neither odor lingers on the equipment to bias the results.4-isotopologue (CDN Isotopes) were diluted with water at 1%. β-Mercaptoethanol was diluted at 0.01%, 0.1%, and 25% in water for the response curve of wild-type and anosmic flies. Because decaborane (Carbosynth) is a potent odorant, potentially toxic at higher concentrations, all assays were carried with the use of a protective mask by the experimenter and with frequent pauses between trials to aerate the room and not to overexpose the flies subject to later experiments. Typical experiments used β-mercaptoethanol at 1% in water unless otherwise specified, while decaborane was used as a solid at 50 mg. Benzaldehyde (Sigma) was used at 10% in IPM, and hexanol (Fluka) was used at 10% in IPM. 2-Hydroxybutyronitrile (Sigma) and 3-hydroxybutyronitrile (Sigma) were diluted in IPM at 5%. All odorants were diluted up to 1 ml total volume.1-Decanol (Sigma) and d21-decanol (CDN Isotopes) were diluted at 5% in isopropyl myristate  in a total of 1 ml. Citronellyl nitrile (Takasago) and citronellal (Fluka) were diluted at 15% and 10%, respectively, in IPM. H-β-mercaptoethanol (Sigma) and its DResults were analyzed parametrically using planned comparisons (least squares method) and the statistical program JMP (SAS).www.scm.com) and Spartan 14 (www.wavefun.com) at either PBE-DZP or B3LYP-6-311 level of theory.Conformations and vibrational spectra of molecules were calculated with Amsterdam Density Functional  except for the presence of the C-D and C-H vibrations at 2150 and 2900 cm-CD/-C≡N C and posTo avoid potential differences in volatility biasing the results, we used the footshock-mediated augmentation of avoidance assay . In thisDrosophila at 1% dilution  and the neutral odorant hexanol , for training and tested subsequent avoidance toward the thiol and borane. Flies shocked in the presence of β-mercaptoethanol showed augmentation of their naive thiol avoidance . This confirms the notion that wild-type flies use OR-type receptors to respond to β-mercaptoethanol and decaborane.Alternatively, once shocked in the presence of any odor, flies could simply avoid any subsequent odor presented to them  and escape toward the unscented maze arm. To address this possibility, we used the unrelated aversive odorant benzaldehyde  and hearing . Unfortunately, the stimulus flexibility in olfaction is not as continuous or easily accessible as in hearing and vision and it will be some time before we understand this. The 2- and 3-hydroxybutyronitrile experiments go some way in that direction and will serve as a benchmark for more accurate calculations of biological IETS line intensities. In fact, our collective results are likely to serve as useful constraints when developing models of biological IETS selection rules.Is there a threshold for vibrational frequency differences beyond which divergence or convergence of physiologic and behavioral readouts reveal differences in odor salience? The resolution of the vibrational component of erations , a therm2, N2) are odorless, as are molecules with very small partial charges such as CO. It appears that spectroscopic selection rules for the biological IETS suggested by our experiments resemble more closely those of IR spectroscopy than, say, those of Raman spectroscopy, where vibrational modes devoid of transition dipole are nevertheless detected by polarizability. Exact selection rules for IETS are the object of intense study (When an inelastic electron tunneling mechanism for vibrational olfaction was proposed twenty years ago, it clarified the features that would be required in order for a molecule to be detected and therefore have an odor . Insofarse study , but it se study  and compDrosophila respond to boranes as if they were thiols possibly because their vibration differences are below resolution for the olfactory receptors engaged. Although they do not prove it, our data suggest that boranes may smell sulfuraceous to flies as has been reported for humans (Drosophila to -SH and -BH may also underlie the not obvious reasons why humans perceive them both as sulfuraceous. However, the G protein-coupled serpentine human olfactory receptors are quite distinct from their channel-like dimeric counterparts in Drosophila and other insects (Drosophila antennal lobes on -SH and -BH exposure will provide a physiologic readout to address this hypothesis independently.Our evidence indicates that r humans . It is p insects . If flieDrosophila (In the combinatorial shape theory , if by sosophila  shows reosophila . It is posophila .in vivo studies on different insect species, these experiments strongly suggest that vibrational sensing is a critical component of insect olfaction.Therefore, we posit that collectively, our results provide evidence that odor character is encoded in the odorant itself, at least for those compounds tested. Together with previous