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The reductive functionalization of CO2 to value-added chemicals using powdered silicon as a reducing agent is a promising sustainable route, but the behavior of employed fluoride catalysts remains largely unknown. Here, the authors use tetrabutylammonium fluoride to catalyze the conversion of a variety of amines to amides with CO2 and H2O reduced by metallic silicon recovered from solar panel production waste and show that the catalyst effectively oxidizes Si atoms on both the surface and interior of the powdered silicon particles.

Background: TGF-beta signaling is a key regulator of immunity and multiple cellular behaviors in cancer. However, the prognostic and therapeutic role of TGF-beta signaling-related genes in ovarian cancer (OV) remains unexplored. Methods: Data of OV used in the current study were sourced from TCGA and GEO databases. Consensus clustering was applied to classify OV patients into different clusters using TGF-beta signaling-related genes. Differentially expressed genes (DEGs) between different clusters were screened by the “limma” R package. Prognostic genes were screened from DEGs by univariate Cox regression, followed by the construction of the TGF-beta signaling-related score. The prognostic value of TGF-beta signaling-related score was evaluated in both training and testing OV cohorts. Moreover, the immune status, GSEA and therapeutic response between low- and high-score groups were performed to further reveal the potential mechanisms. Results: By consensus clustering, OV patients were classified into two clusters with different tumor immune environments. After differential expression and univariate Cox regression analyses, GMPR, PIEZO1, EMP1, CXCL13, GADD45B, SORCS2, FOSL2, PODN, LYNX1 and SLC38A5 were selected as prognostic genes. Using PCA algorithm, the TGF-beta signaling-related score of OV patients was calculated based on prognostic genes. Then OV patients were divided into low- and high-TGF-beta signaling-related score groups. We observed that the two score groups had significantly different survivals, tumor immune environments and expressions of immune checkpoints. In addition, GSEA results showed that immune-related pathways and biological processes, like chemokine signaling pathway, TNF signaling pathway and T cell migration were significantly enriched in the low-score group. Moreover, patients in the low- and high-score groups had remarkably different sensitivity to chemo- and immunotherapy. Conclusion: For the first time, our study identified ten prognostic genes associated with TGF-beta signaling, constructed a prognostic TGF-beta signaling-related score and investigated the effect of TGF-beta signaling-related score on OV immunity and therapy. These findings may enrich our knowledge of the TGF-beta signaling in OV prognosis and help to improve the prognosis prediction and treatment strategies in OV.

(R,S)-(skew) symmetric matrices have numerous applications in civil engineering, information theory, numerical analysis, etc. In this paper, we deal with the (R,S)-(skew) symmetric solutions to the quaternion matrix equation AXB=C. We use a real representation Aτ to obtain the necessary and sufficient conditions for AXB=C to have (R,S)-(skew) symmetric solutions and derive the solutions when it is consistent. We also derive the least-squares (R,S)-(skew) symmetric solution to the above matrix equation.

Destructive interference between electron wavefunctions on the two-dimensional kagome lattice induces an electronic flat band, which could host a variety of interesting quantum states. Key to realize these proposals is to demonstrate the real-space localization of kagome flat-band electrons. The extent to which the complex structure of realistic materials counteract the localizing effect of destructive interference is hitherto unknown. Moreover, a detailed understanding of the real-space distribution of the electronic states of kagome flat bands has not been developed yet. We used scanning tunneling microscopy to visualize the kagome flat band at the surface of CoSn, a kagome metal. Consistent with results from model calculations, we find that the local density of states associated with the kagome flat bands exhibits a unique real-space distribution by which it can be distinguished from the local density of states of dispersive electron bands and trivially localized states, such as well-localized orbitals and surface resonances. Our results further show that these states exhibit an extremely small localization length of two to three angstroms concomitant with a strongly renormalized quasiparticle velocity v≈1×10^{4}m/s, comparable to that of moiré superlattices. Our findings provide fundamental insight into the electronic properties of kagome metals and present a key step for future research on emergent many-body states in these systems.

The ability to manipulate the twisting topology of van der Waals structures offers a new degree of freedom through which to tailor their electrical and optical properties. The twist angle strongly affects the electronic states, excitons and phonons of the twisted structures through interlayer coupling, giving rise to exotic optical, electric and spintronic behaviours1-5. In twisted bilayer graphene, at certain twist angles, long-range periodicity associated with moiré patterns introduces flat electronic bands and highly localized electronic states, resulting in Mott insulating behaviour and superconductivity3,4. Theoretical studies suggest that these twist-induced phenomena are common to layered materials such as transition-metal dichalcogenides and black phosphorus6,7. Twisted van der Waals structures are usually created using a transfer-stacking method, but this method cannot be used for materials with relatively strong interlayer binding. Facile bottom-up growth methods could provide an alternative means to create twisted van der Waals structures. Here we demonstrate that the Eshelby twist, which is associated with a screw dislocation (a chiral topological defect), can drive the formation of such structures on scales ranging from the nanoscale to the mesoscale. In the synthesis, axial screw dislocations are first introduced into nanowires growing along the stacking direction, yielding van der Waals nanostructures with continuous twisting in which the total twist rates are defined by the radii of the nanowires. Further radial growth of those twisted nanowires that are attached to the substrate leads to an increase in elastic energy, as the total twist rate is fixed by the substrate. The stored elastic energy can be reduced by accommodating the fixed twist rate in a series of discrete jumps. This yields mesoscale twisting structures consisting of a helical assembly of nanoplates demarcated by atomically sharp interfaces with a range of twist angles. We further show that the twisting topology can be tailored by controlling the radial size of the structure.

ObjectivesMedical marijuana use may substitute prescription opioid use, whereas nonmedical marijuana use may be a risk factor of prescription opioid misuse. This study examined the associations between recreational marijuana legalization and prescription opioids received by Medicaid enrollees.MethodsState-level quarterly prescription drug utilization records for Medicaid enrollees during 2010-2017 were obtained from Medicaid State Drug Utilization Data. The primary outcome, opioid prescriptions received, was measured in three population-adjusted variables: number of opioid prescriptions, total doses of opioid prescriptions in morphine milligram equivalents, and related Medicaid spending, per quarter per 100 enrollees. Two difference-in-difference models were used to test the associations: eight states and DC that legalized recreational marijuana during the study period were first compared among themselves, then compared to six states with medical marijuana legalized before the study period. Schedule II and III opioids were analyzed separately.ResultsIn models comparing eight states and DC, legalization was not associated with Schedule II opioid outcomes; having recreational marijuana legalization effective in 2015 was associated with reductions in number of prescriptions, total doses, and spending of Schedule III opioids by 32% (95% CI: (-49%, -15%), p = 0.003), 30% ((-55%, -4.4%), p = 0.027), and 31% ((-59%, -3.6%), p = 0.031), respectively. In models comparing eight states and DC to six states with medical marijuana legalization, recreational marijuana legalization was not associated with any opioid outcome.ConclusionsNo evidence suggested that recreational marijuana legalization increased prescription opioids received by Medicaid enrollees. There was some evidence in some states for reduced Schedule III opioids following the legalization.

Background: Outdoor physical activity (PA) brings important health benefits, but exposure to polluted air increases health risks. This study aimed to quantify the tradeoff of PA under fine particulate matter (PM2.5) air pollution by estimating the optimal PA duration under various pollution levels. Methods: A risk-benefit analysis was performed to estimate the optimal outdoor moderate-intensity PA (MPA) duration under varying PM2.5 concentrations. Results: An inverse nonlinear relationship was identified between optimal MPA duration and background PM2.5 concentration levels. When background PM2.5 concentration increased to 186 µg/m3, the optimal outdoor MPA duration decreased to 2.5 h/week, the minimum level recommended by current PA guidelines. When background PM2.5 concentration further increased to 235 µg/m3, the optimal outdoor MPA duration decreased to 1 h/week. The relationship between optimal MPA duration and background PM2.5 concentration levels was stronger when exercising at a location closer to a source of air pollution. Compared to the general adult population, adults aged 60 years and older had substantially steeper curves—the optimal outdoor MPA duration decreased to 2.5 h/week when background PM2.5 concentration reached 45 µg/m3. Conclusion: The health benefit of outdoor MPA by far outweighs the health risk of PM2.5 pollution for the global average urban background concentration (22 μg/m3). This modeling study examined a single type of air pollutant and suffered from measurement errors and estimation uncertainties. Future research should examine other air pollutants and indoor PA, incorporate short- and mid-term health effects of MPA and air pollution into the risk-benefit analysis, and provide estimates specific for high-risk subgroups.

IntroductionThe overall prevalence of Klebsiella spp., a group of important zoonotic pathogens, in the global dairy herds and the risk of cross-species transmission between humans and dairy cows remain to be clarified. This systematic review aimed to determine the prevalence of Klebsiella spp. in milk samples from dairy cows with mastitis worldwide and to assess the factors influencing the prevalence of these strains.MethodsQualified studies published from 2007 to 2021 were retrieved from ScienceDirect, Web of Science, PubMed, WanFang Database, China National Knowledge Infrastructure (CNKI), and VIP Chinese Journal Database. Calculations of prevalence and their 95% confidence intervals (CIs) were performed for all the studies using the Freeman-Tukey double arcsine transformation (PFT).ResultsA total of 79,852 milk samples from 55 manuscripts were examined in this meta-analysis, and 2,478 samples were found to be positive for Klebsiella spp. The pooled prevalence estimates worldwide were 7.95% (95% CI: 6.07%–10.06%), with significant heterogeneity (I2 = 98.8%, p = 0). The sampling period of 2013–2020 had a higher (p < 0.05) Klebsiella-positive proportion of milk samples (12.16%, 95% CI: 8.08%–16.90%) than that of 2007–2012 (3.85%, 95% CI: 2.67%–5.21%), indicating that bovine mastitis caused by Klebsiella may become increasingly prevalent. The risk factors for the high prevalence of Klebsiella in milk samples mainly included: economic development level (developing countries; 11.76%, 95% CI: 8.25%–15.77%), mastitis type (CM; 11.99%, 95% CI: 8.62%–15.79%), and population density (>500 per sq km; 10.28%, 95% CI: 2.73%–21.58%). Additionally, a bivariate meta-regression analysis revealed that the multidrug-resistance (MDR) rate of the epidemic strains was also closely related to economic development level (R2 = 78.87%) and population density (R2 = 87.51%).DiscussionDue to the potential risk of cross-species transmission between humans and cows, the prevalence of mastitis milk-derived Klebsiella and its high MDR rate need to be monitored, especially in developing countries with high population densities.

In most coastal oceans, the impacts of global warming on season duration and timing of seasonal transitions remain unknown. To mirror the reality of the ongoing climate change, the summer and winter seasons are redefined using the local water temperature thresholds in the Bohai Sea. Then the phase variations of these seasons are quantified using the duration and transition timing indices, including the duration (DUR), onset (ONS), and withdrawal (WIT) indices derived from the OSTIA SST dataset at a very high resolution (0.05°). During the last four decades (1982–2019), secular trends of summer indices extracted by the ensemble empirical mode decomposition (EEMD) method reveal that the summer DUR has an accumulated increase of about 17 days (4.5 days decade-1), which is primarily induced by the phase advance of the summer ONS by about 16 days (4.2 days decade-1). Spatial features of the duration and timing indices demonstrate that the lengthening of summer DUR and the phase advance of summer ONS have significantly enhanced in the shallow regions, due to the limited thermal inertia and the shorter period of the ocean’s memory. In contrast, the secular trend of winter DUR exhibits an accumulated shortening of about 18 days (4.8 days decade-1), which is induced by a moderately delayed winter ONS of 6 days (1.6 days decade-1) and a significantly advanced winter WIT of 12 days (3.2 days decade-1). The potential linkage between the phase variations in the oceanic seasonal cycle and those of the atmospheric forcing was investigated by analyzing both the interannual variability and the secular trend. Over the analysis period, the secular trend of an earlier summer ONS is related to a total reduction of cloud cover by 30% of its climatological mean and an increase of incoming solar radiation of 10 W m-2 month-1 in the late spring. Thus, our results highlight the influence of cloud cover in addition to wind speed on the temporal variations of season transition timing.

IntroductionNeuroendocrine prostate cancer (NEPC) is an aggressive subtype of prostate cancer with poor prognosis and resistance to hormone therapy, which has limited therapeutic approaches. Therefore, this study aimed to identify a novel treatment for NEPC and provide evidence of its inhibitory effects.MethodsWe performed a high-throughput drug screening and identified fluoxetine, originally an FDA-approved antidepressant, as candidate therapeutic agent for NEPC. We carried out both in vitro and in vivo experiments to demonstrate the inhibitory effects of fluoxetine on NEPC models and its mechanism in detail.ResultsOur results demonstrated that fluoxetine effectively curbed the neuroendocrine differentiation and inhibited cell viability by targeting the AKT pathway. Preclinical test in NEPC mice model (PBCre4: Ptenf/f; Trp53f/f; Rb1f/f) showed that fluoxetine effectively prolonged the overall survival and reduced the risk of tumor distant metastases.DiscussionThis work repurposed fluoxetine for antitumor application, and supported its clinical development for NEPC therapy, which may provide a promising therapeutic strategy.

Background: Chatbots are computer programs, often built upon large artificial intelligence models, that employ dialogue systems to enable online, natural language conversations with users via text, speech, or both. Body image, broadly defined as a combination of thoughts and feelings about one’s physical appearance, has been implicated in many risk behaviors and health problems, especially among adolescents and young adults. Little is known about how chatbots respond to questions about body image. Methods: This study assessed the responses of 14 widely-used chatbots (eight companion and six therapeutic chatbots) to ten body image-related questions developed upon validated instruments. Chatbots’ responses were documented, with qualities systematically assessed by nine pre-determined criteria. Results: The overall quality of the chatbots’ responses was modest (an average score of five out of nine), with substantial variations in the content and quality of responses across chatbots (individual scores ranging from one to eight). Companion and therapeutic chatbots systematically differed in their responses (e.g., focusing on comforting users vs. trying to identify the causes of negative body image and recommending potential remedies). Some therapeutic chatbots recognized potential mental health crises (self-harm) in test users’ messages. Conclusion: Substantial heterogeneities in the responses were present across chatbots and assessment criteria. Adolescents and young adults struggling with body image could be vulnerable to misleading or biased remarks made by chatbots. Still, the technical and supervision challenges to prevent those adverse consequences remain paramount and unsolved.

Non-pharmaceutical interventions for COVID-19 also reduced incidence of respiratory pathogens such as respiratory syncytial virus (RSV). Here, the authors report the resurgence of RSV in Australia following lifting of some of the restrictions and describe reduction in genetic diversity in circulating clades.

The operating temperature of the transmission line in the traction network is affected by geographical and climatic factors, especially the wind speed. To make better use of the thermal stability transmission capacity of the traction power supply system in improving the short-term emergency transmission capacity, the dynamic rating technology is introduced into the traction power supply system. According to the time-varying characteristics of the actual wind speed, a dynamic rating method of the traction network based on wind speed prediction is proposed and constructed. Based on the time series model in predicting the wind speed series along the corridor of the traction network, the temperature curve of each transmission line under different currents is calculated by combining it with the heat balance equation of an IEEE-738 capacity expansion model, thus the relationship between the peak operating temperature and current of each transmission line in the prediction period is obtained. According to the current distribution coefficient, the capacity increase limit of the traction network is determined. The example shows that the proposed dynamic rating method based on wind speed prediction is an effective method to predict the short-term safe capacity increase limit of the traction network, which can increase the comprehensive capacity of the traction network by about 45% in the next six hours, and the capacity increase effect is obvious, which can provide reference and technical support for short-term emergency dispatching of traction power supply dispatching centres.

Introduction: This study systematically reviewed scientific evidence concerning the influence of green space on obesity in China. Methods: Keyword and reference search was conducted in PubMed, Web of Science, Scopus, EBSCO, and CNKI. Predetermined selection criteria included study designs: experimental and observational studies; subjects: people of all ages; exposures: green space (i.e., any open land partly or entirely covered with grass, trees, shrubs, or other vegetation); outcomes: body weight status (e.g., body mass index [BMI], overweight, or obesity); and country: China. Results: Ten studies met the selection criteria and were included in the review. All studies adopted a cross-sectional design. Overall greenness measures were found to be inversely associated with BMI, overweight, and obesity in most included studies. Street greenness, which measures the perceived greenness at the eye level on streets, was found to be inversely associated with BMI and obesity. By contrast, mixed results were observed for the relationship between green space accessibility and weight outcomes. Air quality was found to mediate the relationship between greenness and obesity. The influence of green space on obesity tended to vary by residents’ gender, age, and socioeconomic status. Boys, women, older residents, and those with lower education or household income were more likely to benefit from greenness exposure. Conclusion: The literature on green space exposure in relation to obesity in China remains limited. Longitudinal and quasi-experimental studies are warranted to assess the causal link between green space and obesity. Future measures should better capture the self-perception, quality, and attractiveness of green space. The underlying pathways through which green space affects residents’ weight outcomes should be further elucidated.

COVID-19 control measures have suppressed circulation of other infections including influenza. Here, the authors analyse WHO global influenza sequence and case report data and describe changes in the phylogenetic and geographic distribution of influenza lineages during the COVID-19 pandemic.

Molecular targeted therapy has become an emerging promising strategy in cancer treatment, and screening the agents targeting at cancer cell specific targets is very desirable for cancer treatment. Our previous study firstly found that a secretory peroxidase of class III derived from foxtail millet bran (FMBP) exhibited excellent targeting anti-colorectal cancer (CRC) activity in vivo and in vitro, whereas its underlying target remains unclear. The highlight of present study focuses on the finding that cell surface glucose-regulated protein 78 (csGRP78) abnormally located on CRC is positively correlated with the anti-CRC effects of FMBP, indicating it serves as a potential target of FMBP against CRC. Further, we demonstrated that the combination of FMBP with the nucleotide binding domain (NBD) of csGRP78 interfered with the downstream activation of signal transducer and activator of transcription 3 (STAT3) in CRC cells, thus promoting the intracellular accumulation of reactive oxygen species (ROS) and cell grown inhibition. These phenomena were further confirmed in nude mice tumor model. Collectively, our study highlights csGRP78 acts as an underlying target of FMBP against CRC, uncovering the clinical potential of FMBP as a targeted agent for CRC in the future.

Salt stress is a major abiotic factor that negatively impacts the growth, performance, and secondary metabolite production in pepper (Capsicum annuum L.) plants. Brassinosteroids (BRs) play a crucial role in enhancing plant tolerance to abiotic stress, yet their potential in mitigating salt stress in pepper plants, particularly by promoting sugar and glycine betaine accumulation, remains underexplored. In this study, we investigated the effects of the foliar application of 2,4-epibrassinolide (EBR) on salt-stressed pepper seedlings. Our findings revealed that EBR treatment significantly increased the levels of proline, sugar, and glycine betaine under salt stress compared to untreated controls. Moreover, EBR enhanced the antioxidant defense mechanisms in pepper seedlings by increasing sugar and glycine betaine levels, which contributed to the reduction of reactive oxygen species (ROS) and malondialdehyde (MDA) accumulation. [ABSTRACT FROM AUTHOR]

The development of efficient nonenzymatic catalysts for the electro-oxidation of glucose is vital for glucose biosensors. Herein, we report the preparation of a branch-structured catalyst comprising an amorphous/crystalline heterophase made from AuCu alloy shells and Cu2O cores (Cu2O@a/c-AuCu). The Cu2O@a/c-AuCu catalyst exhibits a good electrocatalytic activity for the electro-oxidation of glucose. The Cu2O@a/c-AuCu-based glucose biosensor shows a high sensitivity (345 μA mM−1 cm−2) and a wide concentration detection range (0.1–10 mM). The glucose detection accuracy of the Cu2O@a/c-AuCu sensor in animal serum was consistent with that of the commercial glucometer. The outcomes of this work offer insights for constructing alloy-based heterophase nanocatalysts for biosensing and biological applications. [ABSTRACT FROM AUTHOR]

Integrating artificial intelligence (AI) technology into student training programs is strategically crucial for developing future professionals with both forward-thinking capabilities and practical skills. This paper uses steel surface defect detection as a case study to propose a simulation-based teaching method grounded in deep learning. The method encompasses the entire process from data preprocessing and model training to validation analysis and innovation optimization with the goal of deepening students' understanding of AI technology and enhancing their ability to apply it to real-world scenarios. We have designed an experimental framework that incorporates the Efficient Multi-Scale Attention (EMA) mechanism into the Backbone network. This approach helps students understand the principles of feature extraction and the core functions of attention mechanisms. Additionally, we introduced a novel architecture—Convolution 3 Dilated Convolution X (C3DX)—into the Neck network. This architecture effectively expands the network's receptive field, improves its ability to capture multi-scale information, and thus enhances defect detection accuracy. Furthermore, the implementation of the Efficient Intersection over Union (EIoU) loss function optimizes the bounding box predictions, further increasing the model's accuracy and robustness. Overall, the teaching design not only ensures that the content remains at the cutting edge of technology but also emphasizes its practicality and operability. This approach enables students to effectively apply theoretical knowledge to real-world engineering projects. [ABSTRACT FROM AUTHOR]

Objectives: To assess the efficacy and safety of preoperative neoadjuvant everolimus in renal angiomyolipomas (AML) patients with or without Tuberous Sclerosis Complex (TSC). Materials and Methods: This multi‐institutional retrospective study enrolled renal AML patients who underwent partial nephrectomy (PN) or total nephrectomy after receiving at least 1 month of pre‐operative everolimus. Imaging evaluations were collected before and after treatment, along with demographic, surgical, and follow‐up information. The primary outcome was tumor volume reduction of ≥25%, with additional outcomes including recurrence, perioperative outcomes, renal function, and safety. Results: From January 2015 to July 2022, 68 renal AML patients were studied—41 with TSC and 27 without. During everolimus treatment, 61.0% (25/41) of TSC patients and 44.4% (12/27) of non‐TSC patients achieved tumor reduction of ≥25%. Additionally, 41.5% (17/41) of TSC patients and 18.5% (5/27) of non‐TSC patients achieved a ≥ 50% reduction. Three TSC patients and 1 non‐TSC patient discontinued treatment due to side‐effects. Most patients (92.7% TSC, 85.2% non‐TSC) underwent PN. After everolimus treatment, the necessary total nephrectomy decreased to 41.2% (7/17) from baseline. Postoperatively, 1 grade 3 and 3 grade 2 complications occurred, with no grade 4 or 5 complications. After a median follow‐up of 24 months, only 1 TSC patient recurred with a diameter >3 cm. Retrospective nature is the major limitation of this study. Conclusion: Everolimus was effective and well‐tolerated in neoadjuvant treatment for renal AML, especially in TSC patients. This neoadjuvant combination strategy of everolimus and PN could effectively controls recurrence and preserves renal function. [ABSTRACT FROM AUTHOR]

This systematic review aims to synthesize scientific evidence on the effects of oral nutritional supplementation (ONS) on health-related outcomes and nutritional biomarkers among children and adolescents with undernutrition. The review protocol was reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. A comprehensive keyword and reference search was conducted in seven electronic bibliographic databases: PubMed, Academic Search Complete, Academic Search Premier, CINAHL, Global Health, Web of Science, and Scopus. We identified 14 peer-reviewed articles reporting results from 13 unique studies (eight randomized controlled trials, four pre-post studies, and one observational study). Study participants were recruited from 14 countries/regions, with ages ranging from 1 to 14 years. Outcomes of interest include health-related outcomes (acute diseases and infections) and nutritional biomarkers (e.g., serum iron and zinc). Six of the eight studies examining acute diseases/infections and five of the seven examining nutritional biomarkers reported statistically significant improvement in some, but not all, outcomes. A meta-analysis of three studies found that ONS interventions reduce the incidence of upper respiratory tract infection (URTI) by 39% (95% CI, 0.42–0.91) in children at nutritional risk when compared to dietary counseling (DC) alone. This systematic review suggests that ONS interventions can improve certain health-related outcomes and nutritional biomarkers in undernourished children and adolescents. Specifically, the use of ONS significantly reduces the risk of URTI, highlighting its potential to enhance immune function and break the cycle of undernutrition and infection. [ABSTRACT FROM AUTHOR]

The precise and automated diagnosis of apple leaf diseases is essential for maximizing apple yield and advancing agricultural development. Despite the widespread utilization of deep learning techniques, several challenges persist: (1) the presence of small disease spots on apple leaves poses difficulties for models to capture intricate features; (2) the high similarity among different types of apple leaf diseases complicates their differentiation; and (3) images with complex backgrounds often exhibit low contrast, thereby reducing classification accuracy. To tackle these challenges, we propose a three-residual fusion network known as MSCR-FuResNet (Fusion of Multi-scale Feature Extraction and Enhancements of Channels and Residual Blocks Net), which consists of three sub-networks: (1) enhancing detailed feature extraction through multi-scale feature extraction; (2) improving the discrimination of similar features by suppressing insignificant channels and pixels; and (3) increasing low-contrast feature extraction by modifying the activation function and residual blocks. The model was validated with a comprehensive dataset from public repositories, including Plant Village and Baidu Flying Paddle. Various data augmentation techniques were employed to address class imbalance. Experimental results demonstrate that the proposed model outperforms ResNet-50 with an accuracy of 97.27% on the constructed dataset, indicating significant advancements in apple leaf disease recognition. [ABSTRACT FROM AUTHOR]