Automated segmentation of multiple red blood cells with digital holographic microscopy.

We present a method to automatically segment red blood cells (RBCs) visualized by digital holographic microscopy (DHM), which is based on the marker-controlled watershed algorithm. Quantitative phase images of RBCs can be obtained by using off-axis DHM along to provide some important information about each RBC, including size, shape, volume, hemoglobin content, etc. The most important process of segmentation based on marker-controlled watershed is to perform an accurate localization of internal and external markers. Here, we first obtain the binary image via Otsu algorithm. Then, we apply morphological operations to the binary image to get the internal markers. We then apply the distance transform algorithm combined with the watershed algorithm to generate external markers based on internal markers. Finally, combining the internal and external markers, we modify the original gradient image and apply the watershed algorithm. By appropriately identifying the internal and external markers, the problems of oversegmentation and undersegmentation are avoided. Furthermore, the internal and external parts of the RBCs phase image can also be segmented by using the marker-controlled watershed combined with our method, which can identify the internal and external markers appropriately. Our experimental results show that the proposed method achieves good performance in terms of segmenting RBCs and could thus be helpful when combined with an automated classification of RBCs.

Prevalence and predictors of suicide attempt in an incidence cohort of 661 young people with first-episode psychosis

OBJECTIVES: Studies investigating suicidal behaviour in psychosis rarely focus on incidence cohorts of first-episode patients. This is important, because patients who refuse study participation have higher rates of comorbid substance use disorders and longer duration of untreated psychosis as well as worse course illness, variables potentially linked to higher prevalence of suicidal behaviour. The aims of the present study were therefore to examine the prevalence and predictors of suicide and suicide attempt before and during the first 18-24 months of treatment. METHOD: A retrospective file audit of 661 patients was carried out. RESULTS: Six patients (0.9%) died by suicide, 93 (14.3%) attempted suicide prior to entry, and 57 (8.7%) did so during treatment. Predictors of suicide attempt were: previous attempt (odds ratio (OR)=45.54, 95% confidence interval (CI)=9.46-219.15), sexual abuse (OR=8.46, 95%CI=1.88-38.03), comorbid polysubstance (OR=13.63, 95%CI=2.58-71.99), greater insight (OR=0.17, 95%CI=0.06-0.49), lower baseline Global Assessment of Functioning Scale and Scale of Occupational and Functional Assessment score (OR=0.96, 95%CI=0.62-0.91; OR=0.98, 95%CI=0.95-0.99), and longer time in treatment (OR=1.05, 95%CI=1.03-1.08). CONCLUSIONS: The prevalence of suicidal behaviour was high, indicating that suicidal behaviour in incidence populations is higher than in non-epidemiological cohorts of first-episode patients. The rate of repetition of suicide attempt among the sample, however, was lower than expected, suggesting that specialist services can play a role in reducing suicide risk.

Measurement with an automated oscillometric wrist device with position sensor leads to lower values than measurements obtained with an automated oscillometric arm device from the same manufacturer in elderly persons.

OBJECTIVE: Home blood pressure (BP) monitoring is recommended by several clinical guidelines and has been shown to be feasible in elderly persons. Wrist manometers have recently been proposed for such home BP measurement, but their accuracy has not been previously assessed in elderly patients. METHODS: Forty-eight participants (33 women and 15 men, mean age 81.3±8.0 years) had their BP measured with a wrist device with position sensor and an arm device in random order in a sitting position. RESULTS: Average BP measurements were consistently lower with the wrist than arm device for systolic BP (120.1±2.2 vs. 130.5±2.2 mmHg, P<0.001, means±SD) and diastolic BP (66.0±1.3 vs. 69.7±1.3 mmHg, P<0.001). Moreover, a 10 mmHg or greater difference between the arm and wrist device was observed in 54.2 and 18.8% of systolic and diastolic measures, respectively. CONCLUSION: Compared with the arm device, the wrist device with position sensor systematically underestimated systolic as well as diastolic BP. The magnitude of the difference is clinically significant and questions the use of the wrist device to monitor BP in elderly persons. This study points to the need to validate BP measuring devices in all age groups, including in elderly persons.

Automated detection of patient-ventilator asynchrony: new tool or new toy?

Although severe patient-ventilator asynchrony is frequent during invasive and non-invasive mechanical ventilation, diagnosing such asynchronies usually requires the presence at the bedside of an experienced clinician to assess the tracings displayed on the ventilator screen, thus explaining why evaluating patient-ventilator interaction remains a challenge in daily clinical practice. In the previous issue of Critical Care, Sinderby and colleagues present a new automated method to detect, quantify, and display patient-ventilator interaction. In this validation study, the automatic method is as efficient as experts in mechanical ventilation. This promising system could help clinicians extend their knowledge about patient-ventilator interaction and further improve assisted mechanical ventilation.

How Accurate Are Blood (or Breath) Tests for Identifying Self-Reported Heavy Drinking Among People with Alcohol Dependence?

AIMS: Managing patients with alcohol dependence includes assessment for heavy drinking, typically by asking patients. Some recommend biomarkers to detect heavy drinking but evidence of accuracy is limited. METHODS: Among people with dependence, we assessed the performance of disialo-carbohydrate-deficient transferrin (%dCDT, ≥1.7%), gamma-glutamyltransferase (GGT, ≥66 U/l), either %dCDT or GGT positive, and breath alcohol (> 0) for identifying 3 self-reported heavy drinking levels: any heavy drinking (≥4 drinks/day or >7 drinks/week for women, ≥5 drinks/day or >14 drinks/week for men), recurrent (≥5 drinks/day on ≥5 days) and persistent heavy drinking (≥5 drinks/day on ≥7 consecutive days). Subjects (n = 402) with dependence and current heavy drinking were referred to primary care and assessed 6 months later with biomarkers and validated self-reported calendar method assessment of past 30-day alcohol use. RESULTS: The self-reported prevalence of any, recurrent and persistent heavy drinking was 54, 34 and 17%. Sensitivity of %dCDT for detecting any, recurrent and persistent self-reported heavy drinking was 41, 53 and 66%. Specificity was 96, 90 and 84%, respectively. %dCDT had higher sensitivity than GGT and breath test for each alcohol use level but was not adequately sensitive to detect heavy drinking (missing 34-59% of the cases). Either %dCDT or GGT positive improved sensitivity but not to satisfactory levels, and specificity decreased. Neither a breath test nor GGT was sufficiently sensitive (both tests missed 70-80% of cases). CONCLUSIONS: Although biomarkers may provide some useful information, their sensitivity is low the incremental value over self-report in clinical settings is questionable.

Gait disturbances as specific predictive markers of the first fall onset in elderly people: a two-year prospective observational study

Falls are common in the elderly, and potentially result in injury and disability. Thus, preventing falls as soon as possible in older adults is a public health priority, yet there is no specific marker that is predictive of the first fall onset. We hypothesized that gait features should be the most relevant variables for predicting the first fall. Clinical baseline characteristics (e.g., gender, cognitive function) were assessed in 259 home-dwelling people aged 66 to 75 that had never fallen. Likewise, global kinetic behavior of gait was recorded from 22 variables in 1036 walking tests with an accelerometric gait analysis system. Afterward, monthly telephone monitoring reported the date of the first fall over 24 months. A principal components analysis was used to assess the relationship between gait variables and fall status in four groups: non-fallers, fallers from 0 to 6 months, fallers from 6 to 12 months and fallers from 12 to 24 months. The association of significant principal components (PC) with an increased risk of first fall was then evaluated using the area under the Receiver Operator Characteristic Curve (ROC). No effect of clinical confounding variables was shown as a function of groups. An eigenvalue decomposition of the correlation matrix identified a large statistical PC1 (termed "Global kinetics of gait pattern"), which accounted for 36.7% of total variance. Principal component loadings also revealed a PC2 (12.6% of total variance), related to the "Global gait regularity." Subsequent ANOVAs showed that only PC1 discriminated the fall status during the first 6 months, while PC2 discriminated the first fall onset between 6 and 12 months. After one year, any PC was associated with falls. These results were bolstered by the ROC analyses, showing good predictive models of the first fall during the first six months or from 6 to 12 months. Overall, these findings suggest that the performance of a standardized walking test at least once a year is essential for fall prevention.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Once and for all - How people change strategy to ignore irrelevant information in visual tasks

Ignoring irrelevant visual information aids efficient interaction with task environments. We studied how people, after practice, start to ignore the irrelevant aspects of stimuli. For this we focused on how information reduction transfers to rarely practised and novel stimuli. In Experiment 1, we compared competing mathematical models on how people cease to fixate on irrelevant parts of stimuli. Information reduction occurred at the same rate for frequent, infrequent, and novel stimuli. Once acquired with some stimuli, it was applied to all. In Experiment 2, simplification of task processing also occurred in a once-for-all manner when spatial regularities were ruled out so that people could not rely on learning which screen position is irrelevant. Apparently, changes in eye movements were an effect of a once-for-all strategy change rather than a cause of it. Overall, the results suggest that participants incidentally acquired knowledge about regularities in the task material and then decided to voluntarily apply it for efficient task processing. Such decisions should be incorporated into accounts of information reduction and other theories of strategy change in skill acquisition.

Research and development, where people are exposed to nanomaterials

OBJECTIVES: Many nanomaterials (materials with structures smaller than 100 nm) have chemical, physical and bioactive characteristics of interest for novel applications. Considerable research efforts have been launched in this field. This study aimed to study exposure scenarios commonly encountered in research settings. METHODS: We studied one of the leading Swiss universities and first identified all research units dealing with nanomaterials. After a preliminary evaluation of quantities and process types used, a detailed analysis was conducted in units where more than a few micrograms were used per week. RESULTS: In the investigated laboratories, background levels were usually low and in the range of a few thousand particles per cubic centimeter. Powder applications resulted in concentrations of 10,000 to 100,000 particles/cm(3) when measured inside fume hoods, but there were no or mostly minimal increases in the breathing zone of researchers. Mostly low exposures were observed for activities involving liquid applications. However, centrifugation and lyophilization of nanoparticle-containing solutions resulted in high particle number levels (up to 300,000 particles/cm(3)) in work spaces where researchers did not always wear respiratory protection. No significant increases were found for processes involving nanoparticles bound to surfaces, nor were they found in laboratories that were visualizing properties and structure of small amounts of nanomaterials. CONCLUSIONS: Research activities in modern laboratories equipped with control techniques were associated with minimal releases of nanomaterials into the working space. However, the focus should not only be on processes involving nanopowders but should also be on processes involving nanoparticle-containing liquids, especially if the work involves physical agitation, aerosolization or drying of the liquids.

Transactional sex and HIV risks - evidence from a cross-sectional national survey among young people in Uganda.

BACKGROUND: Transactional sex is associated with the HIV epidemic among young people in Uganda. Few quantitative studies based on nationally representative survey data explored the relationship between sexual behaviors, HIV infection, and transactional sex. OBJECTIVE: This study aimed to determine the associations between risky sexual behaviors, participation in transactional sex, and HIV sero-status among men and women aged 15-24 in Uganda. DESIGN: The study uses data from the Uganda AIDS Indicator Survey, a cross-sectional national HIV serological study conducted in 2011. We analyzed data on 1,516 men and 2,824 women aged 15-24 who had been sexually active in the 12 months preceding the survey. Private, face-to-face interviews were also conducted to record the sociodemographics, sexual history, and experiences of sexual coercion. Logistic regression analysis was performed to measure associations between sexual behaviors and transactional sex, and associations between HIV sero-status and transactional sex. RESULTS: Among young people who had been sexually active in the 12 months prior to the survey, 5.2% of young men reported paying for sex while 3.7% of young women reported receiving gifts, favors, or money for sex. Lower educational attainment (ORadjusted 3.25, CI 1.10-9.60) and experience of sexual coercion (ORadjusted 2.83, CI 1.07-7.47) were significantly associated with paying for sex among men. Multiple concurrent sexual relationships were significantly associated with paying for sex among young men (ORadjusted 5.60, CI 2.08-14.95) and receiving something for sex among young women (ORadjusted 8.04, CI 2.55-25.37). Paying for sex among young men and having three to five lifetime sexual partners among young women were associated with increased odds of testing positive for HIV. CONCLUSIONS: Transactional sex is associated with sexual coercion and HIV risk behaviors such as multiple concurrent sexual partnerships among young people in Uganda. In addition, transactional sex appears to place young men at increased risk for HIV in Uganda. Both sexes appear equally vulnerable to risks associated with transactional sex, and therefore should be targeted in intervention programs. In addition, strengthening universal education policy and improving school retention programs may be beneficial in reducing risky sexual behaviors and transactional sex.

Type 1 diabetes mellitus in people with pharmacoresistant epilepsy: Prevalence and clinical characteristics.

BACKGROUND: There have been inconsistent reports on the potential association between diabetes mellitus and epilepsy. METHODS: We examined a consecutive cohort of 2016 people with pharmacoresistant epilepsy admitted to a tertiary medical centre. RESULTS: We identified 20 individuals with type 1 diabetes mellitus (T1DM); a point prevalence of 9.9 (95% CI: 6.4, 15.3) cases per 1000 individuals. This represents a more than two-fold increase relative to published prevalence estimates of T1DM in the general population. The onset of T1DM preceded that of epilepsy in 80% of individuals, by a median of 1.5 years. Individuals with T1DM were significantly more likely to have cryptogenic/unknown epilepsy relative to those with type 2 diabetes mellitus or without diabetes (85% versus 35% and 49%, p=0.045). All individuals with T1DM had focal epilepsy, the majority of which were temporal lobe in origin, although there was no evidence that this proportion was any different from those without T1DM (p>0.999). CONCLUSIONS: The prevalence of T1DM appears to be increased in people with pharmacoresistant epilepsy and is associated with cryptogenic/unknown epilepsy. These findings may have pathophysiological implications, especially in the context of anti-glutamic acid decarboxylase antibodies.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.