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Abstract Background The triglyceride-glucose (TyG) index and estimated glucose disposal rate (eGDR), which are calculated using different parameters, are widely used as markers of insulin resistance and are associated with cardiovascular diseases and prognosis. However, whether they have an additive effect on the risk of mortality remains unclear. This study aimed to explore whether the combined assessment of the TyG index and eGDR improved the prediction of long-term mortality in individuals with and without diabetes. Methods In this cross-sectional and cohort study, data were derived from the National Health and Nutrition Examination Survey (NHANES) 2001–2018, and death record information was obtained from the National Death Index. The associations of the TyG index and eGDR with all-cause and cardiovascular mortality were determined by multivariate Cox regression analysis and restricted cubic splines. Results Among the 17,787 individuals included in the analysis, there were 1946 (10.9%) all-cause deaths and 649 (3.6%) cardiovascular deaths during a median follow-up of 8.92 years. In individuals with diabetes, the restricted cubic spline curves for the associations of the TyG index and eGDR with mortality followed a J-shape and an L-shape, respectively. The risk of mortality significantly increased after the TyG index was > 9.04 (all-cause mortality) or > 9.30 (cardiovascular mortality), and after eGDR was 9.04 and eGDR

Abstract Background Evidence has shown that the individual metrics in Life’s Essential 8 (LE8), an updated cardiovascular health (CVH) concept proposed by the American Heart Association, play a role in the development of inflammatory bowel disease (IBD). However, epidemiological evidence on the overall LE8 on IBD risk remains limited. We aimed to assess the longitudinal associations of LE8-defined CVH and the risks of IBD and its subtypes, ulcerative colitis (UC) and Crohn’s disease (CD). We also tested whether genetic susceptibility could modify these associations. Methods A total of 260,836 participants from the UK Biobank were included. LE8 scores were determined by 8 metrics (physical activity, diet, nicotine exposure, sleep, body mass index, blood pressure, blood glucose, and blood lipids), and were divided into three levels: low CVH (0–49), moderate CVH (50–79), and high CVH (80–100). Cox proportional hazards models were used to calculate the hazard ratios (HRs) and confidence intervals (CIs) of the risk of IBD in relation to CVH status. Results Over a median follow-up 12.3 years, we documented 1,500 IBD cases (including 1,070 UC and 502 CD). Compared to participants with low CVH, the HRs (95% CIs) of those with high CVH for IBD, UC, and CD were 0.67 (0.52, 0.83), 0.70 (0.52, 0.93), and 0.55 (0.38, 0.80), respectively. These associations were not modified by genetic susceptibility (all P for interactions > 0.05). The lowest HR (UC: 0.30, 95% CI: 0.20–0.45; CD: 0.33, 95% CI: 0.20–0.57) was observed in participants with both high CVH and low genetic risk. Conclusions Better CVH, defined by LE8, was associated with significantly lower risks of IBD, UC, and CD, irrespective of genetic predisposition. Our results underscore the importance of adherence to LE8 guidelines for maintaining CVH as a potential strategy in the prevention of IBD.

Cement-soil mortar is a composite material that provides an efficient and cost-effective solution for a wide range of construction applications. This study analyzes the mechanical properties of cement-soil mortar through experimental investigation and explores the application and parameter calibration of the Concrete Damage Plasticity (CDP) model in the finite element simulation of cement-soil mortar. Additionally, an innovative Initial Defect Generation (IDG) method is proposed to enhance the accuracy in simulation of failure mode. The research findings provide a simulation framework that balances simplicity and accuracy for cement-soil mortar. Uniaxial compressive tests are first conducted on cement-soil mortar specimens with water contents ranging from 40 % to 70 %, and cement-to-soil proportions from 30 % to 300 %. Based on the experimental results, the regression relationships correlating unconfined compressive strength (UCS) with elastic modulus, peak strain and stress-strain curves are established. Then, the simplified equations for calculating CDP model parameters from the UCS of cement-soil mortar are further proposed following damage mechanics. A parameter table summarizing the calculation methods for all relevant CDP parameters is provided to streamline the model calibration process. Simulations incorporating the simplified calibration method and IDG method successfully replicated the stress-strain responses and failure modes observed in uniaxial compressive strength tests of cement-soil specimens with varied strength. The results demonstrate the reliability and broad applicability of this simulation framework in predicting the mechanical performance of cement-soil mortar.

The impressive increase in antimicrobial resistance has required the development of alternative treatments that act on multiple non-specific molecular targets and are effective against a broad range of microorganisms. Antimicrobial Photodynamic Therapy (aPDT) is based on microbial inactivation from oxidative stress and represents an important tool for inactivating microorganisms with low risk of resistance selection. Therefore, our research group has been devoted to demonstrating its effectiveness against pathogens that cause pneumonia, one of the most lethal infections worldwide. Previous studies reported the efficiency and safety of an in vitro photoinactivation protocol for Streptococcus pneumoniae and the delivery of infrared light (external illumination) and photosensitizer (PS) in an animal model. However, the in vivo inactivation of microorganisms still poses challenges due to the presence of lung surfactant (LS), which traps PSs, preventing them from reaching the microbial target. This study investigated different approaches such as use of emulsifiers, perfluorocarbon, oxygen nanobubbles, and copolymer towards overcoming LS and optimizing aPDT response. The most promising strategy consisted in combining indocyanine green (ICG) with GantrezTM AN-139 - a Polyvinyl Methyl Ether/Maleic Anhydride copolymer (PVM/MA) – showing high microbial inactivation and safety for human lung epithelial (A549) and fibroblast (MRC-9) cell lines. The in vitro experiments provided an alternative to overcome the limited PS distribution through LS and will serve as the basis for in vivo studies.

This study analyzes the effects of noise equivalent sigma zero (NESZ) on wind retrieval accuracy based on the estimated NESZ and wind retrievals from Gaofen-3 (GF3) synthetic aperture radar (SAR) wave mode data. The NESZ was estimated from the normalized radar cross-section (NRCS) bottom envelope from the calm sea (winds

Abstract Fault slip rates estimated from geodetic data are being integrated into seismic hazard models. The standard approach requires modeling velocities and relative (micro‐)plate motions, which is challenging for fault‐based models. We present a new approach to directly invert strain rates to solve for slip rates and distributed strain simultaneously. We generate velocity and strain rate fields over the southeastern Tibetan Plateau, utilizing Sentinel‐1 Interferometric Synthetic Aperture Radar data spanning 2014–2023. We derive slip rates using block modeling and by inverting strain rates. Our results show a partitioning between localized strain on faults and distributed deformation. The direct inversion of strain rates matches the geodetic data best when incorporating distributed moment sources, accounting for a similar proportion to on‐fault sources. The direct strain methodology also aligns best with the independent geological slip rates, especially near fault tips. As high‐resolution strain rate fields become increasingly available, we recommend direct inversion as the preferred practice.

Overfishing, bycatch, and other anthropogenic threats may lead to the destruction of fragile habitats and substantial losses of marine life. Marine fishery resources can be protected by adjusting fishing intensity and establishing marine reserves. Currently, China adopts the closed fishing season management approach to protect traditional fishing grounds, where fine spatio-temporal prediction is essential to efficiently supervise the wide scope. Fishing vessel behaviors reflect fishers’ experience as well as the information provided by fish detection radar, while the fishery resource distribution is relevant to the marine environment. In this study, we identified fishing vessel behaviors (gillnets, trawls, purse seines, and abnormal behaviors) and qualitatively assessed and predicted fishing time of different fishing vessel behaviors to search for high intensity fishing operation areas by constructing a time-space prediction model. The model was based on big data of fishing vessel automatic identification systems and3 the marine environment, and was verified in the East China Sea. The prediction results generally corresponded with the distribution of traditional fishery resources in the East China Sea and the fishing efforts provided by the Global Fishing Watch. This model can provide an accurate and effective refined fishing vessel operation time prediction, and benefits fishing management and fishery resources protection.

Background: Ambient air pollution might serve as a prognostic factor for ovarian cancer (OC) survival, yet the relationships between plant-based diet indices (PDIs) and OC survival remain unclear. We aimed to investigate the associations of comprehensive air pollution and PDIs with OC survival and explored the effects of air pollution-diet interactions. Methods: The present study encompassed 658 patients diagnosed with OC. The overall plant-based diet index (PDI), the healthful PDI (hPDI), and the unhealthful PDI (uPDI) were evaluated by a self-reported validated food frequency questionnaire. In addition, an air pollution score (APS) was formulated by summing the concentrations of particulate matter with a diameter of 2.5 microns or less, ozone, and nitrogen dioxide. Cox proportional hazard models were applied to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs). The potential interactions of APS with PDIs in relation to overall survival (OS) were assessed on both multiplicative and additive scales. Results: Throughout a median follow-up of 37.60 (interquartile: 24.77–50.70) months, 123 deaths were confirmed. Comparing to the lowest tertiles, highest uPDI was associated with lower OS of OC (HR = 2.06, 95 % CI = 1.30, 3.28; P-trend

ABSTRACT: Marek's disease (MD), an immunosuppression disease induced by Marek's disease virus (MDV), is one of the significant diseases affecting the health and productive performance of poultry. The roles of circular RNAs (circRNAs) in MD development were poorly understood. In this study, we found a circRNA derived from exon 6 of RUNX family transcription factor 2 (RUNX2) gene, named circRUNX2.2, was highly expressed in chicken tumorous spleens (TS) induced by MDV. Through fluorescence in situ hybridization and nuclear-cytoplasmic separation assay, we determined circRUNX2.2 was mainly located in the nucleus. Knockout experiments confirmed that the flanking complementary sequences (RCMs) mediated its circularization. Gain of function assay and dual luciferase reporter gene assay revealed that circRUNX2.2 could promote the expression of RUNX2 via binding with its promoter region. RNA antisense purification assay and mass spectrometry assay showed circRUNX2.2 could recruit proteins such as CHD9 protein. Knocking down CHD9 expression decreased the expression of RUNX2 gene, which confirmed the positive regulation that circRUNX2.2 on RUNX2 expression was probably facilitated via recruiting CHD9 protein. Functional experiments showed that circRUNX2.2 promoted the proliferation of the MD lymphoma-derived chicken cell line, MDCC-MSB1, which confirmed the potential oncogenic role of circRNX2.2 in tumor development. In conclusion, we found that the RUNX2-derived circRUNX2.2 can positively regulate the transcription of the parental gene RUNX2 in a cis-acting manner. The high expression of circRUNX2.2 in MD tumor tissues indicated that it might mediate MD lymphoma progression.

Abstract Background The Gastrodia elata Bl. is an orchid, and its growth demands the presence of Armillaria species. The strong competitiveness of Armillaria species has always been a concern of major threat to other soil organisms, thus disrupting the equilibrium of soil biodiversity. Introducing other species to where G. elata was cultivated, could possibly alleviate the problems associated with the disequilibrium of soil microenvironment; however, their impacts on the soil microbial communities and the underlying mechanisms remain unclear. To reveal the changes of microbial groups associated with soil chemical properties responding to different cultivation species, the chemical property measurements coupled with the next-generation pyrosequencing analyses were applied with soil samples collected from fallow land, cultivation of G. elata and Phallus impudicus, respectively. Results The cultivation of G. elata induced significant increases (p

Abstract Atherosclerosis is the build-up of fatty plaques within blood vessel walls, which can occlude the vessels and cause strokes or heart attacks. It gives rise to both structural and biomolecular changes in the vessel walls. Current single-modality imaging techniques each measure one of these two aspects but fail to provide insight into the combined changes. To address this, our team has developed a dual-modality imaging system which combines optical coherence tomography (OCT) and fluorescence imaging that is optimized for a porphyrin lipid nanoparticle that emits fluorescence and targets atherosclerotic plaques. Atherosclerosis-prone apolipoprotein (Apo)e -/- mice were fed a high cholesterol diet to promote plaque development in descending thoracic aortas. Following infusion of porphyrin lipid nanoparticles in atherosclerotic mice, the fiber-optic probe was inserted into the aorta for imaging, and we were able to robustly detect a porphyrin lipid-specific fluorescence signal that was not present in saline-infused control mice. We observed that the nanoparticle fluorescence colocalized in areas of CD68+ macrophages. These results demonstrate that our system can detect the fluorescence from nanoparticles, providing complementary biological information to the structural information obtained from simultaneously acquired OCT.

Abstract Diabetic kidney disease (DKD) is the leading cause of end‐stage kidney disease. DKD is a heterogeneous disease with complex pathophysiology where early endothelial dysfunction is associated with disease progression. The Tie2 receptor and Angiopoietin 1 and 2 ligands are critical for maintaining endothelial cell permeability and integrity. Tie2 signaling is negatively regulated by the endothelial specific transmembrane receptor Vascular Endothelial Protein Tyrosine Phosphatase (VEPTP). Genetic deletion of VEPTP protects from hypertension and diabetes induced renal injury in a mouse model of DKD. Here, we show that VEPTP inhibition with an extracellular domain targeting VEPTP antibody induced Tie2 phosphorylation and improved VEGF‐A induced vascular permeability both in vitro and in vivo. Treatment with the VEPTP blocking antibody decreased the renal expression of endothelial activation markers (Angpt2, Edn1, and Icam1) but failed to improve kidney function in db/db uninephrectomized ReninAAV DKD mice.

N,N-dimethylformamide (DMF) is an organic solvent with stable chemical properties and high boiling point. Based on its good solubility, DMF is widely used in synthetic textile, leather, electronics, pharmaceutical and pesticide industries. However, the DMF pollutes the environment and does harm to human liver function, kidney function, and nerve function. Herein, an efficient DMF-degrading strain, DM175A1-1, was isolated and identified as Paracoccus sulfuroxidans. This strain can use DMF as the sole source of carbon and nitrogen. Whole-genome sequencing of strain DM175A1-1 revealed that it has a 3.99-Mbp chromosome a 120-kbp plasmid1 and a 40-kbp plasmid2. The chromosome specifically harbors the dmfA1 and dmfA2 essential for the initial steps of DMF degradation. And it also carries the some part of genes facilitating subsequent methylotrophic metabolism and glutathione-dependent pathway. Through further DMF tolerance degradation experiments, DM175A1-1 can tolerate DMF concentrations up to 10,000 mg/L, whereas the majority of Paracoccus strains could only show degradation activity below 1,000 mg/L. And the efficiency of organic nitrogen conversion to NH3-N in DMF can reach 99.0% when the hydraulic retention time (HRT) is controlled at 5 days. Meanwhile, it showed a significant degradation effect at a pharmaceutical enterprise in Zhejiang Province with high concentration of DMF wastewater. This study provides a new strain Paracoccus sulfuroxidans DM175A1-1 which shows a significant influence on DMF degradation, and reveals the characterization on its DMF degradation. It lays the foundation for the application of biological method in the efficient degradation of DMF in industrial wastewater.

A risk-aware scheduling method of multienergy virtual power plant (MEVPP) is proposed to measure the uncertainty in MEVPP. First, a novel day-ahead uncertainty scenario generation method based on denoising diffusion probabilistic model is proposed, and historical data are employed to learn the error relationship between real power curves and predict power curves. The probability distribution of the prediction error which describes the day-ahead output power curve of renewable energy source is learned by parameter training. Subsequently, the effect of risk aversion on decision-making is investigated by implementing conditional value-at-risk in the optimization model, MEVPP operation mode under the carbon trading and green certificate trading mechanism is analyzed. Finally, the proposed scheme is implemented on a test MEVPP with carbon trading, and green certificate trading is addressed in detail through a numerical study. Moreover, the effects of the operator’s risk-averse behavior on the MEVPP are investigated.

This paper proposes an interval prediction technology of photovoltaic (PV) power based on parameter optimization of extreme learning machine (ELM) model. First, the weighted Euclidean distance is proposed as the evaluation index of PV power prediction interval. The historical sample units are screened and the ELM training set is optimized. Then, a hybrid optimization algorithm for ELM parameters is proposed. The hidden layer input and output weights and biases parameters of the ELM model are optimized by using the elitist strategy genetic algorithm and quantile regression, and the trained model is used to predict the PV power range. Finally, an actual calculation example is constructed based on the historical data of PV power plants and weather stations. The PV power interval is predicted, and the results are compared with those obtained by other methods. The results of the calculation example show that the method proposed can greatly improve the accuracy of interval prediction while increasing the reliability of interval prediction.

The Qinghai Nanshan fault is a larger fault in the Northeastern Xizang Plateau. In previous studies, its movement characteristics are mainly investigated with geological and seismic observations, and the tectonic transformation role of the fault on its east is not yet clear. This study uses data fusion to obtain denser GPS observations near the Qinghai Nanshan fault. Based on tectonic characteristics, we establish a block model to investigate the fault slip rate, locking degree, and slip deficit. The results show that the Qinghai Nanshan fault slip rate is characterized by sinistral and convergent movement. Both the sinistral and convergent rates display a decreasing trend from west to east. The locking degree and slip deficit are higher in the western segment (with an average of about 0.74 and 1.1 mm/a) and lower in the eastern segment. Then, we construct a strain rate field using GPS observations to analyze the regional strain characteristics. The results indicate that along the fault, the western segment shows a larger shear strain rate and negative dilation rate. Regional earthquake records show that the frequency of earthquakes is lower near the fault. The joint results suggest that the western segment may have a higher earthquake risk. In addition, the insignificant fault slip rate in the eastern segment may indicate that it does not participate in the tectonic transformation among the Riyueshan, Lajishan, and West Qinling faults.

The application of biofertilizers is becoming an inevitable trend to substitute chemical fertilizers for sustainable agriculture. To better understand the development of biofertilizers from 1980 to 2022, we used bibliometric mining to analyze 12,880 journal articles related to biofertilizer. The network cooccurrence analysis suggested that the biofertilizers research can be separated into three stages. The first stage (1980–2005) focused on nitrogen fixation. The second stage (2006–2015) concentrated on the mechanisms for increasing plant yield. The third stage (2016–2022) was the application of biofertilizers to improve the soil environment. The keyword analysis revealed the mechanisms of biofertilizers to improve plant-growth: biofertilizers can impact the nutritional status of plants, regulate plant hormones, and improve soil environments and the microbiome. The bacteria use as biofertilizers, included Pseudomonas, Azospirillum, and Bacillus, were also identified through bibliometric mining. These findings provide critical discernment to aid further study of biofertilizers for sustainable agriculture.

Abstract Optimum irrigation scheduling is important for ensuring high yield and water productivity in substrate-cultivated vegetables and is determined based on information such as substrate water content, meteorological parameters, and crop growth. The aim of this study was to determine a precise irrigation schedule for coconut coir culture in a solar greenhouse by comparing the irrigation, evapotranspiration (ET), substrate water content (VWC), as well as the crop growth indices and yield of cucumber, and irrigation water productivity (IWP) under three irrigation schedules: the soil moisture sensor-based method (T-VWC), the accumulated radiation combined with soil moisture sensor-based method (Rn-VWC), and the crop evapotranspiration estimated method using the hourly PM-ETo equation with an improved calculation of Kc (T-ETc). The results showed that the daily irrigation and evapotranspiration amount were the highest under T-VWC treatment, while the lowest under T-ETc treatment. In different meteorological environments, the change in irrigation amount was more consistent with the ET,and the VWC was relatively stable in T-ETc treatment compared with that under T-VWC or Rn-VWC treatments. The plant height, leaves number, leaf area, and stem diameter of T-VWC and Rn-VWC treatments were higher than those of the T-ETc treatments, but there was no significant difference in cucumber yield. Compared with the T-VWC treatment, total irrigation amount under Rn-VWC and T-ETc treatments significantly decreased by 25.75% and 34.04%, respectively ( $$\hbox {P}

Sea surface temperature (SST) prediction plays an important role in ocean-related fields. Therefore, it is increasingly important to be able to make more accurate prediction of SST. In this article, we develop a deep generative adversarial network (DGAN) for generating future maps of SSTs, providing a visual method of predicting SSTs. Our DGAN model consists of a generator and a discriminator. The generator is designed to produce more realistic maps of future SSTs, which uses multiple composite layers to capture the changes of SSTs and generates clear maps of future SSTs. The discriminator uses the structure of patchGAN to obtain more SST features, and distinguishes between real and generated SST maps. In addition, we improve the loss function and perform convergence analysis, and then, obtain that minimizing the loss function is equivalent to minimizing Pearson $\chi 2$ divergence, and the relevant explanations are carried out through experiments. The generator and discriminator are training adversarially during the training stage, eventually reaching a relatively balanced state, and the DGAN is able to produce more reliable visual predictions. Finally, the effectiveness of the DGAN in the prediction of SST is verified experimentally, and it is compared with the generative model-DL model and the long short-term memory-GAN model.

Typhoons' rapid variation makes effective hazard prevention difficult, which remains a challenging research topic requiring novel observation technology and analysis methodology. We developed an automatic methodology for mining the information on the rapid variation of typhoon cloud-top motion from high-spatial-temporal-resolution satellite cloud images, which has steps of estimating and decomposing the typhoon cloud-top motion, locating the typhoon cloud-top center, and analyzing the motion and center position variations. The Gaofen-4 satellite acquired 50-m-1-min-resolution cloud images of Typhoon Megi's (2016) landfall over mountainous Taiwan Island. The data provide an excellent chance to explore what such high-spatial-temporal-resolution successive observations can tell about the cloud-top motion variation of a typhoon landfall using the methodology. Before its landfall, Typhoon Megi's cloud-top center dramatically increased the northwestward migration speed from ∼22 to ∼58 km/h in only ∼2.5 h. It also presented small-scale oscillation along its migration path with a 1.6-to-2.4-km amplitude, a 31-to-33-km spatial period, and a 1.46-to-1.48-h temporal period. We averaged the motion speeds (velocity magnitudes) in each motion field to assess the field strength. The so-calculated cloud-top average rotation speed of Typhoon Megi decreased quickly during landfall. Meanwhile, its average divergence speed increased dramatically by ∼30% in a short period of ∼2.5 h, reaching ∼2 times the rotation speed. This result means that Megi's cloud-top motion rapidly changed from a typical rotation motion-dominated status to a divergence motion-dominated status. This rapid transformation from typical rotation motion dominance to divergence motion dominance implies intense upward warm and moist airflows that cause severe precipitation.

Remote-sensing ship monitoring is a crucial area of research with key applications in military and civilian fields. The ability to extract information, such as ship length, width, and heading from remote-sensing data, particularly from synthetic aperture radar (SAR) images, is of paramount importance. Current state-of-the-art SAR image ship monitoring focuses primarily on ship detection. Assessing the direction of ships usually relies on the observability of wake features. However, the observability of these wake features is often affected by factors, such as the SAR system parameters, ship attributes, and dynamic marine environments. This can make accurate direction assessments a challenging task. In response to these challenges, this study has presented a novel and effective algorithm for ship monitoring from SAR images based on an anchor-free framework and the powerful feature extraction capabilities of convolutional neural networks. The proposed method learned the scattering and morphological information of a ship's bow and stern from high-resolution SAR images to determine the ship's direction with a high level of accuracy using a rotating bounding box. The algorithm was tested on a dataset, achieving an average precision of 90.8% and bow classification accuracy of 92.5%, demonstrating its potential contributing to the advancement of remote sensing.

A theoretical model for the micro-texture on the inner wall of the stator rubber in screw pumps was developed. The finite element analysis method was employed. The pressure and streamline distributions for warhead-type, concentric circle-type, and multilayer rectangular-type textured surfaces were calculated. The effects of textured morphology, groove depth, groove width, and other parameters on the lubrication field were systematically investigated and analyzed. A nanosecond laser was employed to process the textured rubber surface of the stator in the screw pump. Subsequently, a micro-texture friction performance test was conducted on the rubber surface of the stator in actual complex well fluids from shale oil wells. Given the results of the simulation analysis and experimental tests, the lubrication characteristics of textured rubber surfaces with varying texture morphologies, rotational speeds, and mating loads were revealed. Furthermore, it indicated that the irregular symmetric warhead-type micro-texture exhibited excellent dynamic pressure lubrication performance compared with concentric circle-type and multilayer rectangular-type textures. The irregular symmetry enhanced the dynamic pressure lubrication effect, enhanced the additional net load-bearing capacity of the oil film surface, and reduced friction. As the groove depth increased, the volume and number of vortices within the groove also increased. The fluid kinetic energy was transformed into vortex energy, leading to a reduction in wall stress on the surface of the oil film, thereby affecting its bearing capacity. Initially, the maximum pressure on the wall surface of the oil film increased and then decreased. The optimal dynamic pressure lubrication effect was achieved with a warhead-type texture size of 3 mm, a groove width of 0.2 mm, and a groove depth of 0.1 mm. Well-designed texture morphology and depth parameters significantly enhanced the oil film-bearing capacity of the stator rubber surface, improving the dynamic pressure lubrication effect, and consequently extending the service life of the stator–rotor interface in the screw pump.

Aiming to address errors in the estimation of the position and attitude of an unmanned vessel, especially during vibration, where the rapid loss of feature point information hinders continuous attitude estimation and global trajectory mapping, this paper improves the monocular ORB-SLAM framework based on the characteristics of the marine environment. In general, we extract the location area of the artificial sea target in the video, build a virtual feature set for it, and filter the background features. When shaking occurs, GNSS information is combined and the target feature set is used to complete the map reconstruction task. Specifically, firstly, the sea target area of interest is detected by YOLOv5, and the feature extraction and matching method is optimized in the front-end tracking stage to adapt to the sea environment. In the key frame selection and local map optimization stage, the characteristics of the feature set are improved to further improve the positioning accuracy, to provide more accurate position and attitude information about the unmanned platform. We use GNSS information to provide the scale and world coordinates for the map. Finally, the target distance is measured by the beam ranging method. In this paper, marine unmanned platform data, GNSS, and AIS position data are autonomously collected, and experiments are carried out using the proposed marine ranging system. Experimental results show that the maximum measurement error of this method is 9.2%, and the average error is 4.7%.

Abstract Rainbands are essential to tropical cyclones (TCs), significantly affecting TC structure and intensity change. High‐resolution synthetic aperture radar (SAR) imagery can capture the footprints of rainbands caused by rain‐induced sea surface roughness modification. Using 464 SAR TC images, we investigated the rainband‐occurrence probability of TCs under different hemispheres, local times (LTs), intensities, and ocean basins. Results show that the rainband‐occurrence probability is highest in the downshear‐left quadrant for Northern Hemisphere TCs (downshear‐right quadrant for Southern Hemisphere TCs). For Northern Hemisphere TCs, the rainband‐occurrence probability is overall higher in the early morning (LT), and the peak region of rainband‐occurrence probability appears farther from the TC center in the evening (LT). Compared with weak TCs, the rainband‐occurrence probability becomes higher for strong TCs in the Northern Hemisphere. Furthermore, TCs have a higher rainband‐occurrence probability in the Northwest Pacific than in the North Atlantic and Northeast Pacific.

The cultivation of largemouth bass (Micropterus salmoides), a species of significant economic value in aquaculture, has experienced notable growth recently. However, the deterioration of water quality seriously affects the metabolic responses of M. salmoides. While compound microbial agent (CMA) is widely utilized for ecological rehabilitation and water filtration, its application in M. salmoides has not been reported. Here, based on physio-biochemical tests and 16S rRNA sequencing, we investigated the effects of CMA (yeast, Bacillus subtilis, and lactic acid bacteria) on the water quality within the recirculating aquaculture system, along with physiological indices and gut microbiota of M. salmoides. Compared to the control and single microbial agent (yeast), CMA treatment improved the water quality by improving the dissolved oxygen and delaying the increase of pH, total nitrogen, total phosphorus, ammonia nitrogen, and nitrite. The 16s rRNA gene sequencing revealed that the water treated with CMA exhibited elevated levels of chao1, Shannon, Pd, and a larger population of dominant bacterial. Besides, higher values of ACE, chao1, Shannon, and OTU level, and lower Simpson index were found in CMA treated M. salmoides samples, suggesting that CMA treatment enhanced the species richness and diversity of gut microbiota of M. salmoides. Furthermore, CMA treatment hindered the generation and proliferation of harmful bacteria, such as the Mycoplasma mobile 163K species and the Erysipelotrichaceae family, which was associated with enhanced antioxidant enzymatic activity and decreased MDA level in both the serum and liver. These findings shed light on the essential roles of CMA in M. salmoides culturing and introduce an innovative approach to enhance the aquatic environment.

BackgroundThe current survival prediction methodologies for primary bone lymphoma (PBL) of the spine are deficient. This study represents the inaugural utilization of conditional survival (CS) to assess the outcome of this disease. Moreover, our objective was to devise a CS-based nomogram for predicting overall survival (OS) in real-time for spinal PBL.MethodsPatients with PBL of the spine diagnosed between January 2000 and December 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The OS was determined through the Kaplan–Meier method. The CS characteristic of patients with spinal PBL was delineated, with the CS being estimated utilizing the formula: CS(α|β) = OS(α+β)/OS(β). CS(α|β) denotes the probability of additional α-year survivorship, assuming the patient has already survived β years after the time of observation. Three methods including univariate Cox regression, best subset regression (BSR) and the least absolute shrinkage and selection operator (LASSO) regression were used to identify predictors for CS-based nomogram construction.ResultsKaplan-Meier analysis was executed to determine the OS rate for these patients, revealing a survival rate of 68% and subsequently 63% at the 3-year and 5-year mark respectively. We then investigated the CS patterning exhibited by these patients and discovered the survival of PBL in the spine progressively improved with time. Meanwhile, through three different prognostic factor selection methods, we identified the best predicter subset including age, tumor histology, tumor stage, chemotherapy and marital status, for survival prediction model construction. Finally, we successfully established and validated a novel CS-based nomogram model for real-time and dynamic survival estimation. Moreover, we further designed a risk stratification system to facilitate the identification of high-risk patients.ConclusionsThis is the first study to analyze the CS pattern of PBL of the spine. And we have also developed a CS-based nomogram that provide dynamic prognostic data in real-time, thereby aiding in the formulation of personalized treatment strategies in clinical practice.

Abstract Background The effectiveness and safety of neoadjuvant PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors is controversial. This systematic review and meta-analysis aimed to evaluate the efficacy and safety of PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors as neoadjuvant therapy for malignant solid tumors. Methods This study has been registered with the number CRD42023407275 on PROSPERO. Systematic searches were conducted in PubMed, Embase, Web of Science and Cochrane Library databases until March 17, 2023. In addition, manual searches were performed. The inclusion criteria encompassed randomized controlled trials (RCTs) that assessed the utilization of neoadjuvant PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors PD-1/PD-L1 inhibitors for patients with solid malignancies. The Cochrane Collaboration's tool for assessing risk of bias in randomized trials (ROB1) were used. Risk ratios (RRs), hazared ratios (HRs) and their respective 95% confidence intervals were calculated using Stata17.0 MP and Review Manager 5.4 software. Results A total of 2780 records were identified, and ultimately 10 studies involving 273 patients were included. The meta-analysis showed that the addition of CTLA-4 inhibitors to PD-1/PD-L1 inhibitors did not demonstrate a significant effect on overall response rate, main pathological response, pathological complete response, surgical resection, radical resection, overall survival, progression-free survival, recurrence-free survival, grade 3–4 adverse events, all-cause mortality, and completed treatment (P > 0.05). However, further subgroup analysis indicated that the combination of PD-1 with CTLA-4 inhibitors significantly increased the occurrence of grade 3–4 adverse events in patients (P

Abstract Gadolinium (Gd3+)-coordinated texaphyrin (Gd-Tex) is a promising radiosensitizer that entered clinical trials, but temporarily fails largely due to insufficient radiosensitization efficacy. Little attention has been given to using nanovesicles to improve its efficacy. Herein, Gd-Tex is transformed into building blocks “Gd-Tex-lipids” to self-assemble nanovesicles called Gd-nanotexaphyrins (Gd-NTs), realizing high density packing of Gd-Tex in a single nanovesicle and achieving high Gd-Tex accumulation in tumors. To elucidate the impact of O2 concentration on Gd-Tex radiosensitization, myoglobin (Mb) is loaded into Gd-NTs (Mb@Gd-NTs), resulting in efficient relief of tumor hypoxia and significant enhancement of Gd-Tex radiosensitization, eventually inducing the obvious long-term antitumor immune memory to inhibit tumor recurrence. In addition to Gd3+, the versatile Mb@Gd-NTs can also chelate 177Lu3+ (Mb@177Lu/Gd-NTs), enabling SPECT/MRI dual-modality imaging for accurately monitoring drug delivery in real-time. This “one-for-all” nanoplatform with the capability of chelating various trivalent metal ions exhibits broad clinical application prospects in imaging-guided radiosensitization therapy.

Oceanic internal waves are an active ocean phenomenon that can be observed, and their relevant characteristics can be acquired using synthetic aperture radar (SAR). The locations of oceanic internal waves must be determined first to obtain the important parameters of oceanic internal waves from SAR images. An oceanic internal wave segmentation method with integrated light and dark stripes was described in this study. To extract the SAR image characteristics of oceanic internal waves, the Gabor transform was initially used, and then the K-means clustering algorithm was used to separate the light (dark) stripes of oceanic internal waves from the background in the SAR images. The regions of the dark (light) stripes were automatically determined based on the differences between the three classes, that is, the dark stripes, light stripes, and background area. Finally, the locations of the dark (light) stripes were determined by shifting a given distance along the normal direction of the long side with the minimum bounding rectangle of the light (dark) stripes. The best segmentation results were obtained based on the intersection over the union of the images, and the accuracy of segmentation was verified. Furthermore, the effectiveness and practicability of the proposed method in the light and dark stripe segmentation of SAR images of oceanic internal waves were illustrated. The proposed method prepares the foundation for future inversion studies of oceanic internal waves.

In view of issues affecting manual on-demand sowing of spinach, such as high working intensity, low seeding efficiency, and high cost, a mechanized precision seeding device for spinach seeds is proposed, based on a spoon-wheel including a combined cell with two intersecting surfaces. The key structure was designed, and motion analysis was conducted employing SolidWorks software (2022). Additionally, the seeding process was simulated using EDEM simulation software (2022). The number of spoons, the radius of the spoons, and the speed of the seed wheel were chosen as the influencing factors, while the qualified index, reseeding index, and missing index were utilized as the evaluation indexes. A response surface method test based on the Box–Behnken design was carried out, and the test results were analyzed to obtain the optimal parameter combination for the seed-metering device. The field test results showed that when the rotation speed was 18 rpm, the radius of each seed spoon was 2.5 mm, and the number of seed spoons was 50, the average qualified index was 90.89%, the reseeding index was 8.22%, and the missed seeding index was 0.89%. The test results satisfy the technical production requirements for spinach seed sowing.

Research on evapotranspiration and its drivers in the Aksu River Basin from the perspectives of climate change and land use is of great significance for promoting the efficient use and precise allocation of its water resources. Theil-Sen median trend analysis (T-S) and the Mann–Kendall nonparametric test (M-K), in addition to correlation analysis, partial correlation analysis, complex correlation analysis, and driving-factor zoning principles, were used to examine the characteristics of the spatiotemporal changes in evapotranspiration and to explore the driving mechanism of the changes in evapotranspiration. The results indicated that the range of fluctuations in the multiyear average evapotranspiration in the Aksu River Basin from 2001 to 2020 was between 481.58 and 772.37 mm/a, which showed the spatial distribution characteristics of being high in the west and central part of the basin, and low in the north and south of the basin. The positive correlation between evapotranspiration and precipitation was stronger, and the negative correlations with temperature and relative humidity were stronger. The change in evapotranspiration in cultivated land is mainly driven by precipitation and relative humidity × precipitation; for grassland, the main drivers were relative humidity and precipitation × relative humidity; for woodland, the main drivers were relative humidity and other climatic factors; and for other land types, the main drivers were other climatic factors.

In this study, wind speed sensitivity and calibration bias were first determined for Surface Water and Ocean Topography (SWOT) satellite Ka-band Radar Interferometer (KaRIn) Normalized Radar Backscatter Cross Section (NRCS) data at VV and HH polarizations. Here, the calibration bias was estimated by comparing the KaRIn NRCS with collocated simulations from a model developed using Global Precipitation Measurement (GPM) satellite Dual-frequency Precipitation Radar (DPR) data. To recalibrate the bias, the correlation coefficient between the KaRIn data and the simulations was estimated, and the data with the corresponding top 10% correlation coefficients were used to estimate the recalibration coefficients. After recalibration, a Ka-band NRCS model was developed from the KaRIn data to retrieve ocean surface wind speeds. Finally, wind speed retrievals were evaluated using the collocated European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis winds, Haiyang-2C scatterometer (HY2C-SCAT) winds and National Data Buoy Center (NDBC) and Tropical Atmosphere Ocean (TAO) buoy winds. Evaluation results show that the Root Mean Square Error (RMSE) at both polarizations is less than 1.52 m/s, 1.34 m/s and 1.57 m/s, respectively, when compared to ECMWF, HY2C-SCAT and buoy collocated winds. Moreover, both the bias and RMSE were constant with the incidence angles and polarizations. This indicates that the winds from the SWOT KaRIn data are capable of correcting the sea state bias for sea surface height products.

AIM: To investigate the effect of orthokeratology lens on ocular surface and meibomian gland in children and adolescents of different ages.METHODS: A total of 120 cases(240 eyes)of myopic children and adolescents treated in the optometry clinic of our hospital from December 2020 to February 2021 were retrospectively selected, and they were divided into the orthokeratology group(60 cases, 120 eyes)and the frame glasses group(60 cases, 120 eyes)according to the myopia correction methods. The changes in ocular surface and meibomian gland after wearing glasses were analyzed, and those changes in patients of different ages were compared between the two groups.RESULTS: Corneal curvature decreased, non-invasive tear film break-up time(NIBUT)shortened and meibomian gland score increased at 3, 6, 9 and 12mo in the orthokeratology group after wearing lens, while lower tear meniscus height increased at 6, 9 and 12mo compared with that before wearing lens. In the frame glasses group, the lower tear meniscus height was higher at 6 and 9mo than that before wearing glasses(both P

Background/purpose: With the wide application of X-rays in dental examinations, it is necessary to assess its potential risk and explore an effective indicator. This study aimed to analyze the response of miR-187-5p to X-ray irradiation and to evaluate its potential of predicting X-ray potential dangers. Materials and methods: Patients that had to receive dental X-ray examination were enrolled and the expression of miR-187-5p in the buccal mucosa swabs were detected by real-time quantitative polymerase chain reaction (PCR). The effect of miR-187-5p on fibrotic buccal mucosal fibroblasts (fBMFs) activities was assessed by cell migration and invasion and the expression of fibrosis markers. In mechanism, the interaction between miR-187-5p and DKK2 and their co-regulatory effects were also estimated. Results: Significant upregulation of miR-187-5p was observed in the patients who received over twice X-ray irradiation. miR-187-5p was found to regulate the luciferase and expression level of DKK2 in fBMFs. Moreover, miR-187-5p knockdown dramatically suppressed the migration and invasion of fBMFs and inhibited the expression of α-SMA, collagen I, and collagen II, three typical fibrosis markers. Silencing could reverse the inhibitory effect of miR-187-5p knockdown on fBMFs activities. Conclusion: Accumulated X-ray irradiation could induce miR-187-5p upregulation, which could regulate the fBMFs activities via modulating DKK2. miR-187-5p could serve as an indicator of X-ray examination dangers to prevent the potential risk during the accumulated application of X-ray irradiation in the dental examination.

The fragility curve expresses the probability that an asset exceeds some serviceability state for a given level of environmental perturbation or other loadings. It is an important component in the quantitative risk analysis and resilience evaluation of infrastructure exposed to natural hazards. Incidences of over-settlement of embankments are increasingly reported due to more intense and longer-duration rainfall events. This paper develops fragility curves for the rainfall-induced embankment settlement. For this purpose, an embankment incorporating enhanced seepage and displacement analysis within unsaturated soil conditions is modelled based on a reported case history. A Monte Carlo simulation is used for rainfall infiltration and embankment deformation analysis under various rainfall scenarios. Probability values are obtained to achieve three levels of damage states in terms of road embankment settlement. The parametric analysis produces the exceedance probability curves for various rainfall intensities, saturated permeabilities and embankment slope angles. This work offers an efficient tool for assessing fragility to rainfall-induced excessive settlement of embankments.

Abstract For centuries, humans have never stopped exploring the nature of light and manipulating it, since light carries multiple information through its intrinsic wave‐particle dualism, including wavelength, amplitude, phase, polarization, spin/orbital angular momentum, etc., which determines the physical language and basic manners we perceive the objective world. Conventional optical devices, such as lenses, prisms, and lasers, are composed of solid elements that are bulky, making it difficult to manipulate light dynamically with multiple degrees‐of‐freedom. Comparatively, some responsive soft matters, especially represented by liquid crystals (LCs), possess distinctive orientational order and spontaneous self‐assembled superstructures, enabling the digital programming of microstructures and multiple degrees‐of‐freedom manipulation of their optical characteristics. The optical manipulation based on these soft superstructures, that is, the “soft‐matter‐photonics”, is playing an impressive role in integrated functional devices, especially in the present age of information explosion. Herein, we review the latest advances, respectively, in the microstructure configurations, multiple degrees‐of‐freedom manipulations, and the relevant prospective applications. Additionally, scientific issues and technical challenges that hinder the programing operation and optical manipulations are discussed. Toward a four‐dimensional optical manipulation of soft condensed matter, this review may have wide implications on a variety of applications, including the integrated fabrication of compact elements, multi‐channel information processing and high‐capacity optical communications.

Antimicrobial photodynamic therapy (aPDT) is an alternative to antibiotics that has potential for the treatment of chronic skin wounds, but requires improved, highly selective photosensitizer systems. Rhenium (Re)‐complex‐ and iridium (Ir)‐complex‐based phospholipid conjugates, as PDT‐functional building blocks for liposomes, are presented, and varying structural components and proportion of compounds are explored, including adjusting the cholesterol and polyethylene glycol (PEG)‐lipid contents, incorporating ethylenediaminetetraacetic acid (EDTA)‐lipid, and introducing the cationic lipid 1,2‐dioleoyl‐3‐trimethylammonium propane (DOTAP) to enhance their efficacy and selectivity in aPDT. Ir/Re‐liposomes have nanostructurally enhanced photoactivity compared to monomeric Ir/Re‐lipids. Ir‐liposomes exhibit stronger light absorption and higher emission generation (>threefold) than Re‐liposomes, resulting in superior efficacy against Staphylococcus aureus while maintaining better tolerability toward host cells. Formulations with higher cholesterol (40 mol%) and PEG‐lipid (5%) content demonstrate increased potency against S. aureus. The incorporation of EDTA‐lipid significantly enhances aPDT efficacy but also increases toxicity toward host cells. Incorporation of DOTAP alters the nanoparticles’ surface charge, potentially improving their interaction with bacterial walls, but negatively impacts their stability, leading to aggregation of the nanoparticles. Ir‐HC demonstrates ideal characteristics (effectiveness, selectivity, and stability) for aPDT under the tested conditions, indicating the importance of the structural design of Re‐ and Ir‐complex liposomes for their selectivity in aPDT.

BackgroundThis study aimed to investigate the therapeutic efficacy and safety of Traditional medicine preparations (TMPs) given in combination with vascular endothelial growth factor receptor (VEGFR)-associated multi-targeted tyrosine kinase inhibitors (TKIs) for the treatment of middle to advanced-stage primary liver cancer (PLC).MethodsThis systematic literature survey employed 10 electronic databases and 2 clinical trial registration platforms to identify relevant studies on the use of TMPs + VEGFR-TKIs to treat patients with middle-advanced PLC. Furthermore, a meta-analysis was performed following the PRISMA guidelines using the risk ratio (RR) at 95% confidence intervals (CI) or standardized mean difference as effect measures.ResultsA total of 26 studies comprising 1678 middle-advanced PLC patients were selected. The meta-analysis revealed that compared with VEGFR-TKI mono-treatment, the co-therapy of TMPs + VEGFR-TKIs considerably enhanced the objective response rate (RR = 1.49, 95% CI: 1.31-1.69), disease control rate (RR = 1.23, 95% CI: 1.16-1.30), and one-year overall survival (RR = 1.49, 95% CI: 1.28-1.74). Furthermore, the co-therapy was associated with reduced incidences of liver dysfunction (RR = 0.64, 95% CI: 0.45-0.91), proteinuria (RR = 0.43, 95% CI: 0.24-0.75), hypertension (RR = 0.66, 95% CI: 0.53-0.83), hand-foot skin reactions (RR = 0.63, 95% CI: 0.49-0.80), myelosuppression (RR = 0.63, 95% CI: 0.46-0.87), and gastrointestinal reactions (RR = 0.64, 95% CI: 0.45-0.92). Moreover, the co-therapy indicated no increase in the incidences of rash and fatigue.ConclusionThis systematic analysis revealed that co-therapy with TMPs + VEGFR-TKIs has a higher effectiveness and safety profile for treating middle-advanced PLC patients. However, further validation using randomized control trials is required.Prospero registration noCRD42022350634.

In this article, we study the trajectory planning and tracking control of a bionic underwater robot under multiple dynamic obstacles. We first introduce the design of the bionic leopard cabinet underwater robot developed in our lab. Then, we model the trajectory planning problem of the bionic underwater robot by combining its dynamics and physical constraints. Furthermore, we conduct global trajectory planning for bionic underwater robots based on the temporal-spatial Bezier curves. In addition, based on the improved proximal policy optimization, local dynamic obstacle avoidance trajectory replanning is carried out. In addition, we design the fuzzy proportional-integral-derivative controller for tracking control of the planned trajectory. Finally, the effectiveness of the real-time trajectory planning and tracking control method is verified by comparative simulation in dynamic environment and semiphysical simulation of UWSim. Among them, the real-time trajectory planning method has advantages in trajectory length, trajectory smoothness, and planning time. The error of trajectory tracking control method is controlled around 0.2 m.

Abstract Microbubble‐enabled focused ultrasound (MB‐FUS) has revolutionized nano and molecular drug delivery capabilities. Yet, the absence of longitudinal, systematic, quantitative studies of microbubble shell pharmacokinetics hinders progress within the MB‐FUS field. Microbubble radiolabeling challenges contribute to this void. This barrier is overcome by developing a one‐pot, purification‐free copper chelation protocol able to stably radiolabel diverse porphyrin‐lipid‐containing Definity® analogues (pDefs) with >95% efficiency while maintaining microbubble physicochemical properties. Five tri‐modal (ultrasound‐, positron emission tomography (PET)‐, and fluorescent‐active) [64Cu]Cu‐pDefs are created with varying lipid acyl chain length and charge, representing the most prevalently studied microbubble compositions. In vitro, C16 chain length microbubbles yield 2–3x smaller nanoprogeny than C18 microbubbles post FUS. In vivo, [64Cu]Cu‐pDefs are tracked in healthy and 4T1 tumor‐bearing mice ± FUS over 48 h qualitatively through fluorescence imaging (to characterize particle disruption) and quantitatively through PET and γ‐counting. These studies reveal the impact of microbubble composition and FUS on microbubble dissolution rates, shell circulation, off‐target tissue retention (predominantly the liver and spleen), and FUS enhancement of tumor delivery. These findings yield pharmacokinetic microbubble structure‐activity relationships that disrupt conventional knowledge, the implications of which on MB‐FUS platform design, safety, and nanomedicine delivery are discussed.

This paper investigates a method for precise mapping of human arm movements using sEMG signals. A multi-channel approach captures the sEMG signals, which, combined with the accurately calculated joint angles from an Inertial Measurement Unit, allows for action recognition and mapping through deep learning algorithms. Firstly, signal acquisition and processing were carried out, which involved acquiring data from various movements (hand gestures, single-degree-of-freedom joint movements, and continuous joint actions) and sensor placement. Then, interference signals were filtered out through filters, and the signals were preprocessed using normalization and moving averages to obtain sEMG signals with obvious features. Additionally, this paper constructs a hybrid network model, combining Convolutional Neural Networks and Artificial Neural Networks, and employs a multi-feature fusion algorithm to enhance the accuracy of gesture recognition. Furthermore, a nonlinear fitting between sEMG signals and joint angles was established based on a backpropagation neural network, incorporating momentum term and adaptive learning rate adjustments. Finally, based on the gesture recognition and joint angle prediction model, prosthetic arm control experiments were conducted, achieving highly accurate arm movement prediction and execution. This paper not only validates the potential application of sEMG signals in the precise control of robotic arms but also lays a solid foundation for the development of more intuitive and responsive prostheses and assistive devices.

Studying the intrinsic properties of concrete is essential for addressing various aspects of concrete structure design, material selection, and sustainability. In this study, a suspended strong magnetic torsion balance device was designed and constructed to investigate the ferromagnetic properties of concrete specimens and their constituent materials. It was found that sand and cement generally exhibit ferromagnetic properties, while aggregates do not possess ferromagnetic properties. Analysis using powder X-ray diffraction (XRD) and chemical experiments confirmed that the ferromagnetic material in sand and cement is elemental iron. A simplified calculation formula for the magnetic force between concrete specimens and an external magnetic field was derived. Three sets of specimens were designed and fabricated for experimental exploration of ferromagnetic properties and magnetic force measurements. The experimental results demonstrate that plain concrete possesses measurable ferromagnetic properties. The magnetic force of concrete initially experiences a rapid decay followed by a gradual leveling off as the distance (from the magnetic field source to the concrete surface) increases. The decay rate approximately follows a fourth-power relationship with distance. Under a loading condition with an applied magnetic field intensity of 0.2 T, the optimal measurement range for ferromagnetic force in concrete is between 0.02 m and 0.05 m.

Despite the substantial burden posed by osteoarthritis (OA) globally, difficult challenges remain in achieving early OA diagnosis and adopting effective disease-modifying treatments. In this study, we use a biomolecular approach to address these limitations by creating an inherently theranostic molecular beacon whose imaging and therapeutic capabilities are activated by early pathological changes in OA. This platform comprised (1) a peptide linker substrate for metalloproteinase-13 (MMP-13), a pathological protease upregulated in OA, which was conjugated to (2) a porphyrin moiety with inherent multimodal imaging, photodynamic therapy, and drug delivery capabilities, and (3) a quencher that silences the porphyrin’s endogenous fluorescence and photoreactivity when the beacon is intact. In diseased OA tissue with upregulated MMP-13 expression, this porphyrin molecular beacon (PPMMP13B) was expected to undergo sequence-specific cleavage, yielding porphyrin fragments with restored fluorescence and photoreactivity that could, respectively, be used as a readout of MMP-13 activity within the joint for early OA imaging and disease-targeted photodynamic therapy. This study focused on the synthesis and characterization of PPMMP13B, followed by a proof-of-concept evaluation of its OA imaging and drug delivery potential. In solution, PPMMP13B demonstrated 90% photoactivity quenching in its intact form and robust MMP-13 activation, yielding a 13-fold increase in fluorescence post-cleavage. In vitro, PPMMP13B was readily uptaken and activated in an MMP-13 cell expression-dependent manner in primary OA synoviocytes without exuding significant cytotoxicity. This translated into effective intra-articular cartilage (to a 50 μm depth) and synovial uptake and activation of PPMMP13B in a destabilization of the medial meniscus OA mouse model, yielding strong fluorescence contrast (7-fold higher signal than background) at the diseased joint site. These results provide the foundation for further exploration of porphyrin molecular beacons for image-guided OA disease stratification, effective articular delivery of disease-modify agents, and OA photodynamic therapy.

Sea surface temperature (SST) is an important parameter for monitoring ocean phenomena. Driven by ocean satellite Big Data, deep neural networks have achieved state-of-the-art performance in forecasting fields of oceanic phenomena. However, when there are some changes in the data set, the performance of these models drops significantly. In order to address this issue, this article develops a robust strong stability-preserving generative adversarial network model (SSPGAN) to forecast SST. The main objective of this article is to continue to produce accurate SST predictions even in the presence of minor data perturbations. The SSPGAN consists of a generator of a deep learning model and a strong stability preserving discriminator. The generator aims to generate SST that are close to the future true SST using SST from the past. The discriminator simultaneously tries to tell the generated SST apart from the real SST. The robust of the discriminator and the overall model is enhanced by the strong stability preserving network. Experiments confirm the SSPGAN's accuracy and robust for predicting SST in the presence of small data perturbations. In this study, we employ the Wasserstein metric to quantify the gap between the actual SST distribution and the generated SST with a perturbation. In addition, this article also analyzes the robust conditions of the deep neural network when the data are disturbed.

Hepatocellular carcinoma (HCC) represents a high-fatality cancer with a 5-year survival of 22%. The Wnt/β-catenin signaling pathway presents as one of the most upregulated pathways in HCC. However, it has so far not been targetable in the clinical setting. Therefore, studying new targets of this signaling cascade from a therapeutic aspect could enable reversal, delay, or prevention of hepatocarcinogenesis. Although enormous advancement has been achieved in HCC research and its therapeutic management, since HCC often occurs in the context of other liver diseases such as cirrhosis leading to liver dysfunction and/or impaired drug metabolism, the current therapies face the challenge of safely and effectively delivering drugs to the HCC tumor site. In this review, we discuss how a targeted nano drug delivery system could help minimize the off-target toxicities of conventional HCC therapies as well as enhance treatment efficacy. We also put forward the current challenges in HCC nanomedicine along with some potential therapeutic targets from the Wnt/β-catenin signaling pathway that could be used for HCC therapy. Overall, this review will provide an insight to the current advances, limitations and how HCC nanomedicine could change the landscape of some of the undruggable targets in the Wnt/β-catenin pathway.

Abstract Sirtuins (SIRTs) are nicotine adenine dinucleotide(+)-dependent histone deacetylases regulating critical signaling pathways in prokaryotes and eukaryotes, and are involved in numerous biological processes. Currently, seven mammalian homologs of yeast Sir2 named SIRT1 to SIRT7 have been identified. Increasing evidence has suggested the vital roles of seven members of the SIRT family in health and disease conditions. Notably, this protein family plays a variety of important roles in cellular biology such as inflammation, metabolism, oxidative stress, and apoptosis, etc., thus, it is considered a potential therapeutic target for different kinds of pathologies including cancer, cardiovascular disease, respiratory disease, and other conditions. Moreover, identification of SIRT modulators and exploring the functions of these different modulators have prompted increased efforts to discover new small molecules, which can modify SIRT activity. Furthermore, several randomized controlled trials have indicated that different interventions might affect the expression of SIRT protein in human samples, and supplementation of SIRT modulators might have diverse impact on physiological function in different participants. In this review, we introduce the history and structure of the SIRT protein family, discuss the molecular mechanisms and biological functions of seven members of the SIRT protein family, elaborate on the regulatory roles of SIRTs in human disease, summarize SIRT inhibitors and activators, and review related clinical studies.

Abstract Background Glucocorticoids (GCs) overuse is associated with decreased bone mass and osseous vasculature destruction, leading to severe osteoporosis. Platelet lysates (PL) as a pool of growth factors (GFs) were widely used in local bone repair by its potent pro-regeneration and pro-angiogenesis. However, it is still seldom applied for treating systemic osteopathia due to the lack of a suitable delivery strategy. The non-targeted distribution of GFs might cause tumorigenesis in other organs. Results In this study, PL-derived exosomes (PL-exo) were isolated to enrich the platelet-derived GFs, followed by conjugating with alendronate (ALN) grafted PEGylated phospholipid (DSPE-PEG-ALN) to establish a bone-targeting PL-exo (PL-exo-ALN). The in vitro hydroxyapatite binding affinity and in vivo bone targeting aggregation of PL-exo were significantly enhanced after ALN modification. Besides directly modulating the osteogenic and angiogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) and endothelial progenitor cells (EPCs), respectively, PL-exo-ALN also facilitate their coupling under GCs’ stimulation. Additionally, intravenous injection of PL-exo-ALN could successfully rescue GCs induced osteoporosis (GIOP) in vivo. Conclusions PL-exo-ALN may be utilized as a novel nanoplatform for precise infusion of GFs to bone sites and exerts promising therapeutic potential for GIOP. Graphical Abstract

This study tried to explore the ground movement induced by triple stacked tunneling (TST) with different construction sequences. A case study in Tianjin, China was used to investigate the ground movement during the TST (upper tunneling (UT)). For this, a modified Peck formula was proposed to predict the surface settlement induced by TST. Next, three sets of finite element analyses (FEA) were used to compare the effects of construction sequences (i.e. UT, middle tunneling (MT), and lower tunneling (LT)) on vertical and lateral ground displacements. The results of Tianjin case and UT reveal that compared to a Gaussian distribution for a single tunnel, the surface settlement curve of triple stacked tunnels is a bimodal distribution. It seems that the proposed modified Peck formula can effectively predict the surface settlement induced by TST. The results of the three sets of FEA demonstrate that the construction sequence has a significant influence on the ground movement. Among the three construction sequences, the largest lateral displacement is observed in the MT and the smallest one in UT. The existing tunnel has an inhibitory effect on the vertical displacement. The maximum value of the lateral displacement occurs at the depth of the new tunnel in each construction sequence.

The generation of entanglement and information distribution among macroscopic systems which are spatially separated are of paramount importance in the realm of quantum networks and quantum communication. In this paper, we propose a scheme that enables the preparation of long-distance entanglement between two magnons and controllable information transfer from a giant atom to either magnon, where the two magnons can be positioned symmetrically or asymmetrically in relation to a giant atom, and all of the magnons and the atom are coupled to a microwave cavity-array waveguide. By considering significant frequency detuning, we can virtually excite photons and establish an indirect interaction between the giant atom and the two magnons. Through the modulation of atom–waveguide coupling rates, we can not only evenly transfer atomic excitation to both magnons, thereby generating maximally entangled states, but also selectively transmit the atomic state to a single magnon. It is our hope that our proposed scheme will prove valuable in the field of quantum communications.

Hainan yellow cattle are indigenous Zebu cattle from southern China known for their tolerance of heat and strong resistance to disease. Generations of adaptation to the tropical environment of southern China and decades of artificial breeding have left identifiable selection signals in their genomic makeup. However, information on the selection signatures of Hainan yellow cattle is scarce. Herein, we compared the genomes of Hainan yellow cattle with those of Zebu, Qinchuan, Nanyang, and Yanbian cattle breeds by the composite likelihood ratio method (CLR), Tajima’s D method, and identifying runs of homozygosity (ROHs), each of which may provide evidence of the genes responsible for heat tolerance in Hainan yellow cattle. The results showed that 5210, 1972, and 1290 single nucleotide polymorphisms (SNPs) were screened by the CLR method, Tajima’s D method, and ROH method, respectively. A total of 453, 450, and 325 genes, respectively, were identified near these SNPs. These genes were significantly enriched in 65 Gene Ontology (GO) functional terms and 11 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (corrected p < 0.05). Five genes—Adenosylhomocysteinase-like 2, DnaJ heat shock protein family (Hsp40) member C3, heat shock protein family A (Hsp70) member 1A, CD53 molecule, and zinc finger and BTB domain containing 12—were recognized as candidate genes associated with heat tolerance. After further functional verification of these genes, the research results may benefit the understanding of the genetic mechanism of the heat tolerance in Hainan yellow cattle, which lay the foundation for subsequent studies on heat stress in this breed.