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Abstract Fail-safe design of devices requires robust integrity assessment procedures which are still absent for 2D materials, hence affecting transfer to applications. Here, a combined on-chip tension and cracking method, and associated data reduction scheme have been developed to determine the fracture toughness and strength of monolayer-monodomain-freestanding graphene. Myriads of specimens are generated providing statistical data. The crack arrest tests provide a definitive fracture toughness of 4.4 MPa $$\sqrt{{{{{{\rm{m}}}}}}}$$ m . Tension on-chip provides Young’s modulus of 950 GPa, fracture strain of 11%, and tensile strength up to 110 GPa, reaching a record of stored elastic energy ~6 GJ m−3 as confirmed by thermodynamics and quantized fracture mechanics. A ~ 1.4 nm crack size is often found responsible for graphene failure, connected to 5-7 pair defects. Micron-sized graphene membranes and smaller can be produced defect-free, and design rules can be based on 110 GPa strength. For larger areas, a fail-safe design should be based on a maximum 57 GPa strength.

Abstract Background Hypoxia-activated prodrugs present new opportunities for safe and effective tumor drug resistance therapy due to their high selectivity for hypoxic cells. However, the uneven distribution of oxygen in solid tumor and insufficient hypoxia in the tumor microenvironment greatly limit its therapeutic efficacy. Results In this paper, a novel AQ4N-Mn(II)@PDA coordination nanoplatform was designed and functionalized with GMBP1 to target drug-resistant tumor cells. Its excellent photothermal conversion efficiency could achieve local high-temperature photothermal therapy in tumors, which could not only effectively exacerbate tumor hypoxia and thus improve the efficacy of hypoxia-activated chemotherapy of AQ4N but also significantly accelerate Mn2+-mediated Fenton-like activity to enhance chemodynamic therapy. Moreover, real-time monitoring of blood oxygen saturation through photoacoustic imaging could reflect the hypoxic status of tumors during treatment. Furthermore, synergistic treatment effectively inhibited tumor growth and improved the survival rate of mice bearing orthotopic drug-resistant tumors. Conclusions This study not only provided a new idea for PTT combined with hypoxia-activated chemotherapy and CDT for drug-resistant tumors but also explored a vital theory for real-time monitoring of hypoxia during treatment.

Abstract Objective TQB3602 is a novel orally bioavailable proteasome inhibitor. This study is the first‐in‐human phase I clinical trial to evaluate the safety, tolerability, pharmacokinetics, and preliminary efficacy of TQB3602 in relapsed/refractory multiple myeloma (RRMM). Methods This is a multicenter phase I clinical trial consisting of the 3+3 dose‐escalation phase and dose expansion phase. Patients with MM who have received ≥2 prior antimyeloma therapies were enrolled. TQB3602 is administered at a dose of 0.5~7mg on days 1, 8, 15 in 28‐day cycle. Results Twenty‐five RRMM patients who relapsed or failed ≥2 lines of therapies were enrolled in the dose escalation phase. Two patients in the 7.0 mg dose group developed dose‐limiting toxicity events (one with grade 2 peripheral neuropathy [PN] complicated by pain and one with diarrhea and abdominal pain), leading to a maximum tolerated dose of 6.0 mg. Any‐grade adverse events (AEs) occurred in 24 (96.0%) patients, while grade ≥3 AEs occurred in 13 (52.0%). The most common grade ≥3 AEs was anemia (6, 24.0%). The incidence rate of PN was 16% with no grade ≥3 PN occurred. TQB3602 was rapidly absorbed, resulting in a time‐to‐plasma peak concentration of 0.8–1.5 h. The mean half‐life was approximately 82 h. The AUClast and Cmax were approximately 1.9 times higher on day 15 than on day 1. Among 22 response‐evaluable patients, 63.7% achieved stable disease or better. Conclusions TQB3602 is well tolerated, with a favorable neurotoxicity profile, and has shown preliminary efficacy in patients with RRMM. The anticipated therapeutic dose was 6 mg and was adopted for an ongoing dose‐expansion phase.

The motor temperature distribution characteristics help to understand the working condition of the unit, thus improving efficiency. Currently, the motors are gradually being used at high altitudes. However, the plateau region has low air pressure, thin air and large differences in humidity. There is a lack of research on the effect of its complex and special working environment on motor temperature. Therefore, in this study, the numerical analysis of the motor temperature field is carried out from the novel perspective of plateau characteristics. In this paper, the finite volume method is used to analyse the flow-heat-solid coupling of a 20 MW motor. By comparing and verifying the experimental data with the simulation data, it is found that the error between the two is within 5 %. In order to have a more comprehensive picture of the motor's operation in the plateau environment, the temperature effects of different air pressure, air intake and relative humidity on the motor were investigated. The results of the study show that air pressure changes have a large effect on the temperature of the stator structure. The temperature decreases when the air pressure increases and the temperature difference decreases gradually with the increase of air pressure. The largest temperature difference in the stator structure occurs when the air pressure increases from 10 kPa to 40 kPa. The change in air intake has a positive effect on the stator structure temperature, which decreases when the air intake increases. After simulation calculations, it was found that the best heat dissipation effect was achieved in the range of air intake between 3.5 m/s and 4.5 m/s. Relative humidity has a minimal effect on the stator structure temperature. The conclusions of this paper can provide certain theoretical reference for the temperature change law of the motor under plateau operation, which is of great significance to improve the comprehensive hydraulic performance.

The feature extraction and state recognition of vibration signals of hydroelectric generating units are of great significance for effectively ensuring the safety and lifespan of unit operation. This paper introduces a novel fault diagnosis approach that leverages a wavelet threshold algorithm for initial signal preprocessing and enhances the Radial Basis Function (RBF) neural network with an optimized Gravitational Search Algorithm (GSA). Initially, the Wavelet Transform (WT) algorithm is employed to denoise the raw signal, which is subsequently decomposed using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). Intrinsic Mode Function (IMF) components are then selected based on their correlation coefficients for sample entropy calculation. A GSA-optimized RBF neural network is constructed to diagnose faults in hydroelectric units. To further enhance the model’s convergence speed and accuracy, Lévy flight and chaotic sequence optimizations are integrated into the GSA, resulting in the development of the LCGSA-RBF diagnosis model. Experimental results demonstrate that this method achieves a 100% accuracy rate, outperforming other comparative models. Specifically, this approach enhances accuracy by 12.5% over the CEEMDAN-RBF method, showing the highest alignment with actual fault diagnosis results. This research significantly contributes to the advancement of safe and reliable operations in hydroelectric generating units.

Interrupted cooling experiments of FGH97 nickel-based powder metallurgy (PM) superalloy with different cooling rates were carried out using a DIL805A quenching dilatometer. The microstructural evolution of the γ′ precipitates during cooling after solution heat-treatment was investigated by means of field emission scanning electron microscopy (FE-SEM), energy dispersive spectrometer (EDS), transmission electron microscopy (TEM), and X-ray diffraction (XRD). Vickers microhardness tests were performed on the samples that were interrupted at different temperatures to establish a relationship between microstructure and mechanical properties. The results revealed that the secondary γ′ precipitates preferentially nucleated at a higher temperature, and gradually grew during the cooling stage. Meanwhile, the morphology of the secondary γ′ precipitates transitioned from spherical to cubic, to rounded cuboidal, to a butterfly-like shape, and ultimately splitting into octo-cubes, whose driving force was attributed to the mutual competition between surface energy and elastic strain energy. During the initial stages of the cooling process, the microhardness decreased due to the growth and coarsening of the secondary γ′ precipitates. As the temperature decreased, the supersaturation within the matrix became sufficient to overcome the energy barrier for a second burst of nucleation, the tertiary γ′ phases precipitated, resulting in an increase in microhardness.

Coilia nasus is an anadromous fish that has been successfully domesticated in the last decade due to its high economic value. The fish exhibits a delayed ovary development during the reproductive season, despite breeding and selection for five to six offspring. The molecular mechanism of the delayed ovary development is still unknown, so the obstacles have not been removed in the large-scale breeding program. This study aims to investigate the key genes regulating ovarian development by comparing the transcriptomes of ovarian-stage IV and stage II brain/pituitary of Coilia nasus. Ovarian stages were validated by histological sections. A total of 75,097,641 and 66,735,592 high-quality reads were obtained from brain and pituitary transcriptomes, respectively, and alternatively spliced transcripts associated with gonadal development were detected. Compared to ovarian Ⅱ- brain, 515 differentially expressed genes (DEGs) were upregulated and 535 DEGs were downregulated in ovarian Ⅳ- brain, whereas 470 DEGs were upregulated and 483 DEGs were downregulated in ovarian Ⅳ- pituitary compared to ovarian Ⅱ- pituitary. DEGs involved in hormone synthesis and secretion and in the GnRH signaling pathway were screened. Weighted gene co-expression network analysis identified gene co-expression modules that were positively correlated with ovarian phenotypic traits. The hub genes Smad4 and TRPC4 in the modules were co-expressed with DEGs including Kiss1 receptor and JUNB, suggesting that ovarian development is controlled by a hypothalamic-pituitary-gonadal axis. Our results have provided new insights that advance our understanding of the molecular mechanism of C. nasus reproductive functions and will be useful for future breeding.

Abstract Introduction Chronic myeloid leukemia (CML) is a chronic disease with treatment-free remission (TFR) increasingly regarded as a feasible goal of treatment. However, various factors may influence adherence to international guidelines for CML management. This study aimed to compare the reporting of care between patients with CML and their treating doctors. Methods Parallel patient and physician online surveys were conducted between September 22, 2021, and March 15, 2022, which focused on the perceptions of 1882 adult patients with CML and 305 physicians regarding tyrosine kinase inhibitor (TKI) treatment options, monitoring and toxicities, TFR, and challenges faced. Results Among the enrolled patients, 69.9% received first-line imatinib treatment, 18.6% received nilotinib, and 4.7% received dasatinib. Among the patients treated with imatinib, 36.7% switched to other TKIs due to imatinib resistance/intolerance (71.1%), exploration of more potent TKIs to achieve TFR (8.9%), and treating physicians’ recommendation (14.0%), with a median duration of initial treatment of 14 months [interquartile range (IQR) 6–36]. Most (91.8%) physicians agreed that the breakpoint cluster region–Abelson 1 (BCR::ABL1) transcript level should be assessed every 3 months, but only 42.7% of individuals committed to 3-monthly testing and only 17.8% strictly followed their treating physicians’ recommendation. Half of the patients aimed for TFR; however, just 45.2% of physicians considered TFR as one of the top three goals for their patients. The major concern in obtaining TFR was patients’ adherence. Fatigue was often distressing for patients with TKIs, while physicians were more concerned about platelet and neutrophil counts. A total of 12% and 20.8% of patients reported moderate/severe anxiety and depression, respectively, while only 53.7% of physicians had concerns about their patients’ mental health. During the coronavirus disease 2019 (COVID-19) pandemic, 69.2% of patients reported a reduction in their income. Among these patients, 61.8% maintained their current treatment, while 7.3% switched to cheaper alternatives or discontinued treatment, with over 80% of these patients belonging to the low-income group. Conclusions Overcoming challenges in patient–physician communication and treatment access is key to improving disease management and quality of life, especially for patients with low income. Trial Registration ClinicalTrials.gov identifier NCT05092048.

Virtual synchronous generator (VSG) technology has achieved some results in distributed generation networks and enhanced system stability. For problems that may occur in the system due to ignoring parameter linkages, this paper designs a synergistic controller that establishes the connection between the active frequency and the reactive voltage control loop based on synergy theory. As the output of the synergetic controller, the derived control law u is added to the power frequency control in the form of negative feedback. Two disturbance forms, a step disturbance, and a three-phase short-circuit fault, are set up. The conventional droop control and synergetic droop control results are compared using a MATLAB simulation system. Then, the system parameter variations were studied and analyzed, and the sensitivity of the control system with different values of parameters K1, K2, and K3 in the case of a three-phase short circuit was analyzed, which provides a reference guide for selecting parameters in later control optimization. Finally, the control effectiveness of a multi-machine VSG system was tested. The simulation results show that the proposed method has a pronounced effect on making the system stabilize quickly, which illustrates the effectiveness of this technique.

Abstract Background The hypomethylating agent decitabine is the standard therapy for intermediate or high risk myelodysplastic syndrome (MDS). Methods In this trial, 191 adult patients with intermediate/high risk MDS (IPSS score ≥ 0.5) randomly received decitabine using a standard regimen (20 mg/m2/day for 5 consecutive days; n = 94) or an extended regimen with lower daily dose (12 mg/m2/day for 8 consecutive days; n = 97) every 4 weeks, for a total of 4 cycles. Results The median follow‐up was 14 months (range 2–36). The primary end point of overall response rate in the intent‐to‐treat analysis was 41.5% and 38.1% in the standard and extended dosing arms, respectively (p = 0.660). Complete remission and marrow complete remission also did not differ between the two arms. Cytopenia was the most frequent adverse event (76.4%). The median duration of neutropenia per cycle did not differ between the two arms during the first two cycles, but significantly shorter in the extended dosing arm in the third cycle (8.5 vs. 15.5 days, p = 0.049) and in the fourth cycle (8 vs. 14 days, p = 0.294). Conclusion The 5‐day 20‐mg/m2/day and 8‐day 12‐mg/m2/day decitabine regimens have similar efficacy and safety in patients with intermediate or high risk MDS.

To enhance the operational efficiency and fault detection accuracy of hydroelectric units, this paper proposes a parallel convolutional neural network model that integrates the Gramian angular summation field (GASF) with an Improved coati optimization algorithm–parallel convolutional neural network (ICOA-PCNN). Additionally, to further improve the model’s accuracy in fault identification, a multi-head self-attention mechanism (MSA) and support vector machine (SVM) are introduced for a secondary optimization of the model. Initially, the GASF technique converts one-dimensional time series signals into two-dimensional images, and a COA-CNN dual-branch model is established for feature extraction. To address the issues of uneven population distribution and susceptibility to local optima in the COA algorithm, various optimization strategies are implemented to improve its global search capability. Experimental results indicate that the accuracy of this model reaches 100%, significantly surpassing other nonoptimized models. This research provides a valuable addition to fault diagnosis technology for modern hydroelectric units.

The utilization of bismuth as a sensing material for the detection of heavy metal ions has gained significant attention due to its exceptional interfacial activity and selective absorption properties. However, it also poses challenges in terms of agglomeration and its inferior electrical conductivity during the synthesis process. This paper employed a facile in situ synthesis and electrodeposition approach to uniformly grow a bismuth film on a conductive carbon cloth, designated as Bi/Ag@CC. The Bi/Ag@CC electrode material exhibited benign electrochemical properties, enabling its application for detecting Pb2+ in tap water and lake water samples. Furthermore, this work investigated the impact of electrochemical parameters, including electrolyte pH, deposition potential and pre-enrichment time, on the detection performance. The results demonstrated the sensor’s wide linear range (from 20 to 400 ppb) and detection limits (0.15 ppb) for heavy metal ion detection, along with excellent anti-interference capabilities and satisfactory repeatability, with an RSD of less than 2.31% (n = 6). This paper offers a novel strategy for positioning the bismuth-based composite as a promising candidate for practical electrochemical sensing applications.

Ensuring the spatial equity of health service facilities (HSFs) is crucial for the well-being of residents. However, previous research has predominantly focused on the accessibility and equity of single-type facilities, neglecting the residents’ demand for diversified types of health services. This study proposes a multi-type, Gaussian-based, two-step floating catchment area method (MT-G2SFCA) to assess the comprehensive accessibility and equity of multi-type HSFs in different age groups in the Hedong District of Tianjin, with the Gini coefficient and the bivariate local Moran’s I. Furthermore, the key factors affecting the accessibility were explored through a geo-detector. The results indicate the following: (1) Neglecting the health benefits of facility type diversity can result in an underestimation of the accessibility and equity; (2) neglecting the differences in walking ability of the elderly can result in an overestimation of the accessibility and equity; and (3) the Pedestrian Route Directness is the key factor affecting the accessibility and equity in high-density urban areas, and especially that the facility density is the key factor for the elderly. This research emphasizes the impact of facility type diversity on the accessibility and equity of HSFs, which can offer more precise and holistic technical assistance and policy recommendations for optimizing the allocation of HSFs.

Expanded polystyrene (EPS) geofoam is a light and deformable geosynthetic that can reduce the pressure on the pipe by surrounding soil. The protective effect of geofoam bocks protection on the buried pipe under stratum settlement was investigated. The effect of settlement displacement, diameter-thickness ratio, internal pressure, surrounding soil, and EPS thickness on the axial strain and ovalisation of pipe were analyzed. The results show that the axial strain and ovalisation of pipe protected with EPS are smaller than that in soil. With the increase of the pipe diameter-thickness ratio, the axial strain and ovalisation of pipe with or without protection increase. With the increase of internal pressure, the buckling mode of pipe buried in soil changes from collapse to wrinkle gradually, but the ovalisation changes of pipe protected with EPS is small. When the surrounding soil is rock, buckling occurred in the without protection is more obvious. The safety of the pipeline is better with thicker EPS.

Abstract Tumor cells may be eliminated by increasing their temperature. This is achieved via photothermal therapy (PTT) by penetrating the tumor tissue with near‐infrared light and converting light energy into heat using photothermal agents. Copper sulfide nanoparticles (CuS NPs) are commonly used as PTAs in PTT. In this review, we aimed to discuss the synergism between tumor PTT with CuS NPs and other therapies such as chemotherapy, radiotherapy, dynamic therapies (photodynamic, chemodynamic, and sonodynamic therapy), immunotherapy, gene therapy, gas therapy, and magnetic hyperthermia. Furthermore, we summarized the results obtained with a combination of two treatments and at least two therapies, with PTT as one of the included therapies. Finally, we summarized the benefits and drawbacks of various therapeutic options and state of the art CuS‐based PTT and provided future directions for such therapies.

Monitoring the spatial distribution and sources of heavy metals (HM) in soil is essential for avoiding health risks and achieving sustainable soil utilization. Multiple geospatial data, including remote sensing, climate, soil and topography data, were used to extract environmental covariates. Additionally, the spatial scene was employed as the alternative data of land use/land cover to describe the urban functions and human activity intensity in more detail. After converting to a uniform resolution of 30 m, these environmental covariates were adopted to characterize several common HM in soil, including copper (Cu), chromium (Cr), lead (Pb), nickel (Ni), and zinc (Zn). The RReliefF algorithm was used to identify several important variables. The quantification models of HM were established using back-propagation neural network (BPNN) and deep neural network (DNN). Besides, the impact of distance from the spatial scenes on HM were analyzed. The result demonstrated that the spatial scene is a key environmental covariate in estimating HM in soil. Compared with BPNN, the DNN model provided better accuracy (R2 = 0.67–0.75) for estimation of five HM elements. Therefore, the DNN model was used to map HM concentrations at a grid scale of 30 m. The spatial scenes with the highest risk of HM pollution are industrial areas, residential areas, road, and commercial areas, and the concentration of HM is negatively correlated with the distance from these spatial scenes. The effective impact distances of industrial and residential areas are about 2000 m, and the effective impact distances of road and commercial areas are 500 m.

Magnetic robots possess an innate ability to navigate through hard-to-reach cavities in the human body, making them promising tools for diagnosing and treating diseases minimally invasively. Despite significant advances, the development of robots with desirable locomotion and full biocompatibility under harsh physiological conditions remains challenging, which put forward new requirements for magnetic robots’ design and material synthesis. Compared to robots that are synthesized with inorganic materials, natural organisms like cells, bacteria or other microalgae exhibit ideal properties for in vivo applications, such as biocompatibility, deformability, auto-fluorescence, and self-propulsion, as well as easy for functional therapeutics engineering. In the process, these organisms can provide autonomous propulsion in biological fluids or external magnetic fields, while retaining their functionalities with integrating artificial robots, thus aiding targeted therapeutic delivery. This kind of robotics is named bio-hybrid magnetic robotics, and in this mini-review, recent progress including their design, engineering and potential for therapeutics delivery will be discussed. Additionally, the historical context and prominent examples will be introduced, and the complexities, potential pitfalls, and opportunities associated with bio-hybrid magnetic robotics will be discussed.

The hydropower turbine parts running in the sand-bearing flow will experience surface wear, leading to a decline in the hydropower unit’s stability, mechanical performance, and efficiency. A voiceprint signal-based method is proposed for extracting the flow sediment content feature of the hydropower unit. Firstly, the operating voiceprint information of the hydropower unit is obtained, and the signal is decomposed by the Ensemble Empirical Mode Decomposition (EEMD) algorithm, and a series of intrinsic mode functions (IMFs) are obtained. Combined with correlation analysis, more sensitive IMF components are extracted and input into a convolutional neural network (CNN) for training, and the multi-dimensional output of the fully connected layer of CNN is used as the feature vector. The k-means clustering algorithm is used to calculate the eigenvector clustering center of the hydropower unit with a clean flow state and a high sediment content state, and the characteristic index of the hydropower unit sediment content is constructed based on the Euclidean distance method. We define this characteristic index as SI, and the change in the SI value can reflect the degree of sediment content in the flow of the unit. A higher SI value indicates a lower sediment content, while a lower SI value suggests a higher sediment content. Combined with the sediment voiceprint data of the test bench, when the water flow changed from clear water to high sediment flow (1.492 × 105 mg/L), the SI value decreased from 1 to 0.06, and when the water flow with high sediment content returned to clear water, the SI value returned to 1. The experiment proves the effectiveness of the method. The extracted feature index can be used to detect the flow sediment content of the hydropower unit and give early warning in time, so as to improve the maintenance level of the hydropower unit.

With the advancement in the developmental project on the lower reaches of the Yarlung Tsangpo River, the influence of the plateau climate environment on the performance of a hydro-generator has received more and more attention from researchers. This study numerically simulated the thermal field of a hydro-generator with a 20 MW capacity under the effect of a plateau climate. Ambient pressure and temperature are two main factors that affect the temperature distribution of the generator. In addition, temperature distributions with different speeds are also studied under a plateau climate. The results show that the generator temperature decreases with increasing air pressure and speed. The generator temperature increases linearly with increasing ambient temperature. Among them, when the pressure lies in the range of 25–85 kPa, the temperature change gradient of the stator structure is very large. The temperature difference gradually decreases with the increase in air pressure. The temperature gradient gradually slows down when the air pressure is above 85 kPa. When the pressure is located at 55–85 kPa, the average temperature difference of the stator windings is 6.325 °C, and the average temperature difference of the stator core is 3.815 °C. Finally, the temperature distribution pattern can provide a basis for staff in different barometric pressure regions. It can also improve the safety and reliability of the hydro-generator under the effect of a plateau climate, which is important for improving its integrated hydraulic performance.

Abstract Background Human amniotic mesenchymal stem cells (hAMSCs) are splendid cell sources for clinical application in the administration of numerous refractory and relapse diseases. Despite the preferable prospect of serum-free (SF) condition for cell product standardization and pathogenic contamination remission, yet the systematic and detailed impact upon hAMSCs at both cellular and transcriptomic levels is largely obscure. Methods For the purpose, we preconditioned hAMSCs under serum-containing (SC) and SF medium for 48 h and compared the biological signatures and biofunctions from the view of cell morphology, immunophenotypes, multi-lineage differentiation in vitro, cell vitality, cytokine expression, and immunosuppressive effect upon the subpopulations of T lymphocytes, together with the PI3K-AKT-mTOR signaling reactivation upon cell vitality. Meanwhile, we took advantage of RNA-SEQ and bioinformatic analyses to verify the gene expression profiling and genetic variation spectrum in the indicated hAMSCs. Results Compared with those maintained in SC medium, hAMSCs pretreated in SF conditions manifested conservation in cell morphology, immunophenotypes, adipogenic differentiation, and immunosuppressive effect upon the proliferation and activation of most of the T cell subpopulations, but with evaluated cytokine expression (e.g., TGF-β1, IDO1, NOS2) and declined osteogenic differentiation and cell proliferation as well as proapoptotic and apoptotic cells. The declined proliferation in the SF group was efficiently rescued by PI3K-AKT-mTOR signaling reactivation. Notably, hAMSCs cultured in SF and SC conditions revealed similarities in gene expression profiling and variations in genetic mutation at the transcriptome level. Instead, based on the differentially expressed genes and variable shear event analyses, we found those genes were mainly involved in DNA synthesis-, protein metabolism-, and cell vitality-associated biological processes and signaling pathways (e.g., P53, KRAS, PI3K-Akt-mTOR). Conclusions Collectively, our data revealed the multifaceted cellular and molecular properties of hAMSCs under SC and SF conditions, which suggested the feasibility of serum-free culture for the preferable preparation of standardized cell products for hAMSC drug development and clinical application.

Bioinformatics, an emerging discipline focusing on genomics and proteomics, is both comprehensive and interdisciplinary of biology, computer science, information engineering and statistics. In the ophthalmic biological genetic research, cornea, lens, aqueous humor, vitreous and retina are ideal bioinformatic research objects in the field of ophthalmic biological genes because of their abundance in biological information. Genomics testing techniques have the characteristics of high efficiency and accuracy, which helps us to screen the differentially expressed genes related to ophthalmic tumors and genetic diseases; Proteomics can help us analyze the protein expression profile and functional changes caused by the high and low gene expression in intraocular fluid or isolated cells in diseases states, revealing the mechanism of disease. This paper mainly summarizes the application of bioinformatics in ophthalmic diseases, and preliminarily envisage its impact on the current treatment, the existing problems and the development trend in the future.

The medical community is constantly searching for new and innovative ways to treat cancer, and cellular-membrane-derived artificial vesicles are emerging as a promising avenue for cancer immunotherapy. These vesicles, which are derived from mammal and bacteria cell membranes, offer a range of benefits, including compatibility with living organisms, minimal immune response, and prolonged circulation. By modifying their surface, manipulating their genes, combining them with other substances, stimulating them externally, and even enclosing drugs within them, cellular vesicles have the potential to be a powerful tool in fighting cancer. The ability to merge drugs with diverse compositions and functionalities in a localized area is particularly exciting, as it offers a way to combine different immunotherapy treatments for maximum impact. This review contains information on the various sources of these vesicles and discusses some recent developments in cancer immunotherapy using this promising technology. While there are still obstacles to overcome, the possibilities for cellular vesicles in cancer treatment are truly exciting.

Studies show that sediment erosion is one of the main factors attributing to hydraulic turbine failure. The present paper represents an investigation into acoustic vibration signals generated by the water flow impacting the hydraulic turbine runner under three different operating conditions. Collected signals were denoised using the ICEEMDAN-wavelet threshold method, and then the spectral characteristics and sample entropy characteristics of the signals for the three operating conditions were analyzed. The results show that when clean water flows through the hydraulic turbine, the sample entropy reaches its smallest values and the dominant frequency component in the spectrogram is 59.39 Hz. When transitioning from clean water to the flood flow containing 2–4 mm sediment particles, the sample entropy is increasing and a high-frequency component higher than 59.39 Hz becomes the prominent frequency of the spectrogram. Meanwhile, the formation of high-frequency components increases with the sand-containing particle size. Based on the spectral characteristics and sample entropy characteristics of the acoustic vibration signals under different operating conditions, it can provide a reference for the sand avoidance operation of the hydraulic turbine during flood season. In addition, it provides a supplement to the existing hydraulic turbine condition’s monitoring systems and a new avenue for subsequent research on early warning of hydraulic turbine failure.

Abstract Background Postoperative chemotherapy for gastric cancer often causes multidrug resistance (MDR), which has serious consequences for therapeutic effects. Individualized treatment based on accurate monitoring of MDR will greatly improve patient survival. Results In this article, a self-enhanced Mn3O4 nanoplatform (MPG NPs) was established, which can react with glutathione to produce Mn2+ to enhance T1-weighted magnetic resonance imaging (MRI) and mediate in vivo real-time MDR monitoring. In vitro MRI results showed that MRI signals could be enhanced in the presence of hydrogen peroxide and glutathione and at acidic pH. In vivo MRI results indicated that MPG NPs could specifically target MDR cells, thereby realizing real-time monitoring of MDR in gastric cancer. Furthermore, MPG NPs have good chemodynamic activity, which can convert the endogenous hydrogen peroxide of tumor cells into highly toxic hydroxyl radical through Fenton-like reaction at acidic pH to play the role of chemodynamic therapy. In addition, Mn3O4 can significantly enhance the chemodynamic therapy effect because of its good photothermal conversion effect. Furthermore, in situ photothermal/chemodynamic synergistic therapy obtained remarkable results, the tumors of the mice in the synergistic therapy group gradually became smaller or even disappeared. Conclusions MPG NPs have good biocompatibility, providing a good nanoplatform for real-time monitoring and precise diagnosis and treatment of MDR in gastric cancer. Graphical Abstract

Abstract Background Photoimmunotherapy is one of the most promising strategies in tumor immunotherapies, but targeted delivery of photosensitizers and adjuvants to tumors remains a major challenge. Here, as a proof of concept, we describe bone marrow mesenchymal stem cell-derived nanovesicles (NVs) displaying anti-PD-L1 antibodies (aPD-L1) that were genetically engineered for targeted drug delivery. Results The high affinity and specificity between aPD-L1 and tumor cells allow aPD-L1 NVs to selectively deliver photosensitizers to cancer tissues and exert potent directed photothermal ablation. The tumor immune microenvironment was programmed via ablation, and the model antigen ovalbumin (OVA) was designed to fuse with aPD-L1. The corresponding membrane vesicles were then extracted as an antigen–antibody integrator (AAI). AAI can work as a nanovaccine with the immune adjuvant R837 encapsulated. This in turn can directly stimulate dendritic cells (DCs) to boast the body's immune response to residual lesions. Conclusions aPD-L1 NV-based photoimmunotherapy significantly improves the efficacy of photothermal ablation and synergistically enhances subsequent immune activation. This study describes a promising strategy for developing ligand-targeted and personalized cancer photoimmunotherapy. Graphic Abstract

Because a single monitoring index cannot fully reflect the overall operating status of the hydropower unit, a comprehensive state evaluation model for hydropower units based on the analytic hierarchy process (AHP) and the Gaussian threshold improved fuzzy evaluation is proposed. First, the unit equipment was divided into a hierarchical system, and a three-tier structure system (target layer-project layer-index layer) of the unit was constructed, and the weight of each component in the system was determined by the comprehensive weighting method. Secondly, according to the characteristics of the normal distribution of the historical health data of the unit, the upper and lower limits of the index were determined based on the Gaussian threshold principle, the real-time monitoring index degradation degree was calculated according to the index limit, and the degradation degree was applied to the fuzzy evaluation model to obtain the fuzzy judgment matrix. The result of assessment was divided into four sections: good, qualified, vigilant, and abnormal. Finally, combined with the unit hierarchical structure system, the weighted calculation of the fuzzy judgment matrix of each indicator, the overall fuzzy judgment matrix of the upper-level indicators of the unit was obtained, and the operating status of the unit was judged according to the matrix. Taking a real power plant unit as an example, the model was verified, and compared with other evaluation methods, the effectiveness and advantages of the proposed method were verified. In addition, the method proposed in this paper effectively solved the problems of index weighting and index limit determination in the existing model of unit condition evaluation.

The non-axisymmetric exciting guided wave can detect the thinning section of the elbow, and the time domain energy value of the signal collected at the outer arch position of the receiving end displays a downward trend as the remaining thickness of the erosion area decreases. To address the difficulty in detecting the erosion degree of the elbow with high accuracy, this paper uses the linear frequency modulation (LFM) signal to excite a non-axisymmetric guided wave that propagates in the 90° elbow and collects signals through four PZT receivers. To predict the erosion degree, the corresponding relationship between the energy value of the four signals after fractional Fourier filtering and the degree of elbow erosion is established through the particle swarm optimization (PSO)–least squares support vector machine (LSSVM) algorithm. The results show that the method proposed has an average accuracy rate of 98.1864%, 94.7167%, 99.119%, and 99.9593% for predicting the erosion degree of four elbow samples, and 94.0039%. and 81.2976% for two new erosion degrees, which are higher than the nonlinear regression model, LSSVM algorithm, and BP neural network algorithm. This study has guiding significance for real-time monitoring of elbow erosion.

ObjectiveThis study aimed to estimate the prevalence of visual impairment and to identify the factors associated with it in China.MethodsData for this cross-sectional study were retrieved from the China Health and Retirement Longitudinal Study (CHARLS) for a total of 16,480 subjects who completed the questionnaire between June 2011 and March 2012. The prevalence of visual impairment was estimated considering the complex survey design and response rate. Associated factors were identified using the weighted logistic regression analysis.ResultsThe overall prevalence of visual impairment among middle-aged and older Chinese adults was 6.22%. Regionally, Qinghai and Gansu provinces showed the highest prevalence of visual impairment, whereas Shanghai showed the lowest prevalence of visual impairment in China. Older age (OR = 1.888; 95% CI: 1.537–2.467) was correlated with a higher likelihood of visual impairment, whereas a non-alcohol intake (OR = 0.072; 95% CI: 0.018–0.246) was correlated with a lower likelihood of visual impairment. Hypertension (OR = 1.299; 95% CI: 1.189–1.467), diabetes (OR = 2.000; 95% CI: 1.163–3.765), lung diseases (OR = 1.795; 95% CI: 1.067–3.019), liver diseases (OR = 1.270; 95% CI: 1.221–2.876), stroke (OR = 1.135; 95% CI: 1.107–3.528), and heart disease (OR = 1.350; 95% CI: 1.104–1.708) were significantly associated with visual impairment.ConclusionGeographical variations in the prevalence of visual impairment in China were defined, indicating that such variations do exist in China. Age, alcohol intake, hypertension, diabetes, lung diseases, liver diseases, stroke, and heart disease were factors associated with visual impairment.

Abstract Background Currently, most research on hemophagocytic lymphohistiocytosis (HLH) have focused on etiology and therapy, leaving few epidemiological reports. The published studies of China are mainly regional investigations. We aimed to present the overall epidemiological status of HLH in China, and provide Chinese data for the international HLH epidemiological investigation. Methods The data of HLH cases in China in 2019 were collected and statistically analyzed. Findings Epstein-Barr virus accounted for 44.01% of the 1445 cases in 31 regions and was the most common cause. Lymphoma-associated HLH patients were more often male (P

Abstract Photoacoustic (PA) imaging is a nonionizing, noninvasive imaging technique that combines optical and ultrasonic imaging modalities to provide images with excellent contrast, spatial resolution, and penetration depth. Exogenous PA contrast agents are created to increase the sensitivity and specificity of PA imaging and to offer diagnostic information for illnesses. The existing PA contrast agents are categorized into two groups in this review: “always‐on” and “turn‐on,” based on their ability to be triggered by target molecules. The present state of these probes, their merits and limitations, and their future development, is explored.

IntroductionAlzheimer’s disease (AD) is the most common form of dementia worldwide. The biological mechanisms underlying the pathogenesis of AD aren’t completely clear. Studies have shown that the gut microbiota could be associated with AD pathogenesis; however, the pathways involved still need to be investigated.AimsTo explore the possible pathways of the involvement of gut microbiota in AD pathogenesis through metabolites and to identify new AD biomarkers.MethodsSeven-month-old APP/PS1 mice were used as AD models. The Morris water maze test was used to examine learning and memory ability. 16S rRNA gene sequencing and widely targeted metabolomics were used to identify the gut microbiota composition and fecal metabolic profile, respectively, followed by a combined analysis of microbiomics and metabolomics.ResultsImpaired learning abilities were observed in APP/PS1 mice. Statistically significant changes in the gut microbiota were detected, including a reduction in β-diversity, a higher ratio of Firmicutes/Bacteroidota, and multiple differential bacteria. Statistically significant changes in fecal metabolism were also detected, with 40 differential fecal metabolites and perturbations in the pyrimidine metabolism. Approximately 40% of the differential fecal metabolites were markedly associated with the gut microbiota, and the top two bacteria associated with the most differential metabolites were Bacillus firmus and Rikenella. Deoxycytidine, which causes changes in the pyrimidine metabolic pathway, was significantly correlated with Clostridium sp. Culture-27.ConclusionsGut microbiota may be involved in the pathological processes associated with cognitive impairment in AD by dysregulating pyrimidine metabolism. B. firmus, Rikenella, Clostridium sp. Culture-27, and deoxyuridine may be important biological markers for AD. Our findings provide new insights into the host-microbe crosstalk in AD pathology and contribute to the discovery of diagnostic markers and therapeutic targets for AD.

Rabdosia serra (Maxim.) Hara (R. serra), one of the source plants of “Xihuangcao”, has been widely used as a Chinese folk herb with the concomitant function of both medicine and foodstuff for the prevention and treatment of liver disease. Diterpenoids were considered as the major bioactive components in R. serra, responsible for their effect on hepatoprotection in previous phytochemical and pharmacological studies, while few comparative pharmacokinetic studies have been conducted under the physiological and pathological conditions. To reveal the difference in the pharmacokinetics process of R. serra extract (RSE) in normal and Con A-induced liver injury rats, a rapid ultra-high-pressure liquid chromatography–tandem mass spectrometry method (total running time: 5 min) was established to simultaneously determine three bioactive diterpenoids (enmein, epinodosin, and isodocarpin) in rat plasma. The results showed significant differences in the pharmacokinetic properties of three analytes between the physiological and pathological states. Compared with normal rats, the AUC of the three analytes was remarkably higher in liver injury rats, while the Tmax, T1/2, and MRT were shortened. It indicated that RSE has higher exposure and quicker elimination in liver injury rats than that in normal rats. Our results suggested that the pharmacokinetics of hepatoprotective medications was affected by liver injury, which prospected to provide essential information for guiding the healthcare and clinical application of R. serra in pathological states.

Gastric cancer (GC) is a disease with macromolecular phenotypic heterogeneity and poor prognosis, especially for metastatic GC (mGC). Chemotherapy is the first choice for second-line treatment. However, the benefits of second-line chemotherapy are limited, so there is an urgent need for new treatment regimens to improve patient outcomes. A 65-year-old man with mGC was HER-2 positive. Standard trastuzumab, combined with chemotherapy, was given in the first-line therapy and progression-free survival (PFS) was 8 months. Second-line treatment with pyrotinib in combination with trastuzumab and chemotherapy yielded a PFS of 20 months, in sharp contrast to a median survival of 2.9-6.2 months for a majority of advanced GC patients. This case provides a meaningful reference for the second-line treatment of mGC patients with HER-2 positive. This case also provides valuable information on the response to pyrotinib plus trastuzumab of patients with brain metastases and a better understanding of dual target combination therapy applications in the future.

In response to the issue of system oscillations in direct current (DC) microgrid systems with constant power loads (CPL), this paper proposes a non-singular terminal sliding-mode control (NTSMC) strategy based on the improved salp swarm algorithm (ISSA). Firstly, the state-feedback exact linearization technique is employed to establish a linearized model of the converter system. Then, the NTSMC based on a composite sliding-mode surface is designed to achieve rapid convergence and effectively weaken the chattering issue in traditional sliding-mode control, ensuring a constant power supply to the load. The parameters of the proposed NTSMC are optimized using the ISSA, which introduces an intelligent NTSMC. Finally, a MATLAB/Simulink simulation model is established. The simulation results show that the ISSA-based composite sliding-mode surface NTSMC system designed for DC microgrid systems with CPL exhibits high robustness and guarantees ideal steady-state characteristics and dynamic responses when input voltage fluctuations and load disturbances occur.

The primary control goals of a wind turbine (WT) are structural load shedding, maximum wind energy capture in the underpowered situation, and consistent power production in the full power condition. A crucial component of the control problem for wind turbines with varying speeds is maximum power tracking control. Conventional maximum power tracking control tracks the ideal blade tip speed ratio to provide the most wind power at the specified wind speeds. However, because of the wind turbine’s great nonlinearity and the significant external disturbances it encounters, it is difficult to react quickly to variations in wind speed, and the tracking speed is sluggish, which lowers the amount of electricity produced annually. In light of this, this work develops a novel preset performance controller for a wind power system maximum power tracking control. With this technique, the convergence rate and tracking precision may be set. In particular, based on the concept of time-varying feedback, a time-varying function, known as the preset performance function, is first created to allow the convergence speed and accuracy to be predetermined; then this time-varying function is used to transform the actual specified time problem of the original system into a bounded time problem of the new system; finally, a direct robust controller design strategy with pre-defined performance is suggested based on the design concept of the backstepping technique. The plan may maximize the rotor power coefficient by altering the wind turbine speed, track the ideal blade tip speed ratio for a given tracking accuracy and speed, and get the most wind power to produce the most power with the strongest robustness. The simulation results show that the recommended control technique works.

The power oscillation induced by pressure fluctuation in the draft tube of the hydraulic turbine is one of the limiting factors preventing the Francis turbine from operating in the vibration zone. At the present power grid with a high proportion of renewable energy resources, we try to improve the load regulation ability of the hydropower units by extending the stable operation zone to the vibration zone. By the mathematical modelling of pressure fluctuation, this paper gives an analytical expression of the power oscillation. We derive the extended Hamiltonian model of the hydropower unit where power oscillation is external excitation. Secondly, the damping injection method introduces some desired interconnection and damping matrices as the Hamiltonian damping factor into the additional damping control. Finally, through theoretical analysis and experimental simulation, this research discusses the resonance characteristics of pressure fluctuation and power oscillation, the equivalent analysis between the damping factor and equivalent damping coefficient, and the control design of vibration zone crossing during the start-up. Simulation results show that when r25 = 1.3, the minimum power oscillation amplitude is 0.5466, which is equivalent to an increase in D by 20. The maximum oscillation amplitude decreases by 4.6%, and the operation limited zone is reduced by 10.1%. The proposed additional damping control can effectively suppress the power oscillation and expand the regulation range.

Abstract Background Hetrombopag, a novel thrombopoietin receptor agonist, has been found in phase I studies to increase platelet counts and reduce bleeding risks in adults with immune thrombocytopenia (ITP). This phase III study aimed to evaluate the efficacy and safety of hetrombopag in ITP patients. Methods Patients who had not responded to or had relapsed after previous treatment were treated with an initial dosage of once-daily 2.5 or 5 mg hetrombopag (defined as the HETROM-2.5 or HETROM-5 group) or with matching placebo in a randomized, double-blind, 10-week treatment period. Patients who received placebo and completed 10 weeks of treatment switched to receive eltrombopag, and patients treated with hetrombopag in the double-blind period continued hetrombopag during the following open-label 14-week treatment. The primary endpoint was the proportion of responders (defined as those achieving a platelet count of ≥ 50 × 109/L) after 8 weeks of treatment. Results The primary endpoint was achieved by significantly more patients in the HETROM-2.5 (58.9%; odds ratio [OR] 25.97, 95% confidence interval [CI] 9.83–68.63; p

In this paper, a mixed $H_{2}/H_{\infty }$ robust control strategy that considers the weights of the $H_{2}$ and $H_{\infty }$ norm in the optimization process is proposed, and it is used to solve the load frequency control (LFC) problem of the micro-grid (MG). The MG load frequency model established in this paper includes battery energy storage system (BESS), fuel cell (FC), wind turbine (WT), photo-voltaic (PV), and diesel engine generator (DEG). The optimal mixed $H_{2}/H_{\infty }$ robust controller takes the minimum square integral of the system’s frequency fluctuation as the goal of control optimization by integrating the robust performance expressed by the $H_{2}/H_{\infty }$ two norms. The hybrid particle swarm optimization and gravitational search algorithm with chaotic map algorithm (CPSOGSA) is used to optimize the weight value reflecting the $H_{2}$ and $H_{\infty }$ performance of the system and the evaluation function’s weighting matrix of the output performance so that the controller can reach the optimum under the constraints. Simulation experiments show that the robust controller designed by the proposed method has better dynamic performance when compared with $H_{\infty }$ robust controller, $H_{2}$ robust controller, and traditional $H_{2}/H_{\infty }$ robust controller, and the results are very satisfactory.

In this paper, a novel Takagi-Sugeno (T-S) fuzzy controller based on eigenstructure assignment (EA) and optimized by differential evolution algorithm (DE) is proposed, and the application of this control strategy in the hydro-turbine governing system (HTGS) is studied. Based on the non-linear model of HTGS, the corresponding state-space equations (SSE) are obtained by linearization through multiple equilibrium points. Combining with the principle of T-S fuzzy control, a T-S fuzzy model of HTGS integrating multiple SSE with generator power angle as a prerequisite is established. This paper adopts the EA method to design the fitness function in the optimization process and uses DE to complete the optimization operation to improve the performance of T-S fuzzy control in HTGS. Which makes each Linear-Quadratic-Regulator (LQR) controller gain in the fuzzy control reach the optimal under the constraint conditions. The simulation results show that compared with the standard fitness functions IAE (integral absolute error), ITAE (integral time absolute error) and ISE (integral square error), the fitness function designed using the EA method can expand the angle between the left and right eigenvectors of the T-S closed-loop system, and push the closed-loop pole from the imaginary axis to the left. That will make the adjustment time of the system shorter and the robustness against external interferences enhanced. The results also show that the proposed control strategy has better dynamic performance during the non-linear motion of HTGS and is superior to the existing control strategy.

The converter is an important component of a wind turbine, and its control system has a significant impact on the dynamic output characteristics of the wind turbine. For the double-fed induction generator (DFIG) converter, the control parameter identification method is proposed. In this paper, a detailed dynamic model of DFIG with the converter is built, and the trajectory sensitivity method is used to study the observation points that are sensitive to the change of control parameters as the observation quantity for control parameter identification; the Whale Optimization Algorithm (WOA) is used to study the converter control system parameters that dominate the output characteristics of DFIG in the dynamic full-process simulation. To validate the proposed method, four classical test functions are used to verify the effectiveness of the algorithm, and the control parameters are identified by setting a three-phase grounded short-circuit fault under maximum power point tracking (MPPT), and the identification results are compared with particle swarm optimization (PSO) and chaotic particle swarm optimization (CPSO) to show the superiority of the proposed method. The final results show that the proposed WOA can identify the control system parameters faster and more accurately.

The central intention of this paper is to explore original teleology and to solve the riddle of matter based on the analysis of the flow of absolute consciousness. The paper unfolds in four steps. Firstly, it analyzes the origin of teleology in terms of Husserl’s theory of intentional acts. Since Husserl’s phenomenology itself contains teleological ideas, the creativity and goal-direction of the will reveals the intrinsic connection between will and teleology. Secondly, the relationship between the will and original teleology is discussed around the riddle of matter raised by Husserl, and the reason why teleology originates in the act of will is explained. Thirdly, the paper reinterprets the divine entelechy from the perspective of the creativity of the divine will, and points out that Husserl’s concept of God is not only the idea of the highest good, but also an entelechy that is constantly engaged in creating and becoming. Finally, in order to further argue for the important role of the will in solving the problem of teleology, this paper discusses the intrinsic relationship between transcendental reduction and the will.

Variations in generator parameters that occur during the operation of a doubly-fed induction wind turbine (DFIG) constitute a significant factor in the degradation of control performance. To address the problem of difficulty in identifying multiple parameters simultaneously in DFIG, a parameter identification method depending on the adaptive grey wolf algorithm with an information-sharing search strategy (ISIAGWO) is proposed to solve the problem of low accuracy and slow identification speed of multiple parameters in DFIG. The easily obtainable generator outlet current was selected as the observed quantity, and the trajectory sensitivity analysis was performed on the five electrical parameters of the DFIG to derive its discriminability. Finally, the parameter recognition of the DFIG was carried out using the ISIAGWO algorithm in the MATLAB/Simulink simulation software, applying the proposed calculation functions. The experimental results show that the ISIAGWO algorithm has better identification accuracy, stability, and convergence for DFIG’s generator parameter identification.

This paper proposes a new cascaded fractional-order controller (CC-FOC) to solve the load frequency control (LFC) problem of an interconnected power system. The CC-FOC consists of a three-degree-of-freedom fractional-order proportional-integral-differential (3DOF-FOPID) controller and a fractional-order proportional-integral (FOPI) controller. Each area of the two-area interconnected power system in this study consists of a thermal unit, a hydro unit, a diesel unit, and a doubly-fed induction generator (DFIG). The enhanced particle swarm optimization (PSO) and gravitational search algorithm (GSA) under the chaotic map optimization (CPSOGSA) technique are used to optimize the controller gains and parameters to enhance the load frequency control performance of the cascade controller. Moreover, simulation experiments are conducted for the interconnected power system under load perturbation and random wind speed fluctuations. The simulation results demonstrate that the proposed cascaded fractional-order controller outperforms the traditional proportional-integral-differential (PID) controller and three other fractional-order controllers in terms of LFC performance. The suggested cascade controller displays strong dynamic control performance and the resilience of the cascade fractional-order controller by adjusting the load disturbance and analyzing the system characteristics.

To provide supporting tools for the community life circle scientific planning and efficient management, the paper takes the urban central area as the research object, and constructs the community life circle database based on multi-source data fusion. High-resolution remote sensing technology and mobile internet complement traditional planning institute data and provide effective ways to obtain multi-source data. When multi-source data describes the same feature, the data content could be repetitive or conflicting, which causes the data to be inaccurate. Multi-source data fusion coordinates repetitive or conflicting data contents, and forms a unified, accurate and useful description on the same feature. The results: (1) Land use, building, supporting facility, and road are important construction elements of community life circle. (2) The planning institute, Baidu place API interface and high-resolution remote sensing technology are the main data acquisition channels. The Baidu POI data is an effective supplement to planning institute facility data. (3) Based on the high-resolution remote sensing images change detection and vector extraction technology, the paper updates planning institute building data. The new information technology has enriched the data sources, the paper contributes to take full advantage of multi-source data and improve the reality, completeness and accuracy of database.

Abstract Thrombosis is a global health issue and one of the leading factors of death. However, its diagnosis has been limited to the late stages, and its therapeutic window is too narrow to provide reasonable and effective treatment. In addition, clinical thrombolytics suffer from a short half-life, allergic reactions, inactivation, and unwanted tissue hemorrhage. Nano-medicines have gained extensive attention in diagnosis, drug delivery, and photo/sound/magnetic-theranostics due to their convertible properties. Furthermore, diagnosis and treatment of thrombosis using nano-medicines have also been widely studied. This review summarizes the recent advances in this area, which revealed six types of nanoparticle approaches: (1) in vitro diagnostic kits using “synthetic biomarkers”; (2) in vivo imaging using nano-contrast agents; (3) targeted drug delivery systems using artificial nanoparticles; (4) microenvironment responsive drug delivery systems; (5) drug delivery systems using biological nanostructures; and (6) treatments with external irradiation. The investigations of nano-medicines are believed to be of great significance, and some of the advanced drug delivery systems show potential applications in clinical theranotics.

Hepatocellular carcinoma (HCC) is characterized by poor prognosis and high mortality. The treatment of HCC is closely related to the stage, and the early-stage of HCC patients usually accompanies a more long-term survival rate after clinical treatment. Hence, there are critical needs to develop effective imaging agents with superior diagnostic precision for HCC detection at an early stage. Recently, mesoporous silica nanoparticles (MSNs) based imaging agents have gained extensive attentions in HCC detection, which can serve as a multifunctional nanoplatform with controllable size and facile surface functionalization. This perspective summarizes recent advances in MSNs based imaging agents for HCC detection by the incorporation of several clinical imaging modalities. Multi-modal imaging system has been developed for higher spatial resolution and sensitivity. Even though some limitations and challenges need to be overcome, we envision the development of novel MSNs based imaging agents will offer great potential applications in clinical HCC detection.

Nutraceuticals provide many biological benefits besides their basic nutritional value. However, their biological efficacies are often limited by poor absorption and low bioavailability. Nanomaterials have received much attention as potential delivery systems of nutrients and phytonutrients for multiple applications. Nanomicelles are nanosized colloidal structures with a hydrophobic core and hydrophilic shell. Due to their unique characteristics, they have shown great perspectives in food and nutraceutical science. In this review, we discussed the unique properties of nanomicelles. We also emphasized the latest advances on the design of different nanomicelles for efficient delivery and improved bioavailability of various nutrients. The role of nanomicelles in the efficacy improvement of bioactive components from nutraceutical and health foods has been included. Importantly, the safety concerns on nano-processed food products were highlighted.

ObjectiveAccumulative evidence suggests that gut microbiota play an important role in bone remodeling and hence bone health maintenance. This study aimed to explore the association of gut microbiota with the risk of osteoporosis and to identify potential disease-related taxa, which may be promising targets in osteoporosis prevention and treatment in the future.MethodsAbsolute quantification 16S ribosomal RNA gene sequencing was used to detect absolute and relative abundances of gut microbiota in 44 patients with osteoporosis and 64 controls. In combination with one of our previous studies, a total of 175 samples were involved in the relative abundance analysis.ResultsCompared with the controls, the patients with osteoporosis had higher absolute and relative abundances of Bacteroidetes phylum, and Bacteroides and Eisenbergiella genera. The absolute abundances of Clostridium_XlVa, Coprococcus, Lactobacillus, and Eggerthella genera increased, and that of the Veillonella genus decreased in the osteoporosis group. As for relative abundance, that of the Parabacteroides and Flavonifractor genera increased, whereas that of the Raoultella genus decreased in the osteoporosis group. Controlling for potential confounders, the associations of Clostridium_XlVa, Coprococcus, and Veillonella genera with the risk of osteoporosis did not maintain significance. Ridge regression analysis suggested that Bacteroides is associated with reduced bone mineral density (BMD) and T-score at lumbar spines, and Anaerovorax is associated with increased BMD at the femoral neck. Functional predictions revealed that 10 Kyoto Encyclopedia of Genes and Genomes pathways were enriched in the osteoporosis group.ConclusionsGut microbiota compositions may contribute to the risk of osteoporosis. Several specific taxa and functional pathways are identified to associate with reduced bone density, thus providing epidemiologic evidence for the potential role of aberrant gut microbiota in osteoporosis pathogenesis.

Due to the excellent electrical properties, the emerging field-effect transistor (FET) based on two-dimensional transition metal dischalcogenide (TMD) is an excellent candidate for future space applications. However, the device performance is significantly impacted by total-ionizing dose (TID) effects. In this paper, the TID effects of TMD FETs are investigated comprehensively by means of developing a surface-potential based drain current model. Not only the radiation-induced trapped charges but also mobility degradation are incorporated into the proposed model. The model approach is demonstrated for a bottom-gated TMD FET, that simulation results are in good agreement with the experimental data. Based on the validity of the proposed method, the influence of TID effects on the TMD-on-insulator (TMDOI) FET is presented and discussed under different total dose levels. The results show that surface potential is strongly dependent on the oxide trapped charges, resulting in a major contribution to the negative shift of threshold voltage and the significant increase of leakage current. Besides, the interface trapped charges reduce the effective carrier mobility, which plays a dominant role on the decrease of transconductance and increase of subthreshold voltage swing. Finally, this paper gives insight into some possible mitigation techniques of TID effects on TMD FETs.

Fracturing pumpheads are typical pressure vessels that experience frequent fatigue failure under the effect of notches in their cross-bore. To enhance the fatigue life of fracturing pumpheads, the study of the notch effect is indispensable and important to establish a reliable mathematical model to predict their fatigue life. In the present paper, two novel fatigue life prediction models are proposed for notched specimens. In these models, two new geometric fatigue failure regions are defined to improve the weight function. Finally, the elaborated novel stress-field intensity approach was applied to three different types of notched specimens. Experiment results indicate that the new SFI approach achieves 47.82%, 39.48%, and 31.85% higher prediction accuracy than the traditional SFI approach, respectively. It was found that the modified SFI approach provided better predictions than the traditional SFI approach and the TCD method. The II-th novel SFI approach had the highest accuracy, and the I-th novel SFI approach was more suitable for sharply notched specimens.