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Abstract Long non‐coding RNAs (lncRNAs) have emerged as significant contributors to the regulation of various biological processes, and their dysregulation has been linked to a variety of human disorders. Accurate prediction of potential correlations between lncRNAs and diseases is crucial for advancing disease diagnostics and treatment procedures. The authors introduced a novel computational method, iGATTLDA, for the prediction of lncRNA‐disease associations. The model utilised lncRNA and disease similarity matrices, with known associations represented in an adjacency matrix. A heterogeneous network was constructed, dissecting lncRNAs and diseases as nodes and their associations as edges. The Graph Attention Network (GAT) is employed to process initial features and corresponding adjacency information. GAT identified significant neighbouring nodes in the network, capturing intricate relationships between lncRNAs and diseases, and generating new feature representations. Subsequently, the transformer captures global dependencies and interactions across the entire sequence of features produced by the GAT. Consequently, iGATTLDA successfully captures complex relationships and interactions that conventional approaches may overlook. In evaluating iGATTLDA, it attained an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95 and an area under the precision recall curve (AUPRC) of 0.96 with a two‐layer multilayer perceptron (MLP) classifier. These results were notably higher compared to the majority of previously proposed models, further substantiating the model’s efficiency in predicting potential lncRNA‐disease associations by incorporating both local and global interactions. The implementation details can be obtained from https://github.com/momanyibiffon/iGATTLDA.

Abstract We investigated the potential correlation between miR‐223 and NAcHT, LRR, and PYd domain‐containing protein 3 (NLRP3) in the context of renal ischemia‐reperfusion injury (RIRI), which is a leading cause of acute renal failure with significant mortality rates. Additionally, miR‐223 has been implicated in renal inflammation, further highlighting its relevance to this study. C57BL/6 male mice were used as RIRI models. After successful modeling, pathological examinations and serum creatinine and miR‐223 levels were tested. Pro‐inflammatory cytokine (IL‐1β, IL‐6, IL‐8, NLPR3, TLR4) expression was detected in mice by western blot (kidney tissue) and enzyme‐linked immunosorbent assay (serum). HK‐2 cells were used for in vitro experiments. A hypoxia/reoxygenation (H/R) model was used, and miR‐223 and pro‐inflammatory cytokine levels were detected using PCR and western blot assays, respectively. A dual‐luciferase reporter assay was conducted to confirm the binding of miR‐223 to NLPR3. Next, NLRP3 was knocked down to determine whether the anti‐inflammatory function of miR‐223 is dependent on NLRP3. MiR‐223 expression was lower in RIRI mice than in the sham operation group. The level of miR‐223 negatively correlated with serum creatinine levels and the severity of tubule injury. Increased proinflammatory cytokine levels in RIRI mice were observed. In vitro, miR‐223 alleviated the inflammatory response in H/R treated cells by inhibiting proinflammatory cytokines. Dual‐luciferase reporter and western blot assays confirmed the binding of miR‐223 to NLRP3. NLRP3 knockdown reversed the anti‐inflammatory effects of miR‐223 in HK‐2 cells. MiR‐223 plays an anti‐inflammatory role in RIRI by targeting NLRP3 to repress pro‐inflammatory factors.

Abstract Glycosylation, a key mode of protein modification in living organisms, is critical in regulating various biological functions by influencing protein folding, transportation, and localization. Changes in glycosylation patterns are a significant feature of cancer, are associated with a range of pathological activities in cancer‐related processes, and serve as critical biomarkers providing new targets for cancer diagnosis and treatment. Glycoproteins like human epidermal growth factor receptor 2 (HER2) for breast cancer, alpha‐fetoprotein (AFP) for liver cancer, carcinoembryonic antigen (CEA) for colon cancer, and prostate‐specific antigen (PSA) for prostate cancer are all tumor biomarkers approved for clinical use. Here, we introduce the diversity of glycosylation structures and newly discovered glycosylation substrate—glycosylated RNA (glycoRNA). This article focuses primarily on tumor metastasis, immune evasion, metabolic reprogramming, aberrant ferroptosis responses, and cellular senescence to illustrate the role of glycosylation in cancer. Additionally, we summarize the clinical applications of protein glycosylation in cancer diagnostics, treatment, and multidrug resistance. We envision a promising future for the clinical applications of protein glycosylation.

Abstract Direct torque control with space vector modulation has been increasingly attracting emphasis for permanent‐magnet synchronous machine control, benefiting from a high dynamic response and low torque ripple. However, the rapid tracking performance of torque and stator flux linkage is gradually deteriorating as the machine enters the overmodulation region because of the output‐voltage limitation of the inverter. Therefore, to enhance the system tracking performance in the overmodulation region, an innovative overmodulation method based on torque and flux optimal tracking is proposed. In contrast to the conventional overmodulation method where only one of the torque and stator flux linkage tracking is considered, the proposed strategy first constructs the weightless cost function to achieve a trade‐off control between the torque and stator flux linkage. Then, by using an equivalent geometric path to intuitively express the weightless cost function, the minimum cost function can be easily solved and the optimal output voltage vector can be determined correspondingly, to achieve the fast‐tracking of both the torque and stator flux linkage. Additionally, the voltage utilization of different overmodulation schemes is also analysed. Finally, the experimental results demonstrate the efficiency and practicality of the proposed strategy.

Abstract To improve the stability of the inverter‐based microgrid (MG), this paper employs a novel data‐driven based method to coordinately adjust control parameters of inverters in a fast local manner. During the design process, an offline eigenvalue based optimization problem that is used to calculate the optimal control parameters under various operating conditions is first constructed. In order to reduce reliance on full system information, a feature selection algorithm is utilized to extract the most relevant local measurements that influence the adjustment of each control parameter. Then, regarding local measurements as input variables and optimal control parameters as output variables, based on northern goshawk optimization (NGO) and long short‐term memory (LSTM) network, a novel deep learning algorithm is proposed to train the local parameter adjustment model (LPAM) by learning the mapping relationship between them. During the application, to guarantee the stability of MG all the time, a security region based shielding mechanism is developed, where the improper control parameter adjustment will be replaced by a safe one. The case study indicates that the proposed algorithm has better mapping accuracy than traditional LSTM neural networks and also faster calculation speed than the traditional offline optimization‐based method. The effectiveness and advantages of the proposed method are demonstrated in a modified 9‐bus MG.

Abstract Conventional methods for identifying voltage sag sources are difficult to categorize accurately due to the complexity of transmission lines and the influence of noise. In order to solve the problem of difficulty in recognizing voltage sag sources of transmission lines under different locations, this paper proposes a new method for transmission line fault diagnosis based on modified wavelet denoising and multi‐location information convolution transformer. The improved wavelet denoising method proposed in this paper solves the problems of discontinuity and bias of the traditional wavelet denoising method, and is able to better reconstruct the original voltage signal in a strong noise environment. In addition, multi‐location information convolution transformer adopts a new model combining multi‐location information convolution and multi‐scale convolution transformer, which realizes the combination of global information and local context information capturing ability under multi‐location faults. This paper validates the method through simulation experiments and practical situations, and the results show that the method can well classify and identify the type and location of voltage sag sources in transmission lines.

Abstract Objective The objective of this study was to report the 12‐month oncological outcomes for patients with non‐muscle‐invasive bladder cancer (NMIBC) within the prospective, international COVIDSurg Cancer study. Patients and methods Eligible patients were aged ≥18 years and scheduled for elective surgical management of NMIBC with curative intent (transurethral resection of bladder tumour [TURBT] or bladder biopsy) from 21 January to 14 April 2020. The primary outcome was disease recurrence within 12 months of previous elective TURBT/bladder biopsy. Secondary outcomes included disease progression within 12 months of previous elective TURBT/bladder biopsy, site‐declared delay to surgery from diagnosis as a consequence of COVID‐19 and deviation in standard care due to COVID‐19. Comparisons were made to cohorts from the pre‐pandemic era. Results Bladder cancer accounted for 2.2% (n = 446) of patients in the COVIDSurg Cancer study, with data contributed by 27 centres across 12 countries internationally. Within this included cohort, 229 patients had NMIBC and 12‐month follow‐up data available. On application of National Institute for Health and Care Excellence (NICE) criteria, 47.2% were classified as having high‐risk disease. Overall disease recurrence and progression rates were 29.3% and 9.7% at 12 months, respectively. In purely high‐risk pre‐pandemic cohorts, the International Bladder Cancer Group (IBCG) estimates a recurrence rate of 25% at 12 months, and the European Association of Urology (EAU) NMIBC 2021 scoring model estimates a 12‐month progression rate of 3.5%. As a consequence of the COVID‐19 pandemic, 10.9% of patients had site‐declared delay to TURBT/bladder biopsy; 7.4% did not undergo intravesical therapy or had early discontinuation of this; 9.2% did not undergo early repeat resection for high‐risk disease; and 18.3% had a delay to cystoscopic follow‐up surveillance. Conclusions This prospective study indicates that there were widespread deviations in usual care for NMIBC during the pandemic and that 12‐month oncological outcomes appear to be impaired compared to published pre‐pandemic outcomes.

Abstract To tackle challenges in road multi‐object detection, such as object occlusion, small object detection, and multi‐scale object detection difficulties, a new YOLOv8n‐RSFM structure is proposed. The key improvement of this structure lies in the introduction of the transformer decoder head, which optimizes the matching between the ground truth and predicted boxes, thereby effectively addressing issues of object overlap and multi‐scale detection. Additionally, a small object detection layer is incorporated to retain crucial information beneficial for detecting small objects, significantly improving the detection accuracy for small targets. To enhance learning capacity and reduce redundant computations, the FasterNet backbone is employed to replace CSPDarknet53, thus accelerating the training process. Finally, the INNER‐MPDIoU loss function is introduced to replace the original algorithm's complete IoU to accelerate the convergence and obtain more accurate regression results. A series of experiments were conducted on different datasets. The experimental results show that the proposed model YOLOv8N‐RSFM outperforms the original model YOLOv8n in small target detection. On the VisDrone, TinyPerson, and VSCrowd datasets, the mean accuracy percentage improved by 7.9%, 12.3%, and 4.5%, respectively.

Objective Previous cementless total knee arthroplasty (TKA) designs faced challenges with insufficient initial fixation on tibial side, resulting in inferior functional outcomes and survival rates. The Zoned Trabecular Bone Cementless Knee is a novel implant designed for cementless TKA which aims to achieve excellent initial fixation, promoting effective osseointegration. The aim of this research was to compare the early clinical and radiographic results of this cementless TKA with cemented TKA. Methods Between September 2021 and April 2022, 64 patients (64 knees) were recruited in this prospective randomized controlled trial to receive either cementless 3D‐printed trabecular metal TKA or a cemented posterior stabilized TKA. Preoperative and postoperative clinical evaluations, including the range of motion (ROM), Knee Society Score (KSS), and the Reduced Western Ontario and MacMaster Universities Score (WOMAC), were conducted and analyzed for comparison. Radiographs and computed tomography scans were utilized to assess the initial fixation. The complications between the two groups were also recorded and compared. Continuous data were analyzed for significance using independent‐samples t‐test or the Mann–Whitney U test and categorical data were analyzed using chi‐squared or Fisher's exact test. Results Both groups demonstrated significant enhancement at 12 months follow‐up in the ROM compared with baseline (ROM: 94.7 ± 23.4 vs. 113.1 ± 12.3 in cementless group and 96.5 ± 14.7 vs. 111.0 ± 12.8 in cemented group, p

ABSTRACT Background Strokes in young individuals often stem from unusual causes. Posterior circulation ischemic stroke caused by vertebral artery insufficiency due to atlantoaxial instability or dislocation is rare. We present a case of posterior circulation ischemic stroke due to an unstable os odontoideum and review the current literature. The clinical features and imaging manifestations are described to promote awareness of etiology, early diagnosis, and assessment. Case Presentation A 24‐year‐old male presented with recurrent right‐sided limb numbness and weakness and cerebellar ataxia due to posterior circulation ischemic stroke. The work‐up revealed thrombosis reformation in the tortuous left vertebral artery. It is noteworthy that the patient developed compression and chronic damage of the vertebral artery secondary to atlantoaxial instability and lateral dislocation due to an os odontoideum. He underwent antiplatelet and anticoagulant therapy, cervical traction, and posterior atlantoaxial screw fixation and fusion with iliac crest autograft. The postoperative course was uneventful. At 6‐month follow‐up, the patient had a solid fusion mass and rigid stability of the atlantoaxial joint without neurologic deficits or ischemic sequelae. Conclusions For unexplained posterior circulation ischemic stroke, it is important to consider unstable os odontoideum as a potential etiology, especially in pediatric and young adult male patients. Atlantoaxial instability and dislocation with os odontoideum, especially when occurring laterally, may cause insufficiency of the vertebral artery and subsequent posterior circulation ischemic strokes. The significance of lateral atlantoaxial dislocation in the genesis of vertebral artery injury and the necessity for specific positional imaging are emphasized.

Abstract The human placenta is a vital organ, encompassing many distinct cell types, that maintains the growth and development of the fetus and is essential for substance exchange, defense, synthesis, and immunity. Abnormalities in placental cells can lead to various pregnancy complications, but the mechanisms remain largely unclear. Single‐cell and spatial transcriptomics technologies have been developed in recent years to demonstrate placental cell heterogeneity and spatial molecular localization. Here, we review and summarize the current literature, demonstrating these technologies and showing the heterogeneity of various placenta cells and cell–cell communication of normal human placenta, as well as placenta‐related diseases, such as preeclampsia, gestational diabetes mellitus, advanced maternal age, recurrent pregnancy loss, and placenta accreta spectrum disorders. Meanwhile, current weaknesses and future direction were discussed.

Abstract Circadian clock serves as a regulator of gastrointestinal health, and the disruption of circadian rhythm may trigger the dysregulation of the intestinal barrier functions. This study investigated the effectiveness of capsaicin (CAP) in mitigating intestinal barrier dysfunction induced by circadian disruption in male SPF C57BL/6J mice. Our findings indicated that CAP supplementation attenuated abnormal weight gain, alterations in serum lipid levels, and misalignment in hepatic and colonic circadian clock gene expressions in mice caused by constant darkness (CD) treatment. The restoration of the intestinal barrier integrity was also observed through the increase in mucosal thickness and goblet cell numbers. Both the diversity and the circadian rhythm of gut microbiota were improved in CAP‐treated group. Correlation analysis indicated that CAP could modulate the gut microbiota by affecting intestinal barrier function and systemic metabolism in CD‐treated mice. These results highlight the potential of CAP as a functional food component in maintaining the intestinal barrier homeostasis through regulating gut microbiota.

Abstract In the realm of plant genomics, virus‐induced gene silencing (VIGS) technology emerges as a potent tool, employing a reverse genetic strategy to elucidate plant gene functions. Recognized for its simplicity, cost‐effectiveness, and broad applicability, VIGS facilitates the exploration of novel genes in vegetable crops and unveils mechanisms underlying disease resistance and stress response. Moreover, it offers vital support for crop enhancement and molecular breeding. In the context of tomato biology, VIGS holds promise for transformative advancements, spanning from genomics and variety improvement to molecular breeding. This review comprehensively analyzes the pivotal breakthroughs achieved in tomato physiology through global applications of VIGS and explores its strengths and limitations. Future prospects suggest VIGS's pivotal role in reshaping tomato biology, modulating secondary metabolism, and bolstering stress resilience. By delineating diverse applications of VIGS technology, this review fosters innovation in tomato research, opening new vistas for its utilization in plant gene functional analysis.

Abstract Reconfigurable intelligent surface (RIS) refers to a two‐dimensional smart surface consisting of massive number of reflecting elements. Both active RIS (ARIS) and passive RIS (PRIS) are promising technologies that can adapt and reconfigure the wireless environment, enhancing the reliability and capacity of wireless networks. The authors focus on enhancing the detection ability of ARIS/PRIS‐aided multiple‐input‐multiple‐output radar system in the presence of signal‐dependent clutter. Constant‐envelope constraint is imposed on the sought radar waveforms to improve the practicability of the radar system. To tackle the resultant non‐convex problem, a cyclic method based on minorisation–maximisation and alternating direction method of multipliers is derived to iteratively optimise the receive filters, the transmit waveforms, and the RIS coefficients. The major finding is that the distance between the radar and the ARIS has little to no impact on the radar signal‐to‐interference‐plus‐noise ratio (SINR). For the PRIS‐aided radar system, a simplified model can significantly improve the operational efficiency and has little impact on the radar SINR. Numerous results verify the effectiveness of the proposed algorithm.

Abstract Objectives This study investigates curcumin's neuroprotective role and its potential in promoting neurogenesis in progenitor cells within the brain. Notably, curcumin's antioxidant properties have been implicated in Alzheimer's disease treatment. However, the association between curcumin's antioxidative effects and its impact on neural stem cells (NSCs) remains to be elucidated. Methods C17.2 neural stem cells were utilized as a model to simulate oxidative stress, induced by hydrogen peroxide (H2O2). We quantified the levels of superoxide dismutase (SOD), malondialdehyde (MDA), and intracellular reactive oxygen species (ROS), alongside the gene expression of SOD1 and SOD2, to assess intracellular oxidative stress. Additionally, Western blot analysis was conducted to measure the expressions of LC3‐II, Beclin‐1, and phosphorylated ERK (p‐ERK), thereby evaluating autophagy and ERK signaling pathway activation. Results Treatment with curcumin resulted in a reduction of MDA and ROS levels, suggesting a protective effect on NSCs against oxidative damage induced by H2O2. Furthermore, a decrease in the relative expressions of LC3‐II, Beclin‐1, and p‐ERK was observed post‐curcumin treatment. Conclusions The findings suggest that curcumin may confer protection against oxidative stress by attenuating autophagy and deactivating the ERK1/2 signaling pathways, which could contribute to therapeutic strategies for Alzheimer's disease.

Abstract Vector‐borne diseases caused by arthropod‐borne viruses (arboviruses) are a considerable challenge to public health globally. Mosquito‐borne arboviruses, such as Chikungunya, Dengue, and Zika viruses, cause a range of human illnesses and may be fatal. Currently, efforts to control these diseases still face challenges due to growing vector resistance towards insecticides, urbanization, and limited effective antiviral treatments and vaccines. Animal models are crucial in antiviral research on mosquito‐borne arboviruses, playing a role in understanding disease mechanisms, vaccine development, and toxicity testing, but the application of animal models still faces the challenges of ethical considerations and animal‐to‐human translational success. Genetically engineered mouse models, hamster models and non‐human primate (NHP) are currently used in arbovirus research, but new models such as tree shrews and novel humanized mice are emerging. In the context of Malaysian research, the use of long‐tailed macaques as potential NHP models for arbovirus research is possible; however, it faces the ethical dilemma of using an endangered species for scientific purposes. Overall, animal models play a crucial role in advancing infectious disease research, but a balance between medical research and species conservation must be upheld.

Abstract Background LDL receptor‐related protein‐1 (LRP1) is a cell‐surface receptor that functions in diverse physiological pathways. We previously demonstrated that hepatocyte‐specific LRP1 deficiency (hLRP1KO) promotes diet‐induced insulin resistance and increases hepatic gluconeogenesis in mice. However, it remains unclear whether LRP1 regulates hepatic glycogenesis. Methods Insulin signaling, glycogenic gene expression, and glycogen content were assessed in mice and HepG2 cells. The pcDNA 3.1 plasmid and adeno‐associated virus serotype 8 vector (AAV8) were used to overexpress the truncated β‐chain (β∆) of LRP1 both in vitro and in vivo. Results On a normal chow diet, hLRP1KO mice exhibited impaired insulin signaling and decreased glycogen content. Moreover, LRP1 expression in HepG2 cells was significantly repressed by palmitate in a dose‐ and time‐dependent manner. Both LRP1 knockdown and palmitate treatment led to reduced phosphorylation of Akt and GSK3β, increased levels of phosphorylated glycogen synthase (GYS), and diminished glycogen synthesis in insulin‐stimulated HepG2 cells, which was restored by exogenous expression of the β∆‐chain. By contrast, AAV8‐mediated hepatic β∆‐chain overexpression significantly improved the insulin signaling pathway, thus activating glycogenesis and enhancing glycogen storage in the livers of high‐fat diet (HFD)‐fed mice. Conclusion Our data revealed that LRP1, especially its β‐chain, facilitates hepatic glycogenesis by improving the insulin signaling pathway, suggesting a new therapeutic strategy for hepatic insulin resistance‐related diseases.

Abstract This article investigates the evolution of vortex structures in the impeller channel of a multiphase pump. By capturing the vortices in the impeller channel using the vorticity and Q‐criterion, the generation location of the vortex structures is analyzed, and the pressure fluctuations induced by vortices in the main flow passage of the impeller are studied in terms of their time‐ and frequency‐domain characteristics. The relationship between the vorticity and the amplitude of pressure fluctuations at the main frequency of the impeller is further investigated. This study develops a method of identifying vortices in the impeller channel of the multiphase pump, and reveals the intrinsic connection between the vortices and pressure fluctuations in the main flow passage. These findings offer some suggestions for eliminating the influence of vortices and enhancing the pressurizing capabilities of multiphase pumps.

Abstract Underwater object detection (UOD) is crucial for marine economic development, environmental protection, and the planet's sustainable development. The main challenges of this task arise from low‐contrast, small objects, and mimicry of aquatic organisms. The key to addressing these challenges is to focus the model on obtaining more discriminative information. The authors observe that the edges of underwater objects are highly unique and can be distinguished from low‐contrast or mimicry environments based on their edges. Motivated by this observation, an Edge‐guided Representation Learning Network, termed ERL‐Net is proposed, that aims to achieve discriminative representation learning and aggregation under the guidance of edge cues. Firstly, an edge‐guided attention module is introduced to model the explicit boundary information, which generates more discriminative features. Secondly, a hierarchical feature aggregation module is proposed to aggregate the multi‐scale discriminative features by regrouping them into three levels, effectively aggregating global and local information for locating and recognising underwater objects. Finally, a wide and asymmetric receptive field block is proposed to enable features to have a wider receptive field, allowing the model to focus on smaller object information. Comprehensive experiments on three challenging underwater datasets show that our method achieves superior performance on the UOD task.

Abstract The electric field distortion caused by the accumulation of space charge in the insulating dielectric is easy to lead to accelerated ageing and even breakdown. In this paper, the space charge characteristics and the interfacial electric field change with time of silicone elastomer under different polarity DC voltages are studied. The results show that the homopolar charge injection is dominant in the silicone elastomer, and the electric field threshold is less than 4 kV/mm. The accumulation of homopolar charge weakens the interfacial electric field, resulting in the reduction of charge injection, and the interfacial electric field and spatial charge distribution gradually stabilise over time. In addition, the electric field at the interface does not decrease to the charge injection field threshold when it reaches stability. A time‐varying electric field model of the metal‐dielectric interface under a direct current field is derived and a calculation method for the time of charge accumulation to stabilise is proposed, based on the Schottky injection model and the relation between current density and volume charge density. The accuracy of the model is verified by comparing it with the experimental results of the stability time of silicone elastomer. This model is used to estimate the time when space charge accumulation reaches stability by means of the electric field threshold and the interface barrier, which can provide reference for the experimental measurement of space charge.

Abstract This paper proposes a method of impulse current generator modulated DC arc by combining the advantages of pulse and the RF to solve the low electron energy problem of direct current arc. Through experimental analyzing the electrical, spectral, and optical characteristics of the arc, the effect of impulse current generator (ICG) on improving electron energy is discussed. The results show that the ICG consumes more energy to enhance the strength of arc discharge, and therefore electron energy is increased in a microsecond scale. In addition, it is found that the electron energy of the arc discharge can be adjusted by varying inductance, capacitance, and discharge tube: increasing the inductance or capacitance can increase the electron energy firstly and then decrease it. In adjusting the three adjustable components, adjusting the inductor is the most effective method, followed by adjusting the capacitor, and adjusting the repetition frequency has the least effect. The reason is discussed, and it is believed that the results are related to leakage inductance and distributed capacitance.

Abstract Emotion recognition in user‐generated videos plays an essential role in affective computing. In general, visual information directly affects human emotions, so the visual modality is significant for emotion recognition. Most classic approaches mainly focus on local temporal information of videos, which potentially restricts their capacity to encode the correlation of long‐range context. To address this issue, a novel network is proposed to recognize emotions in videos. To be specific, a spatio‐temporal correlation‐aware block is designed to depict the long‐range correlations between input tokens, where the convolutional layers are used to learn the local correlations and the inter‐image cross‐attention is designed to learn the long‐range and spatio‐temporal correlations between input tokens. To generate diverse and challenging samples, a dual‐augmentation fusion layer is devised, which fuses each frame with its corresponding frame in the temporal domain. To produce rich video clips, a long‐range sampling layer is designed, which generates clips in a wide range of spatial and temporal domains. Extensive experiments are conducted on two challenging video emotion datasets, namely VideoEmotion‐8 and Ekman‐6. The experimental results demonstrate that the proposed method obtains better performance than baseline methods. Moreover, the proposed method achieves state‐of‐the‐art results on the two datasets. The source code of the proposed network is available at: https://github.com/JinChow/LRCANet.

Abstract Face shape priors such as landmarks, heatmaps, and parsing maps are widely used to improve face super resolution (SR). It is observed that face priors provide locations of high‐frequency details in key facial areas such as the eyes and mouth. However, existing methods fail to effectively exploit the high‐frequency information by using the priors as either constraints or inputs. This paper proposes a novel high frequency highway (H2F) framework to better utilize prior information for face SR, which dynamically decomposes the final SR face into a coarse SR face and a high frequency (HF) face. The coarse SR face is reconstructed from a low‐resolution face via a texture branch, using only pixel‐wise reconstruction loss. Meanwhile, the HF face is directly generated from face priors via an HF branch that employs the proposed inception–hourglass model. As a result, H2F allows the face priors to have a direct impact on the SR face by adding the outputs of both branches as the final result and provides an extra face editing function. Extensive experiments show that H2F significantly outperforms state‐of‐the‐art face SR methods, is general for different texture branch models and face priors, and is robust to dataset mismatch and pose variations.

Abstract Currently, in the field of processing 3D point cloud data, two primary representation methods have emerged: point‐based methods and voxel‐based methods. However, the former suffer from significant computational costs and lack the ease of handling exhibited by voxel‐based methods. Conversely, the later often encounter challenges related to information loss resulting from downsampling operations, thereby impeding subsequent tasks. To address these limitations, this article introduces a novel density‐based representation method for voxel partitioning. Additionally, a corresponding network structure is devised to extract features from this specific density representation, thereby facilitating the successful completion of classification tasks. The experiments are implemented on ModelNet40 and MNIST demonstrate that the proposed 3D convolution can achieve the‐state‐of‐the‐art performance based on the voxels.

Abstract The present article proposes a novel hybrid approach for addressing the synthesis problem of rectangular planar arrays under multiple constraints, through joint optimization of the weight function and the improved grey wolf optimization (IGWO) algorithm. Firstly, the grey wolf optimization (GWO) algorithm is improved by using tent chaotic mapping, nonlinear convergence factor, dominant wolf dynamic belief strategy, and opposition‐based learning strategy to increase the population diversity and the ability to jump out of the local optimum. Secondly, the array elements are weighted using the weight function to generate the position distribution matrix, which reduces the thinned matrix optimization time and improves the optimization efficiency. Finally, the position distribution matrix is used to generate the thinned array, and the IGWO algorithm is applied to perform the sparse optimization with multiple constraints. The effectiveness of the method is verified through numerical simulation and full‐wave simulation experiments, demonstrating its capability to enhance array antenna performance and reduce peak sidelobe level (PSLL). These experimental results hold significant engineering implications and provide valuable references for addressing the array distribution problem under multiple constraints.

Abstract Synaptojanin 2 (SYNJ2) has crucial role in various tumors, but its role in papillary thyroid carcinoma (PTC) remains unexplored. This study first detected SYNJ2 protein expression in PTC using immunohistochemistry method and further assessed SYNJ2 mRNA expression through mRNA chip and RNA sequencing data and its association with clinical characteristics. Additionally, KEGG, GSVA, and GSEA analyses were conducted to investigate potential biological functions, while single‐cell RNA sequencing data were used to explore SYNJ2's underlying mechanisms in PTC. Meanwhile, immune infiltration status in different SYNJ2 expression groups were analyzed. Besides, we investigated the immune checkpoint gene expression and implemented drug sensitivity analysis. Results indicated that SYNJ2 is highly expressed in PTC (SMD = 0.66 [95% CI: 0.17–1.15]) and could distinguish between PTC and non‐PTC tissues (AUC = 0.74 [0.70–0.78]). Furthermore, the study identified 134 intersecting genes of DEGs and CEGs, mainly enriched in the angiogenesis and epithelial‐mesenchymal transition (EMT) pathways. Subsequent analysis showed the above pathways were activated in PTC epithelial cells. PTC patients with high SYNJ2 expression showed higher sensitivity to the six common drugs. Summarily, SYNJ2 may promote PTC progression through angiogenesis and EMT pathways. High SYNJ2 expression is associated with better response to immunotherapy and chemotherapy.

Objective Multitargeted tyrosine kinase inhibitors (TKIs) have been approved as second‐line therapy in refractory sarcoma, prolonging progression‐free survival (PFS) but with short‐lived duration of disease control. Fruquintinib is a TKI that specifically inhibits vascular endothelial growth factor receptor‐1,2,3 with no metabolism by liver enzymes. In this retrospective study, we assessed the efficacy and safety of fruquintinib‐based treatment in patients with refractory sarcoma after developing several lines of TKI resistance. Methods We retrospectively analyzed the clinical data of patients with refractory sarcoma after they had developed several lines of resistance to TKIs and who received fruquintinib‐based treatment from November 2021 to August 2023. The primary endpoint was the progression‐free survival rate at 4 months (4m‐PFSR). Secondary endpoints were the median PFS, overall survival (OS), objective response rate, disease control rate, and adverse effects (AEs). PFS and OS were estimated using the Kaplan–Meier method. A log‐rank test was used to compare survival curves between different clinical and pathological factors. Cox proportional hazards analysis was performed to identify PFS‐related prognostic factors. Results We included 124 patients: 56 (45.2%) with osteosarcoma, 28 (22.6%) with Ewing sarcoma, seven (5.6%) with chondrosarcoma, and 33 (26.6%) with soft tissue sarcomas (STS). Only 18 (14.5%) patients received monotherapy with fruquintinib. With a median follow‐up time of 6.8 (interquartile range [IQR], 4.6–9.4) months, 22 (17.7%) patients had partial response and 78 (62.9%) had stable disease. The 4m‐PFSR was 58.4% (95% confidence interval [CI], 49.6%–67.1%). The median PFS and OS were 4.4 (95% CI, 3.9–5.0) months and 11.4 (95% CI, 10.3–12.5) months. In multivariate analysis, a high hazard ratio for progression was associated with target lesions located outside the lung and bone with 1.79 (95% CI, 1.10–2.93; p = 0.020). Eighty‐eight AEs were recorded in 47 (37.9%) patients; the most common were pneumothorax (18/124, 14.5%), diarrhea (8/124, 6.5%), oral mucositis (7/124, 5.6%), and thrombocytopenia (7/124, 5.6%). Conclusions Fruquintinib may be a potential option for patients with refractory sarcoma after developing several lines of TKI resistance, with a satisfactory efficacy and safety profile in combination therapy. However, the degree of contribution of fruquintinib to results is unclear when combined with other effective substances. Additional prospective trials of fruquintinib should be conducted, especially involving different pathological types and combination regimens.

Background Periprosthetic bone loss is a well‐known phenomenon following total hip arthroplasty (THA). However, the choice of drugs for prevention remains controversial. Therefore, the aim of this study was to determine the best drug to treat periprosthetic bone loss by comparing changes in bone mineral density (BMD) at different times after THA. Methods A comprehensive search of five databases and two clinical trial registration platforms was undertaken from their inception through to August 31, 2023 to identify eligible randomized controlled trials. A Bayesian network meta‐analysis (NMA) was carried out for calculating the standardized mean difference (SMD) and the surface under cumulative ranking curve (SUCRA) of the BMD in calcar (Gruen zone 7) at 6 months, 12 months, and 24 months and over. Results Twenty‐nine trials involving 1427 patients and 10 different interventions were included. The results demonstrated that at 6 months, denosumab had the highest ranking (SUCRA = 0.90), followed by alendronate (SUCRA = 0.76), and zoledronate (SUCRA = 0.73). At 12 months, clodronate ranked highest (SUCRA = 0.96), followed by denosumab (SUCRA = 0.84) and teriparatide (SUCRA = 0.82). For interventions with a duration of 24 months and over, denosumab had the highest SUCRA value (SUCRA = 0.96), followed by raloxifene (SUCRA = 0.90) and zoledronate (SUCRA = 0.75). Conclusion Investigating the existing body of evidence revealed that denosumab demonstrates potential as an intervention of superior efficacy at the three specifically examined time points. However, it remains crucial to conduct further research to confirm these findings and determine the most effective treatment strategy.

ABSTRACT Aims Diabetes mellitus (DM) is closely associated with Alzheimer's disease (AD), and is considered an accelerator of AD. Our previous study has confirmed that the Calpain inhibitor Calpeptin may alleviate AD‐like complications of diabetes mellitus. This work further investigated its underlying mechanism. Materials and Methods Diabetes mellitus rat model was constructed by a high‐fat and high‐sugar diet combined with streptozotocin, followed by the administration of Calpeptin. Moreover, rats were micro‐injected with LV‐TXNIP‐OE/vector into the CA1 region of the hippocampus one day before streptozotocin injection. The Morris water maze test assessed the spatial learning and memory ability of rats. Immunohistochemistry and western blotting detected the expression of the pericyte marker PDGFRβ, tight junction proteins occludin and ZO‐1, calpain‐1, calpain‐2, APP, Aβ, Aβ‐related, and TXNIP/NLRP3 inflammasome‐related proteins. Immunofluorescence staining examined the blood vessel density and neurons in the hippocampus. Evans blue extravasation and fluorescence detected the permeability of the blood–brain barrier (BBB) in rats. Additionally, the oxidative stress markers and inflammatory‐related factors were assessed by enzyme‐linked immunosorbent assay. Results Calpeptin effectively reduced the expression of Calpain‐2 and TXNIP/NLRP3 inflammasome‐related proteins, improved the decreased pericyte marker (PDGFR‐β) and cognitive impairment in hippocampus of DM rats. The neuronal loss, microvessel density, permeability of BBB, Aβ accumulation, inflammation, and oxidative stress injury in the hippocampus of DM rats were also partly rescued by calpeptin treatment. The influence conferred by calpeptin treatment was reversed by TXNIP overexpression. Conclusions These data demonstrated that calpeptin treatment alleviated AD‐like symptoms in DM rats through regulating TXNIP/NLRP3 inflammasome. Thus, calpeptin may be a potential drug to treat AD‐like complications of diabetes mellitus.

Abstract With the development of new technology for multiple energy applications, household appliances using electricity and other energy sources are becoming increasingly abundant. Users can freely choose the way of energy consumption based on the price of electricity and other energy sources. The phenomenon has become one of the important factors affecting real‐time pricing. This study considers real‐time pricing in the case of multiple energy coexistence on the user side. According to the spatiotemporal coupling of electricity and other energy sources and the relationship between other energy sources and total energy consumption, an optimization model that satisfies the actual situation is established. By using the relaxation theory and dual decomposition technology, a partially distributed algorithm is proposed for multi‐period coupling and finding the optimal energy scheduling scheme for the energy company and each user, so as to maximize social welfare. In addition, under the background of multiple energy coupling, real‐time pricing can guide users to adjust their electricity consumption behaviour vertically and horizontally, change the type of energy, meet energy demand for end users and effectively reduce the peak‐to‐average ratio. Simulation results verify the rationality of the model and the effectiveness of the algorithm.

Abstract Aims Acute myocarditis, although a rare disease, can be associated with sudden cardiac death or the need for transplantation in both children and young adults. To date, there is no definitive evidence to support the routine use of immunosuppressive therapy or treatment targeting inflammation in patients with myocarditis. Animal models of cardiovascular (CV), as well as neurological diseases, have demonstrated that cannabidiol has significant anti‐inflammatory properties and may represent a promising therapy in acute myocarditis. This efficacy has been shown in a murine model of autoimmune myocarditis as well as in in vitro and in vivo models of heart failure (HF). Methods and results We present the rationale and design of the ARCHER Trial, an international multicentre, double‐blind, randomized, placebo‐controlled, phase II study examining the safety and efficacy of a pharmaceutically produced cannabidiol formulation, in patients with mild to moderate acute myocarditis. Eligible patients are those with acute myocarditis, randomized within 10 days of the diagnostic cardiac MRI (CMR), which has met defined diagnostic criteria for myocarditis. Oral treatment (cannabidiol or placebo) is titrated from 2.5 mg/kg of body weight up to 10 mg/kg of body weight b.i.d. (or highest tolerated dose) and taken for 12 weeks in addition to standard of care therapy for HF. The primary endpoints are defined as changes in global longitudinal strain (GLS) and extra cellular volume (ECV), measured by CMR at 12 weeks. Assuming 80% power, a 5% alpha risk and 25% missing CMR follow‐up data at Week 12, 100 patients are required to demonstrate the desired treatment effect of 18%. The change in left ventricular ejection fraction (LVEF) from baseline to Week 12 was selected as the secondary endpoint. Additional exploratory endpoints include changes in hs‐troponin, NT‐proBNP, markers of inflammation and endothelial function during the 12‐week treatment period. The trial is ongoing but is now more than 50% recruited. As enrolment in the trial continues, no interim data are available for inclusion in this Design paper. Conclusions The ongoing ARCHER Trial is an international, multicentre, double‐blind, randomized, placebo‐controlled phase II study, designed to determine the effect of a pharmaceutically produced cannabidiol formulation on CMR parameters in patients presenting with acute myocarditis. Enrolment of 100 patients is expected to conclude in Q3 2024. Study results will be available in early 2025.

Abstract Skeleton‐based action recognition has received much attention and achieved remarkable achievements in the field of human action recognition. In time series action prediction for different scales, existing methods mainly focus on attention mechanisms to enhance modelling capabilities in spatial dimensions. However, this approach strongly depends on the local information of a single input feature and fails to facilitate the flow of information between channels. To address these issues, the authors propose a novel Temporal Channel Reconfiguration Multi‐Graph Convolution Network (TRMGCN). In the temporal convolution part, the authors designed a module called Temporal Channel Fusion with Guidance (TCFG) to capture important temporal information within channels at different scales and avoid ignoring cross‐spatio‐temporal dependencies among joints. In the graph convolution part, the authors propose Top‐Down Attention Multi‐graph Independent Convolution (TD‐MIG), which uses multi‐graph independent convolution to learn the topological graph feature for different length time series. Top‐down attention is introduced for spatial and channel modulation to facilitate information flow in channels that do not establish topological relationships. Experimental results on the large‐scale datasets NTU‐RGB + D60 and 120, as well as UAV‐Human, demonstrate that TRMGCN exhibits advanced performance and capabilities. Furthermore, experiments on the smaller dataset NW‐UCLA have indicated that the authors’ model possesses strong generalisation abilities.

Abstract Image captioning is an important task for understanding images. Recently, many studies have used tags to build alignments between image information and language information. However, existing methods ignore the problem that simple semantic tags have difficulty expressing the detailed semantics for different image contents. Therefore, the authors propose a tag‐inferring and tag‐guided Transformer for image captioning to generate fine‐grained captions. First, a tag‐inferring encoder is proposed, which uses the tags extracted by the scene graph model to infer tags with deeper semantic information. Then, with the obtained deep tag information, a tag‐guided decoder that includes short‐term attention to improve the features of words in the sentence and gated cross‐modal attention to combine image features, tag features and language features to produce informative semantic features is proposed. Finally, the word probability distribution of all positions in the sequence is calculated to generate descriptions for the image. The experiments demonstrate that the authors’ method can combine tags to obtain precise captions and that it achieves competitive performance with a 40.6% BLEU‐4 score and 135.3% CIDEr score on the MSCOCO data set.

Abstract Leading digital innovation projects in smart cities requires the right human resources with the right set of competencies. Such requirement is challenging because city managers and built environment professionals are traditionally trained and work in disciplinary and professional silos. This results in a lack of knowledge, abilities, and tools to produce optimal outcomes for communities across multiple sectors. Guided by a socio‐technical and multidisciplinary approach, the DC2‐CF framework is proposed to help urban planners identify, develop and expand the competencies they need to effectively steer responsible digital innovation and ensure public value creation. The DC2‐CF proposes a digital innovation process model to facilitate the delivery of successful urban digital innovation projects based on the lessons learned from working with city digital leaders. In addition, the DC2‐CF provides a delivery structure which identifies specific tasks, competencies, and roles necessary to enable the use off the innovation process model in practice and break down the professional silos currently existing in cities. The framework is envisioned to assist city planners in fostering leadership capacity in local authorities and the private sector in digital city development, contributing to enhancing collaborative working and effective public value creation.

Abstract Bone is a common organ affected by metastasis in various advanced cancers, including lung, breast, prostate, colorectal, and melanoma. Once a patient is diagnosed with bone metastasis, the patient's quality of life and overall survival are significantly reduced owing to a wide range of morbidities and the increasing difficulty of treatment. Many studies have shown that bone metastasis is closely related to bone microenvironment, especially bone immune microenvironment. However, the effects of various immune cells in the bone microenvironment on bone metastasis remain unclear. Here, we described the changes in various immune cells during bone metastasis and discussed their related mechanisms. Osteoblasts, adipocytes, and other non‐immune cells closely related to bone metastasis were also included. This review also summarized the existing treatment methods and potential therapeutic targets, and provided insights for future studies of cancer bone metastasis.

Abstract An equivalent circuit modelling methodology for the ball‐grid‐array (BGA) transition is proposed and validated with full‐wave electromagnetic simulation and measurement results. The BGA transitions modelled with the proposed methodology are validated to have a good accuracy up to 40 GHz. Unlike the existing BGA modelling methodologies which cannot model the BGA transition with short transmission lines within the anti‐pad region, the proposed methodology is developed from the practical BGA modelling scenario and models the irregular‐shape solder pads with transmission lines within the anti‐pad region. The BGA transitions modelled with the proposed methodology can be used for accurate and fast signal integrity simulations, analyses, and optimizations on 2.5D and 3D packaging. Additionally, factors impacting the accuracy of the equivalent circuit model are revealed by the proposed methodology.

Abstract The relationship between the differential protective effect of salt substitute between hypertensive and normotensive individuals and the use of cardiovascular medications remains unclear. This study involved 4211 individuals with a history of stroke or hypertension who participated in the Salt Substitute and Stroke Study (SSaSS) from 120 villages in Shanxi Province. The aim of this study was to investigate the differences in major adverse cardiovascular events and blood pressure changes between the salt substitute and the regular salt group in the subgroups of participants taking different antihypertensive medications. Mixed models were employed and adjusted for the cluster effect (village) and potential confounding variables. During the average follow‐up period of 4.66 years, a significantly protective effect of salt substitute on reducing the risk of cardiovascular events was observed in the participants who taking antihypertensive medications (rate ratio: 0.81, 95% CI: 0.68 to 0.95. p = 0.011), whereas no significant effect in participants not taking antihypertensive medications (rate ratio: 0.91, 95% CI: 0.62 to 1.32, p = 0.612). Significant effects to lower systolic blood pressure of the salt substitutes were observed in the participants who took different antihypertensive medications. This study emphasized that the use of salt substitutes might enhance the efficacy of anti‐hypertensive medications in lowering blood pressure and reducing the risk of adverse cardiovascular events.

Endometrial carcinoma (ECa) is the fourth most common cancer among women. The oncogene PELP1 is frequently overexpressed in a variety of cancers, including ECa. We recently generated SMIP34, a small‐molecule inhibitor of PELP1 that suppresses PELP1 oncogenic signaling. In this study, we assessed the effectiveness of SMIP34 in treating ECa. Treatment of established and primary patient‐derived ECa cells with SMIP34 resulted in a significant reduction of cell viability, colony formation ability, and induction of apoptosis. RNA‐seq analyses showed that SMIP34‐regulated genes were negatively correlated with ribosome biogenesis and eukaryotic translation pathways. Mechanistic studies showed that the Rix complex, which is essential for ribosomal biogenesis, is disrupted upon SMIP34 binding to PELP1. Biochemical assays confirmed that SMIP34 reduced ribosomal biogenesis and new protein synthesis. Further, SMIP34 enhanced the efficacy of mTOR inhibitors in reducing viability of ECa cells. SMIP34 is also effective in reducing cell viability in ECa organoids in vitro and explants ex vivo. Importantly, SMIP34 treatment resulted in a significant reduction of the growth of ECa xenografts. Collectively, these findings underscore the potential of SMIP34 in treating ECa.

Abstract Quorum sensing (QS) inhibition has emerged as a promising target for directed drug design, providing an appealing strategy for developing antimicrobials, particularly against infections caused by drug‐resistant pathogens. In this study, we designed and synthesized a total of 33 β‐nitrostyrene derivatives using 1‐nitro‐2‐phenylethane (NPe) as the lead compound, to target the facultative anaerobic bacterial pathogen Serratia marcescens. The QS‐inhibitory effects of these compounds were evaluated using S. marcescens NJ01 and the reporter strain Chromobacterium violaceum CV026. Among the 33 new β‐nitrostyrene derivatives, (E)‐1‐methyl‐4‐(2‐nitrovinyl)benzene (m‐NPe, compound 28) was proven to be a potent inhibitor that reduced biofilm formation of S. marcescens NJ01 by 79%. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) results revealed that treatment with m‐NPe (50 μg/ml) not only enhanced the susceptibility of the formed biofilms but also disrupted the architecture of biofilms by 84%. m‐NPe (50 μg/ml) decreased virulence factors in S. marcescens NJ01, reducing the activity of protease, prodigiosin, and extracellular polysaccharide (EPS) by 36%, 72%, and 52%, respectively. In S. marcescens 4547, the activities of hemolysin and EPS were reduced by 28% and 40%, respectively, outperforming the positive control, vanillic acid (VAN). The study also found that the expression levels of QS‐ and biofilm‐related genes (flhD, fimA, fimC, sodB, bsmB, pigA, pigC, and shlA) were downregulated by 1.21‐ to 2.32‐fold. Molecular dynamics analysis showed that m‐NPe could bind stably to SmaR, RhlI, RhlR, LasR, and CviR proteins in a 0.1 M sodium chloride solution. Importantly, a microscale thermophoresis (MST) test revealed that SmaR could be a target protein for the screening of a quorum sensing inhibitor (QSI) against S. marcescens. Overall, this study highlights the efficacy of m‐NPe in suppressing the virulence factors of S. marcescens, identifying it as a new potential QSI and antibiofilm agent capable of restoring or improving antimicrobial drug sensitivity.

ABSTRACT Importance Nutrition is associated with neurodevelopment. Infants at high risk of cerebral palsy (CP) usually suffer from undernutrition, yet the relationship between nutritional status and neurodevelopmental levels is unclear. Objective To describe the nutritional status characteristics of infants at high risk of CP, and to explore the relationship between neurodevelopmental levels and nutritional status. Methods This single‐center cross‐sectional study enrolled infants at high risk of CP, with corrected age from 0 days to 12 months. Weight and height were measured and calculated into z‐scores, which were used to classify the nutritional status based on the World Health Organization growth charts and American Society for Parenteral and Enteral Nutrition standards. The Bayley Scales of Infant and Toddler Development were used to evaluate the developmental levels of gross motor, fine motor, cognition, receptive communication, and expressive communication. Results A total of 479 infants at high risk of CP were recruited, with 43.4% classified as undernutrition. Compared to those with normal neurodevelopment, the odds of moderate and severe undernutrition were about 1.8 and 3.9 times higher in gross motor delay, 2.2 and 3.1 times higher in fine motor delay, 2.5 and 9.4 times higher in cognition delay, 2.2 and 3.9 times higher in receptive communication delay, and 3.0 and 5.6 times higher in expressive communication delay. There were significant positive correlations between nutritional status and neurodevelopmental levels (P < 0.001). Interpretation Undernutrition and neurodevelopmental delays are prevalent among infants at high risk of CP. Worse nutritional status was correlated with lower neurodevelopmental levels.

Abstract Background High‐intensity focused ultrasound (HIFU) is widely used in the treatment of deep tumours, but clinical trials on skin tumours are not yet available. Neurofibromatosis Type I (NF1) is among the most common single‐gene inherited conditions worldwide and predisposes to benign and malignant neoplasms of the nervous system. Multiple cutaneous neurofibromas (cNFs) often cause social and functional limitations, itching and pain. Objectives The objective of this study was to investigate the safety, local tolerability and efficacy of a novel method utilizing HIFU for the treatment of cNFs. Methods A 20 MHz HIFU‐device with an integrated dermoscopic guidance and a handpiece with a focus depth of 2.3 mm below the skin surface was used. Doses of acoustic energy with 0.7 J/dose and pulse duration of 250 ms/dose were manually positioned with 1–2 mm distance between each applied dose. Number of applied doses depended on the size of the cNF. No anaesthetic was applied. Results Twenty patients with NF1 were recruited in two centres, and 147 cNFs were treated. There were no serious adverse events. Immediate and transient wheal‐and‐flare reactions occurred at treatment sites and occasionally there was minor epidermal damage which healed in 1–2 weeks. Dyspigmentation occurred in some tumours after 3–9 months but no scarring was observed at 9‐month follow‐up. During treatment, the patient‐reported pain‐score median was 3.5 (range 1–7) on a 0–10‐point scale. Clinical rating of cNFs after 9 months showed 48.9% full or major tumour reduction. The median reduction in tumour thickness measured by ultrasound at 9 months was 0.53 mm (range: –100% to +19%). Conclusions HIFU treatment is a new noninvasive, rapid and tolerable treatment modality that with high precision targets intradermal lesions. This study demonstrates acceptable safety, local tolerance and efficacy of HIFU for the treatment of cNFs that may further be developed also for other skin tumours.

Abstract Background Aberrant TGF‐β signaling pathway can lead to invasive phenotype of colorectal cancer (CRC), resulting in poor prognosis. It is pivotal to develop an effective prognostic factor on the basis of TGF‐β‐related genes to accurately identify risk of CRC patients. Methods We performed differential analysis of TGF‐β‐related genes in CRC patients from databases and previous literature to obtain TGF‐β‐related differentially expressed genes (TRDEGs). LASSO‐Cox regression was utilized to build a CRC prognostic feature model based on TRDEGs. The model was validated using two GEO validation sets. Wilcoxon rank‐sum test was utilized to test correlation of model with clinical factors. ESTIMATE algorithm and ssGSEA and tumor mutation burden (TMB) analysis were used to analyze immune landscape and mutation burden of high‐risk (HR) and low‐risk (LR) groups. CellMiner database was utilized to identify therapeutic drugs with high sensitivity to the feature genes. Results We established a six‐gene risk prognostic model with good predictive accuracy, which independently predicted CRC patients' prognoses. The HR group was more likely to experience immunotherapy benefits due to higher immune infiltration and TMB. The feature gene TGFB2 could inhibit the efficacy of drugs such as XAV‐939, Staurosporine, and Dasatinib, but promote the efficacy of drugs such as CUDC‐305 and by‐product of CUDC‐305. Similarly, RBL1 could inhibit the drug action of Fluphenazine and Imiquimod but promote that of Irofulven. Conclusion A CRC risk prognostic signature was developed on basis of TGF‐β‐related genes, which provides a reference for risk and further therapeutic selection of CRC patients.

Abstract Objective Subcortical nuclei such as the thalamus and striatum have been shown to be related to seizure modulation and termination, especially in drug‐resistant epilepsy. Enhance diffusion‐weighted imaging (eDWI) technique and tri‐component model have been used in previous studies to calculate apparent diffusion coefficient from ultra high b‐values (ADCuh). This study aimed to explore the alterations of ADCuh in the bilateral thalamus and striatum in MRI‐negative drug‐resistant epilepsy. Methods Twenty‐nine patients with MRI‐negative drug‐resistant epilepsy and 18 healthy controls underwent eDWI scan with 15 b‐values (0–5000 s/mm2). The eDWI parameters including standard ADC (ADCst), pure water diffusion (D), and ADCuh were calculated from the 15 b‐values. Regions‐of‐interest (ROIs) analyses were conducted in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus. ADCst, D, and ADCuh values were compared between the MRI‐negative drug‐resistant epilepsy patients and controls using multivariate generalized linear models. Inter‐rater reliability was assessed using the intra‐class correlation coefficient (ICC) and Bland–Altman (BA) analysis. False discovery rate (FDR) method was applied for multiple comparisons correction. Results ADCuh values in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus in MRI‐negative drug‐resistant epilepsy were significantly higher than those in the healthy control subjects (all p

Abstract Particle migration in oil and gas reservoirs is a common phenomenon in the process of oil and gas development, and is considered to be an important reason for the damage of reservoir permeability and the reduction of oil and gas productivity. The mechanism of this phenomenon includes the desorption, migration, and precipitation of particles, which eventually clogs the throat and causes reservoir damage. Therefore, it is necessary to accurately characterize the complex mechanism of particle migration and identify the main controlling factors of particle migration, which is very important for efficient oilfield development and plugging solution. First, the reservoir types are divided into three types and the pore structure models of different types of reservoirs are established. Then, computational fluid dynamics and discrete element coupling method numerical simulation and microscopic visualization of pore throat structure model were combined, to characterize the rules of particles and migration, and analyze the main controlling factors. Finally, a typical model of particle migration and clogging is established. The results show that particle size/throat and particle concentration are the key factors affecting particle plugging, and particle migration has the least effect on the permeability of Type I reservoir and the greatest damage to Type III reservoir. According to the mechanical and hydrodynamic behavior of particles in porous media, three mechanisms and six modes of particle plugging are proposed.

Abstract Predicting and understanding travellers’ mode choices is crucial to developing urban transportation systems and formulating traffic demand management strategies. Machine learning (ML) methods have been widely used as promising alternatives to traditional discrete choice models owing to their high prediction accuracy. However, a significant body of ML methods, especially the branch of neural networks, is constrained by overfitting and a lack of model interpretability. This study employs a neural network with feature selection for predicting travel mode choices and Shapley additive explanations (SHAP) analysis for model interpretation. A dataset collected in Chengdu, China was used for experimentation. The results reveal that the neural network achieves commendable prediction performance, with a 12% improvement over the traditional multinomial logit model. Also, feature selection using a combined result from two embedded methods can alleviate the overfitting tendency of the neural network, while establishing a more robust model against redundant or unnecessary variables. Additionally, the SHAP analysis identifies factors such as travel expenditure, age, driving experience, number of cars owned, individual monthly income, and trip purpose as significant features in our dataset. The heterogeneity of mode choice behaviour is significant among demographic groups, including different age, car ownership, and income levels.

Abstract The exploration of eco‐friendly insulating gas to substitute the most potent greenhouse gas sulphur hexafluoride (SF6) has consistently garnered significant attention. Herein, the authors evaluated the feasibility of utilising perfluoromethyl vinyl ether (PMVE, C3F6O) as a new branch of eco‐friendly insulating gas for the first time. The primary dielectric and stability characteristics of PMVE regarding AC breakdown, partial discharge, dielectric recovery, and decomposition properties were revealed under various gas pressure and electrical field conditions. It was found that PMVE demonstrated superior dielectric strength, with the AC breakdown and PD inception voltage (PDIV) 1.10 and 1.14 times that of pure SF6. Furthermore, the dielectric strength of PMVE exhibits stability even after undergoing 100 cycles of AC breakdowns, and there is no observable formation of solid precipitation on the electrode surface. The discharge decomposition of PMVE mainly generates fluorocarbon (CF4, C2F6, C3F6, C3F8, etc.) and CO. Overall, the exceptional insulation stability and no absence of solid precipitation features endow PMVE to be utilised as a new eco‐friendly gas for SF6‐free gas‐insulated equipment.

Abstract Infection by bacteria leads to tissue damage and inflammation, which need to be tightly controlled by host mechanisms to avoid deleterious consequences. It is previously reported that TMEM16F, a calcium‐activated lipid scramblase expressed in various immune cell types including T cells and neutrophils, is critical for the control of infection by bacterium Listeria monocytogenes (Lm) in vivo. This function correlated with the capacity of TMEM16F to repair the plasma membrane (PM) damage induced in T cells in vitro, by the Lm toxin listeriolysin O (LLO). However, whether the protective effect of TMEM16F on Lm infection in vivo is mediated by an impact in T cells, or in other cell types, is not determined. Herein, the immune cell types and mechanisms implicated in the protective effect of TMEM16F against Lm in vivo are elucidated. Cellular protective effects of TMEM16F correlated with its capacity of lipid scrambling and augment PM fluidity. Using cell type‐specific TMEM16F‐deficient mice, the indication is obtained that TMEM16F expressed in liver Kupffer cells (KCs), but not in T cells or B cells, is key for protection against Listeria in vivo. In the absence of TMEM16F, Listeria induced PM rupture and fragmentation of KCs in vivo. KC death associated with greater liver damage, inflammatory changes, and dysregulated liver metabolism. Overall, the results uncovered that TMEM16F expressed in Kupffer cells is crucial to protect the host against Listeria infection. This influence is associated with the capacity of Kupffer cell‐expressed TMEM16F to prevent excessive inflammation and abnormal liver metabolism.

Abstract Actuation of micro‐objects along unconstrained trajectories in van der Waals contacting systems—in the same capacity as optical tweezers to manipulate particles in fluidic environments—remains a formidable challenge due to the lack of effective methods to overcome and exploit surface friction. Herein, a technique that aims to resolve this difficulty is proposed. This study shows that, by utilizing a moderate power beam of light, micro‐objects adhered on planar solid substrates can be precisely guided to move in arbitrary directions, realizing sub‐nanometer resolution across extended surfaces. The underlying mechanism is the interplay between surface friction and pulsed opto‐thermo‐elastic deformations, and to render a biased motion with off‐centroid light illumination. This technique enables high‐precision assembly, separation control of nanogaps, regulation of rotation angles in various material‐substrate systems, whose capability is further tested in reconfigurable construction of optoelectronic devices. With simple set‐up and theoretical generality, opto‐thermo‐elastic actuation opens up an avenue for versatile optical manipulation in the solid domain.

Abstract Antimicrobial resistance (AMR) remains an urgent and formidable challenge to global public health. Developing new medicines or alternative therapies to address AMR is imperative. Herein, we rationally designed and synthesized a series of Au(I)‐based aggregation‐induced emission luminogens (AIEgens) to combat drug‐resistant bacterial infections. Through systematic screening, we identified an optimal AIEgen, called complex 5, which can rapidly discriminate between gram‐positive (G+) and gram‐negative bacteria (G−) bacteria, and exert robust and broad‐spectrum antimicrobial potency against diverse drug‐resistant bacterial strains, including those intractable to treat in clinic. Furthermore, extensive testing against a variety of clinical drug‐resistant isolates, coupled with the successful treatment of methicillin‐resistant Staphylococcus aureus‐infected skin wounds unequivocally validates the high efficiency and broad‐spectrum activity of complex 5. Therefore, complex 5 emerges as a promising candidate for combating drug‐resistant bacterial infections in clinic, and this work provides inspiration for developing new solutions to address the escalating global challenge of AMR.