Search

Chlorogenic acid (CGA) has strong antioxidant properties. In order to improve the low maturation rate and poor vitrification freezing effect of sheep oocytes caused by oxidative stress. In this study, oocytes from 200 2-3-year-old Kazakh sheep were collected, and different concentrations of CGA were added to the maturation medium and vitrification freezing solution to study the effects of CGA on the maturation rate, cleavage rate, blastocyst rate, reactive oxygen species (ROS) and glutathione (GSH) levels, mitochondrial membrane potential, and the expression levels of oxidation and apoptosis-related genes in sheep oocytes. The results showed that adding 40 μmol/L CGA to the oocyte in vitro maturation solution significantly increased the maturation rate of oocytes, adding 50 μmol/L CGA to the vitrification cryopreservative solution significantly increased the cleavage and blastocyst rates of mature oocytes activated by parthenogenetic activation after freezing. During in vitro maturation and vitrification freezing in sheep oocytes, CGA significantly reduced the level of ROS and the expression of apoptosis-related genes (Caspase-3 and Bax/Bcl-2), and significantly increased the level of glutathione (GSH), mitochondrial membrane potential, and the expression of antioxidant and anti-apoptosis-related genes (SOD-2 and GPX-3). In addition, CGA significantly increased the expression of the anti-apoptotic gene (AKT) and anti-stress gene (FOXO) during vitrification freezing of sheep oocytes. In conclusion, 40 μmol/L CGA improves the maturation rate of sheep oocytes, and 50 μmol/L CGA improves the quality of parthenogenetic activation embryos after vitrification freezing of mature oocytes in sheep. These results provide a basis for the production of sheep in vitro embryos and the establishment of a germplasm resource bank.

In the complex environment of fully mechanized mining faces, the current object detection algorithms face significant challenges in achieving optimal accuracy and real-time detection of mine personnel and safety helmets. This difficulty arises from factors such as uneven lighting conditions and equipment obstructions, which often lead to missed detections. Consequently, these limitations pose a considerable challenge to effective mine safety management. This article presents an enhanced algorithm based on YOLOv11n, referred to as GCB-YOLOv11. The proposed improvements are realized through three key aspects: Firstly, the traditional convolution is replaced with GSConv, which significantly enhances feature extraction capabilities while simultaneously reducing computational costs. Secondly, a novel C3K2_FE module was designed that integrates Faster_block and ECA attention mechanisms. This design aims to improve detection accuracy while also accelerating detection speed. Finally, the introduction of the Bi FPN mechanism in the Neck section optimizes the efficiency of multi-scale feature fusion and addresses issues related to feature loss and redundancy. The experimental results demonstrate that GCB-YOLOv11 exhibits strong performance on the dataset concerning mine personnel and safety helmets, achieving a mean average precision of 93.6%. Additionally, the frames per second reached 90.3 f·s -1 , representing increases of 3.3% and 9.4%, respectively, compared to the baseline model. In addition, when compared to models such as YOLOv5s, YOLOv8s, YOLOv3 Tiny, Fast R-CNN, and RT-DETR, GCB-YOLOv11 demonstrates superior performance in both detection accuracy and model complexity. This highlights its advantages in mining environments and offers a viable technical solution for enhancing the safety of mine personnel.

Zearalenone (ZEN) has been detected in both pet food ingredients and final products, causing acute toxicity and chronic health problems in pets. Therefore, the early detection of mycotoxin contamination in pet food is crucial for ensuring the safety and well-being of animals. This study aims to develop a rapid and cost-effective method using an electronic nose (E-nose) and machine learning algorithms to predict whether ZEN levels in pet food exceed the regulatory limits (250 µg/kg), as set by Chinese pet food legislation. A total of 142 pet food samples from various brands, collected between 2021 and 2023, were analyzed for ZEN contamination via liquid chromatography-tandem mass spectrometry. Additionally, the "AIR PEN 3" E-nose, equipped with 10 metal oxide sensors, was employed to identify volatile compounds in the pet food samples, categorized into 10 different groups. Machine learning algorithms, including liner regression, k-nearest neighbors, support vector machines, random forests, XGBoost, and multi-layer perceptron (MLP), were used to classify the samples based on their volatile profiles. The MLP algorithm showed the highest discrimination accuracy at 86.6% in differentiating between pet food samples above and below the ZEN threshold. Other algorithms showed moderate accuracy, ranging from 77.1% to 84.8%. The ensemble model, which combined the predictions from all classifiers, further improved the classification performance, achieving the highest accuracy at 90.1%. These results suggest that the combination of E-nose technology and machine learning provides a rapid, cost-effective approach for screening ZEN contamination in pet food at the market entry stage.

α-Arbutin is the fourth generation whitening factor in the field of cosmetics, which can block the synthesis of melanin in epidermal cells and has the advantages of good stability and less toxic side effects. Moreover, α-arbutin has potential application value in food, medicine, and other fields. However, the extraction yield from plant tissues is relatively low, which restricts its application value. Currently, enzymatic catalysis is universally deemed the safest and most efficient method for α-arbutin synthesis. Amylosucrase (ASase), one of the most frequently employed glycosyltransferases, has been extensively reported for α-arbutin synthesis. To discover new resources of amylosucrase (ASase), this study synthesized α-arbutin using low-cost sucrose as a glycosyl donor. Probe sequences were used to identify homologous sequences from different microbial strains in protein databases as candidate ASases. Recombinant plasmids were constructed, and the enzymes were successfully expressed in Escherichia coli , followed by the enzymatic synthesis of α-arbutin. One ASase from Calidithermus terrae , named CtAs, was selected for its effective α-arbutin synthesis. The expression conditions for CtAs were optimized, its enzymatic properties were analyzed, and the conditions for the enzymatic synthesis of α-arbutin were further refined to improve its molar yield. The optimal induction conditions for CtA expression were achieved by adding IPTG at a final concentration of 0.5 mmol/L to LB medium when OD 600 reached 1.0, followed by an incubation at 20 °C and 200 r/min for 18 h. The optimal temperature and pH for CtAs were found to be 42 °C and 9.5, respectively, with good stability across the pH range of 5.0-12.0. CtAs was activated by Na + , K + , Mg 2+ , EDTA, methanol, and ethanol, but inhibited by Ca 2+ , Zn 2+ , Ba 2+ , and Ni 2+ . The kinetic parameters were V max = 6.94 μmol/min/mL, K m = 89.39 mmol/L, K cat = 5183.97 min -1 , and K cat / K m = 57.99 L/(mmol·min). At 42 °C and pH 9.5, the hydrolysis/polymerization/isomerization reaction ratios were 23.27:32.96:43.77 with low sucrose concentrations and 38.50:37.12:24.38 with high sucrose concentrations. The optimal conditions for the enzymatic synthesis were determined to be at 25 °C and pH 5.0 using sucrose at a final concentration of 42 mmol/L and hydroquinone at 6 mmol/L (donor-to-acceptor ratio of 7:1), with the addition of 200 μL (0.2 mg/mL) of purified enzyme and 0.10 mmol/L ascorbic acid, under dark conditions for 6 h. The final molar yield of α-arbutin was 62.78%, with a molar conversion rate of hydroquinone of 74.60%, nearly doubling the yield compared to pre-optimization.

Activins and inhibins, members of the transforming growth factor β (TGFβ) superfamily, were initially recognized for their opposing effects on the secretion of follicle-stimulating hormone. Subsequent research has demonstrated their broader biological roles across various tissue types. Primarily, activins and inhibins function through the classical TGFβ SMAD signaling pathway, but studies suggest that they also act through other pathways, with their specific signaling being complex and context-dependent. Recent research has identified significant roles for activins and inhibins in the cardiovascular system. Their actions in other systems and their signaling pathways show strong correlations with the development and progression of cardiovascular diseases, indicating potential broader roles in the cardiovascular system. This review summarizes the progress in research on the biological functions and mechanisms of activins and inhibins and their signaling pathways in cardiovascular diseases, offering new insights for the prevention and treatment of cardiovascular diseases.

The global prevalence of aflatoxin B1 (AFB1) and zearalenone (ZEN) contamination in food and feed poses a serious health risk to humans and animals. Recently, enzymatic detoxification has received increasing attention, yet most enzymes are limited to degrading only one type of mycotoxin, and free enzymes often exhibit reduced stability and activity, limiting their practicality in real-world applications. In this study, the laccase CotA gene from ZEN/AFB1-degrading Bacillus subtilis ZJ-2019-1 was cloned and successfully expressed in Escherichia coli BL21, achieving a protein yield of 7.0 mg/g. The recombinant CotA (rCotA) completely degraded AFB1 and ZEN, with optimal activity at 70 °C and pH 7.0. After rCotA treatment, neither AFB1 nor ZEN showed significantly cytotoxicity to mouse macrophage cell lines. Additionally, the AFB1/ZEN degradation efficiency of rCotA was significantly enhanced by five natural redox mediators: acetosyringone, syringaldehyde, vanillin, matrine, and sophoridin. Among them, the acetosyringone -rCotA was the most effective mediator system, which could completely degrade 10 μg of AFB1 and ZEN within 1 h. Furthermore, the chitosan-immobilized rCotA system exhibited higher degradation activity than free rCotA. The immobilized rCotA degraded 27.95% of ZEN and 41.37% of AFB1 in contaminated maize meal within 12 h, and it still maintained more than 40% activity after 12 reuse cycles. These results suggest that media-assisted or immobilized enzyme systems not only boost degradation efficiency but also demonstrate remarkable reusability, offering promising strategies to enhance the degradation efficiency of rCotA for mycotoxin detoxification.

Two new C 23 -steroids derivatives, cyclocitrinoic acid A ( 1 ) and cyclocitrinoic acid B ( 2 ), and a new isocoumarin metabolite, (3 R ,4 S )-6,8-dihydroxy-3,4,5-trimethyl-7-carboxamidelisocoumarin ( 10 ), together with 12 known compounds ( 3 - 9 , 11 - 15 ) were isolated from the mangrove-sediment fungus Penicillium sp. SCSIO 41429. The structures of the new compounds were comprehensively characterized by 1D and 2D NMR, HRESIMS and ECD calculation. All isolates were evaluated for pancreatic lipase (PL) inhibitory and antioxidant activities. The biological evaluation results revealed that compounds 2 , 14 and 15 displayed weak or moderate inhibition against PL, with IC 50 values of 32.77, 5.15 and 2.42 µM, respectively. In addition, compounds 7 , 12 and 13 showed radical scavenging activities against DPPH, with IC 50 values of 64.70, 48.13, and 75.54 µM, respectively. In addition, molecular docking results indicated that these compounds had potential for PL inhibitory and antioxidant activities, which provided screening candidates for antioxidants and a reduction in obesity.

Severe fever with thrombocytopenia syndrome virus (SFTSV), also known as the Dabie Banda virus, is an emerging tick-borne Bunyavirus that causes severe fever with thrombocytopenia syndrome (SFTS). Currently, symptomatic treatment and antiviral therapy with ribavirin and favipiravir are used in clinical management. However, their therapeutical efficacy is hardly satisfactory in patients with high viral load. In this study, we explored the antiviral effects of selective estrogen receptor modulators (SERMs) on SFTSV infection and the antiviral mechanisms of a representative SERM, bazedoxifene acetate (BZA). Our data show that SERMs potently inhibited SFTSV-induced cytopathic effect (CPE), the proliferation of infectious viral particles, and viral RNA replication and that BZA effectively protected mice from lethal viral challenge. The mode of action analysis reveals that BZA exerts antiviral effects during the post-entry stage of SFTSV infection. The transcriptome analysis reveals that GRASLND and CYP1A1 were upregulated, while TMEM45B and TXNIP were downregulated. Our findings suggest that SERMs have the potential to be used in the treatment of SFTSV infection.

Given the friction and drag reduction effects observed in various biological hexagonal structures in nature, a new design was implemented on the rubber surface of the stator of a submersible screw pump. This design featured a multilayer concentric hexagonal groove structure. Furthermore, a composite multilayer hexagonal structure integrating grooves and pits was also developed and applied. This study investigated the influence of groove layer number, groove depth, pit depth, and multilayer hexagonal groove texture arrangement on the rubber surface flow characteristics. Additionally, the pressure field state, the degree of influence on the oil film-bearing capacity, and the biomimetic and hydrodynamic lubrication theories were tested using the finite element analysis method. Tribological experiments were conducted on nanosecond laser-processed rubber textures under simulated liquid lubrication conditions, reflecting actual shale oil well experiments. These experiments aimed to investigate the influence of multilayer hexagonal shape parameters on the tribological characteristics of the stator-rotor friction pair of a submersible screw pump. The results indicated that with a constant overall size, a multilayer hexagonal structure with ~0.1 mm groove depth enhanced the oil film-bearing capacity, providing significant friction and drag reduction. For composite textures, a deeper pit depth within the study area enhanced the oil film-bearing capacity. Furthermore, a gradient arrangement of groove textures featuring wider outer grooves and shallower depth exhibited superior performance in terms of bearing capacity.

Similar to convolutional neural networks for image processing, existing analysis methods for 3D point clouds often require the designation of a local neighborhood to describe the local features of the point cloud. This local neighborhood is typically manually specified, which makes it impossible for the network to dynamically adjust the receptive field's range. If the range is too large, it tends to overlook local details, and if it is too small, it cannot establish global dependencies. To address this issue, we introduce in this paper a new concept: receptive field space (RFS). With a minor computational cost, we extract features from multiple consecutive receptive field ranges to form this new receptive field space. On this basis, we further propose a receptive field space attention mechanism, enabling the network to adaptively select the most effective receptive field range from RFS, thus equipping the network with the ability to adjust granularity adaptively. Our approach achieved state-of-the-art performance in both point cloud classification, with an overall accuracy (OA) of 94.2%, and part segmentation, achieving an mIoU of 86.0%, demonstrating the effectiveness of our method.

Four glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have been used in children and adolescents with obesity or overweight. This network meta-analysis was conducted to compare the efficacy and safety of these regimens. Embase, PubMed, and Scopus were searched on March 2023 and updated in June 2024 for eligible randomized controlled trials (RCTs). The primary efficacy outcomes were mean difference in actual body weight, BMI (body mass index), BMI z score, and waist circumference. Safety outcomes included nausea, vomiting, diarrhea, abdominal pain, injection-site reaction, and hypoglycemia. Eleven RCTs with 953 participants were eligible. Semaglutide exhibited greater effects in reducing weight, BMI, and BMI z score versus the placebo. Semaglutide was associated with greater weight loss and BMI z score reduction in comparison with exenatide, liraglutide, and dulaglutide. Semaglutide also significantly decreased BMI than exenatide. None of the four GLP-1 RAs were associated with higher risks of diarrhea, headache, and abdominal pain versus the placebo. Liraglutide was more likely to cause nausea, vomiting, hypoglycemia, and injection-site reactions than the placebo. Liraglutide also had higher odds of causing injection-site reactions than other GLP-1 RAs. Semaglutide appeared to be the most effective and safe option among four GLP-1 RAs in children and adolescents with obesity or overweight.

Ionic electroactive polymer (iEAP) actuators are recognized as exceptional candidates for artificial muscle development, with significant potential applications in bionic robotics, space exploration, and biomedical fields. Here, we developed a new iEAP actuator utilizing high-purity single-walled carbon nanotubes (SWCNTs)-reinforced poly(3, 4-ethylenedioxythiophene)/poly(4-styrenesulfonate) (PEDOT: PSS, PP) hybrid electrodes and a Nafion/EMIBF 4 ion-exchange membrane via a straightforward and efficient spray printing technique. The SWCNT/PP actuator exhibits significantly enhanced electric conductivity (262.9 S/cm) and specific capacitance (22.5 mF/cm 2 ), benefitting from the synergistic effect between SWCNTs and PP. These improvements far surpass those observed in activated carbon aerogel bucky-gel-electrode-based actuators. Furthermore, we evaluated the electroactive behaviors of the SWCNT/PP actuator under alternating square-wave voltages (1-3 V) and frequencies (0.01-100 Hz). The results reveal a substantial bending displacement of 6.44 mm and a high bending strain of 0.61% (at 3 V, 0.1 Hz), along with a long operating stability of up to 10,000 cycles (at 2 V, 1 Hz). This study introduces a straightforward and efficient spray printing technique for the successful preparation of iEAP actuators with superior electrochemical and electromechanical properties as intended, which hold promise as artificial muscles in the field of bionic robotics.

This paper designed and developed an online digital imaging excitation sensor for wind power gearbox wear condition monitoring based on an adaptive deep learning method. A digital imaging excitation sensing image information collection architecture for magnetic particles in lubricating oil was established to characterize the wear condition of mechanical equipment, achieving the real-time online collection of wear particles in lubricating oil. On this basis, a mechanical equipment wear condition diagnosis method based on online wear particle images is proposed, obtaining data from an engineering test platform based on a wind power gearbox. Firstly, a foreground segmentation preprocessing method based on the U-Net network can effectively eliminate the interference of bubbles and dark fields in online wear particle images, providing high-quality segmentation results for subsequent image processing, A total of 1960 wear particle images were collected in the experiment, the average intersection union ratio of the validation set is 0.9299, and the accuracy of the validation set is 0.9799. Secondly, based on the foreground segmentation preprocessing of wear particle images, by using the watered algorithm to obtain the number of particles in each size segment, we obtained the number of magnetic particle grades in three different ranges: 4-38 µm, 39-70 µm, and >70 µm. Thirdly, we proposed a method named multidimensional transformer (MTF) network. Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) are used to obtain the error, and the maintenance strategy is formulated according to the predicted trend. The experimental results show that the predictive performance of our proposed model is better than that of LSTM and TCN. Finally, the online real-time monitoring system triggered three alarms, and at the same time, our offline sampling data analysis was conducted, the accuracy of online real-time monitoring alarms was verified, and the gearbox of the wind turbine was shut down for maintenance and repair.

Two new sesquiterpenoid derivatives, elgonenes M ( 1 ) and N ( 2 ), and a new shikimic acid metabolite, methyl 5- O -acetyl-5- epi -shikimate ( 3 ), were isolated from the mangrove sediment-derived fungus Roussoella sp. SCSIO 41427 together with fourteen known compounds ( 4 - 17 ). The planar structures were elucidated through nuclear magnetic resonance (NMR) and mass spectroscopic (MS) analyses. The relative configurations of 1 - 3 were ascertained by NOESY experiments, while their absolute configurations were determined by electronic circular dichroism (ECD) calculation. Elgonene M ( 1 ) exhibited inhibition of interleukin-1β (IL-1β) mRNA, a pro-inflammatory cytokine, at a concentration of 5 μM, with an inhibitory ratio of 31.14%. On the other hand, elgonene N ( 2 ) demonstrated inhibition at a concentration of 20 μM, with inhibitory ratios of 27.57%.

The Zika virus (ZIKV) is a mosquito-borne virus that already poses a danger to worldwide human health. Patients infected with ZIKV generally have mild symptoms like a low-grade fever and joint pain. However, severe symptoms can also occur, such as Guillain-Barré syndrome, neuropathy, and myelitis. Pregnant women infected with ZIKV may also cause microcephaly in newborns. To date, we still lack conventional antiviral drugs to treat ZIKV infections. Marine natural products have novel structures and diverse biological activities. They have been discovered to have antibacterial, antiviral, anticancer, and other therapeutic effects. Therefore, marine products are important resources for compounds for innovative medicines. In this study, we identified a marine natural product, harzianopyridone (HAR), that could inhibit ZIKV replication with EC 50 values from 0.46 to 2.63 µM while not showing obvious cytotoxicity in multiple cellular models (CC 50 > 45 µM). Further, it also reduced the expression of viral proteins and protected cells from viral infection. More importantly, we found that HAR directly bound to the ZIKV RNA-dependent RNA polymerase (RdRp) and suppressed its polymerase activity. Collectively, our findings provide HAR as an option for the development of anti-ZIKV drugs.

This paper proposed a real-time fault diagnostic method for hydraulic systems using data collected from multiple sensors. The method is based on a proposed multi-sensor convolutional neural network (MS-CNN) that incorporates feature extraction, sensor selection, and fault diagnosis into an end-to-end model. Both the sensor selection process and fault diagnosis process are based on abstract fault-related features learned by a CNN deep learning model. Therefore, compared with the traditional sensor-and-feature selection method, the proposed MS-CNN can find the sensor channels containing higher-level fault-related features, which provides two advantages for diagnosis. First, the sensor selection can reduce the redundant information and improve the diagnostic performance of the model. Secondly, the reduced number of sensors simplifies the model, reducing communication burden and computational complexity. These two advantages make the MS-CNN suitable for real-time hydraulic system fault diagnosis, in which the multi-sensor feature extraction and the computation speed are both significant. The proposed MS-CNN approach is evaluated experimentally on an electric-hydraulic subsea control system test rig and an open-source dataset. The proposed method shows obvious superiority in terms of both diagnosis accuracy and computational speed when compared with traditional CNN models and other state-of-the-art multi-sensor diagnostic methods.

Fumonisins (FBs), particularly fumonisin B1 (FB1) and fumonisin B2 (FB2) produced mainly by Fusarium verticillioide and Fusarium proliferatum , are common contaminants in animal feed and pose a serious threat to both animal and human health. The use of microbial enzymes to efficiently and specifically convert fumonisins into non-toxic or low-toxic metabolites has emerged as the most promising approach. However, most of the available enzymes have only been evaluated in vitro and lack systematic evaluation in vivo. In this study, the detoxification efficacy of two carboxylesterases, FumD (FUM zyme ® ) and FumDSB, was evaluated comparatively in piglets. The results show that feeding piglets 4.4 mg/kg FBs-contaminated diets for 32 days did not significantly affect the average daily gain, organ indices, and immunoglobulins of the piglets. However, a significant reduction (21.2%) in anti-inflammatory cytokine interleukin-4 was observed in the FBs group, and supplementation with FUM zyme ® and FumDSB significantly increased interleukin-4 by 62.1% and 28.0%, respectively. In addition, FBs-contaminated diets resulted in a 3-fold increase in the serum sphinganine/sphingosine (Sa/So) ratio, which is a specific biomarker that has been used to accurately reflect fumonisin levels. The serum Sa/So ratio was significantly reduced by 48.8% after the addition of FUM zyme ® , and was insignificantly reduced by 8.2% in the FumDSB group. These results suggested that FUM zyme was more effective than FumDSB in mitigating FBs toxicity in piglets by down-regulating the Sa/So ratio.

The 7075 aluminum alloy deep hole pipe finds extensive applications in the aerospace industry due to its remarkable attributes, such as high strength, exceptional wear resistance, and favorable mechanical properties. However, traditional boring processes for 7075 aluminum alloy deep hole pipes tend to generate elevated cutting forces, potentially leading to deformation issues in these deep holes. In response to these challenges, this study introduces a novel approach involving the use of a two-dimensional ultrasonic elliptical vibration tool. This tool features a single excitation asymmetric structure and aims to enhance the deep hole machining process in 7075 aluminum alloy. The research methodology involved several key steps. First, theoretical analysis and simulation were performed to study the motion trajectory of the cutting edge of the tool. Second, practical experiments were conducted comparing two-dimensional ultrasonic elliptical vibration boring with conventional boring for 7075 aluminum alloy deep hole pipes. The results demonstrate that, in contrast to conventional boring, two-dimensional ultrasonic vibration boring could achieve a maximum reduction of 54.1% and an average reduction of 50.4% in the roundness value of the deep holes. The impact of machining parameters on deep hole roundness is assessed through experimental analysis, leading to the determination of optimal processing parameters. In summary, this experimental research has a certain reference significance for the application of 7075 aluminum alloy deep hole parts in the aerospace field.

The Mycobacterium tuberculosis (MTB) infection causes tuberculosis (TB) and has been a long-standing public-health threat. It is urgent that we discover novel antitubercular agents to manage the increased incidence of multidrug-resistant (MDR) or extensively drug-resistant (XDR) strains of MTB and tackle the adverse effects of the first- and second-line antitubercular drugs. We previously found that gliotoxin ( 1 ), 12, 13-dihydroxy-fumitremorgin C ( 2 ), and helvolic acid ( 3 ) from the cultures of a deep-sea-derived fungus, Aspergillus sp. SCSIO Ind09F01, showed direct anti-TB effects. As macrophages represent the first line of the host defense system against a mycobacteria infection, here we showed that the gliotoxin exerted potent anti-tuberculosis effects in human THP-1-derived macrophages and mouse-macrophage-leukemia cell line RAW 264.7, using CFU assay and laser confocal scanning microscope analysis. Mechanistically, gliotoxin apparently increased the ratio of LC3-II/LC3-I and Atg5 expression, but did not influence macrophage polarization, IL-1β, TNF-a, IL-10 production upon MTB infection, or ROS generation. Further study revealed that 3-MA could suppress gliotoxin-promoted autophagy and restore gliotoxin-inhibited MTB infection, indicating that gliotoxin-inhibited MTB infection can be treated through autophagy in macrophages. Therefore, we propose that marine fungi-derived gliotoxin holds the promise for the development of novel drugs for TB therapy.

Four new sesterterpenes, arthproliferins A-D ( 1 - 4 ), together with four known derivatives, were isolated and characterized from the mangrove-sediment-derived fungus Arthrinium sp. SCSIO41221. Their structures were determined using detailed nuclear magnetic resonance (NMR) and mass spectroscopic (MS) analyses. Some of the isolated compounds were evaluated for their cytotoxicity in vitro. The results revealed that terpestacin ( 6 ) exhibited significant activity with an IC 50 value of 20.3 μM, and compounds 2 and 5 were found to show weak inhibitory effects against U87MG-derived GSCs.

Anticancer peptides (ACPs) have promising prospects for cancer treatment. Traditional ACP identification experiments have the limitations of low efficiency and high cost. In recent years, data-driven deep learning techniques have shown significant potential for ACP prediction. However, data-driven prediction models rely heavily on extensive training data. Furthermore, the current publicly accessible ACP dataset is limited in size, leading to inadequate model generalization. While data augmentation effectively expands dataset size, existing techniques for augmenting ACP data often generate noisy samples, adversely affecting prediction performance. Therefore, this paper proposes a novel augmented sample selection framework for the prediction of anticancer peptides (ACPs-ASSF). First, the prediction model is trained using raw data. Then, the augmented samples generated using the data augmentation technique are fed into the trained model to compute pseudo-labels and estimate the uncertainty of the model prediction. Finally, samples with low uncertainty, high confidence, and pseudo-labels consistent with the original labels are selected and incorporated into the training set to retrain the model. The evaluation results for the ACP240 and ACP740 datasets show that ACPs-ASSF achieved accuracy improvements of up to 5.41% and 5.68%, respectively, compared to the traditional data augmentation method.

In order to ensure the safe operation of buried polyethylene pipelines adjacent to blasting excavations, controlling the effects of blasting vibration loads on the pipelines is a key concern. Model tests on buried polyethylene pipelines under blasting loads were designed and implemented, the vibration velocity and dynamic strain response of the pipelines were obtained using a TC-4850 blast vibrometer and a UT-3408 dynamic strain tester, and the distribution characteristics of blast vibration velocity and dynamic strain were analyzed based on the experimental data. The results show that the blast load has the greatest effect on the circumferential strain of the polyethylene pipe, and the dynamic strain response is greatest at the section of the pipe nearest to the blast source. Pipe peak vibration velocity (PPVV), ground peak particle velocity (GPPV), and the peak dynamic strain of the pipe were highly positively correlated, which verifies the feasibility of using GPPV to characterize pipeline vibration and strain level. According to the failure criteria and relevant codes, combined with the analysis of experimental results, the safety threshold of additional circumferential stress on the pipeline is 1.52 MPa, and the safety control vibration speed of the ground surface is 21.6 cm/s.

As the most abundant white blood cells in humans, neutrophils play a key role in acute and chronic inflammation, suggesting that these cells are a key component of targeted therapies for various inflammation-related diseases. Specific enzyme-responsive or specific ligand-modified polymer nanoparticles are beneficial for improving drug efficacy, reducing toxicity, and enhancing focal site retention. However, there remain significant challenges in biomedical applications of these synthetic polymer nanoparticles, mainly due to their rapid clearance by the reticuloendothelial system. In recent years, biomimetic drug delivery systems such as neutrophils acting directly as drug carriers or neutrophil-membrane-coated nanoparticles have received increasing attention due to the natural advantages of neutrophils. Thus, neutrophil-targeted, neutrophil-assisted, or neutrophil-coated nanoparticles exhibit a prolonged blood circulation time and improved accumulation at the site of inflammation. Despite recent advancements, further clinical research must be performed to evaluate neutrophil-based delivery systems for future biomedical application in the diagnosis and treatment of related inflammatory diseases. In this review, we have summarized new exciting developments and challenges in neutrophil-mediated drug delivery strategies for treating inflammation-related diseases.

After T5 (forging + aging) and different T6 (forging + solution + aging) heat treatments, the AZ80A Mg alloys exhibited microstructures with different fractions of continuous precipitate (CP) regions and discontinuous precipitate (DP) regions. The effects of the fractions of DP regions and CP regions on the tensile properties and fracture behaviors were investigated using microstructural characterizations and analysis. The results showed that increasing the fraction of DP regions enhanced the yield strength and tensile strength at room temperature. However, at the same high temperature, increasing the fractions of DP regions improved the elongation but deteriorated the tensile strength significantly. The different resultant tensile properties at different temperatures were caused by the different precipitation-strengthening effects in the CP and DP regions. The strengthening contribution of the DP regions was more effective at room temperature but became inferior to the effect brought about by the CP regions at high temperatures. Micro-cracks were usually initiated and propagated in the CP regions at room temperature. At high temperatures, however, micro-voids formed more easily in the DP regions, and the fracture path preferred to locate there.

Oligodendrocytes generate myelin sheaths vital for the formation, health, and function of the central nervous system. Mounting evidence suggests that receptor tyrosine kinases (RTKs) are crucial for oligodendrocyte differentiation and myelination in the CNS. It was recently reported that discoidin domain receptor 1 (Ddr1), a collagen-activated RTK, is expressed in oligodendrocyte lineage. However, its specific expression stage and functional role in oligodendrocyte development in the CNS remain to be determined. In this study, we report that Ddr1 is selectively upregulated in newly differentiated oligodendrocytes in the early postnatal CNS and regulates oligodendrocyte differentiation and myelination. Ddr1 knock-out mice of both sexes displayed compromised axonal myelination and apparent motor dysfunction. Ddr1 deficiency alerted the ERK pathway, but not the AKT pathway in the CNS. In addition, Ddr1 function is important for myelin repair after lysolecithin-induced demyelination. Taken together, the current study described, for the first time, the role of Ddr1 in myelin development and repair in the CNS, providing a novel molecule target for the treatment of demyelinating diseases.

This randomized controlled trial examined the impact of a psychoeducational group program on the mental well-being of unit-based nurse leaders, specifically nurse managers and assistant nurse managers. The program was developed around the themes of resilience, insight, self-compassion, and empowerment to fight burnout and enhance purposeful adaptive coping to reduce distress and improve mental wellbeing. The sample included 77 unit-based nurse leaders. Outcomes included post-traumatic growth, resilience, insight, self-compassion, empowerment, perceived stress, burnout, and job satisfaction. Paired samples t-tests and repeated measures ANOVA tests were conducted to compare outcomes at baseline to the follow-up timepoints of endpoint, one-month follow-up, three-month follow-up, and six-month follow-up. The intervention group participants showed significant improvement in post-traumatic growth between baseline and all follow-up timepoints compared to the waitlist control group. Among intervention group participants, there were also significant improvements in self-reflection and insight, self-compassion, psychological empowerment, and compassion satisfaction, as well as significant reductions in perceived stress, burnout, and secondary traumatic stress. This study extends existing evidence that this psychoeducational group program can be an effective intervention for improving and protecting mental wellbeing. Among nurse leaders, it can reduce stress and burnout and improve post-traumatic growth, self-reflection and insight, self-compassion, psychological empowerment, and compassion satisfaction.

To discover bioactive natural products from mangrove sediment-derived microbes, a chemical investigation of the two Beibu Gulf-derived fungi strains, Talaromyces sp. SCSIO 41050 and Penicillium sp. SCSIO 41411, led to the isolation of 23 natural products. Five of them were identified as new ones, including two polyketide derivatives with unusual acid anhydride moieties named cordyanhydride A ethyl ester ( 1 ) and maleicanhydridane ( 4 ), and three hydroxyphenylacetic acid derivatives named stachylines H-J ( 10 - 12 ). Their structures were determined by detailed nuclear magnetic resonance (NMR) and mass spectroscopic (MS) analyses, while the absolute configurations were established by theoretical electronic circular dichroism (ECD) calculation. A variety of bioactive screens revealed three polyketide derivatives ( 1 - 3 ) with obvious antifungal activities, and 4 displayed moderate cytotoxicity against cell lines A549 and WPMY-1. Compounds 1 and 6 at 10 μM exhibited obvious inhibition against phosphodiesterase 4 (PDE4) with inhibitory ratios of 49.7% and 39.6%, respectively, while 5 , 10 , and 11 showed the potential of inhibiting acetylcholinesterase (AChE) by an enzyme activity test, as well as in silico docking analysis.

In recent years, expanded polystyrene (EPS) lightweight soil has been widely used as subgrade in soft soil areas because of its light weight and environmental protection. This study aimed to investigate the dynamic characteristics of sodium silicate modified lime and fly ash treated EPS lightweight soil (SLS) under cyclic loading. The effects of EPS particles on the dynamic elastic modulus ( E d ) and damping ratio ( λ ) of SLS were determined through dynamic triaxial tests at various confining pressures (σ 3 ), amplitudes, and cycle times. Mathematical models of the E d of the SLS, cycle times, and σ 3 were established. The results revealed that the EPS particle content played a decisive role in the E d and λ of the SLS. The E d of the SLS decreased with an increase in the EPS particle content (EC). The E d decreased by 60% in the 1-1.5% range of the EC. The existing forms of lime fly ash soil and EPS particles in the SLS changed from parallel to series. With an increase in σ 3 and amplitude, the E d of the SLS gradually decreased, the λ generally decreased, and the λ variation range was within 0.5%. With an increase in the number of cycles, the E d of the SLS decreased. The E d value and the number of cycles satisfied the power function relationship. Additionally, it can be found from the test results that 0.5% to 1% was the best EPS content for SLS in this work. In addition, the dynamic elastic modulus prediction model established in this study can better describe the varying trend of the dynamic elastic modulus of SLS under different σ 3 values and load cycles, thereby providing a theoretical reference for the application of SLS in practical road engineering.

Microorganisms are the dominating source of food and nutrition for sponges and play an important role in sponge structure, chemical defense, excretion and evolution. In recent years, plentiful secondary metabolites with novel structures and specific activities have been identified from sponge-associated microorganisms. Additionally, as the phenomenon of the drug resistance of pathogenic bacteria is becoming more and more common, it is urgent to discover new antimicrobial agents. In this paper, we reviewed 270 secondary metabolites with potential antimicrobial activity against a variety of pathogenic strains reported in the literature from 2012 to 2022. Among them, 68.5% were derived from fungi, 23.3% originated from actinomycetes, 3.7% were obtained from other bacteria and 4.4% were discovered using the co-culture method. The structures of these compounds include terpenoids (13%), polyketides (51.9%), alkaloids (17.4%), peptides (11.5%), glucosides (3.3%), etc. Significantly, there are 124 new compounds and 146 known compounds, 55 of which have antifungal activity in addition to antipathogenic bacteria. This review will provide a theoretical basis for the further development of antimicrobial drugs.

Infrared gradient refractive index (GRIN) material lenses have attracted much attention due to their continuously varying refractive index as a function of spatial coordinates in the medium. Herein, a glass accumulation thermal diffusion method was used to fabricate a high refractive index GRIN lens. Six Ge 17.2 As 17.2 Se x Te (65- x ) ( x = 10.5-16) glasses with good thermal stability and high refractive index ( n @10 μm ) of 0.12 was achieved in this GRIN lens. After thermal diffusion, the lens still had good transmittance (45%) in the range of 8-12 μm. Thermal imaging confirmed that this lens can be molded into the designed shape. The refractive index profile was indirectly characterized by the structure and composition changes. The structure and composition variation became linear with the increase in temperature from 260 °C to 270 °C for 12 h, indicating that the refractive index changed linearly along the axis. The GRIN lens with a high refractive index could find applications in infrared optical systems and infrared lenses for thermal imaging.n ) of 0.12 was achieved in this GRIN lens. After thermal diffusion, the lens still had good transmittance (45%) in the range of 8-12 μm. Thermal imaging confirmed that this lens can be molded into the designed shape. The refractive index profile was indirectly characterized by the structure and composition changes. The structure and composition variation became linear with the increase in temperature from 260 °C to 270 °C for 12 h, indicating that the refractive index changed linearly along the axis. The GRIN lens with a high refractive index could find applications in infrared optical systems and infrared lenses for thermal imaging.

The pandemic has resulted in a further reduction in travel distance, recreational radius of destinations and other levels of tourism activity, making "local people traveling locally" a new feature. From the perspective of localization of urban residents' recreation, this paper describes a moderated mediation model based on temporal self-regulation theory. Five representative urban parks in Beijing were selected as study areas, and data collected through a questionnaire were used to discuss the behavioral characteristics of localized recreation and the formation mechanism of sense of place among urban residents in Beijing. The results showed that: (1) connectedness beliefs and temporal valuations positively influenced sense of place, and had a positive indirect effect on sense of place through the mediating role of recreation involvement; (2) recreation benefits positively influenced sense of place; (3) recreation benefits reinforced the direct and mediating role of recreation involvement. Based on these findings, the paper concludes with a discussion of the theoretical value and practical implications, as well as future research directions for park and city management.

Cryptochrome is the earliest discovered photoreceptor protein in organisms. However, the effect of CRY (BmCRY), the clock protein in Bombyx mori , on the body or cell metabolism remains unclear. In this study, we continuously interfered with the expression of the BmCry1 gene (Cry1-KD) in the silkworm ovary cell line (BmN), and the BmN cells developed abnormally, with accelerated cell growth and a smaller nucleus. Metabolomics was used to identify the cause of the abnormal development of Cry1-KD cells based on gas chromatography/liquid chromatography-mass spectrometry. A total of 56 differential metabolites including sugars, acids, amino acids, and nucleotides were identified in wild-type and Cry1-KD cells. KEGG enrichment analysis showed that BmCry1 knockdown resulted in significantly upregulated glycometabolism in BmN cells, indicated by glucose-6-phosphate, fructose-6-phosphate, and pyruvic acid levels. The activities of key enzymes BmHK, BmPFK, and BmPK as well as their mRNA levels further confirmed that the glycometabolism level of Cry1-KD cells was significantly increased. Our results show that a possible mechanism of BmCry1 knockdown leading to abnormal cell development is the elevated level of glucose metabolism in cells.

To better reutilize heavy metal contaminated river sediment containing organic matter, the sediments in a river located in Chongming District, Shanghai were collected and Portland cement was used as a curing agent along with commercial organic matter to conduct the solidification/stabilization experiment. The unconfined compressive strength and heavy metal leaching concentrations of solidified blocks with different water content, organic matter content, and cement content were tested and analyzed to determine the optimal ratio. The effects of fulvic acid (FA), humic acid (HA), and an HA/FA ratio on the solidification and stabilization, as well as the speciation of heavy metals in sediment before and after solidification and stabilization, were studied. The results showed that when the organic content of the sediment is 6.16%, the water content is 65% and the cement content is greater than 38%, so the curing effect proves to be satisfactory. Fulvic acid has a stronger inhibiting effect on cement hydration than humic acid, and its consumption in the curing process is more significant. The addition of humic acid contributes to the stabilization of heavy metals, while the increase in fulvic acid greatly weakens the stability of heavy metals. The exchangeable state of heavy metals in the sediment has been reduced to varying degrees after solidification and stabilization. The research results can provide a basis for the reclamation and utilization of heavy metal contaminated river sediment with organic matter.

Upconversion devices (UCDs) have motivated tremendous research interest with their excellent potential and promising application in photovoltaic sensors, semiconductor wafer detection, biomedicine, and light conversion devices, especially near-infrared-(NIR)-to-visible upconversion devices. In this research, a UCD that directly turned NIR light located at 1050 nm into visible light located at 530 nm was fabricated to investigate the underlying working mechanism of UCDs. The simulation and experimental results of this research proved the existence of the quantum tunneling phenomenon in UCDs and found that the quantum tunneling effect can be enhanced by a localized surface plasmon.

Contamination of industry-derived antimony (Sb) is currently of great concern. This study was conducted to identify the source of Sb together with other potential toxic elements (PTEs) in a typical industrial area in China and emphasize the contribution of Sb to ecological risk in the local aquatic environment. By investigating the distribution of nine PTEs in surface water in Wujiang County in dry and wet seasons, this study revealed that textile wastewater was the main source of Sb. The distribution of Sb (0.48~21.4 μg/L) showed the least seasonal variation among the nine elements. Factor analysis revealed that the factor that controlled Sb distribution is unique. In general, Sb was more concentrated in the southeastern part of the study area where there was a large number of textile industries, and was affected by the specific conductivity and total dissolved solids in water ( p < 0.01). Sb concentration in 35.71% of samples collected from the drainage outlet exceeded the standard limit of 10 μg/L. Results from three pollution assessment methods suggested that >5% of the sampling sites were slightly too heavily polluted and Sb contributed the most. Therefore, it is necessary to strengthen the administrative supervision of local textile enterprises and elevate the local standard of textile wastewater emission.

In recent years, thanks to the performance advantages of convolutional neural networks (CNNs), CNNs have been widely used in image denoising. However, most of the CNN-based image-denoising models cannot make full use of the redundancy of image data, which limits the expressiveness of the model. We propose a new image-denoising model that aims to extract the local features of the image through CNN and focus on the global information of the image through the attention similarity module (ASM), especially the global similarity details of the image. Furthermore, dilation convolution is used to enlarge the receptive field to better focus on the global features. Moreover, avg-pooling is used to smooth and suppress noise in the ASM to further improve model performance. In addition, through global residual learning, the effect is enhanced from shallow to deep layers. A large number of experiments show that our proposed model has a better image-denoising effect, including quantitative and visual results. It is more suitable for complex blind noise and real images.

Numerous nanocarriers have been developed to deliver drugs for the treatment of hepatocellular carcinoma. However, the lack of specific targeting ability, the low administration efficiency, and insufficient absorption by hepatocellular carcinoma cells, severely limits the therapeutic effect of the current drugs. Therefore, it is still of great clinical significance to develop highly efficient therapies with few side effects for the treatment of hepatocellular carcinoma. Herein, we developed a highly effective nanocarrier, cyclic RGD peptide-conjugated magnetic mesoporous nanoparticles ( RGD SPIO@MSN NPs), to deliver the chemotherapeutic drug doxorubicin (DOX) to human hepatocellular carcinoma HepG2 cells, and further explored their synergistic apoptosis-promoting effects. The results showed that the prepared RGD SPIO@MSN NPs had good stability, biosafety and drug-loading capacity, and significantly improved the absorption of DOX by HepG2 cells, and that the RGD SPIO@MSN@DOX NPs could synergistically promote the apoptosis of HepG2 cells. Thus, this cyclic RGD peptide-modified magnetic mesoporous silicon therapeutic nanosystem can be regarded as a potentially effective strategy for the targeted treatment of hepatocellular carcinoma.

Fe-Cu-Co prealloyed powder is used for bonding metal of diamond tools. In order to obtain diamond tools with good mechanical properties by pressureless sintering, it is necessary to add Cu-Sn sintering aids. The substrate also has high corrosion resistance requirements, which is conducive to the chemical erosion of diamond tools. This paper mainly studies the effects of Cu-Sn on the corrosion behavior of pressureless sintered Fe-Cu-Co substrate. The results show that the linear contraction rate and relative density of pressureless sintered Fe-Cu-Co alloy at 875 °C reach their peak when the Cu-Sn content is 8 wt.%, 15.13% and 97.5%, respectively. The substrate is mainly composed of α-Fe and Cu-rich phases, and selective corrosion occurs during electrochemical corrosion; namely, α-Fe grains are more prone to corrosion than Cu-rich grains to form porous corrosion surfaces. With the increase in Cu-Sn addition, the volume fraction of the Cu-rich phase increases, the corrosion current density and the passive current density gradually decrease, and the corrosion resistance of the alloy is improved. The amount and integrity of anodic passive film on the Fe-Cu-Co surface increases with the increase in Cu-Sn addition. The oxygen content of the anodic passivation film is lower than that of the active corrosion products of the α-Fe phase, thus reducing the oxygen concentration gradient and slowing down the corrosion. The addition of Cu-Sn is conducive to improving the corrosion resistance of Fe-Cu-Co alloy as the substrate of diamond tools.

Due to the influence of poor lighting conditions and the limitations of existing imaging equipment, captured low-illumination images produce noise, artifacts, darkening, and other unpleasant visual problems. Such problems will have an adverse impact on the following high-level image understanding tasks. To overcome this, a two-stage network is proposed in this paper for better restoring low-illumination images. Specifically, instead of manipulating the raw input directly, our network first decomposes the low-illumination image into three different maps (i.e., reflectance, illumination, and feature) via a Decom-Net. During the decomposition process, only reflectance and illumination are further denoised to suppress the effect of noise, while the feature is preserved to reduce the loss of image details. Subsequently, the illumination is deeply adjusted via another well-designed subnetwork called Enhance-Net. Finally, the three restored maps are fused together to generate the final enhanced output. The entire proposed network is optimized in a zero-shot fashion using a newly introduced loss function. Experimental results demonstrate that the proposed network achieves better performance in terms of both objective evaluation and visual quality.

Background: In contrast to Caucasian melanoma, which has been extensively studied, there are few studies on melanoma in Asian populations. Sporadic studies reported that only 40% of Asian melanoma patients could be druggable, which was much lower than that in Caucasians. More studies are required to refine this conclusion., Methods: Chinese melanoma patients ( n = 469) were sequentially sequenced by DNA-NGS and RNA-NGS. The genomic alterations were determined, and potentially actionable targets were investigated., Results: Patients with potential druggable targets were identified in 75% of Chinese melanoma patients by DNA-NGS based on OncoKB, which was much higher than in a previous Asian study. NRG1 fusions were first identified in melanoma. In addition, up to 11.7% (7/60) of patients in the undruggable group could be recognized as actionable by including RNA-NGS analysis. By comparing the fusion detection rate between DNA-NGS and RNA-NGS, all available samples after DNA-NGS detection were further verified by RNA-NGS. The use of RNA-NGS enhanced the proportion of druggable fusions from 2.56% to 17.27%. In total, the use of RNA-NGS increased the druggable proportion from 75% to 78%., Conclusions: In this study, we systemically analyzed the actionable landscape of melanoma in the largest Asian cohort. In addition, we first demonstrated how DNA and RNA sequential sequencing is essential in bringing clinical benefits to more patients with melanoma., Competing Interests: B.W., C.W., D.Z., Y.N., X.W., W.L., and J.Z. were employed by Jichenjunchuang Clinical Laboratory. All other authors have declared no conflict of interest.

The absence of labeled samples limits the development of speech emotion recognition (SER). Data augmentation is an effective way to address sample sparsity. However, there is a lack of research on data augmentation algorithms in the field of SER. In this paper, the effectiveness of classical acoustic data augmentation methods in SER is analyzed, based on which a strong generalized speech emotion recognition model based on effective data augmentation is proposed. The model uses a multi-channel feature extractor consisting of multiple sub-networks to extract emotional representations. Different kinds of augmented data that can effectively improve SER performance are fed into the sub-networks, and the emotional representations are obtained by the weighted fusion of the output feature maps of each sub-network. And in order to make the model robust to unseen speakers, we employ adversarial training to generalize emotion representations. A discriminator is used to estimate the Wasserstein distance between the feature distributions of different speakers and to force the feature extractor to learn the speaker-invariant emotional representations by adversarial training. The simulation experimental results on the IEMOCAP corpus show that the performance of the proposed method is 2-9% ahead of the related SER algorithm, which proves the effectiveness of the proposed method.

SCL/TAL1 interrupting locus (STIL) regulates centriole replication and causes chromosome instability, which is closely related to malignant tumors. The purpose of our study was to investigate the role of STIL in bladder cancer (BC) tumorigenesis for the first time. The public database indicated that STIL is highly expressed and correlated with the cell cycle in BC. Immunohistochemistry staining showed that STIL expression is significantly elevated in BC tissues compared with paracancer tissues. CRISPR-Cas9 gene editing technology was used to induce BC cells to express STIL-specific sgRNA, revealing a significantly delayed growth rate in STIL knockout BC cells. Moreover, cell cycle arrest in the G0/G1 phase was triggered by decreasing STIL, which led to delayed BC cell growth in vitro and in vivo. Mechanically, STIL knockout inhibited the PI3K/AKT/mTOR pathway and down-regulated the expression of c-myc. Furthermore, SC79 (AKT activating agent) partially reversed the inhibitory effects of STIL knockout on the proliferation and migration of BC cells. In conclusion, STIL enhanced the PI3K/AKT/mTOR pathway, resulting in increased expression of c-myc, ultimately promoting BC occurrence and progression. These results indicate that STIL might be a potential target for BC patients.

Increasing contamination risk from oil/organic liquid leakage creates strong demand for the development of absorbents with excellent hydrophobicity and absorption capacity. Herein, bagasse was carbonized to form porous char with a special structure of array-style and vertically perforated channels, and then the activation process enlarged the pore volume of the char. With the cooperation of low-surface-energy polydimethylsiloxane and diatomaceous earth particles, the modified activated carbon aerogel (MACA) was fabricated by modifying the surface coating and mastoid structure on the bagasse char. Moreover, the MACA demonstrates high porosity oil-water separation, hydrophobicity, and considerable absorption capacity (4.06-12.31 g / g ) for gasoline and various organic solvents. This work converts agricultural waste into an efficient porous adsorbent, offering a scalable and commercially feasible solution to solving the leakages of oil/organic solvents.

Background and Objectives : To compare the oncological and functional outcomes of brachytherapy (BT) and radical prostatectomy (RP) in patients with localized prostate cancer (PCa). Materials and Methods : We retrospectively analyzed data from 557 patients with localized PCa who were treated with BT ( n = 245) or RP ( n = 312) at Northern Jiangsu People's Hospital between January 2012 and December 2017. Biochemical relapse-free survival (bRFS) and cancer-specific survival (CSS) were compared by treatment modality. Multivariate Cox regression analysis was used to evaluate bRFS. Health-related quality of life (HRQoL) was measured using the Expanded Prostate Cancer Index Composite (EPIC) questionnaire. Results : The BT group was older and had a higher initial PSA (iPSA). The 5-year bRFS was 82.9% in the BT group versus 80.1% in the RP group ( p = 0.570). The 5-year CSS was 96.4% in the BT group versus 96.8% in the RP group ( p = 0.967). Based on multivariate Cox regression analysis, Gleason score ≥ 8 was the main independent prognostic factor for bRFS. Regarding the HRQoL, compared with the baseline, both treatments produced a significant decrease in different aspects of HRQoL at 3, 6, and 12 months after treatment. Patients in the BT group had lower HRQoL with regard to urinary irritation/obstruction and bowel function or bother, while patients in the RP group had lower HRQoL concerning urinary incontinence and sexual function or bother. There was no significant difference in HRQoL aspects between the two groups after follow-up for 2 years compared with the baseline. Conclusions : BT provides equivalent oncological control outcomes in terms of bRFS and CSS for patients with localized PCa compared with RP. Gleason score ≥ 8 was the main independent prognostic factor for bRFS. BT had better HRQoL compared with RP, except for urinary irritation/obstruction and bowel function or bother, but returned to baseline after 2 years.

The emergence of different virus variants, the rapidly changing epidemic, and demands for economic recovery all require continual adjustment and optimization of COVID-19 intervention policies. For the purpose, it is both important and necessary to evaluate the effectiveness of different policies already in-place, which is the basis for optimization. Although some scholars have used epidemiological models, such as susceptible-exposed-infected-removed (SEIR), to perform evaluation, they might be inaccurate because those models often ignore the time-varying nature of transmission rate. This study proposes a new scheme to evaluate the efficiency of dynamic COVID-19 interventions using a new model named as iLSEIR-DRAM. First, we improved the traditional LSEIR model by adopting a five-parameter logistic function β(t) to depict the key parameter of transmission rate. Then, we estimated the parameters by using an adaptive Markov Chain Monte Carlo (MCMC) algorithm, which combines delayed rejection and adaptive metropolis samplers (DRAM). Finally, we developed a new quantitative indicator to evaluate the efficiency of COVID-19 interventions, which is based on parameters in β(t) and considers both the decreasing degree of the transmission rate and the emerging time of the epidemic inflection point. This scheme was applied to seven cities in Guangdong Province. We found that the iLSEIR-DRAM model can retrace the COVID-19 transmission quite well, with the simulation accuracy being over 95% in all cities. The proposed indicator succeeds in evaluating the historical intervention efficiency and makes the efficiency comparable among different cities. The comparison results showed that the intervention policies implemented in Guangzhou is the most efficient, which is consistent with public awareness. The proposed scheme for efficiency evaluation in this study is easy to implement and may promote precise prevention and control of the COVID-19 epidemic.

Two new lactones, named Ardisicreolides A-B ( 1 - 2 ), together with four known flavonoids, Quercetin ( 3 ), Myricetrin ( 4 ), Quercitrin ( 5 ), Tamarixetin 3-O-rhamnoside ( 6 ), were isolated from the ethyl acetate portion of 70% ethanol extracts of dried leaves from Ardisia crenata Sims. These compounds were identified from Ardisia crenata Sims for the first time. The structures of 1 - 6 were elucidated according to 1D and 2D-NMR methods and together with the published literature. All of the isolated compounds were evaluated for in vitro anti-microbial effect against Escherichia coli , Pseudomonas aeuroginosa , Enterococcus faecalis , Proteus vulgaris , Staphylococcus aureus , and Bacillus subtilis . In addition, compounds 1 - 2 were assessed for anti-inflammatory activity by acting on LPS-induced RAW 264.7 macrophage cells in vitro. The results showed that only compound 2 exhibited moderate antibacterial activity on Bacillus subtilis . Moreover, compounds 1 and 2 were found to significantly inhibit the production of nitric oxide (NO) and reduce the release of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-4 (IL-4), and interleukin-10 (IL-10) in LPS-induced RAW 264.7 macrophage cells. The present data suggest that lactones from the leaves of A. crenata Sims might be used as a potential source of natural anti-inflammatory agents.

The availability of large-scale genomic data resources makes it very convenient to mine and analyze genes that are related to important agricultural traits in rice. Pan-genomes have been constructed to provide insight into the genome diversity and functionality of different plants, which can be used in genome-assisted crop improvement. Thus, a pan-genome comprising all genetic elements is crucial for comprehensive variation study among the heat-resistant and -susceptible rice varieties. In this study, a rice pan-genome was firstly constructed by using 45 heat-tolerant and 15 heat-sensitive rice varieties. A total of 38,998 pan-genome genes were identified, including 37,859 genes in the reference and 1141 in the non-reference contigs. Genomic variation analysis demonstrated that a total of 76,435 SNPs were detected and identified as the heat-tolerance-related SNPs, which were specifically present in the highly heat-resistant rice cultivars and located in the genic regions or within 2 kbp upstream and downstream of the genes. Meanwhile, 3214 upregulated and 2212 downregulated genes with heat stress tolerance-related SNPs were detected in one or multiple RNA-seq datasets of rice under heat stress, among which 24 were located in the non-reference contigs of the rice pan-genome. We then mapped the DEGs with heat stress tolerance-related SNPs to the heat stress-resistant QTL regions. A total of 1677 DEGs, including 990 upregulated and 687 downregulated genes, were mapped to the 46 heat stress-resistant QTL regions, in which 2 upregulated genes with heat stress tolerance-related SNPs were identified in the non-reference sequences. This pan-genome resource is an important step towards the effective and efficient genetic improvement of heat stress resistance in rice to help meet the rapidly growing needs for improved rice productivity under different environmental stresses. These findings provide further insight into the functional validation of a number of non-reference genes and, especially, the two genes identified in the heat stress-resistant QTLs in rice.

With the development of deep learning, considerable progress has been made in image restoration. Notably, many state-of-the-art single image super-resolution (SR) methods have been proposed. However, most of them contain many parameters, which leads to a significant amount of calculation consumption in the inference phase. To make current SR networks more lightweight and resource-friendly, we present a convolution neural network with the proposed selective channel processing strategy (SCPN). Specifically, the selective channel processing module (SCPM) is first designed to dynamically learn the significance of each channel in the feature map using a channel selection matrix in the training phase. Correspondingly, in the inference phase, only the essential channels indicated by the channel selection matrixes need to be further processed. By doing so, we can significantly reduce the parameters and the calculation consumption. Moreover, the differential channel attention (DCA) block is proposed, which takes into consideration the data distribution of the channels in feature maps to restore more high-frequency information. Extensive experiments are performed on the natural image super-resolution benchmarks (i.e., Set5, Set14, B100, Urban100, Manga109) and remote-sensing benchmarks (i.e., UCTest and RESISCTest), and our method achieves superior results to other state-of-the-art methods. Furthermore, our method keeps a slim size with fewer than 1 M parameters, which proves the superiority of our method. Owing to the proposed SCPM and DCA, our SCPN model achieves a better trade-off between calculation cost and performance in both general and remote-sensing SR applications, and our proposed method can be extended to other computer vision tasks for further research.

The quality of feature extraction plays a significant role in the performance of speech emotion recognition. In order to extract discriminative, affect-salient features from speech signals and then improve the performance of speech emotion recognition, in this paper, a multi-stream convolution-recurrent neural network based on attention mechanism (MSCRNN-A) is proposed. Firstly, a multi-stream sub-branches full convolution network (MSFCN) based on AlexNet is presented to limit the loss of emotional information. In MSFCN, sub-branches are added behind each pooling layer to retain the features of different resolutions, different features from which are fused by adding. Secondly, the MSFCN and Bi-LSTM network are combined to form a hybrid network to extract speech emotion features for the purpose of supplying the temporal structure information of emotional features. Finally, a feature fusion model based on a multi-head attention mechanism is developed to achieve the best fusion features. The proposed method uses an attention mechanism to calculate the contribution degree of different network features, and thereafter realizes the adaptive fusion of different network features by weighting different network features. Aiming to restrain the gradient divergence of the network, different network features and fusion features are connected through shortcut connection to obtain fusion features for recognition. The experimental results on three conventional SER corpora, CASIA, EMODB, and SAVEE, show that our proposed method significantly improves the network recognition performance, with a recognition rate superior to most of the existing state-of-the-art methods.

The promising outcomes of chimeric antigen receptor (CAR) T cell therapy in hematologic malignancies potentiates its capability in the fight against many cancers. Nevertheless, this immunotherapy modality needs significant improvements for the treatment of solid tumors. Researchers have incrementally identified limitations and constantly pursued better CAR designs. However, even if CAR T cells are armed with optimal killer functions, they must overcome and survive suppressive barriers imposed by the tumor microenvironment (TME). In this review, we will discuss in detail the important role of TME in CAR T cell trafficking and how the intrinsic barriers contribute to an immunosuppressive phenotype and cancer progression. It is of critical importance that preclinical models can closely recapitulate the in vivo TME to better predict CAR T activity. Animal models have contributed immensely to our understanding of human diseases, but the intensive care for the animals and unreliable representation of human biology suggest in vivo models cannot be the sole approach to CAR T cell therapy. On the other hand, in vitro models for CAR T cytotoxic assessment offer valuable insights to mechanistic studies at the single cell level, but they often lack in vivo complexities, inter-individual heterogeneity, or physiologically relevant spatial dimension. Understanding the advantages and limitations of preclinical models and their applications would enable more reliable prediction of better clinical outcomes.