Unifying community-wide whole-brain imaging datasets enables robust automated neuron identification and reveals determinants of neuron positioning in C. elegans.

We develop a data harmonization approach for C. elegans volumetric microscopy data, still or video, consisting of a standardized format, data pre-processing techniques, and a set of human-in-the-loop machine learning based analysis software tools. We unify a diverse collection of 118 whole-brain neural activity imaging datasets from 5 labs, storing these and accompanying tools in an online repository called WormID (wormid.org). We use this repository to generate a statistical atlas that, for the first time, enables accurate automated cellular identification that generalizes across labs, approaching human performance in some cases. We mine this repository to identify factors that influence the developmental positioning of neurons. To facilitate communal use of this repository, we created open-source software, code, web-based tools, and tutorials to explore and curate datasets for contribution to the scientific community. This repository provides a growing resource for experimentalists, theorists, and toolmakers to investigate neuroanatomical organization and neural activity across diverse experimental paradigms, develop and benchmark algorithms for automated neuron detection, segmentation, cell identification, tracking, and activity extraction, and inform models of neurobiological development and function.

Lung Cancer in Never Smokers: Delving into Epidemiology, Genomic and Immune Landscape, Prognosis, Treatment, and Screening.

Lung cancer in never smokers (LCINS) represents a growing and distinct entity within the broader landscape of lung malignancies. This review provides a comprehensive overview of LCINS, encompassing its epidemiologic trends, risk factors, distinct genomic alterations, clinical outcomes and the ongoing initiative aimed at formulating screening guidelines tailored to this unique population. As LCINS continues to gain prominence, understanding its intricate genomic landscape has become pivotal for tailoring effective therapeutic strategies. Moreover, LCINS does not meet the criteria for lung cancer screening as per the current guidelines. Hence, there is an urgent need to explore its heterogeneity in order to devise optimal screening guidelines conducive to early-stage detection. This review underscores the vital importance of detailed research to elucidate the multifaceted nature of LCINS, with the potential to shape future clinical management and screening recommendations for this unique and growing patient cohort.

Decellularized Wharton jelly matrix: a biomimetic scaffold for ex vivo hematopoietic stem cell culture.

Hematopoietic stem progenitor cells (HSPCs) reside in the bone marrow (BM) hematopoietic "niche," a special 3-dimensional (3D) microenvironment that regulates HSPC self-renewal and multipotency. In this study, we evaluated a novel 3D in vitro culture system that uses components of the BM hematopoietic niche to expand umbilical cord blood (UCB) CD34+ cells. We developed this model using decellularized Wharton jelly matrix (DWJM) as an extracellular matrix (ECM) scaffold and human BM mesenchymal stromal cells (MSCs) as supporting niche cells. To assess the efficacy of this model in expanding CD34+ cells, we analyzed UCB CD34+ cells, following culture in DWJM, for proliferation, viability, self-renewal, multilineage differentiation, and transmigration capability. We found that DWJM significantly expanded UCB HSPC subset. It promoted UCB CD34+ cell quiescence, while maintaining their viability, differentiation potential with megakaryocytic differentiation bias, and clonogenic capacity. DWJM induced an increase in the frequency of c-kit+ cells, a population with enhanced self-renewal ability, and in CXCR4 expression in CD34+ cells, which enhanced their transmigration capability. The presence of BM MSCs in DWJM, however, impaired UCB CD34+ cell transmigration and suppressed CXCR4 expression. Transcriptome analysis indicated that DWJM upregulates a set of genes that are specifically involved in megakaryocytic differentiation, cell mobility, and BM homing. Collectively, our results indicate that the DWJM-based 3D culture system is a novel in vitro model that supports the proliferation of UCB CD34+ cells with enhanced transmigration potential, while maintaining their differentiation potential. Our findings shed light on the interplay between DWJM and BM MSCs in supporting the ex vivo culture of human UCB CD34+ cells for use in clinical transplantation.

Interdisciplinary treatment for a compensated Class II partially edentulous malocclusion: Orthodontic creation of a posterior implant site.

A 36-year-old woman with good periodontal health sought treatment for a compensated Class II partially edentulous malocclusion associated with a steep mandibular plane (SN-MP, 45°), 9 missing teeth, a 3-mm midline discrepancy, and compromised posterior occlusal function. She had multiple carious lesions, a failing fixed prostheses in the mandibular right quadrant replacing the right first molar, and a severely atrophic edentulous ridge in the area around the mandibular left first and second molars. After restoration of the caries, the mandibular left third molar served as anchorage to correct the mandibular arch crowding. The mandibular left second premolar was retracted with a light force of 2 oz (about 28.3 cN) on the buccal and lingual surfaces to create an implant site between the premolars. Modest lateral root resorption was noted on the distal surface of the mandibular left second premolar after about 7 mm of distal translation in 7 months. Six months later, implants were placed in the mandibular left and right quadrants; the spaces were retained with the fixed appliance for 5 months and a removable retainer for 1 month. Poor cooperation resulted in relapse of the mandibular left second premolar back into the implant site, and it was necessary to reopen the space. When the mandibular left fixture was uncovered, a 3-mm deep osseous defect on the distobuccal surface was found; it was an area of relatively immature bundle bone, because the distal aspect of the space was reopened after the relapse. Subsequent bone grafting resulted in good osseous support of the implant-supported prosthesis. The relatively thin band of attached gingiva on the implant at the mandibular right first molar healed with a recessed contour that was susceptible to food impaction. A free gingival graft restored soft tissue form and function. This severe malocclusion with a discrepancy index value of 28 was treated to an excellent outcome in 38 months of interdisciplinary treatment. The Cast-Radiograph Evaluation score was 13. However, the treatment was complicated by routine relapse and implant osseous support problems. Retreatment of space opening and 2 additional surgeries were required to correct an osseous defect and an inadequate soft tissue contour. Orthodontic treatment is a viable option for creating implant sites, but fixed retention is required until the prosthesis is delivered. Bone augmentation is indicated at the time of implant placement to offset expected bone loss. Complex restorative treatment may result in routine complications that are effectively managed with interdisciplinary care.

Differentiating Wheat Genotypes by Bayesian Hierarchical Nonlinear Mixed Modeling of Wheat Root Density.

Ensuring future food security for a growing population while climate change and urban sprawl put pressure on agricultural land will require sustainable intensification of current farming practices. For the crop breeder this means producing higher crop yields with less resources due to greater environmental stresses. While easy gains in crop yield have been made mostly "above ground," little progress has been made "below ground"; and yet it is these root system traits that can improve productivity and resistance to drought stress. Wheat pre-breeders use soil coring and core-break counts to phenotype root architecture traits, with data collected on rooting density for hundreds of genotypes in small increments of depth. The measured densities are both large datasets and highly variable even within the same genotype, hence, any rigorous, comprehensive statistical analysis of such complex field data would be technically challenging. Traditionally, most attributes of the field data are therefore discarded in favor of simple numerical summary descriptors which retain much of the high variability exhibited by the raw data. This poses practical challenges: although plant scientists have established that root traits do drive resource capture in crops, traits that are more randomly (rather than genetically) determined are difficult to breed for. In this paper we develop a hierarchical nonlinear mixed modeling approach that utilizes the complete field data for wheat genotypes to fit, under the Bayesian paradigm, an "idealized" relative intensity function for the root distribution over depth. Our approach was used to determine heritability: how much of the variation between field samples was purely random vs. being mechanistically driven by the plant genetics? Based on the genotypic intensity functions, the overall heritability estimate was 0.62 (95% Bayesian confidence interval was 0.52 to 0.71). Despite root count profiles that were statistically very noisy, our approach led to denoised profiles which exhibited rigorously discernible phenotypic traits. Profile-specific traits could be representative of a genotype, and thus, used as a quantitative tool to associate phenotypic traits with specific genotypes. This would allow breeders to select for whole root system distributions appropriate for sustainable intensification, and inform policy for mitigating crop yield risk and food insecurity.

Influences of Host Community Characteristics on Borrelia burgdorferi Infection Prevalence in Blacklegged Ticks.

Lyme disease is a major vector-borne bacterial disease in the USA. The disease is caused by Borrelia burgdorferi, and transmitted among hosts and humans, primarily by blacklegged ticks (Ixodes scapularis). The ~25 B. burgdorferi genotypes, based on genotypic variation of their outer surface protein C (ospC), can be phenotypically separated as strains that primarily cause human diseases-human invasive strains (HIS)-or those that rarely do. Additionally, the genotypes are non-randomly associated with host species. The goal of this study was to examine the extent to which phenotypic outcomes of B. burgdorferi could be explained by the host communities fed upon by blacklegged ticks. In 2006 and 2009, we determined the host community composition based on abundance estimates of the vertebrate hosts, and collected host-seeking nymphal ticks in 2007 and 2010 to determine the ospC genotypes within infected ticks. We regressed instances of B. burgdorferi phenotypes on site-specific characteristics of host communities by constructing Bayesian hierarchical models that properly handled missing data. The models provided quantitative support for the relevance of host composition on Lyme disease risk pertaining to B. burgdorferi prevalence (i.e. overall nymphal infection prevalence, or NIPAll) and HIS prevalence among the infected ticks (NIPHIS). In each year, NIPAll and NIPHIS was found to be associated with host relative abundances and diversity. For mice and chipmunks, the association with NIPAll was positive, but tended to be negative with NIPHIS in both years. However, the direction of association between shrew relative abundance with NIPAll or NIPHIS differed across the two years. And, diversity (H') had a negative association with NIPAll, but positive association with NIPHIS in both years. Our analyses highlight that the relationships between the relative abundances of three primary hosts and the community diversity with NIPAll, and NIPHIS, are variable in time and space, and that disease risk inference, based on the role of host community, changes when we examine risk overall or at the phenotypic level. Our discussion focuses on the observed relationships between prevalence and host community characteristics and how they substantiate the ecological understanding of phenotypic Lyme disease risk.

Bimaxillary protrusion with an atrophic alveolar defect: orthodontics, autogenous chin-block graft, soft tissue augmentation, and an implant.

Bimaxillary protrusion in a 28-year-old woman was complicated by multiple missing, restoratively compromised, or hopeless teeth. The maxillary right central incisor had a history of avulsion and replantation that subsequently evolved into generalized external root resorption with Class III mobility and severe loss of the supporting periodontium. This complex malocclusion had a discrepancy index of 21, and 8 additional points were scored for the atrophic dental implant site (maxillary right central incisor). The comprehensive treatment plan included extraction of 4 teeth (both maxillary first premolars, the maxillary right central incisor, and the mandibular right first molar), orthodontic closure of all spaces except for the future implant site (maxillary right central incisor), augmentation of the alveolar defect with an autogenous chin-block graft, enhancement of the gingival biotype with a connective tissue graft, and an implant-supported prosthesis. Orthodontists must understand the limitations of bone grafts. Augmented alveolar defects are slow to completely turn over to living bone, so they are usually good sites for implants but respond poorly to orthodontic space closure. However, postsurgical orthodontic treatment is often indicated to optimally finish the esthetic zone before placing the final prosthesis. The latter was effectively performed for this patient, resulting in a total treatment time of about 36 months for comprehensive interdisciplinary care. An excellent functional and esthetic result was achieved.

Disease and treatment perceptions among Asian Americans diagnosed with chronic hepatitis B infection.

BACKGROUND: In the US, over 1 million Asian Americans are estimated to be living with chronic hepatitis B (CHB). Research has shown low awareness of CHB and different attitudes towards its treatment among the diverse ethnicities of Asian Americans. OBJECTIVE: This study aimed to understand the perceptions and attitudes of CHB treatment among Asian Americans diagnosed with CHB who were either treatment-naïve or being treated for CHB with oral antivirals, and to understand the relative importance of different clinical and economic attributes of oral antivirals that affect CHB treatment decisions and choices. DESIGN: Face-to-face structured survey administered to participants at central research facilities by interviewers of each participating ethnicity. PARTICIPANTS: CHB patients from Chinese, Korean, and Vietnamese communities of New York metropolitan, San Francisco/Bay, and Los Angeles/Orange County areas. MAIN MEASURES: A 'conjoint' exercise (discrete choice model) assessed the relative impact of treatment attributes on treatment choice. Implicit "trade-off" decisions made by respondents were estimated using a hierarchical Bayesian model. KEY RESULTS: Among 252 participants, 36 % were Chinese, 34 % Vietnamese, and 31 % Korean; 56 % were treatment-naïve and 44 % were being treated with an oral antiviral for CHB. The majority (88 %) believed that, if left untreated, CHB can lead to serious liver damage; 72 % believed there are effective prescription medications to treat CHB; and 39 % showed reluctance to be on long-term therapy for CHB because of concerns over side effects. Long-term risk of kidney damage was given the highest relative importance (38 %) when choosing CHB treatment, followed by medication cost (23.4 %), long-term risk of bone thinning (18 %), long-term efficacy (9 %), time on US market (6.8 %), and number of patients treated globally (4.9 %). Results were consistent across ethnicities. CONCLUSIONS: Patients need access to improved education regarding CHB disease progression, its management, disease outcomes, and the importance of long-term treatment of the disease.

Model-based assessment of estuary ecosystem health using the latent health factor index, with application to the richibucto estuary.

The ability to quantitatively assess ecological health is of great interest to those tasked with monitoring and conserving ecosystems. For decades, biomonitoring research and policies have relied on multimetric health indices of various forms. Although indices are numbers, many are constructed based on qualitative procedures, thus limiting the quantitative rigor of the practical interpretations of such indices. The statistical modeling approach to construct the latent health factor index (LHFI) was recently developed. With ecological data that otherwise are used to construct conventional multimetric indices, the LHFI framework expresses such data in a rigorous quantitative model, integrating qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modeling approach allows unified statistical inference of health for observed sites (along with prediction of health for partially observed sites, if desired) and of the relevance of ecological drivers, all accompanied by formal uncertainty statements from a single, integrated analysis. Thus far, the LHFI approach has been demonstrated and validated in a freshwater context. We adapt this approach to modeling estuarine health, and illustrate it on the previously unassessed system in Richibucto in New Brunswick, Canada, where active oyster farming is a potential stressor through its effects on sediment properties. Field data correspond to health metrics that constitute the popular AZTI marine biotic index and the infaunal trophic index, as well as abiotic predictors preconceived to influence biota. Our paper is the first to construct a scientifically sensible model that rigorously identifies the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content-all regarded a priori as qualitatively important abiotic drivers-towards site health in the Richibucto ecosystem. This suggests the potential effectiveness of the LHFI approach for assessing not only freshwater systems but aquatic ecosystems in general.

A unifying approach for food webs, phylogeny, social networks, and statistics.

A food web consists of nodes, each consisting of one or more species. The role of each node as predator or prey determines the trophic relations that weave the web. Much effort in trophic food web research is given to understand the connectivity structure, or the nature and degree of dependence among nodes. Social network analysis (SNA) techniques--quantitative methods commonly used in the social sciences to understand network relational structure--have been used for this purpose, although postanalysis effort or biological theory is still required to determine what natural factors contribute to the feeding behavior. Thus, a conventional SNA alone provides limited insight into trophic structure. Here we show that by using novel statistical modeling methodologies to express network links as the random response of within- and internode characteristics (predictors), we gain a much deeper understanding of food web structure and its contributing factors through a unified statistical SNA. We do so for eight empirical food webs: Phylogeny is shown to have nontrivial influence on trophic relations in many webs, and for each web trophic clustering based on feeding activity and on feeding preference can differ substantially. These and other conclusions about network features are purely empirical, based entirely on observed network attributes while accounting for biological information built directly into the model. Thus, statistical SNA techniques, through statistical inference for feeding activity and preference, provide an alternative perspective of trophic clustering to yield comprehensive insight into food web structure.

Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.

Asthma is a common disease with a complex risk architecture including both genetic and environmental factors. We performed a meta-analysis of North American genome-wide association studies of asthma in 5,416 individuals with asthma (cases) including individuals of European American, African American or African Caribbean, and Latino ancestry, with replication in an additional 12,649 individuals from the same ethnic groups. We identified five susceptibility loci. Four were at previously reported loci on 17q21, near IL1RL1, TSLP and IL33, but we report for the first time, to our knowledge, that these loci are associated with asthma risk in three ethnic groups. In addition, we identified a new asthma susceptibility locus at PYHIN1, with the association being specific to individuals of African descent (P = 3.9 × 10(-9)). These results suggest that some asthma susceptibility loci are robust to differences in ancestry when sufficiently large samples sizes are investigated, and that ancestry-specific associations also contribute to the complex genetic architecture of asthma.

Using imputed genotypes for relative risk estimation in case-parent studies.

Meta-analyses of genome-wide association studies are often based on imputed single nucleotide polymorphism (SNP) data, because component studies were genotyped using different platforms. One would like to include case-parent triad studies along with case-control studies in such meta-analyses. However, there are no published methods for estimating relative risks from imputed data for case-parent triad studies. The authors propose a method for estimating the relative risk for a variant SNP allele based on a log-additive model. Their simulations first confirm that the proposed method performs well with genotyped SNP data. As an empirical test of the method's behavior with imputed SNPs, the authors then apply it to chromosome 22 data from the Mexico City Childhood Asthma Study (1998-2003). For chromosome 22, the authors had data on 7,293 SNPs that were both genotyped and imputed using the software MACH, which relies on linkage disequilibrium with nearby SNPs. Correlation between estimated relative risks based on the actual genotypes and those based on the imputed genotypes was remarkably high (r(2) = 0.95), validating this method of relative risk estimation for the case-parent study design. This method should be useful to investigators who wish to conduct meta-analyses using imputed SNP data from both case-parent triad and case-control studies.

Evaluation of candidate genes in a genome-wide association study of childhood asthma in Mexicans.

BACKGROUND: More than 200 asthma candidate genes have been examined in human association studies or identified with knockout mouse approaches. However, many have not been systematically replicated in human populations, especially those containing a large number of tagging single nucleotide polymorphisms (SNPs). OBJECTIVE: We comprehensively evaluated the association of previously implicated asthma candidate genes with childhood asthma in a Mexico City population. METHODS: From the literature, we identified candidate genes with at least 1 positive report of association with asthma phenotypes in human subjects or implicated in asthma pathogenesis using knockout mouse experiments. We performed a genome-wide association study in 492 asthmatic children aged 5 to 17 years and both parents using the Illumina HumanHap 550v3 BeadChip. Separate candidate gene analyses were performed for 2933 autosomal SNPs in the 237 selected genes by using the log-linear method with a log-additive risk model. RESULTS: Sixty-one of the 237 genes had at least 1 SNP with a P value of less than .05 for association with asthma. The 9 most significant results were observed for rs2241715 in the gene encoding TGF-beta1 (TGFB1; P = 3.3 x 10(-5)), rs13431828 and rs1041973 in the gene encoding IL-1 receptor-like 1 (IL1RL1; P = 2 x 10(-4) and 3.5 x 10(-4)), 5 SNPs in the gene encoding dipeptidyl-peptidase 10 (DPP10; P = 1.6 x 10(-4) to 4.5 x 10(-4)), and rs17599222 in the gene encoding cytoplasmic FMR1 interacting protein 2 (CYFIP2; P = 4.1 x 10(-4)). False discovery rates were less than 0.1 for all 9 SNPs. Multimarker analysis identified TGFB1, IL1RL1, the gene encoding IL-18 receptor 1 (IL18R1), and DPP10 as the genes most significantly associated with asthma. CONCLUSIONS: This comprehensive analysis of literature-based candidate genes suggests that SNPs in several candidate genes, including TGFB1, IL1RL1, IL18R1, and DPP10, might contribute to childhood asthma susceptibility in a Mexican population.

Genome-wide association study implicates chromosome 9q21.31 as a susceptibility locus for asthma in mexican children.

Many candidate genes have been studied for asthma, but replication has varied. Novel candidate genes have been identified for various complex diseases using genome-wide association studies (GWASs). We conducted a GWAS in 492 Mexican children with asthma, predominantly atopic by skin prick test, and their parents using the Illumina HumanHap 550 K BeadChip to identify novel genetic variation for childhood asthma. The 520,767 autosomal single nucleotide polymorphisms (SNPs) passing quality control were tested for association with childhood asthma using log-linear regression with a log-additive risk model. Eleven of the most significantly associated GWAS SNPs were tested for replication in an independent study of 177 Mexican case-parent trios with childhood-onset asthma and atopy using log-linear analysis. The chromosome 9q21.31 SNP rs2378383 (p = 7.10x10(-6) in the GWAS), located upstream of transducin-like enhancer of split 4 (TLE4), gave a p-value of 0.03 and the same direction and magnitude of association in the replication study (combined p = 6.79x10(-7)). Ancestry analysis on chromosome 9q supported an inverse association between the rs2378383 minor allele (G) and childhood asthma. This work identifies chromosome 9q21.31 as a novel susceptibility locus for childhood asthma in Mexicans. Further, analysis of genome-wide expression data in 51 human tissues from the Novartis Research Foundation showed that median GWAS significance levels for SNPs in genes expressed in the lung differed most significantly from genes not expressed in the lung when compared to 50 other tissues, supporting the biological plausibility of our overall GWAS findings and the multigenic etiology of childhood asthma.

Prospective study of breast-feeding in relation to wheeze, atopy, and bronchial hyperresponsiveness in the Avon Longitudinal Study of Parents and Children (ALSPAC).

BACKGROUND: Breast-feeding clearly protects against early wheezing, but recent data suggest that it might increase later risk of atopic disease and asthma. OBJECTIVE: We sought to examine the relationship between breast-feeding and later asthma and allergy outcomes by using data from the Avon Longitudinal Study of Parents and Children, a large birth cohort in the United Kingdom. METHODS: We used adjusted logistic regression models to evaluate the association between breast-feeding and atopy at age 7 years, bronchial responsiveness to methacholine at age 8 years, and wheeze at ages 3 and 7 1/2 years. Bayesian methods were used to assess the possibility of bias caused by an influence of early wheezing on the duration of breast-feeding, as well as selection bias. RESULTS: Breast-feeding was protective for wheeze in the first 3 years of life (odds ratio [OR] of 0.80 [95% CI, 0.70-0.90] for > or = 6 months relative to never) but not wheeze (OR, 0.98; 95% CI, 0.79-1.22), atopy (OR, 1.12; 95% CI, 0.92-1.35), or bronchial hyperresponsiveness (OR, 1.07; 95% CI, 0.82-1.40) at ages 7 to 8 years. Bayesian models adjusting for the longer duration of breast-feeding among children with wheezing in early infancy produced virtually identical results. CONCLUSIONS: We did not find consistent evidence for either a deleterious effect or a protective effect of breast-feeding on later risk of allergic disease in a large prospective birth cohort of children with objective outcome measures and extensive data on potential confounders and effect modifiers. Neither reverse causation nor loss to follow-up appears to have materially biased our results.

Genetic polymorphisms in arginase I and II and childhood asthma and atopy.

BACKGROUND: A recent microarray study implicated arginase I (ARG1) and arginase II (ARG2) in mouse allergic asthma models and human asthma. OBJECTIVES: To examine the association between genetic variation in ARG1 and ARG2 and childhood asthma and atopy risk. METHODS: We enrolled 433 case-parent triads, consisting of patients with asthma 4 to 17 years old and their biologic parents, from the allergy clinic of a public hospital in Mexico City between 1998 and 2003. Atopy to 24 aeroallergens was determined by skin prick tests. We genotyped 4 single nucleotide polymorphisms (SNPs) of ARG1 and 4 SNPs of ARG2 with minor allele frequencies higher than 10% by using the TaqMan assay (Roche Molecular Systems, Pleasanton, Calif). RESULTS: ARG1 SNPs and haplotypes were not associated with asthma, but all 4 ARG1 SNPs were associated with the number of positive skin tests (P = .007-.018). Carrying 2 copies of minor alleles for either of 2 highly associated ARG2 SNPs was associated with a statistically significant increased relative risk (RR) of asthma (1.5, 95% CI = 1.1-2.1 for arg2s1; RR = 1.6, 95% CI = 1.1-2.3 for arg2s2). The association was slightly stronger among children with a smoking parent (arg2s1 RR = 2.1, 95% CI = 1.2 - 3.9 with a smoking parent; RR = 1.2, 95% CI = 0.8-1.9 without; interaction P = .025). Haplotype analyses reduced the sample size but supported the single SNP results. One ARG2 SNP was related to the number of positive skin tests (P = .027). CONCLUSION: Variation in arginase genes may contribute to asthma and atopy in children.