Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

Objective To investigate the effect of the structure of 3D-printed silk fibroin/hydroxypropyl methylcellulose(SF/HPMC)scaffolds on the growth of tracheal epithelial cells in vitro.Methods Six types of SF/HPMC scaffolds with different surface topography,pore size,and porosity were fabricated using a 3D printer by adjusting the concentration of SF/HPMC solutions and printing parameters,combined with freeze-drying.Normal human bronchial epithelial cell lines BEAS-2B were cultured on these scaffolds for 7 days.The cell proliferation was detected by CCK-8 assay and live/dead cell staining,and the cell morphology was observed by scanning electron microscopy(SEM).Results The porosity of 20%(weight percentage)SF/HPMC scaffolds with rough surface and smooth surface were 70.5%±2.0%and 65.5%±6.1%,respectively,and the porosity of 30%(weight percentage)SF/HPMC scaffolds with rough surface and smooth surface were 63.9%±2.1%and 59.6%±2.1%,respectively.The two pore sizes of the rough-surfaced 20%SF/HPMC scaffolds were(443.9±104.1)μm and(681.1±115.1)μm.BEAS-2B cells spread better on the rough-surfaced scaffolds,and their proliferation was higher on scaffolds with higher porosity and smaller pore sizes compared to those with lower porosity and larger pore sizes.Conclusion The 3D-printed SF/HPMC scaffolds are suitable for bronchial epithelial cell growth.Scaffolds with rough surfaces,higher porosity,and appropriate pore sizes might facilitate BEAS-2B cell growth.

Objective To construct a medical consumables selection indicator system based on analytic hierarchy process(AHP)and fuzzy cluster method.Methods Firstly,a medical consumables selection indicator system was established preliminarily with the literature research results and actual situation of hospital consumables management;secondly,13 experts in related fields were selected to execute two rounds of online questionnaires,the expert weights were determined with AHP,the importance of each selection indicator was scored by the expert evaluation method and fuzzy cluster method,and consistency analysis was carried out on the two rounds of expert evaluation results;finally,the final medical consumables selection indicator system was built with the 100-point scale.Results The constructed medical consumables selection indicator system was composed of 5 primary indicators,12 secondary indicators and 38 tertiary indicators.The primary indicators included consumables quality,clinical demand,cost-effectiveness,supply capacity and after-sales service,with the percentage-based scores being 27,25,14,26 and 8,respectively.Conclusion The medical consumables selection indicator system based on AHP and fuzzy cluster method with high reliability provides effective and reliable references for medical institutions to select medical consumables.

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.

Aim To explore the therapeutic effect and mechanism of Qingjie Huagong decoction in modulating PI3K/AKT/NF-κB signaling pathway in inflammatory response of acute pancreatitis(AP)mice.Methods Twenty-four mice were randomly divided into Blank group,Model group,Ustekin group,and Qingjie Hua-gong decoction group,with six mice in each group.The AP model was prepared by using rain frogin.Serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α lev-els were detected by ELISA;the pancreatic pathology was detected by HE staining;the expressions of PI3K,AKT,and NF-κB-related proteins and mRNAs were de-tected by immunohistochemistry,Western blot,and RT-qPCR.Results Compared with the blank group,the model group showed obvious pathological damage to the pancreas,with significantly higher serum α-AMS,PN-LP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels(P＜0.01),and significantly higher levels of PI3K,AKT,and NF-κB-related proteins and mRNA expression(P＜0.01).Compared with the model group,both the Qingjie Huagong decoction group and the ustekin group improved the histopathological changes in the pancreas of AP mice,decreased the serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels,and down-reg-ulated the expression levels of pancreatic PI3K,AKT,NF-κB-related proteins and mRNA(P＜0.05 or P＜0.01).Conclusion Qingjie Huagong decoction may inhibit the inflammatory response and protect pancreat-ic tissues by regulating the expression of PI3K/AKT/NF-κB signaling pathway.

Objective To construct a medical consumables selection indicator system based on analytic hierarchy process(AHP)and fuzzy cluster method.Methods Firstly,a medical consumables selection indicator system was established preliminarily with the literature research results and actual situation of hospital consumables management;secondly,13 experts in related fields were selected to execute two rounds of online questionnaires,the expert weights were determined with AHP,the importance of each selection indicator was scored by the expert evaluation method and fuzzy cluster method,and consistency analysis was carried out on the two rounds of expert evaluation results;finally,the final medical consumables selection indicator system was built with the 100-point scale.Results The constructed medical consumables selection indicator system was composed of 5 primary indicators,12 secondary indicators and 38 tertiary indicators.The primary indicators included consumables quality,clinical demand,cost-effectiveness,supply capacity and after-sales service,with the percentage-based scores being 27,25,14,26 and 8,respectively.Conclusion The medical consumables selection indicator system based on AHP and fuzzy cluster method with high reliability provides effective and reliable references for medical institutions to select medical consumables.

Aim To explore the therapeutic effect and mechanism of Qingjie Huagong decoction in modulating PI3K/AKT/NF-κB signaling pathway in inflammatory response of acute pancreatitis(AP)mice.Methods Twenty-four mice were randomly divided into Blank group,Model group,Ustekin group,and Qingjie Hua-gong decoction group,with six mice in each group.The AP model was prepared by using rain frogin.Serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α lev-els were detected by ELISA;the pancreatic pathology was detected by HE staining;the expressions of PI3K,AKT,and NF-κB-related proteins and mRNAs were de-tected by immunohistochemistry,Western blot,and RT-qPCR.Results Compared with the blank group,the model group showed obvious pathological damage to the pancreas,with significantly higher serum α-AMS,PN-LP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels(P＜0.01),and significantly higher levels of PI3K,AKT,and NF-κB-related proteins and mRNA expression(P＜0.01).Compared with the model group,both the Qingjie Huagong decoction group and the ustekin group improved the histopathological changes in the pancreas of AP mice,decreased the serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels,and down-reg-ulated the expression levels of pancreatic PI3K,AKT,NF-κB-related proteins and mRNA(P＜0.05 or P＜0.01).Conclusion Qingjie Huagong decoction may inhibit the inflammatory response and protect pancreat-ic tissues by regulating the expression of PI3K/AKT/NF-κB signaling pathway.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

OBJECTIVES: To investigate the clinical sub-phenotype (SP) of pediatric acute kidney injury (AKI) and their association with clinical outcomes. METHODS: General status and initial values of laboratory markers within 24 hours after admission to the pediatric intensive care unit (PICU) were recorded for children with AKI in the derivation cohort (n=650) and the validation cohort (n=177). In the derivation cohort, a least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify death-related indicators, and a two-step cluster analysis was employed to obtain the clinical SP of AKI. A logistic regression analysis was used to develop a parsimonious classifier model with simplified metrics, and the area under the curve (AUC) was used to assess the value of this model. This model was then applied to the validation cohort and the combined derivation and validation cohort. The association between SPs and clinical outcomes was analyzed with all children with AKI as subjects. RESULTS: In the derivation cohort, two clinical SPs of AKI (SP1 and SP2) were identified by the two-step cluster analysis using the 20 variables screened by LASSO regression, namely SP_d1 group (n=536) and SP_d2 group (n=114). The simplified classifier model containing eight variables (P<0.05) had an AUC of 0.965 in identifying the two clinical SPs of AKI (P<0.001). The validation cohort was clustered into SP_v1 group (n=156) and SP_v2 group (n=21), and the combined derivation and validation cohort was clustered into SP1 group (n=694) and SP2 group (n=133). After adjustment for confounding factors, compared with the SP1 group, the SP2 group had significantly higher incidence rates of multiple organ dysfunction syndrome and death during the PICU stay (P<0.001), and SP2 was significantly associated with the risk of death within 28 days after admission to the PICU (P<0.001). CONCLUSIONS This study establishes a parsimonious classifier model and identifies two clinical SPs of AKI with different clinical features and outcomes.The SP2 group has more severe disease and worse clinical prognosis.
Humans ; Acute Kidney Injury/diagnosis* ; Prognosis ; Male ; Female ; Child ; Child, Preschool ; Phenotype ; Infant ; Logistic Models ; Adolescent