Back to the drawing board:Overview of the next generation of combination therapy for inflammatory bowel disease

Inflammatory bowel disease(IBD)is entering a potentially new era of combined therapeutics.Triantafillidis et al provide an insightful review of the current state of combination therapy,with a focus on the use of a combined biologic and immunomodulator,as well as emerging data on the future potential of dual-biologic therapy(DBT).While current evidence for DBT is limited,encouraging safety profiles and ongoing trials suggest a brighter future for this approach.The importance of controlled trials should be stressed in establishing new treatment paradigms.Ongoing prospective randomized trials of DBT and perhaps future combinations of biologics and small molecule therapies will hopefully guide the next generation of IBD care.

Combination treatment of inflammatory bowel disease:Present status and future perspectives

The treatment of patients with inflammatory bowel disease(IBD),especially those with severe or refractory disease,represents an important challenge for the clinical gastroenterologist.It seems to be no exaggeration to say that in these patients,not only the scientific background of the gastroenterologist is tested,but also the abundance of“gifts”that he should possess(insight,intuition,determ-ination,ability to take initiative,etc.)for the successful outcome of the treatment.In daily clinical practice,depending on the severity of the attack,IBD is treated with one or a combination of two or more pharmaceutical agents.These combin-ations include not only the first-line drugs(e.g.,mesalazine,corticosteroids,antibiotics,etc)but also second-and third-line drugs(immunosuppressants and biologic agents).It is a fact that despite the significant therapeutic advances there is still a significant percentage of patients who do not satisfactorily respond to the treatment applied.Therefore,a part of these patients are going to surgery.In recent years,several small-size clinical studies,reviews,and case reports have been published combining not only biological agents with other drugs(e.g.,immunosuppressants or corticosteroids)but also the combination of two biologi-cal agents simultaneously,especially in severe cases.In our opinion,it is at least a strange(and largely unexplained)fact that we often use combinations of drugs in a given patient although studies comparing the simultaneous administration of two or more drugs with monotherapy are very few.As mentioned above,there is a timid tendency in the literature to combine two biological agents in severe cases unresponsive to the applied treatment or patients with severe extraintestinal manifestations.The appropriate dosage,the duration of the administration,the suitable timing for checking the clinical and laboratory outcome,as well as the treatment side-effects,should be the subject of intense clinical research shortly.In this editorial,we attempt to summarize the existing data regarding the already applied combination therapies and to humbly formulate thoughts and suggestions for the future application of the combination treatment of biological agents in a well-defined category of patients.We suggest that the application of biomarkers and artificial intelligence could help in establishing new forms of treatment using the available modern drugs in patients with IBD resistant to treatment.

Erlotinib combination with a mitochondria-targeted ubiquinone effectively suppresses pancreatic cancer cell survival

BACKGROUND Pancreatic cancer is a leading cause of cancer-related deaths.Increased activity of the epidermal growth factor receptor(EGFR)is often observed in pancreatic cancer,and the small molecule EGFR inhibitor erlotinib has been approved for pancreatic cancer therapy by the food and drug administration.Nevertheless,erlotinib alone is ineffective and should be combined with other drugs to improve therapeutic outcomes.We previously showed that certain receptor tyrosine kinase inhibitors can increase mitochondrial membrane potential(Δψm),facilitate tumor cell uptake ofΔψm-sensitive agents,disrupt mitochondrial homeostasis,and subsequently trigger tumor cell death.Erlotinib has not been tested for this effect.AIM To determine whether erlotinib can elevateΔψm and increase tumor cell uptake ofΔψm-sensitive agents,subsequently triggering tumor cell death.METHODSΔψm-sensitive fluorescent dye was used to determine how erlotinib affectsΔψm in pancreatic adenocarcinoma(PDAC)cell lines.The viability of conventional and patient-derived primary PDAC cell lines in 2D-and 3D cultures was measured after treating cells sequentially with erlotinib and mitochondria-targeted ubiquinone(MitoQ),aΔψm-sensitive MitoQ.The synergy between erlotinib and MitoQ was then analyzed using SynergyFinder 2.0.The preclinical efficacy of the twodrug combination was determined using immune-compromised nude mice bearing PDAC cell line xenografts.RESULTS Erlotinib elevatedΔψm in PDAC cells,facilitating tumor cell uptake and mitochondrial enrichment ofΔψm-sensitive agents.MitoQ triggered caspase-dependent apoptosis in PDAC cells in culture if used at high doses,while erlotinib pretreatment potentiated low doses of MitoQ.SynergyFinder suggested that these drugs synergistically induced tumor cell lethality.Consistent with in vitro data,erlotinib and MitoQ combination suppressed human PDAC cell line xenografts in mice more effectively than single treatments of each agent.CONCLUSION Our findings suggest that a combination of erlotinib and MitoQ has the potential to suppress pancreatic tumor cell viability effectively.

A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.

A Comprehensive Survey on Deep Learning Multi-Modal Fusion:Methods,Technologies and Applications

Multi-modal fusion technology gradually become a fundamental task in many fields,such as autonomous driving,smart healthcare,sentiment analysis,and human-computer interaction.It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities.Under complex scenes,multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions.However,achieving outstanding performance is challenging because of equipment performance limitations,missing information,and data noise.This paper comprehensively reviews existing methods based onmulti-modal fusion techniques and completes a detailed and in-depth analysis.According to the data fusion stage,multi-modal fusion has four primary methods:early fusion,deep fusion,late fusion,and hybrid fusion.The paper surveys the three majormulti-modal fusion technologies that can significantly enhance the effect of data fusion and further explore the applications of multi-modal fusion technology in various fields.Finally,it discusses the challenges and explores potential research opportunities.Multi-modal tasks still need intensive study because of data heterogeneity and quality.Preserving complementary information and eliminating redundant information between modalities is critical in multi-modal technology.Invalid data fusion methods may introduce extra noise and lead to worse results.This paper provides a comprehensive and detailed summary in response to these challenges.

Towards trustworthy multi-modal motion prediction:Holistic evaluation and interpretability of outputs

Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning.This task is very complex,as the behaviour of road agents depends on many factors and the number of possible future trajectories can be consid-erable(multi-modal).Most prior approaches proposed to address multi-modal motion prediction are based on complex machine learning systems that have limited interpret-ability.Moreover,the metrics used in current benchmarks do not evaluate all aspects of the problem,such as the diversity and admissibility of the output.The authors aim to advance towards the design of trustworthy motion prediction systems,based on some of the re-quirements for the design of Trustworthy Artificial Intelligence.The focus is on evaluation criteria,robustness,and interpretability of outputs.First,the evaluation metrics are comprehensively analysed,the main gaps of current benchmarks are identified,and a new holistic evaluation framework is proposed.Then,a method for the assessment of spatial and temporal robustness is introduced by simulating noise in the perception system.To enhance the interpretability of the outputs and generate more balanced results in the proposed evaluation framework,an intent prediction layer that can be attached to multi-modal motion prediction models is proposed.The effectiveness of this approach is assessed through a survey that explores different elements in the visualisation of the multi-modal trajectories and intentions.The proposed approach and findings make a significant contribution to the development of trustworthy motion prediction systems for autono-mous vehicles,advancing the field towards greater safety and reliability.

Multi-dimension and multi-modal rolling mill vibration prediction model based on multi-level network fusion

Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction models do not consider the features contained in the data,resulting in limited improvement of model accuracy.To address these challenges,this paper proposes a multi-dimensional multi-modal cold rolling vibration time series prediction model(MDMMVPM)based on the deep fusion of multi-level networks.In the model,the long-term and short-term modal features of multi-dimensional data are considered,and the appropriate prediction algorithms are selected for different data features.Based on the established prediction model,the effects of tension and rolling force on mill vibration are analyzed.Taking the 5th stand of a cold mill in a steel mill as the research object,the innovative model is applied to predict the mill vibration for the first time.The experimental results show that the correlation coefficient(R^(2))of the model proposed in this paper is 92.5%,and the root-mean-square error(RMSE)is 0.0011,which significantly improves the modeling accuracy compared with the existing models.The proposed model is also suitable for the hot rolling process,which provides a new method for the prediction of strip rolling vibration.

Multi-modal knowledge graph inference via media convergence and logic rule

Media convergence works by processing information from different modalities and applying them to different domains.It is difficult for the conventional knowledge graph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledge graph inference less effective.To address the issue,an inference method based on Media Convergence and Rule-guided Joint Inference model(MCRJI)has been pro-posed.The authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link prediction.First,a multi-headed self-attention approach is used to obtain the attention of different media features of entities during semantic synthesis.Second,logic rules of different lengths are mined from knowledge graph to learn new entity representations.Finally,knowledge graph inference is performed based on representing entities that converge multi-media features.Numerous experimental results show that MCRJI outperforms other advanced baselines in using multi-media features and knowledge graph inference,demonstrating that MCRJI provides an excellent approach for knowledge graph inference with converged multi-media features.

Research on Multi-modal In-Vehicle Intelligent Personal Assistant Design

Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent personal assistants within the context of visual,auditory,and somatosensory interactions with drivers were discussed.Their impact on the driver’s psychological state through various modes such as visual imagery,voice interaction,and gesture interaction were explored.The study also introduced innovative designs for in-vehicle intelligent personal assistants,incorporating design principles such as driver-centricity,prioritizing passenger safety,and utilizing timely feedback as a criterion.Additionally,the study employed design methods like driver behavior research and driving situation analysis to enhance the emotional connection between drivers and their vehicles,ultimately improving driver satisfaction and trust.

Generative Multi-Modal Mutual Enhancement Video Semantic Communications

Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the research and applications of natural language processing across different modalities,our goal is to accurately extract frame-level semantic information from videos and ultimately transmit high-quality videos.Specifically,we propose a deep learning-basedMulti-ModalMutual Enhancement Video Semantic Communication system,called M3E-VSC.Built upon a VectorQuantized Generative AdversarialNetwork(VQGAN),our systemaims to leverage mutual enhancement among different modalities by using text as the main carrier of transmission.With it,the semantic information can be extracted fromkey-frame images and audio of the video and performdifferential value to ensure that the extracted text conveys accurate semantic information with fewer bits,thus improving the capacity of the system.Furthermore,a multi-frame semantic detection module is designed to facilitate semantic transitions during video generation.Simulation results demonstrate that our proposed model maintains high robustness in complex noise environments,particularly in low signal-to-noise ratio conditions,significantly improving the accuracy and speed of semantic transmission in video communication by approximately 50 percent.

Combination Activity of Standard Antituberculosis Drugs and Extracts of Medicinal Plants Commonly Used in Traditional Treatment of Tuberculosis in Uganda

Introduction: Resistance to antituberculosis drugs and adverse drug reactions remain the leading causes of tuberculosis therapeutic failure globally. Despite the increasing acceptance of medicinal plant use in combination with conventional antituberculosis drugs in treatment of tuberculosis (TB) in Uganda, there is paucity of knowledge on their combination effect. Aim: This research aimed to determine combination activity of standard antituberculosis drugs with extracts of Zanthoxylum leprieurii Guill. & Perr. and Rubia cordifolia L., the two common antituberculosis medicinal plants in Uganda, against pansensitive (H37Rv) and multi-drug resistant (MDR) Mycobacterium tuberculosis strains. Materials and Methods: Two reference MTB strains (H37Rv and MDR strain) were inoculated on Middlebrook 7H11 medium containing a combination of standard antituberculosis drugs and methanol extracts of Z. leprieurii and R. cordifolia at varying concentrations. The number of colonies on the plates was observed and counted weekly for up to 8 weeks. In vitro combination activity was determined using proportion method. Mean percentage inhibition was calculated for the reduction of number of colonies on drug-extract combination medium in relation to drug-extract-free control medium. Results: Drug-extract combinations showed good combination activity against Mycobacterium tuberculosis strains when compared with individual standard anti-TB drugs. This was more exhibited against MDR strain. There was however a reduction in percentage inhibition when extracts were combined with ethambutol and streptomycin against H37Rv strain. Conclusions: Zanthoxylum leprieurii and Rubia cordifolia in combination with standard anti-TB drugs exhibited increased in vitro activity against Mycobacterium tuberculosis, especially MDR-TB strain. This justifies the local use of these plants in traditional treatment of tuberculosis especially in resistant cases in Uganda.

A Bioequivalence Study of Empagliflozin/Metformin Fixed-Dose Combination in Healthy Subjects under Fasting Conditions

Background: This study evaluated the bioequivalence of empagliflozin 12.5 mg/metformin 1000 mg tablets compared to Synjardy® (Empagliflozin 12.5 mg/metformin 1000 mg) tablets in healthy male subjects under fasting conditions. Methods: This was a phase I, randomized, single-dose, two-period, two-sequence, crossover study to evaluate the bioequivalence (BE) profiles of two fixed-dose combinations (FDCs) of empagliflozin/metformin. Cmax, AUC0-t and AUC0-∞ from test and reference formulations were evaluated to access BE. The plasma concentrations were measured using a validated liquid chromatography-mass spectrometry (LC-MS/MS) method. Of the 24 subjects enrolled, 23 completed both periods of the study. The two formulations test and reference were considered bioequivalent if 90% confidence interval (CI) fell within 80.00% - 125.00% for Cmax, AUC0-t and AUC0-∞. Tolerability and safety were assessed throughout the study. Results: The pharmacokinetic (PK) parameters were similar between the test product (T) and reference product (R) Synjardy®. The 90% CI of the test/reference ratios of log-transformed PK parameters point estimates was Cmax: 89.87% (85.68% - 94.27%), AUC0-t: 87.91% (83.65% - 92.39%) and AUC0-∞: 87.16% (82.80% - 91.75%) to empagliflozin and Cmax: 92.19% (87.95% - 96.65%), AUC0-t: 91.38% (84.42% - 98.91%) and AUC0-∞: 93.78% (83.82% - 104.93%) to metformin respectively (90% CI for all PK parameters fell within 80.00% - 125.00%). Conclusion: Our results demonstrated BE between the test and reference formulations of oral tablets of empagliflozin 12.5 mg/metformin 1000 mg (FDC) in healthy male subjects under fasting conditions.

Enhancing metformin-induced tumor metabolism destruction by glucose oxidase for triple-combination therapy

Despite decades of laboratory and clinical trials,breast cancer remains the main cause of cancer-related disease burden in women.Considering the metabolism destruction effect of metformin(Met)and cancer cell starvation induced by glucose oxidase(GOx),after their efficient delivery to tumor sites,GOx and Met may consume a large amount of glucose and produce sufficient hydrogen peroxide in situ.Herein,a pH-responsive epigallocatechin gallate(EGCG)-conjugated low-molecular-weight chitosan(LC-EGCG,LE)nanoparticle(Met–GOx/Fe@LE NPs)was constructed.The coordination between iron ions(Fe3+)and EGCG in this nanoplatform can enhance the efficacy of chemodynamic therapy via the Fenton reaction.Met–GOx/Fe@LE NPs allow GOx to retain its enzymatic activity while simultaneously improving its stability.Moreover,this pH-responsive nanoplatform presents controllable drug release behavior.An in vivo biodistribution study showed that the intracranial accumulation of GOx delivered by this nanoplatform was 3.6-fold higher than that of the free drug.The in vivo anticancer results indicated that this metabolism destruction/starvation/chemodynamic triple-combination therapy could induce increased apoptosis/death of tumor cells and reduce their proliferation.This triple-combination therapy approach is promising for efficient and targeted cancer treatment.

Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

Combinational therapy with Myc decoy oligodeoxynucleotides encapsulated in nanocarrier and X-irradiation on breast cancer cells

The Myc gene is the essential oncogene in triple-negative breast cancer(TNBC).This study investigates the synergistic effects of combining Myc decoy oligodeoxynucleotides-encapsulated niosomes-selenium hybrid nanocarriers with X-irradiation exposure on the MDA-MB-468 cell line.Decoy and scramble ODNs for Myc transcription factor were designed and synthesized based on promoter sequences of the Bcl2 gene.The nanocarriers were synthesized by loading Myc ODNs and selenium into chitosan(Chi-Se-DEC),which was then encapsulated in niosome-nanocarriers(NISM@Chi-Se-DEC).FT-IR,DLS,FESEM,and hemolysis tests were applied to confirm its characterization and physicochemical properties.Moreover,cellular uptake,cellular toxicity,apoptosis,cell cycle,and scratch repair assays were performed to evaluate its anticancer effects on cancer cells.All anticancer assessments were repeated under X-ray irradiation conditions(fractionated 2Gy).Physicochemical characteristics of niosomes containing SeNPs and ODNs showed that it is synthesized appropriately.It revealed that the anticancer effect of NISM@Chi-Se-DEC can be significantly improved in combination with X-ray irradiation treatment.It can be concluded that NISM@Chi-Se-DEC nanocarriers have the potential as a therapeutic agent for cancer treatment,particularly in combination with radiation therapy and in-vivo experiments are necessary to confirm the efficacy of this nano-drug.

Evaluation of soil erosion vulnerability in Hubei Province of China using RUSLE model and combination weighting method

Soil erosion has been recognized as a critical environmental issue worldwide.While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective,there is a notable gap in understanding the intricate interplay between natural and socio-economic factors,especially in the context of spatial heterogeneity and nonlinear impacts of human-land interactions.To address this,our study evaluates the soil erosion vulnerability at a provincial scale,taking Hubei Province as a case study to explore the combined effects of natural and socio-economic factors.We developed an evaluation index system based on 15 indicators of soil erosion vulnerability:exposure,sensitivity,and adaptability.In addition,the combination weighting method was applied to determine index weights,and the spatial interaction was analyzed using spatial autocorrelation,geographical temporally weighted regression and geographical detector.The results showed an overall decreasing soil erosion intensity in Hubei Province during 2000 and 2020.The soil erosion vulnerability increased before 2000 and then.The areas with high soil erosion vulnerability were mainly confined in the central and southern regions of Hubei Province(Xiantao,Tianmen,Qianjiang and Ezhou)with obvious spatial aggregation that intensified over time.Natural factors(habitat quality index)had negative impacts on soil erosion vulnerability,whereas socio-economic factors(population density)showed substantial spatial variability in their influences.There was a positive correlation between soil erosion vulnerability and erosion intensity,with the correlation coefficients ranging from-0.41 and 0.93.The increase of slope was found to enhance the positive correlation between soil erosion vulnerability and intensity.

LociScan,a tool for screening genetic marker combinations for plant variety discrimination

To reduce the cost and increase the efficiency of plant genetic marker fingerprinting for variety discrimination,it is desirable to identify the optimal marker combinations.We describe a marker combination screening model based on the genetic algorithm(GA)and implemented in a software tool,Loci Scan.Ratio-based variety discrimination power provided the largest optimization space among multiple fitness functions.Among GA parameters,an increase in population size and generation number enlarged optimization depth but also calculation workload.Exhaustive algorithm afforded the same optimization depth as GA but vastly increased calculation time.In comparison with two other software tools,Loci Scan accommodated missing data,reduced calculation time,and offered more fitness functions.In large datasets,the sample size of training data exerted the strongest influence on calculation time,whereas the marker size of training data showed no effect,and target marker number had limited effect on analysis speed.

A Clinical Study to Assess the Effectiveness of Oral Combination Kit Therapy in Syndromic Management of Abnormal Vaginal Discharge (FEMINE Study) in Kinshasa, Democratic Republic of Congo

Background: Vaginal discharge is one of most common and nagging problems that women face. About 20% - 25% of women who visit gynecology department complain of vaginal discharge and leucorrhoea. An orally administered combination kit, containing 2 g secnidazole, 1 g azithromycin and 150 mg fluconazole (Azimyn FS Kit), has been successfully evaluated in clinical trials and used in several countries for management syndromic vaginal discharge due to infections. Methods: This is a longitudinal study which aimed to verify the clinical efficacy of the combined oral kit containing secnidazole, azithromycin and fluconazole (Azimyn FS Kit®) in the syndromic treatment of abnormal vaginal discharge in patients received in outpatient consultations in Kinshasa/DR Congo from March to September 2023. Results: Majority of patients had whitish vaginal discharge (51.6%) of average abundance (56.2%), accompanied by pruritus in 72.1% of cases, and dyspareunia in 23.5% of cases and hypogastralgia in 40.2% of cases. One week after treatment with the Azimyn FS® combined kit, at the greatest majority of patients (97.3%), abnormal vaginal discharge had decreased by more than 50% (84.1%). Two weeks after treatment with the Azimyn FS® combined kit, almost all patients (97.3%) no longer had abnormal vaginal discharge which had completely disappeared. Conclusion: A single dose of secnidazole, azithromycin and fluconazole in the form of an oral combi-kit (Azimyn FS Kit) has shown excellent therapeutic effectiveness in the syndromic treatment of abnormal vaginal discharge wherein patients were treated without diagnostic confirmation.

Pathogenicity Analysis on Magnaporthe oryzae from Hybrid Combination Wuyou 308

Eighteen blast isolates were obtained from hybrid combination Wuyou308 using the Magnaporthe oryzae pathogen isolation method.Race identification of these isolates was conducted based on seven Chinese blast differentials and 11 blast monogenic lines.The results indicated that the isolates were identified as the races of ZB13,ZB15 and ZC13,accounting for 66.67%,27.78%,5.56%,respectively,and the resistance genes including Pi-ta2 and Pi-sh,Pi-i were highly susceptible to these isolates,while the resistance genes like Pi-kh,Pi-1,Pi2,Pi-9 and Pi-50 showed good resistance to tested pathogens.All isolates were compatible to the original rice hybrid Wuyou308.Three isolates including GDHY-308-1401 were used for testing their pathogenicity to 45 local varieties.The results demonstrated that 13 varieties appeared highly susceptible to the tested isolates,accounting for 28.89%;two varieties appeared moderately susceptible to the tested isolates,accounting for 4.44%;30 varieties showed moderately/highly resistance,accounting for 66.67%.Among them,some of new hybrid combinations such as Wufengyou 9802,Wuyou 613,Wuyou 1179 showed good resistance to the inoculated strains,and they were recommended to be candidates in the rice region where Wuyou308 showed susceptibility.

Advances in extracellular vesicle-based combination therapies for spinal cord injury

Spinal cord injury is a severe insult to the central nervous system that causes persisting neurological deficits.The currently available treatments involve surgical,medical,and rehabilitative strategies.However,none of these techniques can markedly reverse neurological deficits.Recently,extracellular vesicles from various cell sources have been applied to different models of spinal cord injury,thereby generating new cell-free therapies for the treatment of spinal cord injury.However,the use of extracellular vesicles alone is still associated with some notable shortcomings,such as their uncertainty in targeting damaged spinal cord tissues and inability to provide structural support to damaged axons.Therefore,this paper reviews the latest combined strategies for the use of extracellular vesicle-based technology for spinal cord injury,including the combination of extracellular vesicles with nanoparticles,exogenous drugs and/or biological scaffold materials,which facilitate the targeting ability of extracellular vesicles and the combinatorial effects with extracellular vesicles.We also highlight issues relating to the clinical transformation of these extracellular vesicle-based combination strategies for the treatment of spinal cord injury.