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Background: Craniopharyngioma is a rare and slow-growing benign sellar or parasellar epithelial tumor. The number of patients receiving proton beam therapy (PBT) has increased. This study aimed to systematically evaluate and analyze the comprehensive evidence regarding the safety and efficacy of PBT for craniopharyngioma. Methods: We searched four databases: the Cochrane Library, PubMed, Embase, and Web of Science. The period was from their inception to February 16, 2024. Two researchers independently screened the literature and extracted data. Results: Among 486 candidate articles, eight studies were included in our study. Exactly 393 patients with craniopharyngioma underwent PBT in these studies. These studies reported data on survival and toxicity. The median sample size was 42.5 patients. The median age was 9.1–37 years; the female proportion was 48.9%, and the median follow-up time was 29–91.4 months. All patients were treated once daily, five times a week, with a fraction of 1.8 Gy (RBE) per session. The median total dose was 54.0 Gy (RBE). The local control rates at 3 and 5 years in these studies were 99% and 93%, respectively. The overall survival rates at 3 and 5 years in these studies were both 100%. The incidence of acute and late toxicities was mainly grade 1–2. The main late toxicities included vascular and visual toxicities, hypothalamic obesity, endocrinopathy, and panhypopituitarism. Conclusions: PBT for craniopharyngioma, especially in children and adolescents, has shown impressive local control and acceptable acute and late toxicities. [ABSTRACT FROM AUTHOR]

Automatic crack segmentation plays an essential role in maintaining the structural health of buildings and infrastructure. Despite the success in fully supervised crack segmentation, the costly pixel-level annotation restricts its application, leading to increased exploration in weakly supervised crack segmentation (WSCS). However, WSCS methods inevitably bring in noisy pseudo-labels, which results in large fluctuations. To address this problem, we propose a novel confidence-aware co-training (CAC) framework for WSCS. This framework aims to iteratively refine pseudo-labels, facilitating the learning of a more robust segmentation model. Specifically, a co-training mechanism is designed and constructs two collaborative networks to learn uncertain crack pixels, from easy to hard. Moreover, the dynamic division strategy is designed to divide the pseudo-labels based on the crack confidence score. Among them, the high-confidence pseudo-labels are utilized to optimize the initialization parameters for the collaborative network, while low-confidence pseudo-labels enrich the diversity of crack samples. Extensive experiments conducted on the Crack500, DeepCrack, and CFD datasets demonstrate that the proposed CAC significantly outperforms other WSCS methods. [ABSTRACT FROM AUTHOR]

[Display omitted] • Magnetic CuFe 2 O 4 are uniformly anchored on Al 2 O 3 (CFO@AO) to activate PMS. • CFO@AO/PMS system performs well for degrading TC·HCl in different water matrix. • Synergistic catalysis between CuFe 2 O 4 and Al 2 O 3 enhanced the TC·HCl degradation. • Radical and non-radical species in CFO@AO/PMS system have been investigated. • Reasons for the low leaching and high activity of CFO@AO have been given. Nanoscaled magnetic copper ferrite (CuFe 2 O 4) is widely used as a peroxymonosulfate (PMS) activator but suffers from agglomeration owing to its inherent magnetic properties and high surface energy. In this work, spinel structured CuFe 2 O 4 anchored on mesoporous alumina (denoted as CFO@AO) were synthesized, characterized, and applied as a PMS activator for the removal of tetracycline hydrochloride (TC·HCl). Approximately 97.5 % of TC·HCl was decomposed within 10 min in 30 %–CFO@AO (0.2 g/L)/PMS (0.3 g/L) system, and the corresponding kinetic rate constant of 30 %–CFO@AO/PMS (0.417 min−1) was around 1.57 times higher than that of CuFe 2 O 4 /PMS (0.266 min−1), which indicating that the existence of synergistic catalysis between CuFe 2 O 4 and Al 2 O 3 enhanced the degradation of TC·HCl. Moreover, nano-sized CuFe 2 O 4 were successfully anchored on the surface of Al 2 O 3 because of Fe O Al bond, which could account for the enhanced catalytic activity, superior pH flexibility, and high chemical stability and reusability of 30 %–CFO@AO. Quenching experimentals, electron paramagnetic resonance, and methyl phenyl sulfoxide (PMSO) chemical probe assays confirmed that both radical oxidation (OH) and non-radical oxidation (1O 2 and Fe(IV) O) were proposed in the developed CFO@AO/PMS system, and OH played a key role in the process. Meanwhile, the PMS activation mechanism by CFO@AO composite was also analyzed based on the results of adsorption energy, which was calculated via DFT. Based on UPLC–MS technique, a possible degradation pathway for TC·HCl destruction in 30 %–CFO@AO/PMS system was proposed. The toxicity assessment showed that the catalytic degradation of TC·HCl in 30 %–CFO@AO/PMS system reduced the toxicity of most of degradation intermediates. Present work proved that CuFe 2 O 4 @Al 2 O 3 composite is an efficient, environment-friendly, and recyclable heterogeneous catalyst for practical wastewater treatment via PMS activation. [ABSTRACT FROM AUTHOR]

Background: Exposure to sunlight may decrease the risk of developing Alzheimer's disease (AD), and visible and near infrared light have been proposed as a possible therapeutic strategy for AD. Here, we investigated the effects of the visible, near infrared and far infrared (FIR) light on the cognitive ability of AD mice, and found that FIR light also showed potential in the improvement of cognitive dysfunction in AD. However, the related mechanism remains to be elucidated.Methods: Morris water maze was used to evaluate the cognitive ability of APPswe/PSEN1dE9 double-transgenic AD mice after light treatment. Western blot was carried out to detect the expression of protein involved in synaptic function and amyloid-β (Aβ) production. The protein amount of interleukin (IL)-1β, IL-6, Aβ1-40 and Aβ1-42 were determined using enzyme-linked immunosorbent assay. The mRNA level of receptors was performed using real-time quantitative polymerase chain reaction. Immunostaining was performed to characterize the Aβ burden and microglial Aβ phagocytosis in the brain of AD mice. The Aβ phagocytosis of primary cultured microglia and BV2 were assessed by flow cytometry. The energy metabolism changes were evaluated using related assay kits, including adenosine triphosphate (ATP), lactate content, mitochondrial respiratory chain complex enzymatic activity and oxidized/reduced nicotinamide adenine dinucleotide assay kits.Results: Our results showed that FIR light reduced Aβ burden, a hallmark of AD neuropathology, alleviated neuroinflammation, restored the expression of the presynaptic protein synaptophysin, and ameliorated learning and memory impairment in the AD mice. FIR light enhanced mitochondrial oxidative phosphorylation pathway to increase ATP production. This increased intracellular ATP promoted the extracellular ATP release from microglia stimulated by Aβ, leading to the enhanced Aβ phagocytosis through phosphoinositide 3-kinase/mammalian target of rapamycin pathways for Aβ clearance.Conclusions: Our findings have uncovered a previously unappreciated function of FIR light in inducing microglial phagocytosis to clean Aβ, which may be the mechanisms for FIR light to improve cognitive dysfunction in AD mice. These results suggest that FIR light treatment is a potential therapeutic strategy for AD. [ABSTRACT FROM AUTHOR]

Air pollution is growing ever more serious as a result of rising consumption of energy and other natural resources. Generally, governmental static monitoring stations provide accurate air pollution data, but they are sparsely distributed in the space. In contrast, microstations as a kind of low-cost air monitoring equipment can be distributed densely though their accuracy is relatively low. This article proposes a deep calibration method (DeepCM) for low-cost air monitoring sensors equipped in the microstations, which consists of an encoder and a decoder. In the encoding stage, multilevel time-series features are extracted, including local, global, and periodic time-series features. These features can not only capture local, global, and periodic trend information, but also benefit to alleviating cross-interference and noise effect. In the decoding stage, a final feature extracted by the encoder along with initial features of the moment to be calibrated are fed into the decoder to obtain a calibrated result. The proposed method is evaluated on two real-world datasets. The experimental results demonstrate that our method yields the best performance by comparison with eight baseline methods. [ABSTRACT FROM AUTHOR]

Air pollution is growing ever more serious as a result of rising consumption of energy and other natural resources. Generally, governmental static monitoring stations provide accurate air pollution data, but they are sparsely distributed in the space. In contrast, microstations as a kind of low-cost air monitoring equipment can be distributed densely though their accuracy is relatively low. This article proposes a deep calibration method (DeepCM) for low-cost air monitoring sensors equipped in the microstations, which consists of an encoder and a decoder. In the encoding stage, multilevel time-series features are extracted, including local, global, and periodic time-series features. These features can not only capture local, global, and periodic trend information, but also benefit to alleviating cross-interference and noise effect. In the decoding stage, a final feature extracted by the encoder along with initial features of the moment to be calibrated are fed into the decoder to obtain a calibrated result. The proposed method is evaluated on two real-world datasets. The experimental results demonstrate that our method yields the best performance by comparison with eight baseline methods. [ABSTRACT FROM AUTHOR]

Nuclear factor-κB interacting long non-coding RNA (LncRNA NKILA) is a well-studied tumor suppressor lncRNA in several types of malignancies. The present study reports the involvement of this lncRNA in diabetic cardiomyopathy (DC). A 8-year-follow-up study on 312 diabetic patients without exhibiting obvious complications demonstrated that plasma lncRNA NKILA levels were upregulated specifically in diabetic patients who developed DC but not in patients with other complications. Plasma levels of lncRNA NKILA at 6 months prior to diagnosis is sufficient to distinguish patients with DC from other diabetic patients without significant complications. Although in vitro experiments demonstrated that lncRNA NKILA expression in cardiomyocyte cells was not affected by high-glucose treatment, ectopic lncRNA NKILA expression and lncRNA NKILA knockdown potentiated, and inhibited cardiomyocyte apoptosis, respectively. Therefore, the data from the present study suggests that overexpression of lncRNA NKILA is involved in DC, and overexpression of lncRNA NKILA may serve as a therapeutic target for treating DC. [ABSTRACT FROM AUTHOR]

Computer vision systems have attracted much attention in recent years for use in detecting surface defects on rails; however, accurate and efficient recognition of possible defects remains challenging due to the variations shown by defects and also noise. This paper proposes a coarse-to-fine model (CTFM) to identify defects at different scales. The model works on three scales from coarse to fine: subimage level, region level, and pixel level. At the subimage level, the background subtraction model exploits row consistency in the longitudinal direction, and strongly filters the defect-free range, leaving roughly identified subimages within which defects may exist. At the next level, the region extraction model, inspired by visual saliency models, locates definite defect regions using phase-only Fourier transforms. At the finest level, the pixel subtraction model uses pixel consistency to refine the shape of each defect. The proposed method is evaluated using Type-I and Type-II rail surface defect detection data sets and an actual rail line. The experimental results show that CTFM outperforms state-of-the-art methods according to both the pixel-level index and the defect-level index. [ABSTRACT FROM AUTHOR]

Class incremental learning requires models to learn new-class knowledge without forgetting old-class information. As a natural solution, the parallel one-class framework (POC) has attracted extensive attention. However, POC is prone to suffer the problem of lacking comparability between classifiers due to their inconsistent output distributions. To address this drawback, we propose an incremental learning method based on I dentically D istributed P arallel O ne-class C lassifiers (IDPOC). The core of IDPOC is a novel one-class classifier with Gaussian distributed output, referred to as Deep-SVD 2 D. Deep-SVD 2 D encourages the distribution of sample representations to follow the standard multivariate Gaussian. Consequently, the distance between the representation and its class center will approximately follow a chi-square distribution with some freedom degree. IDPOC further eliminates the freedom degree to ensure the output of all classifiers to follow an identical distribution, thus enhancing the comparability between different classifiers. We evaluate IDPOC on four popular benchmarks: MNIST, CIFAR10, CIFAR100, and Tiny-ImageNet. The experimental results show that IDPOC achieves state-of-the-art performance, e.g., it outperforms the best baseline by 1.6% and 2.8% on two large-scale benchmarks of CIFAR100 and Tiny-ImageNet, respectively 1 1 The source code is publicly available at https://github.com/SunWenJu123/IDPOC.. • An incremental learning method is proposed based on identically distributed one-class classifiers. • A novel one-class classifier Deep-SVD2D is proposed with Gaussian distributed anomaly score. • Extensive experiments show the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

• A novel parallel one-class classifiers method is proposed for incremental learning based on variational auto-encoder (VAE). • A classifier-contrastive loss and an inter-class loss are introduced to enhance the comparability between VAEs. • A hinge reconstruction loss is proposed to improve the modeling robustness of each VAE and ensure its discriminability. • Extensive experiments show the effectiveness and robustness of the proposed method. The exemplar-free class incremental learning (IL) requires classification models to learn new-class knowledge incrementally without retaining any old samples. Recently, the IL framework based on parallel one-class classifiers (POC) has demonstrated promising performance. It trains a one-class classifier (OCC) for each category and thus is immune to the catastrophic forgetting problem. However, the single-class training strategy may incur weak discriminability and low comparability between different classifiers in POC. To meet this challenge, we propose a new IL framework, referred to as D iscriminative and C omparable P arallel O ne-class C lassifiers (DCPOC). Instead of ordinary OCCs (e.g., deep SVDD) used in other POC methods, DCPOC adopts variational auto-encoders (VAE) as OCCs because VAEs can be used not only to identify classes for given samples but also to generate pseudo samples for the trained classes. With this advantage, DCPOC trains a new-class VAE in contrast with the old-class VAEs, which benefits the new-class VAE to reconstruct better for new-class samples but worse for old-class pseudo samples, thus enhancing the comparability. Furthermore, DCPOC introduces a hinge reconstruction loss to reinforce the discriminability. We evaluate our method on MNIST, CIFAR10, CIFAR100, Tiny-ImageNet, and ImageNet. The experimental results show that DCPOC achieves state-of-the-art performance on these datasets. 1 1 The source code is publicly available at https://github.com/SunWenJu123/DCPOC [ABSTRACT FROM AUTHOR]

Global attention learning has been extensively applied in video-based person re-identification due to its superiority in capturing contextual correlations. However, existing global attention learning methods usually adopt the conventional neural network to model non-Euclidean contextual correlations, resulting in a limited representation ability. Inspired by the graph-structure property of the contextual correlations, we propose a spatial-temporal graph-guided global attention network (STG 3 A) for video-based person re-identification. STG 3 A comprises two graph-guided attention modules to capture the spatial contexts within a frame and temporal contexts across all frames in a sequence for global attention learning. Furthermore, the graphs from both modules are encoded as graph representations, which combine with weighted representations to grasp the spatial-temporal contextual information adequately for video feature learning. To reduce the effect of noisy graph nodes and learn robust graph representations, a graph node attention is developed to trade-off the importance of each graph node, leading to noise-tolerant graph models. Finally, we design a graph-guided fusion scheme to integrate the representations output by these two attentive modules for a more compact video feature. Extensive experiments on MARS and DukeMTMCVideoReID datasets demonstrate the superior performance of the STG 3 A. [ABSTRACT FROM AUTHOR]

A series of novel visible-light-driven Ag/Ag 3 PO 4 /WO 3 (AAPW) Z-scheme heterostructures were fabricated using a facile deposition-precipitation method followed by photo-reduction without adding any surfactant. To explore more deeply about the photocatalytic activity of AAPW nanocomposites under neutral and strongly acidic/alkaline conditions, we investigated their photocatalytic rhodamine B (RhB) efficiency at different pH value that was controlled by adding HNO 3 or NaOH aqueous solution. It was found that as-prepared AAPW photocatalysts showed enhanced photocatalytic RhB efficiency under neutral and even strongly acidic/alkaline environment. The process of charge carrier separation and transfer in the AAPW nanocomposites and Z-scheme mechanism for RhB degradation were described in sufficient detail based on systematical characterizations and measurements. The silver particles introduced to build AAPW Z-scheme structure should contribute to more efficient charge separation, resulting in enhanced photocurrent response and photocatalytic activity. We expect that this work will provide systematic study concerning Z-scheme Ag/Ag 3 PO 4 /WO 3 structure, and fulfill the research about photodegrade activity of catalyst under strongly acidic/alkaline conditions. [ABSTRACT FROM AUTHOR]

The understanding of the interactions between starch and cellulose hydrocolloids is crucial for equipment design and definition of operation parameters in the food industry. In the present study, the possible interactions of wheat starch (WS) with different levels (2–10%) of carboxymethyl cellulose (CMC) or microcrystalline cellulose (MCC) in short-term retrogradation were explored by dynamic rheological and Fourier transform infrared spectrum (FTIR) measurements. The chains of water-soluble CMC could creep into the continuous phase during paste gelation. It was found the amylose network structure was broken and the inter- and intra-molecular hydrogen bond of WS were weaken after gelation. Moreover, there were interactions between the chains of CMC and chains of amylose at higher CMC concentration. On other hand, water connected with COO − groups blocked the interactions between CMC chains and amylose, and the interactions among CMC chains. The amorphous phases of high crystalline MCC were just swollen during paste gelation. It results that heterogeneous microstructure with amylose and MCC domains unevenly distributed was in WS/MCC paste. [ABSTRACT FROM AUTHOR]

[Display omitted] • Red mud supported Co 3 O 4 quantum dots are prepared via a facile method. • Co 3 O 4 QDs are uniformly anchored on RM to activate PMS under visible light. • The radical species in Co 3 O 4 /RM/PMS/Vis system have been investigated. • The degradation pathway of LVF and the toxicity study have been presented. • Reasons for the low leaching and high activity of composite have been given. In this work, iron-rich red mud (RM), a industrial waste generated from alumina production by Bayer process, was used as a potential carrier for supporting Co 3 O 4 quantum dots (QDs). A novel heterogeneous catalyst of RM-based Co 3 O 4 QDs (Co 3 O 4 /RM) composite was prepared via a simple method and used for the activation of peroxymonosulfate (PMS) under visible light (Vis) to degrade levofloxacin (LVF). The characterization results demonstrated that in-situ growth of Co 3 O 4 QDs on the surface of RM could increase the surface area, reduce the aggregation, enhance the visible light response and accelerate the separation of photogenerated electron-hole pairs, all of which effectively improved the catalytic activity of Co 3 O 4 /RM composite. Approximately 95.3 % of LVF was decomposed at 20 min in the PMS/Vis system catalyzed by the optimal Co 3 O 4 /RM-1200 composite. Both SO 4 ·- and h+ generated in Co 3 O 4 /RM-1200/PMS/Vis system were responsible for the rapid LVF degradation; especially the SO 4 ·- was the dominant active specie. Based on LC-MS technology and DFT calculation, the reasonable degradation pathways of LVF in Co 3 O 4 /RM-1200/PMS/Vis system were proposed. The ecotoxicity of degradation intermediates was evaluated according to the Toxicity Estimation Software Tool (T.E.S.T.) software. In addition, critical influencing factors on the degradation of LVF in Co 3 O 4 /RM-1200/PMS/Vis system were investigated. Exhilaratingly, it was found that the Co 3 O 4 QDs were deposited homogeneously on the surface of RM with the Fe-O-Co bond between Co 3 O 4 component and Fe 2 O 3 component, which not only prevented the leaching of metal ions but also contributed to the superior stability and reusability. This work has designed a new perspective for the development of a cost-efficiency and stable RM-based Co 3 O 4 QDs catalyst to activate PMS under visible light for the degradation of LVF. [ABSTRACT FROM AUTHOR]

Red mud (RM), a kind of iron-rich industrial waste produced in the alumina production process, can be utilized as a potential iron-based material for the removal of refractory organic pollutants from wastewater in advanced oxidation processes (AOPs). In this work, high-iron RM (rich in iron) was activated in a ball mill and applied as an effective activator of peroxymonosulfate (PMS) for tetracycline hydrochloride (TC-HCl) degradation. Compared with that of unmilled RM (69.7%), the TC-HCl decomposition ratios of ball-milled RM (BM-RM) (72.2%–92.0%) were all improved in the presence of PMS. Systematic characterization suggested that ball milling could optimize the physicochemical properties of RM, such as increased surface area, increased oxygen vacancies, enhanced electrical conductivity, and increased exposure of Fe(II) sites, all of which could effectively improve RM for PMS activation to degrade TC-HCl. The quenching experiments and electron paramagnetic resonance technique revealed that 1O 2 and SO 4 ·- contributed dominantly to the TC-HCl degradation. Ultra performance liquid chromatography mass spectrometry analysis combined with density functional theory calculation revealed that the degradation pathways of TC-HCl were driven by hydroxylation, N-demethylation and dehydration in BM-RM/PMS system. Based on quantitative structure-activity relationship prediction using the Toxicity Estimation Software Tool software, the toxicity of almost all intermediates was significantly reduced. An obvious inhibition effect on TC-HCl was occurred in the presence of Cl−, whereas the presences of NO 3 − and SO 4 2− had little effect. However, HCO 3 − improved TC-HCl removal efficiency. BM-RM had a wide working pH range (pH = 3–11) and showed good stability and reusability in use. Overall, this work not only offers a simple and promising approach to improve the catalytic activity of RM, but also opens new insights into the ball-milled RM as an effective PMS activator for wastewater treatment. [Display omitted] • Ball milling could improve the physicochemical characteristics of red mud. • Ball milling remarkably promoted the generation of oxygen vacancies (OVs). • Electron-rich OVs accelerated the reaction step of O 2 to O 2 ·- and Fe(III) to Fe(II). • 1O 2 together with SO 4 ·- were the main ROS responsible for TC-HCl degradation. • The toxicity of degradation intermediates was reduced by the system of BM-RM/PMS. [ABSTRACT FROM AUTHOR]

In this paper, we chose diffident kinds of ionic liquids to optimal selection an optimal one to extract alkaloids from Phellodendron amurense Rupr . Four ionic liquids with diffident carbon chains or anions have been investigated and 1-butyl-3-methylimidazolium bromide with best productivity. Then, selections have been optimized in different conditions, including concentration of ionic liquid, time for ultrasonic treatment, ultrasonic power and solid–liquid ratio. Moreover, three conditions have been comprehensively assessment by response surface methodology, the optimal conditions were determined as follows ultrasonic power 100 W, extraction time 75 min and ratio of solvent to raw material 1:14. Under these conditions, the yield% (MIX) was 106.7% (extracted by heat reflux being defined 100%). Comparing with other methods, the advantages are saving conserving, time saving, high yield% and especially pollution-free. [ABSTRACT FROM AUTHOR]

In this study, 12 asymmetric curcumin (CUR) analogues and 5 symmetric curcumin derivatives were synthesized, the antioxidant activity of these derivatives were evaluated by radicals 1,1-diphenyl-2-picryl-hydrazyl (DPPH) assay, 2,2-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) assay, ROO (TRAP) assay and O 2− (NET) assay and anti-proliferative activities of these analogues were assessed against the human hepatoma cell line (SMMC-7721), the human breast cancer cell line (MCF-7) and the human prostate cancer cell lines (PC-3). Most of the asymmetric compounds showed stronger antioxidant activities than Vitamin C (Vc). Curcumin analogues reducing free radicals contain two reaction mechanisms: H-atom and electron transfer mechanisms. Compound 14 showed the most significant antioxidant activity compared with curcumin and other derivatives. Shorted the carbon chain of 14 can reduce the O–H bond dissociation enthalpy (BED) to improve the antioxidant activity. The antioxidant activity of 25 was similar to curcumin. All of the compounds performed better in an anti-proliferate assay than curcumin, especially compound 25 , which exhibited the preferential cytotoxic activity against MCF-7 cells( 25 , IC 50 = 9.11 μM, curcumin, IC 50 = 70.2 μM). Considering these data, future studies should be performed to assess the therapeutic values of these asymmetric curcumin analogues. [ABSTRACT FROM AUTHOR]

A novel conjugate of camptothecin and artesunate (C–Q) was prepared and its cytotoxicity was evaluated using the MTT assay. In addition, the antitumour activity and toxicity of C–Q were investigated in mice, and interaction between transferrin (TF) and C–Q was investigated to evaluate its interaction with biological macromolecules. In the MTT assay, C–Q showed better inhibitory activity against MCF7 breast cancer cells and SMMC-7721 liver cancer cells than camptothecin or artesunate. In vivo, C–Q showed lower toxicity and better antitumour activity compared with camptothecin. Fluorescence spectroscopy showed static quenching of TF in the presence of C–Q, and thermodynamic parameters (Δ H > 0 and Δ G < 0) indicated that the reaction was spontaneous and endothermic. The main binding force between C–Q and TF was hydrophobic, as indicated by thermodynamic parameters (Δ H > 0 and Δ S > 0). Thus, synchronous fluorescence spectra showed that C–Q had no influence on the conformation of TF. Our results indicated that C–Q represents a novel potential anticancer therapeutic vector with advantages over current methods of CPT and ART administration. This novel drug delivery system allows the use of these drugs in a manner associated with few side effects for normal tissue, and which facilitates synergistic effects of anti-tumour drugs. [ABSTRACT FROM AUTHOR]

Camptothecin-20(s)- O-glycine ester-[ N-(3′α, 12′α-dihydroxy-24′-carbonyl-5′β-cholan)] ( A2), 10-(3′α,12′α-dihydroxy-5′β-cholan-24′-carboxyl)-(20 s)-camptothecin ( C2), and 10- O-(3- O-(3′α, 12′α-dihydroxy-24′-carbonyl-5′β-cholan)-propyl)-(20 S)-camptothecin ( D2) are novel camptothecin-deoxycholic acid analogues. MTT assays were performed to assess the anticancer activity of these compounds against hepatocellular carcinoma SMMC-7721, breast carcinoma MCF-7, and colorectal carcinoma HCT-116 cells. A2 had a high killing ability on SMMC-7721 cells selectively, but C2 and D2 did not exhibit selectivity with regard to SMMC-7721 killing. Uptake assays were performed in an effort to elucidate the transport mechanisms of A2 into SMMC-7721 cells. A2 increased the mRNA expression of OATP1B3 (an organic anion-transporting polypeptide) and uptake of A2 was inhibited by rifampin (inhibitor of OATP1B3), which indicated that the transporter-mediated transport of A2 was mediated by OATP1B3. In addition, according to the western blot and apoptosis assays, we found that A2 killed SMMC-7721 cells by inducing cell apoptosis mainly via an AIF (apoptosis-inducing factor) pathway and a caspase-dependent mitochondria apoptosis pathway. [ABSTRACT FROM AUTHOR]

The purpose of this work is to prepare a formulation using mannitol coupling Camptothecin (CPT) nanoparticles (CPT-NPs) to circumvent the difficult solubilization practice based on central composite experimental statistical design. CPT-NPs were prepared with a high-pressure homogenization technique method. The independent variables considered for the optimization of CPT-NPs were percentage of CPT in raw material (CPT and mannitol), concentration of CPT in working liquid, cycles numbers and homogenizer pressure for drug loading efficiency, particle size and polydispersity index. Analysis of variance (ANOVA) statistical test was used to assess the optimization. The optimized CPT-NPs showed an appropriate drug loading efficiency (18.09±2.13%), a homogeneous particle size (165.33±37.23nm) and a low polydispersity index (0.29±0.01). The CPT-NPs group show higher inhibition ratio (79.95%) of H22 tumor growth in vivo compared with TPT and CPT at the same dose. Changes in mice body weight demonstrate CPT-NPs have the lower toxicity. The results of biodistribution studies indicated the obviously superiority of CPT-NPs in increasing the accumulation of CPT within tumor. Overall, CPT-NPs under optimum conditions are considered to be potentially feasible to overcome formulation challenges for drug delivery. [ABSTRACT FROM AUTHOR]

Organic anion-transporting polypeptides (OATPs) encoded by the SLCO genes constitute an important transporter superfamily that mediates transmembrane transport of various clinical drugs and endogenous nutrients. Eleven human OATPs with different transport functions are expressed in various tissues. Bile acids, steroid hormone conjugates, prostaglandins, testosterone and thyroid hormones that promote cell proliferation are typical substrates of OATPs. Many important clinical drugs have been identified as substrates of OATP1B1, OATP1B3, OATP2B1 and OATP1A2. Liver-specific OATP1B1 and OATP1B3 as well as testis-specific OATP6A1 are expressed in malignancies and can act as biomarkers for many tumours. Various studies have shown the associations of genetic polymorphisms in OATP genes with the uptake pharmacokinetics of their substrates. Because of their abundant expression in tumours and their high transport activity for many cancer drugs, OATPs should be considered as important therapeutic targets in anti-cancer drug design. [ABSTRACT FROM AUTHOR]

[Display omitted] • OVs-rich M−RM/MMO derived from red mud-based LDH was used as PDS activator. • The vital role of OVs in the M−RM/MMO-700/PDS/VL system was explored. • M−RM/MMO possessed excellent reusability, stability and magnetic behavior in use. • Degradation pathway of CIP was deduced by LC-MS analysis and DFT calculation. • Ecotoxicity of degradation intermediates was analyzed by QSAR method. In this work, a low-cost and oxygen vacancies (OVs) enriched mixed metal oxide (M−RM/MMO) derived from red mud-based layered double hydroxide (M−RM/LDH) was applied as an efficient peroxydisulfate (PDS) activator to realize the degradation of ciprofloxacin (CIP) under visible light (VL) irradiation. The optimal composite of M−RM/MMO-700 exhibited good performance, and approximately 87.4% of CIP (10 mg/L) could be degraded at 60 min via the photocatalysis activation of PDS (1.0 mM) over M−RM/MMO-700 (0.2 g/L). The result indicated the abundant OVs in M−RM/MMO-700 could improve light absorption and promote electron-hole separation, both of which were favorable for the activation of PDS, resulting in promoting the generation of active species in M−RM/MMO-700/PDS/VL system. Quenching experiments and EPR technology indicated that O 2 −, 1O 2 and h+ were the main active species for the degradation of CIP. The M−RM/MMO catalyst possessed excellent reusability, stability and magnetic behavior in use. The degradation pathways of CIP were deduced based on DFT calculation and LC-MS analysis. Based on the quantitative structure–activity relationship (QSAR), the ecotoxicity of the degradation intermediates was analyzed in detail. This work provided a new insight for future designing of red mud-based LDHs-derived MMO heterogeneous catalyst with abundant OVs to efficiently treat antibiotics wastewater via the photocatalysis activation of PDS. [ABSTRACT FROM AUTHOR]

• A novel Cluster-Prototype Matching (CPM) strategy is proposed to solve the domain shift problem of zero-shot learning. • The distribution information of samples in the embedding space, i.e., cluster structure, is utilized to assist in zero-shot learning classification. • The CPM strategy can be applied to most existing ZSL models in a plug-and-play style. • Extensive experiments show the effectiveness and robustness of the proposed method. Given the descriptions of classes, Zero-Shot Learning (ZSL) aims to recognize unseen samples by learning a projection between the visual features of samples and the semantic descriptions (prototypes) of classes from seen data. However, due to the inherent distribution gap between seen and unseen domains, the learned projection is generally biased to seen classes and may produce misleading relationships between unseen samples and prototypes (sample-prototype relationship). To tackle this problem, we propose a Cluster-Prototype Matching (CPM) framework which exploits the distribution information of samples to explore the cluster structure of samples and then use the robust cluster-prototype relationship to correct the biased sample-prototype relationship. Specifically, we first use an iterative cluster generation module to identify the underlying cluster structure of samples based on their embedding features, which are acquired via a basic ZSL model. Then each identified cluster will be matched with a specific class prototype through the Kuhn-Munkres algorithm, based on which we can export a sharp cluster-prototype similarity. Finally, the cluster-prototype similarity is combined with the sample-prototype similarity to determine the class labels of test samples. We apply CPM to five well-established ZSL methods and the experimental results show that CPM can significantly improve the performance of basic models and enable them achieve or beyond the state-of-the-art. [ABSTRACT FROM AUTHOR]

Abstract: A liquid chromatography–tandem mass spectrometry (LC–MS/MS) method was developed to identify and quantify the camptothecin quaternary derivative CPT8 for application in pharmacokinetics and tissue distribution studies. Rat plasma and tissue samples were extracted with methanol by using camptothecin as the internal standard (IS). Chromatographic separation of CPT8 and the IS was achieved using a Hypersil GOLD C18 column, with a flow rate of 1.0mL/min followed by quantification with tandem mass spectrometry, operating with electrospray ionization in the positive ion mode and by applying multiple reaction monitoring. The MS/MS ion transitions were monitored at m/z 484.3–361.2 for CPT8 and m/z 349.0–305.2 for the IS (CPT). A calibration curve was constructed using CPT8 concentrations ranging from 2.5ng/mL to 2500ng/mL (r>0.993). The efficiency of CPT8 extraction from plasma and tissue samples ranged from 91.23% to 105.4%. Intra- and inter-day precision (relative standard deviation) values were 0.21% and 7.25%, respectively. No matrix effects were observed. The freeze–thaw stability, post-extraction stability, and stability following short- and long-term storage at low temperatures ranged from 84.12% to 108.2%. The preclinical data obtained using this method is expected to facilitate future clinical investigations of CPT8. [ABSTRACT FROM AUTHOR]

Abstract: A liquid chromatography–tandem mass spectrometry (LC–MS/MS) method was developed to identify and quantify the camptothecin quaternary derivative CPT8 for application in pharmacokinetics and tissue distribution studies. Rat plasma and tissue samples were extracted with methanol by using camptothecin as the internal standard (IS). Chromatographic separation of CPT8 and the IS was achieved using a Hypersil GOLD C18 column, with a flow rate of 1.0mL/min followed by quantification with tandem mass spectrometry, operating with electrospray ionization in the positive ion mode and by applying multiple reaction monitoring. The MS/MS ion transitions were monitored at m/z 484.3–361.2 for CPT8 and m/z 349.0–305.2 for the IS (CPT). A calibration curve was constructed using CPT8 concentrations ranging from 2.5ng/mL to 2500ng/mL (r>0.993). The efficiency of CPT8 extraction from plasma and tissue samples ranged from 91.23% to 105.4%. Intra- and inter-day precision (relative standard deviation) values were 0.21% and 7.25%, respectively. No matrix effects were observed. The freeze–thaw stability, post-extraction stability, and stability following short- and long-term storage at low temperatures ranged from 84.12% to 108.2%. The preclinical data obtained using this method is expected to facilitate future clinical investigations of CPT8. [Copyright &y& Elsevier]

Highlights: [•] Anticancer effects of B4, a novel berberine–bile acid analog, were tested. [•] B4 inhibited cell proliferation in hepatocellular carcinoma cells. [•] It also stimulated mitochondrial ROS production and membrane depolarization. [•] Effects of B4 were inhibited by a non-specific ROS scavenger. [•] Regulation of ROS generation may be a strategy for treating hepatic carcinoma. [ABSTRACT FROM AUTHOR]

Abstract: In this study, the binding interactions of the water-soluble camptothecin derivatives hydroxycamptothecin (10-HCPT), topotecan (TPT), and camptothecin quaternary salt (CPT8), to bovine serum albumin (BSA) were determined using fluorescence spectra and UV–vis spectra. The results revealed that the fluorescence of BSA was strongly quenched by the binding of camptothecin derivatives to BSA. The quenching mechanism of the camptothecin derivatives was found to be static according to the Stern–Volmer equation. The binding constant and binding sites were confirmed by fluorescence quenching spectra. The thermodynamic parameters Gibbs free energy change (ΔG <0), enthalpy change (ΔH >0), and entropy change (ΔS >0) implied that the interaction process was spontaneous and endothermic, and the interaction forces between camptothecin compounds and BSA were found to be hydrophobic. According to Föster non-radioactive energy transfer, the binding distances between 10-HCPT, TPT, and CPT8, and BSA were determined to be 1.73nm, 1.63nm, and 1.61nm, respectively. The synchronous fluorescence spectra confirmed that the camptothecin compounds cannot cause conformational changes in BSA. A rapid and sensitive method for determining the binding interaction between water-soluble camptothecin derivatives and BSA was established based on these principles of fluorescence quenching. [Copyright &y& Elsevier]

Cloud detection is the precondition for deriving other information (e.g., cloud cover) in ground-based sky imager applications. This paper puts forward an effective cloud detection approach, the Hybrid Thresholding Algorithm (HYTA) that fully exploits the benefits of the combination of fixed and adaptive thresholding methods. First, HYTA transforms an input color cloud image into a normalized blue/red channel ratio image that can keep a distinct contrast, even with noise and outliers. Then, HYTA identifies the ratio image as either unimodal or bimodal according to its standard deviation, and the unimodal and bimodal images are handled by fixed and minimum cross entropy (MCE) thresholding algorithms, respectively. The experimental results demonstrate that HYTA shows an accuracy of 88.53%%, which is far higher than those of either fixed or MCE thresholding alone. Moreover, HYTA is also verified to outperform other state-of-the-art cloud detection approaches. [ABSTRACT FROM AUTHOR]

Abstract: More and more digitized art images are accumulated and expanded in our daily life and techniques are needed to be established on how to organize and retrieve them. Though content-based image retrieval (CBIR) made great progress, current low-level visual information based retrieval technology in CBIR does not allow users to search images by high-level semantics for art image retrieval. We propose a fuzzy approach to describe and to extract the fuzzy aesthetic semantic feature of art images. Aiming to deal with the subjectivity and vagueness of human aesthetic perception, we utilize the linguistic variable to describe the image aesthetic semantics, so it becomes possible to depict images in linguistic expression such as ‘very action’. Furthermore, we apply neural network approach to model the process of human aesthetic perception and to extract the fuzzy aesthetic semantic feature vector. The art image retrieval system based on fuzzy aesthetic semantic feature makes users more naturally search desired images by linguistic expression. We report extensive empirical studies based on a 5000-image set, and experimental results demonstrate that the proposed approach achieves excellent performance in terms of retrieval accuracy. [Copyright &y& Elsevier]

Abstract: In an attempt to improve the antitumor activity and decrease the cytotoxicity of camptothecin, 18 new 10-substituted camptothecin derivatives were prepared. The cytotoxicity in vitro on cancer cell lines and antitumor activity in vivo, and inhibitory properties of topoisomerase I of these derivatives were evaluated. Most of these derivatives possessed lower cytotoxicities than CPT, and the compounds 13, 21, 22, 23, and 24 showed similar topoisomerase I inhibitory activity to CPT. Analogues 13 exhibited the best antitumor activity in vivo among all derivatives we prepared. [Copyright &y& Elsevier]

[Display omitted] • Heterostructure composite was constructed via in-situ growth of Ag 3 PO 4 on red mud. • The composite (APRM) is a new cost-efficiency catalyst for photo-Fenton reaction. • APRM holds excellent catalytic activity and outstanding stability in use. • S-scheme heterojunction can account for the charge transfer pathway in APRM. • The toxicity of TC-HCl could be weakened via photo-Fenton catalyzed by APRM. In our work, using industrial waste red mud (RM) as a host material to grow silver phosphate (Ag 3 PO 4), a low-cost and new heterogeneous Ag 3 PO 4 /RM (APRM) composite was successfully prepared through a facile in-situ deposition method. The characterization results demonstrated Ag 3 PO 4 nanoparticles uniformly deposited on RM to form P-O-Fe bonds, and a semiconductor heterostructure was constructed between the two nanocrystalline components of Ag 3 PO 4 and Fe 2 O 3. The optimal composite of APRM-110 exhibited a remarkable photocatalytic activity for the degradation of tetracycline hydrochloride (TC-HCl) in photo-Fenton reaction. The enhanced photocatalytic performance and stability could be attributed to the S-scheme charge transfer in APRM-110, which accelerated the photo-generated carrier separation and then effectively restrained the photocorrosion of APRM-110. The APRM-110 composite held good reusability, stability and excellent settleability. The main intermediates were identified and the degradation pathway of TC-HCl in photo-Fenton reaction catalyzed by APRM-110 was proposed. The aquatic toxicity of TC-HCl solution could be effectively weakened by the photo-Fenton catalyzed by APRM-110. This work has designed a cost-efficiency and stable RM-based Ag 3 PO 4 composite, and as a highly effective catalyst for TC-HCl degradation in photo-Fenton reaction. [ABSTRACT FROM AUTHOR]

Abstract: In an effort to decrease the toxicity and improve the stability of labile lactone ring of camptothecin, nitrogenous heterocyclic aromatic groups were introduced into 20-position of camptothecin and seventeen new 20s-camptothecin derivatives were obtained in quantitative yield. The cytotoxicity in vitro on three cancer cell lines and the stability of the lactone in phosphate-buffered solution (PBS) of these derivatives were evaluated. Most of these tested derivatives possessed better cytotoxicity than topotecan. Analogues 6, 12 exhibited the best antitumor activity in vivo in all derivatives we prepared. The results suggested that introduction of pyrazole in 10- or 20-position of camptothecin could promote antitumor activity in vitro and in vivo, simultaneously bring much increase of the stability of lactone. [Copyright &y& Elsevier]

• Fe 2 O 3 /Zn-Al LDH has been prepared using red mud as raw material. • The preparing method is simple and green mechanochemical synthesis. • The effects of preparation conditions on the composite have been presented. • The formation mechanism of the composite by this method is proposed. In this work, using industrial waste red mud (RM) as main starting material, a simple method of mechanochemical synthesis (MCS) was introduced as a green approach to synthesize heterogeneous Fe 2 O 3 /Zn-Al layered double hydroxide (F/ZA-LDH), which could be used as a new low-cost catalyst for photo-Fenton reaction. The optimum preparation conditions of F/ZA-LDH were as follows: mass ratio of Zn(NO 3) 2 ·6H 2 O to RM (m Zn :m RM) 2:1, dry milling time 6 h, H 2 O dosage 2 mL, ball-to-powder mass ratio 50:1, and milling speed 250 rpm. The effects of the synthesis conditions on the crystal structure and catalytic activity of F/ZA-LDH were analyzed. The F/ZA-LDH was characterized by XRD, TG, XPS, SEM, (HR)TEM. The characterization results showed the composite had a crystallized hydrotalcite-like structure, and the crystalline phases in the optimum F/ZA-LDH were Fe 2 O 3 and Zn-Al LDH. A hetero-interfaces between Fe 2 O 3 and Zn-Al LDH existed in the synthesized Fe 2 O 3 /Zn-Al LDH composite. Furthermore, the possible mechanism for F/ZA-LDH formation in the MCS process was proposed. Overall, our results provide a systematic understanding of the preparation of LDH composite through MCS using RM as main material, and our findings help to develop green technology for reusing RM. [ABSTRACT FROM AUTHOR]

Streptococcus agalactiae is an important pathogen associated with various aquatic animals, especially tilapia. Streptococcosis has greatly limited the healthy development of tilapia aquaculture in recent times. The development of novel effective vaccines is important for the prevention and control of streptococcosis in fish. We previously constructed a non-encapsulated S. agalactiae strain △ cps by the in-frame deletion method. Here, we evaluated whether this mutant △ cps is safe for tilapia and suitable for protection against streptococcosis. We observed that the △ cps strain was non-pathogenic to tilapia, and there was no reversion of virulence when it was passaged in tilapia. Moreover, the △ cps strain survived for at least 11 d in the main immune organs of tilapia. The tilapia vaccinated via intraperitoneal (IP) injection with △ cps strain induced a high antibody titer, and the IgM antibody levels were significantly higher in the vaccinated group than in the control group. The vaccination protected tilapia against the S. agalactiae challenge with a relative percent survival of 90.47%. In addition, tilapia immunized with the △ cps strain showed significantly higher expression level of IFN-γ , IL-1β , MyD88 , IgM , and MHC-Iα in the head kidney than those in the control during the entire observation period. The expression of MHC-IIβ was inhibited during 1–7 d of immunization. These results revealed that the △ cps strain is able to induce humoral and cell-mediated immune response in tilapia. Therefore, the strain △ cps has a broad application prospect as a target for attenuation in vaccine development. • The △ cps vaccine is very safe for immunization of tilapia. • The attenuated vaccine survives for 11 d in immunized tilapia. • The attenuated vaccine induced a higher antibody titer. • The vaccine provided strong protection against Streptococcus agalactiae infection. [ABSTRACT FROM AUTHOR]

Rail surface defects are potential danger factors for railway systems, and visual inspection of surface defects plays a vital role in rail maintenance. Recently, the methods based on deep learning have been widely used in rail inspection systems, but such systems often face the problem of a lack of defect samples for training deep learning models at start‐up, which is called the cold‐start problem. It is challenging to obtain sufficient defect samples since defects are sparse and even non‐existent for a running railway system. Therefore, a synthetic‐to‐realistic domain adaptation (SRDA) method is proposed for real‐world rail inspection. SRDA adapts synthetic images to look more realistic for reducing the domain gap between synthetic images and realistic rail surface images and obtains translated images that consist of synthetic defect information and realistic rail background. After that, the translated images are used to train a detector for rail inspection of rail surface defects. In order to make the detector more robust to complex backgrounds, SRDA generates images with the same defect‐level semantics but with different texture appearances and makes the detector align these images in the learned feature space. In addition, the synthetic and realistic rail surface defects (SRRSD) dataset containing 20,662 images is built. The experimental results on SRRSD show that SRDA achieves higher detection performance than other established domain adaption methods with 19.0% for F1score${\mathrm{F}}1\ {\mathrm{score}}\ $ and 26.7% for average precision. [ABSTRACT FROM AUTHOR]

Highlights • Bonito hydrolysates exhibited excellent anti-hyperuricemic activity and renal protection function. • Hexapeptide PGACSN and tripeptide WML displayed inhibitory effects on xanthine oxidase. • Hydrophobic amino acids play an important role in the xanthine oxidase inhibitory activity of WML. Abstract Traditional drugs used to treat hyperuricemia have adverse effects. In this study, to identify safer anti-hyperuricemic bioactive peptides isolated from food-derived protein hydrolysates, a hyperuricemia rat model induced by potassium oxonate (PO) was used to evaluate the activity of bonito hydrolysates (BH), dephenolised walnut hydrolysates (DWH), and soybean hydrolysates (SH). The serum uric acid level of rats in the BH group (95.4 ± 27.4 μM, p < 0.01) was significantly reduced compared to that in the model group (212.00 ± 30.00 μM) to a level even lower than that in allopurinol group (114.3 ± 53.0 μM). Furthermore, BH alleviated renal impairment caused by PO in vivo and exhibited the greatest xanthine oxidase (XOD) inhibitory activity (65.5 ± 8.0%) in vitro compared to the other hydrolysates. Two peptides identified from BH bound the catalytic site of XOD, among which the hydrophobic peptide WML entered the active site of XOD more easily compared to the hydrophilic peptide PGACSN, possibly because of hydrophobic interactions. The chemically synthesized WML demonstrated high XOD inhibitory effect compared to PGACSN and a significant change in the secondary structure of XOD. Therefore, hexapeptide PGACSN and tripeptide WML are partially responsible for the anti-hyperuricemic activity of BH, and hydrophobic amino acids play important roles in the XOD inhibitory activity of peptides. [ABSTRACT FROM AUTHOR]

Atmospheric electricity is composed of a series of electric phenomena in the atmosphere. Significant advances in atmospheric electricity research conducted in China have been achieved in recent years. In this paper, the research progress on atmospheric electricity achieved in China during 2019–22 is reviewed focusing on the following aspects: (1) lightning detection and location techniques, (2) thunderstorm electricity, (3) lightning forecasting methods and techniques, (4) physical processes of lightning discharge, (5) high energy emissions and effects of thunderstorms on the upper atmosphere, and (6) the effect of aerosol on lightning. [ABSTRACT FROM AUTHOR]

Carbonate-doped silver orthophosphate (Ag 3 PO 4 ) photocatalyst with doughnut-like morphology was synthesized by an ion exchange method, and its structure and properties were characterized systematically. The X-ray diffraction (XRD), Raman spectra and X-ray photoelectron spectroscopy (XPS) were employed to confirm the doping of CO 3 2− ions into the lattice of Ag 3 PO 4 . Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were performed to display the morphology of as-prepared samples. The photocatalytic activities were evaluated in the degradation of rhodamine B (RhB) and methyl orange (MO) under visible light irradiation. The corresponding photocatalytic mechanism was analyzed according to the results from diffuse reflectance UV–vis spectroscopy (DRS), photoluminescence spectroscopy (PL) and photoelectrochemical tests. On the basis of the results, it can be concluded that because of modification induced by CO 3 2− doping, the carbonate-doped Ag 3 PO 4 photocatalyst showed a higher photocatalytic activity than polyhedral Ag 3 PO 4 , which was attributed to the narrower band gap and effective separation of photoinduced charges. This new work can provide a promising strategy for the preparation of carbonate doped hollow photocatalyst and improving its photocatalytic performance. [ABSTRACT FROM AUTHOR]

Vehicles transporting hazardous material (HAZMAT) pose a severe threat to highway safety, especially in road tunnels. Vehicle reidentification is essential for identifying and warning abnormal states of HAZMAT vehicles in road tunnels. However, there is still no public dataset for benchmarking this task. To this end, this work releases a real-world tunnel HAZMAT vehicle reidentification dataset, VisInt-THV-ReID, including 10,048 images with 865 HAZMAT vehicles and their spatiotemporal information. A method based on multimodal information fusion is proposed to realize vehicle reidentification by fusing vehicle appearance and spatiotemporal information. We design a spatiotemporal similarity determination method for vehicles based on the spatiotemporal law of vehicles in tunnels. Compared with other reidentification methods based on multimodal information fusion, i.e., PROVID, Visual + ST, and Siamese-CNN, experimental results show that our approach significantly improves the vehicle reidentification recognition precision. [ABSTRACT FROM AUTHOR]

[Display omitted] The efficient and secure delivery of intravenous chemotherapeutic agents across the blood–brain barrier (BBB) to the precise location of a brain tumor is a crucial element in glioma treatment. Herein, we introduce a biomimetic nanoplatform (T7-M-C/S) comprising a core made up of irinotecan hydrochloride (CPT11) and its bioactive metabolite, 7-Ethyl-10-hydroxycamptothecin (SN38), surrounded by a layer of T7-peptide-modified macrophage membrane. CPT11 spontaneously assembles with SN38 into stable and water-dispersible nanoparticles (C/S), greatly enhancing the water solubility of SN38. The integration of the modified peptide with the inherent proteins expressed by macrophage cells confers the nanoplatform with enhanced bioavailability and robust glioma-targeting abilities, ultimately resulting in superior therapeutic outcomes. These discoveries highlight a drug delivery system characterized by a high drug loading capacity, leveraging the macrophage membrane, and promising significant potential for glioma treatment. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, urban pollution has become a hot issue of human concern, and people are put forward higher requirements for the accuracy of pollutant concentration simulations. Based on the the WRF-Chem model simulation results and Beijing environmental monitoring data, this study constructed the XGBoost algorithm through the process of data cleaning, feature selection and super parameter optimization, and the optimized simulation of PM 2.5 and O 3 concentrations in Beijing was then carried out based on the constructed algorithm. The results showed that the XGBoost algorithm can better capture the spatial and temporal variation patterns of pollutant concentrations, and has a greater improvement on the simulation results of the WRF-Chem model, and that the XGBoost algorithm shows better optimisation results in urban areas compared to suburban areas. In addition, the overall analysis of the features of PM 2.5 and O 3 concentrations based on the SHAP value theory showed that the time series and periodic features, aerosol ion concentration of Sodium (NAAJ) and Nitrate concentration (NO3AJ) were the important features affecting the prediction of PM 2.5 concentration by the XGBoost algorithm, and the most important factor affecting O 3 concentration is temperature. PM 2.5 and O 3 concentrations were divided into three levels, and several samples were selected for single sample analysis. The analysis showed that at low pollutant concentration, most of the features made negative contributions to the concentration prediction, while at high concentration, most of the features made positive contributions. The contribution values of different features varied greatly and were unevenly distributed. The results of prediction were basically composed of a few features with large feature contributions, and the feature contributions of the same feature to different concentration prediction results were also different. Moreover, the XGBoost algorithm was used to optimize the concentration of pollutant at each grid point in Beijing, and a set of pollutant concentration data set with spatial resolution of 6 km and time resolution of 1 h covering the whole Beijing was established, and the optimized spatial distribution of pollutant concentration was closer to the spatial distribution of observed concentration than WRF-Chem simulation. At last, compared with SVR, LR, DTR and RF algorithms, XGBoost algorithm was better than other statistical algorithms in optimising PM 2.5 and O 3 concentrations. The results of this study provided a new idea for an in-depth analysis of optimization principle of algorithm model for air pollution and a quantitative study of the influencing factors. • Based on WRF-Chem and XGBoost algorithm, the pollutant concentration is optimized. • The optimization of pollutant concentration by XGBoost algorithm are satisfactory. • The principle of algorithm optimization is analyzed based on the Shap value. • A high-quality data set with spatial resolution of 6 km and time resolution of 1 h is established. [ABSTRACT FROM AUTHOR]

Background: 7-p-trifluoromethylphenyl-FL118 (FLQY2) is a camptothecin analog with excellent antitumor efficacy against various solid tumors. However, its poor solubility and low bioavailability limited the development of the drug. Polyvinyl caprolactam-polyvinyl acetate-polyethylene glycol graft copolymer (Soluplus®), an emerging carrier for preparing solid dispersion (SD), encapsulated FLQY2 to circumvent the above limitations. Results: In this project, FLQY2-SD was prepared by solvent evaporation method and self-assembled into micelles in aqueous solutions owing to the amphiphilic nature of Soluplus®. The physicochemical characterizations demonstrated that FLQY2 existed in a homogeneous amorphous form in SD and was rapidly dissolved. The micelles did not affect cytotoxicity or cellular uptake of FLQY2 in vitro, and the oral bioavailability was increased by 12.3-fold compared to the FLQY2 cyclodextrin suspension. The pharmacokinetics of FLQY2-SD showed rapid absorption, accumulation in the intestine, and slow elimination via fecal. Metabolite identification studies showed 14 novel metabolites were identified, including 12 phase I metabolites (M1–M12) and 2 phase II metabolites (M13–M14), of which M2 (oxidation after decarboxylation) and M7 (dioxolane ring cleavage) were the primary metabolites in the positive mode and negative mode, respectively. The tumor growth inhibition rate (TGI, 81.1%) of FLQY2-SD (1.5 mpk, p.o./QW) in tumor-bearing mice after oral administration was higher than that of albumin-bound Paclitaxel (15 mpk, i.v./Q4D) and Irinotecan hydrochloride (100 mpk, i.p./QW). Conclusions: The successful preparation, pharmacokinetics, and pharmacodynamics studies of FLQY2-SD showed that the solubility and bioavailability of FLQY2 were improved, which facilitated the further druggability development of FLQY2. [ABSTRACT FROM AUTHOR]

To improve the forecasting effectiveness of numerical air quality models, two deep learning models, DeepPM and APTR, were constructed and trained in this study using PM 2.5 and O 3 monitoring data, and WRF-Chem numerical forecasts in the south-central Beijing-Tianjin-Hebei region. The optimization effects were evaluated using test datasets and various evaluation metrics. The results show that the PM 2.5 and O 3 forecast results optimized by the DeepPM, and APTR models significantly outperform the WRF-Chem numerical model for both proximity forecasts over the next 24 h and short- to medium-term forecasts over the next 144 h. The APTR model achieves the best optimization results in proximity forecasting, whereas the DeepPM model has a better overall performance in optimizing the short- and medium-term forecasts. WRF-Chem is superior to other models in predicting high O 3 concentration. DeepPM and APTR deep learning models are still significantly better than WRF-Chem for forecasting high concentration bands within the proximity forecast time period. For short- to medium-term forecasting, the DeepPM model outperforms WRF-Chem for forecasting high O 3 concentrations. This paper provides a new method and idea for improving the forecasting performance of air quality numerical models. • Two deep learning models were established to improve forecasting performance of WRF-Chem. • The APTR model achieves the best optimization results in proximity forecasting (24-h). • The DeepPM model has a better performance in optimizing short- and medium-term forecasts (144-h). [ABSTRACT FROM AUTHOR]

[Display omitted] • The potential of clinical drugs to suppress pancreatic cancer using camptothecin derivatives is still not remarkable, whereas the potential of FLQY2 as a camptothecin derivative could significantly suppress pancreatic cancer-patient-derived organoids. • FLQY2 has promising effects on pancreatic cancer in vitro and in vivo. • The TOP Ⅰ binding efficiency and PDK1/AKT/mTOR pathways were involved in FLQY2 treatment of the Mia Paca-2 pancreatic cancer cell. Camptothecin (CPT), a pentacyclic alkaloid with antitumor properties, is derived from the Camptotheca acuminata. Topotecan and irinotecan (CPT derivatives) were first approved by the Food and Drug Administration for cancer treatment over 25 years ago and remain key anticancer drugs today. However, their use is often limited by clinical toxicity. Despite extensive development efforts, many of these derivatives have not succeeded clinically, particularly in their effectiveness against pancreatic cancer which remains modest. This study aimed to evaluate the therapeutic activity of FLQY2, a CPT derivative synthesized in our laboratory, against pancreatic cancer, comparing its efficacy and mechanism of action with those of established clinical drugs. The cytotoxic effects of FLQY2 on cancer cells were assessed using an MTT assay. Patient-derived organoid (PDO) models were employed to compare the sensitivity of FLQY2 to existing clinical drugs across various cancers. The impact of FLQY2 on apoptosis and cell cycle arrest in Mia Paca-2 pancreatic cancer cells was examined through flow cytometry. Transcriptomic and proteomic analyses were conducted to explore the underlying mechanisms of FLQY2′s antitumor activity. Western blotting was used to determine the levels of proteins regulated by FLQY2. Additionally, the antitumor efficacy of FLQY2 in vivo was evaluated in a pancreatic cancer xenograft model. FLQY2 demonstrated (1) potent cytotoxicity; (2) superior tumor-suppressive activity in PDO models compared to current clinical drugs such as gemcitabine, 5-fluorouracil, cisplatin, paclitaxel, ivosidenib, infinitinib, and lenvatinib; (3) significantly greater tumor inhibition than paclitaxel liposomes in a pancreatic cancer xenograft model; (4) robust antitumor effects, closely associated with the inhibition of the TOP I and PDK1/AKT/mTOR signaling pathways. In vitro studies revealed that FLQY2 inhibited cell proliferation, colony formation, induced apoptosis, and caused cell cycle arrest at nanomolar concentrations. Furthermore, the combination of FLQY2 and gemcitabine exhibited significant inhibitory and synergistic effects. The study confirmed the involvement of topoisomerase I and the PDK1/AKT/mTOR pathways in mediating the antitumor activity of FLQY2 in treating Mia Paca-2 pancreatic cancer. Therefore, FLQY2 has potential as a novel therapeutic option for patients with pancreatic cancer. [ABSTRACT FROM AUTHOR]

Irinotecan and Topotecan are two Camptothecin derivatives (CPTs) whose resistance is associated with the high expression of breast cancer resistance protein (BCRP) and P-glycoprotein (P-gp). To reverse this resistance, two novel CPTs, FL77-28 (7-(3-Fluoro-4-methylphenyl)-10,11-methylenedioxy-20(S)-CPT) and FL77-29 (7-(4-Fluoro-3-methylphenyl)-10,11-methylenedioxy-20(S)-CPT), were synthesized by our group. In this study, the anti-tumor activities of FL77-28, FL77-29, and their parent, FL118 (10,11-methylenedioxy-20(S)-CPT), were evaluated and the results showed that FL77-28 and FL77-29 had stronger anti-tumor activities than FL118. The transport and uptake of FL118, FL77-28, and FL77-29 were investigated in Caco-2 cells for the preliminary prediction of intestinal absorption. The apparent permeability coefficient from apical to basolateral (Papp AP-BL) values of FL77-28 and FL77-29 were (2.32 ± 0.04) × 10−6 cm/s and (2.48 ± 0.18) × 10−6 cm/s, respectively, suggesting that the compounds had moderate absorption. Since the transport property of FL77-28 was passive diffusion and the efflux ratio (ER) was less than 2, two chemical inhibitors were added to further confirm the involvement of efflux proteins. The results showed that FL77-28 was not a substrate of P-gp or BCRP, but FL77-29 was mediated by P-gp. In conclusion, FL77-28 might be a promising candidate to overcome drug resistance induced by multiple efflux proteins. [ABSTRACT FROM AUTHOR]

Vehicles carrying hazardous material (hazmat) are severe threats to the safety of highway transportation, and a model that can automatically recognize hazmat markers installed or attached on vehicles is essential for intelligent management systems. However, there is still no public dataset for benchmarking the task of hazmat marker detection. To this end, this paper releases a large-scale vehicle hazmat marker dataset named VisInt-VHM, which includes 10,000 images with a total of 20,023 hazmat markers captured under different environmental conditions from a real-world highway. Meanwhile, we provide an compact hazmat marker detection network named HMD-Net, which utilizes a revised lightweight backbone and is further compressed by channel pruning. As a consequence, the trained-model can be efficiently deployed on a resource-restricted edge device. Experimental results demonstrate that compared with some established methods such as YOLOv3, YOLOv4, their lightweight versions and popular lightweight models, HMD-Net can achieve a better trade-off between the detection accuracy and the inference speed. [ABSTRACT FROM AUTHOR]

Abstract: Micronized camptothecin (CPT) is prepared with a supercritical antisolvent (SAS) apparatus using dimethyl sulfoxide (DMSO) as solvent and carbon dioxide as antisolvent. Four factors, namely CPT solution concentration and flow rate, precipitation temperature and pressure are optimized by a four-level orthogonal array design (OAD). By analysis of variance (ANOVA), only precipitation pressure has a significant effect on the MPS of micronized CPT. The optimum micronization conditions are determined as follows: CPT solution concentration 1.25mg/ml, CPT solution flow rate 6.6ml/min, precipitation temperature 35°C and precipitation pressure 20MPa. Under the optimum conditions, micronized CPT with a MPS of 0.25±0.020μm is obtained. The micronized CPT obtained was characterized by Scanning Electron Microscopy (SEM), Atomic Force Microscope (AFM), High performance liquid chromatography–mass spectrometry (LC–MS), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Differential scanning calorimeters (DSC) and Gas chromatography (GC) analyses. The results showed that the obtained CPT particles have lower crystallinity and SAS micronization process does not induce degradation of CPT. In addition, the residual DMSO is less than the ICH limit for class 3 solvents. [Copyright &y& Elsevier]

Abstract: Some linear sparse coding models have been proposed for modeling responses in the early stage of the visual system, but nonlinear operations are ubiquitous in visual cortex. So we put forward an associative sparse coding neural network (ASCNN) with nonlinear response property in top-layer coding units. In our ASCNN model, the choices of sparseness function must correspond to the characters of activation function. This paper gives several reasonable and efficient methods for constructing sparseness functions and activation functions. Experiment on benchmark natural image dataset shows that our model can successfully simulate receptive field and nonlinear sparse response property of simple cells. Moreover, in two recognition tasks on face images and handwritten digits, experimental results show that our model works much better than linear sparse coding model (Sparsenet) by combining with linear neural network classifier. [Copyright &y& Elsevier]

Fine-grained image retrieval aims at searching relevant images among fine-grained classes given a query. The main difficulty of this task derives from the small interclass distinction and the large intraclass variance of fine-grained images, posing severe challenges to the methods that only resort to global or local features. In this paper, we propose a novel fine-grained image retrieval method, where global–local aware feature representation is learned. Specifically, the global feature is extracted by selecting the most relevant deep descriptors. Meanwhile, we explore the intrinsic relationship of different parts via the frequent pattern mining, thus obtaining the representative local feature. Further, an aggregation feature that learns global–local aware feature representation is designed. Consequently, the discriminative ability among different fine-grained classes is enhanced. We evaluate the proposed method on five popular fine-grained datasets. Extensive experimental results demonstrate that the performance of fine-grained image retrieval is improved with the proposed global–local aware representation. [ABSTRACT FROM AUTHOR]