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Background This study aimed to characterize the risk signals and clinical features of pembrolizumab-associated neutropenia reported as serious adverse events (SAEs) in the US FDA Adverse Event Reporting System (FAERS), and the association between concomitant chemotherapy and time-to-onset. Methods In this retrospective pharmacovigilance study, SAE reports from FAERS (2021Q1–2024Q2) with pembrolizumab designated as the primary suspect drug were analyzed. Among 14,747 pembrolizumab-associated SAE reports, 856 with the Preferred Term “neutropenia” were identified and characterized. Clinical characteristics were summarized, and subgroup analyses explored associations between concomitant chemotherapy and TTO, as well as between sex and the reporting odds ratio (ROR). A supplementary analysis of febrile neutropenia (FN) cases was conducted to assess clinical severity. Results Among 14,747 SAEs, 856 were neutropenia cases, for which a strong signal of disproportional reporting was detected (ROR = 5.23, 95% CI: 4.88–5.60). Median patient age was 61.0 years, and the reported mortality rate was 19.4%. A higher ROR was observed in females (7.06) than males (4.42), a difference likely influenced by the underlying distribution of cancer types and the 9.8% missing data for sex, rather than indicating an intrinsic sex-related risk. The overall median TTO was 19.0 days, with the concomitant chemotherapy group (N = 268) showing a shorter median TTO (14.5 days) than the non-chemotherapy group (N = 55, 39.0 days; p = 0.0006). Among 311 FN cases, 86.5% (269/311) occurred in the concomitant chemotherapy group. Conclusion Pembrolizumab-associated neutropenia represents a notable safety signal in FAERS. The observed early-onset pattern, particularly in the context of concomitant chemotherapy, provides real-world evidence characterizing the clinical features of this adverse event.

Clothing CAD technology is a bridge that combines clothing design and high technology, and is one of the important fields of computer science and technology in the art kingdom. The style-based intelligent clothing style structure design system studied in this paper is mainly for users or design lovers who are not major in clothing design, so that they can realize the intelligent design of a certain style and style series in the friendly human-computer interaction, thereby replacing the Traditional designer hand creation process. This paper presents the system architecture, designs and completes the interactive interface, analyzes and implements the automatic splicing and adjustment functions of style components provided by the system, and explores and implements style-based style retrieval. Through the overall analysis of the intelligent clothing style structure design system, this paper develops a very good clothing design interface with VC. The author innovatively proposes the idea of “primitive structure” and “function simulation”, and realizes the process of using computer to draw clothing accessories, so that the generated accessories can be accurately fitted along the given curve during clothing design, and provides the interface parameters make clothing accessories adjustable and controllable, which better realizes intelligence and facilitates the use of the client.

In the era of experience economy, consumers no longer pursue simple material life, but pursue higher levels of satisfaction. They begin to pay more attention to sensory and spiritual enjoyment, and the requirements for products are not only common basic functions. Major clothing enterprises and brands have started the service of personalized clothing customization, and the market for personalized clothing customization has become competitive. In this context, how to create a personalized clothing customization platform that can bring good user experience to consumers from the perspective of consumers is of great significance to those clothing enterprises that cannot play an advantage in products and those who want to gain long-term competitive advantage on the basis of having good products. Based on the needs of consumers, through the core content of interactive design, and through a detailed survey of the clothing personalized customization platform, this paper draws the feasibility and advantages of interactive design applied to clothing personalized customization.

Based on the Expectation Confirmation Model (ECM), this study explores the impact of perceived educational and emotional support on university students’ continuance intention to engage in e-learning. Researchers conducted a survey using structured questionnaires among 368 university students from three universities in Jiangxi Province. They measured their self-reported responses on six constructs: perceived educational support, perceived emotional support, perceived usefulness, confirmation, satisfaction, and continuance intention. The relationships between predictors and continuance intention, characterized by non-compensatory and non-linear dynamics, were analyzed using Structural Equation Modeling combined with Artificial Neural Networks. Apart from the direct effects of perceived educational and emotional support on perceived usefulness being non-significant, all other hypotheses were confirmed. Furthermore, according to the normalized importance derived from the multilayer perceptron analysis, satisfaction was identified as the most critical predictor (100%), followed by confirmation (29.9%), perceived usefulness (28.3%), perceived educational support (22.6%), and perceived emotional support (21.6%). These constructs explained 62.1% of the total variance in the students’ continuance intention to engage in e-learning. This study utilized a two-stage analytical approach, enhancing the depth and accuracy of data processing and expanding the methodological scope of research in educational technology. The findings of this study contribute to the United Nations’ Sustainable Development Goal 4, which aims to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all by 2030. It provides direction for future research in different environmental and cultural contexts.

Several epidemiological studies have examined the risk of asthma and respiratory diseases in association with long-term exposure to outdoor air pollution. However, little is known regarding the adverse effects of long-term exposure to outdoor air pollution on the development of these outcomes in low- and middle-income countries (LMICs). Our study aims to investigate the association between long-term exposure to outdoor air pollution and asthma and respiratory diseases in LMICs through a systematic review with meta-analysis. This systematic review and meta-analysis will follow the PRISMA (Preferred Reporting for Systematic Reviews and Meta-Analyses) checklist and flowchart guidelines. The inclusion criteria that will be used in our study are 1) Original research articles with full text in English; 2) Studies including adult humans; 3) Studies with long-term air pollution assessment in LMICs, air pollutants including nitrogen oxide (NO2), sulfur oxide (SO2), particulate matter (PM2.5 and PM10), carbon monoxide (CO) and ozone (O3); 4) cohort and cross-sectional studies; 5) Studies reporting associations between air pollution and asthma and respiratory symptoms. A comprehensive search strategy will be used to identify studies published up till August 2022 and indexed in Embase, Medline, and Web of Science. Three reviewers will independently screen records retrieved from the database searches. Where there are enough studies with similar exposure and outcomes, we will calculate, and report pooled effect estimates using meta-analysis. PROSPERO CRD42022311326. Findings from the health effects of long-term exposure to outdoor air pollution may be of importance for policymakers. This review will also identify any gaps in the current literature on this topic in LMICs and provide direction for future research.

Background The false-negative rate of approximately 18% in fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) can lead to understaging by misclassifying M1b disease as M1a of nasopharyngeal carcinoma (NPC), which may result in the inappropriate administration of intensified therapy. This study aims to develop a 18 F-FDG PET/CT-based prediction tool to assist clinicians in diagnosing TNM-9 M1 staging and guiding treatment decisions for patients with synchronous NPC (smNPC). Methods Ninety-seven patients with squamous cell carcinoma smNPC underwent pretreatment 18 F-FDG PET/C. Radiomic features were extracted from primary tumors and all metastatic lymph nodes using CT and PET data. Ten metabolic parameters of the primary tumors and most FDG-avid metastatic lymph node, measured through three methods, were also assessed. After feature selection, nine logistic regression-based radiomics models and one random forest model were developed. Model Performance was evaluated via 10 repeats×5-fold cross-validation mean the Area Under the Receiver Operating Characteristic Curve (AUC). The optimal prediction model was presented using a nomogram developed on the entire cohort and was validated with a calibration curve, decision curve analysis (DCA), and by determining its optimal cut-off value. Results The M1a and M1b patient groups showed no significant differences in baseline characteristics or metabolic parameters from the primary tumors and metastatic lymph nodes ( p  > 0.05). The combined primary tumors and metastatic lymph nodes radiomics model achieved the highest AUC of 0.907 in validation set. The final nomogram demonstrated excellent discrimination (AUC 0.963), with sensitivity of 98.1% and specificity of 86.0% at the optimal cutoff (0.439). Calibration was reliable (slope 0.853, intercept 0.132). DCA confirmed clinical utility, providing net benefit across a wide threshold range (0.135–0.700) with a maximum net benefit of 0.533 at a threshold probability of 0.050. Conclusion This study offers a complementary diagnostic tool for M1 staging of smNPC that may inform treatment decisions. The findings also provide metabolic evidence supporting the robustness of the TNM-9 stage IV classification system of NPC. Trial registration This retrospective study was in accordance with the Declaration of Helsinki and approved by the XXX.

Background Little evidence exists regarding the prevalence of pathogens in bloodstream infections (BSIs), the mortality risk, and the benefit of combination therapy over monotherapy. This study aims to describe patterns of empiric antimicrobial therapy, and the epidemiology of Gram-negative pathogens, and to investigate the effect of appropriate therapy and appropriate combination therapy on the mortality of patients with BSIs. Methods This was a retrospective cohort study including all patients with BSIs of Gram-negative pathogens from January 2017 to December 2022 in a Chinese general hospital. The in-hospital mortality was compared between appropriate and inappropriate therapy, and between monotherapy and combination therapy for patients receiving appropriate therapy. We used Cox regression analysis to identify factors independently associated with in-hospital mortality. Results We included 205 patients in the study, of whom 147 (71.71%) patients received appropriate therapy compared with 58 (28.29%) who received inappropriate therapy. The most common Gram-negative pathogen was Escherichia coli (37.56%). 131 (63.90%) patients received monotherapy and 74 (36.10%) patients received combination therapy. The in-hospital mortality was significantly lower in patients administered appropriate therapy than inappropriate therapy (16.33% vs. 48.28%, p = 0.004); adjusted hazard ratio [HR] 0.55 [95% CI 0.35–0.84], p = 0.006). In-hospital mortality was also not different in combination therapy and monotherapy in the multivariate Cox regression analyses (adjusted HR 0.42 [95% CI 0.15–1.17], p = 0.096). However, combination therapy was associated with lower mortality than monotherapy in patients with sepsis or septic shock (adjusted HR 0.94 [95% CI 0.86–1.02], p = 0.047). Conclusions Appropriate therapy was associated with a protective effect on mortality among patients with BSIs due to Gram-negative pathogens. Combination therapy was associated with improved survival in patients with sepsis or septic shock. Clinicians need to choose optical empirical antimicrobials to improve survival outcomes in patients with BSIs.

Polyacrylamide (PAM) in environmental water has become a major problem in water pollution management due to its high molecular mass, high viscosity and non-absorption by soil. CoFe2O4 with strong magnetic properties was prepared by solvent-thermal synthesis method and used as the catalyst for the removal on PAM in heterogeneous Electro-Fenton (EF) system. It showed that the removal efficiency of PAM by the heterogeneous EF system using CoFe2O4 catalyst was 92.01% at pH 3 after 120 min. Further studies indicated that ·OH was the most significant active species for the removal of PAM, and the contribution of ·O2− and SO4·− for the removal of PAM was less than 15%. The reusability test and XRD, XPS, FTIR analyses proved that the catalyst had good stability. After a repeated use for five times, the catalyst still had a high PAM removal rate and stable structure. The valence distribution and functional groups of the phase components of the catalyst did not change significantly before and after the reaction. The possible mechanism of catalyst activation of H2O2 was deduced by mechanism investigation. The CoFe2O4 is an efficient and promising catalyst for the removal of PAM wastewater.

Ischemic stroke is a severe cerebrovascular disease with high mortality and morbidity. In recent years, reperfusion treatments based on thrombolytic and thrombectomy are major managements for ischemic stroke patients, and the recanalization time window has been extended to over 24 h. However, with the extension of the time window, the risk of ischemia/reperfusion (I/R) injury following reperfusion therapy becomes a big challenge for patient outcomes. I/R injury leads to neuronal death due to the imbalance in metabolic supply and demand, which is usually related to mitochondrial dysfunction. Mitophagy is a type of selective autophagy referring to the process of specific autophagic elimination of damaged or dysfunctional mitochondria to prevent the generation of excessive reactive oxygen species (ROS) and the subsequent cell death. Recent advances have implicated the protective role of mitophagy in cerebral ischemia is mainly associated with its neuroprotective effects in I/R injury. This review discusses the involvement of mitochondria dynamics and mitophagy in the pathophysiology of ischemic stroke and I/R injury in particular, focusing on the therapeutic potential of mitophagy regulation and the possibility of using mitophagy-related interventions as an adjunctive approach for neuroprotective time window extension after ischemic stroke.

With the advancement of remote sensing technology, high-resolution images are widely used in the field of computer vision. However, image quality is often degraded due to hardware limitations and environmental interference. This paper proposes a Residual Separable Super-Resolution Reconstruction Generative Adversarial Network (RSSRGAN) for remote sensing image super-resolution. The model aims to enhance the resolution and edge information of low-resolution images without hardware improvements. The main contributions include (1) designing an optimized generator network by improving the residual dense network and introducing depthwise separable convolutions to remove BN layers, thereby increasing training efficiency—two PatchGAN discriminators are designed to enhance multi-scale detail capture—and (2) introducing content loss and joint perceptual loss on top of adversarial loss to improve global feature representation. Experimental results show that compared to the widely used SRGAN model in remote sensing (exemplified by the satellite-specific SRGAN in this study), this model improves PSNR by approximately 18.8%, SSIM by 8.0%, reduces MSE by 3.6%, and enhances the PI metric by 13.6%. It effectively enhances object information, color, and brightness in images, making it more suitable for remote sensing image super-resolution.