Miracle-dz/UniFAR-FTUs huggingface dataset:
Strategic Management of an Invasive Ant‐scale Mutualism Enables Recovery of a Threatened Tropical Tree Species

Mutualisms between invasive ants and honeydew‐producing insects can have widespread negative effects on natural ecosystems. This is becoming an increasingly serious problem worldwide, causing certain ecosystems to change radically. Management of these abundant and influential mutualistic species is essential if the host ecosystem is to recover to its former non‐invaded status. This negative effect is particularly prevalent on some tropical islands, including Cousine Island, Seychelles. On this island, the invasive ant Pheidole megacephala has caused serious indirect damage to the threatened native Pisonia grandis trees via a mutualism with an invasive scale insect, Pulvinaria urbicola. We aimed to suppress the ant, thereby decoupling the mutualism and enabling recovery of the Pisonia trees. We treated all areas where ant pressure was high with a selective formicidal bait, which was deployed in custom‐made bait stations designed to avoid risk of treatment to endemic fauna. In the treated area, ant foraging activity was reduced by 93 percent and was followed by a 100 percent reduction in scale insect density. Abundance of endemic herbivorous insects and herbivorous activity increased significantly, however, after the decline in mutualistic species densities. Despite the native herbivore increase, there was considerable overall improvement in Pisonia shoot condition and an observed increase in foliage density. Our results demonstrate the benefit of strategic management of highly mutualistic alien species to the native Pisonia trees. It also supports the idea that area‐wide suppression is a feasible alternative to eradication for achieving positive conservation management at the level of the forest ecosystem.
Sustained adaptability: the transaction level

A new system level, called the ‘Transaction Level’ is introduced. I argue that such architectures should not be couched in (macro)cognitive terms, but rather in terms of networks of nodes and links that effectuate transactions. The principle of relationality governing this level states that links are selected to attain transactions. The transaction level is a true systems level rather than a perspective on a particular unit of analysis (individual, team, organization). The novelties and advantages of the introduction of the transaction level for the field of resilience engineering are: (1) an increased emphasis on longitudinal data collection and use of social network analysis as one of the tools to analyse data collected on nodes and links; (2) providing an explanation for when transactions fail and may lead to accidents in sociotechnical systems; (3) a renewed emphasis on the study of patterned interactions of sociomaterial assemblages; (4) providing a language for describing architectures for sustained adaptability and thus advancing relative invariants in the study of Layered Networks.
Aquatic effect duration study of Cry4 toxin with immunoassay and Aedes aegypti larval biotest

Bacillus thuringiensis subsp. israelensis (Bti) preparations are widely used for culicid larvae. There is no suitable commercially available analytical method for Cry4 toxin as active ingredient in Bti preparations. To overcome this limitation, an enzyme-linked immunosorbent assay (ELISA) was developed for quantitative determination of Cry4 toxin allowing a limit of detection (LOD) of ∼2 ng ml−1 in water. Preconcentration of aqueous samples by lyophilisation resulted in low but reproducible recoveries (25.7±6.8%), and the practical LODs for Bti preparations VECTOBAC WDG granulate and VECTOBAC 12 AS suspension were found to be ∼170 ng ml−1 and ∼900 ng ml−1, respectively. ELISA determinations indicated a rapid decay in detectable concentrations of VECTOBAC WDG applied at 400 ng ml−1 concentration in surface water: detected concentrations decreased by 18% and 44% in 4 days in water collected from two locations, and dropped below LOD afterwards. Larval mortality of Aedes aegypti indicated a continuous decrease even thereafter. Thus, quantitative Cry4 toxin detection facilitates proper timing and frequency of treatments to achieve optimal efficacy.
Seasonal dynamics of plant species at fine scale in wooded pastures

A cell-grid method was used to survey seasonal changes in four herbaceous communities of a wooded pasture. Permanent plots consisted in 1-m2 grids subdivided into 100 cells of 1 dm2. In each cell of each plot and every month from May to September, we estimated dominance, and grazing occurrence of all species. Plant communities included an eutrophic grazed meadow, a temporary refused meadow, an underwood herb community and an oligotrophic lawn. Our results showed that seasonal changes in species composition were very strong and scale-dependent. Changes at plot scale were mainly driven by a seasonal shift. Changes at cell scale suggested high small-scale dynamics of species. Despite high changes at cell scale, the structure of the community did not change and local species richness did not show any trend. We found no correlation between the turnover at cell scale and cattle activity. We conclude that dynamics and internal species turnover of the community at fine scale and short time seem more driven by internal characteristics of the community than by disturbances induced by cattle. Furthermore, at seasonal scale, plant communities may be stable in their structure despite fluctuations in their texture.
Selective feeding of Arctodiaptomus salinus (Copepoda, Calanoida) on co‐occurring sibling rotifer species

Summary 1. Using two- and three-dimensional video recordings, we examined the steps involved in predation that lead to the differential vulnerability of three sympatric rotifer sibling species (Brachionus plicatilis, B. ibericus and B. rotundiformis) to a co-occurring, predatory, calanoid copepod (Arctodiaptomus salinus). 2. Brachionus rotundiformis, the smallest prey tested, was the most vulnerable with the highest encounter rate, probability of attack, capture and ingestion, and the lowest handling time. 3. Comparison of our results with those of a previous study shows that A. salinus is a more efficient predator than a co-occurring cyclopoid copepod (Diacyclops bicuspidatus odessanus) feeding on these same rotifer species. However, despite its higher capture rates, A. salinus seems to be less selective than D. b. odessanus based on attack distances and prey handling times. 4. The differential vulnerability to both calanoid and cyclopoid copepod predation can help explain the coexistence and seasonal succession of these co-occurring rotifer species.
Simulating drug effects on blood glucose laboratory test time series with a conditional WGAN

The unexpected effects of medications has led to more than 14 million drug adverse events reported to the Food and Drug Administration (FDA) over the past 10 years in the United States alone, with a little over 1.3 million of them linked to death, and represents a medical and financial burden on our healthcare. Laboratory tests have the potential to capture inter-individual variability in drug responses, but a significant portion of the patient population has unique treatment pathways that impedes forecasting and optimal decision making. Generative Adversarial Networks (GANs) are flexible implicit generative models that have demonstrated their ability to capture complex correlations in field like computer vision and natural language. Their latent representation capacity is an opportunity for drug effect simulation on laboratory test trajectories. In this paper, we developed and evaluated conditional GANs on glucose laboratory tests in patients exposed to drug combinations and showed a proof of concept for these models in the simulation of unseen drug combinations. By using conditional Wasserstein GANs (WGANs) to simulate drug effects in laboratory tests, we hope to pave the way for novel clinical decision support (CDM) systems and enable the development of better predictive models for rare cohorts of patients.
A systematic review and meta-analysis protocol on the association of malaria in pregnancy and adverse birth outcomes

Abstract: Introduction: Malaria in pregnancy contributes to significant adverse birth outcomes. This study is aimed to quantify the relationship between malaria in pregnancy and occurrence of adverse birth outcomes, including preterm delivery, low birth weight, small for gestational age, miscarriages, and stillbirth. Methods and analysis: Observational studies and Randomised controlled trials reporting data on selected birth outcomes separately for pregnancies, with or without malaria will be included. We will search for studies over various information sources and data extraction will be done from included studies. Pooled odds ratio (OR) will be calculated for each birth outcomes using fixed effect model or random effects models, based on the level of heterogeneity. Forest plot will be prepared with effect size (with 95 percent confidence interval) of each study and pooled effect size. The methodological quality will be assessed for included observational studies using the Newcastle-Ottawa scale (NOS). Cochrane Risk of Bias tool will be used to evaluate bias in randomised controlled trials. For publication bias, funnel plot will be prepared and assessed for asymmetry, along with Egger's test. Discussion: This study will provide an estimate of the risk of adverse birth outcomes in pregnancies with malaria. Results of this study will contribute towards planning effective service delivery in areas with a higher risk of malaria transmission. Ethics and dissemination: The current study is a review of published literature, and it does not require ethical committee approval. Results of this review will be published in a peer-reviewed journal. PROSPERO registration number: CRD42020153009
Analysis of asymmetries in the African fruit bats Eidolon helvum and Rousettus egyptiacus (Mammalia: Megachiroptera) from the islands of the Gulf of Guinea. II. Integration and levels of multivariate fluctuating asymmetry across a geographical range

Using a set of cranial morphometric characters, trends of variation in multivariate fluctuating asymmetry were evaluated and compared in populations of African fruit bats Rousettus egyptiacus and Eidolon helvum from the Gulf of Guinea islands, and the adjacent mainland. Levels of asymmetry were compared across populations and species, and significant differences were found in both comparisons. Differences coincided with species‐specific patterns of morphological and genetic differentiation. Concordance of correlation matrices of asymmetry was also compared. Results were significant; concordance is hypothesized to be a by‐product of developmental processes that produce the ‘fox‐like’ morphology shared by these species. Consistency of asymmetry patterns suggests that the developmental pathway producing it is highly canalized. A prediction of the above hypothesis is that a radical change in the ‘fox‐like’ structural pattern would result in breakage of the asymmetry parameter associated with it.
Selecting discriminant function models for predicting the expected richness of aquatic macroinvertebrates

Summary 1. The predictive modelling approach to bioassessment estimates the macroinvertebrate assemblage expected at a stream site if it were in a minimally disturbed reference condition. The difference between expected and observed assemblages then measures the departure of the site from reference condition. 2. Most predictive models employ site classification, followed by discriminant function (DF) modelling, to predict the expected assemblage from a suite of environmental variables. Stepwise DF analysis is normally used to choose a single subset of DF predictor variables with a high accuracy for classifying sites. An alternative is to screen all possible combinations of predictor variables, in order to identify several ‘best’ subsets that yield good overall performance of the predictive model. 3. We applied best-subsets DF analysis to assemblage and environmental data from 199 reference sites in Oregon, U.S.A. Two sets of 66 best DF models containing between one and 14 predictor variables (that is, having model orders from one to 14) were developed, for five-group and 11-group site classifications. 4. Resubstitution classification accuracy of the DF models increased consistently with model order, but cross-validated classification accuracy did not improve beyond seventh or eighth-order models, suggesting that the larger models were overfitted. 5. Overall predictive model performance at model training sites, measured by the root-mean-squared error of the observed/expected species richness ratio, also improved steadily with DF model order. But high-order DF models usually performed poorly at an independent set of validation sites, another sign of model overfitting. 6. Models selected by stepwise DF analysis showed evidence of overfitting and were outperformed by several of the best-subsets models. 7. The group separation strength of a DF model, as measured by Wilks’Λ, was more strongly correlated with overall predictive model performance at training sites than was DF classification accuracy. 8. Our results suggest improved strategies for developing reliable, parsimonious predictive models. We emphasise the value of independent validation data for obtaining a realistic picture of model performance. We also recommend assessing not just one or two, but several, candidate models based on their overall performance as well as the performance of their DF component. 9. We provide links to our free software for stepwise and best-subsets DF analysis.
Parallel Neural Multiprocessing with Gamma Frequency Latencies

The Poisson variability in cortical neural responses has been typically modeled using spike averaging techniques, such as trial averaging and rate coding, since such methods can produce reliable correlates of behavior. However, mechanisms that rely on counting spikes could be slow and inefficient and thus might not be useful in the brain for computations at timescales in the 10 millisecond range. This issue has motivated a search for alternative spike codes that take advantage of spike timing and has resulted in many studies that use synchronized neural networks for communication. Here we focus on recent studies that suggest that the gamma frequency may provide a reference that allows local spike phase representations that could result in much faster information transmission. We have developed a unified model (gamma spike multiplexing) that takes advantage of a single cycle of a cell's somatic gamma frequency to modulate the generation of its action potentials. An important consequence of this coding mechanism is that it allows multiple independent neural processes to run in parallel, thereby greatly increasing the processing capability of the cortex. System-level simulations and preliminary analysis of mouse cortical cell data are presented as support for the proposed theoretical model.
Redescription of Trochosa urbana (Araneae: Lycosidae) with notes on its distribution

Abstract A survey of specimens identified as Trochosa urbana O. Pickard-Cambridge, 1876, kept in the Zoological Museum, University of Turku, reveals that they belong to four species: T. urbana, T. dentichelis Buchar, 1997, T. ruricola (De Geer, 1778), and T. ruricoloides Schenkel, 1963. Trochosa urbana is redescribed based on syntypes, and a lectotype male is designated. Our study found that the actual range of T. urbana is restricted to eastern Africa (from Egypt to the Seychelles) and Israel, and not stretching from Africa to India as was thought before. Four species and one subspecies are synonymized with Trochosa urbana O. Pickard-Cambridge, 1876: Caporiaccosa arctosaeformis (Caporiacco, 1940) syn. n. , Geolycosa gofensis (Strand, 1906) syn. n. , Hogna sansibarensis (Strand, 1907) syn. n. , Pirata molensis Strand, 1908 syn. n. , and Trochosa urbana hova (Strand, 1907) syn. n. Two genera, Caporiaccosa Roewer, 1960 syn. n. and Trochosippa Roewer, 1960 syn. n. are synonymized with Trochosa C. L. Koch, 1847. For two species, we establish new combinations: Trochosa meruensis (Lessert, 1926) comb. n. ex Trochosippa, and Hogna taurirtensis (Schenkel, 1937) comb. n. ex Pirata. Trochosa dentichelis, previously known from Bhutan, is reported from India. Trochosa aquatica Tanaka, 1985 is likely a junior synonym of T. ruricoloides. The latter species, previously known from China, is reported for the first time from India, Indonesia, Malaysia, Papua New Guinea, and Thailand.
Changes in Anthocyanin Content and Composition of Developing Storage Root of Purple-Fleshed Sweet Potato (Ipomoea batatas (L.) Lam)

The changes in the content and composition of anthocyanin in the developing storage root of 10 purple-fleshed sweet potato clones were investigated in order to elucidate the pattern of anthocyanin accumulation between clones with a high and low anthocyanin content. At the 3rd week after transplanting, in most clones, anthocyanins were detected in the young thick roots that had the potential to develop into storage roots. The pattern of anthocyanin accumulation was characterized into three distinctive phases: (1) an initial rapid increase during the 3rd to 6th week, (2) no change or a slight decrease during the 6th to 12th week, and (3) a slight increase during the 12th to 17th week. Northern blot analysis indicated that mRNA levels of dihydroflavonol 4-reductase (DFR), one of the key enzymes of the anthocyanin biosynthetic pathway, was expressed throughout the stage of storage root development. In addition, DFR mRNA appeared to be the most abundant at the 6th week, and reduced an the 9th week, which coincides with the change in anthocyanin content. These results suggest that anthocyanin is synthesized throughout the stage of storage root development, but not in a steady manner, and that anthocyanin accumulation in sweet potato could be related to the transcriptional regulation of anthocyanin biosynthetic genes. The rate of increase in anthocyanin content during the 3rd to 6th week was significantly higher in clones with a high anthocyanin content than in clones with a low anthocyanin content. It may be possible to screen clones after the 9th week when the percentage of peonidin, which is an index for anthocyanin composition in purple-fleshed sweet potato, become constant, and the large storage roots (more than 20 mm in diameter) are produced in most clones.
Digital Cell Sorter (DCS): a cell type identification, anomaly detection, and Hopfield landscapes toolkit for single-cell transcriptomics

Motivation Analysis of singe cell RNA sequencing (scRNA-seq) typically consists of different steps including quality control, batch correction, clustering, cell identification and characterization, and visualization. The amount of scRNA-seq data is growing extremely fast, and novel algorithmic approaches improving these steps are key to extract more biological information. Here, we introduce: (i) two methods for automatic cell type identification (i.e. without expert curator) based on a voting algorithm and a Hopfield classifier, (ii) a method for cell anomaly quantification based on isolation forest, and (iii) a tool for the visualization of cell phenotypic landscapes based on Hopfield energy-like functions. These new approaches are integrated in a software platform that includes many other state-of-the-art methodologies and provides a self-contained toolkit for scRNA-seq analysis. Results We present a suite of software elements for the analysis of scRNA-seq data. This Python-based open source software, Digital Cell Sorter (DCS), consists in an extensive toolkit of methods for scRNA-seq analysis. We illustrate the capability of the software using data from large datasets of peripheral blood mononuclear cells (PBMC), as well as plasma cells of bone marrow samples from healthy donors and multiple myeloma patients. We test the novel algorithms by evaluating their ability to deconvolve cell mixtures and detect small numbers of anomalous cells in PBMC data. Availability The DCS toolkit is available for download and installation through the Python Package Index (PyPI). The software can be deployed using the Python import function following installation. Source code is also available for download on Zenodo: doi.org/10.5281/zenodo.2533377 Contact domansk6@msu.edu
Distinct signatures of calcium activity in brain pericytes

Even though pericytes have been implicated in various neurological disorders, little is known about their function and signaling pathways in the healthy brain. Here, we characterized cortical pericyte calcium dynamics using two-photon imaging of Pdgfrβ-CreERT2;GCaMP6s mice under anesthesia in vivo and in brain slices ex vivo. We found distinct differences between pericyte subtypes in vivo: Ensheathing pericytes exhibited smooth muscle cell-like calcium dynamics, while calcium signals in capillary pericytes were irregular, higher in frequency and occurred in cellular microdomains. In contrast to ensheathing pericytes, capillary pericytes retained their spontaneous calcium signals during prolonged anesthesia and in the absence of blood flow ex vivo. Chemogenetic activation of neurons in vivo and acute increase of extracellular potassium in brain slices strongly decreased calcium activity in capillary pericytes. We propose that neuronal activity-induced elevations in extracellular potassium suppress calcium activity in capillary pericytes, likely mediated by Kir2.2 and KATP channel activation.
Vector dynamics influence spatially imperfect genetic interventions against disease

Background and objectives Genetic engineering and similar technologies offer promising new approaches to controlling human diseases by blocking transmission from vectors. However, in spatially structured populations, imperfect coverage of the vector will leave pockets in which the parasite can persist. Yet movement by humans may disrupt this local persistence and facilitate eradication when these pockets are small, essentially distributing parasite reproduction out of unprotected areas and into areas that block its reproduction. Methodology We develop formal mathematical models of this process similar to standard Ross-Macdonald models, but (i) specifying spatial structure of two patches, with transmission blocked in one patch but not in the other, (ii) allowing temporary human movement (travel instead of migration), and (iii) considering two different modes of mosquito biting. Results We find that there is no invariant effect of disrupting spatial structure with travel. For both biting models, travel out of the unprotected patch has different consequences than travel by visitors into the patch, but the effects are reversed between the two biting models. Conclusions and implications Overall, the effect of human travel on the maintenance of vector-borne diseases in structured habitats must be considered in light of the actual biology of mosquito abundances and biting dynamics. Lay summary Genetic interventions against pathogens transmitted by insect vectors are promising methods of controlling infectious diseases. These interventions may be imperfect, leaving pockets where the parasite persists. How will human movement between protected and unprotected areas affect persistence? Mathematical models developed here show that the answer is ecology-dependent, depending on vector biting behavior.