The Use of Honeybee Hives May Boost Yields of Some Crops in Nepal

Many pollination-dependent crops worldwide need bees for the highest productivity. If the crops are not pollinated, a pollination deficit will result. Consequently, low yields of fruit set and seed set of cultivated plants may be expected. Here, we evaluated how pollination with honeybee (Apis mellifera) hives may affect the production of the bittergourd (Momordica charantia), buckwheat (Fagopyrum esculentum), and mustard (Brassica campestris) in tons or quintal per hectare in Nepal. Our experimental design involved three treatments in blocks within selected areas: (i) the effect of the honeybees alone (caged with beehives), (ii) free insect access under natural field conditions, and (iii) blocks restraining insect access (caged without beehives). We also assessed the flower visiting insects within crops using pan traps and identifying insect orders. We found that the productivity of bittergourd, buckwheat, and mustard significantly increased in the treatments with beehives inside the cage. To a lesser extent, the treatment with free access to the flying insects enhanced the production of the selected crops. Proportionally, Hymenoptera (mainly bees) was the most common taxon within bittergourd, buckwheat, and mustard crops, followed by Diptera and Lepidoptera. Hence, the provision of beehives in cultivated areas such as those evaluated here could be considered as a complementary strategy for supporting the long-term productivity of these crops in Nepal.

Flexibility “of” vs. “in” Systems: A Complementary Strategy for Designing Fleet-Based Systems for Uncertainty

Complex systems must sustain value over extended lifetimes, often in the face of significant uncertainty. Flexibility “in” systems has been shown to be highly valuable for Large Monolithic Systems (LMS). However, other research highlighted that the value of flexibility “in” is highly contingent on delays in implementation. These limitations become more important when applied to other classes of complex systems, including Fleet-Based Systems (FBS). To overcome these challenges, this paper introduces a complementary approach to flexible design, termed “Flexibility ‘of’” and applies it to a case study of a fleet of military vehicles (an FBS). Unlike LMS, FBS are composed of multiple identical units that collectively deliver value. While each unit is itself a complex system (e.g., a tank or aircraft), the collective nature of the operations provides additional paths to flexibility: in addition to implementing flexibility at the vehicle level, flexibility can be applied to the management of the fleet. Flexibility “of” involves procuring a mixed capability fleet upfront and then actively managing which subsets of that fleet are deployed to meet emerging needs. Our results demonstrate the potential value for an “of” strategy and provide guidance for when different flexibility strategies should be adopted alone or in combination.

Efficacy of the commercial plant products acting against influenza-a review

Background Influenza infection always poses a threat to human and animal health. Vaccines and antiviral drugs are recommended to deal with the situation. The drawback of these remedial agents made the scientist change their focus on an alternative therapy. The anti-influenza effects of plants have been extensively studied, and many pharmaceutical companies have prepared their products on this basis. Main body The present review documents the successfully launched anti-influenza commercial products. In specific, it exposes the scientifically validated and evidence-based supporting inhibitory action of influenza and its strains. Conclusion This review highlighted the efficacy of the commercial products which effectively combat influenza. It provides a complementary strategy to deal with the worst-case scenario of flu. Meanwhile, to face the emerging strains, brand new products are in great necessity besides prevailing and available drugs.

Foliar N Application on Tea Plant at Its Dormancy Stage Increases the N Concentration of Mature Leaves and Improves the Quality and Yield of Spring Tea

Over 30% of the Chinese tea plantation is supplied with excess fertilizer, especially nitrogen (N) fertilizer. Whether or not foliar N application on tea plants at the dormancy stage could improve the quality of spring tea and be a complementary strategy to reduce soil fertilization level remains unclear. In this study, the effects of foliar N application on tea plants were investigated by testing the types of fertilizers and their application times, and by applying foliar N under a reduced soil fertilization level using field and 15N-labeling pot experiments. Results showed that the foliar N application of amino acid liquid fertilizer two times at the winter dormancy stage was enough to significantly increase the N concentration of the mature leaves and improved the quality of spring tea. The foliar application of 2% urea or liquid amino acid fertilizer two times at the winter dormancy stage and two times at the spring dormancy stage showed the best performance in tea plants among the other foliar N fertilization methods, as it reduced the soil fertilization levels in tea plantations without decreasing the total N concentration of the mature leaves or deteriorating the quality of spring tea. Therefore, foliar N application on tea plants at its dormancy stage increases the N concentration of the mature leaves, improves the quality and yield of spring tea, and could be a complementary strategy to reduce soil fertilization levels.

Coupling complementary strategy to flexible graph neural network for quick discovery of coformer in diverse co-crystal materials

Cocrystal engineering have been widely applied in pharmaceutical, chemistry and material fields. However, how to effectively choose coformer has been a challenging task on experiments. Here we develop a graph neural network (GNN) based deep learning framework to quickly predict formation of the cocrystal. In order to capture main driving force to crystallization from 6819 positive and 1052 negative samples reported by experiments, a feasible GNN framework is explored to integrate important prior knowledge into end-to-end learning on the molecular graph. The model is strongly validated against seven competitive models and three challenging independent test sets involving pharmaceutical cocrystals, π–π cocrystals and energetic cocrystals, exhibiting superior performance with accuracy higher than 96%, confirming its robustness and generalization. Furthermore, one new energetic cocrystal predicted is successfully synthesized, showcasing high potential of the model in practice. All the data and source codes are available at https://github.com/Saoge123/ccgnet for aiding cocrystal community.

A Neural Network Model Informs Total Synthesis of Clovane Sesquiterpenoids

Efficient syntheses of complex small molecules often involve speculative experimental approaches. The central challenge of such plans is that experimental evaluation of high-risk strategies is resource intensive, as it entails iterative attempts at unsuccessful strategies. Herein, we report a complementary strategy that combines creative human-generated synthetic plans with robust computational prediction of the feasibility of key steps in the proposed synthesis. A neural network model was developed to predict the outcome of a generally disfavored transformation, the 6-endo-trig radical cyclization, and applied to synthetic planning of clovan-2,9-dione, resulting in a 5-step total synthesis that improves on a prior 15-step approach. This work establishes how machine learning can guide multistep syntheses that employ innovative and high-risk human-generated plans.

Enhanced chemoselectivity of a plant cytochrome P450 through protein engineering of surface and catalytic residues

Cytochrome P450s (P450s) are the most versatile catalysts utilized by plants to produce structurally and functionally diverse metabolites. Given the high degree of gene redundancy and challenge to functionally characterize plant P450s, protein engineering is used as a complementary strategy to study the mechanisms of P450-mediated reactions, or to alter their functions. We previously proposed an approach of engineering plant P450s based on combining high-accuracy homology models generated by Rosetta combined with data-driven design using evolutionary information of these enzymes. With this strategy, we repurposed a multi-functional P450 (CYP87D20) into a monooxygenase after redesigning its active site. Since most plant P450s are membrane-anchored proteins that are adapted to the micro-environments of plant cells, expressing them in heterologous hosts usually results in problems of expression or activity. Here, we applied computational design to tackle these issues by simultaneous optimization of the protein surface and active site. After screening 17 variants, effective substitutions of surface residues were observed to improve both expression and activity of CYP87D20. In addition, the identified substitutions were additive and by combining them a highly efficient C11 hydroxylase of cucurbitadienol was created to participate in the mogrol biosynthesis. This study shows the importance of considering the interplay between surface and active site residues for P450 engineering. Our integrated strategy also opens an avenue to create more tailoring enzymes with desired functions for the metabolic engineering of high-valued compounds like mogrol, the precursor of natural sweetener mogrosides.

Effect of Preexisting Immunity to Tetanus Toxoid on the Efficacy of Tetanus Toxoid-Conjugated Heroin Vaccine in Mice

Opioid use disorder (OUD) is a serious health problem that has dramatically increased over the last decade. Although current therapies for the management of OUD can be effective, they have limitations. The complementary strategy to combat the opioid crisis is the development of a conjugate vaccine to generate high affinity antibodies in order to neutralize opioids in circulation before reaching the brain. The components of an opioid vaccine include an opioid hapten (6-AmHap) that is conjugated to a carrier protein (tetanus toxoid) with the addition of adjuvants (Army Liposome Formulation adsorbed to aluminum hydroxide-ALFA). There is no consensus in the literature as to whether preexisting immunity to the carrier protein may impact the immunogenicity of the conjugate vaccine by inducing an enhanced or suppressed immune response to the hapten. Here, we investigated whether pre-exposure to tetanus toxoid would affect the immunogenicity and efficacy of the heroin vaccine, TT-6-AmHap. Mice were primed with diphtheria, tetanus, and acellular pertussis (DTaP) vaccine at weeks -4 and -2, then immunized with TT-6-AmHap vaccine at weeks 0, 3, and 6. Using ELISA and behavioral assays, we found that preexisting immunity to tetanus toxoid had no influence on the immunogenicity and efficacy of the TT-6-AmHap vaccine.

High glucose induced c-Met activation promotes aggressive phenotype and regulates expression of glucose metabolism genes in HCC cells

Hepatocellular carcinoma (HCC) is strongly associated with metabolic dysregulations/deregulations and hyperglycemia is a common metabolic disturbance in metabolic diseases. Hyperglycemia is defined to promote epithelial to mesenchymal transition (EMT) of cancer cells in various cancers but its molecular contribution to HCC progression and aggressiveness is relatively unclear. In this study, we analyzed the molecular mechanisms behind the hyperglycemia-induced EMT in HCC cell lines. Here, we report that high glucose promotes EMT through activating c-Met receptor tyrosine kinase via promoting its ligand-independent homodimerization. c-Met activation is critical for high glucose induced acquisition of mesenchymal phenotype, survival under high glucose stress and reprogramming of cellular metabolism by modulating glucose metabolism gene expression to promote aggressiveness in HCC cells. The crucial role of c-Met in high glucose induced EMT and aggressiveness may be the potential link between metabolic syndrome-related hepatocarcinogenesis and/or HCC progression. Considering c-Met inhibition in hyperglycemic patients would be an important complementary strategy for therapy that favors sensitization of HCC cells to therapeutics.

Development of Agonist-Based PROTACs Targeting Liver X Receptor

Liver X receptors (LXRs) belong to the nuclear hormone receptor superfamily and function as ligand-dependent transcription factors that regulate cholesterol homeostasis, lipid homeostasis, and immune responses. LXR antagonists are promising treatments for hypercholesterolemia and diabetes. However, effective LXR antagonists and inhibitors are yet to be developed. Thus, we aimed to develop LXR degraders (proteolysis targeting chimeras PROTACs against LXR) as a complementary strategy to provide a similar effect to LXR inhibition. In this study, we report the development of GW3965-PEG5-VH032 (3), a PROTAC capable of effectively degrading LXRβ protein. Compound 3 induced the ubiquitin-proteasome system-dependent degradation of the LXRβ protein, which requires VHL E3 ligase. We hope that PROTACs targeting LXR proteins will become novel therapeutic agents for LXR-related diseases.