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Abstract The poor prognosis of hepatocellular carcinoma (HCC) is still an urgent challenge to be solved worldwide. Hence, assembling drugs and targeted short peptides together to construct a novel medicine delivery strategy is crucial for targeted and synergy therapy of HCC. Herein, a high-efficiency nanomedicine delivery strategy has been constructed by combining graphdiyne oxide (GDYO) as a drug-loaded platform, specific peptide (SP94-PEG) as a spear to target HCC cells, sorafenib, doxorubicin-Fe2+ (DOX-Fe2+), and siRNA (SLC7A11-i) as weapons to exert a three-path synergistic attack against HCC cells. In this work, SP94-PEG and GDYO form nanosheets with HCC-targeting properties, the chemotherapeutic drug DOX linked to ferrous ions increases the free iron pool in HCC cells and synergizes with sorafenib to induce cell ferroptosis. As a key gene of ferroptosis, interference with the expression of SLC7A11 makes the ferroptosis effect in HCC cells easier, stronger, and more durable. Through gene interference, drug synergy, and short peptide targeting, the toxic side effects of chemotherapy drugs are reduced. The multifunctional nanomedicine GDYO@SP94/DOX-Fe2+/sorafenib/SLC7A11-i (MNMG) possesses the advantages of strong targeting, good stability, the ability to continuously induce tumor cell ferroptosis and has potential clinical application value, which is different from traditional drugs.

The development of neurodegenerative diseases is closely related to the disruption of central nervous system homeostasis. Microglia, as innate immune cells, play important roles in the maintenance of central nervous system homeostasis, injury response, and neurodegenerative diseases. Lactate has been considered a metabolic waste product, but recent studies are revealing ever more of the physiological functions of lactate. Lactylation is an important pathway in lactate function and is involved in glycolysis-related functions, macrophage polarization, neuromodulation, and angiogenesis and has also been implicated in the development of various diseases. This review provides an overview of the lactate metabolic and homeostatic regulatory processes involved in microglia lactylation, histone versus non-histone lactylation, and therapeutic approaches targeting lactate. Finally, we summarize the current research on microglia lactylation in central nervous system diseases. A deeper understanding of the metabolic regulatory mechanisms of microglia lactylation will provide more options for the treatment of central nervous system diseases.

The intricate task of precisely segmenting retinal vessels from images, which is critical for diagnosing various eye diseases, presents significant challenges for models due to factors such as scale variation, complex anatomical patterns, low contrast, and limitations in training data. Building on these challenges, we offer novel contributions spanning model architecture, loss function design, robustness, and real-time efficacy. To comprehensively address these challenges, a new U-Net-like, lightweight Transformer network for retinal vessel segmentation is presented. By integrating MobileViT+ and a novel local representation in the encoder, our design emphasizes lightweight processing while capturing intricate image structures, enhancing vessel edge precision. A novel joint loss is designed, leveraging the characteristics of weighted cross-entropy and Dice loss to effectively guide the model through the task's challenges, such as foreground-background imbalance and intricate vascular structures. Exhaustive experiments were performed on three prominent retinal image databases. The results underscore the robustness and generalizability of the proposed LiViT-Net, which outperforms other methods in complex scenarios, especially in intricate environments with fine vessels or vessel edges. Importantly, optimized for efficiency, LiViT-Net excels on devices with constrained computational power, as evidenced by its fast performance. To demonstrate the model proposed in this study, a freely accessible and interactive website was established (https://hz-t3.matpool.com:28765?token=aQjYR4hqMI), revealing real-time performance with no login requirements.

Abstract Background Tumor cells have the ability to invade and form small clusters that protrude into adjacent tissues, a phenomenon that is frequently observed at the periphery of a tumor as it expands into healthy tissues. The presence of these clusters is linked to poor prognosis and has proven challenging to treat using conventional therapies. We previously reported that p60AmotL2 expression is localized to invasive colon and breast cancer cells. In vitro, p60AmotL2 promotes epithelial cell invasion by negatively impacting E-cadherin/AmotL2-related mechanotransduction. Methods Using epithelial cells transfected with inducible p60AmotL2, we employed a phenotypic drug screening approach to find compounds that specifically target invasive cells. The phenotypic screen was performed by treating cells for 72 h with a library of compounds with known antitumor activities in a dose-dependent manner. After assessing cell viability using CellTiter-Glo, drug sensitivity scores for each compound were calculated. Candidate hit compounds with a higher drug sensitivity score for p60AmotL2-expressing cells were then validated on lung and colon cell models, both in 2D and in 3D, and on colon cancer patient-derived organoids. Nascent RNA sequencing was performed after BET inhibition to analyse BET-dependent pathways in p60AmotL2-expressing cells. Results We identified 60 compounds that selectively targeted p60AmotL2-expressing cells. Intriguingly, these compounds were classified into two major categories: Epidermal Growth Factor Receptor (EGFR) inhibitors and Bromodomain and Extra-Terminal motif (BET) inhibitors. The latter consistently demonstrated antitumor activity in human cancer cell models, as well as in organoids derived from colon cancer patients. BET inhibition led to a shift towards the upregulation of pro-apoptotic pathways specifically in p60AmotL2-expressing cells. Conclusions BET inhibitors specifically target p60AmotL2-expressing invasive cancer cells, likely by exploiting differences in chromatin accessibility, leading to cell death. Additionally, our findings support the use of this phenotypic strategy to discover novel compounds that can exploit vulnerabilities and specifically target invasive cancer cells.

Abstract Background Inflammation in the eye is often associated with aggravated ocular diseases such as uveal melanoma (UM). Poor prognosis of UM is generally associated with high potential of metastatic liver dissemination. A strong driver of metastatic dissemination is the activation of the epithelial-mesenchymal transition (EMT) regulating transcription factor ZEB1, and high expression of ZEB1 is associated with aggressiveness of UM. While ZEB1 expression can be also associated with immune tolerance, the underlying drivers of ZEB1 activation remain unclear. Methods Transcriptomic, in vitro, ex vivo, and in vivo analyses were used to investigate the impact on clinical prognosis of immune infiltration in the ocular tumor microenvironment. A metastatic liver dissemination model of was developed to address the role of natural killer (NK) cells in driving the migration of UM. Results In a pan-cancer TCGA analysis, natural killer (NK) cells were associated with worse overall survival in uveal melanoma and more abundant in high-risk monosomy 3 tumors. Furthermore, uveal melanoma expressed high levels of the tumor necrosis factor superfamily member 4-1BB ligand, particularly in tumors with monosomy 3 and BAP1 mutations. Tumors expressing 4-1BB ligand induced CD73 expression on NK cells accompanied with the ability to promote tumor dissemination. Through ligation of 4-1BB, NK cells induced the expression of the ZEB1 transcription factor, leading to the formation of liver metastasis of uveal melanoma. Conclusions Taken together, the present study demonstrates a role of NK cells in the aggravation of uveal melanoma towards metastatic disease.

Abstract Background Few studies have analyzed the clinical characteristics and adverse factors affecting prognosis in older patients with tuberculous meningitis (TBM). This study aimed to compare the clinical characteristics of TBM in older patients with those in younger and middle-aged patients. Methods This single-center retrospective study extracted data on the clinical features, cerebrospinal fluid changes, laboratory results, imaging features, and outcomes of patients with TBM from patient medical records and compared the findings in older patients (aged 60 years and older) with those of younger and middle-aged patients (aged 18–59 years). Results The study included 197 patients with TBM, comprising 21 older patients aged 60–76 years at onset, and 176 younger and middle-aged patients aged 18–59 years at onset. Fever was common in both older (81%) and younger and middle-aged patients (79%). Compared with younger and middle-aged patients, older patients were more likely to have changes in awareness levels (67% vs. 40%), peripheral nerve dysfunction (57% vs. 29%), changes in cognitive function (48% vs. 20%), and focal seizures (33% vs. 6%), and less likely to have headache (71% vs. 93%), neck stiffness on meningeal stimulation (38% vs. 62%), and vomiting (47% vs. 68%). The Medical Research Council staging on admission of older patients was stage II (52%) and stage III (38%), whereas most younger and middle-aged patients had stage I (33%) and stage II (55%) disease. Neurological function evaluated on the 28th day of hospitalization was more likely to show poor prognosis in older patients than in younger and middle-aged patients (76% vs. 25%). Older patients had significantly higher red blood cell counts and blood glucose levels, and significantly lower serum albumin and sodium levels than those in younger and middle-aged patients. The cerebrospinal fluid protein levels, nucleated cell counts, glucose levels, and chloride levels did not differ significantly by age. Conclusion In patients with TBM, older patients have more severe clinical manifestations, a higher incidence of hydrocephalus and cerebral infarction, and longer hospital stays than younger and middle-aged patients. Older patients thus require special clinical attention.

Abstract To achieve a green and sustainable wireless communication network, the reconfigurable intelligent surface (RIS) technology has emerged as an emerging technology. The RIS-assisted mmWave massive MIMO vehicle-to-everything (V2X) communications can support enhanced V2X applications for connected and automated vehicles. The design of RIS-assisted mmWave V2X communications is though not exempt of challenges as a result of fast time-varying propagation and highly dynamic vehicular networks and topologies. To address some of these challenges, we propose an attention-deep reinforcement learning jointly beamforming based on tensor decomposition for RIS-assisted mmWave massive MIMO system to improving the safety and traffic efficiency of cooperative automated driving. The received signal of the vehicle is decomposed into four-dimensional tensors and study the channel, frequency and time attention (CFTA) algorithm using the low order tensor characteristics of mmWave channels. This algorithm can extract the frequency and time characteristics of the channel, and obtain the millimeter wave characteristic channel between the corresponding base station (BS) and the vehicles. The problem of jointly optimization of beamforming matrix at the BS and the phase shift matrix on the RIS is constructed and solved using deep reinforcement learning (DRL). Unlike traditional alternating optimization methods, the integration of DRL techniques into the optimal design of the system enables the observation of immediate rewards, learning from the environment and improving it to obtain optimal solutions to high-dimensional jointly beamforming optimization problems ultimately. The simulation results show that the proposed algorithm has meaningful performance compared with other methods.

Abstract Background Predicting the short-term prognosis and severity of tuberculosis meningitis (TBM) patients without HIV infection can be challenging, and there have been no prior studies examining the neutrophil lymphocyte ratio (NLR) as a potential predictor of short-term prognosis or its relationship to TBM severity. We hypothesized that NLR might serve as an independent indicator of short-term prognostic significance and that there might be a correlation between NLR and severity. The aim of this study was to investigate the role of NLR as a predictor of short-term prognosis and its relationship to severity of tuberculosis meningitis patients without HIV infection. Methods We retrospectively collected data from patients diagnosed with TBM in the West China Hospital, Sichuan University, from the period between January 1st, 2018 and August 1st, 2019. Multivariable analysis was executed by the logistic regression model to verify the independence of the 28-day mortality, the discriminative power for predicting short-term prognosis was evaluated using a Receiver Operating Characteristic (ROC) curve, survival outcomes were analyzed using the Kaplan-Meier method and Pearson’s correlation analysis was performed to discuss correlation between NLR and the severity of TBM. Results We collected data from 231 TBM patients without HIV infection. 68 (29.4%) patients are classified as stage (I) 138(59.8%) patients are stage (II) 25(10.8%) patients are stage (III) 16(6.9%) patients died during the follow-up period of 28 days. By multiple logistic regression analyses, the NLR (OR = 1.065, 95% CI = 1.001–1.133, P = 0.045), peripheral neurological deficit (OR 7.335, 95% CI 1.964–27.385, P = 0 0.003) and hydrocephalus (OR 11.338, 95% CI 2.397–53.633, P = 0 0.002) are independent risk factors of 28-day mortality. The area under the ROC curve (AUC) for predicting short prognosis using NLR is 0.683 (95% CI 0.540–0.826, P = 0.015), the optimal cutoff value is 9.99(sensitivity: 56.3%, specificity: 80.9%). The Kaplan-Meier analysis demonstrated that patients with higher NLR(>9.99) had significantly worse survival outcomes(P

ABSTRACTInfusion of natural killer (NK) cells is an attractive therapeutic modality in patients with cancer. However, the activity of NK cells is regulated by several mechanisms operating within solid tumors. Regulatory T (Treg) cells suppress NK cell activity through various mechanisms including deprivation of IL-2 via the IL-2 receptor alpha (CD25). Here, we investigate CD25 expression on NK cells to confer persistence in Treg cells containing solid tumor models of renal cell carcinoma (RCC). Compared with IL-2, stimulation with IL-15 increases the expression of CD25 resulting in enhanced response to IL-2 as evidenced by increased phosphorylation of STAT5. Compared with CD25dim NK cells, CD25bright NK cells isolated from IL-15 primed NK cells display increased proliferative and metabolic activity as well as increased ability to persist in Treg cells containing RCC tumor spheroids. These results support strategies to enrich for or selectively expand CD25bright NK cells for adoptive cellular therapy of NK cells.

Stroke is a high-morbidity central nervous system disease. Its complex pathological process often leads to impaired consciousness, disability and even death. Currently, stroke is treated mainly by thrombolysis, and treatment for its complications, and treatment for pathological processes within the stroke lesion is lacking. This is mainly because most drugs are unable to cross the blood–brain barrier (BBB) to reach the site of injury to exert their therapeutic effects. Therefore, this study aims to develop biomimetic nanocladding devices capable of crossing the BBB, targeting the site of injury, and blocking the pathological process. Since the injury site is a highly inflammatory area, we selected the apoptotic body membrane (ABm) of activated T cells with inflammatory targeting ability to prepare biomimetic nanocladding devices (BND) and use them as the carriers to carry catalase (CAT) (BND-CAT) for the treatment of stroke rats. The results show that BND can not only target inflammatory lesions, but also regulate the transformation of microglia subtypes, thereby inhibiting inflammation within the lesions. In addition, BND-CAT could also inhibit oxidative stress, protect the mitochondria, increase the ATP content in the lesion, suppress the endoplasmic reticulum stress, and ultimately inhibit the apoptosis of neurons in the lesion.

Spinal cord injury (SCI) is a serious central nervous system disease, and secondary injury, including oxidative stress, the inflammatory response and accompanying neuronal apoptosis, will aggravate the condition. Due to the existence of the blood–spinal cord barrier (BSCB), the existing drugs for SCI treatment are difficulty to reach the injury site and thus their efficacy is limited. In this study, we designed chitosan-modified hollow manganese dioxide nanoparticles (CM) for the delivery of resveratrol to help it pass through the BSCB. Resveratrol (Res), a poorly soluble drug, was adsorbed into CM with a particle size of approximately 130 nm via the adsorption method, and the drug loading reached 21.39 ± 2.53%. In vitro dissolution experiment, the Res release of the loaded sample (CMR) showed slowly release behavior and reached about 87% at 36 h. In vitro at the cellular level and in vivo at the animal level experiments demonstrated that CMR could alleviate significantly oxidative stress by reducing level of reactive oxygen species (ROS), malondialdehyde (MDA), superoxide dismutase (SOD), and increasing glutathione peroxidase (GSH) level. Additionally, immunofluorescence (iNOS, IL-1β, and Cl caspase-3) and western blot (iNOS, cox-2, IL-1β, IL-10, Cl caspase-3, bax, and bcl-2) were used to detect the expression of related factors, which verified that CMR could also reduce inflammation and neuronal apoptosis. These results indicated that CM, as a potential central nervous system drug delivery material, was suitable for SCI treatment.

Abstract Natural killer (NK) cells, which are innate lymphocytes endowed with potent cytotoxic activity, have recently attracted attention as potential anticancer therapeutics. While NK cells mediate encouraging responses in patients with leukemia, the therapeutic effects of NK cell infusion in patients with solid tumors are limited. Preclinical and clinical data suggest that the efficacy of NK cell infusion against solid malignancies is hampered by several factors including inadequate tumor infiltration and persistence/activation in the tumor microenvironment (TME). A number of metabolic features of the TME including hypoxia as well as elevated levels of adenosine, reactive oxygen species, and prostaglandins negatively affect NK cell activity. Moreover, cancer-associated fibroblasts, tumor-associated macrophages, myeloid-derived suppressor cells, and regulatory T cells actively suppress NK cell-dependent anticancer immunity. Here, we review the metabolic and cellular barriers that inhibit NK cells in solid neoplasms as we discuss potential strategies to circumvent such obstacles towards superior therapeutic activity.

Preserving an accurate cell count is crucial for maintaining homeostasis. Apical extrusion, a process in which redundant cells are eliminated by neighboring cells, plays a key role in this regard. Recent studies have revealed that apical extrusion can also be triggered in cells transformed by oncogenes, suggesting it may be a mechanism through which tumor cells escape their microenvironment. In previous work, we demonstrated that p60AmotL2 modulates the E-cadherin function by inhibiting its connection to radial actin filaments. This isoform of AmotL2 is expressed in invasive breast and colon tumors and promotes invasion in vitro and in vivo. Transcriptionally regulated by c-Fos, p60AmotL2 is induced by local stress signals such as severe hypoxia. In this study, we investigated the normal role of p60AmotL2 in epithelial tissues. We found that this isoform is predominantly expressed in the gut, where cells experience rapid turnover. Through time-lapse imaging, we present evidence that cells expressing p60AmotL2 are extruded by their normal neighboring cells. Based on these findings, we hypothesize that tumor cells exploit this pathway to detach from normal epithelia and invade surrounding tissues.

The decode-and-forward (DF) based free-space optical-radio frequency (FSO-RF) hybrid system combines the advantages of both FSO links and RF links, which makes the system easy to be deployed and enables the extended transmission coverage. In the case of multiple users, the unreasonable dynamic antenna selection algorithm will lead to multi-user interference (MUI) and reduce the spectral efficiency of the system. Therefore, we propose hybrid precoding based on manifold learning with the antenna partitioning algorithm for dual-hop hybrid FSO-RF systems. In the hybrid precoding of dynamic subarray structure, the high-dimensional channels are embedded into the low-dimensional manifolds by the optimized multidimensional scaling (MDS). The potential spatial correlations of the high-dimensional channel are preserved by the scaling by majorizing a complicated function (SMACOF) algorithm. Through proper user clustering, the hybrid precoding is investigated for the sum-rate maximization problem by manifold quasi-conjugate gradient methods. Meanwhile, an antenna subarray partitioning algorithm is proposed, so that each antenna unit can be assigned to an RF chain based on the increment of the user’s maximum signal to interference noise ratio (SINR). By calculating the simulated equivalent channel SINR for the selected users, the antenna division can greatly reduce the computational complexity and the size of the search space, and ensure fairness among users. Simulation results show that this method can obtain almost the best summation rate and higher spectral efficiency compared with the conventional method.

In the process of steel production, the defects on the surface of steel will adversely affect the subsequent processing of a product. Accurate detection of such defects is the key to improve production efficiency and economic benefits. In this paper, an end-to-end steel surface defect detection and size measurement system based on the YOLOv5 model is designed. Firstly, in consideration of the defect location and direction correlation in the production process, a coordinate attention mechanism is added at the head of YOLOv5 to strengthen the spatial correlation of the steel surface and an adaptive anchor box generation method based on defect shape difference feature is proposed, which realizes the detection of three main types of defects on the Pytorch deep learning framework. Secondly, BiFPN is used to strengthen the feature fusion and a transformer encoder is added to improve the performance of detecting small defects. Thirdly, calculate the conversion ratio between the pixel and the actual size according to the standard reference specimen and obtain the actual size through the pixel statistics of the defect area to achieve pixel level size measurement. Finally, the steel surface defect detection and size measurement system are designed in this paper, which consist of various hardware, related measurement, and detection algorithms. According to the experimental results, the comprehensive defect detection accuracy of this method reaches 93.6%, of which the scratch detection accuracy reaches 95.7%. The detection speed reaches 133 fps and the defect size measurement accuracy reaches 0.5 mm. Experimental result shows that the defect detection and size measurement system designed in this paper can accurately detect and measure various industrial production defects and can be applied to the actual production process.

Abstract Acid mine drainage (AMD) which produced in the process of mining seriously pollutes the water resources and endangers the ecological environment due to its physicochemical characteristics, such as low pH, high salinity and high heavy metal concentrations. In recent decades, the treatment of AMD has become a key issue in the field of environmental protection. One important method of AMD treatment is adsorption method, and the selection of adsorbent is the key of this technique. Bentonite and steel slag are usually sintered at high temperatures to prepare bentonite–steel slag composite. AMD treatment with bentonite–steel slag composite, as a new adsorbent, is emerging as a promising treatment method by physical adsorption, ion exchange and chemical neutralization. The bentonite–steel slag composites mainly include bicomponent composite with bentonite–steel slag and multicomponent composite with bentonite–steel slag modifier. The author found that this important research question was rarely paid attention to, therefore, and the author combined with previous research and theories to promote the explanation of this problem. In this review, the technology of treatment of AMD with bentonite–steel slag composite is comprehensively discussed. Also, the role of its mechanism is also discussed in-depth. This paper provides a scientific reference on the remediation of contaminated environments.

In this study, a new sulfidated nanoscale zero-valent iron (S-nZVI) supported on hydrogel (S-nZVI@H) was successfully synthesized for the removal of chromium (Cr) (VI) from groundwater. The surface morphology, dispersion phenomenon and functional groups of novel S-nZVI@H were characterized by scanning electron microscopy and Fourier transform infrared spectroscopy. Box–Behnken design (BBD) optimization technology based on response surface methodology (RSM) is applied to demonstrate the influence of the interaction of S-nZVI@H dose, initial Cr(VI) concentration, contact time, and initial pH with the Cr(VI) removal efficiency. The analysis of variance results (F = 118.73, P < 0.0001, R2 = 0.9916) show that the quadratic polynomial model is significant enough to reflect the close relationship between the experimental and predicted values. The predicted optimum removal conditions are: S-nZVI@H dose 9.46 g/L, initial Cr(VI) concentration 30 mg/L, contact time 40.7 min, and initial pH 5.27, and the S-nZVI@H dose is the key factor affecting the removal of Cr(VI). The predicted value (99.76%) of Cr (VI) removal efficiency is in good agreement with the experimental value (97.75%), which verifies the validity of the quadratic polynomial model. This demonstrates that RSM with appropriate BBD can be utilized to optimize the design of experiments for removal of Cr(VI). HIGHLIGHTS Hydrogel-supported sulfidated zero-valent iron nanoparticle (S-nZVI@H) was successfully prepared and used to remove Cr(VI) from groundwater.; The effect of the interaction of four independent variables on the removal efficiency of Cr(VI) was studied by RSM.; The optimum removal conditions and key factors for Cr(VI) removal were determined.; BBD is considered to optimize the experimental study of Cr(VI) removal by S-nZVI@H.;

Gastric cancer (GC) is a major global health issue and one of the leading causes of tumor-associated mortality worldwide. Autophagy is thought to play a critical role in the development and progression of GC, and this process is controlled by a set of conserved regulators termed autophagy-related genes (ATGs). However, the complex contribution of autophagy to cancers is not completely understood. Accordingly, we aimed to develop a prognostic model based on the specific role of ATGs in GC to improve the prediction of GC outcomes. First, we screened 148 differentially expressed ATGs between GC and normal tissues in The Cancer Genome Atlas (TCGA) cohort. Consensus clustering in these ATGs was performed, and based on that, 343 patients were grouped into two clusters. According to Kaplan–Meier survival analysis, cluster C2 had a worse prognosis than cluster C1. Then, a disease risk model incorporating nine differentially expressed ATGs was constructed based on the least absolute shrinkage and selection operator (LASSO) regression analysis, and the ability of this model to stratify patients into high- and low-risk groups was verified. The predictive value of the model was confirmed using both training and validation cohorts. In addition, the results of functional enrichment analysis suggested that GC risk is correlated with immune status. Moreover, autophagy inhibition increased sensitivity to cisplatin and exacerbated reactive oxygen species accumulation in GC cell lines. Collectively, the results indicated that this novel constructed risk model is an effective and reliable tool for predicting GC outcomes and could help with individual treatment through ATG targeting.

Downregulation of MHC class I (MHCI) molecules on tumor cells is recognized as a resistance mechanism of cancer immunotherapy. Given that MHCI molecules are potent regulators of immune responses, we postulated that the expression of MHCI by tumor cells influences systemic immune responses. Accordingly, mice-bearing MHCI-deficient tumor cells showed reduced tumor-associated extramedullary myelopoiesis in the spleen. Depletion of natural killer (NK) cells abrogated these differences, suggesting an integral role of immune-regulatory NK cells during tumor progression. Cytokine-profiling revealed an upregulation of TNF-α by NK cells in tumors and spleen in mice-bearing MHCI expressing tumors, and inhibition of TNF-α enhanced host myelopoiesis in mice receiving adoptive transfer of tumor-experienced NK cells. Our study highlights a critical role of NK cells beyond its identity as a killer lymphocyte and more importantly, the potential host responses to a localized tumor as determined by its MHCI expression.

Stroke is a central nervous system disease with a high incidence at present. It can cause pathological changes such as oxidative stress, inflammation, neuronal apoptosis, and lead to disturbance of consciousness, disability, and even death. Due to the existence of the blood-brain barrier (BBB), most of the drugs cannot reach the lesions and exert their efficacy fully. Therefore, the purpose of this research was to design a lactoferrin functionalized hollow mesoporous manganese doped silica nanoparticles (LHMMSN) for delivery of insoluble drug resveratrol (RES). The system could help insoluble drugs pass through the BBB and target inflammatory sites to exert the antioxidant stress, anti-inflammatory and neuroprotective effects. The RES was adsorbed into LHMMSN with a particle size of about 140 nm by adsorption method, and the drug loading reached 39.32 ± 2.46%. In vitro and in vivo experiments showed that LHMMSN-RES could increase the activity of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px), reduce brain reactive oxygen species (ROS) and malondialdehyde (MDA) content, increase the expression of anti-inflammatory factors (IL-10) and anti-apoptotic factors (bcl-2) in brain tissue, and reduce brain tissue pro-inflammatory factors (TNF-α, IL-1β, IL-6) and pro-apoptotic factors (BAX, Cleaved caspase-3) expression. In summary, LHMMSN-RES can reduce inflammation and protect nerve cells by inhibiting oxidative stress, thereby promoting the recovery of motor function in middle cerebral artery occlusion (MCAO) model rats.

Reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) communication systems relying on hybrid beamforming structures are capable of achieving high spectral efficiency at a low hardware complexity and with low power consumption. Tensor-based joint beamforming with low-cost ultrasonic and RIS-assisted Dual-Hop Hybrid free space optical (FSO) mm Wave massive Multiple Input Multiple Output (MIMO) of vehicle-to-everything (V2X) is proposed. To address the occlusion problem for high-speed mobility of the vehicle, an RIS-assisted mixed FSO-MIMO V2X system is proposed. The low-cost ultrasonic array signal model is developed to solve the accurate direction-of-arrival (DOA) estimation. The ultrasonic-assisted RIS phase shift matrix based on subspace self-organizing iterations is designed to track the beam direction between RIS and vehicle. Specifically, the associated bandwidth-efficiency maximization problem is transformed into a series of subproblems, where the subarray of phase shifters and RIS elements is jointly optimized to maximize each subarray’s rate. The vehicle motion state is transformed into a two-dimensional model for prior distribution to calculate the particle weights of the RIS phase. Multi-vehicle Tucker tensor decomposition is used to describe the high-dimensional beam space. We conceive a multi-vehicle joint optimization method for designing the hybrid beamforming matrix of the base station (BS) and the passive beamforming matrix of the RIS. A cascaded channel decomposition method based on Singular Value Decomposition (SVD) is used to obtain the combined matrix beamforming of BS and vehicle. Our simulation results demonstrate the superiority of the proposed method compared to its traditional counterparts.

The objective of this study was to prepare Herceptin-functionalized SK-BR-3 cell membrane-wrapped paclitaxel nanocrystals (HCNCs) as a targeted delivery module for HER2-positive breast cancer. According to transmission electron microscopy (TEM) images, HCNCs presented a membrane-coated cubic shape with a particle size of approximately 220 nm. In vitro release test suggested that HCNCs had a certain sustained release effect of paclitaxel (PTX). Cell uptake experiments, in vivo imaging, and tissue distribution experiments demonstrated that HCNCs had excellent targeting ability to homologous tumor cells (SK-BR-3). The results of MTT, flow cytometry, Western blot, cell immunofluorescence staining, and in vivo antitumor experiments proved that HCNCs had a more significant ability to promote HER2-positive breast cancer cell apoptosis and inhibit its proliferation. These results clearly concluded that HCNCs were a promising nano-targeted preparation in anti-HER2-positive breast cancer.

Background Adenosine is a metabolite that suppresses antitumor immune response of T and NK cells via extracellular binding to the two subtypes of adenosine-2 receptors, A2ARs. While blockade of the A2AARs subtype effectively rescues lymphocyte activity, with four A2AAR antagonists currently in anticancer clinical trials, less is known for the therapeutic potential of the other A2BAR blockade within cancer immunotherapy. Recent studies suggest the formation of A2AAR/A2BAR dimers in tissues that coexpress the two receptor subtypes, where the A2BAR plays a dominant role, suggesting it as a promising target for cancer immunotherapy.Methods We report the synthesis and functional evaluation of five potent A2BAR antagonists and a dual A2AAR/A2BAR antagonist. The compounds were designed using previous pharmacological data assisted by modeling studies. Synthesis was developed using multicomponent approaches. Flow cytometry was used to evaluate the phenotype of T and NK cells on A2BAR antagonist treatment. Functional activity of T and NK cells was tested in patient-derived tumor spheroid models.Results We provide data for six novel small molecules: five A2BAR selective antagonists and a dual A2AAR/A2BAR antagonist. The growth of patient-derived breast cancer spheroids is prevented when treated with A2BAR antagonists. To elucidate if this depends on increased lymphocyte activity, immune cells proliferation, and cytokine production, lymphocyte infiltration was evaluated and compared with the potent A2AAR antagonist AZD-4635. We find that A2BAR antagonists rescue T and NK cell proliferation, IFNγ and perforin production, and increase tumor infiltrating lymphocytes infiltration into tumor spheroids without altering the expression of adhesion molecules.Conclusions Our results demonstrate that A2BAR is a promising target in immunotherapy, identifying ISAM-R56A as the most potent candidate for A2BAR blockade. Inhibition of A2BAR signaling restores T cell function and proliferation. Furthermore, A2BAR and dual A2AAR/A2BAR antagonists showed similar or better results than A2AAR antagonist AZD-4635 reinforcing the idea of dominant role of the A2BAR in the regulation of the immune system.

Two-tier massive multiple-input multiple-output (MIMO) systems achieve high sum spectral efficiency by simultaneously serving large numbers of users. However, as the number of service antennas and users tend to infinity, the performance is limited by directed inter-cell and intra-cell interferences. Handling these interferences are challenging due to the large channel dimensionality and the high complexity associated with implementing large precoding/combining matrices. Moreover, two-tier massive MIMO is computationally demanding, as the high antenna count results in high-dimensional matrix operations when conventional MIMO hybrid precoding is applied. In this paper, a manifold learning two-tier beamforming (MLTB) scheme is proposed to enable efficient and low-complexity operation in large scale dimensional MIMO systems. Users of multi-cell are clustered into several regions of user groups by manifold learning. Most of the high-dimensional channels are embedded in the low-dimensional subspace by manifold learning, while retaining the potential spatial correlation of the high-dimensional channels. The nonlinearity of high-dimensional channel is transformed into local linearity to achieve dimensionality reduction. Through proper user clustering, the beamformers are split into outer beamformers and inner beamformers. The outer beamformers can minimize inter-cell interference and the inner beamformers can minimize multi-user interference of intra-groups. The high signal to interference plus noise ratio (SINR) is achieved and the computational complexity is reduced by avoiding the conventional schemes to deal with high-dimensional channel parameters. Performance evaluations show that the proposed MLTB scheme can obtain near-optimal sum-rate and considerably higher energy efficiency than the conventional schemes.

Nb2O5-supported bimetallic catalysts were prepared by the impregnation method applied for the in situ hydrogenation of guaiacol. Guaiacol can be effectively transformed into cyclohexanol over different bimetallic catalysts using alcohol as the hydrogen donor. Meanwhile, the effects of different hydrogen donors such as isopropanol, sec-pentanol, and ethylene glycol on in situ hydrogenation of guaiacol were investigated in detail, and the results showed that isopropanol is the best hydrogen supply solvent. Then, the dependence of Ni–Mn/Nb2O5 properties on metal loading, reaction time, reaction temperature, and reaction pressure was studied for the in situ hydrogenation of guaiacol by using isopropanol as the hydrogen donor. Guaiacol can be completely converted, and the yield of cyclohexanol reached 71.8% over Ni–Mn/Nb2O5 with isopropanol as the hydrogen donor at 200°C for 5 h. The structures and characteristics of better catalytic properties of the Ni–Mn/Nb2O5 catalyst were determined by BET, NH3-TPD, XRD, XPS, SEM, and TEM, and the results indicated the particle size of the metal was small (approximately 10 nm) and the metal particles are finely dispersed in the whole support. Therefore, a large number of medium acid sites were generated on the 10Ni-10Mn/Nb2O5 with a large specific surface area, which could increase the interface between the metal and the support and may be beneficial to the hydrodeoxygenation of guaiacol.

In this study, nano zero-valent iron-reduced graphene oxide (NZVI-rGO) composites were synthesized to remove 2,4-dichlorophenol (2,4-DCP) as an efficient adsorbent. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) indicated that NZVI particles were successfully loaded and dispersed uniformly on rGO nanosheets. Fourier transform infrared spectroscopy (FTIR) analysis showed that the interaction between NZVI-rGO and 2,4-DCP promoted the adsorption process. A three-level, four-factor Box-Behnken design (BBD) of the response surface methodology (RSM) was used to optimize the influencing factors including NZVI-rGO dosage, 2,4-DCP initial concentration, reaction time and initial pH. A statistically significant, well-fitting quadratic regression model was successfully constructed to predict 2,4-DCP removal rate. The high F value (15.95), very low P value (

The development of new wireless sensing devices could provide significant opportunities for medical and environmental applications. A planar inverted-F antenna (PIFA) is a typical antenna that is widely used in communications. Here, we report here a PIFA for chemical sensing of ion concentrations. When the ion concentration increases, the reflection coefficient of the antenna decreases accordingly. The PIFA sensor shows a linear detection range from 0.15 μM to 15 μM. We expect that this study could offer exciting opportunities for fundamental studies as well as applications of wireless antennas for chemical and biological sensing, and advance related healthcare and environmental applications.

With the increasing customer demand on fabric variety in fashion markets, fabric texture becomes much more diverse, which brings great challenges to accurate fabric defect detection. In this paper, a fabric inspection model, consisting of image preprocessing, image restoration, and thresholding operation, is developed to address the woven fabric defect detection problem in the apparel industry, especially for fabric with complex texture and tiny defects. The image preprocessing first improves the image contrast in order to make the details of defects more salient. Based on the learned sub-dictionaries, a non-locally centralized sparse representation model is adopted to estimate the non-defective version of the input images, so that the possible defects can be easily segmented from the residual images of the estimated images and the inputs by thresholding operation. The performance of the proposed defect detection model was evaluated through extensive experiments with various types of real fabric samples. The proposed detection model was proved to be effective and robust, and superior to some representative detection models in terms of the detection accuracy and false alarms.