A potential tradeoff between feeding rate and aversive learning determines intoxication in a Caenorhabditis elegans host-pathogen system

Despite being the first line of defense against infection, little is known about how host-pathogen interactions determine avoidance. Caenorhabditis elegans can become infected by chemoattractant-producing bacteria through ingestion. The worms can learn to associate these chemoattractants with harm through aversive learning. As a result, the worms will avoid the pathogen. Evolutionary constraints have likely shaped the attraction, intoxication and learning dynamics between bacteria and C. elegans, but these have not been explored. Using bacteria engineered to express an acylhomoserine lactone chemoattractant and a nematicidal protein, we explored how manipulating the amount of attractant produced by the bacteria affects learning and intoxication in mixed stage populations of C. elegans. We found that increasing the production rate of the chemoattractant increased the feeding rate in C. elegans, but decreased the time required for C. elegans to learn to avoid the chemoattractant. Learning generally coincided with a decreased feeding rate. We also observed that the percentage of intoxicated worms was maximized at intermediate production rates of the attractant. We propose that interactions between attractant driven feeding rate and aversive learning are likely responsible for this trend. Our results increase our understanding of behavioral avoidance in C. elegans and have implications in understanding host-pathogen dynamics that shape avoidance.     

Structure and Function of N-Terminal Zinc Finger Domain of SARS-CoV-2 NSP2

Virologica Sinica - SARS-CoV-2 has become a global pandemic threatening human health and safety. It is urgent to find effective therapeutic agents and targets with the continuous emergence of novel...     

Calcite crystal orientation patterns in the bilayers of laminated shells of benthic rotaliid foraminifera

Shells of calcifying foraminifera play a major role in marine biogeochemical cycles; fossil shells form important archives for paleoenvironment reconstruction. Despite their importance in many Earth science disciplines, there is still little consensus on foraminiferal shell mineralization. Geochemical, biochemical, and physiological studies showed that foraminiferal shell formation might take place through various and diverse mineralization mechanisms.In this study, we contribute to benthic foraminiferal shell calcification through deciphering crystallite organization within the shells. We base our conclusions on results gained from electron backscattered diffraction (EBSD) measurements and describe microstructure/texture characteristics within the laminated shell walls of the benthic, symbiontic foraminifera: Ammonia tepida, Amphistegina lobifera, Amphistegina lessonii. We highlight crystallite assembly patterns obtained on differently oriented cuts and discuss crystallite sizes, morphologies, interlinkages, orientations, and co-orientation strengths.We show that: (i) crystals within benthic foraminiferal shells are mesocrystals, (ii) have dendritic-fractal morphologies and (iii) interdigitate strongly. Based on crystal size, we (iv) differentiate between the two layers that comprise the shells and demonstrate that (v) crystals in the septa have different assemblies relative to those in the shell walls. We highlight that (vi) at junctions of different shell elements the axis of crystal orientation jumps abruptly such that their assembly in EBSD maps has a bimodal distribution. We prove (vii) extensive twin-formation within foraminiferal calcite; we demonstrate (viii) the presence of two twin modes: 60°/[0 0 1] and 77°/~[6 –6 1] and visualize their distributions within the shells.In a broader perspective, we draw conclusions on processes that lead to the observed microstructure/texture patterns.     

On dose cube pixel spacing pre-processing for features extraction stability in dosiomic studies

PurposeDosiomics allows to parameterize regions of interest (ROIs) and to produce quantitative dose features encoding the spatial and statistical distribution of radiotherapy dose. The stability of dosiomics features extraction on dose cube pixel spacing variation has been investigated in this study.Material and MethodsBased on 17 clinical delivered dose distributions (P_n), dataset has been generated considering all the possible combinations of four dose grid resolutions and two calculation algorithms. Each dose voxel cube has been post-processed considering 4 different dose cube pixel spacing values: 1x1x1, 2x2x2, 3x3x3 mm³ and the one equal to the planning CT. Dosiomics features extraction has been performed from four different ROIs. The stability of each extracted dosiomic feature has been analyzed in terms of coefficient of variation (CV) intraclass correlation coefficient (ICC).ResultsThe highest CV mean values were observed for PTV ROI and for the grey level size zone matrix features family. On the other hand, the lowest CV mean values have been found for RING ROI for the grey level co-occurrence matrix features family. P₃ showed the highest percentage of CV >1 (1.14%) followed by P₁₅ (0.41%), P₁ (0.29%) and P13 (0.19%). ICC analysis leads to identify features with an ICC >0.95 that could be considered stable to use in dosiomic studies when different dose cube pixel spacing are considered, especially the features in common among the seventeen plans.ConclusionConsidering the observed variability, dosiomic studies should always provide a report not only on grid resolution and algorithm dose calculation, but also on dose cube pixel spacing.     

Biochemical and Molecular Genetic Correlation in Adenylosuccinate Lyase Deficiency

An homology model of human adenylosuccinate lyase structure shows that P100A substitution distorts the amino acid chain of domain I in the proximity of His‐86, which behaves as general acid in the catalysis, and may expose Cys‐98 and Cys‐99 to oxidising agents. This model is in line with the observation that the defective protein is strongly inhibited by 4‐hydroxy‐2‐nonenal, an hydroxyalkenal that is known to form thio‐ether linkage with proteins.     

Synthesis and Structural Analysis of Oxadiazole Carboxamide Deoxyribonucleoside Analogs

Two novel C-linked oxadiazole carboxamide nucleosides 5-(2′-deoxy-3′,5′-β-D-erythro-pentofuranosyl)-1,2,4-oxadiazole-5-carboxamide (1) and 5-(2′-deoxy-3′,5′-β-D-erythro-pentofuranosyl)-1,2,4-oxadiazole-3-carboxamide (2) were successfully synthesized and characterized by X-ray crystallography. The crystallographic analysis shows that both unnatural nucleoside analogs 1 and 2 adapt the C2′-endo (“south”) conformation. The orientation of the oxadiazole carboxamide nucleobase moiety was determined as anti (conformer A) and high anti (conformer B) in the case of the nucleoside analog 1 whereas the syn conformation is adapted by the unnatural nucleoside 2. Furthermore, nucleoside analogs 1 and 2 were converted with high efficiency to corresponding nucleoside triphosphates through the combination chemo-enzymatic approach. Oxadiazole carboxamide deoxyribonucleoside analogs represent valuable tools to study DNA polymerase recognition, fidelity of nucleotide incorporation, and extension.

     

Soil nitrous oxide emissions following crop residue addition: a meta‐analysis

Annual production of crop residues has reached nearly 4 billion metric tons globally. Retention of this large amount of residues on agricultural land can be beneficial to soil C sequestration. Such potential impacts, however, may be offset if residue retention substantially increases soil emissions of N₂O, a potent greenhouse gas and ozone depletion substance. Residue effects on soil N₂O emissions have gained considerable attention since early 1990s; yet, it is still a great challenge to predict the magnitude and direction of soil N₂O emissions following residue amendment. Here, we used a meta‐analysis to assess residue impacts on soil N₂O emissions in relation to soil and residue attributes, i.e., soil pH, soil texture, soil water content, residue C and N input, and residue C : N ratio. Residue effects were negatively associated with C : N ratios, but generally residue amendment could not reduce soil N₂O emissions, even for C : N ratios well above ca. 30, the threshold for net N immobilization. Residue effects were also comparable to, if not greater than, those of synthetic N fertilizers. In addition, residue effects on soil N₂O emissions were positively related to the amounts of residue C input as well as residue effects on soil CO₂ respiration. Furthermore, most significant and stimulatory effects occurred at 60–90% soil water‐filled pore space and soil pH 7.1–7.8. Stimulatory effects were also present for all soil textures except sand or clay content ≤10%. However, inhibitory effects were found for soils with >90% water‐filled pore space. Altogether, our meta‐analysis suggests that crop residues played roles beyond N supply for N₂O production. Perhaps, by stimulating microbial respiration, crop residues enhanced oxygen depletion and therefore promoted anaerobic conditions for denitrification and N₂O production. Our meta‐analysis highlights the necessity to connect the quantity and quality of crop residues with soil properties for predicting soil N₂O emissions.     

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion.Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.