Synthesis and photoluminescence properties of polymer chains based on pre-designed heterometallic Al4Ln4 molecular rings.

Presented herein is a series of chain compounds based on pre-designed heterometallic aluminum-lanthanide (Al-Ln) Al4Ln4 molecular rings. Their photoluminescence quantum yield (PLQY) with Eu3+ (30.41%) and Tb3+ (41.44%) is at a high level among the clusters containing four Ln ions. This study significantly extends the family of Al-Ln heterometallic clusters and demonstrates the synergistic effect of heterometallic ions in enhancing their properties.

A Dual-Adversarial Model for Cross-Time and Cross-Subject Cognitive Workload Decoding.

Electroencephalogram (EEG) signals are widely utilized in the field of cognitive workload decoding (CWD). However, when the recognition scenario is shifted from subject-dependent to subject-independent or spans a long period, the accuracy of CWD deteriorates significantly. Current solutions are either dependent on extensive training datasets or fail to maintain clear distinctions between categories, additionally lacking a robust feature extraction mechanism. In this paper, we tackle these issues by proposing a Bi-Classifier Joint Domain Adaptation (BCJDA) model for EEG-based cross-time and cross-subject CWD. Specifically, the model consists of a feature extractor, a domain discriminator, and a Bi-Classifier, containing two sets of adversarial processes for domain-wise alignment and class-wise alignment. In the adversarial domain adaptation, the feature extractor is forced to learn the common domain features deliberately. The Bi-Classifier also fosters the feature extractor to retain the category discrepancies of the unlabeled domain, so that its classification boundary is consistent with the labeled domain. Furthermore, different adversarial distance functions of the Bi-Classifier are adopted and evaluated in this model. We conduct classification experiments on a publicly available BCI competition dataset for recognizing low, medium, and high cognitive workload levels. The experimental results demonstrate that our proposed BCJDA model based on cross-gradient difference maximization achieves the best performance.

Network-based approach for drug repurposing against mpox.

The current outbreak of mpox presents a significant threat to the global community. However, the lack of mpox-specific drugs necessitates the identification of additional candidates for clinical trials. In this study, a network medicine framework was used to investigate poxviruses-human interactions to identify potential drugs effective against the mpox virus (MPXV). The results indicated that poxviruses preferentially target hubs on the human interactome, and that these virally-targeted proteins (VTPs) tend to aggregate together within specific modules. Comorbidity analysis revealed that mpox is closely related to immune system diseases. Based on predicted drug-target interactions, 268 drugs were identified using the network proximity approach, among which 23 drugs displaying the least side-effects and significant proximity to MPXV were selected as the final candidates. Lastly, specific drugs were explored based on VTPs, differentially expressed proteins, and intermediate nodes, corresponding to different categories. These findings provide novel insights that can contribute to a deeper understanding of the pathogenesis of MPXV and development of ready-to-use treatment strategies based on drug repurposing.

Global pattern and determinant for interaction of seasonal influenza viruses.

BACKGROUND: The prevalence of different types/subtypes varies across seasons and countries for seasonal influenza viruses, indicating underlying interactions between types/subtypes. The global interaction patterns and determinants for seasonal influenza types/subtypes need to be explored. METHODS: Influenza epidemiological surveillance data, as well as multidimensional data that include population-related, environment-related, and virus-related factors from 55 countries worldwide were used to explore type/subtype interactions based on Spearman correlation coefficient. The machine learning method Extreme Gradient Boosting (XGBoost) and interpretable framework SHapley Additive exPlanation (SHAP) were utilized to quantify contributing factors and their effects on interactions among influenza types/subtypes. Additionally, causal relationships between types/subtypes were also explored based on Convergent Cross-mapping (CCM). RESULTS: A consistent globally negative correlation exists between influenza A/H3N2 and A/H1N1. Meanwhile, interactions between influenza A (A/H3N2, A/H1N1) and B show significant differences across countries, primarily influenced by population-related factors. Influenza A has a stronger driving force than influenza B, and A/H3N2 has a stronger driving force than A/H1N1. CONCLUSION: The research elucidated the globally complex and heterogeneous interaction patterns among influenza type/subtypes, identifying key factors shaping their interactions. This sheds light on better seasonal influenza prediction and model construction, informing targeted prevention strategies and ultimately reducing the global burden of seasonal influenza.

Protective Effect of Panax notoginseng Extract Fermented by Four Different Saccharomyces cerevisiae Strains on H2O2 Induced Oxidative Stress in Skin Fibroblasts.

Purpose: To produce Panax notoginseng extract as a cosmetic ingredient through Saccharomyces cerevisiae fermentation. Methods: We first compared the total sugar content, polysaccharide content, reducing sugar content, total phenolic content, total saponin content, DPPH free radical, ABTS free radical, hydroxyl free radical scavenging ability and ferric reducing antioxidant power (FRAP) of Panax notoginseng fermented extract (pnFE) and unfermented extract (pnWE). Their potential correlations were analyzed by Pearson's correlation analysis. Then, the oxidative stress model of H2O2-induced MSFs was used to evaluate the effects of different pnFE on MSF viability, reactive oxygen species (ROS), malondialdehyde (MDA), and the activities of catalase (CAT), glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD) to explore their protective effects on MSFs subjected to H2O2-induced cellular oxidative damage. Finally, their safety and stability were evaluated by using the red blood cell (RBC) test and hen's egg test-chorioallantoic membrane (HET-CAM) assay, and changes in pH and content of soluble solids, respectively. Results: Compared with pnWE, pnFE has more active substances and stronger antioxidant capacity. In addition, pnFE has a protective effect on H2O2-induced oxidative stress in MSFs with appropriate safety and stability. Conclusion: PnFE has broad application prospects in the field of cosmetics.

Spatiotemporal genotype replacement of H5N8 avian influenza viruses contributed to H5N1 emergence in 2021/2022 panzootic.

Since 2020, clade 2.3.4.4b highly pathogenic avian influenza H5N8 and H5N1 viruses have swept through continents, posing serious threats to the world. Through comprehensive analyses of epidemiological, genetic, and bird migration data, we found that the dominant genotype replacement of the H5N8 viruses in 2020 contributed to the H5N1 outbreak in the 2021/2022 wave. The 2020 outbreak of the H5N8 G1 genotype instead of the G0 genotype produced reassortment opportunities and led to the emergence of a new H5N1 virus with G1's HA and MP genes. Despite extensive reassortments in the 2021/2022 wave, the H5N1 virus retained the HA and MP genes, causing a significant outbreak in Europe and North America. Furtherly, through the wild bird migration flyways investigation, we found that the temporal-spatial coincidence between the outbreak of the H5N8 G1 virus and the bird autumn migration may have expanded the H5 viral spread, which may be one of the main drivers of the emergence of the 2020-2022 H5 panzootic.IMPORTANCESince 2020, highly pathogenic avian influenza (HPAI) H5 subtype variants of clade 2.3.4.4b have spread across continents, posing unprecedented threats globally. However, the factors promoting the genesis and spread of H5 HPAI viruses remain unclear. Here, we found that the spatiotemporal genotype replacement of H5N8 HPAI viruses contributed to the emergence of the H5N1 variant that caused the 2021/2022 panzootic, and the viral evolution in poultry of Egypt and surrounding area and autumn bird migration from the Russia-Kazakhstan region to Europe are important drivers of the emergence of the 2020-2022 H5 panzootic. These findings provide important targets for early warning and could help control the current and future HPAI epidemics.

Variation in synonymous evolutionary rates in the SARS-CoV-2 genome.

Introduction: Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Influential variants and mutants of this virus continue to emerge, and more effective virus-related information is urgently required for identifying and predicting new mutants. According to earlier reports, synonymous substitutions were considered phenotypically silent; thus, such mutations were frequently ignored in studies of viral mutations because they did not directly cause amino acid changes. However, recent studies have shown that synonymous substitutions are not completely silent, and their patterns and potential functional correlations should thus be delineated for better control of the pandemic. Methods: In this study, we estimated the synonymous evolutionary rate (SER) across the SARS-CoV-2 genome and used it to infer the relationship between the viral RNA and host protein. We also assessed the patterns of characteristic mutations found in different viral lineages. Results: We found that the SER varies across the genome and that the variation is primarily influenced by codon-related factors. Moreover, the conserved motifs identified based on the SER were found to be related to host RNA transport and regulation. Importantly, the majority of the existing fixed-characteristic mutations for five important virus lineages (Alpha, Beta, Gamma, Delta, and Omicron) were significantly enriched in partially constrained regions. Discussion: Taken together, our results provide unique information on the evolutionary and functional dynamics of SARS-CoV-2 based on synonymous mutations and offer potentially useful information for better control of the SARS-CoV-2 pandemic.

Enhancement of Human Epidermal Cell Defense against UVB Damage by Fermentation of Passiflora edulis Sims Peel with Saccharomyces cerevisiae.

The processing of Passiflora edulis Sims results in large amounts of wasted peel resources and environmental pollution. In order to improve the utilisation of natural plant resources and economic benefits, this study uses Saccharomyces cerevisiae to ferment Passiflora edulis Sims peel to obtain Passiflora edulis Sims peel fermentation broth (PF). The content of active substances in unfermented Passiflora edulis Sims peel water extract (PW) and PF is then determined, as well as their in vitro antioxidant capacity. The protective effects of PF and PW on UVB-induced skin inflammation and skin barrier damage in human immortalised epidermal keratinocytes (HaCaT) cells (including cell viability, ROS, HO-1, NQO1, IL-1ß, IL-8, TNF-α, KLK-7, FLG, AQP3 and Caspase 14 levels) are investigated. Studies have shown that PF enhances the content of active substances more effectively compared to PW, showing a superior ability to scavenge free radical scavenging and antioxidants. PW and PF can effectively scavenge excess intracellular ROS, reduce the cellular secretion of pro-inflammatory factors, regulate the content of skin barrier-related proteins and possibly respond to UVB-induced cell damage by inhibiting the activation of the PI3K/AKT/mTOR signalling pathway. Studies have shown that both PW and PF are safe and non-irritating, with PF exploiting the efficacy of Passiflora edulis Sims peel more significantly, providing a superior process for the utilisation of Passiflora edulis Sims waste. At the same time, PF can be developed and used as a functional protective agent against ultraviolet damage to the skin, thereby increasing the value of the use of Passiflora edulis Sims waste.

The role of gut microbiome in inflammatory bowel disease diagnosis and prognosis.

Inflammatory bowel disease (IBD) is a chronic immune-mediated intestinal disease consisting of ulcerative colitis and Crohn's disease. Inflammatory bowel disease is believed to be developed as a result of interactions between environmental, immune-mediated and microbial factors in a genetically susceptible host. Recent advances in high-throughput sequencing technologies have aided the identification of consistent alterations of the gut microbiome in patients with IBD. Preclinical and murine models have also shed light on the role of beneficial and pathogenic bacteria in IBD. These findings have stimulated interest in development of non-invasive microbial and metabolite biomarkers for predicting disease risk, disease progression, recurrence after surgery and responses to therapeutics. This review briefly summarizes the current evidence on the role of gut microbiome in IBD pathogenesis and mainly discusses the latest literature on the utilization of potential microbial biomarkers in disease diagnosis and prognosis.

A network view of human immune system and virus-human interaction.

The immune system is highly networked and complex, which is continuously changing as encountering old and new pathogens. However, reductionism-based researches do not give a systematic understanding of the molecular mechanism of the immune response and viral pathogenesis. Here, we present HUMPPI-2022, a high-quality human protein-protein interaction (PPI) network, containing > 11,000 protein-coding genes with > 78,000 interactions. The network topology and functional characteristics analyses of the immune-related genes (IRGs) reveal that IRGs are mostly located in the center of the network and link genes of diverse biological processes, which may reflect the gene pleiotropy phenomenon. Moreover, the virus-human interactions reveal that pan-viral targets are mostly hubs, located in the center of the network and enriched in fundamental biological processes, but not for coronavirus. Finally, gene age effect was analyzed from the view of the host network for IRGs and virally-targeted genes (VTGs) during evolution, with IRGs gradually became hubs and integrated into host network through bridging functionally differentiated modules. Briefly, HUMPPI-2022 serves as a valuable resource for gaining a better understanding of the composition and evolution of human immune system, as well as the pathogenesis of viruses.

Two Laminaria japonica Fermentation Broths Alleviate Oxidative Stress and Inflammatory Response Caused by UVB Damage: Photoprotective and Reparative Effects.

UVB radiation can induce oxidative stress and inflammatory response in human epidermal cells. We establish a UVB-induced damage model of human immortalized epidermal keratinocytes (HaCaT) to explore the protective and reparative effects of Laminaria japonica on UVB-damaged epidermal inflammation after fermentation by white Ganoderma lucidum (Curtis) P. Karst and Saccharomyces cerevisiae. Compared with unfermented Laminaria japonica, fermented Laminaria japonica possesses stronger in vitro free radical scavenging ability. Laminaria japonica white Ganoderma lucidum fermentation broth (LJ-G) and Laminaria japonica rice wine yeast fermentation broth (LJ-Y) can more effectively remove excess reactive oxygen species (ROS) in cells and increase the content of the intracellular antioxidant enzymes heme oxygenase-1 (HO-1) and NAD(P)H quinone oxidoreductase 1 (NQO-1). In addition, fermented Laminaria japonica effectively reduces the content of pro-inflammatory factors ILs, TNF-α and MMP-9 secreted by cells. The molecular research results show that fermented Laminaria japonica activates the Nrf2 signaling pathway, increases the synthesis of antioxidant enzymes, inhibits the gene expression levels of pro-inflammatory factors, and alleviates cellular oxidative stress and inflammatory response caused by UVB radiation. Based on the above results, we conclude that fermented Laminaria japonica has stronger antioxidant and anti-inflammatory activity than unfermented Laminaria japonica, possesses good safety, and can be developed and used as a functional inflammation reliever. Fermented Laminaria japonica polysaccharide has a more slender morphological structure and more rockulose, with better moisturizing and rheological properties.

Subtypes specified environmental dependence of seasonal influenza virus.

Understanding the role of meteorological factors in the transmission dynamics of respiratory infectious diseases remains challenging. Our study was to comprehensively investigate the nonlinear effects of environmental factors on influenza transmission, based on multi-region surveillance data from mainland China. An approach related to time-varying reproduction number (Rt) was proposed, which extracts the environment-related components from Rt to estimate the relationship between environmental factors and influenza transmission based on a mixed-effects regression model. Nonlinear relationships for absolute humidity (the lowest transmission was observed at absolute humidity of 12 g/m3) and mean temperature (the lowest transmission was observed at the mean temperature of 18 °C) with influenza transmission were observed. Influenza transmission holds almost constant with the average precipitation below 1 mm or sunshine hour below 9 h/day, but increases for the precipitation and decreases for the sunshine hour afterward. The environmental dependence varies across subtypes: A(H3N2) maintains relatively higher transmission in high temperature and humidity conditions, compared with other influenza subtypes. Overall, the subtypes specified environmental dependence of influenza transmission could explain 23.1 %, 29.2 % and 27.1 % of the variations for A(H1N1)pdm09, A(H3N2) and B-lineage in China. The projected seasonal transmission rates based on our approach could be used as a valuable seasonal proxy to model the influenza dynamics under various meteorological spaces. Finally, our approach is also applicable to obtain novel insights into the impact of environmental factors on other respiratory infectious diseases.

Transmission Patterns of Seasonal Influenza in China between 2010 and 2018.

Background Understanding the transmission source, pattern, and mechanism of infectious diseases is essential for targeted prevention and control. Though it has been studied for many years, the detailed transmission patterns and drivers for the seasonal influenza epidemics in China remain elusive. Methods In this study, utilizing a suite of epidemiological and genetic approaches, we analyzed the updated province-level weekly influenza surveillance, sequence, climate, and demographic data between 1 April 2010 and 31 March 2018 from continental China, to characterize detailed transmission patterns and explore the potential initiating region and drivers of the seasonal influenza epidemics in China. Results An annual cycle for influenza A(H1N1)pdm09 and B and a semi-annual cycle for influenza A(H3N2) were confirmed. Overall, the seasonal influenza A(H3N2) virus caused more infection in China and dominated the summer season in the south. The summer season epidemics in southern China were likely initiated in the "Lingnan" region, which includes the three most southern provinces of Hainan, Guangxi, and Guangdong. Additionally, the regions in the south play more important seeding roles in maintaining the circulation of seasonal influenza in China. Though intense human mobility plays a role in the province-level transmission of influenza epidemics on a temporal scale, climate factors drive the spread of influenza epidemics on both the spatial and temporal scales. Conclusion The surveillance of seasonal influenza in the south, especially the "Lingnan" region in the summer, should be strengthened. More broadly, both the socioeconomic and climate factors contribute to the transmission of seasonal influenza in China. The patterns and mechanisms revealed in this study shed light on the precise forecasting, prevention, and control of seasonal influenza in China and worldwide.

The anti-aging activity of Lycium barbarum polysaccharide extracted by yeast fermentation: In vivo and in vitro studies.

Lycium barbarum polysaccharide (LBP) is an important active substance in Lycium barbarum. In this study, LBP was extracted by the hot water method and yeast fermentation method to obtain products called LBP-W and LBP-Y, respectively. Both LBPs have a strong ability to scavenge DPPH, hydroxyl, and superoxide anion free radicals and have a total antioxidant capacity. Both LBPs prolong the lifespan of C. elegans under normal conditions, oxidative stress and heat stress and do not affect fertility, LBPs could prolong the lifespan of C. elegans by upregulating the expression of daf-16, sod-3 and hsp-16.2 genes, and LBP-Y is more efficacious. The molecular weight of the LBPs was characterized by gel permeation chromatography (GPC), and the results showed that LBP-Y is smaller and more uniform than LBP-W. The skin penetration experiment showed that the absorption effect of LBP-Y is better than that of LBP-W. These lines of evidence suggest that the yeast fermentation extraction of LBP produces better antioxidant and anti-aging effects than those obtained with the traditional hot water extraction, which is more suitable for obtaining raw materials with anti-aging functions that can potentially be used in the food and cosmetic industries.

The effectiveness of governmental nonpharmaceutical interventions against COVID-19 at controlling seasonal influenza transmission: an ecological study.

BACKGROUND: A range of strict nonpharmaceutical interventions (NPIs) were implemented in many countries to combat the coronavirus 2019 (COVID-19) pandemic. These NPIs may also be effective at controlling seasonal influenza virus infections, as influenza viruses have the same transmission path as severe acute respiratory syndrome coronavirus 2. The aim of this study was to evaluate the effects of different NPIs on the control of seasonal influenza. METHODS: Data for 14 NPIs implemented in 33 countries and the corresponding influenza virological surveillance data were collected. The influenza suppression index was calculated as the difference between the influenza positivity rate during its period of decline from 2019 to 2020 and during the influenza epidemic seasons in the previous 9 years. A machine learning model was developed using an extreme gradient boosting tree regressor to fit the NPI and influenza suppression index data. The SHapley Additive exPlanations tool was used to characterize the NPIs that suppressed the transmission of influenza. RESULTS: Of all NPIs tested, gathering limitations had the greatest contribution (37.60%) to suppressing influenza transmission during the 2019-2020 influenza season. The three most effective NPIs were gathering limitations, international travel restrictions, and school closures. For these three NPIs, their intensity threshold required to generate an effect were restrictions on the size of gatherings less than 1000 people, ban of travel to all regions or total border closures, and closing only some categories of schools, respectively. There was a strong positive interaction effect between mask-wearing requirements and gathering limitations, whereas merely implementing a mask-wearing requirement, and not other NPIs, diluted the effectiveness of mask-wearing requirements at suppressing influenza transmission. CONCLUSIONS: Gathering limitations, ban of travel to all regions or total border closures, and closing some levels of schools were found to be the most effective NPIs at suppressing influenza transmission. It is recommended that the mask-wearing requirement be combined with gathering limitations and other NPIs. Our findings could facilitate the precise control of future influenza epidemics and other potential pandemics.

Meta-Transfer Learning Through Hard Tasks.

Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few labeled samples are available. As deep neural networks (DNNs) tend to overfit using a few samples only, typical meta-learning models use shallow neural networks, thus limiting its effectiveness. In order to achieve top performance, some recent works tried to use the DNNs pre-trained on large-scale datasets but mostly in straight-forward manners, e.g., (1) taking their weights as a warm start of meta-training, and (2) freezing their convolutional layers as the feature extractor of base-learners. In this paper, we propose a novel approach called meta-transfer learning (MTL), which learns to transfer the weights of a deep NN for few-shot learning tasks. Specifically, meta refers to training multiple tasks, and transfer is achieved by learning scaling and shifting functions of DNN weights (and biases) for each task. To further boost the learning efficiency of MTL, we introduce the hard task (HT) meta-batch scheme as an effective learning curriculum of few-shot classification tasks. We conduct experiments for five-class few-shot classification tasks on three challenging benchmarks, miniImageNet, tieredImageNet, and Fewshot-CIFAR100 (FC100), in both supervised and semi-supervised settings. Extensive comparisons to related works validate that our MTL approach trained with the proposed HT meta-batch scheme achieves top performance. An ablation study also shows that both components contribute to fast convergence and high accuracy.

Surface modification of cellulose nanocrystals via SI-AGET ATRP and application in waterborne coating for removing of formaldehyde.

The hazardous indoor air pollutants of formaldehyde (HCHO) are harmful for human health. Nowadays, it is important to design and fabricate green and efficient HCHO removal materials for HCHO removal from polluted indoor air. In this manuscript, cellulose nanocrystals (CNCs) as green nanomaterials were successfully surface-initiated by 2-(methacryloyloxy)ethyl acetoacetate (MEAA) as functional monomer via surface-initiated Activator Generated by Electron Transfer Atom Transfer Radical Polymerization (SI-AGET ATRP) for the application in removal of HCHO. The employment of CNCs/Poly(2-(methacryloyloxy)ethyl acetoacetate) (CNCs@PMEAA) as nanocomposites were further implanted self-healing waterborne coating for an effective way to remove HCHO. From the result, the HCHO removal efficiency reached 97.5% of CNCs@PMEAA-type coating within 300 min at room temperature, which was much higher than that of the conventional coating (82.8%). This study provides some promising green methods for designing nanocomposite's waterborne coating to remove HCHO at room temperature.

Retracted: Phenotype of Vascular Smooth Muscle Cells (VSMCs) Is Regulated by miR-29b by Targeting Sirtuin 1.

Our paper "Phenotype of Vascular Smooth Muscle Cells (VSMCs) Is Regulated by miR-29b by Targeting Sirtuin 1" has been accepted by Medical Science Monitor, we found that the article has a little problem, we decide to withdraw our manuscript from the journal because of the rigorous attitude towards scientific research. Reference: Qian-ru Sun, Xiong Zhang, Kun Fang. Phenotype of Vascular Smooth Muscle Cells (VSMCs) Is Regulated by miR-29b by Targeting Sirtuin 1. Med Sci Monit, 2018; 24: 6599-6607. DOI: 10.12659/MSM.910068.

Generating Face Images With Attributes for Free.

With superhuman-level performance of face recognition, we are more concerned about the recognition of fine-grained attributes, such as emotion, age, and gender. However, given that the label space is extremely large and follows a long-tail distribution, it is quite expensive to collect sufficient samples for fine-grained attributes. This results in imbalanced training samples and inferior attribute recognition models. To this end, we propose the use of arbitrary attribute combinations, without human effort, to synthesize face images. In particular, to bridge the semantic gap between high-level attribute label space and low-level face image, we propose a novel neural-network-based approach that maps the target attribute labels to an embedding vector, which can be fed into a pretrained image decoder to synthesize a new face image. Furthermore, to regularize the attribute for image synthesis, we propose to use a perceptual loss to make the new image explicitly faithful to target attributes. Experimental results show that our approach can generate photorealistic face images from attribute labels, and more importantly, by serving as augmented training samples, these images can significantly boost the performance of attribute recognition model. The code is open-sourced at this link.

Vascular endothelial growth factor-loaded poly-lactic-co-glycolic acid nanoparticles with controlled release protect the dopaminergic neurons in Parkinson's rats.

Vascular endothelial growth factor (VEGF) had neuroprotective effects on dopaminergic (DA) neurons. In order to overcome the gastrointestinal digestion and bioaccessibility, VEGF was encapsulated with poly-lactic-co-glycolic acid nanospheres (NS) in order to prevent the VEGF degradation until its release. The caudal administration of VEGF and NS encapsulated VEGF at different doses (1.0, 10.0, and 100.0 ng/ml) on the rats with Parkinson's disease lesion was evaluated. Intravenous injected VEGF at the dose of 1 ng/ml displayed the strongest neuroprotective effect than other groups as well as the stereotaxic group. The NS encapsulated with VEGF can pass through blood-brain barrier and protect the DA neurons. There was no significant difference between intravenous injection method and stereotaxic method, while the first method is simpler and convenient. Injection of NS encapsulated with VEGF may become a valuable neurorescuing therapeutic approach for Parkinson's disease.