First estimation of the diffusive methane flux and concentrations from Lake Winnipeg, a large, shallow and eutrophic lake

Freshwater lakes are increasingly recognized as significant sources of atmospheric methane (CH4), potentially offsetting the terrestrial carbon sink. We present the first study of dissolved CH4 distributions and lake-air flux from Lake Winnipeg, based on two-years of observations collected during all seasons. Methane concentrations across two years had a median of value of 24.6 nmol L-1 (mean: 41.6 ± 68.2 nmol L-1) and ranged between 5.0 and 733.8 nmol L-1, with a 2018 annual median of 24.4 nmol L-1 (mean: 46.8 ± 99.3 nmol L-1) and 25.1 nmol L-1 (mean: 38.8 ± 45.2 nmol L-1) in 2019. The median lake-air flux was 1.1 µmol m−2 h−1 (range: 0.46–70.1 µmol m−2h−1, mean: 2.9 ± 10.2 µmol m−2 h−1) in 2018, and 5.5 µmol m−2h−1 (range: 0.0–78.4 µmol m−2 h−1, mean: 2.7 ± 8.5 µmol m−2 h−1) in 2019, for a total diffusive emission of 0.001 Tg of CH4-C yr−1. We found evidence of consistent spatial variability, with higher concentrations near river inflows. Significant seasonal trends in CH4 concentrations were not observed, though fluxes were highest during the fall season due to strong winds. Our findings suggest Lake Winnipeg is a CH4 source of similar mean magnitude to Lake Erie, with lower concentrations and fluxes per unit area than smaller mid- to high-latitude lakes. Additional work is needed to understand the factors underlying observed spatial variability in dissolved gas concentration, including estimations of production and consumption rates in the water column and sediments

Sequence learning in Associative Neuronal-Astrocytic Network

The neuronal paradigm of studying the brain has left us with limitations in both our understanding of how neurons process information to achieve biological intelligence and how such knowledge may be translated into artificial intelligence and its most brain-derived branch, neuromorphic computing. Overturning our fundamental assumptions of how the brain works, the recent exploration of astrocytes is revealing that these long-neglected brain cells dynamically regulate learning by interacting with neuronal activity at the synaptic level. Following recent experimental evidence, we designed an associative, Hopfield-type, neuronal-astrocytic network and analyzed the dynamics of the interaction between neurons and astrocytes. We show that astrocytes were sufficient to trigger transitions between learned memories in the neuronal component of the network. Further, we mathematically derived the timing of the transitions that was governed by the dynamics of the calcium-dependent slow-currents in the astrocytic processes. Overall, we provide a brain-morphic mechanism for sequence learning that is inspired by, and aligns with, recent experimental findings. To evaluate our model, we emulated astrocytic atrophy and showed that memory recall becomes significantly impaired after a critical point of affected astrocytes was reached. This brain-inspired and brain-validated approach supports our ongoing efforts to incorporate non-neuronal computing elements in neuromorphic information processing.Comment: 8 pages, 5 figure

The Relationship between Asthma and Depression in Primary Care Patients: A Historical Cohort and Nested Case Control Study

Asthma and depression are common health problems in primary care. Evidence of a relationship between asthma and depression is conflicting. Objectives: to determine 1. The incidence rate and incidence rate ratio of depression in primary care patients with asthma compared to those without asthma, and 2. The standardized mortality ratio of depressed compared to non-depressed patients with asthma.A historical cohort and nested case control study using data derived from the United Kingdom General Practice Research Database. Participants: 11,275 incident cases of asthma recorded between 1/1/95 and 31/12/96 age, sex and practice matched with non-cases from the database (ratio 1∶1) and followed up through the database for 10 years. 1,660 cases were matched by date of asthma diagnosis with 1,660 controls. Main outcome measures: number of cases diagnosed with depression, the number of deaths over the study period.The rate of depression in patients with asthma was 22.4/1,000 person years and without asthma 13.8 /1,000 person years. The incident rate ratio (adjusted for age, sex, practice, diabetes, cardiovascular disease, cerebrovascular disease, smoking) was 1.59 (95% CI 1.48–1.71). The increased rate of depression was not associated with asthma severity or oral corticosteroid use. It was associated with the number of consultations (odds ratio per visit 1.09; 95% CI 1.07–1.11). The age and sex adjusted standardized mortality ratio for depressed patients with asthma was 1.87 (95% CI: 1.54–2.27).Asthma is associated with depression. This was not related to asthma severity or oral corticosteroid use but was related to service use. This suggests that a diagnosis of depression is related to health seeking behavior in patients with asthma. There is an increased mortality rate in depressed patients with asthma. The cause of this needs further exploration. Consideration should be given to case-finding for depression in this population

Holocene deglaciation and glacier readvances on the Fildes Peninsula and King George Island (Isla 25 de Mayo), South Shetland Islands, NW Antarctic Peninsula

To provide insights into glacier-climate dynamics of the South Shetland Islands (SSI), NW Antarctic Peninsula, we present a new deglaciation and readvance model for the Bellingshausen Ice Cap (BIC) on Fildes Peninsula and for King George Island/Isla 25 de Mayo (KGI) ~62°S. Deglaciation on KGI began after c. 15 ka cal BP and had progressed to within present-day limits on the Fildes Peninsula, its largest ice-free peninsula, by c. 6.6–5.3 ka cal BP. Probability density phase analysis of chronological data constraining Holocene glacier advances on KGI revealed up to eight 95% probability ‘gaps’ during which readvances could have occurred. These are grouped into four stages – Stage 1: a readvance and marine transgression, well-constrained by field data, between c. 7.4–6.6 ka cal BP; Stage 2: four probability ‘gaps’, less well-constrained by field data, between c. 5.3–2.2 ka cal BP; Stage 3: a well-constrained but restricted ‘readvance’ between c. 1.7–1.5 ka; Stage 4: two further minor ‘readvances’, one less well-constrained by field data between c. 1.3–0.7 ka cal BP (68% probability), and a ‘final’ well-constrained ‘readvance’ after 1950 CE) is associated with recent warming/more positive SAM-like conditions

Non-Linear Neuronal Responses as an Emergent Property of Afferent Networks: A Case Study of the Locust Lobula Giant Movement Detector

In principle it appears advantageous for single neurons to perform non-linear operations. Indeed it has been reported that some neurons show signatures of such operations in their electrophysiological response. A particular case in point is the Lobula Giant Movement Detector (LGMD) neuron of the locust, which is reported to locally perform a functional multiplication. Given the wide ramifications of this suggestion with respect to our understanding of neuronal computations, it is essential that this interpretation of the LGMD as a local multiplication unit is thoroughly tested. Here we evaluate an alternative model that tests the hypothesis that the non-linear responses of the LGMD neuron emerge from the interactions of many neurons in the opto-motor processing structure of the locust. We show, by exposing our model to standard LGMD stimulation protocols, that the properties of the LGMD that were seen as a hallmark of local non-linear operations can be explained as emerging from the dynamics of the pre-synaptic network. Moreover, we demonstrate that these properties strongly depend on the details of the synaptic projections from the medulla to the LGMD. From these observations we deduce a number of testable predictions. To assess the real-time properties of our model we applied it to a high-speed robot. These robot results show that our model of the locust opto-motor system is able to reliably stabilize the movement trajectory of the robot and can robustly support collision avoidance. In addition, these behavioural experiments suggest that the emergent non-linear responses of the LGMD neuron enhance the system's collision detection acuity. We show how all reported properties of this neuron are consistently reproduced by this alternative model, and how they emerge from the overall opto-motor processing structure of the locust. Hence, our results propose an alternative view on neuronal computation that emphasizes the network properties as opposed to the local transformations that can be performed by single neurons

An Integrated Approach for the Analysis of Biological Pathways using Mixed Models

Gene class, ontology, or pathway testing analysis has become increasingly popular in microarray data analysis. Such approaches allow the integration of gene annotation databases, such as Gene Ontology and KEGG Pathway, to formally test for subtle but coordinated changes at a system level. Higher power in gene class testing is gained by combining weak signals from a number of individual genes in each pathway. We propose an alternative approach for gene-class testing based on mixed models, a class of statistical models that

The Pioneer Anomaly

Radio-metric Doppler tracking data received from the Pioneer 10 and 11 spacecraft from heliocentric distances of 20-70 AU has consistently indicated the presence of a small, anomalous, blue-shifted frequency drift uniformly changing with a rate of ~6 x 10^{-9} Hz/s. Ultimately, the drift was interpreted as a constant sunward deceleration of each particular spacecraft at the level of a_P = (8.74 +/- 1.33) x 10^{-10} m/s^2. This apparent violation of the Newton's gravitational inverse-square law has become known as the Pioneer anomaly; the nature of this anomaly remains unexplained. In this review, we summarize the current knowledge of the physical properties of the anomaly and the conditions that led to its detection and characterization. We review various mechanisms proposed to explain the anomaly and discuss the current state of efforts to determine its nature. A comprehensive new investigation of the anomalous behavior of the two Pioneers has begun recently. The new efforts rely on the much-extended set of radio-metric Doppler data for both spacecraft in conjunction with the newly available complete record of their telemetry files and a large archive of original project documentation. As the new study is yet to report its findings, this review provides the necessary background for the new results to appear in the near future. In particular, we provide a significant amount of information on the design, operations and behavior of the two Pioneers during their entire missions, including descriptions of various data formats and techniques used for their navigation and radio-science data analysis. As most of this information was recovered relatively recently, it was not used in the previous studies of the Pioneer anomaly, but it is critical for the new investigation.Comment: 165 pages, 40 figures, 16 tables; accepted for publication in Living Reviews in Relativit

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

RNAi screening identifies Trypanosoma brucei stress response protein kinases required for survival in the mouse

Protein kinases (PKs) are a class of druggable targets in Trypanosoma brucei, the causative agent of Human African Trypanosomiasis (sleeping sickness), yet little is known about which PKs are essential for survival in mammals. A recent kinome-wide RNAi screen with 176 individual bloodstream form Trypanosoma brucei lines identified PKs required for proliferation in culture. In order to assess which PKs are also potential virulence factors essential in vivo, lines were pooled, inoculated into mice, and screened for loss of fitness after 48 h RNAi. The presence of trypanosomes in the bloodstream was assessed using RNAi target sequencing (RITseq) and compared to growth in culture. We identified 49 PKs with a significant loss of fitness in vivo in two independent experiments, and a strong correlation between in vitro and in vivo loss of fitness for the majority. Nine PKs had a more pronounced growth defect in vivo, than in vitro. Amongst these PKs were several with putative functions related to stress responses mediated through the PI3K/TOR or MAPK signaling cascades, which act to protect the parasite from complement-mediated and osmotic lysis. Identification of these virulence-associated PKs provides new insights into T. brucei-host interaction and reveals novel potential protein kinase drug targets