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This paper develops a nonparametric inference framework that is applicable to occupation time curves derived from wearable device data. These curves consider all activity levels within the range of device readings, which is preferable to the practice of classifying activity into discrete categories. Motivated by certain features of these curves, we introduce a powerful likelihood ratio approach to construct confidence bands and compare functional means. Notably, our approach allows discontinuities in the functional covariances while accommodating discretization of the observed trajectories. A simulation study shows that the proposed procedures outperform competing functional data procedures. We illustrate the proposed methods using wearable device data from an NHANES study.

In data analysis using dimension reduction methods, the main goal is to summarize how the response is related to the covariates through a few linear combinations. One key issue is to determine the number of independent, relevant covariate combinations, which is the dimension of the sufficient dimension reduction (SDR) subspace. In this work, we propose an easily-applied approach to conduct inference for the dimension of the SDR subspace, based on augmentation of the covariate set with simulated pseudo-covariates. Applying the partitioning principal to the possible dimensions, we use rigorous sequential testing to select the dimensionality, by comparing the strength of the signal arising from the actual covariates to that appearing to arise from the pseudo-covariates. We show that under a "uniform direction" condition, our approach can be used in conjunction with several popular SDR methods, including sliced inverse regression. In these settings, the test statistic asymptotically follows a beta distribution and therefore is easily calibrated. Moreover, the family-wise type I error rate of our sequential testing is rigorously controlled. Simulation studies and an analysis of newborn anthropometric data demonstrate the robustness of the proposed approach, and indicate that the power is comparable to or greater than the alternatives. This article is protected by copyright. All rights reserved.

Ankylosing spondylitis (AS) is an immune-mediated inflammatory disorder that primarily affects the axial skeleton, especially the sacroiliac joints and spine. This results in chronic back pain and, in extreme cases, ankylosis of the spine. Despite its debilitating effects, the pathogenesis of AS remains to be further elucidated. This study used single cell CITE-seq technology to analyze peripheral blood mononuclear cells (PBMCs) in AS and in healthy controls. We identified a number of molecular features associated with AS. CD52 was found to be overexpressed in both RNA and surface protein expression across several cell types in patients with AS. CD16+ monocytes overexpressed TNFSF10 and IL-18Rα in AS, while CD8+ TEM cells and natural killer cells overexpressed genes linked with cytotoxicity, including GZMH, GZMB, and NKG7. Tregs underexpressed CD39 in AS, suggesting reduced functionality. We identified an overrepresented NK cell subset in AS that overexpressed CD16, CD161, and CD38, as well as cytotoxic genes and pathways. Finally, we developed machine learning models derived from CITE-seq data for the classification of AS and achieved an Area Under the Receiver Operating Characteristic (AUROC) curve of > 0.95. In summary, CITE-seq identification of AS-associated genes and surface proteins in specific cell subsets informs our understanding of pathogenesis and potential new therapeutic targets, while providing new approaches for diagnosis via machine learning.

Early diagnosis of psoriatic arthritis (PSA) is important for successful therapeutic intervention but currently remains challenging due, in part, to the scarcity of non-invasive biomarkers. In this study, we performed single cell profiling of transcriptome and cell surface protein expression to compare the peripheral blood immunocyte populations of individuals with PSA, individuals with cutaneous psoriasis (PSO) alone, and healthy individuals. We identified genes and proteins differentially expressed between PSA, PSO, and healthy subjects across 30 immune cell types and observed that some cell types, as well as specific phenotypic subsets of cells, differed in abundance between these cohorts. Cell type-specific gene and protein expression differences between PSA, PSO, and healthy groups, along with 200 previously published genetic risk factors for PSA, were further used to perform machine learning classification, with the best models achieving AUROC ≥ 0.87 when either classifying subjects among the three groups or specifically distinguishing PSA from PSO. Our findings thus expand the repertoire of gene, protein, and cellular biomarkers relevant to PSA and demonstrate the utility of machine learning-based diagnostics for this disease.

Regulatory T cells (Tregs) reside in nonlymphoid tissues where they carry out unique functions. The molecular mechanisms responsible for Treg accumulation and maintenance in these tissues are relatively unknown. Using an unbiased discovery approach, we identified LAYN (layilin), a C-type lectin-like receptor, to be preferentially and highly expressed on a subset of activated Tregs in healthy and diseased human skin. Expression of layilin on Tregs was induced by TCR-mediated activation in the presence of IL-2 or TGF-β. Mice with a conditional deletion of layilin in Tregs had reduced accumulation of these cells in tumors. However, these animals somewhat paradoxically had enhanced immune regulation in the tumor microenvironment, resulting in increased tumor growth. Mechanistically, layilin expression on Tregs had a minimal effect on their activation and suppressive capacity in vitro. However, expression of this molecule resulted in a cumulative anchoring effect on Treg dynamic motility in vivo. Taken together, our results suggest a model whereby layilin facilitates Treg adhesion in skin and, in doing so, limits their suppressive capacity. These findings uncover a unique mechanism whereby reduced Treg motility acts to limit immune regulation in nonlymphoid organs and may help guide strategies to exploit this phenomenon for therapeutic benefit.

Background Psoriasis is an inflammatory, IL-17–driven skin disease in which autoantigen-induced CD8+ T cells have been identified as pathogenic drivers. Objective Our study focused on comprehensively characterizing the phenotypic variation of CD8+ T cells in psoriatic lesions. Methods We used single-cell RNA sequencing to compare CD8+ T-cell transcriptomic heterogeneity between psoriatic and healthy skin. Results We identified 11 transcriptionally diverse CD8+ T-cell subsets in psoriatic and healthy skin. Among several inflammatory subsets enriched in psoriatic skin, we observed 2 Tc17 cell subsets that were metabolically divergent, were developmentally related, and expressed CXCL13, which we found to be a biomarker of psoriasis severity and which achieved comparable or greater accuracy than IL17A in a support vector machine classifier of psoriasis and healthy transcriptomes. Despite high coinhibitory receptor expression in the Tc17 cell clusters, a comparison of these cells with melanoma-infiltrating CD8+ T cells revealed upregulated cytokine, cytolytic, and metabolic transcriptional activity in the psoriatic cells that differed from an exhaustion program. Conclusion Using high-resolution single-cell profiling in tissue, we have uncovered the diverse landscape of CD8+ T cells in psoriatic and healthy skin, including 2 nonexhausted Tc17 cell subsets associated with disease severity.

Additional file 1: The additional file showed the functionality of the specific methylation site in the control of TSLP expression.

Background Dysregulation of thymic stromal lymphopoietin (TSLP) expressions is linked to asthma and allergic disease. Exposure to phthalate esters, a widely used plasticizer, is associated with respiratory and allergic morbidity. Dibutyl phthalate (DBP) causes TSLP upregulation in the skin. In addition, phthalate exposure is associated with changes in environmentally induced DNA methylation, which might cause phenotypic heterogeneity. This study examined the DNA methylation of the TSLP gene to determine the potential mechanism between phthalate exposure and allergic diseases. Results Among all evaluated, only benzyl butyl phthalate (BBzP) in the settled dusts were negatively correlated with the methylation levels of TSLP and positively associated with children’s respiratory symptoms. The results revealed that every unit increase in BBzP concentration in the settled dust was associated with a 1.75% decrease in the methylation level on upstream 775 bp from the transcription start site (TSS) of TSLP (β = − 1.75, p = 0.015) after adjustment for child’s sex, age, BMI, parents’ smoking status, allergic history, and education levels, PM2.5, formaldehyde, temperature; and relative humidity. Moreover, every percentage increase in the methylation level was associated with a 20% decrease in the risk of morning respiratory symptoms in the children (OR 0.80, 95% CI 0.65–0.99). Conclusions Exposure to BBzP in settled dust might increase children’s respiratory symptoms in the morning through decreasing TSLP methylation. Therefore, the exposure to BBzP should be reduced especially for the children already having allergic diseases.

Background: Sleep dysfunction and sleep disorders are important comorbidities of psoriasis. Not only do these sleep comorbidities contribute to reduced quality of life, but they may also lead to worsening psoriasis and increased susceptibility to cardiometabolic diseases. While psoriasis and sleep dysfunction are thought to be linked by itch, depression, and immune system dysregulation, the relationship between psoriasis and sleep dysfunction is not yet fully understood. Objective: We sought to compare previous studies characterizing the gut microbiome in psoriasis and sleep dysfunction and examine the potential relevance of shared findings on cardiometabolic and overall health. Methods: We performed literature searches of PubMed and Embase databases to find studies evaluating the gut microbiome in psoriasis, sleep dysfunction, and cardiometabolic diseases. Results: Studies characterizing the gut microbiome in psoriasis and sleep dysfunction reveal shared findings, specifically an increased Firmicutes to Bacteroidetes ratio and reduced abundance of short-chain fatty acid–producing bacteria. These dysbiotic features have also been shown to promote systemic inflammation and cardiometabolic disease. Conclusion: In favoring an increased Firmicutes to Bacteroidetes ratio and reduced abundance of short-chain fatty acid–producing bacteria, sleep dysfunction could be contributing to worsening psoriasis and cardiometabolic comorbidities through intestinal dysbiosis. Future studies are needed to determine whether gut- and sleep-targeting interventions could be therapeutic in patients with psoriasis having poor sleep.

Background Psoriasis is a chronic, inflammatory skin disease that impacts 2–3% of the global population. Besides skin manifestations, psoriasis patients have increased susceptibility to a number of comorbidities including psoriatic arthritis, cardiovascular disease, and inflammatory bowel disease. To understand the systemic component of psoriasis pathogenesis, we examined the fecal metagenome, host colonic transcriptome, and host peripheral blood immune profiles of psoriasis patients and healthy controls. Results Our analysis showed increased functional diversity in the gut microbiome of psoriasis patients. In addition, we identified microbial species that preferentially associate with psoriasis patients and which have been previously found to associate with other autoimmune diseases. Intriguingly, our data reveal new insights about psoriasis disease heterogeneity, as we identified three psoriasis subgroups that have distinct microbial and host features. Finally, integrating microbial and host features revealed host-microbe interactions that are specific to psoriasis or particular psoriasis subgroups. Conclusion To our knowledge, this is the first study that provides a comprehensive view of gut microbial function and corresponding host response in psoriasis patients. Our findings provide insight into factors that may affect the development of comorbidities in psoriasis patients and may hold diagnostic potential for early identification of psoriasis patients at risk for these comorbidities.

Determining the clinically optimal dose in methadone maintenance therapy (MMT) is a time-consuming procedure, which considers clinical signs and symptoms.To perform a quantitative trait locus association for identifying genetic variants for MMT dosage that underlie heroin addiction and methadone metabolism and then integrate several genotypic and phenotypic factors are potential predictors for clinically optimal MMT dose for personalized prescription.In total, 316 heroin-dependent patients undergoing MMT were recruited at the Addiction Center of the China Medical University Hospital. A multinomial logistic regression model was used to assess associations between genetic polymorphisms and MMT dosing. The data were randomly separated into training and testing sets. In order to enhance the prediction accuracy and the reliability of the prediction model, we used areas under the receiver operating characteristic curves to evaluate optimal MMT dose in both training and testing sets.Four single nucleotide polymorphisms, namely rs806368 in CNR1, s1386493 in TPH2, s16974799 in CYP2B6, and rs2229205 in OPRL1, were significantly associated with the maximum MMT dose (P < .05). The genetic risk score (GRS) was associated with maximum MMT dose, and after adjustments for age, sex, and body mass index, the GRS remained independently associated with the maximum MMT dose. The area under the receiver operating characteristic curve of the combined GRS and craving score was 0.77 for maximum MMT dose, with 75% sensitivity and 60% specificity.Integrating the GRS and craving scores may be useful in the evaluation of individual MMT dose requirements at treatment initiation. Optimal dose prediction allows clinicians to tailor MMT to each patient's needs.

BACKGROUND: Psoriasis is an inflammatory, IL-17-driven skin disease in which autoantigen-induced CD8(+) T cells have been identified as pathogenic drivers. OBJECTIVE: Our study focused on comprehensively characterizing the phenotypic variation of CD8(+) T cells in psoriatic lesions. METHODS: We used single-cell RNA-seq to compare CD8(+) T cell transcriptomic heterogeneity between psoriatic and healthy skin. RESULTS: We identified 11 transcriptionally diverse CD8(+) T cell subsets in psoriatic and healthy skin. Among several inflammatory subsets enriched in psoriatic skin, we observed two Tc17 subsets that were metabolically divergent, developmentally related, and expressed CXCL13, which we found to be a biomarker of psoriasis severity and which achieved comparable or greater accuracy than IL17A in a support vector machine classifier of psoriasis and healthy transcriptomes. Despite high co-inhibitory receptor expression in the Tc17 clusters, a comparison of these cells with melanoma-infiltrating CD8(+) T cells revealed upregulated cytokine, cytolytic, and metabolic transcriptional activity in the psoriatic cells that differed from an exhaustion program. CONCLUSION: Using high resolution single cell profiling in tissue, we have uncovered the diverse landscape of CD8(+) T cells in psoriatic and healthy skin, including two non-exhausted Tc17 subsets associated with disease severity.

Metabolomics is an emerging new "omics" field involving the systematic analysis of the metabolites in a biologic system. These metabolites provide a molecular snapshot of cellular activity and are thus important for understanding the functional changes in metabolic pathways that drive disease. Recently, metabolomics has been used to study the local and systemic metabolic changes in psoriasis and its cardiometabolic comorbidities. Such studies have revealed novel insights into disease pathogenesis and suggest new biochemical signatures that may be used as a marker of psoriatic disease. This review will discuss common strategies in metabolomics analysis, current findings in the metabolomics of psoriasis, and emerging trends in psoriatic metabolomics.

The IL17A inhibitor secukinumab is efficacious for the treatment of psoriasis. In order to define its mechanism of action, it is important to understand its impact on psoriatic whole skin tissue as well as specific skin-resident immune cell populations such as T lymphocytes. In this study, we treated 15 moderate-to-severe plaque psoriasis patients with secukinumab and characterized the longitudinal transcriptomic changes of whole lesional skin tissue and cutaneous CD4+ T effector cells (Teffs), CD4+ T regulatory cells (Tregs), and CD8+ T effector cells during 12 weeks of treatment. Secukinumab was clinically effective, with 100%, 47%, and 27% of patients in the study achieving PASI75, PASI90, and PASI100 by week 12, respectively. At baseline prior to treatment, we observed that IL17A overexpression predominates in psoriatic CD8+ T cells rather than Teffs, supporting the importance of IL-17-secreting CD8+ T cells (Tc17) compared to IL-17-secreting CD4+ T cells (Th17) cells in the pathogenesis of psoriasis. Although secukinumab targets only IL17A, we observed rapid reduction of IL17A, IL17F, IL23A, IL23R, and IFNG expression in lesional skin as soon as 2 weeks after initiation of treatment and normalization of expression by week 12. Secukinumab treatment resulted in resolution of 89-97% of psoriasis-associated expression differences in both bulk tissue and T cell subsets by week 12 of treatment. Overall, secukinumab appears to rapidly reverse many of the molecular hallmarks of psoriasis.

Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase that has been recognized as a therapeutic target for EML4-ALK fusion-positive nonsmall cell lung cancer (NSCLC) treatment using type I kinase inhibitors such as crizotinib to take over the ATP binding site. According to Shaw’s measurements, ALK carrying G1202R mutation shows reduced response to crizotinib (IC50 = 382 nM vs. IC50 = 20 nM for wild-type), whereas L1198F mutant is more responsive (IC50 = 0.4 nM). Interestingly, the double mutant L1198F/G1202R maintains a similar response (IC50 = 31 nM) to the wild-type. Herein we conducted molecular modeling simulations to elucidate the varied crizotinib sensitivities in three mutants carrying L1198F and/or G1202R. Both L1198 and G1202 are near the ATP pocket. Mutation G1202R causes steric hindrance that blocks crizotinib accessibility, which greatly reduces efficacy, whereas mutation L1198F enlarges the binding pocket entrance and hydrophobically interacts with crizotinib to enhance sensitivity. With respect to the double mutant L1198F/G1202R, F1198 indirectly pulls R1202 away from the binding entrance and consequently alleviates the steric obstacle introduced by R1202. These results demonstrated how the mutated residues tune the crizotinib response and may assist kinase inhibitor development especially for ALK G1202R, analogous to the ROS1 G2302R and MET G1163R mutations that are also resistant to crizotinib treatment in NSCLC.

This paper develops an empirical likelihood approach to testing for stochastic ordering between two univariate distributions under right censorship. The proposed test is based on a maximally selected local empirical likelihood statistic. The asymptotic null distribution is expressed in terms of a Brownian bridge. The new procedure is shown via a simulation study to have superior power to the log-rank and weighted Kaplan–Meier tests under crossing hazard alternatives. The approach is illustrated using data from a randomized clinical trial involving the treatment of severe alcoholic hepatitis.

New nonparametric tests for the ordering of multiple survival functions are developed with the possibility of right censorship taken into account. The motivation comes from non-inferiority trials with multiple treatments. The proposed tests are based on nonparametric likelihood ratio statistics, which are known to provide more powerful tests than Wald-type procedures, but in this setting have only been studied for pairs of survival functions or in the absence of censoring. We introduce a novel type of pool adjacent violator algorithm that leads to a complete solution of the problem. The limit distributions can be expressed as weighted sums of squares involving projections of certain Gaussian processes onto the given ordered alternative. A simulation study shows that the new procedures have superior power to a competing combined-pairwise Cox model approach. We illustrate the proposed methods using data from a three-arm non-inferiority trial.

BackgroundGout is independently associated with increased risk of type 2 diabetes mellitus (T2DM). Urate-lowering therapy (ULT) might be beneficial in lowering the risks of T2DM. Therefore, we conducted a nested case-control study to evaluate the associations between ULT and T2DM.MethodsThis study retrieved the data of 29,765 gout patients from the period of 1998-2010 by using data from Taiwan's National Health Insurance Research Database. Controls (n = 59,530) were matched at a 1:2 ratio by age, sex, and region. Multivariate Cox proportional hazards regression were performed to examine the dose-dependent relationship between ULT and T2DM.ResultsThe adjusted Hazard ratio (HR) for the association of T2DM with allopurinol or benzbromarone exposure was 1.17 (95% confidence interval (CI) 1.07-1.28) and1.09 (95% CI 1.03-1.15), respectively. The HR for the cumulative allopurinol dose was 0.87 (95% CI 0.71-1.07) for patients with dose ≤1.3 mg/day and was 1.31 (95% CI 1.13-1.52) for those with a dose >15.2 mg/day. Similarly, the HR for the cumulative benzbromarone dose was 0.85(95% CI 0.75-0.96) for patients with a dose ≤1.3 mg/day and 1.42 (95% CI 1.30-1.55) for patients with a dose>9.4 mg/day, respectively. Moreover, the average exposure dose of >100 mg/day for allopurinol and >100 mg/day for benzbromarone was associated with a 1.28-fold (95% CI 1.11-1.48) and 1.47-fold (95% CI 1.23-1.76) T2DM risk respectively. The HR for patients in aged >50 years group with cumulative dose ≤1.3 mg/day of allopurinol or benzbromarone had lower risk of T2DM (HR = 0.74, 95% CI 0.58-0.94 for allopurinol; HR = 0.79, 95% CI 0.69-0.90 for benzbromarone).ConclusionGout patients with prolonged ULT and a high dose of ULT were associated with a significant increase in T2DM risk. Although gout patients with age greater than 50 years and a lower dose of ULT may be beneficial in lowering T2DM risk, further clinical studies need to be confirmed these associations.

Background Psoriasis impacts 1–3% of the world’s population and is characterized by hyper-proliferation of keratinocytes and increased inflammation. At the molecular level, psoriasis is commonly driven by a Th17 response, which serves as a major therapeutic target. Microbiome perturbations have been associated with several immune-mediated diseases such as atopic dermatitis, asthma, and multiple sclerosis. Although a few studies have investigated the association between the skin microbiome and psoriasis, conflicting results have been reported plausibly due to the lack of standardized sampling and profiling protocols, or to inherent microbial variability across human subjects and underpowered studies. To better understand the link between the cutaneous microbiota and psoriasis, we conducted an analysis of skin bacterial communities of 28 psoriasis patients and 26 healthy subjects, sampled at six body sites using a standardized protocol and higher sequencing depth compared to previous studies. Mouse studies were employed to examine dermal microbial-immune interactions of bacterial species identified from our study. Results Skin microbiome profiling based on sequencing the 16S rRNA V1–V3 variable region revealed significant differences between the psoriasis-associated and healthy skin microbiota. Comparing the overall community structures, psoriasis-associated microbiota displayed higher diversity and more heterogeneity compared to healthy skin bacterial communities. Specific microbial signatures were associated with psoriatic lesional, psoriatic non-lesional, and healthy skin. Specifically, relative enrichment of Staphylococcus aureus was strongly associated with both lesional and non-lesional psoriatic skin. In contrast, Staphylococcus epidermidis and Propionibacterium acnes were underrepresented in psoriatic lesions compared to healthy skin, especially on the arm, gluteal fold, and trunk. Employing a mouse model to further study the impact of cutaneous Staphylcoccus species on the skin T cell differentiation, we found that newborn mice colonized with Staphylococcus aureus demonstrated strong Th17 polarization, whereas mice colonized with Staphylococcus epidermidis or un-colonized controls showed no such response. Conclusion Our results suggest that microbial communities on psoriatic skin is substantially different from those on healthy skin. The psoriatic skin microbiome has increased diversity and reduced stability compared to the healthy skin microbiome. The loss of community stability and decrease in immunoregulatory bacteria such as Staphylococcus epidermidis and Propionibacterium acnes may lead to higher colonization with pathogens such as Staphylococcus aureus, which could exacerbate cutaneous inflammation along the Th17 axis. Electronic supplementary material The online version of this article (10.1186/s40168-018-0533-1) contains supplementary material, which is available to authorized users.

This review summarizes existing research on the gut microbiome composition and function in psoriasis and psoriatic arthritis, exploring potential roles in disease pathogenesis, progression, and management. A strong relationship between skin, joint, and gastrointestinal inflammation exists, as demonstrated by an increased prevalence of psoriasis, psoriatic arthritis, and inflammatory bowel disease co-occurring together; however, the link between them has not been fully elucidated. Studies analyzing the gut microbiome in psoriasis and psoriatic arthritis reveal a unique pattern of dysbiosis. With regard to the gut microbiome's role in psoriasis and psoriatic arthritis pathogenesis, we discuss several theories including intestinal permeability, altered immune homeostasis, and imbalance of short- and medium-chain fatty acid-producing bacteria. We also discuss how the gut microbiome affects patient risk of psoriatic arthritis and other serious comorbidities, and how fecal microbes could be used clinically as therapeutic targets or markers of disease.

It has long been recognized that anatomic location is an important feature for defining distinct subtypes of plaque psoriasis. However, little is known about the molecular differences between scalp, palmoplantar, and conventional plaque psoriasis. To investigate the molecular heterogeneity of these psoriasis subtypes, we performed RNA-seq and flow cytometry on skin samples from individuals with scalp, palmoplantar, and conventional plaque psoriasis, along with samples from healthy control patients. We performed differential expression analysis and network analysis using weighted gene coexpression network analysis (WGCNA). Our analysis revealed a core set of 763 differentially expressed genes common to all sub-types of psoriasis. In contrast, we identified 605, 632, and 262 genes uniquely differentially expressed in conventional, scalp, and palmoplantar psoriasis, respectively. WGCNA and pathway analysis revealed biological processes for the core genes as well as subtype-specific genes. Flow cytometry analysis revealed a shared increase in the percentage of CD4+ T regulatory cells in all psoriasis subtypes relative to controls, whereas distinct psoriasis subtypes displayed differences in IL-17A, IFN-gamma, and IL-22 production. This work reveals the molecular heterogeneity of plaque psoriasis and identifies subtype-specific signaling pathways that will aid in the development of therapy that is appropriate for each subtype of plaque psoriasis.

Figure S1. Box plot shows the average weighted UniFrac distances among samples within each disease state at (a) arm, (b)trunk, (c)leg, (d)axilla, (e)gluteal fold and (f)scalp (*: p-value

Objective This study reported an intraoperative navigation system for single-splint two-jaw orthognathic surgery, and assessed the accuracy of transferring the computer assisted surgical simulation. Methods A skull model was used for validation, and twenty patients receiving such procedure were enrolled. The procedure contained five phases, including virtual surgery on three-dimensional images, fabrication of surgical positioning guides, preparation of registration and validation landmarks, confirmation of bony position during surgery, and postoperative assessment. Target registration error (TRE) and differences between simulation (T0) and postoperative images (T1) were measured from landmarks to Frankfort horizontal plane (FHP), mid–sagittal plane (MSP), and coronal plane (COP). Results For the model experiment, mean TRE was lowest using the hard tissue landmarks (0.60 ± 0.27 mm), and the mean difference (T1-T0) was less than 1 mm to all three planes. For the patients, mean TRE was 1.07 ± 0.18 mm from the hard tissue landmarks. The mean difference was 0.96. ± 0.60 mm from MSP, 1.39 ± 1.11 mm from FHP, and 2.12 ± 1.82 mm from COP. The differences were not significant. Both surgeons and patients were satisfied with the surgical outcome. Conclusion This study showed that the navigation system had acceptable accuracy and was useful for the two-jaw orthognathic surgery using single-splint method.

Three-dimensional computer-assisted orthognathic surgery has been applied to improve planning and outcome. This study presents our experience with this promising modality for simulation of surgery, prefabrication of positioning guides, and navigation of the surgery.Thirty-seven patients who received surgical simulation and intraoperative navigation for 2-jaw orthognathic surgery were recruited. Preoperative 3-dimensional cone-beam computed tomographic images were used for surgical simulation and design of intraoperative guidance. An initial surgical plan was developed and transferred for 3-dimensional virtual surgery. Modification of the surgical plan was made if facial symmetry and skeletal harmony or collision of ramus segments were concerned. The result of virtual surgery was used to design and manufacture positioning guides and perform preoperative navigation planning. During the operation, the positioning guides were used to transfer the virtual planning to actual surgery, and a real-time navigation system was used to confirm the predetermined position of the maxillomandibular complex. For assessment of the computer-assisted surgical system, the simulation image was superimposed to the postoperative image for comparison.The computer-assisted orthognathic surgery was successfully carried out in all patients. The initial surgical plan was modified in 17 patients in whom the position of maxillomandibular complex was changed. The positioning guides were helpful in controlling the spatial position of the maxillomandibular complex. The BrainLabTR navigation system was useful to further confirm the position of the facial bone. Superimposition of the simulation and postoperative images revealed satisfactory result with acceptable errors. The difference ranged from 0.05 to 1.46 mm, with a mean value of 0.66 mm, for patients using the positioning guides; and the difference ranged from 0.07 to 2.30 mm, with a mean value of 1.20 mm, for patients using the navigation system. Overall, patient and doctor satisfaction was high.This computer-assisted orthognathic surgery system helps to improve surgical planning, reduce surgical difficulty, facilitate positioning and fixation of the maxillomandibular complex, and improve outcome.

Importance Polycyclic aromatic hydrocarbons are common carcinogenic and neurotoxic urban air pollutants. Toxic exposures, including air pollution, are disproportionately high in communities of color and frequently co-occur with chronic economic deprivation. Objectives We examined whether the association between child IQ and prenatal exposure to polycyclic aromatic hydrocarbons differed between groups of children whose mothers reported high vs. low material hardship during their pregnancy and through child age 5. We tested statistical interactions between hardships and polycyclic aromatic hydrocarbons, as measured by DNA adducts in cord blood, to determine whether material hardship exacerbated the association between adducts and IQ scores. Design Prospective cohort. Participants were recruited from 1998 to 2006 and followed from gestation through age 7 years. Setting Urban community (New York City) Participants A community-based sample of 276 minority urban youth Exposure measure Polycyclic aromatic hydrocarbon–DNA adducts in cord blood as an individual biomarker of prenatal polycyclic aromatic hydrocarbon exposure. Maternal material hardship self-reported prenatally and at multiple timepoints through early childhood. Main outcome measure Child IQ at 7 years assessed using the Wechsler Intelligence Scale for Children. Results Significant inverse effects of high cord PAH–DNA adducts on full scale IQ, perceptual reasoning and working memory scores were observed in the groups whose mothers reported a high level of material hardship during pregnancy or recurring high hardship into the child's early years, and not in those without reported high hardship. Significant interactions were observed between high cord adducts and prenatal hardship on working memory scores ( β = − 8.07, 95% CI (− 14.48, − 1.66)) and between high cord adducts and recurrent material hardship ( β = − 9.82, 95% CI (− 16.22, − 3.42)). Conclusion The findings add to other evidence that socioeconomic disadvantage can increase the adverse effects of toxic physical “stressors” like air pollutants. Observed associations between high cord adducts and reduced IQ were significant only among the group of children whose mothers reported high material hardship. These results indicate the need for a multifaceted approach to prevention.

Background/PurposeOrthognathic surgery alters the position of maxilla and mandible, and consequently changes the nasal shape. The nasal change remains a concern to Asian patients. The aim of this study was to measure the nasal changes using a novel three-dimensional photographic imaging method.MethodsA total of 38 patients with Class III malocclusion and prognathism were enrolled. All patients underwent two-jaw surgery with the standard technique. A nasal alar cinching suture was included at the end of procedure. Facial landmarks and nasal morphology were defined and measured from pre- and postoperative three-dimensional photographic images. Intra-rater errors on landmark identification were controlled. Patient's reports of perceptual nasal changes were recorded.ResultsThe average width of the alar base and subalare remained similar after surgery. Alar width was increased by 0.74 mm. Nasal height and length remained the same. Nasolabial angle increased significantly. The area of nostril show revealed a significant increase and was correlated with a decrease of columella inclination. Nasal tip projection decreased significantly, by 1.99 mm. Preoperative nasal morphology was different between patients with and without cleft lip/palate, but most nasal changes were concordant. In the self-perception, 37% of patients reported improved nasal appearance, 58% reported no change, and 5% were not satisfied with the nasal changes.ConclusionAfter the surgery, characteristic nasal changes occurred with an increase of nasolabial angle and nostril show, but a preserved nasal width. The majority of patients did not perceive adverse nasal changes.

To increase the performance of sport team, the tactics analysis of team from game video is essential. Trajectories of the players are the most useful cues in a sport video for tactics analysis. In this paper, we propose a technique to reconstruct the trajectories of players from broadcast basketball videos. We first propose a mosaic based approach to detect the boundary lines of court. Then, the locations of players are determined by the integration of shape and color visual information. A layered graph is constructed for the detected players, which includes all possible trajectories. A dynamic programming based algorithm is applied to find the trajectory of each player. Finally, the trajectories of players are displayed on a standard basketball court model by a homography transformation. In contrast to related works, our approach exploits more spatio-temporal information in video. Experimental results show that the proposed approach works well and outperforms some existing technique.

PurposeTo understand the changes in the microbiome in psoriatic disease, we conducted a systematic review of studies comparing the skin and gut microbiota in psoriatic individuals and healthy controls.FindingsOur review of studies pertaining to the cutaneous microbiome showed a trend towards an increased relative abundance of Streptococcus and a decreased level of Propionibacterium in psoriasis patients compared to controls. In the gut microbiome, the ratio of Firmicutes and Bacteroidetes was perturbed in psoriatic individuals compared to healthy controls. Actinobacteria was also relatively underrepresented in psoriasis patients relative to healthy individuals.SummaryAlthough the field of the psoriatic microbiome is relatively new, these first studies reveal interesting differences in microbiome composition that may be associated with the development of psoriatic comorbidities and serve as novel therapeutic targets.

Recent studies have suggested that the intestinal microbiome plays an important role in modulating risk of several chronic diseases, including inflammatory bowel disease, obesity, type 2 diabetes, cardiovascular disease, and cancer. At the same time, it is now understood that diet plays a significant role in shaping the microbiome, with experiments showing that dietary alterations can induce large, temporary microbial shifts within 24 h. Given this association, there may be significant therapeutic utility in altering microbial composition through diet. This review systematically evaluates current data regarding the effects of several common dietary components on intestinal microbiota. We show that consumption of particular types of food produces predictable shifts in existing host bacterial genera. Furthermore, the identity of these bacteria affects host immune and metabolic parameters, with broad implications for human health. Familiarity with these associations will be of tremendous use to the practitioner as well as the patient.

Summary A decline in mitochondrial electron transport chain (ETC) function has long been implicated in aging and various diseases. Recently, moderate mitochondrial ETC dysfunction has been found to prolong lifespan in diverse organisms, suggesting a conserved and complex role of mitochondria in longevity determination. Several nuclear transcription factors have been demonstrated to mediate the lifespan extension effect associated with partial impairment of the ETC, suggesting that compensatory transcriptional response to be crucial. In this study, we showed that the transcription factors CEP‐1/p53 and CEH‐23 act through a similar mechanism to modulate longevity in response to defective ETC in Caenorhabditis elegans. Genomewide gene expression profiling comparison revealed a new link between these two transcription factors and AAK‐2/AMP kinase (AMPK) signaling. Further functional analyses suggested that CEP‐1/p53 and CEH‐23 act downstream of AAK‐2/AMPK signaling and CRTC‐1 transcriptional coactivator to promote stress resistance and lifespan. As AAK‐2, CEP‐1, and CEH‐23 are all highly conserved, our findings likely provide important insights for understanding the organismal adaptive response to mitochondrial dysfunction in diverse organisms and will be relevant to aging and pathologies with a mitochondrial etiology in human.

Study of factors affecting the functioning of the human brain has been of considerable interest for more than a century. In this paper, we focus on the structure of brain arterial systems in humans and study how this might be related to factors such as age, gender or handedness (left or right handed). To facilitate this study we first represent brain arterial systems using tree-structured objects and construct stochastic systems whose realizations are such tree-structured objects. We show that the parameters of the stochastic system, primarily the branching probabilities, may be effectively studied using a logistic regression framework. This appears to be a fruitful approach for understanding tree-structured data. Applying this novel approach to actual data collected on 98 subjects, we are able to conclude that age and gender do seem to influence brain artery branching patterns. Most brain arteries have decreasing branching probabilities with increasing age, and brain arteries of females are slightly more likely to branch than those of males. In addition, we find an interesting phenomenon that, as age increases, branching probabilities of thick arteries decrease while those of thin arteries increase. Possible medical/biological interpretations of this finding are provided.