Fluorescent Neuronal Cells v2: multi-task, multi-format annotations for deep learning in microscopy.

Fluorescent Neuronal Cells v2 is a collection of fluorescence microscopy images and the corresponding ground-truth annotations, designed to foster innovative research in the domains of Life Sciences and Deep Learning. This dataset encompasses three image collections wherein rodent neuronal cell nuclei and cytoplasm are stained with diverse markers to highlight their anatomical or functional characteristics. Specifically, we release 1874 high-resolution images alongside 750 corresponding ground-truth annotations for several learning tasks, including semantic segmentation, object detection and counting. The contribution is two-fold. First, thanks to the variety of annotations and their accessible formats, we anticipate our work will facilitate methodological advancements in computer vision approaches for segmentation, detection, feature extraction, unsupervised and self-supervised learning, transfer learning, and related areas. Second, by enabling extensive exploration and benchmarking, we hope Fluorescent Neuronal Cells v2 will catalyze breakthroughs in fluorescence microscopy analysis and promote cutting-edge discoveries in life sciences.

Effects of the application of microbiologically activated bio-based fertilizers derived from manures on tomato plants and their rhizospheric communities.

Bio-based fertilizers (BBFs) recovered from animal manure are promising products to optimise resources recovery and generate high agricultural yields. However, their fertilization value may be limited and it is necessary to enrich BBFs with microbial consortia to enhance their fertilization value. Three specific microbial consortia were developed according to the characteristics of three different BBFs produced from manure (bio-dried solid fraction, solid fraction of digestate and biochar) to enhance plant growth and product quality. A greenhouse pot experiment was carried out with tomato plants grown with microbiologically activated BBFs applied either as N-organic fertilizers or as an organic amendment. A next generation sequencing analysis was used to characterise the development of each rhizospheric community. All the activated BBFs gave enhanced tomato yields (fresh and dry weight) compared with the non-activated treatments and similar to, or higher than, chemical fertilization. Concerning the tomato fruits' organoleptic quality, lycopene and carotenoids concentrations were improved by biological activation. Metagenomic analysis points at Trichoderma as the main driver of the positive effects, with the effects of added bacteria being negligible or limited at the early stages after fertilization. In the context of the circular economy, the activated BBFs could be used to replace synthetic fertilisers, reducing costs and environmental burdens and increasing production.

Automating cell counting in fluorescent microscopy through deep learning with c-ResUnet.

Counting cells in fluorescent microscopy is a tedious, time-consuming task that researchers have to accomplish to assess the effects of different experimental conditions on biological structures of interest. Although such objects are generally easy to identify, the process of manually annotating cells is sometimes subject to fatigue errors and suffers from arbitrariness due to the operator's interpretation of the borderline cases. We propose a Deep Learning approach that exploits a fully-convolutional network in a binary segmentation fashion to localize the objects of interest. Counts are then retrieved as the number of detected items. Specifically, we introduce a Unet-like architecture, cell ResUnet (c-ResUnet), and compare its performance against 3 similar architectures. In addition, we evaluate through ablation studies the impact of two design choices, (i) artifacts oversampling and (ii) weight maps that penalize the errors on cells boundaries increasingly with overcrowding. In summary, the c-ResUnet outperforms the competitors with respect to both detection and counting metrics (respectively, [Formula: see text] score = 0.81 and MAE = 3.09). Also, the introduction of weight maps contribute to enhance performances, especially in presence of clumping cells, artifacts and confounding biological structures. Posterior qualitative assessment by domain experts corroborates previous results, suggesting human-level performance inasmuch even erroneous predictions seem to fall within the limits of operator interpretation. Finally, we release the pre-trained model and the annotated dataset to foster research in this and related fields.

Draft Genome Sequence of the Commercial Biocontrol Strain Pantoea agglomerans P10c.

We report here the draft genome sequence of the biocontrol strain Pantoea agglomerans P10c, composed of a draft chromosome and two plasmids: the 559-kb large Pantoea plasmid 1 (pPag3) and a 182-kb plasmid (pPag1). A genomic island containing pantocin A biosynthesis genes was identified.

Antioxidant activity of Calendula officinalis extract: inhibitory effects on chemiluminescence of human neutrophil bursts and electron paramagnetic resonance spectroscopy.

There is growing interest in natural chemical compounds from aromatic, spicy, medicinal and other plants with antioxidant properties in order to find new sources of compounds inactivating free radicals generated by metabolic pathways within body tissue and cells, mainly polymorphonuclear leukocytes (PMNs) whose overregulated recruitment and activation generate a large amount of reactive oxygen species (ROS) and reactive nitrogen species (RNS), leading to an imbalance of redox homeostasis and oxidative stress. The aim of this study was to examine whether a propylene glycol extract of Calendula officinalis interferes with ROS and RNS during the PMN respiratory bursts, and to establish the lowest concentration at which it still exerts antioxidant activity by means of luminol-amplified chemiluminescence. Electron paramagnetic resonance (EPR) spectroscopy was also used in order to confirm the activity of the C. officinalis extract. The C. officinalis extract exerted its anti-ROS and anti-RNS activity in a concentration-dependent manner, with significant effects being observed at even very low concentrations: 0.20 microg/ml without L-arginine, 0.10 microg/ml when L-arginine was added to the test with phorbol 12-myristate 13-acetate and 0.05 microg/ml when it was added to the test with N-formyl-methionyl-leucyl-phenylalanine. The EPR study confirmed these findings, 0.20 microg/ml being the lowest concentration of C. officinalis extract that significantly reduced 2,2-diphenyl-1-picrylhydrazyl. These findings are interesting for improving the antioxidant network and restoring the redox balance in human cells with plant-derived molecules as well as extending the possibility of antagonizing the oxidative stress generated in living organisms when the balance is in favor of free radicals as a result of the depletion of cell antioxidants.

Fenton-dependent damage to carbohydrates: free radical scavenging activity of some simple sugars.

The antioxidant properties of simple carbohydrates were studied in a chemical system. Hydroxyl radicals generated by a Fenton reaction induce damage on simple carbohydrates with a consequent free radical scavenging activity. Carbohydrate activities were measured by different methods as spin-trapping of hydroxyl radical and electron paramagnetic resonance detection and 1,1-diphenyl-2-picrylhydrazyl quenching. Carbohydrate damage was evaluated in a Fenton system by measuring the reactive substances to thiobarbituric acid, by their decreased detection with an HPLC test, and by a gas chromatographic determination of formic acid from sugar oxidation. Different intensities of damage and scavenging were found according to molecular structure, and some hyphotheses on the carbohydrate action against free radicals were attempted. The assayed disaccharides were shown to be more active toward and less damaged by hydroxyl radical than monosaccharides.