For the attractive plasmonic structure consisting of metal nanoparticles (NPs) on a mirror, the coexistence of near-field NP-NP and NP-mirror couplings is numerically studied at normal incidence. By mapping their 3D surface charge distributions directly, we have demonstrated two different kinds of mirror-induced bonding dipole plasmon modes and confirmed the bonding hybridizations of the mirror and the NP-dimer which may offer a much stronger near-field enhancement than that of the isolated NP dimers over a broad wavelength range. Further, it is revealed that the huge near-field enhancement of these two modes exhibit different dependence on the NP-NP and NP-mirror hot spots, while both of their near-field resonance wavelengths can be tuned to the blue exponentially by increasing the NP-NP gaps or the NP-mirror separation. Our results here benifit significantly the fundamental understanding and practical applications of metallic NPs on a mirror in plasmonics. Near-field enhancement is one of the most remarkable phenomena associated with nobel metals in the visible region. When light interacts with metals, collective oscillations of the conduction electrons can be excited at the metal surface, which are known as surface plasmons (SPs)234578101213One of the most geometrically simple but plasmonically important structures is the dimer, consisting of two metal nanoparticles (NPs) separated by a nanoscale gap151720Alternatively, one closely related system composed of metal NPs positioned over a thin metal film has recently received an increasing amount of attention222324262729303233343527283337So far, beside the thickness of the dielectric spacer, the NPOM system is also found to be remarkly sensitive to various other factors, including the angle of incidence, the surrounding medium, the NP size and material27394142432274546474849505152In this paper, the coexistence of near-field NP-NP and NP-mirror couplings at normal incidence is numerically considered using a NP-dimer on a mirror (NPDOM) model. The plasmon hybridizations are investigated by varying the gap width of the NP dimer and the thickness of the dielectric spacer. Although the incident angle can be optimized to achieve a maximum near-field enhancement27224R = 60 nm) located randomly above a metal mirror, separated by a thin Al2O3 dielectric spacer, as is schematically depicted in 2O3 layer can be prepared by atomic layer deposition (ALD) of oxides directly onto the mirror2724442O3 is 1.62 while the metal dielectric functions ε(w) are modeled by a Lorentz-Drude dispersion model fitting the experimental data in Palik’s book3D electrodynamic calculations are performed using frequency-domain finite element method (FEM) in COMSOL Multiphysics software package . Typically, the studied structure consists of Au NPs E0| = 1 V/m is the modulus of incident field and E =  is the local electric field. It is known that the enhancement factor (EF) of SERS is approximately proportional to the forth power of the local electric field intensity (|E|4/|E0|4)62where ison see . As is kρr is the largest at the metal surface S and decreases exponentially when spreading into the metal:To confirm the plasmon mode, 3D surface charge distributions are calculated by considering the skin effect and applying Gauss’ law during FEM calculations. Based on the skin effect, we assume that the induced charge density ρ is the charge density at the surface, r is the depth from the surface and δ is the skin depth6667Q = 0 within the metal NP is thus:where R is the radius of the nanoparticle.where On the other hand, the Gauss’ law in the integral form is:S, ε0 is the permittivity of vacuum,n =  is the outward normal vector of the metal surface and E =  is the local electric field. The surface charge density can then be deduced by:where nx ∙ Ex + ny ∙ Ey + nz ∙ Ez) is used to indicate the surface charge density ρ. The use of this mapping approach makes it possible for us to acquire directly 3D surface charge distributions, which is ideally suited to recognize the geometry (or order) of complicated and hybridized plasmon modesIn the process of FEM calculations and plasmon mapping,  and the ones indicated by down triangle symbols belongs to another plasmon mode (II), which will be demonstrated in g or t increases, both modes exhibit a gradual blueshift and the near-field enhancement sustained by mode II undergoes a modest decrease. For mode I, the peak near-field enhancement decreases rapidly as g increases but stays nearly steady when t changes. These similarities and differences in response to changes of g and t factors are further analyzed in the following parts.The coexistence of near-field NP-NP and NP-mirror couplings present in the NPDOM model is investigated by varying the dimer gap g = 2 nm. The peak intensity 6 occurs at λ = 705 nm, where the plasmon mode is confirmed to be the BDP mode , we find surprisingly that not only is the mirror-induced peak 7) much stronger than that of the isolated dimer, but also, over a broad wavelength range, the near-field enhancement of the NPDOM configuration is stronger than that of the corresponding isolated dimer. In other words, the near-field enhancement of a dimer can be further enhanced by adding a mirror and the NPDOM configuration offers an approach to raise the upper limit of the near-field enhancement based on conventional dimer systems. This additional enhancement mechanism can significantly benefit applications like single molecule detection28As a blank control, the NPDOM structures with mirror removed, i.e., isolated dimers have also been studied. To be specific, the dashed black curve in BDP mode 18. CompaE/E0|4 . g = 2 nm, t = 2 nm; (b) g = 40 nm, t = 2 nm; (c) g = 2 nm, t = 20 nm from left to right, where the maximum EF = 1.3 × 1011, 1.0 × 109, 1.3 × 1010 and 7, 8.8 × 104, 1.8 × 107 respectively. It is easy to see that there are two kinds of hot-spots in g increases, both hot-spots degenerate rapidly  is shown in  rapidly ; when t enerates . The plag = 2 nm, t = 2 nm, mode I and II take place at λ = 1020 and 720 nm respectively (λ = 705 nm). This is consistent with the result predicted by the plasmon hybridization modelAs a conclusion, the extreme near-field enhancement induced by the mirror can now be qualitatively attributed to the bonding hybridizations of the propagating surface plasmon modes on the mirror surface and the localized surface plasmon mode of the NP-dimer, which is also found in the structure for SHINERS52ectively , which ag and the spacer thickness t, respectively. It is clear that for mode I, the responses on near-field enhancement to g and t changes are quite different. As g continues to increase, the peak t increases, it stays nearly steady at a relatively high intensity (7). Thus the total near-field enhancement of MBDP mode I is mainly determined by the NP-NP hot-spot while being affected little by the changes in the spacer thickness. Interestingly, noticing the blueshift of the resonance .


Recent trial results show that an interactive short message service (SMS) text message intervention, Texting to Reduce Alcohol Consumption (TRAC), is effective in reducing heavy drinking in non-treatment-seeking young adults, but may not be optimized.To assess the usability of the TRAC intervention among young adults in an effort to optimize future intervention design.We conducted five focus groups with 18 young adults, aged 18-25 years, who had a history of heavy drinking and had been randomized to 12 weeks of the TRAC intervention as part of a clinical trial. A trained moderator followed a semistructured interview guide. Focus groups were audiotaped, transcribed, and analyzed to identify themes.We identified four themes regarding user experiences with the TRAC intervention: (1) ease of use, (2) comfort and confidentiality, (3) increased awareness of drinking behavior, and (4) accountability for drinking behavior. Participants’ comments supported the existing features of the TRAC intervention, as well as the addition of other features to increase personalization and continuing engagement with the intervention.Young adults perceived the TRAC intervention as a useful way to help them reduce heavy drinking on weekends. Components that promote ease of use, ensure confidentiality, increase awareness of alcohol consumption, and increase accountability were seen as important. Heavy episodic drinking, typically defined as consuming four or more drinks for women and five or more drinks for men over a drinking occasion, is the most common pattern of excessive alcohol consumption in the United States . Young aComputerized interventions may allow for economies of scale and standardization of procedures to ensure replicability that is less feasible with in-person interventions. As well, mobile communication technology allows computerized interventions to provide support over time in an individual’s natural environment, and to adapt feedback based on changing personal circumstances . This maThe Texting to Reduce Alcohol Consumption (TRAC) intervention was iteratively developed from a systematic literature review of alcohol prevention interventions and short message service (SMS) text message interventions for health behaviors, and pilot studies -13. SpecIn this study, we address the need to continually improve the intervention through an iterative process of testing and evaluation, by collecting feedback from young adult drinkers who were exposed to the TRAC intervention. This iterative process follows the guiding principles of user-centered design  as well The specific aim of this study was to understand young adults’ qualitative experiences using the TRAC intervention and explore ways to improve its usability. Five focus groups, each consisting of 3-5 people, were conducted. We probed user reactions to the TRAC intervention in general as well as specific TRAC intervention components, including drinking assessments, goal-setting prompts, and feedback messages. Finally, we gauged participant opinions about candidate additions to the TRAC intervention and probed for any other suggested changes. All participants provided written informed consent. Study procedures were approved by the Institutional Review Board at the University of Pittsburgh. None of the findings reported in this manuscript have been described in prior publications.We recruited focus group participants from those who met eligibility criteria for the TRAC trial . TRAC participants were identified in four emergency departments (EDs) in Pittsburgh, Pennsylvania. TRAC trial inclusion criteria were as follows: 18-25 years of age, having screened positive for past hazardous alcohol consumption—Alcohol Use Disorders Identification Test Consumption (AUDIT-C) score >3 for women and >4 for men —and not The overall goal of the TRAC intervention is to help young adults reduce their alcohol consumption. TRAC targets heavy episodic drinking, given its association with alcohol-related harms , and in Upon enrollment to the TRAC intervention, participants received a series of welcome messages instructing them on what to expect over the 12 weeks and how to quit the program. The flow of text message branching logic can be seen in Each Sunday at 12pm, participants were asked to report the most alcoholic drinks they had consumed on any single occasion between Thursday and Sunday. If they reported that they did not drink , they received a message congratulating them for not drinking. If they reported a value greater than zero, but less than the heavy drinking threshold, they received a message acknowledging their report of drinking and another message with general alcohol education. If they reported drinking above the heavy drinking threshold, they received a message expressing concern and another message prompting them to reconsider their drinking behavior. All feedback messages were modeled on existing language used in brief interventions for alcohol use and in the spirit of motivational interviewing.We chose to conduct focus groups for several reasons. First, focus groups are a fast and efficient method for obtaining data from multiple participants . Second,Before conducting any focus groups, a standardized, semistructured qualitative guide was developed to increase consistency across interview sessions. We pilot-tested the interview guide among 3 young adult volunteers—2 female and 1 male— not previously exposed to the TRAC intervention and made refinements based on their feedback. The guide probed user reactions to the TRAC intervention in general as well as to the three main features of the TRAC intervention: drinking plan and consumption queries, goal-setting prompts, and feedback messages. The interview guide also probed opinions about possible additions to the TRAC intervention. Specifically, we were interested in understanding how young adults felt about incorporating text messaging during drinking episodes because of prior trial findings that a significant proportion of young adults who set drinking limit goals still did not meet them, and our belief that messages delivered more proximal to actual drinking events could enhance potency. We also probed opinions about a Web-based dashboard as an adjunct to text messaging given prior expressed desire among young adult participants for an easier way to track their progress over time.Each focus group was scheduled to comprise small groups—3-4 individuals—to ensure participant interaction and comfort . Each foBefore each focus group began, participants provided written informed consent. The consent highlighted the potentially sensitive nature of the discussions and urged participants to not share discussion content outside the group. As well, at the beginning of each focus group, the moderator stressed the confidential nature of the discussion to the participants. Participants were told that the focus group discussion would be audiotaped, would be used for research purposes only, and would not be accessible to anyone outside the research team. To ensure confidentiality, participants were told not to use their full names. It was stressed that the opinions of the participants were important and that there were no right or wrong answers.The focus groups started with a warm-up where participants were reminded of the TRAC intervention format. Probes were used to encourage clarification and evoke greater detail from participants’ narratives. A research assistant took detailed field notes during the focus groups and the groups were audiotaped and transcribed by personnel at the Qualitative Data Analysis Program at the University Center for Social and Urban Research at the University of Pittsburgh. At the conclusion of each focus group, we debriefed all participants on the preliminary results of the randomized trial and asked for any closing remarks or questions. When all participants’ questions had been exhaustively answered, the participants were thanked and provided with a debit card worth US $30.We chose a thematic content analysis approach and used the qualitative research software package, ATLAS.ti 5.0 (Scientific Software Development). A preliminary codebook was created based on close readings of the first transcripts, incorporating explicit domains from interview guides (deductive themes) as well as recurrent unanticipated themes that were emergent across transcripts (inductive themes). Provisional definitions were given to each code and two analysts applied the codes to each transcript. The coded transcripts were merged for comparison and code definitions were revised based on an examination of coding disagreement. Coded text was further reviewed through an iterative process, resulting in refined themes. We did not record which individual participant said which statement or count how many participants agreed or disagreed with a given statement. In presenting the results, we chose participant quotes that represented both the majority sentiments within each theme as well as any quote that offered a contrasting opinion within that theme.We conducted five focus groups with 18 participants—12 females (67%) and 6 males (33%). Overall, the sample was 44% (8/18) non-Hispanic black and 50% (9/18) non-college educated; 28% (5/18) were under the US legal age of 21 years to purchase or consume alcohol. There was a high rate of cannabis use  and daily tobacco use  among our cohort. Other baseline characteristics of focus group participants can be seen in Analysis revealed the following four major themes regarding experience with the TRAC intervention: (1) ease of use, (2) comfort and confidentiality, (3) increased awareness of drinking behavior, and (4) accountability for drinking behavior.Participants expressed that text messaging was an ideal electronic modality to deliver drinking support. They naturally contrasted text messaging with other electronic modalities. For example, one participant explained, “I remember thinking it was a great method because it’s—you can respond to it very quickly, it’s not like you have to log into a computer.” Another said, “It’s convenient, especially for us for our generation, I think more so than being on the computer, you know, checking our emails.” Another described, “It’s way better than the app because it hits you. You know, it’s a text message right straight to your phone.” One participant did however comment that text messaging is easy to use but may not be the most impactful modality given that it is limited to text and 160 characters: “Even though it is very accessible, I don’t know if it’s the most, you know, high impact way to reach somebody.”Overall, participants seemed to feel comfortable texting about their drinking behaviors. In fact, they described how the text messaging modality was preferred to in-person disclosure of drinking, with a resultant feeling of not being judged. For example, one participant said, “I thought it was more comfortable just because when you’re in front of somebody and you’re like, ‘Oh, I had 20 drinks.’ Some people are kind of like, ‘20 drinks?! That’s a lot.’” Regarding confidentiality, one participant said, “I felt like nobody was going to see it. I know someone was going to see it but it was like, it was on [my] phone, it’s gone, I don’t have to worry about it again, you know? And if I don’t want anyone to look at my phone and see that, then I just delete it.” Some participants did express some concerns about confidentiality, but that it became less of a concern as the intervention continued. One participant summed up his evolving feelings this way: “I thought it was kind of funny at first just like I’m texting this nobody, I didn’t know if it was real or something...but it just became routine...and then I was like, ‘You know what? I’m being honest now.’”Participants indicated that they were not very aware of the extent of their drinking prior to starting the TRAC intervention. For example, one participant said, “I really went into it thinking like, ‘I’m not really going to need this because I don’t drink too much.’” Many recalled that the repetitive nature of the week-to-week drinking assessments helped them develop a habit of paying attention to how much they drank. For example, one participant said, “The consistency keeps reminding you...then you started to think, ‘Well, am I drinking this much this weekend?’” Several participants commented on how it is difficult to estimate drinking quantity in the real world. For example, one participant said, “You know, I might have had four red solo cup glasses, but you know there could have been two shots in there, could have been three shots in there.”Participants commented that the feedback messages on Sunday, after reporting weekend drinking quantity, made them more aware of their drinking, but individuals seemed to have differing opinions on which types of feedback messages were preferred. Some participants liked the statistics on the dangers of heavy drinking: “Any time I get statistics, they obviously like stick in people’s heads with cigarette smoking, drinking, STD, like anything. So, I love the statistics.” Others felt that the messages were not telling them anything they did not already know. For example, one said, “I remember thinking, ‘[pfft] okay, whatever.’ And even with the [protective behavioral] strategies, I think we know what we’re supposed to be doing.”Many discussed how the TRAC intervention helped them become aware of the drinking habits of their peers. For example, one participant commented, “When I go to parties or I see people drinking, I’m just like, ‘Do you know how many drinks you’re consuming?’ Like I count people’s drinks for them...and I’m like, ‘Why are you doing that to yourself?’” Another participant commented about how the intervention influenced their peer group: “It helped my friends too because they’d see me doing [TRAC] and they’d be like, ‘Oh, maybe we shouldn’t have like 12 shots before we go out.’”Overall, participants seemed to feel that the TRAC intervention made them feel more accountable for their drinking choices. One participant illustrated this point in saying, “The fact that it’s constantly in your face and you get a chance to see how much you drink and how often it is, makes you—makes your mind wonder. And it helps you to kind of be able to control it [your drinking], if you want to.” Participants felt that the one feature that seemed to bring about the feeling of accountability was the goal-commitment query sent each Thursday, commenting that it made them be more mindful when they were out drinking. For example, one participant said, “...I thought about it [the goal] when I don’t think I normally would have. So, even if I didn’t reach it [low-drinking-quantity goal], I was at least thinking about the amount I was drinking, which was a positive.” Another TRAC intervention feature that seemed to bring about the feeling of accountability was the alcohol consumption recall query sent each Sunday. One participant recalled, “I’d wake up, you know, ridiculously hungover day after day and I’d start to see these messages. I’m like, ‘Alright, well I should kind of like tone it back.’”Some participants expressed some discomfort with the feeling of being held accountable. For example, one participant said, “It’s like your mom telling you, ‘What the heck are you doing?’ but in a text. But it made you think about it, and sometimes, yeah, it was uncomfortable, but if you’re honest about it, then it’s gonna help you recognize you have a problem.” Some mentioned that the feeling of being accountable for their drinking lasted beyond the intervention period. For example, “I still count. Like I still—I don’t have a calendar but I keep track, which I never did because I never thought about it.”Discussion revealed areas for improvement. For example, some participants reported intervention fatigue; one participant stated, “Sometimes I would answer honestly, but if I didn’t really feel like all the texting, I would just be like, ‘I followed the goal, followed through with my goal’ just so I wouldn’t have to keep going.” However, at least one participant suggested providing the option of continuing the program for longer than 12 weeks, if desired.Participants had noteworthy suggestions for reducing intervention fatigue and improving engagement with the TRAC intervention. In general, participants supported the use of more personalization by sending messages using their first names. Participants also suggested incorporating more tailored feedback. For example, one participant said, “Maybe if you could identify the factor or reason why they were trying to quit, so like saving money and you factor that into the messages.” Regarding tailoring of the goal-commitment query, participants suggested using drinking quantity thresholds higher than the four or five drinks per occasion recommended by the National Institute on Alcohol Abuse and Alcoholism (NIAAA). One participant commented that the recommended maximum drinking quantities during Thursday goal-setting prompts were “pretty much nothing“—that is, they were too low to experience an effect from drinking.When we probed the possibility of incorporating text messages to support low-quantity drinking goals during drinking episodes, participants were ambivalent. For example, one participant stated, “I mean everybody is on their phone when they’re drinking, but I think that some other people might get offended or might get annoyed, irritated. But I think for me, that would be beneficial, just as kind of a reminder in the back of your head, ‘Hey, just reminding you, be mindful of how much you’re drinking.’” A participant suggested that one-way “push” messages, which provided a reminder of the goal to limit drinking, could help to optimize the effect of goal setting while minimizing participant burden.When we probed the possibility of incorporating a Web-based dashboard where their text message data could be stored and graphically displayed, participants were generally supportive. One suggested addition was the ability to compare progress to others. For example, one participant said, “I like to see things quantified and it would actually be interesting, like same age, peers. This is their trend.” It was suggested that the dashboard also incorporate some form of gamification. For example, one participant said, “I could see a lot of value in some sort of a reward scheme.” Additionally, it was suggested that there be a social network component. One participant illustrated how this would be helpful: “If you just had maybe like a website that, you know, just had...other people’s stories and experiences. Like I don’t know how many people would be like, ‘Oh my gosh, my weekend was terrible, anybody else feel the same way?’”This focus group study summarizes the opinions of non-treatment-seeking young adults with past hazardous alcohol consumption who were exposed to an interactive 12-week text message intervention focused on reducing weekend heavy drinking episodes. Participants recalled positive experiences with the TRAC intervention, citing ease of use and immediacy in the natural context of life as major facilitators in reducing alcohol use. Participants recounted how the intervention made them more aware about their own drinking patterns and felt it prompted accountability to drink more moderately. Although each intervention piece, namely the weekend drinking plan query, the goal-commitment prompt, and the Sunday alcohol consumption check-in, seemed to play unique roles, the intervention pieces also seemed to function together synergistically. Moreover, the repetition from week to week seemed to help individuals build alliance with the intervention over time and support reduction in drinking behavior.Participant comments regarding the ease of use is not surprising given that text messaging is ubiquitous on mobile phones, a common mode of communication among young adult drinkers, and combines immediacy with the ability to reply asynchronously . Particiawareness of alcohol consumption occurs as a result of other intervention components  or the components acting together as a whole.The TRAC intervention seemed to help individuals learn how to track the amount of alcohol they consumed. Although the act of assisting self-monitoring of drinking through Sunday alcohol consumption check-ins may be an important mechanism of action, it is clearly not the only necessary element. For example, in our trial findings, the assessment-only control group, which received Sunday alcohol consumption check-ins but did not receive feedback, showed no reductions in alcohol consumption at follow-ups . One poslearned about their drinking behavior over the course of the intervention. It also seemed to stem from their growing awareness of the hazardous drinking patterns of their peer groups. We speculate that these perceived discrepancies motivated many to change their drinking over the course of intervention exposure and fits with one of the main theoretical underpinnings of the TRAC intervention, the theory of planned behavior, which stresses the importance of goal setting and perceived norms regarding alcohol use on alcohol consumption [The TRAC intervention elicited feelings of accountability in some individuals, which seemed to stem from developing a discrepancy between their perception of their drinking and what they had sumption . We alsoThere were a number of design improvements that participants suggested, including increasing personalization and tailoring, such as adding the first name to texts and providing the option to continue the intervention for longer periods. Some participants seemed to desire more adaptive goal-commitment prompts. Specifically, some felt that limiting themselves to four or five drinks was too low of a threshold to commit to, especially when they are used to drinking 10 or more drinks on a weekend evening. This notion was reflected in our trial, where we found that young adults were not willing to commit to a drinking limit goal around half the time. It also raises an interesting dilemma for operationalizing design, where we would essentially ask young adults to commit to drinking less than what they are used to but higher than four or five drinks, the current upper limit of what the NIAAA considers a moderate level of alcohol use. Participants were ambivalent about receiving support messages during weekend drinking occasions, and stressed that, if they are used, they should be one way  to minimize burden and should focus on reminding individuals about their goals, only if they set one. Finally, participants were generally supportive of a Web-based dashboard incorporating features such as graphical feedback, gamification, social networking. This is not surprising given the recent growth in commercial programs to track health that utilize these online features.Our findings complement existing literature describing formative research on how to design text message interventions for hazardous alcohol use prevention. For example, Sharpe et al  found thFindings may not be applicable to other populations, such as young adults with less severe alcohol use, or other age groups, such as adolescents. This is especially relevant given the high rates of comorbid tobacco and marijuana use in our cohort. We only recruited participants in the TRAC intervention arm who had completed at least 6 weeks (50%) of the SMS text messaging assessments, which could have resulted in undersampling the opinions of those who dropped out. Focus groups were conducted at least 6 months after completion of the TRAC intervention, and therefore recall of real-time perceptions might be influenced by memory biases. Finally, the users' opinions were based on their experiences with one intervention design, and may not be the same with different text message alcohol intervention designs.Young adults perceived the TRAC intervention as a useful way to help them reduce heavy drinking on weekends. Important themes regarding usability of the TRAC intervention included its ease of use, confidentiality, and its ability to increase personal awareness of alcohol consumption and accountability for personal drinking behavior. Focus group discussion indicated that text message interventions should attempt to personalize materials based on user-specific features, such as drinking severity, and provide additional support through online adjuncts.


Despite the large and growing public health problem of alcohol use disorders (AUD) in India there is a dearth of evidence about the longitudinal outcomes in AUD. The aim of this study is to describe the course and outcomes of AUD in a population based sample of men in India.A community cohort of 1899 adult (18–49 years at baseline) men who participated in a cross-sectional survey in Goa, India between 2006 and 08, were re-interviewed face to face 6 years later (2012–14). A range of outcomes including social problems , morbidity , biological parameters  and mortality were measured at follow up. For the association of AUD at baseline with outcomes at follow-up, multivariable logistic regression was used to estimate odds ratios (OR). Analyses were weighted to account for baseline sampling design, age distribution, rural and urban sample sizes, number of adults aged 18–49 years in the household (at baseline), and non-response (at baseline).1514 (79.7%) were seen at follow-up; a loss to follow up of 20.3%. At follow up, 3.7% of baseline non-drinkers and 15.0% of baseline casual drinkers had AUD. 46.9% of baseline hazardous drinkers and 55.4% baseline harmful drinkers continued to have AUD at follow up. Of those with AUD at baseline, 21.8% had stopped drinking at follow-up. Compared to being abstinent, harmful drinking at baseline was associated with several outcomes at follow-up: workplace/social problems, hypertension, death, tobacco use, suicidality, anxiety disorders, and raised GGT (p < 0.002). Hazardous drinking at baseline was associated with tobacco use and raised GGT and MCV (p < 0.002) at follow-up.Our findings of high persistent and new AUD in the community and the association with a range of long term adverse events are an important addition to the limited evidence about the course and outcomes of AUD in India, which have the potential for informing health policy. AUD accDespite this large and growing public health problem, India does not have a national alcohol policy. One of the reasons for this is the lack of high quality contextual evidence about the problem. One type of evidence that helps to direct alcohol policy is the long-term course and outcomes in AUD. These have been studied extensively in developed countries , and finIn India, longitudinal evidence of the course and outcomes of AUD is limited by small sample sizes, short follow-up periods and restriction to treatment seeking participants , the latThe aim of this study is to describe the longitudinal course of AUD in a population based sample of men. Our hypotheses are that in a community sample of men with AUD at baseline there is a high persistence of AUD and high prevalence of a range of adverse health , and social outcomes at six years follow up. This is the first community-based cohort study of the course of AUD in India.22.1The study was conducted in Goa, which has a population of just over 1.4 million people, of whom 62% live in urban areas . Unlike 2.2In 2006–08, a cross-sectional survey (adults aged 18–49 years) was conducted in the following study sites: urban , and rural areas (six contiguous villages) of Northern Goa . The vilThe study was designed as a retrospective community cohort study, comprising the 1899 men  who were screened in the baseline survey and we measured a range of outcomes in the cohort at follow-up from September, 2012 to September, 2014.2.3The principal exposure is AUD as detected during the baseline survey, defined by the 10 item Alcohol Use Disorders Identification Test (AUDIT) . AUD was2.4Baseline socio-demographic data were collected. Standard of Living Index (SLI) was computed as a wealth index and derived from information on ownership of household assets . The SLI2.5All consenting participants were administered the self-report questionnaire by trained research workers. Standard protocolised procedures were adopted to measure height, weight and blood pressure, and for drawing and transporting blood samples. The research workers were blind to the exposure status of the participants to avoid misclassification of outcomes. Quality control was conducted by re-interviewing randomly selected participants by the research coordinator, random visits by the research coordinator to directly observe the research workers, and re-testing of randomly selected blood samples at an independent laboratory.2.6Besides the AUDIT score the following data was collected at outcome assessment:2.6.11.Problems at work directly related to drinking: These included four questions from the baseline survey which asked about any illness connected with drinking which kept the drinker from working on his regular activities for a week or more, losing or nearly losing a job because of drinking, people at work indicating that the drinker should cut down on drinking, and drinking hurting the chances for promotion, or salary increases or bonuses, or better jobs.2.Number of work days lost due to poor health in past 28 days measured using an item derived from the WHO Health and Work Performance Questionnaire HPQ; .3.Marital problems related to drinking: These included two questions from the baseline survey which asked about a spouse getting angry with the participant about his drinking or the way the participant behaved while drinking, or a spouse threatening to leave the participant because of his drinking.4.Questions from baseline survey about physical  and/or sexual abuse  of partner/spouse.5.Social problems: These included questions from the baseline survey about getting into a heated argument while drinking, getting into a fight while drinking, prominent people from society  questioning or warning the drinker because of his drinking, drinking contributing to the drinker hurting or harassing someone else emotionally, physically or sexually, getting into trouble because of drunk driving, and being caught/fined/threatened by the police or arrested for drunk driving.The questions about work, social, and marital problems are commonly used to assess social harm of drinking in the National Alcohol Surveys conducted by the Alcohol Research Group at Berkeley .6.Physical health problems measured using questions from the 10/66 Dementia Research Group population-based research programme for which one of the sites was India : Hyperte7.Accidents or injuries.8.Death: The cause of death was determined using the official death certificate.9.(a)Current use of tobacco (smoked and/or chewed): Type , quantity, and frequency in past 12 months.(b)MNS disorders diagnosed using the Mini International Neuropsychiatric Interview (MINI 6.0) a validated short, structured diagnostic interview for DSM-IV and ICD-10 psychiatric disorders  used ext(c)Common Mental Disorders (CMD) assessed using the validated 12 item General Health Questionnaire (GHQ 12)  which haMental, Neurological and Substance Use (MNS) disorders10.Health service utilisation was measured using the adapted version of the validated Client Service Receipt Inventory (CSRI) , which h2.6.22 or >24.9 kg/m2 was coded as positive for ‘unhealthy BMI’.Blood pressure (BP), height, weight, Mean Corpuscular Volume (MCV) and Gamma Glutamyl Transferase (GGT). A MCV value of >92 fL and GGT value of >50 IU/L were coded as abnormal. A BMI of <18.5 kg/m2.7Ethical approval was obtained from the Sangath Institutional Review Board (IRB), ethics committee of the London School of Hygiene and Tropical Medicine (LSHTM) and the Indian Council of Medical Research. Each research worker completed the NIH Protecting Human Research Participant online course. The results of the blood test and its interpretation were fed back to the participants. Participants with abnormal health parameters were offered referral to the local primary healthcare centre. Participants diagnosed with AUD or CMD were offered further free clinical assessment and treatment with by a psychiatrist.2.8Baseline socio-demographic characteristics were described for the full cohort, and were compared between those who had and did not have AUD at baseline using chi square or one way ANOVA as appropriate. Baseline socio-demographic characteristics and baseline AUD status were compared between those who completed follow-up assessments and those who were lost to follow-up (LTFU). Multivariable logistic regression was used to identify factors independently associated with LTFU. For each exposure group at baseline , the proportion followed-up was estimated, with the 95%CI.The primary exposure of interest, baseline alcohol use was a categorical variable , and all outcomes were binary variables. The abstainers and casual drinkers were not collapsed into a single category as they were significantly (p < 0.05) different with regard to area of residence, religion, employment status and SLI. For the association of AUD at baseline with outcomes at follow-up, logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). This was done for each outcome separately. All outcome variables which were associated with baseline AUD at p < 0.1 on univariable analyses were fitted in separate models with baseline AUD adjusted for socio-demographic factors  using multiple logistic regression. The likelihood ratio test was used to estimate p-values for trend. Weights were applied to the data to account for the baseline sampling design, age distribution, rural and urban sample sizes, number of adults aged 18–49 years in the household (at baseline), and non-response (at baseline). To account for the multiple tests, the Bonferroni correction was applied to test each individual hypothesis at the level of 0.002. All analyses were performed using STATA 13.3The 1899 participants enrolled had a mean age of 32.8 years at baseline, and were predominantly Hindu, employed and with at least some formal education . Almost Over the 6 year follow-up period, the proportion LTFU was 20.3%, and was over twice as high in the urban areas compared to rural areas . If none of those LTFU had AUD at follow up then of the non-drinkers at baseline, 3.7% would have AUD at follow-up, compared with 14.5% of baseline casual drinkers. Furthermore, prevalence of AUD at follow-up would be much higher among those with AUD at baseline (35.6% among hazardous drinkers and 42.1% among harmful drinkers).A subgroup analysis was conducted in current drinkers only. On multivariable analysis, compared to casual drinking, hazardous drinking at baseline was strongly associated with tobacco use, and raised MCV and GGT (p < 0.002) at follow up. Compared to casual drinking, harmful drinking at baseline was strongly associated with workplace problems, social problems, death, tobacco use, suicidality, and anxiety disorders (p < 0.002) follow up.6In this unique population based long-term cohort study of AUD in men in India we examined the longitudinal course and impact of AUD in a large sample of men in Goa. We observed that a substantial number of non-drinkers (3.7%) and casual drinkers (15.0%) developed AUD over a relatively short period of six years. Furthermore half of the men who already have AUD continued to have AUD and about 1 in 6 men with less severe AUD (hazardous drinking) developed more severe AUD (harmful drinking). Conversely, over the six-year period almost a third of men with AUD become casual drinkers and almost a fifth of hazardous drinkers and harmful drinkers had stopped drinking over a six-year period. This is an especially important finding in a context where formal help for AUD is minimal. Finally, AUD at baseline was found to be associated with adverse outcomes at follow up in various domains of the drinkers’ life including social problems and interpersonal problems , and physical and mental health problems .Few studies have examined the longitudinal history and impact of AUD in India . All butWe could not find any similar studies from other LMICs, but there are several population cohorts in developed countries with variable findings with regard to longitudinal progression of AUD. In a longitudinal study from Sweden, 48% of the surviving ‘alcoholics’ and 61% of the sample were still problem drinkers at 25 years of follow up . In a naIn this study we observed several adverse bio-psycho-social impacts of AUD which are statistically significant at the conventional cut off value of p = 0.05. Since we have used the Bonferroni correction to offset the influence of multiple hypotheses testing we have not considered these as statistically significant. However, it would be remiss to ignore them completely. These include marital problems, physical abuse, diabetes, COPD, accidents and injuries, and major depression. Evidence for almost all of these have been demonstrated in various studies across the developed world . FurtherOur study has some limitations as outlined below. Although we describe the longitudinal evolution of AUD in a LMIC it is by no means a natural history of AUD because some of these participants might have received treatment for their AUD which might have influenced the course of the disorder. Although we did not collect data on health service utilisation specific to AUD treatment, it is unlikely that many participants would have received such treatment as access to care for AUD is very low . AnotherIndia is a heterogeneous culture and as cultural context is an important determinant of alcohol use the uniform generalisability of our findings across the country has to be treated with caution. Despite this, our findings have several clinical, research and policy implications. One major finding is that half of all AUD remits even within a context where services for AUD are minimal. Furthermore drinking status as well as AUD status changes greatly over relatively short periods of time in these settings. A key research priority is to examine the predictors of such changes, i.e., development of new AUD, persistence of existing AUD, and recovery as these will inform the priorities for programmes for the prevention and treatment of AUD. Data from this cohort will be separately analysed to examine such predictors of various trajectories of AUD. Policymakers too need to take into consideration the high rate of conversion of casual drinking to AUD and the long term impact of drinking on a range of domains of the drinker’s life and accordingly plan integrated alcohol policies which target the problem at various levels, e.g., drunk driving penalties, taxation, and development of relevant health services. Research also needs to examine the mechanisms leading to the various negative long term outcomes of drinking, and the interactions between them, as this will allow the development of complex interventions which can target the disorder at various levels. Interestingly, although there is increasing risk of adverse health outcomes with increasing severity of AUD, there is no concomitant increase in health service utilisation, indicating the need for more demand side interventions. These could include implementing routine screening and brief interventions delivered by non-specialist health workers integrated into existing healthcare platforms, e.g., primary care as demonstrated in a treatment development project in Goa . FurtherTo conclude, substantial numbers of non-drinkers/casual drinkers develop and have persistent AUD over a relatively short period of time; and suffer long term adverse impact on various domains of their lives. This is an important addition to the literature on the course and outcome of AUD in LMIC and can be an important driver to influence health policy in such settings.No conflict declared.Wellcome Trust Research Training Fellowship to Abhijit Nadkarni [grant number WT093897MA]. Vikram Patel is supported by a Wellcome Trust Senior Research Fellowship.The funding agency had no role in the analysis and interpretation of data; in the writing of the manuscript; or in the decision to submit the paper for publication.This work was supported by the Abhijit Nadkarni led the cohort study, conceived the paper, did the analyses, and wrote up the findings. Helen Weiss supported in the drafting of the analyses plan and commented on the first draft of the manuscript and subsequent revisions. Vikram Patel supervised Abhijit in conducting the cohort study, supported in conceiving the paper, and commented on the first draft of the manuscript and subsequent revisions. Aresh Naik and Bhargav Bhat coordinated the cohort study in the field, supervised the data collection, checked the quality of the data, and commented on the first draft of the manuscript and subsequent revisions. All authors read and approved the final manuscript.


While elevated levels of CO2 will likely result in higher crop yields, weed growth is also highly likely to increase, which could increase the incidence of herbicide resistant biotypes. An experiment was conducted in 2012 to determine the effects of an elevated CO2 environment on glyphosate and halosulfuron efficacy for postemergence control of purple and yellow nutsedge (Cyperus rotundus L. and C. esculentus L.). Both species of nutsedge where grown in 3.0-L containers under either ambient or elevated (ambient + 200 μmol mol−1) CO2 in open-top field chambers and treated with either 0.5×, 1.0×, or 1.5× of the manufacturer's labeled rate of halosulfuron, glyphosate, or a tank mix of the two herbicides. The growth of both nutsedge species responded positively to elevated CO2, purple nutsedge had increased shoot and root dry weights and yellow nutsedge had increased shoot, root, and tuber dry weights and counts. Few treatment differences were observed among the herbicides at any of the rates tested. At 3 weeks following herbicide application, both purple and yellow nutsedge were adequately controlled by both herbicides and combinations at all rates tested, regardless of CO2 concentration. Based on this study, it is likely that predicted future CO2 levels will have little impact on the efficacy of single applications of halosulfuron or glyphosate for control of purple and yellow nutsedge at the growth stages described here, although scenarios demanding more persistent control efforts remain a question.Atmospheric concentrations of carbon dioxide (CO Herbicides tested include glyphosate  and halosulfuron . Glyphosate and halosulfuron were selected based upon availability, widespread use, and previous reports showing effective nutsedge control at label rates  and watered in by hand. On June 12, six nutsedge tubers  of either yellow or purple nutsedge were planted 2.5 cm below the media surface in 150 pots each (25% more pots than were needed for the experiment were planted with nutsedge tubers from each species to ensure plants could be selected for uniformity of growth at the time of herbicide application). Each pot was then fertilized by topdressing using 17N-2.2P-9.1K Polyon  control-release fertilizer (10–12 month) at a rate of 20 g (8.31 kg/m3) per pot. Tubers from both species began to germinate on June 17 and 18. On June 18, 120 pots of each species were selected for uniformity of growth and tuber germination and placed inside either ambient- or elevated-level CO2 chambers. A total of 12 outdoor open-top chambers in full sun  CO2 concentrations using a system previously described by Mitchell et al. (2 concentrations (± standard error) for the duration of the study were 405.6 ± 0.2 μmol mol−1  and 608.0 ± 0.6 μmol mol−1 . Ten pots of each nutsedge species were placed inside each of the 12 chambers, resulting in a total of 60 pots of yellow and purple nutsedge inside ambient chambers (10 pots of each species inside each of the 6 chambers) and 60 pots of yellow and purple nutsedge inside elevated chambers (10 pots of each species inside each of the 6 chambers). Pots were grouped by species and arranged randomly near the center of each chamber. Nutsedge remained inside the chambers for 16 days growing to approximately 10 and 20 cm in height for purple and yellow nutsedge, respectively.On June 8, 300 nursery pots (3.0-L) were filled with Faford® 2B potting mix  and placed in full sun in a gravel area near the experiment site  at 172.4 kPa. When halosulfuron was applied alone, a nonionic surfactant  was added at 0.25%. On July 4, pots were placed back into the chambers (either ambient or elevated CO2) in the same manner as previously described.On July 3 , all pots were removed from the chambers and herbicide treatments Table  were app2 treatment being randomly assigned to one open-top chamber within each block prior to study initiation. Each herbicide treatment was replicated 10 times in each CO2 treatment for both purple and yellow nutsedge in each of the 12 chambers. A non-treated control group was also included for both species inside each of the 12 chambers. Nutsedge control ratings were visually estimated using general nutsedge vigor taking into account plant color, structure, and any foliage abnormalities in the scale  at 1, 2, and 3 weeks post-treatment. At 3 weeks post-treatment, all nutsedge were destructively harvested. Shoots were cut at the soil surface and roots were separated from tubers and washed to remove any remaining debris. Tubers were counted and then washed similarly to roots. Following the destructive harvest, shoots, roots and tubers were dried in a forced air oven at 55 C for 7 days at which time dry weights (DW) were recorded. Data were analyzed using the general linear models procedure (Proc GLM) of SAS  to 10.0 . However, at this time control ratings were higher in ambient chambers compared with elevated chambers for purple nutsedge treated with the lowest rate of halosulfuron and the lowest rate of glyphosate. Almost all treatments provided complete control of purple nutsedge at 3 weeks post-treatment, and no differences were observed among treatments or CO2 levels.At 1 week post-treatment, all treatments containing glyphosate generally had higher control ratings than treatments containing halosulfuron alone in both ambient and elevated CO2 chambers compared with those grown in ambient chambers (P = 0.0001) . Similar to results observed for purple nutsedge, few differences were observed among herbicide treatments in terms of shoot, root, or tuber DW. However, in contrast to results observed in purple nutsedge in which tuber counts were similar among all treatments (including non-treated controls), in yellow nutsedge, tuber counts were significantly reduced when glyphosate was applied at either 3.36 or 5.04 kg ai/ha−1 and also when the combination was applied at 0.04 + 1.68 and 0.10 + 5.04 kg ai/ha−1 in ambient chambers. In addition, all yellow nutsedge treated with herbicide had fewer tubers than the non-treated control in elevated chambers.Yellow nutsedge shoot, root, and tuber DW and tuber counts in control treatments showed that yellow nutsedge grew larger in elevated chambers  was reduced at CO2 levels of 720 μmol mol−1 when 0.25× of the manufacturer's rate was applied compared to the 1× rate. Additionally, Ziska et al.  under elevated CO2 conditions when glyphosate was applied at 0.1× compared with the label rate. Although CO2 concentrations used in the present study are comparable to those used in previous reports, a much higher minimum rate (0.5×) was applied in the present study which likely limited the rate and CO2 effect which has been observed previously with glyphosate and other herbicides. To our knowledge, there have been no earlier reports on the effect of elevated CO2 on halosulfuron efficacy, so we are unable compare these results with previous findings.There was no main effect for herbicide rate in either purple or yellow nutsedge regardless of COt et al.  reporteda et al.  showed d2 chambers, similar to previous reports  containers, and it is possible root growth was slightly restricted, although upon visual inspection no plants appeared root-bound in the pots at the time of herbicide application.It is clear that both species of nutsedge grew larger in elevated CO2, so any effects of elevated CO2 on tuber predisposition during development in the field were not captured. While both purple and yellow nutsedge have been shown to produce more tubers under elevated CO2  more pessimistic scenarios, whereas 608 μmol mol−1 is never reached using more optimistic scenarios , halosulfuron, glyphosate, or a combination tank mixture of the two active ingredients will provide acceptable control of both purple and yellow nutsedge at rates as low as 0.5× the manufacturer's maximum label rate when treated at a similar growth stage . Further investigation is needed to determine how herbicide efficacy would be affected by increased exposure time to elevated CO2 or by delaying applications until the nutsedge grew closer to its maximum size or reached the flowering stage. It would also be important to focus future research on determining the impact of herbicide application on tuber viability when applied in an enriched CO2 environment. While this experiment focused on a single-treatment scenario, it should be noted that both of these species typically require repeated herbicide applications supplemented with cultural practices over several years for significant tuber reduction and long-term control (Stoller et al., Results from this study suggest that although both species of nutsedge showed a positive response to elevated COThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Malnutrition is a common cause of morbidity and mortality in children with congenital heart disease (CHD). This study aimed to identify prevalence and predictors of malnutrition in Egyptian children with symptomatic CHD.Z scores for weight for age (WAZ), weight for height (WHZ), and height for age (HAZ) have been calculated. Malnutrition was defined as weight, height, and weight/height Z score ≤–2.This case–control study included 100 children with symptomatic CHD (76 acyanotic and 24 cyanotic) and 100 healthy children matched for age and sex as a control group. Clinical Evaluation and Laboratory Assessment of Nutritional Status were documented. Anthropometric measurements were recorded and The overall prevalence of malnutrition was 84.0% in patients with CHD and 20% in controls. Severe malnutrition was diagnosed in 71.4% of cases. All anthropometric measurements and levels of biochemical markers of nutritional state were significantly lower in the patients group compared to controls. In patients with acyanotic CHD, stunting was proportionately higher (57.89%) than in cyanotic CHD, while wasting was predominant (45.83%) in the latter. Malnutrition correlated significantly with low hemoglobin level, low arterial oxygen saturation, heart failure, pulmonary hypertension, and poor dietary history.Malnutrition is a very common problem in children with symptomatic CHD and predicted by the presence of low hemoglobin level, low arterial oxygen saturation, heart failure, poor dietary history, and pulmonary hypertension. Congenital Heart Disease (CHD) are often associated with malnutrition and failure to thrive . Growth Mechanisms for growth deficiency in CHD are multifactorial including associated chromosomal anomalies/genetic syndromes, inadequate nutrition due to feeding difficulties, and poor nutritional absorption from the digestive tract in chronic congestive heart failure (CHF). Also, increased caloric support is required to sustain the increased myocardial, respiratory, and neuro-humoral functions in CHD-related heart failure. Chronic CHF and chronic under-oxygenation in CHD impair cellular metabolism and cell growth, while repeated chest infections demand an increased metabolism .Malnutrition in children with CHD has been associated with increased morbidity and mortality as indicated by frequent hospitalization, poor surgical outcomes, persistent impairment of somatic growth, and increased death , 7.In Egypt, as in many developing countries, pediatric cardiac programs are not fully established and epidemiological data on CHD-related malnutrition are lacking. Therefore, this study aimed to assess the prevalence, patterns, and predictors of malnutrition in Egyptian children with symptomatic CHD.This study was conducted prospectively as a case–control study at the Pediatric Cardiology Unit, Zagazig University Children’s Hospital during the period from June 2012 to June 2013. It included 100 children aging from 2 months to 6 years with different symptomatic CHD. Patients with other congenital malformations than cardiac anomalies or other diseases (including genetic disorders) affecting the growth or the nutritional status of the children, were excluded.One hundred healthy children matched in age and sex without any abnormal echocardiographic findings represented our control group.Informed consent was obtained from the children’s parents or care-givers, and the study was approved by the ethical committee of faculty medicine of Zagazig University.A full medical history as well as a complete cardiac examination  is documented for all children. Clinical signs of malnutrition, such as symmetrical edema, skin lesions, and dry, thin and depigmented hair, were assessed.Anthropometric measurements included weight (kilogram), length (centimeter), cephalic, thoracic, and abdominal circumferences (centimeter) as well as triceps and subscapular skinfold thickness (millimeter). They were performed according to standard WHO procedures .Z scores for weight for age (WAZ), weight for height (WHZ), and height for age (HAZ) were calculated using the Anthropometric calculator module of WHO Anthro software  (based on The 2006 WHO child growth standards) (andards) .After calculation of WAZ, WHZ, and (HAZ), the studied groups were classified into normal nutritional status and malnutrition (moderate or severe).Z score of ≤-2 to classify low WAZ (underweight), low HAZ (stunting), and low WHZ (wasting) as moderate malnutrition, and a Z score of ≤-3 SD to define severe malnutrition  recommends a cut-off utrition .Laboratory examinations included hemoglobin, serum protein, serum iron, and ferritin levels. Echocardiography was performed using the GE Vivid-7 multipurpose system with different probe sizes according to the recommendations of the American Society of Echocardiography .t-test. Non-parametric values were represented as median and range, and the medians of two groups were compared by Mann–Whitney U test. Qualitative data were represented by their frequency and relative percentage, and chi-square test was used for testing association of qualitative data. Correlations were performed using the Pearson bivariate correlation. A p-value of <0.05 was considered statistically significant.Data were analyzed using the Statistical Package for Social Sciences (SPSS) release 16. Data with a normal distribution are presented as mean and SD. The mean of two groups was compared by A total of 100 children with symptomatic CHD were included in the study. Details of demographic characteristics, anthropometric measurements, and biochemical markers are given in Table All anthropometric measurements were significantly lower in the patients group than in the control group, as well as hemoglobin, serum iron, ferritin, and albumin levels.Table Table In patients with CHD, stunting was proportionately higher (57.89%) in the acyanotic subgroup, while wasting was predominant 45.83%) in the cyanotic subpopulation. There was no difference between cyanotic and acyanotic patients regarding the severity of malnutrition (Table 5.83% in Malnutrition correlated significantly with low hemoglobin level, low arterial oxygen saturation, heart failure, pulmonary hypertension, and poor dietary history Table .Different types of cardiac malformation can affect nutrition and growth to varying degrees. The severity of malnutrition can range from mild under-nutrition to failure to thrive . Our stuThe high prevalence of 84% in our CHD group demonstrates the importance of malnutrition in patients with CHD. Moreover, 71.4% of cases had severe malnutrition.Previous reports showed that CHD-related malnutrition is particularly common in developing countries, but prevalence varies widely from 27% up to 90.4%. For instance, Turkey, Mehrizi, and Drash  reportedAs in the study of Okoromah et al. , the higThe relative proportions of underweight, stunting, and wasting in the patient group were 14.3, 61.9, and 23.8%, respectively. Okoromah and his colleagues  reportedIn agreement with the usual distribution of growth deficiency in the general pediatric population in Egypt , 16, stuIn the present study, stunting was linked to acyanotic CHD, while wasting was associated with cyanotic CHD. Several studies of the patterns of malnutrition in CHD vary widely , 17, 18.These differences in the pattern of malnutrition among cyanotic and acyanotic patients may be due to the significant left to right shunt lesions in the acyanotic group that are more likely to be associated with chronic CHF and recurrent chest infections. These two factors, together with delayed surgical correction, might lead to the stunting type of chronic malnutrition. Second, regional variations in the distribution of malnutrition may also contribute to these differences as stunting was the most common type of malnutrition in the general Egyptian pediatric population , 16. FinIn the present study, the predictors of malnutrition were anemia, low arterial oxygen saturation, heart failure, poor dietary history, and pulmonary hypertension.In agreement with these findings, Okoromah et al.  found thIn south India, Vaidyanthan et al.  reportedMalnutrition is a very common complicating problem in children with symptomatic CHD, predicted by the presence of anemia, low arterial oxygen saturation, heart failure, poor dietary history, and pulmonary hypertension.Based on the results of our study, an aggressive nutritional optimization for children with CHD should be considered, while efforts for early corrective interventions should be intensified. Future research should explore the short- and long-term impacts of improved nutrition on morbidity and mortality before and after corrective interventions for CHD.All authors contributed to the current work as follows: BH, the first author, SM, and EA suggested the idea of the research and designed the work plan. The Egyptian authors contributed to the collecting of patients and interpreting and analyzing their data. BH and SM wrote and revised the paper, the last author, Professor OG, interpreted the results and made the final revision of this article before submission.The authors declare that there is no potential conflicts of interest exist with respect to the research, authorship, and/or publication of this article.


This study tests if the biogeographical affinities of genera are relevant for explaining elevational plant diversity patterns in Nepal. We used simultaneous autoregressive (SAR) models to investigate the explanatory power of several predictors in explaining the diversity-elevation relationships shown in genera with different biogeographical affinities. Delta akaike information criterion (ΔAIC) was used for multi-model inferences and selections. Our results showed that both the total and tropical genus diversity peaked below the mid-point of the elevational gradient, whereas that of temperate genera had a nearly symmetrical, unimodal relationship with elevation. The proportion of temperate genera increased markedly with elevation, while that of tropical genera declined. Compared to tropical genera, temperate genera had wider elevational ranges and were observed at higher elevations. Water-related variables, rather than mid-domain effects (MDE), were the most significant predictors of elevational patterns of tropical genus diversity. The temperate genus diversity was influenced by energy availability, but only in quadratic terms of the models. Though climatic factors and mid-domain effects jointly explained most of the variation in the diversity of temperate genera with elevation, the former played stronger roles. Total genus diversity was most strongly influenced by climate and the floristic overlap of tropical and temperate floras, while the influences of mid-domain effects were relatively weak. The influences of water-related and energy-related variables may vary with biogeographical affinities. The elevational patterns may be most closely related to climatic factors, while MDE may somewhat modify the patterns. Caution is needed when investigating the causal factors underlying diversity patterns for large taxonomic groups composed of taxa of different biogeographical affinities. Right-skewed diversity-elevation patterns may be produced by the differential response of taxa with varying biogeographical affinities to climatic factors and MDE. Understanding what mechanisms generate geographical variation in biodiversity is one of the fundamental goals of biogeography and macroecology . Though iversity . Howeveriversity . Interes species . Lomolin species . We thusOne of the most pervasive explanations for hump-shaped diversity patterns is the mid-domain effects (MDE). MDE suggests that the diversity peaks in mid-elevation are caused by the increasing overlap of species ranges towards the center of the domain or elevational gradient ,11. HoweNepal harbors the longest elevational gradient on the Earth. Within a relatively short horizontal distance, the land traverses large climatic and environmental gradients, from subtropical forests in the lowlands, to glaciated, snowbound upper peaks . Thus, NGrytnes & Vetaas (2002) proposed that the diversity peak in mid-elevation may be due to the intermediate location between the ranges of temperate and tropical flora, which increases the chance of immigration from both directions, i.e. the mass effect . That isIn the present study, we tested the following hypotheses: (i) plants with different biogeographical affinities show different elevational diversity patterns; (ii) floristic overlap strongly shapes the elevational patterns observed in the total diversity of genera; and, (iii) biogeographical affinity modifies the influence of mid-domain effects and climatic factors.Our study area encompasses the entire Nepal, which covers 900 km from east to west on the southern slopes of the Central Himalayas . Three south-eastern to north-western mountain ranges form the main body of Nepal, including the Siwalik range , the Mahabharat range  and the Great Himalayas  , 32. TopNepal harbors a wide range of climatic conditions, which vary with seasons and geography. Overall, annual precipitation ranges from 1,500 to over 3,000 mm . On the Betula utilis and coniferous forest., while the upper elevational limits for Abies spectabilis and Pinus wallichiana forest are 4,000–4,300 m a.s.l; in the alpine zone above 4,000 m, grasslands gain dominance, while in the high alpine zone genera such as Saxifraga, Gentiana and Androsace become common [The mean annual temperature at 100 m a.s.l. in Nepal is around 24.7°C, and with increasing elevation, energy availability steeply decreases and vegetation types range widely ,26. Domie common ,35.http://www.efloras.org/, accessed on Dec 1st in 2013)  . The infWe focused on elevational diversity patterns between 60 and 6,000 m a.s.l., as suggested by Grytnes & Vetaas (2002) . The stuTemp, °C; the standard deviation of mean monthly temperature), (11) precipitation seasonality , (12) the annual range in temperature , and (13) mid-domain effects (MDE). These explanatory variables, with the exception of IFO and mid-domain effects, were grouped into four categories  were taken from WorldClim-Global Climate Data with a 30 second resolution [http://www.worldclim.org/, accessed on Jul 1st 2014). PET, AET, and AI with a 30 second resolution were downloaded from the Consortium for Spatial Information (CGIAR-CSI) [http://www.cgiar-csi.org/, accessed on Jul 1st 2014). All of the climatic factors on elevation can be found in We examined the relationships between genus diversity and thirteen potential explanatory variables as follows: (1) the index of floristic overlap , (2) mean annual temperature , (3) mean temperature of the coldest quarter , (4) annual potential evapotranspiration , (5) warmth index , (6) mean annual precipitation , (7) rainfall , (8) aridity index , (9) annual actual evapotranspiration , (10) temperature seasonality (Stegories : energy solution  (http://IAR-CSI) ,40 (httpTM to obtain the data of other explanatory variables (with the exception of IFO and MDE) over the elevational gradient , to represent plant diversity, in order to account for the effects of area.The area for each elevational band was calculated with the Digital Elevation Model data (DEM) obtained from WorldClim-Global Climate Data with a 30 second resolution  S3 Tabl. The totWe interpolated the presence of each genus on the basis of recorded altitudinal range of each genus . This method assumed that taxa are continuously distributed between their upper and lower limits  ,43. AlthWe used the system proposed by Wu (1991)  for the To investigate elevational patterns in genus diversity, the numbers of tropical, temperate and total genera in each elevational band were tallied. To further explore the elevational diversity patterns of genera with different biogeographical affinities, the proportions of tropical and temperate genera in each elevational band were calculated. All datasets followed normal distributions, which is an important precondition for regression analysis.As floristic overlap, i.e., the co-occurrence of tropical and temperate flora, may be associated with elevational patterns of taxonomic diversity ,48, we cwww.ecoevol.ufg.br/sam/) to generate SAR models of all possible combinations of the aforementioned predictors [www.ecoevol.ufg.br/sam/) [Spatial autocorrelation is frequently observed in elevational taxonomic diversity data, which may result in pseudo-significance of the results as the type I error rate is inflated in significance tests . Besidesedictors ,55  ,55.Tropical, temperate and total genus diversity showed hump-shaped distributions along the elevational gradient . MaximumP<0.05), while tropical genera showed the opposite pattern (P<0.05) (The proportion of temperate genera increased with elevation ((P<0.05) . The flo(P<0.05) .One-way ANOVAs revealed that, compared to tropical genera, temperate genera had wider elevational ranges and were observed at higher elevations (p< 0.001 for both).P>0.05), either in linear or quadratic simultaneous autoregressive (SAR) models, whereas its distribution was significantly influenced by most of the tested climatic factors, and the strongest predictor was MAP in linear form  observed that the proportions of tropical versus temperate species showed the opposite trends over a latitudinal gradient: the proportion of tropical species decreased with latitude, while temperate species increased [Wang ncreased . Taking ncreased –58. MostThe linear regression analyses in this study showed that most of energy related variables strongly and linearly influenced elevational patterns of tropical genus diversity. This suggests that the eco-physiological traits of tropical genera, as indicated by their tropical biogeographical affinities, may be best suited to the warmer environments at lower elevations, and the decreasing thermal energy with elevation may filter out tropical genera. Our findings, therefore, strongly support the species-energy hypothesis  –58.In contrast, we did not observe the negative (linear) relationship between temperate genus diversity and energy variables, all of which decreased linearly with elevation. Oommen & Shanker (2005) found that temperate species diversity showed a nonlinear relationship with temperature . PartialIn summary, the different responses of temperate and tropical genera to energy availability may be one of the important reasons for their differences in elevational diversity patterns. To a certain extent, this confirms one of our main hypotheses that biogeographical affinity may interact with elevation to produce different patterns of taxonomic diversity via modulating the effects of climatic factors.et al. (2007) and Oommen & Shanker (2005) suggested that, compared to temperate genera, tropical genus diversity is more strongly influenced by climatic factors [Both Wang  factors ,17. In cHawkins et al. (2003) proposed that water variables usually showed the strongest influences on taxonomic diversity in low latitudes, whereas energy variables or water–energy variables represented the strongest predictors in high latitudes, as in low latitude regions the energy input is abundant and in high latitude regions the energy input is low, suggesting that the relative effects of water variables and energy or water-energy variables may depend on latitude . Studieset al. (2007) [Mid-domain effects did not explain the diversity-elevation relationship of tropical genera, but they strongly influenced temperate genus diversity, consistent with the findings of Oommen & Shanker (2005)  and Wang. (2007) . The inc. (2007) . In addi. (2007) .Our study did not observe consistent influence of MDE, i.e., the influence of MDE varied with biogeographical affinities, and for total genus diversity, the influence of MDE was weaker than that of climatic factors . Thus, aGenera in the present study were largely either of tropical or temperate affinities, and different biogeographical groups showed different elevational diversity patterns as a result of different influences of MDE and climatic factors. These results suggest that elevational patterns in total genus diversity, even within similar elevational gradients with similar biogeographical history, cannot be explained by the same way . Multiplet al. (2013) argued that most of these putative explanations fail to explain why many distributions are right-skewed (maximum diversity below the middle of the gradient), with the exception of one hypothesis that spatial constraints reduce diversification and immigration at higher elevations [A variety of factors or hypotheses have been proposed to explain the unimodal relationship between diversity and elevation, such as water-energy dynamics , area 99,17 and evations , therebyevations ,67. Howeevations . Here, wBhattarai & Vetaas (2003) suggested that the mid-elevation peak in plant diversity in Nepal may be linked to its intermediate location between the ranges of temperate Himalayan flora at high elevations and of subtropical flora at low elevations . Our stuR2 = 0.96) of the multiple models. Another weakness is that we only used Flora of Nepal as data source (lacking of collected data) and used linear interpolation of range extremes of genera, thereby obtaining genus diversity on elevation. Though this method has been widely used in the publications on elevational patterns of the Nepal flora, its weakness can not be denied. Firstly, compared with plot based study, this method can not efficiently minimize the area-effect as suggested by Lomolino (2001) [One of the weaknesses of the present study is the fact that both climatic variables and genus diversity along the elevation gradients were reduced to elevational bands, hence trends are highly smoothed, which, to certain extent, may result in extremely high explanatory power R2 = 0.6 of the o (2001) . Thirdlyo (2001) . Given tS1 Table(XLS)Click here for additional data file.S2 Table(XLS)Click here for additional data file.S3 Table(XLS)Click here for additional data file.S4 Table(XLS)Click here for additional data file.S5 Table(DOC)Click here for additional data file.


Previous studies have suggested that there is a positive correlation between the extent of video gaming and efficiency of surgical skill acquisition on laparoscopic and endovascular surgical simulators amongst trainees. However, the link between video gaming and orthopaedic trauma simulation remains unexamined, in particular dynamic hip screw (DHS) stimulation.To assess effect of prior video gaming experience on virtual-reality (VR) haptic-enabled DHS simulator performance.38 medical students, naïve to VR surgical simulation, were recruited and stratified relative to their video gaming exposure. Group 1  were defined as those who play more than one hour per day in the last calendar year. Group 2  were defined as those who play video games less than one hour per calendar year. Both cohorts performed five attempts on completing a VR DHS procedure and repeated the task after a week. Metrics assessed included time taken for task, simulated flouroscopy time and screw position. Median and Bonett-Price 95% confidence intervals were calculated for seven real-time objective performance metrics. Data was confirmed as non-parametric by the Kolmogorov-Smirnov test. Analysis was performed using the Mann-Whitney U test for independent data whilst the Wilcoxon signed ranked test was used for paired data. A result was deemed significant when a two-tailed p-value was less than 0.05.All 38 subjects completed the study. The groups were not significantly different at baseline. After ten attempts, there was no difference between Group 1 and Group 2 in any of the metrics tested. These included time taken for task, simulated fluoroscopy time, number of retries, tip-apex distance, percentage cut-out and global score.Contrary to previous literature findings, there was no correlation between video gaming experience and gaining competency on a VR DHS simulator. The last few decades have seen the development of commercially available video games, which have become a part of everyday social culture. Persistent advancements in both software and hardware have led to the development of increasingly realistic video simulation games. Ubiquitous access to the Internet and additional infrastructure to support higher bandwidths has facilitated co-operative play, further increasing popularity of videogames Although video gaming has been associated with negative effects, including lower academic performance The formation of psychomotor mechanisms such as ‘attentional weighting’ refers to the ability to discriminate less significant aspects and give increased attention to those elements of greater importance Alongside this, developments of spatial awareness and hand-eye co-ordination are key skills that can be acquired from video gaming Within orthopaedic trauma, there have been no studies conducted to observe the effects of video gaming on technical objective performance metrics. Previous studies in laparoscopic simulators have found that experience gained from 2D screens of video gaming has influenced performance by improving tasks such as object transfer and figure of eight Within the previously mentioned trial, the methodology focused on providing training on specific video games before conducting a trial To investigate the effect of video gaming on acquisition of technical skills on a haptics-enabled, virtual-reality (VR) DHS simulator. Primary objectives included seven objective performance metrics.Extent of video gaming does not correlate with psychomotor performance, as measured by objective metrics, on a VR DHS simulator.Imperial College Research Ethics Committee granted ethics for this project (MEEC1213-17). Informed, written consent was gained from all participants before the study commenced.All participants were tested on TraumaVision VR , a haptics-enabled, VR, DHS simulator with the additional function of simulated fluoroscopy. The software runs on a standard computer desktop with two foot-pedals (to demonstrate antero-posterior (AP) and lateral fluoroscopic radiography) and a Phantom pen stylus  to simulate guide wire positioning, drilling, reaming and screw driving.The power calculation was based on a preliminary pilot study using surgical trainees with the same inclusion and exclusion criteria. The pilot study consisted of ten participants naïve to simulation. Out of the objective metrics, we determined the Cohen's d effect to be 0.954 to reflect the effect size. We determined that with a two-sided p-value of 0.05 and a power of 80% (β = 0.2 with largest SD = 86.3) we required at least 38 participants in total. To compensate for possible drop-outs, we recruited 42 participants with at least 19 participants in a group.38 novice surgical trainees were recruited for this cohort study. Group 1  and Group 2 .Naivety to DHS procedures and orthopaedic VR simulation. For the video gaming cohort, gamers were defined as a having a minimum of one hour per week of gaming on any platform, whilst non-gaming was defined as less than one hour of gaming, per calendar year.Previous exposure to DHS procedures or orthopaedic simulation.After informed consent, participants viewed a four-minute video to guide them through the steps of the DHS procedure. All testing was carried out in isolation.The standardised task consisted of the following steps:Place a guide wire into the femoral neck and head using the pre-selected 135 degree fixed angle guide, under fluoroscopic guidanceSelect an appropriate reamer length and ream over the guide wireSelect and insert an appropriate length lag screwInsert a four-hole 135 degree plate and align this correctly to the long axis of the femurReduce the plate to the lateral femoral cortex with a simulated malletDrill through the distal hole of the plate through both corticesInsert a depth gauge and measure the width between the medial and lateral femoral corticesSelect and insert an appropriate length screwPrimary objectives consisted of seven objective performance metrics measured by the simulator including (i) total procedural time (secs), (ii) total fluoroscopy time (secs), (iii) number of radiographs taken (n), (iv) Tip-Apex Distance (TAD) (mm), (v) number of unique attempts or retries (n) to place the guide-wire, (vi) the probability of cut-out (%) according to Baumgaertner's graph All data was recorded as median and Bonett-Price 95% confidence intervals. Data was confirmed as non-parametric by the Kolmogorov-Smirnov test. Analysis was performed using the Mann-Whitney U test for independent data whilst the Wilcoxon signed ranked test was used for paired data. A result was deemed significant when a two-tailed p-value was less than 0.05.38 participants completed the study where both cohorts were completely naïve to orthopaedic simulation. The most commonly used systems were the PlayStation 3 (PS3), and ‘Other (PC)’, which were used equally by seven participants (36.8%). No users reported use on mobile gaming systems (iOS & Android) .Seven metrics were used to demonstrate heterogeneity and minimisation of selection bias. There was no difference between cohorts at baseline in all seven metrics .p = 0.53). Both gamer and non-gamer groups demonstrated significant results in terms of improvement via training by taking 74% and by 73% less time respectively . With increasing attempts in gamer and non-gamer groups, there was an insignificant increase in fluoroscopy by 3% and 4% respectively . The gamer group showed a significant decrease of 65% in the number of radiographs taken. The control group also displayed significant results of a 56% decrease . Adjusting for training effect, both the gamer and non-gamer group showed a significant decrease of 100% in retries of inserting the guide-wire (There was zero difference in the number of retries by the end of both cohorts' tenth attempts (ide-wire .p = 0.50) by the end of testing. The gamer group showed a significant improvement by 46% in their TAD and similarly the non-gamer group showed a significant improvement of 52% (The gaming group had a 6% greater TAD compared to non-gamers (t of 52% .p = 0.50). Both gamers and non-gamers showed a significant decrease in the probability of cut out at tenth attempt  for gamers, however, this was insignificant (p = 0.41). Global score improved significantly with repeated attempts in both groups   . LearninThe null hypotheses were accepted for all objective metrics. Both cohorts demonstrated a training effect as evidenced by the significant improvements in all performance metrics. However, there was no significant difference between the cohorts in any of the metrics . This waIn this study, we did not demonstrate a difference in skill acquisition between gamers and non-gamers. Although a coincidental significant training effect was observed in both cohorts (except for fluoroscopy), the video gaming cohort was not superior in any metric compared to the non-gaming group. The correlation coefficients in Video gaming results in improved spatial relationships, visual attentional capacity and enables visual multitasking et al. found that video gaming improved basic surgical tasks, such as knot tying, but was unable to influence more complex surgical tasks A study by Rosenberg et al. found that after a period of training on the Nintendo Wii, medical students performed superiorly to those without training on a laparoscopic simulator, Lap Mentor et al. associated a correlation between baseline performances on three Wii games with laparoscopic score et al. stratified for lifetime experience of gaming, and found that both current and past video gaming experience was associated with improved performance in laparoscopic tasks Within the field of laparoscopic surgery, Giannotti et al. have argued that it is the form and the mechanics of the game that are of greater importance than the content or amount of video games played Gentile The previous studies looking at the correlation between laparoscopic skills and extent of exposure to video gaming do not take into account other surgical simulation platforms. TraumaVision expects the participant to complete the DHS procedure with one hand using a stylus pen to be manipulated in space (somewhat similar to using a laparoscope). However, our simulation programme does not take into account path length and hand speed like the VR laparoscopic and arthroscopic simulators do. The majority of objective performance metrics looks more into mechanical factors of the surgical steps. These included lengths, angulations and visuospatial awareness on achieving optimal TAD using 2D AP and lateral fluoroscopic views.One limitation of our study is that the DHS simulator has not undergone transfer and concurrent validity analysis to ensure that the skills assessed are relevant to the real operating theatre environment. However, the simulator measures clinically validated objective metrics, which has the potential to demonstrate transfer validity into the clinical scenario. Further work should however assess these criteria so that the non-effect of video gaming can be extrapolated to real life operating.Our study is unique in demonstrating that video game exposure does not necessarily correlate with improved DHS simulation performance and scoring. Most importantly, there is no evidence to support that gamers will become technically better at performing DHS procedures.Contrary to previous findings in literature, there was no difference between those with extensive video gaming experience and those without in improving performance on a VR DHS simulator. The DHS simulator, unlike other popular endoscopic simulators, does not take into account the same metrics such as path length and hand speed.Table S1Raw data available from the study.(XLSX)Click here for additional data file.


A single cell can form a colony, and ionizing irradiation has long been known to reduce such a cellular clonogenic potential. Analysis of abortive colonies unable to continue to grow should provide important information on the reproductive cell death (RCD) following irradiation. Our previous analysis with a branching process model showed that the RCD in normal human fibroblasts can persist over 16 generations following irradiation with low linear energy transfer (LET) γ-rays. Here we further set out to evaluate the RCD persistency in abortive colonies arising from normal human fibroblasts exposed to high-LET carbon ions . We found that the abortive colony size distribution determined by biological experiments follows a linear relationship on the log–log plot, and that the Monte Carlo simulation using the RCD probability estimated from such a linear relationship well simulates the experimentally determined surviving fraction and the relative biological effectiveness (RBE). We identified the short-term phase and long-term phase for the persistent RCD following carbon-ion irradiation, which were similar to those previously identified following γ-irradiation. Taken together, our results suggest that subsequent secondary or tertiary colony formation would be invaluable for understanding the long-lasting RCD. All together, our framework for analysis with a branching process model and a colony formation assay is applicable to determination of cellular responses to low- and high-LET radiation, and suggests that the long-lasting RCD is a pivotal determinant of the surviving fraction and the RBE. The relative biological effectiveness (RBE) varies with the linear energy transfer (LET) of ionizing radiation (IR). Compared with low-LET photons like X-rays or γ-rays, high-LET heavy ions cause more dense ionization along trajectories and more complex clustered DNA damage, thereby being more effective at inactivating a cellular clonogenic potential –5.Clonogenicity is the ability of a cell to form a colony, and alters in response to a variety of internal and external stimuli. In a colony formation assay, clonogenic colonies each comprising 50 cells or more are generally evaluated as survivors, while abortive colonies that contain less than 50 cells are regarded as non-survivors because of their failure to continue to grow Figure. A. In conThe probability of reproductive cell death (RCD) is an important parameter for understanding the clonogenic kinetics, and our previous work showed persistence of the RCD probability multiple generations after γ-irradiation . Here we−9 × LET (keV/µm) × fluence (particles/cm2) [For all experiments, AG01522D primary normal human diploid foreskin fibroblasts purchased from the Coriell Cell Repositories at the Coriell Institute for Medical Research  were used. Cells were exposed to carbon ions  delivered from the azimuthally-varying-field cyclotron installed at the Takasaki Ion accelerators for Advanced Radiation Application (TIARA) facility of the Japan Atomic Energy Agency (JAEA). The absorbed dose was calculated according to the formula: dose (Gy) = 1.6 × 10P1 (the probability of the RCD) and P2 (the probability of proliferation) at each branch point, and the f (occurrence frequency of abortive colonies with n cells) was calculated as follows:Irradiated cells should undergo RCD or proliferation, and form an abortive colony through a complicated cell lineage expressed as a branch tree Figure B. To ana1f = 1P and 2P = 1 − 1P.Where P1 (g) (= 1 − P2 (g)) at generation g < 6 from the regression curve for the abortive colony size distribution with a 95% confidence limit, as previously described [P1 (g ≥ 6), where P1 (g = 16) was set as (1 – c) multiplied by P1 (g = 5) and c was the constant.The frequency of 1-cell colonies was estimated from that of 2-cell colonies, assuming a similar probability of RCD for 1- and 2-cell colonies as previously described . The phrescribed . We usedP1 (g) [2. When a cell has no free space in the eight adjacent grid points it cannot divide into two cells. We used the experimentally determined doubling time of 20 h [P1 (g). A clonogenic colony was formed about 13 days (16 divisions) after IR [To simulate the colony formation kinetics, we used the Monte Carlo method based on the branching processes with the estimated RCD probabilities, i.e. P1 (g)   . A cell  of 20 h  and calchttp://ccl.northwestern.edu/netlogo/. NetLogo is a java platform that has been used to analyze complex systems, and adopts the multi-agent modeling Logo languages.For a simulation, the platform of the NetLogo software  was usedP values were corrected using the Bonferroni method.Using the ORIGIN computer program , the non-linear regression analysis and calculations of 95% confidence limits for the colony size distribution were carried out. A better fit model was selected with the Akaike Information Criterion (AIC) with log-transformed data, except for the estimated frequency of 1-cell colonies determined according to the previously described method . A chi-sAbortive colonies with < 16 cells derived from normal human fibroblasts showed a linear relationship on the log–log plot following low-LET radiation exposure . On the R2 were 0.988 for 1 Gy, 0.990 for 2 Gy and 0.976 for 3 Gy). Using the log–log regression curve for the experimental datasets ) and IR-induced excess RCD probabilities at generations 0 to 5 were evaluated from Equation 1. The RCD probability for fibroblasts exposed to 1 Gy of carbon ions demonstrated almost constant values at generations 0 to 5  was set as (1 – c) multiplied by P1 (g = 5), and the values between P1 (g = 5) and P1 (g = 16) were interpolated as previously reported [c values of 0.1, 0.2 and 0.4 . Interestingly, our rough estimate showed little if any difference in RBE values based on the 10% survival dose when the criterion of 10–100  cells/colony was used; however, it should be noted that the smaller the threshold number of cells per colony used as a criterion, the less linear the relationship between the dose and the surviving fraction on the semilog plot Figure . Thus, nSecondary colonies derived from cells in primary colonies are reflective of the delayed RCD , and thiIn conclusion, our present framework for a colony formation assay is applicable to low- and high-LET irradiated cells, and provides a persistent RCD probability. Our findings suggest that the long-lasting RCD is an important determinant of the surviving fraction and its RBE.