Application of computer-generated images to train pattern recognition used in semiquantitative immunohistochemistry scoring

This study aimed to clarify whether the pattern recognition involved in scoring proliferation fractions can be trained by abstract computerized images of virtual tissues. Twenty computer-generated images with randomly distributed blue or red dots were scored by 12 probands (all co-workers or collaborators of the Institute of Pathology, University of Bonn). Afterward, the probands underwent a training phase during which they received an immediate feedback on the actual rate of positivity after each image. Finally, the initial testing series was rescored. In a second round with 15 different probands, 20 Ki-67 immunohistochemistry images of tonsil tissue were scored, followed by the same training phase with computer-generated images, before the immunohistochemistry slides were scored again. Paired t-tests were used to compare the differences in mean rates pre- and post-training. Concerning computerized images, untrained probands scored the percentages of positive dots with a mean deviation from the true rates of 8.2%. Following training, the same testing series was scored significantly better with a mean deviation of 4.9% (mean improvement 3.3%, p < 0.001). Scoring real immunohistochemistry slides, the training with computerized images also improved correct estimations, albeit to a lesser degree (mean improvement 1%, p = 0.03). Abstract computerized images of virtual tissues may be a useful tool to train and improve the accuracy of pattern recognition involved in semiquantitative scoring of immunohistochemistry slides. As a side results, this study highlights the value of computer-generated images to verify the performance of image-analysis software.     

Bench to bedside: recent advances in lung cancer pathological research with implications for diagnostic clinical practice

After decades of relative stagnation lung cancer is emerging as a disease type where rapid progress is being made in diagnosis and therapy, as well as in our understanding of disease biology. Much of this progress is of immediate impact to diagnosticians, and more is likely to affect diagnostic practice in the near future. In this review we seek to briefly summarize several key areas of active research of immediate or probable imminent value to trainee and consultant pulmonary pathologists alike. We cover some major changes in tumour classification, grading, and patient stratification, as well as considering the state of the art in machine-assisted interpretation of lung cancer histology, and the use of genetically modified lung cancer models.     

The impact of neighborhoods and friendships on interracial anxiety among medical students and residents: A report from the medical student CHANGES study

Objective

To examine the experience of interracial anxiety among health professionals and how it may affect the quality of their interactions with patients from racially marginalized populations. We explored the influence of prior interracial exposure—specifically through childhood neighborhoods, college student bodies, and friend groups—on interracial anxiety among medical students and residents. We also examined whether levels of interracial anxiety change from medical school through residency.

Data Source

Web-based longitudinal survey data from the Medical Student Cognitive Habits and Growth Evaluation Study.

Study Design

We used a retrospective longitudinal design with four observations for each trainee. The study population consisted of non-Black US medical trainees surveyed in their 1st and 4th years of medical school and 2nd and 3rd years of residency. Mixed effects longitudinal models were used to assess predictors of interracial anxiety and assess changes in interracial anxiety scores over time.

Principal Findings

In total, 3155 non-Black medical trainees were followed for 7 years. Seventy-eight percent grew up in predominantly White neighborhoods. Living in predominantly White neighborhoods and having less racially diverse friends were associated with higher levels of interracial anxiety among medical trainees. Trainees' interracial anxiety scores did not substantially change over time; interracial anxiety was highest in the 1st year of medical school, lowest in the 4th year, and increased slightly during residency.

Conclusions

Neighborhood and friend group composition had independent effects on interracial anxiety, indicating that premedical racial socialization may affect medical trainees' preparedness to interact effectively with diverse patient populations. Additionally, the lack of substantial change in interracial anxiety throughout medical training suggests the importance of providing curricular tools and structure (e.g., instituting interracial cooperative learning activities) to foster the development of healthy interracial relationships.     

Application of 3D imaging and selfies in forensic dental identification

With increased access to smartphones, the selfie has gained immense popularity in the past decade. Selfie images could be a significant source of ante-mortem (AM) image data in cases where dental records are unavailable or considered insufficient. The application of 3D imaging and selfies has not been explored to its full potential in human dental identification. The present study aimed to evaluate the feasibility of using selfies as AM data and comparing with 3D post-mortem (PM) scans as an alternative to multiple 2D PM photographs in forensic dental identification. The study sample consisted of 18 selfies (12 matching and 6 non-matching) and 15 3D dental scans obtained from the study participants. The study sample was assessed by 6 experienced forensic odontologists (Raters) in two phases; Phase I-Visual comparison of 2D selfies to 3D scans and Phase II-2D selfies superimposed upon 3D scans. Each rater looked at 15 cases, and a total of 1620 comparisons were made by 6 raters (72 for the 12 matching cases and 1548 were for non-matching) and the opinions for each of the comparisons were analyzed. The results of the study show that use of the 3D superimposition method increased the certainty of the conclusions reached by the raters for the cases with correct matches. Furthermore, 94.2% of the 1548 non-matching comparisons were correctly excluded, compared with 77% for the 2D visual comparison method. The study demonstrated the applicability of this 3D method as a valuable tool in assisting the forensic odontologist with dental identification using selfies.     

Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

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Using time series analysis to forecast the health-related quality of life of post-menopausal women with non-metastatic ER+ breast cancer: A tutorial and case study

BackgroundTime series models are widely used forecasting techniques in health care for long time series and are typically built in commercial statistical packages. However, for short time series data, such as health-related quality of life (HRQoL), guidance on how to select and use appropriate time series models is lacking. This tutorial provides a step-by-step guide adopting a time series analysis framework for HRQoL forecasting.ObjectiveWe walk through a case study examining the forecasting of the effects of adjuvant endocrine therapy on the HRQoL of post-menopausal women with non-metastatic ER + breast cancer using data from the HRQoL sub-protocol of the Tamoxifen arm of the Arimidex, tamoxifen, alone or in combination (ATAC) trial.MethodsThe forecasting of HRQoL consists of four steps: 1) data extraction and accuracy check, 2) forecasting horizon definition and identification of data pattern, 3) forecasting model identification and fitting using five forecasting approaches appropriate for short time series ((i) double exponential smoothing, (ii) double moving average, (iii) fuzzy forecasting, (iv) grey forecasting, and (v) Volterra series), 4) forecasting model selection. A user-friendly visual basic for applications (VBA) Excel add-in is made available to interested users to facilitate the application of the tutorial.ResultsThe Grey method and Volterra series appeared to be good candidates to forecast the effects of adjuvant endocrine therapy on the HRQoL of post-menopausal women with non-metastatic ER + breast cancer enrolled in the ATAC trial.ConclusionIt is feasible to forecast the effects of treatments on HRQOL even when the time series is short.     

A benchmark dose study of prenatal exposure to di(2-ethylhexyl) phthalate and behavioral problems in children

IntroductionPrenatal exposure to di(2-ethylhexyl) phthalate (DEHP) has been reported to be associated with adverse effects on neurodevelopment that yield behavior syndromes in young children with an estimated median exposure lower than the currently recommended tolerable daily intake (TDI) and reference dose (RfD).ObjectivesOur aim was to derive the benchmark dose for prenatal exposure to DEHP for the neurodevelopmental health in children.MethodsA total of 122 mother-child pairs from the Taiwan Maternal and Infant Cohort Study were analyzed for the dose-response relationship between maternal exposure to DEHP and children's behavioral syndromes evaluated at 8 years (n = 122, 2009), 11 years (n = 96, 2012), and 14 years (n = 78, 2015) of age. We employed a multivariate regression model to assess the statistical associations between the estimated maternal average daily intake of DEHP and child's individual CBCL scores for boys and girls at each separate age, followed by a mixed model for all the children across three ages accounting for individual variations. We then employed structural equation models by combining the children's specific behavioral problem scores at different ages and obtained a simulated overall latent score in relation to maternal exposure. Based on the established dose-response relationship, we derived the benchmark dose (BMD) and the lower limit (BMDL).ResultsAssociations of maternal DEHP exposure (median 4.54$\mu g/kg\_bw/day$) with the Child Behavior Checklist (CBCL) scores were all significant, except for somatic complaints, adjusting for child's age, gender, IQ, and family income. The BMDL, given a benchmark response of 0.10 (0.05) and a background response of 0.05, was 6.01 (2.16) $\mu g/kg\_bw/day$for an integrated CBCL score.ConclusionsThe current TDI (RfD) of 50 (20) $\mu g/kg\_bw/day$ for DEHP might not protect pregnant women for their children from behavioral problems. There remains the lack of comparable toxicological data. Further investigations are needed.     

Extending multilevel spatial models to include spatially varying coefficients

Multilevel models have long been used by health geographers working on questions of space, place, and health. Similarly, health geographers have pursued interests in determining whether or not the effect of an exposure on a health outcome varies spatially. However, relatively little work has sought to use multilevel models to explore spatial variability in the effects of a contextual exposure on a health outcome. Methodologically, extending multilevel models to allow intercepts and slopes to vary spatially is straightforward. The purpose of this paper, therefore, is to show how multilevel spatial models can be extended to include spatially varying covariate effects. We provide an empirical example on the effect of agriculture on malaria risk in children under 5 years of age in the Democratic Republic of Congo.     

Benzophenone-3 promotion of mammary tumorigenesis is diet-dependent

Benzophenone-3 is a putative endocrine disrupting chemical and common ingredient in sunscreens. The potential of endocrine disrupting chemicals to act as agonists or antagonists in critical hormonally regulated processes, such as mammary gland development and mammary tumorigenesis, demands evaluation of its potential in promoting breast cancer. This study identifies the effects of BP-3 on mammary tumorigenesis with high-fat diet during puberty versus adulthood in Trp53-null transplant BALB/c mice. Benzophenone-3 exposure yielded levels in urine similar to humans subjected to heavy topical sunscreen exposure. Benzophenone-3 was protective for epithelial tumorigenesis in mice fed lifelong low-fat diet, while promotional for epithelial tumorigenesis in mice fed adult high-fat diet. Benzophenone-3 increased tumor cell proliferation, decreased tumor cell apoptosis, and increased tumor vascularity dependent on specific dietary regimen and tumor histopathology. Even in instances of an ostensibly protective effect, other parameters suggest greater risk. Although benzophenone-3 seemed protective on low-fat diet, spindle cell tumors arising in these mice showed increased proliferation and decreased apoptosis. This points to a need for further studies of benzophenone-3 in both animal models and humans as a potential breast cancer risk factor, as well as a more general need to evaluate endocrine disrupting chemicals in varying dietary contexts.