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Abstract Aims This study sought to evaluate the correlation between waist‐to‐height ratio (WHtR) and heart failure (HF) outcomes across different ejection fraction (EF) categories. Methods and results A prospective cohort study was conducted at a comprehensive tertiary hospital in China. The participants were categorized by WHtR and EF quartiles. Outpatient or telephone follow‐up occurred every 6 months after the diagnosis of heart failure. The primary endpoint was all‐cause mortality at 48 months. Cox proportional hazard regression analyses were employed to evaluate the association between WHtR and all‐cause mortality. Among 859 enrolled participants, 545 (63.4%) were male, and the mean age was 65.2 ± 11.1 years. After adjusting for age and sex, WHtR demonstrated a strong correlation with both BMI (correlation = 0.703, P = 0.000) and WHR (correlation = 0.609, P = 0.000). Individuals with a high WHtR (≥0.50) had a higher prevalence of hypertension (56.4% vs. 39.6%) and diabetes (26.5% vs. 13.7%), higher levels of TC (3.61 ± 1.55 vs. 3.36 ± 0.90 mmol/L), TG (1.40 ± 0.81 vs. 1.06 ± 0.59 mmol/L), and LDL‐C (2.03 ± 0.85 vs. 1.86 ± 0.76 mmol/L) compared with patients with low WHtR (

Abstract Background Previously, a chronic social defeat stress (CSDS) model has been widely‐adopted for assessing depressive‐like behaviors in animals. However, there is still room for improvement in the CSDS model to safeguard study accuracy and the welfare of lab rodents. Our study team developed a novel, standardized apparatus to induce CSDS in rodents and assessed the model's practical adaptability. Methods An innovative CSDS cage apparatus and water bottle was designed. To evaluate the effectiveness of the newly developed tools, a variety of animal models, including the tail suspension test (TST), sucrose preference test, forced swimming test (FST), novelty‐suppressed feeding test, female urine sniffing test, and open field test (OFT), were adopted to assess depressive‐like behaviors in mice. Fluoxetine treatment was also administered to observe the reversal effect, as part of the validation. Results The CSDS cage apparatus resulted in the manifestation of depressive‐like behaviors in the model mice. Significant reductions in sucrose preference and urine sniffing time were observed, while the OFT revealed decreased central zone total distance, residence time, and frequency of entry. Moreover, increased immobility was found in the FST and TST. Fluoxetine treatment was found to successfully reverse the modeling effect. Conclusion The CSDS cage apparatus was validated for enhanced usability and addressed the previous challenges of water bottle leakage and lab rodent welfare issues. The consistent results from multiple behavioral tests also supported real‐world application of the apparatus, offering researchers a promising alternative to conventional rodent cages.

ABSTRACT The developed laminar structure of shale makes it possess obvious anisotropic characteristics, and these anisotropic characteristics are one of the important factors leading to the strong and weak heterogeneous properties of shale. Additionally, there is a common phenomenon where the propagation of hydraulic fracture heights is limited in the hydraulic fracturing process of strongly heterogeneous shale reservoirs. To clarify the reasons for the limited height propagation of hydraulic fractures in strongly heterogeneous shale reservoirs, numerical simulation methods were used to study the propagation patterns of hydraulic fractures in shale reservoirs under different levels of anisotropy, flow rate, viscosity, and stress differences. The results show that as the anisotropy value increases and the heterogeneity becomes stronger, it becomes more difficult for hydraulic fractures to expand along the fracture height direction, and the fracture width at the fracture opening becomes larger. For strongly heterogeneous shale reservoir, the hydraulic fracture height can be increased within a certain range by increasing the flow rate, viscosity, and stress difference. When the upper limit value is exceeded, the hydraulic fracture height of the strong heterogeneous shale reservoir gradually becomes stable, and the increasing trend is no longer obvious. The strong or weak heterogeneity caused by the inherent anisotropic characteristics of shale reservoirs affects the development and transformation effectiveness of shale reservoirs. The research in this article will provide some reference material and guidance for the efficient development of shale reservoirs.

Abstract Small interfering RNA (siRNA) has revolutionised biomedical research and drug development through precise post‐transcriptional gene silencing technology. Despite its immense potential, siRNA therapy still faces technical challenges, such as delivery efficiency, targeting specificity, and molecular stability. To address these challenges and facilitate siRNA drug development, we have developed siRNAEfficacyDB, a comprehensive database that integrates experimentally validated siRNA efficacy data. This database contains 3544 siRNA records, covering 42 target genes and 5 cell lines. It provides detailed information on siRNA sequences, target genes, inhibition efficiencies, experimental techniques, cell lines, siRNA concentrations, and incubation times. siRNAEfficacyDB offers a user‐friendly web interface that makes it easy to query, browse and analyse data, enabling efficient access to siRNA‐related information. In summary, siRNAEfficacyDB provides a useful data foundation for siRNA drug design and optimisation, serving as a valuable resource for advancing computer‐aided siRNA design research and nucleic acid drug development. siRNAEfficacyDB is freely available at https://cellknowledge.com.cn/siRNAEfficacy for non‐commercial use.

Abstract Elinzanetant is a potent and selective dual neurokin‐1 (NK‐1) and ‐3 (NK‐3) receptor antagonist that is currently developed for the treatment of women with moderate‐to‐severe vasomotor symptoms (VMS) associated with menopause. Here, we report the development of a population pharmacokinetic (popPK) model for elinzanetant and its principal metabolites based on an integrated dataset from 366 subjects (including 197 women with VMS) collected in 10 phase I or II studies. The pharmacokinetics of elinzanetant and its metabolites could be well described by the popPK model. Within the investigated dose range of 40–160 mg, the oral bioavailability of elinzanetant was dose independent and estimated to be 36.7%. The clearance of elinzanetant was estimated to be 7.26 L/h and the central and peripheral distribution volume were 23.7 and 168 L. No intrinsic or extrinsic influencing factors have been identified in the investigated population other than the effect of a high‐fat breakfast on the oral absorption of elinzanetant. The popPK model was then coupled to a pharmacodynamic model to predict occupancies of the NK‐1 and NK‐3 receptors. After repeated once‐daily administration of the anticipated therapeutic dose of 120 mg elinzanetant, the model‐predicted median receptor occupancies are >99% for NK‐1 and >94.8% for NK‐3 during day and night‐time, indicating sustained and near‐complete inhibition of both target receptors during the dosing interval.

ABSTRACT Background Cancer cachexia can impact prognosis, cause resistance to anticancer treatments and affect the tolerability of treatments. This study aims to identify hepatocellular carcinoma (HCC) with cachexia by characterizing longitudinal body composition (BC) trajectories. Methods This longitudinal, multicentre cohort study included unresectable HCC patients treated with first‐line programmed death‐(ligand)1 inhibitors plus anti‐vascular endothelial growth factor antibody/tyrosine kinase inhibitors between 01/2018–12/2022. BC measurements including skeletal muscle mass (SMM) and total adipose tissue area (TATA) were evaluated by computed tomography at the third lumbar vertebra at baseline and follow‐up imaging. Unsupervised latent class growth mixed models were applied to distinguish potential longitudinal SMM and TATA trajectories for identifying cachexia. The primary study endpoint was overall survival (OS), with secondary endpoints including progression‐free survival (PFS), objective response rate (ORR) and safety. Multiple Cox proportional hazards models were used to calculate adjusted hazard ratios (HRs) for survival. Results A total of 411 patients with 2138 time‐point measurements were included. The median age was 56 years, and 50 (12.2%) patients were female. Two distinct trajectories were identified for SMM and TATA: sharp‐falling and stable. SMM sharply declined in 58 patients (14.1%) and TATA in 71 of 406 patients (17.5%) with significant worse OS (for SMM, 17.0 vs. 24.9 months; p

Abstract Aims The value of the systemic immune‐inflammatory index (SII) in assessing adverse outcomes in various cardiovascular diseases has been extensively discussed. This study aims to evaluate the predictive value and risk stratification ability of SII for 30 day mortality in patients with acute decompensated heart failure (ADHF). Methods This analysis included 1452 patients hospitalized for ADHF, all the participants being part of the China Jiangxi‐acute decompensated heart failure1 project. The risk stratification capability of the SII in patients with ADHF, as well as its correlation with the 30 day mortality risk among ADHF patients, was evaluated utilizing Kaplan–Meier survival analysis and multivariable Cox regression models. A restricted cubic spline was employed to model the dose–response relationship between the two, and the receiver operating characteristic curve was utilized to assess the predictive ability of SII for 30 day mortality. Results The Kaplan–Meier analysis revealed that the risk of mortality in the high SII group (SII ≥ 980 × 109/L) was significantly greater than that in the low SII group (SII

Abstract Glaucoma poses a significant threat to vision, capable of causing irreversible damage and, in severe instances, leading to permanent blindness. Accurate optic cup (OC) and optic disc (OD) segmentation are essential in glaucoma screening. In this study, a novel OC and OD segmentation approach is proposed. Based on U‐Net, it is optimized by introducing cardinality dimensions. Moreover, attention gates are implemented to reinforce salient features while suppressing irrelevant information. Additionally, a convolutional block attention module (CBAM) is integrated into the decoder segment. This fusion hones in on effective information in both channel and spatial dimensions. Meanwhile, an image processing procedure is proposed for image normalization and enhancement. All of these increase the accuracy of the model. This model is evaluated on the ORIGA and REFUGE datasets, demonstrating the model's superiority in OC and OD segmentation compared to the state‐of‐the‐art methods. Additionally, after the proposed image processing, cup‐to‐disc ratio (CDR) prediction on a batch of 155 in‐house fundus images yields an absolute CDR error of 0.099, which is reduced by 0.04 compared to the case where only conventional processing was performed.

Abstract Changes in vegetation greenness have altered the regional terrestrial water cycle, yet their influence on drought remains unclear. To quantify the impact of vegetation greenness change on drought across global vegetation zones, this study conducted two simulations with and without linear trends in the Leaf Area Index (LAI), based on the Standardized Precipitation‐Evapotranspiration Index (SPEI) combined with the calibrated Shuttleworth‐Wallace potential evapotranspiration (PET) equation. Results revealed vegetation greening affected 71% of areas, and over 55% of areas experienced increases in PET, decreases in SPEI (indicating drying), and intensified drought conditions. The linear trends in LAI increased potential transpiration but decreased potential soil evaporation in most regions. The changes in drought are determined by the combined effects of these changes in potential transpiration and soil evaporation. This study highlights the critical role of vegetation greenness change in influencing drought.

ABSTRACT River ecosystems are facing significant degradation from human activities, which impact both biotic (e.g., fish and invertebrates) and abiotic components (e.g., water and habitat). A comprehensive comparison of energy flow patterns and system attributes among river food webs under different levels of human interference is highly important for developing management strategies to protect river ecosystems. Along the subtropical Pearl River, six spatial zones, including agricultural, industrial, island, urban, factory, and estuarine areas, were chosen to construct the Ecopath models. The output results revealed that the highest trophic level of the Pearl River was 3.8–4.2, which was occupied by softshell turtles and piscivorous/carnivorous fish. The most diverse functional groups were found in island and estuarine zones due to their heterogeneous habitats (e.g., high submerged vegetation coverage and the transition area between fresh and brackish water). In contrast, the food web structure in the industrial zone was destroyed due to water pollution (e.g., sewage discharge) and habitat degradation. The increase in exotic species and the decrease in native top predators were two factors that result in the low efficiency of energy transmission. A series of trophic (e.g., Lindeman transfer efficiency and mixed predator–prey impacts), structural (e.g., keystoneness, omnivory, and Finn's path length), and theoretical (e.g., connectance and ascendency) indices revealed that the health and maturity of the Pearl River sections can be ranked as island > estuarine > agricultural > urban > factory > industrial zones. The food chains led by softshell turtles (Pelodiscus sinensis), piscivores (e.g., Elopichthys bambusa), molluscivores (e.g., Mylopharyngodon piceus), and herbivores (e.g., Ctenopharyngodon idelus) could be used to indicate the health and functioning of river ecosystems. Our results suggest that the ecological management of river ecosystems should focus more efforts on protecting original habitats (e.g., the island zone with fish feeding/spawning grounds), monitoring bioindicators with keystone trophic impacts in the food web, and evaluating the food chains that play important roles in upward energy transmission.

ABSTRACT Aims To evaluate the effects of Jiawei Kongsheng Zhenzhong Pill (JKZP) on rats with ischemic mild cognitive impairment (MCI) and investigate the underlying mechanisms. Methods The components of JKZP were analyzed using Q‐Orbitrap high‐resolution mass spectrometry (HRMS). The MCI rat model was prepared through gradual bilateral common carotid artery occlusion (BCCAO). The cognitive function, hippocampal pathological lesions, dendritic spine damage, synapse‐related, and S100 calcium‐binding protein A10 (S100A10)/tissue‐type plasminogen activator (tPA)/brain‐derived neurotrophic factor (BDNF) pathway‐associated molecules alterations were measured. Primary hippocampus neurons were subjected to oxygen‐glucose deprivation/reperfusion (OGD/R) injury, and JKZP‐containing serum was utilized for treatment. Lentiviral‐infected neurons were constructed with S100A10 knockdown using RNAi technology to investigate whether JKZP exerted its anti‐MCI effects via S100A10/tPA/BDNF pathway. Results A total of 64 major components, including β‐asarone, ferulic acid, loganin, senkyunolide H, and cryptotanshinone, were identified by Q‐Orbitrap HRMS technology. JKZP had a notable impact on enhancing the cognitive abilities of rats with MCI. JKZP reduced the damage to the hippocampal CA1 region neuron and synaptic structure, reversed the decrease in dendritic spines, and increased the expressions of synapse‐associated proteins such as synaptophysin (SYN), growth‐associated protein 43 (GAP43), and postsynaptic density protein 95 (PSD95). Furthermore, JKZP treatment dramatically reduced the ratio of protein of BDNF (proBDNF)/mature BDNF (mBDNF) by activating S100A10/tPA, which was confirmed in primary hippocampus neurons in vitro. Moreover, sh‐S100A10 tremendously mitigated the inhibitory action of JKZP on OGD/R‐mediated synapse injury, decreased the activity of tPA, and thus improved the downstream pathway targets’ ratio, proBDNF/mBDNF. Conclusions These results manifested that JKZP promoted neurological recovery after chronic cerebral ischemia by alleviating synaptic damage and activating the S100A10/tPA/BDNF pathway, thereby providing a novel perspective and a solid foundation against MCI.

Abstract Generating computer‐generated holograms (CGHs) for 3D scenes by learning‐based methods can reconstruct arbitrary 3D scenes with higher quality and faster speed. However, the homogenization and difficulty of obtaining 3D high‐resolution datasets seriously limit the generalization ability of the model. A novel approach is proposed to train 3D encoding models based on convolutional neural networks (CNNs) using 2D image datasets. This technique produces virtual depth (VD) images with a statistically uniform distribution. This approach employs a CNN trained with the angular spectrum method (ASM) for calculating diffraction fields layer by layer. A fully convolutional neural network architecture for phase‐only encoding, which is trained on the DIV2K‐VD dataset. Experimental results validate its effectiveness by generating a 4K phase‐only hologram within only 0.061 s, yielding high‐quality holograms that have an average PSNR of 34.7 dB along with an SSIM of 0.836, offering high quality, economic and time efficiencies compared to traditional methods.

Abstract Neuropathic pain, one of the most refractory pain diseases, remains a formidable medical challenge. There is still an unmet demand for effective and safe therapies to address this condition. Herein, a rat model of nerve injury‐induced neuropathic pain is first established to explore its pathophysiological characteristics. Recognizing the role of neuroinflammation, an inflammation‐resolving amphiphilic conjugate PPT is designed and synthesized by simultaneously conjugating polyethylene glycol, phenylboronic acid pinacol ester, and Tempol onto a cyclic scaffold. PPT can self‐assemble into nanomicelles (termed PPTN). Following intravenous injection, PPTN preferentially accumulates in the injured nerve, ameliorates the neuroinflammatory milieu, and promotes nerve regeneration, thereby shortening neuropathic pain duration in rats. Moreover, the Ca2+ channel α2δ1 subunit is identified as a therapeutic target by RNA‐sequencing analysis of the injured nerve. Based on this target, a mimicking peptide (AD peptide) is screened as an analgesic. By packaging AD peptide into PPTN, a combination nano‐analgesic APTN is developed. Besides potentiated anti‐hyperalgesic effects due to site‐specific delivery and on‐demand release of AD peptide at target sites, APTN simultaneously inhibits neuroinflammation and promotes nerve regeneration by reprogramming macrophages via regulating MAPK/NF‐kB signaling pathways and NLRP3 inflammasome activation, thus affording synergistic efficacies in treating nerve injury‐induced neuropathic pain.

Abstract Cuproptosis, caused by an intracellular overload of copper (Cu) ions and overexpression of ferredoxin 1 (FDX1), is identified for its regulatory role in the skin wound healing process. This study verifies the presence of cuproptosis in skin wound beds and reactive oxygen species‐induced cells model. To address the two pathways leading to cell cuproptosis, a nanodrug‐engineered exosomes is proposed. A Cu‐chelator (Clioquinol, CQ) polydopamine (PDA)‐modified stem cell exosome loaded with siRNA‐FDX1, named EXOsiFDX1‐PDA@CQ, is designed to efficiently inhibit the two cuproptosis pathways. The functionalized exosomes are loaded into an injectable hydrogel and applied to treat diabetic wounds in mice and acute skin wounds in pigs. The local and controlled release of EXOsiFDX1‐PDA@CQ ensures the retention of the therapeutic agent at wound beds, effectively promoting wound healing. The strategy of engineered exosomes with functional nanoparticles (NPs) proposed in this study offers an efficient and scalable new approach for regulating cuproptosis.

ABSTRACT We report a rare complication of left ventricular giant thrombus in a patient with fulminant myocarditis after venoarterial extracorporeal membrane oxygenation therapy. This case report offers simple anticoagulant treatment experiences to eliminate significant LV thrombosis in patient undergoing extracorporeal membrane oxygenation, so that patients do not need surgery.

Background Data on the predictive value of coronary computed tomography angiography–derived fractional flow reserve (CT‐FFR) for long‐term outcomes are limited. Methods and Results A retrospective pooled analysis of individual patient data was performed. Deep‐learning‐based CT‐FFR was calculated. All patients enrolled were followed‐up for at least 5 years. The primary outcome was major adverse cardiovascular events. The secondary outcome was death or nonfatal myocardial infarction. Predictive abilities for outcomes were compared among 3 models (model 1, constructed using clinical variables; model 2, model 1+coronary computed tomography angiography–derived anatomical parameters; and model 3, model 2+CT‐FFR). A total of 2566 patients (median age, 60 [53–65] years; 56.0% men) with coronary artery disease were included. During a median follow‐up time of 2197 (2127–2386) days, 237 patients (9.2%) experienced major adverse cardiovascular events. In multivariable‐adjusted Cox models, CT‐FFR≤0.80 (hazard ratio [HR], 5.05 [95% CI, 3.64–7.01]; P

Abstract Mitochondrial dysfunction is a key event driving the maladaptive repair of tubular epithelial cells during the transition from acute kidney injury to chronic kidney disease (CKD). Therefore, identifying potential targets involved in mitochondrial dysfunction in tubular epithelial cells is clinically important. Myeloid‐derived growth factor (MYDGF), a novel secreted protein, plays important roles in multiple cardiovascular diseases, but the function of MYDGF in tubular epithelial cells remains unknown. In the present study, it is found that MYDGF expression is significantly reduced in the cortex of the kidney, especially in the proximal tubules, from mice with CKD. Notably, lower expression of MYDGF is observed in tubules from patients with CKD and the level of MYDGF correlated with key factors related to kidney fibrosis and estimated glomerular filtration rate (eGFR) in patients with CKD. Tubule‐specific deletion of Mydgf exacerbates kidney injury in mice with CKD; however, Mydgf overexpression attenuates kidney fibrosis by remodeling mitochondrial homeostasis in tubular epithelial cells. Mechanistically, renal tubular MYDGF positively regulates the expression of isocitrate dehydrogenase 2 (IDH2), restores mitochondrial homeostasis, and slows CKD progression. Thus, this study indicates that MYDGF derived from tubules may be an effective therapeutic strategy for patients with CKD.

Abstract Infrared (IR) radiation thermography is extensively utilized in diverse fields due to its non‐contact capability. Nevertheless, its effectiveness is often compromised by the significant emissivity variations among different objects, limiting its application to specific setups or focused object types. Colorimetric thermography is introduced as an alternative emissivity‐independent method of radiation thermometry. This technique involves measuring radiance across two or more spectral bands and calculating the object's temperature based on the signal ratio, thereby mitigating emissivity effects under certain conditions. However, this method has the trade‐off of necessitating bulky optical systems, complex filter imaging configurations, and sensor structures. To meet the requirements of IR thermography for compact structure, lightweight design, and customizability, a dual‐band metalens is developed for the IR colorimetric thermography. The central wavelengths targeted are 9.5 and 12.5 µm. The dual‐band IR imaging by the fabricated dual‐band metalens is demonstrated, and the colorimetric thermography of low‐emissivity objects is performed without presetting emissivity values. This approach significantly eliminates measurement errors associated with emissivity by an average of 50.16% across a temperature range of 60–180 °C. This innovation paves the way for dynamic and multi‐target thermography using compact IR systems in complex environments.

Abstract Bacterial infection is a crucial factor resulting in public health issues worldwide, often triggering epidemics and even fatalities. The accurate, rapid, and convenient detection of viable bacteria is an effective method for reducing infections and illness outbreaks. Here, an unsupervised learning–assisted and surface acoustic wave–interdigital transducer‐driven nano‐lens holography biosensing platform is developed for the ultrasensitive and amplification‐free detection of viable bacteria. The monitoring device integrated with the nano‐lens effect can achieve the holographic imaging of polystyrene microsphere probes in an ultra‐wide field of view (∽28.28 mm2), with a sensitivity limit of as low as 99 nm. A lightweight unsupervised learning hologram processing algorithm considerably reduces training time and computing hardware requirements, without requiring datasets with manual labels. By combining phage–mediated viable bacterial DNA extraction and enhanced CRISPR–Cas12a systems, this strategy successfully achieves the ultrasensitive detection of viable Salmonella in various real samples, demonstrating enhanced accuracy validated with the qPCR benchmark method. This approach has a low cost (∽$500) and is rapid (∽1 h) and highly sensitive (∽38 CFU mL−1), allowing for the amplification‐free detection of viable bacteria and emerging as a powerful tool for food safety inspection and clinical diagnosis.

Abstract Automatic generation of image captions is essentially a cross‐modal conversion from image to text. Owing to the differences in linguistic characteristics between Chinese and English, quite a few Chinese image captioning methods have recently been proposed. Nevertheless, the existing Chinese image captioning models usually lack attention to local details of images or tend to produce general descriptions. To address these challenges, a Chinese image captioning method is proposed that incorporates fusion encoder, visual keyword search, and reinforcement learning. The fusion encoder can simultaneously extract local and global features of the input image to enrich the semantic information in the decoding stage, visual keyword search can pursue potential visual words associated with the image content, and the reinforcement learning mechanism can optimize the evaluation metric CIDEr at sentence level to promote the lexical diversity of image description. The results of extensive experiments demonstrate that the proposed model outperforms the state‐of‐the‐art models and delivers expressive and informative Chinese image captions.

Abstract Recent advancements in deep learning have significantly improved performance in the multi‐view stereo (MVS) domain, yet achieving a balance between reconstruction efficiency and quality remains challenging for learning‐based MVS methods. To address this, we introduce MFE‐MVSNet, designed for more effective and precise depth estimation. Our model incorporates a pyramid feature extraction network, featuring efficient multi‐scale attention and multi‐scale feature enhancement modules. These components capture pixel‐level pairwise relationships and semantic features with long‐range contextual information, enhancing feature representation. Additionally, we propose a lightweight 3D UNet regularization network based on depthwise separable convolutions to reduce computational costs. This network employs bi‐directional skip connections, establishing a fluid relationship between encoders and decoders and enabling cyclic reuse of building blocks without adding learnable parameters. By integrating these methods, MFE‐MVSNet effectively balances reconstruction quality and efficiency. Extensive qualitative and quantitative experiments on the DTU dataset validate our model's competitiveness, demonstrating approximately 33% and 12% relative improvements in overall score compared to MVSNet and CasMVSNet, respectively. Compared to other MVS networks, our approach more effectively balances reconstruction quality with efficiency.

Fractures and bone nonunion commonly require surgical intervention. Serious outcomes of non‐healing in the late stages of fracture place a significant financial burden on society and families. Bone nonunion occurs when a fracture stops healing, for many reasons, and leads to a variety of bad outcomes. Numerous factors, including biomechanics and immunology, are involved in the complicated mechanisms of bone nonunion. The immune‐inflammatory response plays a significant part in the emergence of bone nonunion, and the occurrence, control, and remission of inflammation in the bone healing process have a significant influence on the ultimate success of bone tissue repair. In the bone microenvironment, immune cells and associated cytokines control bone repair, which is significantly influenced by macrophages, T cells, and fibroblast growth factor. To limit acute inflammation and balance osteogenesis and osteoblastogenesis for tissue repair and regeneration, immune cells and various cytokines in the local microenvironment must be precisely regulated. As a bad complication of late‐stage fractures, bone nonunion has a significant effect on patients’ quality of life and socioeconomic development. Therefore, in‐depth research on its pathogenesis and treatment methods has important clinical value. To provide more precise, focused therapeutic options for the treatment of bone nonunion, we discuss the regulatory roles of the key immune cells engaged in bone healing within the microenvironment during bone healing and their effect on osteogenesis.

Abstract This study investigated how structural parameters (including injection ducts and exhaust nozzle inner diameters) affect the internal flow field and dilution ratio of diesel particulate sampling diluters. Increasing air injection duct diameter increased the injection chamber pressure and decreased the air velocity peak, mixed gas flow velocity, sample temperature, and mixing rate. Excessively small tube diameters caused uneven and discontinuous flow field distributions, while substantial air blockage rendered the flow state poor. Increasing nozzle inner diameters increased the exhaust flow area and the sample temperature, but decreased the velocity of the exhaust and gas mixtures and the pressure drop. Compared with a 2.0 mm inner diameter, 2.5 and 3.0 mm diameters decreased the peak velocity by 11.18% and 14.41%, respectively, and mixing slowed significantly. Inner nozzle diameters of

Abstract The coalbed methane (CBM) productivity is directly determined by the fracture permeability during hydraulic fracturing, which is regulated by the distribution of proppants. The proppant may be unevenly distributed in the fracture because of variables like the architecture of the fracture and the characteristics of the sand‐carrying fluid. This study used two types of random functions to produce different ununiform distributions of proppant clusters in large‐scale fractures, with the aim of investigating the effect of these distributions on the overall permeability of the fracture. A model of fluid‐structure coupling is proposed. The closure of large‐scale fractures under in‐situ stress is analyzed using solid mechanics and the penalty function; the CBM flowing in proppant clusters and the high‐speed channel between them is simulated using Darcy's law and the Navier–Stokes equation, respectively; and the overall permeability of fractures is computed using the fluid pressure drop throughout the fracture and the fluid flowing velocity in the fracture's outlet. Since most CBM flows along high‐speed channels between the proppant clusters, the simulated findings show that the overall permeability of fractures with an uneven distribution of proppant clusters is significantly higher than that of the proppant cluster itself. As CBM becomes more discretely distributed, the proportion of CBM flowing within the proppant cluster continuously drops. As the permeability of the proppant cluster increases, the volume ratio of proppant clusters decreases, and the distribution of proppant clusters becomes more discrete, the overall permeability of the fracture continuously increases.

Abstract The development of cathode materials with controllable physicochemical structures and explicit catalytic sites is important in rechargeable Zn–air batteries (ZABs). Covalent organic frameworks (COFs) have garnered increasing attention owing to their facile synthesis methods, ordered pore structure, and selectivity of functional groups. However, the sluggish kinetics of oxygen evolution reaction (OER) or oxygen reduction reaction (ORR) inhibit their practical applications in ZABs. Herein, nucleophilic substitution is adopted to synthesize pyridine bi‐triazine covalent organic framework (denoted as O‐COF), and meanwhile, ionothermal conversion synthesis is employed to load MOx (M=Fe, Co) onto carbon nanosheet (named as FeCo@NC) to modulate the electronic structure. The Fe, Co‐N codoped carbon material possesses a large portion of pyridinic N and M‐N, high graphitization, and a larger BET surface area. An outstanding bifunctional activity has been exhibited in FeCo@NC, which provides a small voltage at 10 mA cm−2 for OER (E10 = 1.67 V) and a remarkable half‐wave voltage for ORR (E1/2 = 0.86 V). More impressively, when assembling ZABs, it displays notable rate performance, significant specific capacity (783.9 mAh gZn−1), and satisfactory long‐term endurance. This method of regulating covalent organic framework and ionothermal synthesis can be extended to design diverse catalysts.

Abstract As a novel drug development paradigm, selective activation of prodrugs provides the potential for precise tumor chemotherapy, thereby presenting an opportunity for advancing cancer treatment. The combination of photodynamic therapy (PDT) and prodrug can enhance the therapeutic efficacy while simultaneously enabling real‐time monitoring of drug distribution and release. However, the tumor hypoxia microenvironment and the frequent high‐dose administration of prodrugs significantly impede therapeutic efficacy and escalate treatment‐related risks. Herein, a tumor microenvironment‐specific release prodrug is constructed, termed NBS‐2S‐5FU. Under the influence of glutathione (GSH), NBS‐2S‐5FU undergoes activation, leading to the release of photosensitizer NBS and chemotherapeutic agent 5‐FU derivatives. Under irradiation, NBS produces sufficient superoxide radical (O2−•) while 5‐FU derivatives inhibit DNA biosynthesis, thereby effectively suppressing tumor growth at low doses. Subsequent in vivo studies utilizing NBS‐2S‐5FU liposomes exhibit outstanding anti‐cancer effectiveness. This study highlights a promising direction for advancing combined prodrugs that integrate PDT and chemotherapy.

Abstract Conventional inverter control methods reduce the grid inertia and are susceptible to parameter variations, resulting in a gradual weakening of grid stability. To address the above problems, an improved vector selection model predictive control strategy is proposed, with virtual synchronous generator technology to control the quasi‐Z‐source inverter. First, the influence of different operating states on the quasi‐Z‐source inverter state variables is analysed, and the established quasi‐Z‐source inverter‐virtual synchronous generator discrete‐time model predicts the input current, output capacitor voltage, and load current of the quasi‐Z‐source inverter network. Second, the inverter switching timing is analysed to establish the optimal switching vector set, and the optimal switching vector set is selected by defining the sub‐objective function, which reduces the average switching frequency of the system. Compared with the finite control set model predictive control, this strategy is to reduce the computation time of the system to obtain the optimal solution of the quasi‐Z‐source inverter, to improve the dynamic responsiveness of the system during the control process, and to improve the power quality. Finally, the effectiveness and correctness of the proposed algorithm are verified by experiments.

Abstract This paper presents a network traffic anomaly detection model based on feature grouping and multiple autoencoders (multi‐AEs) integration. This model comprises four modules: feature grouping module, feature learning module, AUC and optimal threshold calculation module, and anomaly detection application module. In the feature grouping module, multiple group features are constructed by selecting the different features according to their attributes and variances. In the feature learning module, the group features of normal traffic are learned based on multi‐AEs. In the AUC and optimal threshold calculation module, the AUC of each AE is calculated according to the ROC curve of the verification data, and the optimal thresholds for each AE are determined using the Youden index. In the anomaly detection application module, the AEs that participated in fusion are selected and their weights are calculated by analysing AUC value, and the scores of unknown traffic in each AE are evaluated considering both the reconstruction error distribution and the optimal threshold. Finally, the anomaly detection result can be obtained by the fusion of these multiple scores. Through validation on the UNSW‐NB15 and CICIDS2017 datasets, the accuracy of the proposed model is improved by 12.04% and 10.52%, respectively, compared to the baseline model.

Abstract The Atmospheric Environment Monitoring Satellite (AEMS), launched by China in 2022, was equipped with active remote sensing lidar for carbon monitoring. It adopts the Integrated Path Differential Absorption (IPDA) technology to monitor global CO2 column concentration (XCO2). The calculation of cloud top XCO2 requires cloud height data. A comparison between SRTM global elevation data and 1,572 nm channel elevation data reveals a coefficient of determination (R2) of 0.998, with an average deviation of 1.24 m. The cloud top XCO2 observations are consistent with the OCO‐2 and CarbonTracker trends. The ocean carbon uptake rate, assessed by the difference in CO2 concentration between cloud top and sea surface, is −0.319 mmol/m2/h, which is in good agreement with the associated carbon flux data. This demonstrates the great potential of IPDA lidar for remote sensing of cloud top CO2 and quantifying ocean carbon uptake.

Background Accumulating evidence indicates that coronary microvascular dysfunction (CMD) caused by hypercholesterolemia can lead to myocardial ischemia, with or without obstructive atherosclerotic coronary artery disease. However, the molecular pathways associated with compromised coronary microvascular function before the development of myocardial ischemic injury remain poorly defined. In this study, we investigated the effects of hypercholesterolemia on the function and integrity of the coronary microcirculation in mice and the underlying mechanisms. Methods and Results Mice were fed a hypercholesterolemic Paigen's diet for 8 weeks. Echocardiography data showed that Paigen's diet caused CMD, characterized by significant reductions in coronary blood flow and coronary flow reserve, but did not affect cardiac remodeling or dysfunction. Immunofluorescence studies revealed that Paigen's diet–induced CMD was associated with activation of coronary arterioles inflammation and increased myocardial inflammatory cell infiltration. These pathological changes occurred in parallel with the upregulation of lysosomal signaling pathways in endothelial cells (ECs). Treating hypercholesterolemic mice with the cholesterol‐lowering drug ezetimibe significantly ameliorated Paigen's diet–induced adverse effects, including hypercholesterolemia, steatohepatitis, reduced coronary flow reserve, coronary endothelial cell inflammation, and myocardial inflammatory cell infiltration. In cultured mouse cardiac ECs, 7‐ketocholesterol increased mitochondrial reactive oxygen species and inflammatory responses. Meanwhile, 7‐ketocholesterol induced the activation of transcriptional factor EB and lysosomal signaling in mouse cardiac ECs, whereas the lysosome inhibitor bafilomycin A1 blocked 7‐ketocholesterol–induced transcriptional factor EB activation and exacerbated 7‐ketocholesterol–induced inflammation and cell death. Interestingly, ezetimibe synergistically enhanced 7‐ketocholesterol–induced transcriptional factor EB activation and attenuated 7‐ketocholesterol–induced mitochondrial reactive oxygen species and inflammatory responses in mouse cardiac ECs. Conclusions These results suggest that CMD can develop and precede detectable cardiac functional or structural changes in the setting of hypercholesterolemia and that upregulation of transcriptional factor EB–mediated lysosomal signaling in endothelial cells plays a protective role against CMD.

Abstract Accurate non‐invasive monitoring of blood glucose (BG) is a challenging issue in the therapy of diabetes. Here near‐infrared (NIR) photoplethysmography (PPG) sensor based on a vapor‐deposited mixed tin‐lead hybrid perovskite photodetector is developed. The device shows a high detectivity of 5.32 × 1012 Jones and a large linear dynamic range (LDR) of 204 dB under NIR light, guaranteeing accurate extraction of eleven features from the PPG signal. By a combination of machine learning, accurate prediction of blood glucose level with mean absolute relative difference (MARD) as small as 2.48% is realized. The self‐powered PPG sensor also works for real‐time outdoor healthcare monitors using sunlight as a light source. The potential for early diabetes diagnoses by the perovskite PPG sensor is demonstrated.

Abstract Emerging from the intricate interplay of topology and magnetism, the giant anomalous Hall effect (AHE) is the most known topological property of the recently discovered kagomé ferromagnetic Weyl semimetal Co3Sn2S2 with the magnetic Co atoms arranged on a kagomé lattice. Here it is reported that the AHE in Co3Sn2S2 can be fine‐tuned by an applied magnetic field orientated within ≈2° of the kagomé plane, while beyond this regime, it stays unchanged. Particularly, it can vanish in magnetic fields parallel to the kagomé plane and even decrease in magnetic fields collinear with the spin direction. This tunable AHE can be attributed to local spin switching enabled by the geometrical frustration of the magnetic kagomé lattice, revealing that spins in a kagomé ferromagnet change their switching behavior as the magnetic field approaches the kagomé plane. These results also suggest a versatile way to tune the properties of a kagomé magnet.

Abstract HIF‐1α (hypoxia induced factor‐1α), a vital protective signal against hypoxia, has a short lifetime after myocardial infarction (MI). Increasing HIF‐1α stability by inhibiting its hydroxylation with prolyl hydroxylases inhibitors such as DPCA (1,4‐dihydrophenonthrolin‐4‐one‐3‐carboxylic acid) presents positive results. However, the optimal inhibitor administration profile for MI treatment is still unexplored. Here, injectable, thermosensitive hydrogels with programmable DPCA release are designed and synthesized. Hydrogel degradation and slow DPCA release are coupled to form a feedback loop by attaching pendant DPCA to polymer backbone, which serve as additional crosslinking points through π–π and hydrophobic interactions. Pendant carboxyl groups are added to the copolymer to accelerate DPCA release. Burst release in the acute phase for myocardial protection and extended near zero‐order release across the inflammatory and fibrotic phases with different rates are achieved. All DPCA‐releasing hydrogels upregulate HIF‐1α, decrease apoptosis, promote angiogenesis, and stimulate cardiomyocyte proliferation, leading to preserved cardiac function and ventricular geometry. Faster hydrogel degradation induced by faster DPCA release results in a HIF‐1α expression eight times of healthy control and better therapeutic effect in MI treatment. This research demonstrates the value of precise regulation of HIF‐1α expression in treating MI and other relevant diseases and provides an implantable device‐based modulation strategy.

Abstract The lossless coding framework of High Efficiency Video Coding (HEVC) comprises prediction and entropy coding, while omitting the transform process. However, residuals derived from prediction continue to demonstrate significant spatial redundancy, which has the potential to compromise the coding efficiency. This article presents an optimized scheme for HEVC intra lossless coding that integrates transform and quantization. In the proposed scheme, a residual block, generated by HEVC, is partitioned into two components: the coefficient block and the error block. The coefficient block, responsible for lossless coding, is obtained through the adoption of the transform and quantization processes employed in HEVC lossy coding. Subsequently, the error block is derived by predicting the residual block using the generated coefficient block. Both the coefficient block and the error block can be effectively encoded utilizing the existing entropy coding scheme in HEVC lossy coding. Rate‐distortion optimization is employed to determine whether the residual block will be partitioned into two components. The proposed scheme is implemented into the HM 12.1 software. Through the utilization of the discrete cosine transform kernel and the discrete sine transform kernel, with a quantization parameter set to 20, on HEVC standard test sequences and the all intra main configuration file, empirical findings substantiate that the proposed methodology attains an average bit‐rate reduction of 3.31%, with a maximum improvement of 12.29% in comparison to HEVC lossless coding.

Background The proliferative capacity of cardiomyocytes in adult mammalian hearts is far too low to replace the cells that are lost to myocardial infarction. Both cardiomyocyte proliferation and myocardial regeneration can be improved via the overexpression of a constitutively active variant of YAP5SA (Yes‐associated protein, 5SA [active] mutant), but persistent overexpression of proliferation‐inducing genes could lead to hypertrophy and arrhythmia, whereas off‐target expression in fibroblasts and macrophages could increase fibrosis and inflammation. Methods and Results Transient overexpression of YAP5SA or GFP (green fluorescent protein; control) was targeted to cardiomyocytes via our cardiomyocyte‐specific modified mRNA translation system (YAP5SACM‐SMRTs or GFPCM‐SMRTs, respectively). YAP5SA‐cardiomyocyte specificity was confirmed via in vitro experiments in cardiomyocytes and cardiac fibroblasts that had been differentiated from human induced‐ pluripotent stem cells and in human umbilical‐vein endothelial cells, and the regenerative potency of YAP5SACM‐SMRTs was evaluated in a mouse myocardial infarction model. In cultured human induced‐pluripotent stem cells‐cardiomyocytes, YAP was abundantly expressed for 3 days after YAP5SACM‐SMRTs administration and was accompanied by increases in the expression of markers for proliferation, before declining to near‐background levels after day 7, whereas GFP fluorescence remained high from days 1 to 3 after GFPCM‐SMRTs treatment and then slowly declined. GFP fluorescence was also observed in human induced‐pluripotent stem cells‐cardiac fibroblasts and human umbilical‐vein endothelial cells on day 1 after GFPCM‐SMRTs administration but declined substantially by day 3. In the mouse myocardial infarction model, echocardiographic assessments of left‐ventricular ejection fraction and fractional shortening were significantly greater, whereas infarct sizes were significantly smaller in YAP5SACM‐SMRTs–treated mice than in vehicle‐treated control animals, and YAP5SACM‐SMRTs appeared to promote cardiomyocyte proliferation. Conclusions The CM‐SMRTs can be used to transiently and specifically overexpress YAP5SA in cardiomyocytes, and this treatment strategy significantly promoted cardiomyocyte proliferation and myocardial regeneration in a mouse myocardial infarction model.

Abstract Sonopiezocatalytic therapy is an emerging therapeutic strategy that utilizes ultrasound irradiation to activate piezoelectric materials, inducing polarization and energy band bending to facilitate the generation of reactive oxygen species (ROS). However, the efficient generation of ROS is hindered by the long distance of charge migration from the bulk to the material surface. Herein, atomically thin Bi2O2(OH)(NO3) (AT‐BON) nanosheets are rationally engineered through disrupting the weaker hydrogen bonds within the [OH] and [NO3] layer in the bulk material. The ultrathin structure of AT‐BON piezocatalytic nanosheets shortens the migration distance of carriers, expands the specific surface area, and accelerates the charge transfer efficiency, showcasing a natural advantage in ROS generation. Importantly, the non‐centrosymmetric polar crystal structure grants the nanosheets the ability to separate electron‐hole pairs. Under ultrasonic mechanical stress, Bi2O2(OH)(NO3) nanosheets with the remarkable piezoelectric feature exhibit the desirable in vivo antineoplastic outcomes in both breast cancer model and liver cancer model. Especially, the AT‐BON‐induced ROS bursts lead to the activation of the Caspase‐1‐driven pyroptosis pathway. This study highlights the beneficial impact of bulk material thinning on enhancing ROS generation efficiency and anti‐cancer effects.

Abstract Objective The relationship between systemic immune‐inflammation index (SII) and psoriasis and its prognosis is not yet clear. In this study, the correlation between SII and psoriasis, psoriasis comorbidities, and all‐cause mortality was investigated based on the National Health and Nutrition Examination Survey (NHANES). Methods The study population was derived from five NHANES cycles: 2003–2006, 2009–2014, and survival follow‐up was as of December 31, 2019. The association between SII and psoriasis and its comorbidities was analyzed using weighted multivariate logistic regression models. Weighted COX regression was used to calculate hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs). Restricted cubic spline, subgroup and sensitivity analyses were also used. Logarithmic conversion was performed on SII(log2SII) to reduce the impact of outliers. Results A total of 21,431 participants were included in this study. As a continuous variable, log2SII was significantly associated with psoriasis in the fully adjusted model [OR = 1.20(1.04–1.39), p = .01]. log2SII remained positively associated with psoriasis after excluding participants with a history of cancer or cardiovascular disease (CVD), or non‐Hispanic black participants. Among psoriasis patients, log2SII was significantly associated with metabolic syndrome (MetS) [OR = 1.68(1.19,2.38), p = .004] and all‐cause mortality [HR = 1.48(1.09,1.99), p = .01]. Similar results were consistently observed when SII was analyzed as a categorical variable (in quartiles). Conclusion This study suggested a positive association between SII and the prevalence of psoriasis. Among psoriasis patients, SII was positively correlated with MetS and all‐cause mortality.

Abstract Precise electromagnetic transient simulation of induction motors (IMs) under voltage sag condition is necessary in Electro‐Magnetic Transient Programme. Although traditional fifth‐order model can accurately reflect the electromagnetic transient behaviour of IMs, the disadvantage of massive computation limits its application in the large‐scale system simulation. Considering voltage sag is a typical power quality issue, a novel reduced‐order electromagnetic transient model based on equivalent flux linkage derivative is proposed to shorten simulation time during voltage sag. When characteristic parameters of voltage sag are given, an equivalent flux linkage derivative can be obtained simply, and the proposed model can effectively shorten the simulation time while ensuring accuracy of the fifth‐order model. Simulation results of small capacity (5.5‐kW) and large capacity (315‐kW and 1600‐kW) IMs in simple system and IEEE 9‐bus system confirm the applicability of the proposed model. It is estimated that simulation time of the proposed model decreases by 76% compared with the fifth‐order model. Finally, the experimental validation with the 5.5‐kW IM is carried out to show the effectiveness of the theory.

Abstract Background Acute thrombotic events play a major role in various cardiovascular diseases. Therefore, direct thrombus imaging can be proved beneficial for early diagnosis and prompt therapy of thrombosis. Our study investigated targeted dual‐modality cyclic arginine‐glycine‐aspartic micro bubbles (cRGD‐MBs) for direct imaging of thrombi by fluorescence and ultrasound. Methods cRGD‐MBs were prepared by mechanical vibration and chemical chelation methods. Results Coulter counter analysis demonstrated that the cRGD‐MBs were well dispersed, with diameters ranging from 1 to 3 μm. They emitted bright red fluorescence under an excitation wavelength of 660 nm. In vivo fluorescence and ultrasound imaging revealed that cRGD‐MBs accumulated at the site of thrombus in the carotid artery with significant fluorescence and ultrasonic signal. Conclusions This study showed that novel microbubble cRGD‐MBs were successfully synthesized, and that these could potentially be used as contrast agents for immediate diagnosis of acute thrombus in vivo.

Abstract The DC multi‐port converter's applications are increasing owing to its favourable features, including variable control mode, high power density, and bi‐directional power supply. On the other hand, the impedance interaction between each port of the electrolytic capacitor‐less DC multi‐port converter may generate an instability. To address the above mentioned problem, a method is proposed in this paper for reshaping the impedances of the energy storage converter by constructing a virtual impedance connected in parallel with the output impedance of the electrolytic capacitor‐less DC multi‐port converter. Furthermore, this paper introduces the stability criterion based on the unified impedance theory, which classifies a converter as either the bus current‐controlled converter or the bus voltage‐controlled converter. The proposed control approaches raise the magnitude of the output impedance of the electrolytic capacitor‐less DC multi‐port converter to satisfy the unified impedance theory criterion without modifying each port. The simulation results show that the proposed method is better than the traditional methods, and comprehensive experimental results are provided to validate the proposed methods.

Abstract Background Neoadjuvant chemoimmunotherapy (NCIT) for locally advanced esophageal squamous cell carcinoma (ESCC) is supported by increasing data, but the sample size is limited, and the findings are not completely consistent. We conducted a real‐world study and a meta‐analysis to evaluate the efficacy and safety of NCIT in locally advanced ESCC. Methods We retrospectively assessed the outcomes of patients with locally advanced ESCC who completed NICT and subsequent esophagectomy at our hospital between January 2019 and December 2022, including pathological complete response (pCR) rate, major pathological response (MPR) rate, 1‐, 2‐, and 3‐year overall survival (OS) rates, disease control rate (DCR), objective response rate (ORR), 1‐year recurrence rate, R0 resection rate and adverse events. Moreover, a meta‐analysis of 27 published literatures was also conducted for comparison. Results In the analysis, 128 patients were studied, with 25% achieving pCR, 46.1% MPR, and 99.2% R0 resection. The 1‐, 2‐, and 3‐year OS rates were 91.41% (95% CI: 85.15%–95.63%), 75.00% (95% CI: 66.58%–82.23%) and 64.84% (95% CI: 55.91%–73.07%).ORR and DCR were 31.2% (95% CI: 23.31–39.99) and 64.1% (95% CI: 55.15%–72.38%), and the 1‐year recurrence rate was 26.7% (95% CI: 22.5%–38.1%). Treatment‐related events occurred in 96.1% but were acceptable. In a meta‐analysis of 27 studies with 1734 patients, pooled rates for pCR, MPR, ORR, DCR, and R0 resection were 29%, 52%, 71%, 97%, and 98%, respectively, with a 1‐year recurrence rate of 12%. Conclusion NCIT is safe and provides potential survival benefits for patients with locally advanced ESCC. However, randomized phase 3 trial data is still needed.

Abstract Due to the requirement for highly precise synchronous sampling and the substantial reliance on time difference calculations, the current partial discharge (PD) localization based on the time difference of arrival is only applicable in certain situations. As digital twin technology has advanced, it is possible to employ virtual models to support gas‐insulated switchgear (GIS) PD localization. To do this, we propose a meta‐learning (ML) network with the aid of digital twin for actual GIS PD localization. Firstly, a GIS digital twin model was established to acquire an auxiliary simulated sample library. Then, a temporal convolutional network is established to extract the discriminable features, effectively obtain the time dependence between features, and improve the accuracy of localization. Next, ML is adopted to quickly learn meta‐knowledge that can be applied across tasks, and the model's sensitivity to task changes is improved. Finally, the model is fine‐tuned through a limited number of samples from the target task, and high precise PD localization is achieved. The experimental results demonstrate that the ML has an average localization error of only 9.25 cm and a probability density rose to 93% within 20 cm, which is clearly superior to previous methods.

Abstract To address the challenges of detecting a large number of objects and a high proportion of small objects in aerial drone imagery, an aerial dense small object detection algorithm called coordinate position attention module you only look once (CPAM‐YOLO) is proposed based on the coordinate position attention module (CPAM). In the backbone network of CPAM‐YOLO, a CPAM is proposed and embedded that decomposes channel attention into two 1D feature encoding processes, and selectively combines the features of each position through the weighted sum of all position features. Finally, features are aggregated along two spatial directions, increasing the effective information utilization of input feature positions and channels. The backbone network, feature enhancement network, and detection heads have been optimized to improve detection accuracy while ensuring a lightweight detection network. Using lightweight backbone networks to significantly reduce the number of parameters while using high‐resolution feature enhancement networks to retain more semantic and detailed features. The algorithm's performance was evaluated using the publicly available VisDrone2019 dataset. Compared to the baseline network YOLOv5l, CPAM‐YOLO achieved a 4.5% improvement in mAP0.5 and a 3.2% improvement in mAP0.95. These experimental results demonstrate the strong practicality of the CPAM‐YOLO object detection network for detecting dense small objects in aerial image.

Abstract Item response theory (IRT) models are usually the best way to analyze composite or rating scale data. Standard methods to evaluate covariate or treatment effects in IRT models do not allow to identify item‐specific effects. Finding subgroups of patients who respond differently to certain items could be very important when designing inclusion or exclusion criteria for clinical trials, and aid in understanding different treatment responses in varying disease manifestations. We present a new method to investigate item‐specific effects in IRT models, which is based on inspection of residuals. The method was investigated in a simulation exercise with a model for the Epworth Sleepiness Scale. We also provide a detailed discussion as a guidance on how to build a robust covariate IRT model.

Abstract Obstructive sleep apnea (OSA) is a sleep disorder which is linked to many health risks. The gold standard to evaluate OSA in clinical trials is the Apnea‐Hypopnea Index (AHI). However, it is time‐consuming, costly, and disregards aspects such as quality of life. Therefore, it is of interest to use patient‐reported outcomes like the Epworth Sleepiness Scale (ESS), which measures daytime sleepiness, as surrogate end points. We investigate the link between AHI and ESS, via item response theory (IRT) modeling. Through the developed IRT model it was identified that AHI and ESS are not correlated to any high degree and probably not measuring the same sleepiness construct. No covariate relationships of clinical relevance were found. This suggests that ESS is a poor choice as an end point for clinical development if treatment is targeted at improving AHI, and especially so in a mild OSA patient group.

Abstract Background PIEZO1 works differently in different cancers and at different stages of development. The objective of the current study was to explore the function and underlying mechanism of PIEZO1 in lung adenocarcinoma (LUAD) cells. Methods Different LUAD cell lines were treated with PIEZO1 inhibitor (GsMTx4) and agonist (Yoda1), and the expression of PIEZO1 in LUAD cells was detected using real‐time quantitative PCR (RT‐qPCR) and western blotting. The effects of PIEZO1 on invasion, migration and epithelial‐mesenchymal transition (EMT) markers protein expression of LUAD cells were detected using the MTT assay, flow cytometry, transwell assay, wound‐healing assay, and western blotting. Reactive oxygen species (ROS) agonists (BAY 87–2243) and inhibitors (NAC) and Wnt/β‐catenin pathway inhibitors (iCRT3) were selected to treat A549 cells to investigate the mechanism of PIEZO1 on ROS production and Wnt/β‐catenin expression in A549 cells. Results In A549, NCI‐H1395, and NCI‐H1975 cells, GsMTx4 promoted cell proliferation, invasion, migration, upregulated EMT‐related marker protein expression, and inhibited cell apoptosis, while Yoda1 exerted effects opposite to those of GsMTx4. In A549 cells, GsMTx4 can reduce ROS production, it also inhibited ROS production, apoptosis, and downregulated proapoptotic markers induced by BAY 87–2243. Importantly, BAY 87–2243 blocked the effect of GSMTX4‐induced Wnt/β‐catenin overexpression. Similarly, Yoda1 can reduce the effect of NAC. In addition, iCRT3 can block the upregulation of EMT‐related marker proteins by GsMTx4, and increase apoptosis and decrease cell invasion and migration. Conclusion In summary, PIEZO1 acts as a cancer suppressor by regulating the ROS/Wnt/β‐catenin axis, providing a new perspective on the role of mechanosensitive channel proteins in cancer.

Abstract Although power conversion efficiency (PCE) of solar cells (SCs) continues to improve, they are still far from practical application because of their complex synthesis process, high cost and inferior operational stability. Carbon quantum dots with high material stability and remarkable photoluminescence are successfully used in light‐emitting diodes. A good light emitter should also be an efficient SC according to the photon balance in Shockley–Quieisser formulation, in which all excitons are ultimately separated. However, the finite quantum‐sized sp2 domain leads to tight exciton bonding, and highly delocalized electron clouds in irregular molecular stacks form disordered charge transfer, resulting in severe energy loss. Herein, an axially growing carbon quantum ribbon (AG‐CQR) with a wide optical absorption range of 440–850 nm is reported. Structural and computational studies reveal that AG‐CQRs (aspect ratio ≈2:1) with carbonyl groups at both ends regulate energy level and efficiently separate excitons. The stacking‐controlled two‐dimensional AG‐CQR film further directionally transfers electrons and holes, particularly in AB stacking mode. Using this film as active layer alone, the SCs yield a maximum PCE of 1.22%, impressive long‐term operational stability of 380 h, and repeatability. This study opens the door for the development of new‐generation carbon‐nanomaterial‐based SCs for practical applications.

Abstract Myocardial Infarction (MI) is a leading cause of death worldwide. Metabolic modulation is a promising therapeutic approach to prevent adverse remodeling after MI. However, whether material‐derived cues can treat MI through metabolic regulation is mainly unexplored. Herein, a Cu2+ loaded casein microgel (CuCMG) aiming to rescue the pathological intramyocardial metabolism for MI amelioration is developed. Cu2+ is an important ion factor involved in metabolic pathways, and intracardiac copper drain is observed after MI. It is thus speculated that intramyocardial supplementation of Cu2+ can rescue myocardial metabolism. Casein, a milk‐derived protein, is screened out as Cu2+ carrier through molecular‐docking based on Cu2+ loading capacity and accessibility. CuCMGs notably attenuate MI‐induced cardiac dysfunction and maladaptive remodeling, accompanied by increased angiogenesis. The results from unbiased transcriptome profiling and oxidative phosphorylation analyses support the hypothesis that CuCMG prominently rescued the metabolic homeostasis of myocardium after MI. These findings enhance the understanding of the design and application of metabolic‐modulating biomaterials for ischemic cardiomyopathy therapy.