Impairments in social skills are central to mental disease, and developing tools for their assessment in mouse models is essential. Here we present the SocioBox, a new behavioral paradigm to measure social recognition. Using this paradigm, we show that male wildtype mice of different strains can readily identify an unfamiliar mouse among 5 newly acquainted animals. In contrast, female mice exhibit lower locomotor activity during social exploration in the SocioBox compared to males and do not seem to discriminate between acquainted and unfamiliar mice, likely reflecting inherent differences in gender-specific territorial tasks. In addition to a simple quantification of social interaction time of mice grounded on predefined spatial zones (zone-based method), we developed a set of unbiased, data-driven analysis tools based on heat map representations and characterized by greater sensitivity. First proof-of-principle that the SocioBox allows diagnosis of social recognition deficits is provided using male PSD-95 heterozygous knockout mice, a mouse model related to psychiatric pathophysiology. A fundamental prerequisite for living in social communities is a highly complex set of social skills that governs interactions between individual members of a group. In consequence, impairments in these social skills, prominently prevalent in human psychiatric disorders such as autism and schizophrenia, have devastating consequences for individuals and society . Major eThis research has been hampered by the limited availability of reliable tools assessing complex social functions. Like humans, mice are capable of a rich set of social behaviors , but vir+/-) and male WT littermate controls was generated from PSD-95 heterozygous breeding pairs and was housed in large cages (60 cm × 38 cm × 20 cm) in groups of 17 mice of mixed genotypes. Food and water were provided ad libitum. The housing room was maintained on a 12 h light–dark cycle (lights off at 7 pm) at 20–22°C. All experiments were approved by the local Animal Care and Use Committee in accordance with the German Animal Protection Law.Wildtype (WT) mice were purchased from Janvier (C57BL/6JRj) or Charles River (C3H/HeNCrl and BALB/cAnNCrl). The age of the mice upon arrival ranged from 3 weeks  to 6 weeks . Mice were group-housed in standard cages , in rooms separated by gender (to avoid olfactory contact). PSD-95 heterozygous knockout mice  on C57BLExperiments on WT mice were conducted using groups of 10 mice  of the same gender and strain  as specified, aged 12–15 weeks at the beginning of testing. C3H mice were used as interaction partners (‘stimulus mice’) for all experiments, based on prior reports that this strain shows robust social interaction in a test situation . Stimulu+/+ mice and 20 PSD-95+/- mice, aged 16 weeks at the beginning of testing. C3H mice were again used as stimulus mice, and testing was performed during the light phase of the day (from 9 am to 6 pm) by an investigator blind to genotype. The experiment described here was part of a test battery conducted on this cohort of mice, the complete results of which will be reported elsewhere.Experiments on PSD-95 heterozygous knockout mice were conducted using a group of 14 PSD-95Figures 1A–E; Table 1) was constructed by the machine shop at the Max Planck Institute of Experimental Medicine. It consisted of a plastic ground plate, an outer ring of five rectangular removable boxes (‘inserts’) separated by fixed dividers of gray plastic, and a central open arena . Experimental mice were placed in the central arena, while stimulus mice were placed in the inserts in the outer ring. The inserts  consisted of 3 walls of gray plastic and 1 front slider of clear plastic, facing the center of the apparatus, with 31 holes (diameter 0.8 cm) to permit social interaction and exchange of odors between the experimental mice and the stimulus mice . The front slider was removable to facilitate cleaning of the inserts between mice. Within the central arena, a circular partition of white plastic  served to spatially and visually separate the experimental mice from the inserts containing the stimulus mice during the initiation stage of the test paradigm (see below).The SocioBox apparatus .An overhead video camera (Samsung) was mounted approximately 130 cm above the SocioBox apparatus. This camera was connected to a computer located in a separate room, enabling the experimenter to record the test session without being present in the room during testing. Videos were acquired with a temporal resolution of 25 frames per sec. An automated software  was used to track the experimental mouse and calculate the time spent in interaction with each stimulus mouse  and any parts of the walls that had been in direct contact with the experimental mouse (including the front sliders of the inserts) were cleaned in this manner.On the day of the test session , mice were exposed to the light conditions (10–15lux) of the experimental procedure in a separate room for approximately 30 min before testing. At the beginning of each test session, 6 assigned C3H stimulus mice were placed into 6 inserts and they stayed in these inserts throughout the test session. Five inserts were then transferred to the room with the SocioBox apparatus and were placed inside the apparatus. The 6th insert stayed in the separate room at the aforementioned light conditions until it was introduced to the apparatus during the recognition test phase. This procedure ensured that all stimulus mice spent equal time inside the inserts, since the activity of the stimulus mice within the insert decreased over time.Figure 1F). To begin the test session, the experimental mouse was placed into the central arena inside the white Plexiglass circular partition, which separated the experimental mouse from the stimulus mice spatially and visually. After 5 min of recovery (‘initiation stage’), the circular partition was lifted, and the experimental mouse was allowed to freely explore the stimulus mice in their inserts for 5 min (‘interaction stage’). At the end of exposure 1, the experimental mouse was removed from the apparatus and placed in the cage used to transport the mouse into the testing room. The central arena was cleaned as described for the habituation session, and the experimental mouse was then returned to the central arena inside the circular partition. Exposure 2 followed immediately and consisted of the same initiation stage and interaction stage. At the end of exposure 2, the experimental mouse was again removed from the apparatus and the central arena was cleaned as above. At this point, 1 of the stimulus mice  was removed with its insert, and the insert containing the 6th stimulus mouse  was introduced in its place. The other stimulus mice  remained in the same position throughout the testing paradigm to avoid potential interference of object location memory .The amount of time spent by the experimental mouse in each of the predefined zones during the 5 min of the interaction stage of each test was automatically calculated by the Viewer3 software. These data were aligned to the position of the S[ori]/S[new] stimulus mouse for purposes of statistical analysis and graphical representation.Figures 4A–K). A custom-written FIJI macro imported and then plotted a 1-pixel-diameter point of intensity 1 at each of the 7500 body coordinates originally generated by the Viewer3 software. This step produced an image stack consisting of 7500 frames for each of the animals. The frames of this stack were summed to generate 1 superimposed image containing all plotted coordinates an individual mouse had occupied during the 5 min of the interaction stage for each test . Geometrical rotations were applied to the individual animal data sets so that the S[ori]/S[new] stimulus mouse was always aligned in the top position. The 2-dimensional heat maps depicting an animal group were then made by adding up the images of the summed coordinates of the individual animals belonging to that group . Gaussian-weighted noise reduction filtering was applied with a 5-pixel radius that revealed 5 average locations the animals preferred during the testing period . The image contrast was enhanced by applying a polychromatic lookup table to more easily recognize potential hotspots signified by aggregations of pixels with similar values. In a next step, thresholding was applied that segmented out 5 regions preferred by the animals . The resulting binary images were used to generate a mask containing 5 regions of interests (ROIs) for each phase of the experiment . Finally, ROIs were applied to the original, non-filtered, summed images of each animal to quantify the number of pixels per individual ROI, where 25 pixels correspond to 1 sec . For the analysis of the PSD-95+/- experiment , heat map representations were first generated separately for each genotype and then summed to generate a combined binary image and mask for quantification.2-dimensional, spatial heat maps depicting average animal location were generated with the open source FIJI image processing package , using tFigures 5A–D). First, the body coordinates generated by the Viewer3 tracking of each animal were imported into the Calc spreadsheet software of the open source LibreOffice5 (libreoffice.org) software package. Geometrical rotations were applied to the individual animal data sets so that the S[ori]/S[new] stimulus mouse was always aligned in the top position. Next, the distance of the experimental mouse to the point of origin  was calculated for each of the recorded 7500 timepoints (25 frames per sec × 300 sec of recording). The resulting distances were imported into FIJI in order to generate a multi-column image in which each column consists of 7500 distance recordings of an individual animal organized in a temporal manner . In order to quantify these data, FIJI was used to generate histograms showing the frequencies with which individual distances occur . For the recognition test , 3 distance frequency populations emerged which corresponded to (i) the location of the new stimulus mouse S[new], (ii) the location of the constant stimulus mice immediately adjacent to the new stimulus mouse, i.e., S[-1] and S[+1], and (ii) the location of the constant stimulus mice opposite to the new stimulus mouse, i.e., S[-2] and S[+2]. To better visualize these 3 populations, a custom green–blue–red lookup table was created, where the colors correspond to the distances 0–8, 10–24, and 26–34 cm, respectively.To obtain a single, global visual representation of mouse behavior during each test phase, heat maps were generated depicting the distance of the experimental mouse from the center of the arena (exposure 1) or the S[new] stimulus mouse (recognition test) across the 5 min of the recording, using the male and female BALB/c data set as an example . The following parameters were considered for detecting outliers: Interaction time with each of the 5 stimulus mice  or social recognition index (SRI) . No outlier analysis was conducted for Figures 5G,H due to the large number of data points involved. Mice for which an outlier was identified in a given data set were excluded from further analysis for this data set. This affected the following data sets: BALB/c males, exposures 1 and 2 ; C57BL/6J females, recognition test ; BALB/c females, exposure 2 ; PSD-95 experiment, PSD-95+/+ mice , PSD-95+/- mice . Moreover, 1 mouse was excluded entirely from the male C57BL/6J data set due to technical issues (escape of a stimulus mouse during the recognition test). Data sets were then analyzed using repeated measures one-way ANOVA , repeated measures two-way ANOVA with gender as between-subjects factor and time as within-subjects factor , or two-tailed unpaired Student’s t-test .Statistical analysis was performed using the Prism software v5.0c (GraphPad). Data were first analyzed for outliers using the Grubbs test outlier calculator (based on the method of Table 1 for nomenclature), in which the mouse of interest  was placed in a central arena surrounded by a ring of 5 unfamiliar mice (‘stimulus mice’) . The stimulus mice were held in rectangular inserts facing the center of the chamber, with holes in the clear front panel to permit exchange of odors . The movement of the experimental mouse was recorded by an overhead camera , and the interaction time with each stimulus mouse , was calculated using an automated software .After a series of optimization experiments (see Supplement for details), we developed a circular behavioral chamber . In each phase, the experimental mouse was first placed into the central arena inside an opaque circular partition, which separated the experimental mouse from the 5 stimulus mice spatially and visually. After 5 min of exploration (‘initiation stage’), the partition was lifted and the experimental mouse was allowed to freely explore the stimulus mice in their inserts for 5 min (‘interaction stage’). For each experimental mouse, the identity and spatial position of the 5 stimulus mice was equal during exposures 1 and 2, while for the recognition test, 1 of the 5 stimulus mice  was replaced with an unfamiliar stimulus mouse . The other stimulus mice  remained in their inserts in the same position throughout the testing paradigm. To control for spatial bias effects, the position of the S[ori]/S[new] stimulus mouse within the SocioBox chamber was rotated for each new experimental mouse. At the end of each phase, the experimental mouse was removed briefly while the arena was cleaned, and then returned to the circular partition to begin the next phase.Using this experimental setup, we established a testing paradigm that produces robust social recognition in wildtype mice . Briefly, mice were first individually habituated to the apparatus for 3 consecutive days to eliminate any novelty-related confounds. On day 4, a test-session was conducted, consisting of 3 consecutive phases: Exposure 1, exposure 2, and recognition test . During exposure 1, experimental mice displayed substantial interest in the 5 stimulus mice , which decreased slightly during exposure 2 , likely due to habituation to these stimulus mice. During the recognition test, experimental mice spent even less time with the constant stimulus mice, but interacted significantly more with the new stimulus mouse . Based on the well-documented tendency of rodents to interact more with a novel object or individual than with a familiar one (Table 2). Together, our data indicate that C57BL/6J male mice can distinguish an unfamiliar mouse from at least 4 other newly acquainted mice, and that the paradigm presented here enables robust assessment of this social recognition.To validate our new paradigm, we first assessed social recognition in male C57BL/6J mice, commonly used as genetic background strain in animal models of psychiatric disorders , and since it extended the length of the procedure and somewhat distracted the mice, we did not include the slider exchange in our subsequent experiments.To confirm that our results were not confounded by olfactory cues left by the experimental mouse on the front sliders of the inserts via touching or nose poking, we repeated the experiment with a slightly modified protocol, which included a complete exchange of sliders for freshly cleaned ones during the recognition test. This procedure did not substantially affect performance in the recognition test , confirming the validity of our paradigm. Interestingly, the SRI for BALB/c mice was significantly higher than for C57BL/6J mice , indicating that male BALB/c mice show particularly pronounced social recognition skills under our conditions. In striking contrast, female mice of all 3 strains exhibited markedly lower preference for the new stimulus mouse , uncovering an essential gender difference in this behavior.We next asked whether our paradigm would be similarly suitable for other mouse strains. Male BALB/c and C3H mice also displayed substantial social interest in exposures 1 and 2 and significant preference for the new stimulus mouse in the recognition test . An important limitation of this zone-based method is that it requires prior assumptions regarding the behavior of experimental mice, and that it may either over- or underestimate the time spent in social interaction if the predefined zones do not accurately match movement patterns of mice. To overcome this limitation, we developed a new set of unbiased, data-driven analysis tools based on heat map representations.All of the above data originated from the Viewer3 software, which uses predefined spatial zones to quantify social interaction time . We identified 5 clearly preferred spatial locations in exposure 1 that corresponded to the location of the 5 stimulus mice , while a strong preference for the location of the new stimulus mouse was observed in the recognition test . These data were used to generate binary masks that defined 5 ROIs for subsequent quantification . Quantification identified a highly significant preference for the new stimulus mouse during the recognition test . Importantly, direct comparison of the data obtained using our new data-driven analysis with those obtained for the same mice using the conventional zone-based analysis  revealed a substantial improvement both in the statistical significance  and in the magnitude of the SRI . These findings confirm that our new data-driven analysis method markedly improves the sensitivity of our paradigm.First, we generated spatial heat maps showing the average localization of all mice in a given test session, using the male C57BL/6J data set as example . This analysis revealed that male BALB/c mice changed their position more often than females , which was also reflected in a higher average speed of locomotion . Male BALB/c mice also spent more time in close proximity to the new stimulus mouse during the recognition test, particularly in the first minute of the test , indicating that they are capable of very rapidly distinguishing between new and familiar stimulus mice.We also generated temporal heat maps that depict the distance of all animals from the new stimulus mouse for the entire recognition test duration, using the BALB/c data set as an example  . Quantification of these data reveals a significant reduction in the SRI using the data-driven analysis method, but not with the zone-based analysis . These data confirm that our SocioBox paradigm is capable of identifying social recognition abnormalities in mutant mouse models, and that the improved sensitivity obtained from the data-driven analysis method can be essential for uncovering subtle disease-related changes. It is also interesting to note that the SRI obtained for the WT mice from the PSD-95 experiment (PSD-95+/+ on a C57BL/6J background) is remarkably similar to that seen in the standard inbred C57BL/6J mice from the first experiment , despite substantial differences in breeding (bred in-house vs. purchased from Janvier) and housing (17 mice per cage vs. 5 mice per cage). This observation confirms that our SocioBox paradigm can reproducibly measure social recognition across a wide range of experimental conditions.To finally validate our new behavioral paradigm and analysis tools using a mutant mouse line relevant to psychiatric disorders, we tested mice with heterozygous deletion of PSD-95 (PSD-95+/-) . PSD-95 +/-) . Alterat+/-) , and mic+/-) . In contf PSD-95 . This laWe conclude that, using a combination of a novel circular testing apparatus, an easy-to-apply experimental paradigm and an advanced set of analysis tools, we have developed a robust and sensitive new behavioral assay to study social recognition in male mice. To our knowledge, this is first report of a paradigm that can assess the ability of mice to discriminate between more than 2 mice using a standardized testing apparatus. Current assays, including the commonly used 3 chambered social approach task , are lim+/- experiment; MM developed visualization and analysis tools; HE, DW, DK-B, MM, and ED analyzed experiments; OMS provided the PSD-95 knockout mouse line and gave conceptual advice; DK-B, DW, MM, and HE wrote the paper. All authors discussed the results and commented on the manuscript at all stages.HE conceived the study; HE, DK-B, and DW designed the study; DW performed experiments on all WT cohorts, supported by AR and DK-B; FD performed PSD-95The 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.


Peripheral arterial disease (PAD) is a clinical manifestation of atherosclerosis and mainly refers to elderly patients, having a negative impact on their functionality and quality of life. The findings of previous studies in HIV-infected patients have shown that cardiovascular risk is higher and PAD occurs more frequently than in the general population. There are also contradictory observations. Much less is known about the ankle-brachial index (ABI) value in asymptomatic HIV-infected patients. The aim of this study was to evaluate the prevalence of PAD and ankle-brachial index abnormalities as well as to determine risk factors related to the disease in a group of Polish HIV–positive patients.One hundred and eleven young to middle aged HIV–positive subjects and 40 noninfected subjects were enrolled into the study. Resting ABI measurements were performed and cardiovascular risk was analysed as well. Subgroups were created according to the ABI values: low (PAD), borderline, normal, high and altered ABI. Symptomatic PAD was observed in 2 HIV–positive patients, asymptomatic PAD was not diagnosed. The ABI value is lower and more varied, in 22.5% of the study group altered ABI values were found. Six subjects demonstrated borderline ABI, and 15 high ABI, including >1.4. In the control group no low or very high values were reported. A relation between low ABI and cardiovascular family history and between altered ABI and high–density–lipoprotein cholesterol (HDL–C) level was demonstrated.In young and middle–aged HIV–positive patients, symptomatic PAD prevalence is comparable to that observed in the overall population. Among asymptomatic patients PAD is not reported. The ABI value in HIV–positive patients is more varied compared to the HIV–negative subjects; the altered ABI shows a strong relation with low HDL–C levels and metabolic syndrome. Due to constant development of antiretroviral therapies and significantly prolonged survival in the population of HIV–positive patients, a higher risk for cardiovascular diseases and increased atherosclerosis progression are observed together with infection-related comorbidities The aim of this study was to evaluate the prevalence of PAD and ankle-brachial index abnormalities as well as to determine relation between the ankle-brachial index outcome and cardiovascular or potential risk factors in a group of Polish HIV-positive patients.All the performed tests except blood sampling during the study were noninvasive. Study protocol was assessed by the ethics committee and the authors of the project obtained the local Bioethic Committee's approval for the study to be conducted. All participants provided their written informed consent to participate in the study, according to the Helsinki Declaration.The study was conducted at the area of Lower Silesia, located in the south-western region of Poland. It is one of the most urbanized and the richest regions of Poland. At the time of the study the region's population counted 2.9 milion inhabitants, which represented 7.54% of the Polish population. The median age of the population in the region was 38.9 years It was an observational, cross-sectional study with participation of two groups: the study group of HIV- infected patients and control group of uninfected, healthy people – residents of the same region. The study was conducted for 10 months since May 2011 to February 2012.The study was conducted in two groups:th of December 2012 HIV infection was reported in 16314 of Polish citizens and of residents of another citizenship. Among them AIDS (acquired immune deficiency syndrome) was diagnosed in 2848 individuals and 1185 died The consecutive, routinely scheduled HIV-positive patients attending the Acquired Immunodeficiency Syndrome Outpatient Clinic who fulfilled the inclusion and exclusion criteria were invited to participate in the study. One hundred twenty one patients agreed to participate, of whom 5, based on exclusion criteria were not included  and 5 persons missed the study visit. One hundred eleven patients (average age 41.1±9.4) were included in the study. The HIV infection characteristics of the patients living in the Lower Silesia region in which our study was conducted are similar  and representative of the entire country. The reported number of HIV-infected people in the region is about 2000. In this out-patient department 1115 patients have been registered. During the study period 750 patients had appointments to attend the clinic. In Poland since 1985 (HIV testing introduction) till the 31The control group included HIV-negative age- and gender-matched healthy subjects recruited contemporaneously  from the study group region, not meeting the project's clinical and laboratory exclusion criteria. These healthy subjects were recruited at random through two general practices in the region's capital and in the province. Seventy one subjects agreed to participate, of whom 31 were not included - two because of positive HBs antigen, 18 because of data in the medical history indicating the occurence of cardiovascular disease or significant chronic disorders and 11 persons missed the study visit). This control group was created to compare the ABI findings between the groups.The planned study group size was 120 patients, with a control group of 40 healthy persons. The actual study group included 111 patients and the control group 40 individuals.The inclusion criterion for the study group was diagnosed HIV infection in patients aged 20–60 years. The exclusion criteria were as follows: a currently diagnosed acute medical condition, currently diagnosed AIDS, creatinine levels of above 2 mg%, and over 5 times higher aminotransferase levels (upper limit 40 IU/L). HIV–positive subjects started the study with a known immunological and virological status with regard to both HIV infection and hepatitis B and/or hepatitis C virus co-infection.The inclusion criterion for the control group was a HIV–negative result in generally healthy patients aged 20–60 years. Cardiovascular disease, significant chronic disorders and all exclusion criteria as for the study group excluded candidates from the control group. The characteristics of HIV infection status of the study group are presented in Among the major cardiovascular risk factors, tobacco smoking, hypertension and family history of cardiovascular diseases were the most representative in the study group. The assessment of body posture revealed a significantly lower body mass index in HIV–positive participants compared to the control group. All cholesterol fraction levels were significantly reduced, triglyceride and homocystein levels were higher in the study group. Despite the differences, the general cardiovascular risk was similarly low in both groups .The patients underwent the following vascular assessments: medical history, including medical records and questions about cardiovascular risk factors and events, intermittent claudication and vascular reconstructive procedures. With regard to HIV infection-related data, the following were assessed: duration of infection, transmission route, a history of AIDS, hepatitis B  or hepatitis C (based on HCV RNA presence) co-infections, treatment duration and applied antiretroviral pharmacotherapy, current CD4 and nadir CD4 cell counts as well as HIV RNA and HIV RNA zenith titres. Historical data such as HIV infection duration, CD4 T cell count nadir or history of AIDS were abstracted from the available patients health reports.The pulse rates of peripheral arteries in the lower limbs and murmurs over large arteries were assessed. In the absence of a pulse, additional arterial ultrasound scans were performed. The following parameters were also obtained: the body mass index (BMI) and the waist-hip ratio (WHR). Blood pressure measurements were performed according to the standard practice. Hypertension was diagnosed if the patient had a history of diagnosed and pharmacologically treated hypertension or based on two pressure measurement results equal to or above 140/90 (at least grade one according to WHO). A family history of cardiovascular diseases was determined based on the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria The ABI was assessed using a hand-held continuous wave Doppler device (Doppler SmartDop 45) with an 8 MHz probe. The test was performed in a properly heated room after 5 minutes of rest in the supine position. A pressure cuff was placed on both arms then bilaterally above the ankles. The probe was placed at the cubital fossa behind the medial malleolus and on the dorsal foot for pulse detection. After the cuff was inflated to 20 mm above the audible pulse signal, it was gradually emptied and the pressure value was recorded when the first pulse signal was detected. The systolic blood pressure was determined in both arms, and the ankle systolic blood pressure was determined for the right and left posterior tibial and dorsalis pedis arteries. The ABI was determined by using the higher of the two values from either the posterior or dorsalis pedis artery for each leg and the higher of the two brachial readings. The qualitative statistical analysis of ABI was conducted by choosing the higher or lower abnormal values per patient if both values were abnormal: high or low; if the ABI value was normal in both legs then the lower value was chosen. If a patient had an abnormal value in one leg then we chose this value. Additionally, ABI values measured for the left and right legs of the study group were compared against a control group as quantitative variable.Symptomatic PAD was diagnosed in patients with intermittent claudication and an ABI value lower than or equal to 0.9. Intermittent claudication was diagnosed based on the Trans-Atlantic Inter-Society Consensus II (TASC II) definition – muscle discomfort in the lower limb, which is reproducibly produced by exercise and relieved by rest The ABI was categorised by its values; based on the standard ABI categories, the following patient s were distinguished:A subgroup with low ABI ≤0.9, indicating PAD, n = 2.A subgroup with borderline ABI 0.91–0.99, n = 6.A subgroup with ABI <1.0– combined subgroups 1+2, n = 8.A subgroup with normal ABI 1.0–1.3, n = 88.A subgroup with high ABI >1.3, n = 15.A subgroup with ABI >1.4, distinguished from subgroup 5, n = 5.LINK 1). The differences in occurrence of cardiovascular risk factors between subgroups 3, 4 and 5 were compared. The ABI findings in the asymptomatic HIV-positive group were compared to those obtained in the control group.Also, a group with altered ABI (subgroups 1+2+5) was created and statistically compared to subgroup 4 . Due to the insufficient sizes of subgroups 1, 2 and 6, they were not subjected to a comparative statistical analysis with the other subgroups . In both patients the ABI test confirmed PAD; an ultrasound scan revealed femoropopliteal occlusion. The patients differed regarding duration of infection and ARV therapy; at the time of the study they showed a good immune status and low viral load. Besides age and gender many cardiovascular risk factors were observed in both patients including heavy smoking, lipid disorders, a family history of cardiovascular diseases and in 1 patient, mild thrombocytosis and hyperhomocysteinaemia. In 1 patient there were indications for endarterectomy of the internal carotid artery (more than 80% stenosis); the other patient underwent femoral thromboendarterectomy. Both patients demonstrated higher than 0.9 mm cIMT values. The remaining patients (n = 109) were asymptomatic. There were no cases of low ABI values suggesting latent PAD.Symptomatic PAD, manifested by intermittent claudication, was diagnosed in 2 HIV-positive male patients  or posterior tibial artery (1) was observed; additional ultrasound scans of these arteries revealed normal patency and a typical triphasic flow spectrum.The ABI median in HIV-positive group was significantly lower within the normal range and ABI values were more diversified, including abnormally high or low values compared to the HIV-negative subjects . In the (LINK 2).The statistical analyses focusing on the occurrence of cardiovascular risk factors as well as infection-related conditions in the subgroups showed that among HIV-positive patients with low ABI values (ABI <1), a family history of cardiovascular diseases is more frequently observed compared to patients with normal or high ABI values (p = 0.03). CRP concentration levels were higher in those patients, although this difference is not statistically significant . In the LINK 3).A comparison of the subgroup with altered ABI and that with normal ABI showed that within this category higher LDL and non-HDL cholesterol levels, lower HDL cholesterol levels, higher CRP levels and more frequent cases of metabolic syndrome are observed, although these findings are not statistically significant . We did not find any relation between the ABI alterations and the status or course of HIV infection nor the duration of antiretroviral treatment. Previous studies have shown that peripheral arterial disease diagnosed on the basis of the resting ABI measurement occurs more frequently in HIV-positive patients than in the general population In the studied group with many cardiovascular risk factors the most typical were smoking, lipid disorders, followed by family history of cardiovascular diseases and hypertension. The prevalence of risk factors in the adult Polish population shows a different pattern, with lipid disorders being the strongest, followed by arterial hypertension and eventually by smoking A current valid and widely used PAD diagnostic method is the resting ABI test In the presented cohort, young and middle-aged adults were included, with a considerably higher number of male patients. This is the first study in Poland focused on PAD occurrence in HIV-positive patients. The prevalence rate of symptomatic PAD at the stage of intermittent claudication confirmed by the ABI test was 1.8% and only referred to two middle-aged (52 on average) men with intermittent claudication and many cardiovascular risk factors. In both patients, atherosclerotic lesions in other vascular areas and high cIMT values were observed.The prevalence of symptomatic PAD in the studied group of HIV-positive people was the lowest when compared to previous studies, where it was assessed as 2.7, 5.1 and 8.7% According to TASC II the prevalence rates of intermittent claudication would appear to increase from about 3% in patients aged 40 to 6% in patients aged 60 years in the general population Among HIV-positive patients with ABI <1.0, there were more cases with a family history compared to patients with ABI >1.0. The study conducted by Periard et al. showed a relation between the family history and PAD in HIV-positive patients in addition to other conventional risk factors  and low CD4 cell counts In the overall population, asymptomatic PAD prevalence is 3 to 4 times higher than that of symptomatic PAD Based on post-exercise ABI measurements, Qaqa et al. diagnosed PAD in 26.5% of HIV-positive patients in an ethnically different and older patient group than ours The median value of ABI in HIV-positive patients was significantly lower  and more varied compared to the HIV-negative subjects. Borderline ABI values were observed in 5.5% of the study subgroup of asymptomatic HIV-positive patients (in the whole group – 5.4%). In the study conducted by Jang et al., this proportion was higher: 18% in a cohort of HIV-positive patients older by 7 years on average Altered high ABI >1.3 (above 1.4 in particular) is considered as a sign of rigidity and noncompressibility of lower limb artery walls. It is mostly observed in diabetic patients with media calcification as well as in patients with metabolic syndrome, and it is associated with conventional risk factors. Similarly to the low values, diagnostic and prognostic significance is also attributed to high ABI values Very high ABI >1.4 values were reported in 4.6% of the study group. According to other authors, ABI >1.4 prevalence rates were 0.5 to 7.1% in the HIV-positive groups, which was affected by smoking as well as by being under- and overweight In addition to the above observations, patients with altered (low or high) ABI values more frequently showed signs of metabolic syndrome, higher CRP, LDL-C, non-HDL-C levels and lower HDL-C levels compared to patients with normal ABI values and show a strong relation to low HDL-C level and metabolic syndrome. These findings are consistent with the results obtained by Jang et al. with regard to CRP levels In the present study we did not find any relation between the ABI alterations and the status of HIV infection or of antiretroviral treatment. The results are consistent with Sharma's reports that precluded an impact of the infection status on ABI values The prevalence rate of PAD in our study group was extremely low; however, nearly one in five asymptomatic, young or middle-aged HIV-patients showed various ABI alterations (19.3% of asymptomatic subjects). Our findings and other authors' reports indicate the need for PAD screening in HIV-positive patients.The resting ABI measurement, as in the general population is the method of choice This study has some limitations. The most important limitation was the relatively small study group although it represented 14.8% of the patients attending the Outpatient Acquired Immune Disorders Clinic and in terms of the characteristics of HIV infection was representative of the entire HIV-positive population in Poland. After dividing the group into subgroups depending on the value of ABI, we had to omit the smallest subgroups in the statistical analysis. Due to the small size of the control group, we could not achieve adequate power of our statistical analysis, and many parameters were on the border of statistical significance. There was no possibility for comparison of our results with another contemporary analysis in the Polish general population, with only data from the 1980s available. Accordingly, in the discussion of our results, we compared them with the results of the most important worldwide research concerning the prevalence of PAD in the general population.In the group of young and middle-aged Polish HIV-positive patients, symptomatic PAD prevalence is comparable with that observed in the overall population and is lower than in the other HIV-positive studies as well. Among asymptomatic patients, PAD is not observed. The ABI value is significantly lower and more varied compared to the HIV-negative subjects. Compared to the gender- and age-matched asymptomatic noninfected group, altered borderline or high ABI >1.4 values tend to be more prevalent in the asymptomatic HIV-positive subjects. Low ABI <1.0 values are strongly related to a family history of cardiovascular diseases. Abnormalities of ankle-brachial index are associated with low high-density lipoprotein cholesterol level and metabolic syndrome. The relationship between observed ABI alterations and the status of HIV infection or antiretroviral treatment needs further studies.


We report an exceptional complex chromosomal rearrangement (CCR) found in three individuals in a family that involves 4 chromosomes with 5 breakpoints. The CCR was ascertained in a phenotypically abnormal newborn with additional chromosomal material on the short arm of chromosome 4. Maternal karyotyping indicated that the mother carried an apparently balanced CCR involving chromosomes 4, 6, 11, and 18. Maternal transmission of the derivative chromosome 4 resulted in partial trisomy for chromosomes 6q and 18q and a partial monosomy of chromosome 4p in the proband. Further family studies found that the maternal grandmother carried the same apparently balanced CCR as the proband's mother, which was confirmed using the whole chromosome painting (WCP) FISH. High resolution whole genome microarray analysis of DNA from the proband's mother found no evidence for copy number imbalance in the vicinity of the CCR translocation breakpoints, or elsewhere in the genome, providing evidence that the mother's and grandmother's CCRs were balanced at a molecular level. This structural rearrangement can be categorized as an exceptional CCR due to its complexity and is a rare example of an exceptional CCR being transmitted in balanced and/or unbalanced form across three generations. Constitutional complex chromosomal rearrangements (CCRs) usually involve at least two chromosomes and three breakpoints with varied outcomes (simple or 3-break insertions are excluded) –4. These Three-way exchange with three breaks from three chromosomes: most three-way CCRs are familial and are usually transmitted through the mother. They are the most common type of CCRs. (2) Double two-way exchange with a coincidence of two separate simple reciprocal translocations: the double two-way CCR is not a true CCR and might be described as a double or a multiple rearrangement. (3) Exceptional CCRs with more complicated rearrangements: most exceptional CCRs are de novo rearrangements and they are more commonly associated with abnormal phenotype.The phenotype of the CCR carrier varies from normal to abnormal with congenital abnormalities and/or intellectual disability. The likelihood of an abnormal phenotype increases with the number of breakpoints associated with the de novo, apparently balanced CCR (BCCR) –7. ApproMost familial transmissions of CCRs are through the mother , 6. Phen5P1A4 from 2 marriages. The four previous pregnancies ended in abortions at around 20 weeks of gestation. The maternal grandmother of the proband  was the 8th of 16 normal phenotype siblings. Her 4th child, who died at 8 months old without any specific causes, was born prematurely with normal phenotype. The great grandmother from the mother's lineage  has 16 children with no miscarriage history. The proband's aunt  has 5 phenotypically normal sons and another aunt  was not involved in this study . Her weight was 1630 grams and length 38 cm. The proband  was delivered from an uneventful, full term pregnancy of a 30-year-old mother with an obstetrical status of Gis study . PatientCytogenetic investigations were carried out on 20 metaphase cells of phytohaemagglutinin- (PHA-) stimulated peripheral blood cultures using standard procedures, and high resolution GTL banding was performed. Analysis undertaken on metaphase chromosomes from the proband at the 550-band level according to ISCN 2009  showed tTo confirm the BCCR karyotyping result, we performed whole chromosome painting FISH (WCP FISH)  using probes for chromosomes 4, 6, 11, and 18 on chromosome spreads from the mother and grandmother of the proband, using standard techniques. The hybridisation patterns were consistent with the karyotyping results .  FigureTo investigate whether the BCCR was balanced at a molecular level, we analysed DNA from the proband's mother using Affymetrix CytoScan HD microarray , with interpretation based on the NCBI36/hg18 (March 2006) human reference sequence. The microarray result showed no clinically significant genomic imbalance. In particular, there was no evidence for copy number imbalance on chromosomes 4, 6, 11, and 18 in the regions of the translocation breakpoints. Therefore, the CCR appeared to be balanced at the effective resolution of this array (approximately 25–50 kb).Complex chromosome rearrangements like the one segregating in this family are categorized as exceptional CCRs, which are the most complicated form of CCRs. This complexity results in a greater potential for producing unbalanced gametes during meiosis. A successful pregnancy is rare because the BCCR carrier has a risk for an abnormal conception due to either malsegregation of derivative chromosomes or generation of recombinant chromosomes . AccordiWCP FISH was performed to confirm the chromosome rearrangement identified by conventional karyotyping. WCP FISH is a highly sensitive and specific technique that can be used to identify both numerical and structural chromosomal aberrations , 17, as Whole genome microarrays have the ability to detect unbalanced de novo and inherited chromosomal abnormalities smaller than 3–5 Mb in size, which is below the resolution of conventional karyotyping , 23, 24.A minimum of 70 unbalanced gametes are theoretically possible due to 4:4, 5:3, 6:2, and 7:1 segregations from an octavalent in the case of a CCR involving five breakpoints in four chromosomes . The risFamilial transmission of the BCCR in our pedigree was through female carriers. This is supported by previous reports that record familial transmissions occurring mainly through female carriers , 6, 21. Due to the complex nature of BCCRs, genetic counselling will always be difficult. The reproductive risk is very specific for each carrier, and the precise risk may be impossible to establish . ReproduIn conclusion, the proband's abnormal clinical presentation was caused by inheriting a derivative chromosome 4, which is an unbalanced form of the BCCR carried by her mother. Although the possibility of having a normal child is greatly reduced, a daughter has inherited the CCR in its balanced form, and another daughter has inherited normal chromosomes. This case is instructive in demonstrating that an exceptional BCCR can be inherited in its full balanced form to the next generation.


The incidence of chronic diseases in low- and middle-income countries is rapidly increasing both in urban and rural regions. A major challenge for health systems globally is to develop innovative solutions for the prevention and control of these diseases. This paper discusses the development and pilot testing of SMARTHealth, a mobile-based, point-of-care Clinical Decision Support (CDS) tool to assess and manage cardiovascular disease (CVD) risk in resource-constrained settings. Through pilot testing, the preliminary acceptability, utility, and efficiency of the CDS tool was obtained.The CDS tool was part of an mHealth system comprising a mobile application that consisted of an evidence-based risk prediction and management algorithm, and a server-side electronic medical record system. Through an agile development process and user-centred design approach, key features of the mobile application that fitted the requirements of the end users and environment were obtained. A comprehensive analytics framework facilitated a data-driven approach to investigate four areas, namely, system efficiency, end-user variability, manual data entry errors, and usefulness of point-of-care management recommendations to the healthcare worker. A four-point Likert scale was used at the end of every risk assessment to gauge ease-of-use of the system.The system was field-tested with eleven village healthcare workers and three Primary Health Centre doctors, who screened a total of 292 adults aged 40 years and above. 34% of participants screened by health workers were identified by the CDS tool to be high CVD risk and referred to a doctor. In-depth analysis of user interactions found the CDS tool feasible for use and easily integrable into the workflow of healthcare workers. Following completion of the pilot, further technical enhancements were implemented to improve uptake of the mHealth platform. It will then be evaluated for effectiveness and cost-effectiveness in a cluster randomized controlled trial involving 54 southern Indian villages and over 16000 individuals at high CVD risk.An evidence-based CVD risk prediction and management tool was used to develop an mHealth platform in rural India for CVD screening and management with proper engagement of health care providers and local communities. With over a third of screened participants being high risk, there is a need to demonstrate the clinical impact of the mHealth platform so that it could contribute to improved CVD detection in high risk low resource settings. Diseases that may affect the heart, arteries and circulation of the blood are collectively referred to as Cardiovascular disease (CVD). This can include ailments such as stroke, coronary heart disease, atherosclerosis, or peripheral arterial disease  and accoWith 5.4 billion mobile phone subscriptions just in the developing world today , the penThere is substantial literature discussing CVD risk prediction and well-cited articles and reviews -14 have In this study, we have designed and pilot tested a multifaceted healthcare worker intervention utilising an mHealth platform that comprises a clinical decision support tool for CVD risk assessment and management in rural India. The outcomes focussed on a preliminary evaluation of the tool for utility, effectiveness and acceptability by the ASHAs and community participants in this setting in order to inform large-scale evaluation.Data on CVD and associated risk factors were collected through an mHealth system consisting primarily of a client side mobile application and server side electronic medical record. The mobile application was compartmentalised into four steps, which enabled health workers to conveniently assess rural participants for CVD risk and disseminate appropriate recommendations. Table Presence or absence of diabetesGenderSmoking statusAgeSystolic blood pressure (SBP)Total blood cholesterol (TC), if known.The World Health Organisation/International Society of Hypertension (WHO/ISH) provide colour-coded charts  which weTreatment and recommendations for the management of CVD were based on Indian national and international guidelines. The prediction and management applications were stringently validated in two stages. The first stage was code validation, where the algorithm was coded by a physician in SPSS, and by an engineer as an Android application. This was run on a large external dataset from the Andhra Pradesh Rural Health Initiative   decision support to both ASHAs and physicians for the management of CVD. This included three categories - general recommendations, referral, and treatment recommendations and were based on international and national guidelines ,19. GeneAn important factor in the success of any technology-based intervention depends on how well it can fit within the needs of the users and the environment . In our Conventional methods of design and development relied on traditional “requirements engineering” , where tsystem requirements  with user requirements . Secondly, we performed phases of prototyping and user assessment  could not be gauged thoroughly through a needs assessment. Therefore, the agile development approach was followed in our study to iteratively design prototypes and elicit feedback from the end-users. However, our approach differed from conventional practice since the end users had little or no experience with using information and communication technology and could not drive the design. To overcome this, firstly we employed a multidisciplinary team comprising an engineer, local physician, sociologist, and an expert physician to balance One touch navigationSince the end user base had little or no experience, touch errors were common and frequent. The mobile application’s design was such that ASHAs could navigate through the majority of the content using a single button. Care was taken to ensure idiosyncrasies of the mobile-based device that interfered with workflow were minimal. For example, in certain cases the virtual keyboard was minimised subsequent to user input.CVD Risk Projection meterThe application had a visual risk projection meter  device (Stabil-O-Graph ) was useSome of the key features that were incorporated through our agile approach included: The CDS-based CVD risk assessment and management tool was built for devices running Android 4.0 and above, and supported both Telugu  and English. The application was optimised to run on a higher-end version of a low-cost tablet (£100) for use by ASHAs, and a Samsung Galaxy 7-inch tablet (£160) to be used by physicians. Low-cost tablets were preferred for two reasons. The first was to assess if they could perform adequately in our setting so as to inform cost-effectiveness of the intervention. The second reason was the high healthcare-worker:doctor ratio in resource-constrained regions which required cost-effective tablets (since they can be replaced more easily if damaged or stolen).The mobile based CDS tool was field tested by 11 ASHAs who performed door-to-door screening of community participants in 3 villages in rural Andhra Pradesh, India. Each ASHA was to screen approximately 20 participants in one month for high risk and a convenience sampling method was followed, where participants could be selected based on their accessibility and proximity to the ASHAs. The ASHAs were trained for one week to use the CDS tool and tablet. The data from each participant screened by the ASHA were uploaded to a secure server hosting an electronic medical record system OpenMRS ,27). Dec. Dec27])A four point Likert scale  was usedth procedure would be taken as our sample for bootstrapping. The 95% CI for the mean was subsequently estimated and plotted individually for the three ASHAs. This is useful to understand how variable the ASHA’s own procedure times can be and with sufficient samples (of risk assessment procedures), we can reliably estimate how long an ASHA can take and how much training is needed until she is proficient to use the CDS tool .The variability in end-user usage was analysed in this study to gauge the performance of ASHAs. This was done in order to identify the stage at which additional support or training was needed if necessary. Data from the three ASHAs, representing all the ASHAs in performance, were analysed individually to obtain an estimate of their mean procedure time over the course of the pilot study. Bootstrapping was performed considering all samples available up until and including that procedure. This was performed to investigate bias towards uneven sampling. For example, if we are to estimate the mean completion time and confidence interval (CI) for an ASHA who has performed 10 risk assessments, her procedure times until and on the 10The ASHAs manually entered the glucose values into the tablet, a process susceptible to errors. However, to assess the extent of errors, the blood glucose values stored in the glucometers were downloaded and compared with those values entered by the ASHA in the tablet during risk assessment. Care was taken to ensure that the glucose readings being compared were taken at the same time. This was performed by obtaining timestamps from the analytics framework in the CDS tool and the glucometer’s memory.In-depth qualitative interviews with the ASHAs and focus group discussions were also undertaken to identify barriers to the adoption of mobile technology. These are detailed in the article by Raghu et al.  and are Ethics: The study was approved by the ethics committee of Centre for Chronic Disease and Control, India and the University of Sydney, Austrlia (registration: CTRI/2013/06/003753). Informed, written consent was obtained from all participants contributing data in the study.HealthTracker) as a clinical decision support tool to screen 65 in-patients (mean age of 55.3 ± 11.7 years) who visited their clinic . Although physicians used the mobile application, the results presented in this paper focuses entirely on usage by the ASHAs.A total of 227 individuals (mean age of 51.4 ±13.1 years) were screened by 11 ASHAs, while 3 PHC physicians independently used the mobile application , 20 (median number of assessments in this study), and 16 (lowest number of assessments amongst ASHAs in our study) risk assessments respectively.The three distinct ASHAs chosen for detailed usage analysis had a mean age of 29 ± 2 years and had the experience of using a mobile phone at the time of this study. We shall refer to the three ASHAs as Figure System Efficiency The overall time taken for screening the community participant’s CVD risk over the duration of the study is shown in Figure npB1, npM1, and npL1 took 00:27:28 (IQR 00:14:05), 00:24:20 (IQR 00:12:12), and 00:33:53 (IQR 00:32:41) respectively. A decreasing trend in completion time as users performed more procedures is observed.The distribution of time taken for each step of CVD risk assessment for all ASHAs is shown in Figure npB1 had a usage rate of 61% (17/28 procedures) with mean BP acquisition time of 00:05:20 (σ = 00:03:36) while npM1 had a usage rate of 50% (10/28) with mean BP acquisition time of 00:07:06 (σ = 00:02:36). ASHA npL1 had a usage rate of 37% (6/16) with mean BP acquisition time of 00:08:24 (σ = 00:02:56). The ASHA who used Bluetooth the most (npB1) for transferring BP readings had the lowest mean BP acquisition time. However, the ASHA with most experience (npM1) showed more consistency when acquiring BP.The number of times the ASHA chose Bluetooth transmission over manual transmission (or the Bluetooth BP device usage rate) was analysed and is shown in Figure th procedure, Bluetooth usage rate was 40% for npB1, 50% for npM1, and 10% for npL1 while after the 10th procedure (midway between their ‘assigned’ target of 20 procedures as previously described in Section ‘Field testing’), the usage rates were 65%, 44%, and 80% respectively.Before the 10User variability From Figure npM1 is consistent and has the most narrow CI  while npL1 has the widest CI  for the estimated mean procedure time towards the end of the study. The three ASHAs show less variability in procedure time over the course of the pilot study (when they complete more risk assessments).npL1 has the largest estimate with mean time 00:53:02, 95% CI . ASHAs npM1 and npB1 have comparable estimate of mean times but the latter has a much wider 95% CI .In the initial stages of the pilot study , the bootstrapped estimate of the mean procedure times for all ASHAs are high with wide CIs. ASHA npL1 - mean time 00:43:31, 95% CI ; npM1 - mean time 00:26:28, 95% CI ; npB1 - mean time 00:35:18, 95% CI ).At the end of 10 procedures (or approximately mid-way through the assigned target of 20 assessments for the ASHAs), the estimated mean time and CI continues to decrease .When 15 procedures have been completed by the ASHAs, the estimated mean stabilizes while CI continues to become narrower  and there has not been an appreciable increase in the number of procedures the ASHA had performed. npM1, having completed 5 more procedures since the last milestone, finishes with a slightly lower estimated mean procedure time 00:24:42 with narrower 95% CI . npB1 had finished 13 procedures more than the previous milestone and ends with a lower estimated mean time 00:31:21 with 95%CI .At the end of the pilot study, Errors in manual entry of Blood Glucose measurements Out of 227 patients assessed, 14 patients had an erroneous value of glucose level entered. The median error was 9.55 mg/dL with IQR 35.75 mg/dL (0.53 mmol/L with IQR 1.99 mmol/L).Usefulness of point-of-care management recommendations for ASHAs Table An important component of the mobile based CDS tool is the referral indication .The CDS tool was designed and developed using the agile development methodology with the close engagement of the ASHAs and physicians. The process was repetitive until the ease of use was confirmed by the end-users and this stage became the final version of the CDS tool. A number of key features were added through this process. The use and integration of open-source telemedicine platforms such as OpenMRS and SanaMobile were intended to increase interoperability. This is important because in the area of mHealth application development, there exists silos of numerous non-interoperable mHealth applications which are likely to increase the risk of duplication in effort and fragmentation of purpose. The risk profiles of screened participants in the three villages in Andhra Pradesh had a bimodal risk distribution, where the participants were mostly either low risk or high risk. The number of participants at high risk of CVD was almost one third of the screened sample. There was a decrease in median completion time with more number of procedures performed. This indicated the ASHA’s increased familiarity with the process as well as provides evidence for expected or optimal usage and actual usage. The median procedure time for ASHAs was 21 minutes for a complete CVD risk assessment with Step-3 (risk factor acquisition) taking maximum time . Acquisition of three BP measurements, on its own, took approximately 7 minutes. This could be useful to assess the maximum number of community participants that can be screened by an ASHA given her usual commitments towards antenatal care.npB1, npM1, and npL1) from four parameters that we have analysed - total number of risk assessments, median completion time and 95% CI, use of Bluetooth functionality, and rate of disseminating management recommendations to participants. npB1 may be classified as one of the better performing ASHAs in the pilot study as, firstly, she performed the highest number of risk assessments amongst all ASHAs. Secondly, she had the highest usage rate of Bluetooth functionality and lowest mean BP acquisition time. Thirdly, she had the highest rate of disseminating management recommendations although her mean procedure time and 95% CI was fairly average compared to other ASHAs. npM1 showed more consistency than any other ASHA in all aspects of her performance. The number of assessments she completed was exactly the same as the approximate target of 20 procedures prescribed for all ASHAs at the start of the pilot. With regard to the automated Bluetooth feature, the usage rate was almost the same before the ASHA’s 10th procedure (50% usage rate) and after her 10th procedure (44% usage rate). With the lowest estimated mean time and smallest 95% CI as well as an approximately average rate of disseminating management recommendations, ASHA npM1 was the most consistent performer. npL1 performed the fewest assessments, had the highest estimated mean time with a wide 95% CI, low dissemination rate of management recommendations, and the lowest usage rate of the automated Bluetooth feature. However, with regard to Bluetooth usage, we observe that even though only a single attempt (or 10%) was made before her 10th procedure, her usage rate increased to 80% thereafter. Though this may indicate a longer learning curve, ASHA npL1 may be identified as one that would need additional attention or performance monitoring. By recording user interactions with the mobile application, we could thus gauge the end-user’s behaviour and effectiveness of the tool’s features such as the rate of dissemination of point-of-care CVD management recommendations.It is interesting to compare the usage patterns of the three ASHAs . ASHAs also recorded difficulties with operation of the BP monitor. Given the current overall adoption rate of 55%, a less sophisticated BP monitor with faster acquisition times may increase adoption and optimise time taken for Step 3. The errors reported from manual data entry during blood glucose measurement demonstrate that transcription and transposition errors were likely and the erroneous values had a wide range. With regard to POC decision support, communication through the risk meter found the lowest adoption in Table By involving the end-users iteratively as well as acquiring information through data analytics, we minimise social desirability bias ,35, an iThe main limitation in this pilot study was the limited sample size. However, this was not designed to be representative. With respect to technical improvements, apart from robust software-engineering, we think it is also necessary to ensure appropriate patient identification  through advanced pattern matching methods which may rely on a combination of patient demographics and risk factors. This would ensure that there is no inadvertent misidentification of patients which may be harmful if treatment regimens are prescribed to the incorrect patient. Infrastructural barriers observed in our pilot study included power constraints as power supply was limited to fixed times of the day, and so the low-cost tablets had to be charged frequently or would not function optimally.In this study, we used an evidence-based CVD risk prediction and management tool to develop an mHealth platform in rural India for CVD screening and management with proper engagement of health care providers and local communities. Field evaluation found the platform to be acceptable and feasible for use. Detailed usage patterns could be gauged from analysing the interaction pattern of ASHAs with the mobile application. With over a third of screened participants being high risk, there is a need to demonstrate the clinical impact of the mHealth platform so that it could contribute to improved CVD detection in high risk low resource settings. With further technical improvements such as robust patient registration, we will conduct a two year cluster randomised trial covering 54 villages in southern India to evaluate the clinical impact of this mHealth platform.


Since 2012, the Centers for Disease Control and Prevention has aired a national tobacco education campaign to encourage quitting, Tips From Former Smokers (Tips), which consists of graphic antismoking advertisements that feature former cigarette smokers. We evaluated phase 2 of the 2014 campaign by using a nationally representative longitudinal cohort.Cigarette smokers who participated in a baseline survey were re-contacted for follow-up  approximately 4 months later, immediately after the campaign’s conclusion. The primary outcomes were incidence of a quit attempt in the previous 3 months, intention to quit within 30 days, and intention to quit within 6 months during the postcampaign period. We used multivariate logistic regression models to estimate the odds of each outcome. We also stratified models by race/ethnicity, education, and mental health status. Postcampaign rates of quit attempts, intentions to quit, and sustained quits were also estimated.P = .03) among baseline smokers and intentions to quit within the next 6 months  among current smokers at follow-up. The Tips campaign was associated with an estimated 1.83 million additional quit attempts, 1.73 million additional smokers intending to quit within 6 months, and 104,000 sustained quits of at least 6 months.Exposure to the campaign was associated with increased odds of a quit attempt in the previous 3 months (OR, 1.17; The Tips campaign continued to have a significant impact on cessation-related behaviors, providing further justification for the continued use of tobacco education campaigns to accelerate progress toward the goal of reducing adult smoking in the United States. In 2012, the Centers for Disease Control and Prevention (CDC) launched the first federally funded, national tobacco education campaign, Tips From Former Smokers (Tips). Tips consists of graphic antismoking advertisements that feature former cigarette smokers discussing their personal stories of having adverse smoking-related health effects , and incAlthough studies suggest that the Tips campaign in 2012 increased quit attempts and intentions to quit, the campaign should be examined over time to determine sustained effectiveness. Phase 2 of the 2014 campaign used a protocol that was similar to that used in previous campaigns, but it lasted only 9 weeks and it had new advertisements featuring new disease conditions. The objective of this study was to assess the effect of phase 2 of the 2014 Tips campaign advertisements on short-term and long-term attempts to quit smoking among a longitudinal cohort of smokers.We examined data from online surveys administered to a panel of cigarette smokers in the United States. Survey participants were recruited from a probability sample of postal addresses derived from the US Postal Service’s Deliver Sequence File, which covers approximately 95% of all US households. The survey sample was drawn for our study and did not include participants with known prior participation in survey panels. Survey invitation letters were sent to all sampled households and provided a website link and password to the survey. All surveys were administered online by GFK Custom Research, which recruits and maintains nationally representative online panels.All analyses for this study were limited to those who were adult smokers at baseline, defined as adults aged 18 years or older who had smoked at least 100 cigarettes in their lifetime and currently smoked either every day or some days at the time of survey. All participants had a known probability of selection and could not volunteer for study enrollment. Participants who did not have Internet access were provided an additional study incentive payment ($20 in addition to a base incentive of $20) to complete the survey in public locations with Internet access, such as libraries. These recruitment procedures are similar to those used in recruitment of GFK’s KnowledgePanel, which are detailed elsewhere ,8. All dData were collected before and after phase 2 of the 2014 Tips campaign. The analysis focused on phase 2 because baseline data for phase 1 were not available. Phase 1 of the 2014 campaign included previous campaign advertisements that had been evaluated ,6 and 2 After follow-up survey 1, we conducted 2 additional follow-up surveys with this cohort to measure sustained cigarette abstinence among those who reported a quit attempt at follow-up survey 1. These additional follow-up surveys were fielded approximately 3 months  and 6 months  after follow-up survey 1 . A totalTo summarize the overall rate of campaign exposure, we measured self-reported recall of advertisements in follow-up survey 1 by using an established protocol for advertisement recognition protocol (We assessed 3 primary outcome variables at baseline and follow-up survey 1: 1) incidence of a quit attempt in the previous 3 months, 2) intention to quit within 30 days (short-term intention), and 3) intention to quit within 6 months (long-term intention). We measured quit attempt incidence with a dichotomous variable for any quit attempt versus no quit attempt of 1 day or longer. Smokers at baseline who reported nonsmoker status at follow-up survey 1, but reported a quit attempt in the previous 3 months, were also considered to have made a quit attempt. The inclusion of current smokers and recent quitters allowed us to account for total quit attempts among the baseline cohort of smokers. We also created separate dichotomous indicator variables among those who reported smoking at follow-up survey 1 to measure intentions to quit smoking within the next 30 days or within the next 6 months. Sustained cigarette abstinence was defined as the proportion of those reporting quit attempts at follow-up survey 1 who remained abstinent from smoking cigarettes in all 3 follow-up surveys.The primary independent variable was an indicator for the postcampaign period of phase 2 of 2014 Tips, which was used to evaluate campaign-attributable pre–post changes in each outcome variable. We included several additional covariates as potential confounders in the relationship between the postcampaign indicator and the primary outcome variables. Individual-level covariates were sex, age (in years), race/ethnicity, education, annual household income, number of tobacco surveys taken in the previous year, time to first cigarette after waking as a measure of nicotine dependence (in minutes), daily hours of television (in hours), presence of another smoker in the household, presence of a child younger than age 18 years in the household, presence of a chronic  health condition, and presence of a mental health condition. We also included covariates for several characteristics of respondents’ media markets, including population size, median income, and proportion of the media market population with a college degree. In addition, we included a market-level variable for gross rating points to account for other Tips advertisements that were aired with state-specific funds during the July to September 2014 time frame of phase 2 of the 2014 Tips campaign. State-level control variables consisted of state per capita tobacco control program funding and cigarette taxes.Our analysis began with calculating weighted proportions for campaign advertisement awareness to facilitate estimates of overall campaign exposure among the national population of smokers. We then used multivariate logistic regression models to estimate the odds of each of the 3 primary outcome variables  as a function of postcampaign time, controlling for covariates. All model estimates were weighted and adjusted to account for the clustering of data on individuals (2 observations per person) and the temporal ordering (baseline and follow-up) of observations within each individual data cluster. To examine differences in the magnitude of pre–post changes in outcomes across key subgroups of interest, we estimated additional models stratified by race/ethnicity, education, and mental health status. Two-sided tests at the .05 level were used as our main tests of significance throughout. All analyses were conducted with Stata Version 13 statistical software (StataCorp LP).Postestimation-predicted values were then used to estimate precampaign and postcampaign rates of quit attempts and intention to quit smoking among the smoker cohort. These rates then were applied to national smoker population totals, derived from 2014 US Census population projections  and estiP = .03) and having intentions to quit smoking within the next 6 months among those who were still smokers at first follow-up . The association between postcampaign time and increased intentions to quit smoking within the next 30 days was not significant .Overall, 79.4% of smokers in our sample reported seeing at least 1 television advertisement from phase 2 of the 2014 Tips campaign. Results from the multivariate logistic regressions  show thaOn the basis of postestimation predictions from these models, we estimated that the population-level quit attempt rate among smokers increased from 37.5%  before the campaign to 41.9%  after the campaign . In addiApplying our population-level quit attempt rate to the 2014 US Census population totals, we estimated that phase 2 of the 2014 Tips campaign was associated with approximately 1.83 million additional quit attempts in the United States . In addiP = .002) but not among African American  or Hispanic smokers . Some college education was the only educational level associated with higher odds of a quit attempt among smokers . We found a significant association between postcampaign time and 6-month intentions to quit among white smokers  and those with a college degree or more . We also found a significant relationship between postcampaign time and higher odds of a quit attempt among smokers who did not report a mental health condition . Among smokers who did not report a mental health condition, postcampaign time was also associated with intentions to quit within the next 6 months . The campaign was not associated with increased quit attempts or intentions to quit among those who had a mental health condition .Results from the stratified regression models  suggest Our findings suggest that the Tips campaign continues to have a significant impact on smoking cessation behaviors and intentions to quit smoking among US adult smokers into its third year of implementation. Our results indicate that the quit attempt rate among smokers increased by 17% after the launch of phase 2 of the 2014 campaign. This translates to approximately 1.83 million additional quit attempts associated with the campaign and an additional 1.73 million smokers intending to quit within 6 months after the end of the campaign. Furthermore, phase 2 was associated with an estimated 104,000 6-month sustained quits. These estimates are similar to the results of the 2012 Tips campaign, which estimated an additional 1.64 million quit attempts. The campaign impact persisted even with differences in implementation and baseline conditions: phase 2 of the 2014 campaign was only 9 weeks in duration, whereas the 2012 campaign was 12 weeks in duration, and the baseline previous-3-month-quit attempt rate was higher before the 2014 campaign than it was before the 2012 campaign. These results suggest that the Tips campaign’s effects did not degrade over time, even as the campaign matured and became more ubiquitous, reinforcing previous evidence (This study also makes several improvements in the measurement of cessation-related outcomes that enhance the precision of estimated Tips campaign effects. For example, our study captured data on total quit attempts by also assessing quit attempt behavior among baseline smokers who reported being nonsmokers at follow-up. Moreover, long-term follow-up data to estimate the sustained quit rate were collected, whereas previous research  relied oPrevious evaluations of the 2012 campaign ,6 reliedAlthough our findings are similar to previous Tips evaluations for the overall population of smokers, the results of our stratified analysis of minority racial/ethnic groups and educational status differ from the results of previous studies. McAfee et al  found anOur study is subject to at least 4 limitations. First, although we recruited a new custom online panel dedicated only to this study, those agreeing to participate in an online panel may not be representative of the general population and therefore may underrepresent some groups such as rural smokers. Second, we were not able to evaluate the impact of phase 1 of the 2014 campaign because we did not have data before implementation; however, no new creative content was used for the phase 1 campaign, and all advertisements were from prior campaign years. Therefore, our evaluation of phase 2 of 2014 Tips would be more comparable to the 2012 Tips evaluation, where all advertisements were new. Third, although we measured pre–post changes in quit attempt rates for phase 2 of the 2014 campaign, there may have been a latency effect from phase 1 of the 2014 campaign, as well as previous campaign years, which may explain the higher incidence of quit attempts at baseline for 2014 Tips compared with baseline for 2012 Tips. Finally, the 2015 Tips campaign was on the air when 6-month follow-up data on sustained quits were collected, potentially modifying sustained cessation behavior during this period. However, our estimated sustained 6-month quit rate was very similar to the literature-derived sustained quit rate used in the 2012 Tips evaluation (Two years after the first federally funded, nationwide Tips campaign was first introduced, we found evidence of its continued and significant impact on cessation-related behaviors, including an increase in quit attempts and sustained quits as well as an increase in intention to quit within 6 months. This finding has important implications for the value of sustained, long-term tobacco education campaigns. Despite the significant investment required to implement campaigns of this scale, our results suggest that these campaigns continue to have significant impact, even after multiyear implementations. The ongoing health and economic burden posed by cigarette smoking indicates a role for expansion of evidence-based initiatives. These data provide further justification for the continued use of tobacco education campaigns by federal and state health agencies to accelerate progress toward the goal of reducing adult smoking in the United States.


Pubertal dynamics plays an important role in physical and psychological development of children and adolescents. We aim to provide reference ranges of plasma testosterone in a large longitudinal sample. Furthermore, we describe a measure of testosterone trajectories during adolescence that can be used in future investigations of development.We carried out longitudinal measurements of plasma testosterone in 2,216 samples obtained from 513 males (9 to 17 years of age) from the Avon Longitudinal Study of Parents and Children. We used integration of a model fitted to each participant’s testosterone trajectory to calculate a measure of average exposure to testosterone over adolescence. We pooled these data with corresponding values reported in the literature to provide a reference range of testosterone levels in males between the ages of 6 and 19 years.The average values of total testosterone in the ALSPAC sample range from 0.82 nmol/L (Standard Deviation [SD]: 0.09) at 9 years of age to 16.5 (SD: 2.65) nmol/L at 17 years of age; these values are congruent with other reports in the literature. The average exposure to testosterone is associated with different features of testosterone trajectories such as Peak Testosterone Change, Age at Peak Testosterone Change, and Testosterone at 17 years of age as well as the timing of the growth spurt during puberty.The average exposure to testosterone is a useful measure for future investigations using testosterone trajectories to examine pubertal dynamics. Puberty  and adolescence  are intertwined The activation of the hypothalamic-pituitary-gonadal (HPG) axis stimulates the male testes and, in turn, increases production of testosterone A number of human studies have investigated changes in testosterone levels throughout the lifespan of males. We reviewed the literature for reports that provided normal ranges of total testosterone during male adolescence, pooled together data from the five studies identified alspac-exec@bristol.ac.uk). The ALSPAC data management plan describes in detail the policy regarding data sharing, which is through a system of managed open access .We used blood samples obtained from participants in the Avon Longitudinal Study of Parents and Children (ALSPAC), a birth cohort that recruited 14,541 pregnant women resident in Avon, United Kingdom with an expected delivery date between April 1991 and December 1992. Since then, the children and their parents have been studied extensively with longitudinal data available from self-administered questionnaires sent to their homes, linkages to medical records, and through clinical examinations carried out during study visits Blood samples were taken at select visits over the course of the study, roughly at the following years of age: 7, 9, 11, 13, 15, and 17. We obtained and analyzed sex steroids from the blood samples of a subset of 513 male participants who had been recruited for further study using magnetic resonance imaging (MRI). We did not utilize blood samples from the 7-year visit, as most individuals are likely to have very low or undetectable levels of sex steroids at this age. All participants had a maximum of five and a minimum of three blood samples across these five visits .The blood samples, in the form of lithium heparin plasma, were sent from ALSPAC to the Biomarker Core Laboratory at The Pennsylvania State University, where enzyme-linked immunosorbent assays were conducted - using commercially available kits - to determine plasma concentrations of testosterone  and SHBG . For testosterone and SHBG, the sample test volumes were 25 ul and 10 ul, respectively. The assays had lower limits of sensitivity of 0.28 nmol/L (testosterone) and 0.77 nmol/L (SHBG), with average inter- and intra-assay coefficients of variation less than 10%. The assay sensitivity is calculated by subtracting two standard deviations from the mean of 20 identical runs of the zero standard.For quality-control purposes, 10% of participant samples were tested in duplicate, balanced across plates while the rest of the samples were run in singlet to increase efficiency. All samples from a participant were run on the same plate. Of the samples run in duplicate, test values that varied by more than 5% were subject to repeat testing. The first-well values from all samples are used in data analyses for consistency. For testosterone samples that yielded undetectable hormone values or values below the lower limit of sensitivity for the assay , we used the lower bound value of the detectable range for the assay: 0.28 nmol/L.Since testosterone demonstrates a circadian rhythm We calculated a measure of average exposure to testosterone throughout adolescence for participants based on the area under the curve of their testosterone trajectory. The longitudinal measurements of total testosterone and the respective age in months at venipuncture were used to plot the participant’s total testosterone values during his childhood and adolescence. The shape preserving spline-interpolation function from the MATLAB Basic Fitting toolbox  was used to generate a curve through the data-points. The area under the curve  was calculated, with respect to ground, for the section of the spline between the first and last blood sample. This is similar to the method applied by Pruessner and colleagues in context of cortisol sampled at multiple points within an hour For each participant, we calculated Age at Peak Height Velocity (APHV) using up to nine height measurements collected at each ALSPAC visit, from 7 through 17 years of age, as described previously We estimated the analogous measures for testosterone data, Peak Testosterone Change and Age at Peak Testosterone Change, by applying the same spline method. This calculation was restricted to participants who had blood collected at all five visits (n = 232), given that fewer than five data-points would likely lead to imprecise estimates.To calculate levels of free testosterone and to derive values of bio-available testosterone, we used the equation  in conjunction with the (measured) SHBG and (estimated) albumin concentrations as described by Södergård We used Stata version 12.1  for multilevel modeling to adjust values of Total Testosterone. Other statistical analyses used JMP 9 for Macintosh : simple linear regression was used to relate the measure of average testosterone exposure to APHV, Age at Peak Testosterone Change, Peak Testosterone Change, and Total Testosterone at 17 years. In order to visualize participants’ testosterone trajectories and to investigate whether they varied in form between those with higher or lower average testosterone, we divided participants into quintiles based on the measure of average exposure to testosterone and graphed trajectories separately for each quintile.To compare our results with the published values of testosterone, we reviewed the literature and included studies that reported either a mean (with standard deviation) or a median (with range) for values of total testosterone measured from plasma or serum samples in males between the ages of 6 and 20 years. Note that the type of a sample (plasma vs. serum) may not affect measured values; we have conducted a pilot study using blood samples from 10 adult participants  to compare testosterone values measured in serum and plasma  and found that these values showed correlations of >0.99 across the different media.To identify such studies, we conducted a PubMed search in January 2012, using combinations of the following search terms: ‘testosterone’, ‘androgen’, ‘normal’, ‘reference range’, ‘adolescence’, ‘childhood’, ‘serum’, and ‘plasma’. We excluded studies for the following reasons: presenting data in a graph without an accompanying table, presenting data in subgroups of large age-ranges , or reporting reference ranges for salivary testosterone or free testosterone without total testosterone. Furthermore, within the selected studies, we included only those age subgroups containing at least 10 participants.First, we standardized the units for total testosterone into nanomoles per liter using a conversion factor where necessary (1 ng/mL = 3.467 nmol/L). For studies reporting median and range, we used methods described by Hozo and colleagues to estimate the mean and standard deviation (SD) The supplementary table  shows a The models we fitted to remove the effect of circadian rhythm explained 1.7%, 9.5%, 5.8%, and 6.3% of the variance in total testosterone at the 9, 11, 15 and 17-year visits, respectively. Models for the 13-year visit were fitted separately for participants who had not yet reached APHV and those that had passed APHV; the variance explained was 17.3% and 22.1%, respectively. Note that the relatively high proportion of variance in the unadjusted levels of testosterone during the 13-year old visit is due to the combination of rising testosterone levels and morning-afternoon sampling schedule in this visit (see Discussion for details). Time of sample explained less than 0.1% of the variance in the (time) adjusted testosterone values at each visit, indicating that the modeling to remove effects of circadian rhythm was successful.These values are similar to those obtained from the ALSPAC sample . Table 3Eight participants with very high APHV estimates (>200 months) were excluded since these values are erroneous extrapolations of the model used to estimate APHV, as described previously The distribution of Age at Peak Testosterone Change in our sample is bimodal (see Discussion), with peaks at 153 and 174 months . On the other hand, values of the Peak Testosterone Change are normally distributed (Mean: 0.63 [(nmol/L)/month], SD: 0.21).n = 213; 2r = 0.08; p = 0.002). In line with age-related increases in testosterone, participants missing a sample from the second or third visits had higher estimates, whereas those missing a sample from the fourth or fifth visit had lower estimates. We used residuals from this model to estimate corrected values  in this subgroup. A total of 445 participants had a measure of average exposure to testosterone calculated . To determine if replacing undetectable values of testosterone with the assay’s lower limit of sensitivity (see methods) could have an effect on the results, we replaced undetectable values with 0.01 nmol/L (in lieu of 0.28 nmol/L) and recalculated the measure of average exposure to testosterone. A Pearson’s correlation between values from the two calculations shows the variable remains essentially unchanged .We excluded the participants missing two blood samples (n = 68) as their calculated values on this measure were lower compared with participants missing one or none. Values from participants missing one sample were not different from participants with all five blood samples. The values within the subgroup of participants missing one sample, however, varied as a function of the visit with a missing sample ; (B) Age at Peak Testosterone Change ; (C) Peak Testosterone Change ; (D) Testosterone at the 17 year visit . These associations are shown in 2 = 0.32; t = −10.42; p<.0001). Note that the analyses related to Peak Testosterone Change  were restricted to individuals with all five samples, hence the lower sample size.The average exposure to testosterone is associated with: (A) Age at Peak Height Velocity (st quintile: 5.92 (0.91); 2nd: 7.43 (0.29); 3rd: 8.43 (0.30); 4th 9.59 (0.39); and 5th: 11.72 (1.56) nmol/L.The means (and SDs) of the quintiles of average exposure to testosterone were: 1The quantification of testosterone in male ALSPAC participants yield values that match with ranges reported in other studies. Comparing We also describe a simple measure for characterizing the average exposure to testosterone over adolescence based on longitudinal measures. We use an integral to derive this measure instead of the arithmetic mean; the latter would bias the estimates if the samples were clustered towards the beginning or end of adolescence. Using the integral of a fitted spline helps minimize this bias.This measure is associated with timing of the pubertal growth spurt and several characteristics of testosterone trajectories: the age and magnitude of the rise in testosterone, and testosterone levels at the end of the trajectory. Participants who achieve an early growth spurt, which is known to be associated with earlier activation of the HPG axis Differences in the shape of testosterone trajectories depicted in Studying testosterone trajectories in a large sample is made challenging by circadian rhythms that cause fluctuations in hormone levels over the time course of a day Testosterone, particularly its bioavailable fraction, is an important androgen that exerts an effect on multiple biological targets in the body. In addition to the multitude of physical changes initiated during puberty, bioavailable testosterone has been implicated in development and maturation of the adolescent brain We plan to embark on such studies using data in ALSPAC, where the database includes longitudinally collected blood samples and measures of psychopathology throughout adolescence, in addition to a single time-point of Magnetic Resonance Imaging in late adolescence to characterize brain structure and function. In such a design, longitudinal measures can be collapsed into a measure of average exposure and then related to an outcome measured at the end of the study as has been done elsewhere, for example, in the context of air pollution and cardiopulmonary mortality Table S1Comparing the sub-sample with the rest of the ALSPAC males.(DOC)Click here for additional data file.