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The hypoxic nature of solid tumors has severely negative effects on oxygen-based photodynamic therapy. In this study, we used porous Pt nanoparticles as a catalase (CAT) nanozyme, the second near-infrared (NIR-II) region photothermal transition agents (PTAs), and carriers of photosensitizer chlorin e6 (Ce6) to synthesize a composite nanosystem Pt-Ce6. In this system, Pt-Ce6 can continuously and stably decompose H2O2 into oxygen, thereby alleviating tumor hypoxia and improving the effect of photodynamic therapy (PDT). With 650 nm illumination, the reactive oxygen species (ROS) produced by Ce6 will decrease the mitochondrial membrane potential (MMP, ΔΨm) to release cytochrome c (Cyt-c) from the mitochondria into the cytoplasm, eventually leading to mitochondrial-mediated cellular apoptosis during the PDT process. In addition, Pt-Ce6 has good photothermal stability and high photothermal conversion efficiency (52.62%) in the NIR-II region. In U14 tumor-bearing mice, Pt-Ce6 completely suppressed tumor growth and recurrence under laser irradiation. Thus the nanocomposite shows excellent PDT/photothermal therapy (PTT) synergistic performance in vitro and in vivo.

In order to analyze the flow field characteristics of the split-stream rushing muffler, a theoretical model describing the velocity of the split streams is established and verified by the tracer test. For this new-principle muffler, the acoustic performance and the relationship between the velocity drop of the airflow and the pressure field are analyzed, also the structure optimization of the muffler is carried out based on the orthogonal test. Finally, a new muffler is fabricated based on the designing theory of this type of muffler for a prototype of diesel engine, and the comparative analyses are conducted compared with its original muffler. The results show that the establishment and analysis of the theoretical model for velocity during the split-streams rushing process are correct. In the frequency range of 0–1000 Hz, the average transmission loss of split-stream rushing muffler is better than that of the original muffler. While the speed of airflow is reduced by split-streams rushing, a certain pressure loss is caused at the same time, which is about 50% of total pressure loss of the muffler, and the average fluid resistance coefficient of the split-stream rushing process is 0.91. Compared to the original muffler of the sample engine, the average insertion loss of the optimized new muffler is increased by 61.2%. At inlet air velocity of 30 m/s, the pressure loss is reduced by 16.8%. The results provide a potential for practical engineering application of this new split-stream rushing muffler in future. © 2020 Institute of Noise Control Engineering

Additional file 3: Fig. S1. Analysis of simple sequence repeats (SSRs) in the cp genomes of three Amomum species. Fig. S2. Frequency of identified SSR motifs in different repeat class types. Fig. S3. Repeat sequences of three Amomum species. F, P, R, and C indicate the repeat types F (forward), P (palindrome), R (reverse), and C (complement), respectively. Fig. S4. ML tree based on ccsA sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S5. ML tree based on trnC-GCA_petN sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S6. ML tree based on ndhB_rps7 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S7. ML tree based on psaI_ycf4 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S8. ML tree based on rpl20 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S9. ML tree based on rpl33 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S10. ML tree based on rps3 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S11. ML tree based on rpoA sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S12. ML tree based on rps4 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S13. ML tree based on ndhD_1 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S14. ML tree based on ndhD_2 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S15. ML tree based on ITS sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S16. ML tree based on ITS2 sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S17. ML tree based on psbA-trnH sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S18. ML tree based on matK sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S19. ML tree based on rbcL sequences of Amomum species. This Bootstrap consensus tree was constructed by K2P model with 1000 bootstrap replicates. Numbers under the nodes indicate bootstrap probabilities. The cut off value for the condensed tree was 50%. Fig. S20. 3D-structure for the represented positively-selected genes with 1 substitution. Fig. S21. Phylogenetic tree constructed by NJ based on complete chloroplast genome. Numbers under the nodes indicate bootstrap probabilities. Our sequenced samples are marked in red. Species from different genuses are marked in different color on the nodes.

Additional file 2: Table S1.. Number of different SSR types detected in three Amomum species. Table S3. Species information of Ka/Ks. Table S5. ITS2 haplotypes of A. villosum and A. longiligulare from Sanger sequencing. Table S6. ITS2 reads of A. villosum and A. longiligulare from NGS data. Table S7. The primers and conditions for PCR.

This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.

Background: Subthreshold depression (SD) is considered to be the precursor stage of major depression, which is correlated with functional impairment and increased suicide rate. Although there are multiple therapies for the treatment of SD, the comparison and efficacy of various methods has yet to be evaluated. This study aimed to evaluate the efficacy of different therapies by performing a Bayesian network meta-analysis. Methods: We searched eight databases on April 3, 2021. Center for Epidemiologic Studies Depression Scale (CES-D), Beck Depression Inventory scale (BDI), the Patient Health Questionnaire-9 (PHQ-9), and the Kessler Screening Scale for Psychological Distress (K-6) were used as efficacy outcomes. This Bayesian network meta-analysis used a fixed-effects model. Findings: Twenty-one randomized controlled trials involving 5,048 participants were included in this study. The results suggested that electroacupuncture (MD −12.00, 95% CrI −15.00, −10.00), conventional acupuncture plus wheat-grain moxibustion (MD −9.70, 95% CrI −14.00, −5.30), and the Chinese traditional peripateticism pill plus group counseling (MD −9.00, 95% CrI −11.00, −6.70) had better efficacy than the control group (CG) in improving CES-D. For BDI outcome, bright light therapy (MD −9.70, 95% CrI −13.00, −6.00), behavioral activation program (MD −5.70, 95% CrI −6.10, −5.40), and dim light therapy (MD −6.30, 95% CrI −10.00, −2.20) were better than the CG. Tai chi (MD −3.00, 95% CrI −4.00, −2.00) was better than CG for PHQ-9 outcomes. Telephone-based cognitive behavioral treatment (MD −2.50 95% CrI −2.70, −2.30) was better than the CG for K-6 scores. Conclusion: Our results suggest that electroacupuncture or bright light therapy appear to be the better choices in the treatment of SD. This study provide new insights into clinical treatment selection and may aid the development of guidelines for the management of SD., Graphical Abstract Graphical abstract of the network meta-analysis. Note: CES-D, Center for Epidemiologic Studies Depression Scale; BDI, Beck Depression Inventory Scale; PHQ-9, the nine-Item Patient Health Questionnaire; K6, Kessler Screening Scale for Psychological Distress; SUCRA, surface area under the cumulative ranking curves.

TGF-β-centered epithelial-mesenchymal transition (EMT) is a key process involved in radiation-induced pulmonary injury (RIPI) and pulmonary fibrosis. PIEZO1, a mechanosensitive calcium channel, is expressed in myeloid cell and has been found to play an important role in bleomycin-induced pulmonary fibrosis. Whether PIEZO1 is related with radiation-induced EMT remains elusive. Herein, we found that PIEZO1 is functional in rat primary type II epithelial cells and RLE-6TN cells. After irradiation, PIEZO1 expression was increased in rat lung alveolar type II epithelial cells and RLE-6TN cell line, which was accompanied with EMT changes evidenced by increased TGF-β1, N-cadherin, Vimentin, Fibronectin, and α-SMA expression and decreased E-cadherin expression. Addition of exogenous TGF-β1 further enhanced these phenomena in vitro. Knockdown of PIEZO1 partly reverses radiation-induced EMT in vitro. Mechanistically, we found that activation of PIEZO1 could upregulate TGF-β1 expression and promote EMT through Ca2+/HIF-1α signaling. Knockdown of HIF-1α partly reverses enhanced TGF-β1 expression caused by radiation. Meanwhile, the expression of PIEZO1 was up-regulated after TGF-β1 co-culture, and the mechanism could be traced to the inhibition of transcription factor C/EBPβ expression by TGF-β1. Irradiation also caused a decrease in C/EBPβ expression in RLE-6TN cells. Dual luciferase reporter assay and chromatin immunoprecipitation assay (ChIP) confirmed that C/EBPβ represses PIEZO1 expression by binding to the PIEZO1 promoter. Furthermore, overexpression of C/EBPβ by using the synonymous mutation to C/EBPβ siRNA could reverse siRNA-induced upregulation of PIEZO1. In summary, our research suggests a critical role of PIEZO1 signaling in radiation-induced EMT by forming positive feedback with TGF-β1.

As antimicrobial resistance has been increasing, new antimicrobial agents are desperately needed. Azalomycin F, a natural polyhydroxy macrolide, presents remarkable antimicrobial activities. To investigate its pharmacokinetic characteristics in rats, the concentrations of azalomycin F contained in biological samples, in vitro, were determined using a validated high-performance liquid chromatography–ultraviolet (HPLC-UV) method, and, in vivo, samples were assayed by an ultra-high performance liquid chromatography–tandem mass spectrometric (UPLC–MS/MS) method. Based on these methods, the pharmacokinetics of azalomycin F were first investigated. Its plasma concentration-time courses and pharmacokinetic parameters in rats were obtained by a non-compartment model for oral (26.4 mg/kg) and intravenous (2.2 mg/kg) administrations. The results indicate that the oral absolute bioavailability of azalomycin F is very low (2.39 ± 1.28%). From combinational analyses of these pharmacokinetic parameters, and of the results of the in-vitro absorption and metabolism experiments, we conclude that azalomycin F is absorbed relatively slowly and with difficulty by the intestinal tract, and subsequently can be rapidly distributed into the tissues and/or intracellular f of rats. Azalomycin F is stable in plasma, whole blood, and the liver, and presents plasma protein binding ratios of more than 90%. Moreover, one of the major elimination routes of azalomycin F is its excretion through bile and feces. Together, the above indicate that azalomycin F is suitable for administration by intravenous injection when used for systemic diseases, while, by oral administration, it can be used in the treatment of diseases of the gastrointestinal tract.

Pulmonary endothelial cell dysfunction plays an important role in ionizing radiation (IR)-induced lung injury. Whether pulmonary endothelial cell ferroptosis occurs after IR and what are the underlying mechanisms remain elusive. Here, we demonstrate that 15-Gy IR induced ferroptosis characterized by lethal accumulation of reactive oxygen species (ROS), lipid peroxidation, mitochondria shrinkage, and decreased glutathione peroxidase 4 (GPX4) and SLC7A11 expression in pulmonary endothelial cells. The phenomena could be mimicked by Yoda1, a specific activator of mechanosensitive calcium channel PIEZO1. PIEZO1 protein expression was upregulated by IR in vivo and in vitro. The increased PIEZO1 expression after IR was accompanied with increased calcium influx and increased calpain activity. The effects of radiation on lung endothelial cell ferroptosis was partly reversed by inhibition of PIEZO1 activity using the selective inhibitor GsMTx4 or inhibition of downstreaming Ca2+/calpain signaling using PD151746. Both IR and activation of PIEZO1 led to increased degradation of VE-cadherin, while PD151746 blocked these effects. VE-cadherin knockdown by specific siRNA causes ferroptosis-like phenomena with increased ROS and lipid peroxidation in the lung endothelial cells. Overexpression of VE-cadherin partly recused the ferroptosis caused by IR or PIEZO1 activation as supported by decreased ROS production, lipid peroxidation and mitochondria shrinkage compared to IR or PIEZO1 activation alone. In summary, our study reveals a previously unrecognized role of PIEZO1 in modulating ferroptosis, providing a new target for future mitigation of radiation-induced lung injury.

Urbanization and the ecological resource environment are mutually influential and interdependent, and their coordinated development is the key to the sustainable development of urbanizatio...

The use of multi-mode remote sensing data for biomass prediction is of potential value to aid planting management and yield maximization. In this study, an advanced biomass estimation approach for sugarcane fields is proposed based on multi-source remote sensing data. Since feature interpretability in agricultural data mining is significant, a feature extraction method of deep archetypal analysis (DAA) that has good model interpretability is introduced and aided by principal component analysis (PCA) for feature mining from the multi-mode multispectral and light detection and ranging (LiDAR) remote sensing data pertaining to sugarcane. In addition, an integrated regression model integrating random forest regression, support vector regression, K-nearest neighbor regression and deep network regression is developed after feature extraction by DAA to precisely predict biomass of sugarcane. In this study, the biomass prediction performance achieved using the proposed integrated learning approach is found to be predominantly better than that achieved by using conventional linear methods in all the time periods of plant growth. Of more significance, according to model interpretability of DAA, only a small set of informative features maintaining their physical meanings (four informative spectral indices and four key LiDAR metrics) can be extracted which eliminates the redundancy of multi-mode data and plays a vital role in accurate biomass prediction. Therefore, the findings in this study provide hands-on experience to planters with indications of the key or informative spectral or LiDAR metrics relevant to the biomass to adjust the corresponding planting management design.

Emerging evidence witnesses the association of air pollution exposure with sleep disorders or the risk of obstructive sleep apnea (OSA); however, the results are not consistent. OSA patients with or without a low arousal threshold (LAT) have different pathology and therapeutic schemes. No study has evaluated the potential diverse effects of air pollution on the phenotypes of OSA. The current study aimed to evaluate the associations of short-term and long-term exposure to air pollution with sleep-disordered measures and OSA phenotypes. This cross-sectional study consisted of 4634 participants from a sleep center in Taipei from January 2015 to April 2019. The personal exposure to ambient PM

Background Highly pathogenic H5N1 influenza viruses remain a pandemic risk to the world population. Although vaccines are the best solution to prevent this threat, a more effective vaccine for H5 strains of influenza has yet to be developed. All existing vaccines target only serum antibody against influenza as the primary outcome, while mucosal immunity has not been addressed. To address these shortcomings we have used an effective mucosal adjuvant system to produce a prototype vaccine that provides antibody, cellular and mucosal immunity to multiple serotypes of H5. Methods Plant-derived recombinant H5 (rH5) antigen was mixed with a novel nanoemulsion NE01 adjuvant. The rH5-NE01 vaccine was administered intranasally to CD-1 mice and ferrets. Immunogenicity of this immunization was evaluated through rH5-specific antibody and cellular immune responses. Hemagglutination inhibition (HI) and virus neutralization (VN) assays were performed. Protection against H5N1 virus challenge was evaluated in ferrets. Results Intranasal immunization with rH5-NE01vaccine induced high titers (>106) of rH5-specific IgG in mice. In mice and ferrets this vaccine also achieved titers of ≥40 for both HI and VN. Additionally, the levels of rH5-specific IgA were significantly increased in bronchial secretions in these animals. The rH5-NE01 vaccine enhanced rH5-specific cellular immune responses including IFN-γ and IL-17. Ten-day survival post challenge was 100% in ferrets that received rH5-NE01compared to 12.5% in the PBS group. Furthermore, this vaccine prevented weight loss and increases in body temperature after H5N1 challenge as compared to the controls. Moreover, H5N1 virus in nasal wash of rH5-NE01-vaccinated ferrets was significantly decreased compared to controls. Conclusion Intranasal immunization with rH5 antigen formulated with NE01 adjuvant elicited strong, broad and balanced immune responses that effectively protect against H5N1 influenza virus infection in the ferret model. The ease of formulation of rH5-NE01 makes this novel combination a promising mucosal vaccine candidate for pandemic influenza.

Reverse water–gas shift reaction using renewable H2 is a promising route for CO2 upgrade, however, it is restricted by the equilibrium. The chemical looping reverse water–gas shift reaction using oxygen carriers (i.e. Fe) has proven a more effective CO2 utilization process to produce CO. However, CO2 with high purity is needed to obtain concentrated CO. Herein, we propose a calcium chemical dual looping using one-pot sol–gel synthesized Ca-Fe dual functional materials (DFMs). The CO2 in the exhaust gas (∼10% CO2) can be captured and transformed into carbonates and then in-situ converted into CO through continuous chemical looping in H2 atmosphere. This process avoids CO2 enrichment, storage and transportation and simultaneously realizes efficient CO2 conversion. The Ca-Fe DFMs possessed significantly improved catalytic efficiency (enhanced real-time CO generation rate) compared to CaO. It is found that Ni1Fe9-CaO could optimally achieve 11.3 mmol gDFM−1 CO yield, 82.5% CO2 conversion and 99.9% CO selectivity at 650 °C. Notably, Ni1Fe9-CaO displayed high CO2 conversion (>80%) and CO selectivity (>99.9%) during the cycle tests and possessed enhanced stability in relation to CO yield after 10 cycles (20.9% and 35.5% decrease for Ni1Fe9-CaO and CaO, respectively). Herein, Ca2Fe2O5 plays two roles: acting as an oxygen carrier for in-situ chemical looping to produce CO and a thermally stable physical barrier to retard the sintering of CaO. It is noted that Fe-related species could be reduced into the metallic state at the end of hydrogenation, resulting in CO formation in the following CO2 capture process.

Additional file 8: Figure S5. Compartmental conversion among chromosomes. A. The frequency of compartmental transition between 18 chromosomes in the control group of venom gland compared with the 3d group of venom gland. B. The frequency of compartmental transition between 18 chromosomes in muscle compared with the 3d group of venom gland.

Additional file 6: Figure S1. Analysis of gene expression of different time and tissues. A. Scatter plot showing gene expression between the control group and 3d group in venom gland. The axes represent normalized RNA-seq log2FoldChange. Red and black dots denote genes whose expression changed significantly and grey dots denote genes whose expression was unchanged. B. The PCA analysis of 6 tissues in B. multicinctus.

Additional file 10: Figure S7–S8. Heatmap and distribution of histone marks around TSS.

We experimentally demonstrate a highly nonlinear organic-silicon hybrid slot waveguide (HN-OSSW), whose nonlinear coefficient reaches to 1.55 × 106 W−1km−1 with the waveguide length of 2mm.

Additional file 7: Figure S2–S4. Chromosomal interactions among control/ 3d group of venom gland and muscle. A. Comparison of intra-chromosomal interactions between MACs and MICs. B. Comparison of inter-chromosomal interactions between MICs and MICs-MACs. C. Comparison of inter-chromosomal interactions between MACs and MICs-MACs. D. Comparison of inter-chromosomal interactions between MACs and MICs.

Visual Grounding (VG) is a task of locating a specific object in an image semantically matching a given linguistic expression. The mapping of the linguistic and visual contents and the understanding of diverse linguistic expressions are the two challenges of this task. The performance of visual grounding is consistently improved by deep visual features in the last few years. While deep visual features contain rich information, they could also be noisy, biased and easily over-fitted. In contrast, symbolic features are discrete, easy to map and usually less noisy. In this work, we propose a novel modular network learning to match both the object's symbolic features and conventional visual features with the linguistic information. Moreover, the Residual Attention Parser is designed to alleviate the difficulty of understanding diverse expressions. Our model achieves competitive performance on three popular datasets of VG. Ministry of Education (MOE) National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Singapore under its AI Singapore Programme (AISG Award No: AISG-RP-2018-003), and the MOE AcRF Tier-1 research grants: RG28/18 (S), RG22/19 (S) and RG95/20.

Additional file 9: Figure S6. Relationship between histone proteins and genes. A. The relationship between transition of A/B Compartment and histone modifications. B. The Pearson correlation coefficients of H3ac and genes. C. The Pearson correlation coefficients of H3K27me3 and genes.

Chronic inflammatory pain is a severe clinical symptom that aggravates the life quality of patients and places a huge economic burden on individuals and society. As one complementary and alternative therapy, electroacupuncture (EA) is widely used in clinical practice to treat chronic inflammatory pain based on its safety and efficacy. Previous studies have revealed the potential role of adenosine, neuropeptides, and inflammatory factors in EA analgesia in various pain models, but the identity of some of the signaling pathways involved remain unknown. In the present study, we explored whether neuregulin1 (NRG1)-ErbB4 signaling is involved in EA analgesia in inflammatory pain. Repeated EA treatment at the acupoints Zusanli (ST36) and Sanyinjiao (SP6) for 3 consecutive days remarkably attenuated mechanical allodynia and thermal hyperalgesia in complete Freund’s adjuvant (CFA)-treated mice, with an increased expression of NRG1 in spinal cord (SC). We found that ErbB4 kinase participated in both the EA and NRG1 mediated analgesic effects on inflammatory pain by pharmacological inhibition or genetic ablation ErbB4 in vivo. Intriguingly, the mice with conditional knockout of ErbB4 from PV+ interneurons in SC showed abnormal basal mechanical threshold. Meanwhile, NRG1 treatment could not relieve tactile allodynia in PV-Erbb4–/– mice or AAV-PV-Erbb4–/– mice after CFA injection. These experimental results suggest that regulating NRG1-ErbB4 signaling in SC could reduce pain hypersensitivity and contribute to EA analgesia in inflammatory pain.

In order to meet the demand of the rapid economic growth for power load, this paper proposes a 500kV substation planning method considering the interconnection structure of 220kV substation. Firstly, the interconnection structure between 220 kV substations is analyzed; secondly, based on the interconnection structure between 220 kV substations and further considering the access of 220 kV high-voltage power supply, a mathematical model of 500 kV substation planning considering the interconnection structure of 220 kV substation is constructed; furthermore, the improved weighted Voronoi diagram algorithm and the low-voltage side line network loss and investment cost are adopted The method of station location optimization is used to solve the planning model of 500kV substation. Finally, the scientificalness and practicability of the proposed method in the planning of 500kV substation is verified by an example.

Background Targeted contrast nanoparticles for breast tumor imaging facilitates early detection and improves treatment efficacy of breast cancer. This manuscript reports the development of an epidermal growth factor receptor-2 (HER-2) specific, bi-modal, dendrimer conjugate to enhance computed tomography (CT) and magnetic resonance imaging (MRI) of HER-2-positive breast cancer. This material employs generation 5 poly(amidoamine) dendrimers, encapsulated gold nanoparticles, chelated gadolinium, and anti-human HER-2 antibody to produce the nanoparticle contrast agent. Results Testing in two mouse tumor models confirms this contrast agent’s ability to image HER-2 positive tumors. Intravenous injection of this nanoparticle in mice bearing HER-2 positive mammary tumors significantly enhances MRI signal intensity by ~ 20% and improves CT resolution and contrast by two-fold. Results by flow cytometry and confocal microscopy validate the specific targeting of the conjugate and its internalization in human HER-2 positive cells. Conclusion These results demonstrate that this nanoparticle conjugate can efficiently target and image HER-2 positive tumors in vivo and provide a basis for the development of this diagnostic tool for early detection, metastatic assessment and therapeutic monitoring of HER-2 positive cancers.