Dermatology residents' perspectives on virtual dermatopathology education.

BACKGROUND: Dermatopathology education accounts for 30% of U.S. dermatology residency training. The COVID-19 pandemic expedited the implementation of virtual dermatopathology in place of traditional microscopy for resident education. This study examined U.S. dermatology residents' perceptions of virtual dermatopathology, as research in this area is lacking. METHODS: An anonymous, confidential, institutional review board-approved survey was electronically distributed to U.S. dermatology residents consisting of 16 questions comparing attitudes towards virtual and traditional dermatopathology education. Responses were n = 59. Statistical analysis was performed using SAS software. RESULTS: Participants believe virtual imaging is superior to conventional microscopy in schedule flexibility (96.6% vs. 1.7%, p < 0.0001), lecture convenience (94.8% vs. 0.0%, p < 0.0001), personal review (96.6% vs. 0.0%, p < 0.0001), cost-effectiveness (64.4% vs. 6.8%, p < 0.0001), and board exam preparation (52.5% vs. 16.9%, p = 0.0005). Conventional microscopy was favored for image quality (50.8% vs. 25.4%, p = 0.0127) and overall utility (50.8% vs. 27.1%, p = 0.0195). CONCLUSIONS: Our study supports virtual dermatopathology utilization as a valuable tool in dermatology residency training. Also it is shown that conventional microscopy training continues to play a key role. Further studies should examine whether, if ever, virtual dermatopathology could gradually replace conventional microscopy with the advent of newer and more powerful digital and scanning technology.

Rod-specific downregulation of omega-3 very-long-chain polyunsaturated fatty acid pathway in age-related macular degeneration.

Docosahexaenoic acid (DHA; 22:6) plays a key role in vision and is the precursor for very-long-chain polyunsaturated fatty acids (VLC-PUFAs). The release of 32- and 34-carbon VLC-PUFAs and DHA from sn-1 and sn-2 of phosphatidylcholine (PC) leads to the synthesis of cell-survival mediators, the elovanoids (ELVs) and neuroprotectin D1 (NPD1), respectively. Macula and periphery from age-related macular degeneration (AMD) donor retinas were assessed for the availability of DHA-related lipids by LC-MS/MS-based lipidomic analysis and MALDI-molecular imaging. We found reduced retina DHA and VLC-PUFA pathways to synthesize omega-3 ELVs from precursors that likely resulted in altered disks and photoreceptor loss. Additionally, we compared omega-3 (n-3) fatty acid with DHA (22:6) and omega-6 (n-6) fatty acid with arachidonic acid (AA; 20:4) pathways. n-3 PC(22:6/22:6, 44:12) and n-6 PC(20:4/20:4, 40:8) showed differences among male/female, macula/periphery, and normal/AMD retinas. Periphery of AMD retina males increased 44:12 abundance, while normal females increased 40:8 (all macula had an upward 40:8 tendency). We also showed that female AMD switched from n-3 to n-6 fatty acids; most changes in AMD occurred in the periphery of female AMD retinas. DHA and VLC-PUFA release from PCs leads to conversion in pro-survival NPD1 and ELVs. The loss of the neuroprotective precursors of ELVs in the retina periphery from AMD facilitates uncompensated stress and cell loss. In AMD, the female retina loses peripheral rods VLC-PUFAs to about 33% less than in males limiting ELV formation and its protective bioactivity.

Membrane-type frizzled-related protein regulates lipidome and transcription for photoreceptor function.

Molecular decision-makers of photoreceptor (PRC) membrane organization and gene regulation are critical to understanding sight and retinal degenerations that lead to blindness. Using Mfrprd6 mice, which develop PRC degeneration, we uncovered that membrane-type frizzled-related protein (MFRP) participates in docosahexaenoic acid (DHA, 22:6) enrichment in a manner similar to adiponectin receptor 1 (AdipoR1). Untargeted imaging mass spectrometry demonstrates cell-specific reduction of phospholipids containing 22:6 and very long-chain polyunsaturated fatty acids (VLC-PUFAs) in Adipor1-/- and Mfrprd6 retinas. Gene expression of pro-inflammatory signaling pathways is increased and gene-encoding proteins for PRC function decrease in both mutants. Thus, we propose that both proteins are necessary for retinal lipidome membrane organization, visual function, and to the understanding of the early pathology of retinal degenerative diseases.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns.

Motivation: Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. Results: We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. Availability and Implementation: The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ . Contact: hlin1@lsuhsc.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Locally optimal designs for some binary dose-response models.

In this paper, we consider the problem of seeking locally optimal designs for nonlinear dose-response models with binary outcomes. Applying the theory of Tchebycheff Systems and other algebraic tools, we show that the locally D-, A-, and c-optimal designs for three binary dose-response models are minimally supported in finite, closed design intervals. The methods to obtain such designs are presented along with examples. The efficiencies of these designs are also discussed.

OPTIMAL DESIGNS FOR SPLINE WAVELET REGRESSION MODELS.

In this article we investigate the optimal design problem for some wavelet regression models. Wavelets are very flexible in modeling complex relations, and optimal designs are appealing as a means of increasing the experimental precision. In contrast to the designs for the Haar wavelet regression model (Herzberg and Traves 1994; Oyet and Wiens 2000), the I-optimal designs we construct are different from the D-optimal designs. We also obtain c-optimal designs. Optimal (D- and I-) quadratic spline wavelet designs are constructed, both analytically and numerically. A case study shows that a significant saving of resources may be realized by employing an optimal design. We also construct model robust designs, to address response misspecification arising from fitting an incomplete set of wavelets.

Neoplastic reprogramming of patient-derived adipose stem cells by prostate cancer cell-associated exosomes.

Emerging evidence suggests that mesenchymal stem cells (MSCs) are often recruited to tumor sites but their functional significance in tumor growth and disease progression remains elusive. Herein we report that prostate cancer (PC) cell microenvironment subverts PC patient adipose-derived stem cells (pASCs) to undergo neoplastic transformation. Unlike normal ASCs, the pASCs primed with PC cell conditioned media (CM) formed prostate-like neoplastic lesions in vivo and reproduced aggressive tumors in secondary recipients. The pASC tumors acquired cytogenetic aberrations and mesenchymal-to-epithelial transition and expressed epithelial, neoplastic, and vasculogenic markers reminiscent of molecular features of PC tumor xenografts. Our mechanistic studies revealed that PC cell-derived exosomes are sufficient to recapitulate formation of prostate tumorigenic mimicry generated by CM-primed pASCs in vivo. In addition to downregulation of the large tumor suppressor homolog2 and the programmed cell death protein 4, a neoplastic transformation inhibitor, the tumorigenic reprogramming of pASCs was associated with trafficking by PC cell-derived exosomes of oncogenic factors, including H-ras and K-ras transcripts, oncomiRNAs miR-125b, miR-130b, and miR-155 as well as the Ras superfamily of GTPases Rab1a, Rab1b, and Rab11a. Our findings implicate a new role for PC cell-derived exosomes in clonal expansion of tumors through neoplastic reprogramming of tumor tropic ASCs in cancer patients.

miR-9 and miR-140-5p target FoxP2 and are regulated as a function of the social context of singing behavior in zebra finches.

Mutations in the FOXP2 gene cause speech and language impairments, accompanied by structural and functional abnormalities in brain regions underlying speech-related sensory-motor processing, including the striatum and cerebellum. The sequence and expression patterns of FOXP2 are highly conserved among higher vertebrates. In the zebra finch brain, FoxP2 is expressed in Area X, a striatal nucleus required for vocal learning, and reduced FoxP2 expression impairs dendritic development and vocal learning. The FoxP2 gene encodes a transcription factor that controls the expression of many downstream genes. However, how FOXP2 gene expression is regulated is not clearly understood. miRNAs regulate gene expression post-transcriptionally by targeting the 3'-untranslated regions (UTRs) of mRNAs, leading to translational suppression or mRNA degradation. In this study, we identified miR-9 and miR-140-5p as potential regulators of the FoxP2 gene. We show that both miR-9 and miR-140-5p target specific sequences in the FoxP2 3'-UTR and downregulate FoxP2 protein and mRNA expression in vitro. We also show that the expression of miR-9 and miR-140-5p in Area X of the zebra finch brain is regulated during song development in juvenile zebra finches. We further show that in adult zebra finches the expression of miR-9 and miR-140-5p in Area X is regulated as a function of the social context of song behavior in males singing undirected songs. Our findings reveal a post-transcriptional mechanism that regulates FoxP2 expression and suggest that social vocal behavior can influence the basal ganglia circuit controlling vocal learning via a miRNA-FoxP2 gene regulatory network.

BCRgt: a Bayesian cluster regression-based genotyping algorithm for the samples with copy number alterations.

BACKGROUND: Accurate genotype calling is a pre-requisite of a successful Genome-Wide Association Study (GWAS). Although most genotyping algorithms can achieve an accuracy rate greater than 99% for genotyping DNA samples without copy number alterations (CNAs), almost all of these algorithms are not designed for genotyping tumor samples that are known to have large regions of CNAs. RESULTS: This study aims to develop a statistical method that can accurately genotype tumor samples with CNAs. The proposed method adds a Bayesian layer to a cluster regression model and is termed a Bayesian Cluster Regression-based genotyping algorithm (BCRgt). We demonstrate that high concordance rates with HapMap calls can be achieved without using reference/training samples, when CNAs do not exist. By adding a training step, we have obtained higher genotyping concordance rates, without requiring large sample sizes. When CNAs exist in the samples, accuracy can be dramatically improved in regions with DNA copy loss and slightly improved in regions with copy number gain, comparing with the Bayesian Robust Linear Model with Mahalanobis distance classifier (BRLMM). CONCLUSIONS: In conclusion, we have demonstrated that BCRgt can provide accurate genotyping calls for tumor samples with CNAs.

PAIR: paired allelic log-intensity-ratio-based normalization method for SNP-CGH arrays.

MOTIVATION: Normalization is critical in DNA copy number analysis. We propose a new method to correctly identify two-copy probes from the genome to obtain representative references for normalization in single nucleotide polymorphism arrays. The method is based on a two-state Hidden Markov Model. Unlike most currently available methods in the literature, the proposed method does not need to assume that the percentage of two-copy state probes is dominant in the genome, as long as there do exist two-copy probes. RESULTS: The real data analysis and simulation study show that the proposed algorithm is successful in that (i) it performs as well as the current methods (e.g. CGHnormaliter and popLowess) for samples with dominant two-copy states and outperforms these methods for samples with less dominant two-copy states; (ii) it can identify the copy-neutral loss of heterozygosity; and (iii) it is efficient in terms of the computational time used. AVAILABILITY: R scripts are available at http://publichealth.lsuhsc.edu/PAIR.html.

D-optimal designs for two-variable logistic regression model with restricted design space.

The problem of constructing locally D-optimal designs for two-variable logistic model with no interaction has been studied in many literature. In Kabera, Haines, and Ndlovu (2015), the model is restricted to have positive slopes and negative intercept for the assumptions that the probability of response increases with doses for both drugs and that the probability of response is less than 0.5 at zero dose level of both drugs. The design space mainly discussed is the set [0, ∞) × [0, ∞), while the finite rectangular design space is presented only in scenarios where the results for the unlimited design space are still appropriate. In this paper, we intend to loose these restrictions and discuss the rectangular design spaces for the model where the D-optimal designs can not be obtained. The result can be extended to the models where drugs have negative or opposite effects, or the models with positive intercept, by using translation and reflection in the first quadrant.

Laryngeal Cancer Screening During Flexible Video Laryngoscopy Using Large Computer Vision Models.

OBJECTIVE: Develop an artificial intelligence assisted computer vision model to screen for laryngeal cancer during flexible laryngoscopy. METHODS: Using laryngeal images and flexible laryngoscopy video recordings, we developed computer vision models to classify video frames for usability and cancer screening. A separate model segments any identified lesions on the frames. We used these computer vision models to construct a video stream annotation system. This system classifies findings from flexible laryngoscopy as "potentially malignant" or "probably benign" and segments any detected lesions. Additionally, the model provides a confidence level for each classification. RESULTS: The overall accuracy of the flexible laryngoscopy cancer screening model was 92%. For cancer screening, it achieved a sensitivity of 97.7% and a specificity of 76.9%. The segmentation model attained an average precision at a 0.50 intersection-over-union of 0.595. The confidence level for positive screening results can assist clinicians in counseling patients regarding the findings. CONCLUSION: Our model is highly sensitive and adequately specific for laryngeal cancer screening. Segmentation helps endoscopists identify and describe potential lesions. Further optimization is required to enable the model's deployment in clinical settings for real-time annotation during flexible laryngoscopy.

Endoscopic surgical field clarity index: An artificial intelligence-based measure of transnasal endoscopic surgical field quality.

KEY POINTS: Clear visualization during transnasal endoscopic surgery (TNES) is crucial for safe, efficient surgery. The endoscopic surgical field clarity index (ESFCI) is an artificial intelligence-enabled measure of surgical field quality. The ESFCI allows researchers to evaluate interventions to improve visualization during TNES.

High circulating estrogens and selective expression of ERß in prostate tumors of Americans: implications for racial disparity of prostate cancer.

Although estrogen receptor beta (ERß) has been implicated in prostate cancer (PCa) progression, its potential role in health disparity of PCa remains elusive. The objective of this study was to examine serum estrogens and prostate tumor ERß expression and examine their correlation with clinical and pathological parameters in African American (AA) versus Caucasian American (CA) men. The circulating 17ß-estradiol (E2) was measured by enzyme immunoassay in blood procured from racially stratified normal subjects and PCa patients. Differential expression profile analysis of ERß was analyzed by quantitative immunohistochemistry using ethnicity-based tissue microarray encompassing 300 PCa tissue cores. In situ ERß expression was validated by quantitative reverse transcription-PCR in matched microdissected normal prostate epithelium and tumor cells and datasets extracted from independent cohorts. In comparison with normal age-matched subjects, circulating E2 levels were significantly elevated in all PCa patients. Further analysis demonstrates an increase in blood E2 levels in AA men in both normal and PCa in comparison with age- and stage-matched counterparts of CA decent. Histochemical score analysis reveals intense nuclear immunoreactivity for ERß in tumor cores of AA men than in CA men. Gene expression analysis in microdissected tumors corroborated the biracial differences in ERß expression. Gene expression analysis from independent cohort datasets revealed correlation between ERß expression and PCa progression. However, unlike in CA men, adjusted multivariate analysis showed that ERß expression correlates with age at diagnosis and low prostate-specific antigen recurrence-free survival in AA men. Taken together, our results suggest that E2-ERß axis may have potential clinical utility in PCa diagnosis and clinical outcome among AA men.

Inferring the expression variability of human transposable element-derived exons by linear model analysis of deep RNA sequencing data.

BACKGROUND: The exonization of transposable elements (TEs) has proven to be a significant mechanism for the creation of novel exons. Existing knowledge of the retention patterns of TE exons in mRNAs were mainly established by the analysis of Expressed Sequence Tag (EST) data and microarray data. RESULTS: This study seeks to validate and extend previous studies on the expression of TE exons by an integrative statistical analysis of high throughput RNA sequencing data. We collected 26 RNA-seq datasets spanning multiple tissues and cancer types. The exon-level digital expressions (indicating retention rates in mRNAs) were quantified by a double normalized measure, called the rescaled RPKM (Reads Per Kilobase of exon model per Million mapped reads). We analyzed the distribution profiles and the variability (across samples and between tissue/disease groups) of TE exon expressions, and compared them with those of other constitutive or cassette exons. We inferred the effects of four genomic factors, including the location, length, cognate TE family and TE nucleotide proportion (RTE, see Methods section) of a TE exon, on the exons' expression level and expression variability. We also investigated the biological implications of an assembly of highly-expressed TE exons. CONCLUSION: Our analysis confirmed prior studies from the following four aspects. First, with relatively high expression variability, most TE exons in mRNAs, especially those without exact counterparts in the UCSC RefSeq (Reference Sequence) gene tables, demonstrate low but still detectable expression levels in most tissue samples. Second, the TE exons in coding DNA sequences (CDSs) are less highly expressed than those in 3' (5') untranslated regions (UTRs). Third, the exons derived from chronologically ancient repeat elements, such as MIRs, tend to be highly expressed in comparison with those derived from younger TEs. Fourth, the previously observed negative relationship between the lengths of exons and the inclusion levels in transcripts is also true for exonized TEs. Furthermore, our study resulted in several novel findings. They include: (1) for the TE exons with non-zero expression and as shown in most of the studied biological samples, a high TE nucleotide proportion leads to their lower retention rates in mRNAs; (2) the considered genomic features (i.e. a continuous variable such as the exon length or a category indicator such as 3'UTR) influence the expression level and the expression variability (CV) of TE exons in an inverse manner; (3) not only the exons derived from Alu elements but also the exons from the TEs of other families were preferentially established in zinc finger (ZNF) genes.

Design and validation issues in RNA-seq experiments.

The next-generation sequencing technologies are being rapidly applied in biological research. Tens of millions of short sequences generated in a single experiment provide us enormous information on genome composition, genetic variants, gene expression levels and protein binding sites depending on the applications. Various methods are being developed for analyzing the data generated by these technologies. However, the relevant experimental design issues have rarely been discussed. In this review, we use RNA-seq as an example to bring this topic into focus and to discuss experimental design and validation issues pertaining to next-generation sequencing in the quantification of transcripts.

Is Methotrexate Ototoxic? Investigating the Ototoxic Late Effects of Pediatric Cancer Treatment.

PURPOSE: Pediatric cancer survivors often experience long-term adverse health conditions or late effects, including hearing loss, that are attributable to cancer therapy. Ototoxic late effects have been documented in patients with cancer treated with cisplatin-based chemotherapy and/or radiation. This study evaluated the late effects of methotrexate as compared to cisplatin and other cancer therapy agents on pediatric cancer survivors at the Children's Hospital of New Orleans in Louisiana (CHNOLA) and patients currently undergoing cancer treatment at Our Lady of the Lake (OLOL) Hospital in Baton Rouge, Louisiana. METHOD: A retrospective chart review was conducted of medical records from the CHNOLA Audiology Clinic and the Treatment After Cancer Late Effects clinic, which followed patients 2-19 years after cancer treatment completion and current patients with pediatric cancer at OLOL. This study identified pediatric cancer survivors between 2 and 24 years of age with treatment protocol information and audiological evaluations. Association studies were performed to calculate p values using an exact chi-square test. RESULTS: More than 44% of late-effects patients had significant hearing loss; mild-to-profound hearing loss was observed in 37.5% of patients who received methotrexate treatment without cisplatin or irradiation. Eighty-three percent of the patients who received cisplatin had late-effect hearing loss. In patients currently receiving cancer treatment, 12% had significant hearing loss. CONCLUSIONS: The results from this study suggest that children who receive therapies not clinically established as ototoxic (i.e., methotrexate) may still be at a high risk of developing long-term hearing loss as a late effect. Due to the high incidence rate of hearing loss among patients with pediatric cancer, we recommend that audiologists be part of the late-effects care team. This study also demonstrates that patients with pediatric cancer treated with methotrexate should receive routine long-term auditory monitoring as part of their standard of care to detect and manage hearing loss early, minimizing adverse outcomes.

Length bias correction for RNA-seq data in gene set analyses.

MOTIVATION: Next-generation sequencing technologies are being rapidly applied to quantifying transcripts (RNA-seq). However, due to the unique properties of the RNA-seq data, the differential expression of longer transcripts is more likely to be identified than that of shorter transcripts with the same effect size. This bias complicates the downstream gene set analysis (GSA) because the methods for GSA previously developed for microarray data are based on the assumption that genes with same effect size have equal probability (power) to be identified as significantly differentially expressed. Since transcript length is not related to gene expression, adjusting for such length dependency in GSA becomes necessary. RESULTS: In this article, we proposed two approaches for transcript-length adjustment for analyses based on Poisson models: (i) At individual gene level, we adjusted each gene's test statistic using the square root of transcript length followed by testing for gene set using the Wilcoxon rank-sum test. (ii) At gene set level, we adjusted the null distribution for the Fisher's exact test by weighting the identification probability of each gene using the square root of its transcript length. We evaluated these two approaches using simulations and a real dataset, and showed that these methods can effectively reduce the transcript-length biases. The top-ranked GO terms obtained from the proposed adjustments show more overlaps with the microarray results. AVAILABILITY: R scripts are at http://www.soph.uab.edu/Statgenetics/People/XCui/r-codes/.

Robust RNA-seq data analysis using an integrated method of ROC curve and Kolmogorov-Smirnov test.

It is a common approach to dichotomize a continuous biomarker in clinical setting for the convenience of application. Analytically, results from using a dichotomized biomarker are often more reliable and resistant to outliers, bi-modal and other unknown distributions. There are two commonly used methods for selecting the best cut-off value for dichotomization of a continuous biomarker, using either maximally selected chi-square statistic or a ROC curve, specifically the Youden Index. In this paper, we explained that in many situations, it is inappropriate to use the former. By using the Maximum Absolute Youden Index (MAYI), we demonstrated that the integration of a MAYI and the Kolmogorov-Smirnov test is not only a robust non-parametric method, but also provides more meaningful p value for selecting the cut-off value than using a Mann-Whitney test. In addition, our method can be applied directly in clinical settings.

Tuned in to communication sounds: Neuronal sensitivity in the túngara frog midbrain to frequency modulated signals.

For complex communication signals, it is often difficult to identify the information-bearing elements and their parameters necessary to elicit functional behavior. Consequently, it may be difficult to design stimuli that test how neurons contribute to communicative processing. For túngara frogs (Physalaemus pustulosus), however, previous behavioral testing with numerous stimuli showed that a particular frequency modulated (FM) transition in the male call is required to elicit phonotaxis and vocal responses. Modeled on such behavioral experiments, we used awake in vivo recordings of single units in the midbrain to determine if their excitation was biased to behaviorally important FM parameters. Comparisons of stimulus driven action potentials revealed greatest excitation to the behaviorally important FM transition: a downward FM sweep or step that crosses ~600 Hz. Previous studies using long-duration acoustic exposure found immediate early gene expression in many midbrain neurons to be most sensitive to similar FM. However, those data could not determine if FM coding was accomplished by the population and/or individual neurons. Our data suggest both coding schemes could operate, as 1) individual neurons are more sensitive to the behaviorally significant FM transition and 2) when single unit recordings are analytically combined across cells, the combined code can produce high stimulus discrimination (FM vs. noise driven excitation), approaching that found in behavioral discrimination of call vs. noise.