Multiple elite strategy enhanced RIME algorithm for 3D UAV path planning.

With the wave of artificial intelligence sweeping the world in recent years, UAVs is widely used in various fields. UAV path planning has attracted much attention from scientists as an essential part of UAV work. In order to design an efficient and reasonable 3D UAV path planning program, recent researchers have invented and improved many algorithms. This paper proposes an elite RIME algorithm for 3D UAV path planning. First, we propose an elite reverse learning population selection strategy based on piecewise mapping to enhance the population diversity of the algorithm for better exploration. Second, this paper proposes a stochastic factor-controlled elite pool exploration strategy so that the algorithm is difficult to enter the local optimum and can better explore the global optimum. Then, this paper proposes a hard frost puncture exploitation strategy based on the sine-cosine function so that the algorithm can find the global optimum faster during the exploitation process. Meanwhile, in order to test the performance of the algorithm proposed in this paper, we compare it with 13 other intelligent optimization algorithms that are classical and popular nowadays on 52 test functions in three test sets, CEC2017, CEC2020, and CEC2022, and obtain competitive results. Finally, we applied it to the 3D UAV path planning problem in three different terrain scenarios, and the ELRIME algorithm achieved good results in all of them. Especially in the 7-peak model, the ELRIME algorithm improves the performance of the RIME algorithm by a factor of two. In the 9-peak model, the average value aspect also reduce the cost by 91 compared to the RIME algorithm, and more importantly, it has the smallest fluctuation in 30 runs, which is among the most stable of all the compared algorithms. In the 12-peak model, its stability is also significantly enhanced, and in terms of worst-case cost, it improves the cost by 340 compared to RIME.

Enhanced Aquila optimizer based on tent chaotic mapping and new rules.

Metaheuristic algorithms, widely applied across various domains due to their simplicity and strong optimization capabilities, play a crucial role in problem-solving. While the Aquila Optimizer is recognized for its effectiveness, it often exhibits slow convergence rates and susceptibility to local optima in certain scenarios. To address these concerns, this paper introduces an enhanced version, termed Tent-enhanced Aquila Optimizer (TEAO). TEAO incorporates the Tent chaotic map to initialize the Aquila population, promoting a more uniform distribution within the solution space. To balance exploration and exploitation, novel formulas are proposed, accelerating convergence while ensuring precision. The effectiveness of the TEAO algorithm is validated through a comprehensive comparison with 14 state-of-the-art algorithms using 23 classical benchmark test functions. Additionally, to assess the practical feasibility of the approach, TEAO is applied to six constrained engineering problems and benchmarked against the performance of the same 14 algorithms. All experimental results consistently demonstrate that TEAO outperforms other advanced algorithms in terms of solution quality and stability, establishing it as a more competitive choice for optimization tasks.

Spatial memory requires hypocretins to elevate medial entorhinal gamma oscillations.

The hypocretin (Hcrt) (also known as orexin) neuropeptidic wakefulness-promoting system is implicated in the regulation of spatial memory, but its specific role and mechanisms remain poorly understood. In this study, we revealed the innervation of the medial entorhinal cortex (MEC) by Hcrt neurons in mice. Using the genetically encoded G-protein-coupled receptor activation-based Hcrt sensor, we observed a significant increase in Hcrt levels in the MEC during novel object-place exploration. We identified the function of Hcrt at presynaptic glutamatergic terminals, where it recruits fast-spiking parvalbumin-positive neurons and promotes gamma oscillations. Bidirectional manipulations of Hcrt neurons' projections from the lateral hypothalamus (LHHcrt) to MEC revealed the essential role of this pathway in regulating object-place memory encoding, but not recall, through the modulation of gamma oscillations. Our findings highlight the significance of the LHHcrt-MEC circuitry in supporting spatial memory and reveal a unique neural basis for the hypothalamic regulation of spatial memory.

[Characterization and application of several lysis cassettes].

Lysis is a common functional module in synthetic biology and is widely used in genetic circuit design. Lysis could be achieved by inducing expression of lysis cassettes originated from phages. However, detailed characterization of lysis cassettes hasn't been reported yet. Here, we first adopted arabinose- and rhamnose-inducible systems to develop inducible expression of five lysis cassettes (S105, A52G, C51S S76C, LKD, LUZ) in Escherichia coli Top10. By measuring OD600, we characterized the lysis behavior of strains harboring different lysis cassettes. These strains were harvested at different growth stages, induced with different concentrations of chemical inducers, or contained plasmids with different copy numbers. We found that although all five lysis cassettes could induce bacterial lysis in Top10, lysis behaviors differed a lot at various conditions. We further found that due to the difference in background expression levels between strain Top10 and Pseudomonas aeruginosa PAO1, it was hard to construct inducible lysis systems in strain PAO1. The lysis cassette controlled by rhamnose-inducible system was finally inserted into the chromosome of strain PAO1 to construct lysis strains after careful screen. The results indicated that LUZ and LKD were more effective in strain PAO1 than S105, A52G and C51S S76C. At last, we constructed an engineered bacteria Q16 using an optogenetic module BphS and the lysis cassette LUZ. The engineered strain was capable of adhering to target surface and achieving light-induced lysis by tuning the strength of ribosome binding sites (RBSs), showing great potential in surface modification.

Remotely Controllable Engineered Bacteria for Targeted Therapy of Pseudomonas aeruginosa Infection.

Pseudomonas aeruginosa (P. aeruginosa) infection has become an intractable problem worldwide due to the decreasing efficacy of the mainstay therapy, antibiotic treatment. Hence, exploring new drugs and therapies to address this issue is crucial. Here, we construct a chimeric pyocin (ChPy) to specifically kill P. aeruginosa and engineer a near-infrared (NIR) light-responsive strain to produce and deliver this drug. Our engineered bacterial strain can continuously produce ChPy in the absence of light and release it to kill P. aeruginosa via remotely and precisely controlled bacterial lysis induced by NIR light. We demonstrate that our engineered bacterial strain is effective in P. aeruginosa-infected wound therapy in the mouse model, as it eradicated PAO1 in mouse wounds and shortened the wound healing time. Our work presents a potentially spatiotemporal and noninvasively controlled therapeutic strategy of engineered bacteria for the targeted treatment of P. aeruginosa infections.

Programming the lifestyles of engineered bacteria for cancer therapy.

Bacteria can be genetically engineered to act as therapeutic delivery vehicles in the treatment of tumors, killing cancer cells or activating the immune system. This is known as bacteria-mediated cancer therapy (BMCT). Tumor invasion, colonization and tumor regression are major biological events, which are directly associated with antitumor effects and are uncontrollable due to the influence of tumor microenvironments during the BMCT process. Here, we developed a genetic circuit for dynamically programming bacterial lifestyles (planktonic, biofilm or lysis), to precisely manipulate the process of bacterial adhesion, colonization and drug release in the BMCT process, via hierarchical modulation of the lighting power density of near-infrared (NIR) light. The deep tissue penetration of NIR offers us a modality for spatio-temporal and non-invasive control of bacterial genetic circuits in vivo. By combining computational modeling with a high-throughput characterization device, we optimized the genetic circuits in engineered bacteria to program the process of bacterial lifestyle transitions by altering the illumination scheme of NIR. Our results showed that programming intratumoral bacterial lifestyle transitions allows precise control of multiple key steps throughout the BMCT process and therapeutic efficacy can be greatly improved by controlling the localization and dosage of therapeutic agents via optimizing the illumination scheme.

A tool kit of highly selective and sensitive genetically encoded neuropeptide sensors.

Neuropeptides are key signaling molecules in the endocrine and nervous systems that regulate many critical physiological processes. Understanding the functions of neuropeptides in vivo requires the ability to monitor their dynamics with high specificity, sensitivity, and spatiotemporal resolution. However, this has been hindered by the lack of direct, sensitive, and noninvasive tools. We developed a series of GRAB (G protein-coupled receptor activation‒based) sensors for detecting somatostatin (SST), corticotropin-releasing factor (CRF), cholecystokinin (CCK), neuropeptide Y (NPY), neurotensin (NTS), and vasoactive intestinal peptide (VIP). These fluorescent sensors, which enable detection of specific neuropeptide binding at nanomolar concentrations, establish a robust tool kit for studying the release, function, and regulation of neuropeptides under both physiological and pathophysiological conditions.

Engineering Gac/Rsm Signaling Cascade for Optogenetic Induction of the Pathogenicity Switch in Pseudomonas aeruginosa.

Bacterial pathogens operate by tightly controlling the pathogenicity to facilitate invasion and survival in host. While small molecule inducers can be designed to modulate pathogenicity to perform studies of pathogen-host interaction, these approaches, due to the diffusion property of chemicals, may have unintended, or pleiotropic effects that can impose limitations on their use. By contrast, light provides superior spatial and temporal resolution. Here, using optogenetics we reengineered GacS of the opportunistic pathogen Pseudomonas aeruginosa, signal transduction protein of the global regulatory Gac/Rsm cascade which is of central importance for the regulation of infection factors. The resultant protein (termed YGS24) displayed significant light-dependent activity of GacS kinases in Pseudomonas aeruginosa. When introduced in the Caenorhabditis elegans host systems, YGS24 stimulated the pathogenicity of the Pseudomonas aeruginosa strain PAO1 in a brain-heart infusion and of another strain, PA14, in slow killing media progressively upon blue-light exposure. This optogenetic system provides an accessible way to spatiotemporally control bacterial pathogenicity in defined hosts, even specific tissues, to develop new pathogenesis systems, which may in turn expedite development of innovative therapeutics.

Adaptive evolution of Saccharomyces cerevisiae in a continuous and closed circulating fermentation (CCCF) system coupled with PDMS membrane pervaporation.

As an efficient means of strain improvement, adaptive evolution is a technique with great potential. Long-term cultivation of Saccharomyces cerevisiae was performed in a polydimethylsiloxane membrane bioreactor system which was constructed by coupling the fermentation with pervaporation. A parent strain was subjected to three rounds of fermentation-screening-transfer procedure lasting 1,500 h in a continuous and closed circulating fermentation (CCCF) system, and its 600-generation descendant S33 was screened. In shaking flask culture test, the selected strain S33 from the third round showed great superiority over the parent strain in the residual broth medium, with the ethanol yield and specific ethanol productivity increasing by 34.5 and 34.7 %, respectively. In the long-term CCCF test, the fermentation performance of the descendant strain in the third round was higher than that of its parent strain in the second round. These results show the potential of this novel adaptive evolution approach in optimization of yeast strains.

Ethanol fermentation kinetics in a continuous and closed-circulating fermentation system with a pervaporation membrane bioreactor.

The kinetics of ethanol fermentation by Saccharomyces cerevisiae was studied in a continuous and closed-circulating fermentation (CCCF) system with a polydimethylsiloxane (PDMS) pervaporation membrane bioreactor. Three sequential 500-h cycles of CCCF experiments were carried out. A glucose volumetric consumption of 3.8 g L(-1) h(-1) and ethanol volumetric productivity of 1.39 g L(-1) h(-1) were obtained in the third cycle, with a specific glucose utilization rate of 0.32 h(-1) and ethanol yield rate of 0.13 h(-1). The prolonged fermentation time and good fermentation performance indicate that the CCCF would be a feasible and promising fermentation process technology.