Tau filaments are tethered within brain extracellular vesicles in Alzheimer's disease

The abnormal assembly of tau protein in neurons is the pathological hallmark of multiple neurodegenerative diseases, including Alzheimer's disease (AD). In addition, assembled tau associates with extracellular vesicles (EVs) in the central nervous system of patients with AD, which is linked to its clearance and prion-like propagation between neurons. However, the identities of the assembled tau species and the EVs, as well as how they associate, are not known. Here, we combined quantitative mass spectrometry, cryo-electron tomography and single-particle cryo-electron microscopy to study brain EVs from AD patients. We found filaments of truncated tau enclosed within EVs enriched in endo-lysosomal proteins. We observed multiple filament interactions, including with molecules that tethered filaments to the EV limiting membrane, suggesting selective packaging. Our findings will guide studies into the molecular mechanisms of EV-mediated secretion of assembled tau and inform the targeting of EV-associated tau as potential therapeutic and biomarker strategies for AD.

Noninvasive, MultiOmic, and Multicompartmental Biomarkers of Reflux Disease: A Systematic Review

BACKGROUND AND AIMS

Gastroesophageal reflux disease (GERD) is a prevalent gastrointestinal disorder that may complicate conditions such as obstructive airway disease. Our group has identified predictive biomarkers of GERD in particulate exposed first responders with obstructive airway disease. In addition, GERD diagnosis and treatment is costly and invasive. In light of these clinical concerns, we aimed to systematically review studies identifying noninvasive, multiOmic, and multicompartmental biomarkers of GERD.

METHODS

A systematic review of PubMed and Embase was performed using keywords focusing on reflux disease and biomarkers and registered with PROSPERO. We included original human studies in English, articles focusing on noninvasive biomarkers of GERD published after December 31, 2009. GERD subtypes (non-erosive reflux disease and erosive esophagitis) and related conditions (Barrett's Esophagus [BE] and Esophageal Adenocarcinoma). Predictive measures were synthesized and risk of bias assessed (Newcastle-Ottawa Scale).

RESULTS

Initial search identified n = 238 studies andn 13 articles remained after applying inclusion/exclusion criteria. Salivary pepsin was the most studied biomarker with significant sensitivity and specificity for GERD. Serum assessment showed elevated levels of Tumor Necrosis Factor-alpha in both GERD and Barrett's. Exhaled breath volatile sulfur compounds and acetic acid were associated with GERD. Oral Microbiome: Models with Lautropia, Streptococcus, and Bacteroidetes showed the greatest discrimination between BE and controls vs Lautropia; ROCAUC 0.94 (95% confidence interval; 0.85-1.00).

CONCLUSION

Prior studies identified significant multiOmic, multicompartmental noninvasive biomarker risks for GERD and BE. However, studies have a high risk of bias and the reliability and accuracy of the biomarkers identified are greatly limited, which further highlights the need to discover and validate clinically relevant noninvasive biomarkers of GERD.

Dynamic Metabolic Risk Profiling of World Trade Center Lung Disease: A Longitudinal Cohort Study

Rationale: Metabolic syndrome (MetSyn) increases the risk of World Trade Center (WTC) lung injury (LI). However, the temporal relationship of MetSyn, exposure intensity, and lung dysfunction is not well understood. Objective: To model the association of longitudinal MetSyn characteristics with WTC lung disease to define modifiable risk. Methods: Firefighters, for whom consent was obtained (N = 5,738), were active duty on September 11, 2001 (9/11). WTC-LI (n = 1,475; FEV₁% predicted <lower limit of normal [LLN]) and non-WTC-LI (n = 4,263; FEV₁% predicted ⩾LLN at all exams) was the primary outcome, and FVC% predicted <LLN and FEV₁/FVC <0.70 were secondary outcomes. We assessed 1) the effect of concurrent MetSyn on longitudinal lung function by linear mixed models, 2) the temporal effect of MetSyn and exposure by Weibull proportional hazards, 3) the effects of MetSyn's rate of change by two-stage models, and 4) the nonlinear joint effect of longitudinal MetSyn components by a partially linear single-index model (PLSI). Measurements and Main Results: WTC-LI cases were more often ever-smokers, arrived in the morning (9/11), and had MetSyn. Body mass index ⩾30 kg/m² and high-density lipoprotein <40 mg/dl were most contributory to concurrent loss of FEV₁% predicted and FVC% predicted while conserving FEV₁/FVC. Body mass index ⩾30 kg/m² and dyslipidemia significantly predicted WTC-LI, FVC% predicted <LLN in a Weibull proportional hazards model. Dynamic risk assessment of WTC-LI on the basis of MetSyn and exposure showed how reduction of MetSyn factors further reduces WTC-LI likelihood in susceptible populations. PLSI demonstrates that MetSyn has a nonlinear relationship with WTC lung disease, and increases in cumulative MetSyn risk factors exponentially increase WTC-LI risk. An interactive metabolic-risk modeling application was developed to simplify PLSI interpretation. Conclusions: MetSyn and WTC exposure contribute to the development of lung disease. Dynamic risk assessment may be used to encourage treatment of MetSyn in susceptible populations. Future studies will focus on dietary intervention as a disease modifier.

PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used automated, machine-learning, high-dimensional data pruning, and validated identified biomarkers. The parent cohort consisted of male, never-smoking firefighters with WTC-LI (FEV_{1, %Pred}< lower limit of normal (LLN); n = 100) and controls (n = 127) and had their biomarkers assessed. Cases and controls (n = 15/group) underwent untargeted metabolomics, then feature selection performed on metabolites, cytokines, chemokines, and clinical data. Cytokines, chemokines, and clinical biomarkers were validated in the non-overlapping parent-cohort via binary logistic regression with 5-fold cross validation. Random forests of metabolites (n = 580), clinical biomarkers (n = 5), and previously assayed cytokines, chemokines (n = 106) identified that the top 5% of biomarkers important to class separation included pigment epithelium-derived factor (PEDF), macrophage derived chemokine (MDC), systolic blood pressure, macrophage inflammatory protein-4 (MIP-4), growth-regulated oncogene protein (GRO), monocyte chemoattractant protein-1 (MCP-1), apolipoprotein-AII (Apo-AII), cell membrane metabolites (sphingolipids, phospholipids), and branched-chain amino acids. Validated models via confounder-adjusted (age on 9/11, BMI, exposure, and pre-9/11 FEV_{1, %Pred}) binary logistic regression had AUC_ROC [0.90(0.84–0.96)]. Decreased PEDF and MIP-4, and increased Apo-AII were associated with increased odds of WTC-LI. Increased GRO, MCP-1, and simultaneously decreased MDC were associated with decreased odds of WTC-LI. In conclusion, automated data pruning identified novel WTC-LI biomarkers; performance was validated in an independent cohort. One biomarker—PEDF, an antiangiogenic agent—is a novel, predictive biomarker of particulate-matter-related lung disease. Other biomarkers—GRO, MCP-1, MDC, MIP-4—reveal immune cell involvement in WTC-LI pathogenesis. Findings of our automated biomarker identification warrant further investigation into these potential pharmacotherapy targets.

Disease related to air pollution causes millions of deaths annually. Large swathes of the general population, as well as certain occupations such as 1^st responders and military personnel, are exposed to particulate matter (PM)—a major component of air pollution. Our longitudinal cohort of FDNY firefighters exposed to the World Trade Center dust cloud on 9/11 is a unique research opportunity to characterize the impact of a single, intense PM exposure by looking at pre- and post-exposure phenotype; however, PM-related lung disease and PM’s systemic effects are complex and call for a systems biological approach coupled with novel computational modelling techniques to fully understand pathogenesis. In the present study, we integrate clinical and environmental biomarkers with the serum metabolome, cytokines, and chemokines to develop a model for early disease detection and identification of potential signaling cascades of PM-related chronic lung disease.

Dietary phenotype and advanced glycation end-products predict WTC-obstructive airways disease: a longitudinal observational study

Background

Diet is a modifier of metabolic syndrome which in turn is associated with World Trade Center obstructive airways disease (WTC-OAD). We have designed this study to (1) assess the dietary phenotype (food types, physical activity, and dietary habits) of the Fire Department of New York (FDNY) WTC-Health Program (WTC-HP) cohort and (2) quantify the association of dietary quality and its advanced glycation end product (AGE) content with the development of WTC-OAD.

Methods

WTC-OAD, defined as developing WTC-Lung Injury (WTC-LI; FEV₁ < LLN) and/or airway hyperreactivity (AHR; positive methacholine and/or positive bronchodilator response). Rapid Eating and Activity Assessment for Participants-Short Version (REAP-S) deployed on 3/1/2018 in the WTC-HP annual monitoring assessment. Clinical and REAP-S data of consented subjects was extracted (7/17/2019). Diet quality [low-(15–19), moderate-(20–29), and high-(30–39)] and AGE content per REAP-S questionnaire were assessed for association with WTC-OAD. Regression models adjusted for smoking, hyperglycemia, hypertension, age on 9/11, WTC-exposure, BMI, and job description.

Results

N = 9508 completed the annual questionnaire, while N = 4015 completed REAP-S and had spirometry. WTC-OAD developed in N = 921, while N = 3094 never developed WTC-OAD. Low- and moderate-dietary quality, eating more (processed meats, fried foods, sugary drinks), fewer (vegetables, whole-grains),and having a diet abundant in AGEs were significantly associated with WTC-OAD. Smoking was not a significant risk factor of WTC-OAD.

Conclusions

REAP-S was successfully implemented in the FDNY WTC-HP monitoring questionnaire and produced valuable dietary phenotyping. Our observational study has identified low dietary quality and AGE abundant dietary habits as risk factors for pulmonary disease in the context of WTC-exposure. Dietary phenotyping, not only focuses our metabolomic/biomarker profiling but also further informs future dietary interventions that may positively impact particulate matter associated lung disease.

Multiomics of World Trade Center Particulate Matter-induced Persistent Airway Hyperreactivity. Role of Receptor for Advanced Glycation End Products

Pulmonary disease after World Trade Center particulate matter (WTC-PM) exposure is associated with dyslipidemia and the receptor for advanced glycation end products (RAGE); however, the mechanisms are not well understood. We used a murine model and a multiomics assessment to understand the role of RAGE in the pulmonary long-term effects of a single high-intensity exposure to WTC-PM. After 1 month, WTC-PM-exposed wild-type (WT) mice had airway hyperreactivity, whereas RAGE-deficient (Ager^-/-) mice were protected. PM-exposed WT mice also had histologic evidence of airspace disease, whereas Ager^-/- mice remained unchanged. Inflammatory mediators such as G-CSF (granulocyte colony-stimulating factor), IP-10 (IFN-γ-induced protein 10), and KC (keratinocyte chemoattractant) were differentially expressed after WTC-PM exposure. WTC-PM induced α-SMA, DIAPH1 (protein diaphanous homolog 1), RAGE, and significant lung collagen deposition in WT compared with Ager^-/- mice. Compared with WT mice with PM exposure, relative expression of phosphorylated to total CREB (cAMP response element-binding protein) and JNK (c-Jun N-terminal kinase) was significantly increased in the lung of PM-exposed Ager^-/- mice, whereas Akt (protein kinase B) was decreased. Random forests of the refined lung metabolomic profile classified subjects with 92% accuracy; principal component analysis captured 86.7% of the variance in three components and demonstrated prominent subpathway involvement, including known mediators of lung disease such as vitamin B₆ metabolites, sphingolipids, fatty acids, and phosphatidylcholines. Treatment with a partial RAGE antagonist, pioglitazone, yielded similar fold-change expression of metabolites (N₆-carboxymethyllysine, 1-methylnicotinamide, N¹+N⁸-acetylspermidine, and succinylcarnitine [C4-DC]) between WT and Ager^-/- mice exposed to WTC-PM. RAGE can mediate WTC-PM-induced airway hyperreactivity and warrants further investigation.

Food Intake REstriction for Health OUtcome Support and Education (FIREHOUSE) Protocol: A Randomized Clinical Trial

Fire Department of New York (FDNY) rescue and recovery workers exposed to World Trade Center (WTC) particulates suffered loss of forced expiratory volume in 1 s (FEV1). Metabolic Syndrome increased the risk of developing WTC-lung injury (WTC-LI). We aim to attenuate the deleterious effects of WTC exposure through a dietary intervention targeting these clinically relevant disease modifiers. We hypothesize that a calorie-restricted Mediterranean dietary intervention will improve metabolic risk, subclinical indicators of cardiopulmonary disease, quality of life, and lung function in firefighters with WTC-LI. To assess our hypothesis, we developed the Food Intake REstriction for Health OUtcome Support and Education (FIREHOUSE), a randomized controlled clinical trial (RCT). Male firefighters with WTC-LI and a BMI > 27 kg/m2 will be included. We will randomize subjects (1:1) to either: (1) Low Calorie Mediterranean (LoCalMed)-an integrative multifactorial, technology-supported approach focused on behavioral modification, nutritional education that will include a self-monitored diet with feedback, physical activity recommendations, and social cognitive theory-based group counseling sessions; or (2) Usual Care. Outcomes include reduction in body mass index (BMI) (primary), improvement in FEV1, fractional exhaled nitric oxide, pulse wave velocity, lipid profiles, targeted metabolic/clinical biomarkers, and quality of life measures (secondary). By implementing a technology-supported LoCalMed diet our FIREHOUSE RCT may help further the treatment of WTC associated pulmonary disease.

Quantitative lung morphology: semi-automated measurement of mean linear intercept

BACKGROUND

Quantifying morphologic changes is critical to our understanding of the pathophysiology of the lung. Mean linear intercept (MLI) measures are important in the assessment of clinically relevant pathology, such as emphysema. However, qualitative measures are prone to error and bias, while quantitative methods such as mean linear intercept (MLI) are manually time consuming. Furthermore, a fully automated, reliable method of assessment is nontrivial and resource-intensive.

METHODS

We propose a semi-automated method to quantify MLI that does not require specialized computer knowledge and uses a free, open-source image-processor (Fiji). We tested the method with a computer-generated, idealized dataset, derived an MLI usage guide, and successfully applied this method to a murine model of particulate matter (PM) exposure. Fields of randomly placed, uniform-radius circles were analyzed. Optimal numbers of chords to assess based on MLI were found via receiver-operator-characteristic (ROC)-area under the curve (AUC) analysis. Intraclass correlation coefficient (ICC) measured reliability.

RESULTS

We demonstrate high accuracy (AUCROC > 0.8 for MLIactual > 63.83 pixels) and excellent reliability (ICC = 0.9998, p < 0.0001). We provide a guide to optimize the number of chords to sample based on MLI. Processing time was 0.03 s/image. We showed elevated MLI in PM-exposed mice compared to PBS-exposed controls. We have also provided the macros that were used and have made an ImageJ plugin available free for academic research use at https://med.nyu.edu/nolanlab.

CONCLUSIONS

Our semi-automated method is reliable, equally fast as fully automated methods, and uses free, open-source software. Additionally, we quantified the optimal number of chords that should be measured per lung field.

Validation of Predictive Metabolic Syndrome Biomarkers of World Trade Center Lung Injury: A 16-Year Longitudinal Study

BACKGROUND

Metabolic syndrome (MetSyn) predicted future development of World Trade Center lung injury (WTC-LI) in a subgroup of firefighters who never smoked and were male. An intracohort validation of MetSyn as a predictor of WTC-LI is examined in the cohort exposed to the World Trade Center (WTC) that has been followed longitudinally for 16 years.

METHODS

Results of pulmonary function tests (n = 98,221) in workers exposed to the WTC (n = 9,566) were evaluated. A baseline cohort of firefighters who had normal FEV1 before 9/11 and who had had serum drawn before site closure on July 24, 2002 (n = 7,487) was investigated. Case subjects with WTC-LI (n = 1,208) were identified if they had at least two measured instances of FEV1 less than the lower limit of normal (LLN). Cox proportional hazards modeled early MetSyn biomarker ability to predict development of FEV1 less than the LLN.

RESULTS

Case subjects were more likely to smoke, be highly exposed, and have MetSyn. There was a significant exposure dose response; the individuals most highly exposed had a 30.1% increased risk of developing WTC-LI, having MetSyn increased risk of developing WTC-LI by 55.7%, and smoking increased risk by 15.2%. There was significant interaction between smoking and exposure.

CONCLUSIONS

We validated the usefulness of MetSyn to predict future WTC-LI in a larger population of individuals who were exposed. MetSyn defined by dyslipidemia, insulin resistance, and cardiovascular disease suggests that systemic inflammation can contribute to future lung function loss.

Receptor for advanced glycation end-products and environmental exposure related obstructive airways disease: a systematic review

Background

Our group has identified the receptor for advanced glycation end-products (RAGE) as a predictor of World Trade Center particulate matter associated lung injury. The aim of this systematic review is to assess the relationship between RAGE and obstructive airways disease secondary to environmental exposure.

Methods

A comprehensive search using PubMed and Embase was performed on January 5, 2018 utilising keywords focusing on environmental exposure, obstructive airways disease and RAGE and was registered with PROSPERO (CRD42018093834). We included original human research studies in English, focusing on pulmonary end-points associated with RAGE and environmental exposure.

Results

A total of 213 studies were identified by the initial search. After removing the duplicates and applying inclusion and exclusion criteria, we screened the titles and abstracts of 61 studies. Finally, 19 full-text articles were included. The exposures discussed in these articles include particulate matter (n=2) and cigarette smoke (n=17).

Conclusion

RAGE is a mediator of inflammation associated end-organ dysfunction such as obstructive airways disease. Soluble RAGE, a decoy receptor, may have a protective effect in some pulmonary processes. Overall, RAGE is biologically relevant in environmental exposure associated lung disease. Future investigations should focus on further understanding the role and therapeutic potential of RAGE in particulate matter exposure associated lung disease.

RAGE is biologically relevant in environmental exposure associated lung disease. Future investigations should focus on further understanding the role and therapeutic potential of RAGE in particulate matter exposure associated lung diseasehttp://ow.ly/gfZz30o7otU

Non-Cardiac Chest Pain: A Review of Environmental Exposure-Associated Comorbidities and Biomarkers

The prevalence of non-cardiac chest pain (NCCP) ranges from 13-33%. A majority of those presenting with a chief complaint of chest pain are found to have a diagnosis of NCCP. Aerodigestive diseases are a cause of NCCP, and billions of dollars are spent annually on the treatment of NCCP. Furthermore, NCCP can cause significant psychological stress. NCCP is commonly diagnosed when patients have chest pain despite a normal cardiac evaluation. The leading cause of NCCP is gastro-oesophageal reflux disease (GORD). GORD should be suspected in patients who report a history of acid regurgitation, cough, dysphagia, and bloating. Another common cause of NCCP is obstructive airway disease (OAD). A thorough history and review of the symptoms should be performed for those with suspected NCCP, especially because of the contributing end organs. It is known that environmental exposures can commonly cause GORD and OAD; however, NCCP has not been fully explored in the context of environmental exposure. Patients with a history of exposure to particulate matter can develop environmental-exposure-associated GORD and coexisting OAD. This narrative review aims to provide a practical overview of NCCP, its causes, their relation to environmental exposure, and associated biomarkers. The authors used a PubMed search that spanned 2003-2018 to accomplish this. Additionally, this review provides a broad overview of biomarkers of GORD-associated NCCP and OAD-associated NCCP due to environmental exposure.

Metabolomics of World Trade Center-Lung Injury: a machine learning approach

Introduction

Biomarkers of metabolic syndrome expressed soon after World Trade Center (WTC) exposure predict development of WTC Lung Injury (WTC-LI). The metabolome remains an untapped resource with potential to comprehensively characterise many aspects of WTC-LI. This case–control study identified a clinically relevant, robust subset of metabolic contributors of WTC-LI through comprehensive high-dimensional metabolic profiling and integration of machine learning techniques.

Methods

Never-smoking, male, WTC-exposed firefighters with normal pre-9/11 lung function were segregated by post-9/11 lung function. Cases of WTC-LI (forced expiratory volume in 1s <lower limit of normal, n=15) and controls (n=15) were identified from previous cohorts. The metabolome of serum drawn within 6 months of 9/11 was quantified. Machine learning was used for dimension reduction to identify metabolites associated with WTC-LI.

Results

580 metabolites qualified for random forests (RF) analysis to identify a refined metabolite profile that yielded maximal class separation. RF of the refined profile correctly classified subjects with a 93.3% estimated success rate. 5 clusters of metabolites emerged within the refined profile. Prominent subpathways include known mediators of lung disease such as sphingolipids (elevated in cases of WTC-LI), and branched-chain amino acids (reduced in cases of WTC-LI). Principal component analysis of the refined profile explained 68.3% of variance in five components, demonstrating class separation.

Conclusion

Analysis of the metabolome of WTC-exposed 9/11 rescue workers has identified biologically plausible pathways associated with loss of lung function. Since metabolites are proximal markers of disease processes, metabolites could capture the complexity of past exposures and better inform treatment. These pathways warrant further mechanistic research.

The Ionospheric Connection Explorer Mission: Mission Goals and Design

The Ionospheric Connection Explorer, or ICON, is a new NASA Explorer mission that will explore the boundary between Earth and space to understand the physical connection between our world and our space environment. This connection is made in the ionosphere, which has long been known to exhibit variability associated with the sun and solar wind. However, it has been recognized in the 21st century that equally significant changes in ionospheric conditions are apparently associated with energy and momentum propagating upward from our own atmosphere. ICON's goal is to weigh the competing impacts of these two drivers as they influence our space environment. Here we describe the specific science objectives that address this goal, as well as the means by which they will be achieved. The instruments selected, the overall performance requirements of the science payload and the operational requirements are also described. ICON's development began in 2013 and the mission is on track for launch in 2017. ICON is developed and managed by the Space Sciences Laboratory at the University of California, Berkeley, with key contributions from several partner institutions.

SAMI3 ICON: MODEL OF THE IONOSPHERE/PLASMASPHERE SYSTEM

The NRL ionosphere/plasmasphere model SAMI3 has been modified to support the NASA ICON mission. Specifically, SAMI3 ICON has been modified to import the thermospheric composition, temperature, and winds from TIEGCM-ICON and the high-latitude potential from AMIE data. The codes will be run on a daily basis during the ICON mission to provide ionosphere and thermosphere properties to the science community. SAMI3 ICON will provide ionospheric and plasmaspheric parameters such as the electron and ion densities, temperatures, and velocities, as well as the total electron content (TEC), peak ionospheric electron density (NmF2) and height of the F layer at NmF2 (hmF2).

Receptor for advanced glycation end-products and World Trade Center particulate induced lung function loss: A case-cohort study and murine model of acute particulate exposure

World Trade Center-particulate matter(WTC-PM) exposure and metabolic-risk are associated with WTC-Lung Injury(WTC-LI). The receptor for advanced glycation end-products (RAGE) is most highly expressed in the lung, mediates metabolic risk, and single-nucleotide polymorphisms at the AGER-locus predict forced expiratory volume(FEV). Our objectives were to test the hypotheses that RAGE is a biomarker of WTC-LI in the FDNY-cohort and that loss of RAGE in a murine model would protect against acute PM-induced lung disease. We know from previous work that early intense exposure at the time of the WTC collapse was most predictive of WTC-LI therefore we utilized a murine model of intense acute PM-exposure to determine if loss of RAGE is protective and to identify signaling/cytokine intermediates. This study builds on a continuing effort to identify serum biomarkers that predict the development of WTC-LI. A case-cohort design was used to analyze a focused cohort of male never-smokers with normal pre-9/11 lung function. Odds of developing WTC-LI increased by 1.2, 1.8 and 1.0 in firefighters with soluble RAGE (sRAGE)≥97pg/mL, CRP≥2.4mg/L, and MMP-9≤397ng/mL, respectively, assessed in a multivariate logistic regression model (ROC_AUC of 0.72). Wild type(WT) and RAGE-deficient(Ager^-/-) mice were exposed to PM or PBS-control by oropharyngeal aspiration. Lung function, airway hyperreactivity, bronchoalveolar lavage, histology, transcription factors and plasma/BAL cytokines were quantified. WT-PM mice had decreased FEV and compliance, and increased airway resistance and methacholine reactivity after 24-hours. Decreased IFN-γ and increased LPA were observed in WT-PM mice; similar findings have been reported for firefighters who eventually develop WTC-LI. In the murine model, lack of RAGE was protective from loss of lung function and airway hyperreactivity and was associated with modulation of MAP kinases. We conclude that in a multivariate adjusted model increased sRAGE is associated with WTC-LI. In our murine model, absence of RAGE mitigated acute deleterious effects of PM and may be a biologically plausible mediator of PM-related lung disease.

First light from a kilometer-baseline Scintillation Auroral GPS Array

We introduce and analyze the first data from an array of closely spaced Global Positioning System (GPS) scintillation receivers established in the auroral zone in late 2013 to measure spatial and temporal variations in L band signals at 100-1000 m and subsecond scales. The seven receivers of the Scintillation Auroral GPS Array (SAGA) are sited at Poker Flat Research Range, Alaska. The receivers produce 100 s scintillation indices and 100 Hz carrier phase and raw in-phase and quadrature-phase samples. SAGA is the largest existing array with baseline lengths of the ionospheric diffractive Fresnel scale at L band. With an initial array of five receivers, we identify a period of simultaneous amplitude and phase scintillation. We compare SAGA power and phase data with collocated 630.0 nm all-sky images of an auroral arc and incoherent scatter radar electron precipitation measurements, to illustrate how SAGA can be used in multi-instrument observations for subkilometer-scale studies.

KEY POINTS

A seven-receiver Scintillation Auroral GPS Array (SAGA) is now at Poker Flat, Alaska SAGA is the largest subkilometer array to enable phase/irregularities studies Simultaneous scintillation, auroral arc, and electron precipitation are observed.

Determination of the antidepressant fluoxetine and its metabolite norfluoxetine in serum by reversed-phase HPLC with ultraviolet detection

A procedure has been developed for measuring fluoxetine and its desmethyl metabolite, norfluoxetine, in serum by reversed-phase high-performance liquid chromatography (HPLC), with ultraviolet detection at 226 nm. Fluoxetine and norfluoxetine are isolated from serum by liquid-liquid extraction. They are then separated by HPLC and quantified, with reduced haloperidol as the internal standard. Fluoxetine, norfluoxetine, and the reduced haloperidol are separated from all interfering peaks in about 15 min. The standard curve is linear (r = 1.000) for both fluoxetine and norfluoxetine concentrations over the range of 25 to 800 micrograms/L. Between-run CVs for 60 and 200 micrograms/L controls (n = 8) were 6.8 and 4.1% for fluoxetine, and 8.8 and 6.2% for norfluoxetine, respectively. In a study of 24 patients with depression who were being treated with 20-60 mg of fluoxetine per day, fluoxetine and norfluoxetine concentrations in serum, measured during the last three weeks of treatment, were 47-469 micrograms/L and 52-446 micrograms/L, respectively.

Determination of the antidepressant fluoxetine and its metabolite norfluoxetine in serum by reversed-phase HPLC with ultraviolet detection

A procedure has been developed for measuring fluoxetine and its desmethyl metabolite, norfluoxetine, in serum by reversed-phase high-performance liquid chromatography (HPLC), with ultraviolet detection at 226 nm. Fluoxetine and norfluoxetine are isolated from serum by liquid-liquid extraction. They are then separated by HPLC and quantified, with reduced haloperidol as the internal standard. Fluoxetine, norfluoxetine, and the reduced haloperidol are separated from all interfering peaks in about 15 min. The standard curve is linear (r = 1.000) for both fluoxetine and norfluoxetine concentrations over the range of 25 to 800 micrograms/L. Between-run CVs for 60 and 200 micrograms/L controls (n = 8) were 6.8 and 4.1% for fluoxetine, and 8.8 and 6.2% for norfluoxetine, respectively. In a study of 24 patients with depression who were being treated with 20-60 mg of fluoxetine per day, fluoxetine and norfluoxetine concentrations in serum, measured during the last three weeks of treatment, were 47-469 micrograms/L and 52-446 micrograms/L, respectively.

Data-reduction methods for immunoradiometric assays of thyrotropin compared

In an attempt to optimize curve fitting for immunoradiometric assays, we investigated eight data-reduction methods with two commercially available assays of thyrotropin. In four of these methods linear data-reduction models are used: logit-log programs of Iso-Data, Micromedic, and Hewlitt-Packard, and probit-log of Hewlitt-Packard. The other four were nonlinear data-reduction models: Iso-Data's "French curve" (modified spline), four-parameter logistic function, and point-to-point methods, as well as a nonlinear least squares method. In using the eight data-reduction methods on data from analyses of 78 patients' samples, we found clinically relevant differences between models. In fact, differences found by changing data-reduction models were greater than the difference between the two commercial kits.

Data-reduction methods for immunoradiometric assays of thyrotropin compared

In an attempt to optimize curve fitting for immunoradiometric assays, we investigated eight data-reduction methods with two commercially available assays of thyrotropin. In four of these methods linear data-reduction models are used: logit-log programs of Iso-Data, Micromedic, and Hewlitt-Packard, and probit-log of Hewlitt-Packard. The other four were nonlinear data-reduction models: Iso-Data's "French curve" (modified spline), four-parameter logistic function, and point-to-point methods, as well as a nonlinear least squares method. In using the eight data-reduction methods on data from analyses of 78 patients' samples, we found clinically relevant differences between models. In fact, differences found by changing data-reduction models were greater than the difference between the two commercial kits.

Free triiodothyronine (T3) and thyroxine (T4) in a group of unipolar depressed patients and normal subjects

We examined levels of free triiodothyronine (fT3) and free thyroxine (fT4) in serum from a group of 32 patients with unipolar major depression and 46 normal control subjects using the Amerlex (Amersham, Arlington Heights, IL) RIA procedures for these hormones. Free T3 levels were significantly lower (p less than 0.004) in the depressed patients as a group (5.02 +/- 1.01 pmol/L, mean +/- SD) than in the normal control subjects (5.74 +/- 1.23 pmol/L). Free T3 levels were lower (p less than 0.01) in depressed men (5.25 +/- 1.43 pmol/L) when compared with male control subjects (6.46 +/- 1.01 pmol/L). Depressed women (4.78 +/- 0.60 pmol/L) also had lower T3 levels than did the female control subjects (5.09 +/- 1.06 pmol/L), but the difference was not statistically significant. Lower fT3 levels were also observed in melancholic depressed patients when compared with nonmelancholic depressed patients or when compared with normal control subjects. No differences in fT4 were observed between groups in this study.

TRH-induced prolactin release is blunted in females with endogenous unipolar major depression

Twenty-five women with unipolar primary major depressive disorder (20 endogenous, 5 nonendogenous) and 20 female control subjects were studied with the thyrotropin-releasing hormone stimulation test (TRH-ST). Prolactin (PRL) levels were measured before and after TRH administration for patients and control subjects. For patients, thyrotropin (thyroid-stimulating hormone; TSH) levels were measured from the same serum specimens as PRL levels, and the 1 mg dexamethasone suppression test (DST) was performed. Patients with endogenous depression (ED) had significantly lower maximal serum PRL levels (max PRL) following TRH, and a significantly reduced increase over basal serum PRL (delta max PRL) compared to normal controls (NC). Nonendogenous depressed (NED) patients did not differ significantly from the ED or NC groups on either of these measures. For the ED group, delta max PRL was inversely correlated with severity of depressive symptomatology. Basal PRL levels did not differentiate the depressed subgroups (ED, NED) from each other or from the NC group. Depressed patients with blunted delta max PRL values tended to have blunted delta max TSH values and vice versa. Almost all patients with blunting of either delta max PRL or delta max TSH were also DST nonsuppressors; conversely, only about half (7 of 12) of patients who were DST nonsuppressors had either blunted delta max PRL or delta max TSH. Patients with clinical diagnoses of melancholia or psychotic features were significantly more likely to have blunted delta max PRL values than patients without these diagnoses. A disturbance of central noradrenergic function could explain these findings.

Progesterone and 5alpha-pregnane-3,20-dione in peripheral blood of normal young women: Daily measurements throughout the menstrual cycle

The peripheral plasma concentrations of progesterone and 5alpha-pregnane-3,20-dione were measured daily throughout the ovarian cycle of five presumptively ovulatory women. The concentrations of progesterone and 5alpha-pregnane-3,20-dione during the follicular phase were 0.11 +/- 0.02 ng/ml (mean +/- SE) and 0.16 +/- 0.01 ng/ml, respectively. In four of these women the concentrations of both progesterone and 5alpha-pregnane-3,20-dione began to rise immediately after the luteinizing hormone (LH) peak and reached maximal concentrations five to eight days later (progesterone: 8.6 to 19.9 ng/ml; 5alpha-pregnane-3,20-dione: 1.4 to 2.8 ng/ml). The luteal phases in these women, measured from the day of the LH peak to the onset of the next menses, varied from 13 to 18 days. In the other woman with a late LH surge (day 27 of the cycle) the peak concentrations of progesterone and 5alpha-pregnane-3,20-dione were reached four days after the LH peak (8.9 ng/ml and 0.8 ng/ml, respectively). The luteal phase in this woman was 11 days. From the results of this study, it appears that the concentrations of 5alpha-pregnane-3,20-dione in peripheral blood during the luteal phase are proportional to the availability of progesterone as substrate for the 5alpha-reductase enzyme system.