Swiss Cheese, Drosophila Ortholog of Hereditary Spastic Paraplegia Gene NTE, Maintains Neuromuscular Junction Development and Microtubule Network

Neuropathy target esterase (NTE) is a molecular target for the organophosphorus compound-induced delayed neuropathy (OPIDN) and also one of the genetic factors responsible for the development of the hereditary spastic paraplegia (HSP), characterized by axon degeneration of motoneurons causing progressive lower-limb spastic paralysis. Both HSP and OPIDN are characterized by the distal axonopathy. The molecular mechanisms underlying the axonopathy involved in HSP and OPIDN are poorly understood. In order to have a better understanding of the mechanisms that NTE is involved in, we used one of the homologs, human NTE. Swiss cheese (sws) is a Drosophila melanogaster ortholog of NTE with 39% homology. Mutations in sws as it was shown before lead to age-dependent neurodegeneration, structure alteration of glia cells, and reduced insect life span. To study SWS functions, we used the system of the third-instar larval neuromuscular junctions of D. melanogaster. In this study, we show that mutations in sws (sws1 and sws76−1 ) and SWS knockdown alter neuromuscular junction’s morphology and synaptic microtubules organization

Risk Perception of Coastal Communities and Authorities on Harmful Algal Blooms in Ecuador

The ocean is intrinsically linked to human health as it provides food and wellbeing, yet shifts in its dynamics can pose climate-ecological risks, such as harmful algal blooms (HABs) that can impact the health and economy of coastal communities. For decades, Ecuadorian coastal communities have witnessed seasonal algal blooms, events that are driven by factors including complex ocean–climate interactions, nutrient availability, and ecological variables. However, little is known about the risk perceived by coastal populations regarding such events. Understanding how specific groups of people in specific places perceive HABs risks is critical for communicating, promoting, and regulating public health measures. This study assessed the knowledge, attitudes, and practices of fishermen, restaurant owners, and coastal authorities in relation to HABs, or ‘red tide’ events, in coastal Ecuador. Methods utilized in this study include a non-probabilistic sampling approach for the two studied populations: coastal communities comprised of fishermen and restaurant owners (N1 = 181), and authorities comprised of coastal officials in the sectors of health, and environment and risk management (N2 = 20). Using contingency tables, chi-square test, Cramer’s V correlation statistic, and multiple correspondence analysis, this study compared the responses of these two groups, coastal communities and authorities, to determine whether principal activity, or livelihood, affected risk perception in each group. This project implemented four workshops to interact with coastal stakeholders and more deeply understand risk perception within studied populations. Results demonstrated that principal activity indeed influenced risk perception of red tides, and that fishermen, restaurant owners, and health authorities had limited knowledge and low risk perception of red tide impacts on human health. Recommendations produced from this research include tailored workshops and improved communication between authorities and coastal communities to enhance algal bloom monitoring and coastal management during future red tide events

Observational constraints on spatial anisotropy of G from orbital motions

A phenomenological anisotropic variation \Delta G/G of the Newtonian gravitational coupling parameter G, if real, would affect the orbital dynamics of a two-body gravitationally bound system in a specific way. We analytically work out the long-term effects that such a putative modification of the usual Newtonian inverse-square law would induce on the trajectory of a test particle orbiting a central mass. Without making any a-priori simplifying assumptions concerning the orbital configuration of the test particle, it turns out that its osculating semi-major axis a, eccentricity e, pericenter \varpi and mean anomaly M undergo long-term temporal variations, while the inclination I and the node \Omega are left unaffected. Moreover, the radial and the transverse components of the position and the velocity vectors r and v of the test particle experience non-vanishing changes per orbit, contrary to the out-of-plane ones. Then, we compute our theoretical predictions for some of the major bodies of the solar system by orienting the gradient of G(r) towards the Galactic Center and keeping it fixed over the characteristic timescales involved. By comparing our calculation to the latest observational determinations for the same bodies, we infer \Delta G/G <= 10^-17 over about 1 au. Finally, we consider also the Supermassive Black Hole hosted by the Galactic Center in Sgr A^* and the main sequence star S2 orbiting it in about 16 yr, obtaining just \Delta G/G <= 10^-2 over 1 kau.Comment: LaTex2e, 18 pages, no figures, 4 tables. Accepted by Classical and Quantum Gravity (CQG). Typo fixed. Reference update

UAVs in Support of Algal Bloom Research: A Review of Current Applications and Future Opportunities

Algal blooms have become major public health and ecosystem vitality concerns globally. The prevalence of blooms has increased due to warming water and additional nutrient inputs into aquatic systems. In response, various remotely-sensed methods of detection, analysis, and forecasting have been developed. Satellite imaging has proven successful in the identification of various inland and coastal blooms at large spatial and temporal scales, and airborne platforms offer higher spatial and often spectral resolution at targeted temporal frequencies. Unmanned aerial vehicles (UAVs) have recently emerged as another tool for algal bloom detection, providing users with on-demand high spatial and temporal resolution at lower costs. However, due to the challenges of processing images of water, payload costs and limitations, and a lack of standardized methods, UAV-based algal bloom studies have not gained critical traction. This literature review explores the current state of this field, and highlights opportunities that could promote its growth. By understanding the technical parameters required to identify algal blooms with airborne platforms, and comparing these capabilities to current UAV technology, such knowledge will assist managers, researchers, and public health officials in utilizing UAVs to monitor and predict blooms at greater spatial and temporal precision, reducing exposure to potentially toxic events

The Good, the Bad, the Algae: Using High Resolution Imagery to Detect Freshwater Algal Blooms in California

Algae are an essential component of aquatic ecosystems. They provide food, habitat,structural support, and oxygen to marine, freshwater, and brackishwater environments alike. However, algae in excess can be problematic. Harmful algal blooms (HABs) are proliferations of both toxic and non-toxic algal species that can cause ecological and environmental damage in lakes, reservoirs, and rivers. As global temperatures rise, coupled with increasing nutrient inputs from eutrophication and atmospheric deposition, many predict HABs will also increase in frequency and intensity. There is a need to advance methods in algal bloom monitoring to keep pace with these global trends. As in situ techniques such as water quality samples, swimming, and laboratory assessments can be time-consuming and expensive, remote sensing may offer a faster, more cost-effective method to investigate blooms at greater spatial and temporal extents in freshwater ecosystems. Rivers, reservoirs, and lakes are particularly important because of their environmental, economic, cultural, and recreational roles in nature and society, and advancing remote sensing methods could improve our ability to monitor and mitigate blooms in these settings across the world. This dissertation explores the spatial and temporal dynamics of algal blooms, both “good” (non-toxic filamentous algae) and “bad” (toxic cyanobacteria), throughout freshwater environments of California. In Chapter 1, I introduce the importance and risks of algae, as well as a background of in situ and remote sensing methods to monitor algae. Chapter 2 examines the use of unoccupied aerial vehicle (UAV) imagery over the Klamath River to understand the distribution of aquatic plants and filamentous algae prior to the largest dam removal in history. Chapter 3 moves upstream in the Klamath River to two reservoirs, Iron Gate and Copco, and uses high-resolution Sentinel-2 satellite imagery to detect the spatial distribution and timing of potentially toxic blooms in a five-year time series. Chapter 4 integrates two statewide harmful algal bloom datasets (one of crowdsourced reports and another of 300-meter Sentinel-3 satellite imagery) with higher-resolution Sentinel-2 imagery in order to monitor a greater number of lakes and reservoirs in California with higher resolution data. Finally, in Chapter 5, I review the major findings, lessons learned, and challenges of this research and posit new directions of future research to improve remote sensing techniques of algal bloom detection in freshwater environments