Soil microbial communities in restored and unrestored coastal dune ecosystems in California

Most restoration projects involving invasive plant eradication tend to focus on plant removal with little consideration given to how these invasives change soil microbial communities. However, soil microorganisms can determine invasibility of habitats and, in turn, be altered by invasives once established, potentially inhibiting native plant establishment. We studied soil microbial communities in coastal dunes with varying invasion intensity and different restoration approaches (herbicide, mechanical excavation) at Point Reyes National Seashore. Overall, we found evidence of a strong link between bacterial and fungal soil communities and the presence of invasives and restoration approach. Heavily invaded sites were characterized by a lower abundance of putatively identified nitrifiers, fermentative bacteria, fungal parasites, and fungal dung saprotrophs and a higher abundance of cellulolytic bacteria and a class of arbuscular mycorrhizal fungi (Archaeosporomycetes). Changes in soil microbiota did not fully dissipate following removal of invasives using herbicide, with exception of reductions in cellulolytic bacteria and Archaeosporomycetes abundance. Mechanical restoration effectively removed both invasives and soil legacy effects by inverting or “flipping” rhizome-contaminated surface soils with soils from below and may have inadvertently induced other adverse effects on soils that impeded reestablishment of native dune plants. Land managers should consider additional measures to counteract lingering legacy effects and/or focus restoration efforts in areas where legacy effects are less pronounced

MR image reconstruction using deep density priors

Algorithms for Magnetic Resonance (MR) image reconstruction from undersampled measurements exploit prior information to compensate for missing k-space data. Deep learning (DL) provides a powerful framework for extracting such information from existing image datasets, through learning, and then using it for reconstruction. Leveraging this, recent methods employed DL to learn mappings from undersampled to fully sampled images using paired datasets, including undersampled and corresponding fully sampled images, integrating prior knowledge implicitly. In this article, we propose an alternative approach that learns the probability distribution of fully sampled MR images using unsupervised DL, specifically Variational Autoencoders (VAE), and use this as an explicit prior term in reconstruction, completely decoupling the encoding operation from the prior. The resulting reconstruction algorithm enjoys a powerful image prior to compensate for missing k-space data without requiring paired datasets for training nor being prone to associated sensitivities, such as deviations in undersampling patterns used in training and test time or coil settings. We evaluated the proposed method with T1 weighted images from a publicly available dataset, multi-coil complex images acquired from healthy volunteers (N=8) and images with white matter lesions. The proposed algorithm, using the VAE prior, produced visually high quality reconstructions and achieved low RMSE values, outperforming most of the alternative methods on the same dataset. On multi-coil complex data, the algorithm yielded accurate magnitude and phase reconstruction results. In the experiments on images with white matter lesions, the method faithfully reconstructed the lesions. Keywords: Reconstruction, MRI, prior probability, machine learning, deep learning, unsupervised learning, density estimationComment: Published in IEEE TMI. Main text and supplementary material, 19 pages tota

The autonomic innervation of the testicular parenchyma: a rat model

The specific roles and direct involvements of autonomic innervations on the spermatogenic process are poorly understood. The aim of this study was to investigate stereologically the relative importance of sympathetic innervations in testicular parenchyma rats in chemically sympathectomized with guanethidine. Treated animals (n=10) were injected intraperitoneally with guanethidine at doses of 10mg/kg/day for 15 days while control animals (n= 5) received an equivalent volume of saline. After routine histological procedures, 5μm thick sections of the testes were selected for examination. Organ volumes were estimated using the Cavalieri Principle of volume measurement by means of consecutive serial sections, using “J Images” software in a computer. At least 10 seminiferous tubules were selected randomly and measured per cross section for evaluation of epithelial heights, luminal diameter and total seminiferous tubule diameter. Testicular volumes and seminiferous tubule measurements of treated animals were found to be affected by the chemical sympathectomy with guanethidine with a a statistically significant difference between experimental and control group (p<0.01). Our findings indicate that chemical sympathectomy with-short term low dose guanethidine might display morphometric changes in the rat testis which indicate the presence of autonomic innervation of its parenchyma

Cell-Instructive Surface Gradients of Photoresponsive Amyloid-like Fibrils

[Image: see text] Gradients of bioactive molecules play a crucial role in various biological processes like vascularization, tissue regeneration, or cell migration. To study these complex biological systems, it is necessary to control the concentration of bioactive molecules on their substrates. Here, we created a photochemical strategy to generate gradients using amyloid-like fibrils as scaffolds functionalized with a model epitope, that is, the integrin-binding peptide RGD, to modulate cell adhesion. The self-assembling β-sheet forming peptide (CKFKFQF) was connected to the RGD epitope via a photosensitive nitrobenzyl linker and assembled into photoresponsive nanofibrils. The fibrils were spray-coated on glass substrates and macroscopic gradients were generated by UV-light over a centimeter-scale. We confirmed the gradient formation using matrix-assisted laser desorption ionization mass spectroscopy imaging (MALDI-MSI), which directly visualizes the molecular species on the surface. The RGD gradient was used to instruct cells. In consequence, A549 adapted their adhesion properties in dependence of the RGD-epitope density

Computer‐assisted bone augmentation, implant planning and placement: An in vitro investigation

Aim To assess in vitro the workflow for alveolar ridge augmentation with customised 3D printed block grafts and simultaneous computer-assisted implant planning and placement. Methods Twenty resin mandible models with an edentulous area and horizontal ridge defect in the region 34–36 were scanned with cone beam computed tomography (CBCT). A block graft for horizontal ridge augmentation in the region 34–36 and an implant in the position 35 were digitally planned. Twenty block grafts were 3D printed out of resin and one template for guided implant placement were stereolithographically produced. The resin block grafts were positioned onto the ridge defects and stabilised with two fixation screws each. Subsequently, one implant was inserted in the position 35 through the corresponding template for guided implant placement. Optical scans of the study models together with the fixated block graft were performed prior to and after implant placement. The scans taken after block grafting were superimposed with the virtual block grafting plan through a best-fit algorithm, and the linear deviation between the planned and the achieved block positions was calculated. The precision of the block fixation was obtained by superimposing the 20 scans taken after grafting and calculating the deviation between the corresponding resin blocks. The superimposition between the scans taken after and prior to implant placement was performed to measure a possible displacement in the block position induced by guided implant placement. The (98–2%)/2 percentile value was determined as a parameter for surface deviation. Results The mean deviation in the position of the block graft compared to the virtual plan amounted to 0.79 ± 0.13 mm. The mean deviation between the positions of the 20 block grafts measured 0.47 ± 0.2 mm, indicating a clinically acceptable precision. Guided implant placement induced a mean shift of 0.16 ± 0.06 mm in the position of the block graft. Conclusions Within the limitations of this in vitro study, it can be concluded that customised block grafts fabricated through CBCT, computer-assisted design and 3D printing allow alveolar ridge augmentation with clinically acceptable predictability and reproducibility. Computer-assisted implant planning and placement can be performed simultaneously with computer-assisted block grafting leading to clinically non-relevant dislocation of block grafts