Enhanced Antitumor Efficacy of Novel Biomimetic Platelet Membrane-Coated Tetrandrine Nanoparticles in Nonsmall Cell Lung Cancer.

Nonsmall cell lung cancer (NSCLC) remains one of the leading causes of cancer-related death worldwide, posing a serious threat to global health. Tetrandrine (Tet) is a small molecule in traditional Chinese medicine with proven primary efficacy against multiple cancers. Although previous studies have demonstrated the potential anticancer effects of Tet on NSCLC, its poor water solubility has limited its further clinical application. Herein, a novel nanoparticle-based drug delivery system, platelet membrane (PLTM)-coated Tet-loaded polycaprolactone-b-poly(ethylene glycol)-b-polycaprolactone nanoparticles (PTeNPs), is proposed to increase the potency of Tet against NSCLC. First, tetrandrine nanoparticles (TeNPs) are created using an emulsion solvent evaporation method, and biomimetic nanoparticles (PTeNPs) are prepared by coating the nanoparticles with PLTMs. When coated with PLTMs, PTeNPs are considerably less phagocytized by macrophages than Tet and TeNPs. In addition, compared with Tet and TeNPs, PTeNPs can significantly inhibit the growth and invasion of NSCLC both in vitro and in vivo. With reliable biosafety, this drug delivery system provides a new method of sustained release and efficient anticancer effects against NSCLC, facilitating the incorporation of Tet in modern nanotechnology.

Biochemical responses of freshwater microalgae Chlorella sorokiniana to combined exposure of Zn(â ¡) and estrone with simultaneous pollutants removal.

With the development of livestock industry, contaminants such as divalent zinc ions (Zn (Ⅱ)) and estrone are often simultaneously detected in livestock wastewater. Nevertheless, the combined toxicity of these two pollutants on microalgae is still unclear. Moreover, microalgae have the potential for biosorption and bioaccumulation of heavy metals and organic compounds. Thus, this study investigated the joint effects of Zn (Ⅱ) and estrone on microalgae Chlorella sorokiniana, in terms of growth, photosynthetic activity and biomolecules, as well as pollutants removal by algae. Interestingly, a low Zn (Ⅱ) concentration promoted C. sorokiniana growth and photosynthetic activity, while the high concentration experienced inhibition. As the increase of estrone concentration, chlorophyll a content increased continuously to resist the environmental stress. Concurrently, the secretion of extracellular polysaccharides and proteins by algae increased with exposure to Zn (Ⅱ) and estrone, reducing toxicity of pollutants to microalgae. Reactive oxygen species and superoxide dismutase activity increased as the increase of pollutant concentration after 96 h cultivation, but high pollutant concentrations resulted in damage of cells, as proved by increased MDA content. Additionally, C. sorokiniana displayed remarkable removal efficiency for Zn (Ⅱ) and estrone, reaching up to 86.14% and 84.96% respectively. The study provides insights into the biochemical responses of microalgae to pollutants and highlights the potential of microalgae in pollutants removal.

Round-Efficient Secure Inference Based on Masked Secret Sharing for Quantized Neural Network.

Existing secure multiparty computation protocol from secret sharing is usually under this assumption of the fast network, which limits the practicality of the scheme on the low bandwidth and high latency network. A proven method is to reduce the communication rounds of the protocol as much as possible or construct a constant-round protocol. In this work, we provide a series of constant-round secure protocols for quantized neural network (QNN) inference. This is given by masked secret sharing (MSS) in the three-party honest-majority setting. Our experiment shows that our protocol is practical and suitable for low-bandwidth and high-latency networks. To the best of our knowledge, this work is the first one where the QNN inference based on masked secret sharing is implemented.

Efficient Privacy-Preserving K-Means Clustering from Secret-Sharing-Based Secure Three-Party Computation.

Privacy-preserving machine learning has become an important study at present due to privacy policies. However, the efficiency gap between the plain-text algorithm and its privacy-preserving version still exists. In this paper, we focus on designing a novel secret-sharing-based K-means clustering algorithm. Particularly, we present an efficient privacy-preserving K-means clustering algorithm based on replicated secret sharing with honest-majority in the semi-honest model. More concretely, the clustering task is outsourced to three semi-honest computing servers. Theoretically, the proposed privacy-preserving scheme can be proven with full data privacy. Furthermore, the experimental results demonstrate that our proposed privacy version reaches the same accuracy as the plain-text one. Compared to the existing privacy-preserving scheme, our proposed protocol can achieve about 16.5×-25.2× faster computation and 63.8×-68.0× lower communication. Consequently, the proposed privacy-preserving scheme is suitable for secret-sharing-based secure outsourced computation.

Lattice-Based Logarithmic-Size Non-Interactive Deniable Ring Signatures.

Deniable ring signature can be regarded as group signature without group manager, in which a singer is capable of singing a message anonymously, but, if necessary, each ring member is allowed to confirm or disavowal its involvement in the signature via an interactive mechanism between the ring member and the verifier. This attractive feature makes the deniable ring signature find many applications in the real world. In this work, we propose an efficient scheme with signature size logarithmic to the cardinality of the ring. From a high level, we adapt Libert et al.'s zero-knowledge argument system (Eurocrypt 2016) to allow the prover to convince the verifier that its witness satisfies an additional condition. Then, using the Fait-Shamir transformation, we get a non-interactive deniable ring signature scheme that satisfies the anonymity, traceability, and non-frameability under the small integer solution assumption in the random oracle model.

Recognition, Intervention, and Monitoring of Neutrophils in Acute Ischemic Stroke.

Neutrophils are implicated in numerous inflammatory diseases, and especially in acute ischemic stroke (AIS). The unchecked migration of neutrophils into cerebral ischemic regions, and their subsequent release of reactive oxygen species, are considered the primary causes of reperfusion injury following AIS. Reducing the infiltration of inflammatory neutrophils may therefore be a useful therapy for AIS. Here, inspired by the specific cell-cell recognition that occurs between platelets and inflammatory neutrophils, we describe platelet-mimetic nanoparticles (PTNPs) that can be used to directly recognize, intervene, and monitor inflammatory neutrophils in the AIS treatment and therapeutic evaluation. We demonstrate that PTNPs, coloaded with piceatannol, a selective spleen tyrosine kinase inhibitor, and superparamagnetic iron oxide (SPIO), a T2 contrast agent, can successfully recognize adherent neutrophils via platelet membrane coating. The loaded piceatannol could then be delivered to adherent neutrophils and detach them into circulation, thus decreasing neutrophil infiltration and reducing infarct size. Moreover, when coupled with magnetic resonance imaging, internalized SPIO could be used to monitor the inflammatory neutrophils, associated with therapeutic effects, in real time. This approach is an innovative method for both the treatment and therapeutic evaluation of AIS, and provides new insights into how to treat and monitor neutrophil-associated diseases.

Two-Party Privacy-Preserving Set Intersection with FHE.

A two-party private set intersection allows two parties, the client and the server, to compute an intersection over their private sets, without revealing any information beyond the intersecting elements. We present a novel private set intersection protocol based on Shuhong Gao's fully homomorphic encryption scheme and prove the security of the protocol in the semi-honest model. We also present a variant of the protocol which is a completely novel construction for computing the intersection based on Bloom filter and fully homomorphic encryption, and the protocol's complexity is independent of the set size of the client. The security of the protocols relies on the learning with errors and ring learning with error problems. Furthermore, in the cloud with malicious adversaries, the computation of the private set intersection can be outsourced to the cloud service provider without revealing any private information.

A New Algorithm for Medical Color Images Encryption Using Chaotic Systems.

In this paper, we present a new algorithm based on chaotic systems to protect medical images against attacks. The proposed algorithm has two main parts: A high-speed permutation process and adaptive diffusion. After the implementation of the algorithm in the MATLAB software, it is observed that the algorithm is effective and appropriate. Also, to quantitatively evaluate the uniformity of the histogram, the chi-square test is done. Key sensitivity analysis demonstrates that images cannot be decrypted whenever a small change happens in the key, which indicates that the algorithm is suitable. Clearly, part of special images is selected to test the selected plain-text, like an all-white image and an all-black image. Entropy results obtained from the implementation of the algorithm on this type of images show that the proposed method is suitable for this particular type of images. In addition, the obtained results from noise and occlusion attacks analysis show that the proposed algorithm can withstand against these types of attacks. Moreover, it can be seen that the images after encryption and decryption are of good quality; the measures such as the correlation coefficients, the entropy, the number of pixel change rate (NPCR), and the uniform average change intensity (UACI) have suitable values; and the method is better than previous methods.

Microalgae cultivation with recycled harvesting water achieved economic and sustainable production of biomass and lipid: Feasibility assessment and inhibitory factors analysis.

This study was conducted to achieve economic and sustainable production of biomass and lipids from Chlorella sorokiniana by recirculating cultivation with recycled harvesting water, to identify the major inhibitory factors in recirculating culture, and to analyze accordingly economic benefits. The results showed that recirculating microalgae cultivation (RMC) could obtain 0.20-0.32 g/L biomass and lipid content increased by 23.1 %-38.5 %. Correlation analysis showed that the extracellular polysaccharide (PSext), chemical oxygen demand (COD) and chromaticity of recirculating water inhibited photosynthesis and induced oxidative stress, thus inhibiting the growth of C. sorokiniana. In addition, the economic benefits analysis found that circulating the medium twice could save about 30 % of production cost, which is the most economical RMC solution. In conclusion, this study verified the feasibility and economy of RMC, and provided a better understanding of inhibitory factors identification in culture.

Cancer cell membrane-camouflaged biomimetic nanoparticles for enhancing chemo-radiation therapy efficacy in glioma.

Glioblastoma multiforme (GBM) presents significant challenges in treatment, with current standard-of-care approaches offering limited efficacy and survival benefits. This necessitates the development of innovative therapeutic strategies to enhance treatment outcomes. Nanotechnology has emerged as a promising avenue in cancer therapy, offering targeted drug delivery and enhanced therapeutic efficacy. Polymeric nanoparticles, particularly those based on Poly (lactic-co-glycolic acid) (PLGA), have gained traction as drug carriers due to their biocompatibility and controlled release properties. However, their interception by macrophages poses challenges to effective drug delivery. Superparamagnetic iron oxide (SPIO) nanoparticles have shown promise as radiosensitizers, enhancing the efficacy of radiotherapy through the generation of reactive oxygen species (ROS). Moreover, cell membrane biomimetic drug delivery systems have garnered attention for their ability to improve biocompatibility and targeting capabilities. Leveraging these concepts, our study introduces a novel multifunctional platform, GM@P (T/S), comprising polymeric nanoparticles coated with cancer cell membrane. By encapsulating temozolomide (TMZ) and SPIO nanoparticles within GM@P (T/S), we aim to synergistically enhance the cytotoxic effects of chemotherapy and radiotherapy against GBM while overcoming limitations associated with conventional treatments. This innovative approach holds promise for addressing the unmet clinical needs in GBM therapy and advancing towards more effective and personalized treatment strategies.

Performance evaluation of typical flocculants for efficient harvesting of Chlorella sorokiniana under different carbon application modes.

In this study, the growth characteristics of microalgae cultured with different carbon sources were analyzed, and the flocculation characteristics under the influence of carbon sources were evaluated using three typical flocculants. The results showed that the organic carbon sources could significantly increase the content of extracellular proteins in microalgae. Specifically, the extracellular protein concentrations of microalgae cultured with pure BG-11, ethanol, sodium acetate and glucose were 18.2 29.2, 97.3, and 34.7 mg/g, respectively. During the flocculation process, microalgae cultured with sodium acetate exhibited a weak response to the flocculant because of excessive extracellular proteins inhibited flocculation. In addition, the flocculation efficiency was also less than 50.0% cultured with sodium acetate in all pH test ranges when alum and chitosan were used as flocculants. It could be inferred that the flocculant initially happened to charge neutralization with the negatively charged proteins in the solution and then bridged the charges with the microalgae. These findings provide insights into the effects of different carbon sources on microalgal flocculation, promising organic integration of microalgae wastewater treatment and harvesting.

[Study on method of tracking the active cells in image sequences based on EKF-PF].

In cell image sequences, due to the nonlinear and nonGaussian motion characteristics of active cells, the accurate prediction and tracking is still an unsolved problem. We applied extended Kalman particle filter (EKF-PF) here in our study, attempting to solve the problem. Firstly we confirmed the existence and positions of the active cells. Then we established a motion model and improved it via adding motion angle estimation. Next we predicted motion parameters, such as displacement, velocity, accelerated velocity and motion angle, in region centers of the cells being tracked. Finally we obtained the motion traces of active cells. There were fourteen active cells in three image sequences which have been tracked. The errors were less than 2.5 pixels when the prediction values were compared with actual values. It showed that the presented algorithm may basically reach the solution of accurate predition and tracking of the active cells.

Towards advanced nutrient removal by microalgae-bacteria symbiosis system for wastewater treatment.

In this study, the microalgae-bacteria symbiosis (ABS) system by co-culturing Chlorella sorokiniana with activated sludge was constructed for pollutants removal, and the according interaction mechanism was investigated. The results showed that the ABS system could almost completely remove ammonia nitrogen, and the removal efficiency of total nitrogen and total phosphorus could accordingly reach up to 65.3 % and 42.6 %. Brevundimonas greatly promoted microalgal biomass growth (maximum chlorophyll-a concentration of 9.4 mg/L), and microalgae contributed to the increase in the abundance of Dokdonella and Thermomonas in ABS system, thus facilitating nitrogen removal. The extended Derjaguin-Landau-Verwey-Overbeek theory indicated a repulsive potential barrier of 561.7 KT, while tryptophan-like proteins and tyrosine-like proteins were key extracellular polymeric substances for the formation of flocs by microalgae and activated sludge. These findings provide an in-depth understanding of interaction mechanism between microalgae and activated sludge for the removal of contaminants from wastewater.

Nutrient removal and lipid production by the co-cultivation of Chlorella vulgaris and Scenedesmus dimorphus in landfill leachate diluted with recycled harvesting water.

Applying microalgae for landfill leachate (LL) treatment is promising. However, LL usually needs to be diluted with much fresh water, aggravating water shortage. In this study, mono- and co-culturing microalgae (Chlorella vulgaris and Scenedesmus dimorphus) were used to treat LL diluted with recycled harvesting water, to investigate nutrient removal and lipid production. The results showed that microalgae in co-culture treatment had more biomass and stronger superoxide dismutase activity, which might be related to humic acids contained in recycled harvesting water, according to dissolved organic matters (DOMs) analysis. In addition, the lipid content and yield of co-cultured microalgae reached 27.60 % and 66.87 mg·L-1, respectively, higher than those of mono-culture, proving the potential of co-culture for the improvement of lipid production. This study provided a freshwater-saving dilution method for LL treatment with recycled harvesting water as well as a strategy for the increase of biomass and lipid accumulation by microalgae co-cultivation.

Responses of microalgae under different physiological phases to struvite as a buffering nutrient source for biomass and lipid production.

Microalgae cultivation for biodiesel production is promising, but the high demand for nutrients, such as nitrogen and phosphorus, remains a limiting factor. This study investigated effects of struvite, a low-cost nutrient source, on microalgae production under different physiological phases. Changes in element concentrations were determined to characterize the controllable nutrient release properties of struvite. Results showed that nutrient elements could be effectively supplemented by struvite. However, responses of microalgae under different growth stages to struvite varied obviously, achieving the highest biomass (0.53 g/L) and the lowest (0.32 g/L). Moreover, the microalgal lipid production was obviously increased by adding struvite during the growth phase, providing the first evidence that struvite could serve as an alternative buffering nutrient source to culture microalgae. The integration of microalgae cultivation with struvite as a buffering nutrient source provides a novel strategy for high ammonia nitrogen wastewater treatment with microalgae for biodiesel production.

[Tracking of neural stem cells in high density image sequence based on Topological constraint combined with Hungarian algorithm].

Analysis of neural stem cells' movements is one of the important parts in the fields of cellular and biological research. The main difficulty existing in cells' movement study is whether the cells tracking system can simultaneously track and analyze thousands of neural stem cells (NSCs) automatically. We present a novel cells' tracking algorithm which is based on segmentation and data association in this paper, aiming to improve the tracking accuracy further in high density NSCs' image. Firstly, we adopted different methods of segmentation base on the characteristics of the two cell image sequences in our experiment. Then we formed a data association and constituted a coefficient matrix by all cells between two adjacent frames according to topological constraints. Finally we applied The Hungarian algorithm to implement inter-cells matching optimally. Cells' tracking can be achieved according to this model from the second frame to the last one in a sequence. Experimental results showed that this approaching method has higher accuracy compared with that using the topological constraints tracking alone. The final tracking accuracies of average of sequence I and sequence II have been improved 10.17% and 4%, respectively.

Mean trapping time for an arbitrary trap site on a class of fractal scale-free trees.

Fractals are ubiquitous in nature and random walks on fractals have attracted lots of scientific attention in the past several years. In this work, we consider discrete random walks on a class of fractal scale-free trees (FST), whose topologies are controlled by two integer parameters (i.e., u≥2 and v≥1) and exhibit a wide range of topological properties by suitably varying the parameters u and v. The mean trapping time (MTT), referred to as T_{y}, which is the mean time it takes the walker to be absorbed by the trap fixed at site y of the FST, is addressed analytically on the FST, and the effects of the trap location y on the MTT for the FST and for the general trees are also analyzed. First, a method, which is based on the connection between the MTT and the effective resistances, to derive analytically T_{y} for an arbitrary site y of the FST is presented, and some examples are provided to show the effectiveness of the method. Then, we compare T_{y} for all the possible site y of the trees, and find the sites where T_{y} achieves the minimum (or maximum) on the FST. Finally, we analyze the effects of trap location on the MTT in general trees and find that the average path length (APL) from an arbitrary site to the trap is the decisive factor which dominates the difference in the MTTs for different trap locations on general trees. We find, for any tree, the MTT obtains the minimum (or maximum) at sites where the APL achieves the minimum (or maximum).

Microalgal cultivation for the upgraded biogas by removing CO2, coupled with the treatment of slurry from anaerobic digestion: A review.

Biogas is the gaseous by product generated from anaerobic digestion (AD), which is mainly composed of methane and CO2. Numerous independent studies have suggested that microalgae cultivation could achieve high efficiency for nutrient uptake or CO2 capture from AD, respectively. However, there is no comprehensive review on the purifying slurry from AD and simultaneously upgrading biogas via microalgal cultivation technology. This paper aims to fill this gap by presenting and discussing an information integration system based on microalgal technology. Furthermore, the review elaborates the mechanisms, configurations, and influencing factors of integrated system and analyzes the possible challenges for practical engineering applications and provides some feasibility suggestions eventually. There is hope that this review will offer a worthwhile and practical guideline to researchers, authorities and potential stakeholders, to promote this industry for sustainable development.

Enhanced antitumor effect of icariin nanoparticles coated with iRGD functionalized erythrocyte membrane.

Lung cancer is the most common cause of incidence and mortality among tumor diseases. Icariin (ICA), a potential Chinese medicine monomer, has been reported to show outstanding antitumor effects. However, the hydrophobic nature and less tumor penetration limit its potential as a topical healing agent. There are few studies report the efficacy of ICA on lung cancer, moreover, there is no biomimetic targeted delivery system in the application of ICA. Herein, we firstly develop a novel ICA bionic targeted nano-preparation, camouflaged by the tumor penetrating peptide iRGD (cRGDKGPDC), functionalized red blood cell membrane (RBCM), has the increased solubility, utilized biocompatibility, and aggravated tumor penetration of ICA. In this study, we constructed the iRGD functionalized RBCM mimetic targeted ICA-loaded nanoparticles (iRINPs) and explored the anti-tumor effect of iRINPs against lung cancer with biochemical and behavioral analysis. The results suggested that iRINPs showed improved biocompatibility and stability, and reduced phagocytic uptakes by macrophages. Besides, the modification of iRGD significantly improved the targeting ability of iRINPs. In vitro and in vivo the treatment effects and safety assays showed that iRINPs attained better therapeutic effects than ICA by inhibiting A549 cell migration, proliferation and invasion, as well as reducing side effects of ICA. Overall, we expected that the new bionic nanocarriers would be a promising nano-platform for ICA in the precise therapy of lung cancer.

Biomimetic Red Blood Cell Membrane-Mediated Nanodrugs Loading Ursolic Acid for Targeting NSCLC Therapy.

As one of the most common cancers worldwide, non-small-cell lung cancer (NSCLC) treatment always fails owing to the tumor microenvironment and resistance. UA, a traditional Chinese medicine, was reported to have antitumor potential in tumor models in vitro and in vivo, but showed impressive results in its potential application for poor water solubility. In this study, a novel biomimetic drug-delivery system based on UA-loaded nanoparticles (UaNPs) with a red blood cell membrane (RBCM) coating was developed. The RBCM-coated UANPs (UMNPs) exhibited improved water solubility, high stability, good biosafety, and efficient tumor accumulation. Importantly, the excellent antitumor efficiency of the UMNPs was confirmed both in vitro and in vivo in cancer models. In addition, we further investigated the antitumor mechanism of UMNPs. The results of Western blotting showed that UMNPs exerted an anticancer effect by inducing the apoptosis and autophagy of NSCLC cells, which makes it superior to free UA. In addition, body weight monitoring, hematoxylin and eosin (HE) analysis, and immunohistochemical (IHC) analysis showed no significant difference between UMNPs and the control group, indicating the safety of UMNPs. Altogether, the preparation of biomimetic UMNPs provides a promising strategy to improve outcomes in NSCLC.