Zinc oxide nanoparticles derived from Penicillium griseofulvum mitigate DMBA/TPA-promoted mice skin carcinogenesis by modulating NF-ĸB associated signalling.

This study investigates the synthesis of zinc oxide nanoparticles using Penicillium griseofulvum (ZnONPs-PG) and their potential role in preventing DMBA/TPA-induced skin cancer. The synthesis process involved using a 1-mM zinc acetate dihydrate as a precursor in P. griseofulvum. Various analytical techniques, including FTIR spectroscopy, UV-Vis, TEM, XRD, and DLS, were utilized to characterize the ZnONPs. The efficacy of ZnONPs-PG was then evaluated in a DMBA/TPA-induced skin cancer model. Mice were treated topically with DMBA/TPA in acetone (200 µL) over 2 weeks, with treatments continuing for 20 weeks. Results showed 100% tumor occurrence, histological changes, elevated lipid peroxidation (LPO) levels, and decreased antioxidant levels in DMBA/TPA-treated mice. However, topical application of ZnONPs magnificently reverted the tumor occurrence, histological changes, elevated malanoldehyde and hydrogen peroxide levels; decreased antioxidant levels in DMBA/TPA-treated mice. ZnONPs-PG treatment suppressed the increased levels of inflammatory markers (COX-2, iNOS and NF-κB,) and cell proliferation markers (Cyclin-E1, Cyclin D1, VEGF, TGF-ß1) exposed mice. In addition, ZnONPs-PG treatment decreased the DMBA/TPA-induced anti-apoptotic Bcl-2 protein and increasing the expression of pro-apoptotic markers (Bax and caspase 3) in skin tissues. Thus, ZnONPs-PG may prevent skin carcinogenesis through its potent antioxidant properties and inhibiting NF-κB-mediated inflammatory and proliferation pathways.

A Zn-MOF-based mixed matrix membrane as an ultrastable luminescent sensor for selective and visual detection of antibiotics and pesticides in food samples.

The detection of antibiotics and pesticides are of great significance since their residues threaten the health of human beings by accumulation. However, most traditional solid chemical sensors are suffer from the limitations of low sensitivity and economic practicability because of the aggregating nature and unstable of solid sensors. Herein, a new luminescent sensor 1@PMMA (1, [(ZnL)·H2O]n (H2L = 5-(4-(pyridin-4-yl)benzamido)benzene-1,3-dioic acid); PMMA = poly(methyl methacrylate)) was successfully prepared. Notably, the polymer matrix provided the chemical protection for MOF particles. The as fabricated 1@PMMA was stable in milk, honey and egg as well as exhibited strong blue emission under ultraviolet light irradiation, which can act as luminescent probe for detecting antibiotics and pesticides. More interestingly, 1@PMMA exhibited visual, real-time and recyclable detection of antibiotics ornidazole (ODZ) and pesticides 2,6-dichloro-4-nitrobenzenamine (DCN) in real food samples. This work shows that the luminescent MOF-based mixed matrix membranes could be applied as good candidates for sensing analytes in practical application.

Cationic Europium-Organic Framework for Chromatographic Column Separation of Ionic Dyes and Stimuli-Responsive Chromic Properties.

A novel 3D europium-based cationic framework (Eu-CMOF) has been constructed solvothermally by employing a viologen derivative as an organic functional building unit. Notably, Eu-CMOF demonstrates its capability as a proficient aqueous-phase ion-exchange host, facilitating the remarkable rapid chromatographic column separation of new coccine and malachite green (NC3-/MG+), as well as new coccine and methylene blue (NC3-/MLB+), in mere 2 to 4 min. Adsorption thermodynamics and kinetics of anionic dyes demonstrate that Eu-CMOF exhibits a higher adsorption capacity for NC3-, as evaluated by the Langmuir model, reaching a value of 173 mg·g-1. The pseudo-second-order rate constant is determined to be 3.84 × 10-3 mg-1·g·min-1. Additionally, Eu-CMOF displays reversible photochromic and amine- and ammonia-induced vapochromic behaviors. Further mechanistic studies reveal that these chromic behaviors are primarily attributed to the generation of free viologen radical stimulated by Xe-light or electron-rich amine/ammonia. This research contributes to the development of advanced materials with applications in rapid chromatographic separation and stimuli-responsive chromic properties, showcasing the potential of Eu-CMOF as a versatile platform for practical applications.

Invasive papillary carcinoma of the breast: A case report.

Invasive papillary carcinoma (IPC) of the breast is a rare form of cancer. The current report documents a case of IPC characterized by a large tumor size and skin involvement. Surgical exploration revealed no evidence of axillary lymph node metastasis in breast cancer. Due to financial constraints, the patient opted solely for anastrozole endocrine therapy at a dosage of 1 mg/day for a period of 5 years post-surgery, foregoing other treatments such as radiotherapy and chemotherapy. Since discharge, 2.5 years have passed, during which the patient has been followed up via phone every 3 months, showing a good prognosis. A literature review indicated that IPC is prevalent amongst the elderly population and can be misdiagnosed due to its morphological, cytomorphological and immunophenotypic overlap with other types of papillary neoplasms. This tumor exhibits a more favorable prognosis compared with IDC, primarily attributed to its advantageous gene and molecular expression patterns, coupled with its decreased invasiveness. Despite limited evidence-based research on the treatment of IPC, the present case report, albeit with limitations, underscores the importance of avoiding over-treatment and suggests the feasibility of combining surgery with endocrine therapy for IPC.

Invasive papillary carcinoma of the breast.

Invasive papillary carcinoma is a rare form of breast cancer that is more likely to occur in postmenopausal women. Previous studies have been limited to case reports and small retrospective studies, leading to low awareness of this type of tumor and difficult clinical management. According to the available literature, invasive papillary carcinoma exhibits unique pathological features and biological behaviors. Invasive papillary carcinoma is mostly luminal type, with a low rate of lymph node metastasis, which underlies its favorable prognosis. The effectiveness of adjuvant therapy in reducing tumor burden and improving prognosis in patients with invasive papillary carcinoma remains uncertain. Due to the rarity of the lesion, conducting prospective clinical trials is impractical. The use of biological models, such as organoids, can help alleviate the impact of the scarcity of this condition on research. In addition, invasive papillary carcinoma is affected by specific genomic events, and more extensive studies of gene expression profiling may provide molecular-level insights to make optimal therapeutic decisions.

The Effect of Dexmedetomidine as a Local Anesthetic Adjuvant for Iliac Fascia Compartment Block on Postoperative Delirium in Elderly Patients Undergoing Elective Hip Surgery.

INTRODUCTION: We analyzed the effect of dexmedetomidine (DEX) as a local anesthetic adjuvant on postoperative delirium (POD) in elderly patients undergoing elective hip surgery. METHODS: In this study, 120 patients undergoing hip surgery were enrolled and randomly assigned to two groups: fascia iliaca compartment block with DEX + ropivacaine (the Y group, n = 60) and fascia iliaca compartment block with ropivacaine (the R group, n = 60). The primary outcomes: presence of delirium during the postanesthesia care unit (PACU) period and on the first day (D1), the second day (D2), and the third day (D3) after surgery. The secondary outcomes: preoperative and postoperative C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), occurrence of insomnia on the preoperative day, day of operation, D1 and D2; HR values of patients in both groups before iliac fascia block (T1), 30 min after iliac fascia block (T2), at surgical incision (T3), 20 min after incision (T4), when they were transferred out of the operating room (T5) and after leaving the recovery room (T6) at each time point; VAS for T1, PACU, D1, D2; the number of patients requiring remedial analgesics within 24 h after blockade and related complications between the two groups. RESULTS: A total of 97 patients were included in the final analysis, with 11 and 12 patients withdrawing from the R and Y groups, respectively. The overall incidence of POD and its incidence in the PACU and ward were all lesser in the Y group than in the R group (p < 0.05). Additionally, fewer cases required remedial analgesia during the PACU period, and more vasoactive drugs were used for maintaining circulatory system stability in the Y group as compared to the R group (p < 0.05). At the same time, the incidence of intraoperative and postoperative bradycardia in the Y group was higher than that in the R group, accompanied by lower postoperative CRP and ESR (all p < 0.05). CONCLUSION: Ultrasound-guided high fascia iliaca compartment block with a combination of ropivacaine and DEX can reduce the incidence of POD, the use of intraoperative opioids and postoperative remedial analgesics, and postoperative inflammation in elderly patients who have undergone hip surgery, indicating that this method could be beneficial in the prevention and treatment of POD.

Brazilin-7-2-butenoate inhibits amyloid ß-protein aggregation, alleviates cytotoxicity, and protects Caenorhabditis elegans.

The fibrillogenesis of amyloid ß-protein (Aß) gradually accumulates to form neurotoxic Aß aggregates in the human brain, which is the direct cause of Alzheimer's disease (AD) related symptoms. There are currently no effective therapies for AD. Brazilin, a natural polyphenol, inhibits Aß fibrillogenesis, disrupts the mature fibrils and alleviates the corresponding cytotoxicity, but it also has the high toxic. Therefore, brazilin-7-2-butenoate (B-7-2-B), a brazilin derivative, was designed and synthesized. B-7-2-B exhibited lower toxicity and stronger inhibitory effect on Aß aggregation than brazilin. B-7-2-B could prevent the formation of Aß fibrils and oligomers, and depolymerize pre-formed aggregates in a dose-dependent manner. Furthermore, B-7-2-B prominently alleviated the cytotoxicity and the oxidative stress induced by Aß aggregates in PC12 cells. The protective impacts of B-7-2-B were further demonstrated by using the Caenorhabditis elegans model, including decreasing the extent of Aß aggregation, improving the motility and sensation disorders. Eventually, B-7-2-B was proven to be no apparent damage to worms. In summarize, it can be concluded that B-7-2-B has the potential as a drug for treating AD.

Study on the Performance of a Surface with Coupled Wettability Difference and Convex-Stripe Array for Improved Air Layer Stability.

The existence of an air layer reduces friction drag on superhydrophobic surfaces. Therefore, improving the air layer stability of superhydrophobic surfaces holds immense significance in reducing both energy consumption and environmental pollution caused by friction drag. Based on the properties of mathematical discretization and the contact angle hysteresis generated by the wettability difference, a surface coupled with a wettability difference treatment and a convex-stripe array is developed by laser engraving and fluorine modification, and its performance in improving the air layer stability is experimentally studied in a von Kármán swirling flow field. The results show that the destabilization of the air layer is mainly caused by the Kelvin-Helmholtz instability, which is triggered by the density difference between gas and liquid, as well as the tangential velocity difference between gas and liquid. When the air layer is relatively thin, tangential wave destabilization occurs, whereas for larger thicknesses, the destabilization mode is coupled wave destabilization. The maximum Reynolds number that keeps the air layer fully covering the surface of the rotating disk (with drag reduction performance) during the disk rotation process is defined as the critical Reynolds number (Rec), which is 1.62 × 105 for the uniform superhydrophobic surface and 3.24 × 105 for the superhydrophobic surface with a convex stripe on the outermost ring (SCSSP). Individual treatments of wettability difference and a convex-stripe array on the SCSSP further improve the air layer stability, but Rec remains at 3.24 × 105. Finally, the coupling of the wettability difference treatment with a convex-stripe array significantly improves the air layer stability, resulting in an increase of Rec to 4.05 × 105, and the drag reduction rate stably maintained around 30%.

Multiobjective Combinatorial Optimization Using a Single Deep Reinforcement Learning Model.

This article proposes utilizing a single deep reinforcement learning model to solve combinatorial multiobjective optimization problems. We use the well-known multiobjective traveling salesman problem (MOTSP) as an example. Our proposed method employs an encoder-decoder framework to learn the mapping from the MOTSP instance to its Pareto-optimal set. Specifically, it leverages a novel routing encoder to extract information for both the entire multiobjective aspect and every individual objective from the MOTSP instance. The global embeddings and each objective's embeddings are adaptively aggregated via a routing network to form the subproblems' embedding that can well represent the MOTSP features. Using a modified context embedding, the subproblems' embeddings are fed into a decoder to produce a set of approximate Pareto-optimal solutions in parallel. Additionally, we develop a Top-k baseline to enable more efficient data utilization and lightweight training for our proposed method. We compare our method with heuristic-based and learning-based ones on various types of MOTSP instances, and the experimental results show that our method can solve MOTSP instances in real-time and outperform the other algorithms, especially on large-scale problem instances.

Micro Multiobjective Evolutionary Algorithm With Piecewise Strategy for Embedded-Processor-Based Industrial Optimization.

In some industrial applications, it is required to do off-line multiobjective optimization in embedded systems. Due to their limited computing and memory capability, embedded processor may not be able to run conventional multiobjective optimization evolutionary algorithms (MOEAs). This article proposes a micro MOEA with piecewise strategy (µ MOEA) for industrial optimization in embedded processor. µ MOEA introduces an improved piecewise strategy based on the MOEA/D framework, which serially optimizes subclusters to be compatible with embedded processor under limited computing power. For the purpose of further enhancing µ MOEA, a dynamic and flexible weight vector update trigger mechanism is proposed, so that the algorithm can save and utilize the computing resources of the embedded processor as much as possible. Abundant artificial test problems are carrying out to test the performance of µ MOEA. Through various experiments, it can be found that µ MOEA has outstanding performance in ZDT, DTLZ, SMOP, and MaF problems. Last and most importantly, µ MOEA is successfully applied to two specific application scenarios of industrial optimization on embedded processor for simulation, such as two different types of semi-autogenous grinding optimization problems and micro-grid energy optimization problem, which prove the feasibility of applying MOEA to embedded processor.

Risk factors associated with postoperative delirium in elderly patients undergoing hip surgery.

Objective: We retrospectively analyzed the occurrence of postoperative delirium following hip surgery and the associated risk factors. The aim was to establish a clinical foundation for preventing postoperative delirium after hip surgery. Methods: We retrospectively selected elderly patients who had hip surgery at our hospital between January 2022 and August 2022. We included patients who experienced delirium in the observation group and those who did not encounter delirium in the control group. We then proceeded to compare various indicators among these two groups of patients. Results: We analyzed a total of 97 cases of hip surgery, and among them, 32 cases experienced postoperative delirium, resulting in an incidence rate of 32.9%. Various factors were found to be linked to the development of postoperative delirium, including age, height, gender (male), preoperative erythrocyte sedimentation rate (ESR), postoperative ESR, preoperative lactate levels, pain scores on the first day after surgery, type of surgical procedure, and the occurrence of delirium in the post-anesthesia care unit (PACU delirium). Additionally, it was observed that 75% of patients who had PACU delirium also experienced postoperative delirium. Conclusion: Postoperative delirium in patients who have hip surgery had an incidence rate of 32.9%. This phenomenon is linked to various factors that pose a risk, such as the patient age, height, gender, preoperative ESR levels, postoperative ESR levels, preoperative lactate levels, pain scores on the day following surgery, and the specific surgical procedure performed. The likelihood of experiencing delirium increases by 12% for every additional 10 years in patient age. Additionally, the occurrence of delirium in the PACU is a strong indicator of the likelihood of experiencing postoperative delirium.

Oxidative stress mediates hippocampal neuronal apoptosis through ROS/JNK/P53 pathway in rats with PTSD triggered by high-voltage electrical burn.

BACKGROUND: The pathogenesis of post-traumatic stress disorder (PTSD) triggered by high-voltage electrical burn (HVEB) remains unclear and the oxidative stress plays a role in this process. The purpose of this study is to investigate the underlying mechanism of oxidative stress mediates hippocampal neuronal apoptosis in rats with PTSD triggered by HVEB. MATERIALS AND METHODS: The PTSD rat model was developed by stimulating with high voltage electricity and screened using behavioral performance including Morris water maze (MWM), elevated plus-maze (EPM) and open-field test (OFT). The reactive oxygen species (ROS) generation was measured by DHE fluorescence staining or flow cytometry. Western blotting assay was used to detect the proteins of p-JNK, JNK, P53, PUMA, Bcl-2 and Bax in hippocampal tissue or HT22 cells treated with electrical stimulation. RESULTS: The serum MDA and 8-OHdG levels were increased (P < 0.001), while the activities of SOD and CAT were decreased (P < 0.001) significantly in patients with HVEB. Behavioral test results showed that high-voltage electric stimulation induced the PTSD-like symptoms and the ROS-JNK-P53 pathway was involved in the neuronal apoptosis in rats with PTSD induced by HVEB. In vitro experiments further confirmed the electrical stimulation induced neuronal apoptosis through ROS/JNK/P53 signaling pathway and the antioxidant NAC could rescued the ROS generation, activation of JNK/P53 proteins and improved the cell apoptosis rate in HT22 cells. Finally, the JNK inhibitor SP600125 could significantly inhibited the percentage of HT22 cell apoptosis induced by electrical stimulation (P < 0.001). CONCLUSIONS: These results indicated that oxidative stress mediates hippocampal neuronal apoptosis through ROS/JNK/P53 pathway in rats with PTSD triggered by HVEB.

A viologen-based Cd(II) coordination polymer as a multifunctional platform for photochromism, chemochromism and a broad range of fluorescence pH sensing.

A multi-responsive Cd(II) coordination polymer (1) has been constructed by introducing a viologen derivative as both the framework backbone and ligand side pendant. Notably, compound 1 exhibits intriguing properties, including photochromism, methanol-assisted photochromism and chemochromism to ammonia. Furthermore, compound 1 also displays fluorescence pH sensing ability in a wide pH range.

Exploring the role of differentially expressed metabolic genes and their mechanisms in bone metastatic prostate cancer.

Background: Approximately 10-20% of patients diagnosed with prostate cancer (PCa) evolve into castration-resistant prostate cancer (CRPC), while nearly 90% of patients with metastatic CRPC (mCRPC) exhibit osseous metastases (BM). These BM are intimately correlated with the stability of the tumour microenvironment. Purpose: This study aspires to uncover the metabolism-related genes and the underlying mechanisms responsible for bone metastatic prostate cancer (BMPCa). Methods: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets of PCa and BM were analyzed through R Studio software to identify differentially expressed genes (DEGs). The DEGs underwent functional enrichment via Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), with key factors screened by a random forest utilized to establish a prognostic model for PCa. The study explored the relationship between DEGs and the stability of the immune microenvironment. The action and specificity of CRISP3 in PCa was validated through western blot analysis, CCK-8 assay, scratch assay, and cellular assay. Results: The screening of GEO and TCGA datasets resulted in the identification of 199 co-differential genes. Three DEGs, including DES, HBB, and SLPI, were selected by random forest classification model and cox regression model. Immuno-infiltration analysis disclosed that a higher infiltration of naïve B cells and resting CD4 memory T cells occurred in the high-expression group of DES, whereas infiltration of resting M1 macrophages and NK cells was greater in the low-expression group of DES. A significant infiltration of neutrophils was observed in the high-expression group of HBB, while greater infiltration of gamma delta T cells and M1 macrophages was noted in the low-expression group of HBB. Resting dendritic cells, CD8 T cells, and resting T regulatory cells (Tregs) infiltrated significantly in the high-expression group of SLPI, while only resting mast cells infiltrated significantly in the low-expression group of SLPI. CRISP3 was established as a critical gene in BMPCa linked to DES expression. Targeting CRISP3, d-glucopyranose may impact tumour prognosis. During the mechanistic experiments, it was established that CRISP3 can advance the proliferation and metastatic potential of PCa by advancing epithelial-to-mesenchymal transition (EMT). Conclusion: By modulating lipid metabolism and maintaining immunological and microenvironmental balance, DES, HBB, and SLPI suppress prostate cancer cell growth. The presence of DES-associated CRISP3 is a harbinger of unfavorable outcomes in prostate cancer and may escalate tumor proliferation and metastatic capabilities by inducing epithelial-mesenchymal transition.

Intestinal tuberculosis presented as spindle cell pseudotumor in a HIV-positive case.

MSP is a rare and atypical form of benign granulomatous inflammation characterised by tumour-like local proliferation of spindle-shaped histiocytes containing acid-fast positive mycobacteria, which should be differentiated from neoplastic lesions. A 26-year-old Chinese man complained an intermittent and mild right lower abdominal pain for 5 months in May 2022.Histopathology of biopsy samples showed Mycobacterial spindle cell pseudotumor (MSP). The test of Mycobacterium tuberculosis detected by polymerase chain reaction using intestinal tissue slice was negative. The metagenomic next-generation sequencing (BGI-Shenzhen) using formalin-fixation and paraffin-embedded intestine samples confirmed Mycobacterium tuberculosis complex (MTBC).

Choose Appropriate Subproblems for Collaborative Modeling in Expensive Multiobjective Optimization.

In dealing with the expensive multiobjective optimization problem, some algorithms convert it into a number of single-objective subproblems for optimization. At each iteration, these algorithms conduct surrogate-assisted optimization on one or multiple subproblems. However, these subproblems may be unnecessary or resolved. Operating on such subproblems can cause server inefficiencies, especially in the case of expensive optimization. To overcome this shortcoming, we propose an adaptive subproblem selection (ASS) strategy to identify the most promising subproblems for further modeling. To better leverage the cross information between the subproblems, we use the collaborative multioutput Gaussian process surrogate to model them jointly. Moreover, the commonly used acquisition functions (also known as infill criteria) are investigated in this article. Our analysis reveals that these acquisition functions may cause severe imbalances between exploitation and exploration in multiobjective optimization scenarios. Consequently, we develop a new acquisition function, namely, adaptive lower confidence bound (ALCB), to cope with it. The experimental results on three different sets of benchmark problems indicate that our proposed algorithm is competitive. Beyond that, we also quantitatively validate the effectiveness of the ASS strategy, the CoMOGP model, and the ALCB acquisition function.

Continuous Encoding for Overlapping Community Detection in Attributed Network.

Detecting overlapping communities of an attribute network is a ubiquitous yet very difficult task, which can be modeled as a discrete optimization problem. Besides the topological structure of the network, node attributes and node overlapping aggravate the difficulty of community detection significantly. In this article, we propose a novel continuous encoding method to convert the discrete-natured detection problem to a continuous one by associating each edge and node attribute in the network with a continuous variable. Based on the encoding, we propose to solve the converted continuous problem by a multiobjective evolutionary algorithm (MOEA) based on decomposition. To find the overlapping nodes, a heuristic based on double-decoding is proposed, which is only with linear complexity. Furthermore, a postprocess community merging method in consideration of node attributes is developed to enhance the homogeneity of nodes in the detected communities. Various synthetic and real-world networks are used to verify the effectiveness of the proposed approach. The experimental results show that the proposed approach performs significantly better than a variety of evolutionary and nonevolutionary methods on most of the benchmark networks.

Generalization Performance of Pure Accuracy and its Application in Selective Ensemble Learning.

The pure accuracy measure is used to eliminate random consistency from the accuracy measure. Biases to both majority and minority classes in the pure accuracy are lower than that in the accuracy measure. In this paper, we demonstrate that compared with the accuracy measure and F-measure, the pure accuracy measure is class distribution insensitive and discriminative for good classifiers. The advantages make the pure accuracy measure suitable for traditional classification. Further, we mainly focus on two points: exploring a tighter generalization bound on pure accuracy based learning paradigm and designing a learning algorithm based on the pure accuracy measure. Particularly, with the self-bounding property, we build an algorithm-independent generalization bound on the pure accuracy measure, which is tighter than the existing bound of an order O(1/√N) (N is the number of instances). The proposed bound is free from making a smoothness or convex assumption on the hypothesis functions. In addition, we design a learning algorithm optimizing the pure accuracy measure and use it in the selective ensemble learning setting. The experiments on sixteen benchmark data sets and four image data sets demonstrate that the proposed method statistically performs better than the other eight representative benchmark algorithms.

Combining Lyapunov Optimization With Evolutionary Transfer Optimization for Long-Term Energy Minimization in IRS-Aided Communications.

This article studies an intelligent reflecting surface (IRS)-aided communication system under the time-varying channels and stochastic data arrivals. In this system, we jointly optimize the phase-shift coefficient and the transmit power in sequential time slots to maximize the long-term energy consumption for all mobile devices while ensuring queue stability. Due to the dynamic environment, it is challenging to ensure queue stability. In addition, making real-time decisions in each short time slot also needs to be considered. To this end, we propose a method (called LETO) that combines Lyapunov optimization with evolutionary transfer optimization (ETO) to solve the above optimization problem. LETO first adopts Lyapunov optimization to decouple the long-term stochastic optimization problem into deterministic optimization problems in sequential time slots. As a result, it can ensure queue stability since the deterministic optimization problem in each time slot does not involve future information. After that, LETO develops an evolutionary transfer method to solve the optimization problem in each time slot. Specifically, we first define a metric to identify the optimization problems in past time slots similar to that in the current time slot, and then transfer their optimal solutions to construct a high-quality initial population in the current time slot. Since ETO effectively accelerates the search, we can make real-time decisions in each short time slot. Experimental studies verify the effectiveness of LETO by comparison with other algorithms.