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.

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.

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.

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 plasma protein expression changes in heatstroke patients using proteomics technology and to identify reliable prognostic biomarkers.Methods A retrospective analysis was conducted on 20 heatstroke patients hospitalized at the 908th Hospital of the Chinese PLA Joint Logistics Support Force from July 2022 to February 2024.Patients were divided into survival(n=16)and death groups(n=4)based on 28-day outcomes.Fasting venous blood samples were collected from both groups for proteomic analysis.Liquid chromatography-mass spectrometry(LC-MS/MS)was used to identify and screen differentially expressed proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)enrichment analyses were performed.LASSO regression was applied to screen key prognostic biomarkers,and receiver operating characteristic(ROC)curve analysis was used to evaluate their predictive value.Results A total of 27 upregulated and 90 downregulated proteins were identified between the two groups.These proteins were primarily involved in biological processes such as immune responses,complement activation,and metabolic processes.LASSO regression analysis indicated that actin-related protein 2(ARP2),cysteine-rich scavenger receptor type 1 M130(CD163),and catalase(CAT)could serve as effective biomarkers for evaluating heatstroke prognosis.ROC curve analysis demonstrated that ARP2 had higher diagnostic efficacy(AUC=0.98,sensitivity=0.80,specificity=1.00)compared to CD163(AUC=0.94,sensitivity=0.76,specificity=1.00),CAT(AUC=0.96,sensitivity=0.67,specificity=1.00),and acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(AUC=0.79,sensitivity=0.44,specificity=1.00).Conclusion Elevated plasma ARP2 level has good clinical value for predicting poor prognosis in heatstroke patients.

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

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 investigate the distribution and antimicrobial resistance of bacterial isolates from blood samples in the hospitals participating in China Antimicrobial Surveillance Network (CHINET) from 2015 to 2021.Methods Bacterial strains isolated from blood samples were collected from 52 medical centers participating in CHINET from 2015 to 2021 for analysis of bacetrial distribution and antimicrobial resistance.Results A total of 153591 isolates were collected,48.8％ of which were gram-positive bacteria and 51.2％ were gram-negative bacteria.The top five bacterial strains were coagulase negative Staphylococcus (28.2％),Escherichia coli (20.7％),Klebsiella (13.7％),Enterococcus (7.2％),and Staphylococcus aureus (6.6％).Compard to female patients,male patients showed lower proportion of E.coli and higher proportions of other bacterial species in all the bacterial isolaets from blood samples.The proportions of Streptococcus pneumoniae and Salmonella in all the bacterial isolaets from blood samples were higher in children compared to adults.Enterobacterales species showed various resistance rates to antimicrobial agents.Overall,≥58.0％,≥36.8％ and ≥56.8％ of E.coli strains were resistant to cefotaxime,gentamicin and levofloxacin respectively over the 7-year period.However,less than 2.5％ of the E.coli strains were resistant to carbapenems.K.pneumoniae showed higher resistance rates to imipenem and meropenem than other Enterobacterales species.During the 7-year period,the prevalence of imipenem-resistant and meropenem-resistant K.pneumoniae increased from 21.4％ and 19.9％ in 2015 to 25.7％ and 26.6％ in 2021,respectively.However,carbapenems still maintained good antibacterial activity against other Enterobacterales,associaetd with lower resistance rates.In the 7-year period,Acinetobacter baumannii showed a dwonward trend in the resistance rates to imipenem and meropenem,but remained 72.9％ and 73.2％ respectively in 2021.The prevalence of imipenem-resistant and meropenem-resistant P.aeruginosa decreased from 26.7％ and 22.9％ in 2015 to 18.5％ and 14.7％ in 2021,respectively.The prevalence of PRSP was 1.5％ in the isolaets from adults and and 0.8％ in the isolates from children.Less than 3.0％ of the Enterococcus faecium and Enterococcus faecalis strains were resistant to vancomycin,teicolanin,or linezolid.The prevalence of methicillin-resistant S.aureus (MRSA) and coagulase negative Staphylococcus (MRCNS) was 32.1％ and 81.0％,respectively.The prevalence of MRSA was relatively stable,28.5％ in 2015 and 28.0％ in 2021.Conclusions Coagulase negative Staphylococcus,E.coli and K.pneumoniae were the main bacterial species isolated from blood samples in the hospitals participaing in the CHINET from 2015 to 2021.Significant sex and age differences were found in the distribution of bcterial isolates from blood samples.The overall resistance rates of the top bacetrial strains from blood samples to antimicrobial agents showed a downward trend.Ongoing surveillance of antimicrobial resistance for the isolates from blood samples is still essential for prescribing rational antimicrobial therapies and curbing bacterial resistance.

Objective To investigate the distribution and antimicrobial resistance of bacterial isolates from blood samples in the hospitals participating in China Antimicrobial Surveillance Network (CHINET) from 2015 to 2021.Methods Bacterial strains isolated from blood samples were collected from 52 medical centers participating in CHINET from 2015 to 2021 for analysis of bacetrial distribution and antimicrobial resistance.Results A total of 153591 isolates were collected,48.8％ of which were gram-positive bacteria and 51.2％ were gram-negative bacteria.The top five bacterial strains were coagulase negative Staphylococcus (28.2％),Escherichia coli (20.7％),Klebsiella (13.7％),Enterococcus (7.2％),and Staphylococcus aureus (6.6％).Compard to female patients,male patients showed lower proportion of E.coli and higher proportions of other bacterial species in all the bacterial isolaets from blood samples.The proportions of Streptococcus pneumoniae and Salmonella in all the bacterial isolaets from blood samples were higher in children compared to adults.Enterobacterales species showed various resistance rates to antimicrobial agents.Overall,≥58.0％,≥36.8％ and ≥56.8％ of E.coli strains were resistant to cefotaxime,gentamicin and levofloxacin respectively over the 7-year period.However,less than 2.5％ of the E.coli strains were resistant to carbapenems.K.pneumoniae showed higher resistance rates to imipenem and meropenem than other Enterobacterales species.During the 7-year period,the prevalence of imipenem-resistant and meropenem-resistant K.pneumoniae increased from 21.4％ and 19.9％ in 2015 to 25.7％ and 26.6％ in 2021,respectively.However,carbapenems still maintained good antibacterial activity against other Enterobacterales,associaetd with lower resistance rates.In the 7-year period,Acinetobacter baumannii showed a dwonward trend in the resistance rates to imipenem and meropenem,but remained 72.9％ and 73.2％ respectively in 2021.The prevalence of imipenem-resistant and meropenem-resistant P.aeruginosa decreased from 26.7％ and 22.9％ in 2015 to 18.5％ and 14.7％ in 2021,respectively.The prevalence of PRSP was 1.5％ in the isolaets from adults and and 0.8％ in the isolates from children.Less than 3.0％ of the Enterococcus faecium and Enterococcus faecalis strains were resistant to vancomycin,teicolanin,or linezolid.The prevalence of methicillin-resistant S.aureus (MRSA) and coagulase negative Staphylococcus (MRCNS) was 32.1％ and 81.0％,respectively.The prevalence of MRSA was relatively stable,28.5％ in 2015 and 28.0％ in 2021.Conclusions Coagulase negative Staphylococcus,E.coli and K.pneumoniae were the main bacterial species isolated from blood samples in the hospitals participaing in the CHINET from 2015 to 2021.Significant sex and age differences were found in the distribution of bcterial isolates from blood samples.The overall resistance rates of the top bacetrial strains from blood samples to antimicrobial agents showed a downward trend.Ongoing surveillance of antimicrobial resistance for the isolates from blood samples is still essential for prescribing rational antimicrobial therapies and curbing bacterial resistance.

Purpose::In patients with heatstroke, disseminated intravascular coagulation (DIC) is associated with greater risk of in-hospital mortality. However, time-consuming assays or a complex diagnostic system may delay immediate treatment. Therefore, the present study proposes a new heatstroke-induced coagulopathy (HIC) score in patients with heat illness as an early warning indicator for DIC.Methods::This retrospective study enrolled patients with heat illness in 24 Chinese hospitals from March 2021 to May 2022. Patients under 18 years old, with a congenital clotting disorder or liver disease, or using anticoagulants were excluded. Data were collected on demographic characteristics, routine blood tests, conventional coagulation assays and biochemical indexes. The risk factors related to coagulation function in heatstroke were identified by regression analysis, and used to construct a scoring system for HIC. The data of patients who met the diagnostic criteria for HIC and International Society on Thrombosis and Haemostasis defined-DIC were analyzed. All statistical analyses were performed using SPSS 26.0.Results::The final analysis included 302 patients with heat illness, of whom 131 (43.4%) suffered from heatstroke, including 7 death (5.3%). Core temperature ( OR = 1.681, 95% CI 1.291 - 2.189, p < 0.001), prothrombin time ( OR = 1.427, 95% CI 1.175 - 1.733, p < 0.001) and D-dimer ( OR = 1.242, 95% CI 1.049 - 1.471, p = 0.012) were independent risk factors for heatstroke, and therefore used to construct an HIC scoring system because of their close relation with abnormal coagulation. A total score ≥ 3 indicated HIC, and HIC scores correlated with the score for International Society of Thrombosis and Hemostasis-DIC ( r = 0.8848, p < 0.001). The incidence of HIC (27.5%) was higher than that of DIC (11.2%) in all of 131 heatstroke patients. Meanwhile, the mortality rate of HIC (19.4%) was lower than that of DIC (46.7%). When HIC developed into DIC, parameters of coagulation dysfunction changed significantly: platelet count decreased, D-dimer level rose, and prothrombin time and activated partial thromboplastin time prolonged ( p < 0.05). Conclusions::The newly proposed HIC score may provide a valuable tool for early detection of HIC and prompt initiation of treatment.