Nipah virus detection at bat roosts following spillover events in Bangladesh, 2012-2019

Knowledge of the dynamics and genetic diversity of Nipah virus circulating in bats and at the human-animal interface is limited by current sampling efforts, which produce few detections of viral RNA. We report on a series of investigations at bat roosts identified near human Nipah cases in Bangladesh between 2012 and 2019. Pooled bat urine samples were collected from 23 roosts; seven roosts (30%) had at least one sample with Nipah RNA detected from the first visit. In subsequent visits to these seven roosts, RNA was detected in bat urine up to 52 days after the presumed exposure of the human case, although the probability of detection declined rapidly with time. These results suggest that rapidly deployed investigations of Nipah virus shedding from bat roosts near human cases could increase the success of viral sequencing compared to background surveillance and enhance our understanding of Nipah virus ecology and evolution.

A reliable islanding identification mechanism for DC microgrid using PCC transient signal

The islanding detection is a major problem for both AC and DC Microgrids. Failure to do so may result in problems such as system instability, increased non-detection zone, out-of-phase reclosing, personnel safety, and power quality deterioration. To address this issue, this paper presents a reliable island identification method for DC Microgrids that employs a Cumulative Sum of Rate of change of Voltage (CSROCOV) to reduce the non-recognition region. The proposed islanding protection scheme employs point of common coupling (PCC) transient signal to detect islands events. The voltage, power, and current sampling are accumulated from the PCC of the distributed generation terminals. The proposed scheme detects islanding in three test cases with varying power mismatching conditions, while non-islanding events are classified as capacitor switching and faults. The system is modelled and simulated in the MATLAB/Simulink environment, then islanding conditions are applied by turning off the main circuit breaker. Simulation results are presented to verify the methodology under different test cases. The robustness of the proposed scheme is also validated against measurement noise.

Comparative genome analysis of Clostridium beijerinckii strains isolated from pit mud of Chinese strong flavor baijiu ecosystem

Clostridium beijerinckii is a well-known anaerobic solventogenic bacterium which inhabits a wide range of different niches. Previously, we isolated five butyrate-producing C. beijerinckii strains from pit mud (PM) of strong-flavor baijiu (SFB) ecosystems. Genome annotation of the five strains showed that they could assimilate various carbon sources as well as ammonium to produce acetate, butyrate, lactate, hydrogen, and esters but did not produce the undesirable flavours isopropanol and acetone, making them useful for further exploration in SFB production. Our analysis of the genomes of an additional 233 C. beijerinckii strains revealed an open pangenome based on current sampling and will likely change with additional genomes. The core genome, accessory genome, and strain-specific genes comprised 1567, 8851, and 2154 genes, respectively. A total of 298 genes were found only in the five C. beijerinckii strains from PM, among which only 77 genes were assigned to Clusters of Orthologous Genes (COG) categories. In addition, 15 transposase and 12 phage integrase families were found in all five C. beijerinckii strains from PM. Between 18 and 21 genome islands (GIs) were predicted for the five C. beijerinckii genomes. The existence of a large number of MGEs indicated that the genomes of the five C. beijerinckii strains evolved with the loss or insertion of DNA fragments in the PM of SFB ecosystems. This study presents a genomic framework of C. beijerinckii strains from PM that could be used for genetic diversification studies and further exploration of these strains.

Leveraging Neuroimaging Tools to Assess Precision and Accuracy in an Alzheimer’s Disease Neuropathologic Sampling Protocol

IntroductionThe study of Alzheimer’s disease investigates topographic patterns of degeneration in the context of connected networks comprised of functionally distinct domains using increasingly sophisticated molecular techniques. Therefore, obtaining high precision and accuracy of neuropathologic tissue sampling will enhance the reliability of molecular studies and contribute to the understanding of Alzheimer’s disease pathology. Neuroimaging tools can help assess these aspects of current sampling protocols as well as contribute directly to their improvement.MethodsUsing a virtual sampling method on magnetic resonance images (MRIs) from 35 participants (21 women), we compared the precision and accuracy of traditional neuropathologic vs. neuroimaging-guided sampling. The impact of the resulting differences was assessed by evaluating the functional connectivity pattern of regions selected by each approach.ResultsVirtual sampling using the traditional neuropathologic approach had low neuroanatomical precision and accuracy for all cortical regions tested. Neuroimaging-guided strategies narrowed these gaps. Discrepancies in the location of traditional and neuroimaging-guided samples corresponded to differences in fMRI measures of functional connectivity.DiscussionIntegrating neuroimaging tools with the neuropathologic assessment will improve neuropathologic-neuroimaging correlations by helping to ensure specific functional domains are accurately sampled for quantitative molecular neuropathologic applications. Our neuroimaging-based simulation of current sampling practices provides a benchmark of precision and accuracy against which to measure improvements when using novel tissue sampling approaches. Our results suggest that relying on gross landmarks alone to select samples at autopsy leads to significant variability, even when sampled by the same neuropathologist. Further, this exercise highlights how sampling precision could be enhanced if neuroimaging were integrated with the standard neuropathologic assessment. More accurate targeting and improved biological homogeneity of sampled brain tissue will facilitate the interpretation of neuropathological analyses in AD and the downstream research applications of brain tissue from biorepositories.

Mosquito Guttersnipe: A New Sampling Tool for Roof Gutters, Tree Holes, and Other Elevated Mosquito Habitats

ABSTRACT Mosquitoes pose health risks to human populations by serving as vectors of diseases. Mosquito control organizations are responsible for inspecting and controlling vector populations to reduce the risk of infection of these diseases. Current sampling methods are effective for numerous types of mosquito habitat, but not conducive for sampling small overhead habitat such as roof gutters or tree holes. We have developed and tested a tool called the Mosquito GutterSnipe to sample these overhead habitats. Volumetric and larval capacity testing of the tool prototype demonstrated comparable sampling integrity to standard mosquito dipping methods. The GutterSnipe can be employed as a reliable way to sample previously overlooked mosquito habitat. Its current model is cost effective and easy to produce for mosquito control organizations and easy to use for inspectors.

Evaluation of a first-event sampling model for monitoring cabbage pests

First-event sampling models for monitoring diamondback moth Plutella xylostella (Lepidoptera: Plutellidae) and small white butterfly, Pieris rapae (Pieridae) are used in integrated production systems of cabbage. Decision-making accuracy and reduced labour needs of those models were unknown compared to fixed-sample monitoring. This we addressed through computer simulations of the currently most used first-event sampling plan for cabbage in DPR Korea. Indeed, this sampling plan in five subplots of a cabbage field at a sampling limit of a maximum 10 plants each, appeared less labour intense than many fixed-sample monitoring plans. However, only a medium accuracy of infestation estimates and correct decision-making for or against pest control was achieved, particularly at high pest densities. If accepting such medium accuracy, the current sampling plan could be reduced from five to three subplots at a sampling limit of 10 plants each, or to a maximum of five assessed plants per each of five subplots, this is, without further loosing accuracy whilst saving labour. Such sampling requires little investment in time and might be therefore applied and validated across more cabbage productions systems of East Asia. Ultimately, first-event sampling, as other sampling plans will remain a compromise between accuracy and practicability.

Probabilistic Thermodynamic Analysis of Metabolic Networks

Motivation Random sampling of metabolic fluxes can provide a comprehensive description of the capabilities of a metabolic network. However, current sampling approaches do not model thermodynamics explicitly, leading to inaccurate predictions of an organism’s potential or actual metabolic operations. Results We present a probabilistic framework combining thermodynamic quantities with steady-state flux constraints to analyze the properties of a metabolic network. It includes methods for probabilistic metabolic optimization and for joint sampling of thermodynamic and flux spaces. Applied to a model of E. coli, we use the methods to reveal known and novel mechanisms of substrate channeling, and to accurately predict reaction directions and metabolite concentrations. Interestingly, predicted flux distributions are multimodal, leading to discrete hypotheses on E. coli’s metabolic capabilities. Availability Python and MATLAB packages available at https://gitlab.com/csb.ethz/pta. Supplementary information Supplementary data are available at Bioinformatics online.

Evaluating the Role of Boat Electrofishing in Fish Monitoring of the Sacramento–San Joaquin Delta

The San Francisco Estuary is an incredibly diverse ecosystem with a mosaic of aquatic habitats inhabited by a number of economically, culturally, and ecologically important fish species. To monitor the temporal and spatial trends of this rich fish community, long-term fish monitoring programs within the estuary use a variety of gear types to capture fish species across life stages and habitats. However, concerns have been raised that current sampling gears may fail to detect certain species—or life stages—that inhabit areas that are not accessible by current gear types (e.g., riprap banks, shallow vegetated areas). Boat electrofishing is one sampling method that has been proposed to supplement current long-term fish monitoring in the upper estuary. In this study, we used fish catch data from past boat electrofishing studies, a long-term beach seine survey, and a couple of long-running trawl surveys to compare the relative probability of detecting various fishes across these sampling gears. Overall, we found that boat electrofishing led to notable improvements in the detection rates for many native and non-native fishes we examined. Boat electrofishing gear was better at detecting the majority of species in the spring (20 out of 38 species, 53%) and fall-winter (24 out of 34 species, 70%) sampling periods. Based on these findings, we recommend that resource managers consider the implementation of a long-term boat electrofishing survey to help them in their long-term conservation planning for fishes within the upper estuary.

Evaluating the Role of Boat Electrofishing in Fish Monitoring of the Sacramento–San Joaquin Delta

The San Francisco Estuary is an incredibly diverse ecosystem with a mosaic of aquatic habitats inhabited by a number of economically, culturally, and ecologically important fish species. To monitor the temporal and spatial trends of this rich fish community, long-term fish monitoring programs within the estuary use a variety of gear types to capture fish species across life stages and habitats. However, concerns have been raised that current sampling gears may fail to detect certain species—or life stages—that inhabit areas that are not accessible by current gear types (e.g., riprap banks, shallow vegetated areas). Boat electrofishing is one sampling method that has been proposed to supplement current long-term fish monitoring in the upper estuary. In this study, we used fish catch data from past boat electrofishing studies, a long-term beach seine survey, and a couple of long-running trawl surveys to compare the relative probability of detecting various fishes across these sampling gears. Overall, we found that boat electrofishing led to notable improvements in the detection rates for many native and non-native fishes we examined. Boat electrofishing gear was better at detecting the majority of species in the spring (20 out of 38 species, 53%) and fall-winter (24 out of 34 species, 70%) sampling periods. Based on these findings, we recommend that resource managers consider the implementation of a long-term boat electrofishing survey to help them in their long-term conservation planning for fishes within the upper estuary.