Not only the butterflies: managing ants on road verges to benefit Phengaris (Maculinea) butterflies

Obligate myrmecophilic butterfly species, such as Phengaris (Maculinea) teleius and P. nausithous, have narrow habitat requirements. Living as a caterpillar in the nests of the ant species Myrmica scabrinodis and M. rubra, respectively, they can only survive on sites with both host ants and the host plant Great Burnet Sanguisorba officinalis. After having been reintroduced into a nature reserve in the Netherlands in 1990, both butterfly species expanded their distribution to linear landscape elements such as road verges and ditch edges outside this reserve. As additional habitat of both butterfly species, vegetation management of these landscape elements became important. Our results show that a management beneficial for Phengaris butterflies should aim to increase the nest density of Myrmica species, at the same time reducing the density of nests of the competitor Lasius niger or at least keeping them at a low density. Unfavourable grassland management under which L. niger thrives, includes not mowing or flail-cutting the grass, or depositing dredgings along the side of the ditch. Management favourable for the two Myrmica species differs, demanding some flexibility if both species are to benefit. M. scabrinodis is best supported with early mowing of the road verge vegetation or late mowing in the nature reserve, both of which result in an open vegetation and warm microclimate. In contrast, the nest sites of M. rubra should be left undisturbed during the summer, and mown in late autumn. Mowing of butterfly habitat should be avoided between mid-June and mid-September as this would remove the flowerheads of the Sanguisorba plants, on which the butterflies lay their eggs

Developmental Toxicity of Endocrine Disrupters Bisphenol A and Vinclozolin in a Terrestrial Isopod

Studies of the effects of endocrine-disrupting compounds (EDCs) on invertebrates are still largely underrepresented. This work aims to fill this gap by assessing the effects of bisphenol A (BPA) and vinclozolin (Vz) on the terrestrial isopod Porcellio scaber (common rough woodlouse). Male adult and sexually undifferentiated juvenile woodlice were exposed to the toxicants. Effects on molting regime and growth were investigated independently for males and female woodlice after sexual differentiation. Both chemicals elicited developmental toxicity to P. scaber by causing overall decreased growth. Nevertheless, BPA induced molting, whereas Vz delayed it. Although the LC50 values for juvenile and adult survival were fairly similar, juvenile woodlice showed an increased chronic sensitivity to both chemicals, and female woodlice were most the sensitive to BPA. We recommend the use of adults, juveniles, female, and male woodlice, as well as a large range of toxicant concentrations, to provide valuable information regarding differential dose responses, effects, and threshold values for EDCs

Does segmentation always improve model performance in credit scoring?

Credit scoring allows for the credit risk assessment of bank customers. A single scoring model (scorecard) can be developed for the entire customer population, e.g. using logistic regression. However, it is often expected that segmentation, i.e. dividing the population into several groups and building separate scorecards for them, will improve the model performance. The most common statistical methods for segmentation are the two-step approaches, where logistic regression follows Classification and Regression Trees (CART) or Chi-squared Automatic Interaction Detection (CHAID) trees etc. In this research, the two-step approaches are applied as well as a new, simultaneous method, in which both segmentation and scorecards are optimised at the same time: Logistic Trees with Unbiased Selection (LOTUS). For reference purposes, a single-scorecard model is used. The above-mentioned methods are applied to the data provided by two of the major UK banks and one of the European credit bureaus. The model performance measures are then compared to examine whether there is improvement due to the segmentation methods used. It is found that segmentation does not always improve model performance in credit scoring: for none of the analysed real-world datasets, the multi-scorecard models perform considerably better than the single-scorecard ones. Moreover, in this application, there is no difference in performance between the two-step and simultaneous approache

Combination, Modulation and Interplay of Modern Radiotherapy with the Tumor Microenvironment and Targeted Therapies in Pancreatic Cancer: Which Candidates to Boost Radiotherapy?

Pancreatic ductal adenocarcinoma cancer (PDAC) is a highly diverse disease with low tumor immunogenicity. PDAC is also one of the deadliest solid tumor and will remain a common cause of cancer death in the future. Treatment options are limited, and tumors frequently develop resistance to current treatment modalities. Since PDAC patients do not respond well to immune checkpoint inhibitors (ICIs), novel methods for overcoming resistance are being explored. Compared to other solid tumors, the PDAC's tumor microenvironment (TME) is unique and complex and prevents systemic agents from effectively penetrating and killing tumor cells. Radiotherapy (RT) has the potential to modulate the TME (e.g., by exposing tumor-specific antigens, recruiting, and infiltrating immune cells) and, therefore, enhance the effectiveness of targeted systemic therapies. Interestingly, combining ICI with RT and/or chemotherapy has yielded promising preclinical results which were not successful when translated into clinical trials. In this context, current standards of care need to be challenged and transformed with modern treatment techniques and novel therapeutic combinations. One way to reconcile these findings is to abandon the concept that the TME is a well-compartmented population with spatial, temporal, physical, and chemical elements acting independently. This review will focus on the most interesting advancements of RT and describe the main components of the TME and their known modulation after RT in PDAC. Furthermore, we will provide a summary of current clinical data for combinations of RT/targeted therapy (tRT) and give an overview of the most promising future directions

Rapid neuronal differentiation of induced pluripotent stem cells for measuring network activity on micro-electrode arrays

Neurons derived from human induced Pluripotent Stem Cells (hiPSCs) provide a promising new tool for studying neurological disorders. In the past decade, many protocols for differentiating hiPSCs into neurons have been developed. However, these protocols are often slow with high variability, low reproducibility, and low efficiency. In addition, the neurons obtained with these protocols are often immature and lack adequate functional activity both at the single-cell and network levels unless the neurons are cultured for several months. Partially due to these limitations, the functional properties of hiPSC-derived neuronal networks are still not well characterized. Here, we adapt a recently published protocol that describes production of human neurons from hiPSCs by forced expression of the transcription factor neurogenin-212. This protocol is rapid (yielding mature neurons within 3 weeks) and efficient, with nearly 100% conversion efficiency of transduced cells (>95% of DAPI-positive cells are MAP2 positive). Furthermore, the protocol yields a homogeneous population of excitatory neurons that would allow the investigation of cell-type specific contributions to neurological disorders. We modified the original protocol by generating stably transduced hiPSC cells, giving us explicit control over the total number of neurons. These cells are then used to generate hiPSC-derived neuronal networks on micro-electrode arrays. In this way, the spontaneous electrophysiological activity of hiPSC-derived neuronal networks can be measured and characterized, while retaining interexperimental consistency in terms of cell density. The presented protocol is broadly applicable, especially for mechanistic and pharmacological studies on human neuronal networks

More frequent, more costly? Health economic modelling aspects of monitoring glaucoma patients in England

BACKGROUND: Chronic open angle glaucoma (COAG) is an age-related eye disease causing irreversible loss of visual field (VF). Health service delivery for COAG is challenging given the large number of diagnosed patients requiring lifelong periodic monitoring by hospital eye services. Yet frequent examination better determines disease worsening and speed of VF loss under treatment. We examine the cost-effectiveness of increasing frequency of VF examinations during follow-up using a health economic model. METHODS: Two different VF monitoring schemes defined as current practice (annual VF testing) and proposed practice (three VF tests per year in the first 2 years after diagnosis) were examined. A purpose written health economic Markov model is used to test the hypothesis that cost effectiveness improves by implementing proposed practice on groups of patients stratified by age and severity of COAG. Further, a new component of the model, estimating costs of visual impairment, was added. Results were derived from a simulated cohort of 10000 patients with quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs) used as main outcome measures. RESULTS: An ICER of £21,392 per QALY was derived for proposed practice improving to a value of £11,382 once savings for prevented visual impairment was added to the model. Proposed practice was more cost-effective in younger patients. Proposed practice for patients with advanced disease at diagnosis generated ICERs > £60,000 per QALY; these cases would likely be on the most intensive treatment pathway making clinical information on speed of VF loss redundant. Sensitivity analysis indicated results to be robust in relation to hypothetical willingness to pay threshold identified by national guidelines, although greatest uncertainty was allied to estimates of implementation and visual impairment costs. CONCLUSION: Increasing VF monitoring at the earliest stages of follow-up for COAG appears to be cost-effective depending on reasonable assumptions about implementation costs. Our health economic model highlights benefits of stratifying patients to more or less monitoring based on age and stage of disease at diagnosis; a prospective study is needed to prove these findings. Further, this works highlights gaps in knowledge about long term costs of visual impairment

A Simple Bias Correction in Linear Regression for Quantitative Trait Association Under Two-Tail Extreme Selection

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias

Atomistic modeling of dopant segregation in alpha-alumina ceramics: Coverage dependent energy of segregation and nominal dopant solubility

Microstructural control is a key aspect in producing ceramics with tailored properties and is often achieved by using dopants in a rather empirical fashion. Atomic scale simulations could provide much needed insight but the long-standing challenge of linking simulation results on isolated grain boundaries to those measured in real ceramics needs to be resolved. Here a novel Monte-Carlo simulation method based on a microstructural model in combination with energies obtained from atomic scale energy minimization is presented. This approach allows, for the first time, the prediction of the nominal solubility of dopants (Y, La and Mg) in a ceramic purely from theory. Results compare well with segregation/precipitation data as a function of grain size, found in the literature. The method can therefore be used in developing experimental guidelines for the effective use of dopants in ceramic production, thus accelerating the development of novel materials required for innovative applications