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Abstract Antibody–drug conjugates (ADCs) are among the fastest-growing classes of anticancer drugs, making it crucial to evaluate their potential for causing peripheral neuropathy. We analyzed data from the FAERS database (January 1, 2014, to June 30, 2023) using disproportionality and Bayesian methods. We identified 3076 cases of ADC-associated peripheral neuropathy. Our study revealed significant signals for all ADCs (ROR 1.82, 95% CI 1.76–1.89). ADCs with tubulin-binding payloads showed significant peripheral neuropathy signals (ROR 2.31, 95% CI 2.23–2.40), whereas those with DNA-targeting (ROR 0.48, 95% CI 0.39–0.59) and topoisomerase 1 inhibitor (ROR 0.56, 95% CI 0.48–0.66) payloads exhibited non-significant signals. Signals for peripheral sensory neuropathy were 4.83, 2.44, 2.74, and 2.21 (calculated based on IC025) for brentuximab vedotin, trastuzumab emtansine, enfortumab vedotin, and polatuzumab vedotin, while signals for peripheral motor neuropathy were 5.31, 0.34, 2.27, and 0.03, respectively. The median time to onset for all ADCs was 127 days (interquartile range 40–457). Tisotumab vedotin had the highest hospitalization rate at 26.67%, followed by brentuximab vedotin at 25.5%. Trastuzumab emtansine had the highest mortality rate ,with 80 deaths (11.96%) among 669 cases. Based on FAERS database, only ADCs with tubulin-binding payloads exhibited significant peripheral neuropathy signals. Brentuximab vedotin and enfortumab vedotin showed similar profiles for peripheral sensory neuropathy and motor neuropathy. Given the delayed time to onset and potentially poor outcomes, ADC-related peripheral neuropathy warrants significant attention.

Cross-view image clustering (CIC) showcases immense potential in recognizing image patterns due to the power to aggregate information between views without labels. However, most CIC ignore intricate coupling relationships between category and redundant features in aggregating complementary information of cross-view images, which may restrict performance in recognizing patterns of images. To this end, a cross-view mutual information decoupling based deep generative clustering approach is proposed for recognizing image patterns (DMID-UIC), which contains information maximization deep generative module and self-supervised posterior inference module. Specifically, the former maximizes the mutual information between data and semantics within the generative adversarial network to decouple category and redundant features hidden in cross-view images, which guarantees the separation of different semantic distributions in the data space. The latter models the distribution fitting between generated data and the prior semantic code as a classification task, via treating partitioning results of common representations between views as self-supervised labels. Meanwhile, to better optimize the model, an EM optimization strategy is designed to enhance the above two module learning in an iterative manner. Finally, comprehensive results verify the superiority and effectiveness of DMID-UIC. DMID-UIC improves ACC by 10.1% on the Caltech 101-7 dataset, compared to the second-best result.

Abstract Rhodococcus equi (R. equi) is a zoonotic opportunistic pathogen that mainly causes fatal lung and extrapulmonary abscesses in foals and immunocompromised individuals. To date, no commercial vaccine against R. equi exists. We previously screened all potential vaccine candidates from the complete genome of R. equi using a reverse vaccinology approach. Five of these candidates, namely ABC transporter substrate-binding protein (ABC transporter), penicillin-binding protein 2 (PBD2), NlpC/P60 family protein (NlpC/P60), esterase family protein (Esterase), and M23 family metallopeptidase (M23) were selected for the evaluation of immunogenicity and immunoprotective effects in BALB/c mice model challenged with R. equi. The results showed that all five vaccine candidate-immunized mice experienced a significant increase in spleen antigen-specific IFN-γ- and TNF-α-positive CD4 + and CD8 + T lymphocytes and generated robust Th1- and Th2-type immune responses and antibody responses. Two weeks after the R. equi challenge, immunization with the five vaccine candidates reduced the bacterial load in the lungs and improved the pathological damage to the lungs and livers compared with those in the control group. NlpC/P60, Esterase, and M23 were more effective than the ABC transporter and PBD2 in inducing protective immunity against R. equi challenge in mice. In addition, these vaccine candidates have the potential to induce T lymphocyte memory immune responses in mice. In summary, these antigens are effective candidates for the development of protective vaccines against R. equi. The R. equi antigen library has been expanded and provides new ideas for the development of multivalent vaccines.

Banana is a significant crop, and three banana leaf diseases, including Sigatoka, Cordana and Pestalotiopsis, have the potential to have a serious impact on banana production. Existing studies are insufficient to provide a reliable method for accurately identifying banana leaf diseases. Therefore, this paper proposes a novel method to identify banana leaf diseases. First, a new algorithm called K-scale VisuShrink algorithm (KVA) is proposed to denoise banana leaf images. The proposed algorithm introduces a new decomposition scale K based on the semi-soft and middle course thresholds, the ideal threshold solution is obtained and substituted with the newly established threshold function to obtain a less noisy banana leaf image. Then, this paper proposes a novel network for image identification called Ghost ResNeSt-Attention RReLU-Swish Net (GR-ARNet) based on Resnet50. In this, the Ghost Module is implemented to improve the network's effectiveness in extracting deep feature information on banana leaf diseases and the identification speed; the ResNeSt Module adjusts the weight of each channel, increasing the ability of banana disease feature extraction and effectively reducing the error rate of similar disease identification; the model's computational speed is increased using the hybrid activation function of RReLU and Swish. Our model achieves an average accuracy of 96.98% and a precision of 89.31% applied to 13,021 images, demonstrating that the proposed method can effectively identify banana leaf diseases.

Coal fine intrusion into hydraulic propped fractures of coal seam easily leads to the blockage of the fracture, resulting in the decrease of the conductivity and the reduction of coal reservoir permeability, which seriously affects the stable discharge and production of coalbed methane well. In this paper, the permeability dynamic evolution models of coal fine intrusion into propped fractures were established before the shutdown and after the restart of coalbed methane well, and the experiments of coal fine intrusion into propped fracture under continuous and intermittent flow conditions were carried out by using the coal-rock conductivity test system, which verified the correctness of the models and studied the influence of coalbed methane well stoppage and drainage velocity on the permeability spatial and temporal evolution laws. The results indicate that with the increase of coal fine migration time, the permeability of propped fracture decreases slowly after a sudden drop, and along the direction of coal fine migration, the spatial pore loss rate of propped fracture decreases gradually, resulting in the permeability of fracture decreases along the direction of coal fine migration. With the continuous coal fine intrusion into propped fracture, the propped fracture pore loss rate after the shut-in and restart of coalbed methane wells is larger than that before the shutdown, and the permeability cannot be restored to the level before the shutdown. The slower the flow rate of drainage, the slower the permeability attenuation rate of coal fine intrusion into propped fracture, and the higher the permeability. During the coal fine invasion into proppant fracture at the low drainage flow rate, the fracture permeability is more sensitive to the flow rate change, and the less damage to the propped fracture permeability caused by the well shutdown. In the process of coal fine intrusion, the larger the deposition coefficient of coal fine is, the smaller the proximal fracture permeability and the larger the distal fracture permeability. The larger the diffusion coefficient is, the smaller the distal fracture permeability of the propped fracture is. The permeability of the proximal fracture is very little affected by the diffusion coefficient, and the damage to the proximal fracture permeability is more serious. In the process of coal fine intrusion, the proximal fracture permeability declines faster, while the distal fracture permeability declines slowly. The deposition coefficient changes have a significant influence on the proximal fracture permeability, while the diffusion coefficient changes have a more significant influence on the distal fracture permeability.

Netrin-1 (NTN1) is involved in psychological alterations caused by central nerve system diseases. The primary objective of this research was to investigate whether a deficiency of neuron-derived NTN1 in the remote brain regions affects SCI outcomes. To examine the roles and mechanisms of neuron-derived NTN1 during SCI, Western blots, Nissl staining, immunochemical technique, RNA-sequence, and related behavioral tests were conducted in the study. Our study revealed that mice lacking NTN1 exhibited normal morphological structure of the spinal cords, hippocampus, and neurological function. While neuron-derived NTN1deletion mechanistically disrupted neuronal regeneration and aggregates neuronal apoptosis and ferroptosis in the intermediate phase following SCI. Additionally, neuroinflammation was significantly enhanced in the early phase, which could be related to activation of the NF-κB signaling pathway. Overall, our findings indicate that the deletion of neuron-derived NTN1 leads to the activation of the NF-κB pathway, contributing to the promotion of neuronal apoptosis and ferroptosis, and the pathological progression of SCI.

Summary: Background: The 5-year survival rate of oesophageal squamous cell carcinoma (ESCC) is approximately 20%. The prognosis and drug response exhibit substantial heterogeneity in ESCC, impeding progress in survival outcomes. Our goal is to identify a signature for tumour subtype classification, enabling precise clinical treatments. Methods: Utilising pre-treatment multi-omics data from an ESCC dataset (n = 310), an enhancer methylation-eRNA-target gene regulation network was constructed and validated by in vitro experiments. Four machine learning methods collectively identified core target genes, establishing an Enhancer Demethylation-Regulated Gene Score (EDRGS) model for classification. The molecular function of EDRGS subtyping was explored in scRNA-seq (n = 60) and bulk-seq (n = 310), and the EDRGS's potential to predict treatment response was assessed in datasets of various cancer types. Findings: EDRGS stratified ESCCs into EDRGS-high/low subtypes, with EDRGS-high signifying a less favourable prognosis in ESCC and nine additional cancer types. EDRGS-high exhibited an immune-hot but immune-suppressive phenotype with elevated immune checkpoint expression, increased T cell infiltration, and IFNγ signalling in ESCC, suggesting a better response to immunotherapy. Notably, EDRGS outperformed PD-L1 in predicting anti-PD-1/L1 therapy effectiveness in ESCC (n = 42), kidney renal clear cell carcinoma (KIRC, n = 181), and bladder urothelial carcinoma (BLCA, n = 348) cohorts. EDRGS-low showed a cell cycle-activated phenotype with higher CDK4 and/or CDK6 expression, demonstrating a superior response to the CDK4/6 inhibitor palbociclib, validated in ESCC (n = 26), melanoma (n = 18), prostate cancer (n = 15) cells, and PDX models derived from patients with pancreatic cancer (n = 30). Interpretation: Identification of EDRGS subtypes enlightens ESCC categorisation, offering clinical insights for patient management in immunotherapy (anti-PD-1/L1) and CDK4/6 inhibitor therapy across cancer types. Funding: This study was supported by funding from the National Key R&D Program of China (2021YFC2501000, 2020YFA0803300), the National Natural Science Foundation of China (82030089, 82188102), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-018, 2022-I2M-2-001, 2021-I2M-1-067), the Fundamental Research Funds for the Central Universities (3332021091).

Abstract Background Nervous system toxicity (NST) is one of the most frequent and dangerous side effects of chimeric antigen receptor T-cell (CAR-T) therapy, which is an effective treatment for related tumors in most relapsed/refractory (r/r) hematologic malignancies. Current clinical trial data do not fully reflect the real-world situation. Therefore, this study evaluated the NST of CAR-T therapy using the FDA Adverse Event Reporting System (FAERS). Methods Data were retrieved from FAERS for the period from January 1, 2017 to March 31, 2023. Disproportionality analysis and Bayesian analysis were used for data mining. The reporting odds ratio (ROR) for NST with 95% confidence interval (CI) was calculated for each CAR-T product. The time to onset (TTO) and clinical outcomes due to CAR-T therapy-associated NST were assessed. Results Overall, 6946 cases of NST associated with CAR-T therapy were identified. The patients had a median age of 61 years (interquartile range [IQR]: 47–69 years). Significant signals were observed for all CAR-T products (ROR: 2.19, 95% CI: 2.13–2.44). Anti-CD19 CAR-T products showed a higher NST signal than anti-B cell maturation antigen (BCMA) CAR-T products (ROR025 2.13 vs. 1.98). Brexucabtagene autoleucel (ROR: 3.17, 95% CI: 2.90–3.47) and axicabtagene ciloleucel (ROR: 2.92, 95% CI: 2.81–3.03) had the two highest NST signals. For the preferred term “brain edema,” the highest signals were obtained for CD28 CAR-T products. The median TTO of NST for all CAR-T products was 7 days (IQR: 3–17 days). The proportion of death, life-threatening and hospitalization adverse events associated with NST was 20.06%, 7.21%, and 32.70%, respectively. The proportion of death outcomes was higher in patients treated with tisagenlecleucel (30.36%) than in those treated with other CAR-T products, except ciltacabtagene autoleucel (P

[Objective] Unlike the existing CBTC (communication-based train control) system control mechanism, the ATC (autonomous train control) system achieves autonomous train operation by directly controlling wayside resources. To improve the operational efficiency of turnout segments, it is necessary to study the control algorithm of ATC system in turnout segments, using smaller granularity turnout safety zones as control resources for ATC system. [Method] The control algorithm of ATC system considers the track section as a shared resource, with turnout safety zones allocated separately for train use. A comparative analysis is conducted between ATC system and CBTC system in scenarios with single-slip turnouts and crossover turnouts, and simulation calculations are performed using real train control system and turnout parameters to improve the operational efficiency. [Result & Conclusion] Compared to the conventional interlocking algorithm of CBTC system, the control algorithm of ATC system for turnout safety zones performs better. In single-slip turnout scenarios, the maximum increase in the safety interval for train operation reaches 74.5%. In crossover turnout zone scenarios, the maximum increase in train turnout-passing time reaches 33.8%. By optimizing the system architecture and control algorithm, ATC system increases flexibility and efficiency, serving as an important direction for the development of the next generation train control system.

In recent years, numerous deep learning-based methods have gained increasing attention in hyperspectral classification, particularly the Graph Neural Network, which exhibits superior capabilities in structural description. However, a single graph structure is not suitable for hyperspectral feature representation. Therefore, we propose a novel Multiple-Scale graph network structure, known as the Multi-Scale Dense Graph Attention network for hyperspectral classification. Firstly, semi-supervised local Fisher discriminant analysis and superpixel segmentation were employed for dimensionality reduction and multi-scale graph construction, respectively. Secondly, Spectral-Spatial convolution is applied to extract shallow features from the image. Subsequently, an improved graph self-attention network is sequentially applied to each scale graph, and the different scale graphs are densely connected through spatial feature alignment modules, designed using twice matrix multiplication. Finally, the combined pixel-level feature map from multiple graph spaces is derived, and Spectral-Spatial convolution is employed to fuse the abundant feature maps for hyperspectral classification. Experimental results on various hyperspectral datasets demonstrate the superiority of our MSDesGATnet over many state-of-the-art methods. The code is available at https://github.com/l7170/MSDesGAT.git.

Abstract This paper presents a numerical model using the boundary element method for determining the hydrodynamic added mass and added damping of an elastic bridge pier with arbitrary cross-section. Combining the Euler–Bernoulli beam theory with the constant boundary element method, the modal superposition method is used to consider the deformable boundary conditions on the surface of elastic piers to couple the interaction between the elastic pier and water, and the equations for the hydrodynamic added mass and added damping of a general section pier considering the effect of pier-water coupling are derived. The accuracy of the developed model is verified by a benchmark experiment. The developed model is calculated for circular piers and compared with the added mass analytical formulation. The effects of oscillating frequency and structure geometry on the added mass and added damping are further investigated. Results demonstrate that the developed model can be used to solve the hydrodynamic added mass and added damping problems of the elastic bridge pier. Compared to the analytical formula, the developed method incorporates the consideration of added damping in the analysis of the pier-water coupling problem. Oscillating frequency and structure geometry have significant effects on added mass and added damping.

To address the problems of the insufficient semantic fusion between text and questions and the lack of consideration of global semantic information encountered in machine reading comprehension models, we proposed a machine reading comprehension model called BERT_hybrid based on the BERT and hybrid attention mechanism. In this model, BERT is utilized to separately map the text and questions into the feature space. Through the integration of Bi-LSTM, an attention mechanism, and a self-attention mechanism, the proposed model achieves a comprehensive semantic fusion between text and questions. The probability distribution of answers is computed using Softmax. The experimental results on the public dataset DuReader demonstrate that the proposed model achieves improvements in BLEU-4 and ROUGE-L scores compared to existing models. Furthermore, to validate the effectiveness of the proposed model design, we analyze the factors influencing the model’s performance.

In order to reduce carbon emissions from the power grid, photovoltaic (PV) generation units and controllable nonlinear loads based on power electronic devices are gradually becoming more prevalent in the power system. In a PV grid-connected system featuring controllable nonlinear loads, the interplay among PV grid-connected inverters, the loads, and the grid can potentially lead to voltage oscillations. To tackle this challenge, this paper introduces an optimization-based method for suppressing oscillations, which carefully balances system stability with response performance. Firstly, an impedance model of the system is established by applying the harmonic linearization method, and system stability is analyzed using the “logarithmic frequency stability criterion”. Subsequently, impedance relative sensitivity is used to identify key parameters that affect system stability, and the interaction between key parameters is considered to analyze the stability range for these parameters. On this basis, a parameter optimization method based on the particle swarm optimization algorithm is proposed to balance system stability and response performance. The effectiveness and robustness of this method are verified through a simulation analysis.

As power big data plays an increasingly important role in the operation, maintenance, and management of power systems, complex and covert false data attacks pose a serious threat to the safe and stable operation of the power system. This article first explores the characteristics of new power systems, and the challenges posed by false data attacks. The application of big data technology in power production optimization, energy consumption analysis, and user service improvement is then investigated. The article classifies typical attacks against the four stages of power big data systems in detail and analyzes the characteristics of the attack types. It comprehensively summarizes the attack detection technologies used in the four key stages of power big data, including state estimation, machine learning, and data-driven attack detection methods in the data collection stage; clock synchronization monitoring and defense strategies in the data transmission stage; data processing and analysis, data integrity verification and protection measures of blockchain technology in the third stage; and traffic supervision, statistics and elastic computing measures in the control and response stage. Finally, the limitations of attack detection mechanisms are proposed and discussed from three dimensions: research problems, existing solutions, and future research directions. It aims to provide useful references and inspiration for researchers in power big data security to promote technological progress in the safe and stable operation of power systems.

The modular multilevel converter based high voltage direct current (MMC-HVDC) is a dynamic power balancing system. The control system of MMC generally adopts a dual closed-loop vector control strategy based on the traditional instantaneous power model under asymmetric grid state, which has complex control structure and low control accuracy. This paper introduces a flexible instantaneous power model and establishes a general power equation with active power and new reactive power as control objects. Based on this, an improved sliding-mode MMC-HVDC direct power control strategy based on the new instantaneous power model is proposed which combines the flexible instantaneous power model and the improved sliding-mode control method to eliminate the twice grid-frequency ripples in both active and reactive power under asymmetric grid states. Furthermore, it omits the inner-loop controller and power compensation terms while optimizing the control structure. Simulation results show that the proposed method has better dynamic responsiveness, control accuracy and robustness under operating conditions such as asymmetric grid state and parameter perturbation which can better exploit the advantages of the flexible instantaneous power model.

Cross-modal retrieval for rice leaf diseases is crucial for prevention, providing agricultural experts with data-driven decision support to address disease threats and safeguard rice production. To overcome the limitations of current crop leaf disease retrieval frameworks, we focused on four common rice leaf diseases and established the first cross-modal rice leaf disease retrieval dataset (CRLDRD). We introduced cross-modal retrieval to the domain of rice leaf disease retrieval and introduced FHTW-Net, a framework for rice leaf disease image–text retrieval. To address the challenge of matching diverse image categories with complex text descriptions during the retrieval process, we initially employed ViT and BERT to extract fine-grained image and text feature sequences enriched with contextual information. Subsequently, two-way mixed self-attention (TMS) was introduced to enhance both image and text feature sequences, with the aim of uncovering important semantic information in both modalities. Then, we developed false-negative elimination–hard negative mining (FNE-HNM) strategy to facilitate in-depth exploration of semantic connections between different modalities. This strategy aids in selecting challenging negative samples for elimination to constrain the model within the triplet loss function. Finally, we introduced warm-up bat algorithm (WBA) for learning rate optimization, which improves the model’s convergence speed and accuracy. Experimental results demonstrated that FHTW-Net outperforms state-of-the-art models. In image-to-text retrieval, it achieved R@1, R@5, and R@10 accuracies of 83.5%, 92%, and 94%, respectively, while in text-to-image retrieval, it achieved accuracies of 82.5%, 98%, and 98.5%, respectively. FHTW-Net offers advanced technical support and algorithmic guidance for cross-modal retrieval of rice leaf diseases.

DNA strand displacement (DSD) is an efficient technology for constructing molecular circuits. However, system computing speed and the scale of logical gate circuits remain a huge challenge. In this paper, a new method of coding DNA domains is proposed to carry out logic computation. The structure of DNA strands is designed regularly, and the rules of domain coding are described. Based on this, multiple-input and one-output logic computing modules are built, which are the basic components forming digital circuits. If the module has n inputs, it can implement 2n logic functions, which reduces the difficulty of designing and simplifies the structure of molecular logic circuits. In order to verify the superiority of this method for developing large-scale complex circuits, the square root and exponentiation molecular circuits are built. Under the same experimental conditions, compared with the dual-track circuits, the simulation results show that the molecular circuits designed based on the domain coding strategy have faster response time, simpler circuit structure, and better parallelism and scalability. The method of forming digital circuits based on domain coding provides a more effective way to realize intricate molecular control systems and promotes the development of DNA computing.

Abstract Calorie restriction (CR) or a fasting regimen is considered one of the most potent non-pharmacological interventions to prevent chronic metabolic disorders, ameliorate autoimmune diseases, and attenuate aging. Despite efforts, the mechanisms by which CR improves health, particularly brain health, are still not fully understood. Metabolic homeostasis is vital for brain function, and a detailed metabolome atlas of the brain is essential for understanding the networks connecting different brain regions. Herein, we applied gas chromatography-mass spectrometry-based metabolomics and lipidomics, covering 797 structurally annotated metabolites, to investigate the metabolome of seven brain regions in fasted (3, 6, 12, and 24 h) and ad libitum fed mice. Using multivariate and univariate statistical techniques, we generated a metabolome atlas of mouse brain on the global metabolic signature dynamics across multiple brain regions following short-term fasting (STF). Significant metabolic differences across brain regions along with STF-triggered region-dependent metabolic remodeling were identified. We found that STF elicited triacylglycerol degradation and lipolysis to compensate for energy demand under fasting conditions. Besides, changes in amino acid profiles were observed, which may play crucial roles in the regulation of energy metabolism, neurotransmitter signaling, and anti-inflammatory and antioxidant in response to STF. Additionally, this study reported, for the first time, that STF triggers a significant elevation of N-acylethanolamines, a class of neuroprotective lipids, in the brain and liver. These findings provide novel insights into the molecular basis and mechanisms of CR and offer a comprehensive resource for further investigation.

Abstract While multi-modal foundation models pre-trained on large-scale data have been successful in natural language understanding and vision recognition, their use in medical domains is still limited due to the fine-grained nature of medical tasks and the high demand for domain knowledge. To address this challenge, we propose an approach called Knowledge-enhanced Auto Diagnosis (KAD) which leverages existing medical domain knowledge to guide vision-language pre-training using paired chest X-rays and radiology reports. We evaluate KAD on four external X-ray datasets and demonstrate that its zero-shot performance is not only comparable to that of fully supervised models but also superior to the average of three expert radiologists for three (out of five) pathologies with statistical significance. Moreover, when few-shot annotation is available, KAD outperforms all existing approaches in fine-tuning settings, demonstrating its potential for application in different clinical scenarios.

Transparent conductive films (TCFs) are crucial components of solar cells. In this study, F, Cl, and Ga co-doped ZnO (FCGZO) TCFs were deposited onto a glass substrate using the sol-gel spin-coating method and rapid thermal annealing. The effects of F-doping content on the structural, morphological, electrical, and optical properties of FCGZO films were examined by XRD, TEM, FE-SEM, PL spectroscopy, XPS, Hall effects testing, and UV–vis–NIR spectroscopy. All prepared ZnO films exhibited a hexagonal wurtzite structure and preferentially grew along the c axis perpendicular to the substrate. Changes in the doping concentration of F changed the interplanar crystal spacing and O vacancies in the film. At a doping ratio of 2% (in mole), the F, Cl, and Ga co-doped ZnO film exhibited the best photoelectric performance, with a carrier concentration of 2.62 × 1020 cm−3, mobility of 14.56 cm2/(V·s), and resistivity of 1.64 × 10−3 Ω·cm. The average transmittance (AT) in the 380–1 600 nm region nearly 90% with air as the reference, and the optical band gap was 3.52 eV.

This paper investigates the attitude control of rigid spacecraft in the presence of uncertainties, disturbances, and actuator faults. In order to effectively address these challenges and improve the performance of the system, a novel actor-critic neural-network-based fractional-order sliding mode control (ACNNFOSMC) has been developed for spacecraft. The integration of actor-critic neural network, fractional-order theory, and sliding mode control enables dual functionality: the actor-critic neural network serves to approximate the aggregate of uncertain parameters, disturbances, and actuator faults, thereby facilitating their compensation, while the fractional-order sliding mode control mechanism significantly improves the system’s tracking precision and overall robustness against uncertainties. Theoretical analyses are presented to analyze the stability of the proposed control framework. Thorough examination via simulation experiments affirms the effectiveness and control precision of attitude of our proposed control strategy, even in complex operational scenarios.

Among non-destructive testing (NDT) techniques, fast neutron radiography with a higher penetration capability has achieved rapid advancements. However, the application of the radiography detector in many fast neutron imaging systems is limited by unfavorable detection efficiency and imaging spatial resolution. In this paper, a fast neutron radiography detector was designed, which was composed of a pixelated EJ200 scintillator array, a 16 × 16 silicon photomultiplier (SiPM) array, and capacitive multiplexing network readout electronics. The main parameters of the detector were optimized using Monte Carlo simulations. In addition, the prototype of the detector was fabricated and tested under a 14 MeV D-T neutron source. The preliminary test results demonstrated that the spatial resolution of the prototype reached 1.2 mm. Moreover, the conflict between spatial resolution and detection efficiency could be mitigated by using a pixelated scintillator structure. Overall, SiPMs enabled the extensive application of the imaging system because of their excellent photon detection performance, relatively low price, and joint possibility for large areas.

Carbon dioxide (CO2) has a wide range of uses such as food additives and raw materials for synthetic chemicals, while its application in the solid-state transformation of pharmaceutical crystals is rare. In this work, we report a case of using 1 atm CO2 as an accelerator to promote the polymorphic transformation of clarithromycin (CLA). Initially, crystal structures of Form 0′ and three solvates were successfully determined by single crystal X-ray diffraction (SCXRD) analysis for the first time and found to be isomorphous. Powder X-ray diffraction (PXRD) and thermal analysis indicated that the solvate desolvates and transforms into the structurally similar non-solvated Form 0′ at room temperature to ~50 °C. Form 0′ and Form II are monotropically related polymorphs with Form II being the most stable. Subsequently, the effect of CO2 on the transformation of CLA solvates to Form II was studied. The results show that CO2 can significantly facilitate the transformation of Form 0′ to Form II, despite no significant effect on the desolvation process. Finally, the molecular mechanism of CO2 promoting the polymorphic transformation was revealed by the combination of the measurement of adsorption capacity, theoretical calculations as well as crystal structure analysis. Based on the above results, a new pathway of preparing CLA Form II was designed: transform CLA solvates into Form 0′ in 1 atm air at 50 °C followed by the transformation of Form 0′ to Form II in 1 atm CO2 at 50 °C. This work provides a new idea for promoting the phase transformation of pharmaceutical crystals as well as a new scenario for the utilization of CO2.

Abstract Aims Inflammatory biomarkers, including CRP, the neutrophil‐to‐lymphocyte ratio (NLR), and the neutrophil‐to‐eosinophil ratio (NER), may predict outcomes in cancer. However, their value in immune checkpoint inhibitor (ICI) therapy‐associated cardiotoxicity remains elusive. We aimed to characterize the relationship of inflammatory markers with severity of ICI‐related cardiotoxicities (iRCs) and prognosis among patients with iRCs. Methods Patients who were diagnosed with iRCs between January 2019 and December 2021 were retrospectively enrolled and were dichotomized based on iRC severity into low‐grade (grade 1–2) vs. high‐grade (grade 3–4) groups. Results Forty‐seven patients were included. The median time‐to‐event from first ICI infusion to onset of iRCs was 35 days (IQR: 19.0–65.5 days). When compared with respective baseline values, cardiac biomarkers and inflammatory markers were significantly elevated at onset of iRCs. Compared with low‐grade iRCs, NER at iRC onset was significantly increased among patients with high‐grade iRCs (Group × Time, P

Abstract Background Artificial ovary (AO) is an alternative approach to provide physiological hormone to post-menopausal women. The therapeutic effects of AO constructed using alginate (ALG) hydrogels are limited by their low angiogenic potential, rigidity, and non-degradability. To address these limitations, biodegradable chitin-based (CTP) hydrogels that promote cell proliferation and vascularization were synthesized, as supportive matrix. Methods In vitro, follicles isolated from 10–12-days-old mice were cultured in 2D, ALG hydrogels, and CTP hydrogels. After 12 days of culture, follicle growth, steroid hormone levels, oocyte meiotic competence, and expression of folliculogenesis-related genes were monitored. Additionally, follicles isolated from 10–12-days-old mice were encapsulated in CTP and ALG hydrogels and transplanted into the peritoneal pockets of ovariectomised (OVX) mice. After transplantation, steroid hormone levels, body weight, rectal temperature, and visceral fat of the mice were monitored every two weeks. At 6 and 10 weeks after transplantation, the uterus, vagina, and femur were collected for histological examination. Results The follicles developed normally in CTP hydrogels under in vitro culture conditions. Additionally, follicular diametre and survival rate, oestrogen production, and expression of folliculogenesis-related genes were significantly higher than those in ALG hydrogels. After one week of transplantation, the numbers of CD34-positive vessels and Ki-67-positive cells in CTP hydrogels were significantly higher than those in ALG hydrogels (P

Abstract Mammalian spermatogenesis shows prominent chromatin and transcriptomic switches in germ cells, but it is unclear how such dynamics are controlled. Here we identify RNA helicase DDX43 as an essential regulator of the chromatin remodeling process during spermiogenesis. Testis-specific Ddx43 knockout mice show male infertility with defective histone-to-protamine replacement and post-meiotic chromatin condensation defects. The loss of its ATP hydrolysis activity by a missense mutation replicates the infertility phenotype in global Ddx43 knockout mice. Single-cell RNA sequencing analyses of germ cells depleted of Ddx43 or expressing the Ddx43 ATPase-dead mutant reveals that DDX43 regulates dynamic RNA regulatory processes that underlie spermatid chromatin remodeling and differentiation. Transcriptomic profiling focusing on early-stage spermatids combined with enhanced crosslinking immunoprecipitation and sequencing further identifies Elfn2 as DDX43-targeted hub gene. These findings illustrate an essential role for DDX43 in spermiogenesis and highlight the single-cell-based strategy to dissect cell-state-specific regulation of male germline development.

Abstract Background DTL has been found to be related with multiple cancers. However, comprehensive analyses, which identify the prediction value of DTL in diagnosis, prognosis, immune infiltration and treatment, have rarely been reported so far. Methods Combined with the data online databases, the gene expression, gene mutation, function enrichment and the correlations with the immunity status and clinical indexes of DTL were analyzed. Expression of DTL and the degree of immune cell infiltration were examined by immunofluorescence (IF) and immunohistochemistry (IHC) and analyzed by statistical analysis. Furthermore, the influences of DTL on the cell cycle, cell proliferation and apoptosis were detected by live cell imaging, IF and flow cytometric (FC) analysis. Genomic stability assays were conducted by chromosome slide preparation. Results DTL was widely expressed in various cells and tissues, while it was overexpressed in tumor tissues except acute myeloid leukemia (LAML). Pan-cancer bioinformatics analysis showed that the expression of DTL was correlated with the prognosis, immunotherapy, and clinical indexes in various cancers. In addition, gene set enrichment analysis (GSEA) uncovered that DTL was enriched in oocyte meiosis, pyrimidine metabolism, the cell cycle, the G2M checkpoint, mTORC1 signaling and E2F targets. Furthermore, the overexpression of DTL, and its association with immune cell infiltration and clinical indexes in liver hepatocellular carcinoma (LIHC), bladder urothelial carcinoma (BLCA) and stomach adenocarcinoma (STAD) were verified in our study. It was also verified that overexpression of DTL could regulate the cell cycle, promote cell proliferation and cause genomic instability in cultured cells, which may be the reason why DTL plays a role in the occurrence, progression and treatment of cancer. Conclusions Collectively, this study suggested that DTL is of clinical value in the diagnosis, prognosis and treatment of various cancers, and may be a potential biomarker in certain cancers.

Summary: Streptococcus agalactiae (S. agalactiae) is a contagious obligate parasite of the udder in dairy cows. Here, we examined S. agalactiae-host interactions in bovine mammary epithelial cells (BMECs) in vitro. We found that S. agalactiae infected BMECs through laminin β2 and integrin. Crk, Vps25, and RhoA were differentially expressed in S. agalactiae-infected cells. S. agalactiae infection activated FAK and Crk. FAK deficiency decreased the number of intracellular S. agalactiae and Crk activation. Knockdown of Crk or Vps25 increased the level of intracellular S. agalactiae, whereas its overexpression had the opposite effect. RhoA expression and actin cytoskeleton were altered in S. agalactiae-infected BMECs. Crk and Vps25 interact in cells, and invaded S. agalactiae also activates Crk, allowing it to cooperate with Vps25 to defend against intracellular infection by S. agalactiae. This study provides insights into the mechanism by which intracellular infection by S. agalactiae is regulated in BMECs.

Manipulating molecular self-assembly and disassembly in vivo may permit temporal control of drug delivery and release. Here, the authors report a fluorogenic cisplatin prodrug for cancer theranostics by leveraging stimuli-triggered in situ self-assembly and intracellular disassembly processes.

Cr coatings with a thickness of about 19 μm were synthesized on Zr-4 cladding using plasma-enhanced arc ion plating. A Zr-Cr micro-diffusion layer was formed via Cr ion cleaning before deposition to enhance the interface bonding strength. Cr coatings exhibit an obvious columnar crystal structure with an average grain size of 1.26 μm using SEM (scanning electron microscopy) and EBSD (electron backscatter diffraction) with a small amount of nanoscale pores on the surface. A long-term aqueous test at 420 ± 3 °C, 10.3 ± 0.7 MPa and isothermal oxidation tests at 900~1300 °C in air were conducted to evaluate the Cr-coated Zr-4 cladding. All the results showed that the Cr coatings had a significant protective effect to the Zr-4 alloy. However, the corrosion deterioration mechanism is different. A gradual thinning of the Cr coating was observed in a long-term aqueous test, but a cyclic corrosion mechanism of void initiation–propagation–cracking at the oxide film interface is the main corrosion characteristic of the Cr coating in isothermal oxidation. Different corrosion models are constructed to explain the corrosion mechanism.

In photovoltaic grid-connected systems, the interaction between grid-connected inverters and the grid may cause harmonic oscillation, which severely affects the normal operation of the system. To improve the quality of the output electrical energy, photovoltaic grid-connected systems often use LCL filters as output filters to filter out high-frequency harmonics. Taking the three-phase LCL-type photovoltaic grid-connected inverter system as an example, this paper addresses the issue of harmonic resonance. Firstly, based on the harmonic linearization method and considering the impact of the coupling compensation term on the grid-side voltage, a modular positive and negative sequence impedance modeling method is proposed, which simplifies the secondary modeling process of the converter under feedback control. Then, the stability analysis is conducted using the Nyquist criterion, revealing the mechanism of high-frequency resonance in photovoltaic grid-connected systems. Furthermore, this paper delves into the impact of changes in system parameters on impedance characteristics and system stability. The results indicate that the proportional coefficient of the internal loop current controller has a significant influence on system impedance characteristics. Additionally, this paper proposes an active damping design method that combines lead correction and capacitor current feedback to impedance-reconstruct the easily oscillating frequency band. Finally, the effectiveness of this method is verified in the simulation platform. Simulation results confirm the effectiveness of this method in suppressing harmonic resonance while maintaining rapid dynamic response.

Lepista sordida is a type of high-quality rare edible and medicinal mushroom, and its research boom is just beginning. More than 80 million tons of grain crop residues are produced each year in Heilongjiang Province. To realize the exploration and utilization of wild L. sordida mushrooms and also provide a theoretical support for the high-value utilization of these resources in Heilongjiang Province, we evaluated the cultivation of L. sordida mushrooms using rice straw, corncob, and soybean straw as substrates. L. sordida grew on all three substrates, and the biological efficiency and yield of the mushrooms grown on soybean straw and corncob were 32.33 ± 1.78% and 4.20 ± 0.23 kg m−2, and 30.15 ± 0.93% and 3.92 ± 0.12 kg m−2, respectively, which increased by 9.38% and 2.08% compared with that on the rice straw substrate with 3.84 ± 0.12 kg m−2 and 29.56 ± 0.89%. The time it took for the mycelia to colonize and initiate primordia on the soybean straw substrate was 22.33 ± 0.58 d and 19.67 ± 0.58 d, respectively, which was delayed by 2 d and 3 d compared with that on the rice straw substrate with 20.67 ± 2.08 d and 16.33 ± 0.58 d, respectively. The fruiting bodies grown on corncob and soybean straw substrates were relatively larger than those on the rice straw substrate. The highest amount of crude protein was 57.38 ± 0.08 g 100 g−1, and the lowest amount of crude polysaccharide was 6.03 ± 0.01 g 100 g−1. They were observed on mushrooms collected from the corncob substrate. The contents of the heavy metal mercury, lead, arsenic, and cadmium in the fruiting bodies grown on each substrate were within the national safety range.

Rhodococcus equi (R. equi) is a zoonotic opportunistic pathogen that can cause life-threatening infections. The rapid evolution of multidrug-resistant R. equi and the fact that there is no currently licensed effective vaccine against R. equi warrant the need for vaccine development. Reverse vaccinology (RV), which involves screening a pathogen’s entire genome and proteome using various web-based prediction tools, is considered one of the most effective approaches for identifying vaccine candidates. Here, we performed a pangenome analysis to determine the core proteins of R. equi. We then used the RV approach to examine the subcellular localization, host and gut flora homology, antigenicity, transmembrane helices, physicochemical properties, and immunogenicity of the core proteins to select potential vaccine candidates. The vaccine candidates were then subjected to epitope mapping to predict the exposed antigenic epitopes that possess the ability to bind with major histocompatibility complex I/II (MHC I/II) molecules. These vaccine candidates and epitopes will form a library of elements for the development of a polyvalent or universal vaccine against R. equi. Sixteen R. equi complete proteomes were found to contain 6,238 protein families, and the core proteins consisted of 3,969 protein families (∼63.63% of the pangenome), reflecting a low degree of intraspecies genomic variability. From the pool of core proteins, 483 nonhost homologous membrane and extracellular proteins were screened, and 12 vaccine candidates were finally identified according to their antigenicity, physicochemical properties and other factors. These included four cell wall/membrane/envelope biogenesis proteins; four amino acid transport and metabolism proteins; one cell cycle control, cell division and chromosome partitioning protein; one carbohydrate transport and metabolism protein; one secondary metabolite biosynthesis, transport and catabolism protein; and one defense mechanism protein. All 12 vaccine candidates have an experimentally validated 3D structure available in the protein data bank (PDB). Epitope mapping of the candidates showed that 16 MHC I epitopes and 13 MHC II epitopes with the strongest immunogenicity were exposed on the protein surface, indicating that they could be used to develop a polypeptide vaccine. Thus, we utilized an analytical strategy that combines pangenome analysis and RV to generate a peptide antigen library that simplifies the development of multivalent or universal vaccines against R. equi and can be applied to the development of other vaccines.

BackgroundNeuroinflammation and neuronal injury have been reported to be associated with the development of postoperative delirium in both preclinical and clinical settings. This study aimed to investigate the potential correlation between biomarkers of neurofilament light chain and glial fibrillary acidic protein and emergence and postoperative delirium in elderly patients undergoing surgery.MethodsPatients who developed emergence delirium (n = 30) and postoperative delirium (n = 32), along with their matched controls, were enrolled after obtaining ethics approval and written informed consent. Delirium was assessed using the Confusion Assessment Method for the Intensive Care Unit or Confusion Assessment Method scale, and blood samples were collected before and after surgery for plasma neurofilament light chain and glial fibrillary acidic protein measurements using a single-molecule array.ResultsThe study found that in patients with emergence delirium, the increase in plasma neurofilament light chain protein levels during surgery was significantly higher than in non-delirium patients (P = 0.002). Additionally, in patients with postoperative delirium, both the increase in plasma neurofilament light chain protein levels (P < 0.001) and the increase in plasma glial fibrillary acidic protein levels during surgery (P = 0.008) were significantly higher than in non-delirium patients. Multivariate logistic regression analysis showed that the increase in plasma neurofilament light chain protein was associated with emergence delirium (adjusted OR = 1.872, P = 0.005), and the increase in plasma glial fibrillary acidic protein was associated with postoperative delirium (adjusted OR = 1.419, P = 0.016). Moreover, the American Society of Anesthesiologists Physical Status Classification and surgical duration were also found to be associated with delirium in elderly patients.ConclusionOur findings suggest that emergence delirium is linked to elevated levels of neurofilament light chain, a biomarker of axonal injury, during surgery. Furthermore, in addition to axonal injury, postoperative delirium was also associated with an increase in glial fibrillary acidic protein, a marker of astrocyte activation.

Black rockfish (Sebastes schlegelii) is one of the most important marine economic viviparous fishes. Recently, germplasm degradation and genetic diversity reduction have occurred due to overfishing and long-term artificial breeding. Germ cell transplantation combined with cryopreservation may be an alternative way to protect genetic resources. However, in viviparous fish that undertake fertilization and embryo development in vivo, transplantation is more difficult than in oviparous fish, including selection of transplantation stage, isolation of germ stem cells, and preparation of sterile recipients. This seriously restricts the development of viviparous transplantation. Therefore, in this study, we aimed to explore a transplantation method suitable for these species. Donor cells were isolated from cryopreserved whole testes of 300–400 ​g male Sebastes schlegelii in May, labeled by PKH26, and intra-peritoneally transplanted into allogeneic larvae at 5–10 days post-birth. Subsequently, the development of donor-derived cells in recipients were continuously detected by fluorescence labeling, histology, microsatellite markers, and fecundity tests. The results showed that donors were rich in spermatogonia (75%) and recipients maintained a high survival rate after transplantation, with a rate of >20% at sexual maturity. Further, donor-derived cells successfully migrated (100%), colonized, and incorporated into the developing recipient gonad (93.33%). Finally, transplanted recipients could normally develop and differentiate into male and female individuals, with donor-derived gametes found in 65.38% of mature recipients. In the present study, we first establish a simple and suitable transplantation method for Sebastes schlegelii using immature males and specific larvae, which will serve as a promising tool in the protection of germplasm resources for this transplantation-restricted marine viviparous species.

Abstract Background Ovarian insufficiency frequently renders postmenopausal women susceptible to osteoporosis and dyslipidaemia. Postmenopausal transplant women are at a higher risk developing osteoporosis and dyslipidaemia due to the concomitant application of glucocorticoids and immunosuppressants after solid organ transplantation. Thus, this study aimed to explore the feasibility of ovarian tissue transplantation (OTT) as an alternative to Hormone replacement therapy (HRT) for postmenopausal women with solid organ transplant needs. Results Sixty mice were randomly divided into four groups: sham operation, ovariectomised (OVX group), ovariectomy plus oestrogen (E2 group), and ovariectomy plus OTT (OTT group). The inhibin levels in the OTT group were increased and the follicle stimulating hormone and luteinizing hormone were suppressed to normal levels, which could not be achieved in the E2 group. The femoral bone mineral density in the OTT group was significantly increased than the E2 group (P

Abstract Methyl-CpG-binding protein 2(MeCP2) is an important epigenetic regulatory factor that promotes many tumor developments, such as liver cancer, breast cancer, and colorectal cancer. So far, no pan-cancer analysis has been reported. Therefore, this study aims to explore pan-cancer's prognostic value, immune infiltration pattern, and biological function. We used bioinformatics methods to analyze the expression and prognostic significance of MeCP2, and the relationship between MeCP2 and clinicopathological parameters, genetic variation, methylation, phosphorylation, immune cell infiltration, and biological function in pan-cancer from using a public database. The results showed that expression of MeCP2 was up-regulated in 8 cancers and down-regulated in 2 cancers, which was remarkably correlated with the prognosis, pathological stage, grade and subtype of cancers. The promoter methylation level of MeCP2 DNA was decreased in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), liver hepatocellular carcinoma (LIHC), prostate adenocarcinoma (PRAD), uterine corpus endometrial carcinoma (UCEC), testicular germ cell tumors (TGCT), and stomach adenocarcinoma (STAD);decreased phosphorylation of S25, S90, S92, S241, S286, S325 and S435 was found in MeCP2, such as UCEC, lung adenocarcinoma (LUAD), ovarian serous cystadenocarcinoma (OV), colon adenocarcinoma (COAD), and kidney renal clear cell carcinoma (KIRC). Furthermore, MeCP2 expression was significantly associated with multiple immunomodulators and immune cell infiltration levels across most tumors. Therefore, our pan-cancer explored the prognostic markers and immunotherapeutic value of MeCP2 in different cancers.

Deubiquitinases (DUBs) targeting Met1-linked ubiquitin chains have important functions in mammals but are barely studied in plants. Here, the authors identify rice OTUB1 as a Met1-targeting DUB, characterize the structural determinants of this activity, and show that these features are conserved in green plants.

Abstract Analysing the steady‐state operation characteristic of the modular multilevel converter (MMC) in time domain poses challenges due to the presence of harmonic components in the arm current and capacitor voltage. While ignoring the influence of the harmonic currents and harmonic voltages would reduce the accuracy of the analysis results for MMC. This paper investigates the circular interaction among the electrical quantities and different order harmonic components in MMC. A new steady‐state model is developed and the general matrix equation is established to accurately describe the explicit analytical expressions for electrical variables in MMC without specific assumptions. Based on the steady‐state operation characteristic analysis, the resonance phenomenon and characteristic are identified for MMC. Finally, the feasibility and accuracy of the proposed method are verified by comparing its analytical results with simulation and experimental results.

Abstract Objective The aim of this study is to evaluate the prognostic value of the modified Glasgow prognostic score (mGPS) in advanced esophageal squamous cell carcinoma (SCC) patients. Methods The study enrolled 311 patients with advanced esophageal SCC from January 2012 to December 2018. Univariate and multivariate analyses were calculated by the Cox proportional hazards regression model in advanced esophageal SCC patients. The Kaplan–Meier method was used to evaluate the ability of the mGPS for survival rates. Propensity score‐matched (PSM) analysis was carried out to balance imbalanced variables. Results The Cox proportional hazards analysis showed that factors including M stage, ECOG, mGPS group, and sex were identified as independent predictors. The mGPS presented a good level of overall survival (OS) prediction with a risk‐adopted classification for advanced esophageal SCC patients. The survival rates in advanced esophageal SCC patients with mGPS 0, 1, and 2 were 18.8%, 8.4%, and 4.2%, respectively (p

BackgroundImmune checkpoint inhibitors (ICIs) combined with angiogenesis inhibitors (AGIs) have become increasingly available for multiple types of cancers, although the cardiovascular safety profiles of this combination therapy in real-world settings have not been elucidated to date. Therefore, we aimed to comprehensively investigate the cardiovascular toxicity profiles of ICIs combined with AGIs in comparison with ICIs alone.MethodsThe Food and Drug Administration Adverse Event Reporting System (FAERS) database from the 1st quarter of 2014 to the 1st quarter of 2022 was retrospectively queried to extract reports of cardiovascular adverse events (AEs) associated with ICIs alone, AGIs alone and combination therapy. To perform disproportionality analysis, the reporting odds ratios (RORs) and information components (ICs) were calculated with statistical shrinkage transformation formulas and a lower limit of the 95% confidence interval (CI) for ROR (ROR025) > 1 or IC (IC025) > 0 with at least 3 reports was considered statistically significant.ResultsA total of 18 854 cardiovascular AE cases/26 059 reports for ICIs alone, 47 168 cases/67 595 reports for AGIs alone, and 3 978 cases/5 263 reports for combination therapy were extracted. Compared to the entire database of patients without AGIs or ICIs, cardiovascular AEs were overreported in patients with combination therapy (IC025/ROR025 = 0.559/1.478), showing stronger signal strength than those taking ICIs alone (IC025/ROR025 = 0.118/1.086) or AGIs alone (IC025/ROR025 = 0.323/1.252). Importantly, compared with ICIs alone, combination therapy showed a decrease in signal strength for noninfectious myocarditis/pericarditis (IC025/ROR025 = 1.142/2.216 vs. IC025/ROR025 = 0.673/1.614), while an increase in signal value for embolic and thrombotic events (IC025/ROR025 = 0.147/1.111 vs. IC025/ROR025 = 0.591/1.519). For outcomes of cardiovascular AEs, the frequency of death and life-threatening AEs was lower for combination therapy than ICIs alone in noninfectious myocarditis/pericarditis (37.7% vs. 49.2%) as well as in embolic and thrombotic events (29.9% vs. 39.6%). Analysis among indications of cancer showed similar findings.ConclusionOverall, ICIs combined with AGIs showed a greater risk of cardiovascular AEs than ICIs alone, mainly due to an increase in embolic and thrombotic events while a decrease in noninfectious myocarditis/pericarditis. In addition, compared with ICIs alone, combination therapy presented a lower frequency of death and life-threatening in noninfectious myocarditis/pericarditis and embolic and thrombotic events.

Finding new targets is necessary for understanding tumorigenesis and developing cancer therapeutics. DExH-box helicase 9 (DHX9) plays a central role in many cellular processes but its expression pattern and prognostic value in most types of cancer remain unclear. In this study, we extracted pan-cancer data from TCGA and GEO databases to explore the prognostic and immunological role of DHX9. The expression levels of DHX9 were then verified in tumor specimens by western blot and immunohistochemistry (IHC). The oncogenic roles of DHX9 in cancers were further verified by in vitro experiments. We first verified that DHX9 is highly expressed in most tumors but significantly decreased in kidney and thyroid cancers, and it is prominently correlated with the prognosis of patients with different tumors. The phosphorylation level of DHX9 was also increased in cancers. Enrichment analysis revealed that DHX9 was involved in Spliceosome, RNA transport and mRNA surveillance pathway. Furthermore, DHX9 expression exhibited strong correlations with immune cell infiltration, immune checkpoint genes, and tumor mutational burden (TMB)/microsatellite instability (MSI). In liver, lung, breast and renal cancer cells, the knockdown or depletion of DHX9 significantly affected the proliferation, metastasis and EMT process of cancer cells. In summary, this pan-cancer investigation provides a comprehensive understanding of the prognostic and immunological role of DHX9 in human cancers, and experiments indicated that DHX9 was a potential target for cancer treatment.

The shear connection joint is an important component of the prefabricated shear wall structure system, which plays a dual role in ensuring reasonable force transmission and structural integrity. A new type of steel shear-connection horizontal joint was proposed in this study. In order to verify the effectiveness of the proposed new joint, the established numerical model and its constitutive relationship were first verified based on the existing experimental results. Then, the influence effect on the mechanical behaviors of this new type of joint was further investigated with 20 computational cases. The corresponding influencing laws were established, and optimal parameter ranges were suggested. Finally, a simplified constitutive model—namely, a bilinear constitutive model based on the M-θ relationship—of the new steel shear-connection joint is further advanced and deduced. The results show that the proposed new joint can provide stable shear capacity and superior energy dissipation capacity. The interlocking slot in the new steel shear-connection joint is suggested to be designed with a slot length of 20~30 mm, a slot number of two or three, and a slot thickness of 20~30 mm so as to guarantee superior mechanical behaviors. The advanced bilinear constitutive model can effectively capture the mechanical characteristics of the new joints, in which the maximum error is only 7.67% between theory and simulation.

This study presents the development and testing of a global navigation satellite system (GNSS) buoy designed for measuring the sea surface elevation and tide level. The precision-point-positioning (PPP) technology is adopted for precise observation. The design of the buoy body is optimized by stability and hydrodynamic calculations. A high-performance embedded data acquisition system with big storage and high-frequency sampling is developed for long-term observation. The GNSS buoy is deployed in a wind farm approximately 70 km offshore of China, and undergoes a 60-day ocean test. A comparison of the sea level elevations obtained from the GNSS buoy and the pressure sensor shows that there is a strong correlation between them, with a correlation coefficient of 0.99. A harmonic analysis is applied to derive the harmonic constants for four key tidal components (M2, S2, O1, and K1). The amplitude differences are −1.2 cm, 1.4 cm, −0.6 cm, and −1.2 cm, respectively, and the phase differences are 1.8°, 2.2°, −1.3°, and −2.9°, respectively. The strong correlation between the measurements of the GNSS buoy and the pressure sensor and the relatively small differences of the amplitude and phase of the main tidal components indicate that the compact GNSS buoy demonstrates a capability to continuously measure the sea surface elevation and tide level with an elevation reference in the open sea.

Pheromones play a vital role in regulating fish behavior, including reproduction, aggregation, hazard recognition and food location. To gain a better understanding of chemical communication in fish produced by density changes, this study analyzed the metabolites released by turbot (Scophthalmus maximus) under different stocking densities. The experiment was conducted at low (LD: 3.01 kg/m2), medium (MD: 6.62 kg/m2) and high (HD: 10.84 kg/m2) densities for 15 days. High-throughput non-targeted metabolomics (LC-MS/MS) was used to identify variations in metabolites released into the aquatic environment by turbot at different densities. Results showed that 29 and 47 metabolites were significantly upregulated in the MD and HD groups, respectively, compared with the LD group. Among them, hexadecanedioic acid, xanthine, phenethylamine, proline and styrene were significantly upregulated in the MD vs. LD, HD vs. MD and HD vs. LD. The VIP diagram of OPLS-DA alignment showed that phenethylamine was the most important metabolite shared by MD vs. LD, HD vs. MD and HD vs. LD. Key gene changes in the GH/IGF-1 signaling pathway, HPI axis of turbot were studied using qRT-PCR for density treatment. The results demonstrated that the expression of GH, GHR and IGF-1 was significantly lower, while the expression of CRH and ACTH was higher in the HD group. Additionally, plasma levels of cortisol, glucose, triglycerides and T3 were also highest in the HD group compared with the LD and MD groups. Phenylethylamine concentration was positively correlated with the HPI axis and negatively correlated with the GH/IGF-1 signaling pathway. To investigate the impact of phenethylamine accumulation on turbot, an acute treatment experiment with phenethylamine was set up. Its concentration in the aquatic environment was set at 0 (CON), 10−7 (LP) and 10−5 (HP) mol/L via exogenous addition, and turbot were exposed to these environments for 2 days. There was a high degree of concordance between the GH/IGF-1 signaling pathway (GH, GHR, IGF-1), HPI axis (CRH, ACTH) and plasma physiological changes (cortisol, glucose, triglycerides, T3) in the phenethylamine-treated group and the density-treated group. Therefore, accumulation of phenethylamine with increasing stocking density may be a potential cause of density stress. Phenylethylamine has a dose-dependent and trace effect as a pheromone.

Composites, such as fiber-reinforced plastics, are produced using layering prepregs with varying ply orientations to achieve enhanced mechanical properties. However, this results in intricate residual stresses, which are influenced by the forming process and ply orientation. In this study, three representative microscopic models—featuring discrete fiber and resin—represent unidirectional, cross-ply, and angle-ply laminates. These models underwent simulations under three different cooling histories using the finite element method. The findings suggest that ply orientation does not significantly influence temperature distribution. However, it significantly impacts the von Mises stress in the fiber closest to the interface between two stacked laminae. This differs from the inter-laminar stresses determined with the macroscopic lamination model. Apart from the free edge, which exhibits a complex stress distribution, the von Mises stress within a unit cell displays a recurring pattern. The magnitude of the von Mises stress decreases as the ply orientation angle increases and shifts when a temperature gradient is present throughout the composite’s thickness. This study provides valuable insights into the mechanics of residual stresses at the microscopic level and highlights potential defect areas influenced by these stresses.