Analysis and Monte Carlo simulation of near-terminal aircraft flight paths

The flight paths of arriving and departing aircraft at an airport are stochastically represented. Radar data of the aircraft movements are used to decompose the flight paths into linear and curvilinear segments. Variables which describe the segments are derived, and the best fitting probability distributions of the variables, based on a sample of flight paths, are found. Conversely, given information on the probability distribution of the variables, generation of a random sample of flight paths in a Monte Carlo simulation is discussed. Actual flight paths at Dulles International Airport are analyzed and simulated

Characterization and Compensation of the Residual Chirp in a Mach-Zehnder-Type Electro-Optical Intensity Modulator

We utilize various techniques to characterize the residual phase modulation of a fiber-based Mach-Zehnder electro-optical intensity modulator. A heterodyne technique is used to directly measure the phase change due to a given change in intensity, thereby determining the chirp parameter of the device. This chirp parameter is also measured by examining the ratio of sidebands for sinusoidal amplitude modulation. Finally, the frequency chirp caused by an intensity pulse on the nanosecond time scale is measured via the heterodyne signal. We show that this chirp can be largely compensated with a separate phase modulator. The various measurements of the chirp parameter are in reasonable agreement.Comment: 11 pages, 6 figure

A Study of the Relationship Between Uric Acid and Substantia Nigra Brain Connectivity in Patients With REM Sleep Behavior Disorder and Parkinson’s Disease

Low levels of the natural antioxidant uric acid (UA) and the presence of REM sleep behavior disorder (RBD) are both associated with an increased likelihood of developing Parkinson’s disease (PD). RBD and PD are also accompanied by basal ganglia dysfunction including decreased nigrostriatal and nigrocortical resting state functional connectivity. Despite these independent findings, the relationship between UA and substantia nigra (SN) functional connectivity remains unknown. In the present study, voxelwise analysis of covariance was used in a cross-sectional design to explore the relationship between UA and whole-brain SN functional connectivity using the eyes-open resting state fMRI method in controls without RBD, patients with idiopathic RBD, and PD patients with and without RBD. The results showed that controls exhibited a positive relationship between UA and SN functional connectivity with left lingual gyrus. The positive relationship was reduced in patients with RBD and PD with RBD, and the relationship was found to be negative in PD patients. These results are the first to show differential relationships between UA and SN functional connectivity among controls, prodromal, and diagnosed PD patients in a ventral occipital region previously documented to be metabolically and structurally altered in RBD and PD. More investigation, including replication in longitudinal designs with larger samples, is needed to understand the pathophysiological significance of these changes

Iga-Biome Profiles Correlate With Clinical Parkinson\u27s Disease Subtypes

BACKGROUND: Parkinson\u27s disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity. OBJECTIVE: Because secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson\u27s disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes. METHODS: Flow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina). RESULTS: IgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson\u27s disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA+ fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples. CONCLUSION: IgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analyses identified a unique proinflammatory microbial signature in the IgA+ fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches

Iga-Biome Profiles Correlate With Clinical Parkinson\u27s Disease Subtypes

BACKGROUND: Parkinson\u27s disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity. OBJECTIVE: Because secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson\u27s disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes. METHODS: Flow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina). RESULTS: IgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson\u27s disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA+ fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples. CONCLUSION: IgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analyses identified a unique proinflammatory microbial signature in the IgA+ fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches

The crossroads of tradition and modern technology: integrative approaches to studying carnivores in low density ecosystems

The study of large carnivores in semi-arid ecosystems presents inherent challenges due to their low densities, extensive home ranges, and elusive nature. We explore the potential for the synthesis of traditional knowledge (i.e. art of tracking) and modern technology to address challenges in conservation and wildlife research in these challenging environments. Our research focuses on the African lion (Panthera leo) in the Central Kalahari region of Botswana as a model system to demonstrate the potential of this integrative approach. Combining GPS tracking and traditional San trackers’ expertise, we present two case studies: (1) the individual identification of lions via a combination of tracking and footprint analysis and (2) the monitoring of territorial behavior through a combination of GPS technology (i.e. GPS collars and handheld GPS devices) and non-invasive tracking. These approaches enhance our understanding of carnivore ecology as well as support conservation efforts by offering a non-invasive, cost-effective, and highly accurate means of monitoring populations. Our findings underscore the value of merging traditional tracking skills with contemporary analytical and technological developments to offer new insights into the ecology of carnivores in challenging environments. This approach not only improves data collection accuracy and efficiency but also fosters a deeper understanding of wildlife, ensuring the conservation and sustainable management of these species. Our work advocates for the inclusion of indigenous knowledge in conservation science, highlighting its relevance and applicability across various disciplines, thereby broadening the methodologies used to study wildlife, monitor populations, and inform conservation strategies

Longitudinal Connectomes as a Candidate Progression Marker for Prodromal Parkinson’s Disease

Parkinson’s disease is the second most prevalent neurodegenerative disorder in the Western world. It is estimated that the neuronal loss related to Parkinson’s disease precedes the clinical diagnosis by more than 10 years (prodromal phase) which leads to a subtle decline that translates into non-specific clinical signs and symptoms. By leveraging diffusion magnetic resonance imaging brain (MRI) data evaluated longitudinally, at least at two different time points, we have the opportunity of detecting and measuring brain changes early on in the neurodegenerative process, thereby allowing early detection and monitoring that can enable development and testing of disease modifying therapies. In this study, we were able to define a longitudinal degenerative Parkinson’s disease progression pattern using diffusion magnetic resonance imaging connectivity information. Such pattern was discovered using a de novo early Parkinson’s disease cohort (n = 21), and a cohort of Controls (n = 30). Afterward, it was tested in a cohort at high risk of being in the Parkinson’s disease prodromal phase (n = 16). This progression pattern was numerically quantified with a longitudinal brain connectome progression score. This score is generated by an interpretable machine learning (ML) algorithm trained, with cross-validation, on the longitudinal connectivity information of Parkinson’s disease and Control groups computed on a nigrostriatal pathway-specific parcellation atlas. Experiments indicated that the longitudinal brain connectome progression score was able to discriminate between the progression of Parkinson’s disease and Control groups with an area under the receiver operating curve of 0.89 [confidence interval (CI): 0.81–0.96] and discriminate the progression of the High Risk Prodromal and Control groups with an area under the curve of 0.76 [CI: 0.66–0.92]. In these same subjects, common motor and cognitive clinical scores used in Parkinson’s disease research showed little or no discriminative ability when evaluated longitudinally. Results suggest that it is possible to quantify neurodegenerative patterns of progression in the prodromal phase with longitudinal diffusion magnetic resonance imaging connectivity data and use these image-based patterns as progression markers for neurodegeneration

CSF from Parkinson disease Patients Differentially Affects Cultured Microglia and Astrocytes

<p>Abstract</p> <p>Background</p> <p>Excessive and abnormal accumulation of alpha-synuclein (α-synuclein) is a factor contributing to pathogenic cell death in Parkinson's disease. The purpose of this study, based on earlier observations of Parkinson's disease cerebrospinal fluid (PD-CSF) initiated cell death, was to determine the effects of CSF from PD patients on the functionally different microglia and astrocyte glial cell lines. Microglia cells from human glioblastoma and astrocytes from fetal brain tissue were cultured, grown to confluence, treated with fixed concentrations of PD-CSF, non-PD disease control CSF, or control no-CSF medium, then photographed and fluorescently probed for α-synuclein content by deconvolution fluorescence microscopy. Outcome measures included manually counted cell growth patterns from day 1-8; α-synuclein density and distribution by antibody tagged 3D model stacked deconvoluted fluorescent imaging.</p> <p>Results</p> <p>After PD-CSF treatment, microglia growth was reduced extensively, and a non-confluent pattern with morphological changes developed, that was not evident in disease control CSF and no-CSF treated cultures. Astrocyte growth rates were similarly reduced by exposure to PD-CSF, but morphological changes were not consistently noted. PD-CSF treated microglia showed a significant increase in α-synuclein content by day 4 compared to other treatments (p ≤ 0.02). In microglia only, α-synuclein aggregated and redistributed to peri-nuclear locations.</p> <p>Conclusions</p> <p>Cultured microglia and astrocytes are differentially affected by PD-CSF exposure compared to non-PD-CSF controls. PD-CSF dramatically impacts microglia cell growth, morphology, and α-synuclein deposition compared to astrocytes, supporting the hypothesis of cell specific susceptibility to PD-CSF toxicity.</p

Survival rates and causes of mortality of leopards Panthera pardus in southern Africa

Estimation of survival rates is important for developing and evaluating conservation options for large carnivores. However, telemetry studies for large carnivores are often characterized by small sample sizes that limit meaningful conclusions. We used data from 10 published and 8 unpublished studies of leopards Panthera pardus in southern Africa to estimate survival rates and investigate causes of leopard mortality. Mean survival rates were significantly lower in non-protected (0.55 ± SE 0.08) compared to protected areas (0.88 ± 0.03). Inside protected areas juveniles had significantly lower survival (0.39 ± 0.10) compared to subadults (0.86 ± 0.07) and adults (0.88 ± 0.04). There was a greater difference in cause of death between protected and non-protected areas for females compared to males, with people being the dominant cause of mortality outside protected areas for both females and males. We suggest there is cause for concern regarding the sustainability of leopard populations in South Africa, as high female mortality may have severe demographic effects and a large proportion of suitable leopard habitat lies in non-protected areas. However, because a large proportion of deaths outside protected areas were attributed to deliberate killing by people, we suggest that management interventions may have the potential to increase leopard survival dramatically. We therefore stress the urgency to initiate actions, such as conflict mitigation programmes, to increase leopard survival in non-protected areas.The International Foundation of Science (D/4984-1), Wild Foundation (2008-011), Wilson Foundation and the University of Pretoria. LHS was further supported by the National Research Foundation (74819), FD by the National Research Foundation and a research fellowship from the University of Pretoria, and MJS by the Department of Science and Technology Centre of Excellence for Invasion Biology and the National Research Foundation.http://journals.cambridge.org/action/displayJournal?jid=ORXam201

A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma

The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000–5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p<0.01 and fold change >5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273–283, FIBA 5–16, and LBN 306–313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens