Microgeographic differentiation in thermal and antipredator responses and their carry-over effects across life stages in a damselfly

Global warming and invasive species, separately or combined, can impose a large impact on the condition of native species. However, we know relatively little about how these two factors, individually and in combination, shape phenotypes in ectotherms across life stages and how this can differ between populations. We investigated the non-consumptive predator effects (NCEs) imposed by native (perch) and invasive (signal crayfish) predators experienced only during the egg stage or during both the egg and larval stages in combination with warming on adult life history traits of the damselfly Ischnura elegans. To explore microgeographic differentiation, we compared two nearby populations differing in thermal conditions and predator history. In the absence of predator cues, warming positively affected damselfly survival, possibly because the warmer temperature was closer to the optimal temperature. In the presence of predator cues, warming decreased survival, indicating a synergistic effect of these two variables on survival. In one population, predator cues from perch led to increased survival, especially under the current temperature, likely because of predator stress acclimation phenomena. While warming decreased, predator cues increased larval development time with a proportionally stronger effect of signal crayfish cues experienced during the egg stage, indicating a negative carry-over effect from egg to larva. Warming and predator cues increased mass at emergence, with the predator effect driven mainly by exposure to signal crayfish cues during the egg stage, indicating a positive carry-over effect from egg to adult. Notably, warming and predator effects were not consistent across the two studied populations, suggesting a phenotypic signal of adaptation at a microgeographic scale to thermal conditions and predator history. We also observed pronounced shifts during ontogeny from synergistic (egg and early larval stage) toward additive (late larval stage up to emergence) effects between warming and predator stress. The results point out that population- and life-stage-specific responses in life-history traits to NCEs are needed to predict fitness consequences of exposure to native and invasive predators and warming in prey at a microgeographic scale.

Longitudinal reciprocal associations between volunteering, health and well-being: evidence for middle-aged and older adults in Europe

BACKGROUND

There is substantial evidence on the importance of voluntary activities for the health of middle-aged and older adults. Evidence on the effects of health and well-being on volunteering is more limited. This study examines reciprocal longitudinal associations between voluntary and/or charity activities and 21 indicators related to physical health, well-being, cognitive impairment and daily life functioning among middle-aged and older adults.

METHODS

Longitudinal data were collected between 2011 and 2020 from a sample of 19 821 middle-aged and older adults from 15 countries participating in the Survey of Health, Ageing and Retirement in Europe. An outcome-wide analysis and an exposure-wide analysis were applied and generalized estimating equations were used. Robustness analyses were conducted.

RESULTS

Voluntary and/or charity activities almost every week or more often were prospectively associated with greater emotional well-being, reduced risks of limitations in activities of daily living and of being diagnosed with Alzheimer's disease at a 6-year follow-up. Positive reverse associations were found from emotional well-being to volunteering. Limitations in daily life activities, increased loneliness, high blood cholesterol, hypertension and chronic lung disease were found to impede participation in voluntary and/or charity activities over time. Feedback loops between voluntary and/or charity activities and well-being and limitations in daily activities may exist.

CONCLUSION

Understanding the reciprocal nature of the relationship between volunteering and health and well-being can help identify strategies to encourage volunteering among middle-aged and older adults with specific health conditions and to target health promotion efforts towards volunteers.

Mechanical and Computational Fluid Dynamic Models for Magnesium-Based Implants

Today, mechanical properties and fluid flow dynamic analysis are considered to be two of the most important steps in implant design for bone tissue engineering. The mechanical behavior is characterized by Young's modulus, which must have a value close to that of the human bone, while from the fluid dynamics point of view, the implant permeability and wall shear stress are two parameters directly linked to cell growth, adhesion, and proliferation. In this study, we proposed two simple geometries with a three-dimensional pore network dedicated to a manufacturing route based on a titanium wire waving procedure used as an intermediary step for Mg-based implant fabrication. Implant deformation under different static loads, von Mises stresses, and safety factors were investigated using finite element analysis. The implant permeability was computed based on Darcy's law following computational fluid dynamic simulations and, based on the pressure drop, was numerically estimated. It was concluded that both models exhibited a permeability close to the human trabecular bone and reduced wall shear stresses within the biological range. As a general finding, the proposed geometries could be useful in orthopedics for bone defect treatment based on numerical analyses because they mimic the trabecular bone properties.

Plasma Treatment of PDMS for Microcontact Printing (μCP) of Lectins Decreases Silicone Transfer and Increases the Adhesion of Bladder Cancer Cells

The present study investigates silicone transfer occurring during microcontact printing (μCP) of lectins with polydimethylsiloxane (PDMS) stamps and its impact on the adhesion of cells. Static adhesion assays and single-cell force spectroscopy (SCFS) are used to compare adhesion of nonmalignant (HCV29) and cancer (HT1376) bladder cells, respectively, to high-affinity lectin layers (PHA-L and WGA, respectively) prepared by physical adsorption and μCP. The chemical composition of the μCP lectin patterns was monitored by time-of-flight secondary ion mass spectrometry (ToF-SIMS). We show that the amount of transferred silicone in the μCP process depends on the preprocessing of the PDMS stamps. It is revealed that silicone contamination within the patterned lectin layers inhibits the adhesion of bladder cells, and the work of adhesion is lower for μCP lectins than for drop-cast lectins. The binding capacity of microcontact printed lectins was larger when the PDMS stamps were treated with UV ozone plasma as compared to sonication in ethanol and deionized water. ToF-SIMS data show that ozone-based treatment of PDMS stamps used for μCP of lectin reduces the silicone contamination in the imprinting protocol regardless of stamp geometry (flat vs microstructured). The role of other possible contributors, such as the lectin conformation and organization of lectin layers, is also discussed.

The effect of temperature and invasive alien predator on genetic and phenotypic variation in the damselfly Ischnura elegans: cross-latitude comparison

BACKGROUND

Understanding and predicting how organisms respond to human-caused environmental changes has become a major concern in conservation biology. Here, we linked gene expression and phenotypic data to identify candidate genes underlying existing phenotypic trait differentiation under individual and combined environmental variables. For this purpose, we used the damselfly Ischnura elegans. Egg clutches from replicated high- (southern Sweden) and central-latitude (southern Poland) populations facing different degrees of seasonal time constraints were collected. Damselfly larvae were exposed to experimental treatments: current and mild warming temperatures crossed with the presence or absence of an invasive alien predator cue released by the spiny-cheek crayfish, Faxonius limosus, which is only present in Poland to date. We measured the following traits: larval development time, body size, mass and growth rate, and used the larvae for gene expression analysis by RNA-seq. Data were analysed using a multivariate approach.

RESULTS

We showed latitudinal differences in coping with mild warming and predator cues. When exposed to an increased temperature and a predator cue, central-latitude individuals had the shortest development and the fastest growth compared to high-latitude individuals. There was a general effect of predator cues regarding mass and growth rate reduction independent of latitude. Transcriptome analysis revealed that metabolic pathways related to larval anatomy and development tended to be upregulated in response to mild warming but only in fast-growing central-latitude individuals. Metabolic pathways linked to oxidative stress tended to be downregulated in response to a predator cue, especially in central-latitude individuals.

CONCLUSION

Different phenotypic and transcriptomic responses to environmental factors might be attributed to the variability in I. elegans life history strategies between the two latitudes caused by seasonal time constraints and to its coexistence with the invasive alien predator in nature. By providing insights into how organisms may respond to future anthropogenic changes, our results may be of particular interest in conservation biology.

Real-time computer-aided diagnosis of focal pancreatic masses from endoscopic ultrasound imaging based on a hybrid convolutional and long short-term memory neural network model

Differential diagnosis of focal pancreatic masses is based on endoscopic ultrasound (EUS) guided fine needle aspiration biopsy (EUS-FNA/FNB). Several imaging techniques (i.e. gray-scale, color Doppler, contrast-enhancement and elastography) are used for differential diagnosis. However, diagnosis remains highly operator dependent. To address this problem, machine learning algorithms (MLA) can generate an automatic computer-aided diagnosis (CAD) by analyzing a large number of clinical images in real-time. We aimed to develop a MLA to characterize focal pancreatic masses during the EUS procedure. The study included 65 patients with focal pancreatic masses, with 20 EUS images selected from each patient (grayscale, color Doppler, arterial and venous phase contrast-enhancement and elastography). Images were classified based on cytopathology exam as: chronic pseudotumoral pancreatitis (CPP), neuroendocrine tumor (PNET) and ductal adenocarcinoma (PDAC). The MLA is based on a deep learning method which combines convolutional (CNN) and long short-term memory (LSTM) neural networks. 2688 images were used for training and 672 images for testing the deep learning models. The CNN was developed to identify the discriminative features of images, while a LSTM neural network was used to extract the dependencies between images. The model predicted the clinical diagnosis with an area under curve index of 0.98 and an overall accuracy of 98.26%. The negative (NPV) and positive (PPV) predictive values and the corresponding 95% confidential intervals (CI) are 96.7%, [94.5, 98.9] and 98.1%, [96.81, 99.4] for PDAC, 96.5%, [94.1, 98.8], and 99.7%, [99.3, 100] for CPP, and 98.9%, [97.5, 100] and 98.3%, [97.1, 99.4] for PNET. Following further validation on a independent test cohort, this method could become an efficient CAD tool to differentiate focal pancreatic masses in real-time.