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To overcome the limitations of geography, climate, and ore characteristics on the ore beneficiation process, bio-oxidation studies on low-grade arsenic-bearing refractory gold ore by pool leaching were carried out, as well as process fitting analysis. The gold particles are encapsulated by pyrite and arsenopyrite. After 60 days of bio-oxidation, the oxidation rates of arsenic, sulfur, and gold were 39%∼69%, 24%∼41%, and 49%∼83%, respectively. The inoculated Acidithiobacillus ferrooxidans, Ferroplasma acidiphilum, and Leptospirillum ferrodiazotrophum could all mediate the initial pyrite/arsenopyrite oxidation and the Fe2+ oxidation reaction, but only the former could mediate the subsequent sulfur compound oxidation. When compared to daily bacterial circulation and bacterial replacement every ten days, aeration improved the gold leaching rate by 14%∼22%. The Boltzmann model could fit both the arsenic and sulfur bio-oxidation, with model fit variances greater than 0.98. Based on the experimental and fitting results, the bio-oxidation cycle was determined to be 60 days, and the bio-oxidation mechanisms are summarized. This study has significant practical implications for the rational utilization of gold resources and provides theoretical and practical guidance for similar gold ores.

Abstract Recent research highlights the significant impact of methionine metabolism on glioma progression. An increasing amount of compelling evidence bridges long non-coding RNAs to abnormal metabolism in gliomas. However, the specific role of long non-coding RNAs in methionine metabolism regulating glioma progression remains unclear. This study reveals that methionine deprivation inhibits the proliferation, migration, and invasion capabilities of gliomas. Interestingly, the expression of TP53TG1, a long non-coding RNA, is also suppressed. TP53TG1 is highly expressed in gliomas and associated with poor patient outcomes. Subsequently, our data proves that inhibition of TP53TG1 suppresses glioma cell proliferation and the epithelial-mesenchymal transition process both in vitro and in vivo. Ultimately, we found that the underlying mechanism involves a competing endogenous RNA regulating network, in which TP53TG1 modulates the target protein STK17B by competitively binding to miR-96-5p, thus regulating glioma progression. These findings suggest that targeting methionine deprivation could be a promising approach for the clinical treatment of glioma.

Highlights Nonflammable gel polymer electrolyte (SGPE) is developed by in situ polymerizing trifluoroethyl methacrylate (TFMA) monomers with flame-retardant triethyl phosphate (TEP) solvents and LiTFSI–LiDFOB dual lithium salts. Molecular polarity interaction between TEP and PTFMA mitigates interfacial reactions and changes the solvation of Li+. SGPE forms stable inorganic-rich solid electrolyte interface/cathode electrolyte interface layer, exhibiting well compatibility with Li anode and LiCoO2-type high-voltage cathode.

Anterior cruciate ligament (ACL) tears are prevalent knee injures, particularly among active individuals. Accurate and timely diagnosis is essential for determining the optimal treatment strategy and assessing patient prognosis. Various previous studies have demonstrated the successful application of deep learning techniques in the field of medical image analysis. This study aimed to develop a deep learning model for detecting ACL tears in knee magnetic resonance Imaging (MRI) to enhance diagnostic accuracy and efficiency. The proposed model consists of three main modules: a Dual-Scale Data Augmentation module (DDA) to enrich the training data on both the spatial and layer scales; a selective group attention module (SG) to capture relationships across the layer, channel, and space scales; and a fusion module to explore the inter-relationships among various perspectives to achieve the final classification. To ensure a fair comparison, the study utilized a public dataset from MRNet, comprising knee MRI scans from 1250 exams, with a focus on three distinct views: axial, coronal, and sagittal. The experimental results demonstrate the superior performance of the proposed model, termed SGNET, in ACL tear detection compared with other comparison models, achieving an accuracy of 0.9250, a sensitivity of 0.9259, a specificity of 0.9242, and an AUC of 0.9747.

Abstract Lithium metal solid‐state battery is the first choice of batteries for electromobiles and consumer electronic products because of the specific capacity of 3860 mAh g−1 and high electrochemical potential (−3.04 V) of Li metal. Flexible polymer solid electrolytes have become the optimal solution to produce high energy density lithium batteries with arbitrary size and shape. In this work, we introduce a halide perovskite, CsSnI3, into the polyethylene oxide/lithium bis‐(trifluoromethanesuphone)imide (PEO–LiTFSI) polymer matrix. The CsSnI3 could form a LixSn alloy with Li, leading to homogenization of the electric field and Li+‐flux at the interface, Sn atom also bonds with the TFSI− anion to provide more dissociated Li+. Besides that, the I atom could interact with Li to form an electronic insulation with a strong blocking effect on electron tunneling. As a proof of concept, the synergy mechanism of the PEO–LiTFSI–CsSnI3 electrolyte improves the stable cycle life of the symmetric battery to more than 500 h, and the Li+ conductivity raised to 6.1 × 10−4 S cm−1 at 60°C. The application of the “zwitter ions analog” halide perovskite in PEO–LiTFSI provides a new choice among various methods to improve the electrochemical performance of polymer solid‐state batteries.

In recent years, concerns have escalated regarding eye health problems arising from Light-emitting diode (LED), which emits high-energy blue light (BL), potentially causing corneal epithelial dysfunctions (CEpD). Nevertheless, the mechanisms underlying this damage remain poorly comprehended. This study endeavors to explore the specific mechanisms through which BL exposure induces CEpD. The study carried out diverse assays and treatments to investigate the toxicological effects of BL exposure. 48 hours (h) of 440 nm of BL exposure decreased the migration of human corneal epithelial cells (hCEpCs) while augmenting reactive oxygen species (ROS) production and apoptosis. RNA-Sequencing and bioinformatic analysis indicated that cellular oxidation and reduction equilibrium, wound healing, the positive regulation of the apoptotic process, and the Phosphoinositide 3-kinase (PI3K)/AKT pathway were significantly influenced by BL exposure. Treatment with N-acetylcysteine (NAC), a ROS scavenger, restored cell viability and AKT/S6 kinase (S6K) activation, suggesting the involvement of ROS in BL-induced damage. NAC also reversed BL-induced apoptosis and migration. Blocking AKT/S6K replicated detrimental effects, while pre-treatment with SC79 (SC), an AKT activator, alleviated the changes caused by BL exposure in hCEpCs. Furthermore, in mice, the combination of AKT inhibition and BL exposure led to CEpD. However, treatment with SC and NAC restored CEpD caused by BL exposure. These results imply that the regulation of the ROS/PI3K/AKT/S6K axis is implicated in BL-induced CEpD. Collectively, this study offers insights into the molecular mechanisms of BL-induced CEpD and proposes targeting the ROS/PI3K/AKT/S6K cascade as a potential therapeutic approach. The findings contribute to ocular health knowledge and establish the basis for developing interventions to safeguard the cornea from the detrimental effects of excessive BL exposure.

Osteoarthritis (OA) is one of the most prevalent joint diseases and severely affects the quality of life in the elderly population. However, there are currently no effective prevention or treatment options for OA. Oxidative stress and pyroptosis play significant roles in the development and progression of OA. To address this issue, we have developed a novel therapeutic approach for OA that targets oxidative stress and pyroptosis. We synthesized tetrahedral framework nucleic acid (tFNAs) to form framework nucleic acid complexes (TNCs), which facilitate the delivery of the naturally occurring polymethoxyflavonoid nobiletin (Nob) to chondrocytes. TNC has demonstrated favorable bioavailability, stability, and biosafety for delivering Nob. Both in vitro and in vivo experiments have shown that TNC can alleviate OA and protect articular cartilage from damage by eliminating oxidative stress, inhibiting pyroptosis, and restoring the extracellular matrix anabolic metabolism of chondrocytes. These findings suggest that TNC has significant potential in the treatment of OA and cartilage injury.

ObjectivesThis study aimed to investigate the psychological stress experienced by frontline medical staff during the Yangbi Earthquake and to understand how coping strategies and social support influence stress responses.MethodsFrom days 3 to 14 post-earthquake, online questionnaires were administered to frontline medical staff to assess perceived social support, coping strategies, and psychological stress responses using the Perceived Social Support Scale (PSSS), Trait Coping Strategies Questionnaire (TCSQ), and Stress Response Questionnaire (SRQ). Data analysis included correlation analysis to explore relationships between variables, multiple linear regression to identify key predictors of stress, and path analysis to determine direct and indirect effects.ResultsA total of 253 valid questionnaires were analyzed, with a participant composition of 81.82% females and 18.18% males, and the majority being nurses (62.06%). Psychological stress responses varied by gender and age, with females and older age groups showing higher physical stress responses (P < 0.05). Correlation and regression analyses indicated that negative coping and lower levels of social support were associated with increased stress responses (P < 0.05). Path analysis revealed that intra-family and extra-family support influenced stress responses directly and indirectly through coping strategies (P < 0.05).ConclusionThis study suggests that perceived social support directly influences stress responses in frontline medical personnel during disasters, with coping strategies mediating this effect. Future research should explore these dynamics over time through longitudinal studies.

Osteoporotic bone defect repair is one of the challenges in orthopedics because there are no preferable biomaterials to readily initiate new bone regeneration in critical-size pathological bone damage. Our previous studies revealed that core–shell Ca-phosphate/silicate microspheres can tune time-evolving biodegradation, which is beneficial for modulating bone repair. Herein, we expanded this strategy to develop core–shell-type 5 % Sr- and 8 % Zn-doped wollastonite fiber-derived granules with different porosities (0 %, 10 %, 20 %) in the shell layer. Physicochemical analyses indicated that granules with higher porosity in the shell layer exhibited more appreciable Sr and Zn ion release and biodissolution in vitro. Osteoporotic femoral bony defects in rabbits were used to verify the osteogenic efficacy of the core–shell granules. The granules with 10 % porosity could initiate more osteogenesis within 6 weeks, and the new bone tissue could grow into the defect region, while the new bone tissue only migrated into the periphery pores under the other granule conditions. Histological evaluation also revealed appreciable new bone ingrowth in the granules with 10 % porosity, whereas the other implant groups had limited new bone tissue. These findings demonstrate that bone repair initiation can be enhanced by finely designed local porosity in specific components of core–shell bioceramic fiber-tailoring granules to control bioactive ion release and osteo-stimulation in vivo; moreover, such bioceramic fabrication is promising for developing osteo-stimulative implants to resolve clinically challenging bone defect repair.

In this study, sensory evaluation and headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were used to identify and analyze the volatile components of Yingjiang Camellia taliensis bud tea (usually called spore tea, marked as spore black tea YBH, spore white tea YBB) and Fengqing large-leaved species bud tea (marked as Fengqing black tea FQH, Fengqing white tea FQB) in order to investigate the aroma composition and differences between Yunnan Yingjiang Camellia taliensis bud tea and Fengqing large-leaved species bud tea. The results of HS-SPME-GC-MS showed that a total of 616 volatile metabolites from 16 categories were detected in the four tea samples. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) showed that in the comparison of two varieties of black tea, 8 unique differential metabolites were detected in YBH, and 7 unique differential metabolites in FQH, while in the comparison of two varieties of white tea, 3 unique differential metabolites were detected in YBB and 4 unique differential metabolites in FQB. The odor activity value (OAV) evaluation of the main characteristic differential volatile metabolites showed that (Z)-2-decenal and geraniol were the potential characteristic aromas to distinguish Yingjiang Camellia taliensis and Fengqing large-leaved species, (Z)-2-decenal (OAV>100) was an important aroma component of Yingjiang Camellia taliensis. It was speculated that damascenone (OAV>1) was the key substances for YBH to produce strong flower and fruit aroma. Caproic acid and linalyl acetate might be the main substances of YBB with natural flower fragrance. β-Ionone (OAV>10) was an important aroma component of Fengqing large-leaved species. It was speculated that benzaldehyde (OAV>1) was the main substance of FQH with flower aroma, and (Z)-2-decenal and caproic acid were the main substances of FQB with floral and fragrance. In summary, the aroma components of Yingjiang Camellia taliensis spore tea are richer than the control variety and the aroma of YBH is more fragrant.

In this manuscript, an efficient self-reinforcing technology—solid hot drawing (SHD) technology—was combined with green processing supercritical carbon dioxide (SC-CO2) foaming technology to promote poly (l-lactic acid) (PLLA) to form an oriented micropore structure. In addition, Polydimethylsiloxane (PDMS), with a high affinity of CO2 and biological safety, was introduced to enhance the nucleation effect in SC-CO2 foaming and co-regulate the uniformity of oriented micropores’ structure. The results showed that orientation induced PLLA crystallization, so the tensile strength was improved; the maximum tensile strength of the oriented micropores’ PLLA reached 151.2 MPa. Furthermore, the micropores mainly improved the toughness; the maximum elongation at break reached 148.3%. It is worth mentioning that PDMS can form an antibacterial film on the surface of the material, so that the material has a continuous antibacterial effect.

BackgroundThe impact of chronic hepatic infection on antigen non-specific immune cells in circulation remains poorly understood. We reported lasting global hyperfunction of peripheral CD8 T cells in HCV-infected individuals with cirrhosis. Whether gene expression patterns in bulk CD8 T cells are associated with the severity of liver fibrosis in HCV infection is not known.MethodsRNA sequencing of blood CD8 T cells from treatment naïve, HCV-infected individuals with minimal (Metavir F0-1 ≤ 7.0 kPa) or advanced fibrosis or cirrhosis (F4 ≥ 12.5 kPa), before and after direct-acting antiviral therapy, was performed. CD8 T cell function was assessed by flow cytometry.ResultsIn CD8 T cells from pre-DAA patients with advanced compared to minimal fibrosis, Gene Ontology analysis and Gene Set Enrichment Analysis identified differential gene expression related to cellular function and metabolism, including upregulated Hedgehog (Hh) signaling, IFN-α, -γ, TGF-β response genes, apoptosis, apical surface pathways, phospholipase signaling, phosphatidyl-choline/inositol activity, and second-messenger-mediated signaling. In contrast, genes in pathways associated with nuclear processes, RNA transport, cytoskeletal dynamics, cMyc/E2F regulation, oxidative phosphorylation, and mTOR signaling, were reduced. Hh signaling pathway was the top featured gene set upregulated in cirrhotics, wherein hallmark genes GLI1 and PTCH1 ranked highly. Inhibition of Smo-dependent Hh signaling ablated the expression of IFN-γ and perforin in stimulated CD8 T cells from chronic HCV-infected patients with advanced compared to minimal fibrosis. CD8 T cell gene expression profiles post-DAA remained clustered with pre-DAA profiles and disparately between advanced and minimal fibrosis, suggesting a persistent perturbation of gene expression long after viral clearance.ConclusionsThis analysis of bulk CD8 T cell gene expression in chronic HCV infection suggests considerable reprogramming of the CD8 T cell pool in the cirrhotic state. Increased Hh signaling in cirrhosis may contribute to generalized CD8 T cell hyperfunction observed in chronic HCV infection. Understanding the lasting nature of immune cell dysfunction may help mitigate remaining clinical challenges after HCV clearance and more generally, improve long term outcomes for individuals with severe liver disease.

Several studies have been devoted to seeking some beneficial plant-related microorganisms for a long time, and on this basis, it has been found that arbuscular mycorrhizal fungi (AMF) have a considerable positive impact on plant health as a biological fungal agent. In this study, we focused on the effects of different AMF on the growth dynamics and root configuration of licorice under saline and alkali conditions. The metabolites of licorice under different AMF were assessed using liquid chromatography–tandem mass spectrometry (LC-MS/MS). Funneliformis mosseae (Fm) and Rhizophagus intraradices (Ri) were added as different AMF treatments, while the sterilized saline–alkali soil was treated as a control. Samples were taken in the R1 period (15 d after AMF treatment) and the R2 period (45 d after AMF treatment). The results showed that the application of AMF significantly increased the root growth of licorice and significantly increased the biomass of both shoot and root. A total of 978 metabolites were detected and divided into 12 groups including lipids, which accounted for 15.44%; organic acids and their derivatives, at 5.83%; benzene compounds and organic heterocyclic compounds, at 5.42%; organic oxides, at 3.78%; and ketones, accounting for 3.17%. Compared with the control, there were significant changes in the differential metabolites with treatment inoculated with AMF; the metabolic pathways and biosynthesis of secondary metabolites were the main differential metabolite enrichment pathways in the R1 period, and those in the R2 period were microbial metabolism in diverse environments and the degradation of aromatic compounds. In conclusion, the use of AMF as biofertilizer can effectively improve the growth of licorice, especially in terms of the root development and metabolites, in saline–alkali soil conditions.

In this study, three different substrate holder shapes—trapezoidal, circular frustum, and adjustable cyclic—were designed and optimized to enhance the quality of polycrystalline diamond films grown using microwave plasma chemical vapor deposition (MPCVD). Simulation results indicate that altering the shape of the substrate holder leads to a uniform distribution of the electric field on the surface, significantly suppressing the formation of secondary plasma. This design ensures a more even distribution of the temperature field and plasma environment on the substrate holder, resulting in a heart-shaped distribution. Polycrystalline diamond films were synthesized under these three different substrate holder conditions, and their morphology and crystal quality were characterized using optical microscopy, Raman spectroscopy, and high-resolution X-ray diffraction. Under conditions of 5 kW power and 90 Torr pressure, the adjustable cyclic substrate holder produced high-quality 3-inch diamond films with low stress and narrow Raman full width at half maximum (FWHM). The results confirm the reliability of the simulations and the effectiveness of the adjustable cyclic substrate holder. This approach provides a viable method for scaling up the size and improving the quality of polycrystalline diamond films for future applications.

In order to probe into the value of exploration and utilization of Yingjiang uncultivated ancient tea resources, representative samples of spore tea from Camellia taliensis in Yingjiang county (spore white tea and spore black tea) were selected, and typical Yunnan samples (Yunnan white tea and Yunnan black tea golden bud) were taken as a control sample of them. At the same time, sensory evaluation and chemical composition test detection were used to compare the differences in taste chemical composition of the sample, and analyze the key taste components of the sample in combination with the method of taste activity value (TAV). The results showed that in sensory evaluation, spore white tea and spore black tea had a unique shape like a bamboo shoot, and their quality of taste was better than that of Yunnan white tea and Yunnan black tea golden bud. The test results of chemical composition showed that the content of chemical components in the taste of spore white tea was generally low and other components were significantly lower than that of Yunnan white tea, except for the content of soluble sugar as high as 9.45%, the content of taste's chemical components of spore black tea such as water extract, free amino acid, soluble sugar, sweet amino acid was high, all of which were significantly higher than that of Yunnan black tea golden bud, especially the content of soluble sugar which was up to 20.37%. While the content of tea polyphenols, caffeine, ester catechins, etc. was relatively low, in which the content of tea polyphenols was as low as 6.98%, showing that the ratio of tea polyphenols to amino acids was low and the ratio of soluble sugar to caffeine was high. Thus, the results were consistent with the sensory evaluation results. The results of TAV analysis showed that the contribution of the bitter and astringent chemical components including catechin components, caffeine and partial amino acids in the key components to spore white tea and spore black tea was lower than that of the control samples. In conclusion, the content of chemical components in the taste of Yingjiang spore tea was quite different from the control sample in Yunnan Province, and the quality of Yingjiang spore tea was excellent. What's more, the uncultivated ancient tea resources of Camellia taliensis had high value of exploration and utilization, especially suitable for making black tea.

ObjectiveOur study aimed to evaluate the cost-effectiveness of the addition of serplulimab to chemotherapy (cisplatin and fluorouracil) for programmed death-ligand 1 (PD-L1) positive advanced esophageal squamous cell carcinoma (ESCC) as the first-line treatment in China.MethodsA three-state Markov model was established to assess the incremental cost-effectiveness ratio (ICER) for serplulimab plus chemotherapy versus chemotherapy alone. Survival data were extrapolated from the ASTRUM-007 trial, cost data were derived from local sources, and utilities were derived from published literature. Health outcomes were measured as quality-adjusted life-years (QALYs). Sensitivity and probability sensitivity analyses were used to investigate the robustness of the model.ResultsIn the base-case analysis, compared with chemotherapy alone, serplulimab gained an additional 0.16 QALYs with an incremental cost of $29,547.88, leading to an ICER of $184,674.25/QALY. Additionally, the subgroup analyses presented that the ICERs of serplulimab plus chemotherapy were $157,892.50/QALY and $127,996.45/QALY in advanced ESCC patients with 1≤ CPS< 10 and CPS≥ 10, respectively. These ICERs significantly exceeded the Chinese willingness-to-pay (WTP) threshold. The deterministic sensitivity analysis illustrated that the cost of progression-free survival in serplulimab plus chemotherapy group was the parameter with the strongest influence on the ICERs.ConclusionIn the Chinese health care system, with 3 times China’s per capita gross domestic product as the WTP threshold, compared with chemotherapy alone, serplulimab combined chemotherapy is not economical for PD-L1-positive advanced ESCC in the first-line setting.

The teaching of the optimization algorithm is a new kind of swarm intelligence optimization technique, which is superior in optimizing many simple functions. Still, it is not evident in processing some complex problems (group and teaching classification). Achieving automatic matching and knowledge transfer in online courses is imperative in mathematics education. This study proposes a design scheme MTCBO-LR (multiobjective capability optimizer-logistic regression), based on multitask optimization, which enables precise knowledge transfer and data interaction among many educators. It incorporates the standard TLBO algorithm to optimize, provides a variety of learning tactics for students at different stages of mathematics instruction, and is capable of adaptively adjusting these strategies in response to actual teaching needs. Experimental results on various datasets reveal that the proposed method enhances searchability and group diversity in various optimization extremes and outperforms similar methods in resolving to multitask teaching problems.

Abstract Developing ionogel electrolytes based on ionic liquid instead of volatile liquid in gel polymer electrolytes is regarded to be effective to diminish safety concerns in terms of overheating and fire. Herein, a zwitterion‐based copolymer matrix based on the copolymerization of trimethylolpropane ethoxylate triacrylate (ETPTA) and 2‐methacryloyloxyethylphosphorylcholine (MPC, one typical zwitterion) is developed. It is shown that introducing zwitterions into ionogel electrolytes can effectively optimize local lithium‐ion (Li+) coordination environment to improve Li+ transport kinetics. The interactions between Li+ and bis(trifluoromethanesulfonyl)imide (TFSI−)/MPC lead to the formation of Li+ coordination shell jointly occupied by MPC and TFSI−. Benefiting from the competitive Li+ attraction of TFSI− and MPC, the energy barrier of Li+ desolvation is sharply decreased and thus the room‐temperature ionic conductivity can reach a value of 4.4 × 10−4 S cm−1. Besides, the coulombic interaction between TFSI− and MPC can greatly decrease the reduction stability of TFSI−, boosting in situ derivation of LiF‐enriched solid electrolyte interface layer on lithium metal surface. As expected, the assembled Li||LiFePO4 cells deliver a high reversible discharge capacity of 139 mAh g−1 at 0.5 C and good cycling stability. Besides, the pouch cells exhibit a steady open‐circuit voltage and can operate normally under abuse testing (fold, cut), showing its outstanding safety performance.

A Gas–solid two-phase flow coupling simulation is widely used to study the working process of pneumatic seed dischargers. Due to the demand for deterministic particle orbit numerical calculation models, seeds are mostly modeled using the particle aggregation method, where the seed model is formed through particle aggregation bonding without overlapping. The smaller the radius and the more filled ball particles used in this method, the closer they resemble the real morphology of the seed. However, this results in the over-consumption of simulation computational resources and simulation time growth. In this study, we used wheat seeds as the research object, studied the effect of seed models with different filled ball radii on the kinetic response characteristics between the particles, and searched for the optimal number of filled ball particles for the seed model. With the help of three-dimensional scanning and inverse fitting methods to obtain the seed profile, we used different radii (0.2 mm, 0.24 mm, 0.28 mm, 0.32 mm, 0.36 mm, and 0.4 mm) to fill the ball particles, and formed a wheat particle bonding model for a gas–solid coupling simulation. We used a combination of real tests and simulation measurements of bottomless cylinder-lifting and slip-stacking. The interspecies static and dynamic friction factors in seed models with different radii of filled spherical particles were first calibrated using the angle of repose as an index. Then, the parameters were verified using bottomless cylinder lifting and slip stacking tests, which used the coefficient of variation for the simulation test’s angle of repose as an index. Our results show that the smaller the radius of the filled ball, the closer the simulation results were to the real value. Validation was conducted using a gas–solid coupling simulation of an air-blown wheat seed discharger, with the seed filling rate as an index. Our results showed that the simulation length and simulation accuracy were optimal when the radius of the filling particle was 0.32 mm.

Abstract Anomaly object detection is the core technology in the application for X‐ray images. However, the accuracy of current X‐ray anomaly object detection method still needs to be improved. In this paper, an effective anomaly object detection network is proposed to improve the detection accuracy of anomaly object for X‐ray images. Firstly, learnable Gabor convolution layer, deformable convolution, and spatial attention mechanism are introduced to enhance the representative ability of features in ResNeXt. Then, dense local regression is applied to predict the offset of multiple dense boxes in region proposal to locate the object accurately. At last, bigger discriminative RoI pooling is proposed to classify the candidate boxes to improve the accuracy of object classification. Experimental results on the SIXray and OPIXray datasets show that compared with the state‐of‐the‐art methods, the proposed EAOD‐Net can achieve the competitive detection performance.

Small molecule NIR-II fluorophores are of interest for a range of applications but can suffer from chemical and photostability issues. Here, the authors report on the development of an acceptor molecule with improved stability in alkaline conditions expanding the range of possible applications.

The pore morphology design of bioceramic scaffolds plays a substantial role in the induction of bone regeneration. Specifically, the effects of different scaffold pore geometry designs on angiogenesis and new bone regeneration remain unclear. Therefore, we fabricated Mg/Sr co-doped wollastonite bioceramic (MS-CSi) scaffolds with three different pore geometries (gyroid, cylindrical, and cubic) and compared their effects on osteogenesis and angiogenesis in vitro and in vivo. The MS-CSi scaffolds were fabricated by digital light processing (DLP) printing technology. The pore structure, mechanical properties, and degradation rate of the scaffolds were investigated. Cell proliferation on the scaffolds was evaluated using CCK-8 assays while angiogenesis was assessed using Transwell migration assays, tube formation assays, and immunofluorescence staining. The underlying mechanism was explored by western blotting. Osteogenic ability of scaffolds was evaluated by alkaline phosphatase (ALP) staining, western blotting, and qRT-PCR. Subsequently, a rabbit femoral defect model was prepared to compare differences in the scaffolds in osteogenesis and angiogenesis in vivo. Cell culture experiments showed that the gyroid pore scaffold downregulated YAP/TAZ phosphorylation and enhanced YAP/TAZ nuclear translocation, thereby promoting proliferation, migration, tube formation, and high expression of CD31 in human umbilical vein endothelial cells (HUVECs) while strut-based (cubic and cylindrical pore) scaffolds promoted osteogenic differentiation in bone marrow mesenchymal stem cells and upregulation of osteogenesis-related genes. The gyroid pore scaffolds were observed to facilitate early angiogenesis in the femoral-defect model rabbits while the strut-based scaffolds promoted the formation of new bone tissue. Our study indicated that the pore geometries and pore curvature characteristics of bioceramic scaffolds can be precisely tuned for enhancing both osteogenesis and angiogenesis. These results may provide new ideas for the design of bioceramic scaffolds for bone regeneration.

Abstract Immunosuppressive tumor microenvironment is a crucial factor that impedes the success of tumor immunotherapy, and tumor-associated macrophages (TAMs) are essential for the formation of tumor immunosuppressive microenvironment. Hyaluronic acid (HA) is highly important brick for glioblastoma microenvironment, but whether it contributes to TAM polarization and glioblastoma immunosuppressive microenvironment is less well known. In our study, we observed that disrupting glioblastoma HA synthesis or blocking HA binding to its receptor CD44 on macrophages increased the proportion of M1 macrophages by upregulating SIRPα in macrophages, the underlying mechanism was elevated SIRPα enhanced STAT1 phosphorylation and suppressed STAT3 phosphorylation in macrophages. Subsequently, the induced macrophages could inhibit glioblastoma growth via a feedback effect. In addition, 4-methylumbelliferone (4MU), a cholecystitis drug, can disrupt the CD47/SIRPα axis by disturbing glioblastoma HA synthesis. Collectively, these findings indicated that HA plays a crucial role in macrophages polarization and CD47/SIRPα signaling between glioblastoma cells and macrophages, and suppressing the HA pathway may be a new immunotherapeutic approach for glioblastoma.

Summary: Diagnosis of primary brain tumors relies heavily on histopathology. Although various computational pathology methods have been developed for automated diagnosis of primary brain tumors, they usually require neuropathologists’ annotation of region of interests or selection of image patches on whole-slide images (WSI). We developed an end-to-end Vision Transformer (ViT) – based deep learning architecture for brain tumor WSI analysis, yielding a highly interpretable deep-learning model, ViT-WSI. Based on the principle of weakly supervised machine learning, ViT-WSI accomplishes the task of major primary brain tumor type and subtype classification. Using a systematic gradient-based attribution analysis procedure, ViT-WSI can discover diagnostic histopathological features for primary brain tumors. Furthermore, we demonstrated that ViT-WSI has high predictive power of inferring the status of three diagnostic glioma molecular markers, IDH1 mutation, p53 mutation, and MGMT methylation, directly from H&E-stained histopathological images, with patient level AUC scores of 0.960, 0.874, and 0.845, respectively.

Abstract With the sharp booming of online live streaming platforms, some anchors seek profits and accumulate popularity by mixing inappropriate content into live programs. After being blacklisted, these anchors even forged their identities to change the platform to continue live, causing great harm to the network environment. Therefore, we propose an anchor voiceprint recognition in live streaming via RawNet-SA and gated recurrent unit (GRU) for anchor identification of live platform. First, the speech of the anchor is extracted from the live streaming by using voice activation detection (VAD) and speech separation. Then, the feature sequence of anchor voiceprint is generated from the speech waveform with the self-attention network RawNet-SA. Finally, the feature sequence of anchor voiceprint is aggregated by GRU to transform into a deep voiceprint feature vector for anchor recognition. Experiments are conducted on the VoxCeleb, CN-Celeb, and MUSAN dataset, and the competitive results demonstrate that our method can effectively recognize the anchor voiceprint in video streaming.

This paper designs a fast image-based indoor localization method based on an anchor control network (FILNet) to improve localization accuracy and shorten the duration of feature matching. Particularly, two stages are developed for the proposed algorithm. The offline stage is to construct an anchor feature fingerprint database based on the concept of an anchor control network. This introduces detailed surveys to infer anchor features according to the information of control anchors using the visual–inertial odometry (VIO) based on Google ARcore. In addition, an affine invariance enhancement algorithm based on feature multi-angle screening and supplementation is developed to solve the image perspective transformation problem and complete the feature fingerprint database construction. In the online stage, a fast spatial indexing approach is adopted to improve the feature matching speed by searching for active anchors and matching only anchor features around the active anchors. Further, to improve the correct matching rate, a homography matrix filter model is used to verify the correctness of feature matching, and the correct matching points are selected. Extensive experiments in real-world scenarios are performed to evaluate the proposed FILNet. The experimental results show that in terms of affine invariance, compared with the initial local features, FILNet significantly improves the recall of feature matching from 26% to 57% when the angular deviation is less than 60 degrees. In the image feature matching stage, compared with the initial K-D tree algorithm, FILNet significantly improves the efficiency of feature matching, and the average time of the test image dataset is reduced from 30.3 ms to 12.7 ms. In terms of localization accuracy, compared with the benchmark method based on image localization, FILNet significantly improves the localization accuracy, and the percentage of images with a localization error of less than 0.1m increases from 31.61% to 55.89%.

In recent years, with the continuous release of HTTP adaptive streaming (HAS) video datasets and network trace datasets, the machine learning methods, such as deep learning and reinforcement learning, have been continuously applied to adaptive bit rate (ABR) algorithms, which obtain the optimal strategy of rate control through interactive learning, and achieve superior performance that surpasses the traditional heuristic methods.Based on the analysis of the research difficulties of ABR algorithms, the research advances of ABR algorithms based on reinforcement learning (including deep reinforcement learning) was investigated.Furthermore, several representative HAS video datasets and network trace datasets were summarized, the evaluation metrics of the performance were depicted.Finally, the existing problems and the future tendency of ABR research were discussed.

Abstract Face image captured via surveillance videos in an open environment is usually of low quality, which seriously affects the visual quality and recognition accuracy. Most image super‐resolution methods adopt paired high‐quality and its interpolated low‐resolution version to train the super‐resolution network. It is difficult to achieve contented visual quality and restoring discriminative features in real scenarios. A discriminative self‐attention cycle generative adversarial network is proposed for real‐world face image super‐resolution. Based on the cycle GAN framework, unpaired samples are adopted to train a degradation network and a reconstruction network simultaneously. A self‐attention mechanism is employed to capture the contextual information for details restoring. A Siamese face recognition network is introduced to provide a constraint on identify consistency. In addition, an asymmetric perceptual loss is introduced to handle the imbalance between the degradation model and the reconstruction model. Experimental results show that the observation model achieved more realistic low‐quality face images, and the super‐resolved face images have shown better subjective quality and higher face recognition performance.

COVID-19 is a critical public health threat, but molecular characterizations of patients’ immunity is still lacking. Here the authors collected blood from patients with various disease severity, and prefiltered to exclude selected comorbidity, to obtain genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles to report a trans-omics landscape.

The membranes of poly(l-lactide acid-p-dioxanone-glycolide) (PLPG) with stereocomplex poly(lactic acid) (sc-PLA) were prepared by the solution blending way. It was observed that sc-PLA significantly heightened the crystallizing behavior of PLLA segments of the PLPG matrix. The crystallizing behavior displayed that the temperature of crystallization shifted to a higher range than that of PLPG. Moreover, the half-time of crystallization sharply decreased in value as the sc-PLA content increased in value on account of the pre-eminent nucleation ability of sc-PLA. TGA results revealed the thermal stability of the samples with the increase of sc-PLA compared to PLPG. Meanwhile, enzymatic degradation results indicated that the mass loss rate of the membrane decreased with the introduction of sc-PLA, but the overall degradation ability was still greater than that of PLLA. In the meantime, the biological experiment indicated that the membrane possessed low cytotoxicity.

Abstract The tumor microenvironment plays an important role in tumor progression. Hyaluronic acid (HA), an important component of the extracellular matrix in the tumor microenvironment, abnormally accumulates in a variety of tumors. However, the role of abnormal HA accumulation in glioma remains unclear. The present study indicated that HA, hyaluronic acid synthase 3 (HAS3), and a receptor of HA named CD44 were expressed at high levels in human glioma tissues and negatively correlated with the prognosis of patients with glioma. Silencing HAS3 expression or blocking CD44 inhibited glioma cell proliferation in vitro and in vivo. The underlying mechanism was attributed to the inhibition of autophagy flux and maintaining glioma cell cycle arrest in G1 phase. More importantly, 4-methylumbelliferone (4-MU), a small competitive inhibitor of Uridine diphosphate (UDP) with the ability to penetrate the blood-brain barrier (BBB), also inhibited glioma cell proliferation in vitro and in vivo. Thus, approaches that interfere with HA metabolism by altering the expression of HAS3 and CD44 and the administration of 4-MU potentially represent effective strategies for glioma treatment.

Abstract Purpose Critically ill COVID-19 patients have significantly increased risk of death. Although several circulating biomarkers are thought to be related to COVID-19 severity, few studies have focused on the characteristics of critically ill patients with different outcomes. The objective of this study was to perform a longitudinal investigation of the potential mechanisms affecting the prognosis of critically ill COVID-19 patients. Methods In addition to clinical data, 113 whole blood samples and 85 serum samples were collected from 33 severe and critical COVID-19 patients without selected comorbidities. Multi-omics analysis was then performed using longitudinal samples. Results Obvious transcriptional transitions were more frequent in critical survivors than in critical non-survivors, indicating that phase transition may be related to survival. Based on analysis of differentially expressed genes during transition, the erythrocyte differentiation pathway was significantly enriched. Furthermore, clinical data indicated that red blood cell counts showed greater fluctuation in survivors than in non-survivors. Moreover, declining red blood cell counts and hemoglobin levels were validated as prognostic markers of poor outcome in an independent cohort of 114 critical COVID-19 patients. Protein–metabolite–lipid network analysis indicated that tryptophan metabolism and melatonin may contribute to molecular transitions in critical COVID-19 patients with different outcomes. Conclusions This study systematically and comprehensively depicted the longitudinal hallmarks of critical COVID-19 patients and indicated that multi-omics transition may impact the prognosis. Take home message Frequent transcriptional phase transitions may contribute to outcome in critically ill COVID-19 patients. Furthermore, fluctuation in red blood cell and hemoglobin levels may relate to poor prognosis. The biological function of melatonin was suppressed in COVID-19 non-survivors, which may provide a potential theoretical basis for clinical administration.

The extended state observer (ESO) has been widely used in the state and perturbation estimation of the electro-hydraulic servo system. It was found that there was a controlled quantity in the transfer function between the perturbation estimation value and the disturbance. This indicates that the traditional linear ESO’s estimation of the disturbance is affected by the change in the control input. To solve this problem, a new structure ESO for a hydraulic system (LHYESO) was designed by introducing the hydraulic system’s load pressure and system model. The corresponding frequency domain analysis results show that it eliminates the control input in the transfer function and reduces the dependence of the high-frequency domain range of the perturbation estimation on the significant observer gain. To improve the estimation speed, a finite-time convergent ESO for hydraulic systems (FTHYESO) was proposed based on the structure of LHYESO, and it was proved that the observation error converged to a sufficiently small value during a finite time. Moreover, a finite-time backstepping controller has been designed by using the Lyapunov method to guarantee the rapidity and precise response of the hydraulic servo system. Finally, the experiment results show the effectiveness of the proposed method.

Abstract Background Intercropping and close planting are important cultivation methods that increase soybean yield in agricultural production. However, plant shading is a major abiotic stress factor that influences soybean growth and development. Although shade affects leaf morphological parameters and decreases leaf photosynthesis capacity, information on the responses of soybean leaf photosynthesis to shading at proteomic level is still lacking. Results Compared with leaves under normal light (CK) treatment, leaves under shading treatment exhibited decreased palisade and spongy tissue thicknesses but significantly increased cell gap. Although shade increased the number of the chloroplast, the thickness of the grana lamella and the photosynthetic pigments per unit mass, but the size of the chloroplast and starch grains and the rate of net photosynthesis decreased compared with those of under CK treatment. A total of 248 differentially expressed proteins, among which 138 were upregulated, and 110 were downregulated, in soybean leaves under shading and CK treatments were detected via isobaric tags for relative and absolute quantification labeling in the three biological repeats. Differentially expressed proteins were classified into 3 large and 20 small groups. Most proteins involved in porphyrin and chlorophyll metabolism, photosynthesis-antenna proteins and carbon fixation in photosynthetic organisms were upregulated. By contrast, proteins involved in photosynthesis were downregulated. The gene family members corresponding to differentially expressed proteins, including protochlorophyllide reductase (Glyma06g247100), geranylgeranyl hydrogenase (Ggh), LHCB1 (Lhcb1) and ferredoxin (N/A) involved in the porphyrin and chlorophyll metabolism, photosynthesis-antenna proteins and photosynthesis pathway were verified with real-time qPCR. The results showed that the expression patterns of the genes were consistent with the expression patterns of the corresponding proteins. Conclusions This study combined the variation of the soybean leaf structure and differentially expressed proteins of soybean leaves under shading. These results demonstrated that shade condition increased the light capture efficiency of photosystem II (PSII) in soybean leaves but decreased the capacity from PSII transmitted to photosystem II (PSI). This maybe the major reason that the photosynthetic capacity was decreased in shading.

Increasing evidence indicates that pyroptosis, a new type of programmed cell death, may participate in random flap necrosis and play an important role. ROS-induced lysosome malfunction is an important inducement of pyroptosis. Transcription factor E3 (TFE3) exerts a decisive effect in oxidative metabolism and lysosomal homeostasis. We explored the effect of pyroptosis in random flap necrosis and discussed the effect of TFE3 in modulating pyroptosis. Histological analysis via hematoxylin-eosin staining, immunohistochemistry, general evaluation of flaps, evaluation of tissue edema, and laser Doppler blood flow were employed to determine the survival of the skin flaps. Western blotting, immunofluorescence, and enzyme-linked immunosorbent assays were used to calculate the expressions of pyroptosis, oxidative stress, lysosome function, and the AMPK-MCOLN1 signaling pathway. In cell experiments, HUVEC cells were utilized to ensure the relationship between TFE3, reactive oxygen species (ROS)-induced lysosome malfunction and cell pyroptosis. Our results indicate that pyroptosis exists in the random skin flap model and oxygen and glucose deprivation/reperfusion cell model. In addition, NLRP3-mediated pyroptosis leads to necrosis of the flaps. Moreover, we also found that ischemic flaps can augment the accumulation of ROS, thereby inducing lysosomal malfunction and finally initiating pyroptosis. Meanwhile, we observed that TFE3 levels are interrelated with ROS levels, and overexpression and low expression of TFE3 levels can, respectively, inhibit and promote ROS-induced lysosomal dysfunction and pyroptosis during in vivo and in vitro experiments. In conclusion, we found the activation of TFE3 in random flaps is partially regulated by the AMPK-MCOLN1 signal pathway. Taken together, TFE3 is a key regulator of ROS-induced pyroptosis in random skin flaps, and TFE3 may be a promising therapeutic target for improving random flap survival.

Random-pattern skin flap replantation is generally used in the reconstruction of surgical tissues and covering a series of skin flap defects. However, ischemia often occurs at the flap distal parts, which lead to flap necrosis. Previous studies have shown that andrographolide (Andro) protects against ischemic cardiovascular diseases, but little is known about the effect of Andro on flap viability. Thus, our study aimed to building a model of random-pattern skin flap to understand the mechanism of Andro-induced effects on flap survival. In this study, fifty-four mice were randomly categorized into the control, Andro group, and the Andro+3-methyladenine group. The skin flap samples were obtained on postoperative day 7. Subsequently, the tissue samples were underwent a series of evaluations such as changes in the appearance of flap tissue, the intensity of blood flow, and neovascularization density of skin flap. In our study, the results revealed that Andro enhanced the viability of random skin flaps by enhancing angiogenesis, inhibiting apoptosis, and reducing oxidative stress. Furthermore, our results have also demonstrated that the administration of Andro caused an elevation in the autophagy, and these remarkable impact of Andro were reversed by 3-methyladenine (3-MA), the most common autophagy inhibitor. Together, our data proves novel evidence that Andro is a potent modulator of autophagy capable of significantly increasing random-pattern skin flap survival.

Brasenia schreberi J. F. Gmel, a perennial floating-leaved macrophyte with high economic value as an aquatic vegetable, has been listed as first-class endangered species in China, mainly due to its habitat loss. Protected cultivation is a potential strategy to meet the demand of both plant conservation and vegetable market, whereas pre-experiments are still needed before series of parameters can be properly set for the large-scale growth of the plants indoor. Light quality is one of the major factors controlling the development of plants and consequently becomes an important factor when planting B. schreberi indoor. This experiment used three artificial light sources to investigate the response of B. schreberi seedlings to different light qualities, including the red-blue LED light (red: blue = 5:1, RB-LED), the white LED light (W-LED) and the white fluorescent (W-Fluo). Our results indicated that the responses of B. schreberi towards varied light qualities differed from those of most terrestrial plants. The total leaf number of the RB-LED treatment was the highest; the number of the submerged leaf and the rolled leaf of the RB-LED treatment was higher than that of the other two treatments, but the number of floating leaves was the lowest. Both the specific leaf weight and the pigment contents per unit leaf area were the lowest in the RB-LED treatment. Quantum yield of PSⅡ (ΦPSⅡ), electron transport rate (ETR) and photochemical quenching (qP) measured through light induction curves followed the sequence from high to low as W-Fluo > W-LED > RB-LED, whereas the trend of non-photochemical quenching (NPQ) reversed. The maximum potential ETR (Ps) and maximum ETR (ETRm) derived from ETR curves further verified the trends.

The current tsunami early warning systems always issue alarms once large undersea earthquakes are detected, inevitably resulting in false warnings since there are no deterministic scaling relations between earthquake size and tsunami potential. In this paper, we assess tsunami potential by analyzing co-seismic ionospheric disturbances (CIDs). We examined CIDs of three megathrusts (the 2014 Mw 8.2 Iquique, the 2015 Mw 8.3 Illapel, and the recent 2021 Mw 8.2 Alaska events) as detected by Global Navigation Satellite System (GNSS) observations. We found that CIDs near the epicenter generated by the 2021 Mw 8.2 Alaska event were significantly weaker than those of the two Chilean events, despite having similar earthquake magnitudes. The propagation direction of CIDs from the Mw 8.2 Alaska earthquake further revealed ruptures toward the deeper seismogenic zone, implying less seafloor uplift and hazardous flooding. Our work sheds light on incorporating GNSS-based CIDs for more trustworthy tsunami warning systems.

The integration of variable stiffness materials and structures into soft robots is a popular trend, allowing soft robots to switch between soft and rigid states in different situations. This concept combines the advantages of rigid mechanisms and soft robots, resulting in not only excellent flexibility but also tunable stiffness for high load capacity and fast and precise operation. Here, a stiffness-tunable soft actuator based on wire/fiber jamming structure is proposed, where the fiber-reinforced soft actuator is responsible for the bending motion, and the jamming structure acts as a stiffness-tunable layer controlled by vacuum pressure. The primary design objective of this study is to fabricate a jamming structure with wide-range stiffness, universal adaptability and high dexterity. Thus, the behaviors of wire/fiber jamming structures with different layouts, materials and wire arrangements are analyzed, and a theoretical model is developed to predict the effect of geometric parameters. Experimental characterizations show that the stiffness can be significantly enhanced in the bending direction, while the stiffness is smaller in the torsion direction. Additionally, by integrating Velcro strips into the design, a quick and detachable scheme for the stiffness-tunable soft actuator is achieved. Application examples exhibit high load capacity and good shape adaptability.

BackgroundSpinal cord ischemia-reperfusion injury (SCIRI) is the main complication after the repair of a complex thoracoabdominal aortic aneurysm. Many clinical treatments are not ideal due to the complex pathophysiological process of this injury. Baicalein (BA), a component derived from the roots of the herb Scutellaria baicalensis, may contribute to the successful treatment of ischemia/reperfusion injury.PurposeIn the present study, the effects of BA on spinal cord ischemia-reperfusion injury and the underlying mechanisms were assessed.Materials and MethodsSpinal cord ischemia was induced in C57BL/6 mice by blocking the aortic arch. Fifty-five mice were then randomly divided into four groups: Sham, SCIR+Vehicle, SCIR+BA, and SCIR+BA +3MA groups. At 0 and 24 h pre-SCIRI and at 24 h and 7 days post-SCIRI, evaluations with the Basso mouse scale (BMS) were performed. On postoperative 24 h, the spinal cord was harvested to assess pyroptosis, endoplasmic reticulum stress mediated apoptosis and autophagy.ResultsBA enhanced the functional recovery of spinal cord ischemia-reperfusion injury. In addition, BA attenuated pyroptosis, alleviated endoplasmic reticulum stress-mediated apoptosis, and activated autophagy. However, the effects of BA on the functional recovery of SCIRI, pyroptosis and endoplasmic reticulum stress-mediated apoptosis were reversed by the inhibition of autophagy.ConclusionsIn general, our findings revealed that BA enhances the functional recovery of spinal cord ischemia-reperfusion injury by dampening pyroptosis and alleviating endoplasmic reticulum stress-mediated apoptosis, which are mediated by the activation of autophagy.

The doped semiconductor nanocrystal with free holes in valence band exhibits strong near-infrared (NIR) local surface plasmon resonance effects, which is essential for photothermal agents. Herein, the hydrophilic Sb doped SnO2 nanocrystals were successfully prepared by a simple hydrothermal synthesis method. The doping makes the Sb doped SnO2 nanocrystals possessing defect structures. Compared with the un-doped SnO2 nanocrystals, Sb doped SnO2 nanocrystals exhibit stronger absorption in the NIR region from 500 to 1,100 nm and higher photothermal conversion efficiency (up to 73.6%) which makes the synthesized Sb doped SnO2 nanocrystals be used as excellent photothermal agents. Importantly, Sb doped SnO2 nanocrystals can efficiently kill cancer cells both in vitro and in vivo under the irradiation of a 980 nm laser with a power density of 0.6 W cm–2. In addition, Sb doped SnO2 nanocrystals can also be served as efficient CT imaging agents owing to the large X-ray attenuation coefficient of tin.

Multiterritory perforator flap survival is commonly applied in surgical tissue reconstructions and covering of large skin defects. However, multiple risk factors such as ischemia, reperfusion injury, and apoptosis after reconstructive surgeries cause necrosis in distal parts with outcomes ranging from poor aesthetic appearance to reconstructive failure. A few studies have reported that sitagliptin (Sit) promotes angiogenesis and inhibits apoptosis. However, little is known about Sit-induced autophagy especially on the flap model. Therefore, our study investigated the effect of Sit and its induced autophagy on the perforator flap survival. Ninety male Sprague-Dawley rats were randomly separated into control, Sit, and Sit+3-methyladenine group. Results revealed that Sit significantly promoted flap survival by enhancing angiogenesis, reducing oxidative stress, and attenuating apoptosis. In addition, flap survival was further improved after co-administration with 3-methyladenine to inhibit autophagy. Overall, our results established that Sit has positive effects in promoting survival of multiterritory perforator flap. Sit-induced autophagy was detrimental for flap survival and its inhibition may further improve flap survival.

Target tracking in low-altitude Unmanned Aerial Vehicle (UAV) videos faces many technical challenges due to the relatively small sizes, various orientation changes of the objects and diverse scenes. As a result, the tracking performance is still not satisfactory. In this paper, we propose a real-time single-target tracking method with multiple Region Proposal Networks (RPNs) and Distance-Intersection-over-Union (Distance-IoU) Discriminative Network (DIDNet), namely MultiRPN-DIDNet, in which ResNet50 is used as the backbone network for feature extraction. Firstly, an instance-based RPN suitable for the target tracking task is constructed under the framework of Simases Neural Network. RPN is to perform bounding box regression and classification, in which channel attention mechanism is integrated to improve the representative capability of the deep features. The RPNs built on the Block 2, Block 3 and Block 4 of ResNet50 output their own Regression (Reg) coefficients and Classification scores (Cls) respectively, which are weighted and then fused to determine the high-quality region proposals. Secondly, a DIDNet is designed to correct the candidate target’s bounding box finely through the fusion of multi-layer features, which is trained with the Distance-IoU loss. Experimental results on the public datasets of UAV20L and DTB70 show that, compared with the state-of-the-art UAV trackers, the proposed MultiRPN-DIDNet can obtain better tracking performance with fewer region proposals and correction iterations. As a result, the tracking speed has reached 33.9 frames per second (FPS), which can meet the requirements of real-time tracking tasks.

In this study, a novel disturbance observer-based (DOB) [inline-formula] robust anti-disturbance tracking control problem is discussed for a kind of single-link flexible-joint manipulator with separate types of disturbances. On the one hand, a disturbance observer is imported to estimate the modelable disturbances. On the other hand, the introduction of [inline-formula] performance index optimises the impact of unmodelled disturbances on the system. A DOB proportional-integral control input is proposed such that the stability of single-link flexible-joint manipulator can be ensured. Furthermore, the satisfactory disturbance rejection and attenuation performance with [inline-formula] index can be obtained simultaneously. Finally, the simulation results verify this feasibility and effectiveness of the proposed control method.

Random-pattern skin flap replantation is commonly used to repair skin defects during plastic and reconstructive surgery. However, flap necrosis due to ischemia and ischemia–reperfusion injury limits clinical applications. Betulinic acid, a plant-derived pentacyclic triterpene, may facilitate flap survival. In the present study, the effects of betulinic acid on flap survival and the underlying mechanisms were assessed. Fifty-four mice with a dorsal random flap model were randomly divided into the control, betulinic acid group, and the betulinic acid + 3-methyladenine group. These groups were treated with dimethyl sulfoxide, betulinic acid, and betulinic acid plus 3-methyladenine, respectively. Flap tissues were acquired on postoperative day 7 to assess angiogenesis, apoptosis, oxidative stress, and autophagy. Betulinic acid promoted survival of the skin flap area, reduced tissue edema, and enhanced the number of microvessels. It also enhanced angiogenesis, attenuated apoptosis, alleviated oxidative stress, and activated autophagy. However, its effects on flap viability and angiogenesis, apoptosis, and oxidative stress were reversed by the autophagy inhibitor 3-methyladenine. Our findings reveal that betulinic acid improves survival of random-pattern skin flaps by promoting angiogenesis, dampening apoptosis, and alleviating oxidative stress, which mediates activation of autophagy.

Visual object tracking in unmanned aerial vehicle (UAV) videos plays an important role in a variety of fields, such as traffic data collection, traffic monitoring, as well as film and television shooting. However, it is still challenging to track the target robustly in UAV vision task due to several factors such as appearance variation, background clutter, and severe occlusion. In this paper, we propose a novel two-stage UAV tracking framework, which includes a target detection stage based on multifeature discrimination and a bounding-box estimation stage based on the instance-aware attention network. In the target detection stage, we explore a feature representation scheme for a small target that integrates handcrafted features, low-level deep features, and high-level deep features. Then, the correlation filter is used to roughly predict target location. In the bounding-box estimation stage, an instance-aware intersection over union (IoU)-Net is integrated together with an instance-aware attention network to estimate the target size based on the bounding-box proposals generated in the target detection stage. Extensive experimental results on the UAV123 and UAVDT datasets show that our tracker, running at over 25 frames per second (FPS), has superior performance as compared with state-of-the-art UAV visual tracking approaches.

DASH (Dynamic Adaptive Streaming over HTTP (HyperText Transfer Protocol)) as a universal unified multimedia streaming standard selects the appropriate video bitrate to improve the user’s Quality of Experience (QoE) according to network conditions, client status, etc. Considering that the quantitative expression of the user’s QoE is also a difficult point in itself, this paper researched the distortion caused due to video compression, network transmission and other aspects, and then proposes a video QoE metric for dynamic adaptive streaming services. Three-Dimensional Convolutional Neural Networks (3D CNN) and Long Short-Term Memory (LSTM) are used together to extract the deep spatial-temporal features to represent the content characteristics of the video. While accounting for the fluctuation in the quality of a video caused by bitrate switching on the QoE, other factors such as video content characteristics, video quality and video fluency, are combined to form the input feature vector. The ridge regression method is adopted to establish a QoE metric that enables to dynamically describe the relationship between the input feature vector and the value of the Mean Opinion Score (MOS). The experimental results on different datasets demonstrate that the prediction accuracy of the proposed method can achieve superior performance over the state-of-the-art methods, which proves the proposed QoE model can effectively guide the client’s bitrate selection in dynamic adaptive streaming media services.

Pedestrian attributes (such as gender, age, hairstyle, and clothing) can effectively represent the appearance of pedestrians. These are high-level semantic features that are robust to illumination, deformation, etc. Therefore, they can be widely used in person re-identification, video structuring analysis and other applications. In this paper, a pedestrian attributes recognition method for surveillance scenarios using a multi-task lightweight convolutional neural network is proposed. Firstly, the labels of the attributes for each pedestrian image are integrated into a label vector. Then, a multi-task lightweight Convolutional Neural Network (CNN) is designed, which consists of five convolutional layers, three pooling layers and two fully connected layers to extract the deep features of pedestrian images. Considering that the data distribution of the datasets is unbalanced, the loss function is improved based on the sigmoid cross-entropy, and the scale factor is added to balance the amount of various attributes data. Through training the network, the mapping relationship model between the deep features of pedestrian images and the integration label vector of their attributes is established, which can be used to predict each attribute of the pedestrian. The experiments were conducted on two public pedestrian attributes datasets in surveillance scenarios, namely PETA and RAP. The results show that, compared with the state-of-the-art pedestrian attributes recognition methods, the proposed method can achieve a superior accuracy by 91.88% on PETA and 87.44% on RAP respectively.

With the explosive growth of mobile videos, helping users quickly and effectively find mobile videos of interest and further provide personalized recommendation services are the developing trends of mobile video applications. Mobile videos are characterized by their wide variety, single content, and short duration, and thus traditional personalized video recommendation methods cannot produce effective recommendation performance. Therefore, a personalized mobile video recommendation method is proposed based on user preference modeling by deep features and social tags. The main contribution of our work is three-fold: (1) deep features of mobile videos are extracted by an improved exponential linear units-3D convolutional neural network (ELU-3DCNN) for representing video content; (2) user preference is modeled by combining user preference for deep features with user preference for social tags that are respectively modeled by maximum likelihood estimation and exponential moving average method; (3) a personalized mobile video recommendation system based on user preference modeling is built after detecting key frames with a differential evolution optimization algorithm. Experiments on YouTube-8M dataset have shown that our method outperforms state-of-the-art methods in terms of both precision and recall of personalized mobile video recommendation.