Characterization of neutralizing chimeric heavy-chain antibodies against tetanus toxin.

Tetanus toxin (TeNT) is one of the most toxic proteins. Neutralizing antibodies against TeNT are effective in prevention and treatment. In this study, 14 anti-tetanus nanobodies were obtained from a phage display nanobody library by immunizing a camel with the C-terminal receptor-binding domain of TeNT (TeNT-Hc) as the antigen. After fusion with the human Fc fragment, 11 chimeric heavy-chain antibodies demonstrated nanomolar binding toward TeNT-Hc. The results of toxin neutralization experiments showed that T83-7, T83-8, and T83-13 completely protected mice against 20 × the median lethal dose (LD50) at a low concentration. The neutralizing potency of T83-7, T83-8, and T83-13 against TeNT is 0.4 IU/mg, 0.4 IU/mg and 0.2 IU/mg, respectively. In the prophylactic setting, we found that 5 mg/kg of T83-13 provided the mice with full protection from tetanus, even when they were injected 14 days before exposure to 20 × LD50 TeNT. T83-7 and T83-8 were less effective, being fully protective only when challenged 7 or 10 days before exposure, respectively. In the therapeutic setting, 12 h after exposure to TeNT, 1 ~ 5 mg/kg of T83-7, and T83-8 could provide complete protection for mice against 5 × LD50 TeNT, while 1 mg/kg T83-13 could provide complete protection 24 h after exposure to 5 × LD50 TeNT. Our results suggested that these antibodies represent prophylactic and therapeutic activities against TeNT in a mouse model. The T83-7, T83-8, and T83-13 could form the basis for the subsequent development of drugs to treat TeNT toxicity.

[Retracted] Potentiation of the antitumor activity of adriamycin against osteosarcoma by cannabinoid WIN­55,212­2.

[This retracts the article DOI: 10.3892/ol.2015.3525.].

Development and comparison of machine learning-based models for predicting heart failure after acute myocardial infarction.

AIMS: Heart failure (HF) is one of the common adverse cardiovascular events after acute myocardial infarction (AMI), but the predictive efficacy of numerous machine learning (ML) built models is unclear. This study aimed to build an optimal model to predict the occurrence of HF in AMI patients by comparing seven ML algorithms. METHODS: Cohort 1 included AMI patients from 2018 to 2019 divided into HF and control groups. All first routine test data of the study subjects were collected as the features to be selected for the model, and seven ML algorithms with screenable features were evaluated. Cohort 2 contains AMI patients from 2020 to 2021 to establish an early warning model with external validation. ROC curve and DCA curve to analyze the diagnostic efficacy and clinical benefit of the model respectively. RESULTS: The best performer among the seven ML algorithms was XgBoost, and the features of XgBoost algorithm for troponin I, triglycerides, urine red blood cell count, γ-glutamyl transpeptidase, glucose, urine specific gravity, prothrombin time, prealbumin, and urea were ranked high in importance. The AUC of the HF-Lab9 prediction model built by the XgBoost algorithm was 0.966 and had good clinical benefits. CONCLUSIONS: This study screened the optimal ML algorithm as XgBoost and developed the model HF-Lab9 will improve the accuracy of clinicians in assessing the occurrence of HF after AMI and provide a reference for the selection of subsequent model-building algorithms.

Diagnostic efficiency of multi-modal MRI based deep learning with Sobel operator in differentiating benign and malignant breast mass lesions-a retrospective study.

Purpose: To compare the diagnostic efficiencies of deep learning single-modal and multi-modal for the classification of benign and malignant breast mass lesions. Methods: We retrospectively collected data from 203 patients (207 lesions, 101 benign and 106 malignant) with breast tumors who underwent breast magnetic resonance imaging (MRI) before surgery or biopsy between January 2014 and October 2020. Mass segmentation was performed based on the three dimensions-region of interest (3D-ROI) minimum bounding cube at the edge of the lesion. We established single-modal models based on a convolutional neural network (CNN) including T2WI and non-fs T1WI, the dynamic contrast-enhanced (DCE-MRI) first phase was pre-contrast T1WI (d1), and Phases 2, 4, and 6 were post-contrast T1WI (d2, d4, d6); and Multi-modal fusion models with a Sobel operator (four_mods:T2WI, non-fs-T1WI, d1, d2). Training set (n = 145), validation set (n = 22), and test set (n = 40). Five-fold cross validation was performed. Accuracy, sensitivity, specificity, negative predictive value, positive predictive value, and area under the ROC curve (AUC) were used as evaluation indicators. Delong's test compared the diagnostic performance of the multi-modal and single-modal models. Results: All models showed good performance, and the AUC values were all greater than 0.750. Among the single-modal models, T2WI, non-fs-T1WI, d1, and d2 had specificities of 77.1%, 77.2%, 80.2%, and 78.2%, respectively. d2 had the highest accuracy of 78.5% and showed the best diagnostic performance with an AUC of 0.827. The multi-modal model with the Sobel operator performed better than single-modal models, with an AUC of 0.887, sensitivity of 79.8%, specificity of 86.1%, and positive prediction value of 85.6%. Delong's test showed that the diagnostic performance of the multi-modal fusion models was higher than that of the six single-modal models (T2WI, non-fs-T1WI, d1, d2, d4, d6); the difference was statistically significant (p = 0.043, 0.017, 0.006, 0.017, 0.020, 0.004, all were greater than 0.05). Conclusions: Multi-modal fusion deep learning models with a Sobel operator had excellent diagnostic value in the classification of breast masses, and further increase the efficiency of diagnosis.

Research on low-carbon dual channel supply chain considering product substitution under government carbon tax and low-carbon subsidy.

Since dual channel supply chain has become one of the main modes of supply chain, its research has acquired great significance. This paper constructs a low-carbon dual channel supply chain composed of one manufacturer and one retailer. The manufacturer produces low-carbon product and high carbon product with substitution relationship. The retailer sells high carbon product in traditional channel. The manufacturer also sells low-carbon product in direct channel. The government, manufacturer and retailer conduct a three-level Stackelberg game. This paper studies the optimal decisions of the government, manufacturer and retailer under the three modes of carbon tax + subsidy, carbon tax only and subsidy only. It has been found that for social welfare, the carbon tax + subsidy model is higher than the subsidy model and carbon tax model. For manufacturer profit, the subsidy mode is the highest, followed by the carbon tax + subsidy mode. For retailer profit, the carbon tax + subsidy model is equal to the carbon tax model. The increase in the proportion of consumers who prefer high carbon product in the total market or product cost of low-carbon product, will increase the profit of traditional channel and reduce the profit of direct channel.

Proteomic profile of Trichinella spiralis infected mice with acute spinal cord injury: A 4D label-free quantitative analysis.

Spinal cord injury (SCI) can cause severe loss of locomotor and sensory activities, with no ideal treatment. Emerging reports suggest that the helminth therapy is highly effective in relieving numerous inflammatory diseases. Proteomic profiling is often used to elucidate the underlying mechanism behind SCI. Herein, we systematically compared the protein expression profiles of murine SCI spinal cord and Trichinella spiralis treated murine SCI spinal cord, using a 4D label-free technique known for its elevated sensitivity. Relative to the SCI mice, the T. spiralis-treated mice exhibited marked alterations in 91 proteins (31 up- and 60 down-regulated). Based on our Gene Ontology (GO) functional analysis, the differentially expressed proteins (DEPs) were primarily enriched in the processes of metabolism, biological regulation, cellular process, antioxidant activity, and other cell functions. In addition, according to the Clusters of Orthologous Groups of protein/EuKaryotic Orthologous Groups (COG/KOG) functional stratification, proteins involved in signaling transduction mechanisms belonged to the largest category. Over-expressed DEPs were also enriched in the "NADPH oxidase complex", "superoxide anion generation", "other types of O-glycan biosynthesis", and "HIF-1 signaling pathway". Furthermore, the protein-protein interaction (PPI) network identified the leading 10 hub proteins. In conclusion, we highlighted the dynamic proteomic profiling of T. spiralis-treated SCI mice. Our findings provide significant insight into the molecular mechanism behind T. spiralis regulation of SCI.

Machine learning predicts the risk of hemorrhagic transformation of acute cerebral infarction and in-hospital death.

BACKGROUND: The incidence of hemorrhagic transformation (HT) during thrombolysis after acute cerebral infarction (ACI) is very high. We aimed to develop a model to predict the occurrence of HT after ACI and the risk of death after HT. METHODS: Cohort 1 is divided into HT and non-HT groups, to train the model and perform internal validation. All first laboratory test results of study subjects were used as features to be selected for machine learning, and the models built by four machine learning algorithms were compared to screen the best algorithm and model. Following that, the HT group was divided into death and non-death for subgroup analysis. Receiver operating characteristic (ROC) curves etc. to evaluate the model. ACI patients in cohort 2 for external validation. RESULTS: In cohort 1, the HT risk prediction model HT-Lab10 built by the XgBoost algorithm performed the best with AUCROC=0.95 (95% CI, 0.93-0.96). Ten features were included in the model, namely B-type natriuretic peptide precursor, ultrasensitive C-reactive protein, glucose, absolute neutrophil value, myoglobin, uric acid, creatinine, Ca2+, Thrombin time, and carbon dioxide combining power. The model also had the ability to predict death after HT with AUCROC=0.85 (95% CI, 0.78-0.91). The ability of HT-Lab10 to predict the occurrence of HT as well as death after HT was validated in cohort 2. CONCLUSIONS: The model HT-Lab10 built using the XgBoost algorithm showed excellent predictive ability in both the occurrence of HT and the risk of HT death, achieving a model with multiple uses.

First-principles study on the electronic structure and photocatalytic property of a novel two-dimensional ZrS2/InSe heterojunction.

Photocatalytic water cracking technology provides a broad prospect for solving the current energy crisis using solar energy and water resources. In this paper, a two-dimensional ZrS2/InSe heterojunction for accelerating the process of hydrogen production from water decomposition was constructed, and its electronic structure and photocatalytic property were studied using first-principles calculation. The results show that the lattice mismatch rate of the heterojunction from monolayer ZrS2 and monolayer InSe is 2.48%, and its binding energy is -1.696 eV, indicating that the structure of the heterojunction is stable. The ZrS2/InSe heterojunction is an indirect bandgap with a bandgap value of 1.41 eV and a typical type-II band arrangement. Importantly, the ZrS2/InSe heterostructure has a Z-scheme structure, which is beneficial to the separation of photogenerated electron hole pairs. Moreover, the ZrS2/InSe heterojunction has a strong absorption ability for visible light (up to 3.84 × 105 cm-1), which is helpful for improving its photocatalytic efficiency. The two-dimensional ZrS2/InSe heterojunction is a very promising photocatalyst, as concluded from the above studies.

Selecting and Characterizing Tyrosinase Inhibitors from Atractylodis macrocephalae Rhizoma Based on Spectrum-Activity Relationship and Molecular Docking.

Atractylodis macrocephalae Rhizoma (AMR) is a famous classical Chinese traditional medicine (CTM), which has been used as a tonic for many diseases for thousands of years. In ancient China, it was used as a supplementary food for beauty in the palace. In preliminary studies, the function of whitening skin and the significant inhibiting effect on tyrosinase (TYR) which is the reactive enzyme in the composition of melanin of AMR were discovered, and the relevant research was rarely reported. In this study, high-performance liquid chromatography (HPLC) along with partial least squares regression analysis (PLS) was applied to survey the coherence between the chemical constituents and the inhibiting activity of 11 batches of AMR on TYR activity. The results of PLS showed that the chromatographic peaks 11 (atractylenolide III) and 15 could be important effective ingredients of the inhibition TYR activity as ascertained by spectrum-activity relationships. Furthermore, TYR inhibitory activity of atractylenolide III was validated by in vitro test by ß-arbutin served as a positive control drug. The results of the in vitro test and the molecular docking showed that atractylenolide III has high TYR inhibitory activity and could link to the residues in TYR catalytic pocket. Therefore, bioassay, molecular docking, and spectrum-activity relationships are appropriate for linking the quality of samples with pharmaceutical-related active ingredients. And our studying would lay a theoretical foundation for applying the water extracts of AMR in whitening cosmetics.

Schistosoma japonicum Cystatin Alleviates Sepsis Through Activating Regulatory Macrophages.

Multi-organ failure caused by the inflammatory cytokine storm induced by severe infection is the major cause of death for sepsis. Sj-Cys is a cysteine protease inhibitor secreted by Schistosoma japonicum with strong immunomodulatory functions on host immune system. Our previous studies have shown that treatment with Sj-Cys recombinant protein (rSj-Cys) attenuated inflammation caused by sepsis. However, the immunological mechanism underlying the immunomodulation of Sj-Cys for regulating inflammatory diseases is not yet known. In this study, we investigated the effect of Sj-Cys on the macrophage M2 polarization and subsequent therapeutic effect on sepsis. The rSj-Cys was expressed in yeast Pichia pastoris. Incubation of mouse bone marrow-derived macrophages (BMDMs) with yeast-expressed rSj-Cys significantly activated the polarization of macrophages to M2 subtype characterized by the expression of F4/80+ CD206+ with the elated secretion of IL-10 and TGF-ß. Adoptive transfer of rSj-Cys treated BMDMs to mice with sepsis induced by cecal ligation and puncture (CLP) significantly improved their survival rates and the systemic clinical manifestations of sepsis compared with mice receiving non-treated normal BMDMs. The therapeutic effect of Sj-Cys-induced M2 macrophages on sepsis was also reflected by the reduced pathological damages in organs of heart, lung, liver and kidney and reduced serological levels of tissue damage-related ALT, AST, BUN and Cr, associated with downregulated pro-inflammatory cytokines (IFN-gamma and IL-6) and upregulated regulatory anti-inflammatory cytokines (IL-10 and TGF-ß). Our results demonstrated that Sj-Cys is a strong immunomodulatory protein with anti-inflammatory features through activating M2 macrophage polarization. The findings of this study suggested that Sj-Cys itself or Sj-Cys-induced M2 macrophages could be used as therapeutic agents in the treatment of sepsis or other inflammatory diseases.

Preparation and Properties of Cyanobacteria-Based Carbon Quantum Dots/Polyvinyl Alcohol/ Nanocellulose Composite.

Blue luminescent carbon quantum dots (CQDs) were prepared from cyanobacteria by a hydrothermal method. The PL quantum yields of the obtained CQDs was 5.30%. Cyanobacteria-based carbon quantum dots/polyvinyl alcohol/nanocellulose composite films were prepared, which could emit bright blue under UV light. FTIR characterization showed that the composite films had hydroxyl groups on the surface and no new groups were formed after combining the three materials. The photoluminescence (PL) spectra revealed that the emission of the prepared CQDs was excitation dependent. Studies on the water resistance performance and light barrier properties of the composite films showed that they possessed higher water resistance properties and better UV/infrared light barrier properties. Therefore, we report the cyanobacteria-based carbon quantum dots/polyvinyl alcohol/nanocellulose composite films have the potential to be applied in flexible packaging materials, anti-fake materials, UV/infrared light barrier materials and so on.

Phytochemistry and biological properties of isoprenoid flavonoids from Sophora flavescens Ait.

Sophora flavescens Ait (Ku-Shen in Chinese) is a popular traditional Chinese herbal medicine in China for a long history. It shows significant pharmacological activities in the treatment of dysentery, eczema, fever, jaundice, vulvar swelling, gastrointestinal hemorrhage and inflammatory disorders. Alkaloids and flavonoids have been identified as virtual components, especially isoprenoid flavanonols are a class of characteristic compounds for S. flavescens. However, few studies have focused on isoprenoid flavonoids analyses and no comprehensive review has yet been published. In the current review, we systematically summarized the isoprenoid flavonoids, a total of 55 compounds have been isolated from S. flavescens, particularly an isoprenyl and a lavandulyl group in backbone structures. Further pharmacological activities, qualitative and quantitative chemical analyses research will contribute to the development of natural isoprenoid flavonoid products in S. flavescens.

Preparation of cyanobacteria-enhanced poly(vinyl)alcohol-based films with resistance to blue-violet light / red light and water.

The harmful cyanobacteria blooms which usually form in spring and summer, cause global eutrophication of freshwater and coastal marine ecosystems. This study tried to utilize cyanobacteria as a raw material to produce biological poly(vinyl)alcohol-based films. Cyanobacteria was firstly modified with poly(ethylene glycol), guanidine hydrochloride, carboxymethyl cellulose and 3-glycidoxypropyltrimethoxysilane as plasticizer, modifier, toughening agent and coupling agent, respectively. And then the modified cyanobacteria was introduced to poly(vinyl)alcohol and cellulose nanofibers/poly(vinyl)alcohol matrix to improve the barrier properties of poly(vinyl)alcohol to light and water. Compared with poly(vinyl)alcohol and cellulose nanofibers/poly(vinyl)alcohol films, the obtained cyanobacteria/poly(vinyl)alcohol and the cyanobacteria/cellulose nanofibers/poly(vinyl)alcohol composites exhibit better resistance to light and water. More interestingly, we found that after adding cyanobacteria, the poly(vinyl)alcohol-based films present better barrier properties to blue-violet light and red light. In adddition, introducing cyanobacteria into poly(vinyl)alcohol or cellulose nanofibers/poly(vinyl)alcohol matrix increases the surface roughness and contact angle to water of the composites.

Preparation and Performance of Radiata-Pine-Derived Polyvinyl Alcohol/Carbon Quantum Dots Fluorescent Films.

In this study, the low-cost processing residue of Radiata pine (Pinus radiata D. Don) was used as the lone carbon source for synthesis of CQDs (Carbon quantum dots) with a QY (The quantum yield of the CQDs) of 1.60%. The CQDs were obtained by the hydrothermal method, and +a PVA-based biofilm was prepared by the fluidized drying method. The effects of CQDs and CNF (cellulose nanofibers) content on the morphology, optical, mechanical, water-resistance, and wettability properties of the PVA/CQDs and PVA/CNF/CQDs films are discussed. The results revealed that, when the excitation wavelength was increased from 340 to 390 nm, the emission peak became slightly red-shifted, which was induced by the condensation between CQDs and PVA. The PVA composite films showed an increase in fluorescence intensity with the addition of the CNF and CQDs to polymers. The chemical structure of prepared films was determined by the FTIR spectroscopy, and no new chemical bonds were formed. In addition, the UV transmittance was inversely proportional to the change of CQDs content, which indicated that CQDs improved the UV barrier properties of the films. Furthermore, embedding CQDs Nano-materials and CNF into the PVA matrix improved the mechanical behavior of the Nano-composite. Tensile modulus and strength at break increased significantly with increasing the concentration of CQDs Nano-materials inside the Nano-composite, which was due to the increased in the density of crosslinking behavior. With the increase of CQDs content (>1 mL), the water absorption and surface contact angle of the prepared films decreased gradually, and the water-resistance and surface wettability of the films were improved. Therefore, PVA/CNF/CQDs bio-nanocomposite films could be used to prepare anti-counterfeiting, high-transparency, and ultraviolet-resistant composites, which have potential applications in ecological packaging materials.

Green Preparation of Fluorescent Carbon Quantum Dots from Cyanobacteria for Biological Imaging.

Biomass-based carbon quantum dots (CQDs) have become a significant carbon materials by their virtues of being cost-effective, easy to fabricate and low in environmental impact. However, there are few reports regarding using cyanobacteria as a carbon source for the synthesis of fluorescent CQDs. In this study, the low-cost biomass of cyanobacteria was used as the sole carbon source to synthesize water-soluble CQDs by a simple hydrothermal method. The synthesized CQDs were mono-dispersed with an average diameter of 2.48 nm and exhibited excitation-dependent emission performance with a quantum yield of 9.24%. Furthermore, the cyanobacteria-derived CQDs had almost no photobleaching under long-time UV irradiation, and exhibited high photostability in the solutions with a wide range of pH and salinity. Since no chemical reagent was involved in the synthesis of CQDs, the as-prepared CQDs were confirmed to have low cytotoxicity for PC12 cells even at a high concentration. Additionally, the CQDs could be efficiently taken up by cells to illuminate the whole cell and create a clear distinction between cytoplasm and nucleus. The combined advantages of green synthesis, cost-effectiveness and low cytotoxicity make synthesized CQDs a significant carbon source and broaden the application of cyanobacteria and provide an economical route to fabricate CQDs on a large scale.

Optimization of Graphene Conductive Ink with 73 wt% Graphene Contents.

With the pace of development accelerating in printed electronics, the fabrication and application of conductive ink have been brought into sharp focus in recent years. The discovery of graphene also unfolded a vigorous research campaign. In this paper, we prepared graphene conductive ink and explored the feasibility of applying the ink to flexible paper-based circuit. Since experimental study concentrating upon ink formulation was insufficient, orthogonal test design was used in the optimization of preparation formula of conductive ink for the first time. The purpose of this study was to determine the effect of constituent dosage on conductivity of graphene conductive ink, so as to obtain the optimized formula and prepare graphene conductive ink with good conductivity. Characterization of optimized graphene conductive ink we fabricated showed good adhesion to substrate and good resistance to acid and water. The graphene concentration of the optimized ink reached 73.17 wt% solid content. Particle size distribution of graphene conductive ink was uniform, which was about 1940 nm. Static surface tension was 28.9 mN/m and equilibrium contact angle was 23°, demonstrating that conductive ink had good wettability. Scanning Electron Microscope (SEM) analysis was also investigated, moreover, the feasibility of lightening a light-emitting diode (LED) light was verified. The graphene conductive ink with optimized formula can be stored for almost eight months, which had potential applications in flexible paper-based circuit in the future.

Comparison of the efficacy and safety of 3 treatments for patients with osteoporotic vertebral compression fractures: A network meta-analysis.

BACKGROUND: Osteoporotic vertebral compression fractures (OVCFs) constitute an age-related health problem that affects approximately 200 million people worldwide. Currently, various treatments are performed with the goal of reducing pain, stabilizing the vertebrate, and restoring mobility. In this study, we aimed to assess the efficacy and safety of vertebroplasty (VP), kyphoplasty (KP), and conservative treatment (CT) for the treatment of OVCFs. METHODS: We performed a network meta-analysis. PubMed and Embase databases were searched to identify randomized controlled trials (RCTs) that contained at least one of the following outcomes: visual analog scale (VAS), Roland-Morris Disability Questionnaire (RDQ), European Quality of Life-5 Dimensions (EQ-5D), and new fractures. Odds ratios with 95% confidence intervals (CIs) were used to calculate the risk of new fractures, and mean differences (MDs) with 95% CIs were utilized to express RDQ, EQ-5D, and VAS outcomes. RESULTS: Sixteen RCTs with 2046 participants were included in this meta-analysis. Compared with CT, patients treated with VP had improved pain relief, daily function, and quality of life; however, no significant differences were found between VP and KP for these 3 outcomes. All treatment options were associated with comparable risk of new fractures. When the rank probability was assessed to distinguish subtle differences between the treatments, VP was the most effective treatment for pain relief, followed by KP and CT; conversely, KP was the most effective in improving daily function and quality of life and decreasing the incidence of new fractures, followed by VP and CT. CONCLUSION: VP might be the best option when pain relief is the principle aim of therapy, but KP was associated with the lowest risk of new fractures and might offer better outcomes in terms of daily function and quality of life.

Potentiation of the antitumor activity of adriamycin against osteosarcoma by cannabinoid WIN-55,212-2.

Osteosarcoma is the most frequent primary malignant bone tumor that occurs in children and adolescents. The present study aimed to identify novel therapeutic strategies for osteosarcoma, by assessing the antitumor activity of the cannabinoid WIN-55,212-2 and its combined effect with adriamycin (ADM) against the MG-63 human osteosarcoma cell line. To evaluate the antiproliferative action of these molecules, a Cell Counting kit-8 (CCK-8) assay was used. The ability of cannabinoid to inhibit the migration, invasion and angiogenic activity of MG-63 cells were assessed by scratch, Transwell® chamber and angiogenesis assays, respectively, in vitro. To examine the alterations in expression of targeted genes, quantitative polymerase chain reaction and western blot analysis were used. The administration of cannabinoid combined with ADM was demonstrated to inhibit the growth of MG-63 cells, resulting in a cell viability of 32.12±3.13%, which was significantly lower (P<0.05) compared with the cell viability following treatment with cannabinoid (70.86±7.55%) and ADM (62.87±5.98%) alone. Greater antimetastasis and antiangiogenic activities were also observed following the coadministration of the two agents compared with individual treatments and controls. In addition, the expression levels of Notch-1, matrix metalloproteinase-2 (MMP-2) and vascular endothelial growth factor (VEGF) in MG-63 cells were downregulated following the treatments with cannabinoid alone or in combination with ADM. In conclusion, the present findings demonstrated that cannabinoid WIN-55,212-2 may significantly potentiate the antiproliferative, antimetastasis and antiangiogenic effects of ADM against MG-63 cells via the downregulation of Notch-1, MMP-2 and VEGF. These findings may offer a novel strategy for the treatment of osteosarcoma.