Widespread utilization of glyphosate has led to environmental residues,posing potential threats to ecological systems and human health.Traditional methods for detection of glyphosate are limited by specialized equipment and operational techniques,resulting in inefficient responses.Therefore,it is urgent to develop a convenient,sensitive and accurate detection method for detection of glyphosate.Herein,a new naphthalenesulfonamide-based"Turn-on"fluorescent probe was synthesized using 2-chloroaniline and dansyl chloride as raw materials through a one-step process,which showed a good linear relationship between the glyphosate concentration in concentration range of 0.003-70 μmol/L and the fluorescence intensity(R2=0.995),with a detection limit of 2.73 nmol/L(S/N=3).Analytical techniques such as nuclear magnetic resonance(NMR)spectroscopy and high-resolution mass spectrometry(HRMS)were used to investigate the interaction mechanism between the fluorescent probe and glyphosate.The results indicated that a nucleophilic substitution reaction occurred between the probe and the secondary amine(—NH—)of glyphosate,inducing a photoinduced electron transfer(PET)effect which enhanced the fluorescence intensity by 11.2 times.The probe showed good anti-interference ability towards coexisting metal ions,anions and pesticides in water.When applied to determination of glyphosate in the samples such as tap water,river water(Xiangxi River Reservoir),soil,soybeans,and corn,the spiking recoveries ranged from 94.7％to 109.9％,demonstrating the high accuracy and broad applicability of this detection method.A portable test strip based on this fluorescent probe was developed for rapid semi-quantitative analysis of glyphosate.The developed method was rapid,sensitive,and portable,providing theoretical and technical support for on-site measurement of environmental contaminants.

A nodule in the right middle lobe of the lung was treated by a combination of cone-beam CT,three-dimensional registration for fusion imaging,and electromagnetic navigation bronchoscopy-guided thermal ablation.The procedure lasted for 90 min,with no significant bleeding observed under the bronchoscope.The total radiation dose during the operation was 384 mGy.The patient recovered well postoperatively,with only a small amount of blood in the sputum and no pneumothorax or other complications.A follow-up chest CT on the first day post operation showed that the ablation area completely covered the lesion,and the patient was discharged successfully.
Humans ; Bronchoscopy/methods* ; Catheter Ablation/methods* ; Cone-Beam Computed Tomography ; Electromagnetic Phenomena ; Imaging, Three-Dimensional ; Lung Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed

Copy number alteration (CNA) is a significant genetic change in pediatric B-cell acute lymphoblastic leukemia (B-ALL), with CDKN2A/B deletions, PAX5 deletions, and IKZF1 deletions being the most common. Recent studies have increasingly highlighted the potential prognostic significance of these gene deletions and multiple co-deletions in pediatric B-ALL. This paper reviews the main detection methods for CNA, as well as the prognostic characteristics and treatment approaches for common CNA in pediatric B-ALL.
Humans ; DNA Copy Number Variations ; Child ; PAX5 Transcription Factor/genetics* ; Precursor B-Cell Lymphoblastic Leukemia-Lymphoma/genetics* ; Cyclin-Dependent Kinase Inhibitor p15/genetics* ; Ikaros Transcription Factor/genetics* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/genetics* ; Gene Deletion ; Cyclin-Dependent Kinase Inhibitor p16/genetics* ; Prognosis

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

Objective To investigate the clinical characteristics of women with abnormal uterine bleeding(AUB)in sub-plateau regions and analyze the factors affecting their treatment methods.Methods AUB patients who were hospitalized from Jan 1,2018 to Dec 31,2022,in a sub-plateau region(Yongping County People's Hospital of Yunnan Province)with an average altitude of 1 620 meters were selected.The general clinical characteristics of the patients were summarized,and patients were classified into two categories(with or without uterine structural lesion)and nine subtypes(PALM-COEIN)according to the FIGO recommended etiological classification guidelines.Then the patients were divided into groups based on the presence or absence of uterine structural lesions,ethnic group(Han and minority),conservative drug treatment and surgical treatment groups,blood transfusion and non-blood transfusion groups.Binary Logistic regression analysis was used to identify factors affecting treatment methods.Results A total of 481 AUB patients enrolled,and the delayed consultation rate was as high as 80.46%,and the proportion of overweight and obese patients was 49.90%,which was higher than the average level among Chinese women.The main cause was AUB-O(AUB-ovulatory dysfunction),accounting for 78.59%of cases,the proportion of patients with delayed medical treatment was higher than those without delayed medical treatment(82.17%vs.74.47%).Patients who received blood transfusion were significantly younger,had lower hemoglobin(HGB)levels,fewer pregnancies,and lower BMI compared to those in the non-blood transfusion group(P<0.05).Univariate analysis showed that the surgical treatment group had older age,longer onset time,higher HGB levels,more pregnancies and deliveries,higher BMI,a higher proportion of Han ethnicity patients,lower rates of non-blood transfusion,higher rates of hypertension,and more uterine structural lesions compared to the conservative drug treatment group.Multivariate regression analysis revealed that blood transfusion treatment reduced the probability of surgical treatment.Age and uterine structural lesions were risk factors for requiring surgical treatment,for each additional year of age,the risk of undergoing surgical treatment increased by 10%.The risk of requiring surgical treatment for patients with uterine structural lesions was 2.987 times higher than for those without.Conclusion AUB patients in this sub-plateau regions have a high rate of delayed consultation and a high proportion of overweight and obesity,with AUB-O being the primary cause.Older age and the presence of uterine structural lesions were risk factors for requiring surgical treatment.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

The minor purchasing process and mode of some hospital were introduced,and the implementation of the hospital's minor purchasing projects in the past year was analyzed.The causes for high failure rate of purchasing were pointed out including long interval between project creation and procurement,unreasonable demand presentation,insufficient demand demonstration and lack of active participation of suppliers.Some suggestions were put forward such as timely adjustment of demands,strengthening of demand demonstration,improvement of supplier motivation and enhancement of procurement process management,which were of great significance for increasing the success rate of minor purchasing of the hospital.[Chinese Medical Equipment Journal,2025,46(8):91-95]

Objective To evaluate the performance of an improved DeepSurv model for survival analysis in lung cancer patients,and investigate key factors affecting the prognosis of lung cancer.Methods The lung cancer data from the SEER database(2018-2021)was used in the study,and the DeepSurv model was optimized by incorporating a self-attention mechanism,a residual network,a LIME module and an entropy regularization term to enhance prediction accuracy and interpretability.Model performance was assessed using C-index and Brier score,and the improved model was utilized to evaluate the effects of various features on the prognosis of lung cancer.Results The improved DeepSurv model achieved a C-index of 0.852 and a Brier score of 0.139.Feature importance analysis identified age as the primary determinant of the survival of lung cancer patients.Conclusion The improved DeepSurv model outperforms both the Cox proportional hazards model and the original DeepSurv model in terms of accuracy,robustness and interpretability,offering a novel methodology for personalized medicine and survival analysis.

A converged network based on deep learning is proposed to realize the efficient and accurate diagnosis of diabetic retinopathy.Both data augmentation technology and generative adversarial network are used to augment the fundus images in EyePACS dataset for effectively addressing the problem of uneven classification of fundus images.The proposed model uses Inception-Resnet-V2 as the main network,and incorporates deep residual shrinkage network and pyramid split attention module for effectively filtering out the irrelevant information in the feature learning process and focusing on the lesion information,thereby improving the network's ability to capture important features.Experimental results show that the optimized model achieves accuracy,recall,specificity,sensitivity,and F1 score of 0.951,0.950,0.990,0.950,and 0.950,respectively,without the need to specify lesion characteristics in advance,demonstrating its superiority in evaluation indicators.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.