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The ultimate goal of LOTUS is to improve confidence in calculated ozone trend values via an improved understanding of the uncertainties. Chapter 3 highlighted many of the challenges facing analyses of long-term ozone time series, and despite the fact that many of those challenges still need to be addressed, it is worthwhile to assess the trend results from this work in such a way as to be able to place those in the context of previous work. This chapter highlights the results of taking the "LOTUS regression" model from Chapter 4 and applying it to the different data sets (i.e., satellite, ground, and model) at different resolutions comparable to those in previous ozone assessments and comprehensive studies (e.g., WMO, 2014; Harris et al., 2015; Steinbrecht et al., 2017). The individual satellite-based trend results are then combined to obtain a single mean ozone trend profile with respective uncertainty estimates. This important yet challenging final step in the assessment has been the cause of debate in the community in recent years. Different methods for combining the individual trend results are discussed and explained, and the final trend profile estimates are analysed for significance.

One of the primary motivations of the LOTUS effort is to attempt to reconcile the discrepancies in ozone trend results from the wealth of literature on the subject. Doing so requires investigating the various methodologies employed to derive long-term trends in ozone as well as to examine the large array of possible variables that feed into those methodologies and analyse their impacts on potential trend results. Given the limited amount of time, the LOTUS group focused on the most common methodology of multiple linear regression and performed a number of sensitivity tests with the goal of trying to establish best practices and come to a consensus on a single regression model to use for this study. This chapter discusses the details and results of the sensitivity tests before describing the components of the final single model that was chosen and the reasons for that choice.

Squamous cell carcinoma (SCC) of the prostate is a rare and clinically aggressive entity that may arise de novo or through transformation of prostatic adenocarcinoma, typically following hormonal or radiation therapy. Confirmation of prostatic origin, especially when evaluating a metastatic focus, often requires correlation with clinical and imaging findings, as the morphologic and immunohistochemical features of SCC are not organ-specific. Comprehensive genomic profiling (CGP) may provide additional information useful for confirming the primary site and for identifying potential targeted therapy options. CGP data may also contribute to our understanding of the molecular basis of squamous differentiation in prostatic malignancies. However, these data are limited, and to our knowledge, there are only three previously published cases of prostatic SCC with reported CGP findings. Herein, we report a case of metastatic keratinizing SCC diagnosed by core needle biopsy in a 68-year-old man with a history of prostatic adenocarcinoma status post radical prostatectomy and androgen deprivation therapy (ADT). NKX3.1 immunohistochemistry was negative. CGP was performed, and a TMPRSS2-ERG fusion, among other genetic alterations, was detected, supporting a diagnosis of metastatic SCC transformed from prostatic adenocarcinoma following ADT. This case supports the use of CGP or other molecular techniques not only to query potential targeted therapy options but also to refine the diagnosis and confirm the primary site of disease in cases with non-specific morphologic and immunophenotypic features, such as SCC.

Recognition of the inverted faces (compared to upright faces) becomes much more difficult, this phenomenon is known as “facial inversion effect”. The role of face inversion on the eye-movement patterns is still under debate. In the current research, we aimed to investigate the effects of face inversion and the number of feature differences on eye-movement patterns during judgement of similarity between two faces. The participants were asked to judge the pairs of faces similarity by a 4-point Likert scale. Eye-movements were recorded during similarity ratings. The faces were presented either upright or inverted. The pairs of the faces were either the same or different. The different pairs of faces were manipulated via the number of feature differences (i.e., one feature or two features). As expected, we found that the inversion of the faces resulted in a higher level of estimated similarity in overall. However, when only the hairs were different between two faces, the inversion of the faces resulted in a lower level of estimated similarity. Surprisingly, the inversion of the faces resulted in a significant decrease of transitions between the pairs of inverted faces. The less eye gaze transitions during similarity rating of inverted pairs suggested that the feature-based processing strategy of inverted faces was less likely to be used in our rating task that presumably exerts no memory load. In conclusion, our findings suggested that both face inversion and the number of feature differences influence the eye-movement patterns during the similarity rating of two simultaneously presented faces.

A wide range of bacteria possess virulence factors such as aminoacyl-tRNA transferases (ATTs) that are capable of rerouting aminoacyl-transfer RNAs away from protein synthesis to conjugate amino acids onto glycerolipids. We recently showed that, although these pathways were thought to be restricted to bacteria, higher fungi also possess ergosteryl-3β-O-L-aspartate synthases (ErdSs), which transfer the L-Asp moiety of aspartyl-tRNA

Background Fine‐needle aspiration with flow cytometry (FNA‐FC) is routinely used in the evaluation of lymph nodes suspicious for lymphoma, yet data comparing immunophenotype distributions and outliers in benign lymph nodes sampled by fine‐needle aspiration (FNA) versus excision are lacking. Methods Flow cytometry data from 289 benign lymph node FNA cases were assessed for the overall antigen distribution, with a focus on outliers relevant to the diagnosis of lymphoma. Distributions and outlier proportions were compared with those of a separate cohort of 298 excisional biopsies. Results Compared with excisional biopsies, FNA specimens overrepresented CD3+ events (72% vs 63%), underrepresented CD19+ events (22% vs 29%), and had 25% fewer large cell–gated events. Normalized antigen distributions in FNA were equivalent to those in excisional biopsy. Twenty‐three percent of FNA‐FC cases exhibited an outlier, including a skewed kappa:lambda light‐chain ratio, increased CD5+ or CD10+ B‐cell events, a skewed CD4:CD8 ratio, and increased CD7 loss on T cells, with no significant differences in frequency or type in comparison with excisional specimens. Outliers for the light‐chain ratio and T‐cell antigens were enriched among older patients and included patients with a variety of autoimmune/rheumatologic conditions. Conclusions Benign lymph node FNA yields flow immunophenotypes remarkably similar to those from excisional biopsies. Outlier flow immunophenotypes are identified in benign lymph nodes sampled by FNA at a frequency similar to that with excisional biopsies. Older patients, who have a higher baseline risk of lymphoma, are more likely to exhibit lymphoma‐mimicking outliers such as a light‐chain predominance on B cells and skewed CD4:CD8 ratios or increased CD7 loss on T cells, and they warrant additional diagnostic caution., Fine‐needle aspiration–based flow cytometry of lymph nodes is comparable to excisional biopsy and exhibits similar outliers. The reference ranges provided in this study can aid pathologists and contribute in the long term to computational flow analysis and biomedical research.