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Eriocaulaceae exhibit a great variety of floral traits associated with insect (e.g. nectariferous structures) and wind pollination (unisexual flowers, exposed sexual organs and small pollen grains), as well as the 'selfing syndrome' (small flowers, short distance between stigma and anthers, and temporal overlap of male and female phases). Paepalanthus bifidus, P. subtilis and P. tortilis are related species that differ in form, size and colour of floral structures. We aimed to investigate the pollination and reproductive biology of these three species.<br /><br /> We analysed the floral biology, floral visitors, pollinator behaviour, and the contribution of insects, wind and spontaneous geitonogamy to fruit set. We also evaluated the floral colour and scent of the species. Colour reflectance of capitula of each species was measured and plotted in models of insect vision. Floral scent samples were extracted and the compounds were compared to vegetative scent samples.<br /><br /> In all species, the staminate and pistillate flowation might be more widespread in Eriocaulaceae than currently assumed. Furthermore, for small monocarpic plants, mixed mating strategies are most favourable, by ensuring reproduction either by outcrossing when pollinators are abundant or by spontaneous geitonogamy when pollinations are scarce/absent.Protein-DNA interactions play crucial roles in the biological systems, and identifying protein-DNA binding sites is the first step for mechanistic understanding of various biological activities (such as transcription and repair) and designing novel drugs. How to accurately identify DNA-binding residues from only protein sequence remains a challenging task. Currently, most existing sequence-based methods only consider contextual features of the sequential neighbors, which are limited to capture spatial information. Based on the recent breakthrough in protein structure prediction by AlphaFold2, we propose an accurate predictor, GraphSite, for identifying DNA-binding residues based on the structural models predicted by AlphaFold2. Here, we convert the binding site prediction problem into a graph node classification task and employ a transformer-based variant model to take the protein structural information into account. By leveraging predicted protein structures and graph transformer, GraphSite substantially improves over the latest sequence-based and structure-based methods. The algorithm is further confirmed on the independent test set of 181 proteins, where GraphSite surpasses the state-of-the-art structure-based method by 16.4% in area under the precision-recall curve and 11.2% in Matthews correlation coefficient, respectively. We provide the datasets, the predicted structures and the source codes along with the pre-trained models of GraphSite at https//github.com/biomed-AI/GraphSite. The GraphSite web server is freely available at https//biomed.nscc-gz.cn/apps/GraphSite.<br /><br /> National guidelines generally recommend 24 hours or less of surgical antibiotic prophylaxis. In a freestanding, regional children's hospital, we evaluated the duration of antibiotic surgical prophylaxis to identify targets for standardization of practice.<br /><br /> All procedures performed in 2017 were extracted from our local data warehouse; those involving an incision were considered a surgical procedure and correlated to antibiotic data. Antibiotic courses were reviewed if administered for &gt;24 hours, or if the duration or indication for prophylaxis was uncertain. Total duration of prophylaxis (including discharge prescriptions) was calculated in hours for all procedures and categorized by department and by the quantity of prophylaxis received none, single dose, multiple doses within 24 hours, and &gt;24 hours. Percentage of procedures and total days of potential excess were calculated.<br /><br /> A total of 15 651 procedures were included; 5009 met criteria for chart review, and after further exclusions, 12 895 procedures were included in the analysis. In total, 55% of all 12 895 procedures received prophylaxis. A single dose was given in 30%. Over 24 hours was administered in 11%, and 14% received multiple doses &lt;24 hours (both potential excess). Results were evaluated by surgical subspecialty and procedure type. There were 5733 cumulative days of surgical prophylaxis administered after 24 hours (potential excess).<br /><br /> In 2017, up to 25% of procedures received potentially unnecessary perioperative prophylaxis, indicating that national guidance specific to pediatrics would have high impact on antibiotic overuse in the pediatric surgical population.<br /><br />In 2017, up to 25% of procedures received potentially unnecessary perioperative prophylaxis, indicating that national guidance specific to pediatrics would have high impact on antibiotic overuse in the pediatric surgical population.Accurate simulation of protein folding is a unique challenge in understanding the physical process of protein folding, with important implications for protein design and drug discovery. Molecular dynamics simulation strongly requires advanced force fields with high accuracy to achieve correct folding. However, the current force fields are inaccurate, inapplicable and inefficient. We propose a machine learning protocol, the inductive transfer learning force field (ITLFF), to construct protein force fields in seconds with any level of accuracy from a small dataset. This process is achieved by incorporating an inductive transfer learning algorithm into deep neural networks, which learn knowledge of any high-level calculations from a large dataset of low-level method. Here, we use a double-hybrid density functional theory (DFT) as a case functional, but ITLFF is suitable for any high-precision functional. The performance of the selected 18 proteins indicates that compared with the fragment-based double-hybrid DFT algorithm, the force field constructed by ITLFF achieves considerable accuracy with a mean absolute error of 0.0039 kcal/mol/atom for energy and a root mean square error of 2.57 $\mathrmkcal/\mathrmmol/\AA$ for force, and it is more than 30 000 times faster and obtains more significant efficiency benefits as the system increases. The outstanding performance of ITLFF provides promising prospects for accurate and efficient protein dynamic simulations and makes an important step toward protein folding simulation. Due to the ability of ITLFF to utilize the knowledge acquired in one task to solve related problems, it is also applicable for various problems in biology, chemistry and material science.Grapevine leafroll-associated virus 3 (GLRaV-3) is one of the causal agents of grapevine leafroll disease (GLD), which severely impacts grapevine production in most viticultural regions of the world. The development of virus-resistant plants is a desirable strategy for the efficient control of viral diseases. However, natural resistant resources have not been reported in the genus Vitis, and anti-GLRaV-3 research has been quite limited in grapevine. In this study, by expressing FnCas9 and LshCas13a, we established a highly effective transgenic construct screening system via an optimized Agrobacterium-mediated transient delivery system in grapevine plantlets. Our study indicated that CRISPR/FnCas9 and LshCas13a caused GLRaV-3 inhibition. Moreover, three vectors-pCR01-CP, pCR11-Hsp70h and pCR11-CP-exhibited the most robust inhibition efficiency compared to those targeting other sites and could be further engineered to generate GLRaV-3-resistant grapevine. In addition, the viral interference efficiency of FnCas9 was dependent on its RNA binding activity. The efficiency of virus inhibition was positively correlated with the level of Cas gene expression. Importantly, we demonstrated that LshCas13a had better interference efficiency against viruses than FnCas9. In summary, this study confirmed that these two RNA-targeting CRISPR mechanisms can confer immunity against viruses in grapevine, providing new avenues to control GLRaV-3 or other RNA viruses in fruit crops.Painless and controlled on-demand drug delivery is the ultimate goal for the management of various chronic diseases, including diabetes. [https://www.selleckchem.com/products/bgj398-nvp-bgj398.html selleck products] To achieve this purpose, microneedle patches are gaining increased attention. While degradable microneedle (MN) arrays are widely employed, the use of non-dissolving MN patches remains a challenge to overcome. In this study, we demonstrate that crosslinking gelatin methacrylate with polyethylene glycol diacrylate (PEGDA) is potent for engineering non-dissolving MN arrays. Incorporation of MoS2 nanosheets as a photothermal component into MN hydrogels results in MNs featuring on-demand release properties. An optimized MoS2-MN array patch formed using a hydrogel solution containing 500 μg mL-1 of MoS2 and photochemically crosslinked for 5 min shows required mechanical behavior under a normal compressive load to penetrate the stratum corneum of mice or pig skin and allows the delivery of macromolecular therapeutics such as insulin upon swelling. Using ex vivo and in vivo models, we show that the MoS2-MN patches can be used for loading and releasing insulin for therapeutic purposes. Indeed, transdermal administration of insulin loaded into MoS2-MN patches reduces blood glucose levels in C57BL/6 mice and mini-pigs comparably to subcutaneously injected insulin. We believe that this on-demand delivery system might alter the current insulin therapies and might be a potential approach for delivery of other proteins.The quantum dynamics of rotational transitions of the diisocyanogen (CNNC) molecule undergoing collision with the helium (He) atom occurring in the interstellar medium (ISM) has been studied. The rotational deexcitation cross sections are extracted by first computing an ab initio potential energy surface of CNNC-He using the coupled-cluster with single and double and perturbative triple excitations with the F12a method (CCSD(T)-F12a) employing the aug-cc-pVTZ basis set. Utilizing the multipole expansions, collisional cross sections are determined for total energies of up to 1000 cm-1 by the close coupling equations. The discussion on propensity rules suggests that the transitions have even Δj values, while odd Δj valued transitions are forbidden due to C and N nuclei spin statistics. Quasi-bound states present in the CNNC-He van der Waals complex resulted in the resonances coming from the rapid oscillations in the values of the cross sections in the region of low energy. Rotational deexcitation rate coefficients are further worked out by averaging the calculated cross sections at temperatures below 200 K. The new findings of the study will be beneficial in modeling the abundance of diisocyanogen in the ISM.Using a template to control the on-surface polymerization process is valuable for building functional molecular nanostructures. Here, the role of the symmetric matching between a halogen-ligand component (H2TBrPP) and the substrate for the fabrication of a regular metal-organic structure on Cu(111) and Cu(100) surfaces was studied using scanning tunnelling microscopy (STM). Considering the formation of short-range order polymers on the Au(111) surface via the process of debromination due to the weak directing effect from the substrate to the precursors, a bilayer of ordered assembled structure of H2TBrPP/Au(111) has been fabricated and the molecules in the top layer are guided by the first-layer molecules. Owing to the steering effect of the substrate-directed molecular template, the H2TBrPP components in the top layer were polymerized into ordered molecular chain arrays along the given direction that is determined by the initial close-packed assembled structure of H2TBrPP components during the post-annealing treatment.