Glaucoma severity at first presentation to an ophthalmologist and risk factors for late presentation in rural Australia: the S1P study.

CLINICAL RELEVANCE: Well-targeted referrals and timely commencement of treatment are essential to limiting vision loss in glaucoma. Optometrists, primary care providers, and public health policymakers can utilise predictors of late to identify and target at-risk populations. BACKGROUND: This study, which aimed to evaluate glaucoma severity at first presentation to an ophthalmologist in a rural Australian population, is the first of its kind in an Australian population. METHODS: Patient records from a large ophthalmology clinic in Port Macquarie, NSW were retrospectively reviewed using the Fight Glaucoma Blindness registry to identify patients who were first diagnosed with glaucoma at an ophthalmology practice in 2020 or 2021. Associations with glaucoma severity at presentation, measured with visual field index (VFI), were analysed using a beta-regression model. Retinal nerve fibre layer measurements were evaluated as a secondary outcome measure using linear regression. RESULTS: From 3548 new patients seen, 110 cases of glaucoma were diagnosed, 95 of whom met inclusion criteria. These comprised 41.8% primary open-angle glaucoma, 32.7% normal-tension glaucoma, 11.8% secondary open-angle glaucoma, 12.7% primary angle closure glaucoma, and 0.9% secondary angle closure glaucoma. The median VFI at presentation was 94.5%, and 71.9% of patients had a VFI ≥ 90%. However, 6.3% of patients presented with a VFI below 50%. Older age, higher intraocular pressure, and worse visual acuity were significantly associated with severity at presentation. No associations were found for remoteness, sex, family history, or glaucoma type. CONCLUSIONS: Glaucoma appears to be diagnosed relatively early in this population. Severity at presentation was associated with age, intraocular pressure, and visual acuity, but not influenced by the social determinants assessed. These findings underscore the importance of frequent comprehensive eye examinations in older patients. Replication in other Australian populations is recommended as the generalisability of these findings is limited.

Steroidogenic Factor-1 form and function: From phospholipids to physiology.

Steroidogenic Factor-1 (SF-1, NR5A1) is a member of the nuclear receptor superfamily of ligand-regulated transcription factors, consisting of a DNA-binding domain (DBD) connected to a transcriptional regulatory ligand binding domain (LBD) via an unstructured hinge domain. SF-1 is a master regulator of development and adult function along the hypothalamic pituitary adrenal and gonadal axes, with strong pathophysiological association with endometriosis and adrenocortical carcinoma. SF-1 was shown to bind and be regulated by phospholipids, one of the most interesting aspects of SF-1 regulation is the manner in which SF-1 interacts with phospholipids: SF-1 buries the phospholipid acyl chains deep in the hydrophobic core of the SF-1 protein, while the lipid headgroups remain solvent-exposed on the exterior of the SF-1 protein surface. Here, we have reviewed several aspects of SF-1 structure, function and physiology, touching on other transcription factors that help regulate SF-1 target genes, non-canonical functions of SF-1, the DNA-binding properties of SF-1, the use of mass spectrometry to identify lipids that associate with SF-1, how protein phosphorylation regulates SF-1 and the structural biology of the phospholipid-ligand binding domain. Together this review summarizes the form and function of Steroidogenic Factor-1 in physiology and in human disease, with particular emphasis on adrenal cancer.

Single-cell genetic models to evaluate orphan gene function: The case of QQS regulating carbon and nitrogen allocation.

We demonstrate two synthetic single-cell systems that can be used to better understand how the acquisition of an orphan gene can affect complex phenotypes. The Arabidopsis orphan gene, Qua-Quine Starch (QQS) has been identified as a regulator of carbon (C) and nitrogen (N) partitioning across multiple plant species. QQS modulates this important biotechnological trait by replacing NF-YB (Nuclear Factor Y, subunit B) in its interaction with NF-YC. In this study, we expand on these prior findings by developing Chlamydomonas reinhardtii and Saccharomyces cerevisiae strains, to refactor the functional interactions between QQS and NF-Y subunits to affect modulations in C and N allocation. Expression of QQS in C. reinhardtii modulates C (i.e., starch) and N (i.e., protein) allocation by affecting interactions between NF-YC and NF-YB subunits. Studies in S. cerevisiae revealed similar functional interactions between QQS and the NF-YC homolog (HAP5), modulating C (i.e., glycogen) and N (i.e., protein) allocation. However, in S. cerevisiae both the NF-YA (HAP2) and NF-YB (HAP3) homologs appear to have redundant functions to enable QQS and HAP5 to affect C and N allocation. The genetically tractable systems that developed herein exhibit the plasticity to modulate highly complex phenotypes.

Modifying the yeast very long chain fatty acid biosynthetic machinery by the expression of plant 3-ketoacyl CoA synthase isozymes.

Eukaryotes express a multi-component fatty acid elongase to produce very long chain fatty acids (VLCFAs), which are building blocks of diverse lipids. Elongation is achieved by cyclical iteration of four reactions, the first of which generates a new carbon-carbon bond, elongating the acyl-chain. This reaction is catalyzed by either ELONGATION DEFECTIVE LIKE (ELO) or 3-ketoacyl-CoA synthase (KCS) enzymes. Whereas plants express both ELO and KCS enzymes, other eukaryotes express only ELOs. We explored the Zea mays KCS enzymatic redundancies by expressing each of the 26 isozymes in yeast strains that lacked endogenous ELO isozymes. Expression of the 26 maize KCS isozymes in wild-type, scelo2 or scelo3 single mutants did not affect VLCFA profiles. However, a complementation screen of each of the 26 KCS isozymes revealed five that were capable of complementing the synthetically lethal scelo2; scelo3 double mutant. These rescued strains express novel VLCFA profiles reflecting the different catalytic capabilities of the KCS isozymes. These novel strains offer a platform to explore the relationship between VLCFA profiles and cellular physiology.

Investigation of male and female infertility in llamas and alpacas.

Llamas and alpacas are important production animals in South America, with increasing interest in other parts of the world. Poor reproductive efficiency combined with several unique anatomical and physiological reproductive features offer challenges in the diagnosis and treatment of infertility in camelids. This review presents an approach to the clinical investigation and common causes of infertility and subfertility in the male and female. The selection of males for breeding should be made based on complete evaluation to eliminate congenital and possibly hereditary disorders. Common disorders of the male reproductive system include testicular hypoplasia, testicular and epididymal cysts and testicular degeneration. Semen evaluation presents some challenges owing to the viscous nature of the ejaculate in these species. Females should be screened for congenital genital defects before breeding. Causes of subfertility in the female are dominated by ovarian and uterine disorders. A systematic clinical approach and the use of endometrial biopsy and advanced techniques, such as laparoscopy, allow early identification of these disorders. Further research is needed for continued understanding of the reproductive pathological processes in these species.

A single-cell platform for reconstituting and characterizing fatty acid elongase component enzymes.

Fatty acids of more than 18-carbons, generally known as very long chain fatty acids (VLCFAs) are essential for eukaryotic cell viability, and uniquely in terrestrial plants they are the precursors of the cuticular lipids that form the organism's outer barrier to the environment. VLCFAs are synthesized by fatty acid elongase (FAE), which is an integral membrane enzyme system with multiple components. The genetic complexity of the FAE system, and its membrane association has hampered the biochemical characterization of FAE. In this study we computationally identified Zea mays genetic sequences that encode the enzymatic components of FAE and developed a heterologous expression system to evaluate their functionality. The ability of the maize components to genetically complement Saccharomyces cerevisiae lethal mutants confirmed the functionality of ZmKCS4, ZmELO1, ZmKCR1, ZmKCR2, ZmHCD and ZmECR, and the VLCFA profiles of the resulting strains were used to infer the ability of each enzyme component to determine the product profile of FAE. These characterizations indicate that the product profile of the FAE system is an attribute shared among the KCS, ELO, and KCR components of FAE.

Effect of age and castration on serum anti-Müllerian hormone concentration in male alpacas.

The synthesis of anti-Müllerian Hormone (AMH) by the Sertoli cells in males is crucial for sexual differentiation. There are no studies on AMH in Camelids. The objectives of this research were to 1) compare AMH serum concentrations in prepubertal and adult male alpacas and 2) determine the effect of castration on these concentrations in adult males to provide a validation of a commercial AMH test in alpacas. Serum samples were obtained from 15 prepubertal animals (5 for each age groups of 6, 7 and 8 months) and from 5 adult males (age 5-9 years), pre- and 24 h post-castration. AMH was determined with a quantitative ELISA according to the manufacture's instructions. There was not significant difference (P < 0.05) in AMH level (pg/ml) between pre-pubertal (549.9 ± 120.8, 789.4 ± 172.3, 597.5 ± 177.3 for ages 4, 7, and 8 months, respectively) and adult alpacas (938.7 ± 175.9). In adult males, AMH concentration decreased significantly following castration (P < 0.05) (938.7 ± 383.5 pg/ml) pre-castration, and 222.1 ± 116.5 pg/ml) after castration). There was a positive correlation between testosterone levels and AMH. In conclusion, the quantitative assay used is a reliable test to determine AMH in alpacas. The AMH level in prepubertal and adult alpacas appear to not differ, contrarily from other mammals, this requires further investigation. The decrease in serum AMH concentrations after castration suggests that measurement of this hormone can be used to diagnose bilateral cryptorchid or hemicastrated unilateral cryptorchid animals in this species.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery.

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

Metabolomics as a Hypothesis-Generating Functional Genomics Tool for the Annotation of Arabidopsis thaliana Genes of "Unknown Function".

Metabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs.