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Abstract Prodrugs have been explored as an alternative to conventional chemotherapy; however, their target specificity remains limited. The tumor microenvironment harbors a range of microorganisms that potentially serve as tumor-targeting vectors for delivering prodrugs. In this study, we harness bacteria-cancer interactions native to the tumor microbiome to achieve high target specificity for prodrug delivery. We identify an oral commensal strain of Lactobacillus plantarum with an intrinsic cancer-binding mechanism and engineer the strain to enable the surface loading of anticancer prodrugs, with nasopharyngeal carcinoma (NPC) as a model cancer. The engineered commensals show specific binding to NPC via OppA-mediated recognition of surface heparan sulfate, and the loaded prodrugs are activated by tumor-associated biosignals to release SN-38, a chemotherapy compound, near NPC. In vitro experiments demonstrate that the prodrug-loaded microbes significantly increase the potency of SN-38 against NPC cell lines, up to 10-fold. In a mouse xenograft model, intravenous injection of the engineered L. plantarum leads to bacterial colonization in NPC tumors and a 67% inhibition in tumor growth, enhancing the efficacy of SN-38 by 54%.

Identifying and analyzing the engine performance and emission characteristics under the condition of performance decay is of significant reference value for fault diagnosis, condition-based maintenance, and health status monitoring. However, there is a lack of relevant research on the currently popular marine large two-stroke dual fuel (DF) engines. To fill the research gap, a detailed zero-/one-dimensional (0D/1D) model of a marine two-stroke DF engine employing the low-pressure gas concept is first established in GT-Power (Version 2020) and validated by comparing the simulation and measured results. Then, three typical types of turbocharger performance decays are defined including turbine efficiency decay, turbine nozzle ring area decay, and turbocharger shaft mechanical efficiency decay. Finally, the three types of decays are introduced to the engine simulation model and parametric runs are performed in both diesel and gas modes to identify and analyze their impacts on the performance and emission characteristics of the investigated marine DF engine. The results reveal that turbocharger performance decay has a significant impact on engine performance parameters, such as brake efficiency, engine speed, boost pressure, etc., as well as CO2 and NOx emissions, and the specified limit value on certain engine operational parameters will be exceeded when turbocharger performance decays to a certain extent. The changing trend of engine performance and emission parameters as turbocharger performance deteriorates are generally consistent in both operating modes but with significant differences in the extent and magnitude, mainly due to the distinct combustion process (Diesel cycle versus Otto cycle). Furthermore, considering the relative decline in brake efficiency, engine speed drop, and relative increase in CO2 emission, the investigated engine is less sensitive to the turbocharger performance decay in gas mode. The simulation results also imply that employing a variable geometry turbine (VGT) is capable of improving the brake efficiency of the investigated marine DF engine.

The visual monitoring of ship-engine-room equipment is an essential component of ship-cabin intelligence. In response to issues such as imbalanced quantities of different categories of engine room equipment and severe occlusion, this paper presents improvements to YOLOv8-M. Firstly, the introduction of the SPPFCSPC module enhances the feature extraction capabilities of the backbone extraction network. Subsequently, improvements are implemented in the neck network to create GCFPN, facilitating further feature fusion, and introducing the Dynamic Head module, which fuses the deformable convolution, in the part of the detection head, so as to improve the performance of the network. Finally, the FOCAL EIOU LOSS is introduced, while mitigating the impact of dataset imbalance through class-wise data augmentation. In this paper, the ship cabin equipment dataset and the public dataset MS COCO2017 are evaluated. Compared with YOLOv8-M, the mAP50 of GCD-YOLOv8 is improved by 2.6% and 0.4%, respectively.

Candida albicans is an opportunistic pathogen, with its infection as one of the causes of morbidity or mortality. Notably, the probiotic yeast Saccharomyces cerevisiae var. boulardii has shown the potential to fight against Candida infections. In this study, we aimed to engineer a commercial boulardii strain to produce medium-chain fatty acids (MCFAs) with antagonistic effects against C. albicans. First, we identified and characterized a boulardii strain and created its auxotrophic strain Δura3. Next, we constructed and expressed a heterologous MCFA biosynthetic pathway under the control of inducible and constitutive promoters. Aside from examining MCFA production and secretion, we confirmed MCFAs’ effects on C. albicans’ anti-biofilm and anti-hyphal formations and the immunomodulatory effect of MCFA-containing supernatants on Caco-2 cells. We found that under constitutive promoters, the engineered boulardii strain constitutively produced and secreted a mixture of C6:0, C8:0, and C10:0. The secreted MCFAs then reduced biofilm and hyphal formations in C. albicans SC5314. We also confirmed that MCFAs upregulated the expression of virulence-related genes in SC5314. Furthermore, we found that the constitutively produced MCFAs in the supernatant induced the upregulation of immune response genes in Caco-2 cells co-cultured with SC5314, indicating MCFAs’ roles in immunomodulation. Overall, the engineered boulardii strain produced and secreted MCFAs, as well as demonstrated antagonistic effects against C. albicans SC5314 and immune-modulatory effects in Caco-2. To our knowledge, this represents the first study tackling the metabolic engineering of a commercial probiotic yeast strain to constitutively produce and secrete MCFAs showing anti-Candida effects. Our study forms the basis of the potential development of a live biotherapeutics probiotic yeast against Candida infections through metabolic engineering strategies.

Abstract Background Poly-γ-glutamic acid (γ-PGA) is a valuable polymer with glutamate as its sole precursor. Enhancement of the intracellular glutamate synthesis is a very important strategy for the improvement of γ-PGA production, especially for those glutamate-independent γ-PGA producing strains. Corynebacterium glutamicum has long been used for industrial glutamate production and it exhibits some unique features for glutamate synthesis; therefore introduction of these metabolic characters into the γ-PGA producing strain might lead to increased intracellular glutamate availability, and thus ultimate γ-PGA production. Results In this study, the unique glutamate synthesis features from C. glutamicum was introduced into the glutamate-independent γ-PGA producing Bacillus amyloliquefaciens NK-1 strain. After introducing the energy-saving NADPH-dependent glutamate dehydrogenase (NADPH-GDH) pathway, the NK-1 (pHT315-gdh) strain showed slightly increase (by 9.1%) in γ-PGA production. Moreover, an optimized metabolic toggle switch for controlling the expression of ɑ-oxoglutarate dehydrogenase complex (ODHC) was introduced into the NK-1 strain, because it was previously shown that the ODHC in C. glutamicum was completely inhibited when glutamate was actively produced. The obtained NK-PO1 (pHT01-xylR) strain showed 66.2% higher γ-PGA production than the NK-1 strain. However, the further combination of these two strategies (introducing both NADPH-GDH pathway and the metabolic toggle switch) did not lead to further increase of γ-PGA production but rather the resultant γ-PGA production was even lower than that in the NK-1 strain. Conclusions We proposed new metabolic engineering strategies to improve the γ-PGA production in B. amyloliquefaciens. The NK-1 (pHT315-gdh) strain with the introduction of NADPH-GDH pathway showed 9.1% improvement in γ-PGA production. The NK-PO1 (pHT01-xylR) strain with the introduction of a metabolic toggle switch for controlling the expression of ODHC showed 66.2% higher γ-PGA production than the NK-1 strain. This work proposed a new strategy for improving the target product in microbial cell factories.

In this article, to meet the requirements of marine engine room simulator on both the simulation speed and simulation accuracy, a mean value engine model (MVEM) for the 7S80ME-C9.2 marine two-stroke diesel engine was developed and validated in the MATLAB/Simulink environment. In consideration of the significant influence of turbocharger compressor on both the engine steady state performance and transient response, a novel compressor model (mass flow rate and isentropic efficiency model) based on a previous study carried out by the first author was proposed with the aim of achieving satisfactory simulation accuracy within the whole engine operating envelope. The predictive and extrapolative capability of the proposed compressor model was validated by carrying out simulation experiments and analyzing the simulation results under steady state condition and during transient process. To make the traditional MVEM capable of predicting in-cylinder pressure trace, the cylinder pressure analytic model proposed by Eriksson and Andersson for the four-stroke SI (spark ignition) engine was adapted to the 7S80ME-C9.2 marine two-stroke diesel engine based on the characteristic of in-cylinder pressure trace of this type of engine and then coupled to the MVEM developed in this paper. Since there is no need to solve any differential equation as it is done in the 0-D model, the advantage of MVEM in running speed is not impaired. For achieving satisfactory simulation accuracy by using the analytic model, the model parameters were calibrated elaborately by using engine measured data and a 0-D model and the relevant tuning procedure was discussed in detail.

Microbial communities and their collective genomes form the gut microbiome, of which bacteria are the major contributor. Through their secreted metabolites, bacteria interact with the host, influencing human health and physiology. Perturbation of the microbiota and metabolome has been associated with various diseases and metabolic conditions. As knowledge on fundamental host-microbiome interactions and genetic engineering tools becomes readily available, targeted manipulation of the gut microbiome for therapeutic applications gains favourable attention. Manipulation of the gut microbiome can be achieved by altering the microbiota population and composition, or by modifying the functional metabolic activity of the microbiome to promote health and restore the microbiome balance. In this article, we review current works that demonstrate various strategies employed to manipulate the gut microbiome in situ to various degrees of precision.

Nuclear delivery and accumulation are very important for many anticancer drugs that interact with DNA or its associated enzymes in the nucleus. However, it is very difficult for neutrally and negatively charged anticancer drugs such as 10-hydroxycamptothecine (HCPT). Here we report a simple strategy to construct supramolecular nanomedicines for nuclear delivery of dual synergistic anticancer drugs. Our strategy utilizes the coassembly of a negatively charged HCPT-peptide amphiphile and the positively charged cisplatin. The resulting nanomaterials behave as the "Trojan Horse" that transported soldiers (anticancer drugs) across the walls of the castle (cell and nucleus membranes). Therefore, they show improved inhibition capacity to cancer cells including the drug resistant cancer cell and promote the synergistic tumor suppression property in vivo. We envision that our strategy of constructing nanomaterials by metal chelation would offer new opportunities to develop nanomedicines for combination chemotherapy. [ABSTRACT FROM AUTHOR]

To improve the application value and range of the traditional marine engine room simulator, a marine engineering virtual training and evaluation system is developed in this paper. Through comparing with the similar applications in the market, advantages of the one developed in this paper are showed. In addition, automatic evaluation function based on fuzzy evaluation method is developed and integrated in the training system, which is able to realize the fixed evaluation items regulated in the seafarers examination outline and the user-defined situation evaluation items by using XML to establish the evaluation question base. To improve the automatic evaluation accuracy, "Least Square Method" is used to fit the fuzzy membership function. At last, to verify the practicability and application value of the learning tool developed in this paper, 60 juniors majored in marine engineering, 10 experienced chief engineers are selected to carry out an experiment. By analyzing the experiment result, it is found that the virtual training system is accepted as a learning tool by the participants and the evaluation score generated by the automatic evaluation module is reasonable and real. [ABSTRACT FROM AUTHOR]