A Combinative Assembly Strategy Inspired Reversibly Borate-Bridged Polymeric Micelles for Lesion-Specific Rapid Release of Anti-Coccidial Drugs

Stimuli-triggered drug delivery systems hold vast promise in local infection treatment for the site-specific targeting and shuttling of drugs.Herein,chitosan conjugates(SPCS)installed with sialic acid(SA)and phenylboronic acid(PBA)were synthesized,of which SA served as targeting ligand for coccidium and reversible-binding bridge for PBA.The enhanced drug-loading capacity of SPCS micelles was attributed to a combination assembly from hydrophobicity-driving and reversible borate bridges.The drug-loaded SPCS micelles shared superior biostability in upper gastrointestinal tract.After reaching the lesions,the borate bridges were snipped by carbohydrates under a higher pH followed by accelerated drug release,while SA exposure on micellar surface facilitated drug cellular internalization to eliminate parasites inside.The drugmicelles revealed an enhanced anti-coccidial capacity with a higher index of 185.72 compared with commercial preparation.The dual-responsive combination of physicochemical assembly could provide an efficient strategy for the exploitation of stable,safe and flexible anti-infectious drug delivery systems.

Novel insights into histone lysine methyltransferases in cancer therapy:From epigenetic regulation to selective drugs

The reversible and precise temporal and spatial regulation of histone lysine methyltransferases(KMTs)is essential for epigenome homeostasis.The dysregulation of KMTs is associated with tumor initiation,metastasis,chemoresistance,invasiveness,and the immune microenvironment.Therapeutically,their promising effects are being evaluated in diversified preclinical and clinical trials,demonstrating encouraging outcomes in multiple malignancies.In this review,we have updated recent understandings of KMTs'functions and the development of their targeted inhibitors.First,we provide an updated overview of the regulatory roles of several KMT activities in oncogenesis,tumor suppression,and immune regulation.In addition,we summarize the current targeting strategies in different cancer types and multiple ongoing clinical trials of combination therapies with KMT inhibitors.In summary,we endeavor to depict the regulation of KMT-mediated epigenetic landscape and provide potential epigenetic targets in the treatment of cancers.

Aromaticity Concerto in Polycyclic Conjugated Hydrocarbons:Fusion Pattern on Combined Aromaticity Strategy Leads to Distinctive Excited State Photophysics of Dinaphthopentalenes

Understanding the structure-property relationships in polycyclic conjugated hydrocarbons(PCHs)is crucial in controlling their electronic properties and developing new optically functional materials.Aromaticity is a fundamentally important and intriguing property of numerous organic chemical structures and has stimulated a myriad of experimental and theoretical investigations.Exploiting aromaticity rules for the rational design of optoelectronic materials with the desired photophysical characteristics is a challenging yet fascinating task.Herein we present an in-depth computational and spectroscopic study on the structure-property relationships of dinaphthopentalenes(DNPs).Results highlight that the different fusion patterns between 4nπand 4n+2πunits endow these PCHs with the tunable aromaticity in the ground state/excited state,which leads to the diverse electronic structures and consequently the distinctive excited state photophysics.Accordingly,we propose a combined aromaticity design strategy for rationally modulating and tailoring electronic and optical properties of PCH skeletons.These outcomes not only present a full picture of the excited state dynamics of the DNP system and afford a new class of efficient singlet fission-active materials but also provide some basic guidelines for exploiting aromaticity rules to design and develop new optical function materials.

Novel algorithm for constructing support vector machine regression ensemble

A novel algorithm for constructing support vector machine regression ensemble is proposed. As to regression prediction, support vector machine regression （SVMR） ensemble is proposed by resampling from given training data sets repeatedly and aggregating several independent SVMRs, each of which is trained to use a replicated training set. After training, several independently trained SVMRs need to be aggregated in an appropriate combination manner. Generally, the linear weighting is usually used like expert weighting score in Boosting Regression and it is without optimization capacity. Three combination techniques are proposed, including simple arithmetic mean, linear least square error weighting and nonlinear hierarchical combining that uses another upper-layer SVMR to combine several lower-layer SVMRs. Finally, simulation experiments demonstrate the accuracy and validity of the presented algorithm.

Performance evaluation of series and parallel strategies for financial time series forecasting

Background:Improving financial time series forecasting is one of the most challenging and vital issues facing numerous financial analysts and decision makers.Given its direct impact on related decisions,various attempts have been made to achieve more accurate and reliable forecasting results,of which the combining of individual models remains a widely applied approach.In general,individual models are combined under two main strategies:series and parallel.While it has been proven that these strategies can improve overall forecasting accuracy,the literature on time series forecasting remains vague on the choice of an appropriate strategy to generate a more accurate hybrid model.Methods:Therefore,this study’s key aim is to evaluate the performance of series and parallel strategies to determine a more accurate one.Results:Accordingly,the predictive capabilities of five hybrid models are constructed on the basis of series and parallel strategies compared with each other and with their base models to forecast stock price.To do so,autoregressive integrated moving average(ARIMA)and multilayer perceptrons(MLPs)are used to construct two series hybrid models,ARIMA-MLP and MLP-ARIMA,and three parallel hybrid models,simple average,linear regression,and genetic algorithm models.Conclusion:The empirical forecasting results for two benchmark datasets,that is,the closing of the Shenzhen Integrated Index(SZII)and that of Standard and Poor’s 500(S&P 500),indicate that although all hybrid models perform better than at least one of their individual components,the series combination strategy produces more accurate hybrid models for financial time series forecasting.

Metabolic interventions combined with CTLA-4 and PD-1/PD-L1 blockade for the treatment of tumors:mechanisms and strategies

Immunotherapies based on immune checkpoint blockade(ICB)have significantly improved patient outcomes and offered new approaches to cancer therapy over the past decade.To date,immune checkpoint inhibitors(ICIs)of CTLA-4 and PD-1/PD-L1 represent the main class of immunotherapy.Blockade of CTLA-4 and PD-1/PD-L1 has shown remarkable efficacy in several specific types of cancers,however,a large subset of refractory patients presents poor responsiveness to ICB therapy;and the underlying mechanism remains elusive.Recently,numerous studies have revealed that metabolic reprogramming of tumor cells restrains immune responses by remodeling the tumor microenvironment(TME)with various products of metabolism,and combination therapies involving metabolic inhibitors and ICIs provide new approaches to cancer therapy.Nevertheless,a systematic summary is lacking regarding the manner by which different targetable metabolic pathways regulate immune checkpoints to overcome ICI resistance.Here,we demonstrate the generalized mechanism of targeting cancer metabolism at three crucial immune checkpoints(CTLA-4,PD-1,and PD-L1)to influence ICB therapy and propose potential combined immunotherapeutic strategies co-targeting tumor metabolic pathways and immune checkpoints.

Research on Dynamic Forecast of Flowering Period Based on Multivariable LSTM and Ensemble Learning Classification Task

The flowering forecast provides recommendations for orchard cleaning, pest control, field management and fertilization, which can help increase tree vigor and resistance. Flowering forecast is not only an important part of the construction of agro-meteorological index system, but also an important part of the meteorological service system. In this paper, by analyzing local meteorological data and phenological data of “Red Fuji” apples in Fen County, Linfen City, Shanxi Province, with the help of machine learning and neural networks, we proposed a method based on the combination of time series forecasting and classification forecasting is proposed to complete the dynamic forecasting model of local flowering in Ji County. Then, we evaluated the effectiveness of the model based on the number of error days and the number of days in advance. The implementation shows that the proposed multivariable LSTM network has a good effect on the prediction of meteorological factors. The model loss is less than 0.2. In the two-category task of flowering judgment, the idea of combining strategies in ensemble learning improves the effect of flowering judgment, and its AUC value increases from 0.81 and 0.80 of single model RF and AdaBoost to 0.82. The proposed model has high applicability and accuracy for flowering forecast. At the same time, the model solves the problem of rounding decimals in the prediction of flowering dates by the regression method.

Emerging non-antibody‒drug conjugates (non-ADCs) therapeutics of toxins for cancer treatment

The non-selective cytotoxicity of toxins limits the clinical relevance of the toxins.In recent years,toxins have been widely used as warheads for antibody-drug conjugates(ADCs)due to their eff-cient killing activity against various cancer cells.Although ADCs confer certain targeting properties to the toxins,low drug loading capacity,possible immunogenicity,and other drawbacks also limit the po-tential application of ADCs.Recently,non-ADC delivery strategies for toxins have been extensively investigated.To further understand the application of toxins in anti-tumor,this paper provided an over-view of prodrugs,nanodrug delivery systems,and biomimetic drug delivery systems.In addition,toxins and their combination strategies with other therapies were discussed.Finally,the prospect and challenge of toxins in cancertreatmentwerealso summarized.

Combination strategies for first-line treatment of patients with unresectable hepatocellular carcinoma:prospect of natural products

Liver cancer stands as a significant global health concern,contributing substantially to cancer incidence and mortality,particularly in Asian countries[1].Hepatocellular carcinoma(HCC)accounts for approximately 90%of all liver cancer cases and is characterized by a high-risk profile and a generally poor prognosis[2].To address advanced HCC,systemic therapy has been recommended,leading to the approval of a range of treatment regimens in clinical practice.Traditionally,first-line therapy involved the use of multitargeted tyrosine kinase inhibitors(TKIs)such as sorafenib or lenvatinib,while cabozantinib,ramucirumab.

Cooking grease particles purification review and technology combination strategy evaluation for commercial kitchens

Effective emission control of cooking oil fumes(COFs),particularly for grease particles,has always been a cause of great concern for catering industry.The review and evaluation of combinations of purification technology are urgently required.This work presents a literature review and combination strategy evaluation of purification technology of grease particles of commercial kitchens.A variety of mainstream purification technologies,such as mechanical separation(M),filtration(F),washing absorption(W)and electrostatic deposition(E)are discussed.In order to establish a complete and efficient fume purification system for commercial kitchen,this study proposes the four-point principles of combined purification technologies as:(1)from easy to difficult(for grease particle diameter);(2)fire prevention and noise reduction;(3)electrostatic deposition postposition;(4)Absorption and dissolution(by-product from electrostatic).Based on the above principles and separation characteristics,the recommended combinations of purification strategies are M-E,F-E,M-F-E and M-E-F.The combination strategy of M-F-E is adopted as an example to evaluate and optimize COFs purification system use life cycle assessment approach.The results indicate that the optimization of the M-F-E purification system using rotating mesh plate instead of baffle filter can reduce the environmental impact of global warming and eutrophication by about 35%which reduces the emissions of CO_(2)and SO_(2)from 92.533 kg and 0.110 kg to 60.214 kg and 0.072 kg,respectively.Besides the review of relevant purification technologies,the study also proposes the combination of principles of purification technologies and the evaluation and optimization of life cycle assessment for the optimal design of combined purification system.

Identification of various food residuals on denim based on hyperspectral imaging system and combination optimal strategy

As the science and technology develop,crime methods and scenes have become increasingly complex and diverse.Trace evidence analysis has become amore and more important criminal investigation technology and liquid is the main form of trace evidence.Food can provide not only energy,but clues to solve crimes.In this study,we build a hyperspectral imaging system to detect liquid residue traces,including apple juice,coffee,cola,milk and tea,on denims with light,middle and dark colors.The obtained hyperspectral images are first subjected to spectral calibration and hyperspectral data pretreatment.Subsequently,Partial Least Squares(PLS)is applied to select the informative wavelengths from the preprocessed spectra.For modeling phase,the combination optimal strategy,support vector machine(SVM)combined with random forest(RF),is developed to establish classification models.The experimental results demonstrate that the combination optimal model can achieve TPR,FPR,Precision,Recall,F1,and AUC of 83.5%,2.30%,79.7%,83.5%,81.6%,and 94.7%for classifying fabrics contaminated by various food residuals.With respect to the classification of liquid and fabric types,the combination optimalmodel also yields satisfactory classification performance.In future work,wewill expand the types of liquid,and make appropriate adjustment to algorithms for improving the robustness of classification models.This research may play a positive role in the construction of a harmonious society.

The Rational Combination Strategy of Immunomodulatory Latency Reversing Agents and Novel Immunotherapy to Achieve HIV-1 Cure

Human immunodeficiency virus(HIV)-1 infection creates a persistent latent reservoir even after antiretroviral therapy,which is the main barrier to HIV cure.One of the most explored strategies is the use of latent reversal agents(LRAs)to activate HIV latent reservoirs,followed by immunotherapy to remove infected cells.Immunomodulatory LRAs have the dual advantage of activating viral latency and promoting immune cell elimination of HIV-infected cells.The emergence of novel immunotherapies has also enhanced the possibility ofHIV clearance.Here we review the activity and potential mechanisms of immunomodulatory agonists and immunotherapies.The possible combinational strategies to achieve HIV functional cure and the problems encountered using this approach are discussed.

Building on the backbone of CD47-based therapy in cancer:Combination strategies,mechanisms,and future perspectives

Described as a“don't eat me”signal,CD47 becomes a vital immune checkpoint in cancer.Its interaction with signal regulatory protein alpha(SIRPa)prevents macrophage phagocytosis.In recent years,a growing body of evidences have unveiled that CD47-based combination therapy exhibits a superior anti-cancer effect.Latest clinical trials about CD47 have adopted the regimen of collaborating with other therapies or developing CD47-directed bispecific antibodies,indicating the combination strategy as a general trend of the future.In this review,clinical and preclinical cases about the current combination strategies targeting CD47 are collected,their underlying mechanisms of action are discussed,and ideas from future perspectives are shared.

CD47 blockade improves the therapeutic effect of osimertinib in non-small cell lung cancer

The third-generation epidermal growth factor receptor (EGFR) inhibitor osimertinib (OSI) has been approved as the first-line treatment for EGFR-mutant non-small cell lung cancer (NSCLC). This study aims to explore a rational combination strategy for enhancing the OSI efficacy. In this study, OSI induced higher CD47 expression, an important anti-phagocytic immune checkpoint, via the NF-κB pathway in EGFR-mutant NSCLC HCC827 and NCI-H1975 cells. The combination treatment of OSI and the anti-CD47 antibody exhibited dramatically increasing phagocytosis in HCC827 and NCI-H1975 cells, which highly relied on the antibody-dependent cellular phagocytosis effect. Consistently, the enhanced phagocytosis index from combination treatment was reversed in CD47 knockout HCC827 cells. Meanwhile, combining the anti-CD47 antibody significantly augmented the anticancer effect of OSI in HCC827 xenograft mice model. Notably, OSI induced the surface exposure of “eat me” signal calreticulin and reduced the expression of immune-inhibitory receptor PD-L1 in cancer cells, which might contribute to the increased phagocytosis on cancer cells pretreated with OSI. In summary, these findings suggest the multidimensional regulation by OSI and encourage the further exploration of combining anti-CD47 antibody with OSI as a new strategy to enhance the anticancer efficacy in EGFR-mutant NSCLC with CD47 activation induced by OSI.

Mission-oriented cooperative 3D path planning for modular solar-powered aircraft with energy optimization

Modular Solar-Powered Aircraft(M-SPA)is a kind of High-Altitude Long-Endurance(HALE)aircraft which exploits the mission advantage of swarm UAV and the HALE advantage of large aspect-ratio SPA.M-SPA’s separated mode and combined mode give it the potential to maximize the mission efficiency with limited solar energy.In this paper,firstly,oriented by the mission of maximizing the cruise area,the overall design of the M-SPA is modeled,including the energy model,the aerodynamic model and the flight environment settings.Secondly,by analyzing the energy consumption of the flight modes,we design a multi-phase flight mission strategy.Then,a 24-hour three-dimensional(3D)flight profile of the M-SPA is optimized,including the sub-SPA cooperative path planning in the separation mode.Finally,inspired by the Traveling Salesman Problem(TSP),an improved Ant Colony Algorithm(ACA)is exploited to find the optimal path for each sub-SPA,which is further developed into a dynamic separation and combination scheme for the M-SPA.The simulation results show that the mission performance of the M-SPA outperforms that of the conventional SPA,and explicitly,the mission coverage of the M-SPA is slightly less than a linear increase under comparable simulation conditions.