Metabolomic profiling to identify early urinary biomarkers and metabolic pathway alterations in autosomal dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the formation of numerous fluid-filled cysts that lead to progressive loss of functional nephrons. Currently, there is an unmet need for diagnostic and prognostic indicators of early stages of the disease. Metabolites were extracted from the urine of patients with early-stage ADPKD (n = 48 study participants) and age- and sex-matched normal controls (n = 47) and analyzed by liquid chromatography-mass spectrometry. Orthogonal partial least squares-discriminant analysis was used to generate a global metabolomic profile of early ADPKD for the identification of metabolic pathway alterations and discriminatory metabolites as candidates of diagnostic and prognostic biomarkers. The global metabolomic profile exhibited alterations in steroid hormone biosynthesis and metabolism, fatty acid metabolism, pyruvate metabolism, amino acid metabolism, and the urea cycle. A panel of 46 metabolite features was identified as candidate diagnostic biomarkers. Notable putative identities of candidate diagnostic biomarkers for early detection include creatinine, cAMP, deoxycytidine monophosphate, various androgens (testosterone; 5-α-androstane-3,17,dione; trans-dehydroandrosterone), betaine aldehyde, phosphoric acid, choline, 18-hydroxycorticosterone, and cortisol. Metabolic pathways associated with variable rates of disease progression included steroid hormone biosynthesis and metabolism, vitamin D3 metabolism, fatty acid metabolism, the pentose phosphate pathway, tricarboxylic acid cycle, amino acid metabolism, sialic acid metabolism, and chondroitin sulfate and heparin sulfate degradation. A panel of 41 metabolite features was identified as candidate prognostic biomarkers. Notable putative identities of candidate prognostic biomarkers include ethanolamine, C20:4 anandamide phosphate, progesterone, various androgens (5-α-dihydrotestosterone, androsterone, etiocholanolone, and epiandrosterone), betaine aldehyde, inflammatory lipids (eicosapentaenoic acid, linoleic acid, and stearolic acid), and choline. Our exploratory data support metabolic reprogramming in early ADPKD and demonstrate the ability of liquid chromatography-mass spectrometry-based global metabolomic profiling to detect metabolic pathway alterations as new therapeutic targets and biomarkers for early diagnosis and tracking disease progression of ADPKD.NEW & NOTEWORTHY To our knowledge, this study is the first to generate urinary global metabolomic profiles from individuals with early-stage ADPKD with preserved renal function for biomarker discovery. The exploratory dataset reveals metabolic pathway alterations that may be responsible for early cystogenesis and rapid disease progression and may be potential therapeutic targets and pathway sources for candidate biomarkers. From these results, we generated a panel of candidate diagnostic and prognostic biomarkers of early-stage ADPKD for future validation.

A spatial model of the plant circadian clock reveals design principles for coordinated timing.

Individual plant cells possess a genetic network, the circadian clock, that times internal processes to the day-night cycle. Mathematical models of the clock are typically either "whole-plant" that ignore tissue or cell type-specific clock behavior, or "phase-only" that do not include molecular components. To address the complex spatial coordination observed in experiments, here we implemented a clock network model on a template of a seedling. In our model, the sensitivity to light varies across the plant, and cells communicate their timing via local or long-distance sharing of clock components, causing their rhythms to couple. We found that both varied light sensitivity and long-distance coupling could generate period differences between organs, while local coupling was required to generate the spatial waves of clock gene expression observed experimentally. We then examined our model under noisy light-dark cycles and found that local coupling minimized timing errors caused by the noise while allowing each plant region to maintain a different clock phase. Thus, local sensitivity to environmental inputs combined with local coupling enables flexible yet robust circadian timing.

Coordinated circadian timing through the integration of local inputs in Arabidopsis thaliana.

Individual plant cells have a genetic circuit, the circadian clock, that times key processes to the day-night cycle. These clocks are aligned to the day-night cycle by multiple environmental signals that vary across the plant. How does the plant integrate clock rhythms, both within and between organs, to ensure coordinated timing? To address this question, we examined the clock at the sub-tissue level across Arabidopsis thaliana seedlings under multiple environmental conditions and genetic backgrounds. Our results show that the clock runs at different speeds (periods) in each organ, which causes the clock to peak at different times across the plant in both constant environmental conditions and light-dark (LD) cycles. Closer examination reveals that spatial waves of clock gene expression propagate both within and between organs. Using a combination of modeling and experiment, we reveal that these spatial waves are the result of the period differences between organs and local coupling, rather than long-distance signaling. With further experiments we show that the endogenous period differences, and thus the spatial waves, can be generated by the organ specificity of inputs into the clock. We demonstrate this by modulating periods using light and metabolic signals, as well as with genetic perturbations. Our results reveal that plant clocks can be set locally by organ-specific inputs but coordinated globally via spatial waves of clock gene expression.

Global metabolomic profiling of human synovial fluid for rheumatoid arthritis biomarkers.

OBJECTIVES: The objective of this study was to analyse the metabolomic profiles of rheumatoid arthritis synovial fluid to test the use of global metabolomics by liquid chromatography-mass spectrometry for clinical analysis of synovial fluid. METHODS: Metabolites were extracted from rheumatoid arthritis (n=3) and healthy (n=5) synovial fluid samples using 50:50 water: acetonitrile. Metabolite extracts were analysed in positive mode by normal phase liquid chromatography-mass spectrometry for global metabolomics. Statistical analyses included hierarchical clustering analysis, principal component analysis, Student's t-test, and volcano plot analysis. Metabolites were matched with known metabolite identities using METLIN and enriched for relevant pathways using IMPaLA. RESULTS: 1018 metabolites were detected by LC-MS analysis in synovial fluid from rheumatoid arthritis and healthy patients, with 162 metabolites identified as significantly different between diseased and control. Pathways upregulated with disease included ibuprofen metabolism, glucocorticoid and mineralocorticoid metabolism, alpha-linolenic acid metabolism, and steroid hormone biosynthesis. Pathways downregulated with disease included purine and pyrimidine metabolism, biological oxidations, arginine and proline metabolism, the citrulline-nitric oxide cycle, and glutathione metabolism. Receiver operating characteristic analysis identified 30 metabolites as putative rheumatoid arthritis biomarkers including various phospholipids, diol and its derivatives, arsonoacetate, oleananoic acid acetate, docosahexaenoic acid methyl ester, and linolenic acid and eicosatrienoic acid derivatives. CONCLUSIONS: This study supports the use of global metabolomic profiling by liquid chromatography-mass spectrometry for synovial fluid analysis to provide insight into the aetiology of disease.

Application of global metabolomic profiling of synovial fluid for osteoarthritis biomarkers.

Osteoarthritis affects over 250 million individuals worldwide. Currently, there are no options for early diagnosis of osteoarthritis, demonstrating the need for biomarker discovery. To find biomarkers of osteoarthritis in human synovial fluid, we used high performance liquid-chromatography mass spectrometry for global metabolomic profiling. Metabolites were extracted from human osteoarthritic (n = 5), rheumatoid arthritic (n = 3), and healthy (n = 5) synovial fluid, and a total of 1233 metabolites were detected. Principal components analysis clearly distinguished the metabolomic profiles of diseased from healthy synovial fluid. Synovial fluid from rheumatoid arthritis patients contained expected metabolites consistent with the inflammatory nature of the disease. Similarly, unsupervised clustering analysis found that each disease state was associated with distinct metabolomic profiles and clusters of co-regulated metabolites. For osteoarthritis, co-regulated metabolites that were upregulated compared to healthy synovial fluid mapped to known disease processes including chondroitin sulfate degradation, arginine and proline metabolism, and nitric oxide metabolism. We utilized receiver operating characteristic analysis to determine the diagnostic value of each metabolite and identified 35 metabolites as potential biomarkers of osteoarthritis, with an area under the receiver operating characteristic curve >0.9. These metabolites included phosphatidylcholine, lysophosphatidylcholine, ceramides, myristate derivatives, and carnitine derivatives. This pilot study provides strong justification for a larger cohort-based study of human osteoarthritic synovial fluid using global metabolomics. The significance of these data is the demonstration that metabolomic profiling of synovial fluid can identify relevant biomarkers of joint disease.

Molecular-based diagnosis of multiple sclerosis and its progressive stage.

OBJECTIVE: Biomarkers aid diagnosis, allow inexpensive screening of therapies, and guide selection of patient-specific therapeutic regimens in most internal medicine disciplines. In contrast, neurology lacks validated measurements of the physiological status, or dysfunction(s) of cells of the central nervous system (CNS). Accordingly, patients with chronic neurological diseases are often treated with a single disease-modifying therapy without understanding patient-specific drivers of disability. Therefore, using multiple sclerosis (MS) as an example of a complex polygenic neurological disease, we sought to determine whether cerebrospinal fluid (CSF) biomarkers are intraindividually stable, cell type-, disease- and/or process-specific, and responsive to therapeutic intervention. METHODS: We used statistical learning in a modeling cohort (n = 225) to develop diagnostic classifiers from DNA-aptamer-based measurements of 1,128 CSF proteins. An independent validation cohort (n = 85) assessed the reliability of derived classifiers. The biological interpretation resulted from in vitro modeling of primary or stem cell-derived human CNS cells and cell lines. RESULTS: The classifier that differentiates MS from CNS diseases that mimic MS clinically, pathophysiologically, and on imaging achieved a validated area under the receiver operating characteristic curve (AUROC) of 0.98, whereas the classifier that differentiates relapsing-remitting from progressive MS achieved a validated AUROC of 0.91. No classifiers could differentiate primary progressive from secondary progressive MS better than random guessing. Treatment-induced changes in biomarkers greatly exceeded intraindividual and technical variabilities of the assay. INTERPRETATION: CNS biological processes reflected by CSF biomarkers are robust, stable, disease specific, or even disease stage specific. This opens opportunities for broad utilization of CSF biomarkers in drug development and precision medicine for CNS disorders. Ann Neurol 2017;82:795-812.

Prokaryotes in the WAIS Divide ice core reflect source and transport changes between Last Glacial Maximum and the early Holocene.

We present the first long-term, highly resolved prokaryotic cell concentration record obtained from a polar ice core. This record, obtained from the West Antarctic Ice Sheet (WAIS) Divide (WD) ice core, spanned from the Last Glacial Maximum (LGM) to the early Holocene (EH) and showed distinct fluctuations in prokaryotic cell concentration coincident with major climatic states. The time series also revealed a ~1,500-year periodicity with greater amplitude during the Last Deglaciation (LDG). Higher prokaryotic cell concentration and lower variability occurred during the LGM and EH than during the LDG. A sevenfold decrease in prokaryotic cell concentration coincided with the LGM/LDG transition and the global 19 ka meltwater pulse. Statistical models revealed significant relationships between the prokaryotic cell record and tracers of both marine (sea-salt sodium [ssNa]) and burning emissions (black carbon [BC]). Collectively, these models, together with visual observations and methanosulfidic acid (MSA) measurements, indicated that the temporal variability in concentration of airborne prokaryotic cells reflected changes in marine/sea-ice regional environments of the WAIS. Our data revealed that variations in source and transport were the most likely processes producing the significant temporal variations in WD prokaryotic cell concentrations. This record provided strong evidence that airborne prokaryotic cell deposition differed during the LGM, LDG, and EH, and that these changes in cell densities could be explained by different environmental conditions during each of these climatic periods. Our observations provide the first ice-core time series evidence for a prokaryotic response to long-term climatic and environmental processes.

Bacterial responses to environmental change on the Tibetan Plateau over the past half century.

Climate change and anthropogenic factors can alter biodiversity and can lead to changes in community structure and function. Despite the potential impacts, no long-term records of climatic influences on microbial communities exist. The Tibetan Plateau is a highly sensitive region that is currently undergoing significant alteration resulting from both climate change and increased human activity. Ice cores from glaciers in this region serve as unique natural archives of bacterial abundance and community composition, and contain concomitant records of climate and environmental change. We report high-resolution profiles of bacterial density and community composition over the past half century in ice cores from three glaciers on the Tibetan Plateau. Statistical analysis showed that the bacterial community composition in the three ice cores converged starting in the 1990s. Changes in bacterial community composition were related to changing precipitation, increasing air temperature and anthropogenic activities in the vicinity of the plateau. Collectively, our ice core data on bacteria in concert with environmental and anthropogenic proxies indicate that the convergence of bacterial communities deposited on glaciers across a wide geographical area and situated in diverse habitat types was likely induced by climatic and anthropogenic drivers.

Cerebrospinal fluid markers reveal intrathecal inflammation in progressive multiple sclerosis.

OBJECTIVE: The management of complex patients with neuroimmunological diseases is hindered by an inability to reliably measure intrathecal inflammation. Currently implemented laboratory tests developed >40 years ago either are not dynamic or fail to capture low levels of central nervous system (CNS) inflammation. Therefore, we aimed to identify and validate biomarkers of CNS inflammation in 2 blinded, prospectively acquired cohorts of untreated patients with neuroimmunological diseases and embedded controls, with the ultimate goal of developing clinically useful tools. METHODS: Because biomarkers with maximum utility reflect immune phenotypes, we included an assessment of cell specificity in purified primary immune cells. Biomarkers were quantified by optimized electrochemiluminescent immunoassays. RESULTS: Among markers with cell-specific secretion, soluble CD27 is a validated biomarker of intrathecal T-cell activation, with an area under the receiver operating characteristic curve of 0.97. Comparing the quantities of cerebrospinal fluid (CSF) immune cells and their respective cell-specific soluble biomarkers (released by CSF cells as well as their counterparts in CNS tissue) provided invaluable information about stationary CNS immune responses, previously attainable via brain biopsy only. Unexpectedly, progressive and relapsing-remitting multiple sclerosis (MS) patients have comparable numbers of activated intrathecal T and B cells, which are preferentially embedded in CNS tissue in the former group. INTERPRETATION: The cell-specific biomarkers of intrathecal inflammation may improve diagnosis and management of neuroimmunological diseases and provide pharmacodynamic markers for future therapeutic developments in patients with intrathecal inflammation that is not captured by imaging, such as in progressive MS.

A Case of Undiagnosed Harlequin Syndrome Presenting in General Dental Practice.

Harlequin syndrome is a rare, clinically striking syndrome characterized by distinctly demarcated asymmetric facial flushing and sweating. It may be of idiopathic aetiology or caused by demonstrable ipsilateral damage to the sympathetic nervous system. A case is described where a patient presented to her general dental practitioner complaining of distinctly demarcated unilateral facial flushing and sweating. Onward referral resulted in a diagnosis of Harlequin syndrome. CPD/CLINICAL RELEVANCE: This article highlights the neurological signs and symptoms of Harlequin syndrome, making it easier to recognize if it presents in general dental practice.

Assessment of Arctic community wastewater impacts on marine benthic invertebrates.

This study sought to understand the performance of arctic treatment systems and the impact of wastewater effluent on benthic invertebrate communities in arctic receiving water habitats. Effluent quality and benthic impacts were monitored in the receiving water of five communities across Nunavut that differed in the type and level of treatment achieved by wastewater infrastructure, the volume of effluent and receiving water mixing environment. We detected minimal impacts to benthic communities (<225 m linear distance from the effluent source) in four out of the five communities (Grise Fiord, Kugaaruk, Pond Inlet, and Pangnirtung), where the population was <2000 people. In these small communities impacts were characterized by increases or decreases in species richness, diversity, evenness, and density, and some differences in benthic species composition. This was in contrast to benthic sediments in Iqaluit (population 6699), which were devoid of benthic fauna up to 580 m from the effluent source in response to sediment anoxia. Variation in benthic community response between sampling locations was attributed primarily to differences in effluent volume, with effluent quality and receiving water hydrodynamics playing secondary roles. The results of this study will help to inform the development of northern specific treatment performance standards which will aid in prioritizing community wastewater system upgrades in arctic communities.

Extracting antipsychotic polypharmacy data from electronic health records: developing and evaluating a novel process.

BACKGROUND: Antipsychotic prescription information is commonly derived from structured fields in clinical health records. However, utilising diverse and comprehensive sources of information is especially important when investigating less frequent patterns of medication prescribing such as antipsychotic polypharmacy (APP). This study describes and evaluates a novel method of extracting APP data from both structured and free-text fields in electronic health records (EHRs), and its use for research purposes. METHODS: Using anonymised EHRs, we identified a cohort of patients with serious mental illness (SMI) who were treated in South London and Maudsley NHS Foundation Trust mental health care services between 1 January and 30 June 2012. Information about antipsychotic co-prescribing was extracted using a combination of natural language processing and a bespoke algorithm. The validity of the data derived through this process was assessed against a manually coded gold standard to establish precision and recall. Lastly, we estimated the prevalence and patterns of antipsychotic polypharmacy. RESULTS: Individual instances of antipsychotic prescribing were detected with high precision (0.94 to 0.97) and moderate recall (0.57-0.77). We detected baseline APP (two or more antipsychotics prescribed in any 6-week window) with 0.92 precision and 0.74 recall and long-term APP (antipsychotic co-prescribing for 6 months) with 0.94 precision and 0.60 recall. Of the 7,201 SMI patients receiving active care during the observation period, 338 (4.7 %; 95 % CI 4.2-5.2) were identified as receiving long-term APP. Two second generation antipsychotics (64.8 %); and first -second generation antipsychotics were most commonly co-prescribed (32.5 %). CONCLUSIONS: These results suggest that this is a potentially practical tool for identifying polypharmacy from mental health EHRs on a large scale. Furthermore, extracted data can be used to allow researchers to characterize patterns of polypharmacy over time including different drug combinations, trends in polypharmacy prescribing, predictors of polypharmacy prescribing and the impact of polypharmacy on patient outcomes.

Essentials of medical history-taking in dental patients.

The starting point in the assessment and management of any patient is dependent on good history-taking. The main parts of the history-taking process well known to practitioners are the presenting complaint, the history of the presenting complaint and the current and past medical history. This paper concentrates on those aspects of the process that are particularly important to dental practitioners. Clinical Relevance: The cornerstone of safe and effective patient management lies with the history. This paper describes various aspects of history-taking and highlights important areas.

Management of specific medical emergencies in dental practice.

In this paper, the actions needed to manage specific medical emergencies are discussed. Each emergency requires a correct diagnosis to be made for effective and safe management. The basis of management in contemporary dental practice avoids the intravenous route where drugs are required to treat the emergency.

High Spatial Resolution Luciferase Imaging of the Arabidopsis thaliana Circadian Clock.

The A. thaliana circadian clock is an example of a gene network that generates rich temporal and spatial dynamics. Bioluminescent imaging has proven a powerful method to help dissect the genetic mechanisms that generate oscillations of gene expression over the course of the day. However, its use for the study of spatial regulation is often limited by resolution. Here, we describe a modified luciferase imaging method for the study of the Arabidopsis circadian clock across the plant at sub-tissue-level resolution.

Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms.

While autopsy studies identify many abnormalities in the central nervous system (CNS) of subjects dying with neurological diseases, without their quantification in living subjects across the lifespan, pathogenic processes cannot be differentiated from epiphenomena. Using machine learning (ML), we searched for likely pathogenic mechanisms of multiple sclerosis (MS). We aggregated cerebrospinal fluid (CSF) biomarkers from 1305 proteins, measured blindly in the training dataset of untreated MS patients (N = 129), into models that predict past and future speed of disability accumulation across all MS phenotypes. Healthy volunteers (N = 24) data differentiated natural aging and sex effects from MS-related mechanisms. Resulting models, validated (Rho 0.40-0.51, p < 0.0001) in an independent longitudinal cohort (N = 98), uncovered intra-individual molecular heterogeneity. While candidate pathogenic processes must be validated in successful clinical trials, measuring them in living people will enable screening drugs for desired pharmacodynamic effects. This will facilitate drug development making, it hopefully more efficient and successful.

Chondrolipoma presenting as a lump on the lateral tongue.

UNLABELLED: The oral cavity is an uncommon site for a true lipoma. A distinct histological variant is chondrolipoma, which is a rare oral lesion. A case of chondrolipoma in a 71-year-old male is reported and histology and differential diagnosis are discussed. CLINICAL RELEVANCE: An oral lump is a common presenting complaint and requires further investigation.

An evaluation of sepsis in dentistry.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is a major health concern and causes substantial morbidity and mortality. It is imperative that the signs of sepsis are identified early in both adult and paediatric patients and appropriately escalated to initiate early treatment and improve prognosis. This paper aims to discuss the change in classification from the previous systemic inflammatory response syndrome (SIRS) criteria to the current definition in adults and also the unchanged definition in children. The hallmark signs of sepsis (both red and amber flags) are discussed in relation to their underlying cellular mechanisms to provide a comprehensive overview for clinicians in primary care, hospital and community settings. The rise of antimicrobial resistance is also an increasing global health concern with resistant bacteria from common infections likely to result in greater patient morbidity and worse outcomes.A literature search identified reported sepsis cases in dentistry through searches in Ovid Medline and Embase from January 1990 to December 2019. Only primary studies were included with no restrictions on languages. Four articles were identified which reported sepsis associated with tooth extractions, dental abscess and submental/submandibular cellulitis. It is well known that locoregional infections of dental origin have the potential to cause sepsis. Therefore, dental healthcare professionals need to be vigilant and understand the specific signs and escalation protocols to ensure patient safety.

Does Elevated [CO2] Only Increase Root Growth in the Topsoil? A FACE Study with Lentil in a Semi-Arid Environment.

Atmospheric carbon dioxide concentrations [CO2] are increasing steadily. Some reports have shown that root growth in grain crops is mostly stimulated in the topsoil rather than evenly throughout the soil profile by e[CO2], which is not optimal for crops grown in semi-arid environments with strong reliance on stored water. An experiment was conducted during the 2014 and 2015 growing seasons with two lentil (Lens culinaris) genotypes grown under Free Air CO2 Enrichment (FACE) in which root growth was observed non-destructively with mini-rhizotrons approximately every 2-3 weeks. Root growth was not always statistically increased by e[CO2] and not consistently between depths and genotypes. In 2014, root growth in the top 15 cm of the soil profile (topsoil) was indeed increased by e[CO2], but increases at lower depths (30-45 cm) later in the season were greater than in the topsoil. In 2015, e[CO2] only increased root length in the topsoil for one genotype, potentially reflecting the lack of plant available soil water between 30-60 cm until recharged by irrigation during grain filling. Our limited data to compare responses to e[CO2] showed that root length increases in the topsoil were correlated with a lower yield response to e[CO2]. The increase in yield response was rather correlated with increases in root growth below 30 cm depth.

Systematic review on effects of bioenergy from edible versus inedible feedstocks on food security.

Achieving food security is a critical challenge of the Anthropocene that may conflict with environmental and societal goals such as increased energy access. The "fuel versus food" debate coupled with climate mitigation efforts has given rise to next-generation biofuels. Findings of this systematic review indicate just over half of the studies (56% of 224 publications) reported a negative impact of bioenergy production on food security. However, no relationship was found between bioenergy feedstocks that are edible versus inedible and food security (P value = 0.15). A strong relationship was found between bioenergy and type of food security parameter (P value < 0.001), sociodemographic index of study location (P value = 0.001), spatial scale (P value < 0.001), and temporal scale (P value = 0.017). Programs and policies focused on bioenergy and climate mitigation should monitor multiple food security parameters at various scales over the long term toward achieving diverse sustainability goals.